[2025-04-28 03:03:06,274 INFO train.py line 129 1619929] => Loading config ... [2025-04-28 03:03:06,274 INFO train.py line 131 1619929] Save path: exp/scannetpp/insseg-sm-spunet-v2-3 [2025-04-28 03:03:08,409 INFO train.py line 132 1619929] Config: weight = 'exp/scannet/insseg-sm-spunet-v2-3-e95-valrot/model/model_best.pth' resume = False evaluate = True test_only = False seed = 5511211 save_path = 'exp/scannetpp/insseg-sm-spunet-v2-3' num_worker = 24 batch_size = 12 batch_size_val = None batch_size_test = None epoch = 512 eval_epoch = 512 sync_bn = False enable_amp = True empty_cache = False empty_cache_per_epoch = False find_unused_parameters = True mix_prob = 0 param_dicts = None hooks = [ dict( type='ScanNetPPCheckpointLoader', keywords='module.', replacement='module.'), dict(type='IterationTimer', warmup_iter=2), dict(type='CustomInformationWriter', interval=50, key='loss'), dict( type='SPInsEvaluator', segment_ignore_index=(-1, ), semantic_ignore_index=(-1, ), instance_ignore_index=-1), dict(type='CustomCheckpointSaver', save_freq=None) ] train = dict(type='DefaultTrainer') test = dict( type='InsSegTester', verbose=True, segment_ignore_index=(-1, ), semantic_ignore_index=(-1, ), instance_ignore_index=-1) CLASS_LABELS_PP = ( 'wall', 'ceiling', 'floor', 'table', 'door', 'ceiling lamp', 'cabinet', 'blinds', 'curtain', 'chair', 'storage cabinet', 'office chair', 'bookshelf', 'whiteboard', 'window', 'box', 'window frame', 'monitor', 'shelf', 'doorframe', 'pipe', 'heater', 'kitchen cabinet', 'sofa', 'windowsill', 'bed', 'shower wall', 'trash can', 'book', 'plant', 'blanket', 'tv', 'computer tower', 'kitchen counter', 'refrigerator', 'jacket', 'electrical duct', 'sink', 'bag', 'picture', 'pillow', 'towel', 'suitcase', 'backpack', 'crate', 'keyboard', 'rack', 'toilet', 'paper', 'printer', 'poster', 'painting', 'microwave', 'board', 'shoes', 'socket', 'bottle', 'bucket', 'cushion', 'basket', 'shoe rack', 'telephone', 'file folder', 'cloth', 'blind rail', 'laptop', 'plant pot', 'exhaust fan', 'cup', 'coat hanger', 'light switch', 'speaker', 'table lamp', 'air vent', 'clothes hanger', 'kettle', 'smoke detector', 'container', 'power strip', 'slippers', 'paper bag', 'mouse', 'cutting board', 'toilet paper', 'paper towel', 'pot', 'clock', 'pan', 'tap', 'jar', 'soap dispenser', 'binder', 'bowl', 'tissue box', 'whiteboard eraser', 'toilet brush', 'spray bottle', 'headphones', 'stapler', 'marker') INST_LABELS_PP = ( 'table', 'door', 'ceiling lamp', 'cabinet', 'blinds', 'curtain', 'chair', 'storage cabinet', 'office chair', 'bookshelf', 'whiteboard', 'window', 'box', 'monitor', 'shelf', 'heater', 'kitchen cabinet', 'sofa', 'bed', 'trash can', 'book', 'plant', 'blanket', 'tv', 'computer tower', 'refrigerator', 'jacket', 'sink', 'bag', 'picture', 'pillow', 'towel', 'suitcase', 'backpack', 'crate', 'keyboard', 'rack', 'toilet', 'printer', 'poster', 'painting', 'microwave', 'shoes', 'socket', 'bottle', 'bucket', 'cushion', 'basket', 'shoe rack', 'telephone', 'file folder', 'laptop', 'plant pot', 'exhaust fan', 'cup', 'coat hanger', 'light switch', 'speaker', 'table lamp', 'kettle', 'smoke detector', 'container', 'power strip', 'slippers', 'paper bag', 'mouse', 'cutting board', 'toilet paper', 'paper towel', 'pot', 'clock', 'pan', 'tap', 'jar', 'soap dispenser', 'binder', 'bowl', 'tissue box', 'whiteboard eraser', 'toilet brush', 'spray bottle', 'headphones', 'stapler', 'marker') evaluate_interval = [(1, 8), (496, 1)] class_names = ('table', 'door', 'ceiling lamp', 'cabinet', 'blinds', 'curtain', 'chair', 'storage cabinet', 'office chair', 'bookshelf', 'whiteboard', 'window', 'box', 'monitor', 'shelf', 'heater', 'kitchen cabinet', 'sofa', 'bed', 'trash can', 'book', 'plant', 'blanket', 'tv', 'computer tower', 'refrigerator', 'jacket', 'sink', 'bag', 'picture', 'pillow', 'towel', 'suitcase', 'backpack', 'crate', 'keyboard', 'rack', 'toilet', 'printer', 'poster', 'painting', 'microwave', 'shoes', 'socket', 'bottle', 'bucket', 'cushion', 'basket', 'shoe rack', 'telephone', 'file folder', 'laptop', 'plant pot', 'exhaust fan', 'cup', 'coat hanger', 'light switch', 'speaker', 'table lamp', 'kettle', 'smoke detector', 'container', 'power strip', 'slippers', 'paper bag', 'mouse', 'cutting board', 'toilet paper', 'paper towel', 'pot', 'clock', 'pan', 'tap', 'jar', 'soap dispenser', 'binder', 'bowl', 'tissue box', 'whiteboard eraser', 'toilet brush', 'spray bottle', 'headphones', 'stapler', 'marker') class_ids = [ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 21, 22, 23, 25, 27, 28, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 ] num_classes = 84 segment_ignore_index = (-1, ) semantic_num_classes = 84 num_channels = 32 normalize = True model = dict( type='SceneMamba', backbone=dict( type='SpUNet-v2m1', in_channels=6, num_channels=32, num_planes=[32, 64, 96, 128, 160], return_blocks=True), decoder=dict( type='SceneMambaScanNetPPV2Decoder', num_class=84, in_channel=32, num_blocks=[1, 1, 1, 1, 1, 1], d_model=256, use_score=False, attn_mask=True, normliaze=True, alpha=0.8, num_query=400, k=8, t_layer=3, order=['hilbert', 'hilbert-trans']), criterion=dict( type='InstanceCriterion', matcher=dict( type='HungarianMatcher', costs=[ dict(type='QueryClassificationCost', weight=0.5), dict(type='MaskBCECost', weight=1.0), dict(type='MaskDiceCost', weight=1.0), dict(type='BBoxCost', weight=1.0) ]), loss_weight=[0.5, 1.0, 1.0, 1.0, 0.2], num_classes=84, non_object_weight=0.1, fix_dice_loss_weight=False, iter_matcher=True, fix_mean_loss=True), semantic_num_classes=84, semantic_ignore_index=-1, segment_ignore_index=(-1, ), instance_ignore_index=-1, topk_insts=300, score_thr=0.0, npoint_thr=100, nms=True, normliaze=True) optimizer = dict(type='AdamW', lr=0.0003, weight_decay=0.05) scheduler = dict(type='PolyLR') dataset_type = 'ScanNetPPSpDataset' data_root = 'data/scannetpp' data = dict( num_classes=84, ignore_label=-1, names=('table', 'door', 'ceiling lamp', 'cabinet', 'blinds', 'curtain', 'chair', 'storage cabinet', 'office chair', 'bookshelf', 'whiteboard', 'window', 'box', 'monitor', 'shelf', 'heater', 'kitchen cabinet', 'sofa', 'bed', 'trash can', 'book', 'plant', 'blanket', 'tv', 'computer tower', 'refrigerator', 'jacket', 'sink', 'bag', 'picture', 'pillow', 'towel', 'suitcase', 'backpack', 'crate', 'keyboard', 'rack', 'toilet', 'printer', 'poster', 'painting', 'microwave', 'shoes', 'socket', 'bottle', 'bucket', 'cushion', 'basket', 'shoe rack', 'telephone', 'file folder', 'laptop', 'plant pot', 'exhaust fan', 'cup', 'coat hanger', 'light switch', 'speaker', 'table lamp', 'kettle', 'smoke detector', 'container', 'power strip', 'slippers', 'paper bag', 'mouse', 'cutting board', 'toilet paper', 'paper towel', 'pot', 'clock', 'pan', 'tap', 'jar', 'soap dispenser', 'binder', 'bowl', 'tissue box', 'whiteboard eraser', 'toilet brush', 'spray bottle', 'headphones', 'stapler', 'marker'), ids=[ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 21, 22, 23, 25, 27, 28, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 ], train=dict( type='ScanNetPPSpDataset', split='train_grid1mm_chunk6x6_stride3x3', data_root='data/scannetpp', transform=[ dict(type='ToTensor'), dict( type='InsClassMapT', ins_cls_ids=[ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 21, 22, 23, 25, 27, 28, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 ]), dict(type='MeanShiftT'), dict( type='RandomDropoutT', dropout_ratio=0.2, dropout_application_ratio=0.5), dict(type='RandomFlipT', p=0.5), dict( type='RandomRotateT', angle=[-1, 1], axis='z', center=[0, 0, 0], p=0.95), dict( type='RandomRotateT', angle=[-0.015625, 0.015625], axis='x', p=0.5), dict( type='RandomRotateT', angle=[-0.015625, 0.015625], axis='y', p=0.5), dict(type='RandomScaleT', scale=[0.8, 1.2]), dict(type='RandomTranslationT', shift=[0.1, 0.1, 0.1]), dict( type='CustomElasticDistortionT', distortion_params=[[10, 60], [30, 180]], p=0.5), dict(type='ChromaticAutoContrastT', p=0.2, blend_factor=None), dict(type='ChromaticTranslationT', p=0.95, ratio=0.1), dict(type='ChromaticJitterT', p=0.95, std=0.05), dict(type='SphereCropT', sample_rate=0.8, mode='random'), dict( type='Copy', keys_dict=dict( coord='origin_coord', instance='origin_instance', segment='origin_segment')), dict( type='CustomGridSampleT', grid_size=0.02, hash_type='fnv', mode='train', return_grid_coord=True, return_inverse=True, keys=('coord', 'color', 'instance', 'segment')), dict(type='NormalizeColorT'), dict( type='InstanceParserT', segment_ignore_index=(-1, ), instance_ignore_index=-1), dict( type='Collect', keys=('coord', 'origin_coord', 'grid_coord', 'segment', 'origin_segment', 'instance', 'origin_instance', 'instance_centroid', 'superpoint', 'inverse'), feat_keys=('color', 'coord'), offset_keys_dict=dict( offset='coord', origin_offset='origin_coord')) ], test_mode=False, loop=1), val=dict( type='ScanNetPPSpDataset', split='val', data_root='data/scannetpp', transform=[ dict(type='ToTensor'), dict( type='InsClassMapT', ins_cls_ids=[ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 21, 22, 23, 25, 27, 28, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 ]), dict(type='MeanShiftT'), dict(type='CustomElasticDistortionT', p=0.0), dict( type='Copy', keys_dict=dict( coord='origin_coord', instance='origin_instance', segment='origin_segment')), dict( type='CustomGridSampleT', grid_size=0.02, hash_type='fnv', mode='train', return_grid_coord=True, return_inverse=True, keys=('coord', 'color', 'instance', 'segment')), dict(type='NormalizeColorT'), dict( type='InstanceParserT', segment_ignore_index=(-1, ), instance_ignore_index=-1), dict( type='Collect', keys=('coord', 'origin_coord', 'grid_coord', 'segment', 'origin_segment', 'instance', 'origin_instance', 'instance_centroid', 'superpoint', 'inverse'), feat_keys=('color', 'coord'), offset_keys_dict=dict( offset='coord', origin_offset='origin_coord')) ], test_mode=False), test=dict()) num_worker_per_gpu = 24 batch_size_per_gpu = 12 batch_size_val_per_gpu = 1 batch_size_test_per_gpu = 1 [2025-04-28 03:03:08,410 INFO train.py line 133 1619929] => Building model ... [2025-04-28 03:03:08,796 INFO train.py line 218 1619929] Num params: 18382421 [2025-04-28 03:03:09,984 INFO train.py line 135 1619929] => Building writer ... [2025-04-28 03:03:09,987 INFO train.py line 228 1619929] Tensorboard writer logging dir: exp/scannetpp/insseg-sm-spunet-v2-3 [2025-04-28 03:03:09,987 INFO train.py line 137 1619929] => Building train dataset & dataloader ... [2025-04-28 03:03:10,003 INFO defaults.py line 68 1619929] Totally 2908 x 1 samples in train_grid1mm_chunk6x6_stride3x3 set. [2025-04-28 03:03:10,004 INFO train.py line 139 1619929] => Building val dataset & dataloader ... [2025-04-28 03:03:10,005 INFO defaults.py line 68 1619929] Totally 50 x 1 samples in val set. [2025-04-28 03:03:10,005 INFO train.py line 141 1619929] => Building optimize, scheduler, scaler(amp) ... [2025-04-28 03:03:10,009 INFO train.py line 145 1619929] => Building hooks ... [2025-04-28 03:03:10,010 INFO hook.py line 564 1619929] => Loading checkpoint & weight ... [2025-04-28 03:03:10,011 INFO hook.py line 566 1619929] Loading weight at: exp/scannet/insseg-sm-spunet-v2-3-e95-valrot/model/model_best.pth [2025-04-28 03:03:10,252 INFO hook.py line 583 1619929] Loading layer weights with keyword: module., replace keyword with: module. [2025-04-28 03:03:10,261 INFO hook.py line 606 1619929] Missing keys: ['decoder.sp_seg_head.2.weight', 'decoder.sp_seg_head.2.bias', 'decoder.out_cls.2.weight', 'decoder.out_cls.2.bias'] [2025-04-28 03:03:10,264 INFO train.py line 152 1619929] >>>>>>>>>>>>>>>> Start Training >>>>>>>>>>>>>>>> [2025-04-28 03:06:10,908 INFO hook.py line 650 1619929] Train: [1/512][50/242] Data 0.018 (0.015) Batch 1.568 (1.428) Remain 49:07:44 loss: 14.3714 Lr: 2.99900e-04 Mem R(MA/MR): 23062 (16088/23062) [2025-04-28 03:07:23,265 INFO hook.py line 650 1619929] Train: [1/512][100/242] Data 0.018 (0.016) Batch 1.691 (1.438) Remain 49:27:02 loss: 13.5428 Lr: 2.99791e-04 Mem R(MA/MR): 23084 (19072/23084) [2025-04-28 03:08:35,688 INFO hook.py line 650 1619929] Train: [1/512][150/242] Data 0.016 (0.016) Batch 1.470 (1.442) Remain 49:33:13 loss: 10.2786 Lr: 2.99682e-04 Mem R(MA/MR): 23096 (19557/23096) [2025-04-28 03:09:45,206 INFO hook.py line 650 1619929] Train: [1/512][200/242] Data 0.014 (0.015) Batch 1.333 (1.429) Remain 49:05:16 loss: 13.6615 Lr: 2.99573e-04 Mem R(MA/MR): 23096 (19557/23096) [2025-04-28 03:10:40,780 INFO misc.py line 135 1619929] Train result: loss_cls: 1.4658 loss_mask: 0.0754 loss_dice: 4.2606 loss_score: 0.0000 loss_bbox: 0.0830 loss_sp_cls: 2.7701 loss: 13.2627 [2025-04-28 03:10:41,670 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:12:17,312 INFO hook.py line 650 1619929] Train: [2/512][50/242] Data 0.020 (0.017) Batch 1.660 (1.549) Remain 53:12:11 loss: 10.1156 Lr: 2.99375e-04 Mem R(MA/MR): 24138 (19557/24138) [2025-04-28 03:13:28,226 INFO hook.py line 650 1619929] Train: [2/512][100/242] Data 0.016 (0.016) Batch 1.329 (1.482) Remain 50:51:41 loss: 10.5548 Lr: 2.99266e-04 Mem R(MA/MR): 25956 (19557/25956) [2025-04-28 03:14:37,455 INFO hook.py line 650 1619929] Train: [2/512][150/242] Data 0.018 (0.016) Batch 1.597 (1.449) Remain 49:42:18 loss: 11.5676 Lr: 2.99157e-04 Mem R(MA/MR): 27784 (19557/27784) [2025-04-28 03:15:48,680 INFO hook.py line 650 1619929] Train: [2/512][200/242] Data 0.015 (0.016) Batch 1.626 (1.443) Remain 49:28:27 loss: 12.4615 Lr: 2.99048e-04 Mem R(MA/MR): 27784 (19557/27784) [2025-04-28 03:16:49,813 INFO misc.py line 135 1619929] Train result: loss_cls: 1.0709 loss_mask: 0.0739 loss_dice: 3.9967 loss_score: 0.0000 loss_bbox: 0.0818 loss_sp_cls: 1.9257 loss: 11.2034 [2025-04-28 03:16:55,238 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:18:23,638 INFO hook.py line 650 1619929] Train: [3/512][50/242] Data 0.017 (0.016) Batch 1.335 (1.449) Remain 49:40:05 loss: 10.2781 Lr: 2.98847e-04 Mem R(MA/MR): 20580 (19557/27784) [2025-04-28 03:19:34,191 INFO hook.py line 650 1619929] Train: [3/512][100/242] Data 0.015 (0.016) Batch 1.450 (1.430) Remain 48:58:18 loss: 11.1103 Lr: 2.98738e-04 Mem R(MA/MR): 25888 (19557/27784) [2025-04-28 03:20:49,268 INFO hook.py line 650 1619929] Train: [3/512][150/242] Data 0.017 (0.016) Batch 2.115 (1.454) Remain 49:47:22 loss: 9.3867 Lr: 2.98629e-04 Mem R(MA/MR): 28472 (19557/28472) [2025-04-28 03:22:02,071 INFO hook.py line 650 1619929] Train: [3/512][200/242] Data 0.016 (0.016) Batch 1.488 (1.455) Remain 49:47:12 loss: 10.0571 Lr: 2.98522e-04 Mem R(MA/MR): 28472 (19557/28472) [2025-04-28 03:22:58,390 INFO misc.py line 135 1619929] Train result: loss_cls: 0.9953 loss_mask: 0.0707 loss_dice: 3.7938 loss_score: 0.0000 loss_bbox: 0.0776 loss_sp_cls: 1.7494 loss: 10.5524 [2025-04-28 03:22:58,479 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:24:34,597 INFO hook.py line 650 1619929] Train: [4/512][50/242] Data 0.015 (0.016) Batch 1.386 (1.462) Remain 49:59:55 loss: 9.7767 Lr: 2.98322e-04 Mem R(MA/MR): 24802 (19557/28472) [2025-04-28 03:25:47,571 INFO hook.py line 650 1619929] Train: [4/512][100/242] Data 0.016 (0.016) Batch 1.316 (1.461) Remain 49:56:12 loss: 12.5552 Lr: 2.98213e-04 Mem R(MA/MR): 26664 (19557/28472) [2025-04-28 03:27:00,410 INFO hook.py line 650 1619929] Train: [4/512][150/242] Data 0.016 (0.016) Batch 1.365 (1.459) Remain 49:52:17 loss: 10.6261 Lr: 2.98104e-04 Mem R(MA/MR): 26672 (19557/28472) [2025-04-28 03:28:09,094 INFO hook.py line 650 1619929] Train: [4/512][200/242] Data 0.016 (0.016) Batch 1.217 (1.438) Remain 49:06:31 loss: 9.0370 Lr: 2.97994e-04 Mem R(MA/MR): 26672 (19557/28472) [2025-04-28 03:29:07,287 INFO misc.py line 135 1619929] Train result: loss_cls: 0.9746 loss_mask: 0.0695 loss_dice: 3.7928 loss_score: 0.0000 loss_bbox: 0.0771 loss_sp_cls: 1.6687 loss: 10.4391 [2025-04-28 03:29:09,533 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:30:43,899 INFO hook.py line 650 1619929] Train: [5/512][50/242] Data 0.015 (0.017) Batch 1.625 (1.492) Remain 50:55:29 loss: 8.8475 Lr: 2.97794e-04 Mem R(MA/MR): 22248 (19557/28472) [2025-04-28 03:31:58,442 INFO hook.py line 650 1619929] Train: [5/512][100/242] Data 0.026 (0.017) Batch 1.554 (1.491) Remain 50:53:07 loss: 9.6714 Lr: 2.97685e-04 Mem R(MA/MR): 24076 (19557/28472) [2025-04-28 03:33:10,524 INFO hook.py line 650 1619929] Train: [5/512][150/242] Data 0.016 (0.017) Batch 1.464 (1.474) Remain 50:17:19 loss: 10.9081 Lr: 2.97576e-04 Mem R(MA/MR): 24076 (19557/28472) [2025-04-28 03:34:22,321 INFO hook.py line 650 1619929] Train: [5/512][200/242] Data 0.015 (0.016) Batch 1.285 (1.465) Remain 49:56:07 loss: 8.0015 Lr: 2.97467e-04 Mem R(MA/MR): 28278 (19557/28472) [2025-04-28 03:35:19,060 INFO misc.py line 135 1619929] Train result: loss_cls: 0.9122 loss_mask: 0.0652 loss_dice: 3.5940 loss_score: 0.0000 loss_bbox: 0.0745 loss_sp_cls: 1.5874 loss: 9.8844 [2025-04-28 03:35:19,757 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:36:55,725 INFO hook.py line 650 1619929] Train: [6/512][50/242] Data 0.015 (0.016) Batch 1.353 (1.429) Remain 48:40:32 loss: 9.3137 Lr: 2.97266e-04 Mem R(MA/MR): 23974 (19557/28472) [2025-04-28 03:38:05,688 INFO hook.py line 650 1619929] Train: [6/512][100/242] Data 0.014 (0.016) Batch 1.371 (1.414) Remain 48:08:16 loss: 7.4318 Lr: 2.97157e-04 Mem R(MA/MR): 23974 (19557/28472) [2025-04-28 03:39:15,610 INFO hook.py line 650 1619929] Train: [6/512][150/242] Data 0.017 (0.016) Batch 1.440 (1.408) Remain 47:56:33 loss: 10.2577 Lr: 2.97048e-04 Mem R(MA/MR): 23974 (19557/28472) [2025-04-28 03:40:26,943 INFO hook.py line 650 1619929] Train: [6/512][200/242] Data 0.016 (0.016) Batch 1.444 (1.413) Remain 48:04:50 loss: 9.7515 Lr: 2.96939e-04 Mem R(MA/MR): 29060 (21200/29060) [2025-04-28 03:41:22,839 INFO misc.py line 135 1619929] Train result: loss_cls: 0.8755 loss_mask: 0.0638 loss_dice: 3.5061 loss_score: 0.0000 loss_bbox: 0.0731 loss_sp_cls: 1.5328 loss: 9.6015 [2025-04-28 03:41:26,779 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:43:02,578 INFO hook.py line 650 1619929] Train: [7/512][50/242] Data 0.017 (0.016) Batch 1.506 (1.477) Remain 50:13:11 loss: 8.8835 Lr: 2.96738e-04 Mem R(MA/MR): 20364 (21200/29060) [2025-04-28 03:44:18,570 INFO hook.py line 650 1619929] Train: [7/512][100/242] Data 0.027 (0.017) Batch 1.847 (1.499) Remain 50:56:54 loss: 8.6128 Lr: 2.96629e-04 Mem R(MA/MR): 20380 (21200/29060) [2025-04-28 03:45:34,152 INFO hook.py line 650 1619929] Train: [7/512][150/242] Data 0.017 (0.017) Batch 1.632 (1.503) Remain 51:04:23 loss: 10.1502 Lr: 2.96520e-04 Mem R(MA/MR): 21868 (21200/29060) [2025-04-28 03:46:49,859 INFO hook.py line 650 1619929] Train: [7/512][200/242] Data 0.020 (0.017) Batch 1.279 (1.506) Remain 51:08:43 loss: 8.6895 Lr: 2.96411e-04 Mem R(MA/MR): 24316 (21200/29060) [2025-04-28 03:47:46,506 INFO misc.py line 135 1619929] Train result: loss_cls: 0.8580 loss_mask: 0.0631 loss_dice: 3.4365 loss_score: 0.0000 loss_bbox: 0.0727 loss_sp_cls: 1.4937 loss: 9.4295 [2025-04-28 03:47:50,358 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:49:22,585 INFO hook.py line 650 1619929] Train: [8/512][50/242] Data 0.016 (0.016) Batch 1.428 (1.419) Remain 48:09:44 loss: 9.0182 Lr: 2.96210e-04 Mem R(MA/MR): 21042 (21200/29060) [2025-04-28 03:50:33,822 INFO hook.py line 650 1619929] Train: [8/512][100/242] Data 0.015 (0.016) Batch 1.260 (1.422) Remain 48:14:13 loss: 8.9206 Lr: 2.96101e-04 Mem R(MA/MR): 22904 (21200/29060) [2025-04-28 03:51:46,840 INFO hook.py line 650 1619929] Train: [8/512][150/242] Data 0.016 (0.016) Batch 1.408 (1.435) Remain 48:39:30 loss: 9.3628 Lr: 2.95992e-04 Mem R(MA/MR): 22926 (21200/29060) [2025-04-28 03:52:57,841 INFO hook.py line 650 1619929] Train: [8/512][200/242] Data 0.014 (0.016) Batch 1.364 (1.431) Remain 48:30:32 loss: 8.8045 Lr: 2.95883e-04 Mem R(MA/MR): 22926 (21200/29060) [2025-04-28 03:53:54,471 INFO misc.py line 135 1619929] Train result: loss_cls: 0.8332 loss_mask: 0.0598 loss_dice: 3.3668 loss_score: 0.0000 loss_bbox: 0.0702 loss_sp_cls: 1.4673 loss: 9.2143 [2025-04-28 03:53:57,875 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 03:54:02,194 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.6462 Process Time: 3.111 Mem R(MA/MR): 4794 (21200/29060) [2025-04-28 03:54:04,496 INFO hook.py line 449 1619929] Test: [2/50] Loss 7.2750 Process Time: 1.165 Mem R(MA/MR): 7630 (21200/29060) [2025-04-28 03:54:06,155 INFO hook.py line 449 1619929] Test: [3/50] Loss 9.3106 Process Time: 0.587 Mem R(MA/MR): 10068 (21200/29060) [2025-04-28 03:54:13,775 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4614 Process Time: 1.210 Mem R(MA/MR): 19722 (21200/29060) [2025-04-28 03:54:15,106 INFO hook.py line 449 1619929] Test: [5/50] Loss 7.0274 Process Time: 0.730 Mem R(MA/MR): 7562 (21200/29060) [2025-04-28 03:54:16,977 INFO hook.py line 449 1619929] Test: [6/50] Loss 7.0225 Process Time: 0.848 Mem R(MA/MR): 11604 (21200/29060) [2025-04-28 03:54:17,622 INFO hook.py line 449 1619929] Test: [7/50] Loss 7.5313 Process Time: 0.295 Mem R(MA/MR): 6640 (21200/29060) [2025-04-28 03:54:17,997 INFO hook.py line 449 1619929] Test: [8/50] Loss 8.5287 Process Time: 0.194 Mem R(MA/MR): 4878 (21200/29060) [2025-04-28 03:54:19,197 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.5328 Process Time: 0.594 Mem R(MA/MR): 11832 (21200/29060) [2025-04-28 03:54:20,585 INFO hook.py line 449 1619929] Test: [10/50] Loss 7.1691 Process Time: 0.484 Mem R(MA/MR): 9922 (21200/29060) [2025-04-28 03:54:24,655 INFO hook.py line 449 1619929] Test: [11/50] Loss 13.2339 Process Time: 1.616 Mem R(MA/MR): 18404 (21200/29060) [2025-04-28 03:54:27,937 INFO hook.py line 449 1619929] Test: [12/50] Loss 8.1575 Process Time: 0.989 Mem R(MA/MR): 15440 (21200/29060) [2025-04-28 03:54:29,167 INFO hook.py line 449 1619929] Test: [13/50] Loss 8.4581 Process Time: 0.499 Mem R(MA/MR): 9086 (21200/29060) [2025-04-28 03:54:29,813 INFO hook.py line 449 1619929] Test: [14/50] Loss 5.7671 Process Time: 0.350 Mem R(MA/MR): 5260 (21200/29060) [2025-04-28 03:54:33,578 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.4400 Process Time: 1.412 Mem R(MA/MR): 16946 (21200/29060) [2025-04-28 03:54:36,310 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.9411 Process Time: 1.045 Mem R(MA/MR): 14614 (21200/29060) [2025-04-28 03:54:37,035 INFO hook.py line 449 1619929] Test: [17/50] Loss 7.9226 Process Time: 0.313 Mem R(MA/MR): 7174 (21200/29060) [2025-04-28 03:54:37,984 INFO hook.py line 449 1619929] Test: [18/50] Loss 4.3489 Process Time: 0.413 Mem R(MA/MR): 8652 (21200/29060) [2025-04-28 03:54:39,440 INFO hook.py line 449 1619929] Test: [19/50] Loss 7.1684 Process Time: 0.523 Mem R(MA/MR): 6664 (21200/29060) [2025-04-28 03:54:42,277 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.5693 Process Time: 1.525 Mem R(MA/MR): 11886 (21200/29060) [2025-04-28 03:54:54,888 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.6614 Process Time: 5.680 Mem R(MA/MR): 23960 (21200/29060) [2025-04-28 03:54:55,723 INFO hook.py line 449 1619929] Test: [22/50] Loss 6.1704 Process Time: 0.381 Mem R(MA/MR): 7312 (21200/29060) [2025-04-28 03:55:03,440 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.8979 Process Time: 0.518 Mem R(MA/MR): 10700 (21200/29060) [2025-04-28 03:55:03,997 INFO hook.py line 449 1619929] Test: [24/50] Loss 7.3754 Process Time: 0.266 Mem R(MA/MR): 5718 (21200/29060) [2025-04-28 03:55:05,295 INFO hook.py line 449 1619929] Test: [25/50] Loss 4.5542 Process Time: 0.511 Mem R(MA/MR): 9868 (21200/29060) [2025-04-28 03:55:15,227 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.7126 Process Time: 2.636 Mem R(MA/MR): 31870 (21200/31870) [2025-04-28 03:55:18,678 INFO hook.py line 449 1619929] Test: [27/50] Loss 9.8276 Process Time: 1.266 Mem R(MA/MR): 10308 (21200/31870) [2025-04-28 03:55:20,031 INFO hook.py line 449 1619929] Test: [28/50] Loss 8.7856 Process Time: 0.546 Mem R(MA/MR): 9250 (21200/31870) [2025-04-28 03:55:25,428 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.1801 Process Time: 0.858 Mem R(MA/MR): 17350 (21200/31870) [2025-04-28 03:55:26,992 INFO hook.py line 449 1619929] Test: [30/50] Loss 7.7256 Process Time: 0.612 Mem R(MA/MR): 8238 (21200/31870) [2025-04-28 03:55:32,040 INFO hook.py line 449 1619929] Test: [31/50] Loss 9.9345 Process Time: 1.497 Mem R(MA/MR): 20640 (21200/31870) [2025-04-28 03:55:32,388 INFO hook.py line 449 1619929] Test: [32/50] Loss 6.1544 Process Time: 0.218 Mem R(MA/MR): 4354 (21200/31870) [2025-04-28 03:55:36,716 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.9926 Process Time: 1.573 Mem R(MA/MR): 24646 (21200/31870) [2025-04-28 03:55:38,387 INFO hook.py line 449 1619929] Test: [34/50] Loss 5.7517 Process Time: 0.630 Mem R(MA/MR): 10138 (21200/31870) [2025-04-28 03:55:40,217 INFO hook.py line 449 1619929] Test: [35/50] Loss 10.4338 Process Time: 0.651 Mem R(MA/MR): 14020 (21200/31870) [2025-04-28 03:55:40,869 INFO hook.py line 449 1619929] Test: [36/50] Loss 6.3604 Process Time: 0.326 Mem R(MA/MR): 7020 (21200/31870) [2025-04-28 03:55:50,096 INFO hook.py line 449 1619929] Test: [37/50] Loss 15.8244 Process Time: 4.987 Mem R(MA/MR): 28512 (21200/31870) [2025-04-28 03:55:52,374 INFO hook.py line 449 1619929] Test: [38/50] Loss 8.1702 Process Time: 0.797 Mem R(MA/MR): 11074 (21200/31870) [2025-04-28 03:55:53,498 INFO hook.py line 449 1619929] Test: [39/50] Loss 7.1155 Process Time: 0.503 Mem R(MA/MR): 5986 (21200/31870) [2025-04-28 03:55:55,414 INFO hook.py line 449 1619929] Test: [40/50] Loss 6.0840 Process Time: 0.773 Mem R(MA/MR): 10574 (21200/31870) [2025-04-28 03:55:56,872 INFO hook.py line 449 1619929] Test: [41/50] Loss 6.3023 Process Time: 0.541 Mem R(MA/MR): 9538 (21200/31870) [2025-04-28 03:55:57,545 INFO hook.py line 449 1619929] Test: [42/50] Loss 7.6531 Process Time: 0.289 Mem R(MA/MR): 5968 (21200/31870) [2025-04-28 03:55:58,267 INFO hook.py line 449 1619929] Test: [43/50] Loss 6.0938 Process Time: 0.328 Mem R(MA/MR): 6080 (21200/31870) [2025-04-28 03:55:59,235 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.4374 Process Time: 0.442 Mem R(MA/MR): 7498 (21200/31870) [2025-04-28 03:56:00,159 INFO hook.py line 449 1619929] Test: [45/50] Loss 6.2063 Process Time: 0.353 Mem R(MA/MR): 5608 (21200/31870) [2025-04-28 03:56:03,934 INFO hook.py line 449 1619929] Test: [46/50] Loss 12.4562 Process Time: 1.711 Mem R(MA/MR): 15040 (21200/31870) [2025-04-28 03:56:12,634 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.1936 Process Time: 1.555 Mem R(MA/MR): 20584 (21200/31870) [2025-04-28 03:56:24,231 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.4942 Process Time: 2.040 Mem R(MA/MR): 35474 (21200/35474) [2025-04-28 03:56:24,870 INFO hook.py line 449 1619929] Test: [49/50] Loss 6.3998 Process Time: 0.261 Mem R(MA/MR): 6218 (21200/35474) [2025-04-28 03:56:27,684 INFO hook.py line 449 1619929] Test: [50/50] Loss 7.1990 Process Time: 0.704 Mem R(MA/MR): 14208 (21200/35474) [2025-04-28 03:56:32,366 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 03:56:32,366 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 03:56:32,366 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] table : 0.127 0.443 0.745 0.614 0.515 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] door : 0.387 0.748 0.810 0.873 0.696 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] ceiling lamp : 0.463 0.646 0.792 0.771 0.652 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] cabinet : 0.207 0.400 0.531 0.614 0.403 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] blinds : 0.117 0.252 0.436 0.440 0.478 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] curtain : 0.211 0.387 0.430 0.667 0.333 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] chair : 0.496 0.655 0.760 0.850 0.602 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] storage cabinet: 0.087 0.312 0.486 0.471 0.320 [2025-04-28 03:56:32,366 INFO hook.py line 395 1619929] office chair : 0.533 0.569 0.593 0.717 0.688 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] bookshelf : 0.080 0.432 0.540 0.545 0.545 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] whiteboard : 0.454 0.645 0.669 0.952 0.571 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] window : 0.048 0.121 0.495 0.345 0.209 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] box : 0.059 0.121 0.308 0.301 0.238 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] monitor : 0.479 0.667 0.719 0.852 0.657 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] shelf : 0.072 0.192 0.240 0.600 0.200 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] heater : 0.314 0.655 0.860 0.711 0.711 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] kitchen cabinet: 0.095 0.172 0.502 0.353 0.240 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] sofa : 0.341 0.483 0.605 0.600 0.500 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] bed : 0.121 0.286 0.636 0.750 0.375 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] trash can : 0.455 0.622 0.655 0.697 0.708 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] book : 0.004 0.014 0.025 0.211 0.045 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] plant : 0.137 0.249 0.518 0.500 0.333 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] blanket : 0.089 0.417 0.624 0.833 0.455 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] tv : 0.752 0.858 0.858 0.857 1.000 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] computer tower : 0.143 0.191 0.343 0.367 0.262 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] refrigerator : 0.051 0.222 0.222 1.000 0.222 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] jacket : 0.017 0.079 0.104 0.333 0.273 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] sink : 0.310 0.607 0.847 0.765 0.591 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] bag : 0.032 0.045 0.045 0.600 0.111 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] picture : 0.107 0.201 0.313 0.438 0.359 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] pillow : 0.423 0.676 0.700 0.700 0.737 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] towel : 0.027 0.076 0.239 0.400 0.211 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] suitcase : 0.010 0.010 0.014 0.143 0.143 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] backpack : 0.341 0.371 0.371 0.833 0.385 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] crate : 0.000 0.000 0.023 0.000 0.000 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] keyboard : 0.161 0.222 0.251 0.769 0.256 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] toilet : 0.580 0.889 1.000 1.000 0.889 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] printer : 0.003 0.014 0.014 0.250 0.111 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,367 INFO hook.py line 395 1619929] microwave : 0.244 0.451 0.697 0.667 0.500 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] shoes : 0.069 0.170 0.262 0.435 0.244 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] socket : 0.095 0.219 0.368 0.681 0.229 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] bottle : 0.025 0.053 0.105 0.211 0.096 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] bucket : 0.010 0.015 0.016 0.091 0.286 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] cushion : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] telephone : 0.141 0.294 0.344 1.000 0.294 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] laptop : 0.036 0.109 0.109 0.333 0.500 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] plant pot : 0.069 0.083 0.301 0.400 0.125 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] cup : 0.117 0.188 0.231 0.429 0.273 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] light switch : 0.099 0.201 0.440 0.500 0.231 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] speaker : 0.162 0.225 0.229 0.750 0.273 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] table lamp : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] smoke detector : 0.547 0.686 0.729 1.000 0.625 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] power strip : 0.006 0.017 0.100 0.333 0.100 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] mouse : 0.293 0.441 0.533 0.652 0.469 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] toilet paper : 0.015 0.015 0.015 0.500 0.059 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] clock : 0.185 0.333 0.333 1.000 0.333 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] tap : 0.037 0.093 0.333 0.667 0.222 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] soap dispenser : 0.205 0.235 0.235 1.000 0.200 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,368 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] whiteboard eraser: 0.000 0.000 0.000 1.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] toilet brush : 0.061 0.111 0.356 0.500 0.333 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 03:56:32,369 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 03:56:32,369 INFO hook.py line 404 1619929] average : 0.133 0.220 0.302 0.450 0.263 [2025-04-28 03:56:32,369 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 03:56:32,369 INFO hook.py line 480 1619929] Total Process Time: 51.357 s [2025-04-28 03:56:32,369 INFO hook.py line 481 1619929] Average Process Time: 984.619 ms [2025-04-28 03:56:32,369 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 03:56:32,421 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.220 [2025-04-28 03:56:32,423 INFO hook.py line 685 1619929] Currently Best AP50: 0.220 [2025-04-28 03:56:32,424 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 03:57:59,201 INFO hook.py line 650 1619929] Train: [9/512][50/242] Data 0.016 (0.016) Batch 1.483 (1.477) Remain 50:02:04 loss: 9.9885 Lr: 2.95682e-04 Mem R(MA/MR): 20754 (21200/35474) [2025-04-28 03:59:09,796 INFO hook.py line 650 1619929] Train: [9/512][100/242] Data 0.015 (0.016) Batch 1.343 (1.444) Remain 48:52:16 loss: 10.7309 Lr: 2.95573e-04 Mem R(MA/MR): 22636 (21200/35474) [2025-04-28 04:00:23,569 INFO hook.py line 650 1619929] Train: [9/512][150/242] Data 0.016 (0.024) Batch 1.432 (1.454) Remain 49:13:00 loss: 8.2242 Lr: 2.95464e-04 Mem R(MA/MR): 24562 (21200/35474) [2025-04-28 04:01:33,513 INFO hook.py line 650 1619929] Train: [9/512][200/242] Data 0.015 (0.022) Batch 1.332 (1.440) Remain 48:43:09 loss: 8.6485 Lr: 2.95355e-04 Mem R(MA/MR): 24562 (21200/35474) [2025-04-28 04:02:30,058 INFO misc.py line 135 1619929] Train result: loss_cls: 0.8211 loss_mask: 0.0583 loss_dice: 3.3253 loss_score: 0.0000 loss_bbox: 0.0689 loss_sp_cls: 1.4434 loss: 9.0928 [2025-04-28 04:02:31,202 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:03:58,114 INFO hook.py line 650 1619929] Train: [10/512][50/242] Data 0.016 (0.016) Batch 1.389 (1.438) Remain 48:36:04 loss: 8.3837 Lr: 2.95154e-04 Mem R(MA/MR): 23632 (21200/35474) [2025-04-28 04:05:09,195 INFO hook.py line 650 1619929] Train: [10/512][100/242] Data 0.018 (0.016) Batch 1.679 (1.429) Remain 48:17:41 loss: 10.5304 Lr: 2.95045e-04 Mem R(MA/MR): 23632 (21200/35474) [2025-04-28 04:06:20,703 INFO hook.py line 650 1619929] Train: [10/512][150/242] Data 0.017 (0.016) Batch 1.555 (1.430) Remain 48:17:01 loss: 10.0429 Lr: 2.94935e-04 Mem R(MA/MR): 23632 (21200/35474) [2025-04-28 04:07:32,772 INFO hook.py line 650 1619929] Train: [10/512][200/242] Data 0.012 (0.016) Batch 1.293 (1.433) Remain 48:21:50 loss: 9.1134 Lr: 2.94826e-04 Mem R(MA/MR): 27046 (21200/35474) [2025-04-28 04:08:28,645 INFO misc.py line 135 1619929] Train result: loss_cls: 0.8054 loss_mask: 0.0590 loss_dice: 3.3074 loss_score: 0.0000 loss_bbox: 0.0690 loss_sp_cls: 1.4200 loss: 9.0097 [2025-04-28 04:08:29,309 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:10:04,036 INFO hook.py line 650 1619929] Train: [11/512][50/242] Data 0.016 (0.016) Batch 1.386 (1.440) Remain 48:33:46 loss: 10.0190 Lr: 2.94625e-04 Mem R(MA/MR): 24388 (21200/35474) [2025-04-28 04:11:14,828 INFO hook.py line 650 1619929] Train: [11/512][100/242] Data 0.017 (0.017) Batch 1.463 (1.427) Remain 48:07:40 loss: 7.9649 Lr: 2.94516e-04 Mem R(MA/MR): 24388 (21200/35474) [2025-04-28 04:12:26,310 INFO hook.py line 650 1619929] Train: [11/512][150/242] Data 0.015 (0.016) Batch 1.366 (1.428) Remain 48:08:03 loss: 8.4346 Lr: 2.94407e-04 Mem R(MA/MR): 24388 (21200/35474) [2025-04-28 04:13:36,640 INFO hook.py line 650 1619929] Train: [11/512][200/242] Data 0.014 (0.016) Batch 1.272 (1.423) Remain 47:55:49 loss: 10.0597 Lr: 2.94298e-04 Mem R(MA/MR): 28814 (21200/35474) [2025-04-28 04:14:33,579 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7914 loss_mask: 0.0600 loss_dice: 3.2657 loss_score: 0.0000 loss_bbox: 0.0686 loss_sp_cls: 1.4008 loss: 8.8920 [2025-04-28 04:14:37,688 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:16:03,094 INFO hook.py line 650 1619929] Train: [12/512][50/242] Data 0.017 (0.017) Batch 1.460 (1.435) Remain 48:18:54 loss: 7.2763 Lr: 2.94099e-04 Mem R(MA/MR): 22226 (21200/35474) [2025-04-28 04:17:13,247 INFO hook.py line 650 1619929] Train: [12/512][100/242] Data 0.015 (0.016) Batch 1.279 (1.419) Remain 47:44:14 loss: 6.1615 Lr: 2.93990e-04 Mem R(MA/MR): 22254 (21200/35474) [2025-04-28 04:18:21,626 INFO hook.py line 650 1619929] Train: [12/512][150/242] Data 0.015 (0.016) Batch 1.492 (1.401) Remain 47:07:58 loss: 9.1259 Lr: 2.93881e-04 Mem R(MA/MR): 22254 (21200/35474) [2025-04-28 04:19:33,044 INFO hook.py line 650 1619929] Train: [12/512][200/242] Data 0.015 (0.016) Batch 1.311 (1.408) Remain 47:20:45 loss: 9.4854 Lr: 2.93771e-04 Mem R(MA/MR): 22254 (21200/35474) [2025-04-28 04:20:29,879 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7730 loss_mask: 0.0575 loss_dice: 3.1934 loss_score: 0.0000 loss_bbox: 0.0673 loss_sp_cls: 1.3762 loss: 8.7047 [2025-04-28 04:20:30,057 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:22:00,774 INFO hook.py line 650 1619929] Train: [13/512][50/242] Data 0.016 (0.016) Batch 1.255 (1.428) Remain 47:58:48 loss: 8.1132 Lr: 2.93571e-04 Mem R(MA/MR): 22076 (21200/35474) [2025-04-28 04:23:09,908 INFO hook.py line 650 1619929] Train: [13/512][100/242] Data 0.017 (0.016) Batch 1.477 (1.405) Remain 47:10:26 loss: 7.8229 Lr: 2.93461e-04 Mem R(MA/MR): 23530 (21200/35474) [2025-04-28 04:24:20,764 INFO hook.py line 650 1619929] Train: [13/512][150/242] Data 0.015 (0.016) Batch 1.419 (1.409) Remain 47:17:47 loss: 7.4529 Lr: 2.93352e-04 Mem R(MA/MR): 26884 (21200/35474) [2025-04-28 04:25:31,509 INFO hook.py line 650 1619929] Train: [13/512][200/242] Data 0.015 (0.016) Batch 1.289 (1.410) Remain 47:19:40 loss: 8.7986 Lr: 2.93243e-04 Mem R(MA/MR): 26884 (21200/35474) [2025-04-28 04:26:27,892 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7675 loss_mask: 0.0587 loss_dice: 3.1828 loss_score: 0.0000 loss_bbox: 0.0672 loss_sp_cls: 1.3683 loss: 8.6670 [2025-04-28 04:26:27,983 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:27:52,220 INFO hook.py line 650 1619929] Train: [14/512][50/242] Data 0.017 (0.016) Batch 1.533 (1.448) Remain 48:33:25 loss: 9.1858 Lr: 2.93042e-04 Mem R(MA/MR): 20678 (21200/35474) [2025-04-28 04:29:01,598 INFO hook.py line 650 1619929] Train: [14/512][100/242] Data 0.016 (0.016) Batch 1.311 (1.417) Remain 47:29:20 loss: 8.3765 Lr: 2.92933e-04 Mem R(MA/MR): 23512 (21200/35474) [2025-04-28 04:30:11,316 INFO hook.py line 650 1619929] Train: [14/512][150/242] Data 0.016 (0.016) Batch 1.380 (1.409) Remain 47:12:45 loss: 9.1679 Lr: 2.92823e-04 Mem R(MA/MR): 26896 (21200/35474) [2025-04-28 04:31:22,933 INFO hook.py line 650 1619929] Train: [14/512][200/242] Data 0.014 (0.016) Batch 1.450 (1.415) Remain 47:23:23 loss: 10.0571 Lr: 2.92714e-04 Mem R(MA/MR): 31096 (21200/35474) [2025-04-28 04:32:19,315 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7630 loss_mask: 0.0560 loss_dice: 3.1739 loss_score: 0.0000 loss_bbox: 0.0676 loss_sp_cls: 1.3642 loss: 8.6317 [2025-04-28 04:32:20,576 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:33:54,506 INFO hook.py line 650 1619929] Train: [15/512][50/242] Data 0.015 (0.016) Batch 1.292 (1.431) Remain 47:53:20 loss: 8.9662 Lr: 2.92513e-04 Mem R(MA/MR): 20022 (21200/35474) [2025-04-28 04:35:03,388 INFO hook.py line 650 1619929] Train: [15/512][100/242] Data 0.016 (0.016) Batch 1.495 (1.404) Remain 46:56:48 loss: 8.0739 Lr: 2.92404e-04 Mem R(MA/MR): 25000 (21200/35474) [2025-04-28 04:36:14,140 INFO hook.py line 650 1619929] Train: [15/512][150/242] Data 0.016 (0.016) Batch 1.555 (1.407) Remain 47:03:30 loss: 6.8344 Lr: 2.92295e-04 Mem R(MA/MR): 25000 (21200/35474) [2025-04-28 04:37:23,117 INFO hook.py line 650 1619929] Train: [15/512][200/242] Data 0.016 (0.016) Batch 1.466 (1.400) Remain 46:48:07 loss: 8.1262 Lr: 2.92185e-04 Mem R(MA/MR): 26886 (21200/35474) [2025-04-28 04:38:19,178 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7629 loss_mask: 0.0563 loss_dice: 3.1640 loss_score: 0.0000 loss_bbox: 0.0680 loss_sp_cls: 1.3507 loss: 8.6185 [2025-04-28 04:38:19,710 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:39:54,165 INFO hook.py line 650 1619929] Train: [16/512][50/242] Data 0.015 (0.016) Batch 1.458 (1.456) Remain 48:36:39 loss: 7.9841 Lr: 2.91984e-04 Mem R(MA/MR): 21122 (21200/35474) [2025-04-28 04:41:05,464 INFO hook.py line 650 1619929] Train: [16/512][100/242] Data 0.016 (0.016) Batch 1.417 (1.440) Remain 48:04:52 loss: 8.5513 Lr: 2.91875e-04 Mem R(MA/MR): 25352 (21200/35474) [2025-04-28 04:42:16,110 INFO hook.py line 650 1619929] Train: [16/512][150/242] Data 0.016 (0.016) Batch 1.542 (1.431) Remain 47:44:59 loss: 8.3767 Lr: 2.91766e-04 Mem R(MA/MR): 25352 (21200/35474) [2025-04-28 04:43:28,788 INFO hook.py line 650 1619929] Train: [16/512][200/242] Data 0.015 (0.016) Batch 1.424 (1.437) Remain 47:55:16 loss: 7.9956 Lr: 2.91656e-04 Mem R(MA/MR): 25352 (21200/35474) [2025-04-28 04:44:24,765 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7478 loss_mask: 0.0579 loss_dice: 3.1090 loss_score: 0.0000 loss_bbox: 0.0674 loss_sp_cls: 1.3391 loss: 8.4857 [2025-04-28 04:44:28,100 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 04:44:30,486 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.8896 Process Time: 0.357 Mem R(MA/MR): 4236 (21200/35474) [2025-04-28 04:44:31,988 INFO hook.py line 449 1619929] Test: [2/50] Loss 8.0479 Process Time: 0.501 Mem R(MA/MR): 7074 (21200/35474) [2025-04-28 04:44:34,617 INFO hook.py line 449 1619929] Test: [3/50] Loss 8.3755 Process Time: 1.227 Mem R(MA/MR): 9580 (21200/35474) [2025-04-28 04:44:42,391 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.6008 Process Time: 1.363 Mem R(MA/MR): 19486 (21200/35474) [2025-04-28 04:44:44,147 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.7600 Process Time: 0.548 Mem R(MA/MR): 7020 (21200/35474) [2025-04-28 04:44:46,079 INFO hook.py line 449 1619929] Test: [6/50] Loss 6.5300 Process Time: 0.869 Mem R(MA/MR): 11100 (21200/35474) [2025-04-28 04:44:46,759 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.6400 Process Time: 0.198 Mem R(MA/MR): 6290 (21200/35474) [2025-04-28 04:44:47,212 INFO hook.py line 449 1619929] Test: [8/50] Loss 7.6632 Process Time: 0.147 Mem R(MA/MR): 4320 (21200/35474) [2025-04-28 04:44:48,165 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.5797 Process Time: 0.261 Mem R(MA/MR): 11292 (21200/35474) [2025-04-28 04:44:49,651 INFO hook.py line 449 1619929] Test: [10/50] Loss 6.6334 Process Time: 0.316 Mem R(MA/MR): 9276 (21200/35474) [2025-04-28 04:44:52,815 INFO hook.py line 449 1619929] Test: [11/50] Loss 14.2033 Process Time: 0.830 Mem R(MA/MR): 18446 (21200/35474) [2025-04-28 04:44:55,800 INFO hook.py line 449 1619929] Test: [12/50] Loss 8.4229 Process Time: 0.570 Mem R(MA/MR): 15350 (21200/35474) [2025-04-28 04:44:56,877 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.8937 Process Time: 0.215 Mem R(MA/MR): 8548 (21200/35474) [2025-04-28 04:44:57,315 INFO hook.py line 449 1619929] Test: [14/50] Loss 4.5635 Process Time: 0.151 Mem R(MA/MR): 4706 (21200/35474) [2025-04-28 04:45:00,114 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.2204 Process Time: 0.287 Mem R(MA/MR): 16498 (21200/35474) [2025-04-28 04:45:03,438 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.9070 Process Time: 1.195 Mem R(MA/MR): 14440 (21200/35474) [2025-04-28 04:45:04,471 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.7836 Process Time: 0.325 Mem R(MA/MR): 6672 (21200/35474) [2025-04-28 04:45:05,241 INFO hook.py line 449 1619929] Test: [18/50] Loss 4.4312 Process Time: 0.187 Mem R(MA/MR): 8226 (21200/35474) [2025-04-28 04:45:06,276 INFO hook.py line 449 1619929] Test: [19/50] Loss 8.4372 Process Time: 0.175 Mem R(MA/MR): 6290 (21200/35474) [2025-04-28 04:45:07,778 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.5622 Process Time: 0.291 Mem R(MA/MR): 11410 (21200/35474) [2025-04-28 04:45:20,541 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8910 Process Time: 0.573 Mem R(MA/MR): 23630 (21200/35474) [2025-04-28 04:45:21,538 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.9089 Process Time: 0.320 Mem R(MA/MR): 6800 (21200/35474) [2025-04-28 04:45:29,929 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.6320 Process Time: 0.512 Mem R(MA/MR): 9976 (21200/35474) [2025-04-28 04:45:30,991 INFO hook.py line 449 1619929] Test: [24/50] Loss 6.0808 Process Time: 0.356 Mem R(MA/MR): 5300 (21200/35474) [2025-04-28 04:45:32,493 INFO hook.py line 449 1619929] Test: [25/50] Loss 4.2263 Process Time: 0.412 Mem R(MA/MR): 9436 (21200/35474) [2025-04-28 04:45:42,479 INFO hook.py line 449 1619929] Test: [26/50] Loss 13.3687 Process Time: 1.248 Mem R(MA/MR): 31346 (21200/35474) [2025-04-28 04:45:44,084 INFO hook.py line 449 1619929] Test: [27/50] Loss 11.1877 Process Time: 0.344 Mem R(MA/MR): 10138 (21200/35474) [2025-04-28 04:45:45,212 INFO hook.py line 449 1619929] Test: [28/50] Loss 8.5527 Process Time: 0.221 Mem R(MA/MR): 8792 (21200/35474) [2025-04-28 04:45:50,544 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.5308 Process Time: 0.968 Mem R(MA/MR): 16844 (21200/35474) [2025-04-28 04:45:51,348 INFO hook.py line 449 1619929] Test: [30/50] Loss 7.7566 Process Time: 0.199 Mem R(MA/MR): 7722 (21200/35474) [2025-04-28 04:45:55,156 INFO hook.py line 449 1619929] Test: [31/50] Loss 9.3961 Process Time: 0.447 Mem R(MA/MR): 20394 (21200/35474) [2025-04-28 04:45:56,512 INFO hook.py line 449 1619929] Test: [32/50] Loss 6.7562 Process Time: 0.473 Mem R(MA/MR): 3960 (21200/35474) [2025-04-28 04:46:00,406 INFO hook.py line 449 1619929] Test: [33/50] Loss 14.4469 Process Time: 0.735 Mem R(MA/MR): 24532 (21200/35474) [2025-04-28 04:46:01,651 INFO hook.py line 449 1619929] Test: [34/50] Loss 5.3036 Process Time: 0.380 Mem R(MA/MR): 9860 (21200/35474) [2025-04-28 04:46:03,195 INFO hook.py line 449 1619929] Test: [35/50] Loss 10.6433 Process Time: 0.400 Mem R(MA/MR): 13692 (21200/35474) [2025-04-28 04:46:04,166 INFO hook.py line 449 1619929] Test: [36/50] Loss 6.0135 Process Time: 0.608 Mem R(MA/MR): 6504 (21200/35474) [2025-04-28 04:46:10,025 INFO hook.py line 449 1619929] Test: [37/50] Loss 15.2499 Process Time: 2.202 Mem R(MA/MR): 28624 (21200/35474) [2025-04-28 04:46:11,677 INFO hook.py line 449 1619929] Test: [38/50] Loss 7.4675 Process Time: 0.401 Mem R(MA/MR): 10598 (21200/35474) [2025-04-28 04:46:12,059 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.8880 Process Time: 0.134 Mem R(MA/MR): 5466 (21200/35474) [2025-04-28 04:46:13,129 INFO hook.py line 449 1619929] Test: [40/50] Loss 5.2610 Process Time: 0.257 Mem R(MA/MR): 10226 (21200/35474) [2025-04-28 04:46:15,252 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.9485 Process Time: 1.004 Mem R(MA/MR): 9036 (21200/35474) [2025-04-28 04:46:15,788 INFO hook.py line 449 1619929] Test: [42/50] Loss 7.4951 Process Time: 0.194 Mem R(MA/MR): 5424 (21200/35474) [2025-04-28 04:46:16,323 INFO hook.py line 449 1619929] Test: [43/50] Loss 6.6330 Process Time: 0.186 Mem R(MA/MR): 5494 (21200/35474) [2025-04-28 04:46:17,337 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.0574 Process Time: 0.478 Mem R(MA/MR): 7022 (21200/35474) [2025-04-28 04:46:18,014 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.6901 Process Time: 0.212 Mem R(MA/MR): 5218 (21200/35474) [2025-04-28 04:46:20,186 INFO hook.py line 449 1619929] Test: [46/50] Loss 12.4865 Process Time: 0.661 Mem R(MA/MR): 14750 (21200/35474) [2025-04-28 04:46:27,852 INFO hook.py line 449 1619929] Test: [47/50] Loss 8.8019 Process Time: 2.018 Mem R(MA/MR): 20304 (21200/35474) [2025-04-28 04:46:51,455 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.4746 Process Time: 13.834 Mem R(MA/MR): 35378 (21200/35474) [2025-04-28 04:46:53,018 INFO hook.py line 449 1619929] Test: [49/50] Loss 6.2233 Process Time: 0.537 Mem R(MA/MR): 5680 (21200/35474) [2025-04-28 04:46:56,399 INFO hook.py line 449 1619929] Test: [50/50] Loss 6.5518 Process Time: 1.045 Mem R(MA/MR): 13778 (21200/35474) [2025-04-28 04:47:00,463 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 04:47:00,464 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 04:47:00,464 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] table : 0.114 0.374 0.741 0.604 0.449 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] door : 0.314 0.653 0.829 0.644 0.709 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] ceiling lamp : 0.440 0.627 0.728 0.790 0.624 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] cabinet : 0.248 0.435 0.505 0.473 0.522 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] blinds : 0.087 0.189 0.329 0.387 0.522 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] curtain : 0.144 0.250 0.533 0.286 0.500 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] chair : 0.419 0.616 0.772 0.675 0.631 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] storage cabinet: 0.106 0.274 0.557 0.407 0.440 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] office chair : 0.574 0.604 0.653 0.711 0.667 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] bookshelf : 0.148 0.501 0.729 0.700 0.636 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] whiteboard : 0.482 0.628 0.670 0.870 0.571 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] window : 0.038 0.112 0.480 0.295 0.198 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] box : 0.097 0.203 0.372 0.417 0.304 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] monitor : 0.465 0.622 0.708 0.865 0.643 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] shelf : 0.027 0.134 0.282 0.385 0.167 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] heater : 0.301 0.542 0.782 0.864 0.500 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] kitchen cabinet: 0.121 0.212 0.703 0.450 0.360 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] sofa : 0.223 0.373 0.638 0.444 0.667 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] bed : 0.109 0.189 0.429 0.400 0.250 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] trash can : 0.410 0.542 0.610 0.764 0.646 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] book : 0.003 0.009 0.026 0.077 0.049 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] plant : 0.129 0.227 0.583 0.389 0.389 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] blanket : 0.188 0.307 0.533 0.750 0.273 [2025-04-28 04:47:00,464 INFO hook.py line 395 1619929] tv : 0.668 0.925 0.925 0.750 1.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] computer tower : 0.165 0.201 0.421 0.667 0.190 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] refrigerator : 0.141 0.176 0.176 0.667 0.222 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] jacket : 0.046 0.174 0.340 0.267 0.364 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] sink : 0.237 0.480 0.820 0.750 0.545 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] bag : 0.035 0.047 0.069 0.188 0.222 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] picture : 0.099 0.195 0.290 0.389 0.359 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] pillow : 0.449 0.646 0.678 0.857 0.632 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] towel : 0.029 0.091 0.295 0.286 0.158 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] suitcase : 0.034 0.047 0.250 0.182 0.286 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] backpack : 0.351 0.381 0.381 0.667 0.462 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] crate : 0.000 0.000 0.091 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] keyboard : 0.217 0.279 0.328 0.909 0.256 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] toilet : 0.745 0.889 0.988 1.000 0.889 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] printer : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] microwave : 0.339 0.472 0.672 0.800 0.500 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] shoes : 0.068 0.094 0.358 0.467 0.171 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] socket : 0.109 0.286 0.470 0.840 0.300 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] bottle : 0.046 0.071 0.178 0.304 0.169 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] bucket : 0.101 0.102 0.106 0.122 0.714 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] cushion : 0.037 0.167 0.167 1.000 0.167 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] telephone : 0.071 0.116 0.213 0.600 0.176 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] laptop : 0.097 0.125 0.375 1.000 0.125 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] plant pot : 0.000 0.000 0.325 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] cup : 0.082 0.138 0.276 0.889 0.182 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] light switch : 0.117 0.291 0.492 0.579 0.338 [2025-04-28 04:47:00,465 INFO hook.py line 395 1619929] speaker : 0.124 0.201 0.288 1.000 0.182 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] table lamp : 0.389 0.500 0.500 1.000 0.500 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] kettle : 0.019 0.028 0.028 0.333 0.167 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] smoke detector : 0.478 0.657 0.661 0.889 0.667 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] power strip : 0.022 0.042 0.097 0.167 0.300 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] mouse : 0.193 0.355 0.424 0.424 0.438 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] cutting board : 0.194 0.500 0.500 1.000 0.500 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] toilet paper : 0.026 0.059 0.118 1.000 0.059 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] clock : 0.389 0.667 0.667 1.000 0.667 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] tap : 0.059 0.176 0.444 0.667 0.222 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] soap dispenser : 0.247 0.373 0.373 0.500 0.600 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] whiteboard eraser: 0.021 0.065 0.065 0.286 0.333 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] toilet brush : 0.054 0.145 0.263 0.429 0.500 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 04:47:00,466 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 04:47:00,466 INFO hook.py line 404 1619929] average : 0.142 0.229 0.333 0.445 0.296 [2025-04-28 04:47:00,466 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 04:47:00,467 INFO hook.py line 480 1619929] Total Process Time: 41.373 s [2025-04-28 04:47:00,467 INFO hook.py line 481 1619929] Average Process Time: 837.066 ms [2025-04-28 04:47:00,467 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 04:47:00,599 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.229 [2025-04-28 04:47:00,601 INFO hook.py line 685 1619929] Currently Best AP50: 0.229 [2025-04-28 04:47:00,603 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:48:28,924 INFO hook.py line 650 1619929] Train: [17/512][50/242] Data 0.015 (0.016) Batch 1.310 (1.421) Remain 47:20:58 loss: 7.7088 Lr: 2.91455e-04 Mem R(MA/MR): 21698 (21200/35474) [2025-04-28 04:49:41,063 INFO hook.py line 650 1619929] Train: [17/512][100/242] Data 0.015 (0.028) Batch 1.330 (1.432) Remain 47:42:32 loss: 7.2441 Lr: 2.91346e-04 Mem R(MA/MR): 21722 (21200/35474) [2025-04-28 04:50:52,054 INFO hook.py line 650 1619929] Train: [17/512][150/242] Data 0.016 (0.024) Batch 1.436 (1.428) Remain 47:33:00 loss: 6.8804 Lr: 2.91237e-04 Mem R(MA/MR): 23550 (21200/35474) [2025-04-28 04:52:01,584 INFO hook.py line 650 1619929] Train: [17/512][200/242] Data 0.018 (0.022) Batch 1.205 (1.418) Remain 47:12:55 loss: 9.4542 Lr: 2.91127e-04 Mem R(MA/MR): 23550 (21200/35474) [2025-04-28 04:52:59,186 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7362 loss_mask: 0.0569 loss_dice: 3.1196 loss_score: 0.0000 loss_bbox: 0.0667 loss_sp_cls: 1.3312 loss: 8.4588 [2025-04-28 04:53:05,043 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 04:54:40,782 INFO hook.py line 650 1619929] Train: [18/512][50/242] Data 0.018 (0.017) Batch 1.441 (1.474) Remain 49:02:12 loss: 7.5788 Lr: 2.90926e-04 Mem R(MA/MR): 26080 (21200/35474) [2025-04-28 04:55:52,687 INFO hook.py line 650 1619929] Train: [18/512][100/242] Data 0.016 (0.016) Batch 1.609 (1.456) Remain 48:23:43 loss: 7.4208 Lr: 2.90817e-04 Mem R(MA/MR): 26092 (21200/35474) [2025-04-28 04:57:06,073 INFO hook.py line 650 1619929] Train: [18/512][150/242] Data 0.016 (0.016) Batch 1.486 (1.460) Remain 48:30:43 loss: 8.9933 Lr: 2.90707e-04 Mem R(MA/MR): 26092 (21200/35474) [2025-04-28 04:58:15,651 INFO hook.py line 650 1619929] Train: [18/512][200/242] Data 0.017 (0.016) Batch 1.385 (1.442) Remain 47:55:03 loss: 9.3557 Lr: 2.90598e-04 Mem R(MA/MR): 26092 (21200/35474) [2025-04-28 04:59:11,624 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7287 loss_mask: 0.0570 loss_dice: 3.0865 loss_score: 0.0000 loss_bbox: 0.0670 loss_sp_cls: 1.3137 loss: 8.3770 [2025-04-28 04:59:14,843 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:00:45,094 INFO hook.py line 650 1619929] Train: [19/512][50/242] Data 0.019 (0.016) Batch 1.560 (1.488) Remain 49:23:49 loss: 7.4213 Lr: 2.90397e-04 Mem R(MA/MR): 23908 (21200/35474) [2025-04-28 05:01:56,570 INFO hook.py line 650 1619929] Train: [19/512][100/242] Data 0.016 (0.016) Batch 1.407 (1.458) Remain 48:22:27 loss: 8.1436 Lr: 2.90288e-04 Mem R(MA/MR): 23944 (21200/35474) [2025-04-28 05:03:05,860 INFO hook.py line 650 1619929] Train: [19/512][150/242] Data 0.016 (0.016) Batch 1.317 (1.433) Remain 47:32:24 loss: 8.5282 Lr: 2.90178e-04 Mem R(MA/MR): 23944 (21200/35474) [2025-04-28 05:04:15,529 INFO hook.py line 650 1619929] Train: [19/512][200/242] Data 0.018 (0.016) Batch 1.393 (1.423) Remain 47:11:01 loss: 10.7987 Lr: 2.90069e-04 Mem R(MA/MR): 23944 (21200/35474) [2025-04-28 05:05:11,443 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7218 loss_mask: 0.0561 loss_dice: 3.0780 loss_score: 0.0000 loss_bbox: 0.0656 loss_sp_cls: 1.3037 loss: 8.3231 [2025-04-28 05:05:16,452 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:06:50,514 INFO hook.py line 650 1619929] Train: [20/512][50/242] Data 0.016 (0.016) Batch 1.375 (1.453) Remain 48:08:45 loss: 7.2184 Lr: 2.89868e-04 Mem R(MA/MR): 22368 (21200/35474) [2025-04-28 05:08:02,041 INFO hook.py line 650 1619929] Train: [20/512][100/242] Data 0.015 (0.016) Batch 1.418 (1.442) Remain 47:44:09 loss: 8.1038 Lr: 2.89758e-04 Mem R(MA/MR): 27604 (21200/35474) [2025-04-28 05:09:12,318 INFO hook.py line 650 1619929] Train: [20/512][150/242] Data 0.016 (0.016) Batch 1.490 (1.429) Remain 47:18:34 loss: 7.9921 Lr: 2.89649e-04 Mem R(MA/MR): 27604 (21200/35474) [2025-04-28 05:10:25,451 INFO hook.py line 650 1619929] Train: [20/512][200/242] Data 0.015 (0.016) Batch 1.408 (1.438) Remain 47:34:11 loss: 8.9628 Lr: 2.89540e-04 Mem R(MA/MR): 27604 (21200/35474) [2025-04-28 05:11:21,820 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7001 loss_mask: 0.0537 loss_dice: 3.0124 loss_score: 0.0000 loss_bbox: 0.0641 loss_sp_cls: 1.2801 loss: 8.1410 [2025-04-28 05:11:26,622 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:13:00,392 INFO hook.py line 650 1619929] Train: [21/512][50/242] Data 0.017 (0.016) Batch 1.370 (1.452) Remain 47:59:12 loss: 8.0907 Lr: 2.89340e-04 Mem R(MA/MR): 23326 (21200/35474) [2025-04-28 05:14:09,189 INFO hook.py line 650 1619929] Train: [21/512][100/242] Data 0.016 (0.016) Batch 1.387 (1.413) Remain 46:40:43 loss: 7.4129 Lr: 2.89231e-04 Mem R(MA/MR): 25086 (21200/35474) [2025-04-28 05:15:18,397 INFO hook.py line 650 1619929] Train: [21/512][150/242] Data 0.015 (0.016) Batch 1.275 (1.403) Remain 46:20:24 loss: 7.9061 Lr: 2.89122e-04 Mem R(MA/MR): 25086 (21200/35474) [2025-04-28 05:16:27,952 INFO hook.py line 650 1619929] Train: [21/512][200/242] Data 0.015 (0.016) Batch 1.332 (1.400) Remain 46:13:18 loss: 7.6487 Lr: 2.89012e-04 Mem R(MA/MR): 25086 (21200/35474) [2025-04-28 05:17:23,803 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7063 loss_mask: 0.0540 loss_dice: 3.0201 loss_score: 0.0000 loss_bbox: 0.0650 loss_sp_cls: 1.2787 loss: 8.1699 [2025-04-28 05:17:26,520 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:18:53,708 INFO hook.py line 650 1619929] Train: [22/512][50/242] Data 0.015 (0.016) Batch 1.331 (1.514) Remain 49:57:03 loss: 7.3482 Lr: 2.88811e-04 Mem R(MA/MR): 26288 (21200/35474) [2025-04-28 05:20:02,721 INFO hook.py line 650 1619929] Train: [22/512][100/242] Data 0.016 (0.016) Batch 1.485 (1.445) Remain 47:39:20 loss: 8.9160 Lr: 2.88701e-04 Mem R(MA/MR): 30122 (21200/35474) [2025-04-28 05:21:13,925 INFO hook.py line 650 1619929] Train: [22/512][150/242] Data 0.019 (0.016) Batch 1.214 (1.438) Remain 47:24:01 loss: 8.6657 Lr: 2.88592e-04 Mem R(MA/MR): 30122 (21200/35474) [2025-04-28 05:22:21,917 INFO hook.py line 650 1619929] Train: [22/512][200/242] Data 0.014 (0.016) Batch 1.376 (1.418) Remain 46:43:39 loss: 9.6238 Lr: 2.88483e-04 Mem R(MA/MR): 30122 (21200/35474) [2025-04-28 05:23:18,753 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7076 loss_mask: 0.0562 loss_dice: 3.0628 loss_score: 0.0000 loss_bbox: 0.0656 loss_sp_cls: 1.2921 loss: 8.2629 [2025-04-28 05:23:18,890 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:24:53,349 INFO hook.py line 650 1619929] Train: [23/512][50/242] Data 0.015 (0.017) Batch 1.458 (1.499) Remain 49:20:59 loss: 6.8788 Lr: 2.88281e-04 Mem R(MA/MR): 20874 (21200/35474) [2025-04-28 05:26:04,220 INFO hook.py line 650 1619929] Train: [23/512][100/242] Data 0.017 (0.017) Batch 1.504 (1.457) Remain 47:56:50 loss: 8.2941 Lr: 2.88172e-04 Mem R(MA/MR): 22454 (21200/35474) [2025-04-28 05:27:14,522 INFO hook.py line 650 1619929] Train: [23/512][150/242] Data 0.022 (0.017) Batch 1.447 (1.440) Remain 47:21:29 loss: 8.5787 Lr: 2.88062e-04 Mem R(MA/MR): 22454 (21200/35474) [2025-04-28 05:28:25,930 INFO hook.py line 650 1619929] Train: [23/512][200/242] Data 0.014 (0.017) Batch 1.284 (1.437) Remain 47:14:35 loss: 7.6423 Lr: 2.87953e-04 Mem R(MA/MR): 24346 (21200/35474) [2025-04-28 05:29:22,044 INFO misc.py line 135 1619929] Train result: loss_cls: 0.7036 loss_mask: 0.0551 loss_dice: 3.0343 loss_score: 0.0000 loss_bbox: 0.0659 loss_sp_cls: 1.2798 loss: 8.2006 [2025-04-28 05:29:26,210 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:30:59,338 INFO hook.py line 650 1619929] Train: [24/512][50/242] Data 0.015 (0.017) Batch 1.243 (1.445) Remain 47:27:50 loss: 6.9759 Lr: 2.87752e-04 Mem R(MA/MR): 19820 (21200/35474) [2025-04-28 05:32:13,534 INFO hook.py line 650 1619929] Train: [24/512][100/242] Data 0.017 (0.016) Batch 1.569 (1.465) Remain 48:06:35 loss: 8.0392 Lr: 2.87642e-04 Mem R(MA/MR): 22190 (21200/35474) [2025-04-28 05:33:25,900 INFO hook.py line 650 1619929] Train: [24/512][150/242] Data 0.016 (0.016) Batch 1.354 (1.459) Remain 47:53:40 loss: 7.6190 Lr: 2.87533e-04 Mem R(MA/MR): 24242 (21200/35474) [2025-04-28 05:34:36,449 INFO hook.py line 650 1619929] Train: [24/512][200/242] Data 0.015 (0.016) Batch 1.407 (1.447) Remain 47:28:33 loss: 8.7689 Lr: 2.87423e-04 Mem R(MA/MR): 24242 (21200/35474) [2025-04-28 05:35:32,370 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6906 loss_mask: 0.0560 loss_dice: 2.9924 loss_score: 0.0000 loss_bbox: 0.0645 loss_sp_cls: 1.2631 loss: 8.0798 [2025-04-28 05:35:36,592 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 05:35:38,986 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.8606 Process Time: 0.345 Mem R(MA/MR): 4368 (21200/35474) [2025-04-28 05:35:40,377 INFO hook.py line 449 1619929] Test: [2/50] Loss 7.3916 Process Time: 0.483 Mem R(MA/MR): 7174 (21200/35474) [2025-04-28 05:35:42,437 INFO hook.py line 449 1619929] Test: [3/50] Loss 8.6602 Process Time: 0.985 Mem R(MA/MR): 9888 (21200/35474) [2025-04-28 05:35:50,399 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.9847 Process Time: 1.130 Mem R(MA/MR): 19578 (21200/35474) [2025-04-28 05:35:52,328 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.5603 Process Time: 0.795 Mem R(MA/MR): 7120 (21200/35474) [2025-04-28 05:35:54,254 INFO hook.py line 449 1619929] Test: [6/50] Loss 6.0531 Process Time: 0.622 Mem R(MA/MR): 11296 (21200/35474) [2025-04-28 05:35:55,056 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.6201 Process Time: 0.212 Mem R(MA/MR): 6234 (21200/35474) [2025-04-28 05:35:55,491 INFO hook.py line 449 1619929] Test: [8/50] Loss 7.4052 Process Time: 0.144 Mem R(MA/MR): 4454 (21200/35474) [2025-04-28 05:35:56,495 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.9979 Process Time: 0.222 Mem R(MA/MR): 11648 (21200/35474) [2025-04-28 05:35:58,073 INFO hook.py line 449 1619929] Test: [10/50] Loss 6.3986 Process Time: 0.382 Mem R(MA/MR): 9558 (21200/35474) [2025-04-28 05:36:01,236 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.8480 Process Time: 0.774 Mem R(MA/MR): 18564 (21200/35474) [2025-04-28 05:36:04,055 INFO hook.py line 449 1619929] Test: [12/50] Loss 8.3148 Process Time: 0.545 Mem R(MA/MR): 15328 (21200/35474) [2025-04-28 05:36:05,207 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.5869 Process Time: 0.224 Mem R(MA/MR): 8866 (21200/35474) [2025-04-28 05:36:05,610 INFO hook.py line 449 1619929] Test: [14/50] Loss 4.4934 Process Time: 0.128 Mem R(MA/MR): 5044 (21200/35474) [2025-04-28 05:36:08,768 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.8380 Process Time: 0.504 Mem R(MA/MR): 16246 (21200/35474) [2025-04-28 05:36:11,860 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0508 Process Time: 1.042 Mem R(MA/MR): 14268 (21200/35474) [2025-04-28 05:36:12,773 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.2788 Process Time: 0.288 Mem R(MA/MR): 6770 (21200/35474) [2025-04-28 05:36:13,678 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.7801 Process Time: 0.222 Mem R(MA/MR): 8554 (21200/35474) [2025-04-28 05:36:15,214 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.1829 Process Time: 0.166 Mem R(MA/MR): 6196 (21200/35474) [2025-04-28 05:36:16,868 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.0482 Process Time: 0.226 Mem R(MA/MR): 11436 (21200/35474) [2025-04-28 05:36:26,396 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8049 Process Time: 1.214 Mem R(MA/MR): 23658 (21200/35474) [2025-04-28 05:36:27,504 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7175 Process Time: 0.362 Mem R(MA/MR): 6952 (21200/35474) [2025-04-28 05:36:35,873 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.4486 Process Time: 0.610 Mem R(MA/MR): 8434 (21200/35474) [2025-04-28 05:36:36,997 INFO hook.py line 449 1619929] Test: [24/50] Loss 6.3094 Process Time: 0.483 Mem R(MA/MR): 5496 (21200/35474) [2025-04-28 05:36:38,673 INFO hook.py line 449 1619929] Test: [25/50] Loss 4.1260 Process Time: 0.659 Mem R(MA/MR): 9780 (21200/35474) [2025-04-28 05:36:46,458 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.8989 Process Time: 1.572 Mem R(MA/MR): 31768 (21200/35474) [2025-04-28 05:36:48,547 INFO hook.py line 449 1619929] Test: [27/50] Loss 10.3119 Process Time: 0.395 Mem R(MA/MR): 10292 (21200/35474) [2025-04-28 05:36:49,897 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.6055 Process Time: 0.427 Mem R(MA/MR): 8946 (21200/35474) [2025-04-28 05:36:54,696 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.7360 Process Time: 0.349 Mem R(MA/MR): 17248 (21200/35474) [2025-04-28 05:36:56,600 INFO hook.py line 449 1619929] Test: [30/50] Loss 7.1795 Process Time: 0.668 Mem R(MA/MR): 7776 (21200/35474) [2025-04-28 05:37:00,874 INFO hook.py line 449 1619929] Test: [31/50] Loss 9.6545 Process Time: 0.909 Mem R(MA/MR): 20600 (21200/35474) [2025-04-28 05:37:01,160 INFO hook.py line 449 1619929] Test: [32/50] Loss 6.1584 Process Time: 0.123 Mem R(MA/MR): 4118 (21200/35474) [2025-04-28 05:37:04,580 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.3565 Process Time: 0.357 Mem R(MA/MR): 24410 (21200/35474) [2025-04-28 05:37:06,483 INFO hook.py line 449 1619929] Test: [34/50] Loss 5.0625 Process Time: 0.499 Mem R(MA/MR): 10008 (21200/35474) [2025-04-28 05:37:08,265 INFO hook.py line 449 1619929] Test: [35/50] Loss 9.5203 Process Time: 0.578 Mem R(MA/MR): 13758 (21200/35474) [2025-04-28 05:37:08,691 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.4683 Process Time: 0.148 Mem R(MA/MR): 6338 (21200/35474) [2025-04-28 05:37:12,378 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.1736 Process Time: 0.712 Mem R(MA/MR): 28340 (21200/35474) [2025-04-28 05:37:14,744 INFO hook.py line 449 1619929] Test: [38/50] Loss 7.3122 Process Time: 1.051 Mem R(MA/MR): 10898 (21200/35474) [2025-04-28 05:37:15,330 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.8829 Process Time: 0.234 Mem R(MA/MR): 5614 (21200/35474) [2025-04-28 05:37:16,573 INFO hook.py line 449 1619929] Test: [40/50] Loss 5.2298 Process Time: 0.386 Mem R(MA/MR): 10328 (21200/35474) [2025-04-28 05:37:17,684 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.7733 Process Time: 0.353 Mem R(MA/MR): 9276 (21200/35474) [2025-04-28 05:37:18,143 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.5349 Process Time: 0.126 Mem R(MA/MR): 5576 (21200/35474) [2025-04-28 05:37:18,562 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.9844 Process Time: 0.125 Mem R(MA/MR): 5668 (21200/35474) [2025-04-28 05:37:19,224 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.9949 Process Time: 0.224 Mem R(MA/MR): 7150 (21200/35474) [2025-04-28 05:37:19,822 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.8966 Process Time: 0.147 Mem R(MA/MR): 5370 (21200/35474) [2025-04-28 05:37:21,969 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.6818 Process Time: 0.623 Mem R(MA/MR): 14740 (21200/35474) [2025-04-28 05:37:30,220 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.5634 Process Time: 1.881 Mem R(MA/MR): 20394 (21200/35474) [2025-04-28 05:37:41,025 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.3453 Process Time: 2.472 Mem R(MA/MR): 35294 (21200/35474) [2025-04-28 05:37:42,424 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.9019 Process Time: 0.332 Mem R(MA/MR): 5764 (21200/35474) [2025-04-28 05:37:44,992 INFO hook.py line 449 1619929] Test: [50/50] Loss 6.7668 Process Time: 0.709 Mem R(MA/MR): 13428 (21200/35474) [2025-04-28 05:37:49,030 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 05:37:49,030 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 05:37:49,030 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] table : 0.128 0.370 0.714 0.593 0.471 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] door : 0.352 0.660 0.823 0.852 0.658 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] ceiling lamp : 0.482 0.656 0.777 0.875 0.619 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] cabinet : 0.208 0.357 0.450 0.540 0.403 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] blinds : 0.225 0.506 0.732 0.560 0.609 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] curtain : 0.248 0.391 0.575 0.412 0.583 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] chair : 0.444 0.646 0.751 0.684 0.693 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] storage cabinet: 0.126 0.287 0.600 0.455 0.400 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] office chair : 0.594 0.604 0.604 0.729 0.729 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] bookshelf : 0.158 0.552 0.601 0.700 0.636 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] whiteboard : 0.479 0.630 0.669 0.821 0.657 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] window : 0.031 0.106 0.462 0.294 0.220 [2025-04-28 05:37:49,030 INFO hook.py line 395 1619929] box : 0.078 0.149 0.354 0.360 0.249 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] monitor : 0.494 0.674 0.770 0.843 0.614 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] shelf : 0.035 0.094 0.286 0.500 0.167 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] heater : 0.295 0.537 0.776 0.870 0.526 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] kitchen cabinet: 0.088 0.266 0.633 0.692 0.360 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] sofa : 0.295 0.396 0.818 0.583 0.583 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] bed : 0.134 0.354 0.510 0.600 0.375 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] trash can : 0.402 0.528 0.627 0.804 0.631 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] book : 0.006 0.019 0.035 0.085 0.064 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] plant : 0.195 0.396 0.689 0.750 0.500 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] blanket : 0.172 0.273 0.521 0.750 0.273 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] tv : 0.698 0.803 0.803 0.833 0.833 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] computer tower : 0.154 0.196 0.325 0.667 0.190 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] refrigerator : 0.213 0.333 0.333 1.000 0.333 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] jacket : 0.014 0.060 0.214 0.174 0.364 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] sink : 0.249 0.462 0.845 0.722 0.591 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] bag : 0.075 0.100 0.138 0.250 0.259 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] picture : 0.123 0.236 0.305 0.600 0.308 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] pillow : 0.372 0.548 0.742 0.786 0.579 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] towel : 0.045 0.119 0.260 0.462 0.158 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] suitcase : 0.059 0.147 0.461 0.267 0.571 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] backpack : 0.299 0.414 0.417 0.545 0.462 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] crate : 0.024 0.115 0.179 0.333 0.182 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] keyboard : 0.263 0.334 0.434 0.652 0.385 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] toilet : 0.720 0.876 1.000 0.889 0.889 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] printer : 0.023 0.028 0.093 0.500 0.111 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.001 0.000 0.000 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] painting : 0.059 0.062 0.083 0.125 1.000 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] microwave : 0.240 0.399 0.646 0.667 0.500 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] shoes : 0.022 0.083 0.351 0.294 0.244 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] socket : 0.089 0.237 0.484 0.364 0.400 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] bottle : 0.056 0.133 0.183 0.316 0.217 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] bucket : 0.047 0.048 0.052 0.138 0.571 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] cushion : 0.000 0.000 0.167 0.000 0.000 [2025-04-28 05:37:49,031 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] telephone : 0.098 0.237 0.479 0.600 0.353 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] laptop : 0.041 0.060 0.060 0.286 0.250 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] plant pot : 0.018 0.059 0.256 0.500 0.188 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] cup : 0.148 0.227 0.305 0.545 0.273 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] light switch : 0.140 0.294 0.473 0.460 0.354 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] speaker : 0.065 0.137 0.257 0.400 0.182 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] kettle : 0.153 0.167 0.167 1.000 0.167 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] smoke detector : 0.554 0.721 0.779 1.000 0.625 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] power strip : 0.003 0.007 0.008 0.143 0.100 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] mouse : 0.311 0.451 0.507 0.737 0.438 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] toilet paper : 0.096 0.176 0.176 1.000 0.176 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] paper towel : 0.056 0.250 0.250 1.000 0.250 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] clock : 0.185 0.333 0.333 1.000 0.333 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] tap : 0.122 0.219 0.484 0.600 0.333 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] soap dispenser : 0.259 0.317 0.317 0.667 0.400 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] whiteboard eraser: 0.019 0.042 0.096 0.500 0.167 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] toilet brush : 0.079 0.203 0.606 0.600 0.500 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,032 INFO hook.py line 395 1619929] headphones : 0.167 0.500 0.500 1.000 0.500 [2025-04-28 05:37:49,033 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,033 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 05:37:49,033 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 05:37:49,033 INFO hook.py line 404 1619929] average : 0.153 0.245 0.352 0.475 0.320 [2025-04-28 05:37:49,033 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 05:37:49,033 INFO hook.py line 480 1619929] Total Process Time: 28.168 s [2025-04-28 05:37:49,033 INFO hook.py line 481 1619929] Average Process Time: 567.800 ms [2025-04-28 05:37:49,033 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 05:37:49,083 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.245 [2025-04-28 05:37:49,085 INFO hook.py line 685 1619929] Currently Best AP50: 0.245 [2025-04-28 05:37:49,087 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:39:24,843 INFO hook.py line 650 1619929] Train: [25/512][50/242] Data 0.018 (0.042) Batch 1.411 (1.466) Remain 48:03:29 loss: 7.2397 Lr: 2.87222e-04 Mem R(MA/MR): 29310 (21200/35474) [2025-04-28 05:40:36,292 INFO hook.py line 650 1619929] Train: [25/512][100/242] Data 0.016 (0.029) Batch 1.563 (1.447) Remain 47:25:06 loss: 6.4515 Lr: 2.87112e-04 Mem R(MA/MR): 29310 (21200/35474) [2025-04-28 05:41:46,328 INFO hook.py line 650 1619929] Train: [25/512][150/242] Data 0.017 (0.025) Batch 1.434 (1.431) Remain 46:53:10 loss: 9.4266 Lr: 2.87003e-04 Mem R(MA/MR): 29310 (21200/35474) [2025-04-28 05:42:56,431 INFO hook.py line 650 1619929] Train: [25/512][200/242] Data 0.015 (0.022) Batch 1.384 (1.424) Remain 46:37:31 loss: 7.2346 Lr: 2.86893e-04 Mem R(MA/MR): 33424 (21200/35474) [2025-04-28 05:43:52,345 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6946 loss_mask: 0.0556 loss_dice: 3.0031 loss_score: 0.0000 loss_bbox: 0.0647 loss_sp_cls: 1.2675 loss: 8.0990 [2025-04-28 05:43:53,045 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:45:27,350 INFO hook.py line 650 1619929] Train: [26/512][50/242] Data 0.015 (0.017) Batch 1.340 (1.459) Remain 47:43:57 loss: 8.5651 Lr: 2.86692e-04 Mem R(MA/MR): 24870 (21200/35474) [2025-04-28 05:46:36,903 INFO hook.py line 650 1619929] Train: [26/512][100/242] Data 0.016 (0.016) Batch 1.416 (1.424) Remain 46:34:19 loss: 7.8021 Lr: 2.86582e-04 Mem R(MA/MR): 24870 (21200/35474) [2025-04-28 05:47:46,417 INFO hook.py line 650 1619929] Train: [26/512][150/242] Data 0.015 (0.016) Batch 1.328 (1.412) Remain 46:10:45 loss: 8.1518 Lr: 2.86473e-04 Mem R(MA/MR): 24870 (21200/35474) [2025-04-28 05:48:56,264 INFO hook.py line 650 1619929] Train: [26/512][200/242] Data 0.015 (0.016) Batch 1.456 (1.408) Remain 46:01:54 loss: 9.3442 Lr: 2.86363e-04 Mem R(MA/MR): 24870 (21200/35474) [2025-04-28 05:49:52,643 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6907 loss_mask: 0.0561 loss_dice: 2.9939 loss_score: 0.0000 loss_bbox: 0.0660 loss_sp_cls: 1.2638 loss: 8.0864 [2025-04-28 05:49:54,238 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:51:31,613 INFO hook.py line 650 1619929] Train: [27/512][50/242] Data 0.016 (0.016) Batch 1.653 (1.481) Remain 48:21:15 loss: 7.1309 Lr: 2.86162e-04 Mem R(MA/MR): 22672 (21200/35474) [2025-04-28 05:52:42,255 INFO hook.py line 650 1619929] Train: [27/512][100/242] Data 0.016 (0.016) Batch 1.349 (1.446) Remain 47:11:29 loss: 7.7641 Lr: 2.86052e-04 Mem R(MA/MR): 22674 (21200/35474) [2025-04-28 05:53:53,662 INFO hook.py line 650 1619929] Train: [27/512][150/242] Data 0.017 (0.016) Batch 1.425 (1.440) Remain 46:58:34 loss: 8.7618 Lr: 2.85943e-04 Mem R(MA/MR): 22682 (21200/35474) [2025-04-28 05:55:04,644 INFO hook.py line 650 1619929] Train: [27/512][200/242] Data 0.015 (0.016) Batch 1.414 (1.435) Remain 46:47:24 loss: 9.2682 Lr: 2.85833e-04 Mem R(MA/MR): 22682 (21200/35474) [2025-04-28 05:56:01,358 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6817 loss_mask: 0.0548 loss_dice: 2.9745 loss_score: 0.0000 loss_bbox: 0.0655 loss_sp_cls: 1.2464 loss: 8.0280 [2025-04-28 05:56:04,138 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 05:57:32,552 INFO hook.py line 650 1619929] Train: [28/512][50/242] Data 0.015 (0.016) Batch 1.463 (1.450) Remain 47:15:42 loss: 9.1760 Lr: 2.85632e-04 Mem R(MA/MR): 20132 (21200/35474) [2025-04-28 05:58:45,045 INFO hook.py line 650 1619929] Train: [28/512][100/242] Data 0.015 (0.016) Batch 1.394 (1.450) Remain 47:14:06 loss: 6.6763 Lr: 2.85522e-04 Mem R(MA/MR): 23850 (21200/35474) [2025-04-28 05:59:56,111 INFO hook.py line 650 1619929] Train: [28/512][150/242] Data 0.017 (0.016) Batch 1.461 (1.440) Remain 46:53:47 loss: 9.1040 Lr: 2.85412e-04 Mem R(MA/MR): 23870 (21200/35474) [2025-04-28 06:01:07,332 INFO hook.py line 650 1619929] Train: [28/512][200/242] Data 0.015 (0.016) Batch 1.524 (1.436) Remain 46:44:44 loss: 7.6265 Lr: 2.85303e-04 Mem R(MA/MR): 23870 (21200/35474) [2025-04-28 06:02:05,874 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6840 loss_mask: 0.0547 loss_dice: 2.9640 loss_score: 0.0000 loss_bbox: 0.0662 loss_sp_cls: 1.2561 loss: 8.0149 [2025-04-28 06:02:05,940 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:03:34,001 INFO hook.py line 650 1619929] Train: [29/512][50/242] Data 0.016 (0.016) Batch 1.491 (1.452) Remain 47:13:42 loss: 9.5281 Lr: 2.85101e-04 Mem R(MA/MR): 25266 (21200/35474) [2025-04-28 06:04:46,465 INFO hook.py line 650 1619929] Train: [29/512][100/242] Data 0.016 (0.016) Batch 1.473 (1.451) Remain 47:09:31 loss: 8.2692 Lr: 2.84992e-04 Mem R(MA/MR): 29310 (21200/35474) [2025-04-28 06:05:57,399 INFO hook.py line 650 1619929] Train: [29/512][150/242] Data 0.015 (0.016) Batch 1.473 (1.440) Remain 46:47:05 loss: 7.7577 Lr: 2.84882e-04 Mem R(MA/MR): 29314 (21200/35474) [2025-04-28 06:07:08,074 INFO hook.py line 650 1619929] Train: [29/512][200/242] Data 0.014 (0.016) Batch 1.226 (1.433) Remain 46:32:53 loss: 5.6861 Lr: 2.84773e-04 Mem R(MA/MR): 29314 (21200/35474) [2025-04-28 06:08:04,952 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6606 loss_mask: 0.0525 loss_dice: 2.8881 loss_score: 0.0000 loss_bbox: 0.0640 loss_sp_cls: 1.2207 loss: 7.8097 [2025-04-28 06:08:05,363 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:09:30,642 INFO hook.py line 650 1619929] Train: [30/512][50/242] Data 0.016 (0.017) Batch 1.454 (1.459) Remain 47:21:28 loss: 7.2617 Lr: 2.84571e-04 Mem R(MA/MR): 22348 (21200/35474) [2025-04-28 06:10:41,128 INFO hook.py line 650 1619929] Train: [30/512][100/242] Data 0.016 (0.016) Batch 1.326 (1.434) Remain 46:30:36 loss: 7.8117 Lr: 2.84461e-04 Mem R(MA/MR): 22352 (21200/35474) [2025-04-28 06:11:53,836 INFO hook.py line 650 1619929] Train: [30/512][150/242] Data 0.015 (0.016) Batch 1.515 (1.441) Remain 46:42:57 loss: 6.7736 Lr: 2.84352e-04 Mem R(MA/MR): 24526 (21200/35474) [2025-04-28 06:13:01,746 INFO hook.py line 650 1619929] Train: [30/512][200/242] Data 0.013 (0.016) Batch 1.259 (1.420) Remain 46:01:03 loss: 5.0492 Lr: 2.84242e-04 Mem R(MA/MR): 24540 (21200/35474) [2025-04-28 06:13:58,358 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6310 loss_mask: 0.0491 loss_dice: 2.8006 loss_score: 0.0000 loss_bbox: 0.0613 loss_sp_cls: 1.1841 loss: 7.5446 [2025-04-28 06:13:58,420 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:15:24,201 INFO hook.py line 650 1619929] Train: [31/512][50/242] Data 0.016 (0.017) Batch 1.354 (1.473) Remain 47:42:07 loss: 6.5737 Lr: 2.84040e-04 Mem R(MA/MR): 22032 (21200/35474) [2025-04-28 06:16:34,613 INFO hook.py line 650 1619929] Train: [31/512][100/242] Data 0.016 (0.016) Batch 1.511 (1.440) Remain 46:36:10 loss: 6.8892 Lr: 2.83931e-04 Mem R(MA/MR): 22032 (21200/35474) [2025-04-28 06:17:47,021 INFO hook.py line 650 1619929] Train: [31/512][150/242] Data 0.015 (0.016) Batch 1.425 (1.442) Remain 46:40:40 loss: 6.9785 Lr: 2.83821e-04 Mem R(MA/MR): 27124 (21200/35474) [2025-04-28 06:18:58,828 INFO hook.py line 650 1619929] Train: [31/512][200/242] Data 0.013 (0.016) Batch 1.412 (1.441) Remain 46:36:21 loss: 7.5604 Lr: 2.83711e-04 Mem R(MA/MR): 29768 (21200/35474) [2025-04-28 06:19:55,371 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6287 loss_mask: 0.0488 loss_dice: 2.7810 loss_score: 0.0000 loss_bbox: 0.0617 loss_sp_cls: 1.1792 loss: 7.5117 [2025-04-28 06:19:56,425 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:21:28,701 INFO hook.py line 650 1619929] Train: [32/512][50/242] Data 0.017 (0.016) Batch 1.423 (1.417) Remain 45:47:33 loss: 7.8280 Lr: 2.83510e-04 Mem R(MA/MR): 18440 (21200/35474) [2025-04-28 06:22:39,091 INFO hook.py line 650 1619929] Train: [32/512][100/242] Data 0.015 (0.016) Batch 1.414 (1.412) Remain 45:37:22 loss: 8.6158 Lr: 2.83400e-04 Mem R(MA/MR): 20216 (21200/35474) [2025-04-28 06:23:46,290 INFO hook.py line 650 1619929] Train: [32/512][150/242] Data 0.016 (0.016) Batch 1.255 (1.389) Remain 44:51:14 loss: 6.4118 Lr: 2.83290e-04 Mem R(MA/MR): 22102 (21200/35474) [2025-04-28 06:24:53,704 INFO hook.py line 650 1619929] Train: [32/512][200/242] Data 0.014 (0.016) Batch 1.360 (1.379) Remain 44:30:04 loss: 8.8054 Lr: 2.83181e-04 Mem R(MA/MR): 22116 (21200/35474) [2025-04-28 06:25:48,312 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6294 loss_mask: 0.0491 loss_dice: 2.7764 loss_score: 0.0000 loss_bbox: 0.0611 loss_sp_cls: 1.1828 loss: 7.5022 [2025-04-28 06:25:51,576 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 06:25:53,871 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.9283 Process Time: 0.382 Mem R(MA/MR): 4344 (21200/35474) [2025-04-28 06:25:55,463 INFO hook.py line 449 1619929] Test: [2/50] Loss 7.1375 Process Time: 0.515 Mem R(MA/MR): 7160 (21200/35474) [2025-04-28 06:25:57,589 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4761 Process Time: 1.022 Mem R(MA/MR): 9872 (21200/35474) [2025-04-28 06:26:05,618 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.6511 Process Time: 1.063 Mem R(MA/MR): 19910 (21200/35474) [2025-04-28 06:26:07,024 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.4189 Process Time: 0.484 Mem R(MA/MR): 6844 (21200/35474) [2025-04-28 06:26:08,389 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.3372 Process Time: 0.405 Mem R(MA/MR): 11608 (21200/35474) [2025-04-28 06:26:08,953 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.6681 Process Time: 0.159 Mem R(MA/MR): 6378 (21200/35474) [2025-04-28 06:26:09,318 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.8783 Process Time: 0.108 Mem R(MA/MR): 4378 (21200/35474) [2025-04-28 06:26:10,236 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.4139 Process Time: 0.207 Mem R(MA/MR): 11892 (21200/35474) [2025-04-28 06:26:11,505 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.7236 Process Time: 0.227 Mem R(MA/MR): 9602 (21200/35474) [2025-04-28 06:26:13,953 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.5507 Process Time: 0.402 Mem R(MA/MR): 19080 (21200/35474) [2025-04-28 06:26:17,171 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.8807 Process Time: 0.872 Mem R(MA/MR): 15514 (21200/35474) [2025-04-28 06:26:18,283 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0991 Process Time: 0.274 Mem R(MA/MR): 8804 (21200/35474) [2025-04-28 06:26:18,618 INFO hook.py line 449 1619929] Test: [14/50] Loss 4.5104 Process Time: 0.114 Mem R(MA/MR): 4938 (21200/35474) [2025-04-28 06:26:20,809 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.4342 Process Time: 0.287 Mem R(MA/MR): 16666 (21200/35474) [2025-04-28 06:26:22,886 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.7361 Process Time: 0.440 Mem R(MA/MR): 14654 (21200/35474) [2025-04-28 06:26:24,175 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.8155 Process Time: 0.536 Mem R(MA/MR): 6722 (21200/35474) [2025-04-28 06:26:25,172 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.4661 Process Time: 0.337 Mem R(MA/MR): 8478 (21200/35474) [2025-04-28 06:26:26,417 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.3614 Process Time: 0.234 Mem R(MA/MR): 6412 (21200/35474) [2025-04-28 06:26:27,838 INFO hook.py line 449 1619929] Test: [20/50] Loss 7.8246 Process Time: 0.226 Mem R(MA/MR): 11794 (21200/35474) [2025-04-28 06:26:36,601 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.7966 Process Time: 0.569 Mem R(MA/MR): 23572 (21200/35474) [2025-04-28 06:26:37,170 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3828 Process Time: 0.159 Mem R(MA/MR): 6876 (21200/35474) [2025-04-28 06:26:45,620 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.3438 Process Time: 0.321 Mem R(MA/MR): 10038 (21200/35474) [2025-04-28 06:26:46,062 INFO hook.py line 449 1619929] Test: [24/50] Loss 6.2517 Process Time: 0.128 Mem R(MA/MR): 5662 (21200/35474) [2025-04-28 06:26:47,163 INFO hook.py line 449 1619929] Test: [25/50] Loss 4.0326 Process Time: 0.238 Mem R(MA/MR): 9700 (21200/35474) [2025-04-28 06:26:54,778 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.7147 Process Time: 1.514 Mem R(MA/MR): 32146 (21200/35474) [2025-04-28 06:26:56,364 INFO hook.py line 449 1619929] Test: [27/50] Loss 9.5629 Process Time: 0.287 Mem R(MA/MR): 10554 (21200/35474) [2025-04-28 06:26:57,444 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.9123 Process Time: 0.204 Mem R(MA/MR): 9042 (21200/35474) [2025-04-28 06:27:03,393 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6185 Process Time: 0.863 Mem R(MA/MR): 17312 (21200/35474) [2025-04-28 06:27:04,224 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3921 Process Time: 0.185 Mem R(MA/MR): 7740 (21200/35474) [2025-04-28 06:27:08,271 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8307 Process Time: 0.366 Mem R(MA/MR): 20890 (21200/35474) [2025-04-28 06:27:09,022 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.8059 Process Time: 0.205 Mem R(MA/MR): 3808 (21200/35474) [2025-04-28 06:27:12,340 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.6726 Process Time: 0.587 Mem R(MA/MR): 24896 (21200/35474) [2025-04-28 06:27:13,269 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.5112 Process Time: 0.238 Mem R(MA/MR): 9918 (21200/35474) [2025-04-28 06:27:14,776 INFO hook.py line 449 1619929] Test: [35/50] Loss 9.0218 Process Time: 0.252 Mem R(MA/MR): 14190 (21200/35474) [2025-04-28 06:27:15,294 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.5844 Process Time: 0.190 Mem R(MA/MR): 6576 (21200/35474) [2025-04-28 06:27:19,487 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.3417 Process Time: 1.035 Mem R(MA/MR): 28568 (21200/35474) [2025-04-28 06:27:21,511 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.3006 Process Time: 0.439 Mem R(MA/MR): 11196 (21200/35474) [2025-04-28 06:27:21,972 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9475 Process Time: 0.147 Mem R(MA/MR): 5844 (21200/35474) [2025-04-28 06:27:23,103 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.6024 Process Time: 0.274 Mem R(MA/MR): 10642 (21200/35474) [2025-04-28 06:27:23,985 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.3756 Process Time: 0.202 Mem R(MA/MR): 9324 (21200/35474) [2025-04-28 06:27:24,440 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9412 Process Time: 0.151 Mem R(MA/MR): 5758 (21200/35474) [2025-04-28 06:27:24,910 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.3652 Process Time: 0.191 Mem R(MA/MR): 5848 (21200/35474) [2025-04-28 06:27:25,774 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.0664 Process Time: 0.373 Mem R(MA/MR): 7080 (21200/35474) [2025-04-28 06:27:26,965 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.3328 Process Time: 0.484 Mem R(MA/MR): 5548 (21200/35474) [2025-04-28 06:27:29,856 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.6034 Process Time: 0.869 Mem R(MA/MR): 15002 (21200/35474) [2025-04-28 06:27:37,428 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.9982 Process Time: 1.008 Mem R(MA/MR): 20118 (21200/35474) [2025-04-28 06:27:48,343 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.7333 Process Time: 2.030 Mem R(MA/MR): 35898 (21200/35898) [2025-04-28 06:27:48,973 INFO hook.py line 449 1619929] Test: [49/50] Loss 5.0842 Process Time: 0.270 Mem R(MA/MR): 6010 (21200/35898) [2025-04-28 06:27:51,859 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.8503 Process Time: 0.718 Mem R(MA/MR): 13914 (21200/35898) [2025-04-28 06:27:56,573 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 06:27:56,574 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 06:27:56,574 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] table : 0.197 0.550 0.770 0.672 0.603 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] door : 0.401 0.689 0.886 0.855 0.595 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] ceiling lamp : 0.500 0.707 0.825 0.921 0.641 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] cabinet : 0.231 0.401 0.487 0.516 0.478 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] blinds : 0.328 0.630 0.774 0.680 0.739 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] curtain : 0.147 0.188 0.536 0.400 0.333 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] chair : 0.561 0.725 0.815 0.781 0.717 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] storage cabinet: 0.146 0.256 0.523 0.526 0.400 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] office chair : 0.585 0.622 0.637 0.673 0.771 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] bookshelf : 0.137 0.549 0.758 0.857 0.545 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] whiteboard : 0.472 0.664 0.699 0.920 0.657 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] window : 0.080 0.221 0.510 0.463 0.275 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] box : 0.085 0.183 0.398 0.456 0.260 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] monitor : 0.518 0.634 0.719 0.898 0.629 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] shelf : 0.020 0.118 0.316 0.500 0.167 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] heater : 0.339 0.603 0.795 0.880 0.579 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] kitchen cabinet: 0.056 0.162 0.679 0.256 0.400 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] sofa : 0.614 0.811 0.878 0.900 0.750 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] bed : 0.160 0.268 0.411 0.600 0.375 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] trash can : 0.507 0.655 0.732 0.754 0.708 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] book : 0.004 0.012 0.031 0.098 0.064 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] plant : 0.320 0.505 0.674 0.769 0.556 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] blanket : 0.290 0.377 0.615 0.556 0.455 [2025-04-28 06:27:56,574 INFO hook.py line 395 1619929] tv : 0.885 1.000 1.000 1.000 1.000 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] computer tower : 0.131 0.185 0.391 0.370 0.238 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] refrigerator : 0.171 0.374 0.374 1.000 0.333 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] jacket : 0.073 0.212 0.420 0.417 0.455 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] sink : 0.328 0.567 0.916 0.700 0.636 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] bag : 0.094 0.140 0.140 0.800 0.148 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] picture : 0.079 0.163 0.305 0.526 0.256 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] pillow : 0.489 0.717 0.751 0.857 0.632 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] towel : 0.101 0.197 0.439 0.406 0.342 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] suitcase : 0.165 0.288 0.368 0.667 0.571 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] backpack : 0.324 0.426 0.481 0.833 0.385 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] crate : 0.008 0.035 0.312 0.188 0.273 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] keyboard : 0.323 0.446 0.524 0.850 0.436 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] toilet : 0.659 0.889 1.000 1.000 0.889 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] printer : 0.031 0.036 0.114 0.286 0.222 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] poster : 0.001 0.011 0.013 0.125 0.111 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] microwave : 0.270 0.625 0.835 1.000 0.625 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] shoes : 0.082 0.189 0.456 0.481 0.317 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] socket : 0.114 0.327 0.543 0.675 0.371 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] bottle : 0.061 0.109 0.193 0.288 0.253 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] bucket : 0.124 0.201 0.201 1.000 0.143 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] cushion : 0.063 0.139 0.500 0.667 0.333 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] telephone : 0.076 0.183 0.359 0.538 0.412 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] laptop : 0.224 0.404 0.585 0.400 0.750 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] plant pot : 0.033 0.177 0.293 0.571 0.250 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] cup : 0.107 0.207 0.254 0.522 0.273 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] light switch : 0.164 0.360 0.501 0.610 0.385 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] speaker : 0.130 0.144 0.182 0.667 0.182 [2025-04-28 06:27:56,575 INFO hook.py line 395 1619929] table lamp : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] smoke detector : 0.594 0.792 0.828 1.000 0.792 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] power strip : 0.039 0.062 0.226 0.400 0.200 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] mouse : 0.413 0.636 0.662 0.714 0.625 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] cutting board : 0.323 0.677 0.677 0.750 0.750 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] toilet paper : 0.063 0.126 0.128 1.000 0.118 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] paper towel : 0.056 0.125 0.125 1.000 0.125 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] clock : 0.333 0.667 0.667 1.000 0.667 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] tap : 0.098 0.171 0.556 0.750 0.333 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] soap dispenser : 0.474 0.707 0.707 1.000 0.600 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] bowl : 0.074 0.083 0.083 0.500 0.333 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] whiteboard eraser: 0.140 0.386 0.386 0.800 0.667 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] toilet brush : 0.163 0.445 0.587 0.571 0.667 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 06:27:56,576 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 06:27:56,576 INFO hook.py line 404 1619929] average : 0.186 0.303 0.411 0.571 0.359 [2025-04-28 06:27:56,576 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 06:27:56,577 INFO hook.py line 480 1619929] Total Process Time: 22.794 s [2025-04-28 06:27:56,577 INFO hook.py line 481 1619929] Average Process Time: 457.380 ms [2025-04-28 06:27:56,577 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 06:27:56,602 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.303 [2025-04-28 06:27:56,606 INFO hook.py line 685 1619929] Currently Best AP50: 0.303 [2025-04-28 06:27:56,606 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:29:29,169 INFO hook.py line 650 1619929] Train: [33/512][50/242] Data 0.016 (0.016) Batch 1.557 (1.419) Remain 45:45:42 loss: 7.5360 Lr: 2.82979e-04 Mem R(MA/MR): 24160 (21200/35898) [2025-04-28 06:30:40,618 INFO hook.py line 650 1619929] Train: [33/512][100/242] Data 0.015 (0.016) Batch 1.504 (1.424) Remain 45:54:35 loss: 8.5076 Lr: 2.82869e-04 Mem R(MA/MR): 26676 (21200/35898) [2025-04-28 06:31:52,470 INFO hook.py line 650 1619929] Train: [33/512][150/242] Data 0.017 (0.024) Batch 1.551 (1.428) Remain 46:01:57 loss: 9.1760 Lr: 2.82760e-04 Mem R(MA/MR): 26676 (21200/35898) [2025-04-28 06:33:03,440 INFO hook.py line 650 1619929] Train: [33/512][200/242] Data 0.014 (0.022) Batch 1.307 (1.426) Remain 45:56:20 loss: 5.8321 Lr: 2.82650e-04 Mem R(MA/MR): 26676 (21200/35898) [2025-04-28 06:33:58,663 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6269 loss_mask: 0.0502 loss_dice: 2.7858 loss_score: 0.0000 loss_bbox: 0.0618 loss_sp_cls: 1.1792 loss: 7.5144 [2025-04-28 06:34:00,105 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:35:35,938 INFO hook.py line 650 1619929] Train: [34/512][50/242] Data 0.016 (0.016) Batch 1.383 (1.472) Remain 47:23:01 loss: 6.3662 Lr: 2.82448e-04 Mem R(MA/MR): 20852 (21200/35898) [2025-04-28 06:36:50,535 INFO hook.py line 650 1619929] Train: [34/512][100/242] Data 0.016 (0.016) Batch 1.450 (1.482) Remain 47:41:27 loss: 7.9681 Lr: 2.82339e-04 Mem R(MA/MR): 20864 (21200/35898) [2025-04-28 06:38:00,637 INFO hook.py line 650 1619929] Train: [34/512][150/242] Data 0.016 (0.016) Batch 1.516 (1.455) Remain 46:47:29 loss: 8.0488 Lr: 2.82229e-04 Mem R(MA/MR): 20864 (21200/35898) [2025-04-28 06:39:12,808 INFO hook.py line 650 1619929] Train: [34/512][200/242] Data 0.019 (0.016) Batch 1.475 (1.452) Remain 46:40:35 loss: 8.1298 Lr: 2.82119e-04 Mem R(MA/MR): 22870 (21200/35898) [2025-04-28 06:40:09,325 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6272 loss_mask: 0.0512 loss_dice: 2.7983 loss_score: 0.0000 loss_bbox: 0.0613 loss_sp_cls: 1.1824 loss: 7.5315 [2025-04-28 06:40:09,392 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:41:42,272 INFO hook.py line 650 1619929] Train: [35/512][50/242] Data 0.015 (0.016) Batch 1.421 (1.438) Remain 46:12:01 loss: 7.0905 Lr: 2.81917e-04 Mem R(MA/MR): 23062 (21200/35898) [2025-04-28 06:42:53,484 INFO hook.py line 650 1619929] Train: [35/512][100/242] Data 0.015 (0.016) Batch 1.566 (1.431) Remain 45:56:43 loss: 6.8748 Lr: 2.81808e-04 Mem R(MA/MR): 24562 (21200/35898) [2025-04-28 06:44:04,385 INFO hook.py line 650 1619929] Train: [35/512][150/242] Data 0.015 (0.016) Batch 1.424 (1.427) Remain 45:46:56 loss: 9.0390 Lr: 2.81698e-04 Mem R(MA/MR): 29512 (21200/35898) [2025-04-28 06:45:13,927 INFO hook.py line 650 1619929] Train: [35/512][200/242] Data 0.015 (0.016) Batch 1.335 (1.418) Remain 45:28:15 loss: 8.4721 Lr: 2.81588e-04 Mem R(MA/MR): 29512 (21200/35898) [2025-04-28 06:46:10,901 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6283 loss_mask: 0.0508 loss_dice: 2.7988 loss_score: 0.0000 loss_bbox: 0.0632 loss_sp_cls: 1.1833 loss: 7.5522 [2025-04-28 06:46:12,524 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:47:39,630 INFO hook.py line 650 1619929] Train: [36/512][50/242] Data 0.016 (0.017) Batch 1.413 (1.478) Remain 47:22:07 loss: 8.8884 Lr: 2.81386e-04 Mem R(MA/MR): 21906 (21200/35898) [2025-04-28 06:48:47,756 INFO hook.py line 650 1619929] Train: [36/512][100/242] Data 0.017 (0.016) Batch 1.425 (1.418) Remain 45:26:32 loss: 7.2915 Lr: 2.81276e-04 Mem R(MA/MR): 23762 (21200/35898) [2025-04-28 06:49:59,715 INFO hook.py line 650 1619929] Train: [36/512][150/242] Data 0.018 (0.016) Batch 1.596 (1.425) Remain 45:38:55 loss: 7.9016 Lr: 2.81167e-04 Mem R(MA/MR): 23762 (21200/35898) [2025-04-28 06:51:10,305 INFO hook.py line 650 1619929] Train: [36/512][200/242] Data 0.013 (0.016) Batch 1.374 (1.422) Remain 45:31:05 loss: 6.9030 Lr: 2.81057e-04 Mem R(MA/MR): 23762 (21200/35898) [2025-04-28 06:52:09,428 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6245 loss_mask: 0.0516 loss_dice: 2.8066 loss_score: 0.0000 loss_bbox: 0.0626 loss_sp_cls: 1.1739 loss: 7.5381 [2025-04-28 06:52:13,417 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:53:48,542 INFO hook.py line 650 1619929] Train: [37/512][50/242] Data 0.016 (0.017) Batch 1.536 (1.446) Remain 46:15:21 loss: 6.7973 Lr: 2.80855e-04 Mem R(MA/MR): 24776 (21200/35898) [2025-04-28 06:54:59,758 INFO hook.py line 650 1619929] Train: [37/512][100/242] Data 0.017 (0.017) Batch 1.397 (1.435) Remain 45:52:30 loss: 7.6636 Lr: 2.80745e-04 Mem R(MA/MR): 28724 (21200/35898) [2025-04-28 06:56:09,320 INFO hook.py line 650 1619929] Train: [37/512][150/242] Data 0.017 (0.016) Batch 1.246 (1.420) Remain 45:22:47 loss: 6.3640 Lr: 2.80636e-04 Mem R(MA/MR): 28750 (21200/35898) [2025-04-28 06:57:18,883 INFO hook.py line 650 1619929] Train: [37/512][200/242] Data 0.015 (0.016) Batch 1.496 (1.413) Remain 45:07:37 loss: 6.2302 Lr: 2.80526e-04 Mem R(MA/MR): 28758 (21200/35898) [2025-04-28 06:58:14,994 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6234 loss_mask: 0.0502 loss_dice: 2.7781 loss_score: 0.0000 loss_bbox: 0.0613 loss_sp_cls: 1.1674 loss: 7.4781 [2025-04-28 06:58:18,923 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 06:59:44,772 INFO hook.py line 650 1619929] Train: [38/512][50/242] Data 0.016 (0.017) Batch 1.419 (1.439) Remain 45:56:20 loss: 7.3749 Lr: 2.80324e-04 Mem R(MA/MR): 18774 (21200/35898) [2025-04-28 07:00:59,295 INFO hook.py line 650 1619929] Train: [38/512][100/242] Data 0.018 (0.016) Batch 1.401 (1.466) Remain 46:45:33 loss: 6.2390 Lr: 2.80214e-04 Mem R(MA/MR): 20818 (21200/35898) [2025-04-28 07:02:09,940 INFO hook.py line 650 1619929] Train: [38/512][150/242] Data 0.016 (0.016) Batch 1.380 (1.448) Remain 46:10:00 loss: 6.1695 Lr: 2.80104e-04 Mem R(MA/MR): 20818 (21200/35898) [2025-04-28 07:03:21,548 INFO hook.py line 650 1619929] Train: [38/512][200/242] Data 0.014 (0.016) Batch 1.385 (1.444) Remain 46:01:14 loss: 5.5920 Lr: 2.79994e-04 Mem R(MA/MR): 20818 (21200/35898) [2025-04-28 07:04:18,698 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5949 loss_mask: 0.0489 loss_dice: 2.7125 loss_score: 0.0000 loss_bbox: 0.0606 loss_sp_cls: 1.1464 loss: 7.2807 [2025-04-28 07:04:23,662 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:05:58,119 INFO hook.py line 650 1619929] Train: [39/512][50/242] Data 0.015 (0.016) Batch 1.220 (1.441) Remain 45:53:01 loss: 8.0219 Lr: 2.79792e-04 Mem R(MA/MR): 21934 (21200/35898) [2025-04-28 07:07:09,692 INFO hook.py line 650 1619929] Train: [39/512][100/242] Data 0.016 (0.016) Batch 1.328 (1.436) Remain 45:42:48 loss: 8.8165 Lr: 2.79683e-04 Mem R(MA/MR): 21934 (21200/35898) [2025-04-28 07:08:19,593 INFO hook.py line 650 1619929] Train: [39/512][150/242] Data 0.017 (0.016) Batch 1.402 (1.423) Remain 45:16:59 loss: 7.2069 Lr: 2.79573e-04 Mem R(MA/MR): 23774 (21200/35898) [2025-04-28 07:09:29,192 INFO hook.py line 650 1619929] Train: [39/512][200/242] Data 0.013 (0.016) Batch 1.500 (1.415) Remain 45:00:45 loss: 8.7385 Lr: 2.79463e-04 Mem R(MA/MR): 26070 (21200/35898) [2025-04-28 07:10:25,403 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5908 loss_mask: 0.0476 loss_dice: 2.6794 loss_score: 0.0000 loss_bbox: 0.0598 loss_sp_cls: 1.1393 loss: 7.2114 [2025-04-28 07:10:26,489 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:12:00,889 INFO hook.py line 650 1619929] Train: [40/512][50/242] Data 0.017 (0.016) Batch 1.472 (1.462) Remain 46:28:18 loss: 7.0072 Lr: 2.79261e-04 Mem R(MA/MR): 21190 (21200/35898) [2025-04-28 07:13:12,459 INFO hook.py line 650 1619929] Train: [40/512][100/242] Data 0.016 (0.016) Batch 1.505 (1.446) Remain 45:56:51 loss: 7.5218 Lr: 2.79151e-04 Mem R(MA/MR): 23426 (21200/35898) [2025-04-28 07:14:24,047 INFO hook.py line 650 1619929] Train: [40/512][150/242] Data 0.016 (0.016) Batch 1.400 (1.441) Remain 45:46:12 loss: 9.3332 Lr: 2.79041e-04 Mem R(MA/MR): 23426 (21200/35898) [2025-04-28 07:15:34,276 INFO hook.py line 650 1619929] Train: [40/512][200/242] Data 0.014 (0.016) Batch 1.433 (1.432) Remain 45:27:13 loss: 7.0990 Lr: 2.78931e-04 Mem R(MA/MR): 23434 (21200/35898) [2025-04-28 07:16:32,113 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5863 loss_mask: 0.0474 loss_dice: 2.6751 loss_score: 0.0000 loss_bbox: 0.0599 loss_sp_cls: 1.1266 loss: 7.1804 [2025-04-28 07:16:36,771 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 07:16:39,114 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.8332 Process Time: 0.333 Mem R(MA/MR): 4070 (21200/35898) [2025-04-28 07:16:40,542 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.9254 Process Time: 0.511 Mem R(MA/MR): 6888 (21200/35898) [2025-04-28 07:16:42,533 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2830 Process Time: 0.851 Mem R(MA/MR): 9430 (21200/35898) [2025-04-28 07:16:50,841 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.8367 Process Time: 1.438 Mem R(MA/MR): 19506 (21200/35898) [2025-04-28 07:16:52,355 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.9205 Process Time: 0.574 Mem R(MA/MR): 6822 (21200/35898) [2025-04-28 07:16:54,383 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.2971 Process Time: 0.888 Mem R(MA/MR): 10766 (21200/35898) [2025-04-28 07:16:55,113 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.7508 Process Time: 0.269 Mem R(MA/MR): 6072 (21200/35898) [2025-04-28 07:16:55,550 INFO hook.py line 449 1619929] Test: [8/50] Loss 7.0554 Process Time: 0.121 Mem R(MA/MR): 4122 (21200/35898) [2025-04-28 07:16:56,571 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6877 Process Time: 0.299 Mem R(MA/MR): 11242 (21200/35898) [2025-04-28 07:16:58,074 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.4499 Process Time: 0.318 Mem R(MA/MR): 9214 (21200/35898) [2025-04-28 07:17:00,971 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.3648 Process Time: 0.810 Mem R(MA/MR): 18348 (21200/35898) [2025-04-28 07:17:03,707 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.9428 Process Time: 0.652 Mem R(MA/MR): 14950 (21200/35898) [2025-04-28 07:17:04,760 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.9594 Process Time: 0.264 Mem R(MA/MR): 8342 (21200/35898) [2025-04-28 07:17:05,223 INFO hook.py line 449 1619929] Test: [14/50] Loss 4.0212 Process Time: 0.134 Mem R(MA/MR): 4516 (21200/35898) [2025-04-28 07:17:07,565 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.0318 Process Time: 0.525 Mem R(MA/MR): 16238 (21200/35898) [2025-04-28 07:17:09,799 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.1357 Process Time: 0.771 Mem R(MA/MR): 14324 (21200/35898) [2025-04-28 07:17:10,473 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.6073 Process Time: 0.180 Mem R(MA/MR): 6480 (21200/35898) [2025-04-28 07:17:11,246 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.5999 Process Time: 0.187 Mem R(MA/MR): 8012 (21200/35898) [2025-04-28 07:17:12,424 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0303 Process Time: 0.218 Mem R(MA/MR): 6086 (21200/35898) [2025-04-28 07:17:13,962 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.1672 Process Time: 0.308 Mem R(MA/MR): 11010 (21200/35898) [2025-04-28 07:17:23,459 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.9723 Process Time: 0.818 Mem R(MA/MR): 22942 (21200/35898) [2025-04-28 07:17:24,528 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7277 Process Time: 0.399 Mem R(MA/MR): 6784 (21200/35898) [2025-04-28 07:17:34,081 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.4799 Process Time: 0.663 Mem R(MA/MR): 9784 (21200/35898) [2025-04-28 07:17:34,693 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9869 Process Time: 0.207 Mem R(MA/MR): 5078 (21200/35898) [2025-04-28 07:17:35,941 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.7398 Process Time: 0.396 Mem R(MA/MR): 9182 (21200/35898) [2025-04-28 07:17:42,392 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.3485 Process Time: 0.918 Mem R(MA/MR): 30798 (21200/35898) [2025-04-28 07:17:45,029 INFO hook.py line 449 1619929] Test: [27/50] Loss 9.8365 Process Time: 0.781 Mem R(MA/MR): 9950 (21200/35898) [2025-04-28 07:17:46,081 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.5198 Process Time: 0.196 Mem R(MA/MR): 8520 (21200/35898) [2025-04-28 07:17:50,725 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.1543 Process Time: 0.339 Mem R(MA/MR): 16942 (21200/35898) [2025-04-28 07:17:51,929 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2605 Process Time: 0.356 Mem R(MA/MR): 7668 (21200/35898) [2025-04-28 07:17:56,171 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.5095 Process Time: 0.690 Mem R(MA/MR): 20286 (21200/35898) [2025-04-28 07:17:56,423 INFO hook.py line 449 1619929] Test: [32/50] Loss 5.1350 Process Time: 0.105 Mem R(MA/MR): 3932 (21200/35898) [2025-04-28 07:17:59,851 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.0262 Process Time: 0.370 Mem R(MA/MR): 24406 (21200/35898) [2025-04-28 07:18:01,777 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.1874 Process Time: 0.633 Mem R(MA/MR): 9700 (21200/35898) [2025-04-28 07:18:03,424 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.7392 Process Time: 0.423 Mem R(MA/MR): 13654 (21200/35898) [2025-04-28 07:18:03,903 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0312 Process Time: 0.159 Mem R(MA/MR): 6306 (21200/35898) [2025-04-28 07:18:07,769 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.1285 Process Time: 0.888 Mem R(MA/MR): 28362 (21200/35898) [2025-04-28 07:18:10,054 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.5175 Process Time: 0.434 Mem R(MA/MR): 10472 (21200/35898) [2025-04-28 07:18:10,627 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.5258 Process Time: 0.207 Mem R(MA/MR): 5276 (21200/35898) [2025-04-28 07:18:11,949 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.9866 Process Time: 0.299 Mem R(MA/MR): 9968 (21200/35898) [2025-04-28 07:18:13,112 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.8917 Process Time: 0.365 Mem R(MA/MR): 8828 (21200/35898) [2025-04-28 07:18:13,609 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.8716 Process Time: 0.148 Mem R(MA/MR): 5204 (21200/35898) [2025-04-28 07:18:14,348 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.7540 Process Time: 0.141 Mem R(MA/MR): 5318 (21200/35898) [2025-04-28 07:18:15,085 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.9004 Process Time: 0.301 Mem R(MA/MR): 6836 (21200/35898) [2025-04-28 07:18:16,111 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0784 Process Time: 0.334 Mem R(MA/MR): 5008 (21200/35898) [2025-04-28 07:18:18,542 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5447 Process Time: 0.508 Mem R(MA/MR): 14526 (21200/35898) [2025-04-28 07:18:26,131 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.8139 Process Time: 1.149 Mem R(MA/MR): 20172 (21200/35898) [2025-04-28 07:18:36,417 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9809 Process Time: 2.002 Mem R(MA/MR): 35398 (21200/35898) [2025-04-28 07:18:37,137 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.1006 Process Time: 0.229 Mem R(MA/MR): 5500 (21200/35898) [2025-04-28 07:18:39,592 INFO hook.py line 449 1619929] Test: [50/50] Loss 6.1689 Process Time: 0.345 Mem R(MA/MR): 13618 (21200/35898) [2025-04-28 07:18:43,753 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 07:18:43,753 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 07:18:43,753 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] table : 0.214 0.528 0.797 0.681 0.566 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] door : 0.435 0.757 0.874 0.859 0.696 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] ceiling lamp : 0.542 0.730 0.819 0.919 0.685 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] cabinet : 0.299 0.442 0.547 0.507 0.507 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] blinds : 0.297 0.473 0.720 0.619 0.565 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] curtain : 0.223 0.350 0.616 0.455 0.417 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] chair : 0.561 0.715 0.787 0.799 0.684 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] storage cabinet: 0.198 0.362 0.594 0.692 0.360 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] office chair : 0.577 0.611 0.627 0.767 0.688 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] bookshelf : 0.275 0.722 0.742 0.667 0.727 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] whiteboard : 0.489 0.617 0.677 0.846 0.629 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] window : 0.078 0.174 0.530 0.355 0.297 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] box : 0.123 0.254 0.409 0.456 0.343 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] monitor : 0.577 0.711 0.808 1.000 0.629 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] shelf : 0.015 0.046 0.215 0.159 0.233 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] heater : 0.440 0.673 0.856 0.737 0.737 [2025-04-28 07:18:43,753 INFO hook.py line 395 1619929] kitchen cabinet: 0.064 0.182 0.669 0.444 0.320 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] sofa : 0.501 0.707 0.755 1.000 0.667 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] bed : 0.052 0.182 0.726 0.444 0.500 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] trash can : 0.475 0.627 0.660 0.762 0.738 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] book : 0.008 0.020 0.046 0.220 0.067 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] plant : 0.452 0.654 0.662 0.857 0.667 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] blanket : 0.291 0.471 0.577 0.545 0.545 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] tv : 0.634 0.782 0.782 1.000 0.667 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] computer tower : 0.211 0.297 0.601 0.383 0.429 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] refrigerator : 0.220 0.385 0.385 1.000 0.333 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] jacket : 0.020 0.062 0.218 0.135 0.455 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] sink : 0.367 0.627 0.919 0.875 0.636 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] bag : 0.148 0.194 0.237 0.273 0.333 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] picture : 0.153 0.255 0.309 0.650 0.333 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] pillow : 0.570 0.758 0.846 0.929 0.684 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] towel : 0.102 0.235 0.417 0.625 0.263 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] suitcase : 0.107 0.220 0.220 0.750 0.429 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] backpack : 0.380 0.460 0.462 0.750 0.462 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] crate : 0.033 0.105 0.371 0.200 0.182 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] keyboard : 0.308 0.414 0.450 0.750 0.385 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] toilet : 0.739 0.876 1.000 0.889 0.889 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] printer : 0.049 0.073 0.073 0.375 0.333 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] poster : 0.012 0.111 0.111 1.000 0.111 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] painting : 0.053 0.056 0.071 0.111 1.000 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] microwave : 0.364 0.630 0.816 0.600 0.750 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] shoes : 0.177 0.295 0.514 0.583 0.341 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] socket : 0.137 0.420 0.626 0.701 0.436 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] bottle : 0.088 0.156 0.215 0.421 0.193 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] bucket : 0.045 0.047 0.053 0.200 0.143 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] cushion : 0.115 0.257 0.257 0.750 0.500 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-28 07:18:43,754 INFO hook.py line 395 1619929] telephone : 0.198 0.444 0.600 0.588 0.588 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] laptop : 0.081 0.226 0.471 0.385 0.625 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] plant pot : 0.144 0.301 0.301 0.833 0.312 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] cup : 0.173 0.261 0.335 0.390 0.364 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] coat hanger : 0.328 0.677 0.750 0.750 0.750 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] light switch : 0.212 0.418 0.571 0.725 0.446 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] speaker : 0.194 0.246 0.246 0.750 0.273 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] table lamp : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] smoke detector : 0.624 0.787 0.833 0.950 0.792 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] power strip : 0.125 0.149 0.151 0.400 0.200 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] mouse : 0.348 0.526 0.577 0.708 0.531 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] cutting board : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] toilet paper : 0.104 0.235 0.240 0.353 0.353 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.031 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] clock : 0.194 0.278 0.278 0.667 0.667 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] tap : 0.129 0.219 0.649 0.600 0.333 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] soap dispenser : 0.218 0.235 0.239 1.000 0.200 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] bowl : 0.091 0.194 0.194 0.500 0.667 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] whiteboard eraser: 0.106 0.308 0.308 0.500 0.667 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] toilet brush : 0.270 0.451 0.728 1.000 0.333 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] headphones : 0.014 0.031 0.500 0.125 0.500 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 07:18:43,755 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 07:18:43,755 INFO hook.py line 404 1619929] average : 0.202 0.322 0.422 0.561 0.400 [2025-04-28 07:18:43,756 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 07:18:43,756 INFO hook.py line 480 1619929] Total Process Time: 24.454 s [2025-04-28 07:18:43,756 INFO hook.py line 481 1619929] Average Process Time: 492.263 ms [2025-04-28 07:18:43,756 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 07:18:43,798 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.322 [2025-04-28 07:18:43,803 INFO hook.py line 685 1619929] Currently Best AP50: 0.322 [2025-04-28 07:18:43,803 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:20:19,037 INFO hook.py line 650 1619929] Train: [41/512][50/242] Data 0.024 (0.017) Batch 1.563 (1.442) Remain 45:44:14 loss: 7.3481 Lr: 2.78729e-04 Mem R(MA/MR): 22740 (21200/35898) [2025-04-28 07:21:32,183 INFO hook.py line 650 1619929] Train: [41/512][100/242] Data 0.016 (0.030) Batch 1.551 (1.453) Remain 46:03:22 loss: 6.5679 Lr: 2.78619e-04 Mem R(MA/MR): 24864 (21200/35898) [2025-04-28 07:22:43,979 INFO hook.py line 650 1619929] Train: [41/512][150/242] Data 0.016 (0.026) Batch 1.365 (1.447) Remain 45:51:15 loss: 6.4786 Lr: 2.78510e-04 Mem R(MA/MR): 24864 (21200/35898) [2025-04-28 07:23:55,860 INFO hook.py line 650 1619929] Train: [41/512][200/242] Data 0.014 (0.023) Batch 1.342 (1.445) Remain 45:45:30 loss: 7.9314 Lr: 2.78402e-04 Mem R(MA/MR): 24864 (21200/35898) [2025-04-28 07:24:52,919 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5976 loss_mask: 0.0478 loss_dice: 2.7063 loss_score: 0.0000 loss_bbox: 0.0602 loss_sp_cls: 1.1410 loss: 7.2661 [2025-04-28 07:24:53,069 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:26:26,330 INFO hook.py line 650 1619929] Train: [42/512][50/242] Data 0.016 (0.017) Batch 1.371 (1.432) Remain 45:18:57 loss: 7.4135 Lr: 2.78200e-04 Mem R(MA/MR): 19150 (21200/35898) [2025-04-28 07:27:38,707 INFO hook.py line 650 1619929] Train: [42/512][100/242] Data 0.016 (0.017) Batch 1.446 (1.440) Remain 45:33:06 loss: 7.4022 Lr: 2.78090e-04 Mem R(MA/MR): 22768 (21200/35898) [2025-04-28 07:28:50,664 INFO hook.py line 650 1619929] Train: [42/512][150/242] Data 0.015 (0.017) Batch 1.522 (1.440) Remain 45:31:20 loss: 8.0858 Lr: 2.77980e-04 Mem R(MA/MR): 22768 (21200/35898) [2025-04-28 07:30:00,499 INFO hook.py line 650 1619929] Train: [42/512][200/242] Data 0.015 (0.016) Batch 1.345 (1.429) Remain 45:09:28 loss: 7.1013 Lr: 2.77870e-04 Mem R(MA/MR): 22768 (21200/35898) [2025-04-28 07:30:58,269 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6362 loss_mask: 0.0522 loss_dice: 2.8494 loss_score: 0.0000 loss_bbox: 0.0638 loss_sp_cls: 1.1930 loss: 7.6520 [2025-04-28 07:31:01,144 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:32:33,333 INFO hook.py line 650 1619929] Train: [43/512][50/242] Data 0.016 (0.018) Batch 1.369 (1.453) Remain 45:54:05 loss: 7.6297 Lr: 2.77668e-04 Mem R(MA/MR): 21104 (21200/35898) [2025-04-28 07:33:44,659 INFO hook.py line 650 1619929] Train: [43/512][100/242] Data 0.016 (0.017) Batch 1.280 (1.440) Remain 45:26:35 loss: 7.1773 Lr: 2.77558e-04 Mem R(MA/MR): 21104 (21200/35898) [2025-04-28 07:34:55,279 INFO hook.py line 650 1619929] Train: [43/512][150/242] Data 0.016 (0.017) Batch 1.586 (1.430) Remain 45:07:51 loss: 8.1885 Lr: 2.77448e-04 Mem R(MA/MR): 21104 (21200/35898) [2025-04-28 07:36:07,837 INFO hook.py line 650 1619929] Train: [43/512][200/242] Data 0.015 (0.017) Batch 1.272 (1.436) Remain 45:16:41 loss: 7.8011 Lr: 2.77338e-04 Mem R(MA/MR): 21118 (21200/35898) [2025-04-28 07:37:04,416 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6368 loss_mask: 0.0531 loss_dice: 2.8507 loss_score: 0.0000 loss_bbox: 0.0632 loss_sp_cls: 1.1896 loss: 7.6596 [2025-04-28 07:37:05,254 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:38:40,766 INFO hook.py line 650 1619929] Train: [44/512][50/242] Data 0.016 (0.016) Batch 1.360 (1.446) Remain 45:34:02 loss: 7.9298 Lr: 2.77136e-04 Mem R(MA/MR): 22104 (21200/35898) [2025-04-28 07:39:51,510 INFO hook.py line 650 1619929] Train: [44/512][100/242] Data 0.017 (0.016) Batch 1.231 (1.430) Remain 45:02:37 loss: 5.9651 Lr: 2.77026e-04 Mem R(MA/MR): 22104 (21200/35898) [2025-04-28 07:41:01,707 INFO hook.py line 650 1619929] Train: [44/512][150/242] Data 0.015 (0.016) Batch 1.398 (1.421) Remain 44:44:41 loss: 7.0735 Lr: 2.76916e-04 Mem R(MA/MR): 22104 (21200/35898) [2025-04-28 07:42:13,626 INFO hook.py line 650 1619929] Train: [44/512][200/242] Data 0.015 (0.016) Batch 1.423 (1.426) Remain 44:51:46 loss: 9.1958 Lr: 2.76806e-04 Mem R(MA/MR): 22104 (21200/35898) [2025-04-28 07:43:08,795 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6325 loss_mask: 0.0521 loss_dice: 2.8248 loss_score: 0.0000 loss_bbox: 0.0634 loss_sp_cls: 1.1754 loss: 7.5927 [2025-04-28 07:43:12,316 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:44:42,339 INFO hook.py line 650 1619929] Train: [45/512][50/242] Data 0.016 (0.016) Batch 1.384 (1.509) Remain 47:27:02 loss: 6.3626 Lr: 2.76604e-04 Mem R(MA/MR): 25524 (21200/35898) [2025-04-28 07:45:54,093 INFO hook.py line 650 1619929] Train: [45/512][100/242] Data 0.015 (0.016) Batch 1.424 (1.471) Remain 46:13:59 loss: 7.8816 Lr: 2.76494e-04 Mem R(MA/MR): 25526 (21200/35898) [2025-04-28 07:47:07,365 INFO hook.py line 650 1619929] Train: [45/512][150/242] Data 0.015 (0.016) Batch 1.343 (1.469) Remain 46:09:15 loss: 7.7421 Lr: 2.76386e-04 Mem R(MA/MR): 27520 (21200/35898) [2025-04-28 07:48:19,141 INFO hook.py line 650 1619929] Train: [45/512][200/242] Data 0.016 (0.016) Batch 1.408 (1.461) Remain 45:52:01 loss: 6.2508 Lr: 2.76276e-04 Mem R(MA/MR): 27528 (21200/35898) [2025-04-28 07:49:16,549 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6614 loss_mask: 0.0554 loss_dice: 2.9404 loss_score: 0.0000 loss_bbox: 0.0644 loss_sp_cls: 1.2025 loss: 7.8821 [2025-04-28 07:49:21,727 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:50:50,079 INFO hook.py line 650 1619929] Train: [46/512][50/242] Data 0.015 (0.016) Batch 1.318 (1.425) Remain 44:43:33 loss: 7.6024 Lr: 2.76074e-04 Mem R(MA/MR): 22170 (21200/35898) [2025-04-28 07:52:02,850 INFO hook.py line 650 1619929] Train: [46/512][100/242] Data 0.015 (0.016) Batch 1.403 (1.441) Remain 45:11:32 loss: 8.3771 Lr: 2.75964e-04 Mem R(MA/MR): 22190 (21200/35898) [2025-04-28 07:53:17,027 INFO hook.py line 650 1619929] Train: [46/512][150/242] Data 0.017 (0.017) Batch 1.377 (1.455) Remain 45:37:37 loss: 9.0037 Lr: 2.75854e-04 Mem R(MA/MR): 24160 (21200/35898) [2025-04-28 07:54:28,571 INFO hook.py line 650 1619929] Train: [46/512][200/242] Data 0.014 (0.016) Batch 1.400 (1.449) Remain 45:24:45 loss: 8.7792 Lr: 2.75744e-04 Mem R(MA/MR): 24160 (21200/35898) [2025-04-28 07:55:24,782 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6854 loss_mask: 0.0580 loss_dice: 3.0365 loss_score: 0.0000 loss_bbox: 0.0663 loss_sp_cls: 1.2356 loss: 8.1363 [2025-04-28 07:55:29,079 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 07:57:00,597 INFO hook.py line 650 1619929] Train: [47/512][50/242] Data 0.021 (0.022) Batch 1.454 (1.586) Remain 49:39:40 loss: 7.1464 Lr: 2.75542e-04 Mem R(MA/MR): 21914 (21200/35898) [2025-04-28 07:58:18,248 INFO hook.py line 650 1619929] Train: [47/512][100/242] Data 0.018 (0.022) Batch 1.488 (1.569) Remain 49:06:26 loss: 9.3391 Lr: 2.75432e-04 Mem R(MA/MR): 26300 (21200/35898) [2025-04-28 07:59:37,838 INFO hook.py line 650 1619929] Train: [47/512][150/242] Data 0.017 (0.021) Batch 1.644 (1.577) Remain 49:19:41 loss: 7.3717 Lr: 2.75322e-04 Mem R(MA/MR): 26300 (21200/35898) [2025-04-28 08:00:54,461 INFO hook.py line 650 1619929] Train: [47/512][200/242] Data 0.017 (0.021) Batch 1.511 (1.566) Remain 48:57:15 loss: 7.7248 Lr: 2.75212e-04 Mem R(MA/MR): 26300 (21200/35898) [2025-04-28 08:01:53,025 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6695 loss_mask: 0.0548 loss_dice: 2.9556 loss_score: 0.0000 loss_bbox: 0.0662 loss_sp_cls: 1.2123 loss: 7.9414 [2025-04-28 08:01:53,162 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:03:29,439 INFO hook.py line 650 1619929] Train: [48/512][50/242] Data 0.016 (0.017) Batch 1.452 (1.474) Remain 46:02:22 loss: 8.3059 Lr: 2.75009e-04 Mem R(MA/MR): 23284 (21200/35898) [2025-04-28 08:04:38,821 INFO hook.py line 650 1619929] Train: [48/512][100/242] Data 0.017 (0.016) Batch 1.375 (1.429) Remain 44:38:10 loss: 7.2391 Lr: 2.74899e-04 Mem R(MA/MR): 27154 (21200/35898) [2025-04-28 08:05:50,125 INFO hook.py line 650 1619929] Train: [48/512][150/242] Data 0.016 (0.016) Batch 1.379 (1.428) Remain 44:34:58 loss: 8.1779 Lr: 2.74789e-04 Mem R(MA/MR): 29692 (21200/35898) [2025-04-28 08:07:02,186 INFO hook.py line 650 1619929] Train: [48/512][200/242] Data 0.015 (0.016) Batch 1.338 (1.431) Remain 44:39:59 loss: 7.9722 Lr: 2.74679e-04 Mem R(MA/MR): 29692 (21200/35898) [2025-04-28 08:07:59,691 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6479 loss_mask: 0.0536 loss_dice: 2.9091 loss_score: 0.0000 loss_bbox: 0.0656 loss_sp_cls: 1.1960 loss: 7.7917 [2025-04-28 08:08:04,683 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 08:08:07,038 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.1275 Process Time: 0.306 Mem R(MA/MR): 4230 (21200/35898) [2025-04-28 08:08:08,492 INFO hook.py line 449 1619929] Test: [2/50] Loss 7.2095 Process Time: 0.507 Mem R(MA/MR): 6910 (21200/35898) [2025-04-28 08:08:10,478 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.9394 Process Time: 0.797 Mem R(MA/MR): 9552 (21200/35898) [2025-04-28 08:08:17,609 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.2706 Process Time: 0.864 Mem R(MA/MR): 19380 (21200/35898) [2025-04-28 08:08:18,879 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.3622 Process Time: 0.557 Mem R(MA/MR): 6918 (21200/35898) [2025-04-28 08:08:20,454 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.6922 Process Time: 0.553 Mem R(MA/MR): 10970 (21200/35898) [2025-04-28 08:08:21,166 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.4543 Process Time: 0.269 Mem R(MA/MR): 6102 (21200/35898) [2025-04-28 08:08:21,660 INFO hook.py line 449 1619929] Test: [8/50] Loss 7.0450 Process Time: 0.154 Mem R(MA/MR): 4278 (21200/35898) [2025-04-28 08:08:22,643 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.8144 Process Time: 0.308 Mem R(MA/MR): 11520 (21200/35898) [2025-04-28 08:08:24,032 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.9406 Process Time: 0.314 Mem R(MA/MR): 9374 (21200/35898) [2025-04-28 08:08:27,038 INFO hook.py line 449 1619929] Test: [11/50] Loss 13.2659 Process Time: 0.967 Mem R(MA/MR): 18264 (21200/35898) [2025-04-28 08:08:29,929 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.5444 Process Time: 0.792 Mem R(MA/MR): 15178 (21200/35898) [2025-04-28 08:08:31,074 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.4811 Process Time: 0.373 Mem R(MA/MR): 8250 (21200/35898) [2025-04-28 08:08:31,569 INFO hook.py line 449 1619929] Test: [14/50] Loss 4.5574 Process Time: 0.198 Mem R(MA/MR): 4644 (21200/35898) [2025-04-28 08:08:34,122 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.5376 Process Time: 0.446 Mem R(MA/MR): 16384 (21200/35898) [2025-04-28 08:08:36,490 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.2249 Process Time: 0.488 Mem R(MA/MR): 14552 (21200/35898) [2025-04-28 08:08:37,288 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.4967 Process Time: 0.196 Mem R(MA/MR): 6576 (21200/35898) [2025-04-28 08:08:38,213 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1233 Process Time: 0.241 Mem R(MA/MR): 7984 (21200/35898) [2025-04-28 08:08:39,507 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.7135 Process Time: 0.206 Mem R(MA/MR): 6118 (21200/35898) [2025-04-28 08:08:40,950 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.0201 Process Time: 0.241 Mem R(MA/MR): 11202 (21200/35898) [2025-04-28 08:08:48,886 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.2760 Process Time: 0.707 Mem R(MA/MR): 22756 (21200/35898) [2025-04-28 08:08:49,560 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.0929 Process Time: 0.241 Mem R(MA/MR): 6884 (21200/35898) [2025-04-28 08:08:58,439 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.9705 Process Time: 0.521 Mem R(MA/MR): 8276 (21200/35898) [2025-04-28 08:08:58,990 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.1676 Process Time: 0.175 Mem R(MA/MR): 5212 (21200/35898) [2025-04-28 08:08:59,941 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.8160 Process Time: 0.269 Mem R(MA/MR): 9136 (21200/35898) [2025-04-28 08:09:06,693 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.6519 Process Time: 1.334 Mem R(MA/MR): 31396 (21200/35898) [2025-04-28 08:09:08,264 INFO hook.py line 449 1619929] Test: [27/50] Loss 9.9790 Process Time: 0.225 Mem R(MA/MR): 10034 (21200/35898) [2025-04-28 08:09:09,954 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.9552 Process Time: 0.757 Mem R(MA/MR): 8802 (21200/35898) [2025-04-28 08:09:15,466 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8475 Process Time: 0.544 Mem R(MA/MR): 16804 (21200/35898) [2025-04-28 08:09:16,241 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.8818 Process Time: 0.205 Mem R(MA/MR): 7600 (21200/35898) [2025-04-28 08:09:20,734 INFO hook.py line 449 1619929] Test: [31/50] Loss 9.3116 Process Time: 0.420 Mem R(MA/MR): 20418 (21200/35898) [2025-04-28 08:09:21,297 INFO hook.py line 449 1619929] Test: [32/50] Loss 5.5682 Process Time: 0.226 Mem R(MA/MR): 3908 (21200/35898) [2025-04-28 08:09:25,157 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.5589 Process Time: 0.514 Mem R(MA/MR): 24468 (21200/35898) [2025-04-28 08:09:26,283 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.7335 Process Time: 0.357 Mem R(MA/MR): 9606 (21200/35898) [2025-04-28 08:09:29,027 INFO hook.py line 449 1619929] Test: [35/50] Loss 9.2417 Process Time: 0.988 Mem R(MA/MR): 13758 (21200/35898) [2025-04-28 08:09:29,815 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.5504 Process Time: 0.309 Mem R(MA/MR): 6478 (21200/35898) [2025-04-28 08:09:33,881 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.1461 Process Time: 0.696 Mem R(MA/MR): 28182 (21200/35898) [2025-04-28 08:09:35,345 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.7544 Process Time: 0.294 Mem R(MA/MR): 10434 (21200/35898) [2025-04-28 08:09:36,482 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.4494 Process Time: 0.545 Mem R(MA/MR): 5316 (21200/35898) [2025-04-28 08:09:37,960 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.7528 Process Time: 0.445 Mem R(MA/MR): 10006 (21200/35898) [2025-04-28 08:09:39,300 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.6120 Process Time: 0.451 Mem R(MA/MR): 8782 (21200/35898) [2025-04-28 08:09:39,887 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.5521 Process Time: 0.207 Mem R(MA/MR): 5396 (21200/35898) [2025-04-28 08:09:40,343 INFO hook.py line 449 1619929] Test: [43/50] Loss 6.2405 Process Time: 0.165 Mem R(MA/MR): 5470 (21200/35898) [2025-04-28 08:09:40,895 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.9374 Process Time: 0.175 Mem R(MA/MR): 6914 (21200/35898) [2025-04-28 08:09:41,415 INFO hook.py line 449 1619929] Test: [45/50] Loss 6.2934 Process Time: 0.137 Mem R(MA/MR): 5158 (21200/35898) [2025-04-28 08:09:43,928 INFO hook.py line 449 1619929] Test: [46/50] Loss 12.1203 Process Time: 0.567 Mem R(MA/MR): 14662 (21200/35898) [2025-04-28 08:09:52,014 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.5112 Process Time: 1.920 Mem R(MA/MR): 20108 (21200/35898) [2025-04-28 08:10:02,029 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.6208 Process Time: 1.758 Mem R(MA/MR): 35540 (21200/35898) [2025-04-28 08:10:03,485 INFO hook.py line 449 1619929] Test: [49/50] Loss 5.2865 Process Time: 0.530 Mem R(MA/MR): 5594 (21200/35898) [2025-04-28 08:10:06,082 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.6250 Process Time: 0.451 Mem R(MA/MR): 13474 (21200/35898) [2025-04-28 08:10:10,673 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 08:10:10,673 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 08:10:10,673 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] table : 0.197 0.541 0.771 0.750 0.574 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] door : 0.400 0.674 0.815 0.768 0.671 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] ceiling lamp : 0.499 0.695 0.829 0.867 0.646 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] cabinet : 0.243 0.396 0.471 0.517 0.448 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] blinds : 0.231 0.536 0.661 0.619 0.565 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] curtain : 0.209 0.370 0.687 0.500 0.583 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] chair : 0.497 0.700 0.792 0.738 0.693 [2025-04-28 08:10:10,673 INFO hook.py line 395 1619929] storage cabinet: 0.091 0.301 0.476 0.407 0.440 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] office chair : 0.573 0.609 0.672 0.629 0.812 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] bookshelf : 0.177 0.737 0.785 1.000 0.636 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] whiteboard : 0.477 0.673 0.812 0.909 0.571 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] window : 0.065 0.204 0.584 0.349 0.319 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] box : 0.074 0.174 0.349 0.395 0.260 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] monitor : 0.540 0.720 0.842 0.957 0.643 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] shelf : 0.054 0.158 0.314 1.000 0.133 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] heater : 0.323 0.588 0.826 0.742 0.605 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] kitchen cabinet: 0.101 0.241 0.656 0.455 0.400 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] sofa : 0.501 0.692 0.732 1.000 0.583 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] bed : 0.118 0.472 0.602 0.800 0.500 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] trash can : 0.443 0.616 0.675 0.741 0.615 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] book : 0.006 0.015 0.050 0.157 0.052 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] plant : 0.225 0.367 0.772 0.750 0.333 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] blanket : 0.222 0.497 0.633 0.667 0.545 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] tv : 0.688 0.785 0.785 0.625 0.833 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] computer tower : 0.155 0.215 0.459 0.500 0.238 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] refrigerator : 0.179 0.419 0.419 0.800 0.444 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] jacket : 0.061 0.222 0.453 0.364 0.364 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] sink : 0.228 0.543 0.903 0.750 0.682 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] bag : 0.047 0.059 0.059 0.667 0.074 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] picture : 0.130 0.286 0.395 0.765 0.333 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] pillow : 0.424 0.680 0.746 1.000 0.526 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] towel : 0.073 0.146 0.368 0.239 0.289 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] suitcase : 0.091 0.305 0.571 0.600 0.429 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] backpack : 0.256 0.338 0.474 1.000 0.308 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] crate : 0.016 0.105 0.362 1.000 0.091 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] keyboard : 0.294 0.395 0.433 0.750 0.385 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] toilet : 0.624 1.000 1.000 1.000 1.000 [2025-04-28 08:10:10,674 INFO hook.py line 395 1619929] printer : 0.321 0.333 0.333 1.000 0.333 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] poster : 0.002 0.012 0.014 0.071 0.222 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] microwave : 0.373 0.676 0.750 1.000 0.625 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] shoes : 0.097 0.231 0.483 0.464 0.317 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] socket : 0.134 0.322 0.489 0.500 0.364 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] bottle : 0.068 0.140 0.231 0.302 0.229 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] bucket : 0.006 0.006 0.007 0.091 0.143 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] cushion : 0.008 0.072 0.301 0.188 0.500 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 1.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] telephone : 0.218 0.410 0.522 0.600 0.529 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] laptop : 0.166 0.179 0.290 0.300 0.375 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] plant pot : 0.038 0.240 0.323 1.000 0.188 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] cup : 0.169 0.281 0.355 0.800 0.273 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.250 1.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] light switch : 0.152 0.365 0.541 0.651 0.431 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] speaker : 0.047 0.102 0.326 0.500 0.273 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] table lamp : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] kettle : 0.080 0.264 0.264 0.667 0.333 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] smoke detector : 0.624 0.790 0.792 0.950 0.792 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] power strip : 0.011 0.039 0.076 0.286 0.200 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] mouse : 0.371 0.575 0.576 0.731 0.594 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] toilet paper : 0.059 0.118 0.176 1.000 0.118 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] paper towel : 0.021 0.021 0.031 0.333 0.125 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] clock : 0.219 0.406 0.406 0.600 1.000 [2025-04-28 08:10:10,675 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] tap : 0.093 0.237 0.444 0.600 0.333 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] soap dispenser : 0.391 0.800 0.800 1.000 0.800 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] bowl : 0.002 0.019 0.021 0.111 0.333 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] whiteboard eraser: 0.133 0.362 0.362 0.667 0.667 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] toilet brush : 0.172 0.386 0.522 0.800 0.667 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] spray bottle : 0.049 0.062 0.500 0.500 0.250 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] headphones : 0.042 0.125 0.125 0.500 0.500 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 08:10:10,676 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:10:10,676 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 08:10:10,676 INFO hook.py line 404 1619929] average : 0.168 0.296 0.412 0.573 0.358 [2025-04-28 08:10:10,676 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 08:10:10,676 INFO hook.py line 480 1619929] Total Process Time: 24.912 s [2025-04-28 08:10:10,676 INFO hook.py line 481 1619929] Average Process Time: 502.148 ms [2025-04-28 08:10:10,676 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 08:10:10,716 INFO hook.py line 685 1619929] Currently Best AP50: 0.322 [2025-04-28 08:10:10,720 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:11:45,370 INFO hook.py line 650 1619929] Train: [49/512][50/242] Data 0.015 (0.041) Batch 1.404 (1.533) Remain 47:48:15 loss: 6.1752 Lr: 2.74477e-04 Mem R(MA/MR): 20628 (21200/35898) [2025-04-28 08:12:59,644 INFO hook.py line 650 1619929] Train: [49/512][100/242] Data 0.016 (0.028) Batch 1.470 (1.509) Remain 47:00:48 loss: 7.0787 Lr: 2.74367e-04 Mem R(MA/MR): 22072 (21200/35898) [2025-04-28 08:14:11,144 INFO hook.py line 650 1619929] Train: [49/512][150/242] Data 0.016 (0.024) Batch 1.381 (1.482) Remain 46:09:34 loss: 7.7350 Lr: 2.74257e-04 Mem R(MA/MR): 23714 (21200/35898) [2025-04-28 08:15:22,484 INFO hook.py line 650 1619929] Train: [49/512][200/242] Data 0.014 (0.022) Batch 1.290 (1.468) Remain 45:42:16 loss: 7.1371 Lr: 2.74147e-04 Mem R(MA/MR): 25542 (21200/35898) [2025-04-28 08:16:18,839 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6406 loss_mask: 0.0530 loss_dice: 2.8476 loss_score: 0.0000 loss_bbox: 0.0652 loss_sp_cls: 1.1764 loss: 7.6622 [2025-04-28 08:16:20,413 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:17:54,246 INFO hook.py line 650 1619929] Train: [50/512][50/242] Data 0.016 (0.017) Batch 1.501 (1.494) Remain 46:28:24 loss: 6.0752 Lr: 2.73944e-04 Mem R(MA/MR): 26270 (21200/35898) [2025-04-28 08:19:07,023 INFO hook.py line 650 1619929] Train: [50/512][100/242] Data 0.015 (0.017) Batch 1.344 (1.474) Remain 45:50:19 loss: 8.6000 Lr: 2.73834e-04 Mem R(MA/MR): 26274 (21200/35898) [2025-04-28 08:20:16,466 INFO hook.py line 650 1619929] Train: [50/512][150/242] Data 0.016 (0.017) Batch 1.415 (1.445) Remain 44:55:01 loss: 8.3771 Lr: 2.73724e-04 Mem R(MA/MR): 26296 (21200/35898) [2025-04-28 08:21:24,787 INFO hook.py line 650 1619929] Train: [50/512][200/242] Data 0.014 (0.017) Batch 1.326 (1.425) Remain 44:16:35 loss: 8.1547 Lr: 2.73614e-04 Mem R(MA/MR): 26296 (21200/35898) [2025-04-28 08:22:20,485 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6311 loss_mask: 0.0524 loss_dice: 2.8179 loss_score: 0.0000 loss_bbox: 0.0643 loss_sp_cls: 1.1756 loss: 7.5816 [2025-04-28 08:22:23,697 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:23:56,403 INFO hook.py line 650 1619929] Train: [51/512][50/242] Data 0.018 (0.016) Batch 1.537 (1.416) Remain 43:57:11 loss: 7.6309 Lr: 2.73411e-04 Mem R(MA/MR): 20558 (21200/35898) [2025-04-28 08:25:07,308 INFO hook.py line 650 1619929] Train: [51/512][100/242] Data 0.014 (0.016) Batch 1.230 (1.417) Remain 43:58:10 loss: 7.4744 Lr: 2.73301e-04 Mem R(MA/MR): 20558 (21200/35898) [2025-04-28 08:26:15,560 INFO hook.py line 650 1619929] Train: [51/512][150/242] Data 0.015 (0.016) Batch 1.342 (1.399) Remain 43:24:02 loss: 8.9439 Lr: 2.73191e-04 Mem R(MA/MR): 20572 (21200/35898) [2025-04-28 08:27:24,554 INFO hook.py line 650 1619929] Train: [51/512][200/242] Data 0.014 (0.016) Batch 1.418 (1.394) Remain 43:13:41 loss: 8.3118 Lr: 2.73081e-04 Mem R(MA/MR): 20572 (21200/35898) [2025-04-28 08:28:19,502 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6190 loss_mask: 0.0515 loss_dice: 2.8091 loss_score: 0.0000 loss_bbox: 0.0639 loss_sp_cls: 1.1557 loss: 7.5306 [2025-04-28 08:28:21,482 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:29:53,109 INFO hook.py line 650 1619929] Train: [52/512][50/242] Data 0.016 (0.016) Batch 1.452 (1.428) Remain 44:13:44 loss: 7.6844 Lr: 2.72878e-04 Mem R(MA/MR): 26164 (21200/35898) [2025-04-28 08:31:02,154 INFO hook.py line 650 1619929] Train: [52/512][100/242] Data 0.016 (0.016) Batch 1.244 (1.404) Remain 43:27:35 loss: 8.2227 Lr: 2.72768e-04 Mem R(MA/MR): 27904 (21200/35898) [2025-04-28 08:32:10,853 INFO hook.py line 650 1619929] Train: [52/512][150/242] Data 0.016 (0.016) Batch 1.386 (1.394) Remain 43:07:40 loss: 7.6747 Lr: 2.72658e-04 Mem R(MA/MR): 29672 (21200/35898) [2025-04-28 08:33:16,966 INFO hook.py line 650 1619929] Train: [52/512][200/242] Data 0.014 (0.016) Batch 1.122 (1.375) Remain 42:32:55 loss: 7.0610 Lr: 2.72548e-04 Mem R(MA/MR): 32272 (21200/35898) [2025-04-28 08:34:11,276 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6124 loss_mask: 0.0510 loss_dice: 2.8011 loss_score: 0.0000 loss_bbox: 0.0636 loss_sp_cls: 1.1464 loss: 7.4813 [2025-04-28 08:34:13,406 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:35:45,263 INFO hook.py line 650 1619929] Train: [53/512][50/242] Data 0.016 (0.016) Batch 1.322 (1.413) Remain 43:41:10 loss: 6.5528 Lr: 2.72346e-04 Mem R(MA/MR): 24392 (21200/35898) [2025-04-28 08:36:54,906 INFO hook.py line 650 1619929] Train: [53/512][100/242] Data 0.015 (0.016) Batch 1.273 (1.403) Remain 43:20:21 loss: 7.3864 Lr: 2.72235e-04 Mem R(MA/MR): 26252 (21200/35898) [2025-04-28 08:38:02,685 INFO hook.py line 650 1619929] Train: [53/512][150/242] Data 0.016 (0.016) Batch 1.318 (1.387) Remain 42:49:25 loss: 8.0172 Lr: 2.72125e-04 Mem R(MA/MR): 28472 (21200/35898) [2025-04-28 08:39:10,631 INFO hook.py line 650 1619929] Train: [53/512][200/242] Data 0.015 (0.016) Batch 1.203 (1.380) Remain 42:35:11 loss: 6.2146 Lr: 2.72015e-04 Mem R(MA/MR): 28472 (21200/35898) [2025-04-28 08:40:05,364 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6076 loss_mask: 0.0509 loss_dice: 2.7637 loss_score: 0.0000 loss_bbox: 0.0629 loss_sp_cls: 1.1446 loss: 7.4134 [2025-04-28 08:40:05,676 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:41:36,782 INFO hook.py line 650 1619929] Train: [54/512][50/242] Data 0.016 (0.017) Batch 1.298 (1.397) Remain 43:05:27 loss: 9.3293 Lr: 2.71812e-04 Mem R(MA/MR): 21284 (21200/35898) [2025-04-28 08:42:45,455 INFO hook.py line 650 1619929] Train: [54/512][100/242] Data 0.015 (0.016) Batch 1.365 (1.385) Remain 42:41:39 loss: 7.7343 Lr: 2.71702e-04 Mem R(MA/MR): 21286 (21200/35898) [2025-04-28 08:43:53,055 INFO hook.py line 650 1619929] Train: [54/512][150/242] Data 0.016 (0.016) Batch 1.317 (1.374) Remain 42:19:46 loss: 6.0831 Lr: 2.71592e-04 Mem R(MA/MR): 21300 (21200/35898) [2025-04-28 08:45:01,485 INFO hook.py line 650 1619929] Train: [54/512][200/242] Data 0.015 (0.016) Batch 1.419 (1.372) Remain 42:16:13 loss: 7.4980 Lr: 2.71482e-04 Mem R(MA/MR): 21300 (21200/35898) [2025-04-28 08:45:56,788 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5808 loss_mask: 0.0482 loss_dice: 2.6685 loss_score: 0.0000 loss_bbox: 0.0613 loss_sp_cls: 1.1103 loss: 7.1593 [2025-04-28 08:46:00,252 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:47:26,978 INFO hook.py line 650 1619929] Train: [55/512][50/242] Data 0.018 (0.016) Batch 1.385 (1.400) Remain 43:05:40 loss: 7.1477 Lr: 2.71279e-04 Mem R(MA/MR): 17488 (21200/35898) [2025-04-28 08:48:37,298 INFO hook.py line 650 1619929] Train: [55/512][100/242] Data 0.014 (0.016) Batch 1.348 (1.403) Remain 43:10:13 loss: 7.8196 Lr: 2.71169e-04 Mem R(MA/MR): 26860 (21200/35898) [2025-04-28 08:49:43,337 INFO hook.py line 650 1619929] Train: [55/512][150/242] Data 0.016 (0.016) Batch 1.453 (1.375) Remain 42:17:11 loss: 7.4516 Lr: 2.71059e-04 Mem R(MA/MR): 26872 (21200/35898) [2025-04-28 08:50:49,528 INFO hook.py line 650 1619929] Train: [55/512][200/242] Data 0.015 (0.016) Batch 1.441 (1.362) Remain 41:51:55 loss: 6.9089 Lr: 2.70949e-04 Mem R(MA/MR): 30694 (21200/35898) [2025-04-28 08:51:43,121 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5676 loss_mask: 0.0478 loss_dice: 2.6493 loss_score: 0.0000 loss_bbox: 0.0598 loss_sp_cls: 1.0979 loss: 7.0682 [2025-04-28 08:51:45,353 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 08:53:18,642 INFO hook.py line 650 1619929] Train: [56/512][50/242] Data 0.016 (0.017) Batch 1.279 (1.441) Remain 44:14:47 loss: 7.2012 Lr: 2.70746e-04 Mem R(MA/MR): 19514 (21200/35898) [2025-04-28 08:54:29,270 INFO hook.py line 650 1619929] Train: [56/512][100/242] Data 0.017 (0.016) Batch 1.423 (1.426) Remain 43:46:36 loss: 7.2869 Lr: 2.70636e-04 Mem R(MA/MR): 25678 (21200/35898) [2025-04-28 08:55:37,764 INFO hook.py line 650 1619929] Train: [56/512][150/242] Data 0.016 (0.016) Batch 1.448 (1.407) Remain 43:10:08 loss: 7.9022 Lr: 2.70525e-04 Mem R(MA/MR): 25680 (21200/35898) [2025-04-28 08:56:47,678 INFO hook.py line 650 1619929] Train: [56/512][200/242] Data 0.014 (0.016) Batch 1.306 (1.405) Remain 43:04:50 loss: 7.4040 Lr: 2.70415e-04 Mem R(MA/MR): 27518 (21200/35898) [2025-04-28 08:57:42,162 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5702 loss_mask: 0.0489 loss_dice: 2.6600 loss_score: 0.0000 loss_bbox: 0.0607 loss_sp_cls: 1.1035 loss: 7.1150 [2025-04-28 08:57:45,147 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 08:57:47,847 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.8971 Process Time: 0.471 Mem R(MA/MR): 5392 (21200/35898) [2025-04-28 08:57:49,837 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.2655 Process Time: 0.549 Mem R(MA/MR): 8168 (21200/35898) [2025-04-28 08:57:51,546 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.0637 Process Time: 0.600 Mem R(MA/MR): 10636 (21200/35898) [2025-04-28 08:57:59,612 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.7420 Process Time: 1.294 Mem R(MA/MR): 20526 (21200/35898) [2025-04-28 08:58:00,631 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.9167 Process Time: 0.379 Mem R(MA/MR): 8080 (21200/35898) [2025-04-28 08:58:02,375 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0541 Process Time: 0.670 Mem R(MA/MR): 12024 (21200/35898) [2025-04-28 08:58:03,331 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.5565 Process Time: 0.433 Mem R(MA/MR): 7184 (21200/35898) [2025-04-28 08:58:03,836 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.4695 Process Time: 0.145 Mem R(MA/MR): 5442 (21200/35898) [2025-04-28 08:58:04,996 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8171 Process Time: 0.414 Mem R(MA/MR): 12348 (21200/35898) [2025-04-28 08:58:06,541 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.5837 Process Time: 0.303 Mem R(MA/MR): 10370 (21200/35898) [2025-04-28 08:58:09,293 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.8733 Process Time: 0.513 Mem R(MA/MR): 19236 (21200/35898) [2025-04-28 08:58:12,345 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.6942 Process Time: 0.926 Mem R(MA/MR): 16072 (21200/35898) [2025-04-28 08:58:13,828 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.3153 Process Time: 0.424 Mem R(MA/MR): 9590 (21200/35898) [2025-04-28 08:58:14,311 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.8817 Process Time: 0.145 Mem R(MA/MR): 5820 (21200/35898) [2025-04-28 08:58:17,450 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.7771 Process Time: 0.425 Mem R(MA/MR): 17320 (21200/35898) [2025-04-28 08:58:19,373 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0260 Process Time: 0.317 Mem R(MA/MR): 15444 (21200/35898) [2025-04-28 08:58:20,353 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.9433 Process Time: 0.263 Mem R(MA/MR): 7792 (21200/35898) [2025-04-28 08:58:21,395 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.4280 Process Time: 0.319 Mem R(MA/MR): 9214 (21200/35898) [2025-04-28 08:58:23,005 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0788 Process Time: 0.286 Mem R(MA/MR): 7142 (21200/35898) [2025-04-28 08:58:24,496 INFO hook.py line 449 1619929] Test: [20/50] Loss 7.7320 Process Time: 0.266 Mem R(MA/MR): 12354 (21200/35898) [2025-04-28 08:58:33,135 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.5802 Process Time: 0.543 Mem R(MA/MR): 24304 (21200/35898) [2025-04-28 08:58:33,766 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3922 Process Time: 0.222 Mem R(MA/MR): 7884 (21200/35898) [2025-04-28 08:58:44,230 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.0577 Process Time: 0.334 Mem R(MA/MR): 9416 (21200/35898) [2025-04-28 08:58:45,043 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.2338 Process Time: 0.361 Mem R(MA/MR): 6236 (21200/35898) [2025-04-28 08:58:46,390 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.5034 Process Time: 0.488 Mem R(MA/MR): 10490 (21200/35898) [2025-04-28 08:58:53,010 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.4347 Process Time: 1.084 Mem R(MA/MR): 32004 (21200/35898) [2025-04-28 08:58:55,579 INFO hook.py line 449 1619929] Test: [27/50] Loss 9.5626 Process Time: 0.813 Mem R(MA/MR): 11040 (21200/35898) [2025-04-28 08:58:56,782 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.9693 Process Time: 0.310 Mem R(MA/MR): 9846 (21200/35898) [2025-04-28 08:59:01,553 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9573 Process Time: 0.299 Mem R(MA/MR): 18116 (21200/35898) [2025-04-28 08:59:02,908 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.5245 Process Time: 0.528 Mem R(MA/MR): 8806 (21200/35898) [2025-04-28 08:59:07,205 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.4842 Process Time: 0.452 Mem R(MA/MR): 21240 (21200/35898) [2025-04-28 08:59:07,482 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.4284 Process Time: 0.110 Mem R(MA/MR): 4908 (21200/35898) [2025-04-28 08:59:10,917 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.4173 Process Time: 0.343 Mem R(MA/MR): 25322 (21200/35898) [2025-04-28 08:59:12,535 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.3731 Process Time: 0.703 Mem R(MA/MR): 10746 (21200/35898) [2025-04-28 08:59:14,350 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.1521 Process Time: 0.371 Mem R(MA/MR): 14900 (21200/35898) [2025-04-28 08:59:14,803 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.5075 Process Time: 0.145 Mem R(MA/MR): 7652 (21200/35898) [2025-04-28 08:59:18,363 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.1162 Process Time: 0.398 Mem R(MA/MR): 29300 (21200/35898) [2025-04-28 08:59:20,012 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.2607 Process Time: 0.383 Mem R(MA/MR): 11460 (21200/35898) [2025-04-28 08:59:20,822 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.7116 Process Time: 0.349 Mem R(MA/MR): 6568 (21200/35898) [2025-04-28 08:59:22,040 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.4610 Process Time: 0.373 Mem R(MA/MR): 11024 (21200/35898) [2025-04-28 08:59:23,074 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.2877 Process Time: 0.306 Mem R(MA/MR): 10060 (21200/35898) [2025-04-28 08:59:23,559 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3391 Process Time: 0.151 Mem R(MA/MR): 6384 (21200/35898) [2025-04-28 08:59:24,100 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.3459 Process Time: 0.261 Mem R(MA/MR): 6606 (21200/35898) [2025-04-28 08:59:24,608 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.5033 Process Time: 0.152 Mem R(MA/MR): 8104 (21200/35898) [2025-04-28 08:59:25,106 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6520 Process Time: 0.115 Mem R(MA/MR): 6134 (21200/35898) [2025-04-28 08:59:26,914 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.2087 Process Time: 0.220 Mem R(MA/MR): 15666 (21200/35898) [2025-04-28 08:59:35,033 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.6000 Process Time: 1.668 Mem R(MA/MR): 21250 (21200/35898) [2025-04-28 08:59:45,071 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9734 Process Time: 2.040 Mem R(MA/MR): 35866 (21200/35898) [2025-04-28 08:59:46,440 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.6032 Process Time: 0.516 Mem R(MA/MR): 6650 (21200/35898) [2025-04-28 08:59:48,874 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5055 Process Time: 0.602 Mem R(MA/MR): 14392 (21200/35898) [2025-04-28 08:59:52,884 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 08:59:52,884 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 08:59:52,885 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] table : 0.217 0.549 0.782 0.786 0.596 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] door : 0.461 0.791 0.888 0.892 0.734 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] ceiling lamp : 0.496 0.691 0.838 0.891 0.635 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] cabinet : 0.352 0.500 0.564 0.620 0.463 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] blinds : 0.393 0.622 0.750 0.750 0.652 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] curtain : 0.187 0.254 0.627 0.412 0.583 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] chair : 0.592 0.735 0.790 0.826 0.660 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] storage cabinet: 0.093 0.222 0.479 0.435 0.400 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] office chair : 0.557 0.593 0.610 0.712 0.771 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] bookshelf : 0.273 0.683 0.730 0.778 0.636 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] whiteboard : 0.511 0.686 0.730 0.828 0.686 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] window : 0.064 0.160 0.553 0.333 0.253 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] box : 0.135 0.252 0.419 0.394 0.359 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] monitor : 0.516 0.672 0.784 0.825 0.671 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] shelf : 0.078 0.191 0.345 0.381 0.267 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] heater : 0.387 0.695 0.749 0.875 0.737 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] kitchen cabinet: 0.196 0.421 0.612 0.571 0.480 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] sofa : 0.612 0.822 0.930 0.786 0.917 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] bed : 0.140 0.406 0.764 0.571 0.500 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] trash can : 0.532 0.674 0.742 0.787 0.738 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] book : 0.013 0.028 0.066 0.161 0.082 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] plant : 0.406 0.620 0.733 0.909 0.556 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] blanket : 0.325 0.394 0.616 0.600 0.545 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] tv : 0.741 0.878 0.878 1.000 0.667 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] computer tower : 0.189 0.274 0.472 0.305 0.429 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] refrigerator : 0.254 0.419 0.437 0.571 0.444 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] jacket : 0.073 0.292 0.558 0.500 0.455 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] sink : 0.242 0.622 0.868 0.800 0.727 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] bag : 0.147 0.219 0.225 0.421 0.296 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] picture : 0.079 0.215 0.380 0.619 0.333 [2025-04-28 08:59:52,885 INFO hook.py line 395 1619929] pillow : 0.562 0.698 0.735 1.000 0.632 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] towel : 0.139 0.219 0.452 0.429 0.316 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] suitcase : 0.294 0.312 0.360 1.000 0.286 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] backpack : 0.351 0.384 0.430 0.545 0.462 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] crate : 0.080 0.176 0.450 0.308 0.364 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] keyboard : 0.313 0.432 0.512 0.750 0.385 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] toilet : 0.709 0.889 1.000 1.000 0.889 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] printer : 0.230 0.416 0.430 0.571 0.444 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] poster : 0.025 0.118 0.119 1.000 0.111 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] painting : 0.033 0.036 0.050 0.071 1.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] microwave : 0.443 0.706 0.957 1.000 0.625 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] shoes : 0.134 0.256 0.475 0.714 0.244 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] socket : 0.149 0.398 0.608 0.519 0.493 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] bottle : 0.110 0.153 0.248 0.567 0.205 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] bucket : 0.014 0.014 0.015 0.087 0.286 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] cushion : 0.000 0.000 0.167 0.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.036 0.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] telephone : 0.187 0.457 0.634 0.889 0.471 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] laptop : 0.259 0.677 0.679 0.667 0.750 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] plant pot : 0.083 0.332 0.563 0.538 0.438 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] cup : 0.192 0.293 0.339 0.722 0.295 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] coat hanger : 0.056 0.500 0.500 1.000 0.500 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] light switch : 0.220 0.472 0.569 0.775 0.477 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] speaker : 0.241 0.383 0.366 0.556 0.455 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] table lamp : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] smoke detector : 0.612 0.741 0.786 1.000 0.708 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] power strip : 0.124 0.188 0.227 0.308 0.400 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] mouse : 0.436 0.606 0.661 0.741 0.625 [2025-04-28 08:59:52,886 INFO hook.py line 395 1619929] cutting board : 0.306 0.500 0.500 1.000 0.500 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] toilet paper : 0.106 0.219 0.270 0.333 0.294 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] clock : 0.398 0.667 0.667 1.000 0.667 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] tap : 0.058 0.154 0.556 0.600 0.333 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] soap dispenser : 0.412 0.600 0.600 1.000 0.600 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] bowl : 0.024 0.131 0.667 0.333 0.667 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] whiteboard eraser: 0.141 0.389 0.411 0.571 0.667 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] toilet brush : 0.291 0.474 0.630 0.800 0.667 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 08:59:52,887 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 08:59:52,887 INFO hook.py line 404 1619929] average : 0.213 0.344 0.450 0.570 0.405 [2025-04-28 08:59:52,887 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 08:59:52,887 INFO hook.py line 480 1619929] Total Process Time: 23.782 s [2025-04-28 08:59:52,887 INFO hook.py line 481 1619929] Average Process Time: 475.728 ms [2025-04-28 08:59:52,887 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 08:59:52,926 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.344 [2025-04-28 08:59:52,928 INFO hook.py line 685 1619929] Currently Best AP50: 0.344 [2025-04-28 08:59:52,931 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:01:26,095 INFO hook.py line 650 1619929] Train: [57/512][50/242] Data 0.016 (0.017) Batch 1.522 (1.427) Remain 43:43:23 loss: 8.4224 Lr: 2.70212e-04 Mem R(MA/MR): 24180 (21200/35898) [2025-04-28 09:02:34,460 INFO hook.py line 650 1619929] Train: [57/512][100/242] Data 0.016 (0.016) Batch 1.301 (1.396) Remain 42:45:37 loss: 6.9813 Lr: 2.70102e-04 Mem R(MA/MR): 24204 (21200/35898) [2025-04-28 09:03:44,772 INFO hook.py line 650 1619929] Train: [57/512][150/242] Data 0.015 (0.022) Batch 1.514 (1.400) Remain 42:50:43 loss: 8.1031 Lr: 2.69992e-04 Mem R(MA/MR): 24204 (21200/35898) [2025-04-28 09:04:52,884 INFO hook.py line 650 1619929] Train: [57/512][200/242] Data 0.014 (0.020) Batch 1.281 (1.390) Remain 42:32:08 loss: 6.7132 Lr: 2.69882e-04 Mem R(MA/MR): 24204 (21200/35898) [2025-04-28 09:05:47,740 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5671 loss_mask: 0.0469 loss_dice: 2.6254 loss_score: 0.0000 loss_bbox: 0.0597 loss_sp_cls: 1.0856 loss: 7.0341 [2025-04-28 09:05:49,168 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:07:24,547 INFO hook.py line 650 1619929] Train: [58/512][50/242] Data 0.017 (0.017) Batch 1.441 (1.449) Remain 44:18:12 loss: 8.4503 Lr: 2.69679e-04 Mem R(MA/MR): 21922 (21200/35898) [2025-04-28 09:08:34,176 INFO hook.py line 650 1619929] Train: [58/512][100/242] Data 0.016 (0.016) Batch 1.394 (1.420) Remain 43:23:33 loss: 6.8970 Lr: 2.69569e-04 Mem R(MA/MR): 21924 (21200/35898) [2025-04-28 09:09:44,521 INFO hook.py line 650 1619929] Train: [58/512][150/242] Data 0.016 (0.016) Batch 1.592 (1.416) Remain 43:14:11 loss: 8.1038 Lr: 2.69458e-04 Mem R(MA/MR): 21924 (21200/35898) [2025-04-28 09:10:55,036 INFO hook.py line 650 1619929] Train: [58/512][200/242] Data 0.014 (0.016) Batch 1.458 (1.414) Remain 43:10:35 loss: 8.1868 Lr: 2.69348e-04 Mem R(MA/MR): 21932 (21200/35898) [2025-04-28 09:11:51,704 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5678 loss_mask: 0.0483 loss_dice: 2.6455 loss_score: 0.0000 loss_bbox: 0.0594 loss_sp_cls: 1.1030 loss: 7.0788 [2025-04-28 09:11:52,308 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:13:23,035 INFO hook.py line 650 1619929] Train: [59/512][50/242] Data 0.016 (0.016) Batch 1.534 (1.379) Remain 42:04:21 loss: 8.2912 Lr: 2.69145e-04 Mem R(MA/MR): 21038 (21200/35898) [2025-04-28 09:14:32,120 INFO hook.py line 650 1619929] Train: [59/512][100/242] Data 0.016 (0.016) Batch 1.402 (1.381) Remain 42:05:34 loss: 6.0342 Lr: 2.69035e-04 Mem R(MA/MR): 21038 (21200/35898) [2025-04-28 09:15:40,393 INFO hook.py line 650 1619929] Train: [59/512][150/242] Data 0.020 (0.016) Batch 1.313 (1.375) Remain 41:55:04 loss: 6.3953 Lr: 2.68925e-04 Mem R(MA/MR): 21038 (21200/35898) [2025-04-28 09:16:49,764 INFO hook.py line 650 1619929] Train: [59/512][200/242] Data 0.014 (0.016) Batch 1.261 (1.378) Remain 41:59:31 loss: 7.8528 Lr: 2.68814e-04 Mem R(MA/MR): 23272 (21200/35898) [2025-04-28 09:17:43,716 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5634 loss_mask: 0.0486 loss_dice: 2.6491 loss_score: 0.0000 loss_bbox: 0.0598 loss_sp_cls: 1.0978 loss: 7.0655 [2025-04-28 09:17:43,782 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:19:16,283 INFO hook.py line 650 1619929] Train: [60/512][50/242] Data 0.017 (0.017) Batch 1.333 (1.372) Remain 41:45:21 loss: 7.7070 Lr: 2.68611e-04 Mem R(MA/MR): 25644 (21200/35898) [2025-04-28 09:20:25,380 INFO hook.py line 650 1619929] Train: [60/512][100/242] Data 0.015 (0.016) Batch 1.389 (1.377) Remain 41:53:42 loss: 7.8060 Lr: 2.68501e-04 Mem R(MA/MR): 26548 (21200/35898) [2025-04-28 09:21:37,901 INFO hook.py line 650 1619929] Train: [60/512][150/242] Data 0.016 (0.016) Batch 1.568 (1.402) Remain 42:38:06 loss: 6.9290 Lr: 2.68391e-04 Mem R(MA/MR): 26548 (21200/35898) [2025-04-28 09:22:46,002 INFO hook.py line 650 1619929] Train: [60/512][200/242] Data 0.014 (0.016) Batch 1.333 (1.392) Remain 42:18:25 loss: 7.6829 Lr: 2.68280e-04 Mem R(MA/MR): 26548 (21200/35898) [2025-04-28 09:23:40,228 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5696 loss_mask: 0.0490 loss_dice: 2.6443 loss_score: 0.0000 loss_bbox: 0.0606 loss_sp_cls: 1.0987 loss: 7.0848 [2025-04-28 09:23:41,462 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:25:04,302 INFO hook.py line 650 1619929] Train: [61/512][50/242] Data 0.016 (0.017) Batch 1.338 (1.382) Remain 41:57:32 loss: 7.2859 Lr: 2.68077e-04 Mem R(MA/MR): 20366 (21200/35898) [2025-04-28 09:26:14,770 INFO hook.py line 650 1619929] Train: [61/512][100/242] Data 0.018 (0.017) Batch 1.260 (1.396) Remain 42:22:27 loss: 6.2959 Lr: 2.67967e-04 Mem R(MA/MR): 22080 (21200/35898) [2025-04-28 09:27:23,212 INFO hook.py line 650 1619929] Train: [61/512][150/242] Data 0.015 (0.016) Batch 1.338 (1.387) Remain 42:04:33 loss: 7.6008 Lr: 2.67859e-04 Mem R(MA/MR): 23852 (21200/35898) [2025-04-28 09:28:30,633 INFO hook.py line 650 1619929] Train: [61/512][200/242] Data 0.015 (0.016) Batch 1.271 (1.377) Remain 41:45:44 loss: 6.6932 Lr: 2.67749e-04 Mem R(MA/MR): 23852 (21200/35898) [2025-04-28 09:29:25,178 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5920 loss_mask: 0.0508 loss_dice: 2.7113 loss_score: 0.0000 loss_bbox: 0.0618 loss_sp_cls: 1.1142 loss: 7.2574 [2025-04-28 09:29:27,620 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:30:55,433 INFO hook.py line 650 1619929] Train: [62/512][50/242] Data 0.014 (0.016) Batch 1.455 (1.356) Remain 41:04:41 loss: 8.1907 Lr: 2.67546e-04 Mem R(MA/MR): 20572 (21200/35898) [2025-04-28 09:32:04,857 INFO hook.py line 650 1619929] Train: [62/512][100/242] Data 0.016 (0.016) Batch 1.386 (1.373) Remain 41:34:22 loss: 8.5883 Lr: 2.67435e-04 Mem R(MA/MR): 24168 (21200/35898) [2025-04-28 09:33:12,973 INFO hook.py line 650 1619929] Train: [62/512][150/242] Data 0.016 (0.016) Batch 1.298 (1.369) Remain 41:26:55 loss: 7.2666 Lr: 2.67325e-04 Mem R(MA/MR): 26020 (21200/35898) [2025-04-28 09:34:22,110 INFO hook.py line 650 1619929] Train: [62/512][200/242] Data 0.015 (0.016) Batch 1.497 (1.373) Remain 41:32:05 loss: 8.1636 Lr: 2.67215e-04 Mem R(MA/MR): 26020 (21200/35898) [2025-04-28 09:35:16,982 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6213 loss_mask: 0.0532 loss_dice: 2.8457 loss_score: 0.0000 loss_bbox: 0.0641 loss_sp_cls: 1.1608 loss: 7.5823 [2025-04-28 09:35:19,617 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:36:51,729 INFO hook.py line 650 1619929] Train: [63/512][50/242] Data 0.016 (0.016) Batch 1.351 (1.409) Remain 42:36:20 loss: 7.8436 Lr: 2.67012e-04 Mem R(MA/MR): 21968 (21200/35898) [2025-04-28 09:37:58,677 INFO hook.py line 650 1619929] Train: [63/512][100/242] Data 0.017 (0.016) Batch 1.221 (1.373) Remain 41:29:36 loss: 7.3750 Lr: 2.66901e-04 Mem R(MA/MR): 23878 (21200/35898) [2025-04-28 09:39:06,703 INFO hook.py line 650 1619929] Train: [63/512][150/242] Data 0.015 (0.016) Batch 1.267 (1.369) Remain 41:20:43 loss: 6.3465 Lr: 2.66791e-04 Mem R(MA/MR): 23878 (21200/35898) [2025-04-28 09:40:17,114 INFO hook.py line 650 1619929] Train: [63/512][200/242] Data 0.015 (0.016) Batch 1.241 (1.379) Remain 41:37:49 loss: 8.4080 Lr: 2.66680e-04 Mem R(MA/MR): 23878 (21200/35898) [2025-04-28 09:41:12,920 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6109 loss_mask: 0.0535 loss_dice: 2.8058 loss_score: 0.0000 loss_bbox: 0.0645 loss_sp_cls: 1.1452 loss: 7.4998 [2025-04-28 09:41:14,604 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:42:42,829 INFO hook.py line 650 1619929] Train: [64/512][50/242] Data 0.019 (0.017) Batch 1.386 (1.438) Remain 43:23:49 loss: 5.9876 Lr: 2.66477e-04 Mem R(MA/MR): 20042 (21200/35898) [2025-04-28 09:43:53,975 INFO hook.py line 650 1619929] Train: [64/512][100/242] Data 0.016 (0.016) Batch 1.479 (1.430) Remain 43:08:08 loss: 7.8490 Lr: 2.66367e-04 Mem R(MA/MR): 21578 (21200/35898) [2025-04-28 09:45:03,865 INFO hook.py line 650 1619929] Train: [64/512][150/242] Data 0.017 (0.017) Batch 1.339 (1.419) Remain 42:46:51 loss: 7.7533 Lr: 2.66256e-04 Mem R(MA/MR): 23372 (21200/35898) [2025-04-28 09:46:11,979 INFO hook.py line 650 1619929] Train: [64/512][200/242] Data 0.014 (0.016) Batch 1.358 (1.405) Remain 42:19:30 loss: 6.4231 Lr: 2.66146e-04 Mem R(MA/MR): 23376 (21200/35898) [2025-04-28 09:47:07,680 INFO misc.py line 135 1619929] Train result: loss_cls: 0.6009 loss_mask: 0.0511 loss_dice: 2.7329 loss_score: 0.0000 loss_bbox: 0.0636 loss_sp_cls: 1.1368 loss: 7.3486 [2025-04-28 09:47:08,088 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 09:47:10,716 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.7753 Process Time: 0.426 Mem R(MA/MR): 4602 (21200/35898) [2025-04-28 09:47:12,530 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.8573 Process Time: 0.822 Mem R(MA/MR): 7218 (21200/35898) [2025-04-28 09:47:14,057 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1629 Process Time: 0.622 Mem R(MA/MR): 9936 (21200/35898) [2025-04-28 09:47:20,993 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.6141 Process Time: 1.076 Mem R(MA/MR): 19864 (21200/35898) [2025-04-28 09:47:22,243 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.9803 Process Time: 0.336 Mem R(MA/MR): 7156 (21200/35898) [2025-04-28 09:47:23,671 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.2126 Process Time: 0.391 Mem R(MA/MR): 11346 (21200/35898) [2025-04-28 09:47:24,232 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3556 Process Time: 0.187 Mem R(MA/MR): 6414 (21200/35898) [2025-04-28 09:47:24,647 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.8254 Process Time: 0.130 Mem R(MA/MR): 4636 (21200/35898) [2025-04-28 09:47:25,523 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7397 Process Time: 0.239 Mem R(MA/MR): 11650 (21200/35898) [2025-04-28 09:47:26,880 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.8168 Process Time: 0.298 Mem R(MA/MR): 9702 (21200/35898) [2025-04-28 09:47:29,633 INFO hook.py line 449 1619929] Test: [11/50] Loss 13.2354 Process Time: 0.521 Mem R(MA/MR): 18892 (21200/35898) [2025-04-28 09:47:32,809 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.9893 Process Time: 0.790 Mem R(MA/MR): 15660 (21200/35898) [2025-04-28 09:47:34,460 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.1809 Process Time: 0.518 Mem R(MA/MR): 8874 (21200/35898) [2025-04-28 09:47:34,967 INFO hook.py line 449 1619929] Test: [14/50] Loss 4.3275 Process Time: 0.169 Mem R(MA/MR): 5004 (21200/35898) [2025-04-28 09:47:37,600 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.1560 Process Time: 0.357 Mem R(MA/MR): 16798 (21200/35898) [2025-04-28 09:47:40,205 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.6124 Process Time: 0.848 Mem R(MA/MR): 14832 (21200/35898) [2025-04-28 09:47:41,032 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.8237 Process Time: 0.194 Mem R(MA/MR): 6780 (21200/35898) [2025-04-28 09:47:42,002 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.7433 Process Time: 0.218 Mem R(MA/MR): 8550 (21200/35898) [2025-04-28 09:47:43,236 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.8517 Process Time: 0.155 Mem R(MA/MR): 6418 (21200/35898) [2025-04-28 09:47:45,126 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.0684 Process Time: 0.459 Mem R(MA/MR): 11528 (21200/35898) [2025-04-28 09:47:54,008 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.4671 Process Time: 0.654 Mem R(MA/MR): 23544 (21200/35898) [2025-04-28 09:47:55,090 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5596 Process Time: 0.376 Mem R(MA/MR): 7104 (21200/35898) [2025-04-28 09:48:05,835 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.4996 Process Time: 0.600 Mem R(MA/MR): 10200 (21200/35898) [2025-04-28 09:48:06,426 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.3963 Process Time: 0.217 Mem R(MA/MR): 5432 (21200/35898) [2025-04-28 09:48:07,478 INFO hook.py line 449 1619929] Test: [25/50] Loss 4.0724 Process Time: 0.246 Mem R(MA/MR): 9726 (21200/35898) [2025-04-28 09:48:14,821 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.6477 Process Time: 0.623 Mem R(MA/MR): 32210 (21200/35898) [2025-04-28 09:48:16,172 INFO hook.py line 449 1619929] Test: [27/50] Loss 10.5450 Process Time: 0.220 Mem R(MA/MR): 10298 (21200/35898) [2025-04-28 09:48:17,343 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.7501 Process Time: 0.270 Mem R(MA/MR): 9052 (21200/35898) [2025-04-28 09:48:21,924 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.5485 Process Time: 0.372 Mem R(MA/MR): 17322 (21200/35898) [2025-04-28 09:48:22,928 INFO hook.py line 449 1619929] Test: [30/50] Loss 7.5199 Process Time: 0.273 Mem R(MA/MR): 8098 (21200/35898) [2025-04-28 09:48:27,112 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.5718 Process Time: 0.454 Mem R(MA/MR): 20792 (21200/35898) [2025-04-28 09:48:27,739 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3375 Process Time: 0.251 Mem R(MA/MR): 4106 (21200/35898) [2025-04-28 09:48:31,471 INFO hook.py line 449 1619929] Test: [33/50] Loss 14.0371 Process Time: 0.520 Mem R(MA/MR): 24762 (21200/35898) [2025-04-28 09:48:32,428 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.5534 Process Time: 0.213 Mem R(MA/MR): 10040 (21200/35898) [2025-04-28 09:48:33,869 INFO hook.py line 449 1619929] Test: [35/50] Loss 9.0090 Process Time: 0.232 Mem R(MA/MR): 14148 (21200/35898) [2025-04-28 09:48:34,801 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0891 Process Time: 0.404 Mem R(MA/MR): 6868 (21200/35898) [2025-04-28 09:48:38,849 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.4961 Process Time: 0.691 Mem R(MA/MR): 28562 (21200/35898) [2025-04-28 09:48:40,263 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.6383 Process Time: 0.237 Mem R(MA/MR): 10904 (21200/35898) [2025-04-28 09:48:40,783 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.8553 Process Time: 0.187 Mem R(MA/MR): 5640 (21200/35898) [2025-04-28 09:48:41,808 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.3331 Process Time: 0.213 Mem R(MA/MR): 10292 (21200/35898) [2025-04-28 09:48:42,780 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.8917 Process Time: 0.221 Mem R(MA/MR): 9266 (21200/35898) [2025-04-28 09:48:43,403 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3350 Process Time: 0.225 Mem R(MA/MR): 5564 (21200/35898) [2025-04-28 09:48:43,922 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.7794 Process Time: 0.200 Mem R(MA/MR): 5662 (21200/35898) [2025-04-28 09:48:44,885 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3111 Process Time: 0.452 Mem R(MA/MR): 7166 (21200/35898) [2025-04-28 09:48:45,459 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.2301 Process Time: 0.161 Mem R(MA/MR): 5368 (21200/35898) [2025-04-28 09:48:48,157 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5584 Process Time: 0.893 Mem R(MA/MR): 14784 (21200/35898) [2025-04-28 09:48:54,848 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.6131 Process Time: 1.096 Mem R(MA/MR): 20594 (21200/35898) [2025-04-28 09:49:05,217 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.7109 Process Time: 1.323 Mem R(MA/MR): 36094 (21200/36094) [2025-04-28 09:49:05,764 INFO hook.py line 449 1619929] Test: [49/50] Loss 5.4066 Process Time: 0.128 Mem R(MA/MR): 5806 (21200/36094) [2025-04-28 09:49:08,016 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.3440 Process Time: 0.410 Mem R(MA/MR): 13854 (21200/36094) [2025-04-28 09:49:12,231 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 09:49:12,231 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 09:49:12,231 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] table : 0.176 0.456 0.745 0.739 0.500 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] door : 0.327 0.713 0.862 0.791 0.671 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] ceiling lamp : 0.498 0.699 0.819 0.826 0.680 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] cabinet : 0.213 0.341 0.485 0.481 0.373 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] blinds : 0.338 0.668 0.813 0.800 0.696 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] curtain : 0.237 0.330 0.633 0.444 0.667 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] chair : 0.465 0.639 0.747 0.763 0.594 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] storage cabinet: 0.140 0.261 0.536 0.355 0.440 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] office chair : 0.478 0.512 0.526 0.727 0.667 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] bookshelf : 0.164 0.526 0.649 0.667 0.545 [2025-04-28 09:49:12,231 INFO hook.py line 395 1619929] whiteboard : 0.455 0.617 0.683 0.913 0.600 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] window : 0.073 0.188 0.576 0.393 0.242 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] box : 0.122 0.242 0.398 0.466 0.304 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] monitor : 0.469 0.611 0.729 0.754 0.657 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] shelf : 0.028 0.086 0.276 0.280 0.233 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] heater : 0.309 0.560 0.791 0.846 0.579 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] kitchen cabinet: 0.110 0.405 0.727 0.452 0.560 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] sofa : 0.386 0.612 0.786 0.857 0.500 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] bed : 0.124 0.422 0.542 0.750 0.375 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] trash can : 0.478 0.607 0.710 0.636 0.754 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] book : 0.013 0.034 0.065 0.157 0.075 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] plant : 0.394 0.557 0.765 0.833 0.556 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] blanket : 0.324 0.528 0.631 0.750 0.545 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] tv : 0.835 0.941 0.941 1.000 0.833 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] computer tower : 0.169 0.236 0.498 0.550 0.262 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] refrigerator : 0.278 0.435 0.446 0.800 0.444 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] jacket : 0.044 0.138 0.310 0.357 0.455 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] sink : 0.326 0.696 0.893 0.833 0.682 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] bag : 0.078 0.090 0.115 0.278 0.185 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] picture : 0.078 0.171 0.405 0.500 0.282 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] pillow : 0.404 0.560 0.770 0.750 0.632 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] towel : 0.178 0.293 0.440 0.483 0.368 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] suitcase : 0.223 0.236 0.240 0.500 0.286 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] backpack : 0.289 0.336 0.417 0.625 0.385 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] crate : 0.015 0.039 0.431 0.143 0.364 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] keyboard : 0.291 0.405 0.511 0.615 0.410 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] toilet : 0.699 0.876 1.000 0.889 0.889 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] printer : 0.230 0.237 0.255 0.600 0.333 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] poster : 0.001 0.008 0.014 0.143 0.111 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] painting : 0.050 0.050 0.071 0.100 1.000 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] microwave : 0.426 0.634 0.903 1.000 0.500 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] shoes : 0.111 0.211 0.423 0.647 0.268 [2025-04-28 09:49:12,232 INFO hook.py line 395 1619929] socket : 0.111 0.296 0.567 0.486 0.379 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] bottle : 0.101 0.147 0.220 0.410 0.193 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] bucket : 0.090 0.246 0.246 0.273 0.429 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] cushion : 0.019 0.167 0.385 1.000 0.167 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] basket : 0.002 0.014 0.018 0.200 0.143 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] telephone : 0.231 0.414 0.443 0.700 0.412 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] laptop : 0.183 0.493 0.521 0.667 0.500 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] plant pot : 0.018 0.079 0.235 0.500 0.188 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] exhaust fan : 0.093 0.106 0.298 0.375 0.200 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] cup : 0.190 0.324 0.377 0.615 0.364 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.250 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] light switch : 0.217 0.481 0.641 0.825 0.508 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] speaker : 0.154 0.258 0.356 0.750 0.273 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] smoke detector : 0.564 0.722 0.765 1.000 0.667 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] power strip : 0.121 0.233 0.252 1.000 0.200 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] mouse : 0.401 0.532 0.628 0.739 0.531 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] cutting board : 0.111 0.250 0.500 1.000 0.250 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] toilet paper : 0.053 0.150 0.214 0.600 0.176 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] clock : 0.330 0.656 0.764 0.600 1.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] tap : 0.054 0.074 0.556 0.500 0.222 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] soap dispenser : 0.229 0.373 0.460 0.500 0.600 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] bowl : 0.083 0.083 0.333 0.500 0.333 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,233 INFO hook.py line 395 1619929] whiteboard eraser: 0.077 0.243 0.271 0.364 0.667 [2025-04-28 09:49:12,234 INFO hook.py line 395 1619929] toilet brush : 0.348 0.659 0.852 0.800 0.667 [2025-04-28 09:49:12,234 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,234 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 09:49:12,234 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,234 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 09:49:12,234 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 09:49:12,234 INFO hook.py line 404 1619929] average : 0.188 0.303 0.432 0.511 0.369 [2025-04-28 09:49:12,234 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 09:49:12,234 INFO hook.py line 480 1619929] Total Process Time: 21.121 s [2025-04-28 09:49:12,234 INFO hook.py line 481 1619929] Average Process Time: 422.348 ms [2025-04-28 09:49:12,234 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 09:49:12,279 INFO hook.py line 685 1619929] Currently Best AP50: 0.344 [2025-04-28 09:49:12,283 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:50:44,284 INFO hook.py line 650 1619929] Train: [65/512][50/242] Data 0.017 (0.016) Batch 1.403 (1.437) Remain 43:14:35 loss: 6.9153 Lr: 2.65943e-04 Mem R(MA/MR): 22916 (21200/36094) [2025-04-28 09:51:53,053 INFO hook.py line 650 1619929] Train: [65/512][100/242] Data 0.017 (0.024) Batch 1.400 (1.405) Remain 42:16:27 loss: 9.8894 Lr: 2.65832e-04 Mem R(MA/MR): 22930 (21200/36094) [2025-04-28 09:53:02,459 INFO hook.py line 650 1619929] Train: [65/512][150/242] Data 0.018 (0.021) Batch 1.349 (1.399) Remain 42:04:53 loss: 7.7247 Lr: 2.65722e-04 Mem R(MA/MR): 22946 (21200/36094) [2025-04-28 09:54:12,311 INFO hook.py line 650 1619929] Train: [65/512][200/242] Data 0.014 (0.020) Batch 1.346 (1.399) Remain 42:02:42 loss: 6.4372 Lr: 2.65612e-04 Mem R(MA/MR): 22946 (21200/36094) [2025-04-28 09:55:06,197 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5990 loss_mask: 0.0514 loss_dice: 2.7307 loss_score: 0.0000 loss_bbox: 0.0632 loss_sp_cls: 1.1274 loss: 7.3309 [2025-04-28 09:55:08,201 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 09:56:40,017 INFO hook.py line 650 1619929] Train: [66/512][50/242] Data 0.017 (0.017) Batch 1.360 (1.395) Remain 41:54:43 loss: 8.1072 Lr: 2.65408e-04 Mem R(MA/MR): 20230 (21200/36094) [2025-04-28 09:57:46,924 INFO hook.py line 650 1619929] Train: [66/512][100/242] Data 0.016 (0.017) Batch 1.423 (1.366) Remain 41:00:21 loss: 8.8386 Lr: 2.65298e-04 Mem R(MA/MR): 22036 (21200/36094) [2025-04-28 09:58:55,756 INFO hook.py line 650 1619929] Train: [66/512][150/242] Data 0.015 (0.016) Batch 1.283 (1.370) Remain 41:05:46 loss: 7.7200 Lr: 2.65187e-04 Mem R(MA/MR): 22036 (21200/36094) [2025-04-28 10:00:03,141 INFO hook.py line 650 1619929] Train: [66/512][200/242] Data 0.014 (0.016) Batch 1.318 (1.364) Remain 40:54:38 loss: 7.1852 Lr: 2.65077e-04 Mem R(MA/MR): 22036 (21200/36094) [2025-04-28 10:00:56,988 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5903 loss_mask: 0.0513 loss_dice: 2.7271 loss_score: 0.0000 loss_bbox: 0.0627 loss_sp_cls: 1.1202 loss: 7.2942 [2025-04-28 10:00:57,489 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:02:29,950 INFO hook.py line 650 1619929] Train: [67/512][50/242] Data 0.015 (0.017) Batch 1.340 (1.406) Remain 42:08:29 loss: 6.7259 Lr: 2.64874e-04 Mem R(MA/MR): 23588 (21200/36094) [2025-04-28 10:03:36,663 INFO hook.py line 650 1619929] Train: [67/512][100/242] Data 0.015 (0.016) Batch 1.319 (1.369) Remain 41:00:37 loss: 6.7450 Lr: 2.64763e-04 Mem R(MA/MR): 23588 (21200/36094) [2025-04-28 10:04:43,442 INFO hook.py line 650 1619929] Train: [67/512][150/242] Data 0.016 (0.016) Batch 1.380 (1.358) Remain 40:38:58 loss: 6.6220 Lr: 2.64653e-04 Mem R(MA/MR): 23588 (21200/36094) [2025-04-28 10:05:51,614 INFO hook.py line 650 1619929] Train: [67/512][200/242] Data 0.014 (0.016) Batch 1.194 (1.359) Remain 40:40:27 loss: 7.3083 Lr: 2.64542e-04 Mem R(MA/MR): 23588 (21200/36094) [2025-04-28 10:06:47,065 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5829 loss_mask: 0.0502 loss_dice: 2.7260 loss_score: 0.0000 loss_bbox: 0.0621 loss_sp_cls: 1.1130 loss: 7.2597 [2025-04-28 10:06:47,145 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:08:20,796 INFO hook.py line 650 1619929] Train: [68/512][50/242] Data 0.016 (0.016) Batch 1.268 (1.425) Remain 42:36:01 loss: 7.0929 Lr: 2.64339e-04 Mem R(MA/MR): 25546 (21200/36094) [2025-04-28 10:09:26,366 INFO hook.py line 650 1619929] Train: [68/512][100/242] Data 0.015 (0.016) Batch 1.310 (1.366) Remain 40:49:59 loss: 6.4830 Lr: 2.64228e-04 Mem R(MA/MR): 25546 (21200/36094) [2025-04-28 10:10:33,535 INFO hook.py line 650 1619929] Train: [68/512][150/242] Data 0.016 (0.016) Batch 1.376 (1.359) Remain 40:34:53 loss: 7.4368 Lr: 2.64118e-04 Mem R(MA/MR): 25550 (21200/36094) [2025-04-28 10:11:39,214 INFO hook.py line 650 1619929] Train: [68/512][200/242] Data 0.014 (0.016) Batch 1.269 (1.347) Remain 40:13:21 loss: 7.8496 Lr: 2.64007e-04 Mem R(MA/MR): 25550 (21200/36094) [2025-04-28 10:12:32,507 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5761 loss_mask: 0.0505 loss_dice: 2.6890 loss_score: 0.0000 loss_bbox: 0.0612 loss_sp_cls: 1.1052 loss: 7.1718 [2025-04-28 10:12:33,994 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:13:58,649 INFO hook.py line 650 1619929] Train: [69/512][50/242] Data 0.015 (0.016) Batch 1.297 (1.397) Remain 41:41:08 loss: 7.3899 Lr: 2.63804e-04 Mem R(MA/MR): 23098 (21200/36094) [2025-04-28 10:15:06,755 INFO hook.py line 650 1619929] Train: [69/512][100/242] Data 0.017 (0.016) Batch 1.355 (1.379) Remain 41:07:31 loss: 7.7546 Lr: 2.63694e-04 Mem R(MA/MR): 23106 (21200/36094) [2025-04-28 10:16:15,313 INFO hook.py line 650 1619929] Train: [69/512][150/242] Data 0.016 (0.016) Batch 1.429 (1.376) Remain 41:01:29 loss: 6.3921 Lr: 2.63583e-04 Mem R(MA/MR): 25630 (21200/36094) [2025-04-28 10:17:25,387 INFO hook.py line 650 1619929] Train: [69/512][200/242] Data 0.014 (0.016) Batch 1.315 (1.383) Remain 41:11:43 loss: 6.7016 Lr: 2.63473e-04 Mem R(MA/MR): 25630 (21200/36094) [2025-04-28 10:18:20,714 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5764 loss_mask: 0.0499 loss_dice: 2.6821 loss_score: 0.0000 loss_bbox: 0.0614 loss_sp_cls: 1.1001 loss: 7.1534 [2025-04-28 10:18:20,790 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:19:54,220 INFO hook.py line 650 1619929] Train: [70/512][50/242] Data 0.015 (0.016) Batch 1.296 (1.447) Remain 43:03:55 loss: 6.3869 Lr: 2.63271e-04 Mem R(MA/MR): 24672 (21200/36094) [2025-04-28 10:21:01,790 INFO hook.py line 650 1619929] Train: [70/512][100/242] Data 0.016 (0.016) Batch 1.368 (1.398) Remain 41:34:53 loss: 8.0480 Lr: 2.63161e-04 Mem R(MA/MR): 26192 (21200/36094) [2025-04-28 10:22:09,870 INFO hook.py line 650 1619929] Train: [70/512][150/242] Data 0.016 (0.016) Batch 1.366 (1.385) Remain 41:11:53 loss: 8.1958 Lr: 2.63050e-04 Mem R(MA/MR): 27964 (21200/36094) [2025-04-28 10:23:17,764 INFO hook.py line 650 1619929] Train: [70/512][200/242] Data 0.016 (0.016) Batch 1.410 (1.378) Remain 40:58:17 loss: 7.6216 Lr: 2.62940e-04 Mem R(MA/MR): 30016 (21200/36094) [2025-04-28 10:24:12,464 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5679 loss_mask: 0.0493 loss_dice: 2.6356 loss_score: 0.0000 loss_bbox: 0.0603 loss_sp_cls: 1.1040 loss: 7.0594 [2025-04-28 10:24:14,376 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:25:40,518 INFO hook.py line 650 1619929] Train: [71/512][50/242] Data 0.016 (0.017) Batch 1.395 (1.475) Remain 43:47:53 loss: 6.0012 Lr: 2.62736e-04 Mem R(MA/MR): 20074 (21200/36094) [2025-04-28 10:26:50,336 INFO hook.py line 650 1619929] Train: [71/512][100/242] Data 0.017 (0.017) Batch 1.306 (1.434) Remain 42:34:40 loss: 6.2276 Lr: 2.62626e-04 Mem R(MA/MR): 20102 (21200/36094) [2025-04-28 10:27:56,513 INFO hook.py line 650 1619929] Train: [71/512][150/242] Data 0.015 (0.016) Batch 1.277 (1.397) Remain 41:26:22 loss: 7.4997 Lr: 2.62515e-04 Mem R(MA/MR): 20102 (21200/36094) [2025-04-28 10:29:03,690 INFO hook.py line 650 1619929] Train: [71/512][200/242] Data 0.015 (0.016) Batch 1.172 (1.383) Remain 41:01:14 loss: 6.8212 Lr: 2.62404e-04 Mem R(MA/MR): 22458 (21200/36094) [2025-04-28 10:29:58,735 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5712 loss_mask: 0.0498 loss_dice: 2.6565 loss_score: 0.0000 loss_bbox: 0.0617 loss_sp_cls: 1.0932 loss: 7.1087 [2025-04-28 10:29:59,660 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:31:25,329 INFO hook.py line 650 1619929] Train: [72/512][50/242] Data 0.016 (0.017) Batch 1.505 (1.398) Remain 41:25:18 loss: 7.1648 Lr: 2.62201e-04 Mem R(MA/MR): 21566 (21200/36094) [2025-04-28 10:32:36,226 INFO hook.py line 650 1619929] Train: [72/512][100/242] Data 0.016 (0.017) Batch 1.433 (1.408) Remain 41:42:30 loss: 7.0865 Lr: 2.62090e-04 Mem R(MA/MR): 21566 (21200/36094) [2025-04-28 10:33:45,069 INFO hook.py line 650 1619929] Train: [72/512][150/242] Data 0.016 (0.016) Batch 1.319 (1.398) Remain 41:22:21 loss: 7.3837 Lr: 2.61980e-04 Mem R(MA/MR): 21566 (21200/36094) [2025-04-28 10:34:52,335 INFO hook.py line 650 1619929] Train: [72/512][200/242] Data 0.015 (0.016) Batch 1.206 (1.384) Remain 40:57:39 loss: 6.6276 Lr: 2.61869e-04 Mem R(MA/MR): 23512 (21200/36094) [2025-04-28 10:35:48,616 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5661 loss_mask: 0.0491 loss_dice: 2.6467 loss_score: 0.0000 loss_bbox: 0.0616 loss_sp_cls: 1.0889 loss: 7.0824 [2025-04-28 10:35:50,231 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 10:35:52,837 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5490 Process Time: 0.417 Mem R(MA/MR): 4240 (21200/36094) [2025-04-28 10:35:54,324 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.8535 Process Time: 0.467 Mem R(MA/MR): 7126 (21200/36094) [2025-04-28 10:35:55,941 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2522 Process Time: 0.567 Mem R(MA/MR): 9674 (21200/36094) [2025-04-28 10:36:03,551 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.7619 Process Time: 1.205 Mem R(MA/MR): 19498 (21200/36094) [2025-04-28 10:36:04,422 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6068 Process Time: 0.323 Mem R(MA/MR): 7086 (21200/36094) [2025-04-28 10:36:05,673 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.2387 Process Time: 0.328 Mem R(MA/MR): 11320 (21200/36094) [2025-04-28 10:36:06,201 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0539 Process Time: 0.201 Mem R(MA/MR): 6582 (21200/36094) [2025-04-28 10:36:06,649 INFO hook.py line 449 1619929] Test: [8/50] Loss 7.1803 Process Time: 0.165 Mem R(MA/MR): 4268 (21200/36094) [2025-04-28 10:36:07,555 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.3793 Process Time: 0.343 Mem R(MA/MR): 11722 (21200/36094) [2025-04-28 10:36:08,992 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.2700 Process Time: 0.422 Mem R(MA/MR): 9414 (21200/36094) [2025-04-28 10:36:11,611 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0801 Process Time: 0.709 Mem R(MA/MR): 18786 (21200/36094) [2025-04-28 10:36:13,713 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.9959 Process Time: 0.310 Mem R(MA/MR): 15426 (21200/36094) [2025-04-28 10:36:14,932 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0181 Process Time: 0.335 Mem R(MA/MR): 8774 (21200/36094) [2025-04-28 10:36:15,353 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.6945 Process Time: 0.172 Mem R(MA/MR): 5212 (21200/36094) [2025-04-28 10:36:18,168 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.1283 Process Time: 0.308 Mem R(MA/MR): 16636 (21200/36094) [2025-04-28 10:36:20,042 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.5438 Process Time: 0.622 Mem R(MA/MR): 14734 (21200/36094) [2025-04-28 10:36:20,717 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.8456 Process Time: 0.175 Mem R(MA/MR): 6990 (21200/36094) [2025-04-28 10:36:21,574 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.3033 Process Time: 0.252 Mem R(MA/MR): 8476 (21200/36094) [2025-04-28 10:36:22,887 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.4254 Process Time: 0.276 Mem R(MA/MR): 6544 (21200/36094) [2025-04-28 10:36:24,294 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.8995 Process Time: 0.362 Mem R(MA/MR): 11728 (21200/36094) [2025-04-28 10:36:32,564 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.9772 Process Time: 0.773 Mem R(MA/MR): 23380 (21200/36094) [2025-04-28 10:36:33,354 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2799 Process Time: 0.231 Mem R(MA/MR): 7130 (21200/36094) [2025-04-28 10:36:42,468 INFO hook.py line 449 1619929] Test: [23/50] Loss 14.4755 Process Time: 0.360 Mem R(MA/MR): 8628 (21200/36094) [2025-04-28 10:36:43,106 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.3788 Process Time: 0.186 Mem R(MA/MR): 5626 (21200/36094) [2025-04-28 10:36:44,058 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.4226 Process Time: 0.221 Mem R(MA/MR): 9298 (21200/36094) [2025-04-28 10:36:50,282 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.9959 Process Time: 0.747 Mem R(MA/MR): 31346 (21200/36094) [2025-04-28 10:36:52,889 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.1434 Process Time: 0.768 Mem R(MA/MR): 10098 (21200/36094) [2025-04-28 10:36:54,074 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.1953 Process Time: 0.258 Mem R(MA/MR): 8862 (21200/36094) [2025-04-28 10:36:58,736 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.1848 Process Time: 0.266 Mem R(MA/MR): 17218 (21200/36094) [2025-04-28 10:37:00,164 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.9203 Process Time: 0.409 Mem R(MA/MR): 7862 (21200/36094) [2025-04-28 10:37:03,798 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.1791 Process Time: 0.424 Mem R(MA/MR): 20360 (21200/36094) [2025-04-28 10:37:04,091 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3386 Process Time: 0.118 Mem R(MA/MR): 4112 (21200/36094) [2025-04-28 10:37:07,713 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.3392 Process Time: 0.490 Mem R(MA/MR): 24538 (21200/36094) [2025-04-28 10:37:08,918 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.1053 Process Time: 0.398 Mem R(MA/MR): 10096 (21200/36094) [2025-04-28 10:37:10,822 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.7334 Process Time: 0.601 Mem R(MA/MR): 14400 (21200/36094) [2025-04-28 10:37:11,328 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0152 Process Time: 0.196 Mem R(MA/MR): 6856 (21200/36094) [2025-04-28 10:37:14,830 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9025 Process Time: 0.565 Mem R(MA/MR): 28492 (21200/36094) [2025-04-28 10:37:16,653 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.6379 Process Time: 0.498 Mem R(MA/MR): 10770 (21200/36094) [2025-04-28 10:37:17,140 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.6355 Process Time: 0.152 Mem R(MA/MR): 5680 (21200/36094) [2025-04-28 10:37:18,513 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.4886 Process Time: 0.407 Mem R(MA/MR): 10344 (21200/36094) [2025-04-28 10:37:19,679 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.0508 Process Time: 0.380 Mem R(MA/MR): 9114 (21200/36094) [2025-04-28 10:37:20,198 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.8689 Process Time: 0.141 Mem R(MA/MR): 5718 (21200/36094) [2025-04-28 10:37:20,827 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9190 Process Time: 0.244 Mem R(MA/MR): 5728 (21200/36094) [2025-04-28 10:37:21,661 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.6765 Process Time: 0.344 Mem R(MA/MR): 7294 (21200/36094) [2025-04-28 10:37:22,481 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0411 Process Time: 0.248 Mem R(MA/MR): 5488 (21200/36094) [2025-04-28 10:37:25,138 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.6291 Process Time: 0.663 Mem R(MA/MR): 14964 (21200/36094) [2025-04-28 10:37:31,671 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.4273 Process Time: 0.836 Mem R(MA/MR): 19842 (21200/36094) [2025-04-28 10:37:41,910 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.6777 Process Time: 1.992 Mem R(MA/MR): 35270 (21200/36094) [2025-04-28 10:37:42,515 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.8265 Process Time: 0.186 Mem R(MA/MR): 5752 (21200/36094) [2025-04-28 10:37:44,743 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.4077 Process Time: 0.344 Mem R(MA/MR): 13954 (21200/36094) [2025-04-28 10:37:48,739 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 10:37:48,740 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 10:37:48,740 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] table : 0.200 0.511 0.766 0.642 0.581 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] door : 0.389 0.687 0.866 0.944 0.646 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] ceiling lamp : 0.512 0.692 0.820 0.835 0.641 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] cabinet : 0.266 0.415 0.507 0.439 0.537 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] blinds : 0.460 0.812 0.831 0.818 0.783 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] curtain : 0.310 0.519 0.681 0.643 0.750 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] chair : 0.532 0.691 0.755 0.735 0.680 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] storage cabinet: 0.195 0.363 0.485 0.750 0.360 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] office chair : 0.495 0.525 0.547 0.708 0.708 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] bookshelf : 0.145 0.483 0.644 0.583 0.636 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] whiteboard : 0.489 0.611 0.724 0.952 0.571 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] window : 0.073 0.197 0.562 0.391 0.275 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] box : 0.109 0.249 0.399 0.430 0.359 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] monitor : 0.527 0.650 0.788 0.957 0.629 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] shelf : 0.032 0.108 0.237 0.500 0.167 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] heater : 0.350 0.687 0.832 0.833 0.789 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] kitchen cabinet: 0.144 0.341 0.634 0.500 0.440 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] sofa : 0.477 0.633 0.774 0.750 0.750 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] bed : 0.050 0.139 1.000 0.227 0.625 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] trash can : 0.450 0.557 0.685 0.760 0.585 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] book : 0.005 0.016 0.063 0.161 0.071 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] plant : 0.415 0.640 0.687 0.917 0.611 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] blanket : 0.456 0.548 0.615 0.583 0.636 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] tv : 0.666 0.765 0.765 0.833 0.833 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] computer tower : 0.166 0.312 0.501 0.722 0.310 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] refrigerator : 0.206 0.334 0.353 0.750 0.333 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] jacket : 0.123 0.282 0.408 0.455 0.455 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] sink : 0.250 0.454 0.889 0.778 0.636 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] bag : 0.166 0.217 0.227 0.667 0.222 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] picture : 0.085 0.146 0.256 0.382 0.333 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] pillow : 0.496 0.702 0.758 0.636 0.737 [2025-04-28 10:37:48,740 INFO hook.py line 395 1619929] towel : 0.144 0.261 0.512 0.522 0.316 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] suitcase : 0.383 0.445 0.445 0.750 0.429 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] backpack : 0.336 0.420 0.420 0.667 0.462 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] crate : 0.039 0.228 0.508 1.000 0.182 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] keyboard : 0.295 0.433 0.505 0.621 0.462 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] toilet : 0.544 0.676 1.000 0.778 0.778 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] printer : 0.249 0.343 0.343 0.571 0.444 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] microwave : 0.350 0.586 0.914 1.000 0.500 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] shoes : 0.078 0.142 0.400 0.423 0.268 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] socket : 0.142 0.391 0.602 0.747 0.400 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] bottle : 0.106 0.170 0.281 0.386 0.265 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] bucket : 0.190 0.308 0.332 0.286 0.571 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] cushion : 0.088 0.221 0.529 0.364 0.667 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] telephone : 0.199 0.440 0.479 1.000 0.412 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] laptop : 0.247 0.423 0.423 0.500 0.625 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] plant pot : 0.023 0.081 0.291 0.600 0.188 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] cup : 0.141 0.243 0.300 0.667 0.227 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] coat hanger : 0.160 0.354 0.396 0.500 0.500 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] light switch : 0.198 0.406 0.495 0.585 0.477 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] speaker : 0.270 0.358 0.427 0.800 0.364 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] kettle : 0.210 0.264 0.264 0.667 0.333 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] smoke detector : 0.637 0.750 0.790 1.000 0.750 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] power strip : 0.048 0.067 0.213 0.500 0.200 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] mouse : 0.395 0.620 0.739 0.778 0.656 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] cutting board : 0.057 0.129 0.500 0.333 0.500 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] toilet paper : 0.148 0.320 0.398 0.857 0.353 [2025-04-28 10:37:48,741 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] clock : 0.150 0.278 0.278 0.667 0.667 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] tap : 0.160 0.272 0.556 0.500 0.333 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] soap dispenser : 0.496 0.800 0.800 1.000 0.800 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.083 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] whiteboard eraser: 0.135 0.397 0.401 0.667 0.667 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] toilet brush : 0.185 0.385 0.640 0.571 0.667 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] headphones : 0.222 0.500 0.500 1.000 0.500 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 10:37:48,742 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 10:37:48,742 INFO hook.py line 404 1619929] average : 0.204 0.323 0.432 0.568 0.392 [2025-04-28 10:37:48,742 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 10:37:48,742 INFO hook.py line 480 1619929] Total Process Time: 21.406 s [2025-04-28 10:37:48,742 INFO hook.py line 481 1619929] Average Process Time: 428.349 ms [2025-04-28 10:37:48,742 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 10:37:48,785 INFO hook.py line 685 1619929] Currently Best AP50: 0.344 [2025-04-28 10:37:48,787 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:39:18,197 INFO hook.py line 650 1619929] Train: [73/512][50/242] Data 0.015 (0.032) Batch 1.337 (1.399) Remain 41:21:58 loss: 7.7508 Lr: 2.61666e-04 Mem R(MA/MR): 21510 (21200/36094) [2025-04-28 10:40:27,948 INFO hook.py line 650 1619929] Train: [73/512][100/242] Data 0.016 (0.024) Batch 1.559 (1.397) Remain 41:16:55 loss: 7.0339 Lr: 2.61555e-04 Mem R(MA/MR): 21510 (21200/36094) [2025-04-28 10:41:35,934 INFO hook.py line 650 1619929] Train: [73/512][150/242] Data 0.016 (0.021) Batch 1.200 (1.384) Remain 40:53:17 loss: 5.8255 Lr: 2.61444e-04 Mem R(MA/MR): 23518 (21200/36094) [2025-04-28 10:42:44,527 INFO hook.py line 650 1619929] Train: [73/512][200/242] Data 0.014 (0.020) Batch 1.210 (1.381) Remain 40:46:31 loss: 7.4752 Lr: 2.61334e-04 Mem R(MA/MR): 23518 (21200/36094) [2025-04-28 10:43:40,330 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5623 loss_mask: 0.0496 loss_dice: 2.6339 loss_score: 0.0000 loss_bbox: 0.0604 loss_sp_cls: 1.0878 loss: 7.0415 [2025-04-28 10:43:43,323 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:45:12,211 INFO hook.py line 650 1619929] Train: [74/512][50/242] Data 0.016 (0.016) Batch 1.433 (1.379) Remain 40:39:54 loss: 7.2020 Lr: 2.61130e-04 Mem R(MA/MR): 22060 (21200/36094) [2025-04-28 10:46:20,160 INFO hook.py line 650 1619929] Train: [74/512][100/242] Data 0.016 (0.016) Batch 1.331 (1.368) Remain 40:20:48 loss: 6.0505 Lr: 2.61020e-04 Mem R(MA/MR): 23924 (21200/36094) [2025-04-28 10:47:27,832 INFO hook.py line 650 1619929] Train: [74/512][150/242] Data 0.016 (0.016) Batch 1.459 (1.363) Remain 40:10:37 loss: 7.9585 Lr: 2.60909e-04 Mem R(MA/MR): 23924 (21200/36094) [2025-04-28 10:48:34,627 INFO hook.py line 650 1619929] Train: [74/512][200/242] Data 0.014 (0.016) Batch 1.296 (1.356) Remain 39:57:11 loss: 5.4450 Lr: 2.60798e-04 Mem R(MA/MR): 23924 (21200/36094) [2025-04-28 10:49:29,060 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5611 loss_mask: 0.0486 loss_dice: 2.6310 loss_score: 0.0000 loss_bbox: 0.0612 loss_sp_cls: 1.0818 loss: 7.0250 [2025-04-28 10:49:29,522 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:51:03,454 INFO hook.py line 650 1619929] Train: [75/512][50/242] Data 0.019 (0.019) Batch 1.360 (1.465) Remain 43:06:06 loss: 7.5897 Lr: 2.60595e-04 Mem R(MA/MR): 19492 (21200/36094) [2025-04-28 10:52:20,727 INFO hook.py line 650 1619929] Train: [75/512][100/242] Data 0.018 (0.020) Batch 1.415 (1.506) Remain 44:18:31 loss: 6.7534 Lr: 2.60484e-04 Mem R(MA/MR): 21308 (21200/36094) [2025-04-28 10:53:35,341 INFO hook.py line 650 1619929] Train: [75/512][150/242] Data 0.023 (0.020) Batch 1.491 (1.502) Remain 44:08:48 loss: 6.3024 Lr: 2.60373e-04 Mem R(MA/MR): 23136 (21200/36094) [2025-04-28 10:54:51,227 INFO hook.py line 650 1619929] Train: [75/512][200/242] Data 0.036 (0.020) Batch 1.552 (1.506) Remain 44:14:50 loss: 5.5932 Lr: 2.60263e-04 Mem R(MA/MR): 23136 (21200/36094) [2025-04-28 10:55:51,454 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5599 loss_mask: 0.0484 loss_dice: 2.6348 loss_score: 0.0000 loss_bbox: 0.0605 loss_sp_cls: 1.0680 loss: 7.0183 [2025-04-28 10:55:51,546 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 10:57:30,432 INFO hook.py line 650 1619929] Train: [76/512][50/242] Data 0.022 (0.021) Batch 1.635 (1.569) Remain 46:04:43 loss: 7.8828 Lr: 2.60059e-04 Mem R(MA/MR): 25626 (21200/36094) [2025-04-28 10:58:48,992 INFO hook.py line 650 1619929] Train: [76/512][100/242] Data 0.023 (0.022) Batch 1.554 (1.570) Remain 46:05:09 loss: 7.6305 Lr: 2.59948e-04 Mem R(MA/MR): 27368 (21200/36094) [2025-04-28 11:00:04,079 INFO hook.py line 650 1619929] Train: [76/512][150/242] Data 0.019 (0.021) Batch 1.580 (1.547) Remain 45:22:47 loss: 8.5631 Lr: 2.59837e-04 Mem R(MA/MR): 29206 (21200/36094) [2025-04-28 11:01:13,893 INFO hook.py line 650 1619929] Train: [76/512][200/242] Data 0.016 (0.020) Batch 1.596 (1.509) Remain 44:14:14 loss: 7.8299 Lr: 2.59727e-04 Mem R(MA/MR): 29210 (21200/36094) [2025-04-28 11:02:08,926 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5548 loss_mask: 0.0490 loss_dice: 2.6300 loss_score: 0.0000 loss_bbox: 0.0608 loss_sp_cls: 1.0773 loss: 7.0044 [2025-04-28 11:02:09,763 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:03:39,808 INFO hook.py line 650 1619929] Train: [77/512][50/242] Data 0.015 (0.016) Batch 1.297 (1.359) Remain 39:48:35 loss: 7.7011 Lr: 2.59523e-04 Mem R(MA/MR): 24016 (21200/36094) [2025-04-28 11:04:48,716 INFO hook.py line 650 1619929] Train: [77/512][100/242] Data 0.016 (0.017) Batch 1.334 (1.369) Remain 40:04:48 loss: 6.8760 Lr: 2.59412e-04 Mem R(MA/MR): 28384 (21200/36094) [2025-04-28 11:05:57,072 INFO hook.py line 650 1619929] Train: [77/512][150/242] Data 0.016 (0.017) Batch 1.488 (1.368) Remain 40:02:40 loss: 7.6676 Lr: 2.59302e-04 Mem R(MA/MR): 28384 (21200/36094) [2025-04-28 11:07:06,027 INFO hook.py line 650 1619929] Train: [77/512][200/242] Data 0.014 (0.016) Batch 1.400 (1.371) Remain 40:06:23 loss: 8.0712 Lr: 2.59191e-04 Mem R(MA/MR): 28384 (21200/36094) [2025-04-28 11:08:00,441 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5512 loss_mask: 0.0485 loss_dice: 2.6154 loss_score: 0.0000 loss_bbox: 0.0610 loss_sp_cls: 1.0761 loss: 6.9720 [2025-04-28 11:08:04,954 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:09:30,413 INFO hook.py line 650 1619929] Train: [78/512][50/242] Data 0.017 (0.018) Batch 1.200 (1.469) Remain 42:56:31 loss: 6.1606 Lr: 2.58987e-04 Mem R(MA/MR): 22814 (21200/36094) [2025-04-28 11:10:38,087 INFO hook.py line 650 1619929] Train: [78/512][100/242] Data 0.015 (0.017) Batch 1.429 (1.410) Remain 41:10:42 loss: 6.9342 Lr: 2.58876e-04 Mem R(MA/MR): 24832 (21200/36094) [2025-04-28 11:11:48,114 INFO hook.py line 650 1619929] Train: [78/512][150/242] Data 0.016 (0.016) Batch 1.381 (1.406) Remain 41:04:09 loss: 6.3489 Lr: 2.58766e-04 Mem R(MA/MR): 24848 (21200/36094) [2025-04-28 11:12:57,351 INFO hook.py line 650 1619929] Train: [78/512][200/242] Data 0.015 (0.016) Batch 1.396 (1.401) Remain 40:53:19 loss: 5.9938 Lr: 2.58655e-04 Mem R(MA/MR): 24864 (21200/36094) [2025-04-28 11:13:54,180 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5340 loss_mask: 0.0462 loss_dice: 2.5524 loss_score: 0.0000 loss_bbox: 0.0596 loss_sp_cls: 1.0492 loss: 6.8016 [2025-04-28 11:13:54,267 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:15:23,153 INFO hook.py line 650 1619929] Train: [79/512][50/242] Data 0.027 (0.017) Batch 1.320 (1.372) Remain 40:01:21 loss: 6.0120 Lr: 2.58451e-04 Mem R(MA/MR): 20452 (21200/36094) [2025-04-28 11:16:30,795 INFO hook.py line 650 1619929] Train: [79/512][100/242] Data 0.016 (0.016) Batch 1.450 (1.362) Remain 39:42:30 loss: 6.9860 Lr: 2.58340e-04 Mem R(MA/MR): 20894 (21200/36094) [2025-04-28 11:17:40,891 INFO hook.py line 650 1619929] Train: [79/512][150/242] Data 0.015 (0.016) Batch 1.358 (1.376) Remain 40:04:53 loss: 5.7651 Lr: 2.58229e-04 Mem R(MA/MR): 20894 (21200/36094) [2025-04-28 11:18:49,483 INFO hook.py line 650 1619929] Train: [79/512][200/242] Data 0.016 (0.016) Batch 1.326 (1.375) Remain 40:01:59 loss: 7.3455 Lr: 2.58119e-04 Mem R(MA/MR): 20896 (21200/36094) [2025-04-28 11:19:44,691 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5127 loss_mask: 0.0447 loss_dice: 2.4947 loss_score: 0.0000 loss_bbox: 0.0580 loss_sp_cls: 1.0248 loss: 6.6365 [2025-04-28 11:19:47,318 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:21:12,140 INFO hook.py line 650 1619929] Train: [80/512][50/242] Data 0.017 (0.017) Batch 1.457 (1.419) Remain 41:17:47 loss: 7.0166 Lr: 2.57917e-04 Mem R(MA/MR): 20092 (21200/36094) [2025-04-28 11:22:20,405 INFO hook.py line 650 1619929] Train: [80/512][100/242] Data 0.016 (0.016) Batch 1.406 (1.392) Remain 40:27:53 loss: 8.0023 Lr: 2.57806e-04 Mem R(MA/MR): 24298 (21200/36094) [2025-04-28 11:23:27,514 INFO hook.py line 650 1619929] Train: [80/512][150/242] Data 0.015 (0.016) Batch 1.318 (1.375) Remain 39:57:27 loss: 6.5067 Lr: 2.57695e-04 Mem R(MA/MR): 24298 (21200/36094) [2025-04-28 11:24:38,465 INFO hook.py line 650 1619929] Train: [80/512][200/242] Data 0.014 (0.016) Batch 1.324 (1.386) Remain 40:15:54 loss: 6.8404 Lr: 2.57585e-04 Mem R(MA/MR): 24310 (21200/36094) [2025-04-28 11:25:33,314 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5529 loss_mask: 0.0482 loss_dice: 2.5997 loss_score: 0.0000 loss_bbox: 0.0599 loss_sp_cls: 1.0628 loss: 6.9417 [2025-04-28 11:25:37,216 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 11:25:39,657 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1426 Process Time: 0.385 Mem R(MA/MR): 4496 (21200/36094) [2025-04-28 11:25:41,651 INFO hook.py line 449 1619929] Test: [2/50] Loss 7.1500 Process Time: 0.798 Mem R(MA/MR): 7306 (21200/36094) [2025-04-28 11:25:43,915 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.7620 Process Time: 1.079 Mem R(MA/MR): 9820 (21200/36094) [2025-04-28 11:25:51,711 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.6098 Process Time: 0.885 Mem R(MA/MR): 19834 (21200/36094) [2025-04-28 11:25:52,912 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.7123 Process Time: 0.527 Mem R(MA/MR): 7216 (21200/36094) [2025-04-28 11:25:54,475 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.2553 Process Time: 0.610 Mem R(MA/MR): 11394 (21200/36094) [2025-04-28 11:25:55,250 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.9476 Process Time: 0.341 Mem R(MA/MR): 6442 (21200/36094) [2025-04-28 11:25:55,845 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.2224 Process Time: 0.248 Mem R(MA/MR): 4548 (21200/36094) [2025-04-28 11:25:56,698 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8650 Process Time: 0.231 Mem R(MA/MR): 11564 (21200/36094) [2025-04-28 11:25:58,149 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.1532 Process Time: 0.260 Mem R(MA/MR): 9660 (21200/36094) [2025-04-28 11:26:00,831 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2086 Process Time: 0.496 Mem R(MA/MR): 18848 (21200/36094) [2025-04-28 11:26:03,311 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2543 Process Time: 0.419 Mem R(MA/MR): 15302 (21200/36094) [2025-04-28 11:26:04,323 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.8811 Process Time: 0.243 Mem R(MA/MR): 8786 (21200/36094) [2025-04-28 11:26:04,813 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.9729 Process Time: 0.193 Mem R(MA/MR): 4870 (21200/36094) [2025-04-28 11:26:07,601 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.6916 Process Time: 0.509 Mem R(MA/MR): 16624 (21200/36094) [2025-04-28 11:26:10,144 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.0168 Process Time: 0.905 Mem R(MA/MR): 14792 (21200/36094) [2025-04-28 11:26:11,117 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7626 Process Time: 0.322 Mem R(MA/MR): 6874 (21200/36094) [2025-04-28 11:26:12,202 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.5936 Process Time: 0.314 Mem R(MA/MR): 8306 (21200/36094) [2025-04-28 11:26:13,612 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0462 Process Time: 0.163 Mem R(MA/MR): 6430 (21200/36094) [2025-04-28 11:26:15,056 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.1173 Process Time: 0.204 Mem R(MA/MR): 11516 (21200/36094) [2025-04-28 11:26:23,521 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.8000 Process Time: 0.742 Mem R(MA/MR): 23288 (21200/36094) [2025-04-28 11:26:24,149 INFO hook.py line 449 1619929] Test: [22/50] Loss 4.9694 Process Time: 0.210 Mem R(MA/MR): 7026 (21200/36094) [2025-04-28 11:26:33,086 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.3867 Process Time: 0.344 Mem R(MA/MR): 10176 (21200/36094) [2025-04-28 11:26:33,868 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8746 Process Time: 0.200 Mem R(MA/MR): 5552 (21200/36094) [2025-04-28 11:26:35,246 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1849 Process Time: 0.444 Mem R(MA/MR): 9498 (21200/36094) [2025-04-28 11:26:42,232 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.0729 Process Time: 1.617 Mem R(MA/MR): 31322 (21200/36094) [2025-04-28 11:26:45,392 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.0789 Process Time: 0.756 Mem R(MA/MR): 10432 (21200/36094) [2025-04-28 11:26:46,511 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.1120 Process Time: 0.297 Mem R(MA/MR): 8938 (21200/36094) [2025-04-28 11:26:51,583 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.4004 Process Time: 0.642 Mem R(MA/MR): 17174 (21200/36094) [2025-04-28 11:26:52,957 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.4064 Process Time: 0.496 Mem R(MA/MR): 7914 (21200/36094) [2025-04-28 11:26:57,734 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0634 Process Time: 0.827 Mem R(MA/MR): 20842 (21200/36094) [2025-04-28 11:26:58,283 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.6563 Process Time: 0.260 Mem R(MA/MR): 4174 (21200/36094) [2025-04-28 11:27:02,491 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.4501 Process Time: 0.859 Mem R(MA/MR): 24982 (21200/36094) [2025-04-28 11:27:03,879 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.2042 Process Time: 0.450 Mem R(MA/MR): 10080 (21200/36094) [2025-04-28 11:27:05,321 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.5563 Process Time: 0.232 Mem R(MA/MR): 14030 (21200/36094) [2025-04-28 11:27:05,865 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0875 Process Time: 0.194 Mem R(MA/MR): 6796 (21200/36094) [2025-04-28 11:27:09,304 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.7391 Process Time: 0.385 Mem R(MA/MR): 28426 (21200/36094) [2025-04-28 11:27:11,085 INFO hook.py line 449 1619929] Test: [38/50] Loss 7.0996 Process Time: 0.455 Mem R(MA/MR): 10828 (21200/36094) [2025-04-28 11:27:11,757 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9140 Process Time: 0.228 Mem R(MA/MR): 5672 (21200/36094) [2025-04-28 11:27:12,914 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9234 Process Time: 0.320 Mem R(MA/MR): 10456 (21200/36094) [2025-04-28 11:27:13,811 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.8100 Process Time: 0.189 Mem R(MA/MR): 9272 (21200/36094) [2025-04-28 11:27:14,287 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.6147 Process Time: 0.145 Mem R(MA/MR): 5674 (21200/36094) [2025-04-28 11:27:14,788 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.2284 Process Time: 0.167 Mem R(MA/MR): 5750 (21200/36094) [2025-04-28 11:27:15,397 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.0656 Process Time: 0.172 Mem R(MA/MR): 7216 (21200/36094) [2025-04-28 11:27:15,908 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7845 Process Time: 0.123 Mem R(MA/MR): 5440 (21200/36094) [2025-04-28 11:27:19,106 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.4507 Process Time: 0.813 Mem R(MA/MR): 14942 (21200/36094) [2025-04-28 11:27:26,848 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.3587 Process Time: 1.146 Mem R(MA/MR): 20388 (21200/36094) [2025-04-28 11:27:37,195 INFO hook.py line 449 1619929] Test: [48/50] Loss 10.7023 Process Time: 1.233 Mem R(MA/MR): 35706 (21200/36094) [2025-04-28 11:27:38,012 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.3467 Process Time: 0.221 Mem R(MA/MR): 5896 (21200/36094) [2025-04-28 11:27:40,126 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0126 Process Time: 0.241 Mem R(MA/MR): 13782 (21200/36094) [2025-04-28 11:27:45,081 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 11:27:45,082 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 11:27:45,082 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] table : 0.192 0.523 0.796 0.752 0.559 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] door : 0.429 0.734 0.886 0.769 0.759 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] ceiling lamp : 0.491 0.703 0.801 0.900 0.646 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] cabinet : 0.264 0.409 0.518 0.544 0.463 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] blinds : 0.388 0.722 0.804 0.833 0.652 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] curtain : 0.344 0.618 0.749 0.579 0.917 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] chair : 0.524 0.711 0.772 0.799 0.668 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] storage cabinet: 0.172 0.391 0.525 0.483 0.560 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] office chair : 0.583 0.613 0.613 0.709 0.812 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] bookshelf : 0.277 0.612 0.672 0.600 0.818 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] whiteboard : 0.520 0.736 0.775 0.821 0.657 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] window : 0.078 0.218 0.635 0.362 0.374 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] box : 0.116 0.269 0.460 0.387 0.409 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] monitor : 0.541 0.741 0.824 0.914 0.757 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] shelf : 0.067 0.177 0.318 0.344 0.367 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] heater : 0.377 0.720 0.844 0.848 0.737 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] kitchen cabinet: 0.093 0.276 0.644 0.667 0.320 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] sofa : 0.387 0.564 0.727 0.588 0.833 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] bed : 0.106 0.370 0.529 0.444 0.500 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] trash can : 0.488 0.655 0.749 0.818 0.692 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] book : 0.010 0.028 0.058 0.212 0.090 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] plant : 0.390 0.588 0.678 0.909 0.556 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] blanket : 0.389 0.458 0.610 1.000 0.364 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] tv : 0.798 0.955 0.955 1.000 0.833 [2025-04-28 11:27:45,082 INFO hook.py line 395 1619929] computer tower : 0.229 0.396 0.609 0.630 0.405 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] refrigerator : 0.209 0.478 0.486 0.800 0.444 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] jacket : 0.047 0.156 0.323 0.375 0.545 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] sink : 0.326 0.575 0.842 0.824 0.636 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] bag : 0.189 0.233 0.272 0.421 0.296 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] picture : 0.099 0.210 0.355 0.483 0.359 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] pillow : 0.516 0.726 0.794 0.923 0.632 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] towel : 0.127 0.257 0.440 0.469 0.395 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] suitcase : 0.131 0.220 0.220 0.750 0.429 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] backpack : 0.311 0.378 0.410 0.625 0.385 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] crate : 0.103 0.300 0.394 1.000 0.273 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] keyboard : 0.350 0.464 0.628 0.731 0.487 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] toilet : 0.647 0.889 1.000 1.000 0.889 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] printer : 0.183 0.208 0.218 0.667 0.222 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.111 0.000 0.000 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] microwave : 0.362 0.629 0.985 0.750 0.750 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] shoes : 0.147 0.262 0.388 0.706 0.293 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] socket : 0.129 0.311 0.528 0.630 0.364 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] bottle : 0.053 0.126 0.307 0.333 0.217 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] bucket : 0.084 0.084 0.140 0.250 0.286 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] cushion : 0.059 0.087 0.167 0.231 0.500 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] shoe rack : 0.111 0.500 0.500 1.000 0.500 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] telephone : 0.260 0.488 0.562 0.750 0.529 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] laptop : 0.288 0.474 0.474 0.500 0.750 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] plant pot : 0.050 0.223 0.283 0.412 0.438 [2025-04-28 11:27:45,083 INFO hook.py line 395 1619929] exhaust fan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] cup : 0.182 0.288 0.380 0.650 0.295 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] coat hanger : 0.167 0.250 0.250 1.000 0.250 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] light switch : 0.205 0.412 0.563 0.744 0.446 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] speaker : 0.242 0.343 0.393 1.000 0.273 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] table lamp : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] smoke detector : 0.552 0.658 0.693 1.000 0.625 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] power strip : 0.104 0.182 0.225 0.667 0.200 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] mouse : 0.390 0.562 0.672 0.714 0.625 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] cutting board : 0.243 0.396 0.396 0.667 0.500 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] toilet paper : 0.151 0.328 0.393 1.000 0.294 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] clock : 0.522 1.000 1.000 1.000 1.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] tap : 0.094 0.257 0.667 0.800 0.444 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] soap dispenser : 0.546 0.697 0.800 0.800 0.800 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] bowl : 0.034 0.042 0.333 0.250 0.333 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] whiteboard eraser: 0.245 0.603 0.603 0.714 0.833 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] toilet brush : 0.494 0.615 0.808 0.800 0.667 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] spray bottle : 0.030 0.042 0.042 0.333 0.250 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] headphones : 0.222 0.500 0.500 1.000 0.500 [2025-04-28 11:27:45,084 INFO hook.py line 395 1619929] stapler : 0.111 0.333 0.431 1.000 0.333 [2025-04-28 11:27:45,085 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 11:27:45,085 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 11:27:45,085 INFO hook.py line 404 1619929] average : 0.220 0.361 0.455 0.618 0.423 [2025-04-28 11:27:45,085 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 11:27:45,085 INFO hook.py line 480 1619929] Total Process Time: 23.539 s [2025-04-28 11:27:45,085 INFO hook.py line 481 1619929] Average Process Time: 472.544 ms [2025-04-28 11:27:45,085 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 11:27:45,123 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.361 [2025-04-28 11:27:45,125 INFO hook.py line 685 1619929] Currently Best AP50: 0.361 [2025-04-28 11:27:45,128 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:29:10,274 INFO hook.py line 650 1619929] Train: [81/512][50/242] Data 0.016 (0.017) Batch 1.325 (1.388) Remain 40:17:23 loss: 6.6954 Lr: 2.57381e-04 Mem R(MA/MR): 20950 (21200/36094) [2025-04-28 11:30:20,025 INFO hook.py line 650 1619929] Train: [81/512][100/242] Data 0.016 (0.016) Batch 1.432 (1.392) Remain 40:22:29 loss: 6.2734 Lr: 2.57270e-04 Mem R(MA/MR): 22576 (21200/36094) [2025-04-28 11:31:29,546 INFO hook.py line 650 1619929] Train: [81/512][150/242] Data 0.015 (0.022) Batch 1.372 (1.391) Remain 40:20:35 loss: 6.7489 Lr: 2.57159e-04 Mem R(MA/MR): 24348 (21200/36094) [2025-04-28 11:32:38,210 INFO hook.py line 650 1619929] Train: [81/512][200/242] Data 0.014 (0.020) Batch 1.255 (1.387) Remain 40:11:31 loss: 7.1541 Lr: 2.57048e-04 Mem R(MA/MR): 24352 (21200/36094) [2025-04-28 11:33:33,644 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5529 loss_mask: 0.0499 loss_dice: 2.6210 loss_score: 0.0000 loss_bbox: 0.0601 loss_sp_cls: 1.0726 loss: 6.9741 [2025-04-28 11:33:37,651 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:35:09,206 INFO hook.py line 650 1619929] Train: [82/512][50/242] Data 0.016 (0.016) Batch 1.353 (1.383) Remain 40:03:39 loss: 5.2342 Lr: 2.56844e-04 Mem R(MA/MR): 21522 (21200/36094) [2025-04-28 11:36:17,905 INFO hook.py line 650 1619929] Train: [82/512][100/242] Data 0.016 (0.016) Batch 1.349 (1.379) Remain 39:54:02 loss: 6.6083 Lr: 2.56733e-04 Mem R(MA/MR): 21536 (21200/36094) [2025-04-28 11:37:26,968 INFO hook.py line 650 1619929] Train: [82/512][150/242] Data 0.016 (0.016) Batch 1.414 (1.379) Remain 39:54:31 loss: 7.3080 Lr: 2.56622e-04 Mem R(MA/MR): 21536 (21200/36094) [2025-04-28 11:38:35,403 INFO hook.py line 650 1619929] Train: [82/512][200/242] Data 0.014 (0.016) Batch 1.365 (1.377) Remain 39:48:40 loss: 7.1472 Lr: 2.56512e-04 Mem R(MA/MR): 21536 (21200/36094) [2025-04-28 11:39:30,867 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5476 loss_mask: 0.0483 loss_dice: 2.5829 loss_score: 0.0000 loss_bbox: 0.0604 loss_sp_cls: 1.0763 loss: 6.9067 [2025-04-28 11:39:34,203 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:41:07,505 INFO hook.py line 650 1619929] Train: [83/512][50/242] Data 0.017 (0.017) Batch 1.404 (1.451) Remain 41:55:23 loss: 8.1934 Lr: 2.56308e-04 Mem R(MA/MR): 22198 (21200/36094) [2025-04-28 11:42:16,595 INFO hook.py line 650 1619929] Train: [83/512][100/242] Data 0.016 (0.017) Batch 1.557 (1.415) Remain 40:52:20 loss: 6.6766 Lr: 2.56197e-04 Mem R(MA/MR): 23706 (21200/36094) [2025-04-28 11:43:28,329 INFO hook.py line 650 1619929] Train: [83/512][150/242] Data 0.016 (0.017) Batch 1.409 (1.422) Remain 41:02:32 loss: 7.1573 Lr: 2.56086e-04 Mem R(MA/MR): 23706 (21200/36094) [2025-04-28 11:44:37,711 INFO hook.py line 650 1619929] Train: [83/512][200/242] Data 0.015 (0.017) Batch 1.379 (1.413) Remain 40:46:18 loss: 6.8762 Lr: 2.55975e-04 Mem R(MA/MR): 28532 (21200/36094) [2025-04-28 11:45:34,003 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5473 loss_mask: 0.0487 loss_dice: 2.5811 loss_score: 0.0000 loss_bbox: 0.0605 loss_sp_cls: 1.0628 loss: 6.9015 [2025-04-28 11:45:37,296 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:47:07,375 INFO hook.py line 650 1619929] Train: [84/512][50/242] Data 0.016 (0.017) Batch 1.196 (1.419) Remain 40:53:51 loss: 6.6580 Lr: 2.55771e-04 Mem R(MA/MR): 21366 (21200/36094) [2025-04-28 11:48:16,264 INFO hook.py line 650 1619929] Train: [84/512][100/242] Data 0.016 (0.016) Batch 1.328 (1.398) Remain 40:16:03 loss: 6.5194 Lr: 2.55660e-04 Mem R(MA/MR): 21370 (21200/36094) [2025-04-28 11:49:25,014 INFO hook.py line 650 1619929] Train: [84/512][150/242] Data 0.016 (0.016) Batch 1.291 (1.390) Remain 40:01:34 loss: 7.7370 Lr: 2.55549e-04 Mem R(MA/MR): 21370 (21200/36094) [2025-04-28 11:50:33,989 INFO hook.py line 650 1619929] Train: [84/512][200/242] Data 0.017 (0.016) Batch 1.407 (1.387) Remain 39:55:50 loss: 9.1817 Lr: 2.55438e-04 Mem R(MA/MR): 21370 (21200/36094) [2025-04-28 11:51:29,653 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5477 loss_mask: 0.0483 loss_dice: 2.5947 loss_score: 0.0000 loss_bbox: 0.0601 loss_sp_cls: 1.0650 loss: 6.9190 [2025-04-28 11:51:32,803 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:53:04,941 INFO hook.py line 650 1619929] Train: [85/512][50/242] Data 0.016 (0.017) Batch 1.204 (1.416) Remain 40:42:42 loss: 7.4264 Lr: 2.55234e-04 Mem R(MA/MR): 19702 (21200/36094) [2025-04-28 11:54:16,307 INFO hook.py line 650 1619929] Train: [85/512][100/242] Data 0.017 (0.017) Batch 1.399 (1.422) Remain 40:51:51 loss: 6.6325 Lr: 2.55123e-04 Mem R(MA/MR): 23138 (21200/36094) [2025-04-28 11:55:25,338 INFO hook.py line 650 1619929] Train: [85/512][150/242] Data 0.018 (0.017) Batch 1.595 (1.408) Remain 40:26:34 loss: 7.1770 Lr: 2.55012e-04 Mem R(MA/MR): 25266 (21200/36094) [2025-04-28 11:56:33,318 INFO hook.py line 650 1619929] Train: [85/512][200/242] Data 0.015 (0.017) Batch 1.368 (1.396) Remain 40:04:21 loss: 6.0182 Lr: 2.54901e-04 Mem R(MA/MR): 25266 (21200/36094) [2025-04-28 11:57:27,678 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5391 loss_mask: 0.0478 loss_dice: 2.5778 loss_score: 0.0000 loss_bbox: 0.0603 loss_sp_cls: 1.0542 loss: 6.8596 [2025-04-28 11:57:28,887 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 11:58:59,535 INFO hook.py line 650 1619929] Train: [86/512][50/242] Data 0.016 (0.016) Batch 1.353 (1.398) Remain 40:07:04 loss: 7.4032 Lr: 2.54697e-04 Mem R(MA/MR): 20568 (21200/36094) [2025-04-28 12:00:06,708 INFO hook.py line 650 1619929] Train: [86/512][100/242] Data 0.016 (0.016) Batch 1.366 (1.370) Remain 39:17:15 loss: 7.0918 Lr: 2.54586e-04 Mem R(MA/MR): 20568 (21200/36094) [2025-04-28 12:01:14,382 INFO hook.py line 650 1619929] Train: [86/512][150/242] Data 0.015 (0.016) Batch 1.459 (1.364) Remain 39:06:25 loss: 6.9260 Lr: 2.54475e-04 Mem R(MA/MR): 20568 (21200/36094) [2025-04-28 12:02:23,800 INFO hook.py line 650 1619929] Train: [86/512][200/242] Data 0.015 (0.016) Batch 1.375 (1.370) Remain 39:15:44 loss: 7.5094 Lr: 2.54364e-04 Mem R(MA/MR): 23136 (21200/36094) [2025-04-28 12:03:17,436 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5395 loss_mask: 0.0472 loss_dice: 2.5581 loss_score: 0.0000 loss_bbox: 0.0600 loss_sp_cls: 1.0493 loss: 6.8273 [2025-04-28 12:03:22,390 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:04:49,680 INFO hook.py line 650 1619929] Train: [87/512][50/242] Data 0.015 (0.017) Batch 1.450 (1.450) Remain 41:29:19 loss: 4.6524 Lr: 2.54160e-04 Mem R(MA/MR): 20000 (21200/36094) [2025-04-28 12:05:57,669 INFO hook.py line 650 1619929] Train: [87/512][100/242] Data 0.016 (0.016) Batch 1.375 (1.403) Remain 40:08:43 loss: 6.5163 Lr: 2.54049e-04 Mem R(MA/MR): 20016 (21200/36094) [2025-04-28 12:07:04,930 INFO hook.py line 650 1619929] Train: [87/512][150/242] Data 0.016 (0.017) Batch 1.340 (1.384) Remain 39:33:41 loss: 6.1022 Lr: 2.53938e-04 Mem R(MA/MR): 20016 (21200/36094) [2025-04-28 12:08:13,615 INFO hook.py line 650 1619929] Train: [87/512][200/242] Data 0.014 (0.016) Batch 1.314 (1.381) Remain 39:28:16 loss: 7.6297 Lr: 2.53827e-04 Mem R(MA/MR): 20016 (21200/36094) [2025-04-28 12:09:07,496 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5345 loss_mask: 0.0475 loss_dice: 2.5608 loss_score: 0.0000 loss_bbox: 0.0589 loss_sp_cls: 1.0512 loss: 6.8142 [2025-04-28 12:09:09,589 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:10:43,011 INFO hook.py line 650 1619929] Train: [88/512][50/242] Data 0.017 (0.017) Batch 1.663 (1.442) Remain 41:09:54 loss: 7.2341 Lr: 2.53623e-04 Mem R(MA/MR): 24018 (21200/36094) [2025-04-28 12:11:52,144 INFO hook.py line 650 1619929] Train: [88/512][100/242] Data 0.017 (0.016) Batch 1.336 (1.411) Remain 40:16:41 loss: 8.8523 Lr: 2.53512e-04 Mem R(MA/MR): 24020 (21200/36094) [2025-04-28 12:13:00,858 INFO hook.py line 650 1619929] Train: [88/512][150/242] Data 0.022 (0.017) Batch 1.457 (1.399) Remain 39:54:01 loss: 6.9283 Lr: 2.53401e-04 Mem R(MA/MR): 24020 (21200/36094) [2025-04-28 12:14:10,002 INFO hook.py line 650 1619929] Train: [88/512][200/242] Data 0.015 (0.017) Batch 1.273 (1.395) Remain 39:45:59 loss: 5.4023 Lr: 2.53290e-04 Mem R(MA/MR): 26242 (21200/36094) [2025-04-28 12:15:04,616 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5104 loss_mask: 0.0466 loss_dice: 2.4929 loss_score: 0.0000 loss_bbox: 0.0587 loss_sp_cls: 1.0205 loss: 6.6282 [2025-04-28 12:15:04,959 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 12:15:07,394 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.3248 Process Time: 0.332 Mem R(MA/MR): 4508 (21200/36094) [2025-04-28 12:15:08,941 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.4968 Process Time: 0.533 Mem R(MA/MR): 7212 (21200/36094) [2025-04-28 12:15:11,025 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4618 Process Time: 0.822 Mem R(MA/MR): 9988 (21200/36094) [2025-04-28 12:15:18,508 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.5376 Process Time: 1.397 Mem R(MA/MR): 19902 (21200/36094) [2025-04-28 12:15:19,930 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.9581 Process Time: 0.579 Mem R(MA/MR): 7278 (21200/36094) [2025-04-28 12:15:21,271 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8762 Process Time: 0.438 Mem R(MA/MR): 11220 (21200/36094) [2025-04-28 12:15:21,826 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.4074 Process Time: 0.147 Mem R(MA/MR): 6312 (21200/36094) [2025-04-28 12:15:22,270 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.0922 Process Time: 0.123 Mem R(MA/MR): 4546 (21200/36094) [2025-04-28 12:15:23,220 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0494 Process Time: 0.204 Mem R(MA/MR): 11504 (21200/36094) [2025-04-28 12:15:24,997 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8932 Process Time: 0.393 Mem R(MA/MR): 9848 (21200/36094) [2025-04-28 12:15:27,774 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.9318 Process Time: 0.529 Mem R(MA/MR): 18694 (21200/36094) [2025-04-28 12:15:30,611 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0046 Process Time: 0.534 Mem R(MA/MR): 15472 (21200/36094) [2025-04-28 12:15:31,717 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2643 Process Time: 0.224 Mem R(MA/MR): 8960 (21200/36094) [2025-04-28 12:15:32,175 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.8851 Process Time: 0.177 Mem R(MA/MR): 5150 (21200/36094) [2025-04-28 12:15:35,038 INFO hook.py line 449 1619929] Test: [15/50] Loss 9.8780 Process Time: 0.329 Mem R(MA/MR): 16498 (21200/36094) [2025-04-28 12:15:37,530 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.7468 Process Time: 0.831 Mem R(MA/MR): 14794 (21200/36094) [2025-04-28 12:15:38,308 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.1834 Process Time: 0.283 Mem R(MA/MR): 6850 (21200/36094) [2025-04-28 12:15:39,366 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.8375 Process Time: 0.351 Mem R(MA/MR): 8630 (21200/36094) [2025-04-28 12:15:40,931 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.2579 Process Time: 0.172 Mem R(MA/MR): 6234 (21200/36094) [2025-04-28 12:15:42,455 INFO hook.py line 449 1619929] Test: [20/50] Loss 7.8831 Process Time: 0.205 Mem R(MA/MR): 11420 (21200/36094) [2025-04-28 12:15:50,628 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.1497 Process Time: 0.836 Mem R(MA/MR): 23724 (21200/36094) [2025-04-28 12:15:51,185 INFO hook.py line 449 1619929] Test: [22/50] Loss 4.8933 Process Time: 0.177 Mem R(MA/MR): 7128 (21200/36094) [2025-04-28 12:16:01,646 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.1294 Process Time: 0.301 Mem R(MA/MR): 8544 (21200/36094) [2025-04-28 12:16:02,449 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8497 Process Time: 0.285 Mem R(MA/MR): 5598 (21200/36094) [2025-04-28 12:16:03,857 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2098 Process Time: 0.544 Mem R(MA/MR): 9694 (21200/36094) [2025-04-28 12:16:10,783 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.7473 Process Time: 1.603 Mem R(MA/MR): 31738 (21200/36094) [2025-04-28 12:16:13,562 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.4011 Process Time: 0.408 Mem R(MA/MR): 10348 (21200/36094) [2025-04-28 12:16:15,154 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5293 Process Time: 0.291 Mem R(MA/MR): 9198 (21200/36094) [2025-04-28 12:16:20,181 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9786 Process Time: 0.285 Mem R(MA/MR): 17284 (21200/36094) [2025-04-28 12:16:21,499 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.4796 Process Time: 0.375 Mem R(MA/MR): 8110 (21200/36094) [2025-04-28 12:16:25,586 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0339 Process Time: 0.691 Mem R(MA/MR): 20710 (21200/36094) [2025-04-28 12:16:25,818 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3975 Process Time: 0.096 Mem R(MA/MR): 4212 (21200/36094) [2025-04-28 12:16:29,554 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.5671 Process Time: 0.373 Mem R(MA/MR): 24908 (21200/36094) [2025-04-28 12:16:30,851 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9387 Process Time: 0.428 Mem R(MA/MR): 9934 (21200/36094) [2025-04-28 12:16:32,587 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3644 Process Time: 0.389 Mem R(MA/MR): 14060 (21200/36094) [2025-04-28 12:16:33,065 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2996 Process Time: 0.172 Mem R(MA/MR): 6980 (21200/36094) [2025-04-28 12:16:36,316 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9925 Process Time: 0.371 Mem R(MA/MR): 28934 (21200/36094) [2025-04-28 12:16:38,490 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.9564 Process Time: 0.785 Mem R(MA/MR): 10860 (21200/36094) [2025-04-28 12:16:39,210 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.8364 Process Time: 0.292 Mem R(MA/MR): 5708 (21200/36094) [2025-04-28 12:16:40,384 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.0803 Process Time: 0.321 Mem R(MA/MR): 10448 (21200/36094) [2025-04-28 12:16:41,588 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.9982 Process Time: 0.427 Mem R(MA/MR): 9412 (21200/36094) [2025-04-28 12:16:41,993 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.7854 Process Time: 0.119 Mem R(MA/MR): 5706 (21200/36094) [2025-04-28 12:16:42,367 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.3818 Process Time: 0.117 Mem R(MA/MR): 5778 (21200/36094) [2025-04-28 12:16:42,962 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.8038 Process Time: 0.183 Mem R(MA/MR): 7242 (21200/36094) [2025-04-28 12:16:43,467 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6359 Process Time: 0.124 Mem R(MA/MR): 5480 (21200/36094) [2025-04-28 12:16:45,465 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.6526 Process Time: 0.238 Mem R(MA/MR): 14822 (21200/36094) [2025-04-28 12:16:53,083 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1686 Process Time: 1.584 Mem R(MA/MR): 20348 (21200/36094) [2025-04-28 12:17:02,547 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.1485 Process Time: 1.744 Mem R(MA/MR): 35512 (21200/36094) [2025-04-28 12:17:03,192 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.5572 Process Time: 0.185 Mem R(MA/MR): 5940 (21200/36094) [2025-04-28 12:17:05,856 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.3885 Process Time: 0.707 Mem R(MA/MR): 13884 (21200/36094) [2025-04-28 12:17:10,766 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 12:17:10,766 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 12:17:10,766 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] table : 0.208 0.552 0.797 0.730 0.596 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] door : 0.398 0.693 0.854 0.931 0.684 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] ceiling lamp : 0.513 0.718 0.816 0.903 0.669 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] cabinet : 0.310 0.471 0.507 0.547 0.522 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] blinds : 0.439 0.691 0.777 0.708 0.739 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] curtain : 0.221 0.395 0.755 0.538 0.583 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] chair : 0.582 0.752 0.817 0.735 0.738 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] storage cabinet: 0.221 0.396 0.606 0.692 0.360 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] office chair : 0.505 0.540 0.600 0.708 0.708 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] bookshelf : 0.170 0.497 0.498 0.714 0.455 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] whiteboard : 0.555 0.718 0.763 0.852 0.657 [2025-04-28 12:17:10,766 INFO hook.py line 395 1619929] window : 0.086 0.180 0.588 0.240 0.319 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] box : 0.139 0.283 0.461 0.500 0.359 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] monitor : 0.584 0.728 0.811 0.867 0.743 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] shelf : 0.065 0.153 0.394 0.381 0.267 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] heater : 0.345 0.606 0.829 0.867 0.684 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] kitchen cabinet: 0.205 0.419 0.715 0.611 0.440 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] sofa : 0.488 0.666 0.875 0.667 0.833 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] bed : 0.307 0.625 0.750 1.000 0.625 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] trash can : 0.462 0.590 0.652 0.786 0.677 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] book : 0.014 0.026 0.075 0.172 0.082 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] plant : 0.364 0.444 0.444 1.000 0.444 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] blanket : 0.407 0.535 0.624 0.750 0.545 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] tv : 0.813 0.974 0.974 0.857 1.000 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] computer tower : 0.211 0.332 0.548 0.548 0.405 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] refrigerator : 0.131 0.397 0.397 1.000 0.333 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] jacket : 0.176 0.405 0.511 0.429 0.545 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] sink : 0.354 0.656 0.918 0.833 0.682 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] bag : 0.155 0.256 0.258 0.500 0.370 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] picture : 0.144 0.315 0.407 0.867 0.333 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] pillow : 0.535 0.842 0.843 0.789 0.789 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] towel : 0.177 0.338 0.546 0.625 0.395 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] suitcase : 0.375 0.418 0.516 0.667 0.571 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] backpack : 0.424 0.476 0.519 0.778 0.538 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] crate : 0.073 0.213 0.436 0.357 0.455 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] keyboard : 0.385 0.511 0.632 0.724 0.538 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] toilet : 0.762 0.889 1.000 1.000 0.889 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] printer : 0.104 0.147 0.158 0.400 0.444 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] poster : 0.002 0.014 0.028 0.250 0.111 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,767 INFO hook.py line 395 1619929] microwave : 0.218 0.706 0.706 1.000 0.625 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] shoes : 0.201 0.290 0.434 0.516 0.390 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] socket : 0.157 0.406 0.616 0.720 0.421 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] bottle : 0.094 0.182 0.270 0.500 0.229 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] bucket : 0.028 0.058 0.062 0.176 0.429 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] cushion : 0.213 0.353 0.353 0.600 0.500 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.018 0.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] telephone : 0.240 0.417 0.573 0.600 0.529 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] laptop : 0.252 0.304 0.304 0.500 0.500 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] plant pot : 0.093 0.189 0.372 0.455 0.312 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] exhaust fan : 0.081 0.133 0.133 1.000 0.133 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] cup : 0.217 0.308 0.391 0.722 0.295 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] coat hanger : 0.065 0.208 0.167 0.667 0.500 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] light switch : 0.183 0.425 0.609 0.674 0.477 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] speaker : 0.201 0.448 0.547 0.545 0.545 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] table lamp : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] kettle : 0.222 0.333 0.333 1.000 0.333 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] smoke detector : 0.626 0.825 0.825 0.909 0.833 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] power strip : 0.135 0.197 0.247 0.600 0.300 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] mouse : 0.431 0.600 0.691 0.870 0.625 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] toilet paper : 0.130 0.222 0.283 0.800 0.235 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] clock : 0.546 1.000 1.000 1.000 1.000 [2025-04-28 12:17:10,768 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] tap : 0.112 0.176 0.333 0.667 0.222 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] soap dispenser : 0.495 0.600 0.600 1.000 0.600 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] bowl : 0.148 0.333 0.333 1.000 0.333 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] whiteboard eraser: 0.270 0.626 0.647 0.714 0.833 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] toilet brush : 0.393 0.667 0.833 1.000 0.667 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] headphones : 0.069 0.500 0.500 1.000 0.500 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] stapler : 0.009 0.083 0.250 0.500 0.333 [2025-04-28 12:17:10,769 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 12:17:10,769 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 12:17:10,769 INFO hook.py line 404 1619929] average : 0.228 0.368 0.451 0.613 0.422 [2025-04-28 12:17:10,769 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 12:17:10,769 INFO hook.py line 480 1619929] Total Process Time: 23.052 s [2025-04-28 12:17:10,769 INFO hook.py line 481 1619929] Average Process Time: 463.673 ms [2025-04-28 12:17:10,770 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 12:17:10,820 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.368 [2025-04-28 12:17:10,822 INFO hook.py line 685 1619929] Currently Best AP50: 0.368 [2025-04-28 12:17:10,825 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:18:44,678 INFO hook.py line 650 1619929] Train: [89/512][50/242] Data 0.017 (0.018) Batch 1.479 (1.471) Remain 41:54:27 loss: 4.0316 Lr: 2.53085e-04 Mem R(MA/MR): 25000 (21200/36094) [2025-04-28 12:19:52,837 INFO hook.py line 650 1619929] Train: [89/512][100/242] Data 0.017 (0.024) Batch 1.321 (1.415) Remain 40:18:05 loss: 5.5640 Lr: 2.52974e-04 Mem R(MA/MR): 27004 (21200/36094) [2025-04-28 12:20:59,963 INFO hook.py line 650 1619929] Train: [89/512][150/242] Data 0.016 (0.021) Batch 1.418 (1.391) Remain 39:34:40 loss: 6.1480 Lr: 2.52863e-04 Mem R(MA/MR): 29106 (21200/36094) [2025-04-28 12:22:07,188 INFO hook.py line 650 1619929] Train: [89/512][200/242] Data 0.015 (0.020) Batch 1.186 (1.379) Remain 39:13:34 loss: 5.4135 Lr: 2.52752e-04 Mem R(MA/MR): 29106 (21200/36094) [2025-04-28 12:23:02,040 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4958 loss_mask: 0.0443 loss_dice: 2.4552 loss_score: 0.0000 loss_bbox: 0.0574 loss_sp_cls: 1.0051 loss: 6.5090 [2025-04-28 12:23:06,161 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:24:37,461 INFO hook.py line 650 1619929] Train: [90/512][50/242] Data 0.015 (0.017) Batch 1.547 (1.395) Remain 39:39:32 loss: 6.7473 Lr: 2.52548e-04 Mem R(MA/MR): 21246 (21200/36094) [2025-04-28 12:25:46,782 INFO hook.py line 650 1619929] Train: [90/512][100/242] Data 0.015 (0.017) Batch 1.302 (1.391) Remain 39:30:27 loss: 5.9799 Lr: 2.52437e-04 Mem R(MA/MR): 21262 (21200/36094) [2025-04-28 12:26:55,574 INFO hook.py line 650 1619929] Train: [90/512][150/242] Data 0.015 (0.016) Batch 1.528 (1.386) Remain 39:20:40 loss: 6.8909 Lr: 2.52326e-04 Mem R(MA/MR): 21268 (21200/36094) [2025-04-28 12:28:03,997 INFO hook.py line 650 1619929] Train: [90/512][200/242] Data 0.014 (0.016) Batch 1.326 (1.381) Remain 39:12:03 loss: 6.4827 Lr: 2.52215e-04 Mem R(MA/MR): 21268 (21200/36094) [2025-04-28 12:28:59,891 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4993 loss_mask: 0.0450 loss_dice: 2.4550 loss_score: 0.0000 loss_bbox: 0.0573 loss_sp_cls: 1.0164 loss: 6.5282 [2025-04-28 12:29:04,904 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:30:36,062 INFO hook.py line 650 1619929] Train: [91/512][50/242] Data 0.022 (0.020) Batch 1.629 (1.519) Remain 43:04:48 loss: 7.7021 Lr: 2.52010e-04 Mem R(MA/MR): 21618 (21200/36094) [2025-04-28 12:31:46,945 INFO hook.py line 650 1619929] Train: [91/512][100/242] Data 0.017 (0.019) Batch 1.421 (1.467) Remain 41:34:31 loss: 7.2122 Lr: 2.51902e-04 Mem R(MA/MR): 23338 (21200/36094) [2025-04-28 12:32:54,992 INFO hook.py line 650 1619929] Train: [91/512][150/242] Data 0.015 (0.018) Batch 1.341 (1.431) Remain 40:31:58 loss: 6.5785 Lr: 2.51790e-04 Mem R(MA/MR): 25168 (21200/36094) [2025-04-28 12:34:02,989 INFO hook.py line 650 1619929] Train: [91/512][200/242] Data 0.015 (0.017) Batch 1.244 (1.413) Remain 40:00:10 loss: 6.8727 Lr: 2.51679e-04 Mem R(MA/MR): 25168 (21200/36094) [2025-04-28 12:34:57,140 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5164 loss_mask: 0.0467 loss_dice: 2.5081 loss_score: 0.0000 loss_bbox: 0.0585 loss_sp_cls: 1.0192 loss: 6.6642 [2025-04-28 12:35:01,217 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:36:33,923 INFO hook.py line 650 1619929] Train: [92/512][50/242] Data 0.015 (0.016) Batch 1.344 (1.418) Remain 40:06:59 loss: 6.4837 Lr: 2.51475e-04 Mem R(MA/MR): 19926 (21200/36094) [2025-04-28 12:37:43,551 INFO hook.py line 650 1619929] Train: [92/512][100/242] Data 0.016 (0.016) Batch 1.261 (1.405) Remain 39:43:22 loss: 6.6598 Lr: 2.51364e-04 Mem R(MA/MR): 19926 (21200/36094) [2025-04-28 12:38:50,150 INFO hook.py line 650 1619929] Train: [92/512][150/242] Data 0.014 (0.016) Batch 1.325 (1.380) Remain 39:00:05 loss: 7.6098 Lr: 2.51253e-04 Mem R(MA/MR): 21916 (21200/36094) [2025-04-28 12:39:58,567 INFO hook.py line 650 1619929] Train: [92/512][200/242] Data 0.014 (0.016) Batch 1.261 (1.377) Remain 38:53:52 loss: 8.1205 Lr: 2.51142e-04 Mem R(MA/MR): 21938 (21200/36094) [2025-04-28 12:40:53,351 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5383 loss_mask: 0.0492 loss_dice: 2.5929 loss_score: 0.0000 loss_bbox: 0.0609 loss_sp_cls: 1.0525 loss: 6.8849 [2025-04-28 12:40:54,439 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:42:28,071 INFO hook.py line 650 1619929] Train: [93/512][50/242] Data 0.015 (0.016) Batch 1.364 (1.441) Remain 40:39:32 loss: 5.8935 Lr: 2.50937e-04 Mem R(MA/MR): 22798 (21200/36094) [2025-04-28 12:43:36,974 INFO hook.py line 650 1619929] Train: [93/512][100/242] Data 0.016 (0.016) Batch 1.296 (1.408) Remain 39:43:34 loss: 7.1965 Lr: 2.50826e-04 Mem R(MA/MR): 24590 (21200/36094) [2025-04-28 12:44:48,211 INFO hook.py line 650 1619929] Train: [93/512][150/242] Data 0.015 (0.017) Batch 1.385 (1.414) Remain 39:51:46 loss: 6.6220 Lr: 2.50715e-04 Mem R(MA/MR): 27116 (21200/36094) [2025-04-28 12:45:57,130 INFO hook.py line 650 1619929] Train: [93/512][200/242] Data 0.014 (0.016) Batch 1.278 (1.405) Remain 39:35:19 loss: 8.6485 Lr: 2.50604e-04 Mem R(MA/MR): 27116 (21200/36094) [2025-04-28 12:46:51,973 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5362 loss_mask: 0.0486 loss_dice: 2.5605 loss_score: 0.0000 loss_bbox: 0.0597 loss_sp_cls: 1.0443 loss: 6.8206 [2025-04-28 12:46:53,987 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:48:22,066 INFO hook.py line 650 1619929] Train: [94/512][50/242] Data 0.017 (0.016) Batch 1.353 (1.376) Remain 38:44:00 loss: 7.8307 Lr: 2.50399e-04 Mem R(MA/MR): 21890 (21200/36094) [2025-04-28 12:49:33,376 INFO hook.py line 650 1619929] Train: [94/512][100/242] Data 0.017 (0.017) Batch 1.431 (1.402) Remain 39:26:39 loss: 7.6245 Lr: 2.50288e-04 Mem R(MA/MR): 21890 (21200/36094) [2025-04-28 12:50:43,036 INFO hook.py line 650 1619929] Train: [94/512][150/242] Data 0.017 (0.017) Batch 1.474 (1.399) Remain 39:20:32 loss: 7.2487 Lr: 2.50177e-04 Mem R(MA/MR): 25630 (21200/36094) [2025-04-28 12:51:51,235 INFO hook.py line 650 1619929] Train: [94/512][200/242] Data 0.015 (0.017) Batch 1.296 (1.390) Remain 39:04:28 loss: 6.8500 Lr: 2.50066e-04 Mem R(MA/MR): 25636 (21200/36094) [2025-04-28 12:52:47,472 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5357 loss_mask: 0.0477 loss_dice: 2.5541 loss_score: 0.0000 loss_bbox: 0.0601 loss_sp_cls: 1.0453 loss: 6.8081 [2025-04-28 12:52:50,767 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 12:54:21,009 INFO hook.py line 650 1619929] Train: [95/512][50/242] Data 0.016 (0.017) Batch 1.284 (1.420) Remain 39:53:20 loss: 5.8390 Lr: 2.49861e-04 Mem R(MA/MR): 20088 (21200/36094) [2025-04-28 12:55:30,195 INFO hook.py line 650 1619929] Train: [95/512][100/242] Data 0.015 (0.016) Batch 1.254 (1.401) Remain 39:20:23 loss: 7.0643 Lr: 2.49750e-04 Mem R(MA/MR): 20090 (21200/36094) [2025-04-28 12:56:38,543 INFO hook.py line 650 1619929] Train: [95/512][150/242] Data 0.015 (0.016) Batch 1.419 (1.390) Remain 38:59:27 loss: 5.0359 Lr: 2.49639e-04 Mem R(MA/MR): 20094 (21200/36094) [2025-04-28 12:57:47,685 INFO hook.py line 650 1619929] Train: [95/512][200/242] Data 0.015 (0.016) Batch 1.254 (1.388) Remain 38:55:24 loss: 7.0348 Lr: 2.49527e-04 Mem R(MA/MR): 20102 (21200/36094) [2025-04-28 12:58:42,755 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5288 loss_mask: 0.0481 loss_dice: 2.5505 loss_score: 0.0000 loss_bbox: 0.0596 loss_sp_cls: 1.0427 loss: 6.7829 [2025-04-28 12:58:46,163 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:00:18,836 INFO hook.py line 650 1619929] Train: [96/512][50/242] Data 0.015 (0.018) Batch 1.471 (1.415) Remain 39:38:50 loss: 7.8677 Lr: 2.49323e-04 Mem R(MA/MR): 22280 (21200/36094) [2025-04-28 13:01:30,631 INFO hook.py line 650 1619929] Train: [96/512][100/242] Data 0.016 (0.017) Batch 1.292 (1.426) Remain 39:55:42 loss: 6.2730 Lr: 2.49212e-04 Mem R(MA/MR): 25580 (21200/36094) [2025-04-28 13:02:39,673 INFO hook.py line 650 1619929] Train: [96/512][150/242] Data 0.016 (0.017) Batch 1.339 (1.411) Remain 39:28:49 loss: 6.5447 Lr: 2.49100e-04 Mem R(MA/MR): 27740 (21200/36094) [2025-04-28 13:03:48,947 INFO hook.py line 650 1619929] Train: [96/512][200/242] Data 0.016 (0.017) Batch 1.399 (1.404) Remain 39:16:58 loss: 5.6491 Lr: 2.48989e-04 Mem R(MA/MR): 27740 (21200/36094) [2025-04-28 13:04:46,002 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5271 loss_mask: 0.0474 loss_dice: 2.5251 loss_score: 0.0000 loss_bbox: 0.0596 loss_sp_cls: 1.0384 loss: 6.7347 [2025-04-28 13:04:49,507 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 13:04:51,981 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.7238 Process Time: 0.295 Mem R(MA/MR): 4368 (21200/36094) [2025-04-28 13:04:53,462 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.8656 Process Time: 0.437 Mem R(MA/MR): 7158 (21200/36094) [2025-04-28 13:04:55,172 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2583 Process Time: 0.683 Mem R(MA/MR): 9858 (21200/36094) [2025-04-28 13:05:03,980 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.1713 Process Time: 1.391 Mem R(MA/MR): 19826 (21200/36094) [2025-04-28 13:05:05,239 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.0197 Process Time: 0.422 Mem R(MA/MR): 7180 (21200/36094) [2025-04-28 13:05:06,655 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8156 Process Time: 0.471 Mem R(MA/MR): 11302 (21200/36094) [2025-04-28 13:05:07,273 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3569 Process Time: 0.230 Mem R(MA/MR): 6168 (21200/36094) [2025-04-28 13:05:07,719 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.7045 Process Time: 0.187 Mem R(MA/MR): 4398 (21200/36094) [2025-04-28 13:05:08,532 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.9381 Process Time: 0.190 Mem R(MA/MR): 11504 (21200/36094) [2025-04-28 13:05:09,967 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.5097 Process Time: 0.365 Mem R(MA/MR): 9636 (21200/36094) [2025-04-28 13:05:12,148 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.7498 Process Time: 0.567 Mem R(MA/MR): 17806 (21200/36094) [2025-04-28 13:05:15,182 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3224 Process Time: 0.463 Mem R(MA/MR): 15482 (21200/36094) [2025-04-28 13:05:16,339 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2692 Process Time: 0.226 Mem R(MA/MR): 8810 (21200/36094) [2025-04-28 13:05:16,799 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.8435 Process Time: 0.160 Mem R(MA/MR): 4948 (21200/36094) [2025-04-28 13:05:19,636 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.5437 Process Time: 0.387 Mem R(MA/MR): 16350 (21200/36094) [2025-04-28 13:05:21,841 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4079 Process Time: 0.516 Mem R(MA/MR): 14572 (21200/36094) [2025-04-28 13:05:22,788 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.8784 Process Time: 0.298 Mem R(MA/MR): 6762 (21200/36094) [2025-04-28 13:05:23,714 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.5420 Process Time: 0.233 Mem R(MA/MR): 8426 (21200/36094) [2025-04-28 13:05:25,080 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.1940 Process Time: 0.190 Mem R(MA/MR): 6176 (21200/36094) [2025-04-28 13:05:26,502 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.4732 Process Time: 0.212 Mem R(MA/MR): 11482 (21200/36094) [2025-04-28 13:05:35,826 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.6970 Process Time: 0.820 Mem R(MA/MR): 23310 (21200/36094) [2025-04-28 13:05:36,534 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5059 Process Time: 0.286 Mem R(MA/MR): 7122 (21200/36094) [2025-04-28 13:05:46,616 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.0293 Process Time: 0.559 Mem R(MA/MR): 8404 (21200/36094) [2025-04-28 13:05:47,619 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.4461 Process Time: 0.414 Mem R(MA/MR): 5438 (21200/36094) [2025-04-28 13:05:48,701 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.8210 Process Time: 0.294 Mem R(MA/MR): 9572 (21200/36094) [2025-04-28 13:05:53,690 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.0929 Process Time: 0.930 Mem R(MA/MR): 29382 (21200/36094) [2025-04-28 13:05:55,914 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.8679 Process Time: 0.366 Mem R(MA/MR): 10366 (21200/36094) [2025-04-28 13:05:57,020 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.3018 Process Time: 0.293 Mem R(MA/MR): 9074 (21200/36094) [2025-04-28 13:06:02,493 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9967 Process Time: 0.801 Mem R(MA/MR): 17218 (21200/36094) [2025-04-28 13:06:03,892 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1291 Process Time: 0.584 Mem R(MA/MR): 7984 (21200/36094) [2025-04-28 13:06:07,981 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.3228 Process Time: 0.952 Mem R(MA/MR): 19840 (21200/36094) [2025-04-28 13:06:08,302 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.7446 Process Time: 0.115 Mem R(MA/MR): 4102 (21200/36094) [2025-04-28 13:06:11,464 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.3397 Process Time: 0.330 Mem R(MA/MR): 24448 (21200/36094) [2025-04-28 13:06:12,504 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8236 Process Time: 0.305 Mem R(MA/MR): 10008 (21200/36094) [2025-04-28 13:06:14,741 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.7388 Process Time: 0.749 Mem R(MA/MR): 13964 (21200/36094) [2025-04-28 13:06:15,359 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2368 Process Time: 0.245 Mem R(MA/MR): 6604 (21200/36094) [2025-04-28 13:06:19,377 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.9002 Process Time: 0.913 Mem R(MA/MR): 28284 (21200/36094) [2025-04-28 13:06:20,703 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.0875 Process Time: 0.247 Mem R(MA/MR): 10900 (21200/36094) [2025-04-28 13:06:21,312 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3567 Process Time: 0.269 Mem R(MA/MR): 5506 (21200/36094) [2025-04-28 13:06:22,795 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.6637 Process Time: 0.610 Mem R(MA/MR): 10208 (21200/36094) [2025-04-28 13:06:24,477 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.7680 Process Time: 0.698 Mem R(MA/MR): 9384 (21200/36094) [2025-04-28 13:06:25,010 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.4556 Process Time: 0.162 Mem R(MA/MR): 5558 (21200/36094) [2025-04-28 13:06:25,434 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.4051 Process Time: 0.166 Mem R(MA/MR): 5634 (21200/36094) [2025-04-28 13:06:26,040 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1938 Process Time: 0.240 Mem R(MA/MR): 7120 (21200/36094) [2025-04-28 13:06:26,477 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.1832 Process Time: 0.153 Mem R(MA/MR): 5310 (21200/36094) [2025-04-28 13:06:28,566 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5370 Process Time: 0.451 Mem R(MA/MR): 14818 (21200/36094) [2025-04-28 13:06:35,923 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.6146 Process Time: 1.158 Mem R(MA/MR): 20404 (21200/36094) [2025-04-28 13:06:44,380 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.8322 Process Time: 1.687 Mem R(MA/MR): 34752 (21200/36094) [2025-04-28 13:06:44,846 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.1679 Process Time: 0.157 Mem R(MA/MR): 5652 (21200/36094) [2025-04-28 13:06:46,960 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1307 Process Time: 0.225 Mem R(MA/MR): 13614 (21200/36094) [2025-04-28 13:06:51,080 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 13:06:51,080 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 13:06:51,080 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 13:06:51,080 INFO hook.py line 395 1619929] table : 0.204 0.495 0.743 0.653 0.566 [2025-04-28 13:06:51,080 INFO hook.py line 395 1619929] door : 0.437 0.716 0.786 0.873 0.696 [2025-04-28 13:06:51,080 INFO hook.py line 395 1619929] ceiling lamp : 0.530 0.703 0.808 0.882 0.663 [2025-04-28 13:06:51,080 INFO hook.py line 395 1619929] cabinet : 0.289 0.443 0.565 0.596 0.463 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] blinds : 0.349 0.522 0.749 0.667 0.609 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] curtain : 0.350 0.595 0.796 0.818 0.750 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] chair : 0.521 0.697 0.753 0.643 0.746 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] storage cabinet: 0.116 0.304 0.391 0.474 0.360 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] office chair : 0.491 0.518 0.518 0.706 0.750 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] bookshelf : 0.288 0.762 0.772 0.889 0.727 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] whiteboard : 0.514 0.690 0.752 0.714 0.714 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] window : 0.099 0.270 0.536 0.423 0.330 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] box : 0.136 0.283 0.467 0.434 0.420 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] monitor : 0.593 0.796 0.810 1.000 0.757 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] shelf : 0.092 0.231 0.334 0.455 0.333 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] heater : 0.369 0.647 0.783 0.778 0.737 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] kitchen cabinet: 0.115 0.282 0.558 0.375 0.360 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] sofa : 0.411 0.667 0.782 0.625 0.833 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] bed : 0.259 0.586 0.586 1.000 0.500 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] trash can : 0.502 0.643 0.708 0.735 0.769 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] book : 0.016 0.028 0.060 0.158 0.086 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] plant : 0.387 0.667 0.667 1.000 0.667 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] blanket : 0.351 0.616 0.680 0.636 0.636 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] tv : 0.661 0.803 0.803 0.833 0.833 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] computer tower : 0.177 0.328 0.602 0.552 0.381 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] refrigerator : 0.087 0.213 0.236 0.500 0.333 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] jacket : 0.037 0.161 0.346 0.357 0.455 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] sink : 0.327 0.659 0.856 0.889 0.727 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] bag : 0.126 0.214 0.271 0.306 0.407 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] picture : 0.149 0.276 0.326 0.567 0.436 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] pillow : 0.479 0.701 0.780 0.923 0.632 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] towel : 0.167 0.276 0.404 0.519 0.368 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] suitcase : 0.406 0.429 0.571 1.000 0.429 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] backpack : 0.371 0.427 0.427 0.583 0.538 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] crate : 0.031 0.190 0.352 0.556 0.455 [2025-04-28 13:06:51,081 INFO hook.py line 395 1619929] keyboard : 0.320 0.435 0.447 0.739 0.436 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] toilet : 0.775 0.889 1.000 1.000 0.889 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] printer : 0.151 0.220 0.315 0.571 0.444 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] painting : 0.125 0.125 0.125 0.250 1.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] microwave : 0.358 0.584 0.925 0.833 0.625 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] shoes : 0.146 0.299 0.450 0.750 0.366 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] socket : 0.151 0.371 0.567 0.688 0.379 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] bottle : 0.138 0.197 0.254 0.368 0.253 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] bucket : 0.085 0.086 0.089 0.250 0.286 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] cushion : 0.042 0.042 0.042 0.500 0.167 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] shoe rack : 0.014 0.125 0.125 0.500 0.500 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] telephone : 0.149 0.371 0.440 0.667 0.353 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] laptop : 0.277 0.348 0.348 0.500 0.375 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] plant pot : 0.157 0.302 0.440 0.545 0.375 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] exhaust fan : 0.059 0.067 0.067 1.000 0.067 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] cup : 0.178 0.348 0.400 0.654 0.386 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] coat hanger : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] light switch : 0.239 0.485 0.638 0.767 0.508 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] speaker : 0.257 0.330 0.366 1.000 0.273 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] smoke detector : 0.628 0.836 0.853 0.808 0.875 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] power strip : 0.128 0.143 0.157 0.400 0.200 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] mouse : 0.453 0.624 0.632 0.864 0.594 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] toilet paper : 0.278 0.430 0.437 0.875 0.412 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] paper towel : 0.003 0.031 0.031 0.500 0.125 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] clock : 0.633 1.000 1.000 1.000 1.000 [2025-04-28 13:06:51,082 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] tap : 0.066 0.106 0.556 0.333 0.333 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] soap dispenser : 0.343 0.542 0.542 0.750 0.600 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] whiteboard eraser: 0.149 0.436 0.436 0.625 0.833 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] toilet brush : 0.329 0.667 0.833 1.000 0.667 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:06:51,083 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 13:06:51,083 INFO hook.py line 404 1619929] average : 0.226 0.355 0.426 0.584 0.422 [2025-04-28 13:06:51,083 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 13:06:51,083 INFO hook.py line 480 1619929] Total Process Time: 23.101 s [2025-04-28 13:06:51,083 INFO hook.py line 481 1619929] Average Process Time: 465.429 ms [2025-04-28 13:06:51,084 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 13:06:51,135 INFO hook.py line 685 1619929] Currently Best AP50: 0.368 [2025-04-28 13:06:51,137 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:08:17,146 INFO hook.py line 650 1619929] Train: [97/512][50/242] Data 0.016 (0.032) Batch 1.218 (1.430) Remain 39:58:47 loss: 7.0868 Lr: 2.48784e-04 Mem R(MA/MR): 22246 (21200/36094) [2025-04-28 13:09:26,339 INFO hook.py line 650 1619929] Train: [97/512][100/242] Data 0.015 (0.024) Batch 1.321 (1.406) Remain 39:17:24 loss: 6.8050 Lr: 2.48673e-04 Mem R(MA/MR): 22246 (21200/36094) [2025-04-28 13:10:34,161 INFO hook.py line 650 1619929] Train: [97/512][150/242] Data 0.016 (0.021) Batch 1.325 (1.389) Remain 38:47:45 loss: 6.1007 Lr: 2.48562e-04 Mem R(MA/MR): 22246 (21200/36094) [2025-04-28 13:11:44,614 INFO hook.py line 650 1619929] Train: [97/512][200/242] Data 0.015 (0.020) Batch 1.393 (1.394) Remain 38:54:58 loss: 5.3229 Lr: 2.48451e-04 Mem R(MA/MR): 22246 (21200/36094) [2025-04-28 13:12:39,535 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5207 loss_mask: 0.0476 loss_dice: 2.5296 loss_score: 0.0000 loss_bbox: 0.0597 loss_sp_cls: 1.0305 loss: 6.7317 [2025-04-28 13:12:43,626 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:14:18,833 INFO hook.py line 650 1619929] Train: [98/512][50/242] Data 0.017 (0.017) Batch 1.466 (1.502) Remain 41:53:34 loss: 6.7142 Lr: 2.48246e-04 Mem R(MA/MR): 22612 (21200/36094) [2025-04-28 13:15:28,098 INFO hook.py line 650 1619929] Train: [98/512][100/242] Data 0.016 (0.017) Batch 1.438 (1.442) Remain 40:11:20 loss: 6.5994 Lr: 2.48135e-04 Mem R(MA/MR): 22612 (21200/36094) [2025-04-28 13:16:39,156 INFO hook.py line 650 1619929] Train: [98/512][150/242] Data 0.016 (0.017) Batch 1.251 (1.435) Remain 39:58:16 loss: 5.7789 Lr: 2.48023e-04 Mem R(MA/MR): 22612 (21200/36094) [2025-04-28 13:17:48,220 INFO hook.py line 650 1619929] Train: [98/512][200/242] Data 0.014 (0.017) Batch 1.291 (1.421) Remain 39:34:19 loss: 8.2472 Lr: 2.47912e-04 Mem R(MA/MR): 22612 (21200/36094) [2025-04-28 13:18:45,648 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5165 loss_mask: 0.0477 loss_dice: 2.5188 loss_score: 0.0000 loss_bbox: 0.0594 loss_sp_cls: 1.0321 loss: 6.6921 [2025-04-28 13:18:49,732 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:20:23,255 INFO hook.py line 650 1619929] Train: [99/512][50/242] Data 0.016 (0.016) Batch 1.431 (1.407) Remain 39:07:37 loss: 6.0512 Lr: 2.47707e-04 Mem R(MA/MR): 26236 (21200/36094) [2025-04-28 13:21:31,643 INFO hook.py line 650 1619929] Train: [99/512][100/242] Data 0.016 (0.016) Batch 1.349 (1.387) Remain 38:33:01 loss: 7.8109 Lr: 2.47596e-04 Mem R(MA/MR): 29604 (21200/36094) [2025-04-28 13:22:40,767 INFO hook.py line 650 1619929] Train: [99/512][150/242] Data 0.016 (0.016) Batch 1.322 (1.385) Remain 38:29:30 loss: 7.0885 Lr: 2.47485e-04 Mem R(MA/MR): 31748 (21200/36094) [2025-04-28 13:23:48,402 INFO hook.py line 650 1619929] Train: [99/512][200/242] Data 0.015 (0.016) Batch 1.444 (1.377) Remain 38:14:37 loss: 6.6629 Lr: 2.47373e-04 Mem R(MA/MR): 31748 (21200/36094) [2025-04-28 13:24:43,335 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5074 loss_mask: 0.0468 loss_dice: 2.4873 loss_score: 0.0000 loss_bbox: 0.0586 loss_sp_cls: 1.0229 loss: 6.6112 [2025-04-28 13:24:43,574 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:26:14,205 INFO hook.py line 650 1619929] Train: [100/512][50/242] Data 0.016 (0.017) Batch 1.633 (1.472) Remain 40:51:16 loss: 5.3556 Lr: 2.47169e-04 Mem R(MA/MR): 24856 (21200/36094) [2025-04-28 13:27:25,814 INFO hook.py line 650 1619929] Train: [100/512][100/242] Data 0.015 (0.017) Batch 1.336 (1.452) Remain 40:15:37 loss: 5.4638 Lr: 2.47057e-04 Mem R(MA/MR): 26954 (21200/36094) [2025-04-28 13:28:35,860 INFO hook.py line 650 1619929] Train: [100/512][150/242] Data 0.016 (0.017) Batch 1.374 (1.434) Remain 39:45:43 loss: 6.6361 Lr: 2.46946e-04 Mem R(MA/MR): 26954 (21200/36094) [2025-04-28 13:29:44,314 INFO hook.py line 650 1619929] Train: [100/512][200/242] Data 0.015 (0.017) Batch 1.384 (1.418) Remain 39:17:00 loss: 7.4736 Lr: 2.46835e-04 Mem R(MA/MR): 26976 (21200/36094) [2025-04-28 13:30:39,198 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4860 loss_mask: 0.0440 loss_dice: 2.4158 loss_score: 0.0000 loss_bbox: 0.0574 loss_sp_cls: 0.9967 loss: 6.4122 [2025-04-28 13:30:43,895 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:32:17,866 INFO hook.py line 650 1619929] Train: [101/512][50/242] Data 0.015 (0.016) Batch 1.331 (1.438) Remain 39:49:02 loss: 5.5800 Lr: 2.46630e-04 Mem R(MA/MR): 21130 (21200/36094) [2025-04-28 13:33:29,394 INFO hook.py line 650 1619929] Train: [101/512][100/242] Data 0.016 (0.017) Batch 1.286 (1.434) Remain 39:41:06 loss: 6.6034 Lr: 2.46518e-04 Mem R(MA/MR): 21144 (21200/36094) [2025-04-28 13:34:37,293 INFO hook.py line 650 1619929] Train: [101/512][150/242] Data 0.016 (0.016) Batch 1.380 (1.408) Remain 38:56:48 loss: 7.0582 Lr: 2.46407e-04 Mem R(MA/MR): 21158 (21200/36094) [2025-04-28 13:35:45,708 INFO hook.py line 650 1619929] Train: [101/512][200/242] Data 0.015 (0.016) Batch 1.391 (1.398) Remain 38:38:46 loss: 6.2964 Lr: 2.46296e-04 Mem R(MA/MR): 21158 (21200/36094) [2025-04-28 13:36:38,479 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4774 loss_mask: 0.0433 loss_dice: 2.4089 loss_score: 0.0000 loss_bbox: 0.0562 loss_sp_cls: 0.9889 loss: 6.3592 [2025-04-28 13:36:40,506 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:38:10,761 INFO hook.py line 650 1619929] Train: [102/512][50/242] Data 0.019 (0.017) Batch 1.463 (1.397) Remain 38:34:03 loss: 6.3250 Lr: 2.46091e-04 Mem R(MA/MR): 22304 (21200/36094) [2025-04-28 13:39:20,316 INFO hook.py line 650 1619929] Train: [102/512][100/242] Data 0.015 (0.017) Batch 1.407 (1.394) Remain 38:28:11 loss: 6.3565 Lr: 2.45979e-04 Mem R(MA/MR): 23064 (21200/36094) [2025-04-28 13:40:29,475 INFO hook.py line 650 1619929] Train: [102/512][150/242] Data 0.016 (0.016) Batch 1.439 (1.390) Remain 38:21:02 loss: 6.6782 Lr: 2.45868e-04 Mem R(MA/MR): 25588 (21200/36094) [2025-04-28 13:41:39,379 INFO hook.py line 650 1619929] Train: [102/512][200/242] Data 0.014 (0.016) Batch 1.332 (1.392) Remain 38:23:12 loss: 6.8413 Lr: 2.45757e-04 Mem R(MA/MR): 25602 (21200/36094) [2025-04-28 13:42:34,383 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4780 loss_mask: 0.0441 loss_dice: 2.4187 loss_score: 0.0000 loss_bbox: 0.0570 loss_sp_cls: 0.9853 loss: 6.3830 [2025-04-28 13:42:36,897 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:44:10,226 INFO hook.py line 650 1619929] Train: [103/512][50/242] Data 0.019 (0.018) Batch 1.489 (1.438) Remain 39:37:09 loss: 6.5187 Lr: 2.45552e-04 Mem R(MA/MR): 21600 (21200/36094) [2025-04-28 13:45:19,025 INFO hook.py line 650 1619929] Train: [103/512][100/242] Data 0.017 (0.017) Batch 1.464 (1.406) Remain 38:42:56 loss: 6.2699 Lr: 2.45440e-04 Mem R(MA/MR): 23666 (21200/36094) [2025-04-28 13:46:29,071 INFO hook.py line 650 1619929] Train: [103/512][150/242] Data 0.018 (0.017) Batch 1.591 (1.404) Remain 38:38:50 loss: 6.4833 Lr: 2.45329e-04 Mem R(MA/MR): 23666 (21200/36094) [2025-04-28 13:47:40,608 INFO hook.py line 650 1619929] Train: [103/512][200/242] Data 0.015 (0.017) Batch 1.420 (1.411) Remain 38:48:43 loss: 5.8427 Lr: 2.45217e-04 Mem R(MA/MR): 23666 (21200/36094) [2025-04-28 13:48:36,408 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4804 loss_mask: 0.0439 loss_dice: 2.3997 loss_score: 0.0000 loss_bbox: 0.0574 loss_sp_cls: 0.9794 loss: 6.3667 [2025-04-28 13:48:36,478 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:50:06,676 INFO hook.py line 650 1619929] Train: [104/512][50/242] Data 0.016 (0.017) Batch 1.416 (1.463) Remain 40:12:41 loss: 5.4745 Lr: 2.45012e-04 Mem R(MA/MR): 22116 (21200/36094) [2025-04-28 13:51:13,590 INFO hook.py line 650 1619929] Train: [104/512][100/242] Data 0.016 (0.017) Batch 1.384 (1.399) Remain 38:25:15 loss: 7.4503 Lr: 2.44901e-04 Mem R(MA/MR): 22116 (21200/36094) [2025-04-28 13:52:22,886 INFO hook.py line 650 1619929] Train: [104/512][150/242] Data 0.018 (0.017) Batch 1.419 (1.394) Remain 38:16:51 loss: 6.5883 Lr: 2.44789e-04 Mem R(MA/MR): 24170 (21200/36094) [2025-04-28 13:53:30,217 INFO hook.py line 650 1619929] Train: [104/512][200/242] Data 0.014 (0.017) Batch 1.189 (1.382) Remain 37:55:42 loss: 6.8399 Lr: 2.44678e-04 Mem R(MA/MR): 24170 (21200/36094) [2025-04-28 13:54:25,881 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4827 loss_mask: 0.0437 loss_dice: 2.4283 loss_score: 0.0000 loss_bbox: 0.0579 loss_sp_cls: 0.9849 loss: 6.4239 [2025-04-28 13:54:30,086 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 13:54:32,598 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.4492 Process Time: 0.329 Mem R(MA/MR): 3990 (21200/36094) [2025-04-28 13:54:34,185 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.4555 Process Time: 0.628 Mem R(MA/MR): 6680 (21200/36094) [2025-04-28 13:54:35,842 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.9586 Process Time: 0.630 Mem R(MA/MR): 9270 (21200/36094) [2025-04-28 13:54:43,632 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3397 Process Time: 1.104 Mem R(MA/MR): 19384 (21200/36094) [2025-04-28 13:54:44,961 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3144 Process Time: 0.464 Mem R(MA/MR): 6744 (21200/36094) [2025-04-28 13:54:46,370 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0497 Process Time: 0.479 Mem R(MA/MR): 10756 (21200/36094) [2025-04-28 13:54:47,035 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2272 Process Time: 0.236 Mem R(MA/MR): 5972 (21200/36094) [2025-04-28 13:54:47,590 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.9694 Process Time: 0.181 Mem R(MA/MR): 4056 (21200/36094) [2025-04-28 13:54:48,422 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0863 Process Time: 0.227 Mem R(MA/MR): 11080 (21200/36094) [2025-04-28 13:54:49,842 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.9350 Process Time: 0.230 Mem R(MA/MR): 9158 (21200/36094) [2025-04-28 13:54:52,123 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.2990 Process Time: 0.352 Mem R(MA/MR): 18164 (21200/36094) [2025-04-28 13:54:54,879 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1415 Process Time: 0.566 Mem R(MA/MR): 14996 (21200/36094) [2025-04-28 13:54:56,083 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.9999 Process Time: 0.353 Mem R(MA/MR): 8390 (21200/36094) [2025-04-28 13:54:56,435 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.7081 Process Time: 0.115 Mem R(MA/MR): 4388 (21200/36094) [2025-04-28 13:54:58,601 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.1684 Process Time: 0.255 Mem R(MA/MR): 16372 (21200/36094) [2025-04-28 13:55:00,449 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4006 Process Time: 0.586 Mem R(MA/MR): 14340 (21200/36094) [2025-04-28 13:55:01,305 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.3467 Process Time: 0.303 Mem R(MA/MR): 6396 (21200/36094) [2025-04-28 13:55:02,725 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.6563 Process Time: 0.605 Mem R(MA/MR): 7920 (21200/36094) [2025-04-28 13:55:04,214 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.7027 Process Time: 0.261 Mem R(MA/MR): 5940 (21200/36094) [2025-04-28 13:55:05,703 INFO hook.py line 449 1619929] Test: [20/50] Loss 7.6398 Process Time: 0.243 Mem R(MA/MR): 11028 (21200/36094) [2025-04-28 13:55:14,901 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.3451 Process Time: 0.589 Mem R(MA/MR): 23282 (21200/36094) [2025-04-28 13:55:15,492 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.1747 Process Time: 0.178 Mem R(MA/MR): 6706 (21200/36094) [2025-04-28 13:55:24,851 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.4711 Process Time: 0.366 Mem R(MA/MR): 9642 (21200/36094) [2025-04-28 13:55:25,339 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0991 Process Time: 0.125 Mem R(MA/MR): 5046 (21200/36094) [2025-04-28 13:55:26,322 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1193 Process Time: 0.230 Mem R(MA/MR): 8996 (21200/36094) [2025-04-28 13:55:33,623 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.1649 Process Time: 1.950 Mem R(MA/MR): 30820 (21200/36094) [2025-04-28 13:55:35,618 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.3384 Process Time: 0.237 Mem R(MA/MR): 9792 (21200/36094) [2025-04-28 13:55:37,197 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.0445 Process Time: 0.571 Mem R(MA/MR): 8510 (21200/36094) [2025-04-28 13:55:42,656 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.7487 Process Time: 0.699 Mem R(MA/MR): 16788 (21200/36094) [2025-04-28 13:55:43,503 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.6920 Process Time: 0.232 Mem R(MA/MR): 7556 (21200/36094) [2025-04-28 13:55:48,115 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0086 Process Time: 0.646 Mem R(MA/MR): 20202 (21200/36094) [2025-04-28 13:55:48,505 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.7596 Process Time: 0.175 Mem R(MA/MR): 3850 (21200/36094) [2025-04-28 13:55:52,608 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.7437 Process Time: 0.484 Mem R(MA/MR): 24530 (21200/36094) [2025-04-28 13:55:54,697 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6715 Process Time: 0.796 Mem R(MA/MR): 9510 (21200/36094) [2025-04-28 13:55:56,930 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.4211 Process Time: 0.542 Mem R(MA/MR): 13628 (21200/36094) [2025-04-28 13:55:57,472 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9158 Process Time: 0.167 Mem R(MA/MR): 6228 (21200/36094) [2025-04-28 13:56:01,222 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.2116 Process Time: 0.405 Mem R(MA/MR): 28382 (21200/36094) [2025-04-28 13:56:03,642 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.7058 Process Time: 0.884 Mem R(MA/MR): 10356 (21200/36094) [2025-04-28 13:56:04,407 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0339 Process Time: 0.331 Mem R(MA/MR): 5122 (21200/36094) [2025-04-28 13:56:05,783 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.4022 Process Time: 0.401 Mem R(MA/MR): 9914 (21200/36094) [2025-04-28 13:56:06,917 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.4657 Process Time: 0.275 Mem R(MA/MR): 8684 (21200/36094) [2025-04-28 13:56:07,402 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.7944 Process Time: 0.134 Mem R(MA/MR): 5124 (21200/36094) [2025-04-28 13:56:07,877 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.2569 Process Time: 0.134 Mem R(MA/MR): 5226 (21200/36094) [2025-04-28 13:56:08,788 INFO hook.py line 449 1619929] Test: [44/50] Loss 6.9853 Process Time: 0.184 Mem R(MA/MR): 6740 (21200/36094) [2025-04-28 13:56:09,384 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5725 Process Time: 0.162 Mem R(MA/MR): 4920 (21200/36094) [2025-04-28 13:56:12,110 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.7667 Process Time: 0.576 Mem R(MA/MR): 14428 (21200/36094) [2025-04-28 13:56:21,012 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.8009 Process Time: 1.368 Mem R(MA/MR): 20082 (21200/36094) [2025-04-28 13:56:31,918 INFO hook.py line 449 1619929] Test: [48/50] Loss 10.6797 Process Time: 2.298 Mem R(MA/MR): 35496 (21200/36094) [2025-04-28 13:56:32,992 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.7098 Process Time: 0.311 Mem R(MA/MR): 5412 (21200/36094) [2025-04-28 13:56:35,010 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.9970 Process Time: 0.263 Mem R(MA/MR): 13270 (21200/36094) [2025-04-28 13:56:39,841 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 13:56:39,841 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 13:56:39,841 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] table : 0.244 0.611 0.777 0.780 0.625 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] door : 0.468 0.753 0.876 0.843 0.747 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] ceiling lamp : 0.535 0.718 0.828 0.891 0.680 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] cabinet : 0.331 0.504 0.568 0.554 0.537 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] blinds : 0.465 0.649 0.805 0.750 0.652 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] curtain : 0.253 0.528 0.765 0.556 0.833 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] chair : 0.596 0.716 0.801 0.826 0.643 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] storage cabinet: 0.269 0.492 0.596 0.733 0.440 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] office chair : 0.526 0.572 0.586 0.712 0.771 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] bookshelf : 0.237 0.712 0.709 0.750 0.818 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] whiteboard : 0.490 0.679 0.706 0.889 0.686 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] window : 0.080 0.210 0.538 0.400 0.330 [2025-04-28 13:56:39,841 INFO hook.py line 395 1619929] box : 0.142 0.301 0.502 0.360 0.470 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] monitor : 0.583 0.752 0.837 0.962 0.729 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] shelf : 0.044 0.101 0.361 0.350 0.233 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] heater : 0.457 0.729 0.804 0.900 0.711 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] kitchen cabinet: 0.116 0.232 0.675 0.455 0.400 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] sofa : 0.473 0.681 0.786 0.818 0.750 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] bed : 0.094 0.219 0.785 0.600 0.375 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] trash can : 0.541 0.688 0.720 0.803 0.754 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] book : 0.015 0.035 0.057 0.265 0.082 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] plant : 0.452 0.657 0.657 0.923 0.667 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] blanket : 0.375 0.608 0.608 1.000 0.545 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] tv : 0.861 0.974 0.974 0.857 1.000 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] computer tower : 0.263 0.355 0.591 0.737 0.333 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] refrigerator : 0.215 0.416 0.417 1.000 0.333 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] jacket : 0.024 0.086 0.345 0.217 0.455 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] sink : 0.347 0.597 0.764 0.667 0.727 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] bag : 0.085 0.179 0.210 0.360 0.333 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] picture : 0.124 0.269 0.327 0.471 0.410 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] pillow : 0.499 0.710 0.872 0.857 0.632 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] towel : 0.173 0.293 0.523 0.591 0.342 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] suitcase : 0.228 0.257 0.357 0.429 0.429 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] backpack : 0.422 0.509 0.558 0.615 0.615 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] crate : 0.091 0.348 0.472 0.538 0.636 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] keyboard : 0.373 0.439 0.592 0.692 0.462 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] toilet : 0.759 0.889 1.000 1.000 0.889 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] printer : 0.239 0.325 0.335 0.385 0.556 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] poster : 0.002 0.014 0.014 0.250 0.111 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] microwave : 0.435 0.731 0.875 0.857 0.750 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] shoes : 0.126 0.219 0.497 0.467 0.341 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] socket : 0.162 0.402 0.615 0.592 0.436 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] bottle : 0.105 0.148 0.280 0.297 0.229 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] bucket : 0.129 0.138 0.142 0.300 0.429 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] cushion : 0.046 0.182 0.276 0.308 0.667 [2025-04-28 13:56:39,842 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 1.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] telephone : 0.273 0.478 0.600 0.727 0.471 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] laptop : 0.258 0.503 0.503 0.750 0.750 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] plant pot : 0.098 0.258 0.407 0.714 0.312 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] exhaust fan : 0.091 0.200 0.200 1.000 0.200 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] cup : 0.160 0.291 0.364 0.517 0.341 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] coat hanger : 0.135 0.500 0.500 1.000 0.500 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] light switch : 0.251 0.510 0.622 0.745 0.538 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] speaker : 0.482 0.559 0.606 0.857 0.545 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] kettle : 0.195 0.333 0.333 1.000 0.333 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] smoke detector : 0.620 0.782 0.784 0.947 0.750 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] power strip : 0.062 0.168 0.189 0.222 0.400 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] paper bag : 0.083 0.083 0.083 0.167 1.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] mouse : 0.495 0.615 0.688 0.909 0.625 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] cutting board : 0.243 0.500 0.500 1.000 0.500 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] toilet paper : 0.142 0.245 0.407 0.455 0.294 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] clock : 0.554 0.764 0.764 0.750 1.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 1.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] tap : 0.039 0.093 0.283 0.667 0.222 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] soap dispenser : 0.405 0.600 0.800 1.000 0.600 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] whiteboard eraser: 0.230 0.547 0.547 0.667 0.667 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] toilet brush : 0.351 0.667 0.833 1.000 0.667 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] headphones : 0.222 0.500 0.500 1.000 0.500 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] stapler : 0.006 0.056 0.250 0.333 0.333 [2025-04-28 13:56:39,843 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 13:56:39,843 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 13:56:39,844 INFO hook.py line 404 1619929] average : 0.236 0.370 0.476 0.586 0.447 [2025-04-28 13:56:39,844 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 13:56:39,844 INFO hook.py line 480 1619929] Total Process Time: 23.859 s [2025-04-28 13:56:39,844 INFO hook.py line 481 1619929] Average Process Time: 480.218 ms [2025-04-28 13:56:39,844 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 13:56:39,884 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.370 [2025-04-28 13:56:39,889 INFO hook.py line 685 1619929] Currently Best AP50: 0.370 [2025-04-28 13:56:39,889 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 13:58:07,144 INFO hook.py line 650 1619929] Train: [105/512][50/242] Data 0.015 (0.017) Batch 1.425 (1.439) Remain 39:27:09 loss: 6.6151 Lr: 2.44473e-04 Mem R(MA/MR): 22244 (21200/36094) [2025-04-28 13:59:16,070 INFO hook.py line 650 1619929] Train: [105/512][100/242] Data 0.016 (0.017) Batch 1.530 (1.408) Remain 38:34:31 loss: 6.3895 Lr: 2.44361e-04 Mem R(MA/MR): 22244 (21200/36094) [2025-04-28 14:00:27,374 INFO hook.py line 650 1619929] Train: [105/512][150/242] Data 0.016 (0.022) Batch 1.533 (1.414) Remain 38:43:30 loss: 7.1835 Lr: 2.44250e-04 Mem R(MA/MR): 22244 (21200/36094) [2025-04-28 14:01:35,257 INFO hook.py line 650 1619929] Train: [105/512][200/242] Data 0.014 (0.021) Batch 1.211 (1.400) Remain 38:18:48 loss: 5.4387 Lr: 2.44138e-04 Mem R(MA/MR): 22244 (21200/36094) [2025-04-28 14:02:29,950 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4822 loss_mask: 0.0437 loss_dice: 2.4192 loss_score: 0.0000 loss_bbox: 0.0569 loss_sp_cls: 0.9887 loss: 6.3994 [2025-04-28 14:02:34,453 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:04:04,716 INFO hook.py line 650 1619929] Train: [106/512][50/242] Data 0.018 (0.017) Batch 1.283 (1.377) Remain 37:38:49 loss: 4.9596 Lr: 2.43933e-04 Mem R(MA/MR): 20738 (21200/36094) [2025-04-28 14:05:14,556 INFO hook.py line 650 1619929] Train: [106/512][100/242] Data 0.016 (0.016) Batch 1.281 (1.387) Remain 37:54:40 loss: 7.4407 Lr: 2.43822e-04 Mem R(MA/MR): 21386 (21200/36094) [2025-04-28 14:06:23,666 INFO hook.py line 650 1619929] Train: [106/512][150/242] Data 0.016 (0.017) Batch 1.330 (1.385) Remain 37:50:46 loss: 6.0805 Lr: 2.43710e-04 Mem R(MA/MR): 21386 (21200/36094) [2025-04-28 14:07:32,836 INFO hook.py line 650 1619929] Train: [106/512][200/242] Data 0.015 (0.017) Batch 1.512 (1.385) Remain 37:48:47 loss: 7.5610 Lr: 2.43599e-04 Mem R(MA/MR): 21386 (21200/36094) [2025-04-28 14:08:28,664 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4861 loss_mask: 0.0437 loss_dice: 2.4377 loss_score: 0.0000 loss_bbox: 0.0579 loss_sp_cls: 0.9874 loss: 6.4449 [2025-04-28 14:08:29,336 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:10:01,905 INFO hook.py line 650 1619929] Train: [107/512][50/242] Data 0.017 (0.017) Batch 1.468 (1.437) Remain 39:12:43 loss: 6.4320 Lr: 2.43394e-04 Mem R(MA/MR): 22240 (21200/36094) [2025-04-28 14:11:13,113 INFO hook.py line 650 1619929] Train: [107/512][100/242] Data 0.017 (0.018) Batch 1.504 (1.431) Remain 39:00:15 loss: 7.0856 Lr: 2.43284e-04 Mem R(MA/MR): 22240 (21200/36094) [2025-04-28 14:12:22,883 INFO hook.py line 650 1619929] Train: [107/512][150/242] Data 0.017 (0.017) Batch 1.499 (1.419) Remain 38:39:30 loss: 7.1609 Lr: 2.43173e-04 Mem R(MA/MR): 22242 (21200/36094) [2025-04-28 14:13:34,584 INFO hook.py line 650 1619929] Train: [107/512][200/242] Data 0.015 (0.017) Batch 1.339 (1.423) Remain 38:44:43 loss: 5.9164 Lr: 2.43061e-04 Mem R(MA/MR): 24014 (21200/36094) [2025-04-28 14:14:30,654 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5125 loss_mask: 0.0478 loss_dice: 2.5285 loss_score: 0.0000 loss_bbox: 0.0604 loss_sp_cls: 1.0316 loss: 6.6994 [2025-04-28 14:14:30,727 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:15:53,989 INFO hook.py line 650 1619929] Train: [108/512][50/242] Data 0.017 (0.017) Batch 1.449 (1.384) Remain 37:39:15 loss: 5.6561 Lr: 2.42856e-04 Mem R(MA/MR): 21002 (21200/36094) [2025-04-28 14:17:03,369 INFO hook.py line 650 1619929] Train: [108/512][100/242] Data 0.018 (0.016) Batch 1.380 (1.386) Remain 37:41:20 loss: 7.1611 Lr: 2.42745e-04 Mem R(MA/MR): 21020 (21200/36094) [2025-04-28 14:18:13,601 INFO hook.py line 650 1619929] Train: [108/512][150/242] Data 0.017 (0.016) Batch 1.532 (1.392) Remain 37:50:39 loss: 7.2735 Lr: 2.42633e-04 Mem R(MA/MR): 21020 (21200/36094) [2025-04-28 14:19:23,690 INFO hook.py line 650 1619929] Train: [108/512][200/242] Data 0.015 (0.016) Batch 1.331 (1.395) Remain 37:53:28 loss: 6.3635 Lr: 2.42521e-04 Mem R(MA/MR): 22966 (21200/36094) [2025-04-28 14:20:19,757 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5353 loss_mask: 0.0491 loss_dice: 2.5690 loss_score: 0.0000 loss_bbox: 0.0600 loss_sp_cls: 1.0468 loss: 6.8412 [2025-04-28 14:20:25,078 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:21:57,236 INFO hook.py line 650 1619929] Train: [109/512][50/242] Data 0.016 (0.017) Batch 1.413 (1.435) Remain 38:57:00 loss: 6.6167 Lr: 2.42316e-04 Mem R(MA/MR): 19008 (21200/36094) [2025-04-28 14:23:07,545 INFO hook.py line 650 1619929] Train: [109/512][100/242] Data 0.016 (0.017) Batch 1.305 (1.420) Remain 38:31:40 loss: 7.4435 Lr: 2.42205e-04 Mem R(MA/MR): 22894 (21200/36094) [2025-04-28 14:24:14,595 INFO hook.py line 650 1619929] Train: [109/512][150/242] Data 0.016 (0.017) Batch 1.312 (1.393) Remain 37:46:42 loss: 6.2704 Lr: 2.42093e-04 Mem R(MA/MR): 22896 (21200/36094) [2025-04-28 14:25:26,134 INFO hook.py line 650 1619929] Train: [109/512][200/242] Data 0.014 (0.017) Batch 1.374 (1.403) Remain 38:01:03 loss: 7.4385 Lr: 2.41981e-04 Mem R(MA/MR): 22896 (21200/36094) [2025-04-28 14:26:22,060 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5192 loss_mask: 0.0482 loss_dice: 2.5262 loss_score: 0.0000 loss_bbox: 0.0597 loss_sp_cls: 1.0287 loss: 6.7100 [2025-04-28 14:26:22,132 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:27:46,502 INFO hook.py line 650 1619929] Train: [110/512][50/242] Data 0.016 (0.017) Batch 1.282 (1.435) Remain 38:51:28 loss: 6.9795 Lr: 2.41776e-04 Mem R(MA/MR): 20750 (21200/36094) [2025-04-28 14:28:54,852 INFO hook.py line 650 1619929] Train: [110/512][100/242] Data 0.017 (0.017) Batch 1.539 (1.400) Remain 37:53:13 loss: 6.5398 Lr: 2.41665e-04 Mem R(MA/MR): 20752 (21200/36094) [2025-04-28 14:30:06,561 INFO hook.py line 650 1619929] Train: [110/512][150/242] Data 0.016 (0.017) Batch 1.380 (1.412) Remain 38:10:57 loss: 6.6855 Lr: 2.41553e-04 Mem R(MA/MR): 20752 (21200/36094) [2025-04-28 14:31:15,632 INFO hook.py line 650 1619929] Train: [110/512][200/242] Data 0.015 (0.017) Batch 1.434 (1.404) Remain 37:57:21 loss: 6.8718 Lr: 2.41441e-04 Mem R(MA/MR): 20764 (21200/36094) [2025-04-28 14:32:11,147 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5191 loss_mask: 0.0475 loss_dice: 2.5315 loss_score: 0.0000 loss_bbox: 0.0592 loss_sp_cls: 1.0309 loss: 6.7155 [2025-04-28 14:32:11,609 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:33:36,828 INFO hook.py line 650 1619929] Train: [111/512][50/242] Data 0.015 (0.017) Batch 1.378 (1.467) Remain 39:36:52 loss: 6.0201 Lr: 2.41236e-04 Mem R(MA/MR): 21806 (21200/36094) [2025-04-28 14:34:48,091 INFO hook.py line 650 1619929] Train: [111/512][100/242] Data 0.016 (0.016) Batch 1.276 (1.445) Remain 39:01:02 loss: 6.4884 Lr: 2.41124e-04 Mem R(MA/MR): 23680 (21200/36094) [2025-04-28 14:35:59,949 INFO hook.py line 650 1619929] Train: [111/512][150/242] Data 0.068 (0.017) Batch 1.533 (1.443) Remain 38:55:20 loss: 6.2002 Lr: 2.41013e-04 Mem R(MA/MR): 25738 (21200/36094) [2025-04-28 14:37:09,267 INFO hook.py line 650 1619929] Train: [111/512][200/242] Data 0.014 (0.017) Batch 1.307 (1.428) Remain 38:31:04 loss: 6.9892 Lr: 2.40901e-04 Mem R(MA/MR): 25738 (21200/36094) [2025-04-28 14:38:04,709 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5109 loss_mask: 0.0476 loss_dice: 2.5175 loss_score: 0.0000 loss_bbox: 0.0586 loss_sp_cls: 1.0163 loss: 6.6637 [2025-04-28 14:38:09,143 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:39:40,991 INFO hook.py line 650 1619929] Train: [112/512][50/242] Data 0.015 (0.017) Batch 1.506 (1.420) Remain 38:15:22 loss: 7.8540 Lr: 2.40696e-04 Mem R(MA/MR): 25956 (21200/36094) [2025-04-28 14:40:50,062 INFO hook.py line 650 1619929] Train: [112/512][100/242] Data 0.017 (0.016) Batch 1.426 (1.400) Remain 37:42:06 loss: 6.5668 Lr: 2.40584e-04 Mem R(MA/MR): 25980 (21200/36094) [2025-04-28 14:41:58,519 INFO hook.py line 650 1619929] Train: [112/512][150/242] Data 0.016 (0.017) Batch 1.481 (1.390) Remain 37:23:57 loss: 8.5351 Lr: 2.40472e-04 Mem R(MA/MR): 27520 (21200/36094) [2025-04-28 14:43:07,435 INFO hook.py line 650 1619929] Train: [112/512][200/242] Data 0.014 (0.017) Batch 1.382 (1.387) Remain 37:18:12 loss: 5.6213 Lr: 2.40361e-04 Mem R(MA/MR): 29762 (21200/36094) [2025-04-28 14:44:01,653 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5054 loss_mask: 0.0472 loss_dice: 2.5084 loss_score: 0.0000 loss_bbox: 0.0589 loss_sp_cls: 1.0093 loss: 6.6321 [2025-04-28 14:44:01,725 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 14:44:04,187 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.3031 Process Time: 0.323 Mem R(MA/MR): 4338 (21200/36094) [2025-04-28 14:44:06,146 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.4421 Process Time: 0.689 Mem R(MA/MR): 7398 (21200/36094) [2025-04-28 14:44:07,877 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.6426 Process Time: 0.619 Mem R(MA/MR): 9794 (21200/36094) [2025-04-28 14:44:16,017 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.4202 Process Time: 1.352 Mem R(MA/MR): 19644 (21200/36094) [2025-04-28 14:44:16,934 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5041 Process Time: 0.374 Mem R(MA/MR): 7192 (21200/36094) [2025-04-28 14:44:18,131 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5839 Process Time: 0.303 Mem R(MA/MR): 11304 (21200/36094) [2025-04-28 14:44:18,669 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3901 Process Time: 0.143 Mem R(MA/MR): 6320 (21200/36094) [2025-04-28 14:44:19,067 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.1020 Process Time: 0.103 Mem R(MA/MR): 4370 (21200/36094) [2025-04-28 14:44:19,898 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7984 Process Time: 0.215 Mem R(MA/MR): 11612 (21200/36094) [2025-04-28 14:44:21,445 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.9507 Process Time: 0.353 Mem R(MA/MR): 9506 (21200/36094) [2025-04-28 14:44:24,654 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.8268 Process Time: 0.913 Mem R(MA/MR): 18768 (21200/36094) [2025-04-28 14:44:27,688 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.4138 Process Time: 0.710 Mem R(MA/MR): 15524 (21200/36094) [2025-04-28 14:44:28,822 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7915 Process Time: 0.275 Mem R(MA/MR): 8742 (21200/36094) [2025-04-28 14:44:29,241 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.4129 Process Time: 0.130 Mem R(MA/MR): 4998 (21200/36094) [2025-04-28 14:44:32,320 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.6534 Process Time: 0.444 Mem R(MA/MR): 16968 (21200/36094) [2025-04-28 14:44:34,532 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6112 Process Time: 0.592 Mem R(MA/MR): 14916 (21200/36094) [2025-04-28 14:44:35,360 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7125 Process Time: 0.239 Mem R(MA/MR): 7140 (21200/36094) [2025-04-28 14:44:36,233 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0588 Process Time: 0.191 Mem R(MA/MR): 8486 (21200/36094) [2025-04-28 14:44:37,630 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9237 Process Time: 0.155 Mem R(MA/MR): 6296 (21200/36094) [2025-04-28 14:44:39,403 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.2881 Process Time: 0.257 Mem R(MA/MR): 11644 (21200/36094) [2025-04-28 14:44:49,713 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.2372 Process Time: 1.302 Mem R(MA/MR): 23248 (21200/36094) [2025-04-28 14:44:50,614 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2471 Process Time: 0.274 Mem R(MA/MR): 7248 (21200/36094) [2025-04-28 14:45:00,647 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.9836 Process Time: 0.535 Mem R(MA/MR): 10376 (21200/36094) [2025-04-28 14:45:01,127 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.5400 Process Time: 0.129 Mem R(MA/MR): 5720 (21200/36094) [2025-04-28 14:45:02,169 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.3753 Process Time: 0.202 Mem R(MA/MR): 9192 (21200/36094) [2025-04-28 14:45:08,622 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.8278 Process Time: 0.945 Mem R(MA/MR): 31342 (21200/36094) [2025-04-28 14:45:10,859 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.9497 Process Time: 0.365 Mem R(MA/MR): 10476 (21200/36094) [2025-04-28 14:45:11,954 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.6763 Process Time: 0.187 Mem R(MA/MR): 8582 (21200/36094) [2025-04-28 14:45:17,046 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.8933 Process Time: 0.310 Mem R(MA/MR): 17430 (21200/36094) [2025-04-28 14:45:18,268 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.7645 Process Time: 0.372 Mem R(MA/MR): 8114 (21200/36094) [2025-04-28 14:45:22,013 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.5355 Process Time: 0.364 Mem R(MA/MR): 20624 (21200/36094) [2025-04-28 14:45:22,322 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1821 Process Time: 0.143 Mem R(MA/MR): 4194 (21200/36094) [2025-04-28 14:45:26,686 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3469 Process Time: 0.840 Mem R(MA/MR): 24620 (21200/36094) [2025-04-28 14:45:27,823 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.4572 Process Time: 0.377 Mem R(MA/MR): 9392 (21200/36094) [2025-04-28 14:45:29,295 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.4766 Process Time: 0.276 Mem R(MA/MR): 14438 (21200/36094) [2025-04-28 14:45:29,755 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8281 Process Time: 0.143 Mem R(MA/MR): 6978 (21200/36094) [2025-04-28 14:45:33,268 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8771 Process Time: 0.643 Mem R(MA/MR): 28134 (21200/36094) [2025-04-28 14:45:35,427 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.7404 Process Time: 0.631 Mem R(MA/MR): 10518 (21200/36094) [2025-04-28 14:45:36,068 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9846 Process Time: 0.213 Mem R(MA/MR): 5814 (21200/36094) [2025-04-28 14:45:37,156 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.1218 Process Time: 0.215 Mem R(MA/MR): 10188 (21200/36094) [2025-04-28 14:45:38,074 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.9727 Process Time: 0.207 Mem R(MA/MR): 9284 (21200/36094) [2025-04-28 14:45:38,546 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.2055 Process Time: 0.135 Mem R(MA/MR): 5800 (21200/36094) [2025-04-28 14:45:38,942 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.4408 Process Time: 0.118 Mem R(MA/MR): 5866 (21200/36094) [2025-04-28 14:45:39,592 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.4249 Process Time: 0.230 Mem R(MA/MR): 7402 (21200/36094) [2025-04-28 14:45:40,247 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0055 Process Time: 0.209 Mem R(MA/MR): 5622 (21200/36094) [2025-04-28 14:45:42,892 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.2397 Process Time: 0.701 Mem R(MA/MR): 14948 (21200/36094) [2025-04-28 14:45:50,343 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.2711 Process Time: 1.324 Mem R(MA/MR): 20552 (21200/36094) [2025-04-28 14:46:02,052 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.3696 Process Time: 2.421 Mem R(MA/MR): 35316 (21200/36094) [2025-04-28 14:46:02,790 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.6216 Process Time: 0.233 Mem R(MA/MR): 5792 (21200/36094) [2025-04-28 14:46:05,293 INFO hook.py line 449 1619929] Test: [50/50] Loss 6.0072 Process Time: 0.503 Mem R(MA/MR): 14238 (21200/36094) [2025-04-28 14:46:09,280 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 14:46:09,280 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 14:46:09,280 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 14:46:09,280 INFO hook.py line 395 1619929] table : 0.168 0.448 0.743 0.762 0.471 [2025-04-28 14:46:09,280 INFO hook.py line 395 1619929] door : 0.391 0.678 0.859 0.885 0.684 [2025-04-28 14:46:09,280 INFO hook.py line 395 1619929] ceiling lamp : 0.544 0.740 0.851 0.866 0.713 [2025-04-28 14:46:09,280 INFO hook.py line 395 1619929] cabinet : 0.275 0.428 0.511 0.515 0.522 [2025-04-28 14:46:09,280 INFO hook.py line 395 1619929] blinds : 0.427 0.710 0.866 0.833 0.652 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] curtain : 0.336 0.509 0.878 0.562 0.750 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] chair : 0.480 0.659 0.735 0.684 0.664 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] storage cabinet: 0.165 0.404 0.514 0.818 0.360 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] office chair : 0.570 0.624 0.666 0.723 0.708 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] bookshelf : 0.231 0.450 0.649 0.667 0.545 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] whiteboard : 0.529 0.720 0.772 0.889 0.686 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] window : 0.083 0.191 0.565 0.434 0.253 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] box : 0.151 0.295 0.532 0.512 0.354 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] monitor : 0.579 0.729 0.804 0.877 0.714 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] shelf : 0.077 0.279 0.451 0.562 0.300 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] heater : 0.348 0.575 0.797 0.641 0.658 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] kitchen cabinet: 0.114 0.288 0.610 0.526 0.400 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] sofa : 0.477 0.666 0.843 0.714 0.833 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] bed : 0.214 0.602 0.731 0.833 0.625 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] trash can : 0.485 0.641 0.732 0.731 0.754 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] book : 0.010 0.026 0.051 0.185 0.082 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] plant : 0.315 0.502 0.722 0.750 0.500 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] blanket : 0.483 0.732 0.769 0.889 0.727 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] tv : 0.654 0.833 0.833 1.000 0.833 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] computer tower : 0.253 0.388 0.573 0.514 0.429 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] refrigerator : 0.166 0.265 0.396 1.000 0.222 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] jacket : 0.121 0.177 0.378 0.417 0.455 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] sink : 0.369 0.746 0.889 0.773 0.773 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] bag : 0.105 0.189 0.189 0.583 0.259 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] picture : 0.112 0.293 0.384 0.536 0.385 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] pillow : 0.580 0.716 0.742 0.923 0.632 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] towel : 0.146 0.261 0.399 0.632 0.316 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] suitcase : 0.238 0.347 0.347 0.500 0.571 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] backpack : 0.184 0.231 0.231 0.714 0.385 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] crate : 0.016 0.068 0.442 0.192 0.455 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] keyboard : 0.321 0.448 0.529 0.692 0.462 [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 14:46:09,281 INFO hook.py line 395 1619929] toilet : 0.767 0.889 1.000 1.000 0.889 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] printer : 0.190 0.297 0.355 0.571 0.444 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.007 0.077 0.111 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] painting : 0.125 0.125 0.125 0.250 1.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] microwave : 0.402 0.702 0.898 0.583 0.875 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] shoes : 0.104 0.210 0.463 0.667 0.293 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] socket : 0.144 0.360 0.572 0.654 0.364 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] bottle : 0.093 0.156 0.268 0.400 0.217 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] bucket : 0.216 0.235 0.247 0.200 0.571 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] cushion : 0.139 0.164 0.247 0.308 0.667 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] telephone : 0.173 0.306 0.379 0.462 0.353 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] laptop : 0.196 0.341 0.392 0.625 0.625 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] plant pot : 0.103 0.260 0.420 0.714 0.312 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] exhaust fan : 0.022 0.067 0.067 1.000 0.067 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] cup : 0.200 0.325 0.375 0.625 0.341 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] coat hanger : 0.083 0.250 0.250 1.000 0.250 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] light switch : 0.196 0.424 0.629 0.667 0.431 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] speaker : 0.265 0.321 0.417 0.571 0.364 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] smoke detector : 0.611 0.782 0.783 1.000 0.708 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] power strip : 0.018 0.040 0.057 0.214 0.300 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] mouse : 0.375 0.517 0.630 0.810 0.531 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] toilet paper : 0.186 0.328 0.337 1.000 0.294 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] paper towel : 0.057 0.125 0.125 1.000 0.125 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 14:46:09,282 INFO hook.py line 395 1619929] clock : 0.376 0.711 0.764 0.600 1.000 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 1.000 0.000 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] tap : 0.031 0.050 0.556 0.400 0.222 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] soap dispenser : 0.468 0.600 0.600 1.000 0.600 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] bowl : 0.025 0.083 0.083 0.500 0.333 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] whiteboard eraser: 0.114 0.346 0.346 0.571 0.667 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] toilet brush : 0.449 0.502 0.901 0.750 0.500 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] headphones : 0.281 0.500 0.500 1.000 0.500 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] stapler : 0.142 0.222 0.222 0.500 0.667 [2025-04-28 14:46:09,283 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 14:46:09,283 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 14:46:09,283 INFO hook.py line 404 1619929] average : 0.220 0.342 0.447 0.598 0.423 [2025-04-28 14:46:09,283 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 14:46:09,283 INFO hook.py line 480 1619929] Total Process Time: 22.927 s [2025-04-28 14:46:09,283 INFO hook.py line 481 1619929] Average Process Time: 461.308 ms [2025-04-28 14:46:09,283 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 14:46:09,342 INFO hook.py line 685 1619929] Currently Best AP50: 0.370 [2025-04-28 14:46:09,348 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:47:37,422 INFO hook.py line 650 1619929] Train: [113/512][50/242] Data 0.017 (0.018) Batch 1.424 (1.461) Remain 39:15:59 loss: 7.5039 Lr: 2.40155e-04 Mem R(MA/MR): 28156 (21200/36094) [2025-04-28 14:48:50,309 INFO hook.py line 650 1619929] Train: [113/512][100/242] Data 0.016 (0.024) Batch 1.405 (1.459) Remain 39:12:00 loss: 5.0136 Lr: 2.40043e-04 Mem R(MA/MR): 29998 (21200/36094) [2025-04-28 14:49:59,730 INFO hook.py line 650 1619929] Train: [113/512][150/242] Data 0.018 (0.021) Batch 1.731 (1.435) Remain 38:31:53 loss: 8.4588 Lr: 2.39932e-04 Mem R(MA/MR): 29998 (21200/36094) [2025-04-28 14:51:08,423 INFO hook.py line 650 1619929] Train: [113/512][200/242] Data 0.015 (0.020) Batch 1.333 (1.420) Remain 38:05:38 loss: 5.7942 Lr: 2.39820e-04 Mem R(MA/MR): 29998 (21200/36094) [2025-04-28 14:52:05,604 INFO misc.py line 135 1619929] Train result: loss_cls: 0.5061 loss_mask: 0.0466 loss_dice: 2.4907 loss_score: 0.0000 loss_bbox: 0.0593 loss_sp_cls: 1.0111 loss: 6.6090 [2025-04-28 14:52:09,295 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:53:41,237 INFO hook.py line 650 1619929] Train: [114/512][50/242] Data 0.016 (0.018) Batch 1.460 (1.435) Remain 38:28:14 loss: 6.5211 Lr: 2.39614e-04 Mem R(MA/MR): 27692 (21200/36094) [2025-04-28 14:54:49,920 INFO hook.py line 650 1619929] Train: [114/512][100/242] Data 0.020 (0.017) Batch 1.454 (1.403) Remain 37:36:10 loss: 6.5823 Lr: 2.39503e-04 Mem R(MA/MR): 27692 (21200/36094) [2025-04-28 14:55:59,089 INFO hook.py line 650 1619929] Train: [114/512][150/242] Data 0.016 (0.017) Batch 1.359 (1.397) Remain 37:24:02 loss: 6.4739 Lr: 2.39391e-04 Mem R(MA/MR): 27692 (21200/36094) [2025-04-28 14:57:10,673 INFO hook.py line 650 1619929] Train: [114/512][200/242] Data 0.015 (0.017) Batch 1.397 (1.406) Remain 37:37:11 loss: 5.7467 Lr: 2.39279e-04 Mem R(MA/MR): 27692 (21200/36094) [2025-04-28 14:58:04,971 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4999 loss_mask: 0.0466 loss_dice: 2.4704 loss_score: 0.0000 loss_bbox: 0.0594 loss_sp_cls: 1.0131 loss: 6.5609 [2025-04-28 14:58:08,481 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 14:59:34,991 INFO hook.py line 650 1619929] Train: [115/512][50/242] Data 0.015 (0.017) Batch 1.499 (1.407) Remain 37:37:29 loss: 5.9864 Lr: 2.39074e-04 Mem R(MA/MR): 22458 (21200/36094) [2025-04-28 15:00:43,429 INFO hook.py line 650 1619929] Train: [115/512][100/242] Data 0.016 (0.016) Batch 1.234 (1.387) Remain 37:04:39 loss: 6.6522 Lr: 2.38962e-04 Mem R(MA/MR): 24376 (21200/36094) [2025-04-28 15:01:52,119 INFO hook.py line 650 1619929] Train: [115/512][150/242] Data 0.017 (0.016) Batch 1.454 (1.383) Remain 36:56:09 loss: 6.9920 Lr: 2.38850e-04 Mem R(MA/MR): 24388 (21200/36094) [2025-04-28 15:03:00,512 INFO hook.py line 650 1619929] Train: [115/512][200/242] Data 0.016 (0.016) Batch 1.547 (1.379) Remain 36:48:58 loss: 7.1990 Lr: 2.38739e-04 Mem R(MA/MR): 24388 (21200/36094) [2025-04-28 15:03:55,915 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4873 loss_mask: 0.0456 loss_dice: 2.4456 loss_score: 0.0000 loss_bbox: 0.0571 loss_sp_cls: 0.9936 loss: 6.4623 [2025-04-28 15:03:57,719 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:05:22,248 INFO hook.py line 650 1619929] Train: [116/512][50/242] Data 0.015 (0.017) Batch 1.398 (1.436) Remain 38:17:22 loss: 6.6664 Lr: 2.38535e-04 Mem R(MA/MR): 22344 (21200/36094) [2025-04-28 15:06:32,084 INFO hook.py line 650 1619929] Train: [116/512][100/242] Data 0.017 (0.017) Batch 1.429 (1.415) Remain 37:44:10 loss: 6.8679 Lr: 2.38423e-04 Mem R(MA/MR): 22356 (21200/36094) [2025-04-28 15:07:42,244 INFO hook.py line 650 1619929] Train: [116/512][150/242] Data 0.016 (0.017) Batch 1.610 (1.411) Remain 37:36:18 loss: 6.5968 Lr: 2.38312e-04 Mem R(MA/MR): 22382 (21200/36094) [2025-04-28 15:08:50,645 INFO hook.py line 650 1619929] Train: [116/512][200/242] Data 0.016 (0.017) Batch 1.283 (1.400) Remain 37:17:34 loss: 6.2718 Lr: 2.38200e-04 Mem R(MA/MR): 24036 (21200/36094) [2025-04-28 15:09:45,081 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4929 loss_mask: 0.0455 loss_dice: 2.4512 loss_score: 0.0000 loss_bbox: 0.0584 loss_sp_cls: 0.9910 loss: 6.4910 [2025-04-28 15:09:45,959 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:11:08,930 INFO hook.py line 650 1619929] Train: [117/512][50/242] Data 0.016 (0.017) Batch 1.330 (1.431) Remain 38:04:35 loss: 5.6722 Lr: 2.37994e-04 Mem R(MA/MR): 23016 (21200/36094) [2025-04-28 15:12:18,034 INFO hook.py line 650 1619929] Train: [117/512][100/242] Data 0.016 (0.017) Batch 1.404 (1.406) Remain 37:23:02 loss: 6.5456 Lr: 2.37882e-04 Mem R(MA/MR): 23020 (21200/36094) [2025-04-28 15:13:28,933 INFO hook.py line 650 1619929] Train: [117/512][150/242] Data 0.016 (0.017) Batch 1.277 (1.410) Remain 37:28:27 loss: 9.7697 Lr: 2.37770e-04 Mem R(MA/MR): 23020 (21200/36094) [2025-04-28 15:14:36,074 INFO hook.py line 650 1619929] Train: [117/512][200/242] Data 0.016 (0.017) Batch 1.381 (1.393) Remain 37:00:07 loss: 7.9852 Lr: 2.37659e-04 Mem R(MA/MR): 23020 (21200/36094) [2025-04-28 15:15:30,505 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4895 loss_mask: 0.0470 loss_dice: 2.4613 loss_score: 0.0000 loss_bbox: 0.0579 loss_sp_cls: 0.9938 loss: 6.5097 [2025-04-28 15:15:32,518 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:17:05,200 INFO hook.py line 650 1619929] Train: [118/512][50/242] Data 0.016 (0.016) Batch 1.343 (1.445) Remain 38:21:20 loss: 7.3938 Lr: 2.37453e-04 Mem R(MA/MR): 27390 (21200/36094) [2025-04-28 15:18:13,990 INFO hook.py line 650 1619929] Train: [118/512][100/242] Data 0.015 (0.016) Batch 1.293 (1.410) Remain 37:23:13 loss: 6.2543 Lr: 2.37341e-04 Mem R(MA/MR): 29898 (21200/36094) [2025-04-28 15:19:21,405 INFO hook.py line 650 1619929] Train: [118/512][150/242] Data 0.017 (0.016) Batch 1.395 (1.389) Remain 36:48:55 loss: 5.1846 Lr: 2.37229e-04 Mem R(MA/MR): 29898 (21200/36094) [2025-04-28 15:20:29,757 INFO hook.py line 650 1619929] Train: [118/512][200/242] Data 0.015 (0.016) Batch 1.356 (1.383) Remain 36:39:02 loss: 7.3735 Lr: 2.37117e-04 Mem R(MA/MR): 29908 (21200/36094) [2025-04-28 15:21:24,629 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4873 loss_mask: 0.0459 loss_dice: 2.4498 loss_score: 0.0000 loss_bbox: 0.0581 loss_sp_cls: 0.9896 loss: 6.4653 [2025-04-28 15:21:24,711 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:22:54,111 INFO hook.py line 650 1619929] Train: [119/512][50/242] Data 0.016 (0.016) Batch 1.266 (1.388) Remain 36:44:31 loss: 5.8201 Lr: 2.36912e-04 Mem R(MA/MR): 21420 (21200/36094) [2025-04-28 15:24:02,393 INFO hook.py line 650 1619929] Train: [119/512][100/242] Data 0.015 (0.016) Batch 1.326 (1.376) Remain 36:25:04 loss: 6.8325 Lr: 2.36800e-04 Mem R(MA/MR): 22980 (21200/36094) [2025-04-28 15:25:10,933 INFO hook.py line 650 1619929] Train: [119/512][150/242] Data 0.016 (0.016) Batch 1.265 (1.375) Remain 36:20:52 loss: 5.3786 Lr: 2.36688e-04 Mem R(MA/MR): 22980 (21200/36094) [2025-04-28 15:26:18,532 INFO hook.py line 650 1619929] Train: [119/512][200/242] Data 0.015 (0.016) Batch 1.370 (1.369) Remain 36:10:39 loss: 5.6672 Lr: 2.36576e-04 Mem R(MA/MR): 22980 (21200/36094) [2025-04-28 15:27:13,325 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4873 loss_mask: 0.0455 loss_dice: 2.4500 loss_score: 0.0000 loss_bbox: 0.0579 loss_sp_cls: 0.9935 loss: 6.4648 [2025-04-28 15:27:14,040 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:28:42,494 INFO hook.py line 650 1619929] Train: [120/512][50/242] Data 0.017 (0.018) Batch 1.287 (1.397) Remain 36:52:31 loss: 5.8149 Lr: 2.36370e-04 Mem R(MA/MR): 22136 (21200/36094) [2025-04-28 15:29:51,583 INFO hook.py line 650 1619929] Train: [120/512][100/242] Data 0.018 (0.017) Batch 1.368 (1.389) Remain 36:39:17 loss: 7.8580 Lr: 2.36258e-04 Mem R(MA/MR): 22172 (21200/36094) [2025-04-28 15:30:59,928 INFO hook.py line 650 1619929] Train: [120/512][150/242] Data 0.016 (0.017) Batch 1.358 (1.381) Remain 36:26:17 loss: 7.5057 Lr: 2.36146e-04 Mem R(MA/MR): 23912 (21200/36094) [2025-04-28 15:32:07,249 INFO hook.py line 650 1619929] Train: [120/512][200/242] Data 0.015 (0.016) Batch 1.355 (1.373) Remain 36:11:03 loss: 5.9345 Lr: 2.36035e-04 Mem R(MA/MR): 23912 (21200/36094) [2025-04-28 15:33:02,397 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4898 loss_mask: 0.0454 loss_dice: 2.4410 loss_score: 0.0000 loss_bbox: 0.0576 loss_sp_cls: 0.9942 loss: 6.4534 [2025-04-28 15:33:03,689 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 15:33:06,249 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.6903 Process Time: 0.344 Mem R(MA/MR): 4080 (21200/36094) [2025-04-28 15:33:07,818 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.5724 Process Time: 0.454 Mem R(MA/MR): 7006 (21200/36094) [2025-04-28 15:33:09,403 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.6936 Process Time: 0.554 Mem R(MA/MR): 9638 (21200/36094) [2025-04-28 15:33:16,713 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.7549 Process Time: 1.276 Mem R(MA/MR): 19338 (21200/36094) [2025-04-28 15:33:17,487 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6472 Process Time: 0.242 Mem R(MA/MR): 6720 (21200/36094) [2025-04-28 15:33:18,629 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6777 Process Time: 0.252 Mem R(MA/MR): 11324 (21200/36094) [2025-04-28 15:33:19,179 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1269 Process Time: 0.156 Mem R(MA/MR): 6260 (21200/36094) [2025-04-28 15:33:19,631 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.7981 Process Time: 0.134 Mem R(MA/MR): 4536 (21200/36094) [2025-04-28 15:33:20,745 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8415 Process Time: 0.425 Mem R(MA/MR): 11562 (21200/36094) [2025-04-28 15:33:22,037 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.0513 Process Time: 0.289 Mem R(MA/MR): 8998 (21200/36094) [2025-04-28 15:33:24,476 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.7409 Process Time: 0.482 Mem R(MA/MR): 18356 (21200/36094) [2025-04-28 15:33:27,105 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0957 Process Time: 0.634 Mem R(MA/MR): 15104 (21200/36094) [2025-04-28 15:33:28,063 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2442 Process Time: 0.216 Mem R(MA/MR): 8200 (21200/36094) [2025-04-28 15:33:28,585 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.7359 Process Time: 0.196 Mem R(MA/MR): 4820 (21200/36094) [2025-04-28 15:33:32,486 INFO hook.py line 449 1619929] Test: [15/50] Loss 10.5815 Process Time: 0.540 Mem R(MA/MR): 16402 (21200/36094) [2025-04-28 15:33:34,268 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.9015 Process Time: 0.353 Mem R(MA/MR): 14362 (21200/36094) [2025-04-28 15:33:35,226 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7988 Process Time: 0.312 Mem R(MA/MR): 6576 (21200/36094) [2025-04-28 15:33:36,159 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.6125 Process Time: 0.220 Mem R(MA/MR): 8054 (21200/36094) [2025-04-28 15:33:37,681 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.1972 Process Time: 0.301 Mem R(MA/MR): 6258 (21200/36094) [2025-04-28 15:33:39,305 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.1503 Process Time: 0.246 Mem R(MA/MR): 11502 (21200/36094) [2025-04-28 15:33:48,037 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.1157 Process Time: 0.618 Mem R(MA/MR): 23204 (21200/36094) [2025-04-28 15:33:48,746 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.1171 Process Time: 0.254 Mem R(MA/MR): 6722 (21200/36094) [2025-04-28 15:33:59,491 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.6961 Process Time: 0.427 Mem R(MA/MR): 9886 (21200/36094) [2025-04-28 15:34:00,050 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0491 Process Time: 0.168 Mem R(MA/MR): 5356 (21200/36094) [2025-04-28 15:34:01,234 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.4007 Process Time: 0.321 Mem R(MA/MR): 9352 (21200/36094) [2025-04-28 15:34:09,056 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.6111 Process Time: 1.325 Mem R(MA/MR): 31720 (21200/36094) [2025-04-28 15:34:11,654 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.4644 Process Time: 0.743 Mem R(MA/MR): 10236 (21200/36094) [2025-04-28 15:34:12,743 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.0732 Process Time: 0.219 Mem R(MA/MR): 8556 (21200/36094) [2025-04-28 15:34:17,740 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6406 Process Time: 0.308 Mem R(MA/MR): 16958 (21200/36094) [2025-04-28 15:34:18,818 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.5537 Process Time: 0.335 Mem R(MA/MR): 7524 (21200/36094) [2025-04-28 15:34:22,612 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.5495 Process Time: 0.419 Mem R(MA/MR): 20288 (21200/36094) [2025-04-28 15:34:22,963 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.5027 Process Time: 0.121 Mem R(MA/MR): 3704 (21200/36094) [2025-04-28 15:34:26,914 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.6193 Process Time: 0.427 Mem R(MA/MR): 24318 (21200/36094) [2025-04-28 15:34:28,156 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.0481 Process Time: 0.430 Mem R(MA/MR): 10086 (21200/36094) [2025-04-28 15:34:30,102 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0725 Process Time: 0.608 Mem R(MA/MR): 13908 (21200/36094) [2025-04-28 15:34:30,653 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2878 Process Time: 0.215 Mem R(MA/MR): 6534 (21200/36094) [2025-04-28 15:34:34,132 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.3526 Process Time: 0.545 Mem R(MA/MR): 28158 (21200/36094) [2025-04-28 15:34:35,832 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.6910 Process Time: 0.475 Mem R(MA/MR): 10834 (21200/36094) [2025-04-28 15:34:36,358 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1864 Process Time: 0.190 Mem R(MA/MR): 5506 (21200/36094) [2025-04-28 15:34:37,434 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9185 Process Time: 0.317 Mem R(MA/MR): 10346 (21200/36094) [2025-04-28 15:34:38,404 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.7279 Process Time: 0.277 Mem R(MA/MR): 8750 (21200/36094) [2025-04-28 15:34:38,899 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.1966 Process Time: 0.168 Mem R(MA/MR): 5492 (21200/36094) [2025-04-28 15:34:39,336 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.1392 Process Time: 0.154 Mem R(MA/MR): 5588 (21200/36094) [2025-04-28 15:34:39,913 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1524 Process Time: 0.222 Mem R(MA/MR): 6986 (21200/36094) [2025-04-28 15:34:40,518 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0378 Process Time: 0.187 Mem R(MA/MR): 5322 (21200/36094) [2025-04-28 15:34:42,609 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5316 Process Time: 0.313 Mem R(MA/MR): 14844 (21200/36094) [2025-04-28 15:34:49,325 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1054 Process Time: 1.118 Mem R(MA/MR): 20098 (21200/36094) [2025-04-28 15:35:00,011 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.9532 Process Time: 1.900 Mem R(MA/MR): 35490 (21200/36094) [2025-04-28 15:35:00,868 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.6923 Process Time: 0.245 Mem R(MA/MR): 5602 (21200/36094) [2025-04-28 15:35:04,309 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5526 Process Time: 0.981 Mem R(MA/MR): 13650 (21200/36094) [2025-04-28 15:35:08,987 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 15:35:08,987 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 15:35:08,987 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] table : 0.222 0.542 0.758 0.794 0.566 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] door : 0.378 0.661 0.831 0.839 0.658 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] ceiling lamp : 0.540 0.720 0.841 0.911 0.680 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] cabinet : 0.300 0.480 0.529 0.630 0.507 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] blinds : 0.526 0.696 0.822 0.762 0.696 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] curtain : 0.258 0.403 0.725 0.500 0.583 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] chair : 0.591 0.715 0.763 0.815 0.668 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] storage cabinet: 0.257 0.417 0.492 0.900 0.360 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] office chair : 0.486 0.517 0.561 0.717 0.688 [2025-04-28 15:35:08,987 INFO hook.py line 395 1619929] bookshelf : 0.319 0.641 0.641 0.692 0.818 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] whiteboard : 0.548 0.694 0.716 0.885 0.657 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] window : 0.067 0.182 0.551 0.438 0.231 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] box : 0.143 0.269 0.455 0.416 0.381 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] monitor : 0.537 0.654 0.742 0.956 0.614 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] shelf : 0.091 0.192 0.358 0.500 0.233 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] heater : 0.350 0.643 0.864 0.659 0.763 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] kitchen cabinet: 0.095 0.392 0.634 0.609 0.560 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] sofa : 0.381 0.568 0.733 0.458 0.917 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] bed : 0.279 0.602 0.750 0.833 0.625 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] trash can : 0.509 0.655 0.714 0.767 0.708 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] book : 0.007 0.017 0.054 0.157 0.075 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] plant : 0.402 0.544 0.715 0.818 0.500 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] blanket : 0.427 0.661 0.662 1.000 0.636 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] tv : 0.659 0.803 0.803 0.833 0.833 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] computer tower : 0.217 0.322 0.567 0.600 0.357 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] refrigerator : 0.176 0.333 0.333 1.000 0.333 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] jacket : 0.136 0.277 0.361 0.714 0.455 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] sink : 0.281 0.487 0.812 0.778 0.636 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] bag : 0.139 0.206 0.301 0.400 0.370 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] picture : 0.167 0.354 0.409 0.600 0.385 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] pillow : 0.578 0.817 0.851 1.000 0.684 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] towel : 0.159 0.270 0.536 0.611 0.289 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] suitcase : 0.502 0.625 0.625 0.800 0.571 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] backpack : 0.412 0.517 0.517 0.636 0.538 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] crate : 0.062 0.207 0.466 0.462 0.545 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] keyboard : 0.319 0.403 0.568 0.442 0.487 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] toilet : 0.757 0.861 1.000 0.889 0.889 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] printer : 0.133 0.195 0.206 0.571 0.444 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] poster : 0.002 0.019 0.028 0.333 0.111 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] painting : 0.077 0.083 0.100 0.167 1.000 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] microwave : 0.285 0.538 0.875 0.833 0.625 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] shoes : 0.142 0.248 0.473 0.545 0.293 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] socket : 0.172 0.410 0.593 0.638 0.429 [2025-04-28 15:35:08,988 INFO hook.py line 395 1619929] bottle : 0.091 0.177 0.272 0.476 0.241 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] bucket : 0.081 0.081 0.084 0.200 0.286 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] cushion : 0.197 0.203 0.203 0.600 0.500 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.012 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] telephone : 0.254 0.517 0.565 0.900 0.529 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] laptop : 0.277 0.436 0.444 0.467 0.875 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] plant pot : 0.090 0.162 0.265 0.500 0.250 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] exhaust fan : 0.030 0.056 0.056 0.667 0.133 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] cup : 0.143 0.245 0.325 0.769 0.227 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] coat hanger : 0.104 0.250 0.250 1.000 0.250 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] light switch : 0.198 0.422 0.667 0.667 0.492 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] speaker : 0.217 0.324 0.402 0.400 0.545 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] kettle : 0.117 0.167 0.167 1.000 0.167 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] smoke detector : 0.622 0.828 0.829 1.000 0.792 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] power strip : 0.078 0.133 0.177 0.500 0.300 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] mouse : 0.445 0.632 0.679 0.909 0.625 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] cutting board : 0.083 0.208 0.500 0.667 0.500 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] toilet paper : 0.121 0.198 0.412 1.000 0.176 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] paper towel : 0.014 0.125 0.125 1.000 0.125 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] clock : 0.378 0.678 0.678 0.500 1.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] tap : 0.115 0.190 0.598 0.429 0.333 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] soap dispenser : 0.434 0.668 0.668 0.667 0.800 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] whiteboard eraser: 0.154 0.417 0.417 0.571 0.667 [2025-04-28 15:35:08,989 INFO hook.py line 395 1619929] toilet brush : 0.422 0.626 0.829 1.000 0.500 [2025-04-28 15:35:08,990 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,990 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.062 0.000 0.000 [2025-04-28 15:35:08,990 INFO hook.py line 395 1619929] stapler : 0.138 0.278 0.278 0.667 0.667 [2025-04-28 15:35:08,990 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 15:35:08,990 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 15:35:08,990 INFO hook.py line 404 1619929] average : 0.224 0.346 0.443 0.591 0.425 [2025-04-28 15:35:08,990 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 15:35:08,990 INFO hook.py line 480 1619929] Total Process Time: 21.652 s [2025-04-28 15:35:08,990 INFO hook.py line 481 1619929] Average Process Time: 434.852 ms [2025-04-28 15:35:08,990 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 15:35:09,040 INFO hook.py line 685 1619929] Currently Best AP50: 0.370 [2025-04-28 15:35:09,045 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:36:42,613 INFO hook.py line 650 1619929] Train: [121/512][50/242] Data 0.018 (0.034) Batch 1.440 (1.415) Remain 37:16:29 loss: 5.6022 Lr: 2.35829e-04 Mem R(MA/MR): 20566 (21200/36094) [2025-04-28 15:37:54,862 INFO hook.py line 650 1619929] Train: [121/512][100/242] Data 0.017 (0.025) Batch 1.466 (1.431) Remain 37:39:27 loss: 6.8222 Lr: 2.35717e-04 Mem R(MA/MR): 20568 (21200/36094) [2025-04-28 15:39:08,126 INFO hook.py line 650 1619929] Train: [121/512][150/242] Data 0.017 (0.022) Batch 1.297 (1.442) Remain 37:56:53 loss: 6.2511 Lr: 2.35605e-04 Mem R(MA/MR): 22454 (21200/36094) [2025-04-28 15:40:15,861 INFO hook.py line 650 1619929] Train: [121/512][200/242] Data 0.016 (0.021) Batch 1.352 (1.420) Remain 37:20:35 loss: 5.7742 Lr: 2.35493e-04 Mem R(MA/MR): 22454 (21200/36094) [2025-04-28 15:41:11,329 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4897 loss_mask: 0.0457 loss_dice: 2.4645 loss_score: 0.0000 loss_bbox: 0.0580 loss_sp_cls: 0.9979 loss: 6.4999 [2025-04-28 15:41:12,635 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:42:44,534 INFO hook.py line 650 1619929] Train: [122/512][50/242] Data 0.014 (0.016) Batch 1.344 (1.420) Remain 37:18:32 loss: 6.2468 Lr: 2.35287e-04 Mem R(MA/MR): 20202 (21200/36094) [2025-04-28 15:43:54,484 INFO hook.py line 650 1619929] Train: [122/512][100/242] Data 0.017 (0.016) Batch 1.526 (1.409) Remain 37:00:07 loss: 5.0765 Lr: 2.35175e-04 Mem R(MA/MR): 20206 (21200/36094) [2025-04-28 15:45:03,414 INFO hook.py line 650 1619929] Train: [122/512][150/242] Data 0.015 (0.016) Batch 1.323 (1.399) Remain 36:42:31 loss: 6.7561 Lr: 2.35063e-04 Mem R(MA/MR): 20206 (21200/36094) [2025-04-28 15:46:12,704 INFO hook.py line 650 1619929] Train: [122/512][200/242] Data 0.016 (0.016) Batch 1.355 (1.396) Remain 36:36:09 loss: 6.3662 Lr: 2.34951e-04 Mem R(MA/MR): 22748 (21200/36094) [2025-04-28 15:47:07,679 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4843 loss_mask: 0.0455 loss_dice: 2.4456 loss_score: 0.0000 loss_bbox: 0.0585 loss_sp_cls: 0.9836 loss: 6.4539 [2025-04-28 15:47:08,637 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:48:41,717 INFO hook.py line 650 1619929] Train: [123/512][50/242] Data 0.017 (0.017) Batch 1.620 (1.456) Remain 38:09:37 loss: 5.3567 Lr: 2.34745e-04 Mem R(MA/MR): 22304 (21200/36094) [2025-04-28 15:49:51,700 INFO hook.py line 650 1619929] Train: [123/512][100/242] Data 0.015 (0.016) Batch 1.386 (1.427) Remain 37:22:29 loss: 6.3561 Lr: 2.34633e-04 Mem R(MA/MR): 22304 (21200/36094) [2025-04-28 15:50:59,542 INFO hook.py line 650 1619929] Train: [123/512][150/242] Data 0.015 (0.016) Batch 1.242 (1.403) Remain 36:43:45 loss: 5.8013 Lr: 2.34521e-04 Mem R(MA/MR): 22304 (21200/36094) [2025-04-28 15:52:06,795 INFO hook.py line 650 1619929] Train: [123/512][200/242] Data 0.015 (0.016) Batch 1.212 (1.388) Remain 36:19:26 loss: 6.2945 Lr: 2.34409e-04 Mem R(MA/MR): 24178 (21200/36094) [2025-04-28 15:53:02,096 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4839 loss_mask: 0.0446 loss_dice: 2.4334 loss_score: 0.0000 loss_bbox: 0.0575 loss_sp_cls: 0.9864 loss: 6.4255 [2025-04-28 15:53:02,777 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 15:54:32,408 INFO hook.py line 650 1619929] Train: [124/512][50/242] Data 0.015 (0.016) Batch 1.440 (1.416) Remain 36:59:47 loss: 6.9773 Lr: 2.34203e-04 Mem R(MA/MR): 26078 (21200/36094) [2025-04-28 15:55:41,359 INFO hook.py line 650 1619929] Train: [124/512][100/242] Data 0.015 (0.016) Batch 1.206 (1.397) Remain 36:29:06 loss: 6.6931 Lr: 2.34091e-04 Mem R(MA/MR): 26090 (21200/36094) [2025-04-28 15:56:51,187 INFO hook.py line 650 1619929] Train: [124/512][150/242] Data 0.017 (0.016) Batch 1.560 (1.397) Remain 36:27:49 loss: 5.5640 Lr: 2.33979e-04 Mem R(MA/MR): 26096 (21200/36094) [2025-04-28 15:58:00,562 INFO hook.py line 650 1619929] Train: [124/512][200/242] Data 0.014 (0.016) Batch 1.270 (1.394) Remain 36:23:02 loss: 6.1198 Lr: 2.33867e-04 Mem R(MA/MR): 26096 (21200/36094) [2025-04-28 15:58:55,679 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4647 loss_mask: 0.0439 loss_dice: 2.3872 loss_score: 0.0000 loss_bbox: 0.0572 loss_sp_cls: 0.9688 loss: 6.2916 [2025-04-28 15:58:59,218 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:00:27,430 INFO hook.py line 650 1619929] Train: [125/512][50/242] Data 0.016 (0.018) Batch 1.505 (1.487) Remain 38:46:26 loss: 6.6610 Lr: 2.33661e-04 Mem R(MA/MR): 21730 (21200/36094) [2025-04-28 16:01:38,913 INFO hook.py line 650 1619929] Train: [125/512][100/242] Data 0.017 (0.018) Batch 1.481 (1.458) Remain 37:58:39 loss: 7.0669 Lr: 2.33549e-04 Mem R(MA/MR): 21734 (21200/36094) [2025-04-28 16:02:46,961 INFO hook.py line 650 1619929] Train: [125/512][150/242] Data 0.017 (0.017) Batch 1.355 (1.425) Remain 37:06:04 loss: 5.9028 Lr: 2.33437e-04 Mem R(MA/MR): 21754 (21200/36094) [2025-04-28 16:03:57,709 INFO hook.py line 650 1619929] Train: [125/512][200/242] Data 0.015 (0.017) Batch 1.285 (1.422) Remain 37:01:00 loss: 5.8123 Lr: 2.33325e-04 Mem R(MA/MR): 21754 (21200/36094) [2025-04-28 16:04:51,841 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4504 loss_mask: 0.0419 loss_dice: 2.3248 loss_score: 0.0000 loss_bbox: 0.0552 loss_sp_cls: 0.9463 loss: 6.1324 [2025-04-28 16:04:55,572 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:06:27,355 INFO hook.py line 650 1619929] Train: [126/512][50/242] Data 0.015 (0.017) Batch 1.237 (1.440) Remain 37:26:25 loss: 6.6968 Lr: 2.33119e-04 Mem R(MA/MR): 22128 (21200/36094) [2025-04-28 16:07:37,131 INFO hook.py line 650 1619929] Train: [126/512][100/242] Data 0.015 (0.017) Batch 1.554 (1.417) Remain 36:49:33 loss: 5.3123 Lr: 2.33007e-04 Mem R(MA/MR): 22128 (21200/36094) [2025-04-28 16:08:44,601 INFO hook.py line 650 1619929] Train: [126/512][150/242] Data 0.016 (0.017) Batch 1.244 (1.394) Remain 36:12:28 loss: 5.4307 Lr: 2.32895e-04 Mem R(MA/MR): 22128 (21200/36094) [2025-04-28 16:09:53,742 INFO hook.py line 650 1619929] Train: [126/512][200/242] Data 0.015 (0.017) Batch 1.450 (1.391) Remain 36:06:53 loss: 5.2763 Lr: 2.32783e-04 Mem R(MA/MR): 22128 (21200/36094) [2025-04-28 16:10:50,127 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4477 loss_mask: 0.0417 loss_dice: 2.3251 loss_score: 0.0000 loss_bbox: 0.0557 loss_sp_cls: 0.9409 loss: 6.1193 [2025-04-28 16:10:53,113 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:12:16,165 INFO hook.py line 650 1619929] Train: [127/512][50/242] Data 0.017 (0.017) Batch 1.350 (1.425) Remain 36:56:56 loss: 7.2089 Lr: 2.32576e-04 Mem R(MA/MR): 24066 (21200/36094) [2025-04-28 16:13:25,040 INFO hook.py line 650 1619929] Train: [127/512][100/242] Data 0.015 (0.017) Batch 1.349 (1.400) Remain 36:17:54 loss: 6.9981 Lr: 2.32464e-04 Mem R(MA/MR): 24066 (21200/36094) [2025-04-28 16:14:35,896 INFO hook.py line 650 1619929] Train: [127/512][150/242] Data 0.017 (0.017) Batch 1.282 (1.406) Remain 36:25:32 loss: 5.6908 Lr: 2.32352e-04 Mem R(MA/MR): 26330 (21200/36094) [2025-04-28 16:15:44,176 INFO hook.py line 650 1619929] Train: [127/512][200/242] Data 0.014 (0.016) Batch 1.368 (1.396) Remain 36:08:26 loss: 6.1973 Lr: 2.32240e-04 Mem R(MA/MR): 26330 (21200/36094) [2025-04-28 16:16:39,979 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4466 loss_mask: 0.0423 loss_dice: 2.3250 loss_score: 0.0000 loss_bbox: 0.0558 loss_sp_cls: 0.9358 loss: 6.1185 [2025-04-28 16:16:41,489 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:18:09,745 INFO hook.py line 650 1619929] Train: [128/512][50/242] Data 0.015 (0.017) Batch 1.517 (1.428) Remain 36:56:22 loss: 6.2553 Lr: 2.32034e-04 Mem R(MA/MR): 20464 (21200/36094) [2025-04-28 16:19:18,172 INFO hook.py line 650 1619929] Train: [128/512][100/242] Data 0.015 (0.016) Batch 1.403 (1.397) Remain 36:07:34 loss: 6.3065 Lr: 2.31922e-04 Mem R(MA/MR): 20464 (21200/36094) [2025-04-28 16:20:24,886 INFO hook.py line 650 1619929] Train: [128/512][150/242] Data 0.016 (0.016) Batch 1.395 (1.376) Remain 35:33:06 loss: 5.2096 Lr: 2.31810e-04 Mem R(MA/MR): 20464 (21200/36094) [2025-04-28 16:21:33,298 INFO hook.py line 650 1619929] Train: [128/512][200/242] Data 0.014 (0.016) Batch 1.282 (1.374) Remain 35:28:58 loss: 6.5323 Lr: 2.31697e-04 Mem R(MA/MR): 21114 (21200/36094) [2025-04-28 16:22:29,034 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4481 loss_mask: 0.0422 loss_dice: 2.3192 loss_score: 0.0000 loss_bbox: 0.0559 loss_sp_cls: 0.9445 loss: 6.1169 [2025-04-28 16:22:29,111 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 16:22:31,553 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.4592 Process Time: 0.301 Mem R(MA/MR): 4238 (21200/36094) [2025-04-28 16:22:33,003 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8683 Process Time: 0.442 Mem R(MA/MR): 7128 (21200/36094) [2025-04-28 16:22:34,647 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3609 Process Time: 0.630 Mem R(MA/MR): 9960 (21200/36094) [2025-04-28 16:22:42,368 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.7083 Process Time: 1.308 Mem R(MA/MR): 19506 (21200/36094) [2025-04-28 16:22:43,485 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6073 Process Time: 0.475 Mem R(MA/MR): 7154 (21200/36094) [2025-04-28 16:22:45,449 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7222 Process Time: 0.743 Mem R(MA/MR): 11440 (21200/36094) [2025-04-28 16:22:46,064 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0626 Process Time: 0.220 Mem R(MA/MR): 6244 (21200/36094) [2025-04-28 16:22:46,530 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.6999 Process Time: 0.160 Mem R(MA/MR): 4258 (21200/36094) [2025-04-28 16:22:47,375 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8156 Process Time: 0.225 Mem R(MA/MR): 11492 (21200/36094) [2025-04-28 16:22:48,914 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.2160 Process Time: 0.349 Mem R(MA/MR): 9802 (21200/36094) [2025-04-28 16:22:51,226 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0755 Process Time: 0.321 Mem R(MA/MR): 18836 (21200/36094) [2025-04-28 16:22:54,338 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.9961 Process Time: 0.847 Mem R(MA/MR): 15130 (21200/36094) [2025-04-28 16:22:55,587 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1373 Process Time: 0.365 Mem R(MA/MR): 9026 (21200/36094) [2025-04-28 16:22:55,915 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1077 Process Time: 0.118 Mem R(MA/MR): 5074 (21200/36094) [2025-04-28 16:22:58,899 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.5094 Process Time: 0.361 Mem R(MA/MR): 16382 (21200/36094) [2025-04-28 16:23:00,673 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.1923 Process Time: 0.453 Mem R(MA/MR): 14456 (21200/36094) [2025-04-28 16:23:01,840 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.8903 Process Time: 0.553 Mem R(MA/MR): 6588 (21200/36094) [2025-04-28 16:23:02,800 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.5210 Process Time: 0.342 Mem R(MA/MR): 8338 (21200/36094) [2025-04-28 16:23:04,179 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6374 Process Time: 0.217 Mem R(MA/MR): 6248 (21200/36094) [2025-04-28 16:23:05,594 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.5328 Process Time: 0.194 Mem R(MA/MR): 11534 (21200/36094) [2025-04-28 16:23:14,243 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.1489 Process Time: 0.809 Mem R(MA/MR): 23306 (21200/36094) [2025-04-28 16:23:14,866 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4790 Process Time: 0.212 Mem R(MA/MR): 6952 (21200/36094) [2025-04-28 16:23:23,555 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.0827 Process Time: 0.297 Mem R(MA/MR): 8506 (21200/36094) [2025-04-28 16:23:24,263 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.1318 Process Time: 0.187 Mem R(MA/MR): 5552 (21200/36094) [2025-04-28 16:23:25,213 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2284 Process Time: 0.259 Mem R(MA/MR): 9590 (21200/36094) [2025-04-28 16:23:32,868 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.2132 Process Time: 1.618 Mem R(MA/MR): 31592 (21200/36094) [2025-04-28 16:23:34,527 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.6872 Process Time: 0.230 Mem R(MA/MR): 10410 (21200/36094) [2025-04-28 16:23:36,316 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.6636 Process Time: 0.624 Mem R(MA/MR): 8942 (21200/36094) [2025-04-28 16:23:40,959 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9061 Process Time: 0.699 Mem R(MA/MR): 17120 (21200/36094) [2025-04-28 16:23:41,686 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3231 Process Time: 0.161 Mem R(MA/MR): 7782 (21200/36094) [2025-04-28 16:23:45,155 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.6483 Process Time: 0.299 Mem R(MA/MR): 20420 (21200/36094) [2025-04-28 16:23:45,916 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3718 Process Time: 0.206 Mem R(MA/MR): 4166 (21200/36094) [2025-04-28 16:23:51,058 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.0833 Process Time: 0.670 Mem R(MA/MR): 24792 (21200/36094) [2025-04-28 16:23:52,095 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6417 Process Time: 0.220 Mem R(MA/MR): 10084 (21200/36094) [2025-04-28 16:23:54,307 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.4868 Process Time: 0.515 Mem R(MA/MR): 13990 (21200/36094) [2025-04-28 16:23:55,110 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0319 Process Time: 0.273 Mem R(MA/MR): 6482 (21200/36094) [2025-04-28 16:23:59,167 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.6432 Process Time: 0.553 Mem R(MA/MR): 28360 (21200/36094) [2025-04-28 16:24:00,884 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5858 Process Time: 0.360 Mem R(MA/MR): 11012 (21200/36094) [2025-04-28 16:24:01,716 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2157 Process Time: 0.331 Mem R(MA/MR): 5612 (21200/36094) [2025-04-28 16:24:03,667 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7645 Process Time: 0.763 Mem R(MA/MR): 10450 (21200/36094) [2025-04-28 16:24:04,850 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.4498 Process Time: 0.340 Mem R(MA/MR): 9426 (21200/36094) [2025-04-28 16:24:05,686 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.6578 Process Time: 0.318 Mem R(MA/MR): 5668 (21200/36094) [2025-04-28 16:24:06,182 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7800 Process Time: 0.147 Mem R(MA/MR): 5714 (21200/36094) [2025-04-28 16:24:06,818 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.2360 Process Time: 0.166 Mem R(MA/MR): 6948 (21200/36094) [2025-04-28 16:24:07,399 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0243 Process Time: 0.130 Mem R(MA/MR): 5450 (21200/36094) [2025-04-28 16:24:09,817 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.2659 Process Time: 0.291 Mem R(MA/MR): 14852 (21200/36094) [2025-04-28 16:24:17,478 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.9942 Process Time: 1.404 Mem R(MA/MR): 20154 (21200/36094) [2025-04-28 16:24:27,734 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.4591 Process Time: 1.781 Mem R(MA/MR): 35700 (21200/36094) [2025-04-28 16:24:29,068 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.3855 Process Time: 0.408 Mem R(MA/MR): 5772 (21200/36094) [2025-04-28 16:24:31,501 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.9751 Process Time: 0.560 Mem R(MA/MR): 13600 (21200/36094) [2025-04-28 16:24:35,621 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 16:24:35,621 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 16:24:35,621 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 16:24:35,621 INFO hook.py line 395 1619929] table : 0.239 0.588 0.796 0.777 0.588 [2025-04-28 16:24:35,621 INFO hook.py line 395 1619929] door : 0.438 0.753 0.883 0.891 0.722 [2025-04-28 16:24:35,621 INFO hook.py line 395 1619929] ceiling lamp : 0.523 0.718 0.838 0.882 0.663 [2025-04-28 16:24:35,621 INFO hook.py line 395 1619929] cabinet : 0.319 0.463 0.502 0.571 0.478 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] blinds : 0.461 0.671 0.820 0.789 0.652 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] curtain : 0.249 0.457 0.755 0.667 0.667 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] chair : 0.578 0.717 0.771 0.758 0.705 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] storage cabinet: 0.186 0.385 0.540 0.519 0.560 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] office chair : 0.550 0.593 0.643 0.649 0.771 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] bookshelf : 0.223 0.579 0.617 0.667 0.727 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] whiteboard : 0.558 0.706 0.721 0.800 0.686 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] window : 0.078 0.217 0.567 0.512 0.231 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] box : 0.171 0.336 0.497 0.562 0.376 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] monitor : 0.544 0.697 0.772 0.907 0.700 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] shelf : 0.073 0.151 0.522 0.833 0.167 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] heater : 0.390 0.677 0.843 0.750 0.789 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] kitchen cabinet: 0.151 0.368 0.765 0.500 0.520 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] sofa : 0.347 0.602 0.880 0.667 0.833 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] bed : 0.257 0.574 0.785 0.833 0.625 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] trash can : 0.506 0.654 0.739 0.758 0.769 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] book : 0.018 0.034 0.059 0.214 0.082 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] plant : 0.323 0.552 0.618 0.647 0.611 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] blanket : 0.398 0.546 0.727 0.875 0.636 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] tv : 0.634 0.833 0.833 1.000 0.833 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] computer tower : 0.225 0.346 0.494 0.615 0.381 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] refrigerator : 0.150 0.353 0.353 1.000 0.333 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] jacket : 0.025 0.049 0.154 0.231 0.273 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] sink : 0.350 0.549 0.710 0.667 0.636 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] bag : 0.169 0.234 0.314 0.455 0.370 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] picture : 0.164 0.321 0.405 0.652 0.385 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] pillow : 0.526 0.777 0.819 0.933 0.737 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] towel : 0.151 0.227 0.471 0.406 0.342 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] suitcase : 0.047 0.056 0.056 0.333 0.286 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] backpack : 0.377 0.434 0.484 0.636 0.538 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] crate : 0.058 0.326 0.466 0.625 0.455 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] keyboard : 0.380 0.492 0.602 0.600 0.538 [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 16:24:35,622 INFO hook.py line 395 1619929] toilet : 0.751 0.889 1.000 1.000 0.889 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] printer : 0.222 0.324 0.454 0.600 0.333 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] poster : 0.000 0.003 0.007 0.056 0.111 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] painting : 0.031 0.033 0.050 0.067 1.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] microwave : 0.371 0.625 0.858 1.000 0.625 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] shoes : 0.145 0.257 0.553 0.600 0.366 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] socket : 0.182 0.415 0.608 0.663 0.450 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] bottle : 0.092 0.175 0.349 0.419 0.217 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] bucket : 0.080 0.149 0.297 0.375 0.429 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] cushion : 0.014 0.046 0.399 0.333 0.167 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] basket : 0.001 0.012 0.012 0.167 0.143 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] telephone : 0.118 0.300 0.462 0.368 0.412 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] laptop : 0.273 0.370 0.589 0.417 0.625 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] plant pot : 0.081 0.218 0.462 0.462 0.375 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] exhaust fan : 0.129 0.298 0.298 0.714 0.333 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] cup : 0.217 0.298 0.392 0.800 0.273 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] coat hanger : 0.146 0.533 0.750 0.600 0.750 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] light switch : 0.217 0.437 0.611 0.778 0.431 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] speaker : 0.229 0.310 0.437 1.000 0.273 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] table lamp : 0.448 0.500 0.500 1.000 0.500 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] smoke detector : 0.621 0.742 0.744 1.000 0.708 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] power strip : 0.147 0.224 0.233 1.000 0.200 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] paper bag : 0.096 0.100 0.125 0.200 1.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] mouse : 0.365 0.601 0.638 0.895 0.531 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] cutting board : 0.222 0.500 0.677 1.000 0.500 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] toilet paper : 0.145 0.283 0.513 0.625 0.294 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] paper towel : 0.019 0.021 0.125 0.333 0.125 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] clock : 0.503 0.903 0.903 0.750 1.000 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] pan : 0.194 0.250 0.396 1.000 0.250 [2025-04-28 16:24:35,623 INFO hook.py line 395 1619929] tap : 0.098 0.149 0.511 0.250 0.222 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] soap dispenser : 0.397 0.600 0.600 1.000 0.600 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.083 0.000 0.000 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] whiteboard eraser: 0.177 0.474 0.474 0.800 0.667 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] toilet brush : 0.453 0.803 0.974 0.833 0.833 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] spray bottle : 0.018 0.021 0.025 0.167 0.250 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] stapler : 0.037 0.333 0.333 1.000 0.333 [2025-04-28 16:24:35,624 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 16:24:35,624 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 16:24:35,624 INFO hook.py line 404 1619929] average : 0.223 0.358 0.475 0.579 0.440 [2025-04-28 16:24:35,624 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 16:24:35,624 INFO hook.py line 480 1619929] Total Process Time: 23.456 s [2025-04-28 16:24:35,624 INFO hook.py line 481 1619929] Average Process Time: 472.552 ms [2025-04-28 16:24:35,624 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 16:24:35,659 INFO hook.py line 685 1619929] Currently Best AP50: 0.370 [2025-04-28 16:24:35,663 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:26:02,945 INFO hook.py line 650 1619929] Train: [129/512][50/242] Data 0.017 (0.016) Batch 1.393 (1.387) Remain 35:47:10 loss: 5.3563 Lr: 2.31491e-04 Mem R(MA/MR): 19748 (21200/36094) [2025-04-28 16:27:13,199 INFO hook.py line 650 1619929] Train: [129/512][100/242] Data 0.015 (0.016) Batch 1.299 (1.396) Remain 36:00:22 loss: 5.6447 Lr: 2.31379e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 16:28:23,808 INFO hook.py line 650 1619929] Train: [129/512][150/242] Data 0.015 (0.017) Batch 1.325 (1.402) Remain 36:07:31 loss: 6.2934 Lr: 2.31267e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 16:29:33,962 INFO hook.py line 650 1619929] Train: [129/512][200/242] Data 0.014 (0.020) Batch 1.403 (1.402) Remain 36:06:53 loss: 5.8563 Lr: 2.31155e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 16:30:29,540 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4480 loss_mask: 0.0425 loss_dice: 2.3249 loss_score: 0.0000 loss_bbox: 0.0561 loss_sp_cls: 0.9425 loss: 6.1343 [2025-04-28 16:30:33,467 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:32:08,653 INFO hook.py line 650 1619929] Train: [130/512][50/242] Data 0.016 (0.016) Batch 1.420 (1.440) Remain 37:02:31 loss: 5.9127 Lr: 2.30948e-04 Mem R(MA/MR): 22580 (21200/36094) [2025-04-28 16:33:17,542 INFO hook.py line 650 1619929] Train: [130/512][100/242] Data 0.018 (0.016) Batch 1.508 (1.408) Remain 36:12:11 loss: 5.2490 Lr: 2.30836e-04 Mem R(MA/MR): 22600 (21200/36094) [2025-04-28 16:34:28,442 INFO hook.py line 650 1619929] Train: [130/512][150/242] Data 0.017 (0.017) Batch 1.392 (1.411) Remain 36:16:25 loss: 4.9911 Lr: 2.30726e-04 Mem R(MA/MR): 22600 (21200/36094) [2025-04-28 16:35:37,773 INFO hook.py line 650 1619929] Train: [130/512][200/242] Data 0.015 (0.017) Batch 1.229 (1.405) Remain 36:05:39 loss: 6.5686 Lr: 2.30614e-04 Mem R(MA/MR): 22600 (21200/36094) [2025-04-28 16:36:32,531 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4666 loss_mask: 0.0449 loss_dice: 2.3816 loss_score: 0.0000 loss_bbox: 0.0564 loss_sp_cls: 0.9691 loss: 6.2791 [2025-04-28 16:36:34,735 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:38:06,160 INFO hook.py line 650 1619929] Train: [131/512][50/242] Data 0.018 (0.016) Batch 1.252 (1.391) Remain 35:42:35 loss: 5.5854 Lr: 2.30408e-04 Mem R(MA/MR): 21336 (21200/36094) [2025-04-28 16:39:14,676 INFO hook.py line 650 1619929] Train: [131/512][100/242] Data 0.016 (0.017) Batch 1.397 (1.381) Remain 35:24:42 loss: 6.0051 Lr: 2.30295e-04 Mem R(MA/MR): 21336 (21200/36094) [2025-04-28 16:40:24,040 INFO hook.py line 650 1619929] Train: [131/512][150/242] Data 0.016 (0.016) Batch 1.411 (1.383) Remain 35:27:05 loss: 5.0159 Lr: 2.30183e-04 Mem R(MA/MR): 21932 (21200/36094) [2025-04-28 16:41:31,465 INFO hook.py line 650 1619929] Train: [131/512][200/242] Data 0.016 (0.016) Batch 1.397 (1.374) Remain 35:12:32 loss: 7.2978 Lr: 2.30071e-04 Mem R(MA/MR): 21938 (21200/36094) [2025-04-28 16:42:25,888 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4893 loss_mask: 0.0469 loss_dice: 2.4713 loss_score: 0.0000 loss_bbox: 0.0587 loss_sp_cls: 0.9953 loss: 6.5202 [2025-04-28 16:42:27,363 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:43:58,951 INFO hook.py line 650 1619929] Train: [132/512][50/242] Data 0.015 (0.017) Batch 1.446 (1.428) Remain 36:33:22 loss: 6.0333 Lr: 2.29865e-04 Mem R(MA/MR): 24062 (21200/36094) [2025-04-28 16:45:09,578 INFO hook.py line 650 1619929] Train: [132/512][100/242] Data 0.015 (0.017) Batch 1.322 (1.420) Remain 36:19:51 loss: 6.5303 Lr: 2.29752e-04 Mem R(MA/MR): 24084 (21200/36094) [2025-04-28 16:46:20,850 INFO hook.py line 650 1619929] Train: [132/512][150/242] Data 0.016 (0.017) Batch 1.463 (1.422) Remain 36:21:28 loss: 5.0064 Lr: 2.29640e-04 Mem R(MA/MR): 24094 (21200/36094) [2025-04-28 16:47:31,644 INFO hook.py line 650 1619929] Train: [132/512][200/242] Data 0.014 (0.016) Batch 1.343 (1.420) Remain 36:17:56 loss: 6.2957 Lr: 2.29528e-04 Mem R(MA/MR): 24094 (21200/36094) [2025-04-28 16:48:25,023 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4918 loss_mask: 0.0466 loss_dice: 2.4477 loss_score: 0.0000 loss_bbox: 0.0589 loss_sp_cls: 0.9928 loss: 6.4879 [2025-04-28 16:48:28,611 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:49:58,865 INFO hook.py line 650 1619929] Train: [133/512][50/242] Data 0.015 (0.017) Batch 1.326 (1.429) Remain 36:29:42 loss: 6.3181 Lr: 2.29321e-04 Mem R(MA/MR): 22126 (21200/36094) [2025-04-28 16:51:08,999 INFO hook.py line 650 1619929] Train: [133/512][100/242] Data 0.017 (0.017) Batch 1.399 (1.416) Remain 36:07:23 loss: 6.1231 Lr: 2.29209e-04 Mem R(MA/MR): 22130 (21200/36094) [2025-04-28 16:52:17,549 INFO hook.py line 650 1619929] Train: [133/512][150/242] Data 0.015 (0.016) Batch 1.443 (1.400) Remain 35:42:57 loss: 6.3089 Lr: 2.29097e-04 Mem R(MA/MR): 25920 (21200/36094) [2025-04-28 16:53:27,823 INFO hook.py line 650 1619929] Train: [133/512][200/242] Data 0.016 (0.016) Batch 1.286 (1.402) Remain 35:43:44 loss: 6.3926 Lr: 2.28984e-04 Mem R(MA/MR): 25920 (21200/36094) [2025-04-28 16:54:22,481 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4884 loss_mask: 0.0460 loss_dice: 2.4548 loss_score: 0.0000 loss_bbox: 0.0586 loss_sp_cls: 0.9803 loss: 6.4813 [2025-04-28 16:54:22,991 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 16:55:48,284 INFO hook.py line 650 1619929] Train: [134/512][50/242] Data 0.016 (0.017) Batch 1.404 (1.451) Remain 36:56:22 loss: 7.0490 Lr: 2.28778e-04 Mem R(MA/MR): 21582 (21200/36094) [2025-04-28 16:56:55,292 INFO hook.py line 650 1619929] Train: [134/512][100/242] Data 0.017 (0.016) Batch 1.431 (1.394) Remain 35:28:08 loss: 5.3979 Lr: 2.28666e-04 Mem R(MA/MR): 21582 (21200/36094) [2025-04-28 16:58:04,557 INFO hook.py line 650 1619929] Train: [134/512][150/242] Data 0.016 (0.016) Batch 1.427 (1.391) Remain 35:22:37 loss: 6.6051 Lr: 2.28553e-04 Mem R(MA/MR): 23786 (21200/36094) [2025-04-28 16:59:12,860 INFO hook.py line 650 1619929] Train: [134/512][200/242] Data 0.015 (0.017) Batch 1.327 (1.385) Remain 35:11:51 loss: 5.4631 Lr: 2.28441e-04 Mem R(MA/MR): 23792 (21200/36094) [2025-04-28 17:00:09,317 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4801 loss_mask: 0.0451 loss_dice: 2.4321 loss_score: 0.0000 loss_bbox: 0.0570 loss_sp_cls: 0.9871 loss: 6.4008 [2025-04-28 17:00:10,151 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:01:34,447 INFO hook.py line 650 1619929] Train: [135/512][50/242] Data 0.016 (0.017) Batch 1.325 (1.456) Remain 36:58:43 loss: 6.3083 Lr: 2.28234e-04 Mem R(MA/MR): 21284 (21200/36094) [2025-04-28 17:02:45,125 INFO hook.py line 650 1619929] Train: [135/512][100/242] Data 0.015 (0.016) Batch 1.422 (1.434) Remain 36:24:08 loss: 6.7970 Lr: 2.28122e-04 Mem R(MA/MR): 24232 (21200/36094) [2025-04-28 17:03:55,894 INFO hook.py line 650 1619929] Train: [135/512][150/242] Data 0.017 (0.016) Batch 1.406 (1.428) Remain 36:13:12 loss: 6.7904 Lr: 2.28010e-04 Mem R(MA/MR): 25950 (21200/36094) [2025-04-28 17:05:04,246 INFO hook.py line 650 1619929] Train: [135/512][200/242] Data 0.016 (0.016) Batch 1.348 (1.412) Remain 35:48:34 loss: 6.3438 Lr: 2.27897e-04 Mem R(MA/MR): 28230 (21200/36094) [2025-04-28 17:05:58,780 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4768 loss_mask: 0.0449 loss_dice: 2.4348 loss_score: 0.0000 loss_bbox: 0.0577 loss_sp_cls: 0.9785 loss: 6.4018 [2025-04-28 17:06:01,116 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:07:30,775 INFO hook.py line 650 1619929] Train: [136/512][50/242] Data 0.015 (0.016) Batch 1.268 (1.400) Remain 35:26:55 loss: 7.6855 Lr: 2.27691e-04 Mem R(MA/MR): 22164 (21200/36094) [2025-04-28 17:08:38,714 INFO hook.py line 650 1619929] Train: [136/512][100/242] Data 0.017 (0.016) Batch 1.454 (1.379) Remain 34:53:52 loss: 6.1502 Lr: 2.27578e-04 Mem R(MA/MR): 22164 (21200/36094) [2025-04-28 17:09:48,048 INFO hook.py line 650 1619929] Train: [136/512][150/242] Data 0.016 (0.017) Batch 1.385 (1.381) Remain 34:56:54 loss: 6.3402 Lr: 2.27466e-04 Mem R(MA/MR): 22196 (21200/36094) [2025-04-28 17:10:55,431 INFO hook.py line 650 1619929] Train: [136/512][200/242] Data 0.016 (0.017) Batch 1.274 (1.373) Remain 34:42:48 loss: 6.0029 Lr: 2.27354e-04 Mem R(MA/MR): 22196 (21200/36094) [2025-04-28 17:11:49,479 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4656 loss_mask: 0.0446 loss_dice: 2.4025 loss_score: 0.0000 loss_bbox: 0.0571 loss_sp_cls: 0.9659 loss: 6.3097 [2025-04-28 17:11:51,029 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 17:11:53,552 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.6337 Process Time: 0.310 Mem R(MA/MR): 4072 (21200/36094) [2025-04-28 17:11:54,945 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.3236 Process Time: 0.453 Mem R(MA/MR): 6808 (21200/36094) [2025-04-28 17:11:56,656 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5062 Process Time: 0.600 Mem R(MA/MR): 9400 (21200/36094) [2025-04-28 17:12:04,537 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.0166 Process Time: 1.631 Mem R(MA/MR): 19586 (21200/36094) [2025-04-28 17:12:05,865 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6094 Process Time: 0.569 Mem R(MA/MR): 7004 (21200/36094) [2025-04-28 17:12:07,647 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.9919 Process Time: 0.623 Mem R(MA/MR): 11022 (21200/36094) [2025-04-28 17:12:08,411 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2498 Process Time: 0.323 Mem R(MA/MR): 5992 (21200/36094) [2025-04-28 17:12:08,869 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.9887 Process Time: 0.197 Mem R(MA/MR): 4090 (21200/36094) [2025-04-28 17:12:09,733 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.4773 Process Time: 0.226 Mem R(MA/MR): 11054 (21200/36094) [2025-04-28 17:12:11,009 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.5280 Process Time: 0.251 Mem R(MA/MR): 8968 (21200/36094) [2025-04-28 17:12:13,240 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.0818 Process Time: 0.292 Mem R(MA/MR): 18346 (21200/36094) [2025-04-28 17:12:16,634 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.4799 Process Time: 0.899 Mem R(MA/MR): 15150 (21200/36094) [2025-04-28 17:12:17,722 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.8099 Process Time: 0.212 Mem R(MA/MR): 8314 (21200/36094) [2025-04-28 17:12:18,152 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.5632 Process Time: 0.182 Mem R(MA/MR): 4464 (21200/36094) [2025-04-28 17:12:21,576 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.3485 Process Time: 0.282 Mem R(MA/MR): 16080 (21200/36094) [2025-04-28 17:12:24,011 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0453 Process Time: 0.849 Mem R(MA/MR): 14290 (21200/36094) [2025-04-28 17:12:25,199 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7835 Process Time: 0.488 Mem R(MA/MR): 6354 (21200/36094) [2025-04-28 17:12:25,974 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.3644 Process Time: 0.211 Mem R(MA/MR): 7936 (21200/36094) [2025-04-28 17:12:27,334 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5514 Process Time: 0.231 Mem R(MA/MR): 5964 (21200/36094) [2025-04-28 17:12:28,851 INFO hook.py line 449 1619929] Test: [20/50] Loss 7.7005 Process Time: 0.208 Mem R(MA/MR): 11172 (21200/36094) [2025-04-28 17:12:36,772 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.6240 Process Time: 0.842 Mem R(MA/MR): 23524 (21200/36094) [2025-04-28 17:12:37,330 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2217 Process Time: 0.157 Mem R(MA/MR): 6594 (21200/36094) [2025-04-28 17:12:46,879 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.2874 Process Time: 0.277 Mem R(MA/MR): 8096 (21200/36094) [2025-04-28 17:12:47,461 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0818 Process Time: 0.206 Mem R(MA/MR): 5088 (21200/36094) [2025-04-28 17:12:49,017 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.5234 Process Time: 0.735 Mem R(MA/MR): 9086 (21200/36094) [2025-04-28 17:12:56,298 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.0227 Process Time: 1.472 Mem R(MA/MR): 31076 (21200/36094) [2025-04-28 17:12:59,038 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.3880 Process Time: 0.870 Mem R(MA/MR): 9612 (21200/36094) [2025-04-28 17:13:00,460 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5337 Process Time: 0.449 Mem R(MA/MR): 8592 (21200/36094) [2025-04-28 17:13:04,808 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.7634 Process Time: 0.286 Mem R(MA/MR): 16700 (21200/36094) [2025-04-28 17:13:05,651 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.5491 Process Time: 0.241 Mem R(MA/MR): 7404 (21200/36094) [2025-04-28 17:13:10,176 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.2664 Process Time: 1.184 Mem R(MA/MR): 20262 (21200/36094) [2025-04-28 17:13:10,458 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.5127 Process Time: 0.112 Mem R(MA/MR): 3884 (21200/36094) [2025-04-28 17:13:14,410 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.7311 Process Time: 0.377 Mem R(MA/MR): 24470 (21200/36094) [2025-04-28 17:13:16,481 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7294 Process Time: 0.872 Mem R(MA/MR): 9518 (21200/36094) [2025-04-28 17:13:18,388 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7824 Process Time: 0.583 Mem R(MA/MR): 13752 (21200/36094) [2025-04-28 17:13:19,062 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.5307 Process Time: 0.255 Mem R(MA/MR): 6286 (21200/36094) [2025-04-28 17:13:22,152 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8837 Process Time: 0.400 Mem R(MA/MR): 28290 (21200/36094) [2025-04-28 17:13:23,482 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.1855 Process Time: 0.244 Mem R(MA/MR): 10356 (21200/36094) [2025-04-28 17:13:24,804 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.5131 Process Time: 0.600 Mem R(MA/MR): 5178 (21200/36094) [2025-04-28 17:13:26,288 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.1015 Process Time: 0.473 Mem R(MA/MR): 9876 (21200/36094) [2025-04-28 17:13:27,779 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.5552 Process Time: 0.521 Mem R(MA/MR): 8740 (21200/36094) [2025-04-28 17:13:28,275 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.0184 Process Time: 0.136 Mem R(MA/MR): 5232 (21200/36094) [2025-04-28 17:13:28,743 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.0744 Process Time: 0.144 Mem R(MA/MR): 5256 (21200/36094) [2025-04-28 17:13:29,370 INFO hook.py line 449 1619929] Test: [44/50] Loss 6.9843 Process Time: 0.171 Mem R(MA/MR): 6808 (21200/36094) [2025-04-28 17:13:30,105 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.2734 Process Time: 0.203 Mem R(MA/MR): 4998 (21200/36094) [2025-04-28 17:13:32,384 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.6328 Process Time: 0.235 Mem R(MA/MR): 14264 (21200/36094) [2025-04-28 17:13:40,545 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.5152 Process Time: 1.471 Mem R(MA/MR): 20026 (21200/36094) [2025-04-28 17:13:50,288 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9879 Process Time: 1.865 Mem R(MA/MR): 35122 (21200/36094) [2025-04-28 17:13:52,238 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.1439 Process Time: 0.568 Mem R(MA/MR): 5490 (21200/36094) [2025-04-28 17:13:54,951 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.6032 Process Time: 0.497 Mem R(MA/MR): 13674 (21200/36094) [2025-04-28 17:13:59,045 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 17:13:59,045 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 17:13:59,045 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 17:13:59,045 INFO hook.py line 395 1619929] table : 0.221 0.511 0.742 0.686 0.596 [2025-04-28 17:13:59,045 INFO hook.py line 395 1619929] door : 0.417 0.766 0.889 0.903 0.709 [2025-04-28 17:13:59,045 INFO hook.py line 395 1619929] ceiling lamp : 0.516 0.742 0.865 0.814 0.751 [2025-04-28 17:13:59,045 INFO hook.py line 395 1619929] cabinet : 0.299 0.450 0.493 0.447 0.507 [2025-04-28 17:13:59,045 INFO hook.py line 395 1619929] blinds : 0.343 0.499 0.743 0.640 0.696 [2025-04-28 17:13:59,045 INFO hook.py line 395 1619929] curtain : 0.352 0.641 0.652 0.556 0.833 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] chair : 0.593 0.731 0.766 0.763 0.738 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] storage cabinet: 0.188 0.297 0.464 0.500 0.360 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] office chair : 0.487 0.517 0.517 0.721 0.646 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] bookshelf : 0.242 0.578 0.664 0.857 0.545 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] whiteboard : 0.412 0.613 0.669 0.840 0.600 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] window : 0.098 0.269 0.649 0.431 0.341 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] box : 0.154 0.299 0.481 0.500 0.365 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] monitor : 0.584 0.765 0.817 0.914 0.757 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] shelf : 0.057 0.149 0.401 0.471 0.267 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] heater : 0.340 0.661 0.784 0.778 0.737 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] kitchen cabinet: 0.137 0.342 0.679 0.450 0.360 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] sofa : 0.530 0.731 0.955 0.900 0.750 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] bed : 0.136 0.451 0.750 0.667 0.500 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] trash can : 0.571 0.691 0.741 0.781 0.769 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] book : 0.009 0.025 0.070 0.156 0.109 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] plant : 0.431 0.601 0.601 0.917 0.611 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] blanket : 0.389 0.618 0.725 0.750 0.545 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] tv : 0.734 0.833 1.000 1.000 0.833 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] computer tower : 0.181 0.276 0.570 0.467 0.333 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] refrigerator : 0.221 0.364 0.367 1.000 0.333 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] jacket : 0.049 0.143 0.278 0.294 0.455 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] sink : 0.427 0.791 0.909 0.857 0.818 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] bag : 0.127 0.170 0.230 0.316 0.222 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] picture : 0.131 0.321 0.423 0.425 0.436 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] pillow : 0.555 0.793 0.793 0.933 0.737 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] towel : 0.141 0.302 0.511 0.421 0.421 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] suitcase : 0.245 0.386 0.386 0.556 0.714 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] backpack : 0.394 0.490 0.490 0.667 0.615 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] crate : 0.101 0.477 0.477 1.000 0.364 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] keyboard : 0.436 0.595 0.655 0.852 0.590 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] toilet : 0.753 0.889 1.000 1.000 0.889 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] printer : 0.211 0.305 0.341 1.000 0.222 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.003 0.000 0.000 [2025-04-28 17:13:59,046 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] microwave : 0.470 0.750 0.875 1.000 0.750 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] shoes : 0.154 0.265 0.535 0.682 0.366 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] socket : 0.158 0.380 0.618 0.536 0.479 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] bottle : 0.146 0.232 0.292 0.391 0.301 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] bucket : 0.037 0.048 0.054 0.111 0.714 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] cushion : 0.019 0.167 0.167 1.000 0.167 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] basket : 0.004 0.012 0.014 0.167 0.143 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] telephone : 0.228 0.512 0.637 1.000 0.412 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] laptop : 0.395 0.461 0.459 0.556 0.625 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] plant pot : 0.182 0.436 0.453 0.600 0.562 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] exhaust fan : 0.006 0.017 0.017 0.500 0.067 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] cup : 0.201 0.326 0.393 0.789 0.341 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] coat hanger : 0.194 0.500 0.750 1.000 0.500 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] light switch : 0.234 0.459 0.637 0.756 0.477 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] speaker : 0.481 0.593 0.593 0.875 0.636 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] table lamp : 0.569 1.000 1.000 1.000 1.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] kettle : 0.189 0.221 0.221 0.400 0.333 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] smoke detector : 0.653 0.840 0.848 0.905 0.792 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] power strip : 0.020 0.046 0.057 0.167 0.300 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] mouse : 0.407 0.597 0.597 0.778 0.656 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] cutting board : 0.328 0.613 0.613 1.000 0.500 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] toilet paper : 0.124 0.257 0.320 0.625 0.294 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] paper towel : 0.034 0.056 0.250 0.250 0.250 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] clock : 0.517 0.903 0.903 0.750 1.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] tap : 0.162 0.283 0.556 0.600 0.333 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,047 INFO hook.py line 395 1619929] soap dispenser : 0.378 0.400 0.400 1.000 0.400 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] bowl : 0.019 0.042 0.056 0.250 0.333 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] whiteboard eraser: 0.213 0.514 0.519 0.600 0.500 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] toilet brush : 0.560 0.766 0.955 1.000 0.667 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] spray bottle : 0.038 0.091 0.119 0.250 0.500 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] headphones : 0.167 0.500 0.500 1.000 0.500 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] stapler : 0.005 0.042 0.111 0.250 0.333 [2025-04-28 17:13:59,048 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 17:13:59,048 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 17:13:59,048 INFO hook.py line 404 1619929] average : 0.238 0.383 0.470 0.598 0.443 [2025-04-28 17:13:59,048 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 17:13:59,048 INFO hook.py line 480 1619929] Total Process Time: 25.483 s [2025-04-28 17:13:59,048 INFO hook.py line 481 1619929] Average Process Time: 513.736 ms [2025-04-28 17:13:59,048 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 17:13:59,099 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.383 [2025-04-28 17:13:59,104 INFO hook.py line 685 1619929] Currently Best AP50: 0.383 [2025-04-28 17:13:59,104 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:15:26,536 INFO hook.py line 650 1619929] Train: [137/512][50/242] Data 0.017 (0.017) Batch 1.336 (1.412) Remain 35:39:57 loss: 6.6891 Lr: 2.27147e-04 Mem R(MA/MR): 23726 (21200/36094) [2025-04-28 17:16:35,747 INFO hook.py line 650 1619929] Train: [137/512][100/242] Data 0.015 (0.023) Batch 1.412 (1.398) Remain 35:17:12 loss: 5.8956 Lr: 2.27034e-04 Mem R(MA/MR): 23750 (21200/36094) [2025-04-28 17:17:44,569 INFO hook.py line 650 1619929] Train: [137/512][150/242] Data 0.015 (0.021) Batch 1.407 (1.390) Remain 35:05:07 loss: 7.3953 Lr: 2.26922e-04 Mem R(MA/MR): 23750 (21200/36094) [2025-04-28 17:18:55,648 INFO hook.py line 650 1619929] Train: [137/512][200/242] Data 0.016 (0.020) Batch 1.523 (1.398) Remain 35:15:57 loss: 5.6755 Lr: 2.26810e-04 Mem R(MA/MR): 23750 (21200/36094) [2025-04-28 17:19:50,148 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4667 loss_mask: 0.0449 loss_dice: 2.3952 loss_score: 0.0000 loss_bbox: 0.0574 loss_sp_cls: 0.9674 loss: 6.3061 [2025-04-28 17:19:50,488 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:21:21,185 INFO hook.py line 650 1619929] Train: [138/512][50/242] Data 0.016 (0.018) Batch 1.459 (1.441) Remain 36:17:48 loss: 5.1972 Lr: 2.26603e-04 Mem R(MA/MR): 27384 (21200/36094) [2025-04-28 17:22:29,881 INFO hook.py line 650 1619929] Train: [138/512][100/242] Data 0.018 (0.017) Batch 1.301 (1.406) Remain 35:24:38 loss: 6.5682 Lr: 2.26490e-04 Mem R(MA/MR): 27384 (21200/36094) [2025-04-28 17:23:40,003 INFO hook.py line 650 1619929] Train: [138/512][150/242] Data 0.014 (0.017) Batch 1.309 (1.405) Remain 35:21:30 loss: 7.0381 Lr: 2.26378e-04 Mem R(MA/MR): 27386 (21200/36094) [2025-04-28 17:24:47,175 INFO hook.py line 650 1619929] Train: [138/512][200/242] Data 0.015 (0.017) Batch 1.279 (1.389) Remain 34:56:45 loss: 6.8455 Lr: 2.26266e-04 Mem R(MA/MR): 27386 (21200/36094) [2025-04-28 17:25:42,273 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4683 loss_mask: 0.0453 loss_dice: 2.3873 loss_score: 0.0000 loss_bbox: 0.0576 loss_sp_cls: 0.9651 loss: 6.3112 [2025-04-28 17:25:44,655 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:27:17,031 INFO hook.py line 650 1619929] Train: [139/512][50/242] Data 0.015 (0.017) Batch 1.390 (1.432) Remain 35:59:17 loss: 6.8323 Lr: 2.26061e-04 Mem R(MA/MR): 19488 (21200/36094) [2025-04-28 17:28:28,002 INFO hook.py line 650 1619929] Train: [139/512][100/242] Data 0.016 (0.016) Batch 1.474 (1.426) Remain 35:48:06 loss: 6.0052 Lr: 2.25949e-04 Mem R(MA/MR): 19508 (21200/36094) [2025-04-28 17:29:37,564 INFO hook.py line 650 1619929] Train: [139/512][150/242] Data 0.017 (0.016) Batch 1.239 (1.414) Remain 35:29:20 loss: 6.8499 Lr: 2.25836e-04 Mem R(MA/MR): 19508 (21200/36094) [2025-04-28 17:30:46,486 INFO hook.py line 650 1619929] Train: [139/512][200/242] Data 0.016 (0.016) Batch 1.273 (1.405) Remain 35:14:36 loss: 4.9843 Lr: 2.25724e-04 Mem R(MA/MR): 20680 (21200/36094) [2025-04-28 17:31:40,353 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4639 loss_mask: 0.0433 loss_dice: 2.3602 loss_score: 0.0000 loss_bbox: 0.0569 loss_sp_cls: 0.9573 loss: 6.2376 [2025-04-28 17:31:41,862 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:33:10,430 INFO hook.py line 650 1619929] Train: [140/512][50/242] Data 0.027 (0.016) Batch 1.434 (1.433) Remain 35:55:06 loss: 7.2975 Lr: 2.25517e-04 Mem R(MA/MR): 21268 (21200/36094) [2025-04-28 17:34:19,372 INFO hook.py line 650 1619929] Train: [140/512][100/242] Data 0.017 (0.016) Batch 1.247 (1.405) Remain 35:11:45 loss: 5.6206 Lr: 2.25404e-04 Mem R(MA/MR): 24752 (21200/36094) [2025-04-28 17:35:28,478 INFO hook.py line 650 1619929] Train: [140/512][150/242] Data 0.016 (0.016) Batch 1.297 (1.397) Remain 34:58:45 loss: 6.8522 Lr: 2.25292e-04 Mem R(MA/MR): 26794 (21200/36094) [2025-04-28 17:36:39,037 INFO hook.py line 650 1619929] Train: [140/512][200/242] Data 0.014 (0.017) Batch 1.415 (1.401) Remain 35:02:52 loss: 6.4052 Lr: 2.25179e-04 Mem R(MA/MR): 26794 (21200/36094) [2025-04-28 17:37:33,657 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4612 loss_mask: 0.0451 loss_dice: 2.3887 loss_score: 0.0000 loss_bbox: 0.0577 loss_sp_cls: 0.9557 loss: 6.2805 [2025-04-28 17:37:33,866 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:39:05,039 INFO hook.py line 650 1619929] Train: [141/512][50/242] Data 0.016 (0.016) Batch 1.268 (1.431) Remain 35:45:18 loss: 6.5299 Lr: 2.24972e-04 Mem R(MA/MR): 22972 (21200/36094) [2025-04-28 17:40:13,451 INFO hook.py line 650 1619929] Train: [141/512][100/242] Data 0.015 (0.016) Batch 1.287 (1.398) Remain 34:55:55 loss: 6.5115 Lr: 2.24860e-04 Mem R(MA/MR): 22972 (21200/36094) [2025-04-28 17:41:22,811 INFO hook.py line 650 1619929] Train: [141/512][150/242] Data 0.017 (0.016) Batch 1.512 (1.395) Remain 34:49:01 loss: 6.8329 Lr: 2.24747e-04 Mem R(MA/MR): 25434 (21200/36094) [2025-04-28 17:42:30,711 INFO hook.py line 650 1619929] Train: [141/512][200/242] Data 0.014 (0.016) Batch 1.234 (1.385) Remain 34:33:56 loss: 6.2381 Lr: 2.24635e-04 Mem R(MA/MR): 25434 (21200/36094) [2025-04-28 17:43:25,365 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4598 loss_mask: 0.0458 loss_dice: 2.3636 loss_score: 0.0000 loss_bbox: 0.0574 loss_sp_cls: 0.9604 loss: 6.2431 [2025-04-28 17:43:28,542 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:44:53,206 INFO hook.py line 650 1619929] Train: [142/512][50/242] Data 0.015 (0.016) Batch 1.431 (1.408) Remain 35:05:24 loss: 6.3179 Lr: 2.24428e-04 Mem R(MA/MR): 22550 (21200/36094) [2025-04-28 17:46:01,237 INFO hook.py line 650 1619929] Train: [142/512][100/242] Data 0.016 (0.016) Batch 1.390 (1.383) Remain 34:27:52 loss: 7.1965 Lr: 2.24315e-04 Mem R(MA/MR): 22550 (21200/36094) [2025-04-28 17:47:11,414 INFO hook.py line 650 1619929] Train: [142/512][150/242] Data 0.015 (0.017) Batch 1.462 (1.390) Remain 34:36:54 loss: 6.1627 Lr: 2.24203e-04 Mem R(MA/MR): 24498 (21200/36094) [2025-04-28 17:48:20,485 INFO hook.py line 650 1619929] Train: [142/512][200/242] Data 0.015 (0.017) Batch 1.341 (1.388) Remain 34:32:24 loss: 6.0368 Lr: 2.24090e-04 Mem R(MA/MR): 24498 (21200/36094) [2025-04-28 17:49:14,649 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4634 loss_mask: 0.0442 loss_dice: 2.3724 loss_score: 0.0000 loss_bbox: 0.0565 loss_sp_cls: 0.9606 loss: 6.2518 [2025-04-28 17:49:15,129 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:50:40,166 INFO hook.py line 650 1619929] Train: [143/512][50/242] Data 0.017 (0.016) Batch 1.580 (1.447) Remain 35:58:44 loss: 7.2753 Lr: 2.23883e-04 Mem R(MA/MR): 20944 (21200/36094) [2025-04-28 17:51:49,029 INFO hook.py line 650 1619929] Train: [143/512][100/242] Data 0.015 (0.016) Batch 1.328 (1.411) Remain 35:03:40 loss: 5.0147 Lr: 2.23771e-04 Mem R(MA/MR): 22834 (21200/36094) [2025-04-28 17:52:59,510 INFO hook.py line 650 1619929] Train: [143/512][150/242] Data 0.017 (0.016) Batch 1.544 (1.411) Remain 35:01:39 loss: 6.5684 Lr: 2.23658e-04 Mem R(MA/MR): 22836 (21200/36094) [2025-04-28 17:54:08,770 INFO hook.py line 650 1619929] Train: [143/512][200/242] Data 0.015 (0.016) Batch 1.349 (1.404) Remain 34:50:52 loss: 6.9922 Lr: 2.23545e-04 Mem R(MA/MR): 24814 (21200/36094) [2025-04-28 17:55:03,359 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4584 loss_mask: 0.0445 loss_dice: 2.3607 loss_score: 0.0000 loss_bbox: 0.0566 loss_sp_cls: 0.9564 loss: 6.2196 [2025-04-28 17:55:03,534 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 17:56:34,302 INFO hook.py line 650 1619929] Train: [144/512][50/242] Data 0.015 (0.017) Batch 1.413 (1.405) Remain 34:50:12 loss: 6.5041 Lr: 2.23338e-04 Mem R(MA/MR): 23604 (21200/36094) [2025-04-28 17:57:43,532 INFO hook.py line 650 1619929] Train: [144/512][100/242] Data 0.016 (0.017) Batch 1.327 (1.395) Remain 34:33:12 loss: 6.0661 Lr: 2.23226e-04 Mem R(MA/MR): 23604 (21200/36094) [2025-04-28 17:58:53,817 INFO hook.py line 650 1619929] Train: [144/512][150/242] Data 0.016 (0.017) Batch 1.289 (1.398) Remain 34:37:40 loss: 7.3322 Lr: 2.23113e-04 Mem R(MA/MR): 23604 (21200/36094) [2025-04-28 18:00:03,560 INFO hook.py line 650 1619929] Train: [144/512][200/242] Data 0.015 (0.016) Batch 1.349 (1.397) Remain 34:35:12 loss: 6.0108 Lr: 2.23000e-04 Mem R(MA/MR): 23604 (21200/36094) [2025-04-28 18:00:56,676 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4541 loss_mask: 0.0431 loss_dice: 2.3501 loss_score: 0.0000 loss_bbox: 0.0572 loss_sp_cls: 0.9490 loss: 6.1971 [2025-04-28 18:00:56,980 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 18:00:59,266 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.6465 Process Time: 0.255 Mem R(MA/MR): 4252 (21200/36094) [2025-04-28 18:01:00,775 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1017 Process Time: 0.532 Mem R(MA/MR): 6938 (21200/36094) [2025-04-28 18:01:03,083 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.6711 Process Time: 1.102 Mem R(MA/MR): 10018 (21200/36094) [2025-04-28 18:01:10,843 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.5631 Process Time: 0.971 Mem R(MA/MR): 19948 (21200/36094) [2025-04-28 18:01:12,148 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.2257 Process Time: 0.461 Mem R(MA/MR): 6676 (21200/36094) [2025-04-28 18:01:13,511 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6247 Process Time: 0.327 Mem R(MA/MR): 11494 (21200/36094) [2025-04-28 18:01:14,003 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.6076 Process Time: 0.138 Mem R(MA/MR): 6262 (21200/36094) [2025-04-28 18:01:14,404 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4579 Process Time: 0.103 Mem R(MA/MR): 4264 (21200/36094) [2025-04-28 18:01:15,273 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0071 Process Time: 0.193 Mem R(MA/MR): 11750 (21200/36094) [2025-04-28 18:01:16,614 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.5459 Process Time: 0.248 Mem R(MA/MR): 9594 (21200/36094) [2025-04-28 18:01:19,121 INFO hook.py line 449 1619929] Test: [11/50] Loss 13.0533 Process Time: 0.502 Mem R(MA/MR): 18888 (21200/36094) [2025-04-28 18:01:22,234 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2127 Process Time: 0.804 Mem R(MA/MR): 15240 (21200/36094) [2025-04-28 18:01:23,341 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.5905 Process Time: 0.326 Mem R(MA/MR): 8722 (21200/36094) [2025-04-28 18:01:23,669 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.6622 Process Time: 0.109 Mem R(MA/MR): 4822 (21200/36094) [2025-04-28 18:01:26,146 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.8418 Process Time: 0.467 Mem R(MA/MR): 16560 (21200/36094) [2025-04-28 18:01:28,547 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3154 Process Time: 0.785 Mem R(MA/MR): 14648 (21200/36094) [2025-04-28 18:01:29,607 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7020 Process Time: 0.332 Mem R(MA/MR): 6660 (21200/36094) [2025-04-28 18:01:30,594 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1739 Process Time: 0.311 Mem R(MA/MR): 8266 (21200/36094) [2025-04-28 18:01:32,079 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.1668 Process Time: 0.205 Mem R(MA/MR): 6188 (21200/36094) [2025-04-28 18:01:33,701 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.8910 Process Time: 0.216 Mem R(MA/MR): 11590 (21200/36094) [2025-04-28 18:01:42,767 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.1079 Process Time: 0.460 Mem R(MA/MR): 23616 (21200/36094) [2025-04-28 18:01:43,395 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.1589 Process Time: 0.224 Mem R(MA/MR): 6762 (21200/36094) [2025-04-28 18:01:53,802 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.0057 Process Time: 0.498 Mem R(MA/MR): 8224 (21200/36094) [2025-04-28 18:01:54,776 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8614 Process Time: 0.353 Mem R(MA/MR): 5548 (21200/36094) [2025-04-28 18:01:55,876 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0892 Process Time: 0.317 Mem R(MA/MR): 9638 (21200/36094) [2025-04-28 18:02:03,254 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.5730 Process Time: 1.459 Mem R(MA/MR): 31510 (21200/36094) [2025-04-28 18:02:05,473 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.7862 Process Time: 0.647 Mem R(MA/MR): 10424 (21200/36094) [2025-04-28 18:02:06,622 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.8606 Process Time: 0.282 Mem R(MA/MR): 8976 (21200/36094) [2025-04-28 18:02:11,365 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0166 Process Time: 0.273 Mem R(MA/MR): 17092 (21200/36094) [2025-04-28 18:02:12,806 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3759 Process Time: 0.578 Mem R(MA/MR): 7834 (21200/36094) [2025-04-28 18:02:16,759 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.4026 Process Time: 0.526 Mem R(MA/MR): 20778 (21200/36094) [2025-04-28 18:02:17,015 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3718 Process Time: 0.103 Mem R(MA/MR): 4002 (21200/36094) [2025-04-28 18:02:20,724 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.7304 Process Time: 0.357 Mem R(MA/MR): 24806 (21200/36094) [2025-04-28 18:02:22,299 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9499 Process Time: 0.525 Mem R(MA/MR): 10204 (21200/36094) [2025-04-28 18:02:24,480 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.8295 Process Time: 0.658 Mem R(MA/MR): 14026 (21200/36094) [2025-04-28 18:02:25,050 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2438 Process Time: 0.183 Mem R(MA/MR): 6504 (21200/36094) [2025-04-28 18:02:29,086 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.2489 Process Time: 0.424 Mem R(MA/MR): 28586 (21200/36094) [2025-04-28 18:02:31,228 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.7523 Process Time: 0.762 Mem R(MA/MR): 10798 (21200/36094) [2025-04-28 18:02:31,768 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.8336 Process Time: 0.200 Mem R(MA/MR): 5674 (21200/36094) [2025-04-28 18:02:32,964 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.0463 Process Time: 0.328 Mem R(MA/MR): 10422 (21200/36094) [2025-04-28 18:02:33,872 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.9082 Process Time: 0.194 Mem R(MA/MR): 8966 (21200/36094) [2025-04-28 18:02:34,309 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.0640 Process Time: 0.119 Mem R(MA/MR): 5682 (21200/36094) [2025-04-28 18:02:34,718 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8003 Process Time: 0.131 Mem R(MA/MR): 5732 (21200/36094) [2025-04-28 18:02:35,334 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.5580 Process Time: 0.179 Mem R(MA/MR): 6978 (21200/36094) [2025-04-28 18:02:36,003 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6714 Process Time: 0.154 Mem R(MA/MR): 5472 (21200/36094) [2025-04-28 18:02:38,436 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.0258 Process Time: 0.319 Mem R(MA/MR): 14722 (21200/36094) [2025-04-28 18:02:45,851 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.2807 Process Time: 0.756 Mem R(MA/MR): 20342 (21200/36094) [2025-04-28 18:02:57,188 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.1546 Process Time: 2.502 Mem R(MA/MR): 35372 (21200/36094) [2025-04-28 18:02:58,090 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.8131 Process Time: 0.355 Mem R(MA/MR): 5794 (21200/36094) [2025-04-28 18:03:00,918 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.8995 Process Time: 0.746 Mem R(MA/MR): 13622 (21200/36094) [2025-04-28 18:03:05,692 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 18:03:05,692 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 18:03:05,692 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 18:03:05,692 INFO hook.py line 395 1619929] table : 0.243 0.577 0.786 0.808 0.588 [2025-04-28 18:03:05,692 INFO hook.py line 395 1619929] door : 0.438 0.750 0.872 0.875 0.709 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] ceiling lamp : 0.522 0.720 0.843 0.821 0.707 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] cabinet : 0.273 0.401 0.528 0.604 0.433 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] blinds : 0.514 0.791 0.863 0.905 0.826 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] curtain : 0.305 0.421 0.719 0.833 0.417 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] chair : 0.546 0.695 0.765 0.816 0.598 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] storage cabinet: 0.121 0.254 0.540 0.364 0.480 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] office chair : 0.513 0.557 0.589 0.655 0.750 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] bookshelf : 0.247 0.482 0.602 0.636 0.636 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] whiteboard : 0.508 0.715 0.765 1.000 0.600 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] window : 0.096 0.242 0.596 0.407 0.363 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] box : 0.190 0.326 0.490 0.551 0.359 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] monitor : 0.535 0.674 0.753 0.957 0.643 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] shelf : 0.054 0.154 0.271 0.615 0.267 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] heater : 0.343 0.570 0.767 0.885 0.605 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] kitchen cabinet: 0.086 0.265 0.736 0.481 0.520 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] sofa : 0.431 0.730 0.926 0.818 0.750 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] bed : 0.140 0.404 0.739 0.667 0.500 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] trash can : 0.597 0.745 0.805 0.765 0.800 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] book : 0.011 0.023 0.060 0.145 0.090 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] plant : 0.339 0.525 0.657 0.714 0.556 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] blanket : 0.349 0.484 0.713 0.750 0.545 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] tv : 0.711 0.833 0.833 1.000 0.833 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] computer tower : 0.252 0.357 0.549 0.696 0.381 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] refrigerator : 0.278 0.404 0.403 1.000 0.333 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] jacket : 0.022 0.098 0.301 0.208 0.455 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] sink : 0.358 0.576 0.863 0.722 0.591 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] bag : 0.082 0.192 0.237 0.455 0.370 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] picture : 0.144 0.266 0.420 0.615 0.410 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] pillow : 0.507 0.770 0.821 0.750 0.789 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] towel : 0.152 0.339 0.528 0.722 0.342 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] suitcase : 0.387 0.434 0.434 0.750 0.429 [2025-04-28 18:03:05,693 INFO hook.py line 395 1619929] backpack : 0.246 0.290 0.334 0.600 0.462 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] crate : 0.095 0.273 0.395 0.600 0.273 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] keyboard : 0.345 0.538 0.603 0.808 0.538 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] toilet : 0.889 0.889 1.000 1.000 0.889 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] printer : 0.107 0.123 0.124 1.000 0.111 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.005 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] microwave : 0.503 0.810 0.923 1.000 0.750 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] shoes : 0.100 0.216 0.534 0.484 0.366 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] socket : 0.179 0.472 0.636 0.708 0.486 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] bottle : 0.110 0.193 0.334 0.488 0.241 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] bucket : 0.020 0.020 0.023 0.088 0.429 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] cushion : 0.045 0.327 0.565 0.429 0.500 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.010 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] telephone : 0.126 0.224 0.375 0.667 0.235 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] laptop : 0.261 0.349 0.396 0.556 0.625 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] plant pot : 0.088 0.230 0.506 0.438 0.438 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] exhaust fan : 0.167 0.306 0.333 0.833 0.333 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] cup : 0.136 0.193 0.321 0.565 0.295 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] coat hanger : 0.200 0.500 0.396 1.000 0.500 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] light switch : 0.217 0.478 0.648 0.680 0.523 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] speaker : 0.216 0.317 0.455 0.800 0.364 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] table lamp : 0.722 1.000 1.000 1.000 1.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] smoke detector : 0.550 0.750 0.786 1.000 0.750 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] power strip : 0.024 0.044 0.063 0.160 0.400 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] paper bag : 0.071 0.071 0.125 0.143 1.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] mouse : 0.401 0.594 0.703 0.947 0.562 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,694 INFO hook.py line 395 1619929] toilet paper : 0.192 0.314 0.395 0.667 0.353 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] clock : 0.524 0.903 0.903 0.750 1.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] pan : 0.083 0.250 0.250 1.000 0.250 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] tap : 0.173 0.289 0.667 0.667 0.444 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] soap dispenser : 0.479 0.697 0.800 0.800 0.800 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] bowl : 0.022 0.083 0.528 0.500 0.333 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] whiteboard eraser: 0.188 0.478 0.478 0.714 0.833 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] toilet brush : 0.413 0.766 0.941 1.000 0.667 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] headphones : 0.224 0.500 0.500 1.000 0.500 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:03:05,695 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 18:03:05,695 INFO hook.py line 404 1619929] average : 0.227 0.359 0.471 0.574 0.428 [2025-04-28 18:03:05,695 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 18:03:05,695 INFO hook.py line 480 1619929] Total Process Time: 23.005 s [2025-04-28 18:03:05,695 INFO hook.py line 481 1619929] Average Process Time: 464.276 ms [2025-04-28 18:03:05,695 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 18:03:05,732 INFO hook.py line 685 1619929] Currently Best AP50: 0.383 [2025-04-28 18:03:05,734 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:04:33,395 INFO hook.py line 650 1619929] Train: [145/512][50/242] Data 0.015 (0.031) Batch 1.229 (1.501) Remain 37:05:55 loss: 4.8593 Lr: 2.22793e-04 Mem R(MA/MR): 22366 (21200/36094) [2025-04-28 18:05:41,963 INFO hook.py line 650 1619929] Train: [145/512][100/242] Data 0.015 (0.023) Batch 1.308 (1.434) Remain 35:25:57 loss: 6.4092 Lr: 2.22681e-04 Mem R(MA/MR): 22380 (21200/36094) [2025-04-28 18:06:51,218 INFO hook.py line 650 1619929] Train: [145/512][150/242] Data 0.017 (0.021) Batch 1.352 (1.417) Remain 35:00:07 loss: 5.7547 Lr: 2.22568e-04 Mem R(MA/MR): 22402 (21200/36094) [2025-04-28 18:08:01,944 INFO hook.py line 650 1619929] Train: [145/512][200/242] Data 0.014 (0.020) Batch 1.445 (1.417) Remain 34:57:55 loss: 6.4918 Lr: 2.22455e-04 Mem R(MA/MR): 22402 (21200/36094) [2025-04-28 18:08:56,684 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4513 loss_mask: 0.0439 loss_dice: 2.3532 loss_score: 0.0000 loss_bbox: 0.0564 loss_sp_cls: 0.9473 loss: 6.1848 [2025-04-28 18:09:00,156 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:10:24,248 INFO hook.py line 650 1619929] Train: [146/512][50/242] Data 0.018 (0.017) Batch 1.474 (1.419) Remain 34:59:03 loss: 5.4593 Lr: 2.22248e-04 Mem R(MA/MR): 25040 (21200/36094) [2025-04-28 18:11:33,596 INFO hook.py line 650 1619929] Train: [146/512][100/242] Data 0.015 (0.017) Batch 1.380 (1.402) Remain 34:33:35 loss: 7.3525 Lr: 2.22135e-04 Mem R(MA/MR): 30542 (21200/36094) [2025-04-28 18:12:43,427 INFO hook.py line 650 1619929] Train: [146/512][150/242] Data 0.016 (0.017) Batch 1.558 (1.400) Remain 34:29:29 loss: 6.5651 Lr: 2.22023e-04 Mem R(MA/MR): 30542 (21200/36094) [2025-04-28 18:13:52,372 INFO hook.py line 650 1619929] Train: [146/512][200/242] Data 0.014 (0.017) Batch 1.370 (1.395) Remain 34:20:15 loss: 7.9825 Lr: 2.21910e-04 Mem R(MA/MR): 30554 (21200/36094) [2025-04-28 18:14:47,198 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4548 loss_mask: 0.0440 loss_dice: 2.3483 loss_score: 0.0000 loss_bbox: 0.0566 loss_sp_cls: 0.9476 loss: 6.1961 [2025-04-28 18:14:47,668 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:16:20,066 INFO hook.py line 650 1619929] Train: [147/512][50/242] Data 0.015 (0.017) Batch 1.342 (1.456) Remain 35:48:28 loss: 6.6214 Lr: 2.21703e-04 Mem R(MA/MR): 23126 (21200/36094) [2025-04-28 18:17:31,219 INFO hook.py line 650 1619929] Train: [147/512][100/242] Data 0.015 (0.016) Batch 1.519 (1.439) Remain 35:22:03 loss: 5.7112 Lr: 2.21590e-04 Mem R(MA/MR): 24848 (21200/36094) [2025-04-28 18:18:39,705 INFO hook.py line 650 1619929] Train: [147/512][150/242] Data 0.016 (0.016) Batch 1.446 (1.416) Remain 34:46:03 loss: 7.1405 Lr: 2.21477e-04 Mem R(MA/MR): 24848 (21200/36094) [2025-04-28 18:19:48,384 INFO hook.py line 650 1619929] Train: [147/512][200/242] Data 0.016 (0.017) Batch 1.266 (1.405) Remain 34:29:12 loss: 5.5280 Lr: 2.21365e-04 Mem R(MA/MR): 24848 (21200/36094) [2025-04-28 18:20:42,880 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4417 loss_mask: 0.0444 loss_dice: 2.3364 loss_score: 0.0000 loss_bbox: 0.0556 loss_sp_cls: 0.9449 loss: 6.1296 [2025-04-28 18:20:43,176 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:22:11,861 INFO hook.py line 650 1619929] Train: [148/512][50/242] Data 0.017 (0.016) Batch 1.423 (1.398) Remain 34:17:18 loss: 6.2475 Lr: 2.21157e-04 Mem R(MA/MR): 24436 (21200/36094) [2025-04-28 18:23:21,466 INFO hook.py line 650 1619929] Train: [148/512][100/242] Data 0.016 (0.016) Batch 1.245 (1.395) Remain 34:11:27 loss: 6.3048 Lr: 2.21045e-04 Mem R(MA/MR): 24446 (21200/36094) [2025-04-28 18:24:31,818 INFO hook.py line 650 1619929] Train: [148/512][150/242] Data 0.016 (0.016) Batch 1.318 (1.399) Remain 34:16:17 loss: 5.5651 Lr: 2.20932e-04 Mem R(MA/MR): 24462 (21200/36094) [2025-04-28 18:25:39,372 INFO hook.py line 650 1619929] Train: [148/512][200/242] Data 0.015 (0.016) Batch 1.243 (1.387) Remain 33:57:12 loss: 5.0552 Lr: 2.20819e-04 Mem R(MA/MR): 24462 (21200/36094) [2025-04-28 18:26:33,923 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4248 loss_mask: 0.0406 loss_dice: 2.2685 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.9132 loss: 5.9509 [2025-04-28 18:26:37,988 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:28:08,246 INFO hook.py line 650 1619929] Train: [149/512][50/242] Data 0.016 (0.017) Batch 1.410 (1.398) Remain 34:11:45 loss: 6.6826 Lr: 2.20612e-04 Mem R(MA/MR): 24186 (21200/36094) [2025-04-28 18:29:15,927 INFO hook.py line 650 1619929] Train: [149/512][100/242] Data 0.015 (0.017) Batch 1.179 (1.375) Remain 33:36:48 loss: 4.5735 Lr: 2.20499e-04 Mem R(MA/MR): 24186 (21200/36094) [2025-04-28 18:30:22,964 INFO hook.py line 650 1619929] Train: [149/512][150/242] Data 0.016 (0.016) Batch 1.538 (1.364) Remain 33:18:26 loss: 6.0320 Lr: 2.20386e-04 Mem R(MA/MR): 24190 (21200/36094) [2025-04-28 18:31:31,782 INFO hook.py line 650 1619929] Train: [149/512][200/242] Data 0.016 (0.016) Batch 1.277 (1.367) Remain 33:22:04 loss: 4.7582 Lr: 2.20274e-04 Mem R(MA/MR): 24190 (21200/36094) [2025-04-28 18:32:26,809 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4230 loss_mask: 0.0415 loss_dice: 2.2588 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.9136 loss: 5.9287 [2025-04-28 18:32:30,077 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:34:01,742 INFO hook.py line 650 1619929] Train: [150/512][50/242] Data 0.043 (0.018) Batch 1.407 (1.454) Remain 35:27:57 loss: 5.7213 Lr: 2.20066e-04 Mem R(MA/MR): 21900 (21200/36094) [2025-04-28 18:35:11,121 INFO hook.py line 650 1619929] Train: [150/512][100/242] Data 0.015 (0.017) Batch 1.220 (1.420) Remain 34:36:29 loss: 4.7642 Lr: 2.19953e-04 Mem R(MA/MR): 23980 (21200/36094) [2025-04-28 18:36:20,482 INFO hook.py line 650 1619929] Train: [150/512][150/242] Data 0.016 (0.017) Batch 1.553 (1.409) Remain 34:19:03 loss: 6.2243 Lr: 2.19841e-04 Mem R(MA/MR): 23980 (21200/36094) [2025-04-28 18:37:29,464 INFO hook.py line 650 1619929] Train: [150/512][200/242] Data 0.016 (0.017) Batch 1.419 (1.401) Remain 34:07:05 loss: 6.0940 Lr: 2.19728e-04 Mem R(MA/MR): 23982 (21200/36094) [2025-04-28 18:38:24,254 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4208 loss_mask: 0.0404 loss_dice: 2.2617 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.9100 loss: 5.9240 [2025-04-28 18:38:24,324 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:39:52,691 INFO hook.py line 650 1619929] Train: [151/512][50/242] Data 0.017 (0.018) Batch 1.584 (1.406) Remain 34:11:49 loss: 5.0925 Lr: 2.19520e-04 Mem R(MA/MR): 23912 (21200/36094) [2025-04-28 18:41:02,900 INFO hook.py line 650 1619929] Train: [151/512][100/242] Data 0.018 (0.017) Batch 1.577 (1.405) Remain 34:09:12 loss: 6.1752 Lr: 2.19407e-04 Mem R(MA/MR): 25716 (21200/36094) [2025-04-28 18:42:11,094 INFO hook.py line 650 1619929] Train: [151/512][150/242] Data 0.015 (0.017) Batch 1.257 (1.391) Remain 33:47:36 loss: 5.6553 Lr: 2.19295e-04 Mem R(MA/MR): 25728 (21200/36094) [2025-04-28 18:43:19,263 INFO hook.py line 650 1619929] Train: [151/512][200/242] Data 0.015 (0.016) Batch 1.335 (1.384) Remain 33:36:12 loss: 5.9816 Lr: 2.19182e-04 Mem R(MA/MR): 28252 (21200/36094) [2025-04-28 18:44:13,598 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4236 loss_mask: 0.0415 loss_dice: 2.2595 loss_score: 0.0000 loss_bbox: 0.0547 loss_sp_cls: 0.9056 loss: 5.9291 [2025-04-28 18:44:17,263 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:45:41,330 INFO hook.py line 650 1619929] Train: [152/512][50/242] Data 0.017 (0.017) Batch 1.372 (1.445) Remain 35:03:17 loss: 4.9414 Lr: 2.18974e-04 Mem R(MA/MR): 26114 (21200/36094) [2025-04-28 18:46:52,714 INFO hook.py line 650 1619929] Train: [152/512][100/242] Data 0.015 (0.016) Batch 1.324 (1.436) Remain 34:48:49 loss: 4.5661 Lr: 2.18861e-04 Mem R(MA/MR): 26144 (21200/36094) [2025-04-28 18:48:03,346 INFO hook.py line 650 1619929] Train: [152/512][150/242] Data 0.017 (0.016) Batch 1.347 (1.428) Remain 34:35:58 loss: 5.9471 Lr: 2.18748e-04 Mem R(MA/MR): 26144 (21200/36094) [2025-04-28 18:49:12,501 INFO hook.py line 650 1619929] Train: [152/512][200/242] Data 0.015 (0.017) Batch 1.489 (1.417) Remain 34:18:08 loss: 5.8630 Lr: 2.18636e-04 Mem R(MA/MR): 28004 (21200/36094) [2025-04-28 18:50:07,368 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4249 loss_mask: 0.0416 loss_dice: 2.2746 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.9196 loss: 5.9619 [2025-04-28 18:50:12,055 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 18:50:14,428 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5325 Process Time: 0.257 Mem R(MA/MR): 4374 (21200/36094) [2025-04-28 18:50:16,003 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8009 Process Time: 0.475 Mem R(MA/MR): 7138 (21200/36094) [2025-04-28 18:50:17,996 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1204 Process Time: 0.846 Mem R(MA/MR): 9694 (21200/36094) [2025-04-28 18:50:24,761 INFO hook.py line 449 1619929] Test: [4/50] Loss 7.0021 Process Time: 1.382 Mem R(MA/MR): 19506 (21200/36094) [2025-04-28 18:50:26,382 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.8105 Process Time: 0.819 Mem R(MA/MR): 7080 (21200/36094) [2025-04-28 18:50:28,396 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5448 Process Time: 0.834 Mem R(MA/MR): 11234 (21200/36094) [2025-04-28 18:50:29,206 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2251 Process Time: 0.325 Mem R(MA/MR): 6264 (21200/36094) [2025-04-28 18:50:29,783 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.0011 Process Time: 0.197 Mem R(MA/MR): 4396 (21200/36094) [2025-04-28 18:50:30,651 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8246 Process Time: 0.254 Mem R(MA/MR): 11414 (21200/36094) [2025-04-28 18:50:31,945 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.9270 Process Time: 0.226 Mem R(MA/MR): 9306 (21200/36094) [2025-04-28 18:50:34,161 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.1472 Process Time: 0.312 Mem R(MA/MR): 18510 (21200/36094) [2025-04-28 18:50:37,272 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2503 Process Time: 1.127 Mem R(MA/MR): 15350 (21200/36094) [2025-04-28 18:50:38,797 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.2424 Process Time: 0.460 Mem R(MA/MR): 8736 (21200/36094) [2025-04-28 18:50:39,175 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9636 Process Time: 0.130 Mem R(MA/MR): 4758 (21200/36094) [2025-04-28 18:50:41,657 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.7898 Process Time: 0.247 Mem R(MA/MR): 16268 (21200/36094) [2025-04-28 18:50:43,492 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.5650 Process Time: 0.516 Mem R(MA/MR): 14442 (21200/36094) [2025-04-28 18:50:45,037 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.4602 Process Time: 0.681 Mem R(MA/MR): 6702 (21200/36094) [2025-04-28 18:50:45,999 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1451 Process Time: 0.312 Mem R(MA/MR): 8088 (21200/36094) [2025-04-28 18:50:47,730 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.8164 Process Time: 0.368 Mem R(MA/MR): 6128 (21200/36094) [2025-04-28 18:50:49,081 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.3220 Process Time: 0.233 Mem R(MA/MR): 11254 (21200/36094) [2025-04-28 18:50:56,909 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8422 Process Time: 0.923 Mem R(MA/MR): 23436 (21200/36094) [2025-04-28 18:50:57,588 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.1428 Process Time: 0.224 Mem R(MA/MR): 6890 (21200/36094) [2025-04-28 18:51:08,081 INFO hook.py line 449 1619929] Test: [23/50] Loss 14.4816 Process Time: 0.329 Mem R(MA/MR): 8380 (21200/36094) [2025-04-28 18:51:08,656 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.5694 Process Time: 0.153 Mem R(MA/MR): 5368 (21200/36094) [2025-04-28 18:51:09,671 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2765 Process Time: 0.300 Mem R(MA/MR): 9194 (21200/36094) [2025-04-28 18:51:18,486 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.2219 Process Time: 2.429 Mem R(MA/MR): 31880 (21200/36094) [2025-04-28 18:51:21,730 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.5450 Process Time: 0.774 Mem R(MA/MR): 9884 (21200/36094) [2025-04-28 18:51:23,084 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.6352 Process Time: 0.399 Mem R(MA/MR): 8828 (21200/36094) [2025-04-28 18:51:28,130 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6865 Process Time: 0.464 Mem R(MA/MR): 17058 (21200/36094) [2025-04-28 18:51:29,648 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.8736 Process Time: 0.562 Mem R(MA/MR): 7680 (21200/36094) [2025-04-28 18:51:33,277 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.4416 Process Time: 0.606 Mem R(MA/MR): 20454 (21200/36094) [2025-04-28 18:51:33,525 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1672 Process Time: 0.116 Mem R(MA/MR): 4002 (21200/36094) [2025-04-28 18:51:37,313 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.6244 Process Time: 0.350 Mem R(MA/MR): 24686 (21200/36094) [2025-04-28 18:51:39,012 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8121 Process Time: 0.537 Mem R(MA/MR): 9690 (21200/36094) [2025-04-28 18:51:41,265 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.5612 Process Time: 0.487 Mem R(MA/MR): 13880 (21200/36094) [2025-04-28 18:51:41,742 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1057 Process Time: 0.157 Mem R(MA/MR): 6560 (21200/36094) [2025-04-28 18:51:45,401 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5727 Process Time: 0.412 Mem R(MA/MR): 28656 (21200/36094) [2025-04-28 18:51:47,897 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.8457 Process Time: 0.646 Mem R(MA/MR): 10538 (21200/36094) [2025-04-28 18:51:48,510 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9155 Process Time: 0.276 Mem R(MA/MR): 5466 (21200/36094) [2025-04-28 18:51:49,532 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.0723 Process Time: 0.317 Mem R(MA/MR): 10018 (21200/36094) [2025-04-28 18:51:50,329 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.9796 Process Time: 0.179 Mem R(MA/MR): 8886 (21200/36094) [2025-04-28 18:51:50,801 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.2401 Process Time: 0.143 Mem R(MA/MR): 5520 (21200/36094) [2025-04-28 18:51:51,210 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.0576 Process Time: 0.129 Mem R(MA/MR): 5592 (21200/36094) [2025-04-28 18:51:51,799 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.9083 Process Time: 0.222 Mem R(MA/MR): 7092 (21200/36094) [2025-04-28 18:51:52,346 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.2423 Process Time: 0.116 Mem R(MA/MR): 5278 (21200/36094) [2025-04-28 18:51:54,151 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8977 Process Time: 0.228 Mem R(MA/MR): 14386 (21200/36094) [2025-04-28 18:52:01,239 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7640 Process Time: 1.153 Mem R(MA/MR): 20074 (21200/36094) [2025-04-28 18:52:11,018 INFO hook.py line 449 1619929] Test: [48/50] Loss 10.9603 Process Time: 1.178 Mem R(MA/MR): 35614 (21200/36094) [2025-04-28 18:52:12,232 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.3413 Process Time: 0.626 Mem R(MA/MR): 5746 (21200/36094) [2025-04-28 18:52:15,597 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.7634 Process Time: 1.005 Mem R(MA/MR): 13630 (21200/36094) [2025-04-28 18:52:20,212 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 18:52:20,212 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 18:52:20,212 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] table : 0.235 0.555 0.725 0.846 0.566 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] door : 0.476 0.775 0.890 0.894 0.747 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] ceiling lamp : 0.552 0.713 0.801 0.875 0.696 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] cabinet : 0.333 0.461 0.520 0.608 0.463 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] blinds : 0.512 0.658 0.812 0.696 0.696 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] curtain : 0.223 0.363 0.660 0.471 0.667 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] chair : 0.593 0.725 0.777 0.691 0.779 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] storage cabinet: 0.174 0.421 0.602 0.469 0.600 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] office chair : 0.570 0.611 0.626 0.723 0.708 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] bookshelf : 0.209 0.541 0.554 0.818 0.818 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] whiteboard : 0.568 0.779 0.779 0.962 0.714 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] window : 0.092 0.192 0.580 0.409 0.297 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] box : 0.191 0.364 0.505 0.550 0.392 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] monitor : 0.577 0.699 0.838 0.885 0.657 [2025-04-28 18:52:20,212 INFO hook.py line 395 1619929] shelf : 0.055 0.161 0.354 0.450 0.300 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] heater : 0.414 0.665 0.739 0.875 0.737 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] kitchen cabinet: 0.189 0.467 0.763 0.579 0.440 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] sofa : 0.423 0.486 0.800 0.643 0.750 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] bed : 0.231 0.602 0.875 0.833 0.625 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] trash can : 0.565 0.727 0.760 0.794 0.831 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] book : 0.018 0.035 0.067 0.255 0.090 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] plant : 0.452 0.710 0.774 0.867 0.722 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] blanket : 0.416 0.691 0.696 1.000 0.636 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] tv : 0.835 0.925 0.925 0.750 1.000 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] computer tower : 0.198 0.306 0.579 0.500 0.357 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] refrigerator : 0.220 0.437 0.446 1.000 0.333 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] jacket : 0.042 0.181 0.274 0.350 0.636 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] sink : 0.308 0.598 0.787 0.789 0.682 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] bag : 0.160 0.232 0.319 0.324 0.444 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] picture : 0.157 0.422 0.473 0.679 0.487 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] pillow : 0.469 0.752 0.788 0.875 0.737 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] towel : 0.155 0.384 0.514 0.567 0.447 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] suitcase : 0.375 0.418 0.418 0.667 0.571 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] backpack : 0.323 0.377 0.482 0.545 0.462 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] crate : 0.053 0.285 0.562 1.000 0.273 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] keyboard : 0.392 0.524 0.582 0.792 0.487 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] toilet : 0.797 0.876 1.000 0.889 0.889 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] printer : 0.203 0.230 0.331 0.400 0.444 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] poster : 0.002 0.019 0.028 0.333 0.111 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] painting : 0.250 0.250 0.250 0.500 1.000 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] microwave : 0.479 0.875 1.000 1.000 0.875 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] shoes : 0.090 0.185 0.507 0.429 0.293 [2025-04-28 18:52:20,213 INFO hook.py line 395 1619929] socket : 0.192 0.448 0.646 0.724 0.450 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] bottle : 0.105 0.174 0.317 0.487 0.229 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] bucket : 0.081 0.142 0.144 0.667 0.286 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] cushion : 0.147 0.236 0.410 0.500 0.333 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] basket : 0.012 0.018 0.064 0.250 0.143 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] shoe rack : 0.028 0.125 0.500 0.500 0.500 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] telephone : 0.253 0.453 0.484 0.875 0.412 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] laptop : 0.225 0.280 0.380 1.000 0.250 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] plant pot : 0.124 0.337 0.500 0.667 0.500 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] exhaust fan : 0.083 0.171 0.212 0.571 0.267 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] cup : 0.163 0.285 0.309 0.857 0.273 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] coat hanger : 0.167 0.500 0.750 1.000 0.500 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] light switch : 0.237 0.495 0.671 0.702 0.508 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] speaker : 0.311 0.464 0.493 0.600 0.545 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.236 1.000 0.167 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] smoke detector : 0.646 0.816 0.816 0.909 0.833 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] power strip : 0.018 0.041 0.142 0.200 0.200 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] paper bag : 0.125 0.125 0.125 0.250 1.000 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] mouse : 0.486 0.654 0.712 0.870 0.625 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] toilet paper : 0.201 0.313 0.386 0.438 0.412 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] paper towel : 0.006 0.013 0.083 0.200 0.125 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] clock : 0.443 0.764 0.764 0.750 1.000 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 18:52:20,214 INFO hook.py line 395 1619929] tap : 0.166 0.407 0.637 0.625 0.556 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] soap dispenser : 0.496 0.542 0.542 0.750 0.600 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] bowl : 0.017 0.033 0.083 0.200 0.333 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] whiteboard eraser: 0.155 0.368 0.368 0.556 0.833 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] toilet brush : 0.413 0.694 0.882 0.800 0.667 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] stapler : 0.004 0.033 0.164 0.200 0.333 [2025-04-28 18:52:20,215 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 18:52:20,215 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 18:52:20,215 INFO hook.py line 404 1619929] average : 0.240 0.372 0.474 0.594 0.465 [2025-04-28 18:52:20,215 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 18:52:20,215 INFO hook.py line 480 1619929] Total Process Time: 25.439 s [2025-04-28 18:52:20,215 INFO hook.py line 481 1619929] Average Process Time: 513.925 ms [2025-04-28 18:52:20,215 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 18:52:20,270 INFO hook.py line 685 1619929] Currently Best AP50: 0.383 [2025-04-28 18:52:20,277 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:53:46,877 INFO hook.py line 650 1619929] Train: [153/512][50/242] Data 0.014 (0.017) Batch 1.393 (1.403) Remain 33:55:45 loss: 5.7503 Lr: 2.18428e-04 Mem R(MA/MR): 18860 (21200/36094) [2025-04-28 18:54:57,400 INFO hook.py line 650 1619929] Train: [153/512][100/242] Data 0.017 (0.017) Batch 1.289 (1.407) Remain 34:00:17 loss: 6.2037 Lr: 2.18315e-04 Mem R(MA/MR): 18870 (21200/36094) [2025-04-28 18:56:04,552 INFO hook.py line 650 1619929] Train: [153/512][150/242] Data 0.016 (0.016) Batch 1.342 (1.385) Remain 33:27:42 loss: 6.2083 Lr: 2.18202e-04 Mem R(MA/MR): 18870 (21200/36094) [2025-04-28 18:57:13,531 INFO hook.py line 650 1619929] Train: [153/512][200/242] Data 0.015 (0.020) Batch 1.263 (1.384) Remain 33:24:32 loss: 6.1355 Lr: 2.18089e-04 Mem R(MA/MR): 21396 (21200/36094) [2025-04-28 18:58:07,823 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4238 loss_mask: 0.0418 loss_dice: 2.2725 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.9135 loss: 5.9582 [2025-04-28 18:58:10,737 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 18:59:41,504 INFO hook.py line 650 1619929] Train: [154/512][50/242] Data 0.015 (0.016) Batch 1.298 (1.438) Remain 34:41:10 loss: 6.6265 Lr: 2.17882e-04 Mem R(MA/MR): 23076 (21200/36094) [2025-04-28 19:00:51,263 INFO hook.py line 650 1619929] Train: [154/512][100/242] Data 0.016 (0.016) Batch 1.594 (1.416) Remain 34:07:55 loss: 6.2830 Lr: 2.17769e-04 Mem R(MA/MR): 23076 (21200/36094) [2025-04-28 19:02:02,616 INFO hook.py line 650 1619929] Train: [154/512][150/242] Data 0.017 (0.017) Batch 1.272 (1.420) Remain 34:12:12 loss: 5.4351 Lr: 2.17656e-04 Mem R(MA/MR): 25438 (21200/36094) [2025-04-28 19:03:10,327 INFO hook.py line 650 1619929] Train: [154/512][200/242] Data 0.015 (0.017) Batch 1.320 (1.403) Remain 33:47:00 loss: 6.5394 Lr: 2.17543e-04 Mem R(MA/MR): 25438 (21200/36094) [2025-04-28 19:04:04,794 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4281 loss_mask: 0.0421 loss_dice: 2.2884 loss_score: 0.0000 loss_bbox: 0.0559 loss_sp_cls: 0.9200 loss: 5.9957 [2025-04-28 19:04:07,573 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:05:37,902 INFO hook.py line 650 1619929] Train: [155/512][50/242] Data 0.017 (0.016) Batch 1.507 (1.382) Remain 33:14:54 loss: 6.9916 Lr: 2.17335e-04 Mem R(MA/MR): 24342 (21200/36094) [2025-04-28 19:06:49,042 INFO hook.py line 650 1619929] Train: [155/512][100/242] Data 0.016 (0.017) Batch 1.254 (1.403) Remain 33:43:48 loss: 4.6028 Lr: 2.17222e-04 Mem R(MA/MR): 24354 (21200/36094) [2025-04-28 19:07:58,010 INFO hook.py line 650 1619929] Train: [155/512][150/242] Data 0.015 (0.017) Batch 1.331 (1.395) Remain 33:30:56 loss: 5.8063 Lr: 2.17109e-04 Mem R(MA/MR): 24354 (21200/36094) [2025-04-28 19:09:07,206 INFO hook.py line 650 1619929] Train: [155/512][200/242] Data 0.016 (0.017) Batch 1.517 (1.392) Remain 33:25:41 loss: 6.3744 Lr: 2.16999e-04 Mem R(MA/MR): 24366 (21200/36094) [2025-04-28 19:10:02,752 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4258 loss_mask: 0.0418 loss_dice: 2.2637 loss_score: 0.0000 loss_bbox: 0.0555 loss_sp_cls: 0.9189 loss: 5.9564 [2025-04-28 19:10:02,881 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:11:31,395 INFO hook.py line 650 1619929] Train: [156/512][50/242] Data 0.067 (0.017) Batch 1.493 (1.383) Remain 33:10:36 loss: 5.4974 Lr: 2.16791e-04 Mem R(MA/MR): 22348 (21200/36094) [2025-04-28 19:12:40,738 INFO hook.py line 650 1619929] Train: [156/512][100/242] Data 0.015 (0.017) Batch 1.341 (1.385) Remain 33:12:08 loss: 4.9449 Lr: 2.16678e-04 Mem R(MA/MR): 22348 (21200/36094) [2025-04-28 19:13:52,179 INFO hook.py line 650 1619929] Train: [156/512][150/242] Data 0.017 (0.017) Batch 1.411 (1.400) Remain 33:32:21 loss: 5.9201 Lr: 2.16565e-04 Mem R(MA/MR): 22348 (21200/36094) [2025-04-28 19:14:59,472 INFO hook.py line 650 1619929] Train: [156/512][200/242] Data 0.015 (0.016) Batch 1.279 (1.386) Remain 33:11:26 loss: 6.2275 Lr: 2.16452e-04 Mem R(MA/MR): 22348 (21200/36094) [2025-04-28 19:15:53,605 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4281 loss_mask: 0.0410 loss_dice: 2.2665 loss_score: 0.0000 loss_bbox: 0.0558 loss_sp_cls: 0.9136 loss: 5.9622 [2025-04-28 19:15:55,322 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:17:26,501 INFO hook.py line 650 1619929] Train: [157/512][50/242] Data 0.015 (0.017) Batch 1.325 (1.410) Remain 33:42:56 loss: 5.5847 Lr: 2.16244e-04 Mem R(MA/MR): 26210 (21200/36094) [2025-04-28 19:18:36,598 INFO hook.py line 650 1619929] Train: [157/512][100/242] Data 0.016 (0.017) Batch 1.332 (1.406) Remain 33:36:01 loss: 6.1669 Lr: 2.16131e-04 Mem R(MA/MR): 26224 (21200/36094) [2025-04-28 19:19:46,058 INFO hook.py line 650 1619929] Train: [157/512][150/242] Data 0.016 (0.016) Batch 1.350 (1.400) Remain 33:26:49 loss: 6.2048 Lr: 2.16018e-04 Mem R(MA/MR): 26224 (21200/36094) [2025-04-28 19:20:54,783 INFO hook.py line 650 1619929] Train: [157/512][200/242] Data 0.015 (0.016) Batch 1.257 (1.394) Remain 33:16:21 loss: 5.5379 Lr: 2.15905e-04 Mem R(MA/MR): 28230 (21200/36094) [2025-04-28 19:21:48,669 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4279 loss_mask: 0.0426 loss_dice: 2.3059 loss_score: 0.0000 loss_bbox: 0.0555 loss_sp_cls: 0.9245 loss: 6.0193 [2025-04-28 19:21:48,746 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:23:13,051 INFO hook.py line 650 1619929] Train: [158/512][50/242] Data 0.017 (0.062) Batch 1.579 (1.453) Remain 34:39:37 loss: 5.9328 Lr: 2.15697e-04 Mem R(MA/MR): 24604 (21200/36094) [2025-04-28 19:24:22,349 INFO hook.py line 650 1619929] Train: [158/512][100/242] Data 0.016 (0.038) Batch 1.282 (1.419) Remain 33:48:49 loss: 5.1675 Lr: 2.15584e-04 Mem R(MA/MR): 24608 (21200/36094) [2025-04-28 19:25:32,460 INFO hook.py line 650 1619929] Train: [158/512][150/242] Data 0.014 (0.031) Batch 1.481 (1.413) Remain 33:39:41 loss: 6.1003 Lr: 2.15471e-04 Mem R(MA/MR): 24608 (21200/36094) [2025-04-28 19:26:40,840 INFO hook.py line 650 1619929] Train: [158/512][200/242] Data 0.015 (0.027) Batch 1.283 (1.401) Remain 33:22:02 loss: 6.9307 Lr: 2.15358e-04 Mem R(MA/MR): 24608 (21200/36094) [2025-04-28 19:27:36,307 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4316 loss_mask: 0.0421 loss_dice: 2.2800 loss_score: 0.0000 loss_bbox: 0.0562 loss_sp_cls: 0.9260 loss: 6.0016 [2025-04-28 19:27:36,376 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:29:05,101 INFO hook.py line 650 1619929] Train: [159/512][50/242] Data 0.017 (0.016) Batch 1.340 (1.407) Remain 33:28:22 loss: 4.7478 Lr: 2.15150e-04 Mem R(MA/MR): 19836 (21200/36094) [2025-04-28 19:30:12,486 INFO hook.py line 650 1619929] Train: [159/512][100/242] Data 0.017 (0.016) Batch 1.378 (1.377) Remain 32:43:17 loss: 6.4595 Lr: 2.15037e-04 Mem R(MA/MR): 21928 (21200/36094) [2025-04-28 19:31:22,829 INFO hook.py line 650 1619929] Train: [159/512][150/242] Data 0.017 (0.016) Batch 1.478 (1.387) Remain 32:56:45 loss: 7.0466 Lr: 2.14924e-04 Mem R(MA/MR): 21928 (21200/36094) [2025-04-28 19:32:32,575 INFO hook.py line 650 1619929] Train: [159/512][200/242] Data 0.014 (0.016) Batch 1.471 (1.389) Remain 32:58:31 loss: 6.5181 Lr: 2.14811e-04 Mem R(MA/MR): 21928 (21200/36094) [2025-04-28 19:33:27,003 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4365 loss_mask: 0.0432 loss_dice: 2.2999 loss_score: 0.0000 loss_bbox: 0.0551 loss_sp_cls: 0.9247 loss: 6.0439 [2025-04-28 19:33:27,068 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:34:49,611 INFO hook.py line 650 1619929] Train: [160/512][50/242] Data 0.016 (0.017) Batch 1.360 (1.449) Remain 34:22:24 loss: 5.2550 Lr: 2.14603e-04 Mem R(MA/MR): 22260 (21200/36094) [2025-04-28 19:35:58,264 INFO hook.py line 650 1619929] Train: [160/512][100/242] Data 0.016 (0.016) Batch 1.363 (1.410) Remain 33:25:13 loss: 6.2472 Lr: 2.14490e-04 Mem R(MA/MR): 22284 (21200/36094) [2025-04-28 19:37:08,539 INFO hook.py line 650 1619929] Train: [160/512][150/242] Data 0.016 (0.017) Batch 1.308 (1.408) Remain 33:21:50 loss: 5.2044 Lr: 2.14376e-04 Mem R(MA/MR): 22284 (21200/36094) [2025-04-28 19:38:19,253 INFO hook.py line 650 1619929] Train: [160/512][200/242] Data 0.017 (0.017) Batch 1.268 (1.410) Remain 33:22:46 loss: 5.8610 Lr: 2.14263e-04 Mem R(MA/MR): 24254 (21200/36094) [2025-04-28 19:39:13,660 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4306 loss_mask: 0.0438 loss_dice: 2.3089 loss_score: 0.0000 loss_bbox: 0.0558 loss_sp_cls: 0.9228 loss: 6.0436 [2025-04-28 19:39:18,037 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 19:39:20,584 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.3917 Process Time: 0.316 Mem R(MA/MR): 4920 (21200/36094) [2025-04-28 19:39:21,925 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.4160 Process Time: 0.407 Mem R(MA/MR): 7246 (21200/36094) [2025-04-28 19:39:23,692 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.0924 Process Time: 0.691 Mem R(MA/MR): 10124 (21200/36094) [2025-04-28 19:39:31,380 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.4028 Process Time: 1.583 Mem R(MA/MR): 19732 (21200/36094) [2025-04-28 19:39:32,467 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6302 Process Time: 0.482 Mem R(MA/MR): 7126 (21200/36094) [2025-04-28 19:39:34,504 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7638 Process Time: 0.709 Mem R(MA/MR): 11816 (21200/36094) [2025-04-28 19:39:35,211 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2260 Process Time: 0.207 Mem R(MA/MR): 6642 (21200/36094) [2025-04-28 19:39:35,784 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.0750 Process Time: 0.200 Mem R(MA/MR): 4958 (21200/36094) [2025-04-28 19:39:36,838 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0015 Process Time: 0.319 Mem R(MA/MR): 11914 (21200/36094) [2025-04-28 19:39:38,349 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.9509 Process Time: 0.244 Mem R(MA/MR): 9766 (21200/36094) [2025-04-28 19:39:40,876 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.1228 Process Time: 0.350 Mem R(MA/MR): 18888 (21200/36094) [2025-04-28 19:39:44,331 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0097 Process Time: 0.973 Mem R(MA/MR): 15600 (21200/36094) [2025-04-28 19:39:45,737 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7961 Process Time: 0.371 Mem R(MA/MR): 9114 (21200/36094) [2025-04-28 19:39:46,118 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1034 Process Time: 0.132 Mem R(MA/MR): 5240 (21200/36094) [2025-04-28 19:39:49,522 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.9509 Process Time: 0.280 Mem R(MA/MR): 16926 (21200/36094) [2025-04-28 19:39:52,062 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.5141 Process Time: 0.986 Mem R(MA/MR): 14892 (21200/36094) [2025-04-28 19:39:52,996 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1107 Process Time: 0.264 Mem R(MA/MR): 7018 (21200/36094) [2025-04-28 19:39:54,000 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.3524 Process Time: 0.262 Mem R(MA/MR): 8800 (21200/36094) [2025-04-28 19:39:55,560 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9043 Process Time: 0.177 Mem R(MA/MR): 6610 (21200/36094) [2025-04-28 19:39:57,173 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.6240 Process Time: 0.272 Mem R(MA/MR): 11906 (21200/36094) [2025-04-28 19:40:06,194 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.9656 Process Time: 0.878 Mem R(MA/MR): 23446 (21200/36094) [2025-04-28 19:40:06,784 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3599 Process Time: 0.180 Mem R(MA/MR): 7224 (21200/36094) [2025-04-28 19:40:16,586 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.4609 Process Time: 0.556 Mem R(MA/MR): 10354 (21200/36094) [2025-04-28 19:40:17,459 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0003 Process Time: 0.319 Mem R(MA/MR): 5992 (21200/36094) [2025-04-28 19:40:18,808 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.3931 Process Time: 0.464 Mem R(MA/MR): 9774 (21200/36094) [2025-04-28 19:40:26,824 INFO hook.py line 449 1619929] Test: [26/50] Loss 14.2478 Process Time: 1.627 Mem R(MA/MR): 32076 (21200/36094) [2025-04-28 19:40:29,447 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.2639 Process Time: 0.543 Mem R(MA/MR): 10794 (21200/36094) [2025-04-28 19:40:30,479 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5528 Process Time: 0.183 Mem R(MA/MR): 9338 (21200/36094) [2025-04-28 19:40:34,873 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.4082 Process Time: 0.299 Mem R(MA/MR): 17146 (21200/36094) [2025-04-28 19:40:36,311 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3649 Process Time: 0.500 Mem R(MA/MR): 7918 (21200/36094) [2025-04-28 19:40:39,933 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.8697 Process Time: 0.478 Mem R(MA/MR): 21016 (21200/36094) [2025-04-28 19:40:40,254 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1803 Process Time: 0.140 Mem R(MA/MR): 4124 (21200/36094) [2025-04-28 19:40:43,591 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.1177 Process Time: 0.390 Mem R(MA/MR): 25080 (21200/36094) [2025-04-28 19:40:45,427 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5503 Process Time: 0.742 Mem R(MA/MR): 10156 (21200/36094) [2025-04-28 19:40:47,372 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.9240 Process Time: 0.565 Mem R(MA/MR): 14484 (21200/36094) [2025-04-28 19:40:47,865 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1576 Process Time: 0.168 Mem R(MA/MR): 6980 (21200/36094) [2025-04-28 19:40:51,204 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.4892 Process Time: 0.513 Mem R(MA/MR): 28506 (21200/36094) [2025-04-28 19:40:53,258 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.8989 Process Time: 0.813 Mem R(MA/MR): 10830 (21200/36094) [2025-04-28 19:40:53,902 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0841 Process Time: 0.204 Mem R(MA/MR): 6162 (21200/36094) [2025-04-28 19:40:55,102 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8740 Process Time: 0.352 Mem R(MA/MR): 10504 (21200/36094) [2025-04-28 19:40:56,231 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.2542 Process Time: 0.384 Mem R(MA/MR): 9522 (21200/36094) [2025-04-28 19:40:56,688 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.9575 Process Time: 0.138 Mem R(MA/MR): 6126 (21200/36094) [2025-04-28 19:40:57,093 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9397 Process Time: 0.119 Mem R(MA/MR): 6180 (21200/36094) [2025-04-28 19:40:57,617 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.7378 Process Time: 0.209 Mem R(MA/MR): 7416 (21200/36094) [2025-04-28 19:40:58,149 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7255 Process Time: 0.128 Mem R(MA/MR): 5584 (21200/36094) [2025-04-28 19:41:00,102 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8770 Process Time: 0.334 Mem R(MA/MR): 15138 (21200/36094) [2025-04-28 19:41:07,407 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.6575 Process Time: 1.255 Mem R(MA/MR): 20156 (21200/36094) [2025-04-28 19:41:17,024 INFO hook.py line 449 1619929] Test: [48/50] Loss 13.6494 Process Time: 0.976 Mem R(MA/MR): 35846 (21200/36094) [2025-04-28 19:41:17,555 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.5450 Process Time: 0.127 Mem R(MA/MR): 6472 (21200/36094) [2025-04-28 19:41:19,559 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2951 Process Time: 0.333 Mem R(MA/MR): 14022 (21200/36094) [2025-04-28 19:41:24,044 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 19:41:24,044 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 19:41:24,044 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 19:41:24,044 INFO hook.py line 395 1619929] table : 0.197 0.522 0.732 0.815 0.485 [2025-04-28 19:41:24,044 INFO hook.py line 395 1619929] door : 0.398 0.667 0.893 0.857 0.684 [2025-04-28 19:41:24,044 INFO hook.py line 395 1619929] ceiling lamp : 0.510 0.687 0.877 0.859 0.641 [2025-04-28 19:41:24,044 INFO hook.py line 395 1619929] cabinet : 0.302 0.459 0.539 0.466 0.507 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] blinds : 0.482 0.674 0.802 0.643 0.783 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] curtain : 0.276 0.374 0.688 0.667 0.500 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] chair : 0.588 0.755 0.788 0.811 0.684 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] storage cabinet: 0.174 0.405 0.641 0.421 0.640 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] office chair : 0.558 0.630 0.644 0.635 0.833 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] bookshelf : 0.265 0.585 0.675 0.700 0.636 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] whiteboard : 0.486 0.634 0.702 0.727 0.686 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] window : 0.068 0.206 0.560 0.439 0.275 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] box : 0.179 0.345 0.551 0.591 0.376 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] monitor : 0.565 0.698 0.799 0.870 0.671 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] shelf : 0.064 0.141 0.296 0.318 0.233 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] heater : 0.371 0.629 0.828 0.862 0.658 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] kitchen cabinet: 0.146 0.353 0.726 0.562 0.360 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] sofa : 0.447 0.825 0.860 0.909 0.833 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] bed : 0.205 0.592 1.000 1.000 0.500 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] trash can : 0.530 0.712 0.745 0.810 0.785 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] book : 0.010 0.027 0.074 0.164 0.094 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] plant : 0.388 0.667 0.709 1.000 0.667 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] blanket : 0.496 0.798 0.798 0.889 0.727 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] tv : 0.717 0.833 0.833 1.000 0.833 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] computer tower : 0.169 0.275 0.592 0.441 0.357 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] refrigerator : 0.243 0.386 0.399 1.000 0.333 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] jacket : 0.032 0.142 0.373 0.269 0.636 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] sink : 0.327 0.551 0.858 0.812 0.591 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] bag : 0.036 0.061 0.160 0.195 0.296 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] picture : 0.142 0.314 0.400 0.519 0.359 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] pillow : 0.535 0.699 0.741 1.000 0.632 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] towel : 0.120 0.289 0.503 0.632 0.316 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] suitcase : 0.250 0.362 0.395 0.750 0.429 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] backpack : 0.400 0.554 0.602 0.857 0.462 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] crate : 0.076 0.352 0.522 0.429 0.545 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] keyboard : 0.339 0.509 0.582 0.731 0.487 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] toilet : 0.815 0.889 1.000 1.000 0.889 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] printer : 0.317 0.326 0.364 0.750 0.333 [2025-04-28 19:41:24,045 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.002 0.036 0.111 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.062 0.125 1.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] microwave : 0.480 0.858 0.985 0.875 0.875 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] shoes : 0.102 0.177 0.453 0.417 0.366 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] socket : 0.200 0.461 0.628 0.739 0.464 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] bottle : 0.094 0.207 0.280 0.690 0.241 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] bucket : 0.029 0.031 0.040 0.200 0.286 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] cushion : 0.069 0.236 0.491 0.500 0.333 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] basket : 0.001 0.006 0.006 0.083 0.143 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] telephone : 0.254 0.458 0.622 0.800 0.471 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] laptop : 0.362 0.456 0.480 0.500 0.750 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] plant pot : 0.119 0.174 0.320 0.500 0.250 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] exhaust fan : 0.067 0.128 0.128 0.571 0.267 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] cup : 0.262 0.371 0.447 0.842 0.364 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] coat hanger : 0.174 0.250 0.500 1.000 0.250 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] light switch : 0.212 0.452 0.636 0.714 0.462 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] speaker : 0.338 0.426 0.426 0.714 0.455 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.264 1.000 0.167 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] smoke detector : 0.709 0.893 0.897 0.950 0.792 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] power strip : 0.041 0.066 0.097 0.222 0.400 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] paper bag : 0.083 0.083 0.083 0.167 1.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] mouse : 0.395 0.573 0.711 0.850 0.531 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] cutting board : 0.378 0.750 0.750 1.000 0.750 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] toilet paper : 0.183 0.283 0.340 0.833 0.294 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] clock : 0.405 0.764 0.764 0.750 1.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] pan : 0.111 0.250 0.250 1.000 0.250 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] tap : 0.164 0.341 0.720 0.800 0.444 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,046 INFO hook.py line 395 1619929] soap dispenser : 0.470 0.510 0.556 0.600 0.600 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] bowl : 0.025 0.042 0.278 0.250 0.333 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] whiteboard eraser: 0.218 0.587 0.603 0.625 0.833 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] toilet brush : 0.435 0.669 0.862 0.800 0.667 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] spray bottle : 0.012 0.018 0.031 0.143 0.250 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] headphones : 0.011 0.028 0.500 0.111 0.500 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] stapler : 0.002 0.019 0.033 0.111 0.333 [2025-04-28 19:41:24,047 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 19:41:24,047 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 19:41:24,047 INFO hook.py line 404 1619929] average : 0.236 0.369 0.483 0.572 0.457 [2025-04-28 19:41:24,047 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 19:41:24,047 INFO hook.py line 480 1619929] Total Process Time: 23.140 s [2025-04-28 19:41:24,047 INFO hook.py line 481 1619929] Average Process Time: 465.800 ms [2025-04-28 19:41:24,047 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 19:41:24,088 INFO hook.py line 685 1619929] Currently Best AP50: 0.383 [2025-04-28 19:41:24,093 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:42:51,135 INFO hook.py line 650 1619929] Train: [161/512][50/242] Data 0.017 (0.017) Batch 1.407 (1.461) Remain 34:32:26 loss: 5.3284 Lr: 2.14055e-04 Mem R(MA/MR): 21754 (21200/36094) [2025-04-28 19:44:03,640 INFO hook.py line 650 1619929] Train: [161/512][100/242] Data 0.018 (0.023) Batch 1.364 (1.455) Remain 34:23:33 loss: 5.6505 Lr: 2.13942e-04 Mem R(MA/MR): 23364 (21200/36094) [2025-04-28 19:45:12,545 INFO hook.py line 650 1619929] Train: [161/512][150/242] Data 0.016 (0.021) Batch 1.462 (1.429) Remain 33:45:09 loss: 7.5708 Lr: 2.13829e-04 Mem R(MA/MR): 26018 (21200/36094) [2025-04-28 19:46:21,937 INFO hook.py line 650 1619929] Train: [161/512][200/242] Data 0.015 (0.019) Batch 1.455 (1.419) Remain 33:29:12 loss: 6.8537 Lr: 2.13716e-04 Mem R(MA/MR): 28254 (21200/36094) [2025-04-28 19:47:17,471 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4303 loss_mask: 0.0421 loss_dice: 2.2896 loss_score: 0.0000 loss_bbox: 0.0555 loss_sp_cls: 0.9213 loss: 6.0079 [2025-04-28 19:47:18,214 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:48:50,144 INFO hook.py line 650 1619929] Train: [162/512][50/242] Data 0.070 (0.018) Batch 1.439 (1.436) Remain 33:51:17 loss: 5.7033 Lr: 2.13508e-04 Mem R(MA/MR): 25932 (21200/36094) [2025-04-28 19:49:59,275 INFO hook.py line 650 1619929] Train: [162/512][100/242] Data 0.015 (0.017) Batch 1.444 (1.408) Remain 33:11:24 loss: 6.1106 Lr: 2.13395e-04 Mem R(MA/MR): 25938 (21200/36094) [2025-04-28 19:51:10,156 INFO hook.py line 650 1619929] Train: [162/512][150/242] Data 0.017 (0.017) Batch 1.463 (1.411) Remain 33:14:41 loss: 5.4710 Lr: 2.13281e-04 Mem R(MA/MR): 25938 (21200/36094) [2025-04-28 19:52:18,008 INFO hook.py line 650 1619929] Train: [162/512][200/242] Data 0.014 (0.017) Batch 1.352 (1.398) Remain 32:54:00 loss: 7.1604 Lr: 2.13168e-04 Mem R(MA/MR): 25938 (21200/36094) [2025-04-28 19:53:15,378 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4322 loss_mask: 0.0434 loss_dice: 2.2978 loss_score: 0.0000 loss_bbox: 0.0557 loss_sp_cls: 0.9291 loss: 6.0324 [2025-04-28 19:53:16,199 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 19:54:46,321 INFO hook.py line 650 1619929] Train: [163/512][50/242] Data 0.016 (0.017) Batch 1.224 (1.432) Remain 33:40:45 loss: 5.2204 Lr: 2.12960e-04 Mem R(MA/MR): 21988 (21200/36094) [2025-04-28 19:55:58,059 INFO hook.py line 650 1619929] Train: [163/512][100/242] Data 0.017 (0.017) Batch 1.394 (1.434) Remain 33:41:19 loss: 5.3161 Lr: 2.12847e-04 Mem R(MA/MR): 23760 (21200/36094) [2025-04-28 19:57:07,992 INFO hook.py line 650 1619929] Train: [163/512][150/242] Data 0.017 (0.016) Batch 1.521 (1.422) Remain 33:23:23 loss: 5.8205 Lr: 2.12734e-04 Mem R(MA/MR): 23760 (21200/36094) [2025-04-28 19:58:17,235 INFO hook.py line 650 1619929] Train: [163/512][200/242] Data 0.016 (0.016) Batch 1.496 (1.412) Remain 33:09:03 loss: 7.4118 Lr: 2.12620e-04 Mem R(MA/MR): 23760 (21200/36094) [2025-04-28 19:59:11,401 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4255 loss_mask: 0.0431 loss_dice: 2.2844 loss_score: 0.0000 loss_bbox: 0.0560 loss_sp_cls: 0.9206 loss: 5.9909 [2025-04-28 19:59:11,468 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:00:36,543 INFO hook.py line 650 1619929] Train: [164/512][50/242] Data 0.015 (0.016) Batch 1.422 (1.396) Remain 32:43:28 loss: 5.0351 Lr: 2.12412e-04 Mem R(MA/MR): 19278 (21200/36094) [2025-04-28 20:01:46,118 INFO hook.py line 650 1619929] Train: [164/512][100/242] Data 0.017 (0.016) Batch 1.458 (1.394) Remain 32:39:18 loss: 5.8007 Lr: 2.12299e-04 Mem R(MA/MR): 21200 (21200/36094) [2025-04-28 20:02:58,186 INFO hook.py line 650 1619929] Train: [164/512][150/242] Data 0.015 (0.016) Batch 1.513 (1.410) Remain 33:00:59 loss: 6.3099 Lr: 2.12186e-04 Mem R(MA/MR): 23556 (21200/36094) [2025-04-28 20:04:06,803 INFO hook.py line 650 1619929] Train: [164/512][200/242] Data 0.015 (0.016) Batch 1.380 (1.400) Remain 32:46:27 loss: 5.6805 Lr: 2.12075e-04 Mem R(MA/MR): 23556 (21200/36094) [2025-04-28 20:05:00,904 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4191 loss_mask: 0.0410 loss_dice: 2.2478 loss_score: 0.0000 loss_bbox: 0.0551 loss_sp_cls: 0.9025 loss: 5.8998 [2025-04-28 20:05:01,225 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:06:30,987 INFO hook.py line 650 1619929] Train: [165/512][50/242] Data 0.016 (0.016) Batch 1.321 (1.409) Remain 32:56:56 loss: 6.5474 Lr: 2.11866e-04 Mem R(MA/MR): 19510 (21200/36094) [2025-04-28 20:07:39,519 INFO hook.py line 650 1619929] Train: [165/512][100/242] Data 0.016 (0.017) Batch 1.437 (1.389) Remain 32:27:48 loss: 7.3260 Lr: 2.11755e-04 Mem R(MA/MR): 20178 (21200/36094) [2025-04-28 20:08:49,452 INFO hook.py line 650 1619929] Train: [165/512][150/242] Data 0.016 (0.017) Batch 1.545 (1.393) Remain 32:31:04 loss: 6.3929 Lr: 2.11642e-04 Mem R(MA/MR): 20186 (21200/36094) [2025-04-28 20:09:59,428 INFO hook.py line 650 1619929] Train: [165/512][200/242] Data 0.014 (0.017) Batch 1.291 (1.394) Remain 32:32:23 loss: 6.3430 Lr: 2.11529e-04 Mem R(MA/MR): 20186 (21200/36094) [2025-04-28 20:10:55,238 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4670 loss_mask: 0.0464 loss_dice: 2.4149 loss_score: 0.0000 loss_bbox: 0.0577 loss_sp_cls: 0.9629 loss: 6.3488 [2025-04-28 20:10:55,360 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:12:20,874 INFO hook.py line 650 1619929] Train: [166/512][50/242] Data 0.016 (0.017) Batch 1.269 (1.428) Remain 33:16:52 loss: 6.7208 Lr: 2.11320e-04 Mem R(MA/MR): 21804 (21200/36094) [2025-04-28 20:13:30,060 INFO hook.py line 650 1619929] Train: [166/512][100/242] Data 0.016 (0.016) Batch 1.402 (1.405) Remain 32:44:01 loss: 4.9722 Lr: 2.11207e-04 Mem R(MA/MR): 21830 (21200/36094) [2025-04-28 20:14:39,498 INFO hook.py line 650 1619929] Train: [166/512][150/242] Data 0.017 (0.017) Batch 1.474 (1.399) Remain 32:35:08 loss: 6.9925 Lr: 2.11094e-04 Mem R(MA/MR): 21830 (21200/36094) [2025-04-28 20:15:48,509 INFO hook.py line 650 1619929] Train: [166/512][200/242] Data 0.015 (0.016) Batch 1.324 (1.395) Remain 32:27:09 loss: 5.0077 Lr: 2.10980e-04 Mem R(MA/MR): 23658 (21200/36094) [2025-04-28 20:16:45,449 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4733 loss_mask: 0.0481 loss_dice: 2.4323 loss_score: 0.0000 loss_bbox: 0.0587 loss_sp_cls: 0.9758 loss: 6.4017 [2025-04-28 20:16:47,092 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:18:10,706 INFO hook.py line 650 1619929] Train: [167/512][50/242] Data 0.016 (0.017) Batch 1.362 (1.438) Remain 33:24:55 loss: 6.2456 Lr: 2.10772e-04 Mem R(MA/MR): 23176 (21200/36094) [2025-04-28 20:19:19,584 INFO hook.py line 650 1619929] Train: [167/512][100/242] Data 0.015 (0.017) Batch 1.237 (1.407) Remain 32:40:38 loss: 4.9361 Lr: 2.10659e-04 Mem R(MA/MR): 24838 (21200/36094) [2025-04-28 20:20:29,283 INFO hook.py line 650 1619929] Train: [167/512][150/242] Data 0.016 (0.017) Batch 1.486 (1.402) Remain 32:33:27 loss: 6.7005 Lr: 2.10545e-04 Mem R(MA/MR): 26736 (21200/36094) [2025-04-28 20:21:38,593 INFO hook.py line 650 1619929] Train: [167/512][200/242] Data 0.016 (0.017) Batch 1.388 (1.398) Remain 32:26:37 loss: 6.0718 Lr: 2.10432e-04 Mem R(MA/MR): 26736 (21200/36094) [2025-04-28 20:22:35,529 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4666 loss_mask: 0.0450 loss_dice: 2.3793 loss_score: 0.0000 loss_bbox: 0.0575 loss_sp_cls: 0.9610 loss: 6.2814 [2025-04-28 20:22:39,719 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:24:07,611 INFO hook.py line 650 1619929] Train: [168/512][50/242] Data 0.015 (0.017) Batch 1.425 (1.450) Remain 33:36:10 loss: 6.3198 Lr: 2.10223e-04 Mem R(MA/MR): 21870 (21200/36094) [2025-04-28 20:25:17,812 INFO hook.py line 650 1619929] Train: [168/512][100/242] Data 0.016 (0.017) Batch 1.332 (1.426) Remain 33:02:11 loss: 7.2511 Lr: 2.10110e-04 Mem R(MA/MR): 21870 (21200/36094) [2025-04-28 20:26:29,666 INFO hook.py line 650 1619929] Train: [168/512][150/242] Data 0.016 (0.017) Batch 1.390 (1.430) Remain 33:06:08 loss: 6.5858 Lr: 2.09997e-04 Mem R(MA/MR): 21876 (21200/36094) [2025-04-28 20:27:37,926 INFO hook.py line 650 1619929] Train: [168/512][200/242] Data 0.016 (0.017) Batch 1.346 (1.413) Remain 32:42:09 loss: 7.9951 Lr: 2.09883e-04 Mem R(MA/MR): 21876 (21200/36094) [2025-04-28 20:28:33,122 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4582 loss_mask: 0.0449 loss_dice: 2.3976 loss_score: 0.0000 loss_bbox: 0.0589 loss_sp_cls: 0.9543 loss: 6.2948 [2025-04-28 20:28:33,191 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 20:28:35,489 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.9145 Process Time: 0.299 Mem R(MA/MR): 4272 (21200/36094) [2025-04-28 20:28:36,729 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.8167 Process Time: 0.403 Mem R(MA/MR): 6576 (21200/36094) [2025-04-28 20:28:39,053 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2548 Process Time: 1.107 Mem R(MA/MR): 9610 (21200/36094) [2025-04-28 20:28:47,104 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.2374 Process Time: 1.218 Mem R(MA/MR): 19388 (21200/36094) [2025-04-28 20:28:48,569 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.3065 Process Time: 0.578 Mem R(MA/MR): 6764 (21200/36094) [2025-04-28 20:28:50,150 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6901 Process Time: 0.467 Mem R(MA/MR): 10982 (21200/36094) [2025-04-28 20:28:50,763 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2722 Process Time: 0.180 Mem R(MA/MR): 6052 (21200/36094) [2025-04-28 20:28:51,196 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.4022 Process Time: 0.142 Mem R(MA/MR): 4310 (21200/36094) [2025-04-28 20:28:52,160 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.9792 Process Time: 0.213 Mem R(MA/MR): 11210 (21200/36094) [2025-04-28 20:28:53,742 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.6018 Process Time: 0.276 Mem R(MA/MR): 9376 (21200/36094) [2025-04-28 20:28:56,564 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0340 Process Time: 0.444 Mem R(MA/MR): 18404 (21200/36094) [2025-04-28 20:28:59,507 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2105 Process Time: 0.736 Mem R(MA/MR): 15026 (21200/36094) [2025-04-28 20:29:00,576 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7606 Process Time: 0.212 Mem R(MA/MR): 8592 (21200/36094) [2025-04-28 20:29:01,002 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.5639 Process Time: 0.146 Mem R(MA/MR): 4662 (21200/36094) [2025-04-28 20:29:03,391 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.7221 Process Time: 0.260 Mem R(MA/MR): 15910 (21200/36094) [2025-04-28 20:29:06,277 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0731 Process Time: 0.965 Mem R(MA/MR): 14438 (21200/36094) [2025-04-28 20:29:07,300 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.1277 Process Time: 0.364 Mem R(MA/MR): 6412 (21200/36094) [2025-04-28 20:29:08,429 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.2702 Process Time: 0.333 Mem R(MA/MR): 8240 (21200/36094) [2025-04-28 20:29:09,668 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.7363 Process Time: 0.147 Mem R(MA/MR): 5816 (21200/36094) [2025-04-28 20:29:11,219 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.7309 Process Time: 0.221 Mem R(MA/MR): 10948 (21200/36094) [2025-04-28 20:29:18,195 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.7682 Process Time: 0.610 Mem R(MA/MR): 22654 (21200/36094) [2025-04-28 20:29:18,734 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4876 Process Time: 0.150 Mem R(MA/MR): 6584 (21200/36094) [2025-04-28 20:29:26,007 INFO hook.py line 449 1619929] Test: [23/50] Loss 13.5231 Process Time: 0.274 Mem R(MA/MR): 8072 (21200/36094) [2025-04-28 20:29:26,442 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.7278 Process Time: 0.121 Mem R(MA/MR): 5106 (21200/36094) [2025-04-28 20:29:27,357 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2172 Process Time: 0.200 Mem R(MA/MR): 9288 (21200/36094) [2025-04-28 20:29:32,757 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.1015 Process Time: 0.699 Mem R(MA/MR): 30800 (21200/36094) [2025-04-28 20:29:35,431 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.4759 Process Time: 0.470 Mem R(MA/MR): 9860 (21200/36094) [2025-04-28 20:29:36,622 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.8051 Process Time: 0.254 Mem R(MA/MR): 8684 (21200/36094) [2025-04-28 20:29:40,790 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.9854 Process Time: 0.260 Mem R(MA/MR): 16534 (21200/36094) [2025-04-28 20:29:42,166 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3753 Process Time: 0.589 Mem R(MA/MR): 7602 (21200/36094) [2025-04-28 20:29:45,980 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.6572 Process Time: 0.553 Mem R(MA/MR): 19918 (21200/36094) [2025-04-28 20:29:46,249 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.5978 Process Time: 0.136 Mem R(MA/MR): 3758 (21200/36094) [2025-04-28 20:29:49,568 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.3031 Process Time: 0.339 Mem R(MA/MR): 24254 (21200/36094) [2025-04-28 20:29:51,272 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8155 Process Time: 0.739 Mem R(MA/MR): 9578 (21200/36094) [2025-04-28 20:29:53,040 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6120 Process Time: 0.377 Mem R(MA/MR): 13572 (21200/36094) [2025-04-28 20:29:53,502 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.7586 Process Time: 0.145 Mem R(MA/MR): 6278 (21200/36094) [2025-04-28 20:29:57,102 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.3675 Process Time: 0.500 Mem R(MA/MR): 28488 (21200/36094) [2025-04-28 20:29:59,549 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.1383 Process Time: 0.723 Mem R(MA/MR): 10220 (21200/36094) [2025-04-28 20:30:00,308 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3646 Process Time: 0.304 Mem R(MA/MR): 5280 (21200/36094) [2025-04-28 20:30:01,644 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8994 Process Time: 0.453 Mem R(MA/MR): 10026 (21200/36094) [2025-04-28 20:30:02,494 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.1692 Process Time: 0.183 Mem R(MA/MR): 8940 (21200/36094) [2025-04-28 20:30:02,909 INFO hook.py line 449 1619929] Test: [42/50] Loss 4.6201 Process Time: 0.119 Mem R(MA/MR): 5264 (21200/36094) [2025-04-28 20:30:03,354 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5880 Process Time: 0.157 Mem R(MA/MR): 5292 (21200/36094) [2025-04-28 20:30:03,934 INFO hook.py line 449 1619929] Test: [44/50] Loss 6.9730 Process Time: 0.175 Mem R(MA/MR): 6750 (21200/36094) [2025-04-28 20:30:04,508 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7654 Process Time: 0.135 Mem R(MA/MR): 5024 (21200/36094) [2025-04-28 20:30:06,689 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.9576 Process Time: 0.392 Mem R(MA/MR): 14486 (21200/36094) [2025-04-28 20:30:13,797 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.0312 Process Time: 0.952 Mem R(MA/MR): 19718 (21200/36094) [2025-04-28 20:30:24,930 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.2943 Process Time: 2.337 Mem R(MA/MR): 34274 (21200/36094) [2025-04-28 20:30:25,964 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1609 Process Time: 0.323 Mem R(MA/MR): 5498 (21200/36094) [2025-04-28 20:30:28,376 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5583 Process Time: 0.563 Mem R(MA/MR): 13500 (21200/36094) [2025-04-28 20:30:32,180 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 20:30:32,180 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 20:30:32,180 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] table : 0.239 0.561 0.769 0.760 0.559 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] door : 0.442 0.768 0.899 0.935 0.734 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] ceiling lamp : 0.523 0.669 0.774 0.829 0.669 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] cabinet : 0.288 0.427 0.494 0.565 0.522 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] blinds : 0.432 0.707 0.714 1.000 0.522 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] curtain : 0.433 0.673 0.720 0.700 0.583 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] chair : 0.554 0.700 0.746 0.743 0.676 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] storage cabinet: 0.278 0.373 0.437 0.520 0.520 [2025-04-28 20:30:32,180 INFO hook.py line 395 1619929] office chair : 0.553 0.603 0.604 0.723 0.708 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] bookshelf : 0.281 0.707 0.721 0.875 0.636 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] whiteboard : 0.602 0.768 0.848 0.962 0.714 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] window : 0.059 0.181 0.497 0.490 0.275 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] box : 0.176 0.310 0.499 0.507 0.381 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] monitor : 0.610 0.757 0.837 0.945 0.743 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] shelf : 0.036 0.114 0.198 0.303 0.333 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] heater : 0.397 0.663 0.795 0.931 0.711 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] kitchen cabinet: 0.123 0.419 0.737 0.632 0.480 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] sofa : 0.404 0.530 0.692 0.778 0.583 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] bed : 0.227 0.504 0.683 0.714 0.625 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] trash can : 0.533 0.687 0.749 0.746 0.769 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] book : 0.008 0.019 0.072 0.185 0.082 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] plant : 0.477 0.667 0.741 1.000 0.667 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] blanket : 0.473 0.667 0.668 1.000 0.636 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] tv : 0.611 0.667 0.667 1.000 0.667 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] computer tower : 0.169 0.353 0.642 0.474 0.429 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] refrigerator : 0.174 0.357 0.383 1.000 0.333 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] jacket : 0.056 0.131 0.247 0.364 0.364 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] sink : 0.389 0.688 0.832 0.850 0.773 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] bag : 0.071 0.094 0.102 0.500 0.185 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] picture : 0.153 0.321 0.416 0.577 0.385 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] pillow : 0.568 0.750 0.801 1.000 0.632 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] towel : 0.145 0.241 0.545 0.536 0.395 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] suitcase : 0.286 0.438 0.438 0.800 0.571 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] backpack : 0.257 0.362 0.404 0.714 0.385 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] crate : 0.036 0.197 0.531 0.429 0.273 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] keyboard : 0.406 0.582 0.640 0.714 0.641 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] toilet : 0.678 0.889 1.000 1.000 0.889 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] printer : 0.367 0.520 0.652 0.625 0.556 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] poster : 0.002 0.019 0.019 0.333 0.111 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] painting : 0.167 0.167 0.167 0.333 1.000 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] microwave : 0.466 0.653 0.935 0.833 0.625 [2025-04-28 20:30:32,181 INFO hook.py line 395 1619929] shoes : 0.093 0.188 0.511 0.542 0.317 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] socket : 0.162 0.381 0.579 0.640 0.393 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] bottle : 0.082 0.152 0.259 0.418 0.277 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] bucket : 0.109 0.136 0.141 0.300 0.429 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] cushion : 0.204 0.333 0.333 1.000 0.333 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] telephone : 0.284 0.661 0.667 1.000 0.588 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] laptop : 0.292 0.407 0.552 0.500 0.625 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] plant pot : 0.082 0.157 0.365 0.231 0.375 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] exhaust fan : 0.158 0.333 0.333 1.000 0.333 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] cup : 0.176 0.326 0.394 0.778 0.318 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] coat hanger : 0.333 0.750 0.750 1.000 0.750 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] light switch : 0.269 0.571 0.660 0.750 0.600 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] speaker : 0.325 0.438 0.566 0.833 0.455 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] kettle : 0.210 0.264 0.264 0.667 0.333 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] smoke detector : 0.642 0.824 0.826 0.950 0.792 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] power strip : 0.070 0.100 0.140 0.667 0.200 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] paper bag : 1.000 1.000 1.000 1.000 1.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] mouse : 0.463 0.631 0.657 0.905 0.594 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] toilet paper : 0.130 0.253 0.266 0.556 0.294 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] paper towel : 0.017 0.031 0.031 0.500 0.125 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] clock : 0.161 0.342 0.342 0.500 1.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] tap : 0.036 0.074 0.419 0.500 0.222 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] soap dispenser : 0.318 0.400 0.400 1.000 0.400 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,182 INFO hook.py line 395 1619929] whiteboard eraser: 0.180 0.474 0.486 0.800 0.667 [2025-04-28 20:30:32,183 INFO hook.py line 395 1619929] toilet brush : 0.424 0.672 0.855 0.800 0.667 [2025-04-28 20:30:32,183 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,183 INFO hook.py line 395 1619929] headphones : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 20:30:32,183 INFO hook.py line 395 1619929] stapler : 0.019 0.083 0.611 0.500 0.333 [2025-04-28 20:30:32,183 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 20:30:32,183 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 20:30:32,183 INFO hook.py line 404 1619929] average : 0.246 0.380 0.472 0.625 0.439 [2025-04-28 20:30:32,183 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 20:30:32,183 INFO hook.py line 480 1619929] Total Process Time: 21.944 s [2025-04-28 20:30:32,183 INFO hook.py line 481 1619929] Average Process Time: 441.733 ms [2025-04-28 20:30:32,183 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 20:30:32,214 INFO hook.py line 685 1619929] Currently Best AP50: 0.383 [2025-04-28 20:30:32,220 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:32:02,982 INFO hook.py line 650 1619929] Train: [169/512][50/242] Data 0.016 (0.034) Batch 1.456 (1.439) Remain 33:15:28 loss: 5.3942 Lr: 2.09675e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 20:33:10,836 INFO hook.py line 650 1619929] Train: [169/512][100/242] Data 0.016 (0.025) Batch 1.513 (1.397) Remain 32:15:40 loss: 5.6136 Lr: 2.09561e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 20:34:20,191 INFO hook.py line 650 1619929] Train: [169/512][150/242] Data 0.016 (0.022) Batch 1.442 (1.393) Remain 32:09:56 loss: 5.6907 Lr: 2.09448e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 20:35:29,864 INFO hook.py line 650 1619929] Train: [169/512][200/242] Data 0.014 (0.020) Batch 1.237 (1.393) Remain 32:08:47 loss: 5.4396 Lr: 2.09335e-04 Mem R(MA/MR): 23316 (21200/36094) [2025-04-28 20:36:25,279 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4466 loss_mask: 0.0447 loss_dice: 2.3431 loss_score: 0.0000 loss_bbox: 0.0571 loss_sp_cls: 0.9377 loss: 6.1503 [2025-04-28 20:36:25,449 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:37:55,284 INFO hook.py line 650 1619929] Train: [170/512][50/242] Data 0.016 (0.017) Batch 1.443 (1.432) Remain 32:59:18 loss: 6.3701 Lr: 2.09126e-04 Mem R(MA/MR): 24982 (21200/36094) [2025-04-28 20:39:06,504 INFO hook.py line 650 1619929] Train: [170/512][100/242] Data 0.017 (0.017) Batch 1.904 (1.428) Remain 32:53:00 loss: 6.8639 Lr: 2.09013e-04 Mem R(MA/MR): 27918 (21200/36094) [2025-04-28 20:40:14,971 INFO hook.py line 650 1619929] Train: [170/512][150/242] Data 0.016 (0.017) Batch 1.465 (1.408) Remain 32:24:19 loss: 7.4380 Lr: 2.08899e-04 Mem R(MA/MR): 29888 (21200/36094) [2025-04-28 20:41:24,615 INFO hook.py line 650 1619929] Train: [170/512][200/242] Data 0.015 (0.017) Batch 1.380 (1.404) Remain 32:17:52 loss: 4.9874 Lr: 2.08786e-04 Mem R(MA/MR): 29888 (21200/36094) [2025-04-28 20:42:20,171 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4377 loss_mask: 0.0445 loss_dice: 2.3310 loss_score: 0.0000 loss_bbox: 0.0566 loss_sp_cls: 0.9288 loss: 6.1048 [2025-04-28 20:42:21,071 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:43:45,980 INFO hook.py line 650 1619929] Train: [171/512][50/242] Data 0.016 (0.016) Batch 1.350 (1.414) Remain 32:28:40 loss: 5.1108 Lr: 2.08577e-04 Mem R(MA/MR): 24838 (21200/36094) [2025-04-28 20:44:53,293 INFO hook.py line 650 1619929] Train: [171/512][100/242] Data 0.016 (0.016) Batch 1.435 (1.379) Remain 31:39:41 loss: 5.5205 Lr: 2.08464e-04 Mem R(MA/MR): 24838 (21200/36094) [2025-04-28 20:46:03,285 INFO hook.py line 650 1619929] Train: [171/512][150/242] Data 0.015 (0.016) Batch 1.334 (1.386) Remain 31:48:22 loss: 5.3244 Lr: 2.08350e-04 Mem R(MA/MR): 24840 (21200/36094) [2025-04-28 20:47:13,402 INFO hook.py line 650 1619929] Train: [171/512][200/242] Data 0.014 (0.016) Batch 1.377 (1.390) Remain 31:52:56 loss: 5.5043 Lr: 2.08237e-04 Mem R(MA/MR): 24848 (21200/36094) [2025-04-28 20:48:08,735 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4388 loss_mask: 0.0430 loss_dice: 2.3235 loss_score: 0.0000 loss_bbox: 0.0566 loss_sp_cls: 0.9335 loss: 6.0969 [2025-04-28 20:48:08,871 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:49:36,312 INFO hook.py line 650 1619929] Train: [172/512][50/242] Data 0.017 (0.016) Batch 1.537 (1.383) Remain 31:40:33 loss: 6.0373 Lr: 2.08028e-04 Mem R(MA/MR): 21934 (21200/36094) [2025-04-28 20:50:45,756 INFO hook.py line 650 1619929] Train: [172/512][100/242] Data 0.015 (0.016) Batch 1.272 (1.386) Remain 31:43:48 loss: 5.2070 Lr: 2.07914e-04 Mem R(MA/MR): 26226 (21200/36094) [2025-04-28 20:51:56,490 INFO hook.py line 650 1619929] Train: [172/512][150/242] Data 0.016 (0.017) Batch 1.345 (1.396) Remain 31:56:05 loss: 5.2943 Lr: 2.07801e-04 Mem R(MA/MR): 27964 (21200/36094) [2025-04-28 20:53:06,340 INFO hook.py line 650 1619929] Train: [172/512][200/242] Data 0.015 (0.017) Batch 1.272 (1.396) Remain 31:55:23 loss: 4.6647 Lr: 2.07687e-04 Mem R(MA/MR): 30108 (21200/36094) [2025-04-28 20:54:00,743 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4339 loss_mask: 0.0425 loss_dice: 2.2887 loss_score: 0.0000 loss_bbox: 0.0562 loss_sp_cls: 0.9251 loss: 6.0220 [2025-04-28 20:54:03,153 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 20:55:34,065 INFO hook.py line 650 1619929] Train: [173/512][50/242] Data 0.021 (0.017) Batch 1.350 (1.431) Remain 32:41:38 loss: 5.8260 Lr: 2.07479e-04 Mem R(MA/MR): 21226 (21200/36094) [2025-04-28 20:56:41,810 INFO hook.py line 650 1619929] Train: [173/512][100/242] Data 0.016 (0.017) Batch 1.400 (1.392) Remain 31:46:29 loss: 5.6367 Lr: 2.07365e-04 Mem R(MA/MR): 21226 (21200/36094) [2025-04-28 20:57:49,771 INFO hook.py line 650 1619929] Train: [173/512][150/242] Data 0.017 (0.017) Batch 1.239 (1.381) Remain 31:30:05 loss: 5.3695 Lr: 2.07254e-04 Mem R(MA/MR): 23180 (21200/36094) [2025-04-28 20:58:56,702 INFO hook.py line 650 1619929] Train: [173/512][200/242] Data 0.014 (0.016) Batch 1.207 (1.370) Remain 31:14:18 loss: 6.1010 Lr: 2.07140e-04 Mem R(MA/MR): 25732 (21200/36094) [2025-04-28 20:59:51,772 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4332 loss_mask: 0.0424 loss_dice: 2.3078 loss_score: 0.0000 loss_bbox: 0.0554 loss_sp_cls: 0.9287 loss: 6.0407 [2025-04-28 20:59:56,395 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:01:27,212 INFO hook.py line 650 1619929] Train: [174/512][50/242] Data 0.016 (0.016) Batch 1.262 (1.420) Remain 32:20:17 loss: 6.2231 Lr: 2.06931e-04 Mem R(MA/MR): 21530 (21200/36094) [2025-04-28 21:02:34,890 INFO hook.py line 650 1619929] Train: [174/512][100/242] Data 0.017 (0.016) Batch 1.334 (1.386) Remain 31:32:22 loss: 4.8795 Lr: 2.06818e-04 Mem R(MA/MR): 23886 (21200/36094) [2025-04-28 21:03:43,618 INFO hook.py line 650 1619929] Train: [174/512][150/242] Data 0.017 (0.016) Batch 1.365 (1.382) Remain 31:26:02 loss: 5.3836 Lr: 2.06704e-04 Mem R(MA/MR): 23886 (21200/36094) [2025-04-28 21:04:52,959 INFO hook.py line 650 1619929] Train: [174/512][200/242] Data 0.014 (0.016) Batch 1.327 (1.383) Remain 31:26:35 loss: 6.0692 Lr: 2.06591e-04 Mem R(MA/MR): 23892 (21200/36094) [2025-04-28 21:05:47,635 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4314 loss_mask: 0.0429 loss_dice: 2.2984 loss_score: 0.0000 loss_bbox: 0.0561 loss_sp_cls: 0.9243 loss: 6.0289 [2025-04-28 21:05:51,223 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:07:15,975 INFO hook.py line 650 1619929] Train: [175/512][50/242] Data 0.016 (0.018) Batch 1.349 (1.424) Remain 32:20:00 loss: 5.1026 Lr: 2.06382e-04 Mem R(MA/MR): 22804 (21200/36094) [2025-04-28 21:08:24,442 INFO hook.py line 650 1619929] Train: [175/512][100/242] Data 0.015 (0.017) Batch 1.291 (1.396) Remain 31:40:30 loss: 4.8978 Lr: 2.06268e-04 Mem R(MA/MR): 22812 (21200/36094) [2025-04-28 21:09:35,104 INFO hook.py line 650 1619929] Train: [175/512][150/242] Data 0.015 (0.017) Batch 1.376 (1.402) Remain 31:47:25 loss: 6.0541 Lr: 2.06155e-04 Mem R(MA/MR): 22818 (21200/36094) [2025-04-28 21:10:45,550 INFO hook.py line 650 1619929] Train: [175/512][200/242] Data 0.015 (0.016) Batch 1.319 (1.404) Remain 31:48:45 loss: 5.1056 Lr: 2.06041e-04 Mem R(MA/MR): 26868 (21200/36094) [2025-04-28 21:11:40,807 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4254 loss_mask: 0.0437 loss_dice: 2.2826 loss_score: 0.0000 loss_bbox: 0.0557 loss_sp_cls: 0.9210 loss: 5.9807 [2025-04-28 21:11:40,887 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:13:04,769 INFO hook.py line 650 1619929] Train: [176/512][50/242] Data 0.016 (0.017) Batch 1.225 (1.460) Remain 33:02:50 loss: 4.4699 Lr: 2.05832e-04 Mem R(MA/MR): 19800 (21200/36094) [2025-04-28 21:14:14,664 INFO hook.py line 650 1619929] Train: [176/512][100/242] Data 0.015 (0.016) Batch 1.400 (1.428) Remain 32:18:22 loss: 5.2868 Lr: 2.05718e-04 Mem R(MA/MR): 19806 (21200/36094) [2025-04-28 21:15:23,947 INFO hook.py line 650 1619929] Train: [176/512][150/242] Data 0.015 (0.016) Batch 1.457 (1.413) Remain 31:57:43 loss: 6.7657 Lr: 2.05605e-04 Mem R(MA/MR): 21412 (21200/36094) [2025-04-28 21:16:32,313 INFO hook.py line 650 1619929] Train: [176/512][200/242] Data 0.015 (0.016) Batch 1.421 (1.402) Remain 31:40:39 loss: 6.2975 Lr: 2.05491e-04 Mem R(MA/MR): 23904 (21200/36094) [2025-04-28 21:17:26,966 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4263 loss_mask: 0.0423 loss_dice: 2.2843 loss_score: 0.0000 loss_bbox: 0.0548 loss_sp_cls: 0.9229 loss: 5.9844 [2025-04-28 21:17:27,772 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 21:17:30,397 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5378 Process Time: 0.559 Mem R(MA/MR): 4922 (21200/36094) [2025-04-28 21:17:32,211 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1495 Process Time: 0.659 Mem R(MA/MR): 7622 (21200/36094) [2025-04-28 21:17:33,782 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.9803 Process Time: 0.476 Mem R(MA/MR): 10144 (21200/36094) [2025-04-28 21:17:41,236 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.2865 Process Time: 1.132 Mem R(MA/MR): 20434 (21200/36094) [2025-04-28 21:17:42,236 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5045 Process Time: 0.409 Mem R(MA/MR): 7586 (21200/36094) [2025-04-28 21:17:43,641 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8159 Process Time: 0.502 Mem R(MA/MR): 11798 (21200/36094) [2025-04-28 21:17:44,179 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.4883 Process Time: 0.176 Mem R(MA/MR): 6782 (21200/36094) [2025-04-28 21:17:44,548 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.1216 Process Time: 0.103 Mem R(MA/MR): 4964 (21200/36094) [2025-04-28 21:17:45,232 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.1676 Process Time: 0.194 Mem R(MA/MR): 11340 (21200/36094) [2025-04-28 21:17:46,506 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.0178 Process Time: 0.248 Mem R(MA/MR): 9944 (21200/36094) [2025-04-28 21:17:49,560 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0317 Process Time: 0.971 Mem R(MA/MR): 18664 (21200/36094) [2025-04-28 21:17:52,118 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.4797 Process Time: 0.692 Mem R(MA/MR): 15164 (21200/36094) [2025-04-28 21:17:53,053 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0724 Process Time: 0.196 Mem R(MA/MR): 9040 (21200/36094) [2025-04-28 21:17:53,387 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.3366 Process Time: 0.105 Mem R(MA/MR): 5296 (21200/36094) [2025-04-28 21:17:55,684 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.8290 Process Time: 0.419 Mem R(MA/MR): 17004 (21200/36094) [2025-04-28 21:17:57,915 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.0683 Process Time: 0.757 Mem R(MA/MR): 14972 (21200/36094) [2025-04-28 21:17:58,703 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.5161 Process Time: 0.301 Mem R(MA/MR): 7238 (21200/36094) [2025-04-28 21:17:59,526 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.4695 Process Time: 0.218 Mem R(MA/MR): 8710 (21200/36094) [2025-04-28 21:18:00,846 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.2008 Process Time: 0.168 Mem R(MA/MR): 6806 (21200/36094) [2025-04-28 21:18:02,274 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.6132 Process Time: 0.237 Mem R(MA/MR): 11692 (21200/36094) [2025-04-28 21:18:10,930 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8955 Process Time: 0.872 Mem R(MA/MR): 24060 (21200/36094) [2025-04-28 21:18:11,460 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4215 Process Time: 0.152 Mem R(MA/MR): 7424 (21200/36094) [2025-04-28 21:18:21,349 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.0226 Process Time: 0.347 Mem R(MA/MR): 8944 (21200/36094) [2025-04-28 21:18:22,367 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8038 Process Time: 0.503 Mem R(MA/MR): 5928 (21200/36094) [2025-04-28 21:18:24,007 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8052 Process Time: 0.667 Mem R(MA/MR): 9916 (21200/36094) [2025-04-28 21:18:30,443 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.0025 Process Time: 0.990 Mem R(MA/MR): 31452 (21200/36094) [2025-04-28 21:18:33,787 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.3905 Process Time: 0.799 Mem R(MA/MR): 10484 (21200/36094) [2025-04-28 21:18:35,142 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.6064 Process Time: 0.310 Mem R(MA/MR): 9350 (21200/36094) [2025-04-28 21:18:40,073 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.2984 Process Time: 0.291 Mem R(MA/MR): 17408 (21200/36094) [2025-04-28 21:18:41,562 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.5643 Process Time: 0.754 Mem R(MA/MR): 8244 (21200/36094) [2025-04-28 21:18:45,701 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.1953 Process Time: 0.839 Mem R(MA/MR): 21246 (21200/36094) [2025-04-28 21:18:45,969 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1902 Process Time: 0.131 Mem R(MA/MR): 4594 (21200/36094) [2025-04-28 21:18:49,407 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.6552 Process Time: 0.395 Mem R(MA/MR): 25090 (21200/36094) [2025-04-28 21:18:50,983 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7780 Process Time: 0.477 Mem R(MA/MR): 10264 (21200/36094) [2025-04-28 21:18:52,998 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6196 Process Time: 0.560 Mem R(MA/MR): 14400 (21200/36094) [2025-04-28 21:18:53,432 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2349 Process Time: 0.158 Mem R(MA/MR): 7190 (21200/36094) [2025-04-28 21:18:56,719 INFO hook.py line 449 1619929] Test: [37/50] Loss 12.5980 Process Time: 0.385 Mem R(MA/MR): 28726 (21200/36094) [2025-04-28 21:18:59,566 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.3443 Process Time: 0.965 Mem R(MA/MR): 11144 (21200/36094) [2025-04-28 21:19:00,292 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.8364 Process Time: 0.268 Mem R(MA/MR): 6004 (21200/36094) [2025-04-28 21:19:01,828 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8014 Process Time: 0.514 Mem R(MA/MR): 10834 (21200/36094) [2025-04-28 21:19:02,747 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.5644 Process Time: 0.201 Mem R(MA/MR): 9554 (21200/36094) [2025-04-28 21:19:03,203 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.6240 Process Time: 0.135 Mem R(MA/MR): 6092 (21200/36094) [2025-04-28 21:19:03,677 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.1571 Process Time: 0.165 Mem R(MA/MR): 6152 (21200/36094) [2025-04-28 21:19:04,292 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.4889 Process Time: 0.173 Mem R(MA/MR): 7568 (21200/36094) [2025-04-28 21:19:04,991 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.1554 Process Time: 0.164 Mem R(MA/MR): 5812 (21200/36094) [2025-04-28 21:19:07,545 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.0949 Process Time: 0.454 Mem R(MA/MR): 15152 (21200/36094) [2025-04-28 21:19:15,168 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.9190 Process Time: 0.612 Mem R(MA/MR): 20484 (21200/36094) [2025-04-28 21:19:26,139 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.6994 Process Time: 2.301 Mem R(MA/MR): 35716 (21200/36094) [2025-04-28 21:19:27,188 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0451 Process Time: 0.370 Mem R(MA/MR): 6268 (21200/36094) [2025-04-28 21:19:29,347 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5560 Process Time: 0.472 Mem R(MA/MR): 13934 (21200/36094) [2025-04-28 21:19:33,930 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 21:19:33,930 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 21:19:33,930 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] table : 0.256 0.593 0.745 0.825 0.588 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] door : 0.415 0.730 0.869 0.946 0.671 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] ceiling lamp : 0.525 0.727 0.812 0.814 0.724 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] cabinet : 0.279 0.386 0.461 0.500 0.478 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] blinds : 0.443 0.609 0.760 0.739 0.739 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] curtain : 0.327 0.384 0.572 0.625 0.417 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] chair : 0.605 0.742 0.809 0.719 0.746 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] storage cabinet: 0.296 0.457 0.597 0.591 0.520 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] office chair : 0.491 0.563 0.583 0.667 0.792 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] bookshelf : 0.276 0.689 0.728 0.692 0.818 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] whiteboard : 0.549 0.712 0.737 0.958 0.657 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] window : 0.084 0.224 0.569 0.397 0.341 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] box : 0.163 0.335 0.485 0.526 0.387 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] monitor : 0.586 0.726 0.828 0.927 0.729 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] shelf : 0.094 0.184 0.391 0.556 0.167 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] heater : 0.418 0.673 0.803 0.771 0.711 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] kitchen cabinet: 0.139 0.349 0.710 0.529 0.360 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] sofa : 0.511 0.706 0.898 0.889 0.667 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] bed : 0.150 0.520 0.816 0.556 0.625 [2025-04-28 21:19:33,930 INFO hook.py line 395 1619929] trash can : 0.497 0.617 0.651 0.807 0.708 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] book : 0.011 0.038 0.067 0.242 0.109 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] plant : 0.382 0.616 0.709 0.857 0.667 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] blanket : 0.341 0.399 0.598 0.600 0.545 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] tv : 0.737 0.833 0.833 1.000 0.833 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] computer tower : 0.226 0.352 0.652 0.442 0.452 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] refrigerator : 0.222 0.369 0.379 1.000 0.333 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] jacket : 0.051 0.174 0.471 0.333 0.636 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] sink : 0.372 0.811 0.931 0.947 0.818 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] bag : 0.157 0.257 0.296 0.375 0.444 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] picture : 0.152 0.380 0.458 0.727 0.410 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] pillow : 0.670 0.847 0.886 0.938 0.789 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] towel : 0.177 0.348 0.523 0.700 0.368 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] suitcase : 0.482 0.513 0.651 1.000 0.429 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] backpack : 0.219 0.264 0.309 0.625 0.385 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] crate : 0.095 0.406 0.473 0.714 0.455 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] keyboard : 0.343 0.525 0.613 0.857 0.462 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] toilet : 0.754 0.876 1.000 0.889 0.889 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] printer : 0.270 0.329 0.333 0.571 0.444 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.083 0.125 1.000 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] microwave : 0.514 0.731 0.858 0.857 0.750 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] shoes : 0.124 0.282 0.593 0.519 0.341 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] socket : 0.178 0.404 0.644 0.535 0.493 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] bottle : 0.122 0.195 0.265 0.513 0.241 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] bucket : 0.182 0.265 0.271 0.188 0.857 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] cushion : 0.312 0.398 0.443 1.000 0.333 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] telephone : 0.307 0.522 0.569 0.692 0.529 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] laptop : 0.319 0.477 0.529 0.750 0.375 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] plant pot : 0.224 0.444 0.547 0.700 0.438 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] exhaust fan : 0.210 0.362 0.377 0.750 0.400 [2025-04-28 21:19:33,931 INFO hook.py line 395 1619929] cup : 0.188 0.339 0.406 0.778 0.318 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] coat hanger : 0.252 0.500 0.637 1.000 0.500 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] light switch : 0.232 0.473 0.620 0.660 0.508 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] speaker : 0.222 0.306 0.386 1.000 0.273 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] table lamp : 0.523 0.708 0.792 0.500 1.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] kettle : 0.021 0.021 0.021 0.250 0.167 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] smoke detector : 0.623 0.785 0.785 0.905 0.792 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] power strip : 0.038 0.055 0.236 0.176 0.300 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] mouse : 0.461 0.612 0.612 0.826 0.594 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] cutting board : 0.419 0.637 0.637 1.000 0.500 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] toilet paper : 0.154 0.279 0.337 0.462 0.353 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] paper towel : 0.059 0.254 0.254 0.500 0.375 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] clock : 0.407 0.667 0.667 1.000 0.667 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] tap : 0.099 0.133 0.417 0.250 0.222 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] soap dispenser : 0.454 0.587 0.587 0.750 0.600 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] bowl : 0.087 0.126 0.130 0.500 0.333 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] whiteboard eraser: 0.165 0.424 0.424 0.556 0.833 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] toilet brush : 0.436 0.722 0.907 1.000 0.667 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] spray bottle : 0.014 0.018 0.018 0.143 0.250 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] headphones : 0.167 0.500 0.500 1.000 0.500 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] stapler : 0.019 0.064 0.218 0.182 0.667 [2025-04-28 21:19:33,932 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 21:19:33,932 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 21:19:33,932 INFO hook.py line 404 1619929] average : 0.248 0.386 0.480 0.584 0.457 [2025-04-28 21:19:33,932 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 21:19:33,933 INFO hook.py line 480 1619929] Total Process Time: 23.945 s [2025-04-28 21:19:33,933 INFO hook.py line 481 1619929] Average Process Time: 477.281 ms [2025-04-28 21:19:33,933 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 21:19:33,982 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.386 [2025-04-28 21:19:33,987 INFO hook.py line 685 1619929] Currently Best AP50: 0.386 [2025-04-28 21:19:33,987 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:21:01,760 INFO hook.py line 650 1619929] Train: [177/512][50/242] Data 0.015 (0.017) Batch 1.380 (1.447) Remain 32:39:11 loss: 6.3189 Lr: 2.05282e-04 Mem R(MA/MR): 22548 (21200/36094) [2025-04-28 21:22:11,237 INFO hook.py line 650 1619929] Train: [177/512][100/242] Data 0.021 (0.017) Batch 1.447 (1.417) Remain 31:58:10 loss: 6.0593 Lr: 2.05168e-04 Mem R(MA/MR): 24376 (21200/36094) [2025-04-28 21:23:20,641 INFO hook.py line 650 1619929] Train: [177/512][150/242] Data 0.016 (0.017) Batch 1.322 (1.407) Remain 31:43:37 loss: 5.7315 Lr: 2.05055e-04 Mem R(MA/MR): 26928 (21200/36094) [2025-04-28 21:24:28,011 INFO hook.py line 650 1619929] Train: [177/512][200/242] Data 0.015 (0.020) Batch 1.378 (1.392) Remain 31:21:54 loss: 5.9155 Lr: 2.04941e-04 Mem R(MA/MR): 26928 (21200/36094) [2025-04-28 21:25:22,883 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4277 loss_mask: 0.0430 loss_dice: 2.2998 loss_score: 0.0000 loss_bbox: 0.0556 loss_sp_cls: 0.9224 loss: 6.0118 [2025-04-28 21:25:22,952 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:26:55,113 INFO hook.py line 650 1619929] Train: [178/512][50/242] Data 0.016 (0.017) Batch 1.400 (1.460) Remain 32:52:07 loss: 7.5484 Lr: 2.04732e-04 Mem R(MA/MR): 19252 (21200/36094) [2025-04-28 21:28:04,312 INFO hook.py line 650 1619929] Train: [178/512][100/242] Data 0.016 (0.017) Batch 1.522 (1.421) Remain 31:57:41 loss: 5.1180 Lr: 2.04618e-04 Mem R(MA/MR): 19258 (21200/36094) [2025-04-28 21:29:13,030 INFO hook.py line 650 1619929] Train: [178/512][150/242] Data 0.015 (0.017) Batch 1.251 (1.405) Remain 31:35:05 loss: 7.0101 Lr: 2.04504e-04 Mem R(MA/MR): 20932 (21200/36094) [2025-04-28 21:30:21,984 INFO hook.py line 650 1619929] Train: [178/512][200/242] Data 0.014 (0.017) Batch 1.304 (1.399) Remain 31:25:00 loss: 5.0789 Lr: 2.04391e-04 Mem R(MA/MR): 20942 (21200/36094) [2025-04-28 21:31:17,671 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4185 loss_mask: 0.0423 loss_dice: 2.2719 loss_score: 0.0000 loss_bbox: 0.0554 loss_sp_cls: 0.9125 loss: 5.9398 [2025-04-28 21:31:21,701 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:32:57,609 INFO hook.py line 650 1619929] Train: [179/512][50/242] Data 0.023 (0.022) Batch 1.500 (1.557) Remain 34:55:33 loss: 5.1069 Lr: 2.04181e-04 Mem R(MA/MR): 22206 (21200/36094) [2025-04-28 21:34:15,559 INFO hook.py line 650 1619929] Train: [179/512][100/242] Data 0.024 (0.022) Batch 1.406 (1.558) Remain 34:56:01 loss: 6.7772 Lr: 2.04068e-04 Mem R(MA/MR): 22220 (21200/36094) [2025-04-28 21:35:32,501 INFO hook.py line 650 1619929] Train: [179/512][150/242] Data 0.016 (0.022) Batch 1.390 (1.551) Remain 34:46:01 loss: 5.4579 Lr: 2.03954e-04 Mem R(MA/MR): 24154 (21200/36094) [2025-04-28 21:36:43,910 INFO hook.py line 650 1619929] Train: [179/512][200/242] Data 0.015 (0.021) Batch 1.572 (1.520) Remain 34:02:44 loss: 5.3181 Lr: 2.03840e-04 Mem R(MA/MR): 24154 (21200/36094) [2025-04-28 21:37:40,877 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4201 loss_mask: 0.0428 loss_dice: 2.2682 loss_score: 0.0000 loss_bbox: 0.0544 loss_sp_cls: 0.9165 loss: 5.9311 [2025-04-28 21:37:43,979 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:39:15,692 INFO hook.py line 650 1619929] Train: [180/512][50/242] Data 0.017 (0.019) Batch 1.510 (1.517) Remain 33:56:41 loss: 5.8799 Lr: 2.03631e-04 Mem R(MA/MR): 22520 (21200/36094) [2025-04-28 21:40:28,294 INFO hook.py line 650 1619929] Train: [180/512][100/242] Data 0.016 (0.018) Batch 1.629 (1.484) Remain 33:10:15 loss: 6.5519 Lr: 2.03517e-04 Mem R(MA/MR): 22520 (21200/36094) [2025-04-28 21:41:37,170 INFO hook.py line 650 1619929] Train: [180/512][150/242] Data 0.017 (0.018) Batch 1.512 (1.448) Remain 32:20:37 loss: 5.4108 Lr: 2.03404e-04 Mem R(MA/MR): 25094 (21200/36094) [2025-04-28 21:42:47,498 INFO hook.py line 650 1619929] Train: [180/512][200/242] Data 0.015 (0.017) Batch 1.382 (1.437) Remain 32:05:28 loss: 6.2688 Lr: 2.03290e-04 Mem R(MA/MR): 25094 (21200/36094) [2025-04-28 21:43:42,565 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4188 loss_mask: 0.0429 loss_dice: 2.2663 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.9167 loss: 5.9345 [2025-04-28 21:43:43,795 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:45:12,665 INFO hook.py line 650 1619929] Train: [181/512][50/242] Data 0.017 (0.017) Batch 1.403 (1.355) Remain 30:13:01 loss: 5.3984 Lr: 2.03080e-04 Mem R(MA/MR): 18876 (21200/36094) [2025-04-28 21:46:20,787 INFO hook.py line 650 1619929] Train: [181/512][100/242] Data 0.017 (0.017) Batch 1.511 (1.359) Remain 30:17:08 loss: 6.1988 Lr: 2.02967e-04 Mem R(MA/MR): 20774 (21200/36094) [2025-04-28 21:47:30,299 INFO hook.py line 650 1619929] Train: [181/512][150/242] Data 0.016 (0.016) Batch 1.533 (1.369) Remain 30:30:20 loss: 5.8511 Lr: 2.02853e-04 Mem R(MA/MR): 20774 (21200/36094) [2025-04-28 21:48:40,874 INFO hook.py line 650 1619929] Train: [181/512][200/242] Data 0.015 (0.016) Batch 1.394 (1.380) Remain 30:43:28 loss: 4.9808 Lr: 2.02739e-04 Mem R(MA/MR): 21566 (21200/36094) [2025-04-28 21:49:37,073 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4153 loss_mask: 0.0417 loss_dice: 2.2683 loss_score: 0.0000 loss_bbox: 0.0546 loss_sp_cls: 0.9106 loss: 5.9162 [2025-04-28 21:49:37,221 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:51:00,156 INFO hook.py line 650 1619929] Train: [182/512][50/242] Data 0.016 (0.017) Batch 1.467 (1.421) Remain 31:35:25 loss: 5.5018 Lr: 2.02530e-04 Mem R(MA/MR): 23508 (21200/36094) [2025-04-28 21:52:10,097 INFO hook.py line 650 1619929] Train: [182/512][100/242] Data 0.015 (0.017) Batch 1.388 (1.409) Remain 31:19:14 loss: 6.5853 Lr: 2.02416e-04 Mem R(MA/MR): 23520 (21200/36094) [2025-04-28 21:53:20,351 INFO hook.py line 650 1619929] Train: [182/512][150/242] Data 0.015 (0.016) Batch 1.385 (1.408) Remain 31:16:04 loss: 4.7100 Lr: 2.02304e-04 Mem R(MA/MR): 23520 (21200/36094) [2025-04-28 21:54:27,741 INFO hook.py line 650 1619929] Train: [182/512][200/242] Data 0.015 (0.016) Batch 1.337 (1.393) Remain 30:54:37 loss: 6.3203 Lr: 2.02190e-04 Mem R(MA/MR): 25532 (21200/36094) [2025-04-28 21:55:23,124 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4039 loss_mask: 0.0412 loss_dice: 2.2148 loss_score: 0.0000 loss_bbox: 0.0546 loss_sp_cls: 0.8916 loss: 5.7929 [2025-04-28 21:55:25,182 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 21:56:55,468 INFO hook.py line 650 1619929] Train: [183/512][50/242] Data 0.016 (0.016) Batch 1.372 (1.405) Remain 31:08:44 loss: 5.8905 Lr: 2.01981e-04 Mem R(MA/MR): 21512 (21200/36094) [2025-04-28 21:58:05,580 INFO hook.py line 650 1619929] Train: [183/512][100/242] Data 0.015 (0.016) Batch 1.405 (1.404) Remain 31:05:44 loss: 7.0431 Lr: 2.01867e-04 Mem R(MA/MR): 23602 (21200/36094) [2025-04-28 21:59:15,325 INFO hook.py line 650 1619929] Train: [183/512][150/242] Data 0.018 (0.016) Batch 1.408 (1.401) Remain 31:00:41 loss: 6.7186 Lr: 2.01753e-04 Mem R(MA/MR): 23614 (21200/36094) [2025-04-28 22:00:22,190 INFO hook.py line 650 1619929] Train: [183/512][200/242] Data 0.014 (0.016) Batch 1.264 (1.385) Remain 30:38:11 loss: 5.9511 Lr: 2.01639e-04 Mem R(MA/MR): 23614 (21200/36094) [2025-04-28 22:01:17,707 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4202 loss_mask: 0.0421 loss_dice: 2.2706 loss_score: 0.0000 loss_bbox: 0.0553 loss_sp_cls: 0.9113 loss: 5.9396 [2025-04-28 22:01:18,318 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:02:53,585 INFO hook.py line 650 1619929] Train: [184/512][50/242] Data 0.023 (0.022) Batch 1.630 (1.586) Remain 35:02:48 loss: 5.0795 Lr: 2.01430e-04 Mem R(MA/MR): 25532 (21200/36094) [2025-04-28 22:04:11,315 INFO hook.py line 650 1619929] Train: [184/512][100/242] Data 0.024 (0.021) Batch 1.884 (1.570) Remain 34:40:19 loss: 6.3469 Lr: 2.01316e-04 Mem R(MA/MR): 29356 (21200/36094) [2025-04-28 22:05:26,186 INFO hook.py line 650 1619929] Train: [184/512][150/242] Data 0.017 (0.021) Batch 1.544 (1.545) Remain 34:06:28 loss: 5.1260 Lr: 2.01202e-04 Mem R(MA/MR): 29360 (21200/36094) [2025-04-28 22:06:41,355 INFO hook.py line 650 1619929] Train: [184/512][200/242] Data 0.014 (0.020) Batch 1.399 (1.534) Remain 33:51:06 loss: 5.9689 Lr: 2.01088e-04 Mem R(MA/MR): 29360 (21200/36094) [2025-04-28 22:07:40,011 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4146 loss_mask: 0.0427 loss_dice: 2.2509 loss_score: 0.0000 loss_bbox: 0.0551 loss_sp_cls: 0.9134 loss: 5.8967 [2025-04-28 22:07:42,698 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 22:07:45,305 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.9492 Process Time: 0.331 Mem R(MA/MR): 4588 (21200/36094) [2025-04-28 22:07:46,837 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1520 Process Time: 0.469 Mem R(MA/MR): 7490 (21200/36094) [2025-04-28 22:07:49,290 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2424 Process Time: 1.258 Mem R(MA/MR): 9904 (21200/36094) [2025-04-28 22:07:56,796 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3975 Process Time: 1.396 Mem R(MA/MR): 19930 (21200/36094) [2025-04-28 22:07:58,051 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.0624 Process Time: 0.504 Mem R(MA/MR): 7494 (21200/36094) [2025-04-28 22:07:59,921 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8498 Process Time: 0.597 Mem R(MA/MR): 11592 (21200/36094) [2025-04-28 22:08:00,581 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3850 Process Time: 0.239 Mem R(MA/MR): 6518 (21200/36094) [2025-04-28 22:08:01,052 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.2475 Process Time: 0.129 Mem R(MA/MR): 4630 (21200/36094) [2025-04-28 22:08:02,003 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.3672 Process Time: 0.227 Mem R(MA/MR): 11586 (21200/36094) [2025-04-28 22:08:03,642 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.2530 Process Time: 0.317 Mem R(MA/MR): 9780 (21200/36094) [2025-04-28 22:08:07,254 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.4791 Process Time: 1.103 Mem R(MA/MR): 18816 (21200/36094) [2025-04-28 22:08:10,516 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1525 Process Time: 0.886 Mem R(MA/MR): 15182 (21200/36094) [2025-04-28 22:08:11,700 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1431 Process Time: 0.266 Mem R(MA/MR): 8958 (21200/36094) [2025-04-28 22:08:12,165 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9637 Process Time: 0.202 Mem R(MA/MR): 5012 (21200/36094) [2025-04-28 22:08:15,189 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.8613 Process Time: 0.897 Mem R(MA/MR): 16640 (21200/36094) [2025-04-28 22:08:17,428 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.8798 Process Time: 0.779 Mem R(MA/MR): 14672 (21200/36094) [2025-04-28 22:08:18,115 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.2708 Process Time: 0.186 Mem R(MA/MR): 6950 (21200/36094) [2025-04-28 22:08:19,002 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9122 Process Time: 0.209 Mem R(MA/MR): 8460 (21200/36094) [2025-04-28 22:08:20,435 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9663 Process Time: 0.162 Mem R(MA/MR): 6528 (21200/36094) [2025-04-28 22:08:22,074 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.1757 Process Time: 0.258 Mem R(MA/MR): 11628 (21200/36094) [2025-04-28 22:08:31,571 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.0707 Process Time: 1.285 Mem R(MA/MR): 24098 (21200/36094) [2025-04-28 22:08:33,173 INFO hook.py line 449 1619929] Test: [22/50] Loss 6.0436 Process Time: 0.399 Mem R(MA/MR): 7108 (21200/36094) [2025-04-28 22:08:42,864 INFO hook.py line 449 1619929] Test: [23/50] Loss 20.0077 Process Time: 0.581 Mem R(MA/MR): 10384 (21200/36094) [2025-04-28 22:08:43,723 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.3719 Process Time: 0.370 Mem R(MA/MR): 5612 (21200/36094) [2025-04-28 22:08:44,710 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0074 Process Time: 0.236 Mem R(MA/MR): 9610 (21200/36094) [2025-04-28 22:08:51,571 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.1275 Process Time: 1.365 Mem R(MA/MR): 31792 (21200/36094) [2025-04-28 22:08:54,597 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.3516 Process Time: 0.554 Mem R(MA/MR): 10396 (21200/36094) [2025-04-28 22:08:55,670 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.7245 Process Time: 0.187 Mem R(MA/MR): 9190 (21200/36094) [2025-04-28 22:09:00,360 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9355 Process Time: 0.536 Mem R(MA/MR): 17106 (21200/36094) [2025-04-28 22:09:01,302 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.8260 Process Time: 0.238 Mem R(MA/MR): 7988 (21200/36094) [2025-04-28 22:09:04,797 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0787 Process Time: 0.382 Mem R(MA/MR): 20634 (21200/36094) [2025-04-28 22:09:05,211 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.4143 Process Time: 0.208 Mem R(MA/MR): 4254 (21200/36094) [2025-04-28 22:09:09,819 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.6541 Process Time: 1.187 Mem R(MA/MR): 25050 (21200/36094) [2025-04-28 22:09:10,918 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7574 Process Time: 0.303 Mem R(MA/MR): 10128 (21200/36094) [2025-04-28 22:09:12,440 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0604 Process Time: 0.230 Mem R(MA/MR): 14186 (21200/36094) [2025-04-28 22:09:12,898 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1116 Process Time: 0.143 Mem R(MA/MR): 6836 (21200/36094) [2025-04-28 22:09:16,424 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.2305 Process Time: 0.400 Mem R(MA/MR): 28904 (21200/36094) [2025-04-28 22:09:18,178 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5733 Process Time: 0.453 Mem R(MA/MR): 10858 (21200/36094) [2025-04-28 22:09:18,733 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.8018 Process Time: 0.205 Mem R(MA/MR): 5794 (21200/36094) [2025-04-28 22:09:19,787 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.2354 Process Time: 0.208 Mem R(MA/MR): 10396 (21200/36094) [2025-04-28 22:09:20,661 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.2061 Process Time: 0.189 Mem R(MA/MR): 9358 (21200/36094) [2025-04-28 22:09:21,116 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3181 Process Time: 0.162 Mem R(MA/MR): 5786 (21200/36094) [2025-04-28 22:09:21,502 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7684 Process Time: 0.118 Mem R(MA/MR): 5852 (21200/36094) [2025-04-28 22:09:22,037 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.7722 Process Time: 0.152 Mem R(MA/MR): 7328 (21200/36094) [2025-04-28 22:09:22,607 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.9490 Process Time: 0.128 Mem R(MA/MR): 5362 (21200/36094) [2025-04-28 22:09:25,475 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.0280 Process Time: 0.560 Mem R(MA/MR): 14824 (21200/36094) [2025-04-28 22:09:31,651 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.8672 Process Time: 0.635 Mem R(MA/MR): 20362 (21200/36094) [2025-04-28 22:09:43,073 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.4735 Process Time: 2.156 Mem R(MA/MR): 35718 (21200/36094) [2025-04-28 22:09:44,135 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1802 Process Time: 0.372 Mem R(MA/MR): 6038 (21200/36094) [2025-04-28 22:09:46,773 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.7019 Process Time: 0.790 Mem R(MA/MR): 13778 (21200/36094) [2025-04-28 22:09:50,874 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 22:09:50,874 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 22:09:50,874 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] table : 0.255 0.596 0.781 0.720 0.625 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] door : 0.430 0.765 0.890 0.870 0.759 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] ceiling lamp : 0.524 0.700 0.836 0.913 0.641 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] cabinet : 0.295 0.460 0.521 0.550 0.493 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] blinds : 0.554 0.740 0.854 0.882 0.652 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] curtain : 0.166 0.342 0.700 0.500 0.667 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] chair : 0.611 0.737 0.809 0.846 0.676 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] storage cabinet: 0.249 0.416 0.567 0.565 0.520 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] office chair : 0.542 0.589 0.602 0.714 0.729 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] bookshelf : 0.340 0.682 0.690 0.800 0.727 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] whiteboard : 0.549 0.710 0.723 1.000 0.657 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] window : 0.111 0.268 0.595 0.404 0.396 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] box : 0.165 0.343 0.530 0.500 0.414 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] monitor : 0.608 0.729 0.788 0.906 0.686 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] shelf : 0.085 0.167 0.449 0.421 0.267 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] heater : 0.424 0.689 0.783 0.867 0.684 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] kitchen cabinet: 0.186 0.328 0.662 0.643 0.360 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] sofa : 0.437 0.586 0.956 0.727 0.667 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] bed : 0.189 0.521 0.964 0.800 0.500 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] trash can : 0.516 0.684 0.719 0.833 0.769 [2025-04-28 22:09:50,874 INFO hook.py line 395 1619929] book : 0.022 0.037 0.062 0.296 0.079 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] plant : 0.460 0.677 0.734 0.917 0.611 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] blanket : 0.463 0.587 0.697 0.636 0.636 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] tv : 0.913 0.955 0.955 1.000 0.833 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] computer tower : 0.202 0.296 0.625 0.486 0.405 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] refrigerator : 0.259 0.440 0.440 1.000 0.333 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] jacket : 0.070 0.234 0.384 0.545 0.545 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] sink : 0.327 0.559 0.820 0.737 0.636 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] bag : 0.091 0.126 0.157 0.350 0.259 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] picture : 0.131 0.302 0.385 0.684 0.333 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] pillow : 0.547 0.782 0.838 0.938 0.789 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] towel : 0.165 0.282 0.465 0.579 0.289 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] suitcase : 0.354 0.364 0.364 0.600 0.429 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] backpack : 0.338 0.387 0.387 0.625 0.385 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] crate : 0.089 0.251 0.468 0.455 0.455 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] keyboard : 0.349 0.490 0.569 0.800 0.513 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] toilet : 0.765 0.876 1.000 0.889 0.889 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] printer : 0.273 0.307 0.444 0.667 0.444 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.006 0.077 0.111 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] painting : 0.042 0.045 0.056 0.091 1.000 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] microwave : 0.281 0.602 0.875 0.833 0.625 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] shoes : 0.194 0.315 0.469 0.684 0.317 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] socket : 0.187 0.434 0.619 0.753 0.457 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] bottle : 0.119 0.181 0.301 0.300 0.289 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] bucket : 0.185 0.217 0.236 0.261 0.857 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] cushion : 0.103 0.500 0.657 1.000 0.500 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] telephone : 0.247 0.528 0.627 0.714 0.588 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] laptop : 0.448 0.597 0.690 0.833 0.625 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] plant pot : 0.080 0.320 0.444 0.636 0.438 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] exhaust fan : 0.148 0.277 0.292 0.556 0.333 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] cup : 0.199 0.308 0.345 0.875 0.318 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] coat hanger : 0.264 0.750 0.750 1.000 0.750 [2025-04-28 22:09:50,875 INFO hook.py line 395 1619929] light switch : 0.191 0.410 0.588 0.523 0.523 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] speaker : 0.373 0.450 0.573 0.600 0.545 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] kettle : 0.111 0.167 0.333 1.000 0.167 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] smoke detector : 0.662 0.849 0.854 0.905 0.792 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] power strip : 0.102 0.160 0.261 0.200 0.400 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] paper bag : 0.125 0.125 0.125 0.250 1.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] mouse : 0.497 0.681 0.769 0.913 0.656 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] toilet paper : 0.186 0.334 0.464 0.636 0.412 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] paper towel : 0.021 0.031 0.031 0.500 0.125 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] clock : 0.556 1.000 1.000 1.000 1.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] pan : 0.028 0.250 0.250 1.000 0.250 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] tap : 0.166 0.280 0.735 0.600 0.333 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] soap dispenser : 0.361 0.600 0.600 1.000 0.600 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] bowl : 0.012 0.024 0.333 0.143 0.333 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] whiteboard eraser: 0.279 0.626 0.626 0.714 0.833 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] toilet brush : 0.553 0.629 0.765 0.800 0.667 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] spray bottle : 0.042 0.062 0.062 0.500 0.250 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] stapler : 0.015 0.083 0.611 0.500 0.333 [2025-04-28 22:09:50,876 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 22:09:50,876 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 22:09:50,876 INFO hook.py line 404 1619929] average : 0.251 0.388 0.501 0.598 0.466 [2025-04-28 22:09:50,876 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 22:09:50,877 INFO hook.py line 480 1619929] Total Process Time: 25.147 s [2025-04-28 22:09:50,877 INFO hook.py line 481 1619929] Average Process Time: 506.450 ms [2025-04-28 22:09:50,877 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 22:09:50,927 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.388 [2025-04-28 22:09:50,932 INFO hook.py line 685 1619929] Currently Best AP50: 0.388 [2025-04-28 22:09:50,932 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:11:15,340 INFO hook.py line 650 1619929] Train: [185/512][50/242] Data 0.017 (0.017) Batch 1.213 (1.379) Remain 30:22:53 loss: 5.5228 Lr: 2.00879e-04 Mem R(MA/MR): 23032 (21200/36094) [2025-04-28 22:12:25,236 INFO hook.py line 650 1619929] Train: [185/512][100/242] Data 0.015 (0.025) Batch 1.441 (1.389) Remain 30:34:46 loss: 5.9247 Lr: 2.00765e-04 Mem R(MA/MR): 23032 (21200/36094) [2025-04-28 22:13:34,096 INFO hook.py line 650 1619929] Train: [185/512][150/242] Data 0.017 (0.022) Batch 1.410 (1.385) Remain 30:28:28 loss: 6.1706 Lr: 2.00651e-04 Mem R(MA/MR): 23032 (21200/36094) [2025-04-28 22:14:42,897 INFO hook.py line 650 1619929] Train: [185/512][200/242] Data 0.014 (0.020) Batch 1.386 (1.383) Remain 30:24:23 loss: 6.6768 Lr: 2.00537e-04 Mem R(MA/MR): 23032 (21200/36094) [2025-04-28 22:15:38,173 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4160 loss_mask: 0.0426 loss_dice: 2.2533 loss_score: 0.0000 loss_bbox: 0.0552 loss_sp_cls: 0.9038 loss: 5.9059 [2025-04-28 22:15:41,245 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:17:12,606 INFO hook.py line 650 1619929] Train: [186/512][50/242] Data 0.016 (0.016) Batch 1.338 (1.436) Remain 31:32:14 loss: 6.5142 Lr: 2.00327e-04 Mem R(MA/MR): 22946 (21200/36094) [2025-04-28 22:18:24,289 INFO hook.py line 650 1619929] Train: [186/512][100/242] Data 0.016 (0.017) Batch 1.411 (1.435) Remain 31:29:44 loss: 5.9880 Lr: 2.00213e-04 Mem R(MA/MR): 22950 (21200/36094) [2025-04-28 22:19:31,792 INFO hook.py line 650 1619929] Train: [186/512][150/242] Data 0.015 (0.017) Batch 1.204 (1.406) Remain 30:50:40 loss: 5.0657 Lr: 2.00099e-04 Mem R(MA/MR): 22978 (21200/36094) [2025-04-28 22:20:39,733 INFO hook.py line 650 1619929] Train: [186/512][200/242] Data 0.016 (0.017) Batch 1.291 (1.394) Remain 30:33:48 loss: 5.3848 Lr: 1.99985e-04 Mem R(MA/MR): 22978 (21200/36094) [2025-04-28 22:21:35,138 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4139 loss_mask: 0.0423 loss_dice: 2.2378 loss_score: 0.0000 loss_bbox: 0.0544 loss_sp_cls: 0.9032 loss: 5.8653 [2025-04-28 22:21:35,279 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:23:05,035 INFO hook.py line 650 1619929] Train: [187/512][50/242] Data 0.015 (0.017) Batch 1.459 (1.390) Remain 30:26:53 loss: 5.3079 Lr: 1.99775e-04 Mem R(MA/MR): 20278 (21200/36094) [2025-04-28 22:24:12,948 INFO hook.py line 650 1619929] Train: [187/512][100/242] Data 0.017 (0.017) Batch 1.313 (1.374) Remain 30:04:02 loss: 6.0189 Lr: 1.99661e-04 Mem R(MA/MR): 20286 (21200/36094) [2025-04-28 22:25:21,679 INFO hook.py line 650 1619929] Train: [187/512][150/242] Data 0.014 (0.016) Batch 1.310 (1.374) Remain 30:03:16 loss: 5.7758 Lr: 1.99547e-04 Mem R(MA/MR): 24048 (21200/36094) [2025-04-28 22:26:29,810 INFO hook.py line 650 1619929] Train: [187/512][200/242] Data 0.015 (0.016) Batch 1.356 (1.371) Remain 29:58:19 loss: 6.0303 Lr: 1.99433e-04 Mem R(MA/MR): 24048 (21200/36094) [2025-04-28 22:27:24,369 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4120 loss_mask: 0.0422 loss_dice: 2.2541 loss_score: 0.0000 loss_bbox: 0.0541 loss_sp_cls: 0.8943 loss: 5.8738 [2025-04-28 22:27:24,543 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:28:52,681 INFO hook.py line 650 1619929] Train: [188/512][50/242] Data 0.015 (0.016) Batch 1.346 (1.376) Remain 30:03:01 loss: 5.6890 Lr: 1.99224e-04 Mem R(MA/MR): 20042 (21200/36094) [2025-04-28 22:30:01,524 INFO hook.py line 650 1619929] Train: [188/512][100/242] Data 0.016 (0.016) Batch 1.471 (1.377) Remain 30:02:13 loss: 6.4107 Lr: 1.99110e-04 Mem R(MA/MR): 20808 (21200/36094) [2025-04-28 22:31:09,647 INFO hook.py line 650 1619929] Train: [188/512][150/242] Data 0.016 (0.016) Batch 1.321 (1.372) Remain 29:54:46 loss: 4.8908 Lr: 1.98996e-04 Mem R(MA/MR): 20818 (21200/36094) [2025-04-28 22:32:19,412 INFO hook.py line 650 1619929] Train: [188/512][200/242] Data 0.015 (0.016) Batch 1.584 (1.378) Remain 30:01:26 loss: 6.0594 Lr: 1.98882e-04 Mem R(MA/MR): 21548 (21200/36094) [2025-04-28 22:33:13,742 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4118 loss_mask: 0.0419 loss_dice: 2.2538 loss_score: 0.0000 loss_bbox: 0.0548 loss_sp_cls: 0.9042 loss: 5.8861 [2025-04-28 22:33:17,527 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:34:49,553 INFO hook.py line 650 1619929] Train: [189/512][50/242] Data 0.017 (0.016) Batch 1.640 (1.446) Remain 31:28:03 loss: 5.9910 Lr: 1.98672e-04 Mem R(MA/MR): 24206 (21200/36094) [2025-04-28 22:35:57,762 INFO hook.py line 650 1619929] Train: [189/512][100/242] Data 0.016 (0.016) Batch 1.405 (1.404) Remain 30:31:58 loss: 6.7265 Lr: 1.98558e-04 Mem R(MA/MR): 24206 (21200/36094) [2025-04-28 22:37:06,942 INFO hook.py line 650 1619929] Train: [189/512][150/242] Data 0.016 (0.016) Batch 1.313 (1.397) Remain 30:21:53 loss: 6.1430 Lr: 1.98444e-04 Mem R(MA/MR): 26180 (21200/36094) [2025-04-28 22:38:15,664 INFO hook.py line 650 1619929] Train: [189/512][200/242] Data 0.014 (0.016) Batch 1.355 (1.391) Remain 30:13:20 loss: 6.6736 Lr: 1.98329e-04 Mem R(MA/MR): 26180 (21200/36094) [2025-04-28 22:39:10,962 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4082 loss_mask: 0.0422 loss_dice: 2.2468 loss_score: 0.0000 loss_bbox: 0.0546 loss_sp_cls: 0.9034 loss: 5.8564 [2025-04-28 22:39:12,700 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:40:46,506 INFO hook.py line 650 1619929] Train: [190/512][50/242] Data 0.016 (0.017) Batch 1.500 (1.443) Remain 31:18:28 loss: 6.7642 Lr: 1.98120e-04 Mem R(MA/MR): 24006 (21200/36094) [2025-04-28 22:41:54,832 INFO hook.py line 650 1619929] Train: [190/512][100/242] Data 0.016 (0.017) Batch 1.278 (1.404) Remain 30:26:06 loss: 5.7432 Lr: 1.98005e-04 Mem R(MA/MR): 25916 (21200/36094) [2025-04-28 22:43:04,546 INFO hook.py line 650 1619929] Train: [190/512][150/242] Data 0.016 (0.017) Batch 1.457 (1.400) Remain 30:20:50 loss: 6.3304 Lr: 1.97891e-04 Mem R(MA/MR): 28196 (21200/36094) [2025-04-28 22:44:12,214 INFO hook.py line 650 1619929] Train: [190/512][200/242] Data 0.015 (0.017) Batch 1.348 (1.388) Remain 30:04:10 loss: 5.2917 Lr: 1.97777e-04 Mem R(MA/MR): 28196 (21200/36094) [2025-04-28 22:45:06,659 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4092 loss_mask: 0.0421 loss_dice: 2.2423 loss_score: 0.0000 loss_bbox: 0.0542 loss_sp_cls: 0.8983 loss: 5.8549 [2025-04-28 22:45:06,778 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:46:44,995 INFO hook.py line 650 1619929] Train: [191/512][50/242] Data 0.018 (0.021) Batch 1.578 (1.557) Remain 33:41:14 loss: 5.8555 Lr: 1.97567e-04 Mem R(MA/MR): 24496 (21200/36094) [2025-04-28 22:48:02,992 INFO hook.py line 650 1619929] Train: [191/512][100/242] Data 0.022 (0.022) Batch 1.425 (1.559) Remain 33:41:44 loss: 5.9830 Lr: 1.97453e-04 Mem R(MA/MR): 27108 (21200/36094) [2025-04-28 22:49:18,943 INFO hook.py line 650 1619929] Train: [191/512][150/242] Data 0.016 (0.021) Batch 1.408 (1.545) Remain 33:22:58 loss: 4.8990 Lr: 1.97339e-04 Mem R(MA/MR): 27108 (21200/36094) [2025-04-28 22:50:32,092 INFO hook.py line 650 1619929] Train: [191/512][200/242] Data 0.022 (0.020) Batch 1.460 (1.524) Remain 32:54:39 loss: 4.4370 Lr: 1.97225e-04 Mem R(MA/MR): 27108 (21200/36094) [2025-04-28 22:51:33,188 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3847 loss_mask: 0.0391 loss_dice: 2.1709 loss_score: 0.0000 loss_bbox: 0.0526 loss_sp_cls: 0.8745 loss: 5.6476 [2025-04-28 22:51:33,274 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 22:53:01,853 INFO hook.py line 650 1619929] Train: [192/512][50/242] Data 0.019 (0.022) Batch 1.576 (1.555) Remain 33:32:27 loss: 6.3218 Lr: 1.97015e-04 Mem R(MA/MR): 19498 (21200/36094) [2025-04-28 22:54:18,709 INFO hook.py line 650 1619929] Train: [192/512][100/242] Data 0.016 (0.022) Batch 1.545 (1.546) Remain 33:18:59 loss: 5.0255 Lr: 1.96901e-04 Mem R(MA/MR): 19508 (21200/36094) [2025-04-28 22:55:33,337 INFO hook.py line 650 1619929] Train: [192/512][150/242] Data 0.017 (0.021) Batch 1.475 (1.528) Remain 32:54:14 loss: 5.6531 Lr: 1.96786e-04 Mem R(MA/MR): 21222 (21200/36094) [2025-04-28 22:56:50,352 INFO hook.py line 650 1619929] Train: [192/512][200/242] Data 0.019 (0.020) Batch 1.569 (1.531) Remain 32:57:02 loss: 5.5034 Lr: 1.96672e-04 Mem R(MA/MR): 21222 (21200/36094) [2025-04-28 22:57:49,157 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3840 loss_mask: 0.0386 loss_dice: 2.1702 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8679 loss: 5.6364 [2025-04-28 22:57:54,470 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 22:57:56,942 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.4166 Process Time: 0.256 Mem R(MA/MR): 3938 (21200/36094) [2025-04-28 22:57:58,537 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9677 Process Time: 0.438 Mem R(MA/MR): 6630 (21200/36094) [2025-04-28 22:58:01,035 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1575 Process Time: 1.234 Mem R(MA/MR): 9300 (21200/36094) [2025-04-28 22:58:09,296 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.9125 Process Time: 1.096 Mem R(MA/MR): 19734 (21200/36094) [2025-04-28 22:58:10,430 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6889 Process Time: 0.358 Mem R(MA/MR): 6708 (21200/36094) [2025-04-28 22:58:12,045 INFO hook.py line 449 1619929] Test: [6/50] Loss 3.9805 Process Time: 0.525 Mem R(MA/MR): 10880 (21200/36094) [2025-04-28 22:58:12,615 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1453 Process Time: 0.175 Mem R(MA/MR): 5956 (21200/36094) [2025-04-28 22:58:13,080 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5901 Process Time: 0.135 Mem R(MA/MR): 4010 (21200/36094) [2025-04-28 22:58:13,949 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0167 Process Time: 0.184 Mem R(MA/MR): 11032 (21200/36094) [2025-04-28 22:58:15,460 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5207 Process Time: 0.249 Mem R(MA/MR): 8922 (21200/36094) [2025-04-28 22:58:18,194 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.4940 Process Time: 0.430 Mem R(MA/MR): 18450 (21200/36094) [2025-04-28 22:58:21,271 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0617 Process Time: 0.801 Mem R(MA/MR): 14764 (21200/36094) [2025-04-28 22:58:22,571 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7150 Process Time: 0.352 Mem R(MA/MR): 8406 (21200/36094) [2025-04-28 22:58:23,024 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0867 Process Time: 0.199 Mem R(MA/MR): 4350 (21200/36094) [2025-04-28 22:58:25,983 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.8268 Process Time: 0.272 Mem R(MA/MR): 16134 (21200/36094) [2025-04-28 22:58:28,343 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.7153 Process Time: 0.816 Mem R(MA/MR): 14322 (21200/36094) [2025-04-28 22:58:29,268 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.8689 Process Time: 0.326 Mem R(MA/MR): 6336 (21200/36094) [2025-04-28 22:58:30,121 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1447 Process Time: 0.217 Mem R(MA/MR): 7818 (21200/36094) [2025-04-28 22:58:31,465 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5699 Process Time: 0.176 Mem R(MA/MR): 5784 (21200/36094) [2025-04-28 22:58:33,367 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.1460 Process Time: 0.544 Mem R(MA/MR): 10802 (21200/36094) [2025-04-28 22:58:41,942 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.7538 Process Time: 0.743 Mem R(MA/MR): 23378 (21200/36094) [2025-04-28 22:58:42,634 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3324 Process Time: 0.308 Mem R(MA/MR): 6682 (21200/36094) [2025-04-28 22:58:52,683 INFO hook.py line 449 1619929] Test: [23/50] Loss 14.8060 Process Time: 0.614 Mem R(MA/MR): 7978 (21200/36094) [2025-04-28 22:58:53,839 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.2524 Process Time: 0.444 Mem R(MA/MR): 5002 (21200/36094) [2025-04-28 22:58:54,960 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8390 Process Time: 0.318 Mem R(MA/MR): 8978 (21200/36094) [2025-04-28 22:59:03,769 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.7977 Process Time: 1.911 Mem R(MA/MR): 31378 (21200/36094) [2025-04-28 22:59:06,573 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.8089 Process Time: 0.567 Mem R(MA/MR): 9610 (21200/36094) [2025-04-28 22:59:07,604 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.7635 Process Time: 0.192 Mem R(MA/MR): 8342 (21200/36094) [2025-04-28 22:59:12,561 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9304 Process Time: 0.519 Mem R(MA/MR): 16674 (21200/36094) [2025-04-28 22:59:13,754 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.6558 Process Time: 0.446 Mem R(MA/MR): 7346 (21200/36094) [2025-04-28 22:59:17,484 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5995 Process Time: 0.376 Mem R(MA/MR): 20304 (21200/36094) [2025-04-28 22:59:17,764 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1939 Process Time: 0.116 Mem R(MA/MR): 3642 (21200/36094) [2025-04-28 22:59:22,280 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.5784 Process Time: 1.107 Mem R(MA/MR): 24494 (21200/36094) [2025-04-28 22:59:24,019 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5171 Process Time: 0.330 Mem R(MA/MR): 9434 (21200/36094) [2025-04-28 22:59:25,569 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.2971 Process Time: 0.234 Mem R(MA/MR): 13592 (21200/36094) [2025-04-28 22:59:26,103 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8558 Process Time: 0.165 Mem R(MA/MR): 6236 (21200/36094) [2025-04-28 22:59:30,179 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8749 Process Time: 0.614 Mem R(MA/MR): 28190 (21200/36094) [2025-04-28 22:59:32,163 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1605 Process Time: 0.449 Mem R(MA/MR): 10166 (21200/36094) [2025-04-28 22:59:32,614 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9532 Process Time: 0.132 Mem R(MA/MR): 5134 (21200/36094) [2025-04-28 22:59:33,905 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.6982 Process Time: 0.373 Mem R(MA/MR): 9768 (21200/36094) [2025-04-28 22:59:35,067 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.7239 Process Time: 0.306 Mem R(MA/MR): 8614 (21200/36094) [2025-04-28 22:59:35,623 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.1011 Process Time: 0.203 Mem R(MA/MR): 5088 (21200/36094) [2025-04-28 22:59:36,307 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7149 Process Time: 0.296 Mem R(MA/MR): 5180 (21200/36094) [2025-04-28 22:59:37,783 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.2418 Process Time: 0.807 Mem R(MA/MR): 6698 (21200/36094) [2025-04-28 22:59:38,756 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.8234 Process Time: 0.237 Mem R(MA/MR): 4888 (21200/36094) [2025-04-28 22:59:41,623 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.9507 Process Time: 0.724 Mem R(MA/MR): 14406 (21200/36094) [2025-04-28 22:59:49,367 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1369 Process Time: 0.940 Mem R(MA/MR): 19928 (21200/36094) [2025-04-28 22:59:59,877 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.6865 Process Time: 1.673 Mem R(MA/MR): 35224 (21200/36094) [2025-04-28 23:00:00,651 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.3294 Process Time: 0.270 Mem R(MA/MR): 5366 (21200/36094) [2025-04-28 23:00:03,261 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.7831 Process Time: 0.483 Mem R(MA/MR): 13382 (21200/36094) [2025-04-28 23:00:08,564 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 23:00:08,564 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 23:00:08,564 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] table : 0.255 0.615 0.770 0.817 0.625 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] door : 0.416 0.702 0.863 0.918 0.709 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] ceiling lamp : 0.564 0.776 0.899 0.810 0.779 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] cabinet : 0.288 0.450 0.511 0.544 0.552 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] blinds : 0.573 0.853 0.860 0.769 0.870 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] curtain : 0.286 0.534 0.732 0.750 0.500 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] chair : 0.632 0.757 0.795 0.723 0.770 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] storage cabinet: 0.231 0.391 0.530 0.647 0.440 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] office chair : 0.575 0.617 0.617 0.683 0.854 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] bookshelf : 0.244 0.723 0.723 0.750 0.818 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] whiteboard : 0.580 0.793 0.806 0.964 0.771 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] window : 0.103 0.224 0.541 0.439 0.319 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] box : 0.225 0.408 0.537 0.544 0.409 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] monitor : 0.613 0.762 0.820 0.981 0.729 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] shelf : 0.094 0.234 0.393 0.500 0.367 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] heater : 0.450 0.717 0.811 0.935 0.763 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] kitchen cabinet: 0.197 0.528 0.780 0.786 0.440 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] sofa : 0.490 0.629 0.903 0.556 0.833 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] bed : 0.246 0.586 1.000 1.000 0.500 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] trash can : 0.560 0.710 0.768 0.820 0.769 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] book : 0.016 0.021 0.052 0.115 0.079 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] plant : 0.469 0.643 0.743 0.800 0.667 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] blanket : 0.299 0.567 0.696 0.636 0.636 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] tv : 0.889 0.974 0.974 0.857 1.000 [2025-04-28 23:00:08,564 INFO hook.py line 395 1619929] computer tower : 0.233 0.334 0.565 0.447 0.405 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] refrigerator : 0.167 0.322 0.323 0.750 0.333 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] jacket : 0.073 0.188 0.362 0.333 0.636 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] sink : 0.361 0.675 0.878 0.773 0.773 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] bag : 0.109 0.205 0.239 0.423 0.407 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] picture : 0.123 0.279 0.407 0.472 0.436 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] pillow : 0.667 0.908 0.908 1.000 0.789 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] towel : 0.212 0.402 0.562 0.714 0.395 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] suitcase : 0.413 0.500 0.544 0.455 0.714 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] backpack : 0.417 0.507 0.547 0.571 0.615 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] crate : 0.108 0.449 0.506 0.714 0.455 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] keyboard : 0.426 0.525 0.635 0.750 0.538 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] toilet : 0.751 0.876 1.000 0.889 0.889 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] printer : 0.291 0.454 0.454 0.625 0.556 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] poster : 0.000 0.003 0.003 0.045 0.111 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] painting : 0.071 0.071 0.071 0.143 1.000 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] microwave : 0.504 0.750 0.875 1.000 0.750 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] shoes : 0.129 0.327 0.604 0.625 0.366 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] socket : 0.161 0.417 0.630 0.682 0.429 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] bottle : 0.100 0.163 0.302 0.412 0.253 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] bucket : 0.094 0.115 0.118 0.176 0.429 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] cushion : 0.072 0.311 0.341 0.500 0.500 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 1.000 0.000 0.000 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] telephone : 0.287 0.543 0.625 0.750 0.529 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] laptop : 0.467 0.676 0.721 0.800 0.500 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] plant pot : 0.156 0.379 0.506 0.667 0.500 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] exhaust fan : 0.085 0.212 0.263 0.500 0.267 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] cup : 0.199 0.366 0.397 0.938 0.341 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] coat hanger : 0.139 0.250 0.500 1.000 0.250 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] light switch : 0.273 0.579 0.712 0.755 0.615 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] speaker : 0.241 0.394 0.562 0.556 0.455 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 23:00:08,565 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] smoke detector : 0.641 0.784 0.786 1.000 0.750 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] power strip : 0.062 0.167 0.182 0.444 0.400 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] paper bag : 0.167 0.167 0.167 0.333 1.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] mouse : 0.388 0.574 0.587 0.783 0.562 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] cutting board : 0.333 0.500 0.500 1.000 0.500 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] toilet paper : 0.225 0.442 0.518 0.875 0.412 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] paper towel : 0.014 0.125 0.125 1.000 0.125 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] clock : 0.593 1.000 1.000 1.000 1.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] tap : 0.150 0.417 0.649 0.714 0.556 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] soap dispenser : 0.486 0.800 0.800 1.000 0.800 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] bowl : 0.420 0.528 0.528 0.667 0.667 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] tissue box : 0.056 0.125 0.125 0.500 0.500 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] whiteboard eraser: 0.131 0.359 0.373 0.600 0.500 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] toilet brush : 0.559 0.732 0.913 1.000 0.667 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] spray bottle : 0.012 0.018 0.018 0.143 0.250 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] stapler : 0.005 0.021 0.033 0.125 0.333 [2025-04-28 23:00:08,566 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:00:08,566 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 23:00:08,566 INFO hook.py line 404 1619929] average : 0.265 0.418 0.509 0.622 0.495 [2025-04-28 23:00:08,566 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 23:00:08,567 INFO hook.py line 480 1619929] Total Process Time: 24.680 s [2025-04-28 23:00:08,567 INFO hook.py line 481 1619929] Average Process Time: 498.459 ms [2025-04-28 23:00:08,567 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 23:00:08,619 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.418 [2025-04-28 23:00:08,624 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-28 23:00:08,624 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:01:33,745 INFO hook.py line 650 1619929] Train: [193/512][50/242] Data 0.015 (0.034) Batch 1.511 (1.492) Remain 32:03:57 loss: 5.2289 Lr: 1.96462e-04 Mem R(MA/MR): 19118 (21200/36094) [2025-04-28 23:02:44,789 INFO hook.py line 650 1619929] Train: [193/512][100/242] Data 0.017 (0.025) Batch 1.443 (1.455) Remain 31:15:43 loss: 5.7118 Lr: 1.96348e-04 Mem R(MA/MR): 23124 (21200/36094) [2025-04-28 23:03:55,494 INFO hook.py line 650 1619929] Train: [193/512][150/242] Data 0.017 (0.022) Batch 1.496 (1.441) Remain 30:56:29 loss: 5.6559 Lr: 1.96234e-04 Mem R(MA/MR): 24962 (21200/36094) [2025-04-28 23:05:04,663 INFO hook.py line 650 1619929] Train: [193/512][200/242] Data 0.015 (0.020) Batch 1.258 (1.427) Remain 30:36:24 loss: 5.5232 Lr: 1.96122e-04 Mem R(MA/MR): 24962 (21200/36094) [2025-04-28 23:05:58,933 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3850 loss_mask: 0.0397 loss_dice: 2.1759 loss_score: 0.0000 loss_bbox: 0.0528 loss_sp_cls: 0.8720 loss: 5.6572 [2025-04-28 23:06:02,301 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:07:32,403 INFO hook.py line 650 1619929] Train: [194/512][50/242] Data 0.016 (0.016) Batch 1.365 (1.385) Remain 29:40:30 loss: 7.1875 Lr: 1.95912e-04 Mem R(MA/MR): 19670 (21200/36094) [2025-04-28 23:08:41,022 INFO hook.py line 650 1619929] Train: [194/512][100/242] Data 0.017 (0.016) Batch 1.355 (1.378) Remain 29:31:09 loss: 5.1679 Lr: 1.95797e-04 Mem R(MA/MR): 21738 (21200/36094) [2025-04-28 23:09:48,589 INFO hook.py line 650 1619929] Train: [194/512][150/242] Data 0.016 (0.016) Batch 1.388 (1.369) Remain 29:18:13 loss: 6.4718 Lr: 1.95683e-04 Mem R(MA/MR): 21738 (21200/36094) [2025-04-28 23:10:57,278 INFO hook.py line 650 1619929] Train: [194/512][200/242] Data 0.015 (0.016) Batch 1.355 (1.370) Remain 29:18:34 loss: 5.0636 Lr: 1.95569e-04 Mem R(MA/MR): 21738 (21200/36094) [2025-04-28 23:11:52,799 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4088 loss_mask: 0.0422 loss_dice: 2.2413 loss_score: 0.0000 loss_bbox: 0.0545 loss_sp_cls: 0.9010 loss: 5.8518 [2025-04-28 23:11:53,034 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:13:22,479 INFO hook.py line 650 1619929] Train: [195/512][50/242] Data 0.018 (0.016) Batch 1.500 (1.406) Remain 30:01:43 loss: 5.3759 Lr: 1.95359e-04 Mem R(MA/MR): 21210 (21200/36094) [2025-04-28 23:14:31,726 INFO hook.py line 650 1619929] Train: [195/512][100/242] Data 0.017 (0.017) Batch 1.404 (1.395) Remain 29:46:54 loss: 6.6073 Lr: 1.95244e-04 Mem R(MA/MR): 24570 (21200/36094) [2025-04-28 23:15:43,421 INFO hook.py line 650 1619929] Train: [195/512][150/242] Data 0.015 (0.016) Batch 1.328 (1.408) Remain 30:02:39 loss: 7.3081 Lr: 1.95130e-04 Mem R(MA/MR): 26578 (21200/36094) [2025-04-28 23:16:53,139 INFO hook.py line 650 1619929] Train: [195/512][200/242] Data 0.015 (0.017) Batch 1.278 (1.405) Remain 29:57:00 loss: 6.6510 Lr: 1.95016e-04 Mem R(MA/MR): 26578 (21200/36094) [2025-04-28 23:17:49,556 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4132 loss_mask: 0.0420 loss_dice: 2.2508 loss_score: 0.0000 loss_bbox: 0.0546 loss_sp_cls: 0.9026 loss: 5.8835 [2025-04-28 23:17:54,660 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:19:26,674 INFO hook.py line 650 1619929] Train: [196/512][50/242] Data 0.016 (0.016) Batch 1.387 (1.444) Remain 30:45:11 loss: 4.8405 Lr: 1.94805e-04 Mem R(MA/MR): 21074 (21200/36094) [2025-04-28 23:20:36,864 INFO hook.py line 650 1619929] Train: [196/512][100/242] Data 0.017 (0.016) Batch 1.244 (1.423) Remain 30:17:27 loss: 5.3040 Lr: 1.94691e-04 Mem R(MA/MR): 21074 (21200/36094) [2025-04-28 23:21:46,940 INFO hook.py line 650 1619929] Train: [196/512][150/242] Data 0.015 (0.017) Batch 1.316 (1.416) Remain 30:06:47 loss: 5.8916 Lr: 1.94577e-04 Mem R(MA/MR): 21074 (21200/36094) [2025-04-28 23:22:56,881 INFO hook.py line 650 1619929] Train: [196/512][200/242] Data 0.015 (0.017) Batch 1.285 (1.412) Remain 30:00:06 loss: 4.2654 Lr: 1.94462e-04 Mem R(MA/MR): 21076 (21200/36094) [2025-04-28 23:23:51,094 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4121 loss_mask: 0.0421 loss_dice: 2.2419 loss_score: 0.0000 loss_bbox: 0.0545 loss_sp_cls: 0.9021 loss: 5.8647 [2025-04-28 23:23:51,197 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:25:20,088 INFO hook.py line 650 1619929] Train: [197/512][50/242] Data 0.017 (0.017) Batch 1.255 (1.427) Remain 30:17:40 loss: 5.3972 Lr: 1.94252e-04 Mem R(MA/MR): 20610 (21200/36094) [2025-04-28 23:26:27,078 INFO hook.py line 650 1619929] Train: [197/512][100/242] Data 0.015 (0.017) Batch 1.360 (1.382) Remain 29:19:12 loss: 5.8851 Lr: 1.94138e-04 Mem R(MA/MR): 20610 (21200/36094) [2025-04-28 23:27:35,787 INFO hook.py line 650 1619929] Train: [197/512][150/242] Data 0.017 (0.016) Batch 1.326 (1.379) Remain 29:14:38 loss: 5.3177 Lr: 1.94023e-04 Mem R(MA/MR): 22434 (21200/36094) [2025-04-28 23:28:44,360 INFO hook.py line 650 1619929] Train: [197/512][200/242] Data 0.013 (0.016) Batch 1.242 (1.377) Remain 29:10:56 loss: 4.8485 Lr: 1.93909e-04 Mem R(MA/MR): 22434 (21200/36094) [2025-04-28 23:29:39,843 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4095 loss_mask: 0.0417 loss_dice: 2.2412 loss_score: 0.0000 loss_bbox: 0.0540 loss_sp_cls: 0.9038 loss: 5.8545 [2025-04-28 23:29:40,002 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:31:08,803 INFO hook.py line 650 1619929] Train: [198/512][50/242] Data 0.016 (0.016) Batch 1.368 (1.419) Remain 30:01:17 loss: 6.1420 Lr: 1.93699e-04 Mem R(MA/MR): 21050 (21200/36094) [2025-04-28 23:32:16,174 INFO hook.py line 650 1619929] Train: [198/512][100/242] Data 0.016 (0.016) Batch 1.349 (1.382) Remain 29:13:28 loss: 5.9608 Lr: 1.93584e-04 Mem R(MA/MR): 22984 (21200/36094) [2025-04-28 23:33:26,744 INFO hook.py line 650 1619929] Train: [198/512][150/242] Data 0.015 (0.016) Batch 1.347 (1.392) Remain 29:25:02 loss: 7.1636 Lr: 1.93470e-04 Mem R(MA/MR): 23030 (21200/36094) [2025-04-28 23:34:35,670 INFO hook.py line 650 1619929] Train: [198/512][200/242] Data 0.017 (0.016) Batch 1.460 (1.389) Remain 29:19:32 loss: 5.2092 Lr: 1.93355e-04 Mem R(MA/MR): 23030 (21200/36094) [2025-04-28 23:35:30,291 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4048 loss_mask: 0.0421 loss_dice: 2.2316 loss_score: 0.0000 loss_bbox: 0.0546 loss_sp_cls: 0.8952 loss: 5.8243 [2025-04-28 23:35:31,308 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:37:00,500 INFO hook.py line 650 1619929] Train: [199/512][50/242] Data 0.018 (0.018) Batch 1.495 (1.394) Remain 29:23:50 loss: 4.9432 Lr: 1.93145e-04 Mem R(MA/MR): 19150 (21200/36094) [2025-04-28 23:38:10,543 INFO hook.py line 650 1619929] Train: [199/512][100/242] Data 0.016 (0.017) Batch 1.461 (1.397) Remain 29:27:26 loss: 6.0585 Lr: 1.93030e-04 Mem R(MA/MR): 21174 (21200/36094) [2025-04-28 23:39:19,967 INFO hook.py line 650 1619929] Train: [199/512][150/242] Data 0.016 (0.017) Batch 1.329 (1.394) Remain 29:22:25 loss: 5.4910 Lr: 1.92916e-04 Mem R(MA/MR): 21194 (21200/36094) [2025-04-28 23:40:28,806 INFO hook.py line 650 1619929] Train: [199/512][200/242] Data 0.015 (0.017) Batch 1.505 (1.390) Remain 29:15:38 loss: 7.6922 Lr: 1.92802e-04 Mem R(MA/MR): 21194 (21200/36094) [2025-04-28 23:41:24,488 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4003 loss_mask: 0.0418 loss_dice: 2.2456 loss_score: 0.0000 loss_bbox: 0.0541 loss_sp_cls: 0.8908 loss: 5.8330 [2025-04-28 23:41:27,881 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:42:52,318 INFO hook.py line 650 1619929] Train: [200/512][50/242] Data 0.015 (0.017) Batch 1.415 (1.415) Remain 29:45:37 loss: 5.8239 Lr: 1.92591e-04 Mem R(MA/MR): 21726 (21200/36094) [2025-04-28 23:44:02,396 INFO hook.py line 650 1619929] Train: [200/512][100/242] Data 0.016 (0.016) Batch 1.321 (1.408) Remain 29:35:28 loss: 5.6730 Lr: 1.92477e-04 Mem R(MA/MR): 21746 (21200/36094) [2025-04-28 23:45:12,279 INFO hook.py line 650 1619929] Train: [200/512][150/242] Data 0.016 (0.016) Batch 1.380 (1.405) Remain 29:29:45 loss: 6.1694 Lr: 1.92362e-04 Mem R(MA/MR): 21746 (21200/36094) [2025-04-28 23:46:20,288 INFO hook.py line 650 1619929] Train: [200/512][200/242] Data 0.014 (0.016) Batch 1.358 (1.393) Remain 29:14:23 loss: 6.1400 Lr: 1.92248e-04 Mem R(MA/MR): 26200 (21200/36094) [2025-04-28 23:47:14,172 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4026 loss_mask: 0.0416 loss_dice: 2.2356 loss_score: 0.0000 loss_bbox: 0.0545 loss_sp_cls: 0.8971 loss: 5.8185 [2025-04-28 23:47:16,501 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-28 23:47:18,966 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.0384 Process Time: 0.295 Mem R(MA/MR): 4452 (21200/36094) [2025-04-28 23:47:20,699 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.3722 Process Time: 0.577 Mem R(MA/MR): 7134 (21200/36094) [2025-04-28 23:47:23,122 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4225 Process Time: 0.908 Mem R(MA/MR): 9706 (21200/36094) [2025-04-28 23:47:31,216 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.9845 Process Time: 1.503 Mem R(MA/MR): 19664 (21200/36094) [2025-04-28 23:47:32,132 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5202 Process Time: 0.271 Mem R(MA/MR): 6914 (21200/36094) [2025-04-28 23:47:33,494 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7533 Process Time: 0.352 Mem R(MA/MR): 11420 (21200/36094) [2025-04-28 23:47:34,065 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.4783 Process Time: 0.183 Mem R(MA/MR): 6404 (21200/36094) [2025-04-28 23:47:34,465 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.6101 Process Time: 0.120 Mem R(MA/MR): 4488 (21200/36094) [2025-04-28 23:47:35,232 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.9253 Process Time: 0.181 Mem R(MA/MR): 11388 (21200/36094) [2025-04-28 23:47:36,577 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.3085 Process Time: 0.216 Mem R(MA/MR): 9540 (21200/36094) [2025-04-28 23:47:39,012 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.5548 Process Time: 0.395 Mem R(MA/MR): 18696 (21200/36094) [2025-04-28 23:47:42,280 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.9876 Process Time: 1.129 Mem R(MA/MR): 15574 (21200/36094) [2025-04-28 23:47:43,433 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1825 Process Time: 0.297 Mem R(MA/MR): 8730 (21200/36094) [2025-04-28 23:47:43,741 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.4366 Process Time: 0.107 Mem R(MA/MR): 4826 (21200/36094) [2025-04-28 23:47:46,626 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.5347 Process Time: 0.244 Mem R(MA/MR): 16356 (21200/36094) [2025-04-28 23:47:48,307 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.7038 Process Time: 0.403 Mem R(MA/MR): 14530 (21200/36094) [2025-04-28 23:47:49,538 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.5816 Process Time: 0.335 Mem R(MA/MR): 6638 (21200/36094) [2025-04-28 23:47:50,457 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.4710 Process Time: 0.332 Mem R(MA/MR): 8210 (21200/36094) [2025-04-28 23:47:51,999 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.3302 Process Time: 0.224 Mem R(MA/MR): 6110 (21200/36094) [2025-04-28 23:47:53,564 INFO hook.py line 449 1619929] Test: [20/50] Loss 7.8561 Process Time: 0.378 Mem R(MA/MR): 11330 (21200/36094) [2025-04-28 23:48:01,438 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.3501 Process Time: 0.487 Mem R(MA/MR): 23238 (21200/36094) [2025-04-28 23:48:02,053 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.8591 Process Time: 0.232 Mem R(MA/MR): 6954 (21200/36094) [2025-04-28 23:48:12,157 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.0680 Process Time: 0.402 Mem R(MA/MR): 8468 (21200/36094) [2025-04-28 23:48:12,633 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8110 Process Time: 0.140 Mem R(MA/MR): 5296 (21200/36094) [2025-04-28 23:48:13,785 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2066 Process Time: 0.396 Mem R(MA/MR): 9402 (21200/36094) [2025-04-28 23:48:21,344 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.8414 Process Time: 1.853 Mem R(MA/MR): 31334 (21200/36094) [2025-04-28 23:48:23,710 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.8828 Process Time: 0.620 Mem R(MA/MR): 9860 (21200/36094) [2025-04-28 23:48:25,456 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.7325 Process Time: 0.418 Mem R(MA/MR): 8974 (21200/36094) [2025-04-28 23:48:31,106 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0250 Process Time: 0.503 Mem R(MA/MR): 16982 (21200/36094) [2025-04-28 23:48:32,936 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.4462 Process Time: 0.673 Mem R(MA/MR): 7858 (21200/36094) [2025-04-28 23:48:37,204 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.7638 Process Time: 0.552 Mem R(MA/MR): 20656 (21200/36094) [2025-04-28 23:48:37,508 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.8885 Process Time: 0.148 Mem R(MA/MR): 3928 (21200/36094) [2025-04-28 23:48:41,453 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.8874 Process Time: 0.402 Mem R(MA/MR): 24534 (21200/36094) [2025-04-28 23:48:42,979 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8458 Process Time: 0.413 Mem R(MA/MR): 9720 (21200/36094) [2025-04-28 23:48:44,796 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.5997 Process Time: 0.502 Mem R(MA/MR): 13806 (21200/36094) [2025-04-28 23:48:45,244 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9189 Process Time: 0.143 Mem R(MA/MR): 6732 (21200/36094) [2025-04-28 23:48:48,886 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.6508 Process Time: 0.393 Mem R(MA/MR): 28474 (21200/36094) [2025-04-28 23:48:51,327 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5440 Process Time: 0.822 Mem R(MA/MR): 10368 (21200/36094) [2025-04-28 23:48:51,842 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.7131 Process Time: 0.191 Mem R(MA/MR): 5426 (21200/36094) [2025-04-28 23:48:53,225 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.0324 Process Time: 0.546 Mem R(MA/MR): 10086 (21200/36094) [2025-04-28 23:48:54,051 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.3612 Process Time: 0.212 Mem R(MA/MR): 9044 (21200/36094) [2025-04-28 23:48:54,482 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1827 Process Time: 0.123 Mem R(MA/MR): 5378 (21200/36094) [2025-04-28 23:48:54,870 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9745 Process Time: 0.119 Mem R(MA/MR): 5460 (21200/36094) [2025-04-28 23:48:55,459 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.7043 Process Time: 0.184 Mem R(MA/MR): 7098 (21200/36094) [2025-04-28 23:48:56,038 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3014 Process Time: 0.153 Mem R(MA/MR): 5206 (21200/36094) [2025-04-28 23:48:58,145 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.7524 Process Time: 0.248 Mem R(MA/MR): 14704 (21200/36094) [2025-04-28 23:49:05,965 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.2012 Process Time: 1.358 Mem R(MA/MR): 20202 (21200/36094) [2025-04-28 23:49:16,639 INFO hook.py line 449 1619929] Test: [48/50] Loss 10.0281 Process Time: 2.331 Mem R(MA/MR): 35274 (21200/36094) [2025-04-28 23:49:18,161 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.6654 Process Time: 0.361 Mem R(MA/MR): 5714 (21200/36094) [2025-04-28 23:49:20,524 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5377 Process Time: 0.514 Mem R(MA/MR): 13560 (21200/36094) [2025-04-28 23:49:24,279 INFO hook.py line 372 1619929] ################################################################## [2025-04-28 23:49:24,280 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-28 23:49:24,280 INFO hook.py line 381 1619929] ################################################################## [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] table : 0.266 0.620 0.797 0.772 0.647 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] door : 0.433 0.766 0.869 0.967 0.734 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] ceiling lamp : 0.542 0.737 0.812 0.914 0.702 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] cabinet : 0.325 0.462 0.540 0.567 0.507 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] blinds : 0.527 0.722 0.833 0.905 0.826 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] curtain : 0.300 0.419 0.659 0.625 0.417 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] chair : 0.598 0.754 0.812 0.802 0.713 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] storage cabinet: 0.271 0.380 0.638 0.438 0.560 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] office chair : 0.625 0.674 0.702 0.694 0.896 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] bookshelf : 0.270 0.630 0.645 0.643 0.818 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] whiteboard : 0.559 0.708 0.765 0.765 0.743 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] window : 0.106 0.246 0.572 0.479 0.374 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] box : 0.194 0.378 0.514 0.537 0.398 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] monitor : 0.619 0.746 0.816 0.911 0.729 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] shelf : 0.094 0.197 0.420 0.435 0.333 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] heater : 0.479 0.747 0.845 0.789 0.789 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] kitchen cabinet: 0.146 0.421 0.616 0.600 0.600 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] sofa : 0.441 0.572 0.875 0.700 0.583 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] bed : 0.242 0.641 0.923 1.000 0.500 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] trash can : 0.560 0.734 0.770 0.825 0.800 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] book : 0.011 0.023 0.067 0.197 0.086 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] plant : 0.427 0.597 0.698 0.846 0.611 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] blanket : 0.409 0.522 0.708 0.857 0.545 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] tv : 0.856 0.974 0.974 0.857 1.000 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] computer tower : 0.265 0.490 0.647 0.909 0.476 [2025-04-28 23:49:24,280 INFO hook.py line 395 1619929] refrigerator : 0.229 0.349 0.351 1.000 0.333 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] jacket : 0.107 0.305 0.408 0.417 0.455 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] sink : 0.404 0.530 0.757 0.875 0.636 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] bag : 0.138 0.208 0.213 0.385 0.370 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] picture : 0.116 0.271 0.429 0.652 0.385 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] pillow : 0.557 0.815 0.815 0.824 0.737 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] towel : 0.170 0.321 0.478 0.517 0.395 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] suitcase : 0.378 0.596 0.668 0.714 0.714 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] backpack : 0.388 0.483 0.525 0.857 0.462 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] crate : 0.080 0.296 0.694 0.714 0.455 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] keyboard : 0.440 0.606 0.686 0.923 0.615 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] toilet : 0.809 0.889 1.000 1.000 0.889 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] printer : 0.205 0.366 0.366 0.714 0.556 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] poster : 0.001 0.007 0.008 0.125 0.111 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] painting : 0.056 0.056 0.083 0.111 1.000 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] microwave : 0.477 0.750 0.875 1.000 0.750 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] shoes : 0.169 0.280 0.479 0.500 0.366 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] socket : 0.159 0.389 0.601 0.575 0.436 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] bottle : 0.112 0.185 0.300 0.309 0.349 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] bucket : 0.152 0.233 0.233 0.286 0.571 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] cushion : 0.062 0.072 0.189 0.333 0.333 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.024 0.000 0.000 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] telephone : 0.246 0.520 0.558 0.800 0.471 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] laptop : 0.200 0.268 0.312 0.333 0.500 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] plant pot : 0.048 0.191 0.573 0.462 0.375 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] exhaust fan : 0.101 0.288 0.333 0.714 0.333 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] cup : 0.181 0.341 0.391 0.789 0.341 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] coat hanger : 0.014 0.042 0.750 0.333 0.250 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] light switch : 0.245 0.510 0.612 0.691 0.585 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] speaker : 0.325 0.433 0.476 0.714 0.455 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] smoke detector : 0.697 0.859 0.859 0.913 0.875 [2025-04-28 23:49:24,281 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] power strip : 0.110 0.145 0.372 0.500 0.300 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] paper bag : 0.056 0.056 0.062 0.111 1.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] mouse : 0.390 0.517 0.616 0.783 0.562 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] cutting board : 0.250 0.500 0.500 1.000 0.500 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] toilet paper : 0.221 0.344 0.454 0.857 0.353 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] paper towel : 0.014 0.031 0.031 0.500 0.125 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 1.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] clock : 0.287 0.519 0.592 0.375 1.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] pan : 0.083 0.250 0.250 1.000 0.250 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] tap : 0.100 0.200 0.430 0.429 0.333 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] soap dispenser : 0.430 0.635 0.635 0.750 0.600 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] bowl : 0.037 0.042 0.056 0.250 0.333 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] whiteboard eraser: 0.218 0.486 0.486 0.800 0.667 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] toilet brush : 0.515 0.722 0.896 1.000 0.667 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] stapler : 0.004 0.033 0.178 0.200 0.333 [2025-04-28 23:49:24,282 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-28 23:49:24,282 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-28 23:49:24,282 INFO hook.py line 404 1619929] average : 0.249 0.381 0.479 0.600 0.472 [2025-04-28 23:49:24,282 INFO hook.py line 405 1619929] ################################################################## [2025-04-28 23:49:24,283 INFO hook.py line 480 1619929] Total Process Time: 23.888 s [2025-04-28 23:49:24,283 INFO hook.py line 481 1619929] Average Process Time: 481.493 ms [2025-04-28 23:49:24,283 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-28 23:49:24,306 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-28 23:49:24,311 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:50:49,081 INFO hook.py line 650 1619929] Train: [201/512][50/242] Data 0.016 (0.017) Batch 1.467 (1.455) Remain 30:30:11 loss: 5.3135 Lr: 1.92037e-04 Mem R(MA/MR): 20274 (21200/36094) [2025-04-28 23:51:58,719 INFO hook.py line 650 1619929] Train: [201/512][100/242] Data 0.015 (0.016) Batch 1.362 (1.423) Remain 29:48:26 loss: 5.5873 Lr: 1.91922e-04 Mem R(MA/MR): 23610 (21200/36094) [2025-04-28 23:53:06,598 INFO hook.py line 650 1619929] Train: [201/512][150/242] Data 0.016 (0.016) Batch 1.431 (1.401) Remain 29:19:16 loss: 6.7919 Lr: 1.91808e-04 Mem R(MA/MR): 25438 (21200/36094) [2025-04-28 23:54:15,195 INFO hook.py line 650 1619929] Train: [201/512][200/242] Data 0.015 (0.019) Batch 1.442 (1.393) Remain 29:08:54 loss: 5.7875 Lr: 1.91693e-04 Mem R(MA/MR): 27336 (21200/36094) [2025-04-28 23:55:10,787 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4007 loss_mask: 0.0407 loss_dice: 2.2214 loss_score: 0.0000 loss_bbox: 0.0537 loss_sp_cls: 0.8887 loss: 5.7804 [2025-04-28 23:55:10,869 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-28 23:56:40,576 INFO hook.py line 650 1619929] Train: [202/512][50/242] Data 0.016 (0.017) Batch 1.342 (1.393) Remain 29:06:35 loss: 4.4868 Lr: 1.91483e-04 Mem R(MA/MR): 27822 (21200/36094) [2025-04-28 23:57:49,961 INFO hook.py line 650 1619929] Train: [202/512][100/242] Data 0.016 (0.017) Batch 1.333 (1.390) Remain 29:01:46 loss: 4.8699 Lr: 1.91368e-04 Mem R(MA/MR): 27822 (21200/36094) [2025-04-28 23:59:01,025 INFO hook.py line 650 1619929] Train: [202/512][150/242] Data 0.016 (0.017) Batch 1.275 (1.401) Remain 29:13:45 loss: 5.1660 Lr: 1.91254e-04 Mem R(MA/MR): 29650 (21200/36094) [2025-04-29 00:00:09,676 INFO hook.py line 650 1619929] Train: [202/512][200/242] Data 0.013 (0.017) Batch 1.263 (1.394) Remain 29:03:44 loss: 5.7047 Lr: 1.91139e-04 Mem R(MA/MR): 32112 (21200/36094) [2025-04-29 00:01:04,500 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3835 loss_mask: 0.0406 loss_dice: 2.1696 loss_score: 0.0000 loss_bbox: 0.0531 loss_sp_cls: 0.8716 loss: 5.6494 [2025-04-29 00:01:09,479 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:02:34,690 INFO hook.py line 650 1619929] Train: [203/512][50/242] Data 0.016 (0.017) Batch 1.450 (1.459) Remain 30:23:21 loss: 5.4331 Lr: 1.90928e-04 Mem R(MA/MR): 22360 (21200/36094) [2025-04-29 00:03:44,110 INFO hook.py line 650 1619929] Train: [203/512][100/242] Data 0.015 (0.017) Batch 1.383 (1.423) Remain 29:36:30 loss: 5.3814 Lr: 1.90814e-04 Mem R(MA/MR): 22360 (21200/36094) [2025-04-29 00:04:56,896 INFO hook.py line 650 1619929] Train: [203/512][150/242] Data 0.015 (0.017) Batch 1.322 (1.434) Remain 29:49:19 loss: 5.6356 Lr: 1.90699e-04 Mem R(MA/MR): 25256 (21200/36094) [2025-04-29 00:06:05,760 INFO hook.py line 650 1619929] Train: [203/512][200/242] Data 0.016 (0.017) Batch 1.240 (1.420) Remain 29:30:12 loss: 6.3553 Lr: 1.90585e-04 Mem R(MA/MR): 25256 (21200/36094) [2025-04-29 00:07:02,101 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3754 loss_mask: 0.0392 loss_dice: 2.1499 loss_score: 0.0000 loss_bbox: 0.0532 loss_sp_cls: 0.8665 loss: 5.5848 [2025-04-29 00:07:03,124 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:08:34,734 INFO hook.py line 650 1619929] Train: [204/512][50/242] Data 0.015 (0.017) Batch 1.240 (1.423) Remain 29:31:53 loss: 5.6758 Lr: 1.90376e-04 Mem R(MA/MR): 21270 (21200/36094) [2025-04-29 00:09:43,725 INFO hook.py line 650 1619929] Train: [204/512][100/242] Data 0.016 (0.017) Batch 1.351 (1.401) Remain 29:03:09 loss: 5.6075 Lr: 1.90261e-04 Mem R(MA/MR): 25702 (21200/36094) [2025-04-29 00:10:52,575 INFO hook.py line 650 1619929] Train: [204/512][150/242] Data 0.016 (0.017) Batch 1.464 (1.393) Remain 28:52:04 loss: 5.7411 Lr: 1.90147e-04 Mem R(MA/MR): 27530 (21200/36094) [2025-04-29 00:12:00,953 INFO hook.py line 650 1619929] Train: [204/512][200/242] Data 0.014 (0.017) Batch 1.431 (1.386) Remain 28:43:01 loss: 6.7112 Lr: 1.90032e-04 Mem R(MA/MR): 27530 (21200/36094) [2025-04-29 00:12:56,011 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3872 loss_mask: 0.0405 loss_dice: 2.1879 loss_score: 0.0000 loss_bbox: 0.0540 loss_sp_cls: 0.8812 loss: 5.6952 [2025-04-29 00:12:59,827 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:14:26,058 INFO hook.py line 650 1619929] Train: [205/512][50/242] Data 0.016 (0.017) Batch 1.570 (1.420) Remain 29:22:58 loss: 7.0194 Lr: 1.89821e-04 Mem R(MA/MR): 23998 (21200/36094) [2025-04-29 00:15:34,400 INFO hook.py line 650 1619929] Train: [205/512][100/242] Data 0.017 (0.016) Batch 1.277 (1.393) Remain 28:47:42 loss: 4.5517 Lr: 1.89707e-04 Mem R(MA/MR): 26490 (21200/36094) [2025-04-29 00:16:42,127 INFO hook.py line 650 1619929] Train: [205/512][150/242] Data 0.016 (0.016) Batch 1.403 (1.380) Remain 28:30:28 loss: 5.7660 Lr: 1.89592e-04 Mem R(MA/MR): 26490 (21200/36094) [2025-04-29 00:17:52,286 INFO hook.py line 650 1619929] Train: [205/512][200/242] Data 0.015 (0.016) Batch 1.278 (1.386) Remain 28:36:43 loss: 6.2794 Lr: 1.89477e-04 Mem R(MA/MR): 26490 (21200/36094) [2025-04-29 00:18:46,556 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3977 loss_mask: 0.0415 loss_dice: 2.2184 loss_score: 0.0000 loss_bbox: 0.0548 loss_sp_cls: 0.8862 loss: 5.7753 [2025-04-29 00:18:46,632 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:20:18,675 INFO hook.py line 650 1619929] Train: [206/512][50/242] Data 0.018 (0.016) Batch 1.366 (1.446) Remain 29:49:52 loss: 6.0239 Lr: 1.89266e-04 Mem R(MA/MR): 22868 (21200/36094) [2025-04-29 00:21:28,175 INFO hook.py line 650 1619929] Train: [206/512][100/242] Data 0.016 (0.016) Batch 1.225 (1.417) Remain 29:12:40 loss: 4.7887 Lr: 1.89152e-04 Mem R(MA/MR): 26224 (21200/36094) [2025-04-29 00:22:36,229 INFO hook.py line 650 1619929] Train: [206/512][150/242] Data 0.017 (0.016) Batch 1.493 (1.398) Remain 28:47:50 loss: 4.8175 Lr: 1.89037e-04 Mem R(MA/MR): 28700 (21200/36094) [2025-04-29 00:23:45,851 INFO hook.py line 650 1619929] Train: [206/512][200/242] Data 0.015 (0.016) Batch 1.378 (1.397) Remain 28:44:52 loss: 5.6082 Lr: 1.88922e-04 Mem R(MA/MR): 28700 (21200/36094) [2025-04-29 00:24:40,620 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3996 loss_mask: 0.0421 loss_dice: 2.2136 loss_score: 0.0000 loss_bbox: 0.0550 loss_sp_cls: 0.8926 loss: 5.7856 [2025-04-29 00:24:44,150 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:26:08,152 INFO hook.py line 650 1619929] Train: [207/512][50/242] Data 0.023 (0.017) Batch 1.306 (1.439) Remain 29:34:19 loss: 4.8599 Lr: 1.88711e-04 Mem R(MA/MR): 22012 (21200/36094) [2025-04-29 00:27:17,534 INFO hook.py line 650 1619929] Train: [207/512][100/242] Data 0.015 (0.017) Batch 1.313 (1.412) Remain 29:00:45 loss: 5.4720 Lr: 1.88597e-04 Mem R(MA/MR): 22012 (21200/36094) [2025-04-29 00:28:27,606 INFO hook.py line 650 1619929] Train: [207/512][150/242] Data 0.015 (0.016) Batch 1.397 (1.409) Remain 28:55:00 loss: 6.9381 Lr: 1.88482e-04 Mem R(MA/MR): 22012 (21200/36094) [2025-04-29 00:29:38,130 INFO hook.py line 650 1619929] Train: [207/512][200/242] Data 0.015 (0.016) Batch 1.291 (1.409) Remain 28:54:24 loss: 5.2965 Lr: 1.88367e-04 Mem R(MA/MR): 22056 (21200/36094) [2025-04-29 00:30:33,380 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3996 loss_mask: 0.0418 loss_dice: 2.2218 loss_score: 0.0000 loss_bbox: 0.0546 loss_sp_cls: 0.8882 loss: 5.7949 [2025-04-29 00:30:35,990 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:32:06,195 INFO hook.py line 650 1619929] Train: [208/512][50/242] Data 0.016 (0.016) Batch 1.295 (1.415) Remain 28:59:08 loss: 4.8284 Lr: 1.88156e-04 Mem R(MA/MR): 20580 (21200/36094) [2025-04-29 00:33:15,529 INFO hook.py line 650 1619929] Train: [208/512][100/242] Data 0.017 (0.016) Batch 1.294 (1.400) Remain 28:40:15 loss: 5.1683 Lr: 1.88041e-04 Mem R(MA/MR): 21904 (21200/36094) [2025-04-29 00:34:24,640 INFO hook.py line 650 1619929] Train: [208/512][150/242] Data 0.017 (0.017) Batch 1.451 (1.394) Remain 28:31:32 loss: 5.4592 Lr: 1.87926e-04 Mem R(MA/MR): 25826 (21200/36094) [2025-04-29 00:35:31,293 INFO hook.py line 650 1619929] Train: [208/512][200/242] Data 0.014 (0.016) Batch 1.217 (1.379) Remain 28:11:21 loss: 5.4058 Lr: 1.87812e-04 Mem R(MA/MR): 25826 (21200/36094) [2025-04-29 00:36:25,374 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3953 loss_mask: 0.0408 loss_dice: 2.2086 loss_score: 0.0000 loss_bbox: 0.0547 loss_sp_cls: 0.8827 loss: 5.7600 [2025-04-29 00:36:26,095 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 00:36:28,415 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.0007 Process Time: 0.307 Mem R(MA/MR): 4574 (21200/36094) [2025-04-29 00:36:29,850 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.7612 Process Time: 0.465 Mem R(MA/MR): 7334 (21200/36094) [2025-04-29 00:36:31,520 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2513 Process Time: 0.612 Mem R(MA/MR): 10054 (21200/36094) [2025-04-29 00:36:38,784 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.2221 Process Time: 1.250 Mem R(MA/MR): 19978 (21200/36094) [2025-04-29 00:36:39,708 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.2480 Process Time: 0.257 Mem R(MA/MR): 7324 (21200/36094) [2025-04-29 00:36:40,962 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.1778 Process Time: 0.324 Mem R(MA/MR): 11482 (21200/36094) [2025-04-29 00:36:41,625 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.5412 Process Time: 0.255 Mem R(MA/MR): 6358 (21200/36094) [2025-04-29 00:36:42,190 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.9246 Process Time: 0.213 Mem R(MA/MR): 4614 (21200/36094) [2025-04-29 00:36:43,053 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.3008 Process Time: 0.253 Mem R(MA/MR): 11606 (21200/36094) [2025-04-29 00:36:44,594 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.0319 Process Time: 0.291 Mem R(MA/MR): 9924 (21200/36094) [2025-04-29 00:36:47,155 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2597 Process Time: 0.470 Mem R(MA/MR): 18828 (21200/36094) [2025-04-29 00:36:49,372 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3947 Process Time: 0.397 Mem R(MA/MR): 15514 (21200/36094) [2025-04-29 00:36:50,323 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.3799 Process Time: 0.209 Mem R(MA/MR): 9062 (21200/36094) [2025-04-29 00:36:50,617 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.4087 Process Time: 0.104 Mem R(MA/MR): 5168 (21200/36094) [2025-04-29 00:36:52,702 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.6160 Process Time: 0.247 Mem R(MA/MR): 16792 (21200/36094) [2025-04-29 00:36:54,592 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6058 Process Time: 0.508 Mem R(MA/MR): 14904 (21200/36094) [2025-04-29 00:36:55,442 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.9026 Process Time: 0.251 Mem R(MA/MR): 6718 (21200/36094) [2025-04-29 00:36:56,318 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9982 Process Time: 0.250 Mem R(MA/MR): 8600 (21200/36094) [2025-04-29 00:36:57,837 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.2663 Process Time: 0.192 Mem R(MA/MR): 6190 (21200/36094) [2025-04-29 00:36:59,212 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.1858 Process Time: 0.195 Mem R(MA/MR): 11598 (21200/36094) [2025-04-29 00:37:06,951 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.4745 Process Time: 0.845 Mem R(MA/MR): 23368 (21200/36094) [2025-04-29 00:37:07,979 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3083 Process Time: 0.432 Mem R(MA/MR): 7132 (21200/36094) [2025-04-29 00:37:17,803 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.9777 Process Time: 0.557 Mem R(MA/MR): 10312 (21200/36094) [2025-04-29 00:37:18,377 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.4451 Process Time: 0.213 Mem R(MA/MR): 5626 (21200/36094) [2025-04-29 00:37:19,429 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1787 Process Time: 0.318 Mem R(MA/MR): 9658 (21200/36094) [2025-04-29 00:37:26,792 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.7323 Process Time: 1.574 Mem R(MA/MR): 31002 (21200/36094) [2025-04-29 00:37:29,314 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.0891 Process Time: 0.420 Mem R(MA/MR): 10302 (21200/36094) [2025-04-29 00:37:30,750 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5830 Process Time: 0.318 Mem R(MA/MR): 9306 (21200/36094) [2025-04-29 00:37:35,632 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0956 Process Time: 0.618 Mem R(MA/MR): 17512 (21200/36094) [2025-04-29 00:37:36,776 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.0692 Process Time: 0.263 Mem R(MA/MR): 7888 (21200/36094) [2025-04-29 00:37:40,477 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8421 Process Time: 0.351 Mem R(MA/MR): 20832 (21200/36094) [2025-04-29 00:37:40,821 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1068 Process Time: 0.135 Mem R(MA/MR): 4294 (21200/36094) [2025-04-29 00:37:44,147 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.5485 Process Time: 0.347 Mem R(MA/MR): 24916 (21200/36094) [2025-04-29 00:37:45,410 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.5105 Process Time: 0.440 Mem R(MA/MR): 10106 (21200/36094) [2025-04-29 00:37:47,537 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7658 Process Time: 0.589 Mem R(MA/MR): 14074 (21200/36094) [2025-04-29 00:37:48,182 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1316 Process Time: 0.344 Mem R(MA/MR): 6552 (21200/36094) [2025-04-29 00:37:51,923 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.0178 Process Time: 0.749 Mem R(MA/MR): 28578 (21200/36094) [2025-04-29 00:37:53,166 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.6519 Process Time: 0.230 Mem R(MA/MR): 10860 (21200/36094) [2025-04-29 00:37:53,606 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.6368 Process Time: 0.138 Mem R(MA/MR): 5732 (21200/36094) [2025-04-29 00:37:54,679 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7570 Process Time: 0.289 Mem R(MA/MR): 10384 (21200/36094) [2025-04-29 00:37:55,516 INFO hook.py line 449 1619929] Test: [41/50] Loss 5.2485 Process Time: 0.182 Mem R(MA/MR): 9298 (21200/36094) [2025-04-29 00:37:56,211 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.0632 Process Time: 0.238 Mem R(MA/MR): 5748 (21200/36094) [2025-04-29 00:37:56,757 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.1016 Process Time: 0.213 Mem R(MA/MR): 5844 (21200/36094) [2025-04-29 00:37:57,463 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.6569 Process Time: 0.263 Mem R(MA/MR): 7312 (21200/36094) [2025-04-29 00:37:58,075 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3294 Process Time: 0.128 Mem R(MA/MR): 5534 (21200/36094) [2025-04-29 00:38:00,262 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.0387 Process Time: 0.313 Mem R(MA/MR): 14804 (21200/36094) [2025-04-29 00:38:06,520 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.8100 Process Time: 0.677 Mem R(MA/MR): 20364 (21200/36094) [2025-04-29 00:38:17,548 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2866 Process Time: 1.777 Mem R(MA/MR): 35198 (21200/36094) [2025-04-29 00:38:18,239 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.7279 Process Time: 0.242 Mem R(MA/MR): 6114 (21200/36094) [2025-04-29 00:38:20,617 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.6065 Process Time: 0.559 Mem R(MA/MR): 13714 (21200/36094) [2025-04-29 00:38:25,355 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 00:38:25,355 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 00:38:25,355 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] table : 0.233 0.549 0.770 0.726 0.603 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] door : 0.430 0.720 0.883 0.848 0.709 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] ceiling lamp : 0.548 0.746 0.836 0.883 0.707 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] cabinet : 0.301 0.412 0.532 0.500 0.493 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] blinds : 0.515 0.734 0.805 0.773 0.739 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] curtain : 0.172 0.260 0.651 0.438 0.583 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] chair : 0.566 0.726 0.801 0.865 0.631 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] storage cabinet: 0.173 0.319 0.482 0.421 0.640 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] office chair : 0.518 0.540 0.605 0.714 0.625 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] bookshelf : 0.337 0.757 0.757 0.889 0.727 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] whiteboard : 0.588 0.752 0.754 0.958 0.657 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] window : 0.103 0.255 0.583 0.444 0.352 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] box : 0.168 0.317 0.502 0.534 0.343 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] monitor : 0.569 0.733 0.834 0.889 0.686 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] shelf : 0.086 0.213 0.470 0.583 0.233 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] heater : 0.447 0.725 0.852 0.903 0.737 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] kitchen cabinet: 0.171 0.489 0.662 0.619 0.520 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] sofa : 0.507 0.804 0.796 1.000 0.583 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] bed : 0.114 0.244 0.655 0.364 0.500 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] trash can : 0.526 0.667 0.722 0.831 0.754 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] book : 0.012 0.027 0.068 0.178 0.097 [2025-04-29 00:38:25,355 INFO hook.py line 395 1619929] plant : 0.487 0.718 0.833 0.929 0.722 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] blanket : 0.340 0.515 0.629 0.857 0.545 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] tv : 0.715 0.833 0.833 1.000 0.833 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] computer tower : 0.210 0.381 0.574 0.654 0.405 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] refrigerator : 0.158 0.364 0.443 1.000 0.333 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] jacket : 0.020 0.044 0.392 0.160 0.364 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] sink : 0.383 0.618 0.877 0.789 0.682 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] bag : 0.131 0.180 0.227 0.450 0.333 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] picture : 0.153 0.301 0.441 0.378 0.436 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] pillow : 0.566 0.789 0.854 0.762 0.842 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] towel : 0.182 0.329 0.514 0.800 0.316 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] suitcase : 0.269 0.365 0.375 0.500 0.429 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] backpack : 0.318 0.398 0.398 0.467 0.538 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] crate : 0.118 0.368 0.586 0.556 0.455 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] keyboard : 0.369 0.498 0.584 0.850 0.436 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] toilet : 0.742 0.889 1.000 1.000 0.889 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] printer : 0.111 0.168 0.220 0.400 0.222 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] poster : 0.000 0.001 0.007 0.018 0.111 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] painting : 0.071 0.071 0.083 0.143 1.000 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] microwave : 0.469 0.750 0.875 1.000 0.750 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] shoes : 0.127 0.208 0.498 0.565 0.317 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] socket : 0.180 0.438 0.635 0.648 0.486 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] bottle : 0.159 0.227 0.317 0.377 0.313 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] bucket : 0.218 0.321 0.325 0.667 0.286 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] cushion : 0.053 0.115 0.366 0.235 0.667 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] basket : 0.002 0.007 0.046 0.100 0.143 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] telephone : 0.267 0.412 0.487 1.000 0.412 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] laptop : 0.239 0.292 0.419 0.500 0.375 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] plant pot : 0.200 0.440 0.475 0.778 0.438 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] exhaust fan : 0.183 0.333 0.333 1.000 0.333 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] cup : 0.191 0.314 0.362 0.700 0.318 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] coat hanger : 0.028 0.250 0.750 1.000 0.250 [2025-04-29 00:38:25,356 INFO hook.py line 395 1619929] light switch : 0.234 0.489 0.678 0.809 0.585 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] speaker : 0.353 0.395 0.545 0.600 0.545 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] smoke detector : 0.664 0.813 0.821 0.905 0.792 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] power strip : 0.013 0.029 0.050 0.182 0.200 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] mouse : 0.471 0.672 0.719 0.957 0.688 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] toilet paper : 0.217 0.364 0.447 0.778 0.412 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] paper towel : 0.115 0.250 0.250 1.000 0.250 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] clock : 0.556 1.000 1.000 1.000 1.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] tap : 0.147 0.255 0.649 0.750 0.333 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] soap dispenser : 0.393 0.585 0.755 0.667 0.800 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] bowl : 0.148 0.278 0.278 0.667 0.667 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] whiteboard eraser: 0.246 0.501 0.501 0.714 0.833 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] toilet brush : 0.611 0.755 0.930 1.000 0.667 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.083 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 00:38:25,357 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 00:38:25,357 INFO hook.py line 404 1619929] average : 0.244 0.381 0.481 0.606 0.446 [2025-04-29 00:38:25,357 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 00:38:25,358 INFO hook.py line 480 1619929] Total Process Time: 20.813 s [2025-04-29 00:38:25,358 INFO hook.py line 481 1619929] Average Process Time: 418.491 ms [2025-04-29 00:38:25,358 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 00:38:25,406 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 00:38:25,412 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:39:54,924 INFO hook.py line 650 1619929] Train: [209/512][50/242] Data 0.016 (0.017) Batch 1.407 (1.400) Remain 28:35:51 loss: 7.6635 Lr: 1.87600e-04 Mem R(MA/MR): 20348 (21200/36094) [2025-04-29 00:41:04,934 INFO hook.py line 650 1619929] Train: [209/512][100/242] Data 0.017 (0.025) Batch 1.331 (1.400) Remain 28:34:35 loss: 5.6029 Lr: 1.87486e-04 Mem R(MA/MR): 22022 (21200/36094) [2025-04-29 00:42:15,774 INFO hook.py line 650 1619929] Train: [209/512][150/242] Data 0.016 (0.022) Batch 1.292 (1.406) Remain 28:40:16 loss: 4.7307 Lr: 1.87371e-04 Mem R(MA/MR): 23848 (21200/36094) [2025-04-29 00:43:26,524 INFO hook.py line 650 1619929] Train: [209/512][200/242] Data 0.015 (0.020) Batch 1.370 (1.408) Remain 28:41:57 loss: 5.4742 Lr: 1.87256e-04 Mem R(MA/MR): 23848 (21200/36094) [2025-04-29 00:44:21,521 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3952 loss_mask: 0.0410 loss_dice: 2.1986 loss_score: 0.0000 loss_bbox: 0.0529 loss_sp_cls: 0.8842 loss: 5.7257 [2025-04-29 00:44:21,609 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:45:50,178 INFO hook.py line 650 1619929] Train: [210/512][50/242] Data 0.017 (0.017) Batch 1.598 (1.496) Remain 30:26:37 loss: 6.0157 Lr: 1.87045e-04 Mem R(MA/MR): 21418 (21200/36094) [2025-04-29 00:46:59,398 INFO hook.py line 650 1619929] Train: [210/512][100/242] Data 0.016 (0.017) Batch 1.211 (1.438) Remain 29:15:23 loss: 5.1924 Lr: 1.86930e-04 Mem R(MA/MR): 21418 (21200/36094) [2025-04-29 00:48:09,724 INFO hook.py line 650 1619929] Train: [210/512][150/242] Data 0.016 (0.017) Batch 1.428 (1.428) Remain 29:00:59 loss: 5.4857 Lr: 1.86815e-04 Mem R(MA/MR): 21420 (21200/36094) [2025-04-29 00:49:18,731 INFO hook.py line 650 1619929] Train: [210/512][200/242] Data 0.015 (0.017) Batch 1.410 (1.415) Remain 28:45:09 loss: 7.0968 Lr: 1.86700e-04 Mem R(MA/MR): 21420 (21200/36094) [2025-04-29 00:50:13,423 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3925 loss_mask: 0.0415 loss_dice: 2.2105 loss_score: 0.0000 loss_bbox: 0.0541 loss_sp_cls: 0.8803 loss: 5.7464 [2025-04-29 00:50:13,494 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:51:44,604 INFO hook.py line 650 1619929] Train: [211/512][50/242] Data 0.017 (0.017) Batch 1.267 (1.410) Remain 28:36:49 loss: 5.5226 Lr: 1.86489e-04 Mem R(MA/MR): 22146 (21200/36094) [2025-04-29 00:52:52,140 INFO hook.py line 650 1619929] Train: [211/512][100/242] Data 0.017 (0.017) Batch 1.333 (1.380) Remain 27:58:13 loss: 5.7145 Lr: 1.86374e-04 Mem R(MA/MR): 22146 (21200/36094) [2025-04-29 00:54:01,744 INFO hook.py line 650 1619929] Train: [211/512][150/242] Data 0.018 (0.017) Batch 1.519 (1.384) Remain 28:02:11 loss: 5.9823 Lr: 1.86259e-04 Mem R(MA/MR): 22146 (21200/36094) [2025-04-29 00:55:13,708 INFO hook.py line 650 1619929] Train: [211/512][200/242] Data 0.015 (0.016) Batch 1.269 (1.398) Remain 28:18:07 loss: 5.6624 Lr: 1.86144e-04 Mem R(MA/MR): 22146 (21200/36094) [2025-04-29 00:56:09,133 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3905 loss_mask: 0.0408 loss_dice: 2.1941 loss_score: 0.0000 loss_bbox: 0.0545 loss_sp_cls: 0.8813 loss: 5.7132 [2025-04-29 00:56:11,626 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 00:57:42,689 INFO hook.py line 650 1619929] Train: [212/512][50/242] Data 0.018 (0.017) Batch 1.365 (1.419) Remain 28:41:30 loss: 6.2684 Lr: 1.85933e-04 Mem R(MA/MR): 21604 (21200/36094) [2025-04-29 00:58:53,908 INFO hook.py line 650 1619929] Train: [212/512][100/242] Data 0.016 (0.016) Batch 1.445 (1.422) Remain 28:43:42 loss: 5.2684 Lr: 1.85818e-04 Mem R(MA/MR): 23670 (21200/36094) [2025-04-29 01:00:03,632 INFO hook.py line 650 1619929] Train: [212/512][150/242] Data 0.016 (0.016) Batch 1.295 (1.412) Remain 28:31:16 loss: 6.3357 Lr: 1.85703e-04 Mem R(MA/MR): 23670 (21200/36094) [2025-04-29 01:01:12,063 INFO hook.py line 650 1619929] Train: [212/512][200/242] Data 0.015 (0.016) Batch 1.315 (1.401) Remain 28:16:36 loss: 4.6672 Lr: 1.85588e-04 Mem R(MA/MR): 23670 (21200/36094) [2025-04-29 01:02:08,582 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3812 loss_mask: 0.0394 loss_dice: 2.1643 loss_score: 0.0000 loss_bbox: 0.0535 loss_sp_cls: 0.8712 loss: 5.6300 [2025-04-29 01:02:12,374 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:03:46,220 INFO hook.py line 650 1619929] Train: [213/512][50/242] Data 0.015 (0.017) Batch 1.324 (1.449) Remain 29:11:40 loss: 4.1890 Lr: 1.85377e-04 Mem R(MA/MR): 23086 (21200/36094) [2025-04-29 01:04:56,086 INFO hook.py line 650 1619929] Train: [213/512][100/242] Data 0.017 (0.017) Batch 1.549 (1.422) Remain 28:38:28 loss: 5.6531 Lr: 1.85262e-04 Mem R(MA/MR): 23100 (21200/36094) [2025-04-29 01:06:04,970 INFO hook.py line 650 1619929] Train: [213/512][150/242] Data 0.016 (0.016) Batch 1.293 (1.407) Remain 28:19:00 loss: 5.3202 Lr: 1.85147e-04 Mem R(MA/MR): 27938 (21200/36094) [2025-04-29 01:07:13,916 INFO hook.py line 650 1619929] Train: [213/512][200/242] Data 0.015 (0.017) Batch 1.322 (1.400) Remain 28:09:13 loss: 4.8881 Lr: 1.85032e-04 Mem R(MA/MR): 30052 (21200/36094) [2025-04-29 01:08:09,168 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3657 loss_mask: 0.0385 loss_dice: 2.1197 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8531 loss: 5.5024 [2025-04-29 01:08:13,345 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:09:42,468 INFO hook.py line 650 1619929] Train: [214/512][50/242] Data 0.017 (0.017) Batch 1.361 (1.377) Remain 27:38:54 loss: 4.8501 Lr: 1.84820e-04 Mem R(MA/MR): 25394 (21200/36094) [2025-04-29 01:10:50,906 INFO hook.py line 650 1619929] Train: [214/512][100/242] Data 0.017 (0.017) Batch 1.310 (1.373) Remain 27:32:54 loss: 5.4539 Lr: 1.84705e-04 Mem R(MA/MR): 27826 (21200/36094) [2025-04-29 01:12:01,736 INFO hook.py line 650 1619929] Train: [214/512][150/242] Data 0.016 (0.017) Batch 1.272 (1.388) Remain 27:49:49 loss: 5.5563 Lr: 1.84590e-04 Mem R(MA/MR): 27826 (21200/36094) [2025-04-29 01:13:11,118 INFO hook.py line 650 1619929] Train: [214/512][200/242] Data 0.014 (0.016) Batch 1.450 (1.388) Remain 27:48:42 loss: 5.6434 Lr: 1.84475e-04 Mem R(MA/MR): 27828 (21200/36094) [2025-04-29 01:14:07,632 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3584 loss_mask: 0.0381 loss_dice: 2.1002 loss_score: 0.0000 loss_bbox: 0.0521 loss_sp_cls: 0.8492 loss: 5.4442 [2025-04-29 01:14:08,107 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:15:33,602 INFO hook.py line 650 1619929] Train: [215/512][50/242] Data 0.015 (0.017) Batch 1.357 (1.431) Remain 28:39:05 loss: 4.3540 Lr: 1.84264e-04 Mem R(MA/MR): 22014 (21200/36094) [2025-04-29 01:16:43,996 INFO hook.py line 650 1619929] Train: [215/512][100/242] Data 0.017 (0.017) Batch 1.414 (1.419) Remain 28:23:25 loss: 6.2063 Lr: 1.84149e-04 Mem R(MA/MR): 23620 (21200/36094) [2025-04-29 01:17:53,858 INFO hook.py line 650 1619929] Train: [215/512][150/242] Data 0.016 (0.017) Batch 1.313 (1.412) Remain 28:13:16 loss: 5.9301 Lr: 1.84034e-04 Mem R(MA/MR): 23628 (21200/36094) [2025-04-29 01:19:04,166 INFO hook.py line 650 1619929] Train: [215/512][200/242] Data 0.014 (0.017) Batch 1.381 (1.410) Remain 28:10:25 loss: 6.1303 Lr: 1.83919e-04 Mem R(MA/MR): 27098 (21200/36094) [2025-04-29 01:19:58,370 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3639 loss_mask: 0.0381 loss_dice: 2.1109 loss_score: 0.0000 loss_bbox: 0.0531 loss_sp_cls: 0.8409 loss: 5.4783 [2025-04-29 01:19:58,535 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:21:29,480 INFO hook.py line 650 1619929] Train: [216/512][50/242] Data 0.016 (0.016) Batch 1.439 (1.436) Remain 28:39:20 loss: 6.3993 Lr: 1.83707e-04 Mem R(MA/MR): 22148 (21200/36094) [2025-04-29 01:22:39,018 INFO hook.py line 650 1619929] Train: [216/512][100/242] Data 0.016 (0.016) Batch 1.354 (1.413) Remain 28:10:04 loss: 4.5975 Lr: 1.83592e-04 Mem R(MA/MR): 23922 (21200/36094) [2025-04-29 01:23:47,199 INFO hook.py line 650 1619929] Train: [216/512][150/242] Data 0.016 (0.016) Batch 1.231 (1.396) Remain 27:48:52 loss: 5.4409 Lr: 1.83477e-04 Mem R(MA/MR): 23922 (21200/36094) [2025-04-29 01:24:55,694 INFO hook.py line 650 1619929] Train: [216/512][200/242] Data 0.016 (0.016) Batch 1.503 (1.389) Remain 27:39:46 loss: 6.1856 Lr: 1.83362e-04 Mem R(MA/MR): 23922 (21200/36094) [2025-04-29 01:25:50,082 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3600 loss_mask: 0.0387 loss_dice: 2.1152 loss_score: 0.0000 loss_bbox: 0.0517 loss_sp_cls: 0.8462 loss: 5.4646 [2025-04-29 01:25:50,647 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 01:25:52,945 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.8383 Process Time: 0.302 Mem R(MA/MR): 4106 (21200/36094) [2025-04-29 01:25:54,484 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.0216 Process Time: 0.416 Mem R(MA/MR): 6692 (21200/36094) [2025-04-29 01:25:55,876 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.6388 Process Time: 0.409 Mem R(MA/MR): 9278 (21200/36094) [2025-04-29 01:26:04,459 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.8338 Process Time: 1.801 Mem R(MA/MR): 19578 (21200/36094) [2025-04-29 01:26:05,874 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5746 Process Time: 0.557 Mem R(MA/MR): 6276 (21200/36094) [2025-04-29 01:26:07,659 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4077 Process Time: 0.587 Mem R(MA/MR): 10970 (21200/36094) [2025-04-29 01:26:08,393 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3140 Process Time: 0.237 Mem R(MA/MR): 5918 (21200/36094) [2025-04-29 01:26:08,864 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.1181 Process Time: 0.126 Mem R(MA/MR): 4154 (21200/36094) [2025-04-29 01:26:09,758 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.5882 Process Time: 0.200 Mem R(MA/MR): 11094 (21200/36094) [2025-04-29 01:26:11,312 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7389 Process Time: 0.214 Mem R(MA/MR): 9130 (21200/36094) [2025-04-29 01:26:14,162 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.0023 Process Time: 0.610 Mem R(MA/MR): 17898 (21200/36094) [2025-04-29 01:26:17,090 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2543 Process Time: 0.543 Mem R(MA/MR): 14810 (21200/36094) [2025-04-29 01:26:18,036 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.4425 Process Time: 0.184 Mem R(MA/MR): 8350 (21200/36094) [2025-04-29 01:26:18,368 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0327 Process Time: 0.107 Mem R(MA/MR): 4454 (21200/36094) [2025-04-29 01:26:21,036 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.0873 Process Time: 0.250 Mem R(MA/MR): 16134 (21200/36094) [2025-04-29 01:26:22,964 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6017 Process Time: 0.627 Mem R(MA/MR): 14216 (21200/36094) [2025-04-29 01:26:24,034 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3901 Process Time: 0.372 Mem R(MA/MR): 6286 (21200/36094) [2025-04-29 01:26:24,953 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1608 Process Time: 0.280 Mem R(MA/MR): 7918 (21200/36094) [2025-04-29 01:26:26,495 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.4704 Process Time: 0.240 Mem R(MA/MR): 5828 (21200/36094) [2025-04-29 01:26:27,971 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.7232 Process Time: 0.194 Mem R(MA/MR): 11226 (21200/36094) [2025-04-29 01:26:35,790 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.9457 Process Time: 0.575 Mem R(MA/MR): 23252 (21200/36094) [2025-04-29 01:26:36,410 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2415 Process Time: 0.234 Mem R(MA/MR): 6380 (21200/36094) [2025-04-29 01:26:47,097 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.9001 Process Time: 0.270 Mem R(MA/MR): 9508 (21200/36094) [2025-04-29 01:26:47,655 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.2202 Process Time: 0.135 Mem R(MA/MR): 5184 (21200/36094) [2025-04-29 01:26:48,522 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1480 Process Time: 0.193 Mem R(MA/MR): 8750 (21200/36094) [2025-04-29 01:26:56,193 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.2092 Process Time: 2.031 Mem R(MA/MR): 30718 (21200/36094) [2025-04-29 01:26:58,072 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.2534 Process Time: 0.211 Mem R(MA/MR): 9886 (21200/36094) [2025-04-29 01:26:59,948 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.6149 Process Time: 0.679 Mem R(MA/MR): 8604 (21200/36094) [2025-04-29 01:27:04,656 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.4179 Process Time: 0.373 Mem R(MA/MR): 16432 (21200/36094) [2025-04-29 01:27:05,435 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.6334 Process Time: 0.163 Mem R(MA/MR): 7110 (21200/36094) [2025-04-29 01:27:08,686 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5959 Process Time: 0.378 Mem R(MA/MR): 20254 (21200/36094) [2025-04-29 01:27:09,037 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1022 Process Time: 0.147 Mem R(MA/MR): 3664 (21200/36094) [2025-04-29 01:27:12,915 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.0375 Process Time: 0.607 Mem R(MA/MR): 24362 (21200/36094) [2025-04-29 01:27:13,788 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5731 Process Time: 0.201 Mem R(MA/MR): 9620 (21200/36094) [2025-04-29 01:27:15,478 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.4492 Process Time: 0.339 Mem R(MA/MR): 13500 (21200/36094) [2025-04-29 01:27:16,340 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0910 Process Time: 0.306 Mem R(MA/MR): 6060 (21200/36094) [2025-04-29 01:27:19,702 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.0747 Process Time: 0.615 Mem R(MA/MR): 27886 (21200/36094) [2025-04-29 01:27:21,043 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.8052 Process Time: 0.223 Mem R(MA/MR): 10350 (21200/36094) [2025-04-29 01:27:21,411 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9325 Process Time: 0.116 Mem R(MA/MR): 5298 (21200/36094) [2025-04-29 01:27:22,366 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.0597 Process Time: 0.219 Mem R(MA/MR): 9988 (21200/36094) [2025-04-29 01:27:23,259 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.9497 Process Time: 0.199 Mem R(MA/MR): 8680 (21200/36094) [2025-04-29 01:27:24,084 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.8271 Process Time: 0.379 Mem R(MA/MR): 5308 (21200/36094) [2025-04-29 01:27:24,990 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.0896 Process Time: 0.473 Mem R(MA/MR): 5342 (21200/36094) [2025-04-29 01:27:25,959 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.6353 Process Time: 0.429 Mem R(MA/MR): 6552 (21200/36094) [2025-04-29 01:27:26,686 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3816 Process Time: 0.211 Mem R(MA/MR): 4934 (21200/36094) [2025-04-29 01:27:29,271 INFO hook.py line 449 1619929] Test: [46/50] Loss 9.7592 Process Time: 0.446 Mem R(MA/MR): 14290 (21200/36094) [2025-04-29 01:27:35,685 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.0266 Process Time: 0.688 Mem R(MA/MR): 19524 (21200/36094) [2025-04-29 01:27:45,918 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.2827 Process Time: 1.872 Mem R(MA/MR): 34692 (21200/36094) [2025-04-29 01:27:46,475 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9156 Process Time: 0.131 Mem R(MA/MR): 5382 (21200/36094) [2025-04-29 01:27:48,345 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.8227 Process Time: 0.226 Mem R(MA/MR): 13430 (21200/36094) [2025-04-29 01:27:52,319 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 01:27:52,319 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 01:27:52,319 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 01:27:52,319 INFO hook.py line 395 1619929] table : 0.260 0.627 0.780 0.862 0.596 [2025-04-29 01:27:52,319 INFO hook.py line 395 1619929] door : 0.484 0.827 0.895 0.968 0.772 [2025-04-29 01:27:52,319 INFO hook.py line 395 1619929] ceiling lamp : 0.564 0.773 0.873 0.832 0.768 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] cabinet : 0.315 0.432 0.536 0.533 0.478 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] blinds : 0.438 0.543 0.748 0.500 0.783 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] curtain : 0.331 0.619 0.661 0.556 0.833 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] chair : 0.604 0.739 0.792 0.663 0.807 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] storage cabinet: 0.144 0.327 0.570 0.647 0.440 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] office chair : 0.564 0.617 0.645 0.722 0.812 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] bookshelf : 0.309 0.685 0.709 0.692 0.818 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] whiteboard : 0.535 0.704 0.756 0.788 0.743 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] window : 0.101 0.232 0.632 0.509 0.308 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] box : 0.227 0.390 0.540 0.581 0.414 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] monitor : 0.589 0.721 0.802 0.850 0.729 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] shelf : 0.144 0.300 0.488 0.625 0.333 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] heater : 0.496 0.753 0.860 0.912 0.816 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] kitchen cabinet: 0.123 0.276 0.680 0.393 0.440 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] sofa : 0.468 0.641 0.833 0.727 0.667 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] bed : 0.121 0.306 0.643 0.667 0.500 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] trash can : 0.522 0.658 0.730 0.831 0.754 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] book : 0.009 0.016 0.052 0.148 0.079 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] plant : 0.470 0.662 0.704 0.923 0.667 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] blanket : 0.325 0.545 0.636 1.000 0.545 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] tv : 0.855 1.000 1.000 1.000 1.000 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] computer tower : 0.262 0.354 0.574 0.435 0.476 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] refrigerator : 0.205 0.386 0.422 1.000 0.333 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] jacket : 0.069 0.149 0.357 0.357 0.455 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] sink : 0.387 0.568 0.875 0.789 0.682 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] bag : 0.133 0.228 0.255 0.478 0.407 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] picture : 0.152 0.318 0.429 0.577 0.385 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] pillow : 0.643 0.913 0.913 0.783 0.947 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] towel : 0.206 0.359 0.549 0.765 0.342 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] suitcase : 0.209 0.270 0.281 0.364 0.571 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] backpack : 0.460 0.548 0.552 0.875 0.538 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] crate : 0.108 0.488 0.562 0.538 0.636 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] keyboard : 0.442 0.598 0.671 0.714 0.641 [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 01:27:52,320 INFO hook.py line 395 1619929] toilet : 0.743 0.844 1.000 0.889 0.889 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] printer : 0.330 0.441 0.497 0.667 0.444 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] poster : 0.001 0.005 0.007 0.091 0.111 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] painting : 0.045 0.045 0.056 0.091 1.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] microwave : 0.523 0.858 0.985 0.875 0.875 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] shoes : 0.138 0.218 0.524 0.533 0.390 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] socket : 0.172 0.441 0.679 0.685 0.450 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] bottle : 0.116 0.172 0.326 0.444 0.241 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] bucket : 0.221 0.305 0.311 0.750 0.429 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] cushion : 0.230 0.320 0.376 0.333 0.667 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] shoe rack : 0.111 0.500 0.500 1.000 0.500 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] telephone : 0.324 0.661 0.664 0.800 0.706 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] laptop : 0.282 0.499 0.505 1.000 0.375 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] plant pot : 0.171 0.277 0.496 0.625 0.312 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] exhaust fan : 0.157 0.317 0.325 0.500 0.467 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] cup : 0.175 0.322 0.356 0.737 0.318 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] coat hanger : 0.141 0.250 0.750 1.000 0.250 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] light switch : 0.246 0.486 0.642 0.727 0.492 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] speaker : 0.326 0.426 0.531 0.714 0.455 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] smoke detector : 0.676 0.855 0.857 1.000 0.750 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] power strip : 0.055 0.100 0.126 0.333 0.300 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] paper bag : 0.056 0.056 0.062 0.111 1.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] mouse : 0.396 0.554 0.681 0.760 0.594 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] toilet paper : 0.240 0.350 0.404 0.750 0.353 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] paper towel : 0.021 0.031 0.031 0.500 0.125 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] clock : 0.160 0.222 0.222 0.500 0.667 [2025-04-29 01:27:52,321 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] tap : 0.105 0.190 0.599 0.429 0.333 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] soap dispenser : 0.422 0.707 0.707 1.000 0.600 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] bowl : 0.006 0.056 0.056 0.333 0.333 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] whiteboard eraser: 0.185 0.408 0.408 0.556 0.833 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] toilet brush : 0.486 0.782 0.955 1.000 0.667 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] spray bottle : 0.007 0.010 0.011 0.083 0.250 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] stapler : 0.006 0.056 0.113 0.333 0.333 [2025-04-29 01:27:52,322 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 01:27:52,322 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 01:27:52,322 INFO hook.py line 404 1619929] average : 0.249 0.384 0.475 0.595 0.478 [2025-04-29 01:27:52,322 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 01:27:52,322 INFO hook.py line 480 1619929] Total Process Time: 21.323 s [2025-04-29 01:27:52,322 INFO hook.py line 481 1619929] Average Process Time: 429.002 ms [2025-04-29 01:27:52,322 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 01:27:52,363 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 01:27:52,365 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:29:17,597 INFO hook.py line 650 1619929] Train: [217/512][50/242] Data 0.015 (0.033) Batch 1.354 (1.420) Remain 28:14:10 loss: 4.9347 Lr: 1.83150e-04 Mem R(MA/MR): 23580 (21200/36094) [2025-04-29 01:30:27,421 INFO hook.py line 650 1619929] Train: [217/512][100/242] Data 0.017 (0.025) Batch 1.519 (1.408) Remain 27:58:29 loss: 5.8686 Lr: 1.83035e-04 Mem R(MA/MR): 23584 (21200/36094) [2025-04-29 01:31:38,309 INFO hook.py line 650 1619929] Train: [217/512][150/242] Data 0.017 (0.022) Batch 1.521 (1.411) Remain 28:01:17 loss: 6.1869 Lr: 1.82920e-04 Mem R(MA/MR): 23592 (21200/36094) [2025-04-29 01:32:46,957 INFO hook.py line 650 1619929] Train: [217/512][200/242] Data 0.014 (0.020) Batch 1.335 (1.402) Remain 27:48:34 loss: 6.5025 Lr: 1.82805e-04 Mem R(MA/MR): 23592 (21200/36094) [2025-04-29 01:33:43,265 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3666 loss_mask: 0.0383 loss_dice: 2.1116 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8466 loss: 5.4838 [2025-04-29 01:33:46,556 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:35:09,705 INFO hook.py line 650 1619929] Train: [218/512][50/242] Data 0.015 (0.017) Batch 1.368 (1.416) Remain 28:03:39 loss: 6.0943 Lr: 1.82593e-04 Mem R(MA/MR): 22248 (21200/36094) [2025-04-29 01:36:19,203 INFO hook.py line 650 1619929] Train: [218/512][100/242] Data 0.016 (0.017) Batch 1.391 (1.403) Remain 27:46:31 loss: 5.3073 Lr: 1.82478e-04 Mem R(MA/MR): 26794 (21200/36094) [2025-04-29 01:37:28,337 INFO hook.py line 650 1619929] Train: [218/512][150/242] Data 0.015 (0.017) Batch 1.377 (1.396) Remain 27:37:17 loss: 6.6300 Lr: 1.82362e-04 Mem R(MA/MR): 30918 (21200/36094) [2025-04-29 01:38:36,959 INFO hook.py line 650 1619929] Train: [218/512][200/242] Data 0.015 (0.017) Batch 1.475 (1.390) Remain 27:29:06 loss: 6.1473 Lr: 1.82247e-04 Mem R(MA/MR): 30918 (21200/36094) [2025-04-29 01:39:31,497 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3633 loss_mask: 0.0395 loss_dice: 2.1120 loss_score: 0.0000 loss_bbox: 0.0529 loss_sp_cls: 0.8469 loss: 5.4834 [2025-04-29 01:39:34,093 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:41:03,155 INFO hook.py line 650 1619929] Train: [219/512][50/242] Data 0.016 (0.017) Batch 1.366 (1.384) Remain 27:20:28 loss: 5.7269 Lr: 1.82035e-04 Mem R(MA/MR): 24254 (21200/36094) [2025-04-29 01:42:15,838 INFO hook.py line 650 1619929] Train: [219/512][100/242] Data 0.015 (0.017) Batch 1.418 (1.420) Remain 28:01:35 loss: 5.2924 Lr: 1.81920e-04 Mem R(MA/MR): 25844 (21200/36094) [2025-04-29 01:43:25,215 INFO hook.py line 650 1619929] Train: [219/512][150/242] Data 0.016 (0.017) Batch 1.235 (1.409) Remain 27:47:18 loss: 4.1495 Lr: 1.81805e-04 Mem R(MA/MR): 28140 (21200/36094) [2025-04-29 01:44:33,948 INFO hook.py line 650 1619929] Train: [219/512][200/242] Data 0.015 (0.017) Batch 1.320 (1.400) Remain 27:35:49 loss: 5.1213 Lr: 1.81690e-04 Mem R(MA/MR): 28140 (21200/36094) [2025-04-29 01:45:29,574 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3667 loss_mask: 0.0383 loss_dice: 2.1363 loss_score: 0.0000 loss_bbox: 0.0520 loss_sp_cls: 0.8481 loss: 5.5233 [2025-04-29 01:45:33,597 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:47:03,108 INFO hook.py line 650 1619929] Train: [220/512][50/242] Data 0.016 (0.016) Batch 1.470 (1.441) Remain 28:21:42 loss: 6.4721 Lr: 1.81478e-04 Mem R(MA/MR): 19880 (21200/36094) [2025-04-29 01:48:13,256 INFO hook.py line 650 1619929] Train: [220/512][100/242] Data 0.016 (0.016) Batch 1.407 (1.421) Remain 27:57:24 loss: 5.2680 Lr: 1.81363e-04 Mem R(MA/MR): 24670 (21200/36094) [2025-04-29 01:49:21,930 INFO hook.py line 650 1619929] Train: [220/512][150/242] Data 0.017 (0.017) Batch 1.494 (1.405) Remain 27:36:58 loss: 5.1572 Lr: 1.81247e-04 Mem R(MA/MR): 26754 (21200/36094) [2025-04-29 01:50:31,760 INFO hook.py line 650 1619929] Train: [220/512][200/242] Data 0.018 (0.017) Batch 1.523 (1.403) Remain 27:33:17 loss: 4.6913 Lr: 1.81132e-04 Mem R(MA/MR): 26754 (21200/36094) [2025-04-29 01:51:26,860 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3627 loss_mask: 0.0394 loss_dice: 2.1223 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8516 loss: 5.4911 [2025-04-29 01:51:27,930 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:52:51,070 INFO hook.py line 650 1619929] Train: [221/512][50/242] Data 0.015 (0.016) Batch 1.450 (1.423) Remain 27:54:35 loss: 5.6238 Lr: 1.80920e-04 Mem R(MA/MR): 21552 (21200/36094) [2025-04-29 01:54:01,326 INFO hook.py line 650 1619929] Train: [221/512][100/242] Data 0.016 (0.017) Batch 1.336 (1.414) Remain 27:42:37 loss: 4.1049 Lr: 1.80805e-04 Mem R(MA/MR): 21552 (21200/36094) [2025-04-29 01:55:12,057 INFO hook.py line 650 1619929] Train: [221/512][150/242] Data 0.016 (0.017) Batch 1.365 (1.414) Remain 27:41:47 loss: 5.5621 Lr: 1.80692e-04 Mem R(MA/MR): 21552 (21200/36094) [2025-04-29 01:56:19,768 INFO hook.py line 650 1619929] Train: [221/512][200/242] Data 0.015 (0.016) Batch 1.256 (1.399) Remain 27:22:48 loss: 4.9886 Lr: 1.80577e-04 Mem R(MA/MR): 21552 (21200/36094) [2025-04-29 01:57:15,657 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3605 loss_mask: 0.0379 loss_dice: 2.0926 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8390 loss: 5.4330 [2025-04-29 01:57:15,746 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 01:58:45,220 INFO hook.py line 650 1619929] Train: [222/512][50/242] Data 0.015 (0.016) Batch 1.335 (1.409) Remain 27:32:02 loss: 5.2173 Lr: 1.80365e-04 Mem R(MA/MR): 21892 (21200/36094) [2025-04-29 01:59:54,602 INFO hook.py line 650 1619929] Train: [222/512][100/242] Data 0.016 (0.017) Batch 1.344 (1.398) Remain 27:18:13 loss: 4.6999 Lr: 1.80249e-04 Mem R(MA/MR): 21892 (21200/36094) [2025-04-29 02:01:03,721 INFO hook.py line 650 1619929] Train: [222/512][150/242] Data 0.016 (0.017) Batch 1.447 (1.393) Remain 27:10:55 loss: 5.3377 Lr: 1.80134e-04 Mem R(MA/MR): 21902 (21200/36094) [2025-04-29 02:02:12,353 INFO hook.py line 650 1619929] Train: [222/512][200/242] Data 0.015 (0.017) Batch 1.404 (1.387) Remain 27:03:52 loss: 5.2945 Lr: 1.80019e-04 Mem R(MA/MR): 21902 (21200/36094) [2025-04-29 02:03:07,270 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3709 loss_mask: 0.0391 loss_dice: 2.1417 loss_score: 0.0000 loss_bbox: 0.0528 loss_sp_cls: 0.8572 loss: 5.5562 [2025-04-29 02:03:08,465 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:04:38,208 INFO hook.py line 650 1619929] Train: [223/512][50/242] Data 0.017 (0.018) Batch 1.457 (1.420) Remain 27:39:51 loss: 6.8569 Lr: 1.79806e-04 Mem R(MA/MR): 18622 (21200/36094) [2025-04-29 02:05:47,744 INFO hook.py line 650 1619929] Train: [223/512][100/242] Data 0.014 (0.017) Batch 1.533 (1.405) Remain 27:21:00 loss: 5.3268 Lr: 1.79691e-04 Mem R(MA/MR): 23012 (21200/36094) [2025-04-29 02:06:56,265 INFO hook.py line 650 1619929] Train: [223/512][150/242] Data 0.015 (0.016) Batch 1.237 (1.393) Remain 27:06:06 loss: 4.8289 Lr: 1.79576e-04 Mem R(MA/MR): 23012 (21200/36094) [2025-04-29 02:08:04,356 INFO hook.py line 650 1619929] Train: [223/512][200/242] Data 0.016 (0.016) Batch 1.392 (1.385) Remain 26:55:39 loss: 5.4457 Lr: 1.79460e-04 Mem R(MA/MR): 23012 (21200/36094) [2025-04-29 02:08:59,660 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3668 loss_mask: 0.0389 loss_dice: 2.1209 loss_score: 0.0000 loss_bbox: 0.0531 loss_sp_cls: 0.8470 loss: 5.5091 [2025-04-29 02:09:01,410 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:10:27,449 INFO hook.py line 650 1619929] Train: [224/512][50/242] Data 0.015 (0.017) Batch 1.354 (1.467) Remain 28:28:42 loss: 4.5552 Lr: 1.79248e-04 Mem R(MA/MR): 20030 (21200/36094) [2025-04-29 02:11:37,131 INFO hook.py line 650 1619929] Train: [224/512][100/242] Data 0.017 (0.017) Batch 1.348 (1.429) Remain 27:43:29 loss: 5.4024 Lr: 1.79133e-04 Mem R(MA/MR): 22402 (21200/36094) [2025-04-29 02:12:47,673 INFO hook.py line 650 1619929] Train: [224/512][150/242] Data 0.016 (0.017) Batch 1.338 (1.423) Remain 27:35:04 loss: 5.8007 Lr: 1.79017e-04 Mem R(MA/MR): 22402 (21200/36094) [2025-04-29 02:13:56,338 INFO hook.py line 650 1619929] Train: [224/512][200/242] Data 0.014 (0.017) Batch 1.339 (1.410) Remain 27:19:14 loss: 4.7359 Lr: 1.78902e-04 Mem R(MA/MR): 22402 (21200/36094) [2025-04-29 02:14:50,711 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3698 loss_mask: 0.0392 loss_dice: 2.1330 loss_score: 0.0000 loss_bbox: 0.0526 loss_sp_cls: 0.8477 loss: 5.5362 [2025-04-29 02:14:52,123 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 02:14:54,383 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.6720 Process Time: 0.239 Mem R(MA/MR): 4260 (21200/36094) [2025-04-29 02:14:55,946 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1346 Process Time: 0.507 Mem R(MA/MR): 7272 (21200/36094) [2025-04-29 02:14:57,783 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3991 Process Time: 0.684 Mem R(MA/MR): 9640 (21200/36094) [2025-04-29 02:15:06,280 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3105 Process Time: 1.319 Mem R(MA/MR): 19964 (21200/36094) [2025-04-29 02:15:07,167 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5453 Process Time: 0.241 Mem R(MA/MR): 7010 (21200/36094) [2025-04-29 02:15:08,611 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.1487 Process Time: 0.288 Mem R(MA/MR): 11498 (21200/36094) [2025-04-29 02:15:09,227 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8251 Process Time: 0.186 Mem R(MA/MR): 6622 (21200/36094) [2025-04-29 02:15:09,760 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.1182 Process Time: 0.148 Mem R(MA/MR): 4262 (21200/36094) [2025-04-29 02:15:10,699 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.1919 Process Time: 0.268 Mem R(MA/MR): 11294 (21200/36094) [2025-04-29 02:15:12,183 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6642 Process Time: 0.265 Mem R(MA/MR): 9454 (21200/36094) [2025-04-29 02:15:14,914 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2632 Process Time: 0.590 Mem R(MA/MR): 18700 (21200/36094) [2025-04-29 02:15:17,575 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2766 Process Time: 0.481 Mem R(MA/MR): 15738 (21200/36094) [2025-04-29 02:15:18,806 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2697 Process Time: 0.347 Mem R(MA/MR): 8802 (21200/36094) [2025-04-29 02:15:19,193 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.8416 Process Time: 0.132 Mem R(MA/MR): 4926 (21200/36094) [2025-04-29 02:15:21,926 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.7711 Process Time: 0.443 Mem R(MA/MR): 16928 (21200/36094) [2025-04-29 02:15:23,769 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.5780 Process Time: 0.536 Mem R(MA/MR): 14778 (21200/36094) [2025-04-29 02:15:24,544 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.9825 Process Time: 0.244 Mem R(MA/MR): 6978 (21200/36094) [2025-04-29 02:15:25,487 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.8243 Process Time: 0.288 Mem R(MA/MR): 8300 (21200/36094) [2025-04-29 02:15:26,637 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9812 Process Time: 0.188 Mem R(MA/MR): 6470 (21200/36094) [2025-04-29 02:15:28,138 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.8993 Process Time: 0.348 Mem R(MA/MR): 11480 (21200/36094) [2025-04-29 02:15:35,850 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8935 Process Time: 0.532 Mem R(MA/MR): 23292 (21200/36094) [2025-04-29 02:15:36,455 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3498 Process Time: 0.171 Mem R(MA/MR): 7154 (21200/36094) [2025-04-29 02:15:44,588 INFO hook.py line 449 1619929] Test: [23/50] Loss 14.7614 Process Time: 0.369 Mem R(MA/MR): 8622 (21200/36094) [2025-04-29 02:15:45,172 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7395 Process Time: 0.171 Mem R(MA/MR): 5580 (21200/36094) [2025-04-29 02:15:46,097 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1639 Process Time: 0.210 Mem R(MA/MR): 8796 (21200/36094) [2025-04-29 02:15:53,107 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.7897 Process Time: 1.420 Mem R(MA/MR): 31200 (21200/36094) [2025-04-29 02:15:55,466 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.2068 Process Time: 0.684 Mem R(MA/MR): 10314 (21200/36094) [2025-04-29 02:15:56,727 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.2828 Process Time: 0.411 Mem R(MA/MR): 8932 (21200/36094) [2025-04-29 02:16:01,241 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.7412 Process Time: 0.409 Mem R(MA/MR): 17452 (21200/36094) [2025-04-29 02:16:02,538 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3448 Process Time: 0.442 Mem R(MA/MR): 7946 (21200/36094) [2025-04-29 02:16:06,128 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5382 Process Time: 0.520 Mem R(MA/MR): 20582 (21200/36094) [2025-04-29 02:16:06,407 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1121 Process Time: 0.105 Mem R(MA/MR): 4038 (21200/36094) [2025-04-29 02:16:10,428 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.8074 Process Time: 0.595 Mem R(MA/MR): 24508 (21200/36094) [2025-04-29 02:16:11,535 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6313 Process Time: 0.294 Mem R(MA/MR): 9598 (21200/36094) [2025-04-29 02:16:13,086 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.2325 Process Time: 0.319 Mem R(MA/MR): 14424 (21200/36094) [2025-04-29 02:16:13,646 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.4240 Process Time: 0.194 Mem R(MA/MR): 6884 (21200/36094) [2025-04-29 02:16:16,965 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8666 Process Time: 0.564 Mem R(MA/MR): 27762 (21200/36094) [2025-04-29 02:16:18,251 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1417 Process Time: 0.261 Mem R(MA/MR): 10672 (21200/36094) [2025-04-29 02:16:18,787 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1271 Process Time: 0.170 Mem R(MA/MR): 5662 (21200/36094) [2025-04-29 02:16:19,882 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9968 Process Time: 0.353 Mem R(MA/MR): 10288 (21200/36094) [2025-04-29 02:16:20,980 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.8569 Process Time: 0.337 Mem R(MA/MR): 8866 (21200/36094) [2025-04-29 02:16:21,444 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9257 Process Time: 0.131 Mem R(MA/MR): 5704 (21200/36094) [2025-04-29 02:16:21,905 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.0999 Process Time: 0.154 Mem R(MA/MR): 5762 (21200/36094) [2025-04-29 02:16:22,429 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.0943 Process Time: 0.169 Mem R(MA/MR): 7326 (21200/36094) [2025-04-29 02:16:22,931 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6905 Process Time: 0.123 Mem R(MA/MR): 5516 (21200/36094) [2025-04-29 02:16:25,372 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8084 Process Time: 0.542 Mem R(MA/MR): 15052 (21200/36094) [2025-04-29 02:16:31,639 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.1221 Process Time: 0.318 Mem R(MA/MR): 20426 (21200/36094) [2025-04-29 02:16:40,950 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.8167 Process Time: 0.999 Mem R(MA/MR): 34862 (21200/36094) [2025-04-29 02:16:41,749 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9426 Process Time: 0.326 Mem R(MA/MR): 6026 (21200/36094) [2025-04-29 02:16:44,394 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.4518 Process Time: 0.689 Mem R(MA/MR): 14004 (21200/36094) [2025-04-29 02:16:48,403 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 02:16:48,404 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 02:16:48,404 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] table : 0.251 0.558 0.770 0.757 0.618 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] door : 0.454 0.762 0.916 0.887 0.797 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] ceiling lamp : 0.559 0.751 0.861 0.840 0.751 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] cabinet : 0.316 0.415 0.513 0.569 0.433 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] blinds : 0.640 0.827 0.867 0.800 0.870 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] curtain : 0.294 0.463 0.585 0.391 0.750 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] chair : 0.560 0.730 0.779 0.628 0.783 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] storage cabinet: 0.237 0.364 0.522 0.464 0.520 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] office chair : 0.490 0.536 0.550 0.720 0.750 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] bookshelf : 0.277 0.575 0.657 0.562 0.818 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] whiteboard : 0.577 0.757 0.758 0.962 0.714 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] window : 0.101 0.242 0.553 0.385 0.385 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] box : 0.198 0.354 0.524 0.490 0.414 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] monitor : 0.592 0.729 0.807 0.911 0.729 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] shelf : 0.085 0.226 0.390 0.409 0.300 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] heater : 0.452 0.752 0.866 0.906 0.763 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] kitchen cabinet: 0.164 0.448 0.676 0.667 0.560 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] sofa : 0.448 0.636 0.898 0.800 0.667 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] bed : 0.145 0.419 1.000 0.600 0.750 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] trash can : 0.503 0.683 0.734 0.806 0.769 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] book : 0.010 0.020 0.073 0.233 0.075 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] plant : 0.376 0.527 0.710 0.733 0.611 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] blanket : 0.425 0.659 0.659 0.875 0.636 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] tv : 0.798 0.833 0.833 1.000 0.833 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] computer tower : 0.248 0.409 0.647 0.679 0.452 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] refrigerator : 0.238 0.422 0.511 0.417 0.556 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] jacket : 0.148 0.367 0.489 0.545 0.545 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] sink : 0.400 0.702 0.899 0.889 0.727 [2025-04-29 02:16:48,404 INFO hook.py line 395 1619929] bag : 0.054 0.102 0.134 0.333 0.333 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] picture : 0.153 0.357 0.424 0.654 0.436 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] pillow : 0.575 0.766 0.810 0.789 0.789 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] towel : 0.154 0.264 0.432 0.444 0.316 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] suitcase : 0.226 0.245 0.301 0.333 0.429 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] backpack : 0.451 0.626 0.690 0.778 0.538 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] crate : 0.124 0.435 0.643 0.571 0.727 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] keyboard : 0.437 0.631 0.736 0.722 0.667 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] toilet : 0.854 0.889 1.000 1.000 0.889 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] printer : 0.179 0.226 0.404 0.500 0.333 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] poster : 0.001 0.002 0.003 0.043 0.111 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] microwave : 0.371 0.558 0.875 0.714 0.625 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] shoes : 0.122 0.218 0.528 0.583 0.341 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] socket : 0.201 0.475 0.658 0.634 0.507 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] bottle : 0.142 0.239 0.361 0.458 0.325 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] bucket : 0.008 0.014 0.018 0.200 0.143 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] cushion : 0.014 0.035 0.252 0.182 0.333 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] basket : 0.025 0.036 0.036 0.500 0.143 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] telephone : 0.255 0.476 0.529 0.889 0.471 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] laptop : 0.332 0.475 0.480 1.000 0.375 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] plant pot : 0.262 0.618 0.618 1.000 0.562 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] exhaust fan : 0.188 0.361 0.404 0.667 0.400 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] cup : 0.233 0.378 0.427 1.000 0.341 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] coat hanger : 0.150 0.677 0.677 0.750 0.750 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] light switch : 0.220 0.437 0.600 0.829 0.446 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] speaker : 0.310 0.419 0.419 0.600 0.545 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] smoke detector : 0.700 0.844 0.849 1.000 0.708 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] power strip : 0.075 0.114 0.149 1.000 0.100 [2025-04-29 02:16:48,405 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] paper bag : 0.074 0.083 0.100 0.167 1.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] mouse : 0.430 0.617 0.671 0.900 0.562 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] cutting board : 0.285 0.500 0.500 1.000 0.500 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] toilet paper : 0.226 0.436 0.492 0.667 0.471 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] paper towel : 0.003 0.008 0.045 0.125 0.125 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] pot : 0.204 0.250 0.250 0.500 1.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] clock : 0.593 1.000 1.000 1.000 1.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 1.000 0.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] tap : 0.173 0.255 0.572 0.750 0.333 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] soap dispenser : 0.409 0.520 0.668 1.000 0.400 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] bowl : 0.056 0.056 0.164 0.333 0.333 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] whiteboard eraser: 0.270 0.626 0.626 0.714 0.833 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] toilet brush : 0.462 0.629 0.803 0.800 0.667 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] spray bottle : 0.018 0.025 0.025 0.200 0.250 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] stapler : 0.003 0.028 0.139 0.167 0.333 [2025-04-29 02:16:48,406 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 02:16:48,406 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 02:16:48,406 INFO hook.py line 404 1619929] average : 0.255 0.400 0.491 0.615 0.485 [2025-04-29 02:16:48,406 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 02:16:48,406 INFO hook.py line 480 1619929] Total Process Time: 19.727 s [2025-04-29 02:16:48,407 INFO hook.py line 481 1619929] Average Process Time: 397.705 ms [2025-04-29 02:16:48,407 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 02:16:48,450 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 02:16:48,454 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:18:19,441 INFO hook.py line 650 1619929] Train: [225/512][50/242] Data 0.017 (0.016) Batch 1.251 (1.422) Remain 27:31:06 loss: 6.2320 Lr: 1.78690e-04 Mem R(MA/MR): 24096 (21200/36094) [2025-04-29 02:19:28,610 INFO hook.py line 650 1619929] Train: [225/512][100/242] Data 0.016 (0.017) Batch 1.485 (1.402) Remain 27:06:33 loss: 4.9617 Lr: 1.78574e-04 Mem R(MA/MR): 24100 (21200/36094) [2025-04-29 02:20:36,612 INFO hook.py line 650 1619929] Train: [225/512][150/242] Data 0.015 (0.017) Batch 1.416 (1.388) Remain 26:48:43 loss: 6.1730 Lr: 1.78459e-04 Mem R(MA/MR): 26672 (21200/36094) [2025-04-29 02:21:46,653 INFO hook.py line 650 1619929] Train: [225/512][200/242] Data 0.014 (0.020) Batch 1.356 (1.391) Remain 26:51:22 loss: 5.4484 Lr: 1.78343e-04 Mem R(MA/MR): 26696 (21200/36094) [2025-04-29 02:22:41,941 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3701 loss_mask: 0.0388 loss_dice: 2.1475 loss_score: 0.0000 loss_bbox: 0.0524 loss_sp_cls: 0.8531 loss: 5.5580 [2025-04-29 02:22:45,412 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:24:17,846 INFO hook.py line 650 1619929] Train: [226/512][50/242] Data 0.017 (0.017) Batch 1.360 (1.419) Remain 27:21:22 loss: 5.5661 Lr: 1.78131e-04 Mem R(MA/MR): 19678 (21200/36094) [2025-04-29 02:25:26,317 INFO hook.py line 650 1619929] Train: [226/512][100/242] Data 0.017 (0.017) Batch 1.373 (1.393) Remain 26:50:39 loss: 5.7261 Lr: 1.78015e-04 Mem R(MA/MR): 22458 (21200/36094) [2025-04-29 02:26:35,085 INFO hook.py line 650 1619929] Train: [226/512][150/242] Data 0.015 (0.017) Batch 1.429 (1.387) Remain 26:42:24 loss: 6.5138 Lr: 1.77902e-04 Mem R(MA/MR): 24100 (21200/36094) [2025-04-29 02:27:42,968 INFO hook.py line 650 1619929] Train: [226/512][200/242] Data 0.016 (0.017) Batch 1.350 (1.380) Remain 26:32:34 loss: 6.3182 Lr: 1.77787e-04 Mem R(MA/MR): 24118 (21200/36094) [2025-04-29 02:28:37,290 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3810 loss_mask: 0.0406 loss_dice: 2.1718 loss_score: 0.0000 loss_bbox: 0.0537 loss_sp_cls: 0.8663 loss: 5.6413 [2025-04-29 02:28:40,798 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:30:12,249 INFO hook.py line 650 1619929] Train: [227/512][50/242] Data 0.014 (0.016) Batch 1.365 (1.372) Remain 26:21:21 loss: 6.2025 Lr: 1.77574e-04 Mem R(MA/MR): 22366 (21200/36094) [2025-04-29 02:31:21,699 INFO hook.py line 650 1619929] Train: [227/512][100/242] Data 0.015 (0.016) Batch 1.313 (1.381) Remain 26:30:23 loss: 5.6656 Lr: 1.77459e-04 Mem R(MA/MR): 22380 (21200/36094) [2025-04-29 02:32:28,686 INFO hook.py line 650 1619929] Train: [227/512][150/242] Data 0.017 (0.016) Batch 1.315 (1.367) Remain 26:13:11 loss: 4.7958 Lr: 1.77343e-04 Mem R(MA/MR): 24314 (21200/36094) [2025-04-29 02:33:34,956 INFO hook.py line 650 1619929] Train: [227/512][200/242] Data 0.014 (0.016) Batch 1.242 (1.356) Remain 25:59:59 loss: 5.8660 Lr: 1.77228e-04 Mem R(MA/MR): 24314 (21200/36094) [2025-04-29 02:34:30,106 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4085 loss_mask: 0.0431 loss_dice: 2.2429 loss_score: 0.0000 loss_bbox: 0.0549 loss_sp_cls: 0.8981 loss: 5.8504 [2025-04-29 02:34:34,431 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:36:05,997 INFO hook.py line 650 1619929] Train: [228/512][50/242] Data 0.015 (0.016) Batch 1.507 (1.399) Remain 26:46:26 loss: 5.8633 Lr: 1.77015e-04 Mem R(MA/MR): 23510 (21200/36094) [2025-04-29 02:37:13,723 INFO hook.py line 650 1619929] Train: [228/512][100/242] Data 0.016 (0.017) Batch 1.548 (1.376) Remain 26:19:14 loss: 5.8819 Lr: 1.76900e-04 Mem R(MA/MR): 27140 (21200/36094) [2025-04-29 02:38:21,583 INFO hook.py line 650 1619929] Train: [228/512][150/242] Data 0.017 (0.017) Batch 1.336 (1.369) Remain 26:10:48 loss: 5.9442 Lr: 1.76784e-04 Mem R(MA/MR): 27140 (21200/36094) [2025-04-29 02:39:28,475 INFO hook.py line 650 1619929] Train: [228/512][200/242] Data 0.015 (0.016) Batch 1.305 (1.361) Remain 26:00:28 loss: 6.2311 Lr: 1.76669e-04 Mem R(MA/MR): 29074 (21200/36094) [2025-04-29 02:40:23,218 INFO misc.py line 135 1619929] Train result: loss_cls: 0.4021 loss_mask: 0.0425 loss_dice: 2.2391 loss_score: 0.0000 loss_bbox: 0.0554 loss_sp_cls: 0.8921 loss: 5.8251 [2025-04-29 02:40:24,256 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:42:00,021 INFO hook.py line 650 1619929] Train: [229/512][50/242] Data 0.017 (0.020) Batch 1.523 (1.554) Remain 29:39:06 loss: 5.3369 Lr: 1.76456e-04 Mem R(MA/MR): 19544 (21200/36094) [2025-04-29 02:43:12,638 INFO hook.py line 650 1619929] Train: [229/512][100/242] Data 0.015 (0.018) Batch 1.354 (1.502) Remain 28:37:42 loss: 6.2214 Lr: 1.76340e-04 Mem R(MA/MR): 21764 (21200/36094) [2025-04-29 02:44:23,760 INFO hook.py line 650 1619929] Train: [229/512][150/242] Data 0.016 (0.017) Batch 1.446 (1.475) Remain 28:05:37 loss: 5.2480 Lr: 1.76225e-04 Mem R(MA/MR): 21780 (21200/36094) [2025-04-29 02:45:32,193 INFO hook.py line 650 1619929] Train: [229/512][200/242] Data 0.015 (0.017) Batch 1.318 (1.448) Remain 27:33:38 loss: 5.8507 Lr: 1.76109e-04 Mem R(MA/MR): 21780 (21200/36094) [2025-04-29 02:46:30,984 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3921 loss_mask: 0.0411 loss_dice: 2.2159 loss_score: 0.0000 loss_bbox: 0.0545 loss_sp_cls: 0.8774 loss: 5.7539 [2025-04-29 02:46:35,041 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:48:08,595 INFO hook.py line 650 1619929] Train: [230/512][50/242] Data 0.016 (0.016) Batch 1.441 (1.443) Remain 27:26:19 loss: 5.4419 Lr: 1.75897e-04 Mem R(MA/MR): 21016 (21200/36094) [2025-04-29 02:49:21,497 INFO hook.py line 650 1619929] Train: [230/512][100/242] Data 0.015 (0.016) Batch 1.413 (1.451) Remain 27:33:44 loss: 5.3360 Lr: 1.75781e-04 Mem R(MA/MR): 22534 (21200/36094) [2025-04-29 02:50:33,435 INFO hook.py line 650 1619929] Train: [230/512][150/242] Data 0.016 (0.016) Batch 1.286 (1.447) Remain 27:27:48 loss: 6.3681 Lr: 1.75665e-04 Mem R(MA/MR): 25928 (21200/36094) [2025-04-29 02:51:43,974 INFO hook.py line 650 1619929] Train: [230/512][200/242] Data 0.014 (0.016) Batch 1.218 (1.438) Remain 27:16:12 loss: 5.1661 Lr: 1.75550e-04 Mem R(MA/MR): 25928 (21200/36094) [2025-04-29 02:52:40,220 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3894 loss_mask: 0.0415 loss_dice: 2.1934 loss_score: 0.0000 loss_bbox: 0.0544 loss_sp_cls: 0.8769 loss: 5.7112 [2025-04-29 02:52:41,241 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 02:54:20,181 INFO hook.py line 650 1619929] Train: [231/512][50/242] Data 0.016 (0.016) Batch 1.340 (1.503) Remain 28:28:08 loss: 5.3187 Lr: 1.75337e-04 Mem R(MA/MR): 25354 (21200/36094) [2025-04-29 02:55:31,618 INFO hook.py line 650 1619929] Train: [231/512][100/242] Data 0.017 (0.016) Batch 1.553 (1.465) Remain 27:43:28 loss: 7.0573 Lr: 1.75221e-04 Mem R(MA/MR): 25354 (21200/36094) [2025-04-29 02:56:40,875 INFO hook.py line 650 1619929] Train: [231/512][150/242] Data 0.018 (0.016) Batch 1.412 (1.438) Remain 27:11:32 loss: 6.1429 Lr: 1.75106e-04 Mem R(MA/MR): 25354 (21200/36094) [2025-04-29 02:57:52,470 INFO hook.py line 650 1619929] Train: [231/512][200/242] Data 0.015 (0.016) Batch 1.551 (1.436) Remain 27:08:42 loss: 5.0043 Lr: 1.74990e-04 Mem R(MA/MR): 25392 (21200/36094) [2025-04-29 02:58:49,210 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3875 loss_mask: 0.0405 loss_dice: 2.1920 loss_score: 0.0000 loss_bbox: 0.0535 loss_sp_cls: 0.8726 loss: 5.6917 [2025-04-29 02:58:52,225 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:00:25,963 INFO hook.py line 650 1619929] Train: [232/512][50/242] Data 0.016 (0.016) Batch 1.330 (1.480) Remain 27:55:54 loss: 5.8239 Lr: 1.74777e-04 Mem R(MA/MR): 21804 (21200/36094) [2025-04-29 03:01:39,838 INFO hook.py line 650 1619929] Train: [232/512][100/242] Data 0.016 (0.016) Batch 1.489 (1.479) Remain 27:53:19 loss: 4.4708 Lr: 1.74661e-04 Mem R(MA/MR): 21804 (21200/36094) [2025-04-29 03:02:54,302 INFO hook.py line 650 1619929] Train: [232/512][150/242] Data 0.016 (0.017) Batch 1.561 (1.482) Remain 27:56:12 loss: 7.0799 Lr: 1.74546e-04 Mem R(MA/MR): 23858 (21200/36094) [2025-04-29 03:04:06,728 INFO hook.py line 650 1619929] Train: [232/512][200/242] Data 0.014 (0.016) Batch 1.284 (1.474) Remain 27:45:19 loss: 5.8186 Lr: 1.74430e-04 Mem R(MA/MR): 23858 (21200/36094) [2025-04-29 03:05:03,279 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3826 loss_mask: 0.0403 loss_dice: 2.1681 loss_score: 0.0000 loss_bbox: 0.0536 loss_sp_cls: 0.8708 loss: 5.6404 [2025-04-29 03:05:07,046 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 03:05:09,324 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1207 Process Time: 0.212 Mem R(MA/MR): 4468 (21200/36094) [2025-04-29 03:05:11,063 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6306 Process Time: 0.560 Mem R(MA/MR): 7064 (21200/36094) [2025-04-29 03:05:12,775 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4778 Process Time: 0.645 Mem R(MA/MR): 9700 (21200/36094) [2025-04-29 03:05:19,648 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.0104 Process Time: 1.015 Mem R(MA/MR): 19512 (21200/36094) [2025-04-29 03:05:20,592 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.1901 Process Time: 0.335 Mem R(MA/MR): 6714 (21200/36094) [2025-04-29 03:05:22,723 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8685 Process Time: 0.823 Mem R(MA/MR): 11244 (21200/36094) [2025-04-29 03:05:23,733 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0578 Process Time: 0.396 Mem R(MA/MR): 6214 (21200/36094) [2025-04-29 03:05:24,323 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3946 Process Time: 0.171 Mem R(MA/MR): 4538 (21200/36094) [2025-04-29 03:05:25,458 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8997 Process Time: 0.425 Mem R(MA/MR): 11324 (21200/36094) [2025-04-29 03:05:27,257 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7418 Process Time: 0.300 Mem R(MA/MR): 9532 (21200/36094) [2025-04-29 03:05:29,842 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.3486 Process Time: 0.430 Mem R(MA/MR): 18524 (21200/36094) [2025-04-29 03:05:33,168 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.8314 Process Time: 1.008 Mem R(MA/MR): 15092 (21200/36094) [2025-04-29 03:05:34,519 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2188 Process Time: 0.369 Mem R(MA/MR): 8690 (21200/36094) [2025-04-29 03:05:35,006 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1113 Process Time: 0.178 Mem R(MA/MR): 4822 (21200/36094) [2025-04-29 03:05:37,767 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.9774 Process Time: 0.291 Mem R(MA/MR): 16394 (21200/36094) [2025-04-29 03:05:40,405 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3064 Process Time: 0.351 Mem R(MA/MR): 14250 (21200/36094) [2025-04-29 03:05:41,447 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2240 Process Time: 0.308 Mem R(MA/MR): 6530 (21200/36094) [2025-04-29 03:05:42,855 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9662 Process Time: 0.436 Mem R(MA/MR): 8260 (21200/36094) [2025-04-29 03:05:44,867 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.4521 Process Time: 0.272 Mem R(MA/MR): 6254 (21200/36094) [2025-04-29 03:05:46,595 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.3093 Process Time: 0.223 Mem R(MA/MR): 11432 (21200/36094) [2025-04-29 03:05:57,638 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8564 Process Time: 3.376 Mem R(MA/MR): 22736 (21200/36094) [2025-04-29 03:05:58,789 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4586 Process Time: 0.317 Mem R(MA/MR): 6686 (21200/36094) [2025-04-29 03:06:10,665 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.5297 Process Time: 0.579 Mem R(MA/MR): 10052 (21200/36094) [2025-04-29 03:06:11,297 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8021 Process Time: 0.192 Mem R(MA/MR): 5540 (21200/36094) [2025-04-29 03:06:12,246 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9527 Process Time: 0.248 Mem R(MA/MR): 9322 (21200/36094) [2025-04-29 03:06:22,931 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.5561 Process Time: 0.700 Mem R(MA/MR): 30502 (21200/36094) [2025-04-29 03:06:26,634 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.1881 Process Time: 1.174 Mem R(MA/MR): 10136 (21200/36094) [2025-04-29 03:06:28,254 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.4963 Process Time: 0.452 Mem R(MA/MR): 8938 (21200/36094) [2025-04-29 03:06:35,985 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.2393 Process Time: 0.304 Mem R(MA/MR): 16704 (21200/36094) [2025-04-29 03:06:36,910 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.9069 Process Time: 0.259 Mem R(MA/MR): 7530 (21200/36094) [2025-04-29 03:06:47,369 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.9991 Process Time: 0.451 Mem R(MA/MR): 20478 (21200/36094) [2025-04-29 03:06:47,697 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.7121 Process Time: 0.130 Mem R(MA/MR): 3872 (21200/36094) [2025-04-29 03:06:52,839 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.0354 Process Time: 0.492 Mem R(MA/MR): 24746 (21200/36094) [2025-04-29 03:06:54,322 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9010 Process Time: 0.486 Mem R(MA/MR): 9810 (21200/36094) [2025-04-29 03:06:56,196 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.1049 Process Time: 0.318 Mem R(MA/MR): 13914 (21200/36094) [2025-04-29 03:06:56,775 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8635 Process Time: 0.206 Mem R(MA/MR): 6466 (21200/36094) [2025-04-29 03:07:00,261 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.6331 Process Time: 0.645 Mem R(MA/MR): 27702 (21200/36094) [2025-04-29 03:07:01,936 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1833 Process Time: 0.392 Mem R(MA/MR): 10808 (21200/36094) [2025-04-29 03:07:02,549 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.6054 Process Time: 0.264 Mem R(MA/MR): 5612 (21200/36094) [2025-04-29 03:07:03,777 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9635 Process Time: 0.496 Mem R(MA/MR): 10242 (21200/36094) [2025-04-29 03:07:04,654 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0141 Process Time: 0.239 Mem R(MA/MR): 8986 (21200/36094) [2025-04-29 03:07:05,162 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.8078 Process Time: 0.162 Mem R(MA/MR): 5664 (21200/36094) [2025-04-29 03:07:05,618 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7516 Process Time: 0.138 Mem R(MA/MR): 5722 (21200/36094) [2025-04-29 03:07:06,119 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.8895 Process Time: 0.167 Mem R(MA/MR): 6892 (21200/36094) [2025-04-29 03:07:06,755 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.2518 Process Time: 0.196 Mem R(MA/MR): 5462 (21200/36094) [2025-04-29 03:07:09,240 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.3307 Process Time: 0.555 Mem R(MA/MR): 14634 (21200/36094) [2025-04-29 03:07:15,658 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1134 Process Time: 0.875 Mem R(MA/MR): 19770 (21200/36094) [2025-04-29 03:07:26,492 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.3040 Process Time: 2.562 Mem R(MA/MR): 35574 (21200/36094) [2025-04-29 03:07:27,675 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1300 Process Time: 0.291 Mem R(MA/MR): 5766 (21200/36094) [2025-04-29 03:07:29,881 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5400 Process Time: 0.403 Mem R(MA/MR): 13554 (21200/36094) [2025-04-29 03:07:33,734 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 03:07:33,734 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 03:07:33,734 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] table : 0.232 0.513 0.730 0.718 0.544 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] door : 0.452 0.757 0.891 0.924 0.772 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] ceiling lamp : 0.533 0.741 0.848 0.815 0.757 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] cabinet : 0.291 0.396 0.537 0.578 0.388 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] blinds : 0.495 0.792 0.810 0.769 0.870 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] curtain : 0.252 0.393 0.661 0.556 0.417 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] chair : 0.614 0.744 0.800 0.729 0.770 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] storage cabinet: 0.190 0.358 0.525 0.650 0.520 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] office chair : 0.520 0.538 0.552 0.688 0.688 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] bookshelf : 0.436 0.722 0.742 0.875 0.636 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] whiteboard : 0.574 0.761 0.802 0.960 0.686 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] window : 0.072 0.176 0.577 0.431 0.341 [2025-04-29 03:07:33,734 INFO hook.py line 395 1619929] box : 0.197 0.329 0.456 0.528 0.365 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] monitor : 0.586 0.730 0.838 0.959 0.671 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] shelf : 0.056 0.145 0.270 0.471 0.267 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] heater : 0.428 0.749 0.840 0.861 0.816 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] kitchen cabinet: 0.109 0.301 0.640 0.464 0.520 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] sofa : 0.458 0.525 0.881 0.562 0.750 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] bed : 0.175 0.364 0.457 0.625 0.625 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] trash can : 0.564 0.720 0.767 0.775 0.846 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] book : 0.023 0.044 0.075 0.279 0.090 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] plant : 0.483 0.714 0.830 0.929 0.722 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] blanket : 0.360 0.386 0.565 1.000 0.364 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] tv : 0.834 0.974 0.974 0.857 1.000 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] computer tower : 0.202 0.319 0.560 0.474 0.429 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] refrigerator : 0.184 0.399 0.412 0.800 0.444 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] jacket : 0.075 0.197 0.356 0.400 0.545 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] sink : 0.377 0.587 0.818 0.882 0.682 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] bag : 0.091 0.168 0.208 0.571 0.296 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] picture : 0.129 0.363 0.423 0.562 0.462 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] pillow : 0.642 0.843 0.869 0.833 0.789 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] towel : 0.170 0.323 0.449 0.421 0.421 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] suitcase : 0.429 0.477 0.477 0.667 0.571 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] backpack : 0.309 0.418 0.418 0.857 0.462 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] crate : 0.064 0.304 0.457 0.667 0.364 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] keyboard : 0.422 0.595 0.710 0.641 0.641 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] toilet : 0.821 0.861 1.000 0.889 0.889 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] printer : 0.218 0.354 0.354 0.667 0.444 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] poster : 0.001 0.005 0.006 0.043 0.222 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] painting : 0.100 0.100 0.100 0.200 1.000 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] microwave : 0.365 0.750 0.875 1.000 0.750 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] shoes : 0.108 0.211 0.481 0.560 0.341 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] socket : 0.182 0.431 0.677 0.687 0.486 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] bottle : 0.080 0.171 0.351 0.312 0.289 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] bucket : 0.222 0.329 0.332 0.500 0.286 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] cushion : 0.021 0.054 0.196 0.286 0.333 [2025-04-29 03:07:33,735 INFO hook.py line 395 1619929] basket : 0.010 0.014 0.047 0.200 0.143 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] shoe rack : 0.021 0.062 1.000 0.250 0.500 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] telephone : 0.336 0.584 0.612 0.769 0.588 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] laptop : 0.377 0.587 0.605 0.625 0.625 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] plant pot : 0.149 0.268 0.264 0.500 0.312 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] exhaust fan : 0.132 0.256 0.306 0.625 0.333 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] cup : 0.240 0.428 0.480 0.783 0.409 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] coat hanger : 0.084 0.500 0.677 1.000 0.500 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] light switch : 0.248 0.519 0.612 0.886 0.477 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] speaker : 0.298 0.452 0.607 0.667 0.545 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] kettle : 0.148 0.167 0.167 1.000 0.167 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] smoke detector : 0.622 0.817 0.825 0.947 0.750 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] power strip : 0.165 0.229 0.245 1.000 0.200 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] paper bag : 0.071 0.071 0.083 0.143 1.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] mouse : 0.467 0.630 0.739 0.913 0.656 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] cutting board : 0.054 0.396 0.396 0.667 0.500 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] toilet paper : 0.295 0.412 0.412 1.000 0.412 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] clock : 0.376 0.638 0.638 0.667 0.667 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] tap : 0.101 0.157 0.629 0.500 0.222 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] soap dispenser : 0.243 0.342 0.466 0.667 0.400 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.042 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] whiteboard eraser: 0.235 0.590 0.599 0.800 0.667 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] toilet brush : 0.595 0.782 0.955 1.000 0.667 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] headphones : 0.388 0.708 0.792 0.500 1.000 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] stapler : 0.002 0.019 0.137 0.111 0.333 [2025-04-29 03:07:33,736 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:07:33,737 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 03:07:33,737 INFO hook.py line 404 1619929] average : 0.247 0.381 0.485 0.575 0.465 [2025-04-29 03:07:33,737 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 03:07:33,737 INFO hook.py line 480 1619929] Total Process Time: 25.816 s [2025-04-29 03:07:33,737 INFO hook.py line 481 1619929] Average Process Time: 522.531 ms [2025-04-29 03:07:33,737 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 03:07:33,916 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 03:07:33,921 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:09:05,592 INFO hook.py line 650 1619929] Train: [233/512][50/242] Data 0.017 (0.017) Batch 1.503 (1.454) Remain 27:21:16 loss: 5.9122 Lr: 1.74217e-04 Mem R(MA/MR): 18462 (21200/36094) [2025-04-29 03:10:18,779 INFO hook.py line 650 1619929] Train: [233/512][100/242] Data 0.016 (0.027) Batch 1.663 (1.459) Remain 27:25:31 loss: 7.1086 Lr: 1.74101e-04 Mem R(MA/MR): 22184 (21200/36094) [2025-04-29 03:11:30,287 INFO hook.py line 650 1619929] Train: [233/512][150/242] Data 0.015 (0.023) Batch 1.367 (1.449) Remain 27:13:09 loss: 4.8394 Lr: 1.73985e-04 Mem R(MA/MR): 22186 (21200/36094) [2025-04-29 03:12:42,303 INFO hook.py line 650 1619929] Train: [233/512][200/242] Data 0.014 (0.022) Batch 1.304 (1.447) Remain 27:09:23 loss: 4.3294 Lr: 1.73870e-04 Mem R(MA/MR): 22186 (21200/36094) [2025-04-29 03:13:40,140 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3756 loss_mask: 0.0404 loss_dice: 2.1661 loss_score: 0.0000 loss_bbox: 0.0539 loss_sp_cls: 0.8668 loss: 5.6145 [2025-04-29 03:13:43,322 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:15:19,061 INFO hook.py line 650 1619929] Train: [234/512][50/242] Data 0.016 (0.016) Batch 1.562 (1.488) Remain 27:53:15 loss: 5.7725 Lr: 1.73657e-04 Mem R(MA/MR): 19924 (21200/36094) [2025-04-29 03:16:33,459 INFO hook.py line 650 1619929] Train: [234/512][100/242] Data 0.016 (0.016) Batch 1.470 (1.488) Remain 27:51:58 loss: 5.0326 Lr: 1.73541e-04 Mem R(MA/MR): 19940 (21200/36094) [2025-04-29 03:17:45,140 INFO hook.py line 650 1619929] Train: [234/512][150/242] Data 0.016 (0.016) Batch 1.501 (1.470) Remain 27:29:58 loss: 6.3414 Lr: 1.73425e-04 Mem R(MA/MR): 19940 (21200/36094) [2025-04-29 03:18:58,369 INFO hook.py line 650 1619929] Train: [234/512][200/242] Data 0.016 (0.016) Batch 1.390 (1.468) Remain 27:27:20 loss: 4.6078 Lr: 1.73309e-04 Mem R(MA/MR): 20700 (21200/36094) [2025-04-29 03:19:55,783 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3741 loss_mask: 0.0398 loss_dice: 2.1454 loss_score: 0.0000 loss_bbox: 0.0532 loss_sp_cls: 0.8635 loss: 5.5784 [2025-04-29 03:19:55,849 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:21:32,227 INFO hook.py line 650 1619929] Train: [235/512][50/242] Data 0.015 (0.017) Batch 1.386 (1.475) Remain 27:33:05 loss: 6.8325 Lr: 1.73096e-04 Mem R(MA/MR): 18520 (21200/36094) [2025-04-29 03:22:44,563 INFO hook.py line 650 1619929] Train: [235/512][100/242] Data 0.016 (0.017) Batch 1.421 (1.461) Remain 27:15:17 loss: 4.8643 Lr: 1.72980e-04 Mem R(MA/MR): 20292 (21200/36094) [2025-04-29 03:23:56,661 INFO hook.py line 650 1619929] Train: [235/512][150/242] Data 0.017 (0.016) Batch 1.488 (1.454) Remain 27:06:58 loss: 5.9863 Lr: 1.72865e-04 Mem R(MA/MR): 22122 (21200/36094) [2025-04-29 03:25:09,931 INFO hook.py line 650 1619929] Train: [235/512][200/242] Data 0.015 (0.016) Batch 1.301 (1.457) Remain 27:08:56 loss: 6.1287 Lr: 1.72749e-04 Mem R(MA/MR): 22124 (21200/36094) [2025-04-29 03:26:08,160 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3517 loss_mask: 0.0379 loss_dice: 2.0824 loss_score: 0.0000 loss_bbox: 0.0519 loss_sp_cls: 0.8403 loss: 5.3990 [2025-04-29 03:26:10,155 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:27:48,969 INFO hook.py line 650 1619929] Train: [236/512][50/242] Data 0.017 (0.017) Batch 1.577 (1.522) Remain 28:18:43 loss: 5.9524 Lr: 1.72536e-04 Mem R(MA/MR): 20412 (21200/36094) [2025-04-29 03:29:01,308 INFO hook.py line 650 1619929] Train: [236/512][100/242] Data 0.016 (0.017) Batch 1.310 (1.483) Remain 27:34:26 loss: 4.4073 Lr: 1.72420e-04 Mem R(MA/MR): 20418 (21200/36094) [2025-04-29 03:30:12,531 INFO hook.py line 650 1619929] Train: [236/512][150/242] Data 0.015 (0.017) Batch 1.380 (1.463) Remain 27:10:59 loss: 5.1977 Lr: 1.72304e-04 Mem R(MA/MR): 20418 (21200/36094) [2025-04-29 03:31:22,861 INFO hook.py line 650 1619929] Train: [236/512][200/242] Data 0.014 (0.017) Batch 1.219 (1.449) Remain 26:53:48 loss: 5.4396 Lr: 1.72188e-04 Mem R(MA/MR): 20418 (21200/36094) [2025-04-29 03:32:19,529 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3478 loss_mask: 0.0370 loss_dice: 2.0599 loss_score: 0.0000 loss_bbox: 0.0516 loss_sp_cls: 0.8334 loss: 5.3425 [2025-04-29 03:32:19,588 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:33:56,039 INFO hook.py line 650 1619929] Train: [237/512][50/242] Data 0.015 (0.017) Batch 1.360 (1.478) Remain 27:24:12 loss: 5.3728 Lr: 1.71975e-04 Mem R(MA/MR): 27350 (21200/36094) [2025-04-29 03:35:07,527 INFO hook.py line 650 1619929] Train: [237/512][100/242] Data 0.018 (0.016) Batch 1.483 (1.453) Remain 26:55:14 loss: 5.5400 Lr: 1.71859e-04 Mem R(MA/MR): 32526 (21200/36094) [2025-04-29 03:36:19,261 INFO hook.py line 650 1619929] Train: [237/512][150/242] Data 0.016 (0.016) Batch 1.281 (1.447) Remain 26:47:02 loss: 5.8319 Lr: 1.71743e-04 Mem R(MA/MR): 32554 (21200/36094) [2025-04-29 03:37:30,602 INFO hook.py line 650 1619929] Train: [237/512][200/242] Data 0.014 (0.017) Batch 1.392 (1.442) Remain 26:40:12 loss: 5.0357 Lr: 1.71627e-04 Mem R(MA/MR): 32554 (21200/36094) [2025-04-29 03:38:28,826 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3486 loss_mask: 0.0381 loss_dice: 2.0720 loss_score: 0.0000 loss_bbox: 0.0516 loss_sp_cls: 0.8305 loss: 5.3644 [2025-04-29 03:38:30,512 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:40:06,779 INFO hook.py line 650 1619929] Train: [238/512][50/242] Data 0.016 (0.017) Batch 1.236 (1.492) Remain 27:34:11 loss: 5.4640 Lr: 1.71414e-04 Mem R(MA/MR): 24156 (21200/36094) [2025-04-29 03:41:18,234 INFO hook.py line 650 1619929] Train: [238/512][100/242] Data 0.017 (0.017) Batch 1.352 (1.460) Remain 26:56:44 loss: 5.0483 Lr: 1.71298e-04 Mem R(MA/MR): 27696 (21200/36094) [2025-04-29 03:42:28,599 INFO hook.py line 650 1619929] Train: [238/512][150/242] Data 0.016 (0.017) Batch 1.729 (1.442) Remain 26:35:44 loss: 6.0863 Lr: 1.71182e-04 Mem R(MA/MR): 27696 (21200/36094) [2025-04-29 03:43:42,689 INFO hook.py line 650 1619929] Train: [238/512][200/242] Data 0.015 (0.017) Batch 1.375 (1.452) Remain 26:45:45 loss: 6.8541 Lr: 1.71066e-04 Mem R(MA/MR): 27696 (21200/36094) [2025-04-29 03:44:40,210 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3457 loss_mask: 0.0376 loss_dice: 2.0841 loss_score: 0.0000 loss_bbox: 0.0515 loss_sp_cls: 0.8307 loss: 5.3703 [2025-04-29 03:44:42,632 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:46:18,833 INFO hook.py line 650 1619929] Train: [239/512][50/242] Data 0.017 (0.016) Batch 1.442 (1.476) Remain 27:10:28 loss: 5.0859 Lr: 1.70852e-04 Mem R(MA/MR): 22768 (21200/36094) [2025-04-29 03:47:30,632 INFO hook.py line 650 1619929] Train: [239/512][100/242] Data 0.017 (0.017) Batch 1.496 (1.456) Remain 26:46:12 loss: 5.7661 Lr: 1.70736e-04 Mem R(MA/MR): 22788 (21200/36094) [2025-04-29 03:48:44,012 INFO hook.py line 650 1619929] Train: [239/512][150/242] Data 0.016 (0.016) Batch 1.228 (1.460) Remain 26:49:30 loss: 4.0679 Lr: 1.70620e-04 Mem R(MA/MR): 24796 (21200/36094) [2025-04-29 03:49:54,680 INFO hook.py line 650 1619929] Train: [239/512][200/242] Data 0.016 (0.016) Batch 1.538 (1.448) Remain 26:35:19 loss: 4.5344 Lr: 1.70504e-04 Mem R(MA/MR): 24802 (21200/36094) [2025-04-29 03:50:52,290 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3463 loss_mask: 0.0375 loss_dice: 2.0683 loss_score: 0.0000 loss_bbox: 0.0516 loss_sp_cls: 0.8302 loss: 5.3506 [2025-04-29 03:50:54,386 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 03:52:31,292 INFO hook.py line 650 1619929] Train: [240/512][50/242] Data 0.017 (0.016) Batch 1.425 (1.465) Remain 26:51:49 loss: 6.0476 Lr: 1.70291e-04 Mem R(MA/MR): 19998 (21200/36094) [2025-04-29 03:53:42,048 INFO hook.py line 650 1619929] Train: [240/512][100/242] Data 0.016 (0.017) Batch 1.392 (1.439) Remain 26:22:22 loss: 5.8948 Lr: 1.70175e-04 Mem R(MA/MR): 21866 (21200/36094) [2025-04-29 03:54:52,094 INFO hook.py line 650 1619929] Train: [240/512][150/242] Data 0.015 (0.016) Batch 1.345 (1.426) Remain 26:06:50 loss: 4.9897 Lr: 1.70059e-04 Mem R(MA/MR): 21866 (21200/36094) [2025-04-29 03:56:04,003 INFO hook.py line 650 1619929] Train: [240/512][200/242] Data 0.014 (0.016) Batch 1.381 (1.429) Remain 26:08:59 loss: 5.7629 Lr: 1.69943e-04 Mem R(MA/MR): 21866 (21200/36094) [2025-04-29 03:57:02,301 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3495 loss_mask: 0.0381 loss_dice: 2.0960 loss_score: 0.0000 loss_bbox: 0.0518 loss_sp_cls: 0.8321 loss: 5.4018 [2025-04-29 03:57:05,762 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 03:57:08,538 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.3649 Process Time: 0.289 Mem R(MA/MR): 4548 (21200/36094) [2025-04-29 03:57:10,425 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9356 Process Time: 0.608 Mem R(MA/MR): 7310 (21200/36094) [2025-04-29 03:57:11,815 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4743 Process Time: 0.428 Mem R(MA/MR): 9702 (21200/36094) [2025-04-29 03:57:19,922 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.7994 Process Time: 1.344 Mem R(MA/MR): 19968 (21200/36094) [2025-04-29 03:57:20,823 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4231 Process Time: 0.343 Mem R(MA/MR): 7244 (21200/36094) [2025-04-29 03:57:22,366 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.0420 Process Time: 0.538 Mem R(MA/MR): 11304 (21200/36094) [2025-04-29 03:57:23,160 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8950 Process Time: 0.314 Mem R(MA/MR): 6440 (21200/36094) [2025-04-29 03:57:23,733 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.8681 Process Time: 0.194 Mem R(MA/MR): 4596 (21200/36094) [2025-04-29 03:57:24,698 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7219 Process Time: 0.289 Mem R(MA/MR): 11416 (21200/36094) [2025-04-29 03:57:26,554 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7989 Process Time: 0.484 Mem R(MA/MR): 9612 (21200/36094) [2025-04-29 03:57:28,926 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.5205 Process Time: 0.392 Mem R(MA/MR): 18816 (21200/36094) [2025-04-29 03:57:31,902 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2681 Process Time: 1.084 Mem R(MA/MR): 15740 (21200/36094) [2025-04-29 03:57:33,155 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.3987 Process Time: 0.372 Mem R(MA/MR): 8778 (21200/36094) [2025-04-29 03:57:33,523 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2758 Process Time: 0.133 Mem R(MA/MR): 4912 (21200/36094) [2025-04-29 03:57:35,908 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.4532 Process Time: 0.324 Mem R(MA/MR): 16646 (21200/36094) [2025-04-29 03:57:37,909 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.6713 Process Time: 0.606 Mem R(MA/MR): 14448 (21200/36094) [2025-04-29 03:57:38,601 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.8195 Process Time: 0.195 Mem R(MA/MR): 6898 (21200/36094) [2025-04-29 03:57:40,021 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7102 Process Time: 0.584 Mem R(MA/MR): 8320 (21200/36094) [2025-04-29 03:57:41,506 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0847 Process Time: 0.314 Mem R(MA/MR): 6474 (21200/36094) [2025-04-29 03:57:42,944 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.0380 Process Time: 0.233 Mem R(MA/MR): 11612 (21200/36094) [2025-04-29 03:57:50,474 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.1288 Process Time: 0.575 Mem R(MA/MR): 23660 (21200/36094) [2025-04-29 03:57:51,363 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4010 Process Time: 0.238 Mem R(MA/MR): 7066 (21200/36094) [2025-04-29 03:58:02,877 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.2163 Process Time: 0.334 Mem R(MA/MR): 10304 (21200/36094) [2025-04-29 03:58:03,372 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.0363 Process Time: 0.156 Mem R(MA/MR): 5478 (21200/36094) [2025-04-29 03:58:04,342 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.3418 Process Time: 0.231 Mem R(MA/MR): 9512 (21200/36094) [2025-04-29 03:58:11,770 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.4787 Process Time: 1.484 Mem R(MA/MR): 31526 (21200/36094) [2025-04-29 03:58:14,670 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.1439 Process Time: 0.987 Mem R(MA/MR): 10292 (21200/36094) [2025-04-29 03:58:16,687 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5502 Process Time: 0.909 Mem R(MA/MR): 9034 (21200/36094) [2025-04-29 03:58:21,188 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.3766 Process Time: 0.294 Mem R(MA/MR): 17134 (21200/36094) [2025-04-29 03:58:22,544 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.4794 Process Time: 0.530 Mem R(MA/MR): 7932 (21200/36094) [2025-04-29 03:58:26,519 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.9484 Process Time: 0.607 Mem R(MA/MR): 20752 (21200/36094) [2025-04-29 03:58:26,765 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.9890 Process Time: 0.103 Mem R(MA/MR): 4230 (21200/36094) [2025-04-29 03:58:30,573 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.6002 Process Time: 0.411 Mem R(MA/MR): 24846 (21200/36094) [2025-04-29 03:58:32,516 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7376 Process Time: 0.807 Mem R(MA/MR): 9964 (21200/36094) [2025-04-29 03:58:34,588 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0406 Process Time: 0.434 Mem R(MA/MR): 14174 (21200/36094) [2025-04-29 03:58:35,025 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.5248 Process Time: 0.148 Mem R(MA/MR): 6748 (21200/36094) [2025-04-29 03:58:38,292 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9354 Process Time: 0.451 Mem R(MA/MR): 28212 (21200/36094) [2025-04-29 03:58:39,909 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5612 Process Time: 0.520 Mem R(MA/MR): 10888 (21200/36094) [2025-04-29 03:58:40,885 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.5498 Process Time: 0.301 Mem R(MA/MR): 5608 (21200/36094) [2025-04-29 03:58:42,263 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.1169 Process Time: 0.495 Mem R(MA/MR): 10406 (21200/36094) [2025-04-29 03:58:43,395 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.1962 Process Time: 0.451 Mem R(MA/MR): 9152 (21200/36094) [2025-04-29 03:58:43,915 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2842 Process Time: 0.164 Mem R(MA/MR): 5688 (21200/36094) [2025-04-29 03:58:44,355 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.0269 Process Time: 0.140 Mem R(MA/MR): 5750 (21200/36094) [2025-04-29 03:58:45,001 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.9266 Process Time: 0.206 Mem R(MA/MR): 7280 (21200/36094) [2025-04-29 03:58:45,666 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6656 Process Time: 0.165 Mem R(MA/MR): 5454 (21200/36094) [2025-04-29 03:58:48,206 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8733 Process Time: 0.314 Mem R(MA/MR): 14822 (21200/36094) [2025-04-29 03:58:57,185 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1412 Process Time: 1.416 Mem R(MA/MR): 20516 (21200/36094) [2025-04-29 03:59:09,353 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.5362 Process Time: 2.026 Mem R(MA/MR): 35676 (21200/36094) [2025-04-29 03:59:10,258 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.6267 Process Time: 0.360 Mem R(MA/MR): 5780 (21200/36094) [2025-04-29 03:59:12,727 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.7578 Process Time: 0.552 Mem R(MA/MR): 13822 (21200/36094) [2025-04-29 03:59:17,359 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 03:59:17,359 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 03:59:17,359 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] table : 0.270 0.630 0.809 0.750 0.662 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] door : 0.443 0.743 0.897 0.891 0.722 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] ceiling lamp : 0.563 0.765 0.873 0.877 0.746 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] cabinet : 0.306 0.420 0.513 0.727 0.358 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] blinds : 0.550 0.788 0.853 0.864 0.826 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] curtain : 0.135 0.218 0.621 0.571 0.333 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] chair : 0.553 0.710 0.769 0.655 0.754 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] storage cabinet: 0.304 0.438 0.562 0.586 0.680 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] office chair : 0.527 0.564 0.592 0.694 0.708 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] bookshelf : 0.264 0.577 0.657 0.571 0.727 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] whiteboard : 0.549 0.741 0.747 0.962 0.714 [2025-04-29 03:59:17,359 INFO hook.py line 395 1619929] window : 0.099 0.211 0.579 0.372 0.352 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] box : 0.158 0.311 0.504 0.464 0.387 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] monitor : 0.574 0.678 0.784 0.787 0.686 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] shelf : 0.130 0.300 0.457 0.769 0.333 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] heater : 0.343 0.557 0.777 0.676 0.658 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] kitchen cabinet: 0.131 0.314 0.695 0.412 0.560 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] sofa : 0.421 0.617 0.706 0.889 0.667 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] bed : 0.255 0.464 0.617 0.556 0.625 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] trash can : 0.482 0.622 0.693 0.758 0.723 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] book : 0.017 0.032 0.072 0.303 0.075 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] plant : 0.449 0.636 0.763 0.917 0.611 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] blanket : 0.414 0.591 0.704 0.778 0.636 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] tv : 0.803 1.000 1.000 1.000 1.000 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] computer tower : 0.261 0.457 0.661 0.800 0.476 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] refrigerator : 0.243 0.422 0.511 1.000 0.333 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] jacket : 0.081 0.204 0.446 0.400 0.545 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] sink : 0.375 0.656 0.799 0.750 0.682 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] bag : 0.102 0.149 0.188 0.400 0.296 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] picture : 0.143 0.311 0.396 0.682 0.385 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] pillow : 0.562 0.670 0.856 0.917 0.579 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] towel : 0.206 0.369 0.527 0.737 0.368 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] suitcase : 0.384 0.434 0.434 0.750 0.429 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] backpack : 0.257 0.484 0.535 0.750 0.462 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] crate : 0.087 0.331 0.537 0.545 0.545 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] keyboard : 0.377 0.524 0.655 0.647 0.564 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] toilet : 0.730 0.889 1.000 1.000 0.889 [2025-04-29 03:59:17,360 INFO hook.py line 395 1619929] printer : 0.357 0.499 0.588 0.625 0.556 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] poster : 0.001 0.008 0.010 0.083 0.111 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] microwave : 0.424 0.750 0.985 1.000 0.750 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] shoes : 0.104 0.169 0.498 0.478 0.268 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] socket : 0.172 0.423 0.632 0.718 0.436 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] bottle : 0.093 0.183 0.289 0.397 0.301 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] bucket : 0.106 0.106 0.110 0.400 0.286 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] cushion : 0.014 0.062 0.240 0.188 0.500 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] basket : 0.009 0.012 0.014 0.167 0.143 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] shoe rack : 0.111 0.500 0.500 1.000 0.500 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] telephone : 0.306 0.668 0.686 0.909 0.588 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] laptop : 0.335 0.510 0.591 0.545 0.750 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] plant pot : 0.087 0.257 0.489 0.600 0.375 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] exhaust fan : 0.127 0.287 0.287 0.833 0.333 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] cup : 0.221 0.377 0.402 0.882 0.341 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] coat hanger : 0.128 0.385 0.750 0.750 0.750 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] light switch : 0.226 0.477 0.596 0.811 0.462 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] speaker : 0.381 0.460 0.545 0.833 0.455 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.333 1.000 0.167 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] smoke detector : 0.623 0.767 0.810 1.000 0.667 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] power strip : 0.141 0.279 0.290 1.000 0.200 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] paper bag : 0.108 0.125 0.125 0.250 1.000 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] mouse : 0.434 0.677 0.705 0.952 0.625 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] cutting board : 0.014 0.042 0.042 0.333 0.250 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] toilet paper : 0.282 0.444 0.456 0.800 0.471 [2025-04-29 03:59:17,361 INFO hook.py line 395 1619929] paper towel : 0.139 0.166 0.166 0.400 0.250 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] clock : 0.417 0.764 0.764 0.750 1.000 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] tap : 0.191 0.307 0.537 0.667 0.444 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] soap dispenser : 0.196 0.437 0.447 1.000 0.400 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] bowl : 0.058 0.141 0.159 0.500 0.333 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] whiteboard eraser: 0.260 0.647 0.647 0.833 0.833 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] toilet brush : 0.503 0.738 0.920 1.000 0.667 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] spray bottle : 0.013 0.018 0.021 0.143 0.250 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] stapler : 0.003 0.028 0.144 0.167 0.333 [2025-04-29 03:59:17,362 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 03:59:17,362 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 03:59:17,362 INFO hook.py line 404 1619929] average : 0.244 0.387 0.486 0.612 0.462 [2025-04-29 03:59:17,362 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 03:59:17,363 INFO hook.py line 480 1619929] Total Process Time: 24.878 s [2025-04-29 03:59:17,363 INFO hook.py line 481 1619929] Average Process Time: 501.804 ms [2025-04-29 03:59:17,363 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 03:59:17,413 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 03:59:17,417 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:00:56,878 INFO hook.py line 650 1619929] Train: [241/512][50/242] Data 0.017 (0.039) Batch 1.423 (1.491) Remain 27:14:25 loss: 3.7209 Lr: 1.69729e-04 Mem R(MA/MR): 23386 (21200/36094) [2025-04-29 04:02:08,410 INFO hook.py line 650 1619929] Train: [241/512][100/242] Data 0.016 (0.027) Batch 1.367 (1.460) Remain 26:39:07 loss: 5.7034 Lr: 1.69613e-04 Mem R(MA/MR): 23402 (21200/36094) [2025-04-29 04:03:21,878 INFO hook.py line 650 1619929] Train: [241/512][150/242] Data 0.015 (0.024) Batch 1.389 (1.463) Remain 26:41:27 loss: 5.0810 Lr: 1.69497e-04 Mem R(MA/MR): 25404 (21200/36094) [2025-04-29 04:04:35,856 INFO hook.py line 650 1619929] Train: [241/512][200/242] Data 0.015 (0.022) Batch 1.233 (1.467) Remain 26:44:48 loss: 4.2458 Lr: 1.69381e-04 Mem R(MA/MR): 25404 (21200/36094) [2025-04-29 04:05:32,269 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3527 loss_mask: 0.0380 loss_dice: 2.0969 loss_score: 0.0000 loss_bbox: 0.0519 loss_sp_cls: 0.8420 loss: 5.4205 [2025-04-29 04:05:34,590 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:07:12,099 INFO hook.py line 650 1619929] Train: [242/512][50/242] Data 0.016 (0.017) Batch 1.587 (1.518) Remain 27:37:59 loss: 5.0550 Lr: 1.69167e-04 Mem R(MA/MR): 21946 (21200/36094) [2025-04-29 04:08:23,032 INFO hook.py line 650 1619929] Train: [242/512][100/242] Data 0.016 (0.017) Batch 1.331 (1.467) Remain 26:40:49 loss: 4.6366 Lr: 1.69051e-04 Mem R(MA/MR): 21956 (21200/36094) [2025-04-29 04:09:33,996 INFO hook.py line 650 1619929] Train: [242/512][150/242] Data 0.017 (0.016) Batch 1.667 (1.451) Remain 26:21:58 loss: 5.0460 Lr: 1.68935e-04 Mem R(MA/MR): 21960 (21200/36094) [2025-04-29 04:10:47,782 INFO hook.py line 650 1619929] Train: [242/512][200/242] Data 0.015 (0.017) Batch 1.347 (1.457) Remain 26:27:42 loss: 5.9196 Lr: 1.68819e-04 Mem R(MA/MR): 21960 (21200/36094) [2025-04-29 04:11:44,614 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3495 loss_mask: 0.0380 loss_dice: 2.0829 loss_score: 0.0000 loss_bbox: 0.0514 loss_sp_cls: 0.8303 loss: 5.3828 [2025-04-29 04:11:46,440 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:13:23,448 INFO hook.py line 650 1619929] Train: [243/512][50/242] Data 0.017 (0.016) Batch 1.403 (1.447) Remain 26:14:05 loss: 4.3393 Lr: 1.68605e-04 Mem R(MA/MR): 23770 (21200/36094) [2025-04-29 04:14:33,977 INFO hook.py line 650 1619929] Train: [243/512][100/242] Data 0.017 (0.016) Batch 1.294 (1.428) Remain 25:52:42 loss: 4.9502 Lr: 1.68491e-04 Mem R(MA/MR): 23770 (21200/36094) [2025-04-29 04:15:47,213 INFO hook.py line 650 1619929] Train: [243/512][150/242] Data 0.015 (0.016) Batch 1.315 (1.440) Remain 26:05:05 loss: 5.4939 Lr: 1.68377e-04 Mem R(MA/MR): 25560 (21200/36094) [2025-04-29 04:16:59,229 INFO hook.py line 650 1619929] Train: [243/512][200/242] Data 0.015 (0.016) Batch 1.438 (1.440) Remain 26:03:50 loss: 6.7928 Lr: 1.68261e-04 Mem R(MA/MR): 25580 (21200/36094) [2025-04-29 04:17:56,138 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3595 loss_mask: 0.0386 loss_dice: 2.0946 loss_score: 0.0000 loss_bbox: 0.0528 loss_sp_cls: 0.8379 loss: 5.4417 [2025-04-29 04:17:58,366 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:19:35,419 INFO hook.py line 650 1619929] Train: [244/512][50/242] Data 0.017 (0.016) Batch 1.489 (1.442) Remain 26:03:30 loss: 5.8481 Lr: 1.68048e-04 Mem R(MA/MR): 20554 (21200/36094) [2025-04-29 04:20:49,846 INFO hook.py line 650 1619929] Train: [244/512][100/242] Data 0.018 (0.017) Batch 1.465 (1.466) Remain 26:28:11 loss: 5.3004 Lr: 1.67931e-04 Mem R(MA/MR): 20562 (21200/36094) [2025-04-29 04:22:03,485 INFO hook.py line 650 1619929] Train: [244/512][150/242] Data 0.016 (0.017) Batch 1.438 (1.468) Remain 26:29:26 loss: 6.0446 Lr: 1.67815e-04 Mem R(MA/MR): 20562 (21200/36094) [2025-04-29 04:23:15,891 INFO hook.py line 650 1619929] Train: [244/512][200/242] Data 0.014 (0.017) Batch 1.198 (1.463) Remain 26:22:40 loss: 4.7703 Lr: 1.67699e-04 Mem R(MA/MR): 22448 (21200/36094) [2025-04-29 04:24:13,028 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3931 loss_mask: 0.0414 loss_dice: 2.2102 loss_score: 0.0000 loss_bbox: 0.0542 loss_sp_cls: 0.8767 loss: 5.7405 [2025-04-29 04:24:15,375 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:25:52,065 INFO hook.py line 650 1619929] Train: [245/512][50/242] Data 0.016 (0.016) Batch 1.439 (1.477) Remain 26:35:22 loss: 4.6088 Lr: 1.67485e-04 Mem R(MA/MR): 22616 (21200/36094) [2025-04-29 04:27:06,691 INFO hook.py line 650 1619929] Train: [245/512][100/242] Data 0.016 (0.017) Batch 1.619 (1.485) Remain 26:42:44 loss: 6.8762 Lr: 1.67369e-04 Mem R(MA/MR): 22616 (21200/36094) [2025-04-29 04:28:20,532 INFO hook.py line 650 1619929] Train: [245/512][150/242] Data 0.016 (0.017) Batch 1.378 (1.482) Remain 26:38:28 loss: 5.9725 Lr: 1.67252e-04 Mem R(MA/MR): 22640 (21200/36094) [2025-04-29 04:29:32,066 INFO hook.py line 650 1619929] Train: [245/512][200/242] Data 0.014 (0.017) Batch 1.424 (1.469) Remain 26:23:09 loss: 7.6476 Lr: 1.67136e-04 Mem R(MA/MR): 22640 (21200/36094) [2025-04-29 04:30:29,632 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3825 loss_mask: 0.0406 loss_dice: 2.1788 loss_score: 0.0000 loss_bbox: 0.0538 loss_sp_cls: 0.8748 loss: 5.6612 [2025-04-29 04:30:29,969 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:32:06,555 INFO hook.py line 650 1619929] Train: [246/512][50/242] Data 0.015 (0.016) Batch 1.498 (1.462) Remain 26:13:40 loss: 5.8981 Lr: 1.66922e-04 Mem R(MA/MR): 21562 (21200/36094) [2025-04-29 04:33:17,850 INFO hook.py line 650 1619929] Train: [246/512][100/242] Data 0.016 (0.017) Batch 1.479 (1.444) Remain 25:52:12 loss: 5.1028 Lr: 1.66806e-04 Mem R(MA/MR): 21562 (21200/36094) [2025-04-29 04:34:28,542 INFO hook.py line 650 1619929] Train: [246/512][150/242] Data 0.015 (0.017) Batch 1.418 (1.433) Remain 25:40:07 loss: 5.1574 Lr: 1.66690e-04 Mem R(MA/MR): 21574 (21200/36094) [2025-04-29 04:35:42,536 INFO hook.py line 650 1619929] Train: [246/512][200/242] Data 0.014 (0.016) Batch 1.324 (1.445) Remain 25:51:34 loss: 4.7526 Lr: 1.66573e-04 Mem R(MA/MR): 23052 (21200/36094) [2025-04-29 04:36:39,847 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3793 loss_mask: 0.0405 loss_dice: 2.1642 loss_score: 0.0000 loss_bbox: 0.0539 loss_sp_cls: 0.8636 loss: 5.6259 [2025-04-29 04:36:39,917 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:38:06,149 INFO hook.py line 650 1619929] Train: [247/512][50/242] Data 0.017 (0.017) Batch 1.629 (1.466) Remain 26:11:24 loss: 6.5034 Lr: 1.66359e-04 Mem R(MA/MR): 22168 (21200/36094) [2025-04-29 04:39:17,524 INFO hook.py line 650 1619929] Train: [247/512][100/242] Data 0.016 (0.017) Batch 1.428 (1.446) Remain 25:49:01 loss: 3.6727 Lr: 1.66243e-04 Mem R(MA/MR): 22168 (21200/36094) [2025-04-29 04:40:30,579 INFO hook.py line 650 1619929] Train: [247/512][150/242] Data 0.018 (0.017) Batch 1.373 (1.451) Remain 25:53:17 loss: 4.7266 Lr: 1.66127e-04 Mem R(MA/MR): 22168 (21200/36094) [2025-04-29 04:41:45,143 INFO hook.py line 650 1619929] Train: [247/512][200/242] Data 0.015 (0.016) Batch 1.473 (1.461) Remain 26:02:58 loss: 6.6772 Lr: 1.66010e-04 Mem R(MA/MR): 22168 (21200/36094) [2025-04-29 04:42:42,753 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3682 loss_mask: 0.0392 loss_dice: 2.1449 loss_score: 0.0000 loss_bbox: 0.0533 loss_sp_cls: 0.8559 loss: 5.5478 [2025-04-29 04:42:43,032 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:44:14,654 INFO hook.py line 650 1619929] Train: [248/512][50/242] Data 0.016 (0.016) Batch 1.417 (1.444) Remain 25:41:43 loss: 5.9489 Lr: 1.65796e-04 Mem R(MA/MR): 19568 (21200/36094) [2025-04-29 04:45:28,793 INFO hook.py line 650 1619929] Train: [248/512][100/242] Data 0.016 (0.016) Batch 1.386 (1.464) Remain 26:02:06 loss: 4.7685 Lr: 1.65680e-04 Mem R(MA/MR): 20964 (21200/36094) [2025-04-29 04:46:40,657 INFO hook.py line 650 1619929] Train: [248/512][150/242] Data 0.016 (0.016) Batch 1.297 (1.455) Remain 25:51:15 loss: 5.5410 Lr: 1.65563e-04 Mem R(MA/MR): 23140 (21200/36094) [2025-04-29 04:47:50,568 INFO hook.py line 650 1619929] Train: [248/512][200/242] Data 0.015 (0.017) Batch 1.449 (1.440) Remain 25:34:46 loss: 7.2230 Lr: 1.65447e-04 Mem R(MA/MR): 23140 (21200/36094) [2025-04-29 04:48:47,639 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3705 loss_mask: 0.0404 loss_dice: 2.1411 loss_score: 0.0000 loss_bbox: 0.0538 loss_sp_cls: 0.8525 loss: 5.5610 [2025-04-29 04:48:48,546 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 04:48:50,859 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5143 Process Time: 0.357 Mem R(MA/MR): 4488 (21200/36094) [2025-04-29 04:48:52,810 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1461 Process Time: 0.778 Mem R(MA/MR): 7310 (21200/36094) [2025-04-29 04:48:54,643 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.0440 Process Time: 0.713 Mem R(MA/MR): 9700 (21200/36094) [2025-04-29 04:49:03,682 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.8063 Process Time: 1.353 Mem R(MA/MR): 19616 (21200/36094) [2025-04-29 04:49:04,457 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3099 Process Time: 0.241 Mem R(MA/MR): 7140 (21200/36094) [2025-04-29 04:49:05,903 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.9901 Process Time: 0.411 Mem R(MA/MR): 11032 (21200/36094) [2025-04-29 04:49:06,452 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1301 Process Time: 0.163 Mem R(MA/MR): 6274 (21200/36094) [2025-04-29 04:49:06,981 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.8231 Process Time: 0.167 Mem R(MA/MR): 4526 (21200/36094) [2025-04-29 04:49:08,066 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.5667 Process Time: 0.420 Mem R(MA/MR): 11190 (21200/36094) [2025-04-29 04:49:09,530 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6535 Process Time: 0.332 Mem R(MA/MR): 9462 (21200/36094) [2025-04-29 04:49:11,914 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.3037 Process Time: 0.481 Mem R(MA/MR): 18220 (21200/36094) [2025-04-29 04:49:14,183 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2713 Process Time: 0.328 Mem R(MA/MR): 15072 (21200/36094) [2025-04-29 04:49:15,885 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.4205 Process Time: 0.571 Mem R(MA/MR): 8744 (21200/36094) [2025-04-29 04:49:16,428 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1023 Process Time: 0.197 Mem R(MA/MR): 4868 (21200/36094) [2025-04-29 04:49:19,928 INFO hook.py line 449 1619929] Test: [15/50] Loss 10.6862 Process Time: 0.519 Mem R(MA/MR): 16326 (21200/36094) [2025-04-29 04:49:21,623 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6887 Process Time: 0.275 Mem R(MA/MR): 14428 (21200/36094) [2025-04-29 04:49:22,733 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.9331 Process Time: 0.434 Mem R(MA/MR): 6688 (21200/36094) [2025-04-29 04:49:24,003 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1872 Process Time: 0.496 Mem R(MA/MR): 8372 (21200/36094) [2025-04-29 04:49:25,846 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.8902 Process Time: 0.468 Mem R(MA/MR): 6122 (21200/36094) [2025-04-29 04:49:27,726 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.9169 Process Time: 0.452 Mem R(MA/MR): 11158 (21200/36094) [2025-04-29 04:49:36,194 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.5052 Process Time: 0.645 Mem R(MA/MR): 23016 (21200/36094) [2025-04-29 04:49:36,891 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7517 Process Time: 0.259 Mem R(MA/MR): 6958 (21200/36094) [2025-04-29 04:49:47,344 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.6216 Process Time: 0.349 Mem R(MA/MR): 10032 (21200/36094) [2025-04-29 04:49:47,968 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7746 Process Time: 0.159 Mem R(MA/MR): 5304 (21200/36094) [2025-04-29 04:49:48,960 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9305 Process Time: 0.287 Mem R(MA/MR): 9230 (21200/36094) [2025-04-29 04:49:56,193 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.3142 Process Time: 1.534 Mem R(MA/MR): 30804 (21200/36094) [2025-04-29 04:49:58,858 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.0777 Process Time: 0.589 Mem R(MA/MR): 9848 (21200/36094) [2025-04-29 04:50:00,112 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.1471 Process Time: 0.328 Mem R(MA/MR): 8980 (21200/36094) [2025-04-29 04:50:05,347 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9861 Process Time: 0.572 Mem R(MA/MR): 16556 (21200/36094) [2025-04-29 04:50:06,443 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.0518 Process Time: 0.329 Mem R(MA/MR): 7868 (21200/36094) [2025-04-29 04:50:10,740 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0804 Process Time: 0.778 Mem R(MA/MR): 20118 (21200/36094) [2025-04-29 04:50:11,188 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.7082 Process Time: 0.193 Mem R(MA/MR): 3962 (21200/36094) [2025-04-29 04:50:15,111 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.8743 Process Time: 0.688 Mem R(MA/MR): 24260 (21200/36094) [2025-04-29 04:50:16,192 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9373 Process Time: 0.351 Mem R(MA/MR): 9712 (21200/36094) [2025-04-29 04:50:18,228 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.8989 Process Time: 0.376 Mem R(MA/MR): 13868 (21200/36094) [2025-04-29 04:50:18,920 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.8111 Process Time: 0.219 Mem R(MA/MR): 6742 (21200/36094) [2025-04-29 04:50:22,840 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.1541 Process Time: 0.575 Mem R(MA/MR): 28046 (21200/36094) [2025-04-29 04:50:24,828 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.7020 Process Time: 0.597 Mem R(MA/MR): 10584 (21200/36094) [2025-04-29 04:50:25,325 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.7350 Process Time: 0.168 Mem R(MA/MR): 5444 (21200/36094) [2025-04-29 04:50:26,537 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8185 Process Time: 0.354 Mem R(MA/MR): 10208 (21200/36094) [2025-04-29 04:50:27,485 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.9361 Process Time: 0.261 Mem R(MA/MR): 9092 (21200/36094) [2025-04-29 04:50:27,990 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.0246 Process Time: 0.142 Mem R(MA/MR): 5464 (21200/36094) [2025-04-29 04:50:28,452 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7277 Process Time: 0.146 Mem R(MA/MR): 5514 (21200/36094) [2025-04-29 04:50:29,143 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.1038 Process Time: 0.280 Mem R(MA/MR): 6980 (21200/36094) [2025-04-29 04:50:29,771 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.9542 Process Time: 0.142 Mem R(MA/MR): 5226 (21200/36094) [2025-04-29 04:50:32,239 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.6806 Process Time: 0.406 Mem R(MA/MR): 14640 (21200/36094) [2025-04-29 04:50:39,642 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.8329 Process Time: 1.185 Mem R(MA/MR): 20158 (21200/36094) [2025-04-29 04:50:50,143 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.8643 Process Time: 1.946 Mem R(MA/MR): 34620 (21200/36094) [2025-04-29 04:50:51,049 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.3944 Process Time: 0.363 Mem R(MA/MR): 5542 (21200/36094) [2025-04-29 04:50:53,614 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.4081 Process Time: 0.568 Mem R(MA/MR): 13592 (21200/36094) [2025-04-29 04:50:57,628 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 04:50:57,628 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 04:50:57,628 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] table : 0.219 0.475 0.723 0.667 0.574 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] door : 0.406 0.691 0.871 0.932 0.696 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] ceiling lamp : 0.539 0.741 0.837 0.855 0.751 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] cabinet : 0.306 0.454 0.489 0.561 0.552 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] blinds : 0.506 0.642 0.764 0.765 0.565 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] curtain : 0.161 0.392 0.484 0.467 0.583 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] chair : 0.624 0.764 0.834 0.831 0.684 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] storage cabinet: 0.182 0.348 0.447 0.542 0.520 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] office chair : 0.513 0.566 0.579 0.655 0.792 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] bookshelf : 0.283 0.735 0.741 0.889 0.727 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] whiteboard : 0.544 0.747 0.827 0.844 0.771 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] window : 0.135 0.260 0.613 0.450 0.297 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] box : 0.177 0.291 0.509 0.459 0.398 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] monitor : 0.606 0.797 0.861 0.962 0.729 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] shelf : 0.134 0.281 0.488 0.750 0.300 [2025-04-29 04:50:57,628 INFO hook.py line 395 1619929] heater : 0.447 0.657 0.796 0.848 0.737 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] kitchen cabinet: 0.163 0.399 0.695 0.545 0.480 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] sofa : 0.499 0.612 0.792 0.692 0.750 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] bed : 0.160 0.592 0.775 0.833 0.625 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] trash can : 0.553 0.716 0.794 0.823 0.785 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] book : 0.022 0.038 0.080 0.235 0.086 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] plant : 0.430 0.602 0.646 1.000 0.556 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] blanket : 0.439 0.636 0.727 1.000 0.636 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] tv : 0.747 0.833 0.833 1.000 0.833 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] computer tower : 0.240 0.404 0.664 0.643 0.429 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] refrigerator : 0.145 0.333 0.333 1.000 0.333 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] jacket : 0.088 0.261 0.336 0.462 0.545 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] sink : 0.355 0.665 0.845 0.800 0.727 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] bag : 0.167 0.238 0.298 0.667 0.296 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] picture : 0.143 0.319 0.376 0.486 0.436 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] pillow : 0.565 0.844 0.892 0.938 0.789 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] towel : 0.188 0.344 0.520 0.600 0.395 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] suitcase : 0.482 0.519 0.519 0.667 0.571 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] backpack : 0.319 0.450 0.540 0.857 0.462 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] crate : 0.059 0.260 0.470 0.714 0.455 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] keyboard : 0.480 0.615 0.666 1.000 0.487 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] toilet : 0.744 0.876 1.000 0.889 0.889 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] printer : 0.315 0.467 0.599 1.000 0.444 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] painting : 0.083 0.083 0.083 0.167 1.000 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] microwave : 0.283 0.625 0.750 1.000 0.625 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] shoes : 0.148 0.257 0.493 0.640 0.390 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] socket : 0.135 0.354 0.598 0.674 0.429 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] bottle : 0.080 0.150 0.259 0.457 0.253 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] bucket : 0.185 0.270 0.281 0.308 0.571 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] cushion : 0.009 0.046 0.219 0.130 0.500 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.143 0.000 0.000 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 04:50:57,629 INFO hook.py line 395 1619929] telephone : 0.296 0.561 0.573 0.750 0.529 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] laptop : 0.252 0.362 0.373 0.667 0.500 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] plant pot : 0.090 0.203 0.431 0.556 0.312 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] exhaust fan : 0.091 0.200 0.200 1.000 0.200 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] cup : 0.218 0.362 0.451 0.933 0.318 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.492 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] light switch : 0.200 0.458 0.596 0.667 0.492 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] speaker : 0.249 0.406 0.406 0.714 0.455 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] kettle : 0.204 0.333 0.333 1.000 0.333 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] smoke detector : 0.648 0.813 0.816 1.000 0.708 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 1.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] power strip : 0.082 0.385 0.436 0.667 0.400 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] paper bag : 0.071 0.071 0.083 0.143 1.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] mouse : 0.533 0.738 0.738 1.000 0.688 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] cutting board : 0.028 0.250 0.250 1.000 0.250 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] toilet paper : 0.200 0.374 0.428 0.857 0.353 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] paper towel : 0.032 0.061 0.267 0.400 0.250 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] clock : 0.539 0.903 0.903 0.750 1.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 1.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] tap : 0.143 0.272 0.592 0.500 0.333 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] soap dispenser : 0.427 0.649 0.755 0.571 0.800 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] bowl : 0.047 0.172 0.192 0.333 0.667 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] whiteboard eraser: 0.171 0.414 0.451 0.667 0.667 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] toilet brush : 0.483 0.726 0.907 1.000 0.667 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] spray bottle : 0.056 0.250 0.250 1.000 0.250 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] headphones : 0.324 0.792 1.000 0.667 1.000 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] stapler : 0.002 0.017 0.065 0.100 0.333 [2025-04-29 04:50:57,630 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 04:50:57,630 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 04:50:57,630 INFO hook.py line 404 1619929] average : 0.242 0.389 0.493 0.630 0.469 [2025-04-29 04:50:57,631 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 04:50:57,631 INFO hook.py line 480 1619929] Total Process Time: 23.942 s [2025-04-29 04:50:57,631 INFO hook.py line 481 1619929] Average Process Time: 481.320 ms [2025-04-29 04:50:57,631 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 04:50:57,678 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 04:50:57,682 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:52:29,408 INFO hook.py line 650 1619929] Train: [249/512][50/242] Data 0.017 (0.016) Batch 1.344 (1.414) Remain 25:04:07 loss: 4.8479 Lr: 1.65233e-04 Mem R(MA/MR): 23594 (21200/36094) [2025-04-29 04:53:40,254 INFO hook.py line 650 1619929] Train: [249/512][100/242] Data 0.016 (0.016) Batch 1.450 (1.415) Remain 25:04:42 loss: 5.2147 Lr: 1.65116e-04 Mem R(MA/MR): 23594 (21200/36094) [2025-04-29 04:54:52,187 INFO hook.py line 650 1619929] Train: [249/512][150/242] Data 0.016 (0.016) Batch 1.428 (1.423) Remain 25:11:57 loss: 5.9634 Lr: 1.65000e-04 Mem R(MA/MR): 23594 (21200/36094) [2025-04-29 04:56:05,994 INFO hook.py line 650 1619929] Train: [249/512][200/242] Data 0.015 (0.022) Batch 1.544 (1.437) Remain 25:25:01 loss: 6.3545 Lr: 1.64884e-04 Mem R(MA/MR): 24338 (21200/36094) [2025-04-29 04:57:04,039 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3638 loss_mask: 0.0390 loss_dice: 2.1264 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8482 loss: 5.5007 [2025-04-29 04:57:04,206 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 04:58:31,664 INFO hook.py line 650 1619929] Train: [250/512][50/242] Data 0.015 (0.017) Batch 1.399 (1.498) Remain 26:27:39 loss: 5.1805 Lr: 1.64669e-04 Mem R(MA/MR): 20556 (21200/36094) [2025-04-29 04:59:42,958 INFO hook.py line 650 1619929] Train: [250/512][100/242] Data 0.017 (0.017) Batch 1.461 (1.461) Remain 25:47:05 loss: 4.5063 Lr: 1.64553e-04 Mem R(MA/MR): 22140 (21200/36094) [2025-04-29 05:00:53,327 INFO hook.py line 650 1619929] Train: [250/512][150/242] Data 0.017 (0.017) Batch 1.490 (1.443) Remain 25:26:39 loss: 4.6260 Lr: 1.64436e-04 Mem R(MA/MR): 22140 (21200/36094) [2025-04-29 05:02:04,709 INFO hook.py line 650 1619929] Train: [250/512][200/242] Data 0.014 (0.017) Batch 1.323 (1.439) Remain 25:21:26 loss: 5.1513 Lr: 1.64320e-04 Mem R(MA/MR): 22144 (21200/36094) [2025-04-29 05:03:01,838 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3683 loss_mask: 0.0398 loss_dice: 2.1246 loss_score: 0.0000 loss_bbox: 0.0532 loss_sp_cls: 0.8536 loss: 5.5320 [2025-04-29 05:03:01,978 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:04:29,167 INFO hook.py line 650 1619929] Train: [251/512][50/242] Data 0.015 (0.016) Batch 1.375 (1.417) Remain 24:56:34 loss: 5.6998 Lr: 1.64105e-04 Mem R(MA/MR): 20180 (21200/36094) [2025-04-29 05:05:41,988 INFO hook.py line 650 1619929] Train: [251/512][100/242] Data 0.016 (0.016) Batch 1.363 (1.437) Remain 25:16:38 loss: 4.9845 Lr: 1.63989e-04 Mem R(MA/MR): 24416 (21200/36094) [2025-04-29 05:06:53,479 INFO hook.py line 650 1619929] Train: [251/512][150/242] Data 0.015 (0.016) Batch 1.468 (1.435) Remain 25:12:42 loss: 5.7594 Lr: 1.63872e-04 Mem R(MA/MR): 26350 (21200/36094) [2025-04-29 05:08:05,480 INFO hook.py line 650 1619929] Train: [251/512][200/242] Data 0.015 (0.016) Batch 1.245 (1.436) Remain 25:12:52 loss: 4.4842 Lr: 1.63756e-04 Mem R(MA/MR): 26350 (21200/36094) [2025-04-29 05:09:02,730 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3625 loss_mask: 0.0396 loss_dice: 2.1337 loss_score: 0.0000 loss_bbox: 0.0534 loss_sp_cls: 0.8470 loss: 5.5172 [2025-04-29 05:09:06,836 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:10:39,095 INFO hook.py line 650 1619929] Train: [252/512][50/242] Data 0.015 (0.016) Batch 1.308 (1.454) Remain 25:29:27 loss: 5.3527 Lr: 1.63544e-04 Mem R(MA/MR): 22922 (21200/36094) [2025-04-29 05:11:49,714 INFO hook.py line 650 1619929] Train: [252/512][100/242] Data 0.016 (0.017) Batch 1.411 (1.433) Remain 25:05:42 loss: 6.6153 Lr: 1.63427e-04 Mem R(MA/MR): 22936 (21200/36094) [2025-04-29 05:13:02,478 INFO hook.py line 650 1619929] Train: [252/512][150/242] Data 0.016 (0.016) Batch 1.526 (1.440) Remain 25:12:36 loss: 7.0905 Lr: 1.63311e-04 Mem R(MA/MR): 22946 (21200/36094) [2025-04-29 05:14:13,285 INFO hook.py line 650 1619929] Train: [252/512][200/242] Data 0.015 (0.016) Batch 1.624 (1.434) Remain 25:04:58 loss: 6.6288 Lr: 1.63194e-04 Mem R(MA/MR): 22948 (21200/36094) [2025-04-29 05:15:09,198 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3619 loss_mask: 0.0384 loss_dice: 2.1121 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8394 loss: 5.4725 [2025-04-29 05:15:09,519 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:16:45,033 INFO hook.py line 650 1619929] Train: [253/512][50/242] Data 0.015 (0.017) Batch 1.446 (1.464) Remain 25:34:10 loss: 4.4788 Lr: 1.62980e-04 Mem R(MA/MR): 20596 (21200/36094) [2025-04-29 05:17:56,230 INFO hook.py line 650 1619929] Train: [253/512][100/242] Data 0.016 (0.017) Batch 1.344 (1.443) Remain 25:11:15 loss: 4.4747 Lr: 1.62863e-04 Mem R(MA/MR): 22292 (21200/36094) [2025-04-29 05:19:09,899 INFO hook.py line 650 1619929] Train: [253/512][150/242] Data 0.016 (0.016) Batch 1.341 (1.454) Remain 25:20:43 loss: 6.0394 Lr: 1.62746e-04 Mem R(MA/MR): 24058 (21200/36094) [2025-04-29 05:20:20,155 INFO hook.py line 650 1619929] Train: [253/512][200/242] Data 0.014 (0.016) Batch 1.309 (1.441) Remain 25:06:39 loss: 6.0988 Lr: 1.62630e-04 Mem R(MA/MR): 25886 (21200/36094) [2025-04-29 05:21:17,981 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3598 loss_mask: 0.0388 loss_dice: 2.1129 loss_score: 0.0000 loss_bbox: 0.0524 loss_sp_cls: 0.8423 loss: 5.4632 [2025-04-29 05:21:18,114 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:22:54,726 INFO hook.py line 650 1619929] Train: [254/512][50/242] Data 0.015 (0.016) Batch 1.436 (1.514) Remain 26:20:13 loss: 5.9388 Lr: 1.62415e-04 Mem R(MA/MR): 18708 (21200/36094) [2025-04-29 05:24:05,859 INFO hook.py line 650 1619929] Train: [254/512][100/242] Data 0.016 (0.016) Batch 1.402 (1.467) Remain 25:29:54 loss: 5.1545 Lr: 1.62298e-04 Mem R(MA/MR): 18708 (21200/36094) [2025-04-29 05:25:18,190 INFO hook.py line 650 1619929] Train: [254/512][150/242] Data 0.015 (0.016) Batch 1.450 (1.460) Remain 25:21:30 loss: 6.5194 Lr: 1.62182e-04 Mem R(MA/MR): 18712 (21200/36094) [2025-04-29 05:26:28,034 INFO hook.py line 650 1619929] Train: [254/512][200/242] Data 0.014 (0.016) Batch 1.504 (1.444) Remain 25:03:36 loss: 5.0725 Lr: 1.62065e-04 Mem R(MA/MR): 20540 (21200/36094) [2025-04-29 05:27:25,366 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3569 loss_mask: 0.0389 loss_dice: 2.0967 loss_score: 0.0000 loss_bbox: 0.0527 loss_sp_cls: 0.8396 loss: 5.4363 [2025-04-29 05:27:27,078 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:28:59,347 INFO hook.py line 650 1619929] Train: [255/512][50/242] Data 0.016 (0.016) Batch 1.384 (1.451) Remain 25:08:43 loss: 4.1375 Lr: 1.61850e-04 Mem R(MA/MR): 19568 (21200/36094) [2025-04-29 05:30:12,178 INFO hook.py line 650 1619929] Train: [255/512][100/242] Data 0.017 (0.016) Batch 1.450 (1.454) Remain 25:10:31 loss: 5.6349 Lr: 1.61734e-04 Mem R(MA/MR): 20240 (21200/36094) [2025-04-29 05:31:27,053 INFO hook.py line 650 1619929] Train: [255/512][150/242] Data 0.016 (0.016) Batch 1.432 (1.469) Remain 25:24:41 loss: 6.3420 Lr: 1.61617e-04 Mem R(MA/MR): 20246 (21200/36094) [2025-04-29 05:32:40,123 INFO hook.py line 650 1619929] Train: [255/512][200/242] Data 0.015 (0.016) Batch 1.436 (1.467) Remain 25:21:32 loss: 5.7085 Lr: 1.61500e-04 Mem R(MA/MR): 20246 (21200/36094) [2025-04-29 05:33:38,246 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3560 loss_mask: 0.0387 loss_dice: 2.0996 loss_score: 0.0000 loss_bbox: 0.0525 loss_sp_cls: 0.8380 loss: 5.4378 [2025-04-29 05:33:41,646 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:35:18,725 INFO hook.py line 650 1619929] Train: [256/512][50/242] Data 0.015 (0.016) Batch 1.399 (1.466) Remain 25:17:59 loss: 5.3597 Lr: 1.61286e-04 Mem R(MA/MR): 22928 (21200/36094) [2025-04-29 05:36:32,462 INFO hook.py line 650 1619929] Train: [256/512][100/242] Data 0.016 (0.016) Batch 1.426 (1.470) Remain 25:21:37 loss: 4.1191 Lr: 1.61169e-04 Mem R(MA/MR): 22948 (21200/36094) [2025-04-29 05:37:44,468 INFO hook.py line 650 1619929] Train: [256/512][150/242] Data 0.016 (0.016) Batch 1.477 (1.460) Remain 25:09:46 loss: 5.7457 Lr: 1.61052e-04 Mem R(MA/MR): 22948 (21200/36094) [2025-04-29 05:38:55,984 INFO hook.py line 650 1619929] Train: [256/512][200/242] Data 0.014 (0.016) Batch 1.321 (1.453) Remain 25:00:46 loss: 5.1385 Lr: 1.60935e-04 Mem R(MA/MR): 22948 (21200/36094) [2025-04-29 05:39:52,311 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3544 loss_mask: 0.0388 loss_dice: 2.1060 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8351 loss: 5.4426 [2025-04-29 05:39:52,416 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 05:39:54,611 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.9260 Process Time: 0.272 Mem R(MA/MR): 3914 (21200/36094) [2025-04-29 05:39:56,347 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.5957 Process Time: 0.656 Mem R(MA/MR): 6650 (21200/36094) [2025-04-29 05:39:58,000 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1409 Process Time: 0.557 Mem R(MA/MR): 9204 (21200/36094) [2025-04-29 05:40:06,412 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4306 Process Time: 1.486 Mem R(MA/MR): 19652 (21200/36094) [2025-04-29 05:40:07,354 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5906 Process Time: 0.317 Mem R(MA/MR): 6484 (21200/36094) [2025-04-29 05:40:08,829 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.3144 Process Time: 0.438 Mem R(MA/MR): 10804 (21200/36094) [2025-04-29 05:40:09,844 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8223 Process Time: 0.431 Mem R(MA/MR): 5864 (21200/36094) [2025-04-29 05:40:10,437 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5115 Process Time: 0.237 Mem R(MA/MR): 3966 (21200/36094) [2025-04-29 05:40:11,302 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0541 Process Time: 0.217 Mem R(MA/MR): 10896 (21200/36094) [2025-04-29 05:40:12,771 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5414 Process Time: 0.374 Mem R(MA/MR): 8946 (21200/36094) [2025-04-29 05:40:15,673 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.3076 Process Time: 0.631 Mem R(MA/MR): 18414 (21200/36094) [2025-04-29 05:40:18,105 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3883 Process Time: 0.358 Mem R(MA/MR): 14858 (21200/36094) [2025-04-29 05:40:19,089 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.0996 Process Time: 0.203 Mem R(MA/MR): 8280 (21200/36094) [2025-04-29 05:40:19,419 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.4771 Process Time: 0.137 Mem R(MA/MR): 4286 (21200/36094) [2025-04-29 05:40:22,752 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.2567 Process Time: 0.829 Mem R(MA/MR): 16124 (21200/36094) [2025-04-29 05:40:24,773 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6954 Process Time: 0.420 Mem R(MA/MR): 14148 (21200/36094) [2025-04-29 05:40:25,681 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.5755 Process Time: 0.317 Mem R(MA/MR): 6272 (21200/36094) [2025-04-29 05:40:26,514 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0021 Process Time: 0.207 Mem R(MA/MR): 7672 (21200/36094) [2025-04-29 05:40:28,060 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0937 Process Time: 0.312 Mem R(MA/MR): 5816 (21200/36094) [2025-04-29 05:40:29,580 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.9959 Process Time: 0.269 Mem R(MA/MR): 10762 (21200/36094) [2025-04-29 05:40:38,654 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.5779 Process Time: 0.851 Mem R(MA/MR): 23324 (21200/36094) [2025-04-29 05:40:39,365 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.0411 Process Time: 0.203 Mem R(MA/MR): 6418 (21200/36094) [2025-04-29 05:40:48,223 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.2479 Process Time: 0.466 Mem R(MA/MR): 9578 (21200/36094) [2025-04-29 05:40:49,107 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7495 Process Time: 0.357 Mem R(MA/MR): 4922 (21200/36094) [2025-04-29 05:40:50,113 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0610 Process Time: 0.288 Mem R(MA/MR): 8640 (21200/36094) [2025-04-29 05:40:57,291 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.6803 Process Time: 1.252 Mem R(MA/MR): 31302 (21200/36094) [2025-04-29 05:40:59,608 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.9433 Process Time: 0.323 Mem R(MA/MR): 9370 (21200/36094) [2025-04-29 05:41:00,856 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.3118 Process Time: 0.344 Mem R(MA/MR): 8352 (21200/36094) [2025-04-29 05:41:05,406 INFO hook.py line 449 1619929] Test: [29/50] Loss 4.9078 Process Time: 0.398 Mem R(MA/MR): 16574 (21200/36094) [2025-04-29 05:41:06,379 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2455 Process Time: 0.245 Mem R(MA/MR): 7312 (21200/36094) [2025-04-29 05:41:09,809 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.3912 Process Time: 0.438 Mem R(MA/MR): 20278 (21200/36094) [2025-04-29 05:41:10,073 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.6930 Process Time: 0.123 Mem R(MA/MR): 3574 (21200/36094) [2025-04-29 05:41:14,797 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.7535 Process Time: 0.961 Mem R(MA/MR): 24272 (21200/36094) [2025-04-29 05:41:16,052 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6859 Process Time: 0.441 Mem R(MA/MR): 9268 (21200/36094) [2025-04-29 05:41:17,853 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.1984 Process Time: 0.321 Mem R(MA/MR): 13508 (21200/36094) [2025-04-29 05:41:18,446 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8055 Process Time: 0.210 Mem R(MA/MR): 6172 (21200/36094) [2025-04-29 05:41:22,677 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5501 Process Time: 0.982 Mem R(MA/MR): 27904 (21200/36094) [2025-04-29 05:41:24,069 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.8952 Process Time: 0.252 Mem R(MA/MR): 10096 (21200/36094) [2025-04-29 05:41:24,639 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9729 Process Time: 0.201 Mem R(MA/MR): 5072 (21200/36094) [2025-04-29 05:41:25,848 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.2409 Process Time: 0.301 Mem R(MA/MR): 9688 (21200/36094) [2025-04-29 05:41:27,208 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0078 Process Time: 0.482 Mem R(MA/MR): 8522 (21200/36094) [2025-04-29 05:41:27,863 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2165 Process Time: 0.263 Mem R(MA/MR): 5044 (21200/36094) [2025-04-29 05:41:28,716 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8001 Process Time: 0.337 Mem R(MA/MR): 5106 (21200/36094) [2025-04-29 05:41:29,406 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.4963 Process Time: 0.232 Mem R(MA/MR): 6664 (21200/36094) [2025-04-29 05:41:30,031 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0422 Process Time: 0.147 Mem R(MA/MR): 4828 (21200/36094) [2025-04-29 05:41:32,826 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.0485 Process Time: 0.652 Mem R(MA/MR): 13998 (21200/36094) [2025-04-29 05:41:40,227 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.5634 Process Time: 0.571 Mem R(MA/MR): 20050 (21200/36094) [2025-04-29 05:41:51,601 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2181 Process Time: 1.754 Mem R(MA/MR): 35530 (21200/36094) [2025-04-29 05:41:52,711 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.4886 Process Time: 0.420 Mem R(MA/MR): 5248 (21200/36094) [2025-04-29 05:41:54,900 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1117 Process Time: 0.378 Mem R(MA/MR): 13164 (21200/36094) [2025-04-29 05:41:59,180 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 05:41:59,180 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 05:41:59,180 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] table : 0.254 0.561 0.757 0.787 0.625 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] door : 0.397 0.702 0.879 0.814 0.722 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] ceiling lamp : 0.527 0.742 0.859 0.894 0.696 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] cabinet : 0.313 0.448 0.513 0.545 0.448 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] blinds : 0.515 0.803 0.832 0.864 0.826 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] curtain : 0.255 0.388 0.639 0.625 0.417 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] chair : 0.611 0.750 0.813 0.807 0.684 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] storage cabinet: 0.160 0.403 0.602 0.421 0.640 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] office chair : 0.580 0.617 0.630 0.691 0.792 [2025-04-29 05:41:59,180 INFO hook.py line 395 1619929] bookshelf : 0.278 0.707 0.723 0.875 0.636 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] whiteboard : 0.506 0.698 0.831 0.765 0.743 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] window : 0.107 0.225 0.605 0.388 0.341 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] box : 0.188 0.349 0.518 0.632 0.331 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] monitor : 0.585 0.714 0.753 0.940 0.671 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] shelf : 0.167 0.326 0.521 0.900 0.300 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] heater : 0.385 0.693 0.862 0.897 0.684 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] kitchen cabinet: 0.218 0.507 0.727 0.636 0.560 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] sofa : 0.311 0.498 0.731 0.778 0.583 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] bed : 0.136 0.368 0.685 0.571 0.500 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] trash can : 0.552 0.702 0.751 0.842 0.738 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] book : 0.017 0.028 0.070 0.163 0.086 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] plant : 0.477 0.662 0.714 0.923 0.667 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] blanket : 0.362 0.593 0.691 1.000 0.545 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] tv : 0.860 1.000 1.000 1.000 1.000 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] computer tower : 0.209 0.355 0.539 0.640 0.381 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] refrigerator : 0.187 0.370 0.379 1.000 0.333 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] jacket : 0.059 0.201 0.332 0.455 0.455 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] sink : 0.412 0.691 0.869 0.895 0.773 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] bag : 0.035 0.075 0.089 0.222 0.296 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] picture : 0.139 0.275 0.376 0.441 0.385 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] pillow : 0.631 0.957 0.957 0.944 0.895 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] towel : 0.198 0.363 0.500 0.667 0.368 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] suitcase : 0.334 0.371 0.371 0.667 0.571 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] backpack : 0.488 0.597 0.597 0.727 0.615 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] crate : 0.056 0.209 0.450 0.500 0.364 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] keyboard : 0.374 0.558 0.708 0.767 0.590 [2025-04-29 05:41:59,181 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] toilet : 0.837 1.000 1.000 1.000 1.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] printer : 0.360 0.554 0.582 0.467 0.778 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.083 0.125 1.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] microwave : 0.615 0.875 0.875 1.000 0.875 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] shoes : 0.107 0.210 0.555 0.536 0.366 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] socket : 0.165 0.436 0.646 0.667 0.457 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] bottle : 0.088 0.196 0.315 0.462 0.217 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] bucket : 0.094 0.095 0.096 0.400 0.286 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] cushion : 0.008 0.038 0.207 0.200 0.333 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] telephone : 0.325 0.606 0.737 1.000 0.529 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] laptop : 0.442 0.730 0.832 0.750 0.750 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] plant pot : 0.122 0.363 0.437 0.667 0.375 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] exhaust fan : 0.092 0.181 0.181 0.750 0.200 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] cup : 0.239 0.408 0.467 1.000 0.386 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] coat hanger : 0.178 0.500 0.500 1.000 0.500 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] light switch : 0.237 0.484 0.620 0.814 0.538 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] speaker : 0.274 0.328 0.361 1.000 0.273 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] kettle : 0.222 0.333 0.333 1.000 0.333 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] smoke detector : 0.651 0.821 0.821 0.909 0.833 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] power strip : 0.147 0.270 0.297 0.444 0.400 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] paper bag : 0.094 0.100 0.100 0.200 1.000 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] mouse : 0.332 0.520 0.690 0.950 0.594 [2025-04-29 05:41:59,182 INFO hook.py line 395 1619929] cutting board : 0.329 0.750 0.750 1.000 0.750 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] toilet paper : 0.192 0.400 0.452 0.857 0.353 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] paper towel : 0.056 0.125 0.166 1.000 0.125 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] pot : 0.123 0.167 0.167 0.333 1.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] clock : 0.593 1.000 1.000 1.000 1.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] pan : 0.194 0.250 0.500 1.000 0.250 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] tap : 0.299 0.487 0.668 0.714 0.556 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] soap dispenser : 0.459 0.638 0.645 1.000 0.600 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.172 0.000 0.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] whiteboard eraser: 0.173 0.436 0.451 0.625 0.833 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] toilet brush : 0.280 0.372 0.833 0.500 0.500 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] stapler : 0.004 0.033 0.250 0.200 0.333 [2025-04-29 05:41:59,183 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 05:41:59,183 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 05:41:59,183 INFO hook.py line 404 1619929] average : 0.256 0.406 0.502 0.625 0.483 [2025-04-29 05:41:59,183 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 05:41:59,184 INFO hook.py line 480 1619929] Total Process Time: 22.864 s [2025-04-29 05:41:59,184 INFO hook.py line 481 1619929] Average Process Time: 461.063 ms [2025-04-29 05:41:59,184 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 05:41:59,232 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 05:41:59,238 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:43:35,377 INFO hook.py line 650 1619929] Train: [257/512][50/242] Data 0.015 (0.017) Batch 1.419 (1.490) Remain 25:37:40 loss: 5.8200 Lr: 1.60720e-04 Mem R(MA/MR): 18860 (21200/36094) [2025-04-29 05:44:47,819 INFO hook.py line 650 1619929] Train: [257/512][100/242] Data 0.018 (0.028) Batch 1.476 (1.469) Remain 25:14:17 loss: 6.8487 Lr: 1.60604e-04 Mem R(MA/MR): 19628 (21200/36094) [2025-04-29 05:46:00,578 INFO hook.py line 650 1619929] Train: [257/512][150/242] Data 0.017 (0.024) Batch 1.363 (1.464) Remain 25:08:15 loss: 6.5334 Lr: 1.60487e-04 Mem R(MA/MR): 22988 (21200/36094) [2025-04-29 05:47:12,244 INFO hook.py line 650 1619929] Train: [257/512][200/242] Data 0.014 (0.022) Batch 1.462 (1.456) Remain 24:58:57 loss: 5.7599 Lr: 1.60370e-04 Mem R(MA/MR): 24906 (21200/36094) [2025-04-29 05:48:09,265 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3546 loss_mask: 0.0383 loss_dice: 2.0924 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8363 loss: 5.4167 [2025-04-29 05:48:09,692 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:49:44,218 INFO hook.py line 650 1619929] Train: [258/512][50/242] Data 0.016 (0.017) Batch 1.391 (1.477) Remain 25:18:22 loss: 6.3365 Lr: 1.60155e-04 Mem R(MA/MR): 18660 (21200/36094) [2025-04-29 05:50:52,930 INFO hook.py line 650 1619929] Train: [258/512][100/242] Data 0.017 (0.017) Batch 1.391 (1.424) Remain 24:22:29 loss: 5.5975 Lr: 1.60038e-04 Mem R(MA/MR): 22710 (21200/36094) [2025-04-29 05:52:05,332 INFO hook.py line 650 1619929] Train: [258/512][150/242] Data 0.017 (0.017) Batch 1.496 (1.432) Remain 24:29:35 loss: 6.2589 Lr: 1.59921e-04 Mem R(MA/MR): 22712 (21200/36094) [2025-04-29 05:53:13,796 INFO hook.py line 650 1619929] Train: [258/512][200/242] Data 0.015 (0.016) Batch 1.270 (1.416) Remain 24:11:59 loss: 5.7650 Lr: 1.59805e-04 Mem R(MA/MR): 22734 (21200/36094) [2025-04-29 05:54:10,559 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3552 loss_mask: 0.0388 loss_dice: 2.1059 loss_score: 0.0000 loss_bbox: 0.0524 loss_sp_cls: 0.8419 loss: 5.4414 [2025-04-29 05:54:14,312 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 05:55:50,336 INFO hook.py line 650 1619929] Train: [259/512][50/242] Data 0.015 (0.017) Batch 1.404 (1.495) Remain 25:29:58 loss: 4.9526 Lr: 1.59590e-04 Mem R(MA/MR): 22240 (21200/36094) [2025-04-29 05:57:03,107 INFO hook.py line 650 1619929] Train: [259/512][100/242] Data 0.018 (0.017) Batch 1.468 (1.474) Remain 25:08:02 loss: 4.9535 Lr: 1.59473e-04 Mem R(MA/MR): 22240 (21200/36094) [2025-04-29 05:58:13,736 INFO hook.py line 650 1619929] Train: [259/512][150/242] Data 0.017 (0.017) Batch 1.353 (1.453) Remain 24:45:18 loss: 5.2858 Lr: 1.59356e-04 Mem R(MA/MR): 24114 (21200/36094) [2025-04-29 05:59:24,937 INFO hook.py line 650 1619929] Train: [259/512][200/242] Data 0.015 (0.017) Batch 1.225 (1.446) Remain 24:36:29 loss: 4.0831 Lr: 1.59239e-04 Mem R(MA/MR): 26440 (21200/36094) [2025-04-29 06:00:20,605 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3538 loss_mask: 0.0387 loss_dice: 2.1058 loss_score: 0.0000 loss_bbox: 0.0526 loss_sp_cls: 0.8368 loss: 5.4374 [2025-04-29 06:00:22,467 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:01:57,693 INFO hook.py line 650 1619929] Train: [260/512][50/242] Data 0.016 (0.017) Batch 1.358 (1.465) Remain 24:54:04 loss: 4.3168 Lr: 1.59024e-04 Mem R(MA/MR): 23494 (21200/36094) [2025-04-29 06:03:10,608 INFO hook.py line 650 1619929] Train: [260/512][100/242] Data 0.018 (0.017) Batch 1.326 (1.462) Remain 24:49:08 loss: 5.1045 Lr: 1.58907e-04 Mem R(MA/MR): 23494 (21200/36094) [2025-04-29 06:04:21,898 INFO hook.py line 650 1619929] Train: [260/512][150/242] Data 0.016 (0.016) Batch 1.561 (1.450) Remain 24:35:29 loss: 6.8553 Lr: 1.58790e-04 Mem R(MA/MR): 23494 (21200/36094) [2025-04-29 06:05:32,589 INFO hook.py line 650 1619929] Train: [260/512][200/242] Data 0.014 (0.017) Batch 1.413 (1.440) Remain 24:25:05 loss: 6.4428 Lr: 1.58675e-04 Mem R(MA/MR): 23494 (21200/36094) [2025-04-29 06:06:29,170 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3420 loss_mask: 0.0377 loss_dice: 2.0590 loss_score: 0.0000 loss_bbox: 0.0517 loss_sp_cls: 0.8312 loss: 5.3203 [2025-04-29 06:06:30,908 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:08:05,790 INFO hook.py line 650 1619929] Train: [261/512][50/242] Data 0.019 (0.016) Batch 1.430 (1.458) Remain 24:40:37 loss: 5.5693 Lr: 1.58460e-04 Mem R(MA/MR): 21438 (21200/36094) [2025-04-29 06:09:18,910 INFO hook.py line 650 1619929] Train: [261/512][100/242] Data 0.017 (0.017) Batch 1.432 (1.460) Remain 24:41:48 loss: 6.3972 Lr: 1.58343e-04 Mem R(MA/MR): 21438 (21200/36094) [2025-04-29 06:10:34,855 INFO hook.py line 650 1619929] Train: [261/512][150/242] Data 0.017 (0.017) Batch 1.603 (1.480) Remain 25:00:47 loss: 6.0574 Lr: 1.58226e-04 Mem R(MA/MR): 25742 (21200/36094) [2025-04-29 06:11:48,940 INFO hook.py line 650 1619929] Train: [261/512][200/242] Data 0.015 (0.017) Batch 1.454 (1.481) Remain 24:59:57 loss: 5.5261 Lr: 1.58109e-04 Mem R(MA/MR): 25742 (21200/36094) [2025-04-29 06:12:47,502 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3491 loss_mask: 0.0387 loss_dice: 2.0852 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8278 loss: 5.3921 [2025-04-29 06:12:53,064 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:14:30,342 INFO hook.py line 650 1619929] Train: [262/512][50/242] Data 0.018 (0.016) Batch 1.283 (1.490) Remain 25:06:51 loss: 3.5038 Lr: 1.57894e-04 Mem R(MA/MR): 19690 (21200/36094) [2025-04-29 06:15:42,289 INFO hook.py line 650 1619929] Train: [262/512][100/242] Data 0.016 (0.016) Batch 1.555 (1.464) Remain 24:39:10 loss: 6.0642 Lr: 1.57777e-04 Mem R(MA/MR): 21534 (21200/36094) [2025-04-29 06:16:55,928 INFO hook.py line 650 1619929] Train: [262/512][150/242] Data 0.016 (0.017) Batch 1.382 (1.467) Remain 24:41:09 loss: 4.4816 Lr: 1.57660e-04 Mem R(MA/MR): 21534 (21200/36094) [2025-04-29 06:18:06,746 INFO hook.py line 650 1619929] Train: [262/512][200/242] Data 0.015 (0.016) Batch 1.444 (1.454) Remain 24:27:02 loss: 4.0347 Lr: 1.57543e-04 Mem R(MA/MR): 23784 (21200/36094) [2025-04-29 06:19:06,433 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3495 loss_mask: 0.0392 loss_dice: 2.1025 loss_score: 0.0000 loss_bbox: 0.0526 loss_sp_cls: 0.8347 loss: 5.4197 [2025-04-29 06:19:07,508 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:20:45,329 INFO hook.py line 650 1619929] Train: [263/512][50/242] Data 0.016 (0.016) Batch 1.290 (1.437) Remain 24:07:30 loss: 4.4620 Lr: 1.57328e-04 Mem R(MA/MR): 20682 (21200/36094) [2025-04-29 06:21:59,092 INFO hook.py line 650 1619929] Train: [263/512][100/242] Data 0.017 (0.017) Batch 1.478 (1.457) Remain 24:26:18 loss: 6.5149 Lr: 1.57211e-04 Mem R(MA/MR): 22250 (21200/36094) [2025-04-29 06:23:10,982 INFO hook.py line 650 1619929] Train: [263/512][150/242] Data 0.015 (0.017) Batch 1.306 (1.450) Remain 24:18:39 loss: 4.4542 Lr: 1.57093e-04 Mem R(MA/MR): 24774 (21200/36094) [2025-04-29 06:24:25,922 INFO hook.py line 650 1619929] Train: [263/512][200/242] Data 0.014 (0.017) Batch 1.431 (1.463) Remain 24:29:51 loss: 5.4516 Lr: 1.56976e-04 Mem R(MA/MR): 24778 (21200/36094) [2025-04-29 06:25:21,581 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3442 loss_mask: 0.0386 loss_dice: 2.0863 loss_score: 0.0000 loss_bbox: 0.0519 loss_sp_cls: 0.8300 loss: 5.3716 [2025-04-29 06:25:25,623 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:27:03,311 INFO hook.py line 650 1619929] Train: [264/512][50/242] Data 0.016 (0.017) Batch 1.443 (1.503) Remain 25:08:29 loss: 7.1396 Lr: 1.56761e-04 Mem R(MA/MR): 20380 (21200/36094) [2025-04-29 06:28:15,787 INFO hook.py line 650 1619929] Train: [264/512][100/242] Data 0.016 (0.017) Batch 1.554 (1.476) Remain 24:39:26 loss: 6.0300 Lr: 1.56644e-04 Mem R(MA/MR): 20412 (21200/36094) [2025-04-29 06:29:27,789 INFO hook.py line 650 1619929] Train: [264/512][150/242] Data 0.017 (0.017) Batch 1.375 (1.463) Remain 24:26:06 loss: 4.1328 Lr: 1.56527e-04 Mem R(MA/MR): 22358 (21200/36094) [2025-04-29 06:30:40,537 INFO hook.py line 650 1619929] Train: [264/512][200/242] Data 0.016 (0.017) Batch 1.473 (1.461) Remain 24:22:43 loss: 4.8180 Lr: 1.56410e-04 Mem R(MA/MR): 22358 (21200/36094) [2025-04-29 06:31:39,473 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3486 loss_mask: 0.0389 loss_dice: 2.0777 loss_score: 0.0000 loss_bbox: 0.0519 loss_sp_cls: 0.8278 loss: 5.3783 [2025-04-29 06:31:44,200 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 06:31:46,614 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2580 Process Time: 0.306 Mem R(MA/MR): 4120 (21200/36094) [2025-04-29 06:31:48,179 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.4416 Process Time: 0.505 Mem R(MA/MR): 7000 (21200/36094) [2025-04-29 06:31:49,764 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3134 Process Time: 0.503 Mem R(MA/MR): 9408 (21200/36094) [2025-04-29 06:31:57,594 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.6354 Process Time: 1.567 Mem R(MA/MR): 19572 (21200/36094) [2025-04-29 06:31:58,818 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3885 Process Time: 0.522 Mem R(MA/MR): 6824 (21200/36094) [2025-04-29 06:32:00,418 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8035 Process Time: 0.519 Mem R(MA/MR): 11038 (21200/36094) [2025-04-29 06:32:01,502 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.9311 Process Time: 0.540 Mem R(MA/MR): 6098 (21200/36094) [2025-04-29 06:32:02,038 INFO hook.py line 449 1619929] Test: [8/50] Loss 6.1095 Process Time: 0.165 Mem R(MA/MR): 4152 (21200/36094) [2025-04-29 06:32:03,029 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0200 Process Time: 0.227 Mem R(MA/MR): 11146 (21200/36094) [2025-04-29 06:32:04,804 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6622 Process Time: 0.298 Mem R(MA/MR): 9250 (21200/36094) [2025-04-29 06:32:07,857 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.3741 Process Time: 0.563 Mem R(MA/MR): 18718 (21200/36094) [2025-04-29 06:32:10,916 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2768 Process Time: 0.557 Mem R(MA/MR): 15262 (21200/36094) [2025-04-29 06:32:12,098 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2494 Process Time: 0.277 Mem R(MA/MR): 8498 (21200/36094) [2025-04-29 06:32:12,657 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1337 Process Time: 0.224 Mem R(MA/MR): 4514 (21200/36094) [2025-04-29 06:32:15,092 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.9828 Process Time: 0.333 Mem R(MA/MR): 16482 (21200/36094) [2025-04-29 06:32:17,682 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.5112 Process Time: 0.948 Mem R(MA/MR): 14518 (21200/36094) [2025-04-29 06:32:19,074 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.0753 Process Time: 0.546 Mem R(MA/MR): 6494 (21200/36094) [2025-04-29 06:32:20,088 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.8226 Process Time: 0.272 Mem R(MA/MR): 7964 (21200/36094) [2025-04-29 06:32:21,379 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.7326 Process Time: 0.188 Mem R(MA/MR): 5966 (21200/36094) [2025-04-29 06:32:23,250 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.5536 Process Time: 0.313 Mem R(MA/MR): 11314 (21200/36094) [2025-04-29 06:32:32,121 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.6143 Process Time: 0.704 Mem R(MA/MR): 23664 (21200/36094) [2025-04-29 06:32:32,939 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3262 Process Time: 0.322 Mem R(MA/MR): 6634 (21200/36094) [2025-04-29 06:32:43,018 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.4060 Process Time: 0.416 Mem R(MA/MR): 8124 (21200/36094) [2025-04-29 06:32:43,917 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7413 Process Time: 0.425 Mem R(MA/MR): 5092 (21200/36094) [2025-04-29 06:32:45,231 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0236 Process Time: 0.546 Mem R(MA/MR): 9114 (21200/36094) [2025-04-29 06:32:53,170 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.2097 Process Time: 1.734 Mem R(MA/MR): 31768 (21200/36094) [2025-04-29 06:32:56,656 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.8136 Process Time: 0.777 Mem R(MA/MR): 9766 (21200/36094) [2025-04-29 06:32:57,822 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.3449 Process Time: 0.221 Mem R(MA/MR): 8612 (21200/36094) [2025-04-29 06:33:03,553 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.9214 Process Time: 0.435 Mem R(MA/MR): 16986 (21200/36094) [2025-04-29 06:33:04,772 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2229 Process Time: 0.367 Mem R(MA/MR): 7514 (21200/36094) [2025-04-29 06:33:08,542 INFO hook.py line 449 1619929] Test: [31/50] Loss 9.7466 Process Time: 0.455 Mem R(MA/MR): 20586 (21200/36094) [2025-04-29 06:33:08,817 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.5109 Process Time: 0.130 Mem R(MA/MR): 3786 (21200/36094) [2025-04-29 06:33:12,761 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.6335 Process Time: 0.486 Mem R(MA/MR): 24566 (21200/36094) [2025-04-29 06:33:14,048 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7677 Process Time: 0.469 Mem R(MA/MR): 9628 (21200/36094) [2025-04-29 06:33:15,849 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.9149 Process Time: 0.424 Mem R(MA/MR): 13882 (21200/36094) [2025-04-29 06:33:16,309 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1066 Process Time: 0.152 Mem R(MA/MR): 6382 (21200/36094) [2025-04-29 06:33:20,127 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.6371 Process Time: 0.931 Mem R(MA/MR): 28412 (21200/36094) [2025-04-29 06:33:22,413 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.8913 Process Time: 0.646 Mem R(MA/MR): 10456 (21200/36094) [2025-04-29 06:33:22,978 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1801 Process Time: 0.194 Mem R(MA/MR): 5224 (21200/36094) [2025-04-29 06:33:24,331 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7312 Process Time: 0.355 Mem R(MA/MR): 10044 (21200/36094) [2025-04-29 06:33:25,445 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.8945 Process Time: 0.296 Mem R(MA/MR): 8750 (21200/36094) [2025-04-29 06:33:26,032 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.5863 Process Time: 0.182 Mem R(MA/MR): 5276 (21200/36094) [2025-04-29 06:33:26,492 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.2319 Process Time: 0.143 Mem R(MA/MR): 5336 (21200/36094) [2025-04-29 06:33:27,216 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.0326 Process Time: 0.237 Mem R(MA/MR): 6836 (21200/36094) [2025-04-29 06:33:28,104 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7938 Process Time: 0.339 Mem R(MA/MR): 5060 (21200/36094) [2025-04-29 06:33:30,951 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.9919 Process Time: 0.584 Mem R(MA/MR): 14414 (21200/36094) [2025-04-29 06:33:38,395 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.4518 Process Time: 0.681 Mem R(MA/MR): 20388 (21200/36094) [2025-04-29 06:33:49,463 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.7942 Process Time: 2.345 Mem R(MA/MR): 35824 (21200/36094) [2025-04-29 06:33:50,373 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.8915 Process Time: 0.214 Mem R(MA/MR): 5496 (21200/36094) [2025-04-29 06:33:53,262 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0123 Process Time: 0.715 Mem R(MA/MR): 13528 (21200/36094) [2025-04-29 06:33:58,017 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 06:33:58,017 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 06:33:58,017 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] table : 0.250 0.523 0.754 0.733 0.566 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] door : 0.399 0.748 0.907 0.919 0.722 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] ceiling lamp : 0.575 0.754 0.859 0.876 0.702 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] cabinet : 0.305 0.446 0.492 0.612 0.448 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] blinds : 0.471 0.705 0.852 0.833 0.652 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] curtain : 0.361 0.480 0.659 0.500 0.667 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] chair : 0.618 0.764 0.811 0.733 0.775 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] storage cabinet: 0.174 0.297 0.350 0.406 0.520 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] office chair : 0.530 0.552 0.596 0.673 0.771 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] bookshelf : 0.290 0.628 0.642 0.600 0.818 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] whiteboard : 0.518 0.743 0.770 0.778 0.800 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] window : 0.153 0.329 0.619 0.535 0.418 [2025-04-29 06:33:58,017 INFO hook.py line 395 1619929] box : 0.189 0.330 0.536 0.504 0.376 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] monitor : 0.594 0.712 0.793 0.907 0.700 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] shelf : 0.047 0.113 0.325 0.370 0.333 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] heater : 0.386 0.591 0.779 0.828 0.632 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] kitchen cabinet: 0.142 0.303 0.609 0.500 0.480 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] sofa : 0.447 0.558 0.919 0.615 0.667 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] bed : 0.218 0.731 0.858 0.857 0.750 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] trash can : 0.508 0.641 0.693 0.727 0.738 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] book : 0.015 0.029 0.073 0.189 0.090 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] plant : 0.400 0.747 0.772 0.929 0.722 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] blanket : 0.448 0.635 0.680 0.750 0.545 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] tv : 0.851 0.974 0.974 0.857 1.000 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] computer tower : 0.217 0.359 0.580 0.543 0.452 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] refrigerator : 0.079 0.176 0.176 0.600 0.333 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] jacket : 0.049 0.111 0.421 0.263 0.455 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] sink : 0.318 0.589 0.750 0.833 0.682 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] bag : 0.128 0.176 0.278 0.750 0.222 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] picture : 0.159 0.336 0.412 0.812 0.333 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] pillow : 0.640 0.852 0.852 0.696 0.842 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] towel : 0.222 0.391 0.533 0.571 0.421 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] suitcase : 0.418 0.539 0.539 0.800 0.571 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] backpack : 0.268 0.344 0.373 0.545 0.462 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] crate : 0.043 0.165 0.393 0.571 0.364 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] keyboard : 0.441 0.612 0.698 0.955 0.538 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] toilet : 0.788 0.876 1.000 0.889 0.889 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] printer : 0.265 0.510 0.510 0.833 0.556 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.003 0.036 0.111 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,018 INFO hook.py line 395 1619929] microwave : 0.469 0.750 0.875 1.000 0.750 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] shoes : 0.072 0.141 0.576 0.429 0.293 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] socket : 0.171 0.412 0.642 0.569 0.500 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] bottle : 0.097 0.171 0.339 0.487 0.229 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] bucket : 0.229 0.232 0.232 0.227 0.714 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] cushion : 0.070 0.078 0.200 0.231 0.500 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] telephone : 0.278 0.526 0.578 1.000 0.471 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] laptop : 0.294 0.547 0.547 0.625 0.625 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] plant pot : 0.077 0.243 0.401 0.600 0.375 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] exhaust fan : 0.151 0.268 0.315 0.750 0.400 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] cup : 0.251 0.356 0.388 0.938 0.341 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] coat hanger : 0.028 0.031 0.750 0.250 0.250 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] light switch : 0.252 0.502 0.701 0.833 0.462 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] speaker : 0.230 0.304 0.358 0.667 0.364 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] kettle : 0.185 0.221 0.356 0.400 0.333 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] smoke detector : 0.565 0.756 0.771 0.818 0.750 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] power strip : 0.105 0.161 0.314 0.364 0.400 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] paper bag : 0.125 0.125 0.125 0.250 1.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] mouse : 0.440 0.695 0.773 0.758 0.781 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] toilet paper : 0.278 0.412 0.447 1.000 0.412 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] pot : 0.121 0.167 0.167 0.333 1.000 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] clock : 0.420 0.528 0.528 0.667 0.667 [2025-04-29 06:33:58,019 INFO hook.py line 395 1619929] pan : 0.139 0.250 0.250 1.000 0.250 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] tap : 0.148 0.343 0.629 0.571 0.444 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] soap dispenser : 0.391 0.623 0.636 1.000 0.600 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] bowl : 0.148 0.333 0.333 1.000 0.333 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] whiteboard eraser: 0.180 0.415 0.417 0.800 0.667 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] toilet brush : 0.531 0.738 0.920 1.000 0.667 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] spray bottle : 0.021 0.031 0.042 0.250 0.250 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] headphones : 0.325 0.662 0.662 1.000 0.500 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] stapler : 0.003 0.028 0.137 0.167 0.333 [2025-04-29 06:33:58,020 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 06:33:58,020 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 06:33:58,020 INFO hook.py line 404 1619929] average : 0.248 0.380 0.476 0.584 0.470 [2025-04-29 06:33:58,020 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 06:33:58,020 INFO hook.py line 480 1619929] Total Process Time: 25.298 s [2025-04-29 06:33:58,021 INFO hook.py line 481 1619929] Average Process Time: 510.051 ms [2025-04-29 06:33:58,021 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 06:33:58,067 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 06:33:58,073 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:35:38,508 INFO hook.py line 650 1619929] Train: [265/512][50/242] Data 0.017 (0.039) Batch 1.444 (1.527) Remain 25:26:31 loss: 6.6441 Lr: 1.56194e-04 Mem R(MA/MR): 20138 (21200/36094) [2025-04-29 06:36:51,084 INFO hook.py line 650 1619929] Train: [265/512][100/242] Data 0.015 (0.027) Batch 1.588 (1.488) Remain 24:46:12 loss: 5.7700 Lr: 1.56077e-04 Mem R(MA/MR): 23738 (21200/36094) [2025-04-29 06:38:06,241 INFO hook.py line 650 1619929] Train: [265/512][150/242] Data 0.017 (0.024) Batch 1.541 (1.493) Remain 24:50:00 loss: 4.9408 Lr: 1.55960e-04 Mem R(MA/MR): 23738 (21200/36094) [2025-04-29 06:39:19,906 INFO hook.py line 650 1619929] Train: [265/512][200/242] Data 0.015 (0.022) Batch 1.428 (1.488) Remain 24:43:41 loss: 5.3154 Lr: 1.55843e-04 Mem R(MA/MR): 25790 (21200/36094) [2025-04-29 06:40:17,639 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3440 loss_mask: 0.0383 loss_dice: 2.0722 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8196 loss: 5.3518 [2025-04-29 06:40:18,538 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:42:01,195 INFO hook.py line 650 1619929] Train: [266/512][50/242] Data 0.016 (0.016) Batch 1.421 (1.505) Remain 24:57:47 loss: 4.9091 Lr: 1.55627e-04 Mem R(MA/MR): 21078 (21200/36094) [2025-04-29 06:43:12,894 INFO hook.py line 650 1619929] Train: [266/512][100/242] Data 0.016 (0.016) Batch 1.372 (1.468) Remain 24:20:16 loss: 5.5003 Lr: 1.55510e-04 Mem R(MA/MR): 24696 (21200/36094) [2025-04-29 06:44:23,708 INFO hook.py line 650 1619929] Train: [266/512][150/242] Data 0.016 (0.016) Batch 1.283 (1.451) Remain 24:01:29 loss: 4.8915 Lr: 1.55392e-04 Mem R(MA/MR): 24696 (21200/36094) [2025-04-29 06:45:37,019 INFO hook.py line 650 1619929] Train: [266/512][200/242] Data 0.014 (0.017) Batch 1.337 (1.455) Remain 24:04:13 loss: 5.2008 Lr: 1.55275e-04 Mem R(MA/MR): 24700 (21200/36094) [2025-04-29 06:46:35,387 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3443 loss_mask: 0.0378 loss_dice: 2.0634 loss_score: 0.0000 loss_bbox: 0.0516 loss_sp_cls: 0.8240 loss: 5.3345 [2025-04-29 06:46:38,702 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:48:17,369 INFO hook.py line 650 1619929] Train: [267/512][50/242] Data 0.016 (0.016) Batch 1.473 (1.519) Remain 25:05:24 loss: 5.1005 Lr: 1.55060e-04 Mem R(MA/MR): 22400 (21200/36094) [2025-04-29 06:49:31,194 INFO hook.py line 650 1619929] Train: [267/512][100/242] Data 0.016 (0.016) Batch 1.465 (1.497) Remain 24:42:41 loss: 5.6916 Lr: 1.54942e-04 Mem R(MA/MR): 22428 (21200/36094) [2025-04-29 06:50:45,786 INFO hook.py line 650 1619929] Train: [267/512][150/242] Data 0.018 (0.016) Batch 1.680 (1.495) Remain 24:39:44 loss: 5.6228 Lr: 1.54825e-04 Mem R(MA/MR): 22438 (21200/36094) [2025-04-29 06:51:59,276 INFO hook.py line 650 1619929] Train: [267/512][200/242] Data 0.016 (0.017) Batch 1.240 (1.489) Remain 24:32:08 loss: 5.6763 Lr: 1.54708e-04 Mem R(MA/MR): 22438 (21200/36094) [2025-04-29 06:52:58,142 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3410 loss_mask: 0.0380 loss_dice: 2.0670 loss_score: 0.0000 loss_bbox: 0.0511 loss_sp_cls: 0.8221 loss: 5.3238 [2025-04-29 06:52:59,253 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 06:54:29,247 INFO hook.py line 650 1619929] Train: [268/512][50/242] Data 0.016 (0.017) Batch 1.617 (1.481) Remain 24:22:15 loss: 4.1018 Lr: 1.54492e-04 Mem R(MA/MR): 22266 (21200/36094) [2025-04-29 06:55:42,422 INFO hook.py line 650 1619929] Train: [268/512][100/242] Data 0.015 (0.016) Batch 1.540 (1.472) Remain 24:12:06 loss: 6.2657 Lr: 1.54375e-04 Mem R(MA/MR): 22268 (21200/36094) [2025-04-29 06:56:54,207 INFO hook.py line 650 1619929] Train: [268/512][150/242] Data 0.016 (0.016) Batch 1.493 (1.460) Remain 23:58:42 loss: 5.5111 Lr: 1.54257e-04 Mem R(MA/MR): 22268 (21200/36094) [2025-04-29 06:58:06,666 INFO hook.py line 650 1619929] Train: [268/512][200/242] Data 0.013 (0.016) Batch 1.426 (1.457) Remain 23:54:53 loss: 5.9813 Lr: 1.54140e-04 Mem R(MA/MR): 22272 (21200/36094) [2025-04-29 06:59:02,645 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3423 loss_mask: 0.0380 loss_dice: 2.0794 loss_score: 0.0000 loss_bbox: 0.0511 loss_sp_cls: 0.8206 loss: 5.3458 [2025-04-29 06:59:07,008 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:00:36,551 INFO hook.py line 650 1619929] Train: [269/512][50/242] Data 0.017 (0.016) Batch 1.411 (1.416) Remain 23:12:35 loss: 5.5836 Lr: 1.53924e-04 Mem R(MA/MR): 20068 (21200/36094) [2025-04-29 07:01:49,653 INFO hook.py line 650 1619929] Train: [269/512][100/242] Data 0.016 (0.017) Batch 1.425 (1.440) Remain 23:34:36 loss: 5.4219 Lr: 1.53807e-04 Mem R(MA/MR): 20068 (21200/36094) [2025-04-29 07:03:00,722 INFO hook.py line 650 1619929] Train: [269/512][150/242] Data 0.016 (0.016) Batch 1.378 (1.434) Remain 23:27:14 loss: 5.6084 Lr: 1.53689e-04 Mem R(MA/MR): 23816 (21200/36094) [2025-04-29 07:04:13,146 INFO hook.py line 650 1619929] Train: [269/512][200/242] Data 0.014 (0.016) Batch 1.379 (1.437) Remain 23:29:45 loss: 7.2743 Lr: 1.53572e-04 Mem R(MA/MR): 23816 (21200/36094) [2025-04-29 07:05:11,904 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3310 loss_mask: 0.0369 loss_dice: 2.0166 loss_score: 0.0000 loss_bbox: 0.0505 loss_sp_cls: 0.8117 loss: 5.2111 [2025-04-29 07:05:16,201 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:06:48,354 INFO hook.py line 650 1619929] Train: [270/512][50/242] Data 0.016 (0.016) Batch 1.294 (1.438) Remain 23:28:22 loss: 4.7815 Lr: 1.53356e-04 Mem R(MA/MR): 18606 (21200/36094) [2025-04-29 07:08:00,298 INFO hook.py line 650 1619929] Train: [270/512][100/242] Data 0.017 (0.017) Batch 1.556 (1.439) Remain 23:27:31 loss: 6.9663 Lr: 1.53239e-04 Mem R(MA/MR): 23568 (21200/36094) [2025-04-29 07:09:11,098 INFO hook.py line 650 1619929] Train: [270/512][150/242] Data 0.015 (0.017) Batch 1.445 (1.431) Remain 23:18:49 loss: 5.3380 Lr: 1.53121e-04 Mem R(MA/MR): 23568 (21200/36094) [2025-04-29 07:10:22,448 INFO hook.py line 650 1619929] Train: [270/512][200/242] Data 0.014 (0.016) Batch 1.391 (1.430) Remain 23:16:40 loss: 4.1590 Lr: 1.53004e-04 Mem R(MA/MR): 23568 (21200/36094) [2025-04-29 07:11:20,722 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3201 loss_mask: 0.0363 loss_dice: 1.9951 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.8009 loss: 5.1346 [2025-04-29 07:11:24,320 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:13:00,782 INFO hook.py line 650 1619929] Train: [271/512][50/242] Data 0.015 (0.018) Batch 1.557 (1.498) Remain 24:21:21 loss: 5.4884 Lr: 1.52788e-04 Mem R(MA/MR): 22052 (21200/36094) [2025-04-29 07:14:14,018 INFO hook.py line 650 1619929] Train: [271/512][100/242] Data 0.019 (0.017) Batch 1.553 (1.481) Remain 24:03:08 loss: 5.7167 Lr: 1.52670e-04 Mem R(MA/MR): 22052 (21200/36094) [2025-04-29 07:15:26,775 INFO hook.py line 650 1619929] Train: [271/512][150/242] Data 0.016 (0.017) Batch 1.567 (1.472) Remain 23:53:19 loss: 6.0321 Lr: 1.52555e-04 Mem R(MA/MR): 22052 (21200/36094) [2025-04-29 07:16:36,594 INFO hook.py line 650 1619929] Train: [271/512][200/242] Data 0.014 (0.017) Batch 1.363 (1.453) Remain 23:33:23 loss: 5.0194 Lr: 1.52438e-04 Mem R(MA/MR): 22052 (21200/36094) [2025-04-29 07:17:35,554 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3317 loss_mask: 0.0368 loss_dice: 2.0291 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.8064 loss: 5.2266 [2025-04-29 07:17:35,984 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:19:05,380 INFO hook.py line 650 1619929] Train: [272/512][50/242] Data 0.016 (0.017) Batch 1.290 (1.511) Remain 24:27:36 loss: 5.0050 Lr: 1.52222e-04 Mem R(MA/MR): 20664 (21200/36094) [2025-04-29 07:20:17,495 INFO hook.py line 650 1619929] Train: [272/512][100/242] Data 0.016 (0.016) Batch 1.412 (1.476) Remain 23:51:54 loss: 4.6530 Lr: 1.52104e-04 Mem R(MA/MR): 25510 (21200/36094) [2025-04-29 07:21:29,996 INFO hook.py line 650 1619929] Train: [272/512][150/242] Data 0.015 (0.016) Batch 1.389 (1.467) Remain 23:42:14 loss: 4.9148 Lr: 1.51987e-04 Mem R(MA/MR): 25510 (21200/36094) [2025-04-29 07:22:43,535 INFO hook.py line 650 1619929] Train: [272/512][200/242] Data 0.015 (0.016) Batch 1.334 (1.468) Remain 23:41:57 loss: 3.7739 Lr: 1.51869e-04 Mem R(MA/MR): 28094 (21200/36094) [2025-04-29 07:23:41,734 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3467 loss_mask: 0.0383 loss_dice: 2.0871 loss_score: 0.0000 loss_bbox: 0.0518 loss_sp_cls: 0.8326 loss: 5.3811 [2025-04-29 07:23:44,771 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 07:23:47,001 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2123 Process Time: 0.248 Mem R(MA/MR): 4858 (21200/36094) [2025-04-29 07:23:48,405 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.7733 Process Time: 0.491 Mem R(MA/MR): 7300 (21200/36094) [2025-04-29 07:23:49,768 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.9600 Process Time: 0.470 Mem R(MA/MR): 10084 (21200/36094) [2025-04-29 07:23:57,882 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.1513 Process Time: 1.401 Mem R(MA/MR): 19608 (21200/36094) [2025-04-29 07:23:59,108 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4120 Process Time: 0.535 Mem R(MA/MR): 7386 (21200/36094) [2025-04-29 07:24:00,403 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4823 Process Time: 0.339 Mem R(MA/MR): 11470 (21200/36094) [2025-04-29 07:24:00,947 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3328 Process Time: 0.178 Mem R(MA/MR): 6576 (21200/36094) [2025-04-29 07:24:01,491 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.6122 Process Time: 0.173 Mem R(MA/MR): 4890 (21200/36094) [2025-04-29 07:24:02,315 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.1457 Process Time: 0.221 Mem R(MA/MR): 11516 (21200/36094) [2025-04-29 07:24:03,890 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.3531 Process Time: 0.371 Mem R(MA/MR): 9926 (21200/36094) [2025-04-29 07:24:06,475 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.3437 Process Time: 0.420 Mem R(MA/MR): 18766 (21200/36094) [2025-04-29 07:24:08,962 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.7095 Process Time: 0.365 Mem R(MA/MR): 15352 (21200/36094) [2025-04-29 07:24:10,232 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.8639 Process Time: 0.413 Mem R(MA/MR): 9090 (21200/36094) [2025-04-29 07:24:10,651 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2272 Process Time: 0.149 Mem R(MA/MR): 5206 (21200/36094) [2025-04-29 07:24:13,547 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.7802 Process Time: 0.282 Mem R(MA/MR): 16658 (21200/36094) [2025-04-29 07:24:15,636 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.1606 Process Time: 0.791 Mem R(MA/MR): 14708 (21200/36094) [2025-04-29 07:24:16,660 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1239 Process Time: 0.474 Mem R(MA/MR): 6994 (21200/36094) [2025-04-29 07:24:17,526 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6645 Process Time: 0.277 Mem R(MA/MR): 8672 (21200/36094) [2025-04-29 07:24:18,626 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.1248 Process Time: 0.172 Mem R(MA/MR): 6408 (21200/36094) [2025-04-29 07:24:20,050 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.5951 Process Time: 0.249 Mem R(MA/MR): 11268 (21200/36094) [2025-04-29 07:24:27,539 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.3610 Process Time: 0.380 Mem R(MA/MR): 22876 (21200/36094) [2025-04-29 07:24:28,571 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.9919 Process Time: 0.458 Mem R(MA/MR): 7116 (21200/36094) [2025-04-29 07:24:36,996 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.1768 Process Time: 0.482 Mem R(MA/MR): 8658 (21200/36094) [2025-04-29 07:24:37,606 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0867 Process Time: 0.197 Mem R(MA/MR): 5680 (21200/36094) [2025-04-29 07:24:38,661 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8978 Process Time: 0.366 Mem R(MA/MR): 9584 (21200/36094) [2025-04-29 07:24:44,604 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.8698 Process Time: 0.567 Mem R(MA/MR): 29920 (21200/36094) [2025-04-29 07:24:46,733 INFO hook.py line 449 1619929] Test: [27/50] Loss 8.0511 Process Time: 0.392 Mem R(MA/MR): 10044 (21200/36094) [2025-04-29 07:24:48,170 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.3353 Process Time: 0.565 Mem R(MA/MR): 9254 (21200/36094) [2025-04-29 07:24:52,518 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.5749 Process Time: 0.411 Mem R(MA/MR): 16846 (21200/36094) [2025-04-29 07:24:53,440 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.4934 Process Time: 0.234 Mem R(MA/MR): 8128 (21200/36094) [2025-04-29 07:24:56,810 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5659 Process Time: 0.490 Mem R(MA/MR): 20116 (21200/36094) [2025-04-29 07:24:57,134 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.8561 Process Time: 0.134 Mem R(MA/MR): 4326 (21200/36094) [2025-04-29 07:25:01,781 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3547 Process Time: 0.714 Mem R(MA/MR): 24954 (21200/36094) [2025-04-29 07:25:03,005 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6322 Process Time: 0.330 Mem R(MA/MR): 10116 (21200/36094) [2025-04-29 07:25:04,997 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0826 Process Time: 0.442 Mem R(MA/MR): 14144 (21200/36094) [2025-04-29 07:25:05,853 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9835 Process Time: 0.413 Mem R(MA/MR): 7082 (21200/36094) [2025-04-29 07:25:09,512 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.4839 Process Time: 0.545 Mem R(MA/MR): 28126 (21200/36094) [2025-04-29 07:25:11,206 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.2329 Process Time: 0.381 Mem R(MA/MR): 10958 (21200/36094) [2025-04-29 07:25:11,712 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3707 Process Time: 0.187 Mem R(MA/MR): 5812 (21200/36094) [2025-04-29 07:25:13,121 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8709 Process Time: 0.450 Mem R(MA/MR): 10422 (21200/36094) [2025-04-29 07:25:14,150 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.8131 Process Time: 0.295 Mem R(MA/MR): 9370 (21200/36094) [2025-04-29 07:25:14,764 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.0584 Process Time: 0.178 Mem R(MA/MR): 5808 (21200/36094) [2025-04-29 07:25:15,262 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.1342 Process Time: 0.181 Mem R(MA/MR): 5878 (21200/36094) [2025-04-29 07:25:15,919 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.7404 Process Time: 0.241 Mem R(MA/MR): 7382 (21200/36094) [2025-04-29 07:25:16,591 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.2713 Process Time: 0.193 Mem R(MA/MR): 5590 (21200/36094) [2025-04-29 07:25:19,093 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.5667 Process Time: 0.515 Mem R(MA/MR): 14868 (21200/36094) [2025-04-29 07:25:25,676 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.1957 Process Time: 0.628 Mem R(MA/MR): 19874 (21200/36094) [2025-04-29 07:25:34,202 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.4480 Process Time: 1.476 Mem R(MA/MR): 33122 (21200/36094) [2025-04-29 07:25:34,895 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.9208 Process Time: 0.213 Mem R(MA/MR): 6170 (21200/36094) [2025-04-29 07:25:37,262 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.7986 Process Time: 0.661 Mem R(MA/MR): 13984 (21200/36094) [2025-04-29 07:25:41,225 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 07:25:41,225 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 07:25:41,225 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] table : 0.250 0.548 0.761 0.702 0.640 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] door : 0.463 0.752 0.865 0.882 0.759 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] ceiling lamp : 0.569 0.746 0.870 0.865 0.740 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] cabinet : 0.377 0.523 0.569 0.727 0.478 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] blinds : 0.600 0.828 0.837 0.826 0.826 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] curtain : 0.347 0.633 0.699 0.889 0.667 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] chair : 0.595 0.734 0.774 0.726 0.750 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] storage cabinet: 0.327 0.499 0.623 0.750 0.480 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] office chair : 0.660 0.706 0.720 0.731 0.792 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] bookshelf : 0.084 0.273 0.467 0.545 0.545 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] whiteboard : 0.536 0.716 0.730 0.958 0.657 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] window : 0.094 0.246 0.583 0.405 0.352 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] box : 0.211 0.387 0.534 0.657 0.370 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] monitor : 0.603 0.766 0.786 0.981 0.757 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] shelf : 0.156 0.304 0.387 0.800 0.267 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] heater : 0.464 0.753 0.822 0.912 0.816 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] kitchen cabinet: 0.182 0.403 0.762 0.714 0.400 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] sofa : 0.528 0.661 0.800 0.875 0.583 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] bed : 0.177 0.376 0.816 0.714 0.625 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] trash can : 0.474 0.599 0.649 0.741 0.662 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] book : 0.010 0.022 0.048 0.180 0.082 [2025-04-29 07:25:41,225 INFO hook.py line 395 1619929] plant : 0.400 0.587 0.690 1.000 0.556 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] blanket : 0.309 0.522 0.668 0.857 0.545 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] tv : 0.837 1.000 1.000 1.000 1.000 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] computer tower : 0.229 0.415 0.513 1.000 0.357 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] refrigerator : 0.163 0.455 0.531 0.667 0.444 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] jacket : 0.092 0.323 0.520 0.714 0.455 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] sink : 0.380 0.643 0.702 0.833 0.682 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] bag : 0.104 0.171 0.201 0.348 0.296 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] picture : 0.128 0.281 0.348 0.560 0.359 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] pillow : 0.604 0.818 0.860 0.929 0.684 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] towel : 0.208 0.352 0.464 0.800 0.316 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] suitcase : 0.396 0.571 0.609 1.000 0.571 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] backpack : 0.325 0.444 0.487 0.583 0.538 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] crate : 0.070 0.358 0.610 0.714 0.455 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] keyboard : 0.432 0.587 0.644 0.815 0.564 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] toilet : 0.689 0.889 1.000 1.000 0.889 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] printer : 0.201 0.222 0.358 1.000 0.222 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.005 0.071 0.111 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] painting : 0.050 0.050 0.062 0.100 1.000 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] microwave : 0.476 0.750 0.985 1.000 0.750 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] shoes : 0.109 0.184 0.541 0.520 0.317 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] socket : 0.178 0.471 0.661 0.661 0.514 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] bottle : 0.107 0.189 0.252 0.514 0.217 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] bucket : 0.101 0.108 0.110 0.222 0.571 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] cushion : 0.219 0.256 0.256 0.235 0.667 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] basket : 0.004 0.018 0.082 0.250 0.143 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] telephone : 0.340 0.713 0.762 0.800 0.706 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] laptop : 0.320 0.371 0.385 0.333 0.625 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] plant pot : 0.086 0.273 0.448 0.462 0.375 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] exhaust fan : 0.148 0.333 0.333 1.000 0.333 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] cup : 0.218 0.403 0.432 0.889 0.364 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] coat hanger : 0.341 0.750 0.677 1.000 0.750 [2025-04-29 07:25:41,226 INFO hook.py line 395 1619929] light switch : 0.230 0.490 0.679 0.850 0.523 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] speaker : 0.327 0.504 0.579 0.750 0.545 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] table lamp : 0.389 0.500 0.500 1.000 0.500 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] smoke detector : 0.591 0.862 0.864 0.909 0.833 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] power strip : 0.150 0.226 0.240 0.375 0.300 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] paper bag : 0.100 0.100 0.125 0.200 1.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] mouse : 0.388 0.648 0.651 0.875 0.656 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] cutting board : 0.371 0.613 0.613 1.000 0.500 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] toilet paper : 0.310 0.479 0.605 0.643 0.529 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] paper towel : 0.019 0.125 0.125 1.000 0.125 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] clock : 0.330 0.528 0.667 0.667 0.667 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] tap : 0.234 0.498 0.778 0.800 0.444 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] soap dispenser : 0.551 0.800 0.800 1.000 0.800 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] bowl : 0.050 0.107 0.131 0.333 0.333 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] whiteboard eraser: 0.218 0.478 0.478 0.714 0.833 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] toilet brush : 0.321 0.667 0.833 1.000 0.667 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] spray bottle : 0.032 0.042 0.042 0.333 0.250 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] headphones : 0.033 0.062 0.708 0.250 0.500 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] stapler : 0.010 0.012 0.075 0.071 0.333 [2025-04-29 07:25:41,227 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 07:25:41,227 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 07:25:41,227 INFO hook.py line 404 1619929] average : 0.255 0.403 0.501 0.625 0.479 [2025-04-29 07:25:41,227 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 07:25:41,228 INFO hook.py line 480 1619929] Total Process Time: 20.739 s [2025-04-29 07:25:41,228 INFO hook.py line 481 1619929] Average Process Time: 418.178 ms [2025-04-29 07:25:41,228 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 07:25:41,253 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 07:25:41,258 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:27:16,368 INFO hook.py line 650 1619929] Train: [273/512][50/242] Data 0.017 (0.017) Batch 1.591 (1.472) Remain 23:43:59 loss: 5.1352 Lr: 1.51653e-04 Mem R(MA/MR): 21478 (21200/36094) [2025-04-29 07:28:28,588 INFO hook.py line 650 1619929] Train: [273/512][100/242] Data 0.017 (0.016) Batch 1.464 (1.458) Remain 23:28:50 loss: 5.5935 Lr: 1.51535e-04 Mem R(MA/MR): 23364 (21200/36094) [2025-04-29 07:29:42,662 INFO hook.py line 650 1619929] Train: [273/512][150/242] Data 0.017 (0.017) Batch 1.554 (1.466) Remain 23:35:21 loss: 6.1448 Lr: 1.51418e-04 Mem R(MA/MR): 23400 (21200/36094) [2025-04-29 07:30:55,299 INFO hook.py line 650 1619929] Train: [273/512][200/242] Data 0.015 (0.022) Batch 1.385 (1.463) Remain 23:30:54 loss: 5.4667 Lr: 1.51300e-04 Mem R(MA/MR): 23400 (21200/36094) [2025-04-29 07:31:51,113 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3457 loss_mask: 0.0384 loss_dice: 2.0755 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8253 loss: 5.3631 [2025-04-29 07:31:51,701 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:33:21,114 INFO hook.py line 650 1619929] Train: [274/512][50/242] Data 0.016 (0.017) Batch 1.400 (1.521) Remain 24:24:52 loss: 4.9773 Lr: 1.51084e-04 Mem R(MA/MR): 19732 (21200/36094) [2025-04-29 07:34:34,873 INFO hook.py line 650 1619929] Train: [274/512][100/242] Data 0.016 (0.017) Batch 1.706 (1.497) Remain 24:00:52 loss: 4.6641 Lr: 1.50966e-04 Mem R(MA/MR): 21264 (21200/36094) [2025-04-29 07:35:47,694 INFO hook.py line 650 1619929] Train: [274/512][150/242] Data 0.016 (0.017) Batch 1.567 (1.483) Remain 23:46:15 loss: 5.1302 Lr: 1.50849e-04 Mem R(MA/MR): 23092 (21200/36094) [2025-04-29 07:37:00,895 INFO hook.py line 650 1619929] Train: [274/512][200/242] Data 0.014 (0.017) Batch 1.399 (1.479) Remain 23:40:18 loss: 4.8918 Lr: 1.50731e-04 Mem R(MA/MR): 25134 (21200/36094) [2025-04-29 07:37:58,161 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3416 loss_mask: 0.0383 loss_dice: 2.0788 loss_score: 0.0000 loss_bbox: 0.0520 loss_sp_cls: 0.8226 loss: 5.3465 [2025-04-29 07:38:01,904 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:39:36,892 INFO hook.py line 650 1619929] Train: [275/512][50/242] Data 0.016 (0.017) Batch 1.437 (1.467) Remain 23:26:37 loss: 5.5489 Lr: 1.50515e-04 Mem R(MA/MR): 25854 (21200/36094) [2025-04-29 07:40:48,402 INFO hook.py line 650 1619929] Train: [275/512][100/242] Data 0.016 (0.017) Batch 1.361 (1.448) Remain 23:07:24 loss: 4.8272 Lr: 1.50397e-04 Mem R(MA/MR): 25866 (21200/36094) [2025-04-29 07:42:00,031 INFO hook.py line 650 1619929] Train: [275/512][150/242] Data 0.017 (0.017) Batch 1.625 (1.443) Remain 23:01:13 loss: 4.2971 Lr: 1.50279e-04 Mem R(MA/MR): 25866 (21200/36094) [2025-04-29 07:43:14,508 INFO hook.py line 650 1619929] Train: [275/512][200/242] Data 0.015 (0.017) Batch 1.414 (1.455) Remain 23:11:25 loss: 5.3862 Lr: 1.50162e-04 Mem R(MA/MR): 27944 (21200/36094) [2025-04-29 07:44:11,571 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3366 loss_mask: 0.0379 loss_dice: 2.0495 loss_score: 0.0000 loss_bbox: 0.0512 loss_sp_cls: 0.8173 loss: 5.2763 [2025-04-29 07:44:14,241 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:45:52,825 INFO hook.py line 650 1619929] Train: [276/512][50/242] Data 0.018 (0.017) Batch 1.552 (1.493) Remain 23:45:43 loss: 5.0838 Lr: 1.49945e-04 Mem R(MA/MR): 20782 (21200/36094) [2025-04-29 07:47:04,376 INFO hook.py line 650 1619929] Train: [276/512][100/242] Data 0.014 (0.017) Batch 1.486 (1.461) Remain 23:14:04 loss: 4.5083 Lr: 1.49828e-04 Mem R(MA/MR): 20782 (21200/36094) [2025-04-29 07:48:17,380 INFO hook.py line 650 1619929] Train: [276/512][150/242] Data 0.016 (0.017) Batch 1.263 (1.461) Remain 23:12:34 loss: 5.0049 Lr: 1.49710e-04 Mem R(MA/MR): 21406 (21200/36094) [2025-04-29 07:49:28,637 INFO hook.py line 650 1619929] Train: [276/512][200/242] Data 0.014 (0.017) Batch 1.477 (1.452) Remain 23:02:47 loss: 5.0197 Lr: 1.49592e-04 Mem R(MA/MR): 21406 (21200/36094) [2025-04-29 07:50:27,516 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3393 loss_mask: 0.0384 loss_dice: 2.0481 loss_score: 0.0000 loss_bbox: 0.0515 loss_sp_cls: 0.8218 loss: 5.2939 [2025-04-29 07:50:28,446 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:51:58,895 INFO hook.py line 650 1619929] Train: [277/512][50/242] Data 0.016 (0.017) Batch 1.605 (1.463) Remain 23:11:22 loss: 5.8577 Lr: 1.49376e-04 Mem R(MA/MR): 22982 (21200/36094) [2025-04-29 07:53:09,412 INFO hook.py line 650 1619929] Train: [277/512][100/242] Data 0.015 (0.016) Batch 1.367 (1.436) Remain 22:44:21 loss: 4.3356 Lr: 1.49258e-04 Mem R(MA/MR): 22982 (21200/36094) [2025-04-29 07:54:23,234 INFO hook.py line 650 1619929] Train: [277/512][150/242] Data 0.016 (0.016) Batch 1.353 (1.450) Remain 22:56:15 loss: 4.9670 Lr: 1.49140e-04 Mem R(MA/MR): 24934 (21200/36094) [2025-04-29 07:55:36,137 INFO hook.py line 650 1619929] Train: [277/512][200/242] Data 0.016 (0.016) Batch 1.455 (1.452) Remain 22:57:04 loss: 6.3696 Lr: 1.49025e-04 Mem R(MA/MR): 24934 (21200/36094) [2025-04-29 07:56:34,958 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3461 loss_mask: 0.0383 loss_dice: 2.0706 loss_score: 0.0000 loss_bbox: 0.0517 loss_sp_cls: 0.8304 loss: 5.3542 [2025-04-29 07:56:36,943 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 07:58:07,718 INFO hook.py line 650 1619929] Train: [278/512][50/242] Data 0.016 (0.016) Batch 1.502 (1.473) Remain 23:15:00 loss: 4.4338 Lr: 1.48808e-04 Mem R(MA/MR): 20366 (21200/36094) [2025-04-29 07:59:20,609 INFO hook.py line 650 1619929] Train: [278/512][100/242] Data 0.016 (0.016) Batch 1.673 (1.465) Remain 23:06:19 loss: 4.1125 Lr: 1.48690e-04 Mem R(MA/MR): 23010 (21200/36094) [2025-04-29 08:00:35,246 INFO hook.py line 650 1619929] Train: [278/512][150/242] Data 0.018 (0.016) Batch 1.537 (1.475) Remain 23:13:57 loss: 5.1716 Lr: 1.48572e-04 Mem R(MA/MR): 23010 (21200/36094) [2025-04-29 08:01:49,861 INFO hook.py line 650 1619929] Train: [278/512][200/242] Data 0.038 (0.016) Batch 1.457 (1.479) Remain 23:16:59 loss: 5.9837 Lr: 1.48455e-04 Mem R(MA/MR): 23010 (21200/36094) [2025-04-29 08:02:47,424 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3668 loss_mask: 0.0405 loss_dice: 2.1473 loss_score: 0.0000 loss_bbox: 0.0529 loss_sp_cls: 0.8523 loss: 5.5598 [2025-04-29 08:02:50,953 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:04:23,324 INFO hook.py line 650 1619929] Train: [279/512][50/242] Data 0.016 (0.017) Batch 1.431 (1.471) Remain 23:06:49 loss: 5.6942 Lr: 1.48238e-04 Mem R(MA/MR): 22922 (21200/36094) [2025-04-29 08:05:35,896 INFO hook.py line 650 1619929] Train: [279/512][100/242] Data 0.018 (0.017) Batch 1.510 (1.461) Remain 22:56:14 loss: 4.2561 Lr: 1.48120e-04 Mem R(MA/MR): 24478 (21200/36094) [2025-04-29 08:06:47,012 INFO hook.py line 650 1619929] Train: [279/512][150/242] Data 0.016 (0.017) Batch 1.453 (1.448) Remain 22:42:43 loss: 7.0385 Lr: 1.48002e-04 Mem R(MA/MR): 26280 (21200/36094) [2025-04-29 08:07:58,331 INFO hook.py line 650 1619929] Train: [279/512][200/242] Data 0.015 (0.017) Batch 1.354 (1.442) Remain 22:36:25 loss: 5.5448 Lr: 1.47884e-04 Mem R(MA/MR): 26280 (21200/36094) [2025-04-29 08:08:55,942 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3626 loss_mask: 0.0406 loss_dice: 2.1351 loss_score: 0.0000 loss_bbox: 0.0528 loss_sp_cls: 0.8492 loss: 5.5170 [2025-04-29 08:09:00,943 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:10:27,637 INFO hook.py line 650 1619929] Train: [280/512][50/242] Data 0.017 (0.017) Batch 1.329 (1.476) Remain 23:05:42 loss: 4.8180 Lr: 1.47667e-04 Mem R(MA/MR): 19214 (21200/36094) [2025-04-29 08:11:40,759 INFO hook.py line 650 1619929] Train: [280/512][100/242] Data 0.017 (0.017) Batch 1.338 (1.469) Remain 22:58:01 loss: 4.7102 Lr: 1.47549e-04 Mem R(MA/MR): 20156 (21200/36094) [2025-04-29 08:12:53,509 INFO hook.py line 650 1619929] Train: [280/512][150/242] Data 0.018 (0.017) Batch 1.535 (1.464) Remain 22:52:19 loss: 5.3354 Lr: 1.47432e-04 Mem R(MA/MR): 20156 (21200/36094) [2025-04-29 08:14:06,914 INFO hook.py line 650 1619929] Train: [280/512][200/242] Data 0.016 (0.017) Batch 1.549 (1.465) Remain 22:52:02 loss: 5.7092 Lr: 1.47314e-04 Mem R(MA/MR): 20156 (21200/36094) [2025-04-29 08:15:05,181 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3517 loss_mask: 0.0396 loss_dice: 2.1161 loss_score: 0.0000 loss_bbox: 0.0531 loss_sp_cls: 0.8370 loss: 5.4542 [2025-04-29 08:15:09,798 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 08:15:12,106 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.0221 Process Time: 0.264 Mem R(MA/MR): 4522 (21200/36094) [2025-04-29 08:15:13,552 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.4366 Process Time: 0.481 Mem R(MA/MR): 7472 (21200/36094) [2025-04-29 08:15:15,239 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5125 Process Time: 0.605 Mem R(MA/MR): 9950 (21200/36094) [2025-04-29 08:15:23,006 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4841 Process Time: 1.462 Mem R(MA/MR): 20000 (21200/36094) [2025-04-29 08:15:24,363 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.7055 Process Time: 0.562 Mem R(MA/MR): 7306 (21200/36094) [2025-04-29 08:15:25,875 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5297 Process Time: 0.399 Mem R(MA/MR): 11684 (21200/36094) [2025-04-29 08:15:26,611 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0676 Process Time: 0.302 Mem R(MA/MR): 6726 (21200/36094) [2025-04-29 08:15:27,108 INFO hook.py line 449 1619929] Test: [8/50] Loss 4.9610 Process Time: 0.152 Mem R(MA/MR): 4534 (21200/36094) [2025-04-29 08:15:28,113 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.1222 Process Time: 0.346 Mem R(MA/MR): 11936 (21200/36094) [2025-04-29 08:15:29,648 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.9802 Process Time: 0.258 Mem R(MA/MR): 9762 (21200/36094) [2025-04-29 08:15:32,196 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.6301 Process Time: 0.674 Mem R(MA/MR): 19114 (21200/36094) [2025-04-29 08:15:35,310 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.6346 Process Time: 0.984 Mem R(MA/MR): 15978 (21200/36094) [2025-04-29 08:15:36,551 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7087 Process Time: 0.337 Mem R(MA/MR): 8952 (21200/36094) [2025-04-29 08:15:36,957 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1072 Process Time: 0.127 Mem R(MA/MR): 5448 (21200/36094) [2025-04-29 08:15:39,472 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.2006 Process Time: 0.288 Mem R(MA/MR): 17200 (21200/36094) [2025-04-29 08:15:40,944 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.2358 Process Time: 0.301 Mem R(MA/MR): 15050 (21200/36094) [2025-04-29 08:15:41,863 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.6903 Process Time: 0.372 Mem R(MA/MR): 7284 (21200/36094) [2025-04-29 08:15:42,984 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1175 Process Time: 0.350 Mem R(MA/MR): 8588 (21200/36094) [2025-04-29 08:15:44,509 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9411 Process Time: 0.238 Mem R(MA/MR): 6542 (21200/36094) [2025-04-29 08:15:46,476 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.6852 Process Time: 0.499 Mem R(MA/MR): 11740 (21200/36094) [2025-04-29 08:15:55,308 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.5307 Process Time: 0.708 Mem R(MA/MR): 23670 (21200/36094) [2025-04-29 08:15:55,859 INFO hook.py line 449 1619929] Test: [22/50] Loss 6.0546 Process Time: 0.168 Mem R(MA/MR): 7378 (21200/36094) [2025-04-29 08:16:03,937 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.4528 Process Time: 0.307 Mem R(MA/MR): 8894 (21200/36094) [2025-04-29 08:16:04,444 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.4797 Process Time: 0.146 Mem R(MA/MR): 5840 (21200/36094) [2025-04-29 08:16:05,341 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.4903 Process Time: 0.199 Mem R(MA/MR): 9198 (21200/36094) [2025-04-29 08:16:12,025 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.1449 Process Time: 0.728 Mem R(MA/MR): 32110 (21200/36094) [2025-04-29 08:16:13,905 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.0607 Process Time: 0.222 Mem R(MA/MR): 9884 (21200/36094) [2025-04-29 08:16:14,969 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.4504 Process Time: 0.195 Mem R(MA/MR): 8724 (21200/36094) [2025-04-29 08:16:19,534 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.5456 Process Time: 0.317 Mem R(MA/MR): 17688 (21200/36094) [2025-04-29 08:16:20,572 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2231 Process Time: 0.270 Mem R(MA/MR): 8218 (21200/36094) [2025-04-29 08:16:23,760 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0570 Process Time: 0.369 Mem R(MA/MR): 20694 (21200/36094) [2025-04-29 08:16:24,133 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.7397 Process Time: 0.131 Mem R(MA/MR): 4336 (21200/36094) [2025-04-29 08:16:28,399 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.1162 Process Time: 0.719 Mem R(MA/MR): 24804 (21200/36094) [2025-04-29 08:16:29,620 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9521 Process Time: 0.366 Mem R(MA/MR): 9490 (21200/36094) [2025-04-29 08:16:31,211 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0656 Process Time: 0.251 Mem R(MA/MR): 14682 (21200/36094) [2025-04-29 08:16:32,047 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8670 Process Time: 0.188 Mem R(MA/MR): 7100 (21200/36094) [2025-04-29 08:16:35,775 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.0237 Process Time: 0.455 Mem R(MA/MR): 28240 (21200/36094) [2025-04-29 08:16:37,464 INFO hook.py line 449 1619929] Test: [38/50] Loss 6.0756 Process Time: 0.365 Mem R(MA/MR): 10456 (21200/36094) [2025-04-29 08:16:38,036 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0153 Process Time: 0.188 Mem R(MA/MR): 5946 (21200/36094) [2025-04-29 08:16:39,194 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9121 Process Time: 0.285 Mem R(MA/MR): 10242 (21200/36094) [2025-04-29 08:16:40,162 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.2794 Process Time: 0.225 Mem R(MA/MR): 8716 (21200/36094) [2025-04-29 08:16:40,649 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.8609 Process Time: 0.163 Mem R(MA/MR): 5938 (21200/36094) [2025-04-29 08:16:41,097 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6897 Process Time: 0.165 Mem R(MA/MR): 5998 (21200/36094) [2025-04-29 08:16:41,735 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.2925 Process Time: 0.177 Mem R(MA/MR): 7624 (21200/36094) [2025-04-29 08:16:42,416 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.1160 Process Time: 0.209 Mem R(MA/MR): 5796 (21200/36094) [2025-04-29 08:16:45,373 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.1137 Process Time: 0.854 Mem R(MA/MR): 15310 (21200/36094) [2025-04-29 08:16:53,004 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.6584 Process Time: 1.257 Mem R(MA/MR): 20580 (21200/36094) [2025-04-29 08:17:03,999 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.7384 Process Time: 2.036 Mem R(MA/MR): 35426 (21200/36094) [2025-04-29 08:17:04,952 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.4584 Process Time: 0.317 Mem R(MA/MR): 6356 (21200/36094) [2025-04-29 08:17:07,290 INFO hook.py line 449 1619929] Test: [50/50] Loss 6.0513 Process Time: 0.375 Mem R(MA/MR): 14306 (21200/36094) [2025-04-29 08:17:11,899 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 08:17:11,899 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 08:17:11,899 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] table : 0.233 0.542 0.776 0.743 0.618 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] door : 0.394 0.680 0.901 0.846 0.696 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] ceiling lamp : 0.600 0.799 0.918 0.913 0.751 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] cabinet : 0.281 0.384 0.462 0.549 0.418 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] blinds : 0.616 0.864 0.864 0.864 0.826 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] curtain : 0.227 0.394 0.567 0.423 0.917 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] chair : 0.642 0.780 0.809 0.902 0.680 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] storage cabinet: 0.240 0.427 0.532 0.520 0.520 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] office chair : 0.556 0.598 0.598 0.729 0.729 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] bookshelf : 0.417 0.737 0.776 0.889 0.727 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] whiteboard : 0.566 0.738 0.793 0.962 0.714 [2025-04-29 08:17:11,899 INFO hook.py line 395 1619929] window : 0.107 0.239 0.608 0.333 0.374 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] box : 0.190 0.325 0.511 0.584 0.365 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] monitor : 0.642 0.815 0.809 0.948 0.786 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] shelf : 0.061 0.163 0.447 0.471 0.267 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] heater : 0.471 0.717 0.860 0.871 0.711 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] kitchen cabinet: 0.109 0.265 0.691 0.444 0.320 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] sofa : 0.433 0.643 0.856 0.800 0.667 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] bed : 0.051 0.100 0.845 0.500 0.250 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] trash can : 0.481 0.627 0.717 0.787 0.738 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] book : 0.015 0.026 0.072 0.161 0.086 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] plant : 0.447 0.654 0.654 0.857 0.667 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] blanket : 0.512 0.656 0.708 0.800 0.727 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] tv : 0.888 1.000 1.000 1.000 1.000 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] computer tower : 0.220 0.314 0.603 0.593 0.381 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] refrigerator : 0.285 0.480 0.525 0.800 0.444 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] jacket : 0.075 0.201 0.312 0.316 0.545 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] sink : 0.430 0.664 0.819 0.789 0.682 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] bag : 0.120 0.166 0.166 0.833 0.185 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] picture : 0.146 0.262 0.371 0.609 0.359 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] pillow : 0.590 0.831 0.832 0.933 0.737 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] towel : 0.175 0.338 0.555 0.750 0.316 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] suitcase : 0.441 0.498 0.573 0.800 0.571 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] backpack : 0.341 0.415 0.463 0.833 0.385 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] crate : 0.076 0.294 0.625 0.625 0.455 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] keyboard : 0.424 0.606 0.736 0.667 0.615 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] toilet : 0.813 1.000 1.000 1.000 1.000 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] printer : 0.296 0.511 0.521 1.000 0.444 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] poster : 0.001 0.007 0.008 0.125 0.111 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] painting : 0.125 0.125 0.125 0.250 1.000 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] microwave : 0.393 0.750 0.875 1.000 0.750 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] shoes : 0.111 0.218 0.490 0.591 0.317 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] socket : 0.159 0.424 0.612 0.620 0.479 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] bottle : 0.098 0.181 0.268 0.500 0.253 [2025-04-29 08:17:11,900 INFO hook.py line 395 1619929] bucket : 0.106 0.106 0.208 0.179 0.714 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] cushion : 0.069 0.104 0.132 0.250 0.500 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] basket : 0.011 0.036 0.119 0.500 0.143 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] shoe rack : 0.111 0.500 0.500 1.000 0.500 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] telephone : 0.292 0.475 0.619 0.692 0.529 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] laptop : 0.305 0.469 0.660 0.429 0.750 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] plant pot : 0.103 0.274 0.371 0.700 0.438 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] exhaust fan : 0.119 0.288 0.306 0.714 0.333 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] cup : 0.219 0.321 0.375 0.533 0.364 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] coat hanger : 0.069 0.354 0.677 0.500 0.500 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] light switch : 0.249 0.502 0.601 0.767 0.508 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] speaker : 0.166 0.239 0.379 0.385 0.455 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] smoke detector : 0.680 0.906 0.907 0.880 0.917 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] power strip : 0.098 0.141 0.153 0.214 0.300 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] mouse : 0.504 0.740 0.786 0.857 0.750 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] cutting board : 0.225 0.396 0.396 0.667 0.500 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] toilet paper : 0.134 0.214 0.319 0.667 0.235 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] paper towel : 0.044 0.166 0.166 0.400 0.250 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] clock : 0.528 1.000 1.000 1.000 1.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] tap : 0.152 0.283 0.511 0.444 0.444 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] soap dispenser : 0.495 0.615 0.702 0.750 0.600 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] whiteboard eraser: 0.187 0.434 0.434 0.556 0.833 [2025-04-29 08:17:11,901 INFO hook.py line 395 1619929] toilet brush : 0.495 0.667 0.833 1.000 0.667 [2025-04-29 08:17:11,902 INFO hook.py line 395 1619929] spray bottle : 0.024 0.031 0.031 0.250 0.250 [2025-04-29 08:17:11,902 INFO hook.py line 395 1619929] headphones : 0.296 0.662 0.792 1.000 0.500 [2025-04-29 08:17:11,902 INFO hook.py line 395 1619929] stapler : 0.009 0.028 0.278 0.167 0.333 [2025-04-29 08:17:11,902 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 08:17:11,902 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 08:17:11,902 INFO hook.py line 404 1619929] average : 0.254 0.391 0.490 0.586 0.470 [2025-04-29 08:17:11,902 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 08:17:11,902 INFO hook.py line 480 1619929] Total Process Time: 21.358 s [2025-04-29 08:17:11,902 INFO hook.py line 481 1619929] Average Process Time: 430.491 ms [2025-04-29 08:17:11,902 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 08:17:11,944 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 08:17:11,948 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:18:42,016 INFO hook.py line 650 1619929] Train: [281/512][50/242] Data 0.016 (0.017) Batch 1.470 (1.421) Remain 22:08:12 loss: 5.2840 Lr: 1.47097e-04 Mem R(MA/MR): 22072 (21200/36094) [2025-04-29 08:19:55,400 INFO hook.py line 650 1619929] Train: [281/512][100/242] Data 0.016 (0.027) Batch 1.581 (1.445) Remain 22:29:38 loss: 5.8667 Lr: 1.46979e-04 Mem R(MA/MR): 22080 (21200/36094) [2025-04-29 08:21:07,183 INFO hook.py line 650 1619929] Train: [281/512][150/242] Data 0.018 (0.023) Batch 1.342 (1.442) Remain 22:25:29 loss: 4.4980 Lr: 1.46861e-04 Mem R(MA/MR): 22080 (21200/36094) [2025-04-29 08:22:18,888 INFO hook.py line 650 1619929] Train: [281/512][200/242] Data 0.017 (0.022) Batch 1.358 (1.440) Remain 22:22:28 loss: 4.2744 Lr: 1.46743e-04 Mem R(MA/MR): 23918 (21200/36094) [2025-04-29 08:23:16,973 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3461 loss_mask: 0.0387 loss_dice: 2.0803 loss_score: 0.0000 loss_bbox: 0.0521 loss_sp_cls: 0.8341 loss: 5.3753 [2025-04-29 08:23:19,082 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:24:48,997 INFO hook.py line 650 1619929] Train: [282/512][50/242] Data 0.016 (0.017) Batch 1.426 (1.440) Remain 22:20:36 loss: 5.7790 Lr: 1.46526e-04 Mem R(MA/MR): 20674 (21200/36094) [2025-04-29 08:26:02,291 INFO hook.py line 650 1619929] Train: [282/512][100/242] Data 0.017 (0.017) Batch 1.356 (1.453) Remain 22:31:43 loss: 5.7810 Lr: 1.46408e-04 Mem R(MA/MR): 24084 (21200/36094) [2025-04-29 08:27:13,016 INFO hook.py line 650 1619929] Train: [282/512][150/242] Data 0.015 (0.017) Batch 1.395 (1.440) Remain 22:18:13 loss: 4.7933 Lr: 1.46290e-04 Mem R(MA/MR): 24084 (21200/36094) [2025-04-29 08:28:24,602 INFO hook.py line 650 1619929] Train: [282/512][200/242] Data 0.014 (0.017) Batch 1.387 (1.438) Remain 22:15:01 loss: 4.9763 Lr: 1.46172e-04 Mem R(MA/MR): 24084 (21200/36094) [2025-04-29 08:29:22,719 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3425 loss_mask: 0.0385 loss_dice: 2.0926 loss_score: 0.0000 loss_bbox: 0.0512 loss_sp_cls: 0.8324 loss: 5.3687 [2025-04-29 08:29:24,952 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:31:00,508 INFO hook.py line 650 1619929] Train: [283/512][50/242] Data 0.015 (0.017) Batch 1.306 (1.439) Remain 22:13:15 loss: 4.8668 Lr: 1.45955e-04 Mem R(MA/MR): 19954 (21200/36094) [2025-04-29 08:32:12,341 INFO hook.py line 650 1619929] Train: [283/512][100/242] Data 0.017 (0.017) Batch 1.378 (1.438) Remain 22:11:10 loss: 5.1079 Lr: 1.45837e-04 Mem R(MA/MR): 22276 (21200/36094) [2025-04-29 08:33:26,310 INFO hook.py line 650 1619929] Train: [283/512][150/242] Data 0.015 (0.017) Batch 1.537 (1.452) Remain 22:23:08 loss: 5.7841 Lr: 1.45719e-04 Mem R(MA/MR): 28318 (21268/36094) [2025-04-29 08:34:37,651 INFO hook.py line 650 1619929] Train: [283/512][200/242] Data 0.016 (0.017) Batch 1.358 (1.445) Remain 22:16:04 loss: 5.0840 Lr: 1.45600e-04 Mem R(MA/MR): 28318 (21268/36094) [2025-04-29 08:35:35,938 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3405 loss_mask: 0.0391 loss_dice: 2.0714 loss_score: 0.0000 loss_bbox: 0.0520 loss_sp_cls: 0.8263 loss: 5.3442 [2025-04-29 08:35:36,228 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:37:09,756 INFO hook.py line 650 1619929] Train: [284/512][50/242] Data 0.016 (0.016) Batch 1.331 (1.474) Remain 22:40:27 loss: 5.8894 Lr: 1.45383e-04 Mem R(MA/MR): 21692 (21268/36094) [2025-04-29 08:38:22,211 INFO hook.py line 650 1619929] Train: [284/512][100/242] Data 0.016 (0.016) Batch 1.470 (1.461) Remain 22:27:16 loss: 6.0341 Lr: 1.45265e-04 Mem R(MA/MR): 26818 (21268/36094) [2025-04-29 08:39:34,467 INFO hook.py line 650 1619929] Train: [284/512][150/242] Data 0.016 (0.016) Batch 1.423 (1.456) Remain 22:20:58 loss: 4.0276 Lr: 1.45147e-04 Mem R(MA/MR): 26818 (21268/36094) [2025-04-29 08:40:46,197 INFO hook.py line 650 1619929] Train: [284/512][200/242] Data 0.066 (0.017) Batch 1.429 (1.450) Remain 22:14:49 loss: 4.5662 Lr: 1.45029e-04 Mem R(MA/MR): 26828 (21268/36094) [2025-04-29 08:41:42,354 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3376 loss_mask: 0.0390 loss_dice: 2.0625 loss_score: 0.0000 loss_bbox: 0.0518 loss_sp_cls: 0.8197 loss: 5.3176 [2025-04-29 08:41:47,648 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:43:16,160 INFO hook.py line 650 1619929] Train: [285/512][50/242] Data 0.017 (0.017) Batch 1.464 (1.498) Remain 22:55:51 loss: 5.1211 Lr: 1.44812e-04 Mem R(MA/MR): 21436 (21268/36094) [2025-04-29 08:44:28,571 INFO hook.py line 650 1619929] Train: [285/512][100/242] Data 0.016 (0.017) Batch 1.449 (1.472) Remain 22:31:18 loss: 4.8077 Lr: 1.44693e-04 Mem R(MA/MR): 24820 (21268/36094) [2025-04-29 08:45:40,496 INFO hook.py line 650 1619929] Train: [285/512][150/242] Data 0.018 (0.017) Batch 1.439 (1.461) Remain 22:19:35 loss: 4.6889 Lr: 1.44575e-04 Mem R(MA/MR): 24828 (21268/36094) [2025-04-29 08:46:52,437 INFO hook.py line 650 1619929] Train: [285/512][200/242] Data 0.015 (0.017) Batch 1.388 (1.455) Remain 22:13:18 loss: 5.3934 Lr: 1.44457e-04 Mem R(MA/MR): 24838 (21268/36094) [2025-04-29 08:47:49,938 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3334 loss_mask: 0.0382 loss_dice: 2.0606 loss_score: 0.0000 loss_bbox: 0.0516 loss_sp_cls: 0.8101 loss: 5.2889 [2025-04-29 08:47:53,189 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:49:27,740 INFO hook.py line 650 1619929] Train: [286/512][50/242] Data 0.017 (0.017) Batch 1.529 (1.457) Remain 22:12:59 loss: 5.2349 Lr: 1.44240e-04 Mem R(MA/MR): 22464 (21268/36094) [2025-04-29 08:50:38,740 INFO hook.py line 650 1619929] Train: [286/512][100/242] Data 0.018 (0.017) Batch 1.400 (1.438) Remain 21:54:13 loss: 4.8581 Lr: 1.44121e-04 Mem R(MA/MR): 25822 (21268/36094) [2025-04-29 08:51:50,589 INFO hook.py line 650 1619929] Train: [286/512][150/242] Data 0.017 (0.017) Batch 1.496 (1.438) Remain 21:52:41 loss: 4.2013 Lr: 1.44003e-04 Mem R(MA/MR): 25822 (21268/36094) [2025-04-29 08:53:00,912 INFO hook.py line 650 1619929] Train: [286/512][200/242] Data 0.015 (0.017) Batch 1.322 (1.430) Remain 21:44:16 loss: 6.0726 Lr: 1.43885e-04 Mem R(MA/MR): 25822 (21268/36094) [2025-04-29 08:53:58,016 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3191 loss_mask: 0.0371 loss_dice: 1.9901 loss_score: 0.0000 loss_bbox: 0.0497 loss_sp_cls: 0.7947 loss: 5.1227 [2025-04-29 08:53:58,837 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 08:55:29,368 INFO hook.py line 650 1619929] Train: [287/512][50/242] Data 0.016 (0.017) Batch 1.389 (1.469) Remain 22:17:51 loss: 4.5107 Lr: 1.43667e-04 Mem R(MA/MR): 25990 (21268/36094) [2025-04-29 08:56:40,066 INFO hook.py line 650 1619929] Train: [287/512][100/242] Data 0.016 (0.017) Batch 1.374 (1.441) Remain 21:50:46 loss: 4.2645 Lr: 1.43549e-04 Mem R(MA/MR): 27876 (21268/36094) [2025-04-29 08:57:51,680 INFO hook.py line 650 1619929] Train: [287/512][150/242] Data 0.016 (0.017) Batch 1.329 (1.438) Remain 21:47:00 loss: 5.8031 Lr: 1.43431e-04 Mem R(MA/MR): 27880 (21268/36094) [2025-04-29 08:59:04,250 INFO hook.py line 650 1619929] Train: [287/512][200/242] Data 0.014 (0.017) Batch 1.499 (1.441) Remain 21:48:57 loss: 5.4128 Lr: 1.43313e-04 Mem R(MA/MR): 27880 (21268/36094) [2025-04-29 09:00:02,146 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3137 loss_mask: 0.0363 loss_dice: 1.9882 loss_score: 0.0000 loss_bbox: 0.0500 loss_sp_cls: 0.7904 loss: 5.1014 [2025-04-29 09:00:04,630 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:01:28,280 INFO hook.py line 650 1619929] Train: [288/512][50/242] Data 0.018 (0.017) Batch 1.489 (1.441) Remain 21:46:18 loss: 5.1499 Lr: 1.43095e-04 Mem R(MA/MR): 20946 (21268/36094) [2025-04-29 09:02:41,582 INFO hook.py line 650 1619929] Train: [288/512][100/242] Data 0.017 (0.017) Batch 1.481 (1.454) Remain 21:56:54 loss: 4.7992 Lr: 1.42977e-04 Mem R(MA/MR): 24988 (21268/36094) [2025-04-29 09:03:54,162 INFO hook.py line 650 1619929] Train: [288/512][150/242] Data 0.017 (0.017) Batch 1.572 (1.453) Remain 21:54:59 loss: 6.1978 Lr: 1.42858e-04 Mem R(MA/MR): 24988 (21268/36094) [2025-04-29 09:05:06,245 INFO hook.py line 650 1619929] Train: [288/512][200/242] Data 0.015 (0.017) Batch 1.335 (1.450) Remain 21:51:11 loss: 5.2200 Lr: 1.42740e-04 Mem R(MA/MR): 24988 (21268/36094) [2025-04-29 09:06:04,419 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3153 loss_mask: 0.0365 loss_dice: 1.9872 loss_score: 0.0000 loss_bbox: 0.0503 loss_sp_cls: 0.7924 loss: 5.1086 [2025-04-29 09:06:05,178 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 09:06:07,540 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1620 Process Time: 0.287 Mem R(MA/MR): 4344 (21268/36094) [2025-04-29 09:06:09,209 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.7850 Process Time: 0.556 Mem R(MA/MR): 7116 (21268/36094) [2025-04-29 09:06:11,599 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.9559 Process Time: 1.095 Mem R(MA/MR): 9668 (21268/36094) [2025-04-29 09:06:19,162 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.8857 Process Time: 1.033 Mem R(MA/MR): 19578 (21268/36094) [2025-04-29 09:06:20,900 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6247 Process Time: 0.653 Mem R(MA/MR): 6958 (21268/36094) [2025-04-29 09:06:22,761 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4646 Process Time: 0.582 Mem R(MA/MR): 11298 (21268/36094) [2025-04-29 09:06:23,472 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.4541 Process Time: 0.301 Mem R(MA/MR): 6310 (21268/36094) [2025-04-29 09:06:23,965 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3497 Process Time: 0.159 Mem R(MA/MR): 4370 (21268/36094) [2025-04-29 09:06:24,891 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0752 Process Time: 0.222 Mem R(MA/MR): 11394 (21268/36094) [2025-04-29 09:06:26,588 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5883 Process Time: 0.245 Mem R(MA/MR): 9480 (21268/36094) [2025-04-29 09:06:29,782 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.6765 Process Time: 0.836 Mem R(MA/MR): 18576 (21268/36094) [2025-04-29 09:06:32,671 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.8175 Process Time: 0.525 Mem R(MA/MR): 15516 (21268/36094) [2025-04-29 09:06:33,788 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.5556 Process Time: 0.236 Mem R(MA/MR): 8694 (21268/36094) [2025-04-29 09:06:34,212 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0695 Process Time: 0.138 Mem R(MA/MR): 4754 (21268/36094) [2025-04-29 09:06:37,846 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.5316 Process Time: 0.282 Mem R(MA/MR): 16462 (21268/36094) [2025-04-29 09:06:40,302 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4128 Process Time: 0.888 Mem R(MA/MR): 14456 (21268/36094) [2025-04-29 09:06:41,156 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.7347 Process Time: 0.284 Mem R(MA/MR): 6658 (21268/36094) [2025-04-29 09:06:41,912 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6977 Process Time: 0.180 Mem R(MA/MR): 8170 (21268/36094) [2025-04-29 09:06:43,067 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.8455 Process Time: 0.139 Mem R(MA/MR): 6010 (21268/36094) [2025-04-29 09:06:44,665 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.0048 Process Time: 0.260 Mem R(MA/MR): 11308 (21268/36094) [2025-04-29 09:06:53,283 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.7131 Process Time: 1.293 Mem R(MA/MR): 23304 (21268/36094) [2025-04-29 09:06:54,583 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.0733 Process Time: 0.740 Mem R(MA/MR): 6966 (21268/36094) [2025-04-29 09:07:05,065 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.8320 Process Time: 0.901 Mem R(MA/MR): 10110 (21268/36094) [2025-04-29 09:07:05,916 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9854 Process Time: 0.280 Mem R(MA/MR): 5330 (21268/36094) [2025-04-29 09:07:07,237 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1684 Process Time: 0.521 Mem R(MA/MR): 9196 (21268/36094) [2025-04-29 09:07:14,175 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.2726 Process Time: 0.961 Mem R(MA/MR): 31500 (21268/36094) [2025-04-29 09:07:16,983 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.0599 Process Time: 0.695 Mem R(MA/MR): 9956 (21268/36094) [2025-04-29 09:07:18,360 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.1979 Process Time: 0.284 Mem R(MA/MR): 8842 (21268/36094) [2025-04-29 09:07:23,923 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8751 Process Time: 0.413 Mem R(MA/MR): 17024 (21268/36094) [2025-04-29 09:07:25,007 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2882 Process Time: 0.335 Mem R(MA/MR): 7698 (21268/36094) [2025-04-29 09:07:28,426 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.1825 Process Time: 0.344 Mem R(MA/MR): 20558 (21268/36094) [2025-04-29 09:07:28,896 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.0618 Process Time: 0.167 Mem R(MA/MR): 3996 (21268/36094) [2025-04-29 09:07:32,967 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.1590 Process Time: 0.709 Mem R(MA/MR): 24674 (21268/36094) [2025-04-29 09:07:34,194 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9611 Process Time: 0.433 Mem R(MA/MR): 9734 (21268/36094) [2025-04-29 09:07:35,921 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6802 Process Time: 0.273 Mem R(MA/MR): 13890 (21268/36094) [2025-04-29 09:07:36,354 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.7849 Process Time: 0.150 Mem R(MA/MR): 6508 (21268/36094) [2025-04-29 09:07:39,842 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8479 Process Time: 0.413 Mem R(MA/MR): 28226 (21268/36094) [2025-04-29 09:07:42,104 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.3475 Process Time: 0.591 Mem R(MA/MR): 10512 (21268/36094) [2025-04-29 09:07:42,760 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0156 Process Time: 0.248 Mem R(MA/MR): 5442 (21268/36094) [2025-04-29 09:07:43,895 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9924 Process Time: 0.230 Mem R(MA/MR): 10106 (21268/36094) [2025-04-29 09:07:44,890 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.8200 Process Time: 0.207 Mem R(MA/MR): 8878 (21268/36094) [2025-04-29 09:07:45,481 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.5080 Process Time: 0.150 Mem R(MA/MR): 5474 (21268/36094) [2025-04-29 09:07:45,947 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8387 Process Time: 0.166 Mem R(MA/MR): 5510 (21268/36094) [2025-04-29 09:07:46,579 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.0629 Process Time: 0.176 Mem R(MA/MR): 7034 (21268/36094) [2025-04-29 09:07:47,283 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5147 Process Time: 0.215 Mem R(MA/MR): 5252 (21268/36094) [2025-04-29 09:07:50,460 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.7597 Process Time: 1.029 Mem R(MA/MR): 14352 (21268/36094) [2025-04-29 09:07:59,628 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.6371 Process Time: 1.577 Mem R(MA/MR): 20158 (21268/36094) [2025-04-29 09:08:10,976 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.0254 Process Time: 1.847 Mem R(MA/MR): 35436 (21268/36094) [2025-04-29 09:08:11,761 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.7664 Process Time: 0.280 Mem R(MA/MR): 5544 (21268/36094) [2025-04-29 09:08:13,878 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1115 Process Time: 0.392 Mem R(MA/MR): 13496 (21268/36094) [2025-04-29 09:08:18,733 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 09:08:18,734 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 09:08:18,734 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] table : 0.265 0.600 0.761 0.776 0.610 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] door : 0.431 0.730 0.922 0.855 0.747 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] ceiling lamp : 0.596 0.797 0.902 0.864 0.773 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] cabinet : 0.361 0.506 0.556 0.642 0.507 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] blinds : 0.587 0.794 0.827 0.741 0.870 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] curtain : 0.228 0.449 0.595 0.600 0.500 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] chair : 0.622 0.775 0.832 0.800 0.738 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] storage cabinet: 0.286 0.508 0.612 0.500 0.640 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] office chair : 0.686 0.733 0.719 0.705 0.896 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] bookshelf : 0.359 0.687 0.720 0.800 0.727 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] whiteboard : 0.530 0.730 0.767 0.923 0.686 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] window : 0.113 0.266 0.584 0.587 0.297 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] box : 0.180 0.338 0.529 0.500 0.414 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] monitor : 0.617 0.785 0.824 0.981 0.757 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] shelf : 0.125 0.261 0.512 0.571 0.267 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] heater : 0.468 0.705 0.869 0.839 0.684 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] kitchen cabinet: 0.227 0.529 0.793 0.765 0.520 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] sofa : 0.483 0.753 0.930 0.900 0.750 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] bed : 0.274 0.566 0.839 1.000 0.500 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] trash can : 0.606 0.760 0.777 0.810 0.785 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] book : 0.023 0.039 0.077 0.333 0.082 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] plant : 0.508 0.768 0.814 1.000 0.722 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] blanket : 0.574 0.717 0.717 0.889 0.727 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] tv : 0.918 1.000 1.000 1.000 1.000 [2025-04-29 09:08:18,734 INFO hook.py line 395 1619929] computer tower : 0.264 0.444 0.688 0.714 0.476 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] refrigerator : 0.241 0.482 0.500 0.800 0.444 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] jacket : 0.081 0.160 0.467 0.296 0.727 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] sink : 0.454 0.734 0.866 0.842 0.727 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] bag : 0.123 0.160 0.206 0.375 0.333 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] picture : 0.176 0.365 0.437 0.531 0.436 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] pillow : 0.565 0.785 0.832 0.923 0.632 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] towel : 0.202 0.343 0.592 0.556 0.395 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] suitcase : 0.340 0.364 0.387 0.600 0.429 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] backpack : 0.411 0.468 0.468 0.583 0.538 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] crate : 0.061 0.196 0.634 0.400 0.364 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] keyboard : 0.426 0.619 0.661 0.634 0.667 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] toilet : 0.862 0.889 1.000 1.000 0.889 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] printer : 0.240 0.390 0.420 0.556 0.556 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] microwave : 0.315 0.612 0.875 0.545 0.750 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] shoes : 0.118 0.269 0.524 0.737 0.341 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] socket : 0.179 0.434 0.683 0.619 0.464 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] bottle : 0.094 0.172 0.261 0.442 0.277 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] bucket : 0.118 0.120 0.120 0.217 0.714 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] cushion : 0.240 0.290 0.288 0.357 0.833 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.036 0.000 0.000 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] shoe rack : 0.111 0.500 0.500 1.000 0.500 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] telephone : 0.206 0.588 0.631 1.000 0.588 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] laptop : 0.231 0.428 0.517 0.625 0.625 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] plant pot : 0.149 0.325 0.459 0.529 0.562 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] exhaust fan : 0.250 0.400 0.400 0.700 0.467 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] cup : 0.163 0.290 0.352 0.500 0.318 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] coat hanger : 0.076 0.354 0.613 0.500 0.500 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] light switch : 0.267 0.567 0.695 0.878 0.554 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] speaker : 0.139 0.304 0.489 0.400 0.545 [2025-04-29 09:08:18,735 INFO hook.py line 395 1619929] table lamp : 0.722 1.000 1.000 1.000 1.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] smoke detector : 0.623 0.781 0.783 0.947 0.750 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] power strip : 0.021 0.031 0.074 0.182 0.200 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] mouse : 0.454 0.663 0.719 0.952 0.625 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] toilet paper : 0.207 0.344 0.502 0.857 0.353 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] paper towel : 0.014 0.125 0.125 1.000 0.125 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] clock : 0.539 0.903 0.903 0.750 1.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 1.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] tap : 0.192 0.387 0.714 0.500 0.444 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] soap dispenser : 0.483 0.800 0.800 1.000 0.800 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] whiteboard eraser: 0.253 0.563 0.563 0.800 0.667 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] toilet brush : 0.558 0.667 0.833 1.000 0.667 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] spray bottle : 0.008 0.013 0.014 0.100 0.250 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] headphones : 0.352 0.633 0.662 1.000 0.500 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] stapler : 0.003 0.028 0.139 0.167 0.333 [2025-04-29 09:08:18,736 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:08:18,736 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 09:08:18,736 INFO hook.py line 404 1619929] average : 0.265 0.414 0.504 0.591 0.472 [2025-04-29 09:08:18,736 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 09:08:18,737 INFO hook.py line 480 1619929] Total Process Time: 24.924 s [2025-04-29 09:08:18,737 INFO hook.py line 481 1619929] Average Process Time: 502.789 ms [2025-04-29 09:08:18,737 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 09:08:18,782 INFO hook.py line 685 1619929] Currently Best AP50: 0.418 [2025-04-29 09:08:18,787 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:09:51,014 INFO hook.py line 650 1619929] Train: [289/512][50/242] Data 0.017 (0.038) Batch 1.478 (1.498) Remain 22:32:10 loss: 4.6549 Lr: 1.42522e-04 Mem R(MA/MR): 22856 (21268/36094) [2025-04-29 09:11:04,041 INFO hook.py line 650 1619929] Train: [289/512][100/242] Data 0.017 (0.027) Batch 1.649 (1.479) Remain 22:13:29 loss: 6.0722 Lr: 1.42404e-04 Mem R(MA/MR): 24684 (21268/36094) [2025-04-29 09:12:17,172 INFO hook.py line 650 1619929] Train: [289/512][150/242] Data 0.015 (0.023) Batch 1.549 (1.473) Remain 22:07:20 loss: 6.1325 Lr: 1.42286e-04 Mem R(MA/MR): 26752 (21268/36094) [2025-04-29 09:13:28,233 INFO hook.py line 650 1619929] Train: [289/512][200/242] Data 0.015 (0.022) Batch 1.341 (1.460) Remain 21:54:13 loss: 5.6757 Lr: 1.42167e-04 Mem R(MA/MR): 26752 (21268/36094) [2025-04-29 09:14:26,825 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3166 loss_mask: 0.0361 loss_dice: 1.9823 loss_score: 0.0000 loss_bbox: 0.0507 loss_sp_cls: 0.7933 loss: 5.1055 [2025-04-29 09:14:30,820 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:16:07,234 INFO hook.py line 650 1619929] Train: [290/512][50/242] Data 0.017 (0.017) Batch 1.600 (1.514) Remain 22:40:53 loss: 5.0166 Lr: 1.41949e-04 Mem R(MA/MR): 20704 (21268/36094) [2025-04-29 09:17:20,804 INFO hook.py line 650 1619929] Train: [290/512][100/242] Data 0.018 (0.017) Batch 1.555 (1.492) Remain 22:19:41 loss: 5.6699 Lr: 1.41831e-04 Mem R(MA/MR): 24374 (21268/36094) [2025-04-29 09:18:32,470 INFO hook.py line 650 1619929] Train: [290/512][150/242] Data 0.015 (0.016) Batch 1.460 (1.472) Remain 22:00:28 loss: 5.5955 Lr: 1.41713e-04 Mem R(MA/MR): 24378 (21268/36094) [2025-04-29 09:19:43,324 INFO hook.py line 650 1619929] Train: [290/512][200/242] Data 0.043 (0.016) Batch 1.448 (1.458) Remain 21:46:42 loss: 5.0905 Lr: 1.41594e-04 Mem R(MA/MR): 24378 (21268/36094) [2025-04-29 09:20:39,569 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3105 loss_mask: 0.0362 loss_dice: 1.9920 loss_score: 0.0000 loss_bbox: 0.0494 loss_sp_cls: 0.7889 loss: 5.0942 [2025-04-29 09:20:39,650 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:22:06,492 INFO hook.py line 650 1619929] Train: [291/512][50/242] Data 0.016 (0.017) Batch 1.450 (1.457) Remain 21:43:12 loss: 4.0565 Lr: 1.41376e-04 Mem R(MA/MR): 25960 (21268/36094) [2025-04-29 09:23:17,996 INFO hook.py line 650 1619929] Train: [291/512][100/242] Data 0.017 (0.017) Batch 1.400 (1.443) Remain 21:29:43 loss: 5.7968 Lr: 1.41258e-04 Mem R(MA/MR): 25960 (21268/36094) [2025-04-29 09:24:31,132 INFO hook.py line 650 1619929] Train: [291/512][150/242] Data 0.015 (0.017) Batch 1.429 (1.450) Remain 21:34:29 loss: 5.2519 Lr: 1.41139e-04 Mem R(MA/MR): 27908 (21268/36094) [2025-04-29 09:25:45,188 INFO hook.py line 650 1619929] Train: [291/512][200/242] Data 0.016 (0.017) Batch 1.516 (1.458) Remain 21:40:22 loss: 6.5786 Lr: 1.41021e-04 Mem R(MA/MR): 27908 (21268/36094) [2025-04-29 09:26:43,016 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3098 loss_mask: 0.0365 loss_dice: 1.9822 loss_score: 0.0000 loss_bbox: 0.0502 loss_sp_cls: 0.7897 loss: 5.0840 [2025-04-29 09:26:43,088 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:28:16,847 INFO hook.py line 650 1619929] Train: [292/512][50/242] Data 0.017 (0.017) Batch 1.515 (1.469) Remain 21:48:35 loss: 4.7436 Lr: 1.40803e-04 Mem R(MA/MR): 20498 (21268/36094) [2025-04-29 09:29:32,628 INFO hook.py line 650 1619929] Train: [292/512][100/242] Data 0.015 (0.017) Batch 1.492 (1.493) Remain 22:08:30 loss: 4.8744 Lr: 1.40684e-04 Mem R(MA/MR): 22106 (21268/36094) [2025-04-29 09:30:44,892 INFO hook.py line 650 1619929] Train: [292/512][150/242] Data 0.017 (0.017) Batch 1.615 (1.477) Remain 21:52:47 loss: 4.6869 Lr: 1.40566e-04 Mem R(MA/MR): 22106 (21268/36094) [2025-04-29 09:31:59,048 INFO hook.py line 650 1619929] Train: [292/512][200/242] Data 0.016 (0.017) Batch 1.466 (1.479) Remain 21:52:57 loss: 5.0907 Lr: 1.40447e-04 Mem R(MA/MR): 23878 (21268/36094) [2025-04-29 09:32:57,021 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3155 loss_mask: 0.0364 loss_dice: 1.9918 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.7873 loss: 5.1091 [2025-04-29 09:32:58,421 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:34:27,923 INFO hook.py line 650 1619929] Train: [293/512][50/242] Data 0.017 (0.017) Batch 1.408 (1.542) Remain 22:46:39 loss: 3.9123 Lr: 1.40229e-04 Mem R(MA/MR): 21946 (21268/36094) [2025-04-29 09:35:41,353 INFO hook.py line 650 1619929] Train: [293/512][100/242] Data 0.016 (0.017) Batch 1.567 (1.504) Remain 22:12:00 loss: 5.4715 Lr: 1.40111e-04 Mem R(MA/MR): 25458 (21268/36094) [2025-04-29 09:36:53,454 INFO hook.py line 650 1619929] Train: [293/512][150/242] Data 0.016 (0.017) Batch 1.418 (1.483) Remain 21:52:07 loss: 6.1189 Lr: 1.39992e-04 Mem R(MA/MR): 27368 (21268/36094) [2025-04-29 09:38:05,362 INFO hook.py line 650 1619929] Train: [293/512][200/242] Data 0.015 (0.017) Batch 1.426 (1.472) Remain 21:40:50 loss: 6.2825 Lr: 1.39873e-04 Mem R(MA/MR): 27368 (21268/36094) [2025-04-29 09:39:03,221 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3147 loss_mask: 0.0371 loss_dice: 1.9977 loss_score: 0.0000 loss_bbox: 0.0500 loss_sp_cls: 0.7940 loss: 5.1290 [2025-04-29 09:39:08,291 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:40:43,096 INFO hook.py line 650 1619929] Train: [294/512][50/242] Data 0.016 (0.016) Batch 1.452 (1.476) Remain 21:42:36 loss: 5.3676 Lr: 1.39655e-04 Mem R(MA/MR): 20970 (21268/36094) [2025-04-29 09:41:55,892 INFO hook.py line 650 1619929] Train: [294/512][100/242] Data 0.016 (0.017) Batch 1.637 (1.466) Remain 21:32:10 loss: 4.9780 Lr: 1.39536e-04 Mem R(MA/MR): 23974 (21268/36094) [2025-04-29 09:43:11,661 INFO hook.py line 650 1619929] Train: [294/512][150/242] Data 0.017 (0.017) Batch 1.474 (1.483) Remain 21:45:51 loss: 4.1017 Lr: 1.39418e-04 Mem R(MA/MR): 25746 (21268/36094) [2025-04-29 09:44:23,614 INFO hook.py line 650 1619929] Train: [294/512][200/242] Data 0.016 (0.017) Batch 1.492 (1.472) Remain 21:34:54 loss: 5.1526 Lr: 1.39299e-04 Mem R(MA/MR): 27714 (21268/36094) [2025-04-29 09:45:20,828 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3065 loss_mask: 0.0358 loss_dice: 1.9717 loss_score: 0.0000 loss_bbox: 0.0502 loss_sp_cls: 0.7896 loss: 5.0515 [2025-04-29 09:45:22,242 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:46:57,575 INFO hook.py line 650 1619929] Train: [295/512][50/242] Data 0.015 (0.017) Batch 1.663 (1.479) Remain 21:39:11 loss: 4.6654 Lr: 1.39081e-04 Mem R(MA/MR): 23116 (21268/36094) [2025-04-29 09:48:10,528 INFO hook.py line 650 1619929] Train: [295/512][100/242] Data 0.017 (0.017) Batch 1.582 (1.469) Remain 21:28:56 loss: 5.9833 Lr: 1.38962e-04 Mem R(MA/MR): 26788 (21268/36094) [2025-04-29 09:49:25,541 INFO hook.py line 650 1619929] Train: [295/512][150/242] Data 0.018 (0.017) Batch 1.485 (1.479) Remain 21:37:07 loss: 4.7117 Lr: 1.38844e-04 Mem R(MA/MR): 26788 (21268/36094) [2025-04-29 09:50:41,355 INFO hook.py line 650 1619929] Train: [295/512][200/242] Data 0.015 (0.017) Batch 1.451 (1.489) Remain 21:44:05 loss: 5.3809 Lr: 1.38725e-04 Mem R(MA/MR): 26788 (21268/36094) [2025-04-29 09:51:38,277 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3004 loss_mask: 0.0351 loss_dice: 1.9529 loss_score: 0.0000 loss_bbox: 0.0490 loss_sp_cls: 0.7722 loss: 4.9939 [2025-04-29 09:51:39,125 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 09:53:13,646 INFO hook.py line 650 1619929] Train: [296/512][50/242] Data 0.018 (0.016) Batch 1.437 (1.464) Remain 21:19:44 loss: 4.8083 Lr: 1.38506e-04 Mem R(MA/MR): 20166 (21268/36094) [2025-04-29 09:54:28,634 INFO hook.py line 650 1619929] Train: [296/512][100/242] Data 0.015 (0.017) Batch 1.528 (1.482) Remain 21:34:48 loss: 4.7491 Lr: 1.38388e-04 Mem R(MA/MR): 21920 (21268/36094) [2025-04-29 09:55:40,524 INFO hook.py line 650 1619929] Train: [296/512][150/242] Data 0.016 (0.017) Batch 1.452 (1.467) Remain 21:20:24 loss: 3.9952 Lr: 1.38269e-04 Mem R(MA/MR): 21920 (21268/36094) [2025-04-29 09:56:55,621 INFO hook.py line 650 1619929] Train: [296/512][200/242] Data 0.015 (0.017) Batch 1.451 (1.476) Remain 21:26:53 loss: 5.3317 Lr: 1.38150e-04 Mem R(MA/MR): 21920 (21268/36094) [2025-04-29 09:57:52,696 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2994 loss_mask: 0.0342 loss_dice: 1.9356 loss_score: 0.0000 loss_bbox: 0.0491 loss_sp_cls: 0.7744 loss: 4.9660 [2025-04-29 09:57:55,523 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 09:57:57,936 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0068 Process Time: 0.322 Mem R(MA/MR): 4516 (21268/36094) [2025-04-29 09:57:59,610 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9629 Process Time: 0.532 Mem R(MA/MR): 7302 (21268/36094) [2025-04-29 09:58:01,343 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.7176 Process Time: 0.686 Mem R(MA/MR): 9980 (21268/36094) [2025-04-29 09:58:08,221 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.2362 Process Time: 0.761 Mem R(MA/MR): 19430 (21268/36094) [2025-04-29 09:58:08,939 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4511 Process Time: 0.199 Mem R(MA/MR): 6918 (21268/36094) [2025-04-29 09:58:10,299 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6041 Process Time: 0.335 Mem R(MA/MR): 11692 (21268/36094) [2025-04-29 09:58:11,107 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0763 Process Time: 0.354 Mem R(MA/MR): 6538 (21268/36094) [2025-04-29 09:58:11,528 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5553 Process Time: 0.121 Mem R(MA/MR): 4516 (21268/36094) [2025-04-29 09:58:12,391 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6067 Process Time: 0.257 Mem R(MA/MR): 11590 (21268/36094) [2025-04-29 09:58:14,004 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7248 Process Time: 0.423 Mem R(MA/MR): 9676 (21268/36094) [2025-04-29 09:58:16,345 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2575 Process Time: 0.349 Mem R(MA/MR): 18634 (21268/36094) [2025-04-29 09:58:19,014 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1522 Process Time: 0.714 Mem R(MA/MR): 15362 (21268/36094) [2025-04-29 09:58:20,343 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2439 Process Time: 0.291 Mem R(MA/MR): 8512 (21268/36094) [2025-04-29 09:58:20,823 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.3298 Process Time: 0.184 Mem R(MA/MR): 4784 (21268/36094) [2025-04-29 09:58:24,076 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4194 Process Time: 0.470 Mem R(MA/MR): 16708 (21268/36094) [2025-04-29 09:58:25,858 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.9314 Process Time: 0.516 Mem R(MA/MR): 14652 (21268/36094) [2025-04-29 09:58:26,642 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.5899 Process Time: 0.257 Mem R(MA/MR): 6822 (21268/36094) [2025-04-29 09:58:27,608 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7447 Process Time: 0.329 Mem R(MA/MR): 8058 (21268/36094) [2025-04-29 09:58:29,048 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6102 Process Time: 0.291 Mem R(MA/MR): 6224 (21268/36094) [2025-04-29 09:58:30,818 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.1467 Process Time: 0.507 Mem R(MA/MR): 11684 (21268/36094) [2025-04-29 09:58:38,815 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.4295 Process Time: 0.517 Mem R(MA/MR): 23674 (21268/36094) [2025-04-29 09:58:39,451 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.8814 Process Time: 0.224 Mem R(MA/MR): 6974 (21268/36094) [2025-04-29 09:58:48,743 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.0419 Process Time: 0.311 Mem R(MA/MR): 10194 (21268/36094) [2025-04-29 09:58:49,278 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.5582 Process Time: 0.157 Mem R(MA/MR): 5406 (21268/36094) [2025-04-29 09:58:50,253 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8075 Process Time: 0.260 Mem R(MA/MR): 9574 (21268/36094) [2025-04-29 09:58:57,989 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.2493 Process Time: 1.749 Mem R(MA/MR): 31834 (21268/36094) [2025-04-29 09:59:00,097 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5924 Process Time: 0.299 Mem R(MA/MR): 9978 (21268/36094) [2025-04-29 09:59:01,502 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.2195 Process Time: 0.375 Mem R(MA/MR): 8796 (21268/36094) [2025-04-29 09:59:06,679 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.1766 Process Time: 0.693 Mem R(MA/MR): 17160 (21268/36094) [2025-04-29 09:59:07,467 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2907 Process Time: 0.185 Mem R(MA/MR): 7700 (21268/36094) [2025-04-29 09:59:10,931 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.9988 Process Time: 0.384 Mem R(MA/MR): 20296 (21268/36094) [2025-04-29 09:59:11,596 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.6384 Process Time: 0.261 Mem R(MA/MR): 3936 (21268/36094) [2025-04-29 09:59:15,737 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.2822 Process Time: 0.716 Mem R(MA/MR): 24496 (21268/36094) [2025-04-29 09:59:16,662 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.3370 Process Time: 0.276 Mem R(MA/MR): 9866 (21268/36094) [2025-04-29 09:59:18,369 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6107 Process Time: 0.274 Mem R(MA/MR): 14268 (21268/36094) [2025-04-29 09:59:19,347 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0850 Process Time: 0.471 Mem R(MA/MR): 6702 (21268/36094) [2025-04-29 09:59:22,875 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.0392 Process Time: 0.667 Mem R(MA/MR): 27998 (21268/36094) [2025-04-29 09:59:24,116 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.4368 Process Time: 0.239 Mem R(MA/MR): 10710 (21268/36094) [2025-04-29 09:59:24,551 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.5241 Process Time: 0.144 Mem R(MA/MR): 5904 (21268/36094) [2025-04-29 09:59:25,524 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.3096 Process Time: 0.215 Mem R(MA/MR): 10292 (21268/36094) [2025-04-29 09:59:26,465 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.9017 Process Time: 0.233 Mem R(MA/MR): 8922 (21268/36094) [2025-04-29 09:59:27,179 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1908 Process Time: 0.250 Mem R(MA/MR): 5512 (21268/36094) [2025-04-29 09:59:27,869 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5531 Process Time: 0.276 Mem R(MA/MR): 5570 (21268/36094) [2025-04-29 09:59:28,709 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1494 Process Time: 0.347 Mem R(MA/MR): 7180 (21268/36094) [2025-04-29 09:59:29,425 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7840 Process Time: 0.186 Mem R(MA/MR): 5356 (21268/36094) [2025-04-29 09:59:31,925 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.7319 Process Time: 0.559 Mem R(MA/MR): 15048 (21268/36094) [2025-04-29 09:59:37,704 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.4629 Process Time: 0.485 Mem R(MA/MR): 20064 (21268/36094) [2025-04-29 09:59:48,658 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9715 Process Time: 1.983 Mem R(MA/MR): 35216 (21268/36094) [2025-04-29 09:59:49,362 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.4469 Process Time: 0.189 Mem R(MA/MR): 6278 (21268/36094) [2025-04-29 09:59:51,367 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2580 Process Time: 0.258 Mem R(MA/MR): 13936 (21268/36094) [2025-04-29 09:59:55,488 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 09:59:55,488 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 09:59:55,488 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 09:59:55,488 INFO hook.py line 395 1619929] table : 0.251 0.547 0.745 0.775 0.581 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] door : 0.499 0.759 0.910 0.836 0.772 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] ceiling lamp : 0.588 0.786 0.904 0.883 0.751 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] cabinet : 0.348 0.475 0.537 0.600 0.493 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] blinds : 0.604 0.880 0.878 0.870 0.870 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] curtain : 0.268 0.415 0.620 0.400 0.667 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] chair : 0.594 0.711 0.769 0.820 0.615 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] storage cabinet: 0.320 0.460 0.573 0.667 0.480 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] office chair : 0.533 0.564 0.578 0.698 0.771 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] bookshelf : 0.327 0.572 0.647 0.667 0.545 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] whiteboard : 0.566 0.751 0.751 1.000 0.657 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] window : 0.145 0.308 0.625 0.550 0.363 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] box : 0.189 0.362 0.555 0.488 0.442 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] monitor : 0.616 0.777 0.836 0.887 0.786 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] shelf : 0.078 0.194 0.382 0.241 0.467 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] heater : 0.461 0.730 0.834 0.780 0.842 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] kitchen cabinet: 0.141 0.393 0.727 0.464 0.520 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] sofa : 0.497 0.773 0.841 1.000 0.667 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] bed : 0.127 0.477 0.835 0.667 0.500 [2025-04-29 09:59:55,489 INFO hook.py line 395 1619929] trash can : 0.548 0.724 0.724 0.877 0.769 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] book : 0.027 0.050 0.094 0.239 0.097 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] plant : 0.494 0.630 0.694 0.846 0.611 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] blanket : 0.506 0.633 0.692 0.875 0.636 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] tv : 0.956 1.000 1.000 1.000 1.000 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] computer tower : 0.213 0.325 0.639 0.515 0.405 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] refrigerator : 0.313 0.667 0.684 0.583 0.778 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] jacket : 0.074 0.191 0.461 0.308 0.727 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] sink : 0.409 0.611 0.800 0.789 0.682 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] bag : 0.095 0.148 0.184 0.312 0.370 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] picture : 0.128 0.290 0.382 0.565 0.333 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] pillow : 0.593 0.815 0.815 0.762 0.842 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] towel : 0.230 0.369 0.545 0.571 0.421 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] suitcase : 0.400 0.477 0.477 0.667 0.571 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] backpack : 0.351 0.513 0.612 0.778 0.538 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] crate : 0.102 0.535 0.535 0.750 0.545 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] keyboard : 0.415 0.682 0.757 0.794 0.692 [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 09:59:55,490 INFO hook.py line 395 1619929] toilet : 0.774 0.889 1.000 1.000 0.889 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] printer : 0.319 0.411 0.478 0.667 0.444 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.006 0.077 0.111 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] painting : 0.057 0.062 0.071 0.125 1.000 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] microwave : 0.552 0.875 1.000 1.000 0.875 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] shoes : 0.109 0.209 0.482 0.533 0.390 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] socket : 0.219 0.482 0.653 0.770 0.479 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] bottle : 0.123 0.197 0.308 0.621 0.217 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] bucket : 0.322 0.348 0.364 0.292 1.000 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] cushion : 0.121 0.277 0.305 0.357 0.833 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] basket : 0.017 0.024 0.024 0.333 0.143 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] shoe rack : 0.014 0.125 1.000 0.500 0.500 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] telephone : 0.209 0.445 0.761 0.636 0.412 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] laptop : 0.336 0.585 0.892 0.545 0.750 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] plant pot : 0.126 0.359 0.500 0.429 0.562 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] exhaust fan : 0.135 0.292 0.292 0.625 0.333 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] cup : 0.234 0.400 0.446 0.941 0.364 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] coat hanger : 0.412 0.750 0.750 1.000 0.750 [2025-04-29 09:59:55,491 INFO hook.py line 395 1619929] light switch : 0.264 0.522 0.661 0.816 0.477 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] speaker : 0.432 0.478 0.485 1.000 0.455 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] kettle : 0.280 0.451 0.581 0.750 0.500 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] smoke detector : 0.631 0.828 0.829 1.000 0.792 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] power strip : 0.096 0.208 0.218 0.571 0.400 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] paper bag : 0.071 0.071 0.083 0.143 1.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] mouse : 0.444 0.628 0.733 0.700 0.656 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] cutting board : 0.306 0.500 0.500 1.000 0.500 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] toilet paper : 0.269 0.395 0.471 0.875 0.412 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] paper towel : 0.014 0.125 0.125 1.000 0.125 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] clock : 0.504 0.711 0.764 0.600 1.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 1.000 0.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] tap : 0.147 0.244 0.477 0.600 0.333 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,492 INFO hook.py line 395 1619929] soap dispenser : 0.359 0.452 0.452 1.000 0.400 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] bowl : 0.037 0.333 0.472 1.000 0.333 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] whiteboard eraser: 0.169 0.446 0.446 0.800 0.667 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] toilet brush : 0.530 0.718 0.907 1.000 0.667 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] spray bottle : 0.013 0.021 0.021 0.167 0.250 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] headphones : 0.327 0.613 0.613 1.000 0.500 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] stapler : 0.002 0.015 0.065 0.091 0.333 [2025-04-29 09:59:55,493 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 09:59:55,493 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 09:59:55,493 INFO hook.py line 404 1619929] average : 0.273 0.422 0.520 0.623 0.514 [2025-04-29 09:59:55,493 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 09:59:55,494 INFO hook.py line 480 1619929] Total Process Time: 21.080 s [2025-04-29 09:59:55,494 INFO hook.py line 481 1619929] Average Process Time: 423.632 ms [2025-04-29 09:59:55,496 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 09:59:55,543 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.422 [2025-04-29 09:59:55,549 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 09:59:55,549 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:01:24,317 INFO hook.py line 650 1619929] Train: [297/512][50/242] Data 0.016 (0.017) Batch 1.457 (1.495) Remain 21:41:31 loss: 4.7722 Lr: 1.37932e-04 Mem R(MA/MR): 25152 (21268/36094) [2025-04-29 10:02:38,001 INFO hook.py line 650 1619929] Train: [297/512][100/242] Data 0.017 (0.017) Batch 1.462 (1.484) Remain 21:30:32 loss: 5.3652 Lr: 1.37813e-04 Mem R(MA/MR): 25152 (21268/36094) [2025-04-29 10:03:53,713 INFO hook.py line 650 1619929] Train: [297/512][150/242] Data 0.018 (0.017) Batch 1.376 (1.494) Remain 21:38:11 loss: 5.5484 Lr: 1.37694e-04 Mem R(MA/MR): 25170 (21268/36094) [2025-04-29 10:05:04,934 INFO hook.py line 650 1619929] Train: [297/512][200/242] Data 0.016 (0.022) Batch 1.399 (1.477) Remain 21:21:31 loss: 4.3599 Lr: 1.37575e-04 Mem R(MA/MR): 25170 (21268/36094) [2025-04-29 10:06:02,879 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3006 loss_mask: 0.0351 loss_dice: 1.9510 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7735 loss: 4.9970 [2025-04-29 10:06:05,681 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:07:38,821 INFO hook.py line 650 1619929] Train: [298/512][50/242] Data 0.017 (0.016) Batch 1.321 (1.437) Remain 20:44:54 loss: 4.5491 Lr: 1.37357e-04 Mem R(MA/MR): 19938 (21268/36094) [2025-04-29 10:08:50,434 INFO hook.py line 650 1619929] Train: [298/512][100/242] Data 0.017 (0.016) Batch 1.500 (1.435) Remain 20:41:35 loss: 5.2562 Lr: 1.37238e-04 Mem R(MA/MR): 19942 (21268/36094) [2025-04-29 10:10:05,033 INFO hook.py line 650 1619929] Train: [298/512][150/242] Data 0.015 (0.017) Batch 1.472 (1.454) Remain 20:57:17 loss: 4.5562 Lr: 1.37119e-04 Mem R(MA/MR): 22132 (21268/36094) [2025-04-29 10:11:15,922 INFO hook.py line 650 1619929] Train: [298/512][200/242] Data 0.013 (0.017) Batch 1.366 (1.445) Remain 20:48:08 loss: 3.8125 Lr: 1.37000e-04 Mem R(MA/MR): 22132 (21268/36094) [2025-04-29 10:12:13,163 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2978 loss_mask: 0.0344 loss_dice: 1.9551 loss_score: 0.0000 loss_bbox: 0.0489 loss_sp_cls: 0.7726 loss: 4.9900 [2025-04-29 10:12:14,537 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:13:48,861 INFO hook.py line 650 1619929] Train: [299/512][50/242] Data 0.016 (0.016) Batch 1.315 (1.427) Remain 20:30:08 loss: 4.2539 Lr: 1.36781e-04 Mem R(MA/MR): 20896 (21268/36094) [2025-04-29 10:14:59,002 INFO hook.py line 650 1619929] Train: [299/512][100/242] Data 0.016 (0.017) Batch 1.472 (1.414) Remain 20:18:25 loss: 5.3136 Lr: 1.36662e-04 Mem R(MA/MR): 20898 (21268/36094) [2025-04-29 10:16:10,158 INFO hook.py line 650 1619929] Train: [299/512][150/242] Data 0.016 (0.016) Batch 1.446 (1.417) Remain 20:19:48 loss: 5.5488 Lr: 1.36544e-04 Mem R(MA/MR): 22952 (21268/36094) [2025-04-29 10:17:23,498 INFO hook.py line 650 1619929] Train: [299/512][200/242] Data 0.015 (0.016) Batch 1.354 (1.430) Remain 20:29:25 loss: 5.6203 Lr: 1.36425e-04 Mem R(MA/MR): 22952 (21268/36094) [2025-04-29 10:18:20,946 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3008 loss_mask: 0.0347 loss_dice: 1.9546 loss_score: 0.0000 loss_bbox: 0.0496 loss_sp_cls: 0.7715 loss: 5.0014 [2025-04-29 10:18:21,937 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:19:58,279 INFO hook.py line 650 1619929] Train: [300/512][50/242] Data 0.016 (0.017) Batch 1.342 (1.509) Remain 21:35:10 loss: 4.6157 Lr: 1.36206e-04 Mem R(MA/MR): 22396 (21268/36094) [2025-04-29 10:21:11,295 INFO hook.py line 650 1619929] Train: [300/512][100/242] Data 0.015 (0.017) Batch 1.391 (1.484) Remain 21:12:22 loss: 5.0712 Lr: 1.36087e-04 Mem R(MA/MR): 22408 (21268/36094) [2025-04-29 10:22:24,030 INFO hook.py line 650 1619929] Train: [300/512][150/242] Data 0.017 (0.017) Batch 1.493 (1.474) Remain 21:02:37 loss: 5.5509 Lr: 1.35968e-04 Mem R(MA/MR): 22408 (21268/36094) [2025-04-29 10:23:34,506 INFO hook.py line 650 1619929] Train: [300/512][200/242] Data 0.016 (0.017) Batch 1.369 (1.458) Remain 20:47:23 loss: 5.8397 Lr: 1.35849e-04 Mem R(MA/MR): 22408 (21268/36094) [2025-04-29 10:24:30,843 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3034 loss_mask: 0.0355 loss_dice: 1.9684 loss_score: 0.0000 loss_bbox: 0.0496 loss_sp_cls: 0.7786 loss: 5.0331 [2025-04-29 10:24:31,383 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:26:02,589 INFO hook.py line 650 1619929] Train: [301/512][50/242] Data 0.015 (0.018) Batch 1.400 (1.425) Remain 20:17:11 loss: 4.6350 Lr: 1.35630e-04 Mem R(MA/MR): 22194 (21268/36094) [2025-04-29 10:27:13,679 INFO hook.py line 650 1619929] Train: [301/512][100/242] Data 0.016 (0.017) Batch 1.494 (1.423) Remain 20:14:39 loss: 3.5554 Lr: 1.35511e-04 Mem R(MA/MR): 22194 (21268/36094) [2025-04-29 10:28:25,934 INFO hook.py line 650 1619929] Train: [301/512][150/242] Data 0.016 (0.017) Batch 1.426 (1.431) Remain 20:19:46 loss: 5.4177 Lr: 1.35392e-04 Mem R(MA/MR): 25678 (21268/36094) [2025-04-29 10:29:38,356 INFO hook.py line 650 1619929] Train: [301/512][200/242] Data 0.015 (0.017) Batch 1.325 (1.435) Remain 20:22:25 loss: 4.5545 Lr: 1.35273e-04 Mem R(MA/MR): 25678 (21268/36094) [2025-04-29 10:30:37,074 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3023 loss_mask: 0.0356 loss_dice: 1.9678 loss_score: 0.0000 loss_bbox: 0.0495 loss_sp_cls: 0.7774 loss: 5.0256 [2025-04-29 10:30:39,981 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:32:13,316 INFO hook.py line 650 1619929] Train: [302/512][50/242] Data 0.015 (0.016) Batch 1.442 (1.494) Remain 21:10:19 loss: 4.1073 Lr: 1.35054e-04 Mem R(MA/MR): 19716 (21268/36094) [2025-04-29 10:33:24,703 INFO hook.py line 650 1619929] Train: [302/512][100/242] Data 0.016 (0.016) Batch 1.401 (1.460) Remain 20:39:59 loss: 4.8276 Lr: 1.34935e-04 Mem R(MA/MR): 19748 (21268/36094) [2025-04-29 10:34:34,914 INFO hook.py line 650 1619929] Train: [302/512][150/242] Data 0.016 (0.016) Batch 1.659 (1.441) Remain 20:22:42 loss: 5.6643 Lr: 1.34816e-04 Mem R(MA/MR): 19748 (21268/36094) [2025-04-29 10:35:49,975 INFO hook.py line 650 1619929] Train: [302/512][200/242] Data 0.015 (0.016) Batch 1.607 (1.456) Remain 20:34:28 loss: 5.8603 Lr: 1.34699e-04 Mem R(MA/MR): 21634 (21268/36094) [2025-04-29 10:36:46,953 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3026 loss_mask: 0.0359 loss_dice: 1.9581 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7729 loss: 5.0128 [2025-04-29 10:36:48,545 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:38:17,505 INFO hook.py line 650 1619929] Train: [303/512][50/242] Data 0.015 (0.016) Batch 1.408 (1.441) Remain 20:19:38 loss: 4.8815 Lr: 1.34480e-04 Mem R(MA/MR): 24068 (21268/36094) [2025-04-29 10:39:29,103 INFO hook.py line 650 1619929] Train: [303/512][100/242] Data 0.016 (0.016) Batch 1.314 (1.436) Remain 20:14:18 loss: 4.1909 Lr: 1.34361e-04 Mem R(MA/MR): 24072 (21268/36094) [2025-04-29 10:40:40,359 INFO hook.py line 650 1619929] Train: [303/512][150/242] Data 0.016 (0.016) Batch 1.359 (1.433) Remain 20:09:51 loss: 5.4254 Lr: 1.34242e-04 Mem R(MA/MR): 24076 (21268/36094) [2025-04-29 10:41:50,424 INFO hook.py line 650 1619929] Train: [303/512][200/242] Data 0.015 (0.016) Batch 1.249 (1.425) Remain 20:01:57 loss: 5.0772 Lr: 1.34122e-04 Mem R(MA/MR): 26106 (21268/36094) [2025-04-29 10:42:47,722 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3028 loss_mask: 0.0355 loss_dice: 1.9740 loss_score: 0.0000 loss_bbox: 0.0499 loss_sp_cls: 0.7830 loss: 5.0411 [2025-04-29 10:42:49,553 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:44:23,714 INFO hook.py line 650 1619929] Train: [304/512][50/242] Data 0.016 (0.016) Batch 1.358 (1.452) Remain 20:23:11 loss: 4.7821 Lr: 1.33903e-04 Mem R(MA/MR): 21326 (21268/36094) [2025-04-29 10:45:37,195 INFO hook.py line 650 1619929] Train: [304/512][100/242] Data 0.017 (0.016) Batch 1.678 (1.461) Remain 20:29:23 loss: 4.9087 Lr: 1.33784e-04 Mem R(MA/MR): 21326 (21268/36094) [2025-04-29 10:46:47,279 INFO hook.py line 650 1619929] Train: [304/512][150/242] Data 0.017 (0.016) Batch 1.447 (1.441) Remain 20:11:08 loss: 4.7315 Lr: 1.33665e-04 Mem R(MA/MR): 21326 (21268/36094) [2025-04-29 10:47:58,713 INFO hook.py line 650 1619929] Train: [304/512][200/242] Data 0.015 (0.016) Batch 1.282 (1.438) Remain 20:07:18 loss: 4.7267 Lr: 1.33546e-04 Mem R(MA/MR): 21326 (21268/36094) [2025-04-29 10:48:55,544 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3108 loss_mask: 0.0353 loss_dice: 1.9610 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.7869 loss: 5.0498 [2025-04-29 10:48:59,344 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 10:49:01,654 INFO hook.py line 449 1619929] Test: [1/50] Loss 4.1443 Process Time: 0.256 Mem R(MA/MR): 4472 (21268/36094) [2025-04-29 10:49:03,478 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.7070 Process Time: 0.706 Mem R(MA/MR): 7170 (21268/36094) [2025-04-29 10:49:05,186 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3055 Process Time: 0.657 Mem R(MA/MR): 9754 (21268/36094) [2025-04-29 10:49:12,589 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4437 Process Time: 0.835 Mem R(MA/MR): 20054 (21268/36094) [2025-04-29 10:49:13,661 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.8761 Process Time: 0.468 Mem R(MA/MR): 7178 (21268/36094) [2025-04-29 10:49:15,020 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5052 Process Time: 0.374 Mem R(MA/MR): 11392 (21268/36094) [2025-04-29 10:49:16,095 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.3782 Process Time: 0.412 Mem R(MA/MR): 6404 (21268/36094) [2025-04-29 10:49:16,514 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.7593 Process Time: 0.141 Mem R(MA/MR): 4472 (21268/36094) [2025-04-29 10:49:17,391 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0716 Process Time: 0.229 Mem R(MA/MR): 11462 (21268/36094) [2025-04-29 10:49:18,960 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8355 Process Time: 0.274 Mem R(MA/MR): 9540 (21268/36094) [2025-04-29 10:49:21,633 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.7980 Process Time: 0.690 Mem R(MA/MR): 18890 (21268/36094) [2025-04-29 10:49:25,058 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9728 Process Time: 1.203 Mem R(MA/MR): 15352 (21268/36094) [2025-04-29 10:49:26,107 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.6320 Process Time: 0.300 Mem R(MA/MR): 8748 (21268/36094) [2025-04-29 10:49:26,594 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9240 Process Time: 0.184 Mem R(MA/MR): 4800 (21268/36094) [2025-04-29 10:49:29,964 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4490 Process Time: 0.362 Mem R(MA/MR): 16522 (21268/36094) [2025-04-29 10:49:32,484 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4127 Process Time: 0.752 Mem R(MA/MR): 14406 (21268/36094) [2025-04-29 10:49:33,633 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.5111 Process Time: 0.475 Mem R(MA/MR): 6732 (21268/36094) [2025-04-29 10:49:34,562 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9213 Process Time: 0.241 Mem R(MA/MR): 8154 (21268/36094) [2025-04-29 10:49:36,065 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9842 Process Time: 0.164 Mem R(MA/MR): 6184 (21268/36094) [2025-04-29 10:49:37,916 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.9009 Process Time: 0.343 Mem R(MA/MR): 11744 (21268/36094) [2025-04-29 10:49:46,108 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.1043 Process Time: 0.938 Mem R(MA/MR): 23622 (21268/36094) [2025-04-29 10:49:46,751 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.6407 Process Time: 0.229 Mem R(MA/MR): 7062 (21268/36094) [2025-04-29 10:49:57,029 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.0301 Process Time: 0.449 Mem R(MA/MR): 10184 (21268/36094) [2025-04-29 10:49:57,951 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.3667 Process Time: 0.264 Mem R(MA/MR): 5434 (21268/36094) [2025-04-29 10:49:59,065 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9727 Process Time: 0.461 Mem R(MA/MR): 9300 (21268/36094) [2025-04-29 10:50:07,502 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.3048 Process Time: 1.540 Mem R(MA/MR): 32014 (21268/36094) [2025-04-29 10:50:09,736 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.1394 Process Time: 0.294 Mem R(MA/MR): 10184 (21268/36094) [2025-04-29 10:50:11,014 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9026 Process Time: 0.218 Mem R(MA/MR): 8992 (21268/36094) [2025-04-29 10:50:15,918 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.5347 Process Time: 0.357 Mem R(MA/MR): 17156 (21268/36094) [2025-04-29 10:50:17,059 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.0590 Process Time: 0.295 Mem R(MA/MR): 7846 (21268/36094) [2025-04-29 10:50:21,056 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.3403 Process Time: 0.406 Mem R(MA/MR): 20666 (21268/36094) [2025-04-29 10:50:21,767 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2328 Process Time: 0.349 Mem R(MA/MR): 4130 (21268/36094) [2025-04-29 10:50:26,602 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.0912 Process Time: 0.771 Mem R(MA/MR): 24920 (21268/36094) [2025-04-29 10:50:27,757 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8072 Process Time: 0.289 Mem R(MA/MR): 9944 (21268/36094) [2025-04-29 10:50:29,530 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.4860 Process Time: 0.292 Mem R(MA/MR): 14080 (21268/36094) [2025-04-29 10:50:30,286 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0183 Process Time: 0.320 Mem R(MA/MR): 6664 (21268/36094) [2025-04-29 10:50:34,748 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.2880 Process Time: 0.768 Mem R(MA/MR): 28492 (21268/36094) [2025-04-29 10:50:36,273 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5298 Process Time: 0.265 Mem R(MA/MR): 10788 (21268/36094) [2025-04-29 10:50:36,901 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0711 Process Time: 0.188 Mem R(MA/MR): 5582 (21268/36094) [2025-04-29 10:50:38,154 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7101 Process Time: 0.323 Mem R(MA/MR): 10198 (21268/36094) [2025-04-29 10:50:39,425 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.3260 Process Time: 0.394 Mem R(MA/MR): 9140 (21268/36094) [2025-04-29 10:50:40,548 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9048 Process Time: 0.496 Mem R(MA/MR): 5546 (21268/36094) [2025-04-29 10:50:41,250 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6710 Process Time: 0.315 Mem R(MA/MR): 5630 (21268/36094) [2025-04-29 10:50:42,011 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.6792 Process Time: 0.227 Mem R(MA/MR): 7152 (21268/36094) [2025-04-29 10:50:42,930 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3402 Process Time: 0.293 Mem R(MA/MR): 5334 (21268/36094) [2025-04-29 10:50:45,766 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.5966 Process Time: 0.660 Mem R(MA/MR): 14646 (21268/36094) [2025-04-29 10:50:52,591 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.4124 Process Time: 0.365 Mem R(MA/MR): 20388 (21268/36094) [2025-04-29 10:51:02,745 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2564 Process Time: 1.447 Mem R(MA/MR): 35408 (21268/36094) [2025-04-29 10:51:03,349 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.5498 Process Time: 0.138 Mem R(MA/MR): 5788 (21268/36094) [2025-04-29 10:51:05,573 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1154 Process Time: 0.352 Mem R(MA/MR): 13686 (21268/36094) [2025-04-29 10:51:09,699 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 10:51:09,699 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 10:51:09,699 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 10:51:09,699 INFO hook.py line 395 1619929] table : 0.276 0.604 0.778 0.779 0.596 [2025-04-29 10:51:09,699 INFO hook.py line 395 1619929] door : 0.428 0.750 0.889 0.848 0.709 [2025-04-29 10:51:09,699 INFO hook.py line 395 1619929] ceiling lamp : 0.574 0.787 0.894 0.854 0.713 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] cabinet : 0.339 0.451 0.496 0.596 0.418 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] blinds : 0.527 0.764 0.790 0.810 0.739 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] curtain : 0.392 0.553 0.763 0.667 0.667 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] chair : 0.596 0.741 0.797 0.699 0.791 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] storage cabinet: 0.201 0.332 0.475 0.542 0.520 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] office chair : 0.527 0.575 0.591 0.685 0.771 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] bookshelf : 0.331 0.589 0.589 0.889 0.727 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] whiteboard : 0.540 0.715 0.753 0.821 0.657 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] window : 0.118 0.282 0.546 0.507 0.385 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] box : 0.193 0.322 0.516 0.607 0.359 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] monitor : 0.570 0.735 0.801 0.839 0.743 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] shelf : 0.128 0.299 0.510 0.800 0.267 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] heater : 0.382 0.549 0.638 0.917 0.579 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] kitchen cabinet: 0.131 0.288 0.727 0.450 0.360 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] sofa : 0.431 0.602 0.942 0.857 0.500 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] bed : 0.134 0.272 0.944 0.667 0.500 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] trash can : 0.535 0.721 0.775 0.812 0.800 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] book : 0.019 0.037 0.099 0.167 0.094 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] plant : 0.376 0.586 0.810 0.917 0.611 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] blanket : 0.500 0.652 0.652 1.000 0.545 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] tv : 0.712 0.833 0.833 1.000 0.833 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] computer tower : 0.200 0.343 0.594 0.526 0.476 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] refrigerator : 0.233 0.382 0.429 1.000 0.333 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] jacket : 0.081 0.165 0.383 0.417 0.455 [2025-04-29 10:51:09,700 INFO hook.py line 395 1619929] sink : 0.326 0.524 0.764 0.765 0.591 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] bag : 0.044 0.082 0.093 0.209 0.333 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] picture : 0.164 0.377 0.411 0.875 0.359 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] pillow : 0.562 0.740 0.766 0.640 0.842 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] towel : 0.202 0.388 0.530 0.789 0.395 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] suitcase : 0.339 0.387 0.387 0.750 0.429 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] backpack : 0.420 0.514 0.514 1.000 0.462 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] crate : 0.065 0.281 0.440 0.375 0.545 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] keyboard : 0.407 0.586 0.717 0.821 0.590 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] toilet : 0.845 0.889 1.000 1.000 0.889 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] printer : 0.282 0.345 0.725 0.625 0.556 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.002 0.033 0.111 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] painting : 0.050 0.050 0.062 0.100 1.000 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] microwave : 0.556 0.944 0.944 0.800 1.000 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] shoes : 0.119 0.235 0.422 0.538 0.341 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] socket : 0.196 0.441 0.657 0.691 0.464 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] bottle : 0.134 0.246 0.382 0.556 0.301 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] bucket : 0.110 0.143 0.148 0.400 0.286 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] cushion : 0.126 0.159 0.214 0.333 0.500 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] basket : 0.004 0.014 0.014 0.200 0.143 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] telephone : 0.278 0.550 0.565 0.769 0.588 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] laptop : 0.405 0.624 0.630 0.714 0.625 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] plant pot : 0.144 0.317 0.431 0.750 0.375 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] exhaust fan : 0.200 0.377 0.377 0.857 0.400 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] cup : 0.188 0.356 0.401 1.000 0.318 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] coat hanger : 0.021 0.062 0.750 0.500 0.250 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] light switch : 0.254 0.492 0.672 0.879 0.446 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] speaker : 0.352 0.513 0.727 1.000 0.455 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 1.000 1.000 0.500 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] smoke detector : 0.676 0.844 0.844 0.913 0.875 [2025-04-29 10:51:09,701 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] power strip : 0.072 0.094 0.094 0.500 0.300 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] paper bag : 0.050 0.050 0.056 0.100 1.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] mouse : 0.489 0.647 0.730 0.909 0.625 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] cutting board : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] toilet paper : 0.320 0.412 0.477 1.000 0.412 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] paper towel : 0.016 0.073 0.198 0.500 0.250 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] clock : 0.667 1.000 1.000 1.000 1.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] pan : 0.194 0.250 0.500 1.000 0.250 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] tap : 0.116 0.237 0.556 0.600 0.333 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] jar : 0.004 0.018 0.205 0.500 0.071 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] soap dispenser : 0.375 0.600 0.600 1.000 0.600 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] bowl : 0.000 0.000 0.333 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] whiteboard eraser: 0.241 0.599 0.590 0.800 0.667 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] toilet brush : 0.323 0.667 0.833 1.000 0.667 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] spray bottle : 0.022 0.031 0.031 0.250 0.250 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.137 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 10:51:09,702 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 10:51:09,702 INFO hook.py line 404 1619929] average : 0.257 0.387 0.501 0.631 0.460 [2025-04-29 10:51:09,702 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 10:51:09,703 INFO hook.py line 480 1619929] Total Process Time: 22.768 s [2025-04-29 10:51:09,703 INFO hook.py line 481 1619929] Average Process Time: 459.445 ms [2025-04-29 10:51:09,703 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 10:51:09,740 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 10:51:09,744 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:52:42,240 INFO hook.py line 650 1619929] Train: [305/512][50/242] Data 0.017 (0.017) Batch 1.432 (1.497) Remain 20:54:26 loss: 5.2698 Lr: 1.33326e-04 Mem R(MA/MR): 21620 (21268/36094) [2025-04-29 10:53:57,230 INFO hook.py line 650 1619929] Train: [305/512][100/242] Data 0.015 (0.027) Batch 1.471 (1.498) Remain 20:54:30 loss: 6.0136 Lr: 1.33207e-04 Mem R(MA/MR): 23550 (21268/36094) [2025-04-29 10:55:08,051 INFO hook.py line 650 1619929] Train: [305/512][150/242] Data 0.017 (0.023) Batch 1.439 (1.470) Remain 20:29:57 loss: 4.7273 Lr: 1.33088e-04 Mem R(MA/MR): 26012 (21268/36094) [2025-04-29 10:56:19,184 INFO hook.py line 650 1619929] Train: [305/512][200/242] Data 0.016 (0.022) Batch 1.548 (1.458) Remain 20:18:35 loss: 5.9022 Lr: 1.32969e-04 Mem R(MA/MR): 26012 (21268/36094) [2025-04-29 10:57:17,360 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3075 loss_mask: 0.0360 loss_dice: 1.9708 loss_score: 0.0000 loss_bbox: 0.0499 loss_sp_cls: 0.7848 loss: 5.0595 [2025-04-29 10:57:20,371 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 10:58:47,580 INFO hook.py line 650 1619929] Train: [306/512][50/242] Data 0.015 (0.017) Batch 1.428 (1.477) Remain 20:31:52 loss: 4.1124 Lr: 1.32749e-04 Mem R(MA/MR): 23626 (21268/36094) [2025-04-29 10:59:58,850 INFO hook.py line 650 1619929] Train: [306/512][100/242] Data 0.015 (0.017) Batch 1.313 (1.450) Remain 20:08:29 loss: 5.6538 Lr: 1.32630e-04 Mem R(MA/MR): 23626 (21268/36094) [2025-04-29 11:01:11,862 INFO hook.py line 650 1619929] Train: [306/512][150/242] Data 0.016 (0.017) Batch 1.466 (1.454) Remain 20:10:05 loss: 4.2786 Lr: 1.32510e-04 Mem R(MA/MR): 23630 (21268/36094) [2025-04-29 11:02:25,083 INFO hook.py line 650 1619929] Train: [306/512][200/242] Data 0.014 (0.017) Batch 1.648 (1.456) Remain 20:11:08 loss: 4.8498 Lr: 1.32391e-04 Mem R(MA/MR): 23630 (21268/36094) [2025-04-29 11:03:22,098 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3070 loss_mask: 0.0351 loss_dice: 1.9618 loss_score: 0.0000 loss_bbox: 0.0496 loss_sp_cls: 0.7795 loss: 5.0295 [2025-04-29 11:03:27,396 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:04:58,887 INFO hook.py line 650 1619929] Train: [307/512][50/242] Data 0.016 (0.018) Batch 1.469 (1.481) Remain 20:29:04 loss: 5.9356 Lr: 1.32172e-04 Mem R(MA/MR): 20774 (21268/36094) [2025-04-29 11:06:12,746 INFO hook.py line 650 1619929] Train: [307/512][100/242] Data 0.015 (0.017) Batch 1.398 (1.479) Remain 20:26:18 loss: 5.4080 Lr: 1.32055e-04 Mem R(MA/MR): 25350 (21268/36094) [2025-04-29 11:07:24,692 INFO hook.py line 650 1619929] Train: [307/512][150/242] Data 0.017 (0.017) Batch 1.382 (1.465) Remain 20:13:48 loss: 4.8602 Lr: 1.31935e-04 Mem R(MA/MR): 28808 (21268/36094) [2025-04-29 11:08:38,668 INFO hook.py line 650 1619929] Train: [307/512][200/242] Data 0.014 (0.017) Batch 1.352 (1.469) Remain 20:15:34 loss: 5.6383 Lr: 1.31816e-04 Mem R(MA/MR): 30742 (21268/36094) [2025-04-29 11:09:35,958 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3243 loss_mask: 0.0369 loss_dice: 2.0225 loss_score: 0.0000 loss_bbox: 0.0520 loss_sp_cls: 0.7984 loss: 5.2027 [2025-04-29 11:09:37,641 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:11:13,281 INFO hook.py line 650 1619929] Train: [308/512][50/242] Data 0.016 (0.016) Batch 1.461 (1.493) Remain 20:33:14 loss: 6.2385 Lr: 1.31596e-04 Mem R(MA/MR): 21700 (21268/36094) [2025-04-29 11:12:26,394 INFO hook.py line 650 1619929] Train: [308/512][100/242] Data 0.017 (0.016) Batch 1.464 (1.477) Remain 20:18:53 loss: 4.8185 Lr: 1.31477e-04 Mem R(MA/MR): 21732 (21268/36094) [2025-04-29 11:13:39,079 INFO hook.py line 650 1619929] Train: [308/512][150/242] Data 0.017 (0.016) Batch 1.410 (1.469) Remain 20:11:05 loss: 5.0193 Lr: 1.31357e-04 Mem R(MA/MR): 21732 (21268/36094) [2025-04-29 11:14:51,487 INFO hook.py line 650 1619929] Train: [308/512][200/242] Data 0.014 (0.016) Batch 1.387 (1.464) Remain 20:05:28 loss: 6.2316 Lr: 1.31238e-04 Mem R(MA/MR): 24284 (21268/36094) [2025-04-29 11:15:47,728 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3351 loss_mask: 0.0385 loss_dice: 2.0693 loss_score: 0.0000 loss_bbox: 0.0523 loss_sp_cls: 0.8135 loss: 5.3171 [2025-04-29 11:15:47,832 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:17:14,052 INFO hook.py line 650 1619929] Train: [309/512][50/242] Data 0.015 (0.017) Batch 1.451 (1.468) Remain 20:06:14 loss: 5.8865 Lr: 1.31018e-04 Mem R(MA/MR): 19984 (21268/36094) [2025-04-29 11:18:27,137 INFO hook.py line 650 1619929] Train: [309/512][100/242] Data 0.015 (0.016) Batch 1.558 (1.464) Remain 20:02:32 loss: 4.5382 Lr: 1.30899e-04 Mem R(MA/MR): 20004 (21268/36094) [2025-04-29 11:19:38,767 INFO hook.py line 650 1619929] Train: [309/512][150/242] Data 0.018 (0.016) Batch 1.569 (1.454) Remain 19:52:26 loss: 4.5614 Lr: 1.30779e-04 Mem R(MA/MR): 20004 (21268/36094) [2025-04-29 11:20:49,967 INFO hook.py line 650 1619929] Train: [309/512][200/242] Data 0.015 (0.017) Batch 1.469 (1.446) Remain 19:45:03 loss: 5.2025 Lr: 1.30660e-04 Mem R(MA/MR): 20004 (21268/36094) [2025-04-29 11:21:47,029 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3302 loss_mask: 0.0384 loss_dice: 2.0512 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8100 loss: 5.2758 [2025-04-29 11:21:47,420 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:23:21,871 INFO hook.py line 650 1619929] Train: [310/512][50/242] Data 0.016 (0.016) Batch 1.384 (1.473) Remain 20:04:25 loss: 6.5928 Lr: 1.30440e-04 Mem R(MA/MR): 24546 (21268/36094) [2025-04-29 11:24:32,193 INFO hook.py line 650 1619929] Train: [310/512][100/242] Data 0.017 (0.016) Batch 1.390 (1.438) Remain 19:35:21 loss: 4.5469 Lr: 1.30320e-04 Mem R(MA/MR): 24562 (21268/36094) [2025-04-29 11:25:44,001 INFO hook.py line 650 1619929] Train: [310/512][150/242] Data 0.015 (0.017) Batch 1.374 (1.438) Remain 19:33:31 loss: 5.0636 Lr: 1.30201e-04 Mem R(MA/MR): 26628 (21268/36094) [2025-04-29 11:26:55,139 INFO hook.py line 650 1619929] Train: [310/512][200/242] Data 0.016 (0.016) Batch 1.450 (1.434) Remain 19:29:14 loss: 4.9213 Lr: 1.30081e-04 Mem R(MA/MR): 26628 (21268/36094) [2025-04-29 11:27:54,059 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3264 loss_mask: 0.0381 loss_dice: 2.0328 loss_score: 0.0000 loss_bbox: 0.0522 loss_sp_cls: 0.8038 loss: 5.2307 [2025-04-29 11:27:54,896 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:29:32,440 INFO hook.py line 650 1619929] Train: [311/512][50/242] Data 0.016 (0.017) Batch 1.530 (1.475) Remain 20:00:30 loss: 5.0720 Lr: 1.29861e-04 Mem R(MA/MR): 22556 (21268/36094) [2025-04-29 11:30:45,311 INFO hook.py line 650 1619929] Train: [311/512][100/242] Data 0.017 (0.017) Batch 1.563 (1.466) Remain 19:51:54 loss: 5.4963 Lr: 1.29742e-04 Mem R(MA/MR): 24312 (21268/36094) [2025-04-29 11:31:56,711 INFO hook.py line 650 1619929] Train: [311/512][150/242] Data 0.017 (0.017) Batch 1.313 (1.453) Remain 19:40:12 loss: 4.6730 Lr: 1.29622e-04 Mem R(MA/MR): 26144 (21268/36094) [2025-04-29 11:33:07,057 INFO hook.py line 650 1619929] Train: [311/512][200/242] Data 0.015 (0.017) Batch 1.374 (1.441) Remain 19:29:30 loss: 4.7251 Lr: 1.29502e-04 Mem R(MA/MR): 28294 (21268/36094) [2025-04-29 11:34:03,372 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3266 loss_mask: 0.0382 loss_dice: 2.0227 loss_score: 0.0000 loss_bbox: 0.0515 loss_sp_cls: 0.8049 loss: 5.2160 [2025-04-29 11:34:04,559 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:35:41,747 INFO hook.py line 650 1619929] Train: [312/512][50/242] Data 0.016 (0.017) Batch 1.610 (1.512) Remain 20:24:51 loss: 6.8851 Lr: 1.29282e-04 Mem R(MA/MR): 19120 (21268/36094) [2025-04-29 11:36:54,899 INFO hook.py line 650 1619929] Train: [312/512][100/242] Data 0.016 (0.017) Batch 1.429 (1.487) Remain 20:02:59 loss: 5.3450 Lr: 1.29163e-04 Mem R(MA/MR): 19122 (21268/36094) [2025-04-29 11:38:07,619 INFO hook.py line 650 1619929] Train: [312/512][150/242] Data 0.015 (0.017) Batch 1.464 (1.476) Remain 19:52:48 loss: 4.4277 Lr: 1.29043e-04 Mem R(MA/MR): 19122 (21268/36094) [2025-04-29 11:39:18,573 INFO hook.py line 650 1619929] Train: [312/512][200/242] Data 0.015 (0.017) Batch 1.347 (1.461) Remain 19:39:56 loss: 4.9327 Lr: 1.28923e-04 Mem R(MA/MR): 19148 (21268/36094) [2025-04-29 11:40:15,505 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3198 loss_mask: 0.0375 loss_dice: 2.0042 loss_score: 0.0000 loss_bbox: 0.0508 loss_sp_cls: 0.7991 loss: 5.1550 [2025-04-29 11:40:15,920 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 11:40:18,202 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5606 Process Time: 0.382 Mem R(MA/MR): 4426 (21268/36094) [2025-04-29 11:40:20,076 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.2284 Process Time: 0.752 Mem R(MA/MR): 7170 (21268/36094) [2025-04-29 11:40:22,135 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1387 Process Time: 0.770 Mem R(MA/MR): 9732 (21268/36094) [2025-04-29 11:40:29,335 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.6608 Process Time: 1.539 Mem R(MA/MR): 19650 (21268/36094) [2025-04-29 11:40:30,661 INFO hook.py line 449 1619929] Test: [5/50] Loss 6.1270 Process Time: 0.351 Mem R(MA/MR): 7044 (21268/36094) [2025-04-29 11:40:32,336 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4209 Process Time: 0.493 Mem R(MA/MR): 11292 (21268/36094) [2025-04-29 11:40:32,944 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8571 Process Time: 0.246 Mem R(MA/MR): 6374 (21268/36094) [2025-04-29 11:40:33,459 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.9008 Process Time: 0.226 Mem R(MA/MR): 4454 (21268/36094) [2025-04-29 11:40:34,296 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.9019 Process Time: 0.228 Mem R(MA/MR): 11332 (21268/36094) [2025-04-29 11:40:36,158 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4790 Process Time: 0.373 Mem R(MA/MR): 9492 (21268/36094) [2025-04-29 11:40:39,428 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.4005 Process Time: 0.782 Mem R(MA/MR): 18750 (21268/36094) [2025-04-29 11:40:42,231 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3919 Process Time: 0.541 Mem R(MA/MR): 15474 (21268/36094) [2025-04-29 11:40:43,384 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0121 Process Time: 0.240 Mem R(MA/MR): 8726 (21268/36094) [2025-04-29 11:40:43,729 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2496 Process Time: 0.123 Mem R(MA/MR): 4766 (21268/36094) [2025-04-29 11:40:46,666 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.2370 Process Time: 0.308 Mem R(MA/MR): 16578 (21268/36094) [2025-04-29 11:40:48,889 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3564 Process Time: 0.608 Mem R(MA/MR): 14548 (21268/36094) [2025-04-29 11:40:49,746 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2504 Process Time: 0.271 Mem R(MA/MR): 6756 (21268/36094) [2025-04-29 11:40:50,585 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1212 Process Time: 0.221 Mem R(MA/MR): 8156 (21268/36094) [2025-04-29 11:40:51,739 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2143 Process Time: 0.141 Mem R(MA/MR): 6180 (21268/36094) [2025-04-29 11:40:53,209 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.2758 Process Time: 0.208 Mem R(MA/MR): 11578 (21268/36094) [2025-04-29 11:41:00,871 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.1437 Process Time: 0.774 Mem R(MA/MR): 23566 (21268/36094) [2025-04-29 11:41:01,477 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2376 Process Time: 0.222 Mem R(MA/MR): 7016 (21268/36094) [2025-04-29 11:41:11,089 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.1145 Process Time: 0.422 Mem R(MA/MR): 8438 (21268/36094) [2025-04-29 11:41:11,738 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.3574 Process Time: 0.241 Mem R(MA/MR): 5374 (21268/36094) [2025-04-29 11:41:13,616 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.7726 Process Time: 0.830 Mem R(MA/MR): 9288 (21268/36094) [2025-04-29 11:41:22,113 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.8521 Process Time: 1.859 Mem R(MA/MR): 32012 (21268/36094) [2025-04-29 11:41:24,864 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5416 Process Time: 0.365 Mem R(MA/MR): 9742 (21268/36094) [2025-04-29 11:41:26,209 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.7443 Process Time: 0.392 Mem R(MA/MR): 8828 (21268/36094) [2025-04-29 11:41:30,525 INFO hook.py line 449 1619929] Test: [29/50] Loss 7.0435 Process Time: 0.301 Mem R(MA/MR): 17244 (21268/36094) [2025-04-29 11:41:32,233 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.0890 Process Time: 0.593 Mem R(MA/MR): 7732 (21268/36094) [2025-04-29 11:41:36,131 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.4631 Process Time: 0.670 Mem R(MA/MR): 20946 (21268/36094) [2025-04-29 11:41:36,408 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.7793 Process Time: 0.118 Mem R(MA/MR): 4064 (21268/36094) [2025-04-29 11:41:39,812 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3310 Process Time: 0.389 Mem R(MA/MR): 24812 (21268/36094) [2025-04-29 11:41:41,374 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.9196 Process Time: 0.482 Mem R(MA/MR): 9816 (21268/36094) [2025-04-29 11:41:43,254 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.4668 Process Time: 0.493 Mem R(MA/MR): 14040 (21268/36094) [2025-04-29 11:41:43,766 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.8598 Process Time: 0.183 Mem R(MA/MR): 6640 (21268/36094) [2025-04-29 11:41:47,257 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.3519 Process Time: 0.519 Mem R(MA/MR): 28550 (21268/36094) [2025-04-29 11:41:49,271 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.3415 Process Time: 0.756 Mem R(MA/MR): 10616 (21268/36094) [2025-04-29 11:41:50,295 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3127 Process Time: 0.477 Mem R(MA/MR): 5552 (21268/36094) [2025-04-29 11:41:51,834 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5891 Process Time: 0.452 Mem R(MA/MR): 10208 (21268/36094) [2025-04-29 11:41:53,223 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.3074 Process Time: 0.459 Mem R(MA/MR): 8988 (21268/36094) [2025-04-29 11:41:53,796 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.2278 Process Time: 0.225 Mem R(MA/MR): 5562 (21268/36094) [2025-04-29 11:41:54,464 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5257 Process Time: 0.371 Mem R(MA/MR): 5572 (21268/36094) [2025-04-29 11:41:55,233 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.3430 Process Time: 0.305 Mem R(MA/MR): 7164 (21268/36094) [2025-04-29 11:41:55,859 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.0863 Process Time: 0.155 Mem R(MA/MR): 5316 (21268/36094) [2025-04-29 11:41:58,279 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8941 Process Time: 0.485 Mem R(MA/MR): 14280 (21268/36094) [2025-04-29 11:42:06,914 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.9034 Process Time: 1.135 Mem R(MA/MR): 20702 (21268/36094) [2025-04-29 11:42:18,107 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9331 Process Time: 1.895 Mem R(MA/MR): 35628 (21268/36094) [2025-04-29 11:42:18,709 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.2055 Process Time: 0.162 Mem R(MA/MR): 5740 (21268/36094) [2025-04-29 11:42:20,589 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.8661 Process Time: 0.299 Mem R(MA/MR): 13458 (21268/36094) [2025-04-29 11:42:25,318 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 11:42:25,318 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 11:42:25,318 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] table : 0.235 0.539 0.757 0.784 0.559 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] door : 0.396 0.696 0.896 0.841 0.734 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] ceiling lamp : 0.544 0.729 0.856 0.874 0.729 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] cabinet : 0.325 0.491 0.579 0.583 0.522 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] blinds : 0.514 0.650 0.754 0.875 0.609 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] curtain : 0.265 0.500 0.710 0.583 0.583 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] chair : 0.502 0.677 0.741 0.896 0.566 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] storage cabinet: 0.174 0.349 0.525 0.667 0.400 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] office chair : 0.501 0.509 0.523 0.714 0.625 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] bookshelf : 0.174 0.386 0.456 0.583 0.636 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] whiteboard : 0.564 0.713 0.763 0.862 0.714 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] window : 0.096 0.231 0.533 0.516 0.352 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] box : 0.190 0.381 0.560 0.523 0.442 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] monitor : 0.597 0.741 0.815 0.912 0.743 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] shelf : 0.122 0.260 0.445 0.391 0.300 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] heater : 0.363 0.614 0.737 0.885 0.605 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] kitchen cabinet: 0.113 0.395 0.720 0.650 0.520 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] sofa : 0.430 0.611 0.848 0.529 0.750 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] bed : 0.178 0.472 0.915 0.800 0.500 [2025-04-29 11:42:25,318 INFO hook.py line 395 1619929] trash can : 0.502 0.647 0.721 0.726 0.815 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] book : 0.014 0.028 0.088 0.208 0.082 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] plant : 0.385 0.573 0.741 0.917 0.611 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] blanket : 0.511 0.751 0.752 1.000 0.545 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] tv : 0.912 1.000 1.000 1.000 1.000 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] computer tower : 0.209 0.366 0.601 0.476 0.476 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] refrigerator : 0.359 0.756 0.784 0.778 0.778 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] jacket : 0.112 0.274 0.419 0.600 0.545 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] sink : 0.347 0.623 0.762 0.833 0.682 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] bag : 0.035 0.082 0.126 0.412 0.259 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] picture : 0.140 0.269 0.378 0.667 0.359 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] pillow : 0.474 0.737 0.793 0.857 0.632 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] towel : 0.195 0.352 0.530 0.577 0.395 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] suitcase : 0.436 0.570 0.570 0.556 0.714 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] backpack : 0.415 0.488 0.569 1.000 0.385 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] crate : 0.098 0.565 0.565 1.000 0.455 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] keyboard : 0.466 0.665 0.680 0.730 0.692 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] toilet : 0.806 1.000 1.000 1.000 1.000 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] printer : 0.308 0.393 0.393 1.000 0.333 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] poster : 0.001 0.006 0.019 0.111 0.111 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] microwave : 0.645 0.858 0.985 0.875 0.875 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] shoes : 0.069 0.163 0.524 0.429 0.293 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] socket : 0.175 0.402 0.609 0.747 0.421 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] bottle : 0.084 0.160 0.252 0.273 0.289 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] bucket : 0.066 0.066 0.071 0.143 0.571 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] cushion : 0.016 0.066 0.182 0.500 0.167 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] basket : 0.111 0.143 0.143 1.000 0.143 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] telephone : 0.301 0.586 0.586 0.714 0.588 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] laptop : 0.218 0.369 0.523 0.455 0.625 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] plant pot : 0.049 0.214 0.429 0.545 0.375 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] exhaust fan : 0.154 0.287 0.287 0.833 0.333 [2025-04-29 11:42:25,319 INFO hook.py line 395 1619929] cup : 0.196 0.327 0.353 0.867 0.295 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] coat hanger : 0.000 0.000 0.750 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] light switch : 0.258 0.528 0.657 0.723 0.523 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] speaker : 0.332 0.422 0.574 0.800 0.364 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] kettle : 0.238 0.311 0.328 0.500 0.500 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] smoke detector : 0.641 0.829 0.829 1.000 0.792 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] power strip : 0.054 0.082 0.134 0.182 0.400 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] paper bag : 0.167 0.167 0.167 0.333 1.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] mouse : 0.419 0.662 0.749 0.952 0.625 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] toilet paper : 0.145 0.231 0.426 0.625 0.294 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] paper towel : 0.062 0.140 0.250 1.000 0.125 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] clock : 0.472 0.903 0.903 0.750 1.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] tap : 0.049 0.173 0.629 0.571 0.444 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] soap dispenser : 0.537 0.800 0.800 1.000 0.800 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] bowl : 0.142 0.278 0.278 0.667 0.667 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] whiteboard eraser: 0.276 0.696 0.696 0.714 0.833 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] toilet brush : 0.473 0.667 0.941 1.000 0.667 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] spray bottle : 0.011 0.016 0.018 0.125 0.250 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] headphones : 0.075 0.161 1.000 0.333 0.500 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] stapler : 0.004 0.033 0.137 0.200 0.333 [2025-04-29 11:42:25,320 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 11:42:25,320 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 11:42:25,320 INFO hook.py line 404 1619929] average : 0.246 0.385 0.504 0.595 0.459 [2025-04-29 11:42:25,320 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 11:42:25,321 INFO hook.py line 480 1619929] Total Process Time: 24.833 s [2025-04-29 11:42:25,321 INFO hook.py line 481 1619929] Average Process Time: 499.008 ms [2025-04-29 11:42:25,321 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 11:42:25,363 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 11:42:25,367 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:43:56,140 INFO hook.py line 650 1619929] Train: [313/512][50/242] Data 0.018 (0.036) Batch 1.487 (1.515) Remain 20:20:55 loss: 5.9542 Lr: 1.28703e-04 Mem R(MA/MR): 21730 (21268/36094) [2025-04-29 11:45:08,282 INFO hook.py line 650 1619929] Train: [313/512][100/242] Data 0.017 (0.026) Batch 1.543 (1.478) Remain 19:49:40 loss: 5.9834 Lr: 1.28583e-04 Mem R(MA/MR): 21730 (21268/36094) [2025-04-29 11:46:21,848 INFO hook.py line 650 1619929] Train: [313/512][150/242] Data 0.016 (0.023) Batch 1.364 (1.476) Remain 19:46:40 loss: 5.3847 Lr: 1.28464e-04 Mem R(MA/MR): 24070 (21268/36094) [2025-04-29 11:47:33,594 INFO hook.py line 650 1619929] Train: [313/512][200/242] Data 0.014 (0.021) Batch 1.404 (1.465) Remain 19:37:08 loss: 5.7090 Lr: 1.28344e-04 Mem R(MA/MR): 24070 (21268/36094) [2025-04-29 11:48:32,271 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3156 loss_mask: 0.0370 loss_dice: 1.9936 loss_score: 0.0000 loss_bbox: 0.0511 loss_sp_cls: 0.7963 loss: 5.1270 [2025-04-29 11:48:35,109 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:50:04,880 INFO hook.py line 650 1619929] Train: [314/512][50/242] Data 0.016 (0.017) Batch 1.277 (1.493) Remain 19:56:44 loss: 4.7099 Lr: 1.28124e-04 Mem R(MA/MR): 24056 (21268/36094) [2025-04-29 11:51:16,557 INFO hook.py line 650 1619929] Train: [314/512][100/242] Data 0.018 (0.017) Batch 1.484 (1.462) Remain 19:31:06 loss: 4.2897 Lr: 1.28004e-04 Mem R(MA/MR): 26194 (21268/36094) [2025-04-29 11:52:27,809 INFO hook.py line 650 1619929] Train: [314/512][150/242] Data 0.015 (0.017) Batch 1.381 (1.450) Remain 19:19:48 loss: 5.6548 Lr: 1.27884e-04 Mem R(MA/MR): 26194 (21268/36094) [2025-04-29 11:53:37,688 INFO hook.py line 650 1619929] Train: [314/512][200/242] Data 0.014 (0.016) Batch 1.244 (1.436) Remain 19:08:03 loss: 4.4985 Lr: 1.27764e-04 Mem R(MA/MR): 26194 (21268/36094) [2025-04-29 11:54:36,027 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3148 loss_mask: 0.0372 loss_dice: 2.0081 loss_score: 0.0000 loss_bbox: 0.0503 loss_sp_cls: 0.7930 loss: 5.1390 [2025-04-29 11:54:37,735 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 11:56:06,447 INFO hook.py line 650 1619929] Train: [315/512][50/242] Data 0.017 (0.017) Batch 1.676 (1.454) Remain 19:20:16 loss: 4.6779 Lr: 1.27544e-04 Mem R(MA/MR): 21594 (21268/36094) [2025-04-29 11:57:20,527 INFO hook.py line 650 1619929] Train: [315/512][100/242] Data 0.018 (0.016) Batch 1.686 (1.468) Remain 19:30:13 loss: 5.7779 Lr: 1.27424e-04 Mem R(MA/MR): 23366 (21268/36094) [2025-04-29 11:58:33,834 INFO hook.py line 650 1619929] Train: [315/512][150/242] Data 0.016 (0.016) Batch 1.367 (1.468) Remain 19:28:23 loss: 5.5137 Lr: 1.27304e-04 Mem R(MA/MR): 23366 (21268/36094) [2025-04-29 11:59:45,071 INFO hook.py line 650 1619929] Train: [315/512][200/242] Data 0.014 (0.016) Batch 1.515 (1.457) Remain 19:18:31 loss: 5.7562 Lr: 1.27184e-04 Mem R(MA/MR): 23366 (21268/36094) [2025-04-29 12:00:43,184 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3134 loss_mask: 0.0366 loss_dice: 1.9943 loss_score: 0.0000 loss_bbox: 0.0504 loss_sp_cls: 0.7896 loss: 5.1158 [2025-04-29 12:00:44,517 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:02:14,622 INFO hook.py line 650 1619929] Train: [316/512][50/242] Data 0.016 (0.017) Batch 1.532 (1.455) Remain 19:14:53 loss: 6.3269 Lr: 1.26964e-04 Mem R(MA/MR): 23104 (21268/36094) [2025-04-29 12:03:26,040 INFO hook.py line 650 1619929] Train: [316/512][100/242] Data 0.016 (0.016) Batch 1.440 (1.441) Remain 19:02:47 loss: 5.7770 Lr: 1.26844e-04 Mem R(MA/MR): 23104 (21268/36094) [2025-04-29 12:04:40,293 INFO hook.py line 650 1619929] Train: [316/512][150/242] Data 0.015 (0.017) Batch 1.514 (1.456) Remain 19:13:23 loss: 5.4421 Lr: 1.26724e-04 Mem R(MA/MR): 24964 (21268/36094) [2025-04-29 12:05:53,015 INFO hook.py line 650 1619929] Train: [316/512][200/242] Data 0.015 (0.016) Batch 1.437 (1.456) Remain 19:11:49 loss: 5.3553 Lr: 1.26604e-04 Mem R(MA/MR): 26844 (21268/36094) [2025-04-29 12:06:50,768 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2995 loss_mask: 0.0349 loss_dice: 1.9472 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7708 loss: 4.9881 [2025-04-29 12:06:54,631 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:08:23,949 INFO hook.py line 650 1619929] Train: [317/512][50/242] Data 0.017 (0.017) Batch 1.588 (1.434) Remain 18:52:35 loss: 4.8419 Lr: 1.26383e-04 Mem R(MA/MR): 22160 (21268/36094) [2025-04-29 12:09:36,662 INFO hook.py line 650 1619929] Train: [317/512][100/242] Data 0.018 (0.017) Batch 1.654 (1.445) Remain 18:59:32 loss: 5.1249 Lr: 1.26264e-04 Mem R(MA/MR): 25496 (21268/36094) [2025-04-29 12:10:50,412 INFO hook.py line 650 1619929] Train: [317/512][150/242] Data 0.018 (0.017) Batch 1.497 (1.455) Remain 19:06:29 loss: 5.5085 Lr: 1.26146e-04 Mem R(MA/MR): 25496 (21268/36094) [2025-04-29 12:12:03,786 INFO hook.py line 650 1619929] Train: [317/512][200/242] Data 0.015 (0.017) Batch 1.528 (1.458) Remain 19:07:48 loss: 6.7873 Lr: 1.26026e-04 Mem R(MA/MR): 25496 (21268/36094) [2025-04-29 12:13:01,594 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3005 loss_mask: 0.0348 loss_dice: 1.9412 loss_score: 0.0000 loss_bbox: 0.0496 loss_sp_cls: 0.7734 loss: 4.9815 [2025-04-29 12:13:05,309 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:14:34,994 INFO hook.py line 650 1619929] Train: [318/512][50/242] Data 0.017 (0.016) Batch 1.367 (1.456) Remain 19:04:16 loss: 5.5903 Lr: 1.25805e-04 Mem R(MA/MR): 21152 (21268/36094) [2025-04-29 12:15:46,711 INFO hook.py line 650 1619929] Train: [318/512][100/242] Data 0.016 (0.017) Batch 1.465 (1.445) Remain 18:54:07 loss: 4.1737 Lr: 1.25685e-04 Mem R(MA/MR): 24854 (21268/36094) [2025-04-29 12:17:01,604 INFO hook.py line 650 1619929] Train: [318/512][150/242] Data 0.017 (0.017) Batch 1.463 (1.463) Remain 19:06:59 loss: 4.9926 Lr: 1.25565e-04 Mem R(MA/MR): 24878 (21268/36094) [2025-04-29 12:18:14,107 INFO hook.py line 650 1619929] Train: [318/512][200/242] Data 0.014 (0.016) Batch 1.445 (1.460) Remain 19:03:12 loss: 4.8464 Lr: 1.25445e-04 Mem R(MA/MR): 24878 (21268/36094) [2025-04-29 12:19:10,703 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3165 loss_mask: 0.0364 loss_dice: 1.9975 loss_score: 0.0000 loss_bbox: 0.0505 loss_sp_cls: 0.7933 loss: 5.1320 [2025-04-29 12:19:15,691 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:20:48,620 INFO hook.py line 650 1619929] Train: [319/512][50/242] Data 0.015 (0.017) Batch 1.295 (1.485) Remain 19:20:38 loss: 4.9491 Lr: 1.25224e-04 Mem R(MA/MR): 25324 (21268/36094) [2025-04-29 12:22:00,477 INFO hook.py line 650 1619929] Train: [319/512][100/242] Data 0.016 (0.016) Batch 1.529 (1.460) Remain 19:00:10 loss: 5.5460 Lr: 1.25104e-04 Mem R(MA/MR): 25350 (21268/36094) [2025-04-29 12:23:10,747 INFO hook.py line 650 1619929] Train: [319/512][150/242] Data 0.016 (0.016) Batch 1.378 (1.442) Remain 18:44:24 loss: 5.5058 Lr: 1.24984e-04 Mem R(MA/MR): 25350 (21268/36094) [2025-04-29 12:24:19,938 INFO hook.py line 650 1619929] Train: [319/512][200/242] Data 0.016 (0.016) Batch 1.424 (1.427) Remain 18:31:46 loss: 4.4772 Lr: 1.24864e-04 Mem R(MA/MR): 27248 (21268/36094) [2025-04-29 12:25:17,539 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3121 loss_mask: 0.0367 loss_dice: 1.9915 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.7843 loss: 5.1013 [2025-04-29 12:25:17,962 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:26:43,246 INFO hook.py line 650 1619929] Train: [320/512][50/242] Data 0.016 (0.017) Batch 1.328 (1.471) Remain 19:04:08 loss: 5.2327 Lr: 1.24643e-04 Mem R(MA/MR): 21022 (21268/36094) [2025-04-29 12:27:56,481 INFO hook.py line 650 1619929] Train: [320/512][100/242] Data 0.016 (0.016) Batch 1.518 (1.468) Remain 19:00:14 loss: 4.7362 Lr: 1.24523e-04 Mem R(MA/MR): 26182 (21268/36094) [2025-04-29 12:29:08,019 INFO hook.py line 650 1619929] Train: [320/512][150/242] Data 0.018 (0.017) Batch 1.595 (1.455) Remain 18:49:11 loss: 5.0128 Lr: 1.24403e-04 Mem R(MA/MR): 26182 (21268/36094) [2025-04-29 12:30:21,349 INFO hook.py line 650 1619929] Train: [320/512][200/242] Data 0.014 (0.017) Batch 1.387 (1.458) Remain 18:50:13 loss: 5.2186 Lr: 1.24283e-04 Mem R(MA/MR): 26182 (21268/36094) [2025-04-29 12:31:19,126 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3121 loss_mask: 0.0363 loss_dice: 1.9784 loss_score: 0.0000 loss_bbox: 0.0512 loss_sp_cls: 0.7881 loss: 5.0939 [2025-04-29 12:31:19,255 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 12:31:21,604 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.9501 Process Time: 0.393 Mem R(MA/MR): 4980 (21268/36094) [2025-04-29 12:31:23,732 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1778 Process Time: 0.851 Mem R(MA/MR): 7810 (21268/36094) [2025-04-29 12:31:25,508 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.8571 Process Time: 0.618 Mem R(MA/MR): 10172 (21268/36094) [2025-04-29 12:31:33,319 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.6244 Process Time: 1.241 Mem R(MA/MR): 20168 (21268/36094) [2025-04-29 12:31:34,378 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5675 Process Time: 0.468 Mem R(MA/MR): 7670 (21268/36094) [2025-04-29 12:31:35,830 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.1783 Process Time: 0.392 Mem R(MA/MR): 11914 (21268/36094) [2025-04-29 12:31:36,347 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.7438 Process Time: 0.148 Mem R(MA/MR): 6906 (21268/36094) [2025-04-29 12:31:36,760 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3880 Process Time: 0.112 Mem R(MA/MR): 5038 (21268/36094) [2025-04-29 12:31:37,709 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8935 Process Time: 0.307 Mem R(MA/MR): 12110 (21268/36094) [2025-04-29 12:31:39,122 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8846 Process Time: 0.229 Mem R(MA/MR): 10144 (21268/36094) [2025-04-29 12:31:42,392 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.7297 Process Time: 1.162 Mem R(MA/MR): 19392 (21268/36094) [2025-04-29 12:31:45,242 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.6878 Process Time: 0.857 Mem R(MA/MR): 16222 (21268/36094) [2025-04-29 12:31:46,305 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.3111 Process Time: 0.223 Mem R(MA/MR): 9366 (21268/36094) [2025-04-29 12:31:46,627 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.3071 Process Time: 0.115 Mem R(MA/MR): 5382 (21268/36094) [2025-04-29 12:31:49,186 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.1526 Process Time: 0.365 Mem R(MA/MR): 17084 (21268/36094) [2025-04-29 12:31:52,019 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3908 Process Time: 1.136 Mem R(MA/MR): 15160 (21268/36094) [2025-04-29 12:31:53,022 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7022 Process Time: 0.398 Mem R(MA/MR): 7346 (21268/36094) [2025-04-29 12:31:54,010 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9348 Process Time: 0.254 Mem R(MA/MR): 8692 (21268/36094) [2025-04-29 12:31:55,527 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6137 Process Time: 0.170 Mem R(MA/MR): 6888 (21268/36094) [2025-04-29 12:31:57,164 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.0618 Process Time: 0.230 Mem R(MA/MR): 12076 (21268/36094) [2025-04-29 12:32:06,749 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.8289 Process Time: 1.157 Mem R(MA/MR): 24434 (21268/36094) [2025-04-29 12:32:08,307 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.0304 Process Time: 0.580 Mem R(MA/MR): 7356 (21268/36094) [2025-04-29 12:32:19,804 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.9359 Process Time: 0.545 Mem R(MA/MR): 10712 (21268/36094) [2025-04-29 12:32:20,313 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0180 Process Time: 0.155 Mem R(MA/MR): 5968 (21268/36094) [2025-04-29 12:32:21,214 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0256 Process Time: 0.201 Mem R(MA/MR): 9990 (21268/36094) [2025-04-29 12:32:26,894 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.7553 Process Time: 0.802 Mem R(MA/MR): 31836 (21268/36094) [2025-04-29 12:32:29,809 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.9855 Process Time: 0.612 Mem R(MA/MR): 10632 (21268/36094) [2025-04-29 12:32:31,055 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.1002 Process Time: 0.359 Mem R(MA/MR): 9390 (21268/36094) [2025-04-29 12:32:35,906 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6774 Process Time: 0.328 Mem R(MA/MR): 17770 (21268/36094) [2025-04-29 12:32:36,996 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1847 Process Time: 0.321 Mem R(MA/MR): 8308 (21268/36094) [2025-04-29 12:32:40,461 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8017 Process Time: 0.430 Mem R(MA/MR): 21302 (21268/36094) [2025-04-29 12:32:40,825 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1255 Process Time: 0.139 Mem R(MA/MR): 4638 (21268/36094) [2025-04-29 12:32:45,622 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3939 Process Time: 0.702 Mem R(MA/MR): 25260 (21268/36094) [2025-04-29 12:32:46,966 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7179 Process Time: 0.330 Mem R(MA/MR): 10418 (21268/36094) [2025-04-29 12:32:48,686 INFO hook.py line 449 1619929] Test: [35/50] Loss 6.6841 Process Time: 0.311 Mem R(MA/MR): 14528 (21268/36094) [2025-04-29 12:32:49,261 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.3570 Process Time: 0.207 Mem R(MA/MR): 7230 (21268/36094) [2025-04-29 12:32:53,001 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9722 Process Time: 0.590 Mem R(MA/MR): 28782 (21268/36094) [2025-04-29 12:32:54,662 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.0022 Process Time: 0.388 Mem R(MA/MR): 11220 (21268/36094) [2025-04-29 12:32:55,331 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2938 Process Time: 0.287 Mem R(MA/MR): 6152 (21268/36094) [2025-04-29 12:32:56,428 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8081 Process Time: 0.314 Mem R(MA/MR): 10870 (21268/36094) [2025-04-29 12:32:57,355 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0944 Process Time: 0.283 Mem R(MA/MR): 9550 (21268/36094) [2025-04-29 12:32:57,868 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2502 Process Time: 0.174 Mem R(MA/MR): 6140 (21268/36094) [2025-04-29 12:32:58,266 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9251 Process Time: 0.125 Mem R(MA/MR): 6190 (21268/36094) [2025-04-29 12:32:59,034 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3958 Process Time: 0.337 Mem R(MA/MR): 7738 (21268/36094) [2025-04-29 12:32:59,804 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7211 Process Time: 0.300 Mem R(MA/MR): 5864 (21268/36094) [2025-04-29 12:33:02,847 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8109 Process Time: 1.121 Mem R(MA/MR): 15128 (21268/36094) [2025-04-29 12:33:10,231 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.6697 Process Time: 1.055 Mem R(MA/MR): 20990 (21268/36094) [2025-04-29 12:33:21,077 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.0737 Process Time: 1.525 Mem R(MA/MR): 36162 (21268/36162) [2025-04-29 12:33:22,283 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9257 Process Time: 0.576 Mem R(MA/MR): 6220 (21268/36162) [2025-04-29 12:33:24,349 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1786 Process Time: 0.253 Mem R(MA/MR): 14294 (21268/36162) [2025-04-29 12:33:28,872 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 12:33:28,872 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 12:33:28,872 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 12:33:28,872 INFO hook.py line 395 1619929] table : 0.283 0.627 0.758 0.842 0.588 [2025-04-29 12:33:28,872 INFO hook.py line 395 1619929] door : 0.418 0.716 0.858 0.877 0.722 [2025-04-29 12:33:28,872 INFO hook.py line 395 1619929] ceiling lamp : 0.571 0.786 0.883 0.834 0.779 [2025-04-29 12:33:28,872 INFO hook.py line 395 1619929] cabinet : 0.346 0.485 0.609 0.494 0.567 [2025-04-29 12:33:28,872 INFO hook.py line 395 1619929] blinds : 0.511 0.785 0.860 0.724 0.913 [2025-04-29 12:33:28,872 INFO hook.py line 395 1619929] curtain : 0.375 0.520 0.736 0.667 0.500 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] chair : 0.597 0.754 0.813 0.753 0.738 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] storage cabinet: 0.214 0.375 0.541 0.522 0.480 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] office chair : 0.562 0.594 0.624 0.686 0.729 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] bookshelf : 0.296 0.680 0.753 0.727 0.727 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] whiteboard : 0.544 0.764 0.782 0.818 0.771 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] window : 0.141 0.334 0.568 0.536 0.407 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] box : 0.185 0.352 0.505 0.529 0.403 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] monitor : 0.644 0.786 0.826 0.931 0.771 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] shelf : 0.101 0.290 0.551 0.833 0.333 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] heater : 0.418 0.696 0.770 0.879 0.763 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] kitchen cabinet: 0.077 0.225 0.579 0.333 0.400 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] sofa : 0.504 0.660 0.783 0.625 0.833 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] bed : 0.296 0.625 0.896 1.000 0.625 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] trash can : 0.498 0.658 0.698 0.810 0.785 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] book : 0.015 0.033 0.069 0.184 0.109 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] plant : 0.478 0.606 0.662 0.917 0.611 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] blanket : 0.483 0.695 0.696 1.000 0.636 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] tv : 0.948 1.000 1.000 1.000 1.000 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] computer tower : 0.198 0.351 0.556 0.654 0.405 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] refrigerator : 0.280 0.452 0.453 0.667 0.444 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] jacket : 0.060 0.161 0.322 0.333 0.455 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] sink : 0.396 0.653 0.908 0.889 0.727 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] bag : 0.083 0.140 0.181 0.300 0.333 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] picture : 0.164 0.358 0.399 0.700 0.359 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] pillow : 0.601 0.788 0.828 0.789 0.789 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] towel : 0.178 0.289 0.478 0.714 0.263 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] suitcase : 0.358 0.477 0.477 0.667 0.571 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] backpack : 0.362 0.452 0.519 0.714 0.385 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] crate : 0.070 0.382 0.550 0.714 0.455 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] keyboard : 0.464 0.646 0.686 1.000 0.538 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] toilet : 0.857 1.000 1.000 1.000 1.000 [2025-04-29 12:33:28,873 INFO hook.py line 395 1619929] printer : 0.313 0.488 0.492 1.000 0.444 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.002 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] painting : 0.073 0.083 0.100 0.167 1.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] microwave : 0.433 0.706 0.875 1.000 0.625 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] shoes : 0.158 0.277 0.575 0.567 0.415 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] socket : 0.181 0.436 0.658 0.609 0.500 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] bottle : 0.080 0.156 0.292 0.568 0.253 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] bucket : 0.026 0.026 0.026 0.154 0.286 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] cushion : 0.130 0.325 0.459 0.333 0.667 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 1.000 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] telephone : 0.239 0.575 0.684 1.000 0.471 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] laptop : 0.249 0.401 0.411 0.417 0.625 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] plant pot : 0.098 0.233 0.404 0.571 0.500 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] exhaust fan : 0.150 0.298 0.333 0.714 0.333 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] cup : 0.185 0.342 0.443 0.778 0.318 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] coat hanger : 0.139 0.500 0.500 1.000 0.500 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] light switch : 0.227 0.468 0.617 0.721 0.477 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] speaker : 0.384 0.465 0.473 0.667 0.545 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.500 1.000 0.333 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] smoke detector : 0.536 0.750 0.750 1.000 0.750 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] power strip : 0.127 0.165 0.173 0.200 0.400 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] mouse : 0.500 0.755 0.760 0.889 0.750 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] toilet paper : 0.214 0.353 0.433 1.000 0.353 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] paper towel : 0.045 0.073 0.177 0.500 0.250 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] clock : 0.528 1.000 1.000 1.000 1.000 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] pan : 0.194 0.250 0.500 1.000 0.250 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] tap : 0.205 0.272 0.545 0.500 0.333 [2025-04-29 12:33:28,874 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] soap dispenser : 0.313 0.465 0.473 1.000 0.400 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] bowl : 0.009 0.042 0.056 0.250 0.333 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] whiteboard eraser: 0.164 0.427 0.434 0.800 0.667 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] toilet brush : 0.412 0.660 0.871 0.800 0.667 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] spray bottle : 0.009 0.014 0.014 0.111 0.250 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] stapler : 0.006 0.033 0.206 0.200 0.333 [2025-04-29 12:33:28,875 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 12:33:28,875 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 12:33:28,875 INFO hook.py line 404 1619929] average : 0.258 0.400 0.496 0.612 0.466 [2025-04-29 12:33:28,875 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 12:33:28,875 INFO hook.py line 480 1619929] Total Process Time: 24.176 s [2025-04-29 12:33:28,876 INFO hook.py line 481 1619929] Average Process Time: 485.364 ms [2025-04-29 12:33:28,876 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 12:33:28,915 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 12:33:28,920 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:35:00,161 INFO hook.py line 650 1619929] Train: [321/512][50/242] Data 0.016 (0.017) Batch 1.412 (1.516) Remain 19:32:29 loss: 5.6542 Lr: 1.24061e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 12:36:14,195 INFO hook.py line 650 1619929] Train: [321/512][100/242] Data 0.017 (0.017) Batch 1.484 (1.498) Remain 19:17:15 loss: 4.4921 Lr: 1.23941e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 12:37:25,719 INFO hook.py line 650 1619929] Train: [321/512][150/242] Data 0.019 (0.017) Batch 1.447 (1.475) Remain 18:58:23 loss: 4.9440 Lr: 1.23821e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 12:38:38,050 INFO hook.py line 650 1619929] Train: [321/512][200/242] Data 0.015 (0.022) Batch 1.171 (1.468) Remain 18:51:38 loss: 5.3143 Lr: 1.23701e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 12:39:34,968 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3103 loss_mask: 0.0362 loss_dice: 1.9827 loss_score: 0.0000 loss_bbox: 0.0497 loss_sp_cls: 0.7805 loss: 5.0749 [2025-04-29 12:39:38,136 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:41:13,312 INFO hook.py line 650 1619929] Train: [322/512][50/242] Data 0.018 (0.016) Batch 1.608 (1.474) Remain 18:54:20 loss: 5.2429 Lr: 1.23480e-04 Mem R(MA/MR): 20424 (21268/36162) [2025-04-29 12:42:27,881 INFO hook.py line 650 1619929] Train: [322/512][100/242] Data 0.016 (0.016) Batch 1.369 (1.483) Remain 18:59:58 loss: 4.6118 Lr: 1.23359e-04 Mem R(MA/MR): 24862 (21268/36162) [2025-04-29 12:43:40,971 INFO hook.py line 650 1619929] Train: [322/512][150/242] Data 0.020 (0.017) Batch 1.314 (1.476) Remain 18:53:12 loss: 5.0915 Lr: 1.23239e-04 Mem R(MA/MR): 24864 (21268/36162) [2025-04-29 12:44:54,120 INFO hook.py line 650 1619929] Train: [322/512][200/242] Data 0.015 (0.016) Batch 1.255 (1.473) Remain 18:49:28 loss: 5.9754 Lr: 1.23119e-04 Mem R(MA/MR): 27344 (21268/36162) [2025-04-29 12:45:51,889 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3120 loss_mask: 0.0370 loss_dice: 1.9862 loss_score: 0.0000 loss_bbox: 0.0507 loss_sp_cls: 0.7881 loss: 5.0989 [2025-04-29 12:45:53,846 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:47:30,410 INFO hook.py line 650 1619929] Train: [323/512][50/242] Data 0.016 (0.016) Batch 1.414 (1.483) Remain 18:54:56 loss: 4.9477 Lr: 1.22897e-04 Mem R(MA/MR): 19886 (21268/36162) [2025-04-29 12:48:42,474 INFO hook.py line 650 1619929] Train: [323/512][100/242] Data 0.015 (0.017) Batch 1.383 (1.461) Remain 18:37:25 loss: 4.6844 Lr: 1.22777e-04 Mem R(MA/MR): 20586 (21268/36162) [2025-04-29 12:49:54,470 INFO hook.py line 650 1619929] Train: [323/512][150/242] Data 0.018 (0.017) Batch 1.703 (1.454) Remain 18:30:38 loss: 5.4490 Lr: 1.22657e-04 Mem R(MA/MR): 20590 (21268/36162) [2025-04-29 12:51:06,979 INFO hook.py line 650 1619929] Train: [323/512][200/242] Data 0.014 (0.017) Batch 1.376 (1.453) Remain 18:28:41 loss: 4.6333 Lr: 1.22536e-04 Mem R(MA/MR): 20596 (21268/36162) [2025-04-29 12:52:04,860 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3059 loss_mask: 0.0367 loss_dice: 1.9701 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.7811 loss: 5.0505 [2025-04-29 12:52:08,881 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 12:53:47,302 INFO hook.py line 650 1619929] Train: [324/512][50/242] Data 0.015 (0.016) Batch 1.327 (1.500) Remain 19:02:18 loss: 4.8834 Lr: 1.22315e-04 Mem R(MA/MR): 23052 (21268/36162) [2025-04-29 12:55:01,424 INFO hook.py line 650 1619929] Train: [324/512][100/242] Data 0.016 (0.016) Batch 1.441 (1.491) Remain 18:54:06 loss: 5.0186 Lr: 1.22195e-04 Mem R(MA/MR): 24952 (21268/36162) [2025-04-29 12:56:15,028 INFO hook.py line 650 1619929] Train: [324/512][150/242] Data 0.016 (0.016) Batch 1.482 (1.485) Remain 18:47:58 loss: 4.2359 Lr: 1.22074e-04 Mem R(MA/MR): 24954 (21268/36162) [2025-04-29 12:57:30,203 INFO hook.py line 650 1619929] Train: [324/512][200/242] Data 0.015 (0.016) Batch 1.250 (1.489) Remain 18:50:23 loss: 4.2936 Lr: 1.21954e-04 Mem R(MA/MR): 24954 (21268/36162) [2025-04-29 12:58:28,009 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3056 loss_mask: 0.0360 loss_dice: 1.9725 loss_score: 0.0000 loss_bbox: 0.0502 loss_sp_cls: 0.7807 loss: 5.0490 [2025-04-29 12:58:31,875 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:00:08,816 INFO hook.py line 650 1619929] Train: [325/512][50/242] Data 0.016 (0.017) Batch 1.312 (1.459) Remain 18:25:23 loss: 3.9872 Lr: 1.21732e-04 Mem R(MA/MR): 24014 (21268/36162) [2025-04-29 13:01:23,970 INFO hook.py line 650 1619929] Train: [325/512][100/242] Data 0.016 (0.017) Batch 1.432 (1.482) Remain 18:41:12 loss: 5.2350 Lr: 1.21612e-04 Mem R(MA/MR): 25902 (21268/36162) [2025-04-29 13:02:35,574 INFO hook.py line 650 1619929] Train: [325/512][150/242] Data 0.016 (0.017) Batch 1.492 (1.465) Remain 18:27:09 loss: 4.0318 Lr: 1.21491e-04 Mem R(MA/MR): 26842 (21268/36162) [2025-04-29 13:03:48,642 INFO hook.py line 650 1619929] Train: [325/512][200/242] Data 0.015 (0.017) Batch 1.366 (1.464) Remain 18:25:15 loss: 4.7459 Lr: 1.21371e-04 Mem R(MA/MR): 26846 (21268/36162) [2025-04-29 13:04:46,344 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3012 loss_mask: 0.0363 loss_dice: 1.9611 loss_score: 0.0000 loss_bbox: 0.0503 loss_sp_cls: 0.7768 loss: 5.0191 [2025-04-29 13:04:47,308 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:06:16,239 INFO hook.py line 650 1619929] Train: [326/512][50/242] Data 0.021 (0.016) Batch 1.676 (1.494) Remain 18:45:18 loss: 5.5285 Lr: 1.21149e-04 Mem R(MA/MR): 24566 (21268/36162) [2025-04-29 13:07:30,227 INFO hook.py line 650 1619929] Train: [326/512][100/242] Data 0.018 (0.016) Batch 1.585 (1.486) Remain 18:38:40 loss: 5.4606 Lr: 1.21029e-04 Mem R(MA/MR): 26568 (21268/36162) [2025-04-29 13:08:41,015 INFO hook.py line 650 1619929] Train: [326/512][150/242] Data 0.019 (0.016) Batch 1.342 (1.462) Remain 18:19:21 loss: 4.5073 Lr: 1.20908e-04 Mem R(MA/MR): 26568 (21268/36162) [2025-04-29 13:09:52,497 INFO hook.py line 650 1619929] Train: [326/512][200/242] Data 0.015 (0.016) Batch 1.462 (1.454) Remain 18:11:53 loss: 5.8212 Lr: 1.20788e-04 Mem R(MA/MR): 26570 (21268/36162) [2025-04-29 13:10:51,710 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2920 loss_mask: 0.0347 loss_dice: 1.9194 loss_score: 0.0000 loss_bbox: 0.0499 loss_sp_cls: 0.7600 loss: 4.9151 [2025-04-29 13:10:56,643 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:12:31,557 INFO hook.py line 650 1619929] Train: [327/512][50/242] Data 0.018 (0.016) Batch 1.551 (1.476) Remain 18:26:11 loss: 4.7467 Lr: 1.20566e-04 Mem R(MA/MR): 20186 (21268/36162) [2025-04-29 13:13:44,549 INFO hook.py line 650 1619929] Train: [327/512][100/242] Data 0.017 (0.016) Batch 1.692 (1.468) Remain 18:18:38 loss: 5.8301 Lr: 1.20445e-04 Mem R(MA/MR): 20186 (21268/36162) [2025-04-29 13:14:58,454 INFO hook.py line 650 1619929] Train: [327/512][150/242] Data 0.016 (0.016) Batch 1.404 (1.471) Remain 18:20:04 loss: 4.2000 Lr: 1.20325e-04 Mem R(MA/MR): 22786 (21268/36162) [2025-04-29 13:16:11,937 INFO hook.py line 650 1619929] Train: [327/512][200/242] Data 0.015 (0.016) Batch 1.351 (1.471) Remain 18:18:32 loss: 5.0503 Lr: 1.20206e-04 Mem R(MA/MR): 22786 (21268/36162) [2025-04-29 13:17:10,123 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2888 loss_mask: 0.0349 loss_dice: 1.9355 loss_score: 0.0000 loss_bbox: 0.0489 loss_sp_cls: 0.7571 loss: 4.9247 [2025-04-29 13:17:10,197 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:18:43,165 INFO hook.py line 650 1619929] Train: [328/512][50/242] Data 0.017 (0.016) Batch 1.363 (1.477) Remain 18:20:48 loss: 4.4606 Lr: 1.19984e-04 Mem R(MA/MR): 21218 (21268/36162) [2025-04-29 13:19:57,375 INFO hook.py line 650 1619929] Train: [328/512][100/242] Data 0.018 (0.016) Batch 1.615 (1.481) Remain 18:22:21 loss: 5.4452 Lr: 1.19864e-04 Mem R(MA/MR): 21218 (21268/36162) [2025-04-29 13:21:09,386 INFO hook.py line 650 1619929] Train: [328/512][150/242] Data 0.016 (0.016) Batch 1.296 (1.467) Remain 18:10:54 loss: 4.1144 Lr: 1.19743e-04 Mem R(MA/MR): 21232 (21268/36162) [2025-04-29 13:22:22,432 INFO hook.py line 650 1619929] Train: [328/512][200/242] Data 0.015 (0.016) Batch 1.444 (1.465) Remain 18:08:32 loss: 4.0428 Lr: 1.19622e-04 Mem R(MA/MR): 23134 (21268/36162) [2025-04-29 13:23:20,303 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3030 loss_mask: 0.0356 loss_dice: 1.9513 loss_score: 0.0000 loss_bbox: 0.0503 loss_sp_cls: 0.7697 loss: 5.0085 [2025-04-29 13:23:22,376 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 13:23:24,615 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.6593 Process Time: 0.289 Mem R(MA/MR): 4380 (21268/36162) [2025-04-29 13:23:26,632 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.0654 Process Time: 0.781 Mem R(MA/MR): 7570 (21268/36162) [2025-04-29 13:23:28,270 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.0616 Process Time: 0.546 Mem R(MA/MR): 9240 (21268/36162) [2025-04-29 13:23:34,974 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.2186 Process Time: 1.021 Mem R(MA/MR): 19734 (21268/36162) [2025-04-29 13:23:35,693 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.2019 Process Time: 0.182 Mem R(MA/MR): 6728 (21268/36162) [2025-04-29 13:23:37,081 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7425 Process Time: 0.452 Mem R(MA/MR): 11534 (21268/36162) [2025-04-29 13:23:37,673 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0207 Process Time: 0.229 Mem R(MA/MR): 6324 (21268/36162) [2025-04-29 13:23:38,115 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.7920 Process Time: 0.190 Mem R(MA/MR): 4362 (21268/36162) [2025-04-29 13:23:38,996 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6276 Process Time: 0.272 Mem R(MA/MR): 11608 (21268/36162) [2025-04-29 13:23:40,503 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6100 Process Time: 0.364 Mem R(MA/MR): 9524 (21268/36162) [2025-04-29 13:23:42,917 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.5537 Process Time: 0.417 Mem R(MA/MR): 18976 (21268/36162) [2025-04-29 13:23:45,472 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0293 Process Time: 0.677 Mem R(MA/MR): 15454 (21268/36162) [2025-04-29 13:23:46,620 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.4864 Process Time: 0.309 Mem R(MA/MR): 8902 (21268/36162) [2025-04-29 13:23:47,021 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0850 Process Time: 0.141 Mem R(MA/MR): 4536 (21268/36162) [2025-04-29 13:23:49,685 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.4164 Process Time: 0.317 Mem R(MA/MR): 16390 (21268/36162) [2025-04-29 13:23:51,721 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.5556 Process Time: 0.720 Mem R(MA/MR): 14896 (21268/36162) [2025-04-29 13:23:52,678 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.4776 Process Time: 0.255 Mem R(MA/MR): 6592 (21268/36162) [2025-04-29 13:23:53,456 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.5379 Process Time: 0.211 Mem R(MA/MR): 8400 (21268/36162) [2025-04-29 13:23:54,719 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6343 Process Time: 0.186 Mem R(MA/MR): 6076 (21268/36162) [2025-04-29 13:23:56,129 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.9011 Process Time: 0.253 Mem R(MA/MR): 11728 (21268/36162) [2025-04-29 13:24:04,159 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.7865 Process Time: 0.969 Mem R(MA/MR): 23134 (21268/36162) [2025-04-29 13:24:04,721 INFO hook.py line 449 1619929] Test: [22/50] Loss 4.9629 Process Time: 0.156 Mem R(MA/MR): 6708 (21268/36162) [2025-04-29 13:24:15,013 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.1840 Process Time: 0.295 Mem R(MA/MR): 10396 (21268/36162) [2025-04-29 13:24:15,566 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.5137 Process Time: 0.152 Mem R(MA/MR): 5324 (21268/36162) [2025-04-29 13:24:16,663 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0726 Process Time: 0.349 Mem R(MA/MR): 8968 (21268/36162) [2025-04-29 13:24:23,128 INFO hook.py line 449 1619929] Test: [26/50] Loss 13.5381 Process Time: 1.110 Mem R(MA/MR): 30530 (21268/36162) [2025-04-29 13:24:24,965 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.5124 Process Time: 0.359 Mem R(MA/MR): 9768 (21268/36162) [2025-04-29 13:24:26,050 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5192 Process Time: 0.224 Mem R(MA/MR): 8628 (21268/36162) [2025-04-29 13:24:30,958 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.3116 Process Time: 0.503 Mem R(MA/MR): 17420 (21268/36162) [2025-04-29 13:24:31,990 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.8005 Process Time: 0.283 Mem R(MA/MR): 8072 (21268/36162) [2025-04-29 13:24:35,834 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.7224 Process Time: 0.596 Mem R(MA/MR): 20670 (21268/36162) [2025-04-29 13:24:36,108 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.7113 Process Time: 0.107 Mem R(MA/MR): 4182 (21268/36162) [2025-04-29 13:24:39,979 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.2162 Process Time: 0.512 Mem R(MA/MR): 24688 (21268/36162) [2025-04-29 13:24:40,898 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6650 Process Time: 0.223 Mem R(MA/MR): 9342 (21268/36162) [2025-04-29 13:24:42,980 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.9903 Process Time: 0.457 Mem R(MA/MR): 14146 (21268/36162) [2025-04-29 13:24:43,558 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.6407 Process Time: 0.189 Mem R(MA/MR): 6456 (21268/36162) [2025-04-29 13:24:47,519 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.2494 Process Time: 0.801 Mem R(MA/MR): 28154 (21268/36162) [2025-04-29 13:24:48,954 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1835 Process Time: 0.239 Mem R(MA/MR): 10698 (21268/36162) [2025-04-29 13:24:49,601 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3043 Process Time: 0.280 Mem R(MA/MR): 5834 (21268/36162) [2025-04-29 13:24:50,800 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.6525 Process Time: 0.393 Mem R(MA/MR): 10054 (21268/36162) [2025-04-29 13:24:51,786 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0573 Process Time: 0.274 Mem R(MA/MR): 8794 (21268/36162) [2025-04-29 13:24:52,441 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9278 Process Time: 0.279 Mem R(MA/MR): 5830 (21268/36162) [2025-04-29 13:24:53,068 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.5862 Process Time: 0.281 Mem R(MA/MR): 5860 (21268/36162) [2025-04-29 13:24:53,559 INFO hook.py line 449 1619929] Test: [44/50] Loss 9.1718 Process Time: 0.174 Mem R(MA/MR): 7404 (21268/36162) [2025-04-29 13:24:54,151 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.2262 Process Time: 0.148 Mem R(MA/MR): 5314 (21268/36162) [2025-04-29 13:24:56,284 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.0156 Process Time: 0.445 Mem R(MA/MR): 14764 (21268/36162) [2025-04-29 13:25:02,588 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.4427 Process Time: 0.894 Mem R(MA/MR): 20146 (21268/36162) [2025-04-29 13:25:12,128 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.6021 Process Time: 0.959 Mem R(MA/MR): 35034 (21268/36162) [2025-04-29 13:25:12,794 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1664 Process Time: 0.277 Mem R(MA/MR): 5802 (21268/36162) [2025-04-29 13:25:15,100 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5210 Process Time: 0.575 Mem R(MA/MR): 13718 (21268/36162) [2025-04-29 13:25:19,049 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 13:25:19,049 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 13:25:19,049 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] table : 0.283 0.589 0.752 0.804 0.632 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] door : 0.469 0.745 0.842 0.938 0.759 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] ceiling lamp : 0.573 0.766 0.866 0.858 0.735 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] cabinet : 0.372 0.490 0.523 0.529 0.552 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] blinds : 0.604 0.864 0.898 1.000 0.826 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] curtain : 0.423 0.685 0.764 1.000 0.500 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] chair : 0.660 0.796 0.826 0.869 0.709 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] storage cabinet: 0.280 0.491 0.570 0.593 0.640 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] office chair : 0.572 0.586 0.616 0.655 0.750 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] bookshelf : 0.245 0.601 0.686 0.778 0.636 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] whiteboard : 0.545 0.715 0.757 0.774 0.686 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] window : 0.101 0.260 0.607 0.517 0.341 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] box : 0.211 0.395 0.530 0.485 0.459 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] monitor : 0.610 0.756 0.803 0.926 0.714 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] shelf : 0.126 0.236 0.377 0.435 0.333 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] heater : 0.365 0.546 0.666 0.788 0.684 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] kitchen cabinet: 0.106 0.327 0.717 0.395 0.680 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] sofa : 0.435 0.636 0.860 0.625 0.833 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] bed : 0.266 0.510 0.845 0.625 0.625 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] trash can : 0.521 0.686 0.740 0.758 0.769 [2025-04-29 13:25:19,049 INFO hook.py line 395 1619929] book : 0.023 0.038 0.088 0.168 0.112 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] plant : 0.537 0.722 0.771 1.000 0.722 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] blanket : 0.438 0.644 0.644 0.800 0.727 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] tv : 0.930 1.000 1.000 1.000 1.000 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] computer tower : 0.213 0.356 0.621 0.543 0.452 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] refrigerator : 0.310 0.472 0.472 0.429 0.667 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] jacket : 0.152 0.424 0.621 0.562 0.818 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] sink : 0.342 0.537 0.808 0.857 0.545 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] bag : 0.092 0.140 0.160 0.450 0.333 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] picture : 0.129 0.233 0.346 0.395 0.385 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] pillow : 0.487 0.676 0.734 0.846 0.579 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] towel : 0.204 0.328 0.551 0.600 0.316 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] suitcase : 0.466 0.647 0.647 1.000 0.571 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] backpack : 0.321 0.394 0.441 0.667 0.462 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] crate : 0.105 0.419 0.674 0.600 0.545 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] keyboard : 0.432 0.563 0.577 0.778 0.538 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] toilet : 0.851 0.876 1.000 0.889 0.889 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] printer : 0.274 0.521 0.521 0.714 0.556 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] poster : 0.001 0.006 0.007 0.111 0.111 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] painting : 0.065 0.071 0.071 0.143 1.000 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] microwave : 0.661 0.750 0.875 1.000 0.750 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] shoes : 0.160 0.298 0.474 0.636 0.341 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] socket : 0.200 0.458 0.685 0.722 0.500 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] bottle : 0.129 0.224 0.310 0.618 0.253 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] bucket : 0.025 0.026 0.072 0.097 0.429 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] cushion : 0.111 0.233 0.233 0.444 0.667 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] basket : 0.012 0.018 0.064 0.250 0.143 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] telephone : 0.234 0.471 0.544 0.800 0.471 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] laptop : 0.156 0.248 0.462 0.357 0.625 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] plant pot : 0.106 0.258 0.371 0.700 0.438 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] exhaust fan : 0.178 0.362 0.400 0.857 0.400 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] cup : 0.253 0.406 0.469 0.850 0.386 [2025-04-29 13:25:19,050 INFO hook.py line 395 1619929] coat hanger : 0.169 0.354 0.533 0.500 0.500 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] light switch : 0.249 0.487 0.632 0.648 0.538 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] speaker : 0.242 0.316 0.382 0.333 0.636 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.792 1.000 0.500 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] smoke detector : 0.603 0.767 0.768 0.864 0.792 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] power strip : 0.041 0.079 0.112 0.267 0.400 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] paper bag : 0.066 0.071 0.083 0.143 1.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] mouse : 0.549 0.783 0.821 0.833 0.781 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] cutting board : 0.306 0.500 0.677 1.000 0.500 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] toilet paper : 0.265 0.412 0.450 1.000 0.412 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.125 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] clock : 0.554 0.850 0.903 1.000 0.667 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] pan : 0.111 0.250 0.250 1.000 0.250 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] tap : 0.095 0.206 0.667 0.667 0.444 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] soap dispenser : 0.472 0.652 0.656 1.000 0.600 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] bowl : 0.028 0.083 0.083 0.500 0.333 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] whiteboard eraser: 0.160 0.474 0.486 0.800 0.667 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] toilet brush : 0.500 0.667 0.833 1.000 0.667 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] spray bottle : 0.012 0.018 0.018 0.143 0.250 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] stapler : 0.022 0.107 0.250 0.333 0.333 [2025-04-29 13:25:19,051 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 13:25:19,051 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 13:25:19,051 INFO hook.py line 404 1619929] average : 0.266 0.401 0.498 0.601 0.496 [2025-04-29 13:25:19,051 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 13:25:19,052 INFO hook.py line 480 1619929] Total Process Time: 20.316 s [2025-04-29 13:25:19,052 INFO hook.py line 481 1619929] Average Process Time: 408.716 ms [2025-04-29 13:25:19,052 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 13:25:19,091 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 13:25:19,096 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:26:55,143 INFO hook.py line 650 1619929] Train: [329/512][50/242] Data 0.016 (0.017) Batch 1.331 (1.480) Remain 18:17:18 loss: 4.7569 Lr: 1.19400e-04 Mem R(MA/MR): 20670 (21268/36162) [2025-04-29 13:28:09,257 INFO hook.py line 650 1619929] Train: [329/512][100/242] Data 0.018 (0.027) Batch 1.499 (1.481) Remain 18:16:50 loss: 5.3500 Lr: 1.19280e-04 Mem R(MA/MR): 20670 (21268/36162) [2025-04-29 13:29:23,066 INFO hook.py line 650 1619929] Train: [329/512][150/242] Data 0.019 (0.024) Batch 1.484 (1.480) Remain 18:14:18 loss: 5.2172 Lr: 1.19159e-04 Mem R(MA/MR): 20692 (21268/36162) [2025-04-29 13:30:36,621 INFO hook.py line 650 1619929] Train: [329/512][200/242] Data 0.016 (0.022) Batch 1.332 (1.477) Remain 18:11:30 loss: 5.8027 Lr: 1.19038e-04 Mem R(MA/MR): 22746 (21268/36162) [2025-04-29 13:31:34,269 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3092 loss_mask: 0.0366 loss_dice: 1.9748 loss_score: 0.0000 loss_bbox: 0.0505 loss_sp_cls: 0.7832 loss: 5.0716 [2025-04-29 13:31:37,047 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:33:05,450 INFO hook.py line 650 1619929] Train: [330/512][50/242] Data 0.016 (0.016) Batch 1.398 (1.438) Remain 17:39:55 loss: 4.7995 Lr: 1.18816e-04 Mem R(MA/MR): 20988 (21268/36162) [2025-04-29 13:34:18,171 INFO hook.py line 650 1619929] Train: [330/512][100/242] Data 0.016 (0.017) Batch 1.461 (1.446) Remain 17:45:05 loss: 5.9559 Lr: 1.18695e-04 Mem R(MA/MR): 24308 (21268/36162) [2025-04-29 13:35:31,260 INFO hook.py line 650 1619929] Train: [330/512][150/242] Data 0.017 (0.017) Batch 1.532 (1.452) Remain 17:47:45 loss: 3.8003 Lr: 1.18575e-04 Mem R(MA/MR): 24308 (21268/36162) [2025-04-29 13:36:43,738 INFO hook.py line 650 1619929] Train: [330/512][200/242] Data 0.014 (0.016) Batch 1.321 (1.451) Remain 17:46:11 loss: 5.3380 Lr: 1.18454e-04 Mem R(MA/MR): 24322 (21268/36162) [2025-04-29 13:37:39,235 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3028 loss_mask: 0.0359 loss_dice: 1.9568 loss_score: 0.0000 loss_bbox: 0.0506 loss_sp_cls: 0.7776 loss: 5.0179 [2025-04-29 13:37:39,549 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:39:16,528 INFO hook.py line 650 1619929] Train: [331/512][50/242] Data 0.016 (0.017) Batch 1.414 (1.497) Remain 18:17:55 loss: 4.6695 Lr: 1.18231e-04 Mem R(MA/MR): 23010 (21268/36162) [2025-04-29 13:40:29,496 INFO hook.py line 650 1619929] Train: [331/512][100/242] Data 0.015 (0.017) Batch 1.390 (1.478) Remain 18:02:19 loss: 4.6905 Lr: 1.18111e-04 Mem R(MA/MR): 23010 (21268/36162) [2025-04-29 13:41:41,817 INFO hook.py line 650 1619929] Train: [331/512][150/242] Data 0.016 (0.017) Batch 1.358 (1.467) Remain 17:53:17 loss: 4.8131 Lr: 1.17990e-04 Mem R(MA/MR): 23010 (21268/36162) [2025-04-29 13:42:52,163 INFO hook.py line 650 1619929] Train: [331/512][200/242] Data 0.016 (0.016) Batch 1.280 (1.452) Remain 17:40:54 loss: 4.5410 Lr: 1.17869e-04 Mem R(MA/MR): 23010 (21268/36162) [2025-04-29 13:43:49,228 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3022 loss_mask: 0.0354 loss_dice: 1.9611 loss_score: 0.0000 loss_bbox: 0.0503 loss_sp_cls: 0.7758 loss: 5.0238 [2025-04-29 13:43:52,014 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:45:26,525 INFO hook.py line 650 1619929] Train: [332/512][50/242] Data 0.016 (0.017) Batch 1.371 (1.450) Remain 17:37:29 loss: 5.3627 Lr: 1.17646e-04 Mem R(MA/MR): 22664 (21268/36162) [2025-04-29 13:46:36,383 INFO hook.py line 650 1619929] Train: [332/512][100/242] Data 0.015 (0.017) Batch 1.480 (1.423) Remain 17:16:21 loss: 5.2370 Lr: 1.17526e-04 Mem R(MA/MR): 22676 (21268/36162) [2025-04-29 13:47:47,361 INFO hook.py line 650 1619929] Train: [332/512][150/242] Data 0.016 (0.016) Batch 1.443 (1.422) Remain 17:14:21 loss: 4.6242 Lr: 1.17405e-04 Mem R(MA/MR): 26950 (21268/36162) [2025-04-29 13:48:59,847 INFO hook.py line 650 1619929] Train: [332/512][200/242] Data 0.014 (0.016) Batch 1.383 (1.429) Remain 17:18:20 loss: 4.9292 Lr: 1.17284e-04 Mem R(MA/MR): 26950 (21268/36162) [2025-04-29 13:49:57,707 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3010 loss_mask: 0.0358 loss_dice: 1.9639 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7713 loss: 5.0133 [2025-04-29 13:50:01,783 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:51:34,596 INFO hook.py line 650 1619929] Train: [333/512][50/242] Data 0.015 (0.016) Batch 1.468 (1.472) Remain 17:47:18 loss: 4.5933 Lr: 1.17061e-04 Mem R(MA/MR): 21424 (21268/36162) [2025-04-29 13:52:45,049 INFO hook.py line 650 1619929] Train: [333/512][100/242] Data 0.020 (0.016) Batch 1.552 (1.439) Remain 17:22:37 loss: 4.9188 Lr: 1.16940e-04 Mem R(MA/MR): 21430 (21268/36162) [2025-04-29 13:53:54,467 INFO hook.py line 650 1619929] Train: [333/512][150/242] Data 0.017 (0.016) Batch 1.566 (1.422) Remain 17:08:52 loss: 4.4689 Lr: 1.16819e-04 Mem R(MA/MR): 23484 (21268/36162) [2025-04-29 13:55:06,116 INFO hook.py line 650 1619929] Train: [333/512][200/242] Data 0.016 (0.016) Batch 1.670 (1.425) Remain 17:09:41 loss: 5.8058 Lr: 1.16698e-04 Mem R(MA/MR): 23484 (21268/36162) [2025-04-29 13:56:06,171 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2985 loss_mask: 0.0355 loss_dice: 1.9434 loss_score: 0.0000 loss_bbox: 0.0500 loss_sp_cls: 0.7692 loss: 4.9771 [2025-04-29 13:56:09,625 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 13:57:45,138 INFO hook.py line 650 1619929] Train: [334/512][50/242] Data 0.017 (0.016) Batch 1.442 (1.455) Remain 17:29:04 loss: 4.9457 Lr: 1.16475e-04 Mem R(MA/MR): 24362 (21268/36162) [2025-04-29 13:58:58,669 INFO hook.py line 650 1619929] Train: [334/512][100/242] Data 0.018 (0.016) Batch 1.618 (1.463) Remain 17:33:45 loss: 5.4731 Lr: 1.16354e-04 Mem R(MA/MR): 24374 (21268/36162) [2025-04-29 14:00:12,371 INFO hook.py line 650 1619929] Train: [334/512][150/242] Data 0.017 (0.017) Batch 1.358 (1.467) Remain 17:35:14 loss: 3.6829 Lr: 1.16233e-04 Mem R(MA/MR): 24374 (21268/36162) [2025-04-29 14:01:23,618 INFO hook.py line 650 1619929] Train: [334/512][200/242] Data 0.015 (0.017) Batch 1.327 (1.456) Remain 17:26:24 loss: 5.4852 Lr: 1.16112e-04 Mem R(MA/MR): 26428 (21268/36162) [2025-04-29 14:02:22,040 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2973 loss_mask: 0.0357 loss_dice: 1.9617 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7682 loss: 4.9987 [2025-04-29 14:02:23,266 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:03:50,904 INFO hook.py line 650 1619929] Train: [335/512][50/242] Data 0.015 (0.016) Batch 1.499 (1.477) Remain 17:39:16 loss: 4.9520 Lr: 1.15890e-04 Mem R(MA/MR): 19732 (21268/36162) [2025-04-29 14:05:04,469 INFO hook.py line 650 1619929] Train: [335/512][100/242] Data 0.048 (0.017) Batch 1.380 (1.474) Remain 17:35:52 loss: 5.7430 Lr: 1.15768e-04 Mem R(MA/MR): 21860 (21268/36162) [2025-04-29 14:06:16,227 INFO hook.py line 650 1619929] Train: [335/512][150/242] Data 0.017 (0.016) Batch 1.450 (1.461) Remain 17:25:10 loss: 6.0912 Lr: 1.15647e-04 Mem R(MA/MR): 21860 (21268/36162) [2025-04-29 14:07:29,495 INFO hook.py line 650 1619929] Train: [335/512][200/242] Data 0.014 (0.016) Batch 1.448 (1.462) Remain 17:24:45 loss: 5.5551 Lr: 1.15526e-04 Mem R(MA/MR): 21860 (21268/36162) [2025-04-29 14:08:26,437 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3005 loss_mask: 0.0356 loss_dice: 1.9554 loss_score: 0.0000 loss_bbox: 0.0500 loss_sp_cls: 0.7709 loss: 5.0043 [2025-04-29 14:08:29,682 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:10:07,395 INFO hook.py line 650 1619929] Train: [336/512][50/242] Data 0.016 (0.016) Batch 1.540 (1.505) Remain 17:53:05 loss: 5.1656 Lr: 1.15303e-04 Mem R(MA/MR): 25334 (21268/36162) [2025-04-29 14:11:21,180 INFO hook.py line 650 1619929] Train: [336/512][100/242] Data 0.017 (0.017) Batch 1.373 (1.490) Remain 17:41:07 loss: 4.9456 Lr: 1.15182e-04 Mem R(MA/MR): 25334 (21268/36162) [2025-04-29 14:12:33,134 INFO hook.py line 650 1619929] Train: [336/512][150/242] Data 0.016 (0.016) Batch 1.463 (1.473) Remain 17:27:35 loss: 5.1885 Lr: 1.15061e-04 Mem R(MA/MR): 27046 (21268/36162) [2025-04-29 14:13:46,399 INFO hook.py line 650 1619929] Train: [336/512][200/242] Data 0.015 (0.016) Batch 1.276 (1.471) Remain 17:25:03 loss: 3.4428 Lr: 1.14940e-04 Mem R(MA/MR): 27046 (21268/36162) [2025-04-29 14:14:43,656 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2887 loss_mask: 0.0339 loss_dice: 1.9207 loss_score: 0.0000 loss_bbox: 0.0493 loss_sp_cls: 0.7588 loss: 4.9049 [2025-04-29 14:14:46,487 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 14:14:49,007 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.8121 Process Time: 0.443 Mem R(MA/MR): 4768 (21268/36162) [2025-04-29 14:14:50,585 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8597 Process Time: 0.463 Mem R(MA/MR): 7600 (21268/36162) [2025-04-29 14:14:52,301 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.6956 Process Time: 0.667 Mem R(MA/MR): 10078 (21268/36162) [2025-04-29 14:14:59,463 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.5182 Process Time: 1.224 Mem R(MA/MR): 19952 (21268/36162) [2025-04-29 14:15:00,432 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.1108 Process Time: 0.292 Mem R(MA/MR): 7460 (21268/36162) [2025-04-29 14:15:02,064 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5101 Process Time: 0.584 Mem R(MA/MR): 11724 (21268/36162) [2025-04-29 14:15:02,557 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8802 Process Time: 0.150 Mem R(MA/MR): 6690 (21268/36162) [2025-04-29 14:15:03,218 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.8708 Process Time: 0.318 Mem R(MA/MR): 4764 (21268/36162) [2025-04-29 14:15:04,213 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.1597 Process Time: 0.350 Mem R(MA/MR): 11640 (21268/36162) [2025-04-29 14:15:05,928 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8876 Process Time: 0.494 Mem R(MA/MR): 9928 (21268/36162) [2025-04-29 14:15:08,407 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2485 Process Time: 0.450 Mem R(MA/MR): 19012 (21268/36162) [2025-04-29 14:15:10,733 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.7243 Process Time: 0.436 Mem R(MA/MR): 15538 (21268/36162) [2025-04-29 14:15:11,755 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.6103 Process Time: 0.217 Mem R(MA/MR): 9140 (21268/36162) [2025-04-29 14:15:12,254 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.5973 Process Time: 0.226 Mem R(MA/MR): 5148 (21268/36162) [2025-04-29 14:15:15,092 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.8362 Process Time: 0.451 Mem R(MA/MR): 16782 (21268/36162) [2025-04-29 14:15:16,853 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.7671 Process Time: 0.535 Mem R(MA/MR): 14596 (21268/36162) [2025-04-29 14:15:17,632 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.6790 Process Time: 0.276 Mem R(MA/MR): 7112 (21268/36162) [2025-04-29 14:15:18,384 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7953 Process Time: 0.179 Mem R(MA/MR): 8558 (21268/36162) [2025-04-29 14:15:19,936 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0483 Process Time: 0.434 Mem R(MA/MR): 6470 (21268/36162) [2025-04-29 14:15:21,496 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.9500 Process Time: 0.310 Mem R(MA/MR): 11746 (21268/36162) [2025-04-29 14:15:29,259 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.0573 Process Time: 0.497 Mem R(MA/MR): 23476 (21268/36162) [2025-04-29 14:15:30,425 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2921 Process Time: 0.556 Mem R(MA/MR): 7264 (21268/36162) [2025-04-29 14:15:42,224 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.8799 Process Time: 0.383 Mem R(MA/MR): 10470 (21268/36162) [2025-04-29 14:15:42,821 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0934 Process Time: 0.203 Mem R(MA/MR): 5728 (21268/36162) [2025-04-29 14:15:44,046 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2718 Process Time: 0.437 Mem R(MA/MR): 9578 (21268/36162) [2025-04-29 14:15:49,688 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.7825 Process Time: 0.792 Mem R(MA/MR): 31026 (21268/36162) [2025-04-29 14:15:51,579 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.8648 Process Time: 0.262 Mem R(MA/MR): 10332 (21268/36162) [2025-04-29 14:15:52,938 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0363 Process Time: 0.333 Mem R(MA/MR): 9298 (21268/36162) [2025-04-29 14:15:57,443 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8479 Process Time: 0.493 Mem R(MA/MR): 17406 (21268/36162) [2025-04-29 14:15:58,322 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.8111 Process Time: 0.218 Mem R(MA/MR): 8084 (21268/36162) [2025-04-29 14:16:02,049 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.1151 Process Time: 0.527 Mem R(MA/MR): 20972 (21268/36162) [2025-04-29 14:16:02,740 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.8177 Process Time: 0.265 Mem R(MA/MR): 4386 (21268/36162) [2025-04-29 14:16:07,092 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.7846 Process Time: 0.547 Mem R(MA/MR): 25296 (21268/36162) [2025-04-29 14:16:08,363 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6160 Process Time: 0.286 Mem R(MA/MR): 10280 (21268/36162) [2025-04-29 14:16:10,115 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.5875 Process Time: 0.347 Mem R(MA/MR): 14372 (21268/36162) [2025-04-29 14:16:10,692 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2009 Process Time: 0.205 Mem R(MA/MR): 6964 (21268/36162) [2025-04-29 14:16:14,456 INFO hook.py line 449 1619929] Test: [37/50] Loss 12.7362 Process Time: 0.582 Mem R(MA/MR): 28772 (21268/36162) [2025-04-29 14:16:15,925 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.6908 Process Time: 0.275 Mem R(MA/MR): 11066 (21268/36162) [2025-04-29 14:16:16,527 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1990 Process Time: 0.215 Mem R(MA/MR): 5906 (21268/36162) [2025-04-29 14:16:17,718 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.1880 Process Time: 0.357 Mem R(MA/MR): 10634 (21268/36162) [2025-04-29 14:16:18,886 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.6442 Process Time: 0.333 Mem R(MA/MR): 9376 (21268/36162) [2025-04-29 14:16:19,383 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.5888 Process Time: 0.130 Mem R(MA/MR): 5912 (21268/36162) [2025-04-29 14:16:19,790 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8482 Process Time: 0.123 Mem R(MA/MR): 5944 (21268/36162) [2025-04-29 14:16:20,719 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.7639 Process Time: 0.488 Mem R(MA/MR): 7446 (21268/36162) [2025-04-29 14:16:21,277 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.9207 Process Time: 0.182 Mem R(MA/MR): 5624 (21268/36162) [2025-04-29 14:16:23,414 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.8576 Process Time: 0.543 Mem R(MA/MR): 14748 (21268/36162) [2025-04-29 14:16:30,586 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.3760 Process Time: 1.220 Mem R(MA/MR): 20478 (21268/36162) [2025-04-29 14:16:40,196 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.3138 Process Time: 1.727 Mem R(MA/MR): 34928 (21268/36162) [2025-04-29 14:16:40,872 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0463 Process Time: 0.272 Mem R(MA/MR): 6030 (21268/36162) [2025-04-29 14:16:43,199 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2130 Process Time: 0.298 Mem R(MA/MR): 14078 (21268/36162) [2025-04-29 14:16:47,803 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 14:16:47,804 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 14:16:47,804 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] table : 0.276 0.620 0.739 0.832 0.618 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] door : 0.444 0.727 0.883 0.866 0.734 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] ceiling lamp : 0.597 0.800 0.888 0.795 0.812 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] cabinet : 0.357 0.465 0.551 0.625 0.448 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] blinds : 0.637 0.801 0.820 0.864 0.826 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] curtain : 0.374 0.519 0.835 0.750 0.500 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] chair : 0.672 0.799 0.830 0.876 0.721 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] storage cabinet: 0.188 0.273 0.464 0.478 0.440 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] office chair : 0.637 0.649 0.649 0.722 0.812 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] bookshelf : 0.317 0.606 0.675 0.727 0.727 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] whiteboard : 0.535 0.704 0.828 0.893 0.714 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] window : 0.131 0.317 0.641 0.517 0.330 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] box : 0.198 0.365 0.529 0.545 0.431 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] monitor : 0.617 0.767 0.814 0.902 0.786 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] shelf : 0.140 0.293 0.449 0.550 0.367 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] heater : 0.434 0.649 0.854 0.750 0.711 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] kitchen cabinet: 0.087 0.380 0.575 0.579 0.440 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] sofa : 0.443 0.822 0.934 0.818 0.750 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] bed : 0.146 0.366 0.676 0.667 0.500 [2025-04-29 14:16:47,804 INFO hook.py line 395 1619929] trash can : 0.494 0.658 0.695 0.847 0.769 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] book : 0.028 0.048 0.079 0.187 0.120 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] plant : 0.507 0.711 0.878 1.000 0.667 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] blanket : 0.489 0.665 0.666 0.875 0.636 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] tv : 0.817 0.941 0.941 1.000 0.833 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] computer tower : 0.208 0.308 0.614 0.607 0.405 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] refrigerator : 0.146 0.342 0.349 0.600 0.333 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] jacket : 0.084 0.236 0.426 0.500 0.455 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] sink : 0.354 0.595 0.836 0.824 0.636 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] bag : 0.102 0.238 0.258 0.533 0.296 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] picture : 0.156 0.274 0.337 0.591 0.333 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] pillow : 0.546 0.780 0.780 0.722 0.684 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] towel : 0.160 0.271 0.456 0.476 0.263 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] suitcase : 0.381 0.429 0.429 1.000 0.429 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] backpack : 0.293 0.544 0.583 0.667 0.615 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] crate : 0.113 0.477 0.477 0.667 0.545 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] keyboard : 0.468 0.636 0.676 0.955 0.538 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] toilet : 0.826 0.876 1.000 0.889 0.889 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] printer : 0.258 0.336 0.336 0.385 0.556 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] poster : 0.000 0.001 0.001 0.018 0.111 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.083 0.125 1.000 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] microwave : 0.560 0.750 0.985 1.000 0.750 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] shoes : 0.147 0.250 0.523 0.667 0.341 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] socket : 0.191 0.452 0.689 0.673 0.500 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] bottle : 0.093 0.184 0.312 0.370 0.325 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] bucket : 0.049 0.053 0.053 0.500 0.143 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] cushion : 0.040 0.085 0.164 0.214 0.500 [2025-04-29 14:16:47,805 INFO hook.py line 395 1619929] basket : 0.019 0.036 0.082 0.500 0.143 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] telephone : 0.202 0.407 0.471 0.727 0.471 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] laptop : 0.281 0.512 0.570 0.625 0.625 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] plant pot : 0.122 0.288 0.444 0.692 0.562 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] exhaust fan : 0.263 0.433 0.447 0.778 0.467 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] cup : 0.231 0.411 0.472 0.895 0.386 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] coat hanger : 0.153 0.500 0.533 1.000 0.500 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] light switch : 0.237 0.482 0.602 0.784 0.446 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] speaker : 0.323 0.402 0.529 0.600 0.545 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] kettle : 0.334 0.382 0.382 0.750 0.500 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] smoke detector : 0.663 0.847 0.851 0.808 0.875 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] power strip : 0.045 0.072 0.084 0.231 0.300 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] paper bag : 0.100 0.100 0.100 0.200 1.000 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] mouse : 0.485 0.666 0.667 0.875 0.656 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] cutting board : 0.049 0.062 0.062 0.500 0.250 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] toilet paper : 0.211 0.360 0.386 0.857 0.353 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] paper towel : 0.041 0.104 0.250 0.667 0.250 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] clock : 0.420 0.528 0.528 0.667 0.667 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] pan : 0.056 0.250 0.250 1.000 0.250 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] tap : 0.278 0.430 0.720 0.714 0.556 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] soap dispenser : 0.493 0.755 0.755 0.800 0.800 [2025-04-29 14:16:47,806 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] bowl : 0.037 0.042 0.042 0.250 0.333 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] whiteboard eraser: 0.188 0.451 0.451 0.800 0.667 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] toilet brush : 0.449 0.667 0.833 1.000 0.667 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] spray bottle : 0.007 0.011 0.013 0.091 0.250 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] stapler : 0.016 0.082 0.185 0.222 0.667 [2025-04-29 14:16:47,807 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 14:16:47,807 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 14:16:47,807 INFO hook.py line 404 1619929] average : 0.259 0.395 0.482 0.606 0.482 [2025-04-29 14:16:47,807 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 14:16:47,807 INFO hook.py line 480 1619929] Total Process Time: 21.598 s [2025-04-29 14:16:47,807 INFO hook.py line 481 1619929] Average Process Time: 431.726 ms [2025-04-29 14:16:47,807 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 14:16:47,851 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 14:16:47,857 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:18:25,162 INFO hook.py line 650 1619929] Train: [337/512][50/242] Data 0.016 (0.035) Batch 1.437 (1.522) Remain 17:58:54 loss: 5.1071 Lr: 1.14717e-04 Mem R(MA/MR): 23902 (21268/36162) [2025-04-29 14:19:36,152 INFO hook.py line 650 1619929] Train: [337/512][100/242] Data 0.017 (0.025) Batch 1.599 (1.469) Remain 17:20:26 loss: 5.2454 Lr: 1.14595e-04 Mem R(MA/MR): 23902 (21268/36162) [2025-04-29 14:20:48,142 INFO hook.py line 650 1619929] Train: [337/512][150/242] Data 0.017 (0.022) Batch 1.549 (1.459) Remain 17:12:09 loss: 4.9332 Lr: 1.14474e-04 Mem R(MA/MR): 23902 (21268/36162) [2025-04-29 14:21:59,889 INFO hook.py line 650 1619929] Train: [337/512][200/242] Data 0.014 (0.021) Batch 1.459 (1.453) Remain 17:06:36 loss: 4.6845 Lr: 1.14353e-04 Mem R(MA/MR): 23902 (21268/36162) [2025-04-29 14:22:57,112 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2805 loss_mask: 0.0335 loss_dice: 1.9018 loss_score: 0.0000 loss_bbox: 0.0488 loss_sp_cls: 0.7508 loss: 4.8457 [2025-04-29 14:23:00,282 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:24:38,040 INFO hook.py line 650 1619929] Train: [338/512][50/242] Data 0.018 (0.017) Batch 1.459 (1.483) Remain 17:25:12 loss: 5.3526 Lr: 1.14130e-04 Mem R(MA/MR): 20718 (21268/36162) [2025-04-29 14:25:51,231 INFO hook.py line 650 1619929] Train: [338/512][100/242] Data 0.015 (0.017) Batch 1.335 (1.473) Remain 17:17:10 loss: 3.4965 Lr: 1.14008e-04 Mem R(MA/MR): 23978 (21268/36162) [2025-04-29 14:27:02,707 INFO hook.py line 650 1619929] Train: [338/512][150/242] Data 0.018 (0.017) Batch 1.493 (1.458) Remain 17:05:33 loss: 5.3661 Lr: 1.13887e-04 Mem R(MA/MR): 25750 (21268/36162) [2025-04-29 14:28:15,432 INFO hook.py line 650 1619929] Train: [338/512][200/242] Data 0.017 (0.016) Batch 1.524 (1.457) Remain 17:03:42 loss: 4.8956 Lr: 1.13766e-04 Mem R(MA/MR): 29490 (21268/36162) [2025-04-29 14:29:14,159 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2836 loss_mask: 0.0337 loss_dice: 1.8960 loss_score: 0.0000 loss_bbox: 0.0482 loss_sp_cls: 0.7547 loss: 4.8448 [2025-04-29 14:29:14,602 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:30:47,402 INFO hook.py line 650 1619929] Train: [339/512][50/242] Data 0.015 (0.016) Batch 1.248 (1.441) Remain 16:50:16 loss: 4.4830 Lr: 1.13542e-04 Mem R(MA/MR): 22450 (21268/36162) [2025-04-29 14:31:59,450 INFO hook.py line 650 1619929] Train: [339/512][100/242] Data 0.018 (0.016) Batch 1.588 (1.441) Remain 16:48:56 loss: 5.3133 Lr: 1.13421e-04 Mem R(MA/MR): 22450 (21268/36162) [2025-04-29 14:33:10,925 INFO hook.py line 650 1619929] Train: [339/512][150/242] Data 0.017 (0.016) Batch 1.401 (1.437) Remain 16:44:59 loss: 4.2946 Lr: 1.13300e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 14:34:23,051 INFO hook.py line 650 1619929] Train: [339/512][200/242] Data 0.014 (0.017) Batch 1.245 (1.439) Remain 16:44:45 loss: 5.2021 Lr: 1.13178e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 14:35:19,863 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2820 loss_mask: 0.0337 loss_dice: 1.8872 loss_score: 0.0000 loss_bbox: 0.0487 loss_sp_cls: 0.7473 loss: 4.8265 [2025-04-29 14:35:20,497 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:36:51,713 INFO hook.py line 650 1619929] Train: [340/512][50/242] Data 0.015 (0.016) Batch 1.715 (1.419) Remain 16:28:54 loss: 4.6907 Lr: 1.12955e-04 Mem R(MA/MR): 19180 (21268/36162) [2025-04-29 14:38:04,547 INFO hook.py line 650 1619929] Train: [340/512][100/242] Data 0.018 (0.016) Batch 1.518 (1.438) Remain 16:41:16 loss: 4.5612 Lr: 1.12833e-04 Mem R(MA/MR): 20878 (21268/36162) [2025-04-29 14:39:16,990 INFO hook.py line 650 1619929] Train: [340/512][150/242] Data 0.016 (0.016) Batch 1.302 (1.442) Remain 16:42:33 loss: 5.6086 Lr: 1.12712e-04 Mem R(MA/MR): 22812 (21268/36162) [2025-04-29 14:40:27,708 INFO hook.py line 650 1619929] Train: [340/512][200/242] Data 0.015 (0.016) Batch 1.319 (1.435) Remain 16:36:29 loss: 4.7018 Lr: 1.12590e-04 Mem R(MA/MR): 22812 (21268/36162) [2025-04-29 14:41:25,109 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2813 loss_mask: 0.0336 loss_dice: 1.8848 loss_score: 0.0000 loss_bbox: 0.0487 loss_sp_cls: 0.7470 loss: 4.8157 [2025-04-29 14:41:28,215 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:43:01,050 INFO hook.py line 650 1619929] Train: [341/512][50/242] Data 0.016 (0.016) Batch 1.488 (1.486) Remain 17:09:42 loss: 4.7714 Lr: 1.12367e-04 Mem R(MA/MR): 21830 (21268/36162) [2025-04-29 14:44:15,297 INFO hook.py line 650 1619929] Train: [341/512][100/242] Data 0.016 (0.016) Batch 1.543 (1.486) Remain 17:08:03 loss: 4.4804 Lr: 1.12245e-04 Mem R(MA/MR): 24182 (21268/36162) [2025-04-29 14:45:27,572 INFO hook.py line 650 1619929] Train: [341/512][150/242] Data 0.016 (0.016) Batch 1.507 (1.472) Remain 16:57:25 loss: 5.2887 Lr: 1.12124e-04 Mem R(MA/MR): 24182 (21268/36162) [2025-04-29 14:46:38,470 INFO hook.py line 650 1619929] Train: [341/512][200/242] Data 0.015 (0.016) Batch 1.491 (1.458) Remain 16:46:45 loss: 5.7360 Lr: 1.12002e-04 Mem R(MA/MR): 24200 (21268/36162) [2025-04-29 14:47:35,259 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2844 loss_mask: 0.0335 loss_dice: 1.9004 loss_score: 0.0000 loss_bbox: 0.0492 loss_sp_cls: 0.7533 loss: 4.8580 [2025-04-29 14:47:38,152 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:49:16,431 INFO hook.py line 650 1619929] Train: [342/512][50/242] Data 0.017 (0.017) Batch 1.710 (1.524) Remain 17:29:54 loss: 5.4446 Lr: 1.11778e-04 Mem R(MA/MR): 20616 (21268/36162) [2025-04-29 14:50:28,380 INFO hook.py line 650 1619929] Train: [342/512][100/242] Data 0.016 (0.017) Batch 1.457 (1.480) Remain 16:58:26 loss: 4.3038 Lr: 1.11657e-04 Mem R(MA/MR): 20616 (21268/36162) [2025-04-29 14:51:42,167 INFO hook.py line 650 1619929] Train: [342/512][150/242] Data 0.015 (0.017) Batch 1.455 (1.479) Remain 16:56:10 loss: 5.8198 Lr: 1.11535e-04 Mem R(MA/MR): 20648 (21268/36162) [2025-04-29 14:52:55,038 INFO hook.py line 650 1619929] Train: [342/512][200/242] Data 0.014 (0.016) Batch 1.468 (1.473) Remain 16:51:13 loss: 4.6344 Lr: 1.11414e-04 Mem R(MA/MR): 22570 (21268/36162) [2025-04-29 14:53:52,187 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2840 loss_mask: 0.0344 loss_dice: 1.8975 loss_score: 0.0000 loss_bbox: 0.0493 loss_sp_cls: 0.7554 loss: 4.8562 [2025-04-29 14:53:52,991 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 14:55:25,362 INFO hook.py line 650 1619929] Train: [343/512][50/242] Data 0.016 (0.017) Batch 1.569 (1.460) Remain 16:40:08 loss: 5.4131 Lr: 1.11190e-04 Mem R(MA/MR): 18610 (21268/36162) [2025-04-29 14:56:37,920 INFO hook.py line 650 1619929] Train: [343/512][100/242] Data 0.018 (0.017) Batch 1.692 (1.456) Remain 16:35:39 loss: 5.5454 Lr: 1.11068e-04 Mem R(MA/MR): 20102 (21268/36162) [2025-04-29 14:57:49,480 INFO hook.py line 650 1619929] Train: [343/512][150/242] Data 0.015 (0.017) Batch 1.429 (1.447) Remain 16:28:45 loss: 4.7819 Lr: 1.10947e-04 Mem R(MA/MR): 21614 (21268/36162) [2025-04-29 14:59:02,296 INFO hook.py line 650 1619929] Train: [343/512][200/242] Data 0.015 (0.016) Batch 1.385 (1.450) Remain 16:29:07 loss: 4.2261 Lr: 1.10827e-04 Mem R(MA/MR): 25264 (21268/36162) [2025-04-29 14:59:59,839 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2854 loss_mask: 0.0346 loss_dice: 1.9113 loss_score: 0.0000 loss_bbox: 0.0495 loss_sp_cls: 0.7518 loss: 4.8794 [2025-04-29 15:00:02,547 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:01:32,336 INFO hook.py line 650 1619929] Train: [344/512][50/242] Data 0.016 (0.016) Batch 1.467 (1.433) Remain 16:15:22 loss: 4.9438 Lr: 1.10603e-04 Mem R(MA/MR): 20992 (21268/36162) [2025-04-29 15:02:43,574 INFO hook.py line 650 1619929] Train: [344/512][100/242] Data 0.018 (0.016) Batch 1.377 (1.429) Remain 16:11:24 loss: 4.4103 Lr: 1.10482e-04 Mem R(MA/MR): 22958 (21268/36162) [2025-04-29 15:03:55,163 INFO hook.py line 650 1619929] Train: [344/512][150/242] Data 0.015 (0.016) Batch 1.519 (1.430) Remain 16:10:57 loss: 4.3314 Lr: 1.10360e-04 Mem R(MA/MR): 22958 (21268/36162) [2025-04-29 15:05:07,577 INFO hook.py line 650 1619929] Train: [344/512][200/242] Data 0.014 (0.016) Batch 1.460 (1.434) Remain 16:12:57 loss: 4.7519 Lr: 1.10238e-04 Mem R(MA/MR): 25558 (21268/36162) [2025-04-29 15:06:05,727 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3073 loss_mask: 0.0378 loss_dice: 1.9635 loss_score: 0.0000 loss_bbox: 0.0493 loss_sp_cls: 0.7791 loss: 5.0434 [2025-04-29 15:06:06,484 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 15:06:08,922 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5977 Process Time: 0.367 Mem R(MA/MR): 3774 (21268/36162) [2025-04-29 15:06:10,543 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6593 Process Time: 0.464 Mem R(MA/MR): 6714 (21268/36162) [2025-04-29 15:06:12,462 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.8675 Process Time: 0.801 Mem R(MA/MR): 8950 (21268/36162) [2025-04-29 15:06:20,578 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.9859 Process Time: 1.275 Mem R(MA/MR): 19316 (21268/36162) [2025-04-29 15:06:21,788 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.8631 Process Time: 0.400 Mem R(MA/MR): 6508 (21268/36162) [2025-04-29 15:06:23,339 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4003 Process Time: 0.341 Mem R(MA/MR): 11050 (21268/36162) [2025-04-29 15:06:23,960 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.5992 Process Time: 0.198 Mem R(MA/MR): 5940 (21268/36162) [2025-04-29 15:06:24,487 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.6357 Process Time: 0.181 Mem R(MA/MR): 4192 (21268/36162) [2025-04-29 15:06:25,455 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.1527 Process Time: 0.265 Mem R(MA/MR): 11096 (21268/36162) [2025-04-29 15:06:27,168 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7144 Process Time: 0.303 Mem R(MA/MR): 8854 (21268/36162) [2025-04-29 15:06:30,042 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.1552 Process Time: 0.521 Mem R(MA/MR): 18316 (21268/36162) [2025-04-29 15:06:32,401 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.7121 Process Time: 0.420 Mem R(MA/MR): 14896 (21268/36162) [2025-04-29 15:06:33,652 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.6020 Process Time: 0.264 Mem R(MA/MR): 8050 (21268/36162) [2025-04-29 15:06:34,006 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.4452 Process Time: 0.157 Mem R(MA/MR): 4404 (21268/36162) [2025-04-29 15:06:36,698 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.7536 Process Time: 0.385 Mem R(MA/MR): 16266 (21268/36162) [2025-04-29 15:06:38,329 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.1078 Process Time: 0.375 Mem R(MA/MR): 14120 (21268/36162) [2025-04-29 15:06:39,372 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.4025 Process Time: 0.411 Mem R(MA/MR): 6246 (21268/36162) [2025-04-29 15:06:40,183 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0446 Process Time: 0.233 Mem R(MA/MR): 7518 (21268/36162) [2025-04-29 15:06:41,767 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5069 Process Time: 0.367 Mem R(MA/MR): 5820 (21268/36162) [2025-04-29 15:06:43,141 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.1913 Process Time: 0.219 Mem R(MA/MR): 11394 (21268/36162) [2025-04-29 15:06:51,932 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.3581 Process Time: 0.849 Mem R(MA/MR): 23542 (21268/36162) [2025-04-29 15:06:52,589 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.0405 Process Time: 0.271 Mem R(MA/MR): 6392 (21268/36162) [2025-04-29 15:07:03,150 INFO hook.py line 449 1619929] Test: [23/50] Loss 15.3473 Process Time: 0.423 Mem R(MA/MR): 9580 (21268/36162) [2025-04-29 15:07:04,173 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7423 Process Time: 0.466 Mem R(MA/MR): 5036 (21268/36162) [2025-04-29 15:07:05,146 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0735 Process Time: 0.305 Mem R(MA/MR): 8472 (21268/36162) [2025-04-29 15:07:12,675 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.3006 Process Time: 2.057 Mem R(MA/MR): 31642 (21268/36162) [2025-04-29 15:07:15,071 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.9516 Process Time: 0.537 Mem R(MA/MR): 9866 (21268/36162) [2025-04-29 15:07:16,126 INFO hook.py line 449 1619929] Test: [28/50] Loss 7.0245 Process Time: 0.203 Mem R(MA/MR): 8190 (21268/36162) [2025-04-29 15:07:20,587 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0775 Process Time: 0.289 Mem R(MA/MR): 16560 (21268/36162) [2025-04-29 15:07:22,075 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.8139 Process Time: 0.584 Mem R(MA/MR): 7134 (21268/36162) [2025-04-29 15:07:25,492 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5217 Process Time: 0.520 Mem R(MA/MR): 20034 (21268/36162) [2025-04-29 15:07:25,747 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.0115 Process Time: 0.108 Mem R(MA/MR): 3508 (21268/36162) [2025-04-29 15:07:29,744 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.9473 Process Time: 0.378 Mem R(MA/MR): 24108 (21268/36162) [2025-04-29 15:07:31,530 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7503 Process Time: 0.720 Mem R(MA/MR): 9500 (21268/36162) [2025-04-29 15:07:33,584 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0047 Process Time: 0.358 Mem R(MA/MR): 13790 (21268/36162) [2025-04-29 15:07:34,121 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2323 Process Time: 0.169 Mem R(MA/MR): 6120 (21268/36162) [2025-04-29 15:07:37,745 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.2168 Process Time: 0.449 Mem R(MA/MR): 28250 (21268/36162) [2025-04-29 15:07:40,066 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8937 Process Time: 0.752 Mem R(MA/MR): 10540 (21268/36162) [2025-04-29 15:07:40,571 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.7766 Process Time: 0.182 Mem R(MA/MR): 5126 (21268/36162) [2025-04-29 15:07:41,843 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.0674 Process Time: 0.393 Mem R(MA/MR): 9850 (21268/36162) [2025-04-29 15:07:42,743 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.3317 Process Time: 0.213 Mem R(MA/MR): 8064 (21268/36162) [2025-04-29 15:07:43,268 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2697 Process Time: 0.161 Mem R(MA/MR): 5152 (21268/36162) [2025-04-29 15:07:43,690 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.1025 Process Time: 0.134 Mem R(MA/MR): 5194 (21268/36162) [2025-04-29 15:07:44,362 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.6571 Process Time: 0.198 Mem R(MA/MR): 6624 (21268/36162) [2025-04-29 15:07:45,036 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.2768 Process Time: 0.135 Mem R(MA/MR): 4964 (21268/36162) [2025-04-29 15:07:47,203 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.9545 Process Time: 0.255 Mem R(MA/MR): 14086 (21268/36162) [2025-04-29 15:07:54,326 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.2392 Process Time: 0.990 Mem R(MA/MR): 19558 (21268/36162) [2025-04-29 15:08:04,104 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.5157 Process Time: 1.391 Mem R(MA/MR): 35608 (21268/36162) [2025-04-29 15:08:05,259 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0607 Process Time: 0.486 Mem R(MA/MR): 5264 (21268/36162) [2025-04-29 15:08:08,300 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1685 Process Time: 1.100 Mem R(MA/MR): 13428 (21268/36162) [2025-04-29 15:08:12,271 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 15:08:12,272 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 15:08:12,272 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] table : 0.258 0.553 0.760 0.767 0.581 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] door : 0.436 0.756 0.896 0.921 0.734 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] ceiling lamp : 0.588 0.809 0.872 0.875 0.773 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] cabinet : 0.357 0.471 0.529 0.627 0.478 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] blinds : 0.582 0.837 0.872 0.826 0.826 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] curtain : 0.342 0.464 0.711 0.500 0.750 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] chair : 0.646 0.764 0.807 0.740 0.770 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] storage cabinet: 0.209 0.368 0.534 0.542 0.520 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] office chair : 0.576 0.619 0.636 0.700 0.729 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] bookshelf : 0.191 0.532 0.566 0.800 0.727 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] whiteboard : 0.542 0.695 0.766 0.917 0.629 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] window : 0.128 0.278 0.639 0.577 0.330 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] box : 0.200 0.349 0.535 0.478 0.475 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] monitor : 0.592 0.736 0.813 0.898 0.757 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] shelf : 0.130 0.289 0.550 0.588 0.333 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] heater : 0.438 0.611 0.808 0.812 0.684 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] kitchen cabinet: 0.169 0.342 0.698 0.474 0.360 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] sofa : 0.478 0.621 0.821 0.667 0.667 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] bed : 0.047 0.094 0.626 0.273 0.375 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] trash can : 0.570 0.719 0.773 0.810 0.785 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] book : 0.020 0.034 0.086 0.307 0.086 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] plant : 0.408 0.550 0.611 0.909 0.556 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] blanket : 0.553 0.700 0.737 0.727 0.727 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] tv : 0.940 1.000 1.000 1.000 1.000 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] computer tower : 0.277 0.405 0.677 0.833 0.357 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] refrigerator : 0.246 0.560 0.561 0.833 0.556 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] jacket : 0.092 0.235 0.368 0.500 0.364 [2025-04-29 15:08:12,272 INFO hook.py line 395 1619929] sink : 0.467 0.759 0.920 1.000 0.727 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] bag : 0.036 0.069 0.116 0.269 0.259 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] picture : 0.147 0.335 0.394 0.593 0.410 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] pillow : 0.655 0.865 0.863 0.850 0.895 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] towel : 0.158 0.233 0.530 0.429 0.316 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] suitcase : 0.397 0.453 0.453 0.750 0.429 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] backpack : 0.427 0.528 0.528 0.875 0.538 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] crate : 0.034 0.198 0.428 0.667 0.364 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] keyboard : 0.483 0.676 0.741 0.806 0.641 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] toilet : 0.771 0.876 1.000 0.889 0.889 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] printer : 0.386 0.556 0.556 1.000 0.556 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] poster : 0.000 0.001 0.001 0.022 0.111 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] microwave : 0.457 0.750 0.875 1.000 0.750 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] shoes : 0.144 0.248 0.531 0.545 0.439 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] socket : 0.182 0.416 0.655 0.756 0.421 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] bottle : 0.112 0.186 0.315 0.449 0.265 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] bucket : 0.083 0.083 0.135 0.200 0.714 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] cushion : 0.054 0.085 0.154 0.182 0.667 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] telephone : 0.260 0.532 0.595 1.000 0.471 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] laptop : 0.343 0.545 0.646 1.000 0.500 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] plant pot : 0.211 0.378 0.441 0.533 0.500 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] exhaust fan : 0.056 0.153 0.200 0.750 0.200 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] cup : 0.198 0.313 0.354 0.737 0.318 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] coat hanger : 0.260 0.613 0.677 1.000 0.500 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] light switch : 0.267 0.547 0.652 0.850 0.523 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] speaker : 0.098 0.233 0.373 0.545 0.545 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] table lamp : 0.502 1.000 1.000 1.000 1.000 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] kettle : 0.352 0.500 0.500 1.000 0.500 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] smoke detector : 0.634 0.841 0.845 1.000 0.708 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,273 INFO hook.py line 395 1619929] power strip : 0.081 0.147 0.207 0.600 0.300 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] paper bag : 0.058 0.062 0.062 0.125 1.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] mouse : 0.466 0.698 0.792 0.759 0.688 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] cutting board : 0.125 0.208 0.208 0.667 0.500 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] toilet paper : 0.256 0.403 0.453 0.857 0.353 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] paper towel : 0.010 0.016 0.150 0.091 0.250 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] clock : 0.420 0.528 0.528 0.667 0.667 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] tap : 0.114 0.157 0.432 0.500 0.222 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] soap dispenser : 0.538 0.682 0.707 1.000 0.600 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] bowl : 0.087 0.159 0.278 0.286 0.667 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] whiteboard eraser: 0.267 0.626 0.626 0.714 0.833 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] toilet brush : 0.405 0.629 0.803 0.800 0.667 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] spray bottle : 0.009 0.014 0.018 0.111 0.250 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] stapler : 0.008 0.053 0.190 0.143 0.667 [2025-04-29 15:08:12,274 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 15:08:12,274 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 15:08:12,274 INFO hook.py line 404 1619929] average : 0.260 0.393 0.484 0.584 0.479 [2025-04-29 15:08:12,274 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 15:08:12,275 INFO hook.py line 480 1619929] Total Process Time: 23.023 s [2025-04-29 15:08:12,275 INFO hook.py line 481 1619929] Average Process Time: 462.363 ms [2025-04-29 15:08:12,275 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 15:08:12,310 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 15:08:12,315 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:09:46,441 INFO hook.py line 650 1619929] Train: [345/512][50/242] Data 0.019 (0.017) Batch 1.566 (1.474) Remain 16:37:13 loss: 5.6055 Lr: 1.10014e-04 Mem R(MA/MR): 22106 (21268/36162) [2025-04-29 15:10:58,923 INFO hook.py line 650 1619929] Train: [345/512][100/242] Data 0.016 (0.016) Batch 1.245 (1.461) Remain 16:27:41 loss: 4.9056 Lr: 1.09892e-04 Mem R(MA/MR): 23880 (21268/36162) [2025-04-29 15:12:09,537 INFO hook.py line 650 1619929] Train: [345/512][150/242] Data 0.016 (0.016) Batch 1.457 (1.445) Remain 16:15:13 loss: 4.5352 Lr: 1.09770e-04 Mem R(MA/MR): 23880 (21268/36162) [2025-04-29 15:13:22,326 INFO hook.py line 650 1619929] Train: [345/512][200/242] Data 0.014 (0.021) Batch 1.350 (1.447) Remain 16:15:56 loss: 4.9892 Lr: 1.09648e-04 Mem R(MA/MR): 25718 (21268/36162) [2025-04-29 15:14:18,504 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3094 loss_mask: 0.0360 loss_dice: 1.9743 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.7810 loss: 5.0608 [2025-04-29 15:14:18,655 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:15:54,652 INFO hook.py line 650 1619929] Train: [346/512][50/242] Data 0.017 (0.017) Batch 1.335 (1.522) Remain 17:04:03 loss: 4.1119 Lr: 1.09424e-04 Mem R(MA/MR): 20082 (21268/36162) [2025-04-29 15:17:06,065 INFO hook.py line 650 1619929] Train: [346/512][100/242] Data 0.017 (0.017) Batch 1.557 (1.474) Remain 16:30:13 loss: 4.4459 Lr: 1.09302e-04 Mem R(MA/MR): 21800 (21268/36162) [2025-04-29 15:18:21,271 INFO hook.py line 650 1619929] Train: [346/512][150/242] Data 0.018 (0.017) Batch 1.444 (1.484) Remain 16:35:55 loss: 4.0468 Lr: 1.09180e-04 Mem R(MA/MR): 21800 (21268/36162) [2025-04-29 15:19:33,035 INFO hook.py line 650 1619929] Train: [346/512][200/242] Data 0.015 (0.017) Batch 1.414 (1.472) Remain 16:26:23 loss: 6.3654 Lr: 1.09059e-04 Mem R(MA/MR): 23628 (21268/36162) [2025-04-29 15:20:30,330 INFO misc.py line 135 1619929] Train result: loss_cls: 0.3059 loss_mask: 0.0363 loss_dice: 1.9659 loss_score: 0.0000 loss_bbox: 0.0501 loss_sp_cls: 0.7748 loss: 5.0372 [2025-04-29 15:20:30,909 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:22:06,249 INFO hook.py line 650 1619929] Train: [347/512][50/242] Data 0.016 (0.016) Batch 1.338 (1.459) Remain 16:15:50 loss: 4.7387 Lr: 1.08834e-04 Mem R(MA/MR): 21088 (21268/36162) [2025-04-29 15:23:19,051 INFO hook.py line 650 1619929] Train: [347/512][100/242] Data 0.018 (0.016) Batch 1.502 (1.458) Remain 16:13:30 loss: 5.3749 Lr: 1.08712e-04 Mem R(MA/MR): 21094 (21268/36162) [2025-04-29 15:24:30,399 INFO hook.py line 650 1619929] Train: [347/512][150/242] Data 0.015 (0.017) Batch 1.507 (1.447) Remain 16:05:19 loss: 4.3622 Lr: 1.08590e-04 Mem R(MA/MR): 24800 (21268/36162) [2025-04-29 15:25:43,295 INFO hook.py line 650 1619929] Train: [347/512][200/242] Data 0.015 (0.017) Batch 1.418 (1.450) Remain 16:05:56 loss: 4.7666 Lr: 1.08468e-04 Mem R(MA/MR): 26866 (21268/36162) [2025-04-29 15:26:40,137 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2991 loss_mask: 0.0360 loss_dice: 1.9512 loss_score: 0.0000 loss_bbox: 0.0499 loss_sp_cls: 0.7703 loss: 4.9933 [2025-04-29 15:26:42,691 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:28:20,895 INFO hook.py line 650 1619929] Train: [348/512][50/242] Data 0.015 (0.017) Batch 1.425 (1.487) Remain 16:28:33 loss: 3.9580 Lr: 1.08244e-04 Mem R(MA/MR): 25220 (21268/36162) [2025-04-29 15:29:31,742 INFO hook.py line 650 1619929] Train: [348/512][100/242] Data 0.016 (0.017) Batch 1.371 (1.451) Remain 16:03:14 loss: 4.4804 Lr: 1.08122e-04 Mem R(MA/MR): 25242 (21268/36162) [2025-04-29 15:30:43,826 INFO hook.py line 650 1619929] Train: [348/512][150/242] Data 0.017 (0.016) Batch 1.410 (1.448) Remain 15:59:55 loss: 4.8471 Lr: 1.08000e-04 Mem R(MA/MR): 25242 (21268/36162) [2025-04-29 15:31:58,436 INFO hook.py line 650 1619929] Train: [348/512][200/242] Data 0.015 (0.016) Batch 1.319 (1.459) Remain 16:06:10 loss: 3.1942 Lr: 1.07878e-04 Mem R(MA/MR): 27342 (21268/36162) [2025-04-29 15:32:57,373 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2934 loss_mask: 0.0354 loss_dice: 1.9347 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7637 loss: 4.9441 [2025-04-29 15:33:01,427 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:34:35,309 INFO hook.py line 650 1619929] Train: [349/512][50/242] Data 0.016 (0.017) Batch 1.332 (1.422) Remain 15:39:11 loss: 5.3495 Lr: 1.07653e-04 Mem R(MA/MR): 21050 (21268/36162) [2025-04-29 15:35:48,983 INFO hook.py line 650 1619929] Train: [349/512][100/242] Data 0.016 (0.016) Batch 1.420 (1.448) Remain 15:55:37 loss: 5.5847 Lr: 1.07531e-04 Mem R(MA/MR): 24396 (21268/36162) [2025-04-29 15:37:01,891 INFO hook.py line 650 1619929] Train: [349/512][150/242] Data 0.017 (0.016) Batch 1.243 (1.452) Remain 15:56:35 loss: 4.0523 Lr: 1.07409e-04 Mem R(MA/MR): 24412 (21268/36162) [2025-04-29 15:38:15,425 INFO hook.py line 650 1619929] Train: [349/512][200/242] Data 0.015 (0.017) Batch 1.420 (1.457) Remain 15:58:34 loss: 5.6952 Lr: 1.07287e-04 Mem R(MA/MR): 24412 (21268/36162) [2025-04-29 15:39:11,886 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2944 loss_mask: 0.0345 loss_dice: 1.9242 loss_score: 0.0000 loss_bbox: 0.0494 loss_sp_cls: 0.7604 loss: 4.9277 [2025-04-29 15:39:12,211 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:40:40,971 INFO hook.py line 650 1619929] Train: [350/512][50/242] Data 0.017 (0.017) Batch 1.567 (1.512) Remain 16:32:33 loss: 4.2332 Lr: 1.07062e-04 Mem R(MA/MR): 21464 (21268/36162) [2025-04-29 15:41:53,483 INFO hook.py line 650 1619929] Train: [350/512][100/242] Data 0.017 (0.017) Batch 1.502 (1.480) Remain 16:10:33 loss: 5.2932 Lr: 1.06940e-04 Mem R(MA/MR): 27030 (21268/36162) [2025-04-29 15:43:08,310 INFO hook.py line 650 1619929] Train: [350/512][150/242] Data 0.016 (0.017) Batch 1.452 (1.486) Remain 16:13:00 loss: 4.6576 Lr: 1.06818e-04 Mem R(MA/MR): 27030 (21268/36162) [2025-04-29 15:44:20,162 INFO hook.py line 650 1619929] Train: [350/512][200/242] Data 0.015 (0.017) Batch 1.374 (1.473) Remain 16:03:41 loss: 4.6829 Lr: 1.06695e-04 Mem R(MA/MR): 27042 (21268/36162) [2025-04-29 15:45:18,662 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2953 loss_mask: 0.0355 loss_dice: 1.9419 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7635 loss: 4.9616 [2025-04-29 15:45:22,331 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:47:00,188 INFO hook.py line 650 1619929] Train: [351/512][50/242] Data 0.017 (0.016) Batch 1.510 (1.460) Remain 15:52:26 loss: 5.3215 Lr: 1.06470e-04 Mem R(MA/MR): 19508 (21268/36162) [2025-04-29 15:48:13,373 INFO hook.py line 650 1619929] Train: [351/512][100/242] Data 0.016 (0.016) Batch 1.358 (1.462) Remain 15:52:38 loss: 5.2413 Lr: 1.06348e-04 Mem R(MA/MR): 22552 (21268/36162) [2025-04-29 15:49:26,073 INFO hook.py line 650 1619929] Train: [351/512][150/242] Data 0.025 (0.017) Batch 1.645 (1.459) Remain 15:49:40 loss: 5.1291 Lr: 1.06226e-04 Mem R(MA/MR): 24108 (21268/36162) [2025-04-29 15:50:38,676 INFO hook.py line 650 1619929] Train: [351/512][200/242] Data 0.016 (0.017) Batch 1.302 (1.457) Remain 15:47:20 loss: 3.9724 Lr: 1.06104e-04 Mem R(MA/MR): 25726 (21268/36162) [2025-04-29 15:51:36,541 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2927 loss_mask: 0.0346 loss_dice: 1.9417 loss_score: 0.0000 loss_bbox: 0.0500 loss_sp_cls: 0.7669 loss: 4.9610 [2025-04-29 15:51:40,840 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 15:53:17,435 INFO hook.py line 650 1619929] Train: [352/512][50/242] Data 0.017 (0.016) Batch 1.476 (1.488) Remain 16:04:41 loss: 4.7567 Lr: 1.05879e-04 Mem R(MA/MR): 23270 (21268/36162) [2025-04-29 15:54:31,790 INFO hook.py line 650 1619929] Train: [352/512][100/242] Data 0.017 (0.016) Batch 1.400 (1.487) Remain 16:03:18 loss: 5.7758 Lr: 1.05756e-04 Mem R(MA/MR): 26594 (21268/36162) [2025-04-29 15:55:43,057 INFO hook.py line 650 1619929] Train: [352/512][150/242] Data 0.017 (0.016) Batch 1.370 (1.466) Remain 15:48:26 loss: 5.7179 Lr: 1.05634e-04 Mem R(MA/MR): 26600 (21268/36162) [2025-04-29 15:56:55,622 INFO hook.py line 650 1619929] Train: [352/512][200/242] Data 0.015 (0.016) Batch 1.406 (1.462) Remain 15:44:46 loss: 4.6764 Lr: 1.05512e-04 Mem R(MA/MR): 28940 (21268/36162) [2025-04-29 15:57:54,126 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2783 loss_mask: 0.0338 loss_dice: 1.8912 loss_score: 0.0000 loss_bbox: 0.0492 loss_sp_cls: 0.7512 loss: 4.8276 [2025-04-29 15:57:55,261 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 15:57:57,625 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.4190 Process Time: 0.365 Mem R(MA/MR): 4462 (21268/36162) [2025-04-29 15:57:59,067 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.5755 Process Time: 0.409 Mem R(MA/MR): 7246 (21268/36162) [2025-04-29 15:58:00,992 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.8416 Process Time: 0.858 Mem R(MA/MR): 9668 (21268/36162) [2025-04-29 15:58:08,277 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.1402 Process Time: 1.363 Mem R(MA/MR): 19524 (21268/36162) [2025-04-29 15:58:09,303 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.2168 Process Time: 0.379 Mem R(MA/MR): 7052 (21268/36162) [2025-04-29 15:58:11,048 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8635 Process Time: 0.713 Mem R(MA/MR): 11280 (21268/36162) [2025-04-29 15:58:11,775 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2407 Process Time: 0.288 Mem R(MA/MR): 6450 (21268/36162) [2025-04-29 15:58:12,258 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.0014 Process Time: 0.154 Mem R(MA/MR): 4480 (21268/36162) [2025-04-29 15:58:13,195 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7696 Process Time: 0.346 Mem R(MA/MR): 11384 (21268/36162) [2025-04-29 15:58:14,611 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7051 Process Time: 0.215 Mem R(MA/MR): 9438 (21268/36162) [2025-04-29 15:58:17,538 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.1669 Process Time: 0.622 Mem R(MA/MR): 18788 (21268/36162) [2025-04-29 15:58:20,051 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1559 Process Time: 0.624 Mem R(MA/MR): 15194 (21268/36162) [2025-04-29 15:58:21,321 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.3522 Process Time: 0.322 Mem R(MA/MR): 8686 (21268/36162) [2025-04-29 15:58:21,920 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2923 Process Time: 0.238 Mem R(MA/MR): 4788 (21268/36162) [2025-04-29 15:58:25,143 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.7284 Process Time: 0.352 Mem R(MA/MR): 16694 (21268/36162) [2025-04-29 15:58:27,431 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4743 Process Time: 0.761 Mem R(MA/MR): 14670 (21268/36162) [2025-04-29 15:58:28,535 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.4974 Process Time: 0.367 Mem R(MA/MR): 6758 (21268/36162) [2025-04-29 15:58:29,403 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6551 Process Time: 0.283 Mem R(MA/MR): 8168 (21268/36162) [2025-04-29 15:58:30,751 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9201 Process Time: 0.189 Mem R(MA/MR): 6150 (21268/36162) [2025-04-29 15:58:32,206 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.2628 Process Time: 0.246 Mem R(MA/MR): 11514 (21268/36162) [2025-04-29 15:58:39,641 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.2967 Process Time: 0.612 Mem R(MA/MR): 23818 (21268/36162) [2025-04-29 15:58:40,167 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.6250 Process Time: 0.158 Mem R(MA/MR): 6974 (21268/36162) [2025-04-29 15:58:49,792 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.0383 Process Time: 0.321 Mem R(MA/MR): 10174 (21268/36162) [2025-04-29 15:58:50,429 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.1182 Process Time: 0.208 Mem R(MA/MR): 5428 (21268/36162) [2025-04-29 15:58:51,413 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9297 Process Time: 0.237 Mem R(MA/MR): 9196 (21268/36162) [2025-04-29 15:58:58,898 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.4677 Process Time: 1.674 Mem R(MA/MR): 30652 (21268/36162) [2025-04-29 15:59:01,477 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.6250 Process Time: 0.386 Mem R(MA/MR): 10076 (21268/36162) [2025-04-29 15:59:02,973 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.2049 Process Time: 0.412 Mem R(MA/MR): 8890 (21268/36162) [2025-04-29 15:59:08,679 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.5003 Process Time: 0.539 Mem R(MA/MR): 17098 (21268/36162) [2025-04-29 15:59:09,799 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1884 Process Time: 0.360 Mem R(MA/MR): 7988 (21268/36162) [2025-04-29 15:59:14,120 INFO hook.py line 449 1619929] Test: [31/50] Loss 6.9878 Process Time: 0.766 Mem R(MA/MR): 20460 (21268/36162) [2025-04-29 15:59:14,516 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.9205 Process Time: 0.151 Mem R(MA/MR): 4256 (21268/36162) [2025-04-29 15:59:18,322 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.4593 Process Time: 0.437 Mem R(MA/MR): 25060 (21268/36162) [2025-04-29 15:59:19,780 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8127 Process Time: 0.357 Mem R(MA/MR): 9756 (21268/36162) [2025-04-29 15:59:22,225 INFO hook.py line 449 1619929] Test: [35/50] Loss 6.8449 Process Time: 0.840 Mem R(MA/MR): 14176 (21268/36162) [2025-04-29 15:59:22,677 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.6730 Process Time: 0.160 Mem R(MA/MR): 6650 (21268/36162) [2025-04-29 15:59:25,901 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.7189 Process Time: 0.402 Mem R(MA/MR): 28878 (21268/36162) [2025-04-29 15:59:27,973 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.7433 Process Time: 0.641 Mem R(MA/MR): 10716 (21268/36162) [2025-04-29 15:59:28,821 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0331 Process Time: 0.322 Mem R(MA/MR): 5580 (21268/36162) [2025-04-29 15:59:30,013 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5847 Process Time: 0.411 Mem R(MA/MR): 10156 (21268/36162) [2025-04-29 15:59:31,039 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0460 Process Time: 0.280 Mem R(MA/MR): 8956 (21268/36162) [2025-04-29 15:59:31,746 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.0264 Process Time: 0.153 Mem R(MA/MR): 5554 (21268/36162) [2025-04-29 15:59:32,111 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8386 Process Time: 0.119 Mem R(MA/MR): 5602 (21268/36162) [2025-04-29 15:59:32,682 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3882 Process Time: 0.166 Mem R(MA/MR): 7170 (21268/36162) [2025-04-29 15:59:33,364 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.8336 Process Time: 0.231 Mem R(MA/MR): 5324 (21268/36162) [2025-04-29 15:59:35,387 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.1592 Process Time: 0.285 Mem R(MA/MR): 14822 (21268/36162) [2025-04-29 15:59:43,745 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.2456 Process Time: 1.362 Mem R(MA/MR): 20406 (21268/36162) [2025-04-29 15:59:55,486 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.7966 Process Time: 2.475 Mem R(MA/MR): 35684 (21268/36162) [2025-04-29 15:59:56,523 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.7920 Process Time: 0.331 Mem R(MA/MR): 5860 (21268/36162) [2025-04-29 15:59:58,764 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0592 Process Time: 0.373 Mem R(MA/MR): 13852 (21268/36162) [2025-04-29 16:00:03,436 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 16:00:03,436 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 16:00:03,436 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] table : 0.277 0.588 0.777 0.821 0.574 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] door : 0.439 0.727 0.888 0.922 0.747 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] ceiling lamp : 0.575 0.790 0.875 0.839 0.779 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] cabinet : 0.346 0.492 0.540 0.673 0.493 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] blinds : 0.635 0.857 0.857 0.870 0.870 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] curtain : 0.351 0.692 0.687 0.875 0.583 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] chair : 0.709 0.833 0.865 0.846 0.791 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] storage cabinet: 0.247 0.378 0.489 0.733 0.440 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] office chair : 0.537 0.568 0.583 0.667 0.750 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] bookshelf : 0.249 0.554 0.682 0.727 0.727 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] whiteboard : 0.553 0.758 0.773 0.931 0.771 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] window : 0.116 0.306 0.669 0.466 0.374 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] box : 0.201 0.393 0.529 0.620 0.414 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] monitor : 0.638 0.763 0.825 0.981 0.729 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] shelf : 0.127 0.279 0.557 0.364 0.400 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] heater : 0.428 0.634 0.745 0.897 0.684 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] kitchen cabinet: 0.135 0.301 0.681 0.271 0.640 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] sofa : 0.484 0.516 0.813 0.875 0.583 [2025-04-29 16:00:03,436 INFO hook.py line 395 1619929] bed : 0.121 0.239 0.869 0.500 0.500 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] trash can : 0.521 0.650 0.709 0.773 0.785 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] book : 0.018 0.028 0.075 0.190 0.082 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] plant : 0.409 0.562 0.715 0.917 0.611 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] blanket : 0.527 0.685 0.764 1.000 0.545 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] tv : 0.912 1.000 1.000 1.000 1.000 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] computer tower : 0.239 0.369 0.559 0.581 0.429 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] refrigerator : 0.256 0.416 0.461 1.000 0.333 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] jacket : 0.061 0.287 0.425 0.625 0.455 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] sink : 0.447 0.768 0.852 0.895 0.773 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] bag : 0.081 0.164 0.202 0.667 0.222 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] picture : 0.097 0.253 0.339 0.611 0.282 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] pillow : 0.593 0.850 0.861 0.882 0.789 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] towel : 0.203 0.304 0.505 0.438 0.368 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] suitcase : 0.332 0.385 0.399 0.400 0.571 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] backpack : 0.334 0.571 0.571 0.875 0.538 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] crate : 0.052 0.194 0.480 0.417 0.455 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] keyboard : 0.519 0.686 0.770 0.871 0.692 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] toilet : 0.829 0.876 1.000 0.889 0.889 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] printer : 0.405 0.463 0.472 0.800 0.444 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.002 0.037 0.111 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] painting : 0.033 0.033 0.045 0.067 1.000 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] microwave : 0.603 0.839 0.875 0.875 0.875 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] shoes : 0.119 0.230 0.507 0.500 0.415 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] socket : 0.194 0.466 0.692 0.742 0.493 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] bottle : 0.139 0.214 0.312 0.439 0.301 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] bucket : 0.193 0.309 0.309 1.000 0.286 [2025-04-29 16:00:03,437 INFO hook.py line 395 1619929] cushion : 0.134 0.195 0.219 0.333 0.500 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] basket : 0.003 0.009 0.012 0.125 0.143 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] shoe rack : 0.014 0.125 0.500 0.500 0.500 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] telephone : 0.222 0.430 0.563 0.800 0.471 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] laptop : 0.328 0.581 0.677 0.800 0.500 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] plant pot : 0.272 0.513 0.545 0.818 0.562 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] exhaust fan : 0.122 0.258 0.258 0.714 0.333 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] cup : 0.196 0.327 0.420 0.812 0.295 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] coat hanger : 0.347 0.750 0.750 1.000 0.750 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] light switch : 0.291 0.580 0.715 0.678 0.615 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] speaker : 0.206 0.212 0.352 0.500 0.364 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] kettle : 0.259 0.333 0.333 1.000 0.333 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] smoke detector : 0.639 0.816 0.817 0.950 0.792 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] power strip : 0.047 0.062 0.069 0.333 0.200 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] paper bag : 0.167 0.167 0.167 0.333 1.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] mouse : 0.515 0.742 0.743 0.958 0.719 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] toilet paper : 0.262 0.471 0.542 1.000 0.471 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] paper towel : 0.125 0.125 0.125 1.000 0.125 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] clock : 0.548 0.656 0.764 0.600 1.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] tap : 0.130 0.194 0.335 0.667 0.222 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] soap dispenser : 0.531 0.800 0.878 1.000 0.800 [2025-04-29 16:00:03,438 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] bowl : 0.081 0.278 0.278 0.667 0.667 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] whiteboard eraser: 0.200 0.446 0.478 0.625 0.833 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] toilet brush : 0.507 0.707 0.883 1.000 0.667 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] spray bottle : 0.006 0.018 0.018 0.143 0.250 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,439 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:00:03,439 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 16:00:03,439 INFO hook.py line 404 1619929] average : 0.273 0.406 0.494 0.631 0.487 [2025-04-29 16:00:03,439 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 16:00:03,439 INFO hook.py line 480 1619929] Total Process Time: 24.265 s [2025-04-29 16:00:03,439 INFO hook.py line 481 1619929] Average Process Time: 487.759 ms [2025-04-29 16:00:03,439 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 16:00:03,478 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 16:00:03,483 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:01:36,063 INFO hook.py line 650 1619929] Train: [353/512][50/242] Data 0.018 (0.016) Batch 1.351 (1.461) Remain 15:41:51 loss: 4.5371 Lr: 1.05286e-04 Mem R(MA/MR): 21904 (21268/36162) [2025-04-29 16:02:46,965 INFO hook.py line 650 1619929] Train: [353/512][100/242] Data 0.017 (0.016) Batch 1.408 (1.439) Remain 15:26:15 loss: 4.1318 Lr: 1.05164e-04 Mem R(MA/MR): 21904 (21268/36162) [2025-04-29 16:03:58,802 INFO hook.py line 650 1619929] Train: [353/512][150/242] Data 0.017 (0.022) Batch 1.391 (1.438) Remain 15:24:33 loss: 4.3161 Lr: 1.05042e-04 Mem R(MA/MR): 23974 (21268/36162) [2025-04-29 16:05:10,622 INFO hook.py line 650 1619929] Train: [353/512][200/242] Data 0.015 (0.021) Batch 1.300 (1.438) Remain 15:23:03 loss: 4.5701 Lr: 1.04919e-04 Mem R(MA/MR): 23986 (21268/36162) [2025-04-29 16:06:06,918 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2751 loss_mask: 0.0336 loss_dice: 1.8776 loss_score: 0.0000 loss_bbox: 0.0481 loss_sp_cls: 0.7429 loss: 4.7868 [2025-04-29 16:06:07,086 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:07:42,172 INFO hook.py line 650 1619929] Train: [354/512][50/242] Data 0.016 (0.016) Batch 1.285 (1.474) Remain 15:44:01 loss: 4.4582 Lr: 1.04694e-04 Mem R(MA/MR): 27134 (21268/36162) [2025-04-29 16:08:54,324 INFO hook.py line 650 1619929] Train: [354/512][100/242] Data 0.016 (0.017) Batch 1.499 (1.458) Remain 15:32:36 loss: 4.3055 Lr: 1.04571e-04 Mem R(MA/MR): 27134 (21268/36162) [2025-04-29 16:10:07,358 INFO hook.py line 650 1619929] Train: [354/512][150/242] Data 0.018 (0.017) Batch 1.407 (1.459) Remain 15:31:57 loss: 4.8372 Lr: 1.04449e-04 Mem R(MA/MR): 27134 (21268/36162) [2025-04-29 16:11:20,800 INFO hook.py line 650 1619929] Train: [354/512][200/242] Data 0.015 (0.017) Batch 1.399 (1.461) Remain 15:32:21 loss: 5.8411 Lr: 1.04326e-04 Mem R(MA/MR): 27142 (21268/36162) [2025-04-29 16:12:17,730 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2739 loss_mask: 0.0329 loss_dice: 1.8733 loss_score: 0.0000 loss_bbox: 0.0477 loss_sp_cls: 0.7447 loss: 4.7667 [2025-04-29 16:12:22,173 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:13:53,340 INFO hook.py line 650 1619929] Train: [355/512][50/242] Data 0.016 (0.018) Batch 1.502 (1.470) Remain 15:35:25 loss: 5.3089 Lr: 1.04101e-04 Mem R(MA/MR): 20246 (21268/36162) [2025-04-29 16:15:07,796 INFO hook.py line 650 1619929] Train: [355/512][100/242] Data 0.016 (0.017) Batch 1.484 (1.480) Remain 15:40:31 loss: 4.1990 Lr: 1.03978e-04 Mem R(MA/MR): 20264 (21268/36162) [2025-04-29 16:16:21,529 INFO hook.py line 650 1619929] Train: [355/512][150/242] Data 0.018 (0.017) Batch 1.460 (1.478) Remain 15:38:11 loss: 5.3338 Lr: 1.03856e-04 Mem R(MA/MR): 20264 (21268/36162) [2025-04-29 16:17:34,608 INFO hook.py line 650 1619929] Train: [355/512][200/242] Data 0.015 (0.017) Batch 1.461 (1.474) Remain 15:34:19 loss: 5.0931 Lr: 1.03733e-04 Mem R(MA/MR): 22036 (21268/36162) [2025-04-29 16:18:32,636 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2722 loss_mask: 0.0339 loss_dice: 1.8777 loss_score: 0.0000 loss_bbox: 0.0478 loss_sp_cls: 0.7471 loss: 4.7712 [2025-04-29 16:18:33,392 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:20:10,623 INFO hook.py line 650 1619929] Train: [356/512][50/242] Data 0.016 (0.017) Batch 1.578 (1.504) Remain 15:50:55 loss: 4.9041 Lr: 1.03507e-04 Mem R(MA/MR): 20920 (21268/36162) [2025-04-29 16:21:23,018 INFO hook.py line 650 1619929] Train: [356/512][100/242] Data 0.017 (0.017) Batch 1.390 (1.475) Remain 15:31:30 loss: 4.7567 Lr: 1.03385e-04 Mem R(MA/MR): 23672 (21268/36162) [2025-04-29 16:22:32,969 INFO hook.py line 650 1619929] Train: [356/512][150/242] Data 0.017 (0.016) Batch 1.505 (1.449) Remain 15:13:59 loss: 6.1204 Lr: 1.03262e-04 Mem R(MA/MR): 26772 (21268/36162) [2025-04-29 16:23:43,874 INFO hook.py line 650 1619929] Train: [356/512][200/242] Data 0.016 (0.016) Batch 1.454 (1.441) Remain 15:07:50 loss: 5.5102 Lr: 1.03139e-04 Mem R(MA/MR): 32316 (21268/36162) [2025-04-29 16:24:42,431 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2766 loss_mask: 0.0335 loss_dice: 1.8785 loss_score: 0.0000 loss_bbox: 0.0487 loss_sp_cls: 0.7461 loss: 4.7938 [2025-04-29 16:24:44,783 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:26:20,823 INFO hook.py line 650 1619929] Train: [357/512][50/242] Data 0.016 (0.016) Batch 1.513 (1.465) Remain 15:20:48 loss: 4.5037 Lr: 1.02914e-04 Mem R(MA/MR): 20678 (21268/36162) [2025-04-29 16:27:33,182 INFO hook.py line 650 1619929] Train: [357/512][100/242] Data 0.016 (0.017) Batch 1.409 (1.456) Remain 15:13:41 loss: 4.0962 Lr: 1.02791e-04 Mem R(MA/MR): 20684 (21268/36162) [2025-04-29 16:28:44,686 INFO hook.py line 650 1619929] Train: [357/512][150/242] Data 0.015 (0.016) Batch 1.378 (1.447) Remain 15:06:56 loss: 5.0656 Lr: 1.02668e-04 Mem R(MA/MR): 25002 (21268/36162) [2025-04-29 16:29:56,580 INFO hook.py line 650 1619929] Train: [357/512][200/242] Data 0.015 (0.017) Batch 1.348 (1.445) Remain 15:04:16 loss: 5.2288 Lr: 1.02546e-04 Mem R(MA/MR): 25030 (21268/36162) [2025-04-29 16:30:53,226 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2758 loss_mask: 0.0335 loss_dice: 1.8786 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7448 loss: 4.7827 [2025-04-29 16:30:53,990 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:32:30,819 INFO hook.py line 650 1619929] Train: [358/512][50/242] Data 0.016 (0.016) Batch 1.498 (1.481) Remain 15:24:45 loss: 4.6487 Lr: 1.02320e-04 Mem R(MA/MR): 21222 (21268/36162) [2025-04-29 16:33:44,710 INFO hook.py line 650 1619929] Train: [358/512][100/242] Data 0.016 (0.017) Batch 1.461 (1.479) Remain 15:22:26 loss: 4.2493 Lr: 1.02197e-04 Mem R(MA/MR): 21222 (21268/36162) [2025-04-29 16:34:56,480 INFO hook.py line 650 1619929] Train: [358/512][150/242] Data 0.018 (0.017) Batch 1.655 (1.464) Remain 15:11:52 loss: 5.7265 Lr: 1.02074e-04 Mem R(MA/MR): 23426 (21268/36162) [2025-04-29 16:36:08,774 INFO hook.py line 650 1619929] Train: [358/512][200/242] Data 0.014 (0.017) Batch 1.284 (1.460) Remain 15:07:43 loss: 4.6362 Lr: 1.01951e-04 Mem R(MA/MR): 23426 (21268/36162) [2025-04-29 16:37:05,313 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2753 loss_mask: 0.0338 loss_dice: 1.8768 loss_score: 0.0000 loss_bbox: 0.0486 loss_sp_cls: 0.7398 loss: 4.7837 [2025-04-29 16:37:07,527 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:38:42,869 INFO hook.py line 650 1619929] Train: [359/512][50/242] Data 0.015 (0.017) Batch 1.422 (1.488) Remain 15:22:55 loss: 4.1916 Lr: 1.01725e-04 Mem R(MA/MR): 21126 (21268/36162) [2025-04-29 16:39:56,779 INFO hook.py line 650 1619929] Train: [359/512][100/242] Data 0.016 (0.017) Batch 1.388 (1.483) Remain 15:18:35 loss: 7.0782 Lr: 1.01602e-04 Mem R(MA/MR): 21126 (21268/36162) [2025-04-29 16:41:09,672 INFO hook.py line 650 1619929] Train: [359/512][150/242] Data 0.015 (0.017) Batch 1.822 (1.474) Remain 15:12:06 loss: 5.0176 Lr: 1.01479e-04 Mem R(MA/MR): 22468 (21268/36162) [2025-04-29 16:42:21,135 INFO hook.py line 650 1619929] Train: [359/512][200/242] Data 0.016 (0.017) Batch 1.354 (1.463) Remain 15:03:47 loss: 4.3892 Lr: 1.01359e-04 Mem R(MA/MR): 22468 (21268/36162) [2025-04-29 16:43:19,283 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2791 loss_mask: 0.0343 loss_dice: 1.8949 loss_score: 0.0000 loss_bbox: 0.0484 loss_sp_cls: 0.7495 loss: 4.8235 [2025-04-29 16:43:20,392 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:44:54,022 INFO hook.py line 650 1619929] Train: [360/512][50/242] Data 0.016 (0.016) Batch 1.374 (1.447) Remain 14:51:27 loss: 6.1168 Lr: 1.01133e-04 Mem R(MA/MR): 17374 (21268/36162) [2025-04-29 16:46:06,521 INFO hook.py line 650 1619929] Train: [360/512][100/242] Data 0.014 (0.017) Batch 1.245 (1.448) Remain 14:51:19 loss: 4.4616 Lr: 1.01010e-04 Mem R(MA/MR): 19768 (21268/36162) [2025-04-29 16:47:18,907 INFO hook.py line 650 1619929] Train: [360/512][150/242] Data 0.015 (0.017) Batch 1.510 (1.448) Remain 14:50:00 loss: 4.0588 Lr: 1.00887e-04 Mem R(MA/MR): 20914 (21268/36162) [2025-04-29 16:48:31,254 INFO hook.py line 650 1619929] Train: [360/512][200/242] Data 0.015 (0.017) Batch 1.312 (1.448) Remain 14:48:37 loss: 5.5292 Lr: 1.00764e-04 Mem R(MA/MR): 20914 (21268/36162) [2025-04-29 16:49:29,646 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2969 loss_mask: 0.0357 loss_dice: 1.9362 loss_score: 0.0000 loss_bbox: 0.0497 loss_sp_cls: 0.7659 loss: 4.9581 [2025-04-29 16:49:30,369 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 16:49:32,754 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.7293 Process Time: 0.417 Mem R(MA/MR): 4696 (21268/36162) [2025-04-29 16:49:34,528 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6926 Process Time: 0.524 Mem R(MA/MR): 7622 (21268/36162) [2025-04-29 16:49:36,237 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.5186 Process Time: 0.663 Mem R(MA/MR): 10216 (21268/36162) [2025-04-29 16:49:43,864 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4488 Process Time: 0.953 Mem R(MA/MR): 20010 (21268/36162) [2025-04-29 16:49:44,706 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.0249 Process Time: 0.321 Mem R(MA/MR): 7228 (21268/36162) [2025-04-29 16:49:46,318 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.9079 Process Time: 0.527 Mem R(MA/MR): 12024 (21268/36162) [2025-04-29 16:49:46,829 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1996 Process Time: 0.157 Mem R(MA/MR): 6878 (21268/36162) [2025-04-29 16:49:47,247 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5507 Process Time: 0.130 Mem R(MA/MR): 4740 (21268/36162) [2025-04-29 16:49:48,076 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0154 Process Time: 0.208 Mem R(MA/MR): 12020 (21268/36162) [2025-04-29 16:49:49,885 INFO hook.py line 449 1619929] Test: [10/50] Loss 5.6561 Process Time: 0.600 Mem R(MA/MR): 9756 (21268/36162) [2025-04-29 16:49:52,727 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.6457 Process Time: 0.797 Mem R(MA/MR): 19046 (21268/36162) [2025-04-29 16:49:54,920 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.3547 Process Time: 0.297 Mem R(MA/MR): 15686 (21268/36162) [2025-04-29 16:49:55,974 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.6244 Process Time: 0.261 Mem R(MA/MR): 8930 (21268/36162) [2025-04-29 16:49:56,401 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.4502 Process Time: 0.169 Mem R(MA/MR): 5426 (21268/36162) [2025-04-29 16:49:59,383 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.7514 Process Time: 0.335 Mem R(MA/MR): 17068 (21268/36162) [2025-04-29 16:50:00,959 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4338 Process Time: 0.362 Mem R(MA/MR): 15078 (21268/36162) [2025-04-29 16:50:01,676 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.0227 Process Time: 0.224 Mem R(MA/MR): 7214 (21268/36162) [2025-04-29 16:50:02,580 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1116 Process Time: 0.231 Mem R(MA/MR): 8524 (21268/36162) [2025-04-29 16:50:03,949 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2797 Process Time: 0.178 Mem R(MA/MR): 6606 (21268/36162) [2025-04-29 16:50:05,288 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.6162 Process Time: 0.251 Mem R(MA/MR): 12216 (21268/36162) [2025-04-29 16:50:14,781 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.2301 Process Time: 1.259 Mem R(MA/MR): 24092 (21268/36162) [2025-04-29 16:50:15,961 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5414 Process Time: 0.557 Mem R(MA/MR): 7342 (21268/36162) [2025-04-29 16:50:27,216 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.3415 Process Time: 0.420 Mem R(MA/MR): 10522 (21268/36162) [2025-04-29 16:50:27,855 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7536 Process Time: 0.232 Mem R(MA/MR): 5938 (21268/36162) [2025-04-29 16:50:28,923 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0886 Process Time: 0.302 Mem R(MA/MR): 9764 (21268/36162) [2025-04-29 16:50:37,272 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.3582 Process Time: 2.209 Mem R(MA/MR): 32672 (21268/36162) [2025-04-29 16:50:39,071 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.4103 Process Time: 0.306 Mem R(MA/MR): 10482 (21268/36162) [2025-04-29 16:50:40,239 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.1299 Process Time: 0.287 Mem R(MA/MR): 9172 (21268/36162) [2025-04-29 16:50:45,947 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.5491 Process Time: 1.011 Mem R(MA/MR): 17588 (21268/36162) [2025-04-29 16:50:46,874 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.4575 Process Time: 0.290 Mem R(MA/MR): 8070 (21268/36162) [2025-04-29 16:50:50,198 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5797 Process Time: 0.343 Mem R(MA/MR): 20688 (21268/36162) [2025-04-29 16:50:50,861 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3064 Process Time: 0.207 Mem R(MA/MR): 4332 (21268/36162) [2025-04-29 16:50:54,791 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.4956 Process Time: 0.763 Mem R(MA/MR): 24968 (21268/36162) [2025-04-29 16:50:55,844 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5357 Process Time: 0.262 Mem R(MA/MR): 10454 (21268/36162) [2025-04-29 16:50:57,521 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3886 Process Time: 0.282 Mem R(MA/MR): 14632 (21268/36162) [2025-04-29 16:50:58,143 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0778 Process Time: 0.293 Mem R(MA/MR): 6994 (21268/36162) [2025-04-29 16:51:02,545 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.3661 Process Time: 1.120 Mem R(MA/MR): 28548 (21268/36162) [2025-04-29 16:51:04,236 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.9135 Process Time: 0.415 Mem R(MA/MR): 11442 (21268/36162) [2025-04-29 16:51:04,689 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.6586 Process Time: 0.172 Mem R(MA/MR): 6088 (21268/36162) [2025-04-29 16:51:05,855 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7108 Process Time: 0.293 Mem R(MA/MR): 10824 (21268/36162) [2025-04-29 16:51:07,328 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.9726 Process Time: 0.608 Mem R(MA/MR): 9168 (21268/36162) [2025-04-29 16:51:08,071 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.8987 Process Time: 0.311 Mem R(MA/MR): 6096 (21268/36162) [2025-04-29 16:51:08,619 INFO hook.py line 449 1619929] Test: [43/50] Loss 5.4484 Process Time: 0.231 Mem R(MA/MR): 6168 (21268/36162) [2025-04-29 16:51:09,419 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.9170 Process Time: 0.358 Mem R(MA/MR): 7472 (21268/36162) [2025-04-29 16:51:10,364 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6337 Process Time: 0.200 Mem R(MA/MR): 5922 (21268/36162) [2025-04-29 16:51:12,793 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.4491 Process Time: 0.471 Mem R(MA/MR): 15088 (21268/36162) [2025-04-29 16:51:20,032 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.2135 Process Time: 0.555 Mem R(MA/MR): 20808 (21268/36162) [2025-04-29 16:51:29,184 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.7384 Process Time: 1.213 Mem R(MA/MR): 36182 (21268/36182) [2025-04-29 16:51:29,857 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9439 Process Time: 0.283 Mem R(MA/MR): 6128 (21268/36182) [2025-04-29 16:51:31,988 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0348 Process Time: 0.418 Mem R(MA/MR): 14242 (21268/36182) [2025-04-29 16:51:36,693 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 16:51:36,693 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 16:51:36,693 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] table : 0.274 0.616 0.777 0.824 0.618 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] door : 0.408 0.745 0.916 0.894 0.747 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] ceiling lamp : 0.566 0.760 0.881 0.789 0.785 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] cabinet : 0.331 0.481 0.548 0.660 0.463 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] blinds : 0.589 0.820 0.860 0.870 0.870 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] curtain : 0.256 0.432 0.489 0.500 0.750 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] chair : 0.650 0.777 0.828 0.920 0.660 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] storage cabinet: 0.175 0.269 0.470 0.480 0.480 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] office chair : 0.518 0.548 0.562 0.720 0.750 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] bookshelf : 0.250 0.687 0.687 0.800 0.727 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] whiteboard : 0.567 0.737 0.771 1.000 0.657 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] window : 0.122 0.300 0.621 0.614 0.385 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] box : 0.177 0.358 0.511 0.532 0.409 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] monitor : 0.667 0.823 0.851 0.906 0.829 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] shelf : 0.077 0.222 0.439 0.414 0.400 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] heater : 0.412 0.633 0.794 0.763 0.763 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] kitchen cabinet: 0.076 0.222 0.565 0.317 0.520 [2025-04-29 16:51:36,693 INFO hook.py line 395 1619929] sofa : 0.442 0.549 0.833 0.800 0.667 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] bed : 0.081 0.169 0.793 0.357 0.625 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] trash can : 0.532 0.655 0.698 0.810 0.723 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] book : 0.024 0.040 0.093 0.176 0.097 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] plant : 0.496 0.695 0.750 1.000 0.667 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] blanket : 0.435 0.538 0.643 0.600 0.545 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] tv : 0.921 1.000 1.000 1.000 1.000 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] computer tower : 0.296 0.379 0.527 0.545 0.429 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] refrigerator : 0.202 0.333 0.367 1.000 0.333 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] jacket : 0.090 0.232 0.383 0.400 0.545 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] sink : 0.376 0.719 0.814 0.762 0.727 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] bag : 0.080 0.181 0.209 0.409 0.333 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] picture : 0.095 0.175 0.326 0.412 0.359 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] pillow : 0.434 0.629 0.668 0.700 0.737 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] towel : 0.196 0.310 0.442 0.667 0.316 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] suitcase : 0.269 0.281 0.281 0.429 0.429 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] backpack : 0.352 0.442 0.507 0.600 0.462 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] crate : 0.065 0.155 0.404 0.333 0.455 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] keyboard : 0.520 0.684 0.738 0.929 0.667 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] toilet : 0.853 0.876 1.000 0.889 0.889 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] printer : 0.322 0.355 0.438 0.556 0.556 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] poster : 0.000 0.001 0.001 0.020 0.111 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] microwave : 0.502 0.750 1.000 1.000 0.750 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] shoes : 0.130 0.230 0.489 0.652 0.366 [2025-04-29 16:51:36,694 INFO hook.py line 395 1619929] socket : 0.178 0.427 0.654 0.688 0.457 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] bottle : 0.150 0.239 0.354 0.512 0.265 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] bucket : 0.133 0.155 0.160 0.375 0.429 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] cushion : 0.026 0.032 0.111 0.143 0.333 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] basket : 0.009 0.010 0.012 0.143 0.143 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] telephone : 0.250 0.514 0.553 0.889 0.471 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] laptop : 0.360 0.643 0.726 0.500 0.750 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] plant pot : 0.205 0.543 0.584 0.818 0.562 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] exhaust fan : 0.208 0.370 0.370 0.750 0.400 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] cup : 0.195 0.352 0.404 0.933 0.318 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] coat hanger : 0.231 0.500 0.637 1.000 0.500 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] light switch : 0.246 0.512 0.674 0.708 0.523 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] speaker : 0.321 0.414 0.572 0.714 0.455 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.792 1.000 0.500 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] kettle : 0.296 0.500 0.500 1.000 0.500 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] smoke detector : 0.673 0.854 0.855 0.909 0.833 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] power strip : 0.125 0.205 0.242 0.500 0.500 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.042 0.000 0.000 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] mouse : 0.480 0.686 0.735 0.880 0.688 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] cutting board : 0.042 0.062 0.062 0.500 0.250 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] toilet paper : 0.236 0.311 0.395 1.000 0.294 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] paper towel : 0.021 0.060 0.153 0.286 0.250 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 1.000 0.000 [2025-04-29 16:51:36,695 INFO hook.py line 395 1619929] clock : 0.637 0.817 0.850 1.000 0.667 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] tap : 0.120 0.237 0.546 0.600 0.333 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] soap dispenser : 0.422 0.506 0.518 1.000 0.400 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] bowl : 0.039 0.042 0.083 0.250 0.333 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] whiteboard eraser: 0.265 0.647 0.647 0.833 0.833 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] toilet brush : 0.354 0.667 0.913 1.000 0.667 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] spray bottle : 0.010 0.014 0.014 0.111 0.250 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] headphones : 0.061 0.500 0.500 1.000 0.500 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] stapler : 0.034 0.249 0.150 0.429 1.000 [2025-04-29 16:51:36,696 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 16:51:36,696 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 16:51:36,696 INFO hook.py line 404 1619929] average : 0.253 0.389 0.479 0.604 0.470 [2025-04-29 16:51:36,696 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 16:51:36,696 INFO hook.py line 480 1619929] Total Process Time: 23.277 s [2025-04-29 16:51:36,696 INFO hook.py line 481 1619929] Average Process Time: 466.535 ms [2025-04-29 16:51:36,697 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 16:51:36,749 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 16:51:36,755 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:53:04,633 INFO hook.py line 650 1619929] Train: [361/512][50/242] Data 0.016 (0.033) Batch 1.424 (1.488) Remain 15:11:06 loss: 5.6882 Lr: 1.00538e-04 Mem R(MA/MR): 21664 (21268/36182) [2025-04-29 16:54:17,581 INFO hook.py line 650 1619929] Train: [361/512][100/242] Data 0.017 (0.024) Batch 1.314 (1.473) Remain 15:00:39 loss: 3.7507 Lr: 1.00414e-04 Mem R(MA/MR): 23312 (21268/36182) [2025-04-29 16:55:29,597 INFO hook.py line 650 1619929] Train: [361/512][150/242] Data 0.018 (0.022) Batch 1.360 (1.462) Remain 14:52:37 loss: 4.4114 Lr: 1.00291e-04 Mem R(MA/MR): 26826 (21268/36182) [2025-04-29 16:56:44,658 INFO hook.py line 650 1619929] Train: [361/512][200/242] Data 0.020 (0.021) Batch 1.620 (1.472) Remain 14:57:28 loss: 6.2649 Lr: 1.00168e-04 Mem R(MA/MR): 26826 (21268/36182) [2025-04-29 16:57:42,620 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2911 loss_mask: 0.0352 loss_dice: 1.9201 loss_score: 0.0000 loss_bbox: 0.0495 loss_sp_cls: 0.7626 loss: 4.9121 [2025-04-29 16:57:46,645 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 16:59:22,430 INFO hook.py line 650 1619929] Train: [362/512][50/242] Data 0.016 (0.017) Batch 1.491 (1.486) Remain 15:03:54 loss: 4.7646 Lr: 9.99419e-05 Mem R(MA/MR): 23570 (21268/36182) [2025-04-29 17:00:35,432 INFO hook.py line 650 1619929] Train: [362/512][100/242] Data 0.018 (0.017) Batch 1.801 (1.473) Remain 14:54:28 loss: 5.3668 Lr: 9.98187e-05 Mem R(MA/MR): 25342 (21268/36182) [2025-04-29 17:01:48,337 INFO hook.py line 650 1619929] Train: [362/512][150/242] Data 0.016 (0.017) Batch 1.518 (1.468) Remain 14:50:14 loss: 4.1874 Lr: 9.96956e-05 Mem R(MA/MR): 25342 (21268/36182) [2025-04-29 17:03:01,234 INFO hook.py line 650 1619929] Train: [362/512][200/242] Data 0.015 (0.017) Batch 1.380 (1.465) Remain 14:47:30 loss: 4.4572 Lr: 9.95725e-05 Mem R(MA/MR): 27186 (21268/36182) [2025-04-29 17:03:58,757 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2861 loss_mask: 0.0351 loss_dice: 1.9284 loss_score: 0.0000 loss_bbox: 0.0497 loss_sp_cls: 0.7602 loss: 4.9162 [2025-04-29 17:04:01,226 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:05:37,697 INFO hook.py line 650 1619929] Train: [363/512][50/242] Data 0.016 (0.017) Batch 1.406 (1.483) Remain 14:56:00 loss: 5.0452 Lr: 9.93458e-05 Mem R(MA/MR): 18656 (21268/36182) [2025-04-29 17:06:47,139 INFO hook.py line 650 1619929] Train: [363/512][100/242] Data 0.016 (0.016) Batch 1.503 (1.434) Remain 14:25:27 loss: 4.7442 Lr: 9.92226e-05 Mem R(MA/MR): 23444 (21268/36182) [2025-04-29 17:08:01,071 INFO hook.py line 650 1619929] Train: [363/512][150/242] Data 0.016 (0.016) Batch 1.370 (1.450) Remain 14:33:19 loss: 5.3602 Lr: 9.90994e-05 Mem R(MA/MR): 23444 (21268/36182) [2025-04-29 17:09:13,856 INFO hook.py line 650 1619929] Train: [363/512][200/242] Data 0.015 (0.017) Batch 1.370 (1.451) Remain 14:33:04 loss: 6.1244 Lr: 9.89762e-05 Mem R(MA/MR): 23446 (21268/36182) [2025-04-29 17:10:13,068 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2875 loss_mask: 0.0354 loss_dice: 1.9161 loss_score: 0.0000 loss_bbox: 0.0498 loss_sp_cls: 0.7515 loss: 4.8968 [2025-04-29 17:10:13,166 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:11:47,409 INFO hook.py line 650 1619929] Train: [364/512][50/242] Data 0.016 (0.016) Batch 1.473 (1.454) Remain 14:32:42 loss: 4.1622 Lr: 9.87494e-05 Mem R(MA/MR): 27612 (21268/36182) [2025-04-29 17:13:01,292 INFO hook.py line 650 1619929] Train: [364/512][100/242] Data 0.016 (0.016) Batch 1.360 (1.466) Remain 14:38:44 loss: 4.1545 Lr: 9.86261e-05 Mem R(MA/MR): 30224 (21268/36182) [2025-04-29 17:14:13,032 INFO hook.py line 650 1619929] Train: [364/512][150/242] Data 0.017 (0.016) Batch 1.422 (1.456) Remain 14:31:07 loss: 4.6190 Lr: 9.85028e-05 Mem R(MA/MR): 30238 (21268/36182) [2025-04-29 17:15:26,195 INFO hook.py line 650 1619929] Train: [364/512][200/242] Data 0.016 (0.016) Batch 1.438 (1.458) Remain 14:31:04 loss: 5.3159 Lr: 9.83795e-05 Mem R(MA/MR): 30238 (21268/36182) [2025-04-29 17:16:25,475 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2850 loss_mask: 0.0347 loss_dice: 1.9053 loss_score: 0.0000 loss_bbox: 0.0488 loss_sp_cls: 0.7495 loss: 4.8675 [2025-04-29 17:16:25,969 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:17:59,644 INFO hook.py line 650 1619929] Train: [365/512][50/242] Data 0.015 (0.016) Batch 1.445 (1.459) Remain 14:29:48 loss: 5.1181 Lr: 9.81525e-05 Mem R(MA/MR): 20514 (21268/36182) [2025-04-29 17:19:12,378 INFO hook.py line 650 1619929] Train: [365/512][100/242] Data 0.016 (0.016) Batch 1.499 (1.457) Remain 14:27:11 loss: 5.2387 Lr: 9.80292e-05 Mem R(MA/MR): 24522 (21268/36182) [2025-04-29 17:20:25,325 INFO hook.py line 650 1619929] Train: [365/512][150/242] Data 0.017 (0.017) Batch 1.537 (1.458) Remain 14:26:24 loss: 5.4667 Lr: 9.79058e-05 Mem R(MA/MR): 24522 (21268/36182) [2025-04-29 17:21:39,201 INFO hook.py line 650 1619929] Train: [365/512][200/242] Data 0.015 (0.017) Batch 1.433 (1.463) Remain 14:28:12 loss: 3.9668 Lr: 9.77824e-05 Mem R(MA/MR): 24522 (21268/36182) [2025-04-29 17:22:37,095 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2827 loss_mask: 0.0342 loss_dice: 1.9098 loss_score: 0.0000 loss_bbox: 0.0484 loss_sp_cls: 0.7531 loss: 4.8597 [2025-04-29 17:22:37,709 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:24:06,644 INFO hook.py line 650 1619929] Train: [366/512][50/242] Data 0.018 (0.019) Batch 1.414 (1.488) Remain 14:41:08 loss: 5.6089 Lr: 9.75553e-05 Mem R(MA/MR): 19186 (21268/36182) [2025-04-29 17:25:19,074 INFO hook.py line 650 1619929] Train: [366/512][100/242] Data 0.017 (0.018) Batch 1.439 (1.468) Remain 14:27:49 loss: 4.7356 Lr: 9.74318e-05 Mem R(MA/MR): 22404 (21268/36182) [2025-04-29 17:26:30,212 INFO hook.py line 650 1619929] Train: [366/512][150/242] Data 0.016 (0.017) Batch 1.266 (1.453) Remain 14:17:33 loss: 4.2973 Lr: 9.73084e-05 Mem R(MA/MR): 22404 (21268/36182) [2025-04-29 17:27:41,432 INFO hook.py line 650 1619929] Train: [366/512][200/242] Data 0.015 (0.017) Batch 1.504 (1.445) Remain 14:12:08 loss: 4.8375 Lr: 9.71849e-05 Mem R(MA/MR): 24232 (21268/36182) [2025-04-29 17:28:38,124 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2838 loss_mask: 0.0347 loss_dice: 1.9002 loss_score: 0.0000 loss_bbox: 0.0489 loss_sp_cls: 0.7472 loss: 4.8510 [2025-04-29 17:28:40,029 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:30:15,777 INFO hook.py line 650 1619929] Train: [367/512][50/242] Data 0.016 (0.017) Batch 1.531 (1.458) Remain 14:17:06 loss: 4.9867 Lr: 9.69576e-05 Mem R(MA/MR): 20006 (21268/36182) [2025-04-29 17:31:30,230 INFO hook.py line 650 1619929] Train: [367/512][100/242] Data 0.017 (0.017) Batch 1.437 (1.474) Remain 14:25:25 loss: 4.7957 Lr: 9.68341e-05 Mem R(MA/MR): 20728 (21268/36182) [2025-04-29 17:32:40,597 INFO hook.py line 650 1619929] Train: [367/512][150/242] Data 0.017 (0.016) Batch 1.376 (1.451) Remain 14:10:56 loss: 3.8093 Lr: 9.67106e-05 Mem R(MA/MR): 23040 (21268/36182) [2025-04-29 17:33:52,010 INFO hook.py line 650 1619929] Train: [367/512][200/242] Data 0.015 (0.016) Batch 1.457 (1.445) Remain 14:06:19 loss: 4.8317 Lr: 9.65870e-05 Mem R(MA/MR): 23040 (21268/36182) [2025-04-29 17:34:50,267 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2833 loss_mask: 0.0349 loss_dice: 1.9182 loss_score: 0.0000 loss_bbox: 0.0484 loss_sp_cls: 0.7538 loss: 4.8771 [2025-04-29 17:34:55,369 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:36:22,531 INFO hook.py line 650 1619929] Train: [368/512][50/242] Data 0.017 (0.016) Batch 1.708 (1.444) Remain 14:03:16 loss: 5.6630 Lr: 9.63596e-05 Mem R(MA/MR): 19602 (21268/36182) [2025-04-29 17:37:36,873 INFO hook.py line 650 1619929] Train: [368/512][100/242] Data 0.016 (0.016) Batch 1.477 (1.466) Remain 14:14:57 loss: 4.3676 Lr: 9.62360e-05 Mem R(MA/MR): 21534 (21268/36182) [2025-04-29 17:38:49,114 INFO hook.py line 650 1619929] Train: [368/512][150/242] Data 0.016 (0.016) Batch 1.307 (1.459) Remain 14:09:31 loss: 5.0331 Lr: 9.61123e-05 Mem R(MA/MR): 21534 (21268/36182) [2025-04-29 17:40:02,702 INFO hook.py line 650 1619929] Train: [368/512][200/242] Data 0.015 (0.016) Batch 1.344 (1.462) Remain 14:10:13 loss: 4.9096 Lr: 9.59887e-05 Mem R(MA/MR): 21534 (21268/36182) [2025-04-29 17:40:59,726 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2687 loss_mask: 0.0339 loss_dice: 1.8793 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7413 loss: 4.7658 [2025-04-29 17:40:59,860 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 17:41:02,327 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.3296 Process Time: 0.468 Mem R(MA/MR): 4270 (21268/36182) [2025-04-29 17:41:04,340 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.2412 Process Time: 0.845 Mem R(MA/MR): 7134 (21268/36182) [2025-04-29 17:41:06,635 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2040 Process Time: 1.022 Mem R(MA/MR): 9660 (21268/36182) [2025-04-29 17:41:14,352 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.8713 Process Time: 1.344 Mem R(MA/MR): 19612 (21268/36182) [2025-04-29 17:41:15,550 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6534 Process Time: 0.472 Mem R(MA/MR): 7146 (21268/36182) [2025-04-29 17:41:17,387 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4436 Process Time: 0.535 Mem R(MA/MR): 11224 (21268/36182) [2025-04-29 17:41:18,016 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0449 Process Time: 0.215 Mem R(MA/MR): 6094 (21268/36182) [2025-04-29 17:41:18,484 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2803 Process Time: 0.143 Mem R(MA/MR): 4312 (21268/36182) [2025-04-29 17:41:19,522 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7896 Process Time: 0.319 Mem R(MA/MR): 11294 (21268/36182) [2025-04-29 17:41:21,270 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8241 Process Time: 0.402 Mem R(MA/MR): 9364 (21268/36182) [2025-04-29 17:41:24,758 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0315 Process Time: 0.903 Mem R(MA/MR): 18638 (21268/36182) [2025-04-29 17:41:27,476 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9436 Process Time: 0.437 Mem R(MA/MR): 15432 (21268/36182) [2025-04-29 17:41:28,622 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0485 Process Time: 0.246 Mem R(MA/MR): 8588 (21268/36182) [2025-04-29 17:41:29,067 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2972 Process Time: 0.176 Mem R(MA/MR): 4638 (21268/36182) [2025-04-29 17:41:32,413 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.1088 Process Time: 0.700 Mem R(MA/MR): 16432 (21268/36182) [2025-04-29 17:41:34,197 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.5403 Process Time: 0.373 Mem R(MA/MR): 14354 (21268/36182) [2025-04-29 17:41:34,891 INFO hook.py line 449 1619929] Test: [17/50] Loss 6.1248 Process Time: 0.234 Mem R(MA/MR): 6558 (21268/36182) [2025-04-29 17:41:35,664 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.4831 Process Time: 0.183 Mem R(MA/MR): 8076 (21268/36182) [2025-04-29 17:41:36,801 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.1027 Process Time: 0.159 Mem R(MA/MR): 5802 (21268/36182) [2025-04-29 17:41:38,159 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.7398 Process Time: 0.223 Mem R(MA/MR): 11424 (21268/36182) [2025-04-29 17:41:47,299 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.5643 Process Time: 0.797 Mem R(MA/MR): 23692 (21268/36182) [2025-04-29 17:41:48,170 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3763 Process Time: 0.362 Mem R(MA/MR): 6854 (21268/36182) [2025-04-29 17:41:58,892 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.6964 Process Time: 0.987 Mem R(MA/MR): 10008 (21268/36182) [2025-04-29 17:41:59,603 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9385 Process Time: 0.264 Mem R(MA/MR): 5062 (21268/36182) [2025-04-29 17:42:00,879 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0676 Process Time: 0.459 Mem R(MA/MR): 9208 (21268/36182) [2025-04-29 17:42:08,904 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.1653 Process Time: 2.113 Mem R(MA/MR): 31666 (21268/36182) [2025-04-29 17:42:11,895 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4140 Process Time: 0.532 Mem R(MA/MR): 9596 (21268/36182) [2025-04-29 17:42:13,218 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0449 Process Time: 0.353 Mem R(MA/MR): 8840 (21268/36182) [2025-04-29 17:42:18,506 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0812 Process Time: 0.318 Mem R(MA/MR): 16992 (21268/36182) [2025-04-29 17:42:19,527 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1483 Process Time: 0.316 Mem R(MA/MR): 7574 (21268/36182) [2025-04-29 17:42:22,756 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.4822 Process Time: 0.358 Mem R(MA/MR): 20498 (21268/36182) [2025-04-29 17:42:23,347 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.9964 Process Time: 0.288 Mem R(MA/MR): 3920 (21268/36182) [2025-04-29 17:42:28,706 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.7183 Process Time: 1.120 Mem R(MA/MR): 24468 (21268/36182) [2025-04-29 17:42:29,930 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.7007 Process Time: 0.394 Mem R(MA/MR): 9770 (21268/36182) [2025-04-29 17:42:31,814 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.5451 Process Time: 0.282 Mem R(MA/MR): 13898 (21268/36182) [2025-04-29 17:42:32,663 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0669 Process Time: 0.369 Mem R(MA/MR): 6242 (21268/36182) [2025-04-29 17:42:37,733 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.1738 Process Time: 1.272 Mem R(MA/MR): 28598 (21268/36182) [2025-04-29 17:42:39,246 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.9121 Process Time: 0.263 Mem R(MA/MR): 10558 (21268/36182) [2025-04-29 17:42:39,758 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9431 Process Time: 0.159 Mem R(MA/MR): 5384 (21268/36182) [2025-04-29 17:42:40,934 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7384 Process Time: 0.307 Mem R(MA/MR): 9898 (21268/36182) [2025-04-29 17:42:42,308 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.1325 Process Time: 0.561 Mem R(MA/MR): 8850 (21268/36182) [2025-04-29 17:42:43,623 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1322 Process Time: 0.472 Mem R(MA/MR): 5254 (21268/36182) [2025-04-29 17:42:44,162 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9662 Process Time: 0.220 Mem R(MA/MR): 5302 (21268/36182) [2025-04-29 17:42:44,994 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.2179 Process Time: 0.347 Mem R(MA/MR): 7066 (21268/36182) [2025-04-29 17:42:45,691 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5905 Process Time: 0.187 Mem R(MA/MR): 5036 (21268/36182) [2025-04-29 17:42:48,027 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.9359 Process Time: 0.320 Mem R(MA/MR): 14234 (21268/36182) [2025-04-29 17:42:54,915 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.4839 Process Time: 0.343 Mem R(MA/MR): 20242 (21268/36182) [2025-04-29 17:43:04,341 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2882 Process Time: 0.988 Mem R(MA/MR): 35454 (21268/36182) [2025-04-29 17:43:04,996 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.8420 Process Time: 0.231 Mem R(MA/MR): 5568 (21268/36182) [2025-04-29 17:43:07,487 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.4590 Process Time: 0.375 Mem R(MA/MR): 13604 (21268/36182) [2025-04-29 17:43:12,263 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 17:43:12,263 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 17:43:12,264 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] table : 0.272 0.617 0.766 0.786 0.676 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] door : 0.468 0.788 0.925 0.886 0.785 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] ceiling lamp : 0.548 0.742 0.864 0.784 0.762 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] cabinet : 0.338 0.463 0.547 0.423 0.612 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] blinds : 0.584 0.843 0.851 0.792 0.826 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] curtain : 0.393 0.647 0.769 0.857 0.500 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] chair : 0.618 0.750 0.802 0.771 0.730 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] storage cabinet: 0.231 0.351 0.425 0.500 0.600 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] office chair : 0.562 0.581 0.597 0.711 0.667 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] bookshelf : 0.125 0.360 0.627 0.529 0.818 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] whiteboard : 0.569 0.749 0.777 0.833 0.714 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] window : 0.138 0.357 0.634 0.576 0.418 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] box : 0.170 0.316 0.523 0.561 0.354 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] monitor : 0.609 0.748 0.804 0.897 0.743 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] shelf : 0.180 0.365 0.470 1.000 0.300 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] heater : 0.476 0.774 0.860 0.938 0.789 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] kitchen cabinet: 0.155 0.425 0.632 0.667 0.480 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] sofa : 0.420 0.532 0.750 0.727 0.667 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] bed : 0.129 0.338 0.619 0.571 0.500 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] trash can : 0.497 0.646 0.674 0.865 0.692 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] book : 0.021 0.040 0.075 0.232 0.086 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] plant : 0.421 0.612 0.795 0.917 0.611 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] blanket : 0.495 0.691 0.769 0.875 0.636 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] tv : 0.948 1.000 1.000 1.000 1.000 [2025-04-29 17:43:12,264 INFO hook.py line 395 1619929] computer tower : 0.281 0.479 0.675 0.733 0.524 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] refrigerator : 0.262 0.518 0.541 1.000 0.333 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] jacket : 0.106 0.362 0.523 0.800 0.364 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] sink : 0.429 0.673 0.766 0.762 0.727 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] bag : 0.125 0.179 0.214 0.667 0.222 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] picture : 0.147 0.303 0.401 0.700 0.359 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] pillow : 0.649 0.897 0.897 0.655 1.000 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] towel : 0.186 0.298 0.526 0.378 0.368 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] suitcase : 0.432 0.495 0.505 1.000 0.429 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] backpack : 0.448 0.606 0.606 0.889 0.615 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] crate : 0.045 0.195 0.423 0.667 0.364 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] keyboard : 0.485 0.665 0.736 0.862 0.641 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] toilet : 0.864 0.889 1.000 1.000 0.889 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] printer : 0.582 0.649 0.649 0.857 0.667 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] poster : 0.001 0.003 0.004 0.053 0.111 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] microwave : 0.599 0.683 0.985 0.833 0.625 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] shoes : 0.121 0.189 0.529 0.500 0.268 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] socket : 0.187 0.427 0.617 0.721 0.443 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] bottle : 0.167 0.229 0.374 0.480 0.289 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] bucket : 0.094 0.119 0.122 0.222 0.571 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] cushion : 0.077 0.094 0.173 0.167 0.833 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] basket : 0.001 0.012 0.012 0.167 0.143 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] telephone : 0.293 0.614 0.644 0.909 0.588 [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 17:43:12,265 INFO hook.py line 395 1619929] laptop : 0.385 0.592 0.595 0.545 0.750 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] plant pot : 0.100 0.278 0.365 0.583 0.438 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] exhaust fan : 0.215 0.390 0.390 0.857 0.400 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] cup : 0.216 0.359 0.406 0.882 0.341 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] coat hanger : 0.275 0.750 0.750 1.000 0.750 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] light switch : 0.240 0.484 0.656 0.795 0.477 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] speaker : 0.346 0.366 0.443 0.571 0.364 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.792 1.000 0.500 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] kettle : 0.241 0.333 0.333 1.000 0.333 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] smoke detector : 0.636 0.790 0.790 0.950 0.792 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] power strip : 0.067 0.137 0.192 0.444 0.400 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] paper bag : 0.066 0.071 0.083 0.143 1.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] mouse : 0.486 0.741 0.787 0.786 0.688 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] cutting board : 0.035 0.062 0.062 0.500 0.250 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] toilet paper : 0.255 0.389 0.404 0.778 0.412 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] paper towel : 0.015 0.031 0.031 0.500 0.125 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] clock : 0.556 1.000 1.000 1.000 1.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] tap : 0.228 0.417 0.667 0.800 0.444 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] soap dispenser : 0.404 0.600 0.648 1.000 0.600 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] bowl : 0.064 0.083 0.083 0.500 0.333 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] whiteboard eraser: 0.150 0.386 0.386 0.800 0.667 [2025-04-29 17:43:12,266 INFO hook.py line 395 1619929] toilet brush : 0.424 0.667 0.833 1.000 0.667 [2025-04-29 17:43:12,267 INFO hook.py line 395 1619929] spray bottle : 0.014 0.018 0.018 0.143 0.250 [2025-04-29 17:43:12,267 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 17:43:12,267 INFO hook.py line 395 1619929] stapler : 0.006 0.028 0.178 0.167 0.333 [2025-04-29 17:43:12,267 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 17:43:12,267 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 17:43:12,267 INFO hook.py line 404 1619929] average : 0.270 0.412 0.495 0.628 0.484 [2025-04-29 17:43:12,267 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 17:43:12,267 INFO hook.py line 480 1619929] Total Process Time: 24.759 s [2025-04-29 17:43:12,267 INFO hook.py line 481 1619929] Average Process Time: 495.723 ms [2025-04-29 17:43:12,267 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 17:43:12,303 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 17:43:12,308 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:44:38,478 INFO hook.py line 650 1619929] Train: [369/512][50/242] Data 0.017 (0.017) Batch 1.485 (1.433) Remain 13:50:48 loss: 4.3623 Lr: 9.57611e-05 Mem R(MA/MR): 22276 (21268/36182) [2025-04-29 17:45:53,400 INFO hook.py line 650 1619929] Train: [369/512][100/242] Data 0.016 (0.017) Batch 1.470 (1.467) Remain 14:09:18 loss: 5.2377 Lr: 9.56374e-05 Mem R(MA/MR): 25050 (21268/36182) [2025-04-29 17:47:04,515 INFO hook.py line 650 1619929] Train: [369/512][150/242] Data 0.015 (0.017) Batch 1.414 (1.451) Remain 13:59:23 loss: 4.4081 Lr: 9.55137e-05 Mem R(MA/MR): 25050 (21268/36182) [2025-04-29 17:48:16,907 INFO hook.py line 650 1619929] Train: [369/512][200/242] Data 0.015 (0.022) Batch 1.455 (1.451) Remain 13:57:38 loss: 5.3561 Lr: 9.53900e-05 Mem R(MA/MR): 25050 (21268/36182) [2025-04-29 17:49:15,562 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2705 loss_mask: 0.0330 loss_dice: 1.8647 loss_score: 0.0000 loss_bbox: 0.0482 loss_sp_cls: 0.7397 loss: 4.7520 [2025-04-29 17:49:15,667 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:50:53,306 INFO hook.py line 650 1619929] Train: [370/512][50/242] Data 0.015 (0.017) Batch 1.286 (1.561) Remain 14:59:16 loss: 4.0790 Lr: 9.51622e-05 Mem R(MA/MR): 22946 (21268/36182) [2025-04-29 17:52:03,225 INFO hook.py line 650 1619929] Train: [370/512][100/242] Data 0.017 (0.016) Batch 1.448 (1.477) Remain 14:09:38 loss: 3.7306 Lr: 9.50384e-05 Mem R(MA/MR): 27766 (21268/36182) [2025-04-29 17:53:13,218 INFO hook.py line 650 1619929] Train: [370/512][150/242] Data 0.016 (0.017) Batch 1.427 (1.451) Remain 13:53:16 loss: 5.6098 Lr: 9.49146e-05 Mem R(MA/MR): 27766 (21268/36182) [2025-04-29 17:54:24,646 INFO hook.py line 650 1619929] Train: [370/512][200/242] Data 0.014 (0.016) Batch 1.313 (1.445) Remain 13:48:47 loss: 4.7631 Lr: 9.47933e-05 Mem R(MA/MR): 27770 (21268/36182) [2025-04-29 17:55:22,970 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2662 loss_mask: 0.0331 loss_dice: 1.8594 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7327 loss: 4.7217 [2025-04-29 17:55:23,040 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 17:56:49,911 INFO hook.py line 650 1619929] Train: [371/512][50/242] Data 0.016 (0.017) Batch 1.379 (1.482) Remain 14:07:18 loss: 4.5559 Lr: 9.45654e-05 Mem R(MA/MR): 19098 (21268/36182) [2025-04-29 17:58:02,628 INFO hook.py line 650 1619929] Train: [371/512][100/242] Data 0.019 (0.017) Batch 1.496 (1.468) Remain 13:58:03 loss: 4.2784 Lr: 9.44415e-05 Mem R(MA/MR): 20630 (21268/36182) [2025-04-29 17:59:14,179 INFO hook.py line 650 1619929] Train: [371/512][150/242] Data 0.016 (0.017) Batch 1.396 (1.455) Remain 13:49:45 loss: 5.5311 Lr: 9.43176e-05 Mem R(MA/MR): 23976 (21268/36182) [2025-04-29 18:00:24,666 INFO hook.py line 650 1619929] Train: [371/512][200/242] Data 0.016 (0.017) Batch 1.411 (1.444) Remain 13:41:59 loss: 3.8150 Lr: 9.41937e-05 Mem R(MA/MR): 25846 (21268/36182) [2025-04-29 18:01:22,120 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2782 loss_mask: 0.0347 loss_dice: 1.8804 loss_score: 0.0000 loss_bbox: 0.0486 loss_sp_cls: 0.7410 loss: 4.8013 [2025-04-29 18:01:24,525 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:03:00,876 INFO hook.py line 650 1619929] Train: [372/512][50/242] Data 0.016 (0.017) Batch 1.452 (1.501) Remain 14:12:17 loss: 5.1525 Lr: 9.39657e-05 Mem R(MA/MR): 22208 (21268/36182) [2025-04-29 18:04:13,174 INFO hook.py line 650 1619929] Train: [372/512][100/242] Data 0.017 (0.017) Batch 1.501 (1.473) Remain 13:54:59 loss: 4.4243 Lr: 9.38417e-05 Mem R(MA/MR): 22208 (21268/36182) [2025-04-29 18:05:23,646 INFO hook.py line 650 1619929] Train: [372/512][150/242] Data 0.015 (0.017) Batch 1.426 (1.451) Remain 13:41:36 loss: 4.8210 Lr: 9.37177e-05 Mem R(MA/MR): 22212 (21268/36182) [2025-04-29 18:06:35,610 INFO hook.py line 650 1619929] Train: [372/512][200/242] Data 0.015 (0.017) Batch 1.438 (1.448) Remain 13:38:42 loss: 4.7143 Lr: 9.35937e-05 Mem R(MA/MR): 22212 (21268/36182) [2025-04-29 18:07:34,401 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2799 loss_mask: 0.0344 loss_dice: 1.8902 loss_score: 0.0000 loss_bbox: 0.0487 loss_sp_cls: 0.7468 loss: 4.8244 [2025-04-29 18:07:34,470 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:09:10,090 INFO hook.py line 650 1619929] Train: [373/512][50/242] Data 0.015 (0.018) Batch 1.590 (1.492) Remain 14:01:14 loss: 5.4529 Lr: 9.33655e-05 Mem R(MA/MR): 21556 (21268/36182) [2025-04-29 18:10:22,180 INFO hook.py line 650 1619929] Train: [373/512][100/242] Data 0.019 (0.017) Batch 1.548 (1.466) Remain 13:45:25 loss: 5.2844 Lr: 9.32415e-05 Mem R(MA/MR): 21558 (21268/36182) [2025-04-29 18:11:33,962 INFO hook.py line 650 1619929] Train: [373/512][150/242] Data 0.017 (0.017) Batch 1.328 (1.456) Remain 13:38:22 loss: 4.0399 Lr: 9.31174e-05 Mem R(MA/MR): 22208 (21268/36182) [2025-04-29 18:12:46,833 INFO hook.py line 650 1619929] Train: [373/512][200/242] Data 0.015 (0.016) Batch 1.390 (1.456) Remain 13:37:24 loss: 5.5248 Lr: 9.29933e-05 Mem R(MA/MR): 22220 (21268/36182) [2025-04-29 18:13:45,518 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2794 loss_mask: 0.0349 loss_dice: 1.8873 loss_score: 0.0000 loss_bbox: 0.0486 loss_sp_cls: 0.7445 loss: 4.8243 [2025-04-29 18:13:45,600 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:15:16,929 INFO hook.py line 650 1619929] Train: [374/512][50/242] Data 0.015 (0.017) Batch 1.376 (1.479) Remain 13:48:06 loss: 5.5080 Lr: 9.27649e-05 Mem R(MA/MR): 22110 (21268/36182) [2025-04-29 18:16:29,340 INFO hook.py line 650 1619929] Train: [374/512][100/242] Data 0.015 (0.017) Batch 1.352 (1.463) Remain 13:37:55 loss: 4.5384 Lr: 9.26408e-05 Mem R(MA/MR): 23710 (21268/36182) [2025-04-29 18:17:40,662 INFO hook.py line 650 1619929] Train: [374/512][150/242] Data 0.016 (0.017) Batch 1.480 (1.451) Remain 13:29:42 loss: 4.7182 Lr: 9.25166e-05 Mem R(MA/MR): 27824 (21268/36182) [2025-04-29 18:18:53,117 INFO hook.py line 650 1619929] Train: [374/512][200/242] Data 0.013 (0.017) Batch 1.465 (1.450) Remain 13:28:16 loss: 4.7093 Lr: 9.23925e-05 Mem R(MA/MR): 27824 (21268/36182) [2025-04-29 18:19:52,684 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2807 loss_mask: 0.0343 loss_dice: 1.8972 loss_score: 0.0000 loss_bbox: 0.0485 loss_sp_cls: 0.7472 loss: 4.8364 [2025-04-29 18:19:55,107 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:21:25,270 INFO hook.py line 650 1619929] Train: [375/512][50/242] Data 0.017 (0.017) Batch 1.364 (1.494) Remain 13:50:27 loss: 4.2164 Lr: 9.21639e-05 Mem R(MA/MR): 22854 (21268/36182) [2025-04-29 18:22:38,895 INFO hook.py line 650 1619929] Train: [375/512][100/242] Data 0.017 (0.017) Batch 1.634 (1.483) Remain 13:42:59 loss: 4.3630 Lr: 9.20397e-05 Mem R(MA/MR): 25920 (21268/36182) [2025-04-29 18:23:52,557 INFO hook.py line 650 1619929] Train: [375/512][150/242] Data 0.016 (0.016) Batch 1.659 (1.480) Remain 13:39:54 loss: 4.6160 Lr: 9.19154e-05 Mem R(MA/MR): 25920 (21268/36182) [2025-04-29 18:25:05,530 INFO hook.py line 650 1619929] Train: [375/512][200/242] Data 0.015 (0.017) Batch 1.378 (1.475) Remain 13:35:49 loss: 4.7669 Lr: 9.17912e-05 Mem R(MA/MR): 25932 (21268/36182) [2025-04-29 18:26:02,263 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2764 loss_mask: 0.0333 loss_dice: 1.8920 loss_score: 0.0000 loss_bbox: 0.0487 loss_sp_cls: 0.7413 loss: 4.8124 [2025-04-29 18:26:04,277 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:27:38,644 INFO hook.py line 650 1619929] Train: [376/512][50/242] Data 0.016 (0.016) Batch 1.425 (1.465) Remain 13:28:27 loss: 5.3431 Lr: 9.15625e-05 Mem R(MA/MR): 24560 (21268/36182) [2025-04-29 18:28:49,301 INFO hook.py line 650 1619929] Train: [376/512][100/242] Data 0.016 (0.016) Batch 1.389 (1.438) Remain 13:12:25 loss: 4.6746 Lr: 9.14382e-05 Mem R(MA/MR): 26220 (21268/36182) [2025-04-29 18:30:00,368 INFO hook.py line 650 1619929] Train: [376/512][150/242] Data 0.016 (0.017) Batch 1.407 (1.433) Remain 13:08:01 loss: 4.6607 Lr: 9.13138e-05 Mem R(MA/MR): 27940 (21268/36182) [2025-04-29 18:31:13,184 INFO hook.py line 650 1619929] Train: [376/512][200/242] Data 0.013 (0.017) Batch 1.315 (1.439) Remain 13:10:08 loss: 4.6137 Lr: 9.11895e-05 Mem R(MA/MR): 30604 (21268/36182) [2025-04-29 18:32:12,395 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2734 loss_mask: 0.0339 loss_dice: 1.8790 loss_score: 0.0000 loss_bbox: 0.0487 loss_sp_cls: 0.7433 loss: 4.7833 [2025-04-29 18:32:14,769 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 18:32:17,234 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2181 Process Time: 0.388 Mem R(MA/MR): 4248 (21268/36182) [2025-04-29 18:32:19,023 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6440 Process Time: 0.667 Mem R(MA/MR): 7112 (21268/36182) [2025-04-29 18:32:20,793 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.6420 Process Time: 0.745 Mem R(MA/MR): 9570 (21268/36182) [2025-04-29 18:32:28,547 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.5078 Process Time: 1.239 Mem R(MA/MR): 20028 (21268/36182) [2025-04-29 18:32:29,405 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.8188 Process Time: 0.283 Mem R(MA/MR): 6964 (21268/36182) [2025-04-29 18:32:30,733 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6675 Process Time: 0.324 Mem R(MA/MR): 11202 (21268/36182) [2025-04-29 18:32:31,285 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.2321 Process Time: 0.196 Mem R(MA/MR): 6198 (21268/36182) [2025-04-29 18:32:31,913 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.6208 Process Time: 0.206 Mem R(MA/MR): 4300 (21268/36182) [2025-04-29 18:32:32,821 INFO hook.py line 449 1619929] Test: [9/50] Loss 4.0591 Process Time: 0.262 Mem R(MA/MR): 11336 (21268/36182) [2025-04-29 18:32:34,321 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7781 Process Time: 0.379 Mem R(MA/MR): 9348 (21268/36182) [2025-04-29 18:32:37,002 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.4862 Process Time: 0.644 Mem R(MA/MR): 18728 (21268/36182) [2025-04-29 18:32:39,941 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.4780 Process Time: 0.984 Mem R(MA/MR): 15548 (21268/36182) [2025-04-29 18:32:41,046 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.9267 Process Time: 0.258 Mem R(MA/MR): 8564 (21268/36182) [2025-04-29 18:32:41,353 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2620 Process Time: 0.110 Mem R(MA/MR): 4608 (21268/36182) [2025-04-29 18:32:44,102 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.1671 Process Time: 0.416 Mem R(MA/MR): 16634 (21268/36182) [2025-04-29 18:32:45,999 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4929 Process Time: 0.625 Mem R(MA/MR): 14536 (21268/36182) [2025-04-29 18:32:46,762 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1352 Process Time: 0.267 Mem R(MA/MR): 6594 (21268/36182) [2025-04-29 18:32:47,570 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.5818 Process Time: 0.211 Mem R(MA/MR): 8100 (21268/36182) [2025-04-29 18:32:48,897 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5054 Process Time: 0.179 Mem R(MA/MR): 5988 (21268/36182) [2025-04-29 18:32:50,463 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.6857 Process Time: 0.293 Mem R(MA/MR): 11378 (21268/36182) [2025-04-29 18:32:59,510 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.2177 Process Time: 1.193 Mem R(MA/MR): 24022 (21268/36182) [2025-04-29 18:33:00,851 INFO hook.py line 449 1619929] Test: [22/50] Loss 6.0485 Process Time: 0.628 Mem R(MA/MR): 6768 (21268/36182) [2025-04-29 18:33:12,234 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.6227 Process Time: 0.763 Mem R(MA/MR): 10104 (21268/36182) [2025-04-29 18:33:12,880 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.5014 Process Time: 0.257 Mem R(MA/MR): 5268 (21268/36182) [2025-04-29 18:33:13,861 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9853 Process Time: 0.246 Mem R(MA/MR): 9118 (21268/36182) [2025-04-29 18:33:20,515 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.2325 Process Time: 0.958 Mem R(MA/MR): 31780 (21268/36182) [2025-04-29 18:33:22,653 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.6920 Process Time: 0.343 Mem R(MA/MR): 9802 (21268/36182) [2025-04-29 18:33:23,708 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0966 Process Time: 0.195 Mem R(MA/MR): 8724 (21268/36182) [2025-04-29 18:33:28,967 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.3723 Process Time: 0.541 Mem R(MA/MR): 17212 (21268/36182) [2025-04-29 18:33:29,880 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2721 Process Time: 0.254 Mem R(MA/MR): 7614 (21268/36182) [2025-04-29 18:33:33,426 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.0679 Process Time: 0.410 Mem R(MA/MR): 20510 (21268/36182) [2025-04-29 18:33:33,855 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3820 Process Time: 0.229 Mem R(MA/MR): 4088 (21268/36182) [2025-04-29 18:33:38,248 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.5331 Process Time: 0.680 Mem R(MA/MR): 24790 (21268/36182) [2025-04-29 18:33:39,291 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.8383 Process Time: 0.337 Mem R(MA/MR): 9772 (21268/36182) [2025-04-29 18:33:41,238 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.9818 Process Time: 0.430 Mem R(MA/MR): 13936 (21268/36182) [2025-04-29 18:33:41,791 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.6915 Process Time: 0.217 Mem R(MA/MR): 6472 (21268/36182) [2025-04-29 18:33:45,275 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.2240 Process Time: 0.585 Mem R(MA/MR): 28526 (21268/36182) [2025-04-29 18:33:47,122 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5803 Process Time: 0.414 Mem R(MA/MR): 10660 (21268/36182) [2025-04-29 18:33:47,755 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.7509 Process Time: 0.268 Mem R(MA/MR): 5410 (21268/36182) [2025-04-29 18:33:48,794 INFO hook.py line 449 1619929] Test: [40/50] Loss 4.1061 Process Time: 0.283 Mem R(MA/MR): 9996 (21268/36182) [2025-04-29 18:33:49,726 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.9860 Process Time: 0.282 Mem R(MA/MR): 8738 (21268/36182) [2025-04-29 18:33:50,143 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.3668 Process Time: 0.127 Mem R(MA/MR): 5386 (21268/36182) [2025-04-29 18:33:50,639 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6932 Process Time: 0.199 Mem R(MA/MR): 5474 (21268/36182) [2025-04-29 18:33:51,653 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.0436 Process Time: 0.428 Mem R(MA/MR): 7008 (21268/36182) [2025-04-29 18:33:52,517 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.2640 Process Time: 0.313 Mem R(MA/MR): 5124 (21268/36182) [2025-04-29 18:33:55,106 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.6545 Process Time: 0.569 Mem R(MA/MR): 14444 (21268/36182) [2025-04-29 18:34:02,803 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.8181 Process Time: 0.969 Mem R(MA/MR): 20402 (21268/36182) [2025-04-29 18:34:14,134 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.4774 Process Time: 1.882 Mem R(MA/MR): 35904 (21268/36182) [2025-04-29 18:34:14,685 INFO hook.py line 449 1619929] Test: [49/50] Loss 4.3175 Process Time: 0.140 Mem R(MA/MR): 5582 (21268/36182) [2025-04-29 18:34:16,851 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2030 Process Time: 0.289 Mem R(MA/MR): 13526 (21268/36182) [2025-04-29 18:34:21,768 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 18:34:21,768 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 18:34:21,768 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] table : 0.284 0.589 0.743 0.745 0.603 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] door : 0.435 0.713 0.853 0.889 0.709 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] ceiling lamp : 0.574 0.776 0.877 0.899 0.740 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] cabinet : 0.341 0.486 0.544 0.506 0.612 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] blinds : 0.539 0.729 0.774 0.750 0.783 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] curtain : 0.341 0.513 0.682 0.571 0.667 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] chair : 0.705 0.828 0.868 0.830 0.783 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] storage cabinet: 0.187 0.299 0.484 0.483 0.560 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] office chair : 0.648 0.678 0.706 0.717 0.792 [2025-04-29 18:34:21,768 INFO hook.py line 395 1619929] bookshelf : 0.259 0.522 0.699 0.750 0.545 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] whiteboard : 0.553 0.722 0.735 0.960 0.686 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] window : 0.088 0.234 0.582 0.396 0.418 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] box : 0.215 0.372 0.508 0.474 0.453 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] monitor : 0.615 0.793 0.849 0.902 0.786 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] shelf : 0.123 0.263 0.432 0.529 0.300 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] heater : 0.465 0.684 0.794 0.784 0.763 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] kitchen cabinet: 0.169 0.336 0.611 0.542 0.520 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] sofa : 0.449 0.698 0.813 0.750 0.750 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] bed : 0.265 0.586 0.827 1.000 0.500 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] trash can : 0.503 0.649 0.696 0.790 0.754 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] book : 0.015 0.028 0.072 0.152 0.101 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] plant : 0.409 0.633 0.633 0.867 0.722 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] blanket : 0.558 0.690 0.693 0.875 0.636 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] tv : 0.880 1.000 1.000 1.000 1.000 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] computer tower : 0.252 0.418 0.656 0.576 0.452 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] refrigerator : 0.216 0.404 0.404 0.667 0.444 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] jacket : 0.166 0.338 0.525 0.333 0.818 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] sink : 0.455 0.757 0.921 0.900 0.818 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] bag : 0.111 0.172 0.225 0.571 0.296 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] picture : 0.123 0.310 0.364 0.517 0.385 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] pillow : 0.571 0.830 0.855 1.000 0.684 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] towel : 0.199 0.367 0.547 0.459 0.447 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] suitcase : 0.524 0.571 0.571 1.000 0.571 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] backpack : 0.367 0.519 0.519 0.857 0.462 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] crate : 0.055 0.261 0.438 0.625 0.455 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] keyboard : 0.492 0.695 0.779 0.844 0.692 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] toilet : 0.875 0.889 1.000 1.000 0.889 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] printer : 0.242 0.474 0.520 0.600 0.667 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] poster : 0.001 0.011 0.014 0.083 0.222 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,769 INFO hook.py line 395 1619929] microwave : 0.453 0.625 0.875 1.000 0.625 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] shoes : 0.138 0.217 0.407 0.600 0.293 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] socket : 0.175 0.414 0.635 0.626 0.514 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] bottle : 0.120 0.197 0.285 0.322 0.337 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] bucket : 0.043 0.045 0.047 0.130 0.429 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] cushion : 0.052 0.103 0.230 0.235 0.667 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] basket : 0.004 0.014 0.018 0.200 0.143 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 1.000 1.000 0.500 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] telephone : 0.308 0.600 0.675 0.900 0.529 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] laptop : 0.436 0.700 0.760 0.538 0.875 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] plant pot : 0.141 0.258 0.404 0.444 0.500 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] exhaust fan : 0.186 0.333 0.333 1.000 0.333 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] cup : 0.242 0.402 0.438 1.000 0.364 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] coat hanger : 0.278 0.750 0.750 1.000 0.750 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] light switch : 0.240 0.491 0.700 0.655 0.554 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] speaker : 0.334 0.372 0.372 0.600 0.545 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] table lamp : 0.449 0.500 0.500 1.000 0.500 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] smoke detector : 0.677 0.856 0.859 0.840 0.875 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] power strip : 0.054 0.073 0.080 0.400 0.200 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] paper bag : 0.250 0.250 0.250 0.500 1.000 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] mouse : 0.439 0.640 0.694 0.909 0.625 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] cutting board : 0.333 0.500 0.500 1.000 0.500 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] toilet paper : 0.220 0.368 0.430 0.750 0.353 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] paper towel : 0.125 0.125 0.125 1.000 0.125 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] clock : 0.370 0.422 0.442 1.000 0.333 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] tap : 0.118 0.222 0.341 0.500 0.333 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] soap dispenser : 0.390 0.571 0.576 0.600 0.600 [2025-04-29 18:34:21,770 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] bowl : 0.296 0.333 0.528 1.000 0.333 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] tissue box : 0.035 0.083 0.125 0.333 0.500 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] whiteboard eraser: 0.272 0.522 0.522 0.833 0.833 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] toilet brush : 0.409 0.667 0.833 1.000 0.667 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] spray bottle : 0.012 0.016 0.016 0.125 0.250 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] stapler : 0.003 0.015 0.070 0.091 0.333 [2025-04-29 18:34:21,771 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 18:34:21,771 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 18:34:21,771 INFO hook.py line 404 1619929] average : 0.273 0.411 0.491 0.626 0.494 [2025-04-29 18:34:21,771 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 18:34:21,771 INFO hook.py line 480 1619929] Total Process Time: 23.108 s [2025-04-29 18:34:21,771 INFO hook.py line 481 1619929] Average Process Time: 463.680 ms [2025-04-29 18:34:21,771 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 18:34:21,801 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 18:34:21,805 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:36:00,096 INFO hook.py line 650 1619929] Train: [377/512][50/242] Data 0.021 (0.017) Batch 1.576 (1.541) Remain 14:04:03 loss: 4.5986 Lr: 9.09606e-05 Mem R(MA/MR): 21782 (21268/36182) [2025-04-29 18:37:15,219 INFO hook.py line 650 1619929] Train: [377/512][100/242] Data 0.018 (0.017) Batch 1.469 (1.521) Remain 13:51:53 loss: 5.5583 Lr: 9.08362e-05 Mem R(MA/MR): 24966 (21268/36182) [2025-04-29 18:38:27,593 INFO hook.py line 650 1619929] Train: [377/512][150/242] Data 0.016 (0.022) Batch 1.328 (1.496) Remain 13:36:55 loss: 4.0047 Lr: 9.07117e-05 Mem R(MA/MR): 24966 (21268/36182) [2025-04-29 18:39:41,930 INFO hook.py line 650 1619929] Train: [377/512][200/242] Data 0.014 (0.021) Batch 1.305 (1.494) Remain 13:34:23 loss: 4.3034 Lr: 9.05873e-05 Mem R(MA/MR): 24966 (21268/36182) [2025-04-29 18:40:38,519 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2734 loss_mask: 0.0344 loss_dice: 1.8801 loss_score: 0.0000 loss_bbox: 0.0486 loss_sp_cls: 0.7436 loss: 4.7872 [2025-04-29 18:40:41,972 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:42:18,251 INFO hook.py line 650 1619929] Train: [378/512][50/242] Data 0.015 (0.016) Batch 1.496 (1.473) Remain 13:20:36 loss: 4.8879 Lr: 9.03583e-05 Mem R(MA/MR): 24992 (21268/36182) [2025-04-29 18:43:30,349 INFO hook.py line 650 1619929] Train: [378/512][100/242] Data 0.016 (0.017) Batch 1.463 (1.457) Remain 13:10:47 loss: 5.6198 Lr: 9.02338e-05 Mem R(MA/MR): 24996 (21268/36182) [2025-04-29 18:44:43,707 INFO hook.py line 650 1619929] Train: [378/512][150/242] Data 0.016 (0.017) Batch 1.463 (1.460) Remain 13:11:29 loss: 5.4947 Lr: 9.01092e-05 Mem R(MA/MR): 28464 (21268/36182) [2025-04-29 18:45:56,225 INFO hook.py line 650 1619929] Train: [378/512][200/242] Data 0.016 (0.017) Batch 1.513 (1.458) Remain 13:08:54 loss: 4.2256 Lr: 8.99847e-05 Mem R(MA/MR): 30338 (21268/36182) [2025-04-29 18:46:52,434 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2705 loss_mask: 0.0338 loss_dice: 1.8783 loss_score: 0.0000 loss_bbox: 0.0484 loss_sp_cls: 0.7405 loss: 4.7754 [2025-04-29 18:46:52,810 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:48:25,907 INFO hook.py line 650 1619929] Train: [379/512][50/242] Data 0.016 (0.017) Batch 1.610 (1.466) Remain 13:11:02 loss: 4.7799 Lr: 8.97555e-05 Mem R(MA/MR): 24954 (21268/36182) [2025-04-29 18:49:38,638 INFO hook.py line 650 1619929] Train: [379/512][100/242] Data 0.015 (0.017) Batch 1.365 (1.460) Remain 13:06:41 loss: 4.7093 Lr: 8.96309e-05 Mem R(MA/MR): 27034 (21268/36182) [2025-04-29 18:50:47,964 INFO hook.py line 650 1619929] Train: [379/512][150/242] Data 0.020 (0.016) Batch 1.295 (1.435) Remain 12:52:00 loss: 4.3869 Lr: 8.95088e-05 Mem R(MA/MR): 27034 (21268/36182) [2025-04-29 18:51:58,882 INFO hook.py line 650 1619929] Train: [379/512][200/242] Data 0.016 (0.016) Batch 1.549 (1.431) Remain 12:48:32 loss: 5.7689 Lr: 8.93841e-05 Mem R(MA/MR): 27034 (21268/36182) [2025-04-29 18:52:57,250 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2693 loss_mask: 0.0335 loss_dice: 1.8473 loss_score: 0.0000 loss_bbox: 0.0483 loss_sp_cls: 0.7401 loss: 4.7194 [2025-04-29 18:53:02,326 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 18:54:27,588 INFO hook.py line 650 1619929] Train: [380/512][50/242] Data 0.016 (0.017) Batch 1.377 (1.450) Remain 12:56:39 loss: 5.9276 Lr: 8.91547e-05 Mem R(MA/MR): 19666 (21268/36182) [2025-04-29 18:55:40,750 INFO hook.py line 650 1619929] Train: [380/512][100/242] Data 0.016 (0.016) Batch 1.424 (1.457) Remain 12:59:04 loss: 4.8301 Lr: 8.90301e-05 Mem R(MA/MR): 23080 (21268/36182) [2025-04-29 18:56:53,616 INFO hook.py line 650 1619929] Train: [380/512][150/242] Data 0.017 (0.016) Batch 1.468 (1.457) Remain 12:57:56 loss: 5.3632 Lr: 8.89053e-05 Mem R(MA/MR): 23080 (21268/36182) [2025-04-29 18:58:05,151 INFO hook.py line 650 1619929] Train: [380/512][200/242] Data 0.017 (0.016) Batch 1.523 (1.450) Remain 12:53:10 loss: 5.2525 Lr: 8.87806e-05 Mem R(MA/MR): 23092 (21268/36182) [2025-04-29 18:59:03,871 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2734 loss_mask: 0.0337 loss_dice: 1.8753 loss_score: 0.0000 loss_bbox: 0.0485 loss_sp_cls: 0.7394 loss: 4.7809 [2025-04-29 18:59:05,586 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:00:33,908 INFO hook.py line 650 1619929] Train: [381/512][50/242] Data 0.016 (0.017) Batch 1.595 (1.490) Remain 13:11:54 loss: 6.0013 Lr: 8.85511e-05 Mem R(MA/MR): 26394 (21268/36182) [2025-04-29 19:01:44,941 INFO hook.py line 650 1619929] Train: [381/512][100/242] Data 0.015 (0.016) Batch 1.503 (1.454) Remain 12:51:42 loss: 4.4560 Lr: 8.84263e-05 Mem R(MA/MR): 26410 (21268/36182) [2025-04-29 19:02:57,448 INFO hook.py line 650 1619929] Train: [381/512][150/242] Data 0.015 (0.016) Batch 1.436 (1.453) Remain 12:49:48 loss: 3.9975 Lr: 8.83015e-05 Mem R(MA/MR): 26410 (21268/36182) [2025-04-29 19:04:09,241 INFO hook.py line 650 1619929] Train: [381/512][200/242] Data 0.014 (0.016) Batch 1.332 (1.448) Remain 12:46:20 loss: 4.4617 Lr: 8.81767e-05 Mem R(MA/MR): 26410 (21268/36182) [2025-04-29 19:05:05,608 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2733 loss_mask: 0.0337 loss_dice: 1.8723 loss_score: 0.0000 loss_bbox: 0.0484 loss_sp_cls: 0.7406 loss: 4.7700 [2025-04-29 19:05:06,587 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:06:41,382 INFO hook.py line 650 1619929] Train: [382/512][50/242] Data 0.017 (0.017) Batch 1.439 (1.516) Remain 13:19:51 loss: 4.7296 Lr: 8.79469e-05 Mem R(MA/MR): 22606 (21268/36182) [2025-04-29 19:07:54,249 INFO hook.py line 650 1619929] Train: [382/512][100/242] Data 0.025 (0.017) Batch 1.595 (1.486) Remain 13:02:36 loss: 4.6060 Lr: 8.78220e-05 Mem R(MA/MR): 22606 (21268/36182) [2025-04-29 19:09:06,630 INFO hook.py line 650 1619929] Train: [382/512][150/242] Data 0.015 (0.017) Batch 1.530 (1.473) Remain 12:54:31 loss: 4.8698 Lr: 8.76971e-05 Mem R(MA/MR): 22606 (21268/36182) [2025-04-29 19:10:18,530 INFO hook.py line 650 1619929] Train: [382/512][200/242] Data 0.015 (0.017) Batch 1.439 (1.464) Remain 12:48:39 loss: 6.0439 Lr: 8.75722e-05 Mem R(MA/MR): 22606 (21268/36182) [2025-04-29 19:11:15,562 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2669 loss_mask: 0.0334 loss_dice: 1.8604 loss_score: 0.0000 loss_bbox: 0.0486 loss_sp_cls: 0.7345 loss: 4.7335 [2025-04-29 19:11:20,166 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:12:55,062 INFO hook.py line 650 1619929] Train: [383/512][50/242] Data 0.016 (0.016) Batch 1.519 (1.433) Remain 12:30:23 loss: 3.6299 Lr: 8.73423e-05 Mem R(MA/MR): 23106 (21268/36182) [2025-04-29 19:14:06,341 INFO hook.py line 650 1619929] Train: [383/512][100/242] Data 0.017 (0.016) Batch 1.533 (1.429) Remain 12:27:04 loss: 4.6834 Lr: 8.72173e-05 Mem R(MA/MR): 24784 (21268/36182) [2025-04-29 19:15:17,531 INFO hook.py line 650 1619929] Train: [383/512][150/242] Data 0.016 (0.016) Batch 1.445 (1.427) Remain 12:24:54 loss: 4.2274 Lr: 8.70924e-05 Mem R(MA/MR): 26708 (21268/36182) [2025-04-29 19:16:29,307 INFO hook.py line 650 1619929] Train: [383/512][200/242] Data 0.016 (0.016) Batch 1.412 (1.430) Remain 12:24:46 loss: 4.1115 Lr: 8.69673e-05 Mem R(MA/MR): 29170 (21268/36182) [2025-04-29 19:17:26,812 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2682 loss_mask: 0.0337 loss_dice: 1.8452 loss_score: 0.0000 loss_bbox: 0.0485 loss_sp_cls: 0.7303 loss: 4.7142 [2025-04-29 19:17:28,369 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:19:03,339 INFO hook.py line 650 1619929] Train: [384/512][50/242] Data 0.016 (0.016) Batch 1.394 (1.445) Remain 12:30:52 loss: 4.5175 Lr: 8.67373e-05 Mem R(MA/MR): 21952 (21268/36182) [2025-04-29 19:20:14,878 INFO hook.py line 650 1619929] Train: [384/512][100/242] Data 0.017 (0.017) Batch 1.392 (1.438) Remain 12:25:44 loss: 5.4193 Lr: 8.66122e-05 Mem R(MA/MR): 23962 (21268/36182) [2025-04-29 19:21:28,499 INFO hook.py line 650 1619929] Train: [384/512][150/242] Data 0.018 (0.017) Batch 1.449 (1.450) Remain 12:30:37 loss: 5.9546 Lr: 8.64871e-05 Mem R(MA/MR): 23968 (21268/36182) [2025-04-29 19:22:40,211 INFO hook.py line 650 1619929] Train: [384/512][200/242] Data 0.014 (0.017) Batch 1.342 (1.446) Remain 12:27:24 loss: 4.5317 Lr: 8.63620e-05 Mem R(MA/MR): 23968 (21268/36182) [2025-04-29 19:23:38,257 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2678 loss_mask: 0.0335 loss_dice: 1.8548 loss_score: 0.0000 loss_bbox: 0.0484 loss_sp_cls: 0.7339 loss: 4.7201 [2025-04-29 19:23:40,564 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 19:23:43,306 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0761 Process Time: 0.617 Mem R(MA/MR): 4488 (21268/36182) [2025-04-29 19:23:45,206 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.3019 Process Time: 0.789 Mem R(MA/MR): 7238 (21268/36182) [2025-04-29 19:23:46,913 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1823 Process Time: 0.631 Mem R(MA/MR): 9798 (21268/36182) [2025-04-29 19:23:53,918 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.6308 Process Time: 0.768 Mem R(MA/MR): 19726 (21268/36182) [2025-04-29 19:23:54,861 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.1977 Process Time: 0.253 Mem R(MA/MR): 7206 (21268/36182) [2025-04-29 19:23:56,378 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5309 Process Time: 0.305 Mem R(MA/MR): 11446 (21268/36182) [2025-04-29 19:23:57,177 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.9956 Process Time: 0.301 Mem R(MA/MR): 6410 (21268/36182) [2025-04-29 19:23:57,744 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3151 Process Time: 0.150 Mem R(MA/MR): 4488 (21268/36182) [2025-04-29 19:23:58,822 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.9914 Process Time: 0.289 Mem R(MA/MR): 11618 (21268/36182) [2025-04-29 19:24:00,608 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6073 Process Time: 0.345 Mem R(MA/MR): 9602 (21268/36182) [2025-04-29 19:24:03,615 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2703 Process Time: 0.519 Mem R(MA/MR): 19028 (21268/36182) [2025-04-29 19:24:06,084 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9180 Process Time: 0.366 Mem R(MA/MR): 15482 (21268/36182) [2025-04-29 19:24:07,373 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.4569 Process Time: 0.302 Mem R(MA/MR): 8738 (21268/36182) [2025-04-29 19:24:07,882 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9345 Process Time: 0.213 Mem R(MA/MR): 4780 (21268/36182) [2025-04-29 19:24:10,820 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.8781 Process Time: 0.444 Mem R(MA/MR): 16522 (21268/36182) [2025-04-29 19:24:13,003 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.9433 Process Time: 0.610 Mem R(MA/MR): 14588 (21268/36182) [2025-04-29 19:24:13,718 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1280 Process Time: 0.176 Mem R(MA/MR): 6782 (21268/36182) [2025-04-29 19:24:14,656 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7860 Process Time: 0.246 Mem R(MA/MR): 8228 (21268/36182) [2025-04-29 19:24:15,966 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.4530 Process Time: 0.205 Mem R(MA/MR): 6064 (21268/36182) [2025-04-29 19:24:17,874 INFO hook.py line 449 1619929] Test: [20/50] Loss 8.2953 Process Time: 0.529 Mem R(MA/MR): 11406 (21268/36182) [2025-04-29 19:24:28,108 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.1818 Process Time: 1.246 Mem R(MA/MR): 23822 (21268/36182) [2025-04-29 19:24:28,787 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2667 Process Time: 0.213 Mem R(MA/MR): 6902 (21268/36182) [2025-04-29 19:24:37,571 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.1831 Process Time: 0.432 Mem R(MA/MR): 8494 (21268/36182) [2025-04-29 19:24:38,076 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.5540 Process Time: 0.136 Mem R(MA/MR): 5454 (21268/36182) [2025-04-29 19:24:38,895 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9463 Process Time: 0.184 Mem R(MA/MR): 9158 (21268/36182) [2025-04-29 19:24:45,568 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.9422 Process Time: 1.197 Mem R(MA/MR): 31994 (21268/36182) [2025-04-29 19:24:47,625 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.1522 Process Time: 0.293 Mem R(MA/MR): 9904 (21268/36182) [2025-04-29 19:24:48,743 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9309 Process Time: 0.292 Mem R(MA/MR): 8924 (21268/36182) [2025-04-29 19:24:52,907 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.8772 Process Time: 0.491 Mem R(MA/MR): 17134 (21268/36182) [2025-04-29 19:24:53,904 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2888 Process Time: 0.271 Mem R(MA/MR): 7758 (21268/36182) [2025-04-29 19:24:57,469 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.3557 Process Time: 0.395 Mem R(MA/MR): 20864 (21268/36182) [2025-04-29 19:24:57,864 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.8306 Process Time: 0.160 Mem R(MA/MR): 4116 (21268/36182) [2025-04-29 19:25:02,067 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.4798 Process Time: 0.755 Mem R(MA/MR): 24822 (21268/36182) [2025-04-29 19:25:03,175 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5305 Process Time: 0.277 Mem R(MA/MR): 9844 (21268/36182) [2025-04-29 19:25:05,057 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3414 Process Time: 0.406 Mem R(MA/MR): 13920 (21268/36182) [2025-04-29 19:25:05,549 INFO hook.py line 449 1619929] Test: [36/50] Loss 6.1832 Process Time: 0.181 Mem R(MA/MR): 6684 (21268/36182) [2025-04-29 19:25:09,104 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.2334 Process Time: 0.515 Mem R(MA/MR): 28404 (21268/36182) [2025-04-29 19:25:10,997 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.3792 Process Time: 0.523 Mem R(MA/MR): 10742 (21268/36182) [2025-04-29 19:25:11,694 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.8945 Process Time: 0.264 Mem R(MA/MR): 5580 (21268/36182) [2025-04-29 19:25:12,865 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8152 Process Time: 0.344 Mem R(MA/MR): 10062 (21268/36182) [2025-04-29 19:25:13,823 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.8677 Process Time: 0.243 Mem R(MA/MR): 8854 (21268/36182) [2025-04-29 19:25:14,317 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.7593 Process Time: 0.142 Mem R(MA/MR): 5604 (21268/36182) [2025-04-29 19:25:14,866 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7660 Process Time: 0.212 Mem R(MA/MR): 5650 (21268/36182) [2025-04-29 19:25:15,838 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1956 Process Time: 0.428 Mem R(MA/MR): 7188 (21268/36182) [2025-04-29 19:25:16,649 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5532 Process Time: 0.252 Mem R(MA/MR): 5318 (21268/36182) [2025-04-29 19:25:20,425 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.7882 Process Time: 1.135 Mem R(MA/MR): 14568 (21268/36182) [2025-04-29 19:25:28,407 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.8491 Process Time: 1.146 Mem R(MA/MR): 20424 (21268/36182) [2025-04-29 19:25:40,249 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.0831 Process Time: 2.216 Mem R(MA/MR): 35692 (21268/36182) [2025-04-29 19:25:40,748 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9558 Process Time: 0.136 Mem R(MA/MR): 5684 (21268/36182) [2025-04-29 19:25:42,734 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2062 Process Time: 0.237 Mem R(MA/MR): 13514 (21268/36182) [2025-04-29 19:25:47,261 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 19:25:47,262 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 19:25:47,262 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] table : 0.302 0.614 0.797 0.746 0.647 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] door : 0.420 0.730 0.849 0.919 0.722 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] ceiling lamp : 0.550 0.739 0.847 0.839 0.746 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] cabinet : 0.354 0.513 0.558 0.633 0.567 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] blinds : 0.593 0.779 0.836 0.783 0.783 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] curtain : 0.448 0.553 0.702 0.500 0.667 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] chair : 0.605 0.726 0.766 0.760 0.713 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] storage cabinet: 0.233 0.383 0.513 0.650 0.520 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] office chair : 0.516 0.544 0.544 0.673 0.688 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] bookshelf : 0.207 0.469 0.595 0.615 0.727 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] whiteboard : 0.569 0.726 0.778 0.857 0.686 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] window : 0.093 0.254 0.596 0.547 0.319 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] box : 0.185 0.372 0.554 0.638 0.370 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] monitor : 0.613 0.799 0.837 0.915 0.771 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] shelf : 0.117 0.264 0.429 0.526 0.333 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] heater : 0.468 0.810 0.844 0.912 0.816 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] kitchen cabinet: 0.134 0.307 0.491 0.571 0.480 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] sofa : 0.434 0.617 0.975 0.667 0.667 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] bed : 0.173 0.358 0.606 0.714 0.625 [2025-04-29 19:25:47,262 INFO hook.py line 395 1619929] trash can : 0.531 0.689 0.750 0.754 0.800 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] book : 0.026 0.042 0.086 0.200 0.086 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] plant : 0.514 0.741 0.792 1.000 0.667 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] blanket : 0.597 0.693 0.719 1.000 0.636 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] tv : 0.956 1.000 1.000 1.000 1.000 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] computer tower : 0.301 0.505 0.667 0.815 0.524 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] refrigerator : 0.179 0.352 0.355 1.000 0.333 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] jacket : 0.136 0.400 0.525 0.538 0.636 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] sink : 0.425 0.668 0.838 0.875 0.636 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] bag : 0.111 0.212 0.242 0.455 0.370 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] picture : 0.150 0.307 0.384 0.667 0.359 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] pillow : 0.498 0.704 0.704 0.846 0.579 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] towel : 0.222 0.401 0.577 0.500 0.447 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] suitcase : 0.382 0.519 0.562 0.667 0.571 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] backpack : 0.417 0.520 0.581 0.778 0.538 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] crate : 0.037 0.211 0.489 0.800 0.364 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] keyboard : 0.436 0.648 0.684 0.957 0.564 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] toilet : 0.783 0.876 1.000 0.889 0.889 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] printer : 0.316 0.406 0.468 0.800 0.444 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] painting : 0.074 0.083 0.083 0.167 1.000 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] microwave : 0.505 0.680 1.000 0.857 0.750 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] shoes : 0.159 0.277 0.583 0.556 0.366 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] socket : 0.203 0.462 0.665 0.653 0.550 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] bottle : 0.128 0.205 0.323 0.458 0.265 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] bucket : 0.167 0.251 0.261 0.250 0.571 [2025-04-29 19:25:47,263 INFO hook.py line 395 1619929] cushion : 0.043 0.096 0.127 0.200 0.500 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] basket : 0.036 0.143 0.143 1.000 0.143 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] telephone : 0.356 0.605 0.714 0.714 0.588 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] laptop : 0.272 0.435 0.501 0.800 0.500 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] plant pot : 0.072 0.178 0.392 0.462 0.375 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] exhaust fan : 0.223 0.401 0.401 0.875 0.467 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] cup : 0.258 0.421 0.456 0.895 0.386 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] coat hanger : 0.158 0.412 0.750 0.429 0.750 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] light switch : 0.251 0.490 0.669 0.694 0.523 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] speaker : 0.070 0.182 0.312 0.333 0.364 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] table lamp : 0.446 0.500 0.500 1.000 0.500 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] kettle : 0.194 0.236 0.236 0.500 0.333 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] smoke detector : 0.653 0.813 0.815 0.905 0.792 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] power strip : 0.060 0.207 0.355 0.500 0.500 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] paper bag : 0.085 0.100 0.100 0.200 1.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] mouse : 0.461 0.686 0.720 0.875 0.656 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] cutting board : 0.306 0.500 0.595 1.000 0.500 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] toilet paper : 0.247 0.366 0.458 1.000 0.353 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.166 0.000 0.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] clock : 0.656 0.850 0.903 1.000 0.667 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] tap : 0.104 0.171 0.637 0.400 0.222 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-29 19:25:47,264 INFO hook.py line 395 1619929] soap dispenser : 0.479 0.707 0.707 1.000 0.600 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] bowl : 0.333 0.333 0.333 1.000 0.333 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] whiteboard eraser: 0.226 0.522 0.522 0.833 0.833 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] toilet brush : 0.366 0.629 0.803 0.800 0.667 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] spray bottle : 0.019 0.025 0.042 0.200 0.250 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] headphones : 0.344 0.662 0.662 1.000 0.500 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] stapler : 0.017 0.070 0.240 0.200 0.667 [2025-04-29 19:25:47,265 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 19:25:47,265 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 19:25:47,265 INFO hook.py line 404 1619929] average : 0.269 0.410 0.504 0.619 0.491 [2025-04-29 19:25:47,265 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 19:25:47,265 INFO hook.py line 480 1619929] Total Process Time: 22.779 s [2025-04-29 19:25:47,265 INFO hook.py line 481 1619929] Average Process Time: 452.293 ms [2025-04-29 19:25:47,265 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 19:25:47,303 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 19:25:47,308 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:27:16,884 INFO hook.py line 650 1619929] Train: [385/512][50/242] Data 0.015 (0.037) Batch 1.429 (1.509) Remain 12:58:00 loss: 4.0563 Lr: 8.61317e-05 Mem R(MA/MR): 25274 (21268/36182) [2025-04-29 19:28:29,350 INFO hook.py line 650 1619929] Train: [385/512][100/242] Data 0.015 (0.026) Batch 1.461 (1.478) Remain 12:40:48 loss: 4.2437 Lr: 8.60066e-05 Mem R(MA/MR): 25274 (21268/36182) [2025-04-29 19:29:44,568 INFO hook.py line 650 1619929] Train: [385/512][150/242] Data 0.016 (0.023) Batch 1.452 (1.487) Remain 12:44:05 loss: 6.0377 Lr: 8.58814e-05 Mem R(MA/MR): 25274 (21268/36182) [2025-04-29 19:30:55,942 INFO hook.py line 650 1619929] Train: [385/512][200/242] Data 0.016 (0.021) Batch 1.554 (1.472) Remain 12:35:04 loss: 5.5777 Lr: 8.57562e-05 Mem R(MA/MR): 25294 (21268/36182) [2025-04-29 19:31:53,224 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2714 loss_mask: 0.0335 loss_dice: 1.8644 loss_score: 0.0000 loss_bbox: 0.0477 loss_sp_cls: 0.7335 loss: 4.7445 [2025-04-29 19:31:53,791 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:33:28,318 INFO hook.py line 650 1619929] Train: [386/512][50/242] Data 0.017 (0.017) Batch 1.415 (1.474) Remain 12:33:58 loss: 4.2026 Lr: 8.55257e-05 Mem R(MA/MR): 22740 (21268/36182) [2025-04-29 19:34:40,438 INFO hook.py line 650 1619929] Train: [386/512][100/242] Data 0.017 (0.017) Batch 1.386 (1.458) Remain 12:24:20 loss: 5.1207 Lr: 8.54005e-05 Mem R(MA/MR): 22758 (21268/36182) [2025-04-29 19:35:54,104 INFO hook.py line 650 1619929] Train: [386/512][150/242] Data 0.018 (0.017) Batch 1.368 (1.463) Remain 12:25:48 loss: 3.6295 Lr: 8.52752e-05 Mem R(MA/MR): 25284 (21268/36182) [2025-04-29 19:37:05,573 INFO hook.py line 650 1619929] Train: [386/512][200/242] Data 0.016 (0.017) Batch 1.437 (1.455) Remain 12:20:13 loss: 4.8433 Lr: 8.51499e-05 Mem R(MA/MR): 25284 (21268/36182) [2025-04-29 19:38:03,473 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2674 loss_mask: 0.0335 loss_dice: 1.8411 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7355 loss: 4.6981 [2025-04-29 19:38:05,843 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:39:44,733 INFO hook.py line 650 1619929] Train: [387/512][50/242] Data 0.015 (0.017) Batch 1.427 (1.507) Remain 12:44:41 loss: 4.6742 Lr: 8.49192e-05 Mem R(MA/MR): 23210 (21268/36182) [2025-04-29 19:40:58,403 INFO hook.py line 650 1619929] Train: [387/512][100/242] Data 0.017 (0.016) Batch 1.538 (1.490) Remain 12:34:36 loss: 5.5419 Lr: 8.47939e-05 Mem R(MA/MR): 23210 (21268/36182) [2025-04-29 19:42:13,783 INFO hook.py line 650 1619929] Train: [387/512][150/242] Data 0.020 (0.017) Batch 1.356 (1.496) Remain 12:36:26 loss: 4.5606 Lr: 8.46685e-05 Mem R(MA/MR): 23210 (21268/36182) [2025-04-29 19:43:26,118 INFO hook.py line 650 1619929] Train: [387/512][200/242] Data 0.015 (0.017) Batch 1.423 (1.483) Remain 12:28:54 loss: 4.1657 Lr: 8.45431e-05 Mem R(MA/MR): 23210 (21268/36182) [2025-04-29 19:44:22,931 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2679 loss_mask: 0.0337 loss_dice: 1.8528 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7338 loss: 4.7207 [2025-04-29 19:44:25,760 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:45:59,735 INFO hook.py line 650 1619929] Train: [388/512][50/242] Data 0.015 (0.016) Batch 1.326 (1.452) Remain 12:10:44 loss: 4.2281 Lr: 8.43123e-05 Mem R(MA/MR): 21614 (21268/36182) [2025-04-29 19:47:12,010 INFO hook.py line 650 1619929] Train: [388/512][100/242] Data 0.016 (0.016) Batch 1.333 (1.449) Remain 12:07:53 loss: 5.0236 Lr: 8.41868e-05 Mem R(MA/MR): 21626 (21268/36182) [2025-04-29 19:48:23,949 INFO hook.py line 650 1619929] Train: [388/512][150/242] Data 0.017 (0.017) Batch 1.385 (1.445) Remain 12:05:01 loss: 4.1953 Lr: 8.40613e-05 Mem R(MA/MR): 21626 (21268/36182) [2025-04-29 19:49:35,712 INFO hook.py line 650 1619929] Train: [388/512][200/242] Data 0.015 (0.017) Batch 1.345 (1.443) Remain 12:02:33 loss: 4.7699 Lr: 8.39358e-05 Mem R(MA/MR): 24010 (21268/36182) [2025-04-29 19:50:32,816 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2557 loss_mask: 0.0327 loss_dice: 1.8169 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7167 loss: 4.6173 [2025-04-29 19:50:34,590 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:52:06,957 INFO hook.py line 650 1619929] Train: [389/512][50/242] Data 0.015 (0.017) Batch 1.504 (1.507) Remain 12:32:13 loss: 4.7331 Lr: 8.37048e-05 Mem R(MA/MR): 24292 (21268/36182) [2025-04-29 19:53:19,150 INFO hook.py line 650 1619929] Train: [389/512][100/242] Data 0.016 (0.017) Batch 1.476 (1.474) Remain 12:14:51 loss: 4.1992 Lr: 8.35792e-05 Mem R(MA/MR): 24312 (21268/36182) [2025-04-29 19:54:33,073 INFO hook.py line 650 1619929] Train: [389/512][150/242] Data 0.016 (0.017) Batch 1.530 (1.476) Remain 12:14:20 loss: 4.5766 Lr: 8.34537e-05 Mem R(MA/MR): 29224 (21268/36182) [2025-04-29 19:55:45,318 INFO hook.py line 650 1619929] Train: [389/512][200/242] Data 0.016 (0.017) Batch 1.461 (1.468) Remain 12:09:14 loss: 4.9415 Lr: 8.33280e-05 Mem R(MA/MR): 29224 (21268/36182) [2025-04-29 19:56:43,950 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2555 loss_mask: 0.0325 loss_dice: 1.8208 loss_score: 0.0000 loss_bbox: 0.0469 loss_sp_cls: 0.7182 loss: 4.6192 [2025-04-29 19:56:48,725 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 19:58:19,911 INFO hook.py line 650 1619929] Train: [390/512][50/242] Data 0.016 (0.017) Batch 1.508 (1.470) Remain 12:08:01 loss: 4.5975 Lr: 8.30969e-05 Mem R(MA/MR): 18866 (21268/36182) [2025-04-29 19:59:34,132 INFO hook.py line 650 1619929] Train: [390/512][100/242] Data 0.015 (0.017) Batch 1.464 (1.477) Remain 12:10:28 loss: 4.0592 Lr: 8.29712e-05 Mem R(MA/MR): 18894 (21268/36182) [2025-04-29 20:00:47,504 INFO hook.py line 650 1619929] Train: [390/512][150/242] Data 0.016 (0.017) Batch 1.378 (1.474) Remain 12:07:34 loss: 4.5342 Lr: 8.28455e-05 Mem R(MA/MR): 20086 (21268/36182) [2025-04-29 20:02:00,387 INFO hook.py line 650 1619929] Train: [390/512][200/242] Data 0.016 (0.017) Batch 1.403 (1.470) Remain 12:04:18 loss: 4.8243 Lr: 8.27198e-05 Mem R(MA/MR): 20086 (21268/36182) [2025-04-29 20:02:58,152 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2560 loss_mask: 0.0323 loss_dice: 1.8233 loss_score: 0.0000 loss_bbox: 0.0471 loss_sp_cls: 0.7161 loss: 4.6258 [2025-04-29 20:02:58,446 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:04:31,124 INFO hook.py line 650 1619929] Train: [391/512][50/242] Data 0.019 (0.017) Batch 1.459 (1.446) Remain 11:50:14 loss: 4.5998 Lr: 8.24884e-05 Mem R(MA/MR): 22160 (21268/36182) [2025-04-29 20:05:44,792 INFO hook.py line 650 1619929] Train: [391/512][100/242] Data 0.016 (0.017) Batch 1.301 (1.460) Remain 11:55:59 loss: 3.9389 Lr: 8.23627e-05 Mem R(MA/MR): 23932 (21268/36182) [2025-04-29 20:06:58,216 INFO hook.py line 650 1619929] Train: [391/512][150/242] Data 0.016 (0.016) Batch 1.317 (1.463) Remain 11:56:11 loss: 4.1102 Lr: 8.22369e-05 Mem R(MA/MR): 25972 (21268/36182) [2025-04-29 20:08:08,775 INFO hook.py line 650 1619929] Train: [391/512][200/242] Data 0.015 (0.016) Batch 1.494 (1.450) Remain 11:48:33 loss: 5.5785 Lr: 8.21111e-05 Mem R(MA/MR): 25974 (21268/36182) [2025-04-29 20:09:06,906 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2557 loss_mask: 0.0322 loss_dice: 1.8131 loss_score: 0.0000 loss_bbox: 0.0478 loss_sp_cls: 0.7149 loss: 4.6138 [2025-04-29 20:09:09,196 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:10:37,310 INFO hook.py line 650 1619929] Train: [392/512][50/242] Data 0.015 (0.016) Batch 1.440 (1.394) Remain 11:19:20 loss: 4.5884 Lr: 8.18795e-05 Mem R(MA/MR): 22070 (21268/36182) [2025-04-29 20:11:50,826 INFO hook.py line 650 1619929] Train: [392/512][100/242] Data 0.017 (0.017) Batch 1.580 (1.434) Remain 11:37:12 loss: 4.0914 Lr: 8.17536e-05 Mem R(MA/MR): 22076 (21268/36182) [2025-04-29 20:13:06,499 INFO hook.py line 650 1619929] Train: [392/512][150/242] Data 0.017 (0.017) Batch 1.453 (1.461) Remain 11:49:13 loss: 4.3134 Lr: 8.16277e-05 Mem R(MA/MR): 24070 (21268/36182) [2025-04-29 20:14:17,962 INFO hook.py line 650 1619929] Train: [392/512][200/242] Data 0.015 (0.016) Batch 1.480 (1.453) Remain 11:44:08 loss: 3.7370 Lr: 8.15018e-05 Mem R(MA/MR): 24082 (21268/36182) [2025-04-29 20:15:15,894 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2555 loss_mask: 0.0322 loss_dice: 1.8307 loss_score: 0.0000 loss_bbox: 0.0473 loss_sp_cls: 0.7134 loss: 4.6349 [2025-04-29 20:15:18,961 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 20:15:21,412 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2214 Process Time: 0.387 Mem R(MA/MR): 4542 (21973/36182) [2025-04-29 20:15:22,931 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1581 Process Time: 0.491 Mem R(MA/MR): 7262 (21973/36182) [2025-04-29 20:15:25,037 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5758 Process Time: 0.992 Mem R(MA/MR): 9872 (21973/36182) [2025-04-29 20:15:32,257 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.8314 Process Time: 0.884 Mem R(MA/MR): 19810 (21973/36182) [2025-04-29 20:15:33,364 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.0718 Process Time: 0.493 Mem R(MA/MR): 7060 (21973/36182) [2025-04-29 20:15:34,646 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8159 Process Time: 0.274 Mem R(MA/MR): 11230 (21973/36182) [2025-04-29 20:15:35,258 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0220 Process Time: 0.221 Mem R(MA/MR): 6308 (21973/36182) [2025-04-29 20:15:35,918 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5040 Process Time: 0.354 Mem R(MA/MR): 4558 (21973/36182) [2025-04-29 20:15:37,151 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.9425 Process Time: 0.518 Mem R(MA/MR): 11698 (21973/36182) [2025-04-29 20:15:38,537 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6584 Process Time: 0.250 Mem R(MA/MR): 9576 (21973/36182) [2025-04-29 20:15:41,112 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.5805 Process Time: 0.558 Mem R(MA/MR): 18920 (21973/36182) [2025-04-29 20:15:43,668 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0520 Process Time: 0.639 Mem R(MA/MR): 15556 (21973/36182) [2025-04-29 20:15:44,777 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.6040 Process Time: 0.340 Mem R(MA/MR): 8794 (21973/36182) [2025-04-29 20:15:45,125 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2245 Process Time: 0.137 Mem R(MA/MR): 4888 (21973/36182) [2025-04-29 20:15:48,035 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.9450 Process Time: 0.289 Mem R(MA/MR): 16728 (21973/36182) [2025-04-29 20:15:49,674 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6030 Process Time: 0.382 Mem R(MA/MR): 14728 (21973/36182) [2025-04-29 20:15:50,504 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.6491 Process Time: 0.272 Mem R(MA/MR): 6620 (21973/36182) [2025-04-29 20:15:51,594 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7509 Process Time: 0.352 Mem R(MA/MR): 8324 (21973/36182) [2025-04-29 20:15:53,004 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.7943 Process Time: 0.184 Mem R(MA/MR): 6030 (21973/36182) [2025-04-29 20:15:54,723 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.8373 Process Time: 0.264 Mem R(MA/MR): 11766 (21973/36182) [2025-04-29 20:16:04,274 INFO hook.py line 449 1619929] Test: [21/50] Loss 6.9641 Process Time: 0.971 Mem R(MA/MR): 23906 (21973/36182) [2025-04-29 20:16:04,884 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3894 Process Time: 0.233 Mem R(MA/MR): 6902 (21973/36182) [2025-04-29 20:16:15,042 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.7794 Process Time: 0.448 Mem R(MA/MR): 10338 (21973/36182) [2025-04-29 20:16:15,702 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7588 Process Time: 0.246 Mem R(MA/MR): 5314 (21973/36182) [2025-04-29 20:16:16,739 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8335 Process Time: 0.273 Mem R(MA/MR): 9466 (21973/36182) [2025-04-29 20:16:23,738 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.7533 Process Time: 1.256 Mem R(MA/MR): 32156 (21973/36182) [2025-04-29 20:16:26,215 INFO hook.py line 449 1619929] Test: [27/50] Loss 7.1528 Process Time: 0.503 Mem R(MA/MR): 9816 (21973/36182) [2025-04-29 20:16:27,460 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.8642 Process Time: 0.282 Mem R(MA/MR): 8998 (21973/36182) [2025-04-29 20:16:31,938 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.0861 Process Time: 0.336 Mem R(MA/MR): 17084 (21973/36182) [2025-04-29 20:16:32,845 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.6579 Process Time: 0.298 Mem R(MA/MR): 7806 (21973/36182) [2025-04-29 20:16:36,914 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.1585 Process Time: 0.667 Mem R(MA/MR): 20852 (21973/36182) [2025-04-29 20:16:37,319 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.7978 Process Time: 0.180 Mem R(MA/MR): 3980 (21973/36182) [2025-04-29 20:16:41,194 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.7753 Process Time: 0.448 Mem R(MA/MR): 24708 (21973/36182) [2025-04-29 20:16:42,451 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6917 Process Time: 0.359 Mem R(MA/MR): 9782 (21973/36182) [2025-04-29 20:16:44,705 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0833 Process Time: 0.666 Mem R(MA/MR): 14050 (21973/36182) [2025-04-29 20:16:45,264 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9459 Process Time: 0.208 Mem R(MA/MR): 6528 (21973/36182) [2025-04-29 20:16:49,097 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.6701 Process Time: 0.596 Mem R(MA/MR): 28662 (21973/36182) [2025-04-29 20:16:50,732 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.0546 Process Time: 0.366 Mem R(MA/MR): 10716 (21973/36182) [2025-04-29 20:16:51,273 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9629 Process Time: 0.217 Mem R(MA/MR): 5450 (21973/36182) [2025-04-29 20:16:52,496 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8030 Process Time: 0.348 Mem R(MA/MR): 10048 (21973/36182) [2025-04-29 20:16:53,775 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.3469 Process Time: 0.344 Mem R(MA/MR): 9100 (21973/36182) [2025-04-29 20:16:54,311 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2591 Process Time: 0.145 Mem R(MA/MR): 5490 (21973/36182) [2025-04-29 20:16:54,819 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8189 Process Time: 0.181 Mem R(MA/MR): 5496 (21973/36182) [2025-04-29 20:16:55,510 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.0303 Process Time: 0.249 Mem R(MA/MR): 7224 (21973/36182) [2025-04-29 20:16:56,163 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.1618 Process Time: 0.134 Mem R(MA/MR): 5260 (21973/36182) [2025-04-29 20:16:58,422 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5195 Process Time: 0.381 Mem R(MA/MR): 14610 (21973/36182) [2025-04-29 20:17:06,521 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.4801 Process Time: 1.469 Mem R(MA/MR): 20246 (21973/36182) [2025-04-29 20:17:18,064 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.8884 Process Time: 1.919 Mem R(MA/MR): 35712 (21973/36182) [2025-04-29 20:17:18,723 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9988 Process Time: 0.178 Mem R(MA/MR): 5740 (21973/36182) [2025-04-29 20:17:21,007 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1638 Process Time: 0.357 Mem R(MA/MR): 13892 (21973/36182) [2025-04-29 20:17:25,493 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 20:17:25,494 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 20:17:25,494 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] table : 0.296 0.586 0.742 0.792 0.559 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] door : 0.466 0.786 0.904 0.938 0.772 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] ceiling lamp : 0.574 0.763 0.856 0.876 0.740 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] cabinet : 0.313 0.422 0.512 0.569 0.493 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] blinds : 0.536 0.765 0.875 0.895 0.739 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] curtain : 0.456 0.593 0.808 1.000 0.417 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] chair : 0.684 0.805 0.841 0.886 0.734 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] storage cabinet: 0.283 0.378 0.570 0.600 0.480 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] office chair : 0.599 0.649 0.650 0.717 0.792 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] bookshelf : 0.200 0.623 0.635 0.875 0.636 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] whiteboard : 0.586 0.746 0.777 1.000 0.686 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] window : 0.142 0.334 0.641 0.552 0.407 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] box : 0.180 0.352 0.494 0.634 0.354 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] monitor : 0.635 0.763 0.821 0.915 0.771 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] shelf : 0.141 0.340 0.469 0.750 0.300 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] heater : 0.451 0.747 0.795 0.933 0.737 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] kitchen cabinet: 0.154 0.336 0.601 0.588 0.400 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] sofa : 0.464 0.618 0.940 1.000 0.500 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] bed : 0.242 0.625 0.774 1.000 0.625 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] trash can : 0.513 0.649 0.740 0.766 0.754 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] book : 0.017 0.036 0.077 0.155 0.090 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] plant : 0.387 0.581 0.718 0.857 0.667 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] blanket : 0.475 0.624 0.727 0.875 0.636 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] tv : 0.956 1.000 1.000 1.000 1.000 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] computer tower : 0.260 0.384 0.588 0.593 0.381 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] refrigerator : 0.240 0.457 0.466 0.667 0.444 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] jacket : 0.055 0.280 0.491 0.455 0.455 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] sink : 0.468 0.823 0.863 0.895 0.773 [2025-04-29 20:17:25,494 INFO hook.py line 395 1619929] bag : 0.104 0.193 0.250 0.533 0.296 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] picture : 0.142 0.287 0.390 0.737 0.359 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] pillow : 0.640 0.866 0.866 0.720 0.947 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] towel : 0.156 0.268 0.427 0.464 0.342 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] suitcase : 0.325 0.453 0.453 0.750 0.429 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] backpack : 0.476 0.584 0.653 0.889 0.615 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] crate : 0.067 0.223 0.430 0.714 0.455 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] keyboard : 0.465 0.698 0.745 0.867 0.667 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] toilet : 0.851 0.876 1.000 0.889 0.889 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] printer : 0.337 0.379 0.393 1.000 0.333 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.005 0.071 0.111 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] microwave : 0.625 0.750 0.875 1.000 0.750 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] shoes : 0.144 0.237 0.590 0.647 0.268 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] socket : 0.205 0.494 0.697 0.670 0.507 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] bottle : 0.135 0.209 0.336 0.426 0.277 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] bucket : 0.025 0.034 0.034 0.136 0.429 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] cushion : 0.086 0.149 0.165 0.273 0.500 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] basket : 0.024 0.036 0.036 0.500 0.143 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] telephone : 0.320 0.518 0.633 0.889 0.471 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] laptop : 0.358 0.652 0.698 0.600 0.750 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] plant pot : 0.137 0.259 0.431 0.636 0.438 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] exhaust fan : 0.199 0.350 0.362 0.667 0.400 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] cup : 0.231 0.365 0.428 0.640 0.364 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] coat hanger : 0.139 0.250 0.500 1.000 0.250 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] light switch : 0.293 0.577 0.695 0.878 0.554 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] speaker : 0.307 0.422 0.426 0.625 0.455 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] kettle : 0.194 0.221 0.264 0.400 0.333 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] smoke detector : 0.607 0.788 0.788 1.000 0.750 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,495 INFO hook.py line 395 1619929] power strip : 0.068 0.173 0.202 0.357 0.500 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] paper bag : 0.167 0.167 0.167 0.333 1.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] mouse : 0.486 0.779 0.782 0.957 0.688 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] cutting board : 0.313 0.500 0.500 1.000 0.500 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] toilet paper : 0.286 0.412 0.471 1.000 0.412 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] paper towel : 0.023 0.166 0.166 0.400 0.250 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] clock : 0.639 0.850 0.850 1.000 0.667 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] tap : 0.153 0.387 0.667 0.800 0.444 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] soap dispenser : 0.484 0.707 0.727 1.000 0.600 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] bowl : 0.011 0.033 0.033 0.200 0.333 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] whiteboard eraser: 0.164 0.441 0.450 0.667 0.667 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] toilet brush : 0.333 0.581 0.838 0.800 0.667 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] spray bottle : 0.007 0.010 0.011 0.083 0.250 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] headphones : 0.225 0.500 0.500 1.000 0.500 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] stapler : 0.003 0.014 0.075 0.083 0.333 [2025-04-29 20:17:25,496 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 20:17:25,496 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 20:17:25,496 INFO hook.py line 404 1619929] average : 0.272 0.414 0.492 0.635 0.466 [2025-04-29 20:17:25,496 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 20:17:25,496 INFO hook.py line 480 1619929] Total Process Time: 22.542 s [2025-04-29 20:17:25,497 INFO hook.py line 481 1619929] Average Process Time: 452.137 ms [2025-04-29 20:17:25,497 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 20:17:25,530 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 20:17:25,535 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:18:55,936 INFO hook.py line 650 1619929] Train: [393/512][50/242] Data 0.017 (0.017) Batch 1.386 (1.501) Remain 12:05:27 loss: 3.9544 Lr: 8.12701e-05 Mem R(MA/MR): 22494 (21973/36182) [2025-04-29 20:20:08,111 INFO hook.py line 650 1619929] Train: [393/512][100/242] Data 0.017 (0.017) Batch 1.560 (1.472) Remain 11:49:47 loss: 5.0223 Lr: 8.11441e-05 Mem R(MA/MR): 22494 (21973/36182) [2025-04-29 20:21:20,356 INFO hook.py line 650 1619929] Train: [393/512][150/242] Data 0.017 (0.017) Batch 1.544 (1.463) Remain 11:44:11 loss: 4.4115 Lr: 8.10181e-05 Mem R(MA/MR): 22494 (21973/36182) [2025-04-29 20:22:35,217 INFO hook.py line 650 1619929] Train: [393/512][200/242] Data 0.015 (0.022) Batch 1.394 (1.471) Remain 11:47:12 loss: 5.1464 Lr: 8.08921e-05 Mem R(MA/MR): 24380 (21973/36182) [2025-04-29 20:23:33,356 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2565 loss_mask: 0.0326 loss_dice: 1.8296 loss_score: 0.0000 loss_bbox: 0.0476 loss_sp_cls: 0.7238 loss: 4.6414 [2025-04-29 20:23:36,039 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:25:11,597 INFO hook.py line 650 1619929] Train: [394/512][50/242] Data 0.019 (0.017) Batch 1.654 (1.460) Remain 11:39:27 loss: 5.8104 Lr: 8.06601e-05 Mem R(MA/MR): 20752 (21973/36182) [2025-04-29 20:26:23,317 INFO hook.py line 650 1619929] Train: [394/512][100/242] Data 0.016 (0.017) Batch 1.448 (1.447) Remain 11:31:58 loss: 4.1481 Lr: 8.05340e-05 Mem R(MA/MR): 20758 (21973/36182) [2025-04-29 20:27:35,868 INFO hook.py line 650 1619929] Train: [394/512][150/242] Data 0.016 (0.017) Batch 1.365 (1.448) Remain 11:31:27 loss: 4.6499 Lr: 8.04079e-05 Mem R(MA/MR): 20758 (21973/36182) [2025-04-29 20:28:46,069 INFO hook.py line 650 1619929] Train: [394/512][200/242] Data 0.013 (0.017) Batch 1.346 (1.437) Remain 11:24:54 loss: 3.8777 Lr: 8.02818e-05 Mem R(MA/MR): 20758 (21973/36182) [2025-04-29 20:29:42,957 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2541 loss_mask: 0.0321 loss_dice: 1.8163 loss_score: 0.0000 loss_bbox: 0.0475 loss_sp_cls: 0.7133 loss: 4.6103 [2025-04-29 20:29:45,168 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:31:19,403 INFO hook.py line 650 1619929] Train: [395/512][50/242] Data 0.016 (0.016) Batch 1.420 (1.431) Remain 11:19:54 loss: 5.2962 Lr: 8.00496e-05 Mem R(MA/MR): 25448 (21973/36182) [2025-04-29 20:32:31,134 INFO hook.py line 650 1619929] Train: [395/512][100/242] Data 0.017 (0.016) Batch 1.484 (1.433) Remain 11:19:34 loss: 5.7735 Lr: 7.99235e-05 Mem R(MA/MR): 27004 (21973/36182) [2025-04-29 20:33:46,610 INFO hook.py line 650 1619929] Train: [395/512][150/242] Data 0.016 (0.017) Batch 1.505 (1.459) Remain 11:30:43 loss: 4.9015 Lr: 7.97972e-05 Mem R(MA/MR): 29034 (21973/36182) [2025-04-29 20:34:59,621 INFO hook.py line 650 1619929] Train: [395/512][200/242] Data 0.014 (0.017) Batch 1.369 (1.459) Remain 11:29:39 loss: 5.1779 Lr: 7.96710e-05 Mem R(MA/MR): 29034 (21973/36182) [2025-04-29 20:35:55,962 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2601 loss_mask: 0.0329 loss_dice: 1.8305 loss_score: 0.0000 loss_bbox: 0.0475 loss_sp_cls: 0.7225 loss: 4.6573 [2025-04-29 20:35:56,038 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:37:29,230 INFO hook.py line 650 1619929] Train: [396/512][50/242] Data 0.015 (0.016) Batch 1.280 (1.444) Remain 11:20:15 loss: 4.1294 Lr: 7.94412e-05 Mem R(MA/MR): 20992 (21973/36182) [2025-04-29 20:38:40,660 INFO hook.py line 650 1619929] Train: [396/512][100/242] Data 0.016 (0.016) Batch 1.495 (1.436) Remain 11:15:19 loss: 5.1656 Lr: 7.93149e-05 Mem R(MA/MR): 20992 (21973/36182) [2025-04-29 20:39:50,413 INFO hook.py line 650 1619929] Train: [396/512][150/242] Data 0.016 (0.016) Batch 1.353 (1.422) Remain 11:07:33 loss: 4.4092 Lr: 7.91886e-05 Mem R(MA/MR): 20992 (21973/36182) [2025-04-29 20:41:03,880 INFO hook.py line 650 1619929] Train: [396/512][200/242] Data 0.014 (0.016) Batch 1.389 (1.434) Remain 11:11:59 loss: 5.9356 Lr: 7.90622e-05 Mem R(MA/MR): 20992 (21973/36182) [2025-04-29 20:42:00,161 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2556 loss_mask: 0.0324 loss_dice: 1.8146 loss_score: 0.0000 loss_bbox: 0.0477 loss_sp_cls: 0.7136 loss: 4.6159 [2025-04-29 20:42:01,664 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:43:34,996 INFO hook.py line 650 1619929] Train: [397/512][50/242] Data 0.016 (0.017) Batch 1.582 (1.465) Remain 11:24:18 loss: 5.0326 Lr: 7.88297e-05 Mem R(MA/MR): 22572 (21973/36182) [2025-04-29 20:44:47,780 INFO hook.py line 650 1619929] Train: [397/512][100/242] Data 0.016 (0.017) Batch 1.600 (1.460) Remain 11:20:47 loss: 4.3704 Lr: 7.87033e-05 Mem R(MA/MR): 22578 (21973/36182) [2025-04-29 20:45:58,647 INFO hook.py line 650 1619929] Train: [397/512][150/242] Data 0.016 (0.017) Batch 1.385 (1.446) Remain 11:12:46 loss: 3.3465 Lr: 7.85769e-05 Mem R(MA/MR): 22584 (21973/36182) [2025-04-29 20:47:08,118 INFO hook.py line 650 1619929] Train: [397/512][200/242] Data 0.013 (0.016) Batch 1.251 (1.431) Remain 11:04:56 loss: 5.6694 Lr: 7.84504e-05 Mem R(MA/MR): 22602 (21973/36182) [2025-04-29 20:48:04,092 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2547 loss_mask: 0.0327 loss_dice: 1.8360 loss_score: 0.0000 loss_bbox: 0.0474 loss_sp_cls: 0.7196 loss: 4.6436 [2025-04-29 20:48:08,326 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:49:44,066 INFO hook.py line 650 1619929] Train: [398/512][50/242] Data 0.015 (0.017) Batch 1.451 (1.501) Remain 11:34:59 loss: 4.1705 Lr: 7.82177e-05 Mem R(MA/MR): 21670 (21973/36182) [2025-04-29 20:50:56,477 INFO hook.py line 650 1619929] Train: [398/512][100/242] Data 0.016 (0.017) Batch 1.431 (1.474) Remain 11:21:08 loss: 5.3679 Lr: 7.80912e-05 Mem R(MA/MR): 21670 (21973/36182) [2025-04-29 20:52:05,221 INFO hook.py line 650 1619929] Train: [398/512][150/242] Data 0.017 (0.017) Batch 1.524 (1.440) Remain 11:04:23 loss: 4.8136 Lr: 7.79646e-05 Mem R(MA/MR): 21690 (21973/36182) [2025-04-29 20:53:17,569 INFO hook.py line 650 1619929] Train: [398/512][200/242] Data 0.015 (0.017) Batch 1.420 (1.442) Remain 11:03:59 loss: 4.7278 Lr: 7.78380e-05 Mem R(MA/MR): 21714 (21973/36182) [2025-04-29 20:54:14,392 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2601 loss_mask: 0.0328 loss_dice: 1.8202 loss_score: 0.0000 loss_bbox: 0.0482 loss_sp_cls: 0.7206 loss: 4.6436 [2025-04-29 20:54:17,472 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 20:55:53,180 INFO hook.py line 650 1619929] Train: [399/512][50/242] Data 0.016 (0.016) Batch 1.428 (1.481) Remain 11:19:47 loss: 4.6416 Lr: 7.76051e-05 Mem R(MA/MR): 24904 (21973/36182) [2025-04-29 20:57:06,282 INFO hook.py line 650 1619929] Train: [399/512][100/242] Data 0.018 (0.017) Batch 1.332 (1.471) Remain 11:14:02 loss: 4.8490 Lr: 7.74785e-05 Mem R(MA/MR): 26478 (21973/36182) [2025-04-29 20:58:21,126 INFO hook.py line 650 1619929] Train: [399/512][150/242] Data 0.016 (0.017) Batch 1.602 (1.480) Remain 11:16:48 loss: 4.1340 Lr: 7.73518e-05 Mem R(MA/MR): 28262 (21973/36182) [2025-04-29 20:59:34,880 INFO hook.py line 650 1619929] Train: [399/512][200/242] Data 0.015 (0.017) Batch 1.358 (1.479) Remain 11:15:00 loss: 4.3354 Lr: 7.72252e-05 Mem R(MA/MR): 30072 (21973/36182) [2025-04-29 21:00:33,428 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2595 loss_mask: 0.0328 loss_dice: 1.8295 loss_score: 0.0000 loss_bbox: 0.0479 loss_sp_cls: 0.7190 loss: 4.6472 [2025-04-29 21:00:35,566 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:02:12,685 INFO hook.py line 650 1619929] Train: [400/512][50/242] Data 0.016 (0.017) Batch 1.467 (1.493) Remain 11:19:18 loss: 6.3245 Lr: 7.69945e-05 Mem R(MA/MR): 21258 (21973/36182) [2025-04-29 21:03:25,508 INFO hook.py line 650 1619929] Train: [400/512][100/242] Data 0.015 (0.017) Batch 1.381 (1.474) Remain 11:09:28 loss: 5.3111 Lr: 7.68678e-05 Mem R(MA/MR): 23088 (21973/36182) [2025-04-29 21:04:39,116 INFO hook.py line 650 1619929] Train: [400/512][150/242] Data 0.015 (0.017) Batch 1.598 (1.474) Remain 11:07:54 loss: 5.1419 Lr: 7.67410e-05 Mem R(MA/MR): 23088 (21973/36182) [2025-04-29 21:05:50,239 INFO hook.py line 650 1619929] Train: [400/512][200/242] Data 0.014 (0.017) Batch 1.291 (1.461) Remain 11:00:49 loss: 4.7576 Lr: 7.66143e-05 Mem R(MA/MR): 23088 (21973/36182) [2025-04-29 21:06:48,332 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2716 loss_mask: 0.0338 loss_dice: 1.8623 loss_score: 0.0000 loss_bbox: 0.0486 loss_sp_cls: 0.7341 loss: 4.7510 [2025-04-29 21:06:49,999 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 21:06:52,321 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.6585 Process Time: 0.260 Mem R(MA/MR): 4672 (21973/36182) [2025-04-29 21:06:54,142 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.1138 Process Time: 0.608 Mem R(MA/MR): 7674 (21973/36182) [2025-04-29 21:06:56,086 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.7933 Process Time: 0.829 Mem R(MA/MR): 10222 (21973/36182) [2025-04-29 21:07:03,960 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.0848 Process Time: 1.220 Mem R(MA/MR): 20108 (21973/36182) [2025-04-29 21:07:04,749 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.9265 Process Time: 0.260 Mem R(MA/MR): 7242 (21973/36182) [2025-04-29 21:07:06,543 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.2299 Process Time: 0.556 Mem R(MA/MR): 12084 (21973/36182) [2025-04-29 21:07:07,250 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.9119 Process Time: 0.219 Mem R(MA/MR): 6868 (21973/36182) [2025-04-29 21:07:07,726 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4195 Process Time: 0.136 Mem R(MA/MR): 5076 (21973/36182) [2025-04-29 21:07:08,803 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7812 Process Time: 0.327 Mem R(MA/MR): 12278 (21973/36182) [2025-04-29 21:07:10,491 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7727 Process Time: 0.315 Mem R(MA/MR): 9746 (21973/36182) [2025-04-29 21:07:13,411 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.7054 Process Time: 0.646 Mem R(MA/MR): 18952 (21973/36182) [2025-04-29 21:07:16,791 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3528 Process Time: 1.007 Mem R(MA/MR): 16014 (21973/36182) [2025-04-29 21:07:17,903 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.3390 Process Time: 0.269 Mem R(MA/MR): 8916 (21973/36182) [2025-04-29 21:07:18,397 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0654 Process Time: 0.239 Mem R(MA/MR): 5350 (21973/36182) [2025-04-29 21:07:21,509 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4019 Process Time: 0.343 Mem R(MA/MR): 17120 (21973/36182) [2025-04-29 21:07:23,256 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.7065 Process Time: 0.352 Mem R(MA/MR): 15120 (21973/36182) [2025-04-29 21:07:24,061 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2107 Process Time: 0.240 Mem R(MA/MR): 7170 (21973/36182) [2025-04-29 21:07:25,099 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.5121 Process Time: 0.282 Mem R(MA/MR): 8392 (21973/36182) [2025-04-29 21:07:26,513 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2004 Process Time: 0.172 Mem R(MA/MR): 6694 (21973/36182) [2025-04-29 21:07:28,196 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.8931 Process Time: 0.300 Mem R(MA/MR): 12218 (21973/36182) [2025-04-29 21:07:38,551 INFO hook.py line 449 1619929] Test: [21/50] Loss 5.3670 Process Time: 0.901 Mem R(MA/MR): 24364 (21973/36182) [2025-04-29 21:07:39,425 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.3245 Process Time: 0.282 Mem R(MA/MR): 7226 (21973/36182) [2025-04-29 21:07:49,905 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.4049 Process Time: 0.335 Mem R(MA/MR): 10654 (21973/36182) [2025-04-29 21:07:50,416 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7501 Process Time: 0.133 Mem R(MA/MR): 5912 (21973/36182) [2025-04-29 21:07:51,445 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1133 Process Time: 0.277 Mem R(MA/MR): 9836 (21973/36182) [2025-04-29 21:07:58,355 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.5626 Process Time: 0.920 Mem R(MA/MR): 31946 (21973/36182) [2025-04-29 21:08:00,652 INFO hook.py line 449 1619929] Test: [27/50] Loss 5.8737 Process Time: 0.334 Mem R(MA/MR): 10664 (21973/36182) [2025-04-29 21:08:01,664 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.7725 Process Time: 0.205 Mem R(MA/MR): 9164 (21973/36182) [2025-04-29 21:08:07,155 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0911 Process Time: 0.699 Mem R(MA/MR): 17404 (21973/36182) [2025-04-29 21:08:07,940 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.0685 Process Time: 0.172 Mem R(MA/MR): 8064 (21973/36182) [2025-04-29 21:08:11,136 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.3947 Process Time: 0.343 Mem R(MA/MR): 20750 (21973/36182) [2025-04-29 21:08:11,627 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.4926 Process Time: 0.169 Mem R(MA/MR): 4274 (21973/36182) [2025-04-29 21:08:15,970 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.8833 Process Time: 0.880 Mem R(MA/MR): 24940 (21973/36182) [2025-04-29 21:08:17,231 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5784 Process Time: 0.270 Mem R(MA/MR): 10574 (21973/36182) [2025-04-29 21:08:19,228 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6989 Process Time: 0.340 Mem R(MA/MR): 14646 (21973/36182) [2025-04-29 21:08:20,257 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.7360 Process Time: 0.405 Mem R(MA/MR): 7060 (21973/36182) [2025-04-29 21:08:24,181 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.9126 Process Time: 0.627 Mem R(MA/MR): 28862 (21973/36182) [2025-04-29 21:08:25,579 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.3890 Process Time: 0.251 Mem R(MA/MR): 11378 (21973/36182) [2025-04-29 21:08:26,030 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2668 Process Time: 0.136 Mem R(MA/MR): 6078 (21973/36182) [2025-04-29 21:08:27,184 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.6335 Process Time: 0.238 Mem R(MA/MR): 10962 (21973/36182) [2025-04-29 21:08:28,566 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.3628 Process Time: 0.464 Mem R(MA/MR): 9250 (21973/36182) [2025-04-29 21:08:29,100 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1589 Process Time: 0.162 Mem R(MA/MR): 6030 (21973/36182) [2025-04-29 21:08:29,933 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.4788 Process Time: 0.408 Mem R(MA/MR): 6086 (21973/36182) [2025-04-29 21:08:30,627 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1453 Process Time: 0.238 Mem R(MA/MR): 7568 (21973/36182) [2025-04-29 21:08:31,294 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.8933 Process Time: 0.214 Mem R(MA/MR): 5884 (21973/36182) [2025-04-29 21:08:33,697 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.1491 Process Time: 0.445 Mem R(MA/MR): 15298 (21973/36182) [2025-04-29 21:08:41,506 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7070 Process Time: 1.123 Mem R(MA/MR): 20694 (21973/36182) [2025-04-29 21:08:51,247 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.6151 Process Time: 1.633 Mem R(MA/MR): 35738 (21973/36182) [2025-04-29 21:08:51,833 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1925 Process Time: 0.172 Mem R(MA/MR): 6232 (21973/36182) [2025-04-29 21:08:53,920 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.6367 Process Time: 0.359 Mem R(MA/MR): 14298 (21973/36182) [2025-04-29 21:08:58,770 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 21:08:58,770 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 21:08:58,770 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] table : 0.268 0.557 0.744 0.812 0.574 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] door : 0.426 0.738 0.901 0.870 0.759 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] ceiling lamp : 0.559 0.763 0.874 0.821 0.762 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] cabinet : 0.355 0.515 0.527 0.660 0.463 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] blinds : 0.440 0.705 0.808 0.810 0.739 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] curtain : 0.323 0.478 0.665 0.700 0.583 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] chair : 0.682 0.808 0.842 0.844 0.775 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] storage cabinet: 0.265 0.400 0.462 0.647 0.440 [2025-04-29 21:08:58,770 INFO hook.py line 395 1619929] office chair : 0.581 0.607 0.636 0.692 0.750 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] bookshelf : 0.249 0.527 0.567 0.636 0.636 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] whiteboard : 0.595 0.773 0.788 0.923 0.686 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] window : 0.116 0.272 0.629 0.486 0.374 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] box : 0.173 0.317 0.468 0.366 0.453 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] monitor : 0.628 0.790 0.887 1.000 0.686 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] shelf : 0.162 0.338 0.438 0.818 0.300 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] heater : 0.369 0.630 0.768 0.852 0.605 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] kitchen cabinet: 0.147 0.383 0.625 0.647 0.440 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] sofa : 0.425 0.689 0.792 1.000 0.500 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] bed : 0.273 0.646 0.812 1.000 0.500 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] trash can : 0.557 0.711 0.780 0.864 0.785 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] book : 0.027 0.040 0.097 0.175 0.075 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] plant : 0.425 0.693 0.769 1.000 0.611 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] blanket : 0.464 0.618 0.702 0.700 0.636 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] tv : 0.921 1.000 1.000 1.000 1.000 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] computer tower : 0.255 0.425 0.567 0.690 0.476 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] refrigerator : 0.215 0.435 0.448 1.000 0.333 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] jacket : 0.080 0.238 0.417 0.381 0.727 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] sink : 0.367 0.666 0.853 0.889 0.727 [2025-04-29 21:08:58,771 INFO hook.py line 395 1619929] bag : 0.142 0.199 0.274 0.545 0.222 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] picture : 0.155 0.304 0.358 0.556 0.385 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] pillow : 0.577 0.780 0.810 0.867 0.684 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] towel : 0.219 0.340 0.508 0.560 0.368 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] suitcase : 0.347 0.393 0.393 0.400 0.571 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] backpack : 0.323 0.435 0.510 0.833 0.385 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] crate : 0.089 0.340 0.521 0.750 0.545 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] keyboard : 0.435 0.620 0.737 0.781 0.641 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] toilet : 0.846 1.000 1.000 1.000 1.000 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] printer : 0.273 0.368 0.480 0.750 0.333 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.002 0.000 0.000 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] painting : 0.039 0.042 0.050 0.083 1.000 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] microwave : 0.512 0.717 0.858 1.000 0.625 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] shoes : 0.127 0.217 0.574 0.577 0.366 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] socket : 0.189 0.445 0.638 0.813 0.436 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] bottle : 0.123 0.186 0.293 0.488 0.241 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] bucket : 0.006 0.029 0.036 0.250 0.143 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] cushion : 0.024 0.050 0.255 0.182 0.333 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] basket : 0.007 0.036 0.082 0.500 0.143 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 21:08:58,772 INFO hook.py line 395 1619929] telephone : 0.355 0.568 0.724 0.667 0.588 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] laptop : 0.502 0.771 0.794 1.000 0.625 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] plant pot : 0.115 0.304 0.450 0.529 0.562 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] exhaust fan : 0.246 0.400 0.400 1.000 0.400 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] cup : 0.235 0.378 0.423 0.773 0.386 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] coat hanger : 0.210 0.354 0.750 0.500 0.500 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] light switch : 0.224 0.468 0.621 0.727 0.492 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] speaker : 0.471 0.593 0.595 0.875 0.636 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] kettle : 0.181 0.264 0.382 0.667 0.333 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] smoke detector : 0.680 0.868 0.868 0.952 0.833 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] power strip : 0.024 0.041 0.113 0.500 0.100 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] paper bag : 0.125 0.125 0.125 0.250 1.000 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] mouse : 0.470 0.655 0.747 0.833 0.625 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] cutting board : 0.097 0.208 0.208 0.667 0.500 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] toilet paper : 0.224 0.472 0.576 0.643 0.529 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] paper towel : 0.006 0.021 0.198 0.333 0.125 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 21:08:58,773 INFO hook.py line 395 1619929] clock : 0.597 1.000 1.000 1.000 1.000 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] pan : 0.139 0.250 0.250 1.000 0.250 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] tap : 0.135 0.288 0.637 0.429 0.333 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 1.000 0.000 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] soap dispenser : 0.360 0.600 0.600 1.000 0.600 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] bowl : 0.089 0.172 0.278 0.333 0.667 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] tissue box : 0.066 0.500 0.500 1.000 0.500 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] whiteboard eraser: 0.156 0.474 0.474 0.800 0.667 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] toilet brush : 0.473 0.782 0.955 1.000 0.667 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] spray bottle : 0.007 0.011 0.013 0.091 0.250 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] stapler : 0.001 0.011 0.085 0.067 0.333 [2025-04-29 21:08:58,774 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 21:08:58,774 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 21:08:58,774 INFO hook.py line 404 1619929] average : 0.265 0.419 0.506 0.657 0.486 [2025-04-29 21:08:58,774 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 21:08:58,775 INFO hook.py line 480 1619929] Total Process Time: 21.714 s [2025-04-29 21:08:58,775 INFO hook.py line 481 1619929] Average Process Time: 437.826 ms [2025-04-29 21:08:58,775 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 21:08:58,818 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 21:08:58,823 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:10:31,420 INFO hook.py line 650 1619929] Train: [401/512][50/242] Data 0.016 (0.017) Batch 1.299 (1.423) Remain 10:41:31 loss: 3.7567 Lr: 7.63809e-05 Mem R(MA/MR): 22346 (21973/36182) [2025-04-29 21:11:42,098 INFO hook.py line 650 1619929] Train: [401/512][100/242] Data 0.018 (0.017) Batch 1.520 (1.418) Remain 10:38:11 loss: 5.7987 Lr: 7.62541e-05 Mem R(MA/MR): 22346 (21973/36182) [2025-04-29 21:12:55,700 INFO hook.py line 650 1619929] Train: [401/512][150/242] Data 0.016 (0.022) Batch 1.448 (1.436) Remain 10:45:16 loss: 6.1088 Lr: 7.61272e-05 Mem R(MA/MR): 24220 (21973/36182) [2025-04-29 21:14:08,164 INFO hook.py line 650 1619929] Train: [401/512][200/242] Data 0.015 (0.021) Batch 1.396 (1.440) Remain 10:45:32 loss: 5.0760 Lr: 7.60003e-05 Mem R(MA/MR): 24220 (21973/36182) [2025-04-29 21:15:06,558 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2697 loss_mask: 0.0344 loss_dice: 1.8699 loss_score: 0.0000 loss_bbox: 0.0488 loss_sp_cls: 0.7300 loss: 4.7578 [2025-04-29 21:15:10,804 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:16:47,328 INFO hook.py line 650 1619929] Train: [402/512][50/242] Data 0.016 (0.017) Batch 1.508 (1.457) Remain 10:51:17 loss: 5.3035 Lr: 7.57667e-05 Mem R(MA/MR): 19638 (21973/36182) [2025-04-29 21:18:01,351 INFO hook.py line 650 1619929] Train: [402/512][100/242] Data 0.018 (0.017) Batch 1.574 (1.469) Remain 10:55:21 loss: 5.3104 Lr: 7.56398e-05 Mem R(MA/MR): 22886 (21973/36182) [2025-04-29 21:19:14,740 INFO hook.py line 650 1619929] Train: [402/512][150/242] Data 0.016 (0.017) Batch 1.462 (1.469) Remain 10:53:54 loss: 5.2262 Lr: 7.55128e-05 Mem R(MA/MR): 28488 (21973/36182) [2025-04-29 21:20:27,731 INFO hook.py line 650 1619929] Train: [402/512][200/242] Data 0.015 (0.017) Batch 1.392 (1.467) Remain 10:51:40 loss: 6.2975 Lr: 7.53858e-05 Mem R(MA/MR): 28488 (21973/36182) [2025-04-29 21:21:25,505 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2684 loss_mask: 0.0337 loss_dice: 1.8569 loss_score: 0.0000 loss_bbox: 0.0485 loss_sp_cls: 0.7343 loss: 4.7293 [2025-04-29 21:21:28,238 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:23:05,195 INFO hook.py line 650 1619929] Train: [403/512][50/242] Data 0.017 (0.018) Batch 1.369 (1.530) Remain 11:17:32 loss: 3.1327 Lr: 7.51520e-05 Mem R(MA/MR): 22634 (21973/36182) [2025-04-29 21:24:17,638 INFO hook.py line 650 1619929] Train: [403/512][100/242] Data 0.016 (0.017) Batch 1.517 (1.488) Remain 10:57:46 loss: 3.9200 Lr: 7.50249e-05 Mem R(MA/MR): 22634 (21973/36182) [2025-04-29 21:25:29,173 INFO hook.py line 650 1619929] Train: [403/512][150/242] Data 0.019 (0.017) Batch 1.479 (1.469) Remain 10:47:54 loss: 3.4597 Lr: 7.48978e-05 Mem R(MA/MR): 22634 (21973/36182) [2025-04-29 21:26:40,352 INFO hook.py line 650 1619929] Train: [403/512][200/242] Data 0.015 (0.017) Batch 1.354 (1.457) Remain 10:41:39 loss: 4.9631 Lr: 7.47707e-05 Mem R(MA/MR): 22634 (21973/36182) [2025-04-29 21:27:38,441 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2686 loss_mask: 0.0334 loss_dice: 1.8667 loss_score: 0.0000 loss_bbox: 0.0481 loss_sp_cls: 0.7283 loss: 4.7373 [2025-04-29 21:27:41,578 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:29:16,846 INFO hook.py line 650 1619929] Train: [404/512][50/242] Data 0.017 (0.016) Batch 1.465 (1.513) Remain 11:03:42 loss: 4.8614 Lr: 7.45367e-05 Mem R(MA/MR): 28116 (21973/36182) [2025-04-29 21:30:29,040 INFO hook.py line 650 1619929] Train: [404/512][100/242] Data 0.018 (0.016) Batch 1.480 (1.477) Remain 10:46:56 loss: 5.5216 Lr: 7.44095e-05 Mem R(MA/MR): 28116 (21973/36182) [2025-04-29 21:31:41,901 INFO hook.py line 650 1619929] Train: [404/512][150/242] Data 0.018 (0.016) Batch 1.482 (1.470) Remain 10:42:44 loss: 5.1336 Lr: 7.42823e-05 Mem R(MA/MR): 28116 (21973/36182) [2025-04-29 21:32:54,551 INFO hook.py line 650 1619929] Train: [404/512][200/242] Data 0.017 (0.016) Batch 1.442 (1.466) Remain 10:39:35 loss: 3.8476 Lr: 7.41550e-05 Mem R(MA/MR): 28116 (21973/36182) [2025-04-29 21:33:53,159 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2635 loss_mask: 0.0337 loss_dice: 1.8478 loss_score: 0.0000 loss_bbox: 0.0478 loss_sp_cls: 0.7290 loss: 4.6966 [2025-04-29 21:33:53,558 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:35:30,203 INFO hook.py line 650 1619929] Train: [405/512][50/242] Data 0.015 (0.017) Batch 1.363 (1.522) Remain 11:01:33 loss: 4.1490 Lr: 7.39208e-05 Mem R(MA/MR): 22546 (21973/36182) [2025-04-29 21:36:41,632 INFO hook.py line 650 1619929] Train: [405/512][100/242] Data 0.015 (0.016) Batch 1.354 (1.474) Remain 10:39:27 loss: 4.4449 Lr: 7.37935e-05 Mem R(MA/MR): 27870 (21973/36182) [2025-04-29 21:37:52,896 INFO hook.py line 650 1619929] Train: [405/512][150/242] Data 0.016 (0.016) Batch 1.411 (1.457) Remain 10:31:06 loss: 5.3777 Lr: 7.36662e-05 Mem R(MA/MR): 27870 (21973/36182) [2025-04-29 21:39:03,941 INFO hook.py line 650 1619929] Train: [405/512][200/242] Data 0.015 (0.017) Batch 1.235 (1.448) Remain 10:25:55 loss: 4.6148 Lr: 7.35388e-05 Mem R(MA/MR): 27870 (21973/36182) [2025-04-29 21:40:01,142 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2598 loss_mask: 0.0331 loss_dice: 1.8320 loss_score: 0.0000 loss_bbox: 0.0480 loss_sp_cls: 0.7214 loss: 4.6592 [2025-04-29 21:40:03,939 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:41:32,538 INFO hook.py line 650 1619929] Train: [406/512][50/242] Data 0.017 (0.017) Batch 1.626 (1.498) Remain 10:45:10 loss: 5.4348 Lr: 7.33044e-05 Mem R(MA/MR): 21770 (21973/36182) [2025-04-29 21:42:45,261 INFO hook.py line 650 1619929] Train: [406/512][100/242] Data 0.017 (0.017) Batch 1.448 (1.476) Remain 10:34:19 loss: 4.0059 Lr: 7.31770e-05 Mem R(MA/MR): 21778 (21973/36182) [2025-04-29 21:43:57,956 INFO hook.py line 650 1619929] Train: [406/512][150/242] Data 0.017 (0.017) Batch 1.329 (1.468) Remain 10:29:56 loss: 4.2902 Lr: 7.30495e-05 Mem R(MA/MR): 21802 (21973/36182) [2025-04-29 21:45:07,390 INFO hook.py line 650 1619929] Train: [406/512][200/242] Data 0.016 (0.017) Batch 1.367 (1.448) Remain 10:20:04 loss: 4.2835 Lr: 7.29220e-05 Mem R(MA/MR): 21802 (21973/36182) [2025-04-29 21:46:04,748 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2588 loss_mask: 0.0332 loss_dice: 1.8237 loss_score: 0.0000 loss_bbox: 0.0482 loss_sp_cls: 0.7256 loss: 4.6443 [2025-04-29 21:46:08,026 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:47:43,980 INFO hook.py line 650 1619929] Train: [407/512][50/242] Data 0.015 (0.016) Batch 1.410 (1.463) Remain 10:24:22 loss: 5.2705 Lr: 7.26874e-05 Mem R(MA/MR): 21154 (21973/36182) [2025-04-29 21:48:56,977 INFO hook.py line 650 1619929] Train: [407/512][100/242] Data 0.018 (0.016) Batch 1.532 (1.462) Remain 10:22:25 loss: 4.8742 Lr: 7.25598e-05 Mem R(MA/MR): 23720 (21973/36182) [2025-04-29 21:50:10,085 INFO hook.py line 650 1619929] Train: [407/512][150/242] Data 0.015 (0.017) Batch 1.362 (1.462) Remain 10:21:17 loss: 4.2028 Lr: 7.24322e-05 Mem R(MA/MR): 23720 (21973/36182) [2025-04-29 21:51:20,546 INFO hook.py line 650 1619929] Train: [407/512][200/242] Data 0.014 (0.017) Batch 1.319 (1.448) Remain 10:14:25 loss: 3.5500 Lr: 7.23046e-05 Mem R(MA/MR): 23720 (21973/36182) [2025-04-29 21:52:16,451 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2565 loss_mask: 0.0326 loss_dice: 1.8289 loss_score: 0.0000 loss_bbox: 0.0479 loss_sp_cls: 0.7182 loss: 4.6388 [2025-04-29 21:52:20,715 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 21:53:56,523 INFO hook.py line 650 1619929] Train: [408/512][50/242] Data 0.015 (0.017) Batch 1.399 (1.469) Remain 10:20:55 loss: 3.6562 Lr: 7.20698e-05 Mem R(MA/MR): 23706 (21973/36182) [2025-04-29 21:55:08,543 INFO hook.py line 650 1619929] Train: [408/512][100/242] Data 0.016 (0.017) Batch 1.527 (1.454) Remain 10:13:27 loss: 4.3344 Lr: 7.19421e-05 Mem R(MA/MR): 23710 (21973/36182) [2025-04-29 21:56:20,526 INFO hook.py line 650 1619929] Train: [408/512][150/242] Data 0.017 (0.017) Batch 1.410 (1.449) Remain 10:10:09 loss: 5.9202 Lr: 7.18144e-05 Mem R(MA/MR): 25424 (21973/36182) [2025-04-29 21:57:32,201 INFO hook.py line 650 1619929] Train: [408/512][200/242] Data 0.014 (0.017) Batch 1.449 (1.445) Remain 10:07:16 loss: 5.8581 Lr: 7.16867e-05 Mem R(MA/MR): 27204 (21973/36182) [2025-04-29 21:58:29,950 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2515 loss_mask: 0.0326 loss_dice: 1.8203 loss_score: 0.0000 loss_bbox: 0.0471 loss_sp_cls: 0.7205 loss: 4.6103 [2025-04-29 21:58:31,504 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 21:58:33,814 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2958 Process Time: 0.240 Mem R(MA/MR): 4254 (21973/36182) [2025-04-29 21:58:35,456 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.7528 Process Time: 0.621 Mem R(MA/MR): 7106 (21973/36182) [2025-04-29 21:58:37,036 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4160 Process Time: 0.646 Mem R(MA/MR): 9484 (21973/36182) [2025-04-29 21:58:44,307 INFO hook.py line 449 1619929] Test: [4/50] Loss 7.0992 Process Time: 1.425 Mem R(MA/MR): 19518 (21973/36182) [2025-04-29 21:58:45,487 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4536 Process Time: 0.539 Mem R(MA/MR): 6950 (21973/36182) [2025-04-29 21:58:46,888 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.9329 Process Time: 0.361 Mem R(MA/MR): 11122 (21973/36182) [2025-04-29 21:58:47,817 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8263 Process Time: 0.325 Mem R(MA/MR): 6198 (21973/36182) [2025-04-29 21:58:48,341 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4599 Process Time: 0.150 Mem R(MA/MR): 4252 (21973/36182) [2025-04-29 21:58:49,332 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6613 Process Time: 0.325 Mem R(MA/MR): 11298 (21973/36182) [2025-04-29 21:58:50,975 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.9229 Process Time: 0.346 Mem R(MA/MR): 9382 (21973/36182) [2025-04-29 21:58:53,342 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0713 Process Time: 0.390 Mem R(MA/MR): 18568 (21973/36182) [2025-04-29 21:58:55,733 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3037 Process Time: 0.387 Mem R(MA/MR): 15372 (21973/36182) [2025-04-29 21:58:56,954 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1447 Process Time: 0.319 Mem R(MA/MR): 8676 (21973/36182) [2025-04-29 21:58:57,429 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0980 Process Time: 0.190 Mem R(MA/MR): 4542 (21973/36182) [2025-04-29 21:59:00,254 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.3787 Process Time: 0.310 Mem R(MA/MR): 16418 (21973/36182) [2025-04-29 21:59:01,820 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3518 Process Time: 0.456 Mem R(MA/MR): 14350 (21973/36182) [2025-04-29 21:59:02,800 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.5405 Process Time: 0.436 Mem R(MA/MR): 6584 (21973/36182) [2025-04-29 21:59:04,083 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7110 Process Time: 0.467 Mem R(MA/MR): 8030 (21973/36182) [2025-04-29 21:59:05,936 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5573 Process Time: 0.463 Mem R(MA/MR): 6036 (21973/36182) [2025-04-29 21:59:07,534 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.5634 Process Time: 0.225 Mem R(MA/MR): 11270 (21973/36182) [2025-04-29 21:59:17,465 INFO hook.py line 449 1619929] Test: [21/50] Loss 9.4083 Process Time: 1.119 Mem R(MA/MR): 23948 (21973/36182) [2025-04-29 21:59:18,063 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.6849 Process Time: 0.211 Mem R(MA/MR): 6734 (21973/36182) [2025-04-29 21:59:28,689 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.2608 Process Time: 0.352 Mem R(MA/MR): 10052 (21973/36182) [2025-04-29 21:59:29,601 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9697 Process Time: 0.480 Mem R(MA/MR): 5196 (21973/36182) [2025-04-29 21:59:30,766 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8182 Process Time: 0.337 Mem R(MA/MR): 9078 (21973/36182) [2025-04-29 21:59:36,618 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.8927 Process Time: 1.034 Mem R(MA/MR): 30218 (21973/36182) [2025-04-29 21:59:39,370 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.6052 Process Time: 0.593 Mem R(MA/MR): 9818 (21973/36182) [2025-04-29 21:59:41,120 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0630 Process Time: 0.560 Mem R(MA/MR): 8744 (21973/36182) [2025-04-29 21:59:46,479 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6242 Process Time: 0.382 Mem R(MA/MR): 16952 (21973/36182) [2025-04-29 21:59:48,180 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.8546 Process Time: 0.654 Mem R(MA/MR): 7604 (21973/36182) [2025-04-29 21:59:52,377 INFO hook.py line 449 1619929] Test: [31/50] Loss 8.0031 Process Time: 0.547 Mem R(MA/MR): 20680 (21973/36182) [2025-04-29 21:59:52,847 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.8688 Process Time: 0.223 Mem R(MA/MR): 3990 (21973/36182) [2025-04-29 21:59:57,353 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.0743 Process Time: 0.560 Mem R(MA/MR): 24704 (21973/36182) [2025-04-29 21:59:58,776 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5319 Process Time: 0.524 Mem R(MA/MR): 9468 (21973/36182) [2025-04-29 22:00:00,610 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6432 Process Time: 0.359 Mem R(MA/MR): 13900 (21973/36182) [2025-04-29 22:00:01,143 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8278 Process Time: 0.193 Mem R(MA/MR): 6418 (21973/36182) [2025-04-29 22:00:04,671 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5411 Process Time: 0.704 Mem R(MA/MR): 28314 (21973/36182) [2025-04-29 22:00:06,872 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8229 Process Time: 0.623 Mem R(MA/MR): 10454 (21973/36182) [2025-04-29 22:00:07,403 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1566 Process Time: 0.215 Mem R(MA/MR): 5352 (21973/36182) [2025-04-29 22:00:08,454 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9923 Process Time: 0.277 Mem R(MA/MR): 9712 (21973/36182) [2025-04-29 22:00:09,287 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0090 Process Time: 0.191 Mem R(MA/MR): 8770 (21973/36182) [2025-04-29 22:00:09,694 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.7055 Process Time: 0.124 Mem R(MA/MR): 5316 (21973/36182) [2025-04-29 22:00:10,165 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6439 Process Time: 0.183 Mem R(MA/MR): 5432 (21973/36182) [2025-04-29 22:00:10,744 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.6372 Process Time: 0.207 Mem R(MA/MR): 6956 (21973/36182) [2025-04-29 22:00:11,295 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.3108 Process Time: 0.138 Mem R(MA/MR): 4982 (21973/36182) [2025-04-29 22:00:13,630 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.6985 Process Time: 0.670 Mem R(MA/MR): 14276 (21973/36182) [2025-04-29 22:00:21,497 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.8765 Process Time: 1.263 Mem R(MA/MR): 20212 (21973/36182) [2025-04-29 22:00:32,525 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.2678 Process Time: 2.294 Mem R(MA/MR): 35054 (21973/36182) [2025-04-29 22:00:33,665 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.6767 Process Time: 0.320 Mem R(MA/MR): 5636 (21973/36182) [2025-04-29 22:00:36,173 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.8130 Process Time: 0.425 Mem R(MA/MR): 13482 (21973/36182) [2025-04-29 22:00:40,756 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 22:00:40,757 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 22:00:40,757 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] table : 0.256 0.531 0.721 0.736 0.574 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] door : 0.484 0.768 0.913 0.849 0.785 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] ceiling lamp : 0.591 0.796 0.881 0.840 0.785 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] cabinet : 0.339 0.486 0.536 0.586 0.507 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] blinds : 0.598 0.807 0.799 0.941 0.696 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] curtain : 0.264 0.336 0.625 0.545 0.500 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] chair : 0.589 0.714 0.763 0.683 0.750 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] storage cabinet: 0.196 0.321 0.407 0.632 0.480 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] office chair : 0.595 0.626 0.626 0.712 0.771 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] bookshelf : 0.171 0.418 0.684 0.667 0.545 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] whiteboard : 0.597 0.782 0.803 0.931 0.771 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] window : 0.123 0.301 0.657 0.571 0.396 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] box : 0.203 0.374 0.525 0.523 0.442 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] monitor : 0.595 0.773 0.850 0.887 0.786 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] shelf : 0.161 0.296 0.388 0.692 0.300 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] heater : 0.360 0.574 0.689 0.778 0.737 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] kitchen cabinet: 0.122 0.319 0.546 0.361 0.520 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] sofa : 0.411 0.595 0.805 0.727 0.667 [2025-04-29 22:00:40,757 INFO hook.py line 395 1619929] bed : 0.075 0.240 0.522 0.333 0.500 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] trash can : 0.590 0.749 0.794 0.823 0.785 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] book : 0.023 0.040 0.083 0.203 0.090 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] plant : 0.466 0.778 0.833 1.000 0.778 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] blanket : 0.421 0.609 0.609 0.875 0.636 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] tv : 0.948 1.000 1.000 1.000 1.000 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] computer tower : 0.301 0.458 0.689 0.750 0.500 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] refrigerator : 0.336 0.556 0.560 0.833 0.556 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] jacket : 0.078 0.205 0.383 0.350 0.636 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] sink : 0.419 0.604 0.828 0.875 0.636 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] bag : 0.125 0.179 0.190 0.364 0.296 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] picture : 0.151 0.290 0.386 0.857 0.308 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] pillow : 0.490 0.661 0.689 0.917 0.579 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] towel : 0.199 0.346 0.484 0.700 0.368 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] suitcase : 0.397 0.427 0.430 0.750 0.429 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] backpack : 0.397 0.462 0.570 1.000 0.462 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] crate : 0.071 0.274 0.536 0.500 0.545 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] keyboard : 0.407 0.538 0.588 0.947 0.462 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] toilet : 0.825 0.876 1.000 0.889 0.889 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] printer : 0.352 0.412 0.412 0.556 0.556 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.005 0.067 0.111 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] painting : 0.039 0.042 0.050 0.083 1.000 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] microwave : 0.624 0.750 1.000 1.000 0.750 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] shoes : 0.158 0.310 0.542 0.667 0.341 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] socket : 0.218 0.491 0.676 0.805 0.500 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] bottle : 0.111 0.208 0.331 0.478 0.265 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] bucket : 0.042 0.042 0.044 0.136 0.429 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] cushion : 0.080 0.080 0.170 0.190 0.667 [2025-04-29 22:00:40,758 INFO hook.py line 395 1619929] basket : 0.005 0.008 0.009 0.111 0.143 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] telephone : 0.307 0.514 0.663 0.800 0.471 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] laptop : 0.381 0.634 0.777 0.800 0.500 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] plant pot : 0.232 0.646 0.695 0.688 0.688 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] exhaust fan : 0.232 0.400 0.400 1.000 0.400 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] cup : 0.218 0.365 0.427 0.938 0.341 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] coat hanger : 0.144 0.396 0.573 0.667 0.500 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] light switch : 0.264 0.529 0.657 0.805 0.508 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] speaker : 0.356 0.432 0.432 0.700 0.636 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] kettle : 0.389 0.500 0.500 1.000 0.500 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] smoke detector : 0.666 0.829 0.829 0.952 0.833 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] power strip : 0.037 0.088 0.100 0.333 0.300 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] mouse : 0.484 0.700 0.757 0.880 0.688 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] toilet paper : 0.225 0.439 0.555 0.875 0.412 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] paper towel : 0.074 0.158 0.158 0.333 0.250 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] clock : 0.741 1.000 1.000 1.000 1.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.342 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] tap : 0.209 0.415 0.844 0.667 0.444 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.018 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] soap dispenser : 0.530 0.800 0.800 1.000 0.800 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:00:40,759 INFO hook.py line 395 1619929] bowl : 0.259 0.333 0.333 1.000 0.333 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] tissue box : 0.024 0.062 0.083 0.250 0.500 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] whiteboard eraser: 0.272 0.501 0.522 0.714 0.833 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] toilet brush : 0.427 0.629 0.803 0.800 0.667 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] spray bottle : 0.032 0.042 0.042 0.333 0.250 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] stapler : 0.001 0.013 0.067 0.077 0.333 [2025-04-29 22:00:40,760 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:00:40,760 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 22:00:40,760 INFO hook.py line 404 1619929] average : 0.274 0.410 0.497 0.626 0.490 [2025-04-29 22:00:40,760 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 22:00:40,760 INFO hook.py line 480 1619929] Total Process Time: 24.384 s [2025-04-29 22:00:40,760 INFO hook.py line 481 1619929] Average Process Time: 492.737 ms [2025-04-29 22:00:40,761 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 22:00:40,803 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 22:00:40,808 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:02:15,488 INFO hook.py line 650 1619929] Train: [409/512][50/242] Data 0.017 (0.038) Batch 1.410 (1.538) Remain 10:44:02 loss: 4.6526 Lr: 7.14516e-05 Mem R(MA/MR): 20910 (21973/36182) [2025-04-29 22:03:27,557 INFO hook.py line 650 1619929] Train: [409/512][100/242] Data 0.018 (0.027) Batch 1.425 (1.488) Remain 10:21:51 loss: 5.3376 Lr: 7.13238e-05 Mem R(MA/MR): 23958 (21973/36182) [2025-04-29 22:04:38,365 INFO hook.py line 650 1619929] Train: [409/512][150/242] Data 0.017 (0.023) Batch 1.478 (1.464) Remain 10:10:22 loss: 5.1662 Lr: 7.11960e-05 Mem R(MA/MR): 25840 (21973/36182) [2025-04-29 22:05:51,462 INFO hook.py line 650 1619929] Train: [409/512][200/242] Data 0.015 (0.021) Batch 1.383 (1.463) Remain 10:08:57 loss: 3.7094 Lr: 7.10681e-05 Mem R(MA/MR): 25840 (21973/36182) [2025-04-29 22:06:47,363 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2506 loss_mask: 0.0324 loss_dice: 1.8108 loss_score: 0.0000 loss_bbox: 0.0473 loss_sp_cls: 0.7126 loss: 4.5924 [2025-04-29 22:06:52,542 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:08:21,969 INFO hook.py line 650 1619929] Train: [410/512][50/242] Data 0.016 (0.017) Batch 1.518 (1.526) Remain 10:32:34 loss: 4.8914 Lr: 7.08354e-05 Mem R(MA/MR): 23924 (21973/36182) [2025-04-29 22:09:36,098 INFO hook.py line 650 1619929] Train: [410/512][100/242] Data 0.017 (0.016) Batch 1.404 (1.503) Remain 10:22:05 loss: 4.6741 Lr: 7.07075e-05 Mem R(MA/MR): 24748 (21973/36182) [2025-04-29 22:10:50,616 INFO hook.py line 650 1619929] Train: [410/512][150/242] Data 0.016 (0.017) Batch 1.477 (1.499) Remain 10:18:59 loss: 3.9716 Lr: 7.05795e-05 Mem R(MA/MR): 26576 (21973/36182) [2025-04-29 22:12:02,643 INFO hook.py line 650 1619929] Train: [410/512][200/242] Data 0.015 (0.017) Batch 1.337 (1.484) Remain 10:11:37 loss: 4.9662 Lr: 7.04515e-05 Mem R(MA/MR): 26582 (21973/36182) [2025-04-29 22:12:59,741 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2560 loss_mask: 0.0326 loss_dice: 1.8234 loss_score: 0.0000 loss_bbox: 0.0481 loss_sp_cls: 0.7181 loss: 4.6349 [2025-04-29 22:12:59,820 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:14:32,649 INFO hook.py line 650 1619929] Train: [411/512][50/242] Data 0.017 (0.017) Batch 1.412 (1.459) Remain 09:58:54 loss: 4.0022 Lr: 7.02160e-05 Mem R(MA/MR): 21634 (21973/36182) [2025-04-29 22:15:43,992 INFO hook.py line 650 1619929] Train: [411/512][100/242] Data 0.016 (0.017) Batch 1.419 (1.442) Remain 09:50:58 loss: 4.3514 Lr: 7.00880e-05 Mem R(MA/MR): 21636 (21973/36182) [2025-04-29 22:16:56,138 INFO hook.py line 650 1619929] Train: [411/512][150/242] Data 0.016 (0.017) Batch 1.445 (1.443) Remain 09:49:50 loss: 4.5294 Lr: 6.99599e-05 Mem R(MA/MR): 21636 (21973/36182) [2025-04-29 22:18:07,789 INFO hook.py line 650 1619929] Train: [411/512][200/242] Data 0.014 (0.017) Batch 1.331 (1.440) Remain 09:47:39 loss: 5.6833 Lr: 6.98318e-05 Mem R(MA/MR): 23464 (21973/36182) [2025-04-29 22:19:05,589 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2529 loss_mask: 0.0329 loss_dice: 1.8349 loss_score: 0.0000 loss_bbox: 0.0471 loss_sp_cls: 0.7175 loss: 4.6327 [2025-04-29 22:19:06,892 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:20:43,182 INFO hook.py line 650 1619929] Train: [412/512][50/242] Data 0.018 (0.020) Batch 1.405 (1.531) Remain 10:22:15 loss: 5.6003 Lr: 6.95960e-05 Mem R(MA/MR): 23974 (21973/36182) [2025-04-29 22:21:55,985 INFO hook.py line 650 1619929] Train: [412/512][100/242] Data 0.016 (0.018) Batch 1.551 (1.492) Remain 10:05:23 loss: 4.8889 Lr: 6.94678e-05 Mem R(MA/MR): 23992 (21973/36182) [2025-04-29 22:23:08,894 INFO hook.py line 650 1619929] Train: [412/512][150/242] Data 0.016 (0.018) Batch 1.531 (1.481) Remain 09:59:27 loss: 5.0098 Lr: 6.93396e-05 Mem R(MA/MR): 23994 (21973/36182) [2025-04-29 22:24:20,329 INFO hook.py line 650 1619929] Train: [412/512][200/242] Data 0.015 (0.017) Batch 1.412 (1.467) Remain 09:52:53 loss: 4.8026 Lr: 6.92114e-05 Mem R(MA/MR): 23994 (21973/36182) [2025-04-29 22:25:18,732 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2611 loss_mask: 0.0328 loss_dice: 1.8315 loss_score: 0.0000 loss_bbox: 0.0470 loss_sp_cls: 0.7210 loss: 4.6517 [2025-04-29 22:25:18,998 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:26:48,182 INFO hook.py line 650 1619929] Train: [413/512][50/242] Data 0.015 (0.016) Batch 1.413 (1.432) Remain 09:36:16 loss: 4.6327 Lr: 6.89754e-05 Mem R(MA/MR): 20502 (21973/36182) [2025-04-29 22:28:00,497 INFO hook.py line 650 1619929] Train: [413/512][100/242] Data 0.018 (0.016) Batch 1.609 (1.439) Remain 09:38:05 loss: 4.9263 Lr: 6.88471e-05 Mem R(MA/MR): 20502 (21973/36182) [2025-04-29 22:29:13,747 INFO hook.py line 650 1619929] Train: [413/512][150/242] Data 0.016 (0.016) Batch 1.481 (1.448) Remain 09:40:23 loss: 4.7011 Lr: 6.87188e-05 Mem R(MA/MR): 22274 (21973/36182) [2025-04-29 22:30:26,275 INFO hook.py line 650 1619929] Train: [413/512][200/242] Data 0.015 (0.017) Batch 1.390 (1.449) Remain 09:39:27 loss: 3.7804 Lr: 6.85904e-05 Mem R(MA/MR): 22274 (21973/36182) [2025-04-29 22:31:23,222 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2546 loss_mask: 0.0327 loss_dice: 1.8146 loss_score: 0.0000 loss_bbox: 0.0476 loss_sp_cls: 0.7169 loss: 4.6162 [2025-04-29 22:31:25,139 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:32:59,584 INFO hook.py line 650 1619929] Train: [414/512][50/242] Data 0.016 (0.017) Batch 1.375 (1.481) Remain 09:50:08 loss: 4.0907 Lr: 6.83542e-05 Mem R(MA/MR): 20566 (21973/36182) [2025-04-29 22:34:13,952 INFO hook.py line 650 1619929] Train: [414/512][100/242] Data 0.017 (0.017) Batch 1.515 (1.484) Remain 09:50:12 loss: 5.1108 Lr: 6.82258e-05 Mem R(MA/MR): 20570 (21973/36182) [2025-04-29 22:35:28,277 INFO hook.py line 650 1619929] Train: [414/512][150/242] Data 0.015 (0.017) Batch 1.329 (1.485) Remain 09:49:16 loss: 4.3321 Lr: 6.80973e-05 Mem R(MA/MR): 22746 (21973/36182) [2025-04-29 22:36:40,597 INFO hook.py line 650 1619929] Train: [414/512][200/242] Data 0.015 (0.017) Batch 1.422 (1.475) Remain 09:44:08 loss: 5.0949 Lr: 6.79688e-05 Mem R(MA/MR): 22746 (21973/36182) [2025-04-29 22:37:36,198 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2541 loss_mask: 0.0325 loss_dice: 1.8240 loss_score: 0.0000 loss_bbox: 0.0471 loss_sp_cls: 0.7150 loss: 4.6189 [2025-04-29 22:37:36,901 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:39:05,889 INFO hook.py line 650 1619929] Train: [415/512][50/242] Data 0.016 (0.018) Batch 1.454 (1.470) Remain 09:39:56 loss: 4.2718 Lr: 6.77324e-05 Mem R(MA/MR): 22020 (21973/36182) [2025-04-29 22:40:18,806 INFO hook.py line 650 1619929] Train: [415/512][100/242] Data 0.018 (0.017) Batch 1.527 (1.464) Remain 09:36:16 loss: 4.6731 Lr: 6.76038e-05 Mem R(MA/MR): 23872 (21973/36182) [2025-04-29 22:41:30,479 INFO hook.py line 650 1619929] Train: [415/512][150/242] Data 0.016 (0.017) Batch 1.401 (1.454) Remain 09:30:57 loss: 4.1659 Lr: 6.74752e-05 Mem R(MA/MR): 23872 (21973/36182) [2025-04-29 22:42:42,882 INFO hook.py line 650 1619929] Train: [415/512][200/242] Data 0.016 (0.017) Batch 1.302 (1.452) Remain 09:29:11 loss: 5.2046 Lr: 6.73466e-05 Mem R(MA/MR): 23872 (21973/36182) [2025-04-29 22:43:39,442 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2527 loss_mask: 0.0328 loss_dice: 1.8120 loss_score: 0.0000 loss_bbox: 0.0470 loss_sp_cls: 0.7201 loss: 4.5987 [2025-04-29 22:43:42,221 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:45:16,886 INFO hook.py line 650 1619929] Train: [416/512][50/242] Data 0.016 (0.017) Batch 1.412 (1.473) Remain 09:34:58 loss: 4.3025 Lr: 6.71099e-05 Mem R(MA/MR): 23918 (21973/36182) [2025-04-29 22:46:28,582 INFO hook.py line 650 1619929] Train: [416/512][100/242] Data 0.017 (0.017) Batch 1.494 (1.453) Remain 09:25:55 loss: 4.6652 Lr: 6.69812e-05 Mem R(MA/MR): 23922 (21973/36182) [2025-04-29 22:47:42,483 INFO hook.py line 650 1619929] Train: [416/512][150/242] Data 0.018 (0.017) Batch 1.553 (1.461) Remain 09:28:04 loss: 5.6241 Lr: 6.68525e-05 Mem R(MA/MR): 23932 (21973/36182) [2025-04-29 22:48:53,003 INFO hook.py line 650 1619929] Train: [416/512][200/242] Data 0.015 (0.017) Batch 1.385 (1.448) Remain 09:21:50 loss: 5.7595 Lr: 6.67237e-05 Mem R(MA/MR): 23934 (21973/36182) [2025-04-29 22:49:49,197 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2503 loss_mask: 0.0326 loss_dice: 1.8124 loss_score: 0.0000 loss_bbox: 0.0472 loss_sp_cls: 0.7148 loss: 4.5922 [2025-04-29 22:49:53,201 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 22:49:55,584 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2972 Process Time: 0.280 Mem R(MA/MR): 4116 (21973/36182) [2025-04-29 22:49:57,317 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9029 Process Time: 0.534 Mem R(MA/MR): 7236 (21973/36182) [2025-04-29 22:49:59,021 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.0646 Process Time: 0.698 Mem R(MA/MR): 9506 (21973/36182) [2025-04-29 22:50:05,713 INFO hook.py line 449 1619929] Test: [4/50] Loss 6.4111 Process Time: 1.326 Mem R(MA/MR): 19632 (21973/36182) [2025-04-29 22:50:06,556 INFO hook.py line 449 1619929] Test: [5/50] Loss 4.7520 Process Time: 0.267 Mem R(MA/MR): 6928 (21973/36182) [2025-04-29 22:50:07,989 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.2721 Process Time: 0.450 Mem R(MA/MR): 11550 (21973/36182) [2025-04-29 22:50:08,746 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0693 Process Time: 0.273 Mem R(MA/MR): 6278 (21973/36182) [2025-04-29 22:50:09,178 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.8410 Process Time: 0.124 Mem R(MA/MR): 4118 (21973/36182) [2025-04-29 22:50:10,040 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0435 Process Time: 0.251 Mem R(MA/MR): 11684 (21973/36182) [2025-04-29 22:50:11,462 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6509 Process Time: 0.255 Mem R(MA/MR): 9338 (21973/36182) [2025-04-29 22:50:13,875 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.1855 Process Time: 0.468 Mem R(MA/MR): 18646 (21973/36182) [2025-04-29 22:50:16,352 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9129 Process Time: 0.498 Mem R(MA/MR): 15336 (21973/36182) [2025-04-29 22:50:17,348 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.9463 Process Time: 0.236 Mem R(MA/MR): 8572 (21973/36182) [2025-04-29 22:50:17,682 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2169 Process Time: 0.118 Mem R(MA/MR): 4496 (21973/36182) [2025-04-29 22:50:20,216 INFO hook.py line 449 1619929] Test: [15/50] Loss 14.4074 Process Time: 0.319 Mem R(MA/MR): 16544 (21973/36182) [2025-04-29 22:50:21,637 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.9442 Process Time: 0.252 Mem R(MA/MR): 14594 (21973/36182) [2025-04-29 22:50:22,248 INFO hook.py line 449 1619929] Test: [17/50] Loss 4.7469 Process Time: 0.164 Mem R(MA/MR): 6596 (21973/36182) [2025-04-29 22:50:23,399 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6849 Process Time: 0.459 Mem R(MA/MR): 8222 (21973/36182) [2025-04-29 22:50:24,521 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5396 Process Time: 0.176 Mem R(MA/MR): 5890 (21973/36182) [2025-04-29 22:50:25,976 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.3366 Process Time: 0.292 Mem R(MA/MR): 11840 (21973/36182) [2025-04-29 22:50:34,644 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.0626 Process Time: 0.832 Mem R(MA/MR): 23558 (21973/36182) [2025-04-29 22:50:35,254 INFO hook.py line 449 1619929] Test: [22/50] Loss 4.9918 Process Time: 0.165 Mem R(MA/MR): 6900 (21973/36182) [2025-04-29 22:50:47,250 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.2569 Process Time: 0.389 Mem R(MA/MR): 10334 (21973/36182) [2025-04-29 22:50:48,165 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.6220 Process Time: 0.343 Mem R(MA/MR): 5570 (21973/36182) [2025-04-29 22:50:49,255 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1050 Process Time: 0.257 Mem R(MA/MR): 8728 (21973/36182) [2025-04-29 22:50:56,982 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.5137 Process Time: 1.840 Mem R(MA/MR): 31422 (21973/36182) [2025-04-29 22:50:59,673 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5162 Process Time: 0.511 Mem R(MA/MR): 9680 (21973/36182) [2025-04-29 22:51:00,776 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.2539 Process Time: 0.233 Mem R(MA/MR): 8342 (21973/36182) [2025-04-29 22:51:05,082 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.9065 Process Time: 0.449 Mem R(MA/MR): 16966 (21973/36182) [2025-04-29 22:51:06,448 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.9533 Process Time: 0.441 Mem R(MA/MR): 7788 (21973/36182) [2025-04-29 22:51:09,890 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.6312 Process Time: 0.430 Mem R(MA/MR): 20402 (21973/36182) [2025-04-29 22:51:10,117 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.6714 Process Time: 0.101 Mem R(MA/MR): 3892 (21973/36182) [2025-04-29 22:51:13,617 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.1779 Process Time: 0.378 Mem R(MA/MR): 24522 (21973/36182) [2025-04-29 22:51:14,570 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4234 Process Time: 0.235 Mem R(MA/MR): 9092 (21973/36182) [2025-04-29 22:51:16,904 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.1400 Process Time: 0.815 Mem R(MA/MR): 14276 (21973/36182) [2025-04-29 22:51:17,558 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1757 Process Time: 0.269 Mem R(MA/MR): 6422 (21973/36182) [2025-04-29 22:51:21,047 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.1654 Process Time: 0.457 Mem R(MA/MR): 28252 (21973/36182) [2025-04-29 22:51:22,400 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1432 Process Time: 0.241 Mem R(MA/MR): 10308 (21973/36182) [2025-04-29 22:51:23,033 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3852 Process Time: 0.232 Mem R(MA/MR): 5662 (21973/36182) [2025-04-29 22:51:24,129 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8243 Process Time: 0.339 Mem R(MA/MR): 9716 (21973/36182) [2025-04-29 22:51:25,162 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0675 Process Time: 0.255 Mem R(MA/MR): 8440 (21973/36182) [2025-04-29 22:51:25,643 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9968 Process Time: 0.125 Mem R(MA/MR): 5704 (21973/36182) [2025-04-29 22:51:26,101 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6663 Process Time: 0.189 Mem R(MA/MR): 5776 (21973/36182) [2025-04-29 22:51:26,929 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.5128 Process Time: 0.324 Mem R(MA/MR): 7160 (21973/36182) [2025-04-29 22:51:27,432 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.8413 Process Time: 0.132 Mem R(MA/MR): 5336 (21973/36182) [2025-04-29 22:51:29,208 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.5857 Process Time: 0.275 Mem R(MA/MR): 14646 (21973/36182) [2025-04-29 22:51:35,966 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.3393 Process Time: 1.138 Mem R(MA/MR): 20056 (21973/36182) [2025-04-29 22:51:45,949 INFO hook.py line 449 1619929] Test: [48/50] Loss 14.1701 Process Time: 1.630 Mem R(MA/MR): 35150 (21973/36182) [2025-04-29 22:51:46,526 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.8978 Process Time: 0.141 Mem R(MA/MR): 5858 (21973/36182) [2025-04-29 22:51:48,612 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.6522 Process Time: 0.352 Mem R(MA/MR): 13928 (21973/36182) [2025-04-29 22:51:53,237 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 22:51:53,237 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 22:51:53,237 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] table : 0.263 0.574 0.733 0.822 0.610 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] door : 0.499 0.831 0.927 0.877 0.810 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] ceiling lamp : 0.582 0.774 0.880 0.855 0.751 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] cabinet : 0.320 0.461 0.491 0.487 0.567 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] blinds : 0.561 0.783 0.804 0.850 0.739 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] curtain : 0.507 0.652 0.802 0.643 0.750 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] chair : 0.627 0.755 0.799 0.712 0.799 [2025-04-29 22:51:53,237 INFO hook.py line 395 1619929] storage cabinet: 0.270 0.358 0.481 0.520 0.520 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] office chair : 0.584 0.642 0.658 0.714 0.729 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] bookshelf : 0.123 0.335 0.633 0.545 0.545 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] whiteboard : 0.537 0.732 0.774 0.923 0.686 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] window : 0.131 0.299 0.653 0.538 0.385 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] box : 0.205 0.346 0.517 0.575 0.359 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] monitor : 0.627 0.776 0.875 0.981 0.729 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] shelf : 0.133 0.310 0.525 0.361 0.433 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] heater : 0.459 0.734 0.875 0.833 0.789 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] kitchen cabinet: 0.077 0.211 0.543 0.364 0.480 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] sofa : 0.428 0.572 0.872 0.875 0.583 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] bed : 0.248 0.558 1.000 0.714 0.625 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] trash can : 0.511 0.653 0.715 0.746 0.769 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] book : 0.019 0.034 0.062 0.160 0.105 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] plant : 0.396 0.591 0.691 0.917 0.611 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] blanket : 0.545 0.654 0.654 0.875 0.636 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] tv : 0.930 1.000 1.000 1.000 1.000 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] computer tower : 0.213 0.362 0.594 0.581 0.429 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] refrigerator : 0.201 0.389 0.395 1.000 0.333 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] jacket : 0.109 0.241 0.488 0.500 0.364 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] sink : 0.457 0.820 0.870 0.818 0.818 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] bag : 0.115 0.194 0.265 0.417 0.370 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] picture : 0.166 0.318 0.383 0.583 0.359 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] pillow : 0.545 0.776 0.776 0.667 0.842 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] towel : 0.172 0.312 0.461 0.542 0.342 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] suitcase : 0.417 0.596 0.649 0.714 0.714 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] backpack : 0.547 0.762 0.762 0.909 0.769 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] crate : 0.057 0.227 0.340 0.625 0.455 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] keyboard : 0.404 0.575 0.657 0.840 0.538 [2025-04-29 22:51:53,238 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] toilet : 0.865 0.876 1.000 0.889 0.889 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] printer : 0.321 0.444 0.444 1.000 0.444 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] poster : 0.001 0.009 0.018 0.167 0.111 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] painting : 0.061 0.071 0.071 0.143 1.000 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] microwave : 0.631 0.750 0.875 1.000 0.750 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] shoes : 0.116 0.217 0.525 0.577 0.366 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] socket : 0.211 0.484 0.689 0.786 0.471 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] bottle : 0.090 0.157 0.314 0.375 0.289 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] bucket : 0.102 0.175 0.175 0.286 0.286 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] cushion : 0.144 0.224 0.224 0.357 0.833 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] basket : 0.006 0.009 0.010 0.125 0.143 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] telephone : 0.361 0.576 0.688 0.909 0.588 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] laptop : 0.403 0.683 0.774 0.500 1.000 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] plant pot : 0.263 0.557 0.553 0.714 0.625 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] exhaust fan : 0.198 0.350 0.362 0.667 0.400 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] cup : 0.251 0.405 0.450 0.941 0.364 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] coat hanger : 0.167 0.500 0.637 1.000 0.500 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] light switch : 0.285 0.542 0.676 0.740 0.569 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] speaker : 0.458 0.547 0.634 0.714 0.455 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] smoke detector : 0.611 0.812 0.813 1.000 0.708 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 1.000 0.000 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] power strip : 0.063 0.146 0.176 0.400 0.400 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,239 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] mouse : 0.469 0.714 0.738 1.000 0.625 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] cutting board : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] toilet paper : 0.303 0.412 0.412 1.000 0.412 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] paper towel : 0.014 0.031 0.125 0.500 0.125 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] clock : 0.481 0.667 0.667 1.000 0.667 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] pan : 0.139 0.250 0.458 1.000 0.250 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] tap : 0.147 0.326 0.667 0.667 0.444 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] soap dispenser : 0.525 0.800 0.800 1.000 0.800 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] bowl : 0.235 0.278 0.278 0.667 0.667 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] whiteboard eraser: 0.253 0.522 0.522 0.833 0.833 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] toilet brush : 0.498 0.667 0.833 1.000 0.667 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] spray bottle : 0.008 0.011 0.013 0.091 0.250 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] headphones : 0.355 0.662 0.708 1.000 0.500 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] stapler : 0.037 0.131 0.249 0.333 0.667 [2025-04-29 22:51:53,240 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 22:51:53,240 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 22:51:53,240 INFO hook.py line 404 1619929] average : 0.280 0.419 0.510 0.640 0.495 [2025-04-29 22:51:53,240 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 22:51:53,241 INFO hook.py line 480 1619929] Total Process Time: 20.958 s [2025-04-29 22:51:53,241 INFO hook.py line 481 1619929] Average Process Time: 422.004 ms [2025-04-29 22:51:53,241 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 22:51:53,276 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 22:51:53,281 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:53:26,534 INFO hook.py line 650 1619929] Train: [417/512][50/242] Data 0.018 (0.017) Batch 1.469 (1.466) Remain 09:26:18 loss: 4.1472 Lr: 6.64868e-05 Mem R(MA/MR): 18842 (21973/36182) [2025-04-29 22:54:39,798 INFO hook.py line 650 1619929] Train: [417/512][100/242] Data 0.017 (0.017) Batch 1.471 (1.466) Remain 09:25:00 loss: 4.5527 Lr: 6.63579e-05 Mem R(MA/MR): 19482 (21973/36182) [2025-04-29 22:55:50,596 INFO hook.py line 650 1619929] Train: [417/512][150/242] Data 0.019 (0.017) Batch 1.545 (1.449) Remain 09:17:18 loss: 4.6859 Lr: 6.62291e-05 Mem R(MA/MR): 19506 (21973/36182) [2025-04-29 22:57:04,176 INFO hook.py line 650 1619929] Train: [417/512][200/242] Data 0.015 (0.022) Batch 1.346 (1.454) Remain 09:18:19 loss: 4.3287 Lr: 6.61002e-05 Mem R(MA/MR): 19506 (21973/36182) [2025-04-29 22:58:03,614 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2523 loss_mask: 0.0329 loss_dice: 1.8100 loss_score: 0.0000 loss_bbox: 0.0481 loss_sp_cls: 0.7109 loss: 4.6039 [2025-04-29 22:58:07,779 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 22:59:43,480 INFO hook.py line 650 1619929] Train: [418/512][50/242] Data 0.015 (0.017) Batch 1.442 (1.497) Remain 09:32:17 loss: 4.2756 Lr: 6.58630e-05 Mem R(MA/MR): 26800 (21973/36182) [2025-04-29 23:00:56,873 INFO hook.py line 650 1619929] Train: [418/512][100/242] Data 0.018 (0.017) Batch 1.529 (1.482) Remain 09:25:20 loss: 4.9347 Lr: 6.57340e-05 Mem R(MA/MR): 28696 (21973/36182) [2025-04-29 23:02:08,181 INFO hook.py line 650 1619929] Train: [418/512][150/242] Data 0.017 (0.017) Batch 1.341 (1.463) Remain 09:16:53 loss: 3.8280 Lr: 6.56050e-05 Mem R(MA/MR): 28696 (21973/36182) [2025-04-29 23:03:19,651 INFO hook.py line 650 1619929] Train: [418/512][200/242] Data 0.015 (0.017) Batch 1.405 (1.454) Remain 09:12:26 loss: 4.4920 Lr: 6.54760e-05 Mem R(MA/MR): 28696 (21973/36182) [2025-04-29 23:04:16,383 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2461 loss_mask: 0.0319 loss_dice: 1.7982 loss_score: 0.0000 loss_bbox: 0.0465 loss_sp_cls: 0.7101 loss: 4.5543 [2025-04-29 23:04:17,797 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:05:50,774 INFO hook.py line 650 1619929] Train: [419/512][50/242] Data 0.014 (0.016) Batch 1.240 (1.417) Remain 08:56:08 loss: 4.9036 Lr: 6.52385e-05 Mem R(MA/MR): 24050 (21973/36182) [2025-04-29 23:07:02,475 INFO hook.py line 650 1619929] Train: [419/512][100/242] Data 0.016 (0.016) Batch 1.434 (1.426) Remain 08:58:12 loss: 3.6429 Lr: 6.51095e-05 Mem R(MA/MR): 24068 (21973/36182) [2025-04-29 23:08:13,144 INFO hook.py line 650 1619929] Train: [419/512][150/242] Data 0.017 (0.017) Batch 1.501 (1.422) Remain 08:55:25 loss: 4.2639 Lr: 6.49803e-05 Mem R(MA/MR): 24068 (21973/36182) [2025-04-29 23:09:24,159 INFO hook.py line 650 1619929] Train: [419/512][200/242] Data 0.014 (0.017) Batch 1.454 (1.421) Remain 08:54:07 loss: 5.0111 Lr: 6.48512e-05 Mem R(MA/MR): 24068 (21973/36182) [2025-04-29 23:10:20,960 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2430 loss_mask: 0.0312 loss_dice: 1.7603 loss_score: 0.0000 loss_bbox: 0.0470 loss_sp_cls: 0.7002 loss: 4.4783 [2025-04-29 23:10:24,089 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:11:56,277 INFO hook.py line 650 1619929] Train: [420/512][50/242] Data 0.018 (0.017) Batch 1.525 (1.459) Remain 09:05:55 loss: 4.3856 Lr: 6.46135e-05 Mem R(MA/MR): 25476 (21973/36182) [2025-04-29 23:13:09,063 INFO hook.py line 650 1619929] Train: [420/512][100/242] Data 0.017 (0.017) Batch 1.511 (1.457) Remain 09:04:08 loss: 5.0503 Lr: 6.44868e-05 Mem R(MA/MR): 25488 (21973/36182) [2025-04-29 23:14:20,754 INFO hook.py line 650 1619929] Train: [420/512][150/242] Data 0.016 (0.017) Batch 1.438 (1.449) Remain 08:59:58 loss: 4.4188 Lr: 6.43575e-05 Mem R(MA/MR): 27980 (21973/36182) [2025-04-29 23:15:33,367 INFO hook.py line 650 1619929] Train: [420/512][200/242] Data 0.016 (0.017) Batch 1.397 (1.450) Remain 08:59:03 loss: 3.8454 Lr: 6.42282e-05 Mem R(MA/MR): 27980 (21973/36182) [2025-04-29 23:16:30,890 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2504 loss_mask: 0.0321 loss_dice: 1.8050 loss_score: 0.0000 loss_bbox: 0.0474 loss_sp_cls: 0.7055 loss: 4.5759 [2025-04-29 23:16:34,393 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:18:08,123 INFO hook.py line 650 1619929] Train: [421/512][50/242] Data 0.015 (0.017) Batch 1.397 (1.416) Remain 08:44:09 loss: 4.7911 Lr: 6.39903e-05 Mem R(MA/MR): 19610 (21973/36182) [2025-04-29 23:19:21,002 INFO hook.py line 650 1619929] Train: [421/512][100/242] Data 0.016 (0.017) Batch 1.527 (1.437) Remain 08:50:56 loss: 5.2387 Lr: 6.38609e-05 Mem R(MA/MR): 21738 (21973/36182) [2025-04-29 23:20:33,874 INFO hook.py line 650 1619929] Train: [421/512][150/242] Data 0.017 (0.017) Batch 1.472 (1.444) Remain 08:52:15 loss: 5.1929 Lr: 6.37315e-05 Mem R(MA/MR): 21738 (21973/36182) [2025-04-29 23:21:48,642 INFO hook.py line 650 1619929] Train: [421/512][200/242] Data 0.015 (0.017) Batch 1.360 (1.457) Remain 08:55:50 loss: 5.4449 Lr: 6.36021e-05 Mem R(MA/MR): 21744 (21973/36182) [2025-04-29 23:22:46,538 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2539 loss_mask: 0.0322 loss_dice: 1.8078 loss_score: 0.0000 loss_bbox: 0.0478 loss_sp_cls: 0.7111 loss: 4.5933 [2025-04-29 23:22:50,546 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:24:27,547 INFO hook.py line 650 1619929] Train: [422/512][50/242] Data 0.016 (0.017) Batch 1.321 (1.527) Remain 09:19:05 loss: 4.7072 Lr: 6.33638e-05 Mem R(MA/MR): 22690 (21973/36182) [2025-04-29 23:25:39,123 INFO hook.py line 650 1619929] Train: [422/512][100/242] Data 0.019 (0.017) Batch 1.481 (1.478) Remain 08:59:52 loss: 4.2196 Lr: 6.32343e-05 Mem R(MA/MR): 22690 (21973/36182) [2025-04-29 23:26:50,031 INFO hook.py line 650 1619929] Train: [422/512][150/242] Data 0.016 (0.017) Batch 1.403 (1.457) Remain 08:51:16 loss: 4.7183 Lr: 6.31048e-05 Mem R(MA/MR): 22690 (21973/36182) [2025-04-29 23:28:02,478 INFO hook.py line 650 1619929] Train: [422/512][200/242] Data 0.014 (0.016) Batch 1.365 (1.455) Remain 08:49:16 loss: 3.6393 Lr: 6.29752e-05 Mem R(MA/MR): 24576 (21973/36182) [2025-04-29 23:29:00,932 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2499 loss_mask: 0.0320 loss_dice: 1.7905 loss_score: 0.0000 loss_bbox: 0.0467 loss_sp_cls: 0.7118 loss: 4.5482 [2025-04-29 23:29:04,486 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:30:32,405 INFO hook.py line 650 1619929] Train: [423/512][50/242] Data 0.018 (0.017) Batch 1.628 (1.480) Remain 08:56:08 loss: 5.1435 Lr: 6.27367e-05 Mem R(MA/MR): 19902 (21973/36182) [2025-04-29 23:31:44,432 INFO hook.py line 650 1619929] Train: [423/512][100/242] Data 0.016 (0.017) Batch 1.395 (1.460) Remain 08:47:28 loss: 3.9221 Lr: 6.26070e-05 Mem R(MA/MR): 19902 (21973/36182) [2025-04-29 23:32:57,807 INFO hook.py line 650 1619929] Train: [423/512][150/242] Data 0.018 (0.017) Batch 1.403 (1.462) Remain 08:47:12 loss: 4.2988 Lr: 6.24773e-05 Mem R(MA/MR): 19904 (21973/36182) [2025-04-29 23:34:10,504 INFO hook.py line 650 1619929] Train: [423/512][200/242] Data 0.014 (0.017) Batch 1.485 (1.460) Remain 08:45:12 loss: 4.5393 Lr: 6.23476e-05 Mem R(MA/MR): 23974 (21973/36182) [2025-04-29 23:35:08,018 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2516 loss_mask: 0.0320 loss_dice: 1.8068 loss_score: 0.0000 loss_bbox: 0.0473 loss_sp_cls: 0.7059 loss: 4.5819 [2025-04-29 23:35:12,105 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:36:49,539 INFO hook.py line 650 1619929] Train: [424/512][50/242] Data 0.017 (0.017) Batch 1.580 (1.492) Remain 08:54:26 loss: 4.2514 Lr: 6.21089e-05 Mem R(MA/MR): 20876 (21973/36182) [2025-04-29 23:38:02,072 INFO hook.py line 650 1619929] Train: [424/512][100/242] Data 0.015 (0.017) Batch 1.462 (1.471) Remain 08:45:31 loss: 4.8887 Lr: 6.19791e-05 Mem R(MA/MR): 20880 (21973/36182) [2025-04-29 23:39:13,765 INFO hook.py line 650 1619929] Train: [424/512][150/242] Data 0.016 (0.017) Batch 1.478 (1.458) Remain 08:39:49 loss: 4.7320 Lr: 6.18492e-05 Mem R(MA/MR): 21568 (21973/36182) [2025-04-29 23:40:25,385 INFO hook.py line 650 1619929] Train: [424/512][200/242] Data 0.015 (0.017) Batch 1.265 (1.452) Remain 08:36:16 loss: 4.3277 Lr: 6.17194e-05 Mem R(MA/MR): 22280 (21973/36182) [2025-04-29 23:41:22,397 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2490 loss_mask: 0.0327 loss_dice: 1.7998 loss_score: 0.0000 loss_bbox: 0.0468 loss_sp_cls: 0.7112 loss: 4.5668 [2025-04-29 23:41:25,009 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-29 23:41:27,372 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1815 Process Time: 0.295 Mem R(MA/MR): 4282 (21973/36182) [2025-04-29 23:41:29,109 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8569 Process Time: 0.524 Mem R(MA/MR): 7100 (21973/36182) [2025-04-29 23:41:31,176 INFO hook.py line 449 1619929] Test: [3/50] Loss 6.8780 Process Time: 1.006 Mem R(MA/MR): 9694 (21973/36182) [2025-04-29 23:41:38,509 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4538 Process Time: 0.897 Mem R(MA/MR): 19506 (21973/36182) [2025-04-29 23:41:39,521 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.1631 Process Time: 0.386 Mem R(MA/MR): 6946 (21973/36182) [2025-04-29 23:41:41,099 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7136 Process Time: 0.552 Mem R(MA/MR): 11034 (21973/36182) [2025-04-29 23:41:41,688 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0605 Process Time: 0.207 Mem R(MA/MR): 6258 (21973/36182) [2025-04-29 23:41:42,198 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.0695 Process Time: 0.184 Mem R(MA/MR): 4286 (21973/36182) [2025-04-29 23:41:43,084 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.4791 Process Time: 0.283 Mem R(MA/MR): 11318 (21973/36182) [2025-04-29 23:41:44,439 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4898 Process Time: 0.244 Mem R(MA/MR): 9432 (21973/36182) [2025-04-29 23:41:47,331 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.9801 Process Time: 0.937 Mem R(MA/MR): 18708 (21973/36182) [2025-04-29 23:41:50,059 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3339 Process Time: 0.797 Mem R(MA/MR): 15134 (21973/36182) [2025-04-29 23:41:51,266 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.5138 Process Time: 0.380 Mem R(MA/MR): 8526 (21973/36182) [2025-04-29 23:41:51,670 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9367 Process Time: 0.141 Mem R(MA/MR): 4612 (21973/36182) [2025-04-29 23:41:54,326 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.5409 Process Time: 0.367 Mem R(MA/MR): 16628 (21973/36182) [2025-04-29 23:41:56,378 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.1379 Process Time: 0.680 Mem R(MA/MR): 14526 (21973/36182) [2025-04-29 23:41:57,215 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2918 Process Time: 0.297 Mem R(MA/MR): 6570 (21973/36182) [2025-04-29 23:41:58,273 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7725 Process Time: 0.424 Mem R(MA/MR): 7936 (21973/36182) [2025-04-29 23:41:59,527 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6761 Process Time: 0.197 Mem R(MA/MR): 5928 (21973/36182) [2025-04-29 23:42:01,083 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.9277 Process Time: 0.244 Mem R(MA/MR): 11140 (21973/36182) [2025-04-29 23:42:10,112 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.5584 Process Time: 0.596 Mem R(MA/MR): 23902 (21973/36182) [2025-04-29 23:42:10,704 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4209 Process Time: 0.172 Mem R(MA/MR): 6676 (21973/36182) [2025-04-29 23:42:20,079 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.5971 Process Time: 0.407 Mem R(MA/MR): 10080 (21973/36182) [2025-04-29 23:42:20,689 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.6224 Process Time: 0.212 Mem R(MA/MR): 5252 (21973/36182) [2025-04-29 23:42:22,050 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0391 Process Time: 0.604 Mem R(MA/MR): 9186 (21973/36182) [2025-04-29 23:42:28,883 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.8690 Process Time: 1.566 Mem R(MA/MR): 31506 (21973/36182) [2025-04-29 23:42:31,736 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5203 Process Time: 0.857 Mem R(MA/MR): 9736 (21973/36182) [2025-04-29 23:42:33,041 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0886 Process Time: 0.379 Mem R(MA/MR): 8706 (21973/36182) [2025-04-29 23:42:37,925 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.2403 Process Time: 0.504 Mem R(MA/MR): 16900 (21973/36182) [2025-04-29 23:42:38,952 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2240 Process Time: 0.314 Mem R(MA/MR): 7564 (21973/36182) [2025-04-29 23:42:43,579 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.1636 Process Time: 0.867 Mem R(MA/MR): 20550 (21973/36182) [2025-04-29 23:42:43,946 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1673 Process Time: 0.138 Mem R(MA/MR): 3940 (21973/36182) [2025-04-29 23:42:48,241 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.0607 Process Time: 0.647 Mem R(MA/MR): 24644 (21973/36182) [2025-04-29 23:42:49,750 INFO hook.py line 449 1619929] Test: [34/50] Loss 4.0920 Process Time: 0.479 Mem R(MA/MR): 9578 (21973/36182) [2025-04-29 23:42:51,896 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.3354 Process Time: 0.346 Mem R(MA/MR): 13960 (21973/36182) [2025-04-29 23:42:52,398 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2785 Process Time: 0.171 Mem R(MA/MR): 6422 (21973/36182) [2025-04-29 23:42:56,237 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.2631 Process Time: 0.536 Mem R(MA/MR): 28618 (21973/36182) [2025-04-29 23:42:58,394 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.5075 Process Time: 0.669 Mem R(MA/MR): 10628 (21973/36182) [2025-04-29 23:42:58,928 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9600 Process Time: 0.172 Mem R(MA/MR): 5394 (21973/36182) [2025-04-29 23:42:59,983 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7679 Process Time: 0.243 Mem R(MA/MR): 9864 (21973/36182) [2025-04-29 23:43:00,977 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.1382 Process Time: 0.259 Mem R(MA/MR): 8830 (21973/36182) [2025-04-29 23:43:01,539 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1605 Process Time: 0.168 Mem R(MA/MR): 5448 (21973/36182) [2025-04-29 23:43:02,161 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6786 Process Time: 0.284 Mem R(MA/MR): 5506 (21973/36182) [2025-04-29 23:43:02,941 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3159 Process Time: 0.303 Mem R(MA/MR): 7054 (21973/36182) [2025-04-29 23:43:03,689 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7325 Process Time: 0.209 Mem R(MA/MR): 5202 (21973/36182) [2025-04-29 23:43:06,628 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5195 Process Time: 0.794 Mem R(MA/MR): 14362 (21973/36182) [2025-04-29 23:43:13,992 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.4991 Process Time: 0.781 Mem R(MA/MR): 20168 (21973/36182) [2025-04-29 23:43:25,305 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9481 Process Time: 2.305 Mem R(MA/MR): 35834 (21973/36182) [2025-04-29 23:43:26,063 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.8826 Process Time: 0.263 Mem R(MA/MR): 5656 (21973/36182) [2025-04-29 23:43:28,218 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.9988 Process Time: 0.395 Mem R(MA/MR): 13426 (21973/36182) [2025-04-29 23:43:32,102 INFO hook.py line 372 1619929] ################################################################## [2025-04-29 23:43:32,103 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-29 23:43:32,103 INFO hook.py line 381 1619929] ################################################################## [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] table : 0.239 0.517 0.715 0.772 0.574 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] door : 0.461 0.764 0.930 0.892 0.734 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] ceiling lamp : 0.562 0.759 0.872 0.854 0.746 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] cabinet : 0.319 0.477 0.523 0.586 0.507 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] blinds : 0.651 0.862 0.880 0.905 0.826 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] curtain : 0.312 0.608 0.765 0.600 0.750 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] chair : 0.665 0.805 0.841 0.807 0.754 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] storage cabinet: 0.300 0.458 0.522 0.765 0.520 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] office chair : 0.512 0.554 0.567 0.685 0.771 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] bookshelf : 0.153 0.348 0.538 0.636 0.636 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] whiteboard : 0.585 0.789 0.800 0.962 0.714 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] window : 0.123 0.283 0.651 0.559 0.363 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] box : 0.188 0.367 0.514 0.488 0.442 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] monitor : 0.636 0.802 0.864 0.905 0.814 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] shelf : 0.164 0.330 0.484 0.818 0.300 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] heater : 0.453 0.707 0.750 0.935 0.763 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] kitchen cabinet: 0.101 0.338 0.603 0.333 0.600 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] sofa : 0.503 0.624 0.842 0.875 0.583 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] bed : 0.261 0.538 0.663 0.833 0.625 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] trash can : 0.570 0.741 0.768 0.773 0.892 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] book : 0.023 0.039 0.083 0.203 0.101 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] plant : 0.404 0.722 0.759 1.000 0.722 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] blanket : 0.548 0.642 0.717 1.000 0.545 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] computer tower : 0.203 0.339 0.656 0.526 0.476 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] refrigerator : 0.288 0.496 0.533 0.714 0.556 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] jacket : 0.044 0.127 0.488 0.241 0.636 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] sink : 0.414 0.696 0.807 0.882 0.682 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] bag : 0.050 0.087 0.109 0.320 0.296 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] picture : 0.150 0.275 0.390 0.706 0.308 [2025-04-29 23:43:32,103 INFO hook.py line 395 1619929] pillow : 0.666 0.856 0.896 0.800 0.842 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] towel : 0.222 0.356 0.616 0.517 0.395 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] suitcase : 0.409 0.516 0.516 0.556 0.714 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] backpack : 0.470 0.671 0.671 0.800 0.615 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] crate : 0.097 0.218 0.545 0.400 0.364 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] keyboard : 0.496 0.649 0.729 0.622 0.718 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] toilet : 0.857 0.889 1.000 1.000 0.889 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] printer : 0.215 0.335 0.406 0.444 0.444 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.005 0.077 0.111 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] painting : 0.046 0.050 0.050 0.100 1.000 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] microwave : 0.705 0.858 0.969 0.875 0.875 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] shoes : 0.141 0.313 0.623 0.556 0.366 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] socket : 0.197 0.466 0.679 0.725 0.471 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] bottle : 0.138 0.256 0.345 0.520 0.313 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] bucket : 0.017 0.017 0.017 0.105 0.286 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] cushion : 0.066 0.133 0.210 0.200 0.667 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] basket : 0.011 0.018 0.018 0.250 0.143 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] telephone : 0.316 0.558 0.653 0.571 0.706 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] laptop : 0.233 0.569 0.573 0.600 0.750 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] plant pot : 0.191 0.512 0.567 0.818 0.562 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] exhaust fan : 0.167 0.321 0.321 0.833 0.333 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] cup : 0.254 0.365 0.446 0.708 0.386 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] coat hanger : 0.153 0.500 0.750 1.000 0.500 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] light switch : 0.254 0.510 0.689 0.811 0.462 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] speaker : 0.423 0.521 0.589 0.583 0.636 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 1.000 1.000 0.500 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] kettle : 0.242 0.264 0.264 0.667 0.333 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] smoke detector : 0.653 0.863 0.863 0.913 0.875 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] power strip : 0.057 0.146 0.187 0.333 0.500 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.083 0.000 0.000 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,104 INFO hook.py line 395 1619929] mouse : 0.490 0.699 0.742 0.885 0.719 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] cutting board : 0.049 0.062 0.062 0.500 0.250 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] toilet paper : 0.222 0.314 0.522 0.833 0.294 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] paper towel : 0.075 0.153 0.153 0.286 0.250 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] clock : 0.622 0.817 0.850 1.000 0.667 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] tap : 0.145 0.265 0.683 0.429 0.333 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] soap dispenser : 0.518 0.800 0.800 1.000 0.800 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] bowl : 0.235 0.278 0.278 0.667 0.667 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] whiteboard eraser: 0.190 0.465 0.474 0.800 0.667 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] toilet brush : 0.467 0.667 0.833 1.000 0.667 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] spray bottle : 0.020 0.031 0.031 0.250 0.250 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.500 1.000 0.500 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] stapler : 0.003 0.024 0.082 0.143 0.333 [2025-04-29 23:43:32,105 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-29 23:43:32,105 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-29 23:43:32,105 INFO hook.py line 404 1619929] average : 0.272 0.413 0.505 0.595 0.499 [2025-04-29 23:43:32,105 INFO hook.py line 405 1619929] ################################################################## [2025-04-29 23:43:32,106 INFO hook.py line 480 1619929] Total Process Time: 24.679 s [2025-04-29 23:43:32,106 INFO hook.py line 481 1619929] Average Process Time: 497.638 ms [2025-04-29 23:43:32,106 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-29 23:43:32,155 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-29 23:43:32,159 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:45:03,149 INFO hook.py line 650 1619929] Train: [425/512][50/242] Data 0.017 (0.016) Batch 1.341 (1.453) Remain 08:34:26 loss: 5.2485 Lr: 6.14803e-05 Mem R(MA/MR): 24290 (21973/36182) [2025-04-29 23:46:14,649 INFO hook.py line 650 1619929] Train: [425/512][100/242] Data 0.016 (0.017) Batch 1.420 (1.441) Remain 08:29:04 loss: 5.1651 Lr: 6.13504e-05 Mem R(MA/MR): 24290 (21973/36182) [2025-04-29 23:47:27,498 INFO hook.py line 650 1619929] Train: [425/512][150/242] Data 0.018 (0.023) Batch 1.541 (1.446) Remain 08:29:46 loss: 3.6087 Lr: 6.12204e-05 Mem R(MA/MR): 24290 (21973/36182) [2025-04-29 23:48:41,091 INFO hook.py line 650 1619929] Train: [425/512][200/242] Data 0.015 (0.021) Batch 1.560 (1.453) Remain 08:30:50 loss: 5.6687 Lr: 6.10904e-05 Mem R(MA/MR): 24290 (21973/36182) [2025-04-29 23:49:39,117 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2499 loss_mask: 0.0321 loss_dice: 1.7927 loss_score: 0.0000 loss_bbox: 0.0472 loss_sp_cls: 0.7066 loss: 4.5565 [2025-04-29 23:49:42,109 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:51:12,491 INFO hook.py line 650 1619929] Train: [426/512][50/242] Data 0.016 (0.017) Batch 1.395 (1.442) Remain 08:24:46 loss: 4.9832 Lr: 6.08511e-05 Mem R(MA/MR): 22764 (21973/36182) [2025-04-29 23:52:25,224 INFO hook.py line 650 1619929] Train: [426/512][100/242] Data 0.016 (0.017) Batch 1.383 (1.448) Remain 08:25:51 loss: 5.1249 Lr: 6.07210e-05 Mem R(MA/MR): 24606 (21973/36182) [2025-04-29 23:53:38,610 INFO hook.py line 650 1619929] Train: [426/512][150/242] Data 0.015 (0.017) Batch 1.375 (1.455) Remain 08:26:56 loss: 4.0266 Lr: 6.05908e-05 Mem R(MA/MR): 24606 (21973/36182) [2025-04-29 23:54:49,746 INFO hook.py line 650 1619929] Train: [426/512][200/242] Data 0.016 (0.017) Batch 1.443 (1.447) Remain 08:22:52 loss: 3.8396 Lr: 6.04607e-05 Mem R(MA/MR): 24606 (21973/36182) [2025-04-29 23:55:48,206 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2477 loss_mask: 0.0323 loss_dice: 1.7951 loss_score: 0.0000 loss_bbox: 0.0463 loss_sp_cls: 0.7115 loss: 4.5489 [2025-04-29 23:55:49,020 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-29 23:57:22,956 INFO hook.py line 650 1619929] Train: [427/512][50/242] Data 0.016 (0.017) Batch 1.406 (1.475) Remain 08:30:32 loss: 4.4620 Lr: 6.02211e-05 Mem R(MA/MR): 21478 (21973/36182) [2025-04-29 23:58:36,464 INFO hook.py line 650 1619929] Train: [427/512][100/242] Data 0.017 (0.017) Batch 1.377 (1.473) Remain 08:28:22 loss: 4.1790 Lr: 6.00908e-05 Mem R(MA/MR): 21496 (21973/36182) [2025-04-29 23:59:47,636 INFO hook.py line 650 1619929] Train: [427/512][150/242] Data 0.016 (0.017) Batch 1.382 (1.456) Remain 08:21:22 loss: 3.9983 Lr: 5.99606e-05 Mem R(MA/MR): 21496 (21973/36182) [2025-04-30 00:00:58,563 INFO hook.py line 650 1619929] Train: [427/512][200/242] Data 0.015 (0.017) Batch 1.383 (1.446) Remain 08:16:54 loss: 5.1794 Lr: 5.98302e-05 Mem R(MA/MR): 21500 (21973/36182) [2025-04-30 00:01:55,252 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2488 loss_mask: 0.0320 loss_dice: 1.7962 loss_score: 0.0000 loss_bbox: 0.0470 loss_sp_cls: 0.7117 loss: 4.5579 [2025-04-30 00:01:58,282 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:03:32,592 INFO hook.py line 650 1619929] Train: [428/512][50/242] Data 0.015 (0.018) Batch 1.366 (1.449) Remain 08:15:26 loss: 4.1983 Lr: 5.95904e-05 Mem R(MA/MR): 23248 (21973/36182) [2025-04-30 00:04:43,956 INFO hook.py line 650 1619929] Train: [428/512][100/242] Data 0.017 (0.017) Batch 1.351 (1.438) Remain 08:10:28 loss: 5.2739 Lr: 5.94600e-05 Mem R(MA/MR): 25122 (21973/36182) [2025-04-30 00:05:55,486 INFO hook.py line 650 1619929] Train: [428/512][150/242] Data 0.016 (0.017) Batch 1.433 (1.435) Remain 08:08:27 loss: 3.3989 Lr: 5.93295e-05 Mem R(MA/MR): 25128 (21973/36182) [2025-04-30 00:07:07,638 INFO hook.py line 650 1619929] Train: [428/512][200/242] Data 0.015 (0.017) Batch 1.257 (1.437) Remain 08:07:56 loss: 3.7987 Lr: 5.91991e-05 Mem R(MA/MR): 27378 (21973/36182) [2025-04-30 00:08:06,855 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2423 loss_mask: 0.0317 loss_dice: 1.7730 loss_score: 0.0000 loss_bbox: 0.0472 loss_sp_cls: 0.7043 loss: 4.5047 [2025-04-30 00:08:09,885 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:09:46,351 INFO hook.py line 650 1619929] Train: [429/512][50/242] Data 0.018 (0.019) Batch 1.439 (1.521) Remain 08:34:00 loss: 3.5510 Lr: 5.89589e-05 Mem R(MA/MR): 25626 (21973/36182) [2025-04-30 00:10:59,578 INFO hook.py line 650 1619929] Train: [429/512][100/242] Data 0.016 (0.018) Batch 1.396 (1.492) Remain 08:22:57 loss: 3.6314 Lr: 5.88284e-05 Mem R(MA/MR): 27998 (21973/36182) [2025-04-30 00:12:10,268 INFO hook.py line 650 1619929] Train: [429/512][150/242] Data 0.016 (0.017) Batch 1.352 (1.465) Remain 08:12:47 loss: 3.4728 Lr: 5.86978e-05 Mem R(MA/MR): 27998 (21973/36182) [2025-04-30 00:13:21,321 INFO hook.py line 650 1619929] Train: [429/512][200/242] Data 0.015 (0.017) Batch 1.439 (1.454) Remain 08:07:47 loss: 4.9992 Lr: 5.85672e-05 Mem R(MA/MR): 27998 (21973/36182) [2025-04-30 00:14:17,962 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2400 loss_mask: 0.0311 loss_dice: 1.7546 loss_score: 0.0000 loss_bbox: 0.0460 loss_sp_cls: 0.7012 loss: 4.4584 [2025-04-30 00:14:19,791 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:15:53,779 INFO hook.py line 650 1619929] Train: [430/512][50/242] Data 0.015 (0.016) Batch 1.491 (1.478) Remain 08:13:41 loss: 4.6394 Lr: 5.83293e-05 Mem R(MA/MR): 24726 (21973/36182) [2025-04-30 00:17:07,483 INFO hook.py line 650 1619929] Train: [430/512][100/242] Data 0.016 (0.017) Batch 1.460 (1.476) Remain 08:11:42 loss: 4.2136 Lr: 5.81986e-05 Mem R(MA/MR): 26384 (21973/36182) [2025-04-30 00:18:20,154 INFO hook.py line 650 1619929] Train: [430/512][150/242] Data 0.017 (0.017) Batch 1.508 (1.468) Remain 08:07:54 loss: 3.8668 Lr: 5.80679e-05 Mem R(MA/MR): 28212 (21973/36182) [2025-04-30 00:19:32,506 INFO hook.py line 650 1619929] Train: [430/512][200/242] Data 0.014 (0.017) Batch 1.304 (1.463) Remain 08:04:53 loss: 3.9609 Lr: 5.79371e-05 Mem R(MA/MR): 28212 (21973/36182) [2025-04-30 00:20:29,155 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2450 loss_mask: 0.0319 loss_dice: 1.7748 loss_score: 0.0000 loss_bbox: 0.0475 loss_sp_cls: 0.6976 loss: 4.5130 [2025-04-30 00:20:30,516 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:22:06,452 INFO hook.py line 650 1619929] Train: [431/512][50/242] Data 0.017 (0.017) Batch 1.478 (1.500) Remain 08:14:58 loss: 4.7954 Lr: 5.76964e-05 Mem R(MA/MR): 22646 (21973/36182) [2025-04-30 00:23:18,904 INFO hook.py line 650 1619929] Train: [431/512][100/242] Data 0.016 (0.016) Batch 1.501 (1.474) Remain 08:05:01 loss: 4.5427 Lr: 5.75655e-05 Mem R(MA/MR): 25760 (21973/36182) [2025-04-30 00:24:30,048 INFO hook.py line 650 1619929] Train: [431/512][150/242] Data 0.015 (0.017) Batch 1.416 (1.457) Remain 07:58:05 loss: 5.0058 Lr: 5.74346e-05 Mem R(MA/MR): 25760 (21973/36182) [2025-04-30 00:25:42,725 INFO hook.py line 650 1619929] Train: [431/512][200/242] Data 0.015 (0.016) Batch 1.338 (1.456) Remain 07:56:37 loss: 4.9621 Lr: 5.73037e-05 Mem R(MA/MR): 27532 (21973/36182) [2025-04-30 00:26:42,346 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2456 loss_mask: 0.0323 loss_dice: 1.7869 loss_score: 0.0000 loss_bbox: 0.0474 loss_sp_cls: 0.7055 loss: 4.5340 [2025-04-30 00:26:45,388 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:28:21,395 INFO hook.py line 650 1619929] Train: [432/512][50/242] Data 0.020 (0.017) Batch 1.381 (1.458) Remain 07:55:06 loss: 4.4747 Lr: 5.70626e-05 Mem R(MA/MR): 20800 (21973/36182) [2025-04-30 00:29:32,839 INFO hook.py line 650 1619929] Train: [432/512][100/242] Data 0.016 (0.017) Batch 1.419 (1.443) Remain 07:49:01 loss: 4.7190 Lr: 5.69316e-05 Mem R(MA/MR): 25200 (21973/36182) [2025-04-30 00:30:43,093 INFO hook.py line 650 1619929] Train: [432/512][150/242] Data 0.016 (0.017) Batch 1.518 (1.430) Remain 07:43:38 loss: 4.5508 Lr: 5.68005e-05 Mem R(MA/MR): 25200 (21973/36182) [2025-04-30 00:31:54,227 INFO hook.py line 650 1619929] Train: [432/512][200/242] Data 0.015 (0.016) Batch 1.442 (1.428) Remain 07:41:50 loss: 4.0139 Lr: 5.66694e-05 Mem R(MA/MR): 25200 (21973/36182) [2025-04-30 00:32:53,520 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2422 loss_mask: 0.0320 loss_dice: 1.7828 loss_score: 0.0000 loss_bbox: 0.0469 loss_sp_cls: 0.7048 loss: 4.5164 [2025-04-30 00:32:56,365 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 00:32:58,753 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0181 Process Time: 0.306 Mem R(MA/MR): 4668 (21973/36182) [2025-04-30 00:33:00,358 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8699 Process Time: 0.433 Mem R(MA/MR): 7514 (21973/36182) [2025-04-30 00:33:01,959 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2309 Process Time: 0.599 Mem R(MA/MR): 9990 (21973/36182) [2025-04-30 00:33:09,833 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.0194 Process Time: 0.825 Mem R(MA/MR): 20300 (21973/36182) [2025-04-30 00:33:10,572 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.1163 Process Time: 0.217 Mem R(MA/MR): 7388 (21973/36182) [2025-04-30 00:33:12,010 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.2509 Process Time: 0.362 Mem R(MA/MR): 11602 (21973/36182) [2025-04-30 00:33:12,639 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0181 Process Time: 0.243 Mem R(MA/MR): 6682 (21973/36182) [2025-04-30 00:33:13,423 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3833 Process Time: 0.345 Mem R(MA/MR): 4718 (21973/36182) [2025-04-30 00:33:14,667 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7568 Process Time: 0.572 Mem R(MA/MR): 11732 (21973/36182) [2025-04-30 00:33:16,407 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5644 Process Time: 0.401 Mem R(MA/MR): 9768 (21973/36182) [2025-04-30 00:33:19,517 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.6098 Process Time: 0.609 Mem R(MA/MR): 19318 (21973/36182) [2025-04-30 00:33:22,043 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.5257 Process Time: 0.321 Mem R(MA/MR): 15760 (21973/36182) [2025-04-30 00:33:23,591 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.2841 Process Time: 0.518 Mem R(MA/MR): 9080 (21973/36182) [2025-04-30 00:33:24,271 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1087 Process Time: 0.292 Mem R(MA/MR): 5060 (21973/36182) [2025-04-30 00:33:27,690 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.0445 Process Time: 0.415 Mem R(MA/MR): 16706 (21973/36182) [2025-04-30 00:33:29,984 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.0171 Process Time: 0.700 Mem R(MA/MR): 14768 (21973/36182) [2025-04-30 00:33:31,022 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3751 Process Time: 0.390 Mem R(MA/MR): 7024 (21973/36182) [2025-04-30 00:33:32,339 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0057 Process Time: 0.393 Mem R(MA/MR): 8482 (21973/36182) [2025-04-30 00:33:33,676 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6301 Process Time: 0.198 Mem R(MA/MR): 6384 (21973/36182) [2025-04-30 00:33:35,334 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.7676 Process Time: 0.232 Mem R(MA/MR): 11674 (21973/36182) [2025-04-30 00:33:44,887 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.8069 Process Time: 0.583 Mem R(MA/MR): 24158 (21973/36182) [2025-04-30 00:33:45,402 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2184 Process Time: 0.169 Mem R(MA/MR): 7132 (21973/36182) [2025-04-30 00:33:54,690 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.8650 Process Time: 0.326 Mem R(MA/MR): 10436 (21973/36182) [2025-04-30 00:33:55,328 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7225 Process Time: 0.164 Mem R(MA/MR): 5652 (21973/36182) [2025-04-30 00:33:56,799 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.4204 Process Time: 0.593 Mem R(MA/MR): 9556 (21973/36182) [2025-04-30 00:34:04,291 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.0149 Process Time: 1.451 Mem R(MA/MR): 32330 (21973/36182) [2025-04-30 00:34:07,153 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.6792 Process Time: 0.487 Mem R(MA/MR): 10092 (21973/36182) [2025-04-30 00:34:08,564 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.6366 Process Time: 0.374 Mem R(MA/MR): 9230 (21973/36182) [2025-04-30 00:34:13,860 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8523 Process Time: 0.297 Mem R(MA/MR): 17512 (21973/36182) [2025-04-30 00:34:15,417 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.9378 Process Time: 0.477 Mem R(MA/MR): 8048 (21973/36182) [2025-04-30 00:34:19,593 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8813 Process Time: 0.628 Mem R(MA/MR): 21118 (21973/36182) [2025-04-30 00:34:19,926 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.0731 Process Time: 0.149 Mem R(MA/MR): 4350 (21973/36182) [2025-04-30 00:34:23,581 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.9405 Process Time: 0.438 Mem R(MA/MR): 25052 (21973/36182) [2025-04-30 00:34:24,833 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6557 Process Time: 0.391 Mem R(MA/MR): 10054 (21973/36182) [2025-04-30 00:34:27,079 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.6712 Process Time: 0.597 Mem R(MA/MR): 14252 (21973/36182) [2025-04-30 00:34:27,561 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.6837 Process Time: 0.150 Mem R(MA/MR): 6960 (21973/36182) [2025-04-30 00:34:31,526 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8316 Process Time: 0.793 Mem R(MA/MR): 28712 (21973/36182) [2025-04-30 00:34:33,609 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.9696 Process Time: 0.796 Mem R(MA/MR): 11066 (21973/36182) [2025-04-30 00:34:34,167 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1584 Process Time: 0.213 Mem R(MA/MR): 5838 (21973/36182) [2025-04-30 00:34:35,349 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5719 Process Time: 0.335 Mem R(MA/MR): 10394 (21973/36182) [2025-04-30 00:34:36,165 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.9763 Process Time: 0.193 Mem R(MA/MR): 9308 (21973/36182) [2025-04-30 00:34:36,586 INFO hook.py line 449 1619929] Test: [42/50] Loss 7.0643 Process Time: 0.129 Mem R(MA/MR): 5826 (21973/36182) [2025-04-30 00:34:36,987 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9267 Process Time: 0.147 Mem R(MA/MR): 5876 (21973/36182) [2025-04-30 00:34:37,546 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.6531 Process Time: 0.198 Mem R(MA/MR): 7468 (21973/36182) [2025-04-30 00:34:38,155 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.3908 Process Time: 0.167 Mem R(MA/MR): 5584 (21973/36182) [2025-04-30 00:34:40,755 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5627 Process Time: 0.660 Mem R(MA/MR): 14838 (21973/36182) [2025-04-30 00:34:48,106 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.7443 Process Time: 0.830 Mem R(MA/MR): 20674 (21973/36182) [2025-04-30 00:35:03,710 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.1043 Process Time: 6.648 Mem R(MA/MR): 36104 (21973/36182) [2025-04-30 00:35:04,218 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.5956 Process Time: 0.137 Mem R(MA/MR): 6078 (21973/36182) [2025-04-30 00:35:06,600 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1609 Process Time: 0.456 Mem R(MA/MR): 14018 (21973/36182) [2025-04-30 00:35:11,276 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 00:35:11,276 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 00:35:11,276 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] table : 0.283 0.599 0.746 0.794 0.625 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] door : 0.452 0.749 0.907 0.923 0.759 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] ceiling lamp : 0.607 0.810 0.898 0.930 0.735 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] cabinet : 0.341 0.458 0.526 0.630 0.433 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] blinds : 0.675 0.846 0.888 0.895 0.739 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] curtain : 0.324 0.615 0.706 0.889 0.667 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] chair : 0.634 0.793 0.845 0.822 0.717 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] storage cabinet: 0.276 0.386 0.431 0.600 0.600 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] office chair : 0.638 0.661 0.677 0.700 0.729 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] bookshelf : 0.246 0.536 0.709 0.615 0.727 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] whiteboard : 0.597 0.730 0.750 0.923 0.686 [2025-04-30 00:35:11,276 INFO hook.py line 395 1619929] window : 0.149 0.347 0.664 0.467 0.462 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] box : 0.189 0.350 0.536 0.518 0.392 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] monitor : 0.634 0.794 0.852 0.964 0.771 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] shelf : 0.158 0.330 0.442 0.818 0.300 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] heater : 0.465 0.684 0.838 0.750 0.789 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] kitchen cabinet: 0.116 0.302 0.570 0.462 0.480 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] sofa : 0.487 0.582 0.949 0.875 0.583 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] bed : 0.097 0.264 0.750 0.750 0.375 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] trash can : 0.521 0.704 0.742 0.757 0.815 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] book : 0.021 0.033 0.076 0.189 0.086 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] plant : 0.461 0.770 0.847 0.933 0.778 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] blanket : 0.388 0.494 0.538 0.667 0.545 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] computer tower : 0.247 0.356 0.593 0.773 0.405 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] refrigerator : 0.318 0.503 0.505 0.462 0.667 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] jacket : 0.060 0.206 0.537 0.455 0.455 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] sink : 0.453 0.832 0.894 0.833 0.909 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] bag : 0.141 0.236 0.290 0.600 0.333 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] picture : 0.144 0.304 0.418 0.472 0.436 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] pillow : 0.530 0.707 0.797 0.700 0.737 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] towel : 0.182 0.377 0.539 0.640 0.421 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] suitcase : 0.369 0.502 0.502 0.571 0.571 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] backpack : 0.553 0.606 0.694 0.889 0.615 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] crate : 0.059 0.198 0.437 0.750 0.273 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] keyboard : 0.584 0.719 0.833 0.794 0.692 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] toilet : 0.859 1.000 1.000 1.000 1.000 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] printer : 0.186 0.202 0.214 0.364 0.444 [2025-04-30 00:35:11,277 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.011 0.071 0.111 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] painting : 0.040 0.042 0.045 0.083 1.000 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] microwave : 0.651 0.875 1.000 1.000 0.875 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] shoes : 0.161 0.269 0.527 0.737 0.341 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] socket : 0.208 0.486 0.663 0.690 0.493 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] bottle : 0.129 0.235 0.287 0.510 0.301 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] bucket : 0.006 0.006 0.006 0.091 0.143 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] cushion : 0.130 0.137 0.219 0.208 0.833 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] basket : 0.008 0.012 0.012 0.167 0.143 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] telephone : 0.323 0.601 0.635 0.647 0.647 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] laptop : 0.413 0.644 0.712 0.800 0.500 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] plant pot : 0.068 0.225 0.423 0.421 0.500 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] exhaust fan : 0.202 0.355 0.355 0.750 0.400 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] cup : 0.231 0.373 0.409 0.889 0.364 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] coat hanger : 0.361 0.750 0.944 1.000 0.750 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] light switch : 0.211 0.451 0.663 0.673 0.508 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] speaker : 0.379 0.470 0.606 0.750 0.545 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] kettle : 0.231 0.264 0.264 0.667 0.333 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] smoke detector : 0.657 0.828 0.829 1.000 0.792 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] power strip : 0.040 0.046 0.077 0.250 0.200 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] mouse : 0.443 0.675 0.714 0.950 0.594 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] cutting board : 0.447 0.750 0.750 1.000 0.750 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] toilet paper : 0.237 0.344 0.499 1.000 0.294 [2025-04-30 00:35:11,278 INFO hook.py line 395 1619929] paper towel : 0.016 0.125 0.144 1.000 0.125 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] clock : 0.367 0.528 0.528 0.667 0.667 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 1.000 0.000 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] tap : 0.126 0.239 0.649 0.375 0.333 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] soap dispenser : 0.525 0.697 0.697 0.800 0.800 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] bowl : 0.041 0.083 0.135 0.500 0.333 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] whiteboard eraser: 0.166 0.417 0.421 0.800 0.667 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] toilet brush : 0.382 0.576 0.790 0.800 0.667 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] spray bottle : 0.025 0.042 0.042 0.333 0.250 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] headphones : 0.486 0.792 1.000 0.667 1.000 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] stapler : 0.011 0.019 0.150 0.111 0.333 [2025-04-30 00:35:11,279 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 00:35:11,279 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 00:35:11,279 INFO hook.py line 404 1619929] average : 0.280 0.420 0.513 0.617 0.498 [2025-04-30 00:35:11,279 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 00:35:11,280 INFO hook.py line 480 1619929] Total Process Time: 27.347 s [2025-04-30 00:35:11,280 INFO hook.py line 481 1619929] Average Process Time: 551.868 ms [2025-04-30 00:35:11,280 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 00:35:11,325 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-30 00:35:11,330 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:36:46,612 INFO hook.py line 650 1619929] Train: [433/512][50/242] Data 0.016 (0.036) Batch 1.482 (1.501) Remain 08:03:12 loss: 5.8378 Lr: 5.64281e-05 Mem R(MA/MR): 24438 (21973/36182) [2025-04-30 00:38:00,387 INFO hook.py line 650 1619929] Train: [433/512][100/242] Data 0.018 (0.026) Batch 1.548 (1.488) Remain 07:57:40 loss: 4.0623 Lr: 5.62969e-05 Mem R(MA/MR): 26326 (21973/36182) [2025-04-30 00:39:12,661 INFO hook.py line 650 1619929] Train: [433/512][150/242] Data 0.015 (0.023) Batch 1.440 (1.474) Remain 07:51:47 loss: 4.6001 Lr: 5.61657e-05 Mem R(MA/MR): 28284 (21973/36182) [2025-04-30 00:40:25,081 INFO hook.py line 650 1619929] Train: [433/512][200/242] Data 0.014 (0.021) Batch 1.303 (1.467) Remain 07:48:31 loss: 4.6425 Lr: 5.60344e-05 Mem R(MA/MR): 28284 (21973/36182) [2025-04-30 00:41:22,130 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2426 loss_mask: 0.0311 loss_dice: 1.7802 loss_score: 0.0000 loss_bbox: 0.0463 loss_sp_cls: 0.6978 loss: 4.5030 [2025-04-30 00:41:23,049 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:42:56,026 INFO hook.py line 650 1619929] Train: [434/512][50/242] Data 0.016 (0.018) Batch 1.498 (1.517) Remain 08:01:57 loss: 4.5869 Lr: 5.57928e-05 Mem R(MA/MR): 23456 (21973/36182) [2025-04-30 00:44:08,623 INFO hook.py line 650 1619929] Train: [434/512][100/242] Data 0.015 (0.017) Batch 1.498 (1.483) Remain 07:50:08 loss: 4.6450 Lr: 5.56614e-05 Mem R(MA/MR): 23466 (21973/36182) [2025-04-30 00:45:20,934 INFO hook.py line 650 1619929] Train: [434/512][150/242] Data 0.021 (0.017) Batch 1.456 (1.471) Remain 07:44:55 loss: 4.7754 Lr: 5.55300e-05 Mem R(MA/MR): 23466 (21973/36182) [2025-04-30 00:46:33,940 INFO hook.py line 650 1619929] Train: [434/512][200/242] Data 0.015 (0.017) Batch 1.366 (1.468) Remain 07:42:51 loss: 5.1362 Lr: 5.53986e-05 Mem R(MA/MR): 23480 (21973/36182) [2025-04-30 00:47:31,838 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2464 loss_mask: 0.0320 loss_dice: 1.7910 loss_score: 0.0000 loss_bbox: 0.0468 loss_sp_cls: 0.7039 loss: 4.5377 [2025-04-30 00:47:32,063 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:48:58,187 INFO hook.py line 650 1619929] Train: [435/512][50/242] Data 0.017 (0.017) Batch 1.492 (1.504) Remain 07:51:59 loss: 4.2605 Lr: 5.51567e-05 Mem R(MA/MR): 19072 (21973/36182) [2025-04-30 00:50:11,522 INFO hook.py line 650 1619929] Train: [435/512][100/242] Data 0.015 (0.017) Batch 1.520 (1.485) Remain 07:44:40 loss: 5.1919 Lr: 5.50252e-05 Mem R(MA/MR): 19082 (21973/36182) [2025-04-30 00:51:21,333 INFO hook.py line 650 1619929] Train: [435/512][150/242] Data 0.017 (0.017) Batch 1.316 (1.455) Remain 07:34:01 loss: 4.7683 Lr: 5.48936e-05 Mem R(MA/MR): 19082 (21973/36182) [2025-04-30 00:52:35,816 INFO hook.py line 650 1619929] Train: [435/512][200/242] Data 0.016 (0.017) Batch 1.465 (1.464) Remain 07:35:34 loss: 4.6544 Lr: 5.47620e-05 Mem R(MA/MR): 19100 (21973/36182) [2025-04-30 00:53:33,546 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2472 loss_mask: 0.0316 loss_dice: 1.7725 loss_score: 0.0000 loss_bbox: 0.0461 loss_sp_cls: 0.7020 loss: 4.5090 [2025-04-30 00:53:36,932 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 00:55:10,607 INFO hook.py line 650 1619929] Train: [436/512][50/242] Data 0.016 (0.017) Batch 1.510 (1.448) Remain 07:28:31 loss: 4.2592 Lr: 5.45197e-05 Mem R(MA/MR): 24408 (21973/36182) [2025-04-30 00:56:21,188 INFO hook.py line 650 1619929] Train: [436/512][100/242] Data 0.016 (0.016) Batch 1.418 (1.429) Remain 07:21:30 loss: 4.7819 Lr: 5.43880e-05 Mem R(MA/MR): 26236 (21973/36182) [2025-04-30 00:57:34,226 INFO hook.py line 650 1619929] Train: [436/512][150/242] Data 0.016 (0.017) Batch 1.444 (1.440) Remain 07:23:36 loss: 5.7065 Lr: 5.42563e-05 Mem R(MA/MR): 28402 (21973/36182) [2025-04-30 00:58:45,314 INFO hook.py line 650 1619929] Train: [436/512][200/242] Data 0.015 (0.016) Batch 1.412 (1.435) Remain 07:20:59 loss: 4.2968 Lr: 5.41245e-05 Mem R(MA/MR): 28402 (21973/36182) [2025-04-30 00:59:42,133 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2449 loss_mask: 0.0315 loss_dice: 1.7752 loss_score: 0.0000 loss_bbox: 0.0467 loss_sp_cls: 0.7020 loss: 4.5113 [2025-04-30 00:59:46,617 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:01:17,896 INFO hook.py line 650 1619929] Train: [437/512][50/242] Data 0.017 (0.017) Batch 1.625 (1.459) Remain 07:25:59 loss: 4.0390 Lr: 5.38820e-05 Mem R(MA/MR): 19066 (21973/36182) [2025-04-30 01:02:30,682 INFO hook.py line 650 1619929] Train: [437/512][100/242] Data 0.016 (0.017) Batch 1.300 (1.457) Remain 07:24:16 loss: 4.0707 Lr: 5.37501e-05 Mem R(MA/MR): 21190 (21973/36182) [2025-04-30 01:03:43,262 INFO hook.py line 650 1619929] Train: [437/512][150/242] Data 0.017 (0.017) Batch 1.416 (1.455) Remain 07:22:28 loss: 4.3778 Lr: 5.36182e-05 Mem R(MA/MR): 21190 (21973/36182) [2025-04-30 01:04:55,533 INFO hook.py line 650 1619929] Train: [437/512][200/242] Data 0.015 (0.017) Batch 1.304 (1.453) Remain 07:20:29 loss: 4.7625 Lr: 5.34863e-05 Mem R(MA/MR): 21192 (21973/36182) [2025-04-30 01:05:51,687 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2410 loss_mask: 0.0319 loss_dice: 1.7835 loss_score: 0.0000 loss_bbox: 0.0469 loss_sp_cls: 0.7023 loss: 4.5150 [2025-04-30 01:05:53,440 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:07:24,458 INFO hook.py line 650 1619929] Train: [438/512][50/242] Data 0.016 (0.016) Batch 1.505 (1.445) Remain 07:16:02 loss: 4.4676 Lr: 5.32434e-05 Mem R(MA/MR): 17932 (21973/36182) [2025-04-30 01:08:36,505 INFO hook.py line 650 1619929] Train: [438/512][100/242] Data 0.016 (0.016) Batch 1.380 (1.443) Remain 07:14:08 loss: 4.3869 Lr: 5.31113e-05 Mem R(MA/MR): 24364 (21973/36182) [2025-04-30 01:09:47,905 INFO hook.py line 650 1619929] Train: [438/512][150/242] Data 0.017 (0.016) Batch 1.452 (1.438) Remain 07:11:23 loss: 3.5309 Lr: 5.29793e-05 Mem R(MA/MR): 26136 (21973/36182) [2025-04-30 01:11:01,520 INFO hook.py line 650 1619929] Train: [438/512][200/242] Data 0.015 (0.016) Batch 1.369 (1.447) Remain 07:12:48 loss: 4.3382 Lr: 5.28471e-05 Mem R(MA/MR): 26136 (21973/36182) [2025-04-30 01:12:01,579 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2391 loss_mask: 0.0313 loss_dice: 1.7719 loss_score: 0.0000 loss_bbox: 0.0460 loss_sp_cls: 0.6991 loss: 4.4824 [2025-04-30 01:12:05,389 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:13:41,859 INFO hook.py line 650 1619929] Train: [439/512][50/242] Data 0.018 (0.017) Batch 1.654 (1.478) Remain 07:20:00 loss: 4.2518 Lr: 5.26039e-05 Mem R(MA/MR): 23014 (21973/36182) [2025-04-30 01:14:55,520 INFO hook.py line 650 1619929] Train: [439/512][100/242] Data 0.015 (0.017) Batch 1.423 (1.476) Remain 07:17:59 loss: 5.3628 Lr: 5.24717e-05 Mem R(MA/MR): 25234 (21973/36182) [2025-04-30 01:16:09,015 INFO hook.py line 650 1619929] Train: [439/512][150/242] Data 0.017 (0.017) Batch 1.510 (1.474) Remain 07:16:10 loss: 4.4851 Lr: 5.23394e-05 Mem R(MA/MR): 25234 (21973/36182) [2025-04-30 01:17:21,532 INFO hook.py line 650 1619929] Train: [439/512][200/242] Data 0.016 (0.017) Batch 1.540 (1.468) Remain 07:13:11 loss: 4.0992 Lr: 5.22071e-05 Mem R(MA/MR): 25234 (21973/36182) [2025-04-30 01:18:17,949 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2345 loss_mask: 0.0307 loss_dice: 1.7404 loss_score: 0.0000 loss_bbox: 0.0457 loss_sp_cls: 0.6873 loss: 4.4103 [2025-04-30 01:18:23,053 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:19:57,045 INFO hook.py line 650 1619929] Train: [440/512][50/242] Data 0.018 (0.017) Batch 1.420 (1.483) Remain 07:15:19 loss: 4.0382 Lr: 5.19636e-05 Mem R(MA/MR): 26060 (21973/36182) [2025-04-30 01:21:10,894 INFO hook.py line 650 1619929] Train: [440/512][100/242] Data 0.018 (0.017) Batch 1.424 (1.480) Remain 07:13:13 loss: 3.8651 Lr: 5.18312e-05 Mem R(MA/MR): 26060 (21973/36182) [2025-04-30 01:22:24,375 INFO hook.py line 650 1619929] Train: [440/512][150/242] Data 0.017 (0.017) Batch 1.560 (1.476) Remain 07:10:58 loss: 4.9370 Lr: 5.16988e-05 Mem R(MA/MR): 26948 (21973/36182) [2025-04-30 01:23:36,433 INFO hook.py line 650 1619929] Train: [440/512][200/242] Data 0.015 (0.017) Batch 1.413 (1.467) Remain 07:07:09 loss: 4.2455 Lr: 5.15663e-05 Mem R(MA/MR): 26948 (21973/36182) [2025-04-30 01:24:32,565 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2354 loss_mask: 0.0298 loss_dice: 1.7387 loss_score: 0.0000 loss_bbox: 0.0462 loss_sp_cls: 0.6899 loss: 4.4118 [2025-04-30 01:24:35,281 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 01:24:37,564 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0370 Process Time: 0.337 Mem R(MA/MR): 4216 (21973/36182) [2025-04-30 01:24:39,125 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9319 Process Time: 0.483 Mem R(MA/MR): 7002 (21973/36182) [2025-04-30 01:24:40,857 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4879 Process Time: 0.684 Mem R(MA/MR): 9528 (21973/36182) [2025-04-30 01:24:48,327 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.7700 Process Time: 0.899 Mem R(MA/MR): 19462 (21973/36182) [2025-04-30 01:24:49,446 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4635 Process Time: 0.470 Mem R(MA/MR): 6740 (21973/36182) [2025-04-30 01:24:51,077 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.2181 Process Time: 0.533 Mem R(MA/MR): 11078 (21973/36182) [2025-04-30 01:24:51,844 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0635 Process Time: 0.295 Mem R(MA/MR): 6024 (21973/36182) [2025-04-30 01:24:52,676 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2525 Process Time: 0.376 Mem R(MA/MR): 4234 (21973/36182) [2025-04-30 01:24:53,802 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0884 Process Time: 0.399 Mem R(MA/MR): 11360 (21973/36182) [2025-04-30 01:24:55,575 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8452 Process Time: 0.415 Mem R(MA/MR): 9278 (21973/36182) [2025-04-30 01:24:58,134 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.5345 Process Time: 0.614 Mem R(MA/MR): 18532 (21973/36182) [2025-04-30 01:25:00,486 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0360 Process Time: 0.495 Mem R(MA/MR): 15040 (21973/36182) [2025-04-30 01:25:01,835 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.5428 Process Time: 0.449 Mem R(MA/MR): 8502 (21973/36182) [2025-04-30 01:25:02,170 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1229 Process Time: 0.129 Mem R(MA/MR): 4556 (21973/36182) [2025-04-30 01:25:04,920 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.3550 Process Time: 0.492 Mem R(MA/MR): 16276 (21973/36182) [2025-04-30 01:25:06,870 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0507 Process Time: 0.446 Mem R(MA/MR): 14434 (21973/36182) [2025-04-30 01:25:07,610 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2456 Process Time: 0.235 Mem R(MA/MR): 6290 (21973/36182) [2025-04-30 01:25:08,743 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7326 Process Time: 0.396 Mem R(MA/MR): 7844 (21973/36182) [2025-04-30 01:25:10,184 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.5120 Process Time: 0.184 Mem R(MA/MR): 5736 (21973/36182) [2025-04-30 01:25:11,775 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.9750 Process Time: 0.275 Mem R(MA/MR): 11200 (21973/36182) [2025-04-30 01:25:20,990 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.2971 Process Time: 1.021 Mem R(MA/MR): 23500 (21973/36182) [2025-04-30 01:25:21,789 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.1107 Process Time: 0.292 Mem R(MA/MR): 6608 (21973/36182) [2025-04-30 01:25:33,052 INFO hook.py line 449 1619929] Test: [23/50] Loss 16.6406 Process Time: 0.376 Mem R(MA/MR): 9930 (21973/36182) [2025-04-30 01:25:33,679 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.4947 Process Time: 0.161 Mem R(MA/MR): 4976 (21973/36182) [2025-04-30 01:25:34,752 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0432 Process Time: 0.275 Mem R(MA/MR): 8898 (21973/36182) [2025-04-30 01:25:41,707 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.7008 Process Time: 0.655 Mem R(MA/MR): 31620 (21973/36182) [2025-04-30 01:25:44,299 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5250 Process Time: 0.518 Mem R(MA/MR): 9670 (21973/36182) [2025-04-30 01:25:45,537 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.8222 Process Time: 0.348 Mem R(MA/MR): 8696 (21973/36182) [2025-04-30 01:25:50,100 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.4823 Process Time: 0.469 Mem R(MA/MR): 16868 (21973/36182) [2025-04-30 01:25:51,001 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.8277 Process Time: 0.250 Mem R(MA/MR): 7698 (21973/36182) [2025-04-30 01:25:54,520 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.7263 Process Time: 0.404 Mem R(MA/MR): 20298 (21973/36182) [2025-04-30 01:25:54,972 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1221 Process Time: 0.173 Mem R(MA/MR): 3824 (21973/36182) [2025-04-30 01:25:59,090 INFO hook.py line 449 1619929] Test: [33/50] Loss 10.8607 Process Time: 0.492 Mem R(MA/MR): 24542 (21973/36182) [2025-04-30 01:26:00,250 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6007 Process Time: 0.367 Mem R(MA/MR): 9456 (21973/36182) [2025-04-30 01:26:02,113 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7161 Process Time: 0.371 Mem R(MA/MR): 13912 (21973/36182) [2025-04-30 01:26:02,700 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9097 Process Time: 0.246 Mem R(MA/MR): 6146 (21973/36182) [2025-04-30 01:26:06,611 INFO hook.py line 449 1619929] Test: [37/50] Loss 12.9955 Process Time: 0.842 Mem R(MA/MR): 28284 (21973/36182) [2025-04-30 01:26:08,119 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8516 Process Time: 0.279 Mem R(MA/MR): 10318 (21973/36182) [2025-04-30 01:26:08,691 INFO hook.py line 449 1619929] Test: [39/50] Loss 5.9432 Process Time: 0.203 Mem R(MA/MR): 5164 (21973/36182) [2025-04-30 01:26:09,787 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.3695 Process Time: 0.252 Mem R(MA/MR): 9680 (21973/36182) [2025-04-30 01:26:11,241 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.0533 Process Time: 0.628 Mem R(MA/MR): 8764 (21973/36182) [2025-04-30 01:26:11,932 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1507 Process Time: 0.227 Mem R(MA/MR): 5176 (21973/36182) [2025-04-30 01:26:12,566 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5938 Process Time: 0.219 Mem R(MA/MR): 5196 (21973/36182) [2025-04-30 01:26:13,314 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.0105 Process Time: 0.274 Mem R(MA/MR): 6962 (21973/36182) [2025-04-30 01:26:13,968 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5686 Process Time: 0.160 Mem R(MA/MR): 4924 (21973/36182) [2025-04-30 01:26:16,499 INFO hook.py line 449 1619929] Test: [46/50] Loss 10.7101 Process Time: 0.605 Mem R(MA/MR): 14392 (21973/36182) [2025-04-30 01:26:23,841 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.2148 Process Time: 0.843 Mem R(MA/MR): 19900 (21973/36182) [2025-04-30 01:26:34,702 INFO hook.py line 449 1619929] Test: [48/50] Loss 10.6815 Process Time: 1.891 Mem R(MA/MR): 35652 (21973/36182) [2025-04-30 01:26:35,760 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.7329 Process Time: 0.281 Mem R(MA/MR): 5422 (21973/36182) [2025-04-30 01:26:38,315 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2480 Process Time: 0.420 Mem R(MA/MR): 13552 (21973/36182) [2025-04-30 01:26:42,970 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 01:26:42,970 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 01:26:42,970 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] table : 0.296 0.622 0.767 0.761 0.610 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] door : 0.468 0.755 0.901 0.889 0.709 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] ceiling lamp : 0.582 0.759 0.844 0.840 0.757 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] cabinet : 0.333 0.445 0.537 0.628 0.403 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] blinds : 0.525 0.723 0.776 0.850 0.739 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] curtain : 0.410 0.524 0.886 0.778 0.583 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] chair : 0.657 0.773 0.812 0.870 0.689 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] storage cabinet: 0.246 0.416 0.481 0.684 0.520 [2025-04-30 01:26:42,970 INFO hook.py line 395 1619929] office chair : 0.580 0.607 0.637 0.698 0.771 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] bookshelf : 0.209 0.414 0.749 0.500 0.727 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] whiteboard : 0.560 0.713 0.712 0.889 0.686 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] window : 0.155 0.338 0.664 0.587 0.407 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] box : 0.179 0.338 0.505 0.563 0.370 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] monitor : 0.651 0.804 0.852 0.964 0.771 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] shelf : 0.145 0.271 0.474 0.344 0.367 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] heater : 0.500 0.710 0.859 0.909 0.789 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] kitchen cabinet: 0.146 0.331 0.541 0.524 0.440 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] sofa : 0.497 0.721 0.809 0.818 0.750 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] bed : 0.309 0.625 0.791 1.000 0.625 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] trash can : 0.558 0.717 0.738 0.791 0.815 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] book : 0.023 0.049 0.098 0.219 0.105 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] plant : 0.428 0.648 0.828 0.857 0.667 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] blanket : 0.588 0.710 0.710 0.889 0.727 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] tv : 0.929 1.000 1.000 1.000 1.000 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] computer tower : 0.346 0.498 0.757 0.649 0.571 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] refrigerator : 0.286 0.449 0.457 1.000 0.333 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] jacket : 0.109 0.245 0.565 0.400 0.545 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] sink : 0.446 0.749 0.883 0.850 0.773 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] bag : 0.111 0.185 0.235 0.450 0.333 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] picture : 0.150 0.331 0.426 0.650 0.333 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] pillow : 0.599 0.786 0.818 0.875 0.737 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] towel : 0.161 0.303 0.481 0.632 0.316 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] suitcase : 0.433 0.487 0.487 1.000 0.429 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] backpack : 0.432 0.518 0.561 0.700 0.538 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] crate : 0.064 0.164 0.519 0.444 0.364 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] keyboard : 0.474 0.641 0.692 0.857 0.615 [2025-04-30 01:26:42,971 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] toilet : 0.873 0.889 1.000 1.000 0.889 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] printer : 0.298 0.406 0.524 0.500 0.667 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.006 0.077 0.111 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.071 0.125 1.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] microwave : 0.541 0.750 0.875 1.000 0.750 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] shoes : 0.154 0.225 0.548 0.684 0.317 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] socket : 0.189 0.443 0.654 0.680 0.486 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] bottle : 0.138 0.249 0.345 0.400 0.361 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] bucket : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] cushion : 0.044 0.057 0.221 0.200 0.333 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] basket : 0.006 0.014 0.014 0.200 0.143 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] telephone : 0.323 0.618 0.644 0.786 0.647 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] laptop : 0.360 0.667 0.667 0.833 0.625 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] plant pot : 0.189 0.499 0.541 0.889 0.500 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] exhaust fan : 0.246 0.400 0.400 1.000 0.400 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] cup : 0.254 0.425 0.446 0.826 0.432 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] coat hanger : 0.163 0.750 0.750 1.000 0.750 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] light switch : 0.241 0.483 0.623 0.738 0.477 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] speaker : 0.182 0.242 0.389 0.750 0.273 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] smoke detector : 0.661 0.821 0.824 0.950 0.792 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 1.000 0.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] power strip : 0.059 0.110 0.124 0.308 0.400 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,972 INFO hook.py line 395 1619929] mouse : 0.470 0.741 0.793 0.955 0.656 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] cutting board : 0.333 0.500 0.500 1.000 0.500 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] toilet paper : 0.254 0.353 0.471 1.000 0.353 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.166 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] clock : 0.659 0.764 0.764 0.750 1.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] tap : 0.134 0.255 0.552 0.600 0.333 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] soap dispenser : 0.403 0.755 0.893 0.800 0.800 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] bowl : 0.211 0.278 0.278 0.667 0.667 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] whiteboard eraser: 0.169 0.434 0.438 0.800 0.667 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] toilet brush : 0.540 0.722 0.896 1.000 0.667 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] spray bottle : 0.011 0.016 0.016 0.125 0.250 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] headphones : 0.075 0.258 1.000 0.333 1.000 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] stapler : 0.002 0.012 0.065 0.071 0.333 [2025-04-30 01:26:42,973 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 01:26:42,973 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 01:26:42,973 INFO hook.py line 404 1619929] average : 0.280 0.413 0.516 0.615 0.486 [2025-04-30 01:26:42,973 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 01:26:42,974 INFO hook.py line 480 1619929] Total Process Time: 22.149 s [2025-04-30 01:26:42,974 INFO hook.py line 481 1619929] Average Process Time: 445.135 ms [2025-04-30 01:26:42,974 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 01:26:43,017 INFO hook.py line 685 1619929] Currently Best AP50: 0.422 [2025-04-30 01:26:43,022 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:28:19,185 INFO hook.py line 650 1619929] Train: [441/512][50/242] Data 0.018 (0.017) Batch 1.529 (1.490) Remain 07:11:23 loss: 3.8327 Lr: 5.13224e-05 Mem R(MA/MR): 24482 (21973/36182) [2025-04-30 01:29:33,522 INFO hook.py line 650 1619929] Train: [441/512][100/242] Data 0.017 (0.017) Batch 1.551 (1.488) Remain 07:09:41 loss: 3.8835 Lr: 5.11898e-05 Mem R(MA/MR): 26472 (21973/36182) [2025-04-30 01:30:46,864 INFO hook.py line 650 1619929] Train: [441/512][150/242] Data 0.016 (0.017) Batch 1.389 (1.481) Remain 07:06:21 loss: 3.8346 Lr: 5.10572e-05 Mem R(MA/MR): 26472 (21973/36182) [2025-04-30 01:31:58,843 INFO hook.py line 650 1619929] Train: [441/512][200/242] Data 0.014 (0.021) Batch 1.259 (1.470) Remain 07:02:07 loss: 4.0018 Lr: 5.09245e-05 Mem R(MA/MR): 26472 (21973/36182) [2025-04-30 01:32:55,703 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2360 loss_mask: 0.0306 loss_dice: 1.7380 loss_score: 0.0000 loss_bbox: 0.0460 loss_sp_cls: 0.6856 loss: 4.4131 [2025-04-30 01:32:56,669 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:34:32,753 INFO hook.py line 650 1619929] Train: [442/512][50/242] Data 0.015 (0.017) Batch 1.457 (1.464) Remain 06:57:54 loss: 4.1493 Lr: 5.06803e-05 Mem R(MA/MR): 23728 (21973/36182) [2025-04-30 01:35:46,133 INFO hook.py line 650 1619929] Train: [442/512][100/242] Data 0.015 (0.017) Batch 1.450 (1.466) Remain 06:57:16 loss: 4.9148 Lr: 5.05476e-05 Mem R(MA/MR): 26312 (21973/36182) [2025-04-30 01:36:58,381 INFO hook.py line 650 1619929] Train: [442/512][150/242] Data 0.016 (0.017) Batch 1.452 (1.459) Remain 06:54:03 loss: 4.8876 Lr: 5.04147e-05 Mem R(MA/MR): 26312 (21973/36182) [2025-04-30 01:38:09,712 INFO hook.py line 650 1619929] Train: [442/512][200/242] Data 0.015 (0.017) Batch 1.362 (1.450) Remain 06:50:32 loss: 4.3791 Lr: 5.02819e-05 Mem R(MA/MR): 26312 (21973/36182) [2025-04-30 01:39:04,931 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2369 loss_mask: 0.0309 loss_dice: 1.7465 loss_score: 0.0000 loss_bbox: 0.0467 loss_sp_cls: 0.6897 loss: 4.4343 [2025-04-30 01:39:05,913 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:40:41,193 INFO hook.py line 650 1619929] Train: [443/512][50/242] Data 0.016 (0.016) Batch 1.462 (1.518) Remain 07:07:23 loss: 5.3994 Lr: 5.00373e-05 Mem R(MA/MR): 29752 (21973/36182) [2025-04-30 01:41:56,770 INFO hook.py line 650 1619929] Train: [443/512][100/242] Data 0.016 (0.016) Batch 1.427 (1.515) Remain 07:05:09 loss: 4.4976 Lr: 4.99044e-05 Mem R(MA/MR): 29752 (21973/36182) [2025-04-30 01:43:12,086 INFO hook.py line 650 1619929] Train: [443/512][150/242] Data 0.017 (0.017) Batch 1.493 (1.512) Remain 07:03:05 loss: 4.8084 Lr: 4.97714e-05 Mem R(MA/MR): 32380 (21973/36182) [2025-04-30 01:44:23,257 INFO hook.py line 650 1619929] Train: [443/512][200/242] Data 0.016 (0.017) Batch 1.551 (1.489) Remain 06:55:33 loss: 3.8168 Lr: 4.96383e-05 Mem R(MA/MR): 32380 (21973/36182) [2025-04-30 01:45:19,617 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2362 loss_mask: 0.0309 loss_dice: 1.7491 loss_score: 0.0000 loss_bbox: 0.0466 loss_sp_cls: 0.6916 loss: 4.4441 [2025-04-30 01:45:21,282 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:47:00,836 INFO hook.py line 650 1619929] Train: [444/512][50/242] Data 0.015 (0.017) Batch 1.373 (1.483) Remain 06:51:28 loss: 4.1515 Lr: 4.93934e-05 Mem R(MA/MR): 20952 (21973/36182) [2025-04-30 01:48:11,761 INFO hook.py line 650 1619929] Train: [444/512][100/242] Data 0.017 (0.017) Batch 1.506 (1.450) Remain 06:41:02 loss: 4.4858 Lr: 4.92603e-05 Mem R(MA/MR): 23402 (21973/36182) [2025-04-30 01:49:25,636 INFO hook.py line 650 1619929] Train: [444/512][150/242] Data 0.018 (0.017) Batch 1.317 (1.459) Remain 06:42:26 loss: 3.8489 Lr: 4.91271e-05 Mem R(MA/MR): 23424 (21973/36182) [2025-04-30 01:50:37,157 INFO hook.py line 650 1619929] Train: [444/512][200/242] Data 0.014 (0.016) Batch 1.264 (1.452) Remain 06:39:13 loss: 3.7196 Lr: 4.89938e-05 Mem R(MA/MR): 25334 (21973/36182) [2025-04-30 01:51:36,361 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2346 loss_mask: 0.0308 loss_dice: 1.7552 loss_score: 0.0000 loss_bbox: 0.0463 loss_sp_cls: 0.6866 loss: 4.4425 [2025-04-30 01:51:39,899 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:53:15,940 INFO hook.py line 650 1619929] Train: [445/512][50/242] Data 0.017 (0.018) Batch 1.461 (1.485) Remain 06:46:10 loss: 4.8375 Lr: 4.87486e-05 Mem R(MA/MR): 25756 (21973/36182) [2025-04-30 01:54:28,649 INFO hook.py line 650 1619929] Train: [445/512][100/242] Data 0.017 (0.017) Batch 1.591 (1.469) Remain 06:40:32 loss: 4.9947 Lr: 4.86152e-05 Mem R(MA/MR): 25756 (21973/36182) [2025-04-30 01:55:42,186 INFO hook.py line 650 1619929] Train: [445/512][150/242] Data 0.021 (0.017) Batch 1.434 (1.470) Remain 06:39:26 loss: 5.6853 Lr: 4.84818e-05 Mem R(MA/MR): 25756 (21973/36182) [2025-04-30 01:56:53,558 INFO hook.py line 650 1619929] Train: [445/512][200/242] Data 0.015 (0.017) Batch 1.266 (1.459) Remain 06:35:18 loss: 3.4795 Lr: 4.83484e-05 Mem R(MA/MR): 25762 (21973/36182) [2025-04-30 01:57:51,440 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2325 loss_mask: 0.0308 loss_dice: 1.7543 loss_score: 0.0000 loss_bbox: 0.0461 loss_sp_cls: 0.6895 loss: 4.4277 [2025-04-30 01:57:51,620 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 01:59:24,894 INFO hook.py line 650 1619929] Train: [446/512][50/242] Data 0.015 (0.018) Batch 1.474 (1.470) Remain 06:36:08 loss: 4.4163 Lr: 4.81054e-05 Mem R(MA/MR): 19044 (21973/36182) [2025-04-30 02:00:37,668 INFO hook.py line 650 1619929] Train: [446/512][100/242] Data 0.016 (0.017) Batch 1.500 (1.463) Remain 06:32:50 loss: 4.4047 Lr: 4.79719e-05 Mem R(MA/MR): 19836 (21973/36182) [2025-04-30 02:01:50,744 INFO hook.py line 650 1619929] Train: [446/512][150/242] Data 0.018 (0.017) Batch 1.485 (1.462) Remain 06:31:30 loss: 4.2644 Lr: 4.78383e-05 Mem R(MA/MR): 19836 (21973/36182) [2025-04-30 02:03:02,226 INFO hook.py line 650 1619929] Train: [446/512][200/242] Data 0.014 (0.017) Batch 1.276 (1.454) Remain 06:28:04 loss: 5.6124 Lr: 4.77047e-05 Mem R(MA/MR): 19836 (21973/36182) [2025-04-30 02:03:59,418 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2425 loss_mask: 0.0313 loss_dice: 1.7813 loss_score: 0.0000 loss_bbox: 0.0470 loss_sp_cls: 0.6983 loss: 4.5074 [2025-04-30 02:04:03,886 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:05:35,499 INFO hook.py line 650 1619929] Train: [447/512][50/242] Data 0.016 (0.016) Batch 1.383 (1.416) Remain 06:15:48 loss: 4.3125 Lr: 4.74587e-05 Mem R(MA/MR): 25014 (21973/36182) [2025-04-30 02:06:48,010 INFO hook.py line 650 1619929] Train: [447/512][100/242] Data 0.018 (0.016) Batch 1.328 (1.434) Remain 06:19:16 loss: 3.7760 Lr: 4.73249e-05 Mem R(MA/MR): 25028 (21973/36182) [2025-04-30 02:08:00,292 INFO hook.py line 650 1619929] Train: [447/512][150/242] Data 0.017 (0.016) Batch 1.452 (1.438) Remain 06:19:08 loss: 5.6032 Lr: 4.71911e-05 Mem R(MA/MR): 25028 (21973/36182) [2025-04-30 02:09:14,685 INFO hook.py line 650 1619929] Train: [447/512][200/242] Data 0.017 (0.017) Batch 1.499 (1.450) Remain 06:21:17 loss: 4.3070 Lr: 4.70573e-05 Mem R(MA/MR): 25028 (21973/36182) [2025-04-30 02:10:12,379 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2437 loss_mask: 0.0313 loss_dice: 1.7721 loss_score: 0.0000 loss_bbox: 0.0467 loss_sp_cls: 0.6931 loss: 4.4948 [2025-04-30 02:10:16,682 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:11:51,776 INFO hook.py line 650 1619929] Train: [448/512][50/242] Data 0.016 (0.016) Batch 1.309 (1.472) Remain 06:24:45 loss: 4.5885 Lr: 4.68110e-05 Mem R(MA/MR): 21048 (21973/36182) [2025-04-30 02:13:04,757 INFO hook.py line 650 1619929] Train: [448/512][100/242] Data 0.016 (0.016) Batch 1.526 (1.466) Remain 06:21:49 loss: 5.1745 Lr: 4.66770e-05 Mem R(MA/MR): 21048 (21973/36182) [2025-04-30 02:14:16,119 INFO hook.py line 650 1619929] Train: [448/512][150/242] Data 0.016 (0.017) Batch 1.272 (1.453) Remain 06:17:12 loss: 3.4926 Lr: 4.65430e-05 Mem R(MA/MR): 21064 (21973/36182) [2025-04-30 02:15:28,394 INFO hook.py line 650 1619929] Train: [448/512][200/242] Data 0.014 (0.017) Batch 1.337 (1.451) Remain 06:15:31 loss: 5.1436 Lr: 4.64090e-05 Mem R(MA/MR): 24670 (21973/36182) [2025-04-30 02:16:25,071 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2389 loss_mask: 0.0310 loss_dice: 1.7606 loss_score: 0.0000 loss_bbox: 0.0469 loss_sp_cls: 0.6974 loss: 4.4695 [2025-04-30 02:16:26,362 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 02:16:28,543 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2477 Process Time: 0.270 Mem R(MA/MR): 4412 (21973/36182) [2025-04-30 02:16:30,309 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6881 Process Time: 0.540 Mem R(MA/MR): 7178 (21973/36182) [2025-04-30 02:16:32,139 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1853 Process Time: 0.667 Mem R(MA/MR): 9922 (21973/36182) [2025-04-30 02:16:39,413 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4118 Process Time: 0.880 Mem R(MA/MR): 19388 (21973/36182) [2025-04-30 02:16:40,851 INFO hook.py line 449 1619929] Test: [5/50] Loss 4.7467 Process Time: 0.590 Mem R(MA/MR): 6898 (21973/36182) [2025-04-30 02:16:42,415 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.1848 Process Time: 0.549 Mem R(MA/MR): 11558 (21973/36182) [2025-04-30 02:16:43,560 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.7638 Process Time: 0.539 Mem R(MA/MR): 6406 (21973/36182) [2025-04-30 02:16:43,987 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3276 Process Time: 0.138 Mem R(MA/MR): 4430 (21973/36182) [2025-04-30 02:16:44,838 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6782 Process Time: 0.250 Mem R(MA/MR): 11568 (21973/36182) [2025-04-30 02:16:46,304 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.3753 Process Time: 0.298 Mem R(MA/MR): 9672 (21973/36182) [2025-04-30 02:16:48,614 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.1088 Process Time: 0.332 Mem R(MA/MR): 18630 (21973/36182) [2025-04-30 02:16:50,973 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9674 Process Time: 0.405 Mem R(MA/MR): 15242 (21973/36182) [2025-04-30 02:16:52,359 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.5059 Process Time: 0.356 Mem R(MA/MR): 8882 (21973/36182) [2025-04-30 02:16:52,712 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9987 Process Time: 0.135 Mem R(MA/MR): 4932 (21973/36182) [2025-04-30 02:16:55,752 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.7025 Process Time: 0.296 Mem R(MA/MR): 16622 (21973/36182) [2025-04-30 02:16:57,510 INFO hook.py line 449 1619929] Test: [16/50] Loss 5.8796 Process Time: 0.290 Mem R(MA/MR): 14700 (21973/36182) [2025-04-30 02:16:58,655 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1937 Process Time: 0.485 Mem R(MA/MR): 6760 (21973/36182) [2025-04-30 02:16:59,633 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0212 Process Time: 0.270 Mem R(MA/MR): 8418 (21973/36182) [2025-04-30 02:17:01,334 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.3821 Process Time: 0.412 Mem R(MA/MR): 6128 (21973/36182) [2025-04-30 02:17:03,002 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.5529 Process Time: 0.329 Mem R(MA/MR): 11800 (21973/36182) [2025-04-30 02:17:12,535 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.0336 Process Time: 0.891 Mem R(MA/MR): 23642 (21973/36182) [2025-04-30 02:17:13,260 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4589 Process Time: 0.265 Mem R(MA/MR): 6746 (21973/36182) [2025-04-30 02:17:23,700 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.6567 Process Time: 0.386 Mem R(MA/MR): 10064 (21973/36182) [2025-04-30 02:17:24,279 INFO hook.py line 449 1619929] Test: [24/50] Loss 5.0606 Process Time: 0.178 Mem R(MA/MR): 5280 (21973/36182) [2025-04-30 02:17:25,524 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.6927 Process Time: 0.475 Mem R(MA/MR): 9488 (21973/36182) [2025-04-30 02:17:31,655 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.1191 Process Time: 1.116 Mem R(MA/MR): 30120 (21973/36182) [2025-04-30 02:17:34,170 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.3746 Process Time: 0.504 Mem R(MA/MR): 9796 (21973/36182) [2025-04-30 02:17:35,391 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9299 Process Time: 0.332 Mem R(MA/MR): 9072 (21973/36182) [2025-04-30 02:17:40,899 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.5479 Process Time: 0.564 Mem R(MA/MR): 16926 (21973/36182) [2025-04-30 02:17:41,829 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1400 Process Time: 0.314 Mem R(MA/MR): 7614 (21973/36182) [2025-04-30 02:17:45,820 INFO hook.py line 449 1619929] Test: [31/50] Loss 6.5791 Process Time: 0.510 Mem R(MA/MR): 20644 (21973/36182) [2025-04-30 02:17:46,175 INFO hook.py line 449 1619929] Test: [32/50] Loss 5.0195 Process Time: 0.128 Mem R(MA/MR): 3864 (21973/36182) [2025-04-30 02:17:50,102 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.4672 Process Time: 0.469 Mem R(MA/MR): 24868 (21973/36182) [2025-04-30 02:17:51,020 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5324 Process Time: 0.280 Mem R(MA/MR): 9772 (21973/36182) [2025-04-30 02:17:53,246 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0151 Process Time: 0.713 Mem R(MA/MR): 14138 (21973/36182) [2025-04-30 02:17:54,213 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.5874 Process Time: 0.418 Mem R(MA/MR): 6610 (21973/36182) [2025-04-30 02:17:58,290 INFO hook.py line 449 1619929] Test: [37/50] Loss 12.8814 Process Time: 0.623 Mem R(MA/MR): 28510 (21973/36182) [2025-04-30 02:17:59,710 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8779 Process Time: 0.282 Mem R(MA/MR): 10696 (21973/36182) [2025-04-30 02:18:00,428 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2917 Process Time: 0.320 Mem R(MA/MR): 5786 (21973/36182) [2025-04-30 02:18:01,625 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8452 Process Time: 0.438 Mem R(MA/MR): 10116 (21973/36182) [2025-04-30 02:18:03,017 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5095 Process Time: 0.387 Mem R(MA/MR): 9222 (21973/36182) [2025-04-30 02:18:03,553 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.8037 Process Time: 0.159 Mem R(MA/MR): 5830 (21973/36182) [2025-04-30 02:18:04,113 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5779 Process Time: 0.252 Mem R(MA/MR): 5892 (21973/36182) [2025-04-30 02:18:04,746 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.6532 Process Time: 0.223 Mem R(MA/MR): 7114 (21973/36182) [2025-04-30 02:18:05,343 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.2391 Process Time: 0.192 Mem R(MA/MR): 5288 (21973/36182) [2025-04-30 02:18:07,241 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.2943 Process Time: 0.270 Mem R(MA/MR): 14746 (21973/36182) [2025-04-30 02:18:13,774 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.9147 Process Time: 0.363 Mem R(MA/MR): 19978 (21973/36182) [2025-04-30 02:18:24,722 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.3910 Process Time: 1.561 Mem R(MA/MR): 34360 (21973/36182) [2025-04-30 02:18:25,341 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.8819 Process Time: 0.170 Mem R(MA/MR): 5932 (21973/36182) [2025-04-30 02:18:27,436 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.3757 Process Time: 0.306 Mem R(MA/MR): 13836 (21973/36182) [2025-04-30 02:18:32,076 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 02:18:32,076 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 02:18:32,076 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] table : 0.283 0.584 0.740 0.754 0.632 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] door : 0.444 0.762 0.923 0.861 0.785 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] ceiling lamp : 0.594 0.790 0.901 0.903 0.724 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] cabinet : 0.358 0.518 0.581 0.867 0.388 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] blinds : 0.604 0.866 0.864 0.947 0.783 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] curtain : 0.366 0.769 0.805 0.833 0.833 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] chair : 0.657 0.795 0.827 0.775 0.803 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] storage cabinet: 0.264 0.334 0.507 0.522 0.480 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] office chair : 0.523 0.557 0.557 0.714 0.729 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] bookshelf : 0.364 0.591 0.725 0.615 0.727 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] whiteboard : 0.605 0.799 0.832 1.000 0.714 [2025-04-30 02:18:32,076 INFO hook.py line 395 1619929] window : 0.162 0.358 0.589 0.457 0.473 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] box : 0.232 0.426 0.546 0.689 0.403 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] monitor : 0.650 0.788 0.840 0.932 0.786 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] shelf : 0.165 0.337 0.430 0.556 0.333 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] heater : 0.420 0.730 0.812 0.853 0.763 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] kitchen cabinet: 0.087 0.274 0.513 0.308 0.640 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] sofa : 0.559 0.685 0.857 0.800 0.667 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] bed : 0.184 0.415 0.816 0.385 0.625 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] trash can : 0.503 0.652 0.685 0.788 0.800 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] book : 0.016 0.033 0.067 0.259 0.079 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] plant : 0.403 0.676 0.797 0.917 0.611 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] blanket : 0.537 0.755 0.755 0.800 0.727 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] tv : 0.887 0.974 0.974 0.857 1.000 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] computer tower : 0.294 0.472 0.746 0.686 0.571 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] refrigerator : 0.220 0.379 0.379 1.000 0.333 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] jacket : 0.087 0.233 0.346 0.400 0.545 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] sink : 0.420 0.688 0.874 0.773 0.773 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] bag : 0.124 0.206 0.251 0.367 0.407 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] picture : 0.123 0.272 0.364 0.609 0.359 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] pillow : 0.594 0.787 0.787 0.923 0.632 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] towel : 0.217 0.351 0.467 0.750 0.316 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] suitcase : 0.438 0.476 0.476 1.000 0.429 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] backpack : 0.494 0.664 0.668 1.000 0.615 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] crate : 0.098 0.487 0.489 1.000 0.455 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] keyboard : 0.443 0.622 0.686 0.885 0.590 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] toilet : 0.856 0.889 1.000 1.000 0.889 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] printer : 0.460 0.535 0.556 0.833 0.556 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] poster : 0.000 0.003 0.018 0.056 0.111 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] painting : 0.038 0.038 0.045 0.077 1.000 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] microwave : 0.567 0.875 0.875 1.000 0.875 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] shoes : 0.140 0.285 0.614 0.714 0.366 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] socket : 0.195 0.494 0.688 0.667 0.514 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] bottle : 0.133 0.216 0.371 0.435 0.325 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] bucket : 0.011 0.016 0.016 0.111 0.286 [2025-04-30 02:18:32,077 INFO hook.py line 395 1619929] cushion : 0.084 0.172 0.260 0.312 0.833 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] basket : 0.032 0.143 0.143 1.000 0.143 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] telephone : 0.331 0.563 0.565 1.000 0.529 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] laptop : 0.321 0.557 0.571 0.545 0.750 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] plant pot : 0.223 0.579 0.579 0.818 0.562 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] exhaust fan : 0.237 0.356 0.356 0.667 0.400 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] cup : 0.203 0.349 0.375 0.750 0.341 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] coat hanger : 0.344 0.613 0.595 1.000 0.500 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] light switch : 0.242 0.505 0.632 0.739 0.523 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] speaker : 0.270 0.409 0.608 0.625 0.455 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] kettle : 0.204 0.264 0.264 0.667 0.333 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] smoke detector : 0.654 0.824 0.825 1.000 0.750 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] power strip : 0.052 0.100 0.112 0.333 0.400 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.056 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] mouse : 0.536 0.729 0.761 1.000 0.656 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] cutting board : 0.333 0.500 0.500 1.000 0.500 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] toilet paper : 0.263 0.446 0.458 0.727 0.471 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] paper towel : 0.014 0.125 0.125 1.000 0.125 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] clock : 0.441 0.528 0.528 0.667 0.667 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] tap : 0.245 0.535 0.778 0.833 0.556 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] jar : 0.004 0.018 0.018 0.500 0.071 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] soap dispenser : 0.486 0.800 0.800 1.000 0.800 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] bowl : 0.065 0.083 0.083 0.500 0.333 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] whiteboard eraser: 0.195 0.438 0.438 0.800 0.667 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] toilet brush : 0.438 0.667 0.833 1.000 0.667 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] spray bottle : 0.012 0.018 0.018 0.143 0.250 [2025-04-30 02:18:32,078 INFO hook.py line 395 1619929] headphones : 0.326 0.613 0.633 1.000 0.500 [2025-04-30 02:18:32,079 INFO hook.py line 395 1619929] stapler : 0.002 0.019 0.097 0.111 0.333 [2025-04-30 02:18:32,079 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 02:18:32,079 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 02:18:32,079 INFO hook.py line 404 1619929] average : 0.280 0.432 0.499 0.651 0.495 [2025-04-30 02:18:32,079 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 02:18:32,079 INFO hook.py line 480 1619929] Total Process Time: 21.119 s [2025-04-30 02:18:32,079 INFO hook.py line 481 1619929] Average Process Time: 425.483 ms [2025-04-30 02:18:32,079 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 02:18:32,095 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.432 [2025-04-30 02:18:32,097 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 02:18:32,100 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:20:08,849 INFO hook.py line 650 1619929] Train: [449/512][50/242] Data 0.016 (0.016) Batch 1.461 (1.503) Remain 06:26:41 loss: 4.1220 Lr: 4.61622e-05 Mem R(MA/MR): 23226 (21973/36182) [2025-04-30 02:21:22,600 INFO hook.py line 650 1619929] Train: [449/512][100/242] Data 0.016 (0.016) Batch 1.630 (1.489) Remain 06:21:45 loss: 4.2019 Lr: 4.60281e-05 Mem R(MA/MR): 27454 (21973/36182) [2025-04-30 02:22:36,329 INFO hook.py line 650 1619929] Train: [449/512][150/242] Data 0.018 (0.022) Batch 1.535 (1.484) Remain 06:19:17 loss: 4.5325 Lr: 4.58938e-05 Mem R(MA/MR): 27454 (21973/36182) [2025-04-30 02:23:49,209 INFO hook.py line 650 1619929] Train: [449/512][200/242] Data 0.016 (0.021) Batch 1.528 (1.477) Remain 06:16:22 loss: 3.7024 Lr: 4.57596e-05 Mem R(MA/MR): 27458 (21973/36182) [2025-04-30 02:24:45,727 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2371 loss_mask: 0.0312 loss_dice: 1.7602 loss_score: 0.0000 loss_bbox: 0.0460 loss_sp_cls: 0.6944 loss: 4.4535 [2025-04-30 02:24:46,842 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:26:16,095 INFO hook.py line 650 1619929] Train: [450/512][50/242] Data 0.017 (0.017) Batch 1.501 (1.478) Remain 06:14:18 loss: 4.7983 Lr: 4.55125e-05 Mem R(MA/MR): 29528 (21973/36182) [2025-04-30 02:27:30,816 INFO hook.py line 650 1619929] Train: [450/512][100/242] Data 0.017 (0.017) Batch 1.494 (1.486) Remain 06:15:12 loss: 3.2618 Lr: 4.53781e-05 Mem R(MA/MR): 29528 (21973/36182) [2025-04-30 02:28:45,038 INFO hook.py line 650 1619929] Train: [450/512][150/242] Data 0.016 (0.017) Batch 1.471 (1.486) Remain 06:13:48 loss: 4.0476 Lr: 4.52437e-05 Mem R(MA/MR): 32080 (21973/36182) [2025-04-30 02:29:54,876 INFO hook.py line 650 1619929] Train: [450/512][200/242] Data 0.015 (0.017) Batch 1.398 (1.463) Remain 06:06:54 loss: 4.0199 Lr: 4.51092e-05 Mem R(MA/MR): 32086 (21973/36182) [2025-04-30 02:30:52,562 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2376 loss_mask: 0.0314 loss_dice: 1.7598 loss_score: 0.0000 loss_bbox: 0.0459 loss_sp_cls: 0.6955 loss: 4.4617 [2025-04-30 02:30:54,123 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:32:23,875 INFO hook.py line 650 1619929] Train: [451/512][50/242] Data 0.016 (0.017) Batch 1.423 (1.458) Remain 06:03:19 loss: 3.6520 Lr: 4.48617e-05 Mem R(MA/MR): 25132 (21973/36182) [2025-04-30 02:33:36,640 INFO hook.py line 650 1619929] Train: [451/512][100/242] Data 0.019 (0.017) Batch 1.695 (1.457) Remain 06:01:47 loss: 4.6071 Lr: 4.47271e-05 Mem R(MA/MR): 25132 (21973/36182) [2025-04-30 02:34:49,670 INFO hook.py line 650 1619929] Train: [451/512][150/242] Data 0.015 (0.017) Batch 1.387 (1.458) Remain 06:00:55 loss: 4.6240 Lr: 4.45925e-05 Mem R(MA/MR): 25132 (21973/36182) [2025-04-30 02:36:00,838 INFO hook.py line 650 1619929] Train: [451/512][200/242] Data 0.014 (0.017) Batch 1.283 (1.449) Remain 05:57:33 loss: 3.2248 Lr: 4.44578e-05 Mem R(MA/MR): 25132 (21973/36182) [2025-04-30 02:36:59,727 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2357 loss_mask: 0.0309 loss_dice: 1.7396 loss_score: 0.0000 loss_bbox: 0.0458 loss_sp_cls: 0.6856 loss: 4.4100 [2025-04-30 02:37:03,996 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:38:41,849 INFO hook.py line 650 1619929] Train: [452/512][50/242] Data 0.017 (0.021) Batch 1.521 (1.530) Remain 06:15:10 loss: 3.5502 Lr: 4.42098e-05 Mem R(MA/MR): 24516 (21973/36182) [2025-04-30 02:39:56,370 INFO hook.py line 650 1619929] Train: [452/512][100/242] Data 0.017 (0.019) Batch 1.479 (1.510) Remain 06:08:54 loss: 4.2137 Lr: 4.40750e-05 Mem R(MA/MR): 24534 (21973/36182) [2025-04-30 02:41:11,421 INFO hook.py line 650 1619929] Train: [452/512][150/242] Data 0.022 (0.019) Batch 1.586 (1.507) Remain 06:06:55 loss: 4.6940 Lr: 4.39402e-05 Mem R(MA/MR): 24534 (21973/36182) [2025-04-30 02:42:29,167 INFO hook.py line 650 1619929] Train: [452/512][200/242] Data 0.017 (0.019) Batch 1.450 (1.519) Remain 06:08:38 loss: 5.3713 Lr: 4.38053e-05 Mem R(MA/MR): 24548 (21973/36182) [2025-04-30 02:43:27,105 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2378 loss_mask: 0.0317 loss_dice: 1.7594 loss_score: 0.0000 loss_bbox: 0.0470 loss_sp_cls: 0.6908 loss: 4.4610 [2025-04-30 02:43:31,274 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:45:09,101 INFO hook.py line 650 1619929] Train: [453/512][50/242] Data 0.017 (0.018) Batch 1.472 (1.506) Remain 06:03:09 loss: 4.5252 Lr: 4.35569e-05 Mem R(MA/MR): 22316 (21973/36182) [2025-04-30 02:46:25,019 INFO hook.py line 650 1619929] Train: [453/512][100/242] Data 0.018 (0.019) Batch 1.322 (1.512) Remain 06:03:26 loss: 4.1266 Lr: 4.34219e-05 Mem R(MA/MR): 22320 (21973/36182) [2025-04-30 02:47:41,814 INFO hook.py line 650 1619929] Train: [453/512][150/242] Data 0.020 (0.019) Batch 1.549 (1.520) Remain 06:04:06 loss: 4.3055 Lr: 4.32868e-05 Mem R(MA/MR): 22342 (21973/36182) [2025-04-30 02:48:56,032 INFO hook.py line 650 1619929] Train: [453/512][200/242] Data 0.015 (0.019) Batch 1.338 (1.511) Remain 06:00:40 loss: 4.6365 Lr: 4.31517e-05 Mem R(MA/MR): 22342 (21973/36182) [2025-04-30 02:49:54,106 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2338 loss_mask: 0.0309 loss_dice: 1.7562 loss_score: 0.0000 loss_bbox: 0.0465 loss_sp_cls: 0.6881 loss: 4.4428 [2025-04-30 02:49:57,630 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:51:34,572 INFO hook.py line 650 1619929] Train: [454/512][50/242] Data 0.017 (0.017) Batch 1.365 (1.487) Remain 05:52:42 loss: 3.5764 Lr: 4.29030e-05 Mem R(MA/MR): 20878 (21973/36182) [2025-04-30 02:52:48,776 INFO hook.py line 650 1619929] Train: [454/512][100/242] Data 0.016 (0.017) Batch 1.444 (1.486) Remain 05:51:03 loss: 4.6369 Lr: 4.27704e-05 Mem R(MA/MR): 24512 (21973/36182) [2025-04-30 02:54:00,632 INFO hook.py line 650 1619929] Train: [454/512][150/242] Data 0.017 (0.017) Batch 1.380 (1.469) Remain 05:45:56 loss: 5.1014 Lr: 4.26351e-05 Mem R(MA/MR): 24512 (21973/36182) [2025-04-30 02:55:14,950 INFO hook.py line 650 1619929] Train: [454/512][200/242] Data 0.015 (0.017) Batch 1.555 (1.474) Remain 05:45:44 loss: 4.1947 Lr: 4.24997e-05 Mem R(MA/MR): 24540 (21973/36182) [2025-04-30 02:56:12,320 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2335 loss_mask: 0.0309 loss_dice: 1.7513 loss_score: 0.0000 loss_bbox: 0.0465 loss_sp_cls: 0.6889 loss: 4.4305 [2025-04-30 02:56:17,706 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 02:57:45,674 INFO hook.py line 650 1619929] Train: [455/512][50/242] Data 0.018 (0.017) Batch 1.408 (1.496) Remain 05:48:46 loss: 4.2258 Lr: 4.22506e-05 Mem R(MA/MR): 25720 (21973/36182) [2025-04-30 02:58:59,877 INFO hook.py line 650 1619929] Train: [455/512][100/242] Data 0.015 (0.017) Batch 1.435 (1.490) Remain 05:46:04 loss: 5.5681 Lr: 4.21151e-05 Mem R(MA/MR): 28950 (21973/36182) [2025-04-30 03:00:10,900 INFO hook.py line 650 1619929] Train: [455/512][150/242] Data 0.019 (0.017) Batch 1.530 (1.466) Remain 05:39:21 loss: 3.3449 Lr: 4.19795e-05 Mem R(MA/MR): 28956 (21973/36182) [2025-04-30 03:01:23,374 INFO hook.py line 650 1619929] Train: [455/512][200/242] Data 0.017 (0.017) Batch 1.586 (1.462) Remain 05:37:08 loss: 3.2751 Lr: 4.18439e-05 Mem R(MA/MR): 30830 (21973/36182) [2025-04-30 03:02:22,397 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2353 loss_mask: 0.0313 loss_dice: 1.7512 loss_score: 0.0000 loss_bbox: 0.0461 loss_sp_cls: 0.6867 loss: 4.4337 [2025-04-30 03:02:25,971 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:03:58,122 INFO hook.py line 650 1619929] Train: [456/512][50/242] Data 0.017 (0.016) Batch 1.333 (1.443) Remain 05:30:35 loss: 4.9636 Lr: 4.15943e-05 Mem R(MA/MR): 23076 (21973/36182) [2025-04-30 03:05:10,774 INFO hook.py line 650 1619929] Train: [456/512][100/242] Data 0.017 (0.017) Batch 1.570 (1.448) Remain 05:30:32 loss: 3.9128 Lr: 4.14586e-05 Mem R(MA/MR): 23080 (21973/36182) [2025-04-30 03:06:23,083 INFO hook.py line 650 1619929] Train: [456/512][150/242] Data 0.017 (0.017) Batch 1.442 (1.448) Remain 05:29:10 loss: 4.5143 Lr: 4.13228e-05 Mem R(MA/MR): 23080 (21973/36182) [2025-04-30 03:07:34,795 INFO hook.py line 650 1619929] Train: [456/512][200/242] Data 0.015 (0.017) Batch 1.461 (1.444) Remain 05:27:12 loss: 3.8172 Lr: 4.11870e-05 Mem R(MA/MR): 23080 (21973/36182) [2025-04-30 03:08:33,339 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2341 loss_mask: 0.0311 loss_dice: 1.7363 loss_score: 0.0000 loss_bbox: 0.0466 loss_sp_cls: 0.6877 loss: 4.4083 [2025-04-30 03:08:38,205 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 03:08:40,656 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.5813 Process Time: 0.395 Mem R(MA/MR): 4298 (21973/36182) [2025-04-30 03:08:42,568 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9564 Process Time: 0.620 Mem R(MA/MR): 7162 (21973/36182) [2025-04-30 03:08:44,538 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4933 Process Time: 0.838 Mem R(MA/MR): 9626 (21973/36182) [2025-04-30 03:08:53,525 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.5407 Process Time: 1.085 Mem R(MA/MR): 19780 (21973/36182) [2025-04-30 03:08:54,920 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.1551 Process Time: 0.681 Mem R(MA/MR): 7018 (21973/36182) [2025-04-30 03:08:56,547 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7319 Process Time: 0.599 Mem R(MA/MR): 11190 (21973/36182) [2025-04-30 03:08:57,189 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.7536 Process Time: 0.223 Mem R(MA/MR): 6264 (21973/36182) [2025-04-30 03:08:57,659 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.6232 Process Time: 0.147 Mem R(MA/MR): 4330 (21973/36182) [2025-04-30 03:08:58,461 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0465 Process Time: 0.202 Mem R(MA/MR): 11282 (21973/36182) [2025-04-30 03:08:59,962 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5686 Process Time: 0.276 Mem R(MA/MR): 9474 (21973/36182) [2025-04-30 03:09:02,510 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.5011 Process Time: 0.524 Mem R(MA/MR): 18704 (21973/36182) [2025-04-30 03:09:05,265 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.8911 Process Time: 0.643 Mem R(MA/MR): 15332 (21973/36182) [2025-04-30 03:09:06,905 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7086 Process Time: 0.514 Mem R(MA/MR): 8668 (21973/36182) [2025-04-30 03:09:07,294 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.7816 Process Time: 0.155 Mem R(MA/MR): 4628 (21973/36182) [2025-04-30 03:09:10,496 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.5070 Process Time: 0.371 Mem R(MA/MR): 16418 (21973/36182) [2025-04-30 03:09:12,563 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4449 Process Time: 0.572 Mem R(MA/MR): 14374 (21973/36182) [2025-04-30 03:09:13,523 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.0394 Process Time: 0.365 Mem R(MA/MR): 6618 (21973/36182) [2025-04-30 03:09:14,315 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.4059 Process Time: 0.234 Mem R(MA/MR): 8078 (21973/36182) [2025-04-30 03:09:15,460 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.3930 Process Time: 0.138 Mem R(MA/MR): 5930 (21973/36182) [2025-04-30 03:09:16,853 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.4088 Process Time: 0.244 Mem R(MA/MR): 11262 (21973/36182) [2025-04-30 03:09:25,878 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.7929 Process Time: 1.054 Mem R(MA/MR): 23508 (21973/36182) [2025-04-30 03:09:26,416 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7327 Process Time: 0.206 Mem R(MA/MR): 6638 (21973/36182) [2025-04-30 03:09:36,257 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.6803 Process Time: 0.503 Mem R(MA/MR): 10108 (21973/36182) [2025-04-30 03:09:37,202 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.6318 Process Time: 0.227 Mem R(MA/MR): 5220 (21973/36182) [2025-04-30 03:09:38,801 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0200 Process Time: 0.695 Mem R(MA/MR): 8976 (21973/36182) [2025-04-30 03:09:46,382 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.5990 Process Time: 1.022 Mem R(MA/MR): 31742 (21973/36182) [2025-04-30 03:09:48,795 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.1962 Process Time: 0.508 Mem R(MA/MR): 9860 (21973/36182) [2025-04-30 03:09:50,114 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.8936 Process Time: 0.405 Mem R(MA/MR): 8776 (21973/36182) [2025-04-30 03:09:54,886 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.9662 Process Time: 0.308 Mem R(MA/MR): 17082 (21973/36182) [2025-04-30 03:09:56,040 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3642 Process Time: 0.425 Mem R(MA/MR): 7598 (21973/36182) [2025-04-30 03:10:00,315 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.7365 Process Time: 0.531 Mem R(MA/MR): 20500 (21973/36182) [2025-04-30 03:10:00,818 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3271 Process Time: 0.190 Mem R(MA/MR): 3934 (21973/36182) [2025-04-30 03:10:05,118 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.4147 Process Time: 0.499 Mem R(MA/MR): 24618 (21973/36182) [2025-04-30 03:10:06,260 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4755 Process Time: 0.329 Mem R(MA/MR): 9704 (21973/36182) [2025-04-30 03:10:08,221 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7904 Process Time: 0.486 Mem R(MA/MR): 13972 (21973/36182) [2025-04-30 03:10:08,767 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1212 Process Time: 0.232 Mem R(MA/MR): 6474 (21973/36182) [2025-04-30 03:10:12,594 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9721 Process Time: 0.483 Mem R(MA/MR): 28450 (21973/36182) [2025-04-30 03:10:15,328 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1198 Process Time: 0.862 Mem R(MA/MR): 10644 (21973/36182) [2025-04-30 03:10:15,872 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0640 Process Time: 0.183 Mem R(MA/MR): 5408 (21973/36182) [2025-04-30 03:10:16,914 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.6848 Process Time: 0.240 Mem R(MA/MR): 9992 (21973/36182) [2025-04-30 03:10:18,083 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5570 Process Time: 0.407 Mem R(MA/MR): 8896 (21973/36182) [2025-04-30 03:10:18,676 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.5927 Process Time: 0.168 Mem R(MA/MR): 5418 (21973/36182) [2025-04-30 03:10:19,313 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7640 Process Time: 0.324 Mem R(MA/MR): 5472 (21973/36182) [2025-04-30 03:10:20,066 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.4398 Process Time: 0.214 Mem R(MA/MR): 7018 (21973/36182) [2025-04-30 03:10:20,895 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.8440 Process Time: 0.280 Mem R(MA/MR): 5198 (21973/36182) [2025-04-30 03:10:23,553 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.3646 Process Time: 0.714 Mem R(MA/MR): 14330 (21973/36182) [2025-04-30 03:10:31,970 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.0645 Process Time: 1.015 Mem R(MA/MR): 20104 (21973/36182) [2025-04-30 03:10:42,565 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.5571 Process Time: 1.939 Mem R(MA/MR): 35656 (21973/36182) [2025-04-30 03:10:43,341 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.3816 Process Time: 0.269 Mem R(MA/MR): 5688 (21973/36182) [2025-04-30 03:10:45,770 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.4015 Process Time: 0.377 Mem R(MA/MR): 13650 (21973/36182) [2025-04-30 03:10:50,520 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 03:10:50,521 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 03:10:50,521 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] table : 0.293 0.599 0.739 0.790 0.610 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] door : 0.470 0.766 0.915 0.882 0.759 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] ceiling lamp : 0.587 0.760 0.871 0.868 0.724 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] cabinet : 0.329 0.468 0.540 0.550 0.493 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] blinds : 0.564 0.818 0.855 0.944 0.739 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] curtain : 0.377 0.594 0.848 0.750 0.750 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] chair : 0.643 0.780 0.810 0.769 0.750 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] storage cabinet: 0.266 0.403 0.587 0.560 0.560 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] office chair : 0.580 0.598 0.612 0.735 0.750 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] bookshelf : 0.362 0.610 0.680 0.800 0.727 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] whiteboard : 0.545 0.716 0.803 0.957 0.629 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] window : 0.151 0.326 0.653 0.625 0.385 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] box : 0.199 0.372 0.530 0.566 0.425 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] monitor : 0.607 0.742 0.845 0.883 0.757 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] shelf : 0.147 0.308 0.510 0.500 0.367 [2025-04-30 03:10:50,521 INFO hook.py line 395 1619929] heater : 0.492 0.757 0.781 0.900 0.711 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] kitchen cabinet: 0.126 0.343 0.667 0.467 0.560 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] sofa : 0.472 0.596 0.986 0.692 0.750 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] bed : 0.157 0.383 0.687 0.800 0.500 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] trash can : 0.499 0.649 0.699 0.793 0.708 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] book : 0.020 0.034 0.067 0.247 0.082 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] plant : 0.443 0.699 0.754 0.923 0.667 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] blanket : 0.504 0.602 0.662 0.875 0.636 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] tv : 0.778 0.833 0.833 1.000 0.833 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] computer tower : 0.323 0.549 0.756 0.800 0.571 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] refrigerator : 0.236 0.403 0.426 1.000 0.333 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] jacket : 0.120 0.483 0.481 0.474 0.818 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] sink : 0.505 0.788 0.863 0.850 0.773 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] bag : 0.095 0.150 0.172 0.500 0.259 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] picture : 0.140 0.291 0.447 0.722 0.333 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] pillow : 0.661 0.887 0.887 0.708 0.895 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] towel : 0.188 0.339 0.480 0.684 0.342 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] suitcase : 0.414 0.468 0.472 1.000 0.429 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] backpack : 0.447 0.675 0.678 0.692 0.692 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] crate : 0.080 0.246 0.530 0.667 0.364 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] keyboard : 0.502 0.660 0.745 0.774 0.615 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] toilet : 0.868 0.889 1.000 1.000 0.889 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] printer : 0.429 0.483 0.562 0.600 0.667 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] poster : 0.001 0.005 0.007 0.091 0.111 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] painting : 0.051 0.056 0.056 0.111 1.000 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] microwave : 0.643 0.717 1.000 1.000 0.625 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] shoes : 0.120 0.200 0.590 0.538 0.341 [2025-04-30 03:10:50,522 INFO hook.py line 395 1619929] socket : 0.200 0.509 0.706 0.679 0.529 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] bottle : 0.112 0.199 0.305 0.489 0.277 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] bucket : 0.027 0.044 0.044 0.182 0.286 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] cushion : 0.093 0.103 0.237 0.250 0.500 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] basket : 0.007 0.010 0.044 0.143 0.143 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] telephone : 0.365 0.655 0.658 1.000 0.588 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] laptop : 0.348 0.566 0.699 1.000 0.500 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] plant pot : 0.102 0.228 0.414 0.471 0.500 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] exhaust fan : 0.219 0.382 0.390 0.750 0.400 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] cup : 0.237 0.360 0.384 1.000 0.318 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] coat hanger : 0.111 0.250 0.637 1.000 0.250 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] light switch : 0.261 0.554 0.673 0.791 0.523 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] speaker : 0.264 0.380 0.469 0.625 0.455 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] table lamp : 0.444 0.500 0.500 1.000 0.500 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] smoke detector : 0.688 0.904 0.907 0.880 0.917 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] power strip : 0.033 0.077 0.091 0.375 0.300 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] paper bag : 0.052 0.056 0.062 0.111 1.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] mouse : 0.493 0.700 0.703 1.000 0.625 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] cutting board : 0.275 0.396 0.396 0.667 0.500 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] toilet paper : 0.258 0.389 0.447 0.778 0.412 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] paper towel : 0.006 0.013 0.166 0.200 0.125 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 03:10:50,523 INFO hook.py line 395 1619929] tap : 0.154 0.272 0.510 0.500 0.333 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] soap dispenser : 0.499 0.800 0.800 1.000 0.800 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] bowl : 0.157 0.333 0.333 1.000 0.333 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] whiteboard eraser: 0.154 0.382 0.436 0.500 0.833 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] toilet brush : 0.473 0.700 0.890 0.800 0.667 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] spray bottle : 0.009 0.011 0.013 0.091 0.250 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] headphones : 0.290 0.662 0.708 1.000 0.500 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] stapler : 0.001 0.012 0.021 0.071 0.333 [2025-04-30 03:10:50,524 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 03:10:50,524 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 03:10:50,524 INFO hook.py line 404 1619929] average : 0.279 0.412 0.508 0.615 0.487 [2025-04-30 03:10:50,524 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 03:10:50,524 INFO hook.py line 480 1619929] Total Process Time: 23.922 s [2025-04-30 03:10:50,525 INFO hook.py line 481 1619929] Average Process Time: 480.131 ms [2025-04-30 03:10:50,525 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 03:10:50,575 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 03:10:50,580 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:12:25,831 INFO hook.py line 650 1619929] Train: [457/512][50/242] Data 0.017 (0.039) Batch 1.573 (1.503) Remain 05:38:09 loss: 4.5873 Lr: 4.09370e-05 Mem R(MA/MR): 23104 (21973/36182) [2025-04-30 03:13:39,798 INFO hook.py line 650 1619929] Train: [457/512][100/242] Data 0.015 (0.027) Batch 1.510 (1.491) Remain 05:34:12 loss: 4.6607 Lr: 4.08010e-05 Mem R(MA/MR): 24894 (21973/36182) [2025-04-30 03:14:52,644 INFO hook.py line 650 1619929] Train: [457/512][150/242] Data 0.018 (0.024) Batch 1.552 (1.479) Remain 05:30:23 loss: 4.4930 Lr: 4.06650e-05 Mem R(MA/MR): 26768 (21973/36182) [2025-04-30 03:16:07,076 INFO hook.py line 650 1619929] Train: [457/512][200/242] Data 0.015 (0.022) Batch 1.274 (1.482) Remain 05:29:42 loss: 3.8362 Lr: 4.05289e-05 Mem R(MA/MR): 26768 (21973/36182) [2025-04-30 03:17:02,852 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2350 loss_mask: 0.0309 loss_dice: 1.7501 loss_score: 0.0000 loss_bbox: 0.0465 loss_sp_cls: 0.6871 loss: 4.4367 [2025-04-30 03:17:07,935 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:18:35,187 INFO hook.py line 650 1619929] Train: [458/512][50/242] Data 0.017 (0.017) Batch 1.413 (1.473) Remain 05:25:27 loss: 4.3628 Lr: 4.02784e-05 Mem R(MA/MR): 20654 (21973/36182) [2025-04-30 03:19:48,019 INFO hook.py line 650 1619929] Train: [458/512][100/242] Data 0.015 (0.017) Batch 1.355 (1.464) Remain 05:22:24 loss: 3.9625 Lr: 4.01422e-05 Mem R(MA/MR): 20668 (21973/36182) [2025-04-30 03:21:00,289 INFO hook.py line 650 1619929] Train: [458/512][150/242] Data 0.019 (0.017) Batch 1.346 (1.458) Remain 05:19:46 loss: 4.1700 Lr: 4.00059e-05 Mem R(MA/MR): 22698 (21973/36182) [2025-04-30 03:22:12,719 INFO hook.py line 650 1619929] Train: [458/512][200/242] Data 0.015 (0.017) Batch 1.320 (1.456) Remain 05:18:02 loss: 4.4895 Lr: 3.98696e-05 Mem R(MA/MR): 22698 (21973/36182) [2025-04-30 03:23:11,379 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2314 loss_mask: 0.0309 loss_dice: 1.7395 loss_score: 0.0000 loss_bbox: 0.0459 loss_sp_cls: 0.6893 loss: 4.4041 [2025-04-30 03:23:11,982 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:24:40,196 INFO hook.py line 650 1619929] Train: [459/512][50/242] Data 0.018 (0.016) Batch 1.337 (1.418) Remain 05:07:43 loss: 3.1150 Lr: 3.96186e-05 Mem R(MA/MR): 19314 (21973/36182) [2025-04-30 03:25:52,466 INFO hook.py line 650 1619929] Train: [459/512][100/242] Data 0.016 (0.016) Batch 1.544 (1.432) Remain 05:09:33 loss: 4.2432 Lr: 3.94822e-05 Mem R(MA/MR): 19314 (21973/36182) [2025-04-30 03:27:03,093 INFO hook.py line 650 1619929] Train: [459/512][150/242] Data 0.018 (0.016) Batch 1.309 (1.426) Remain 05:06:55 loss: 4.1546 Lr: 3.93457e-05 Mem R(MA/MR): 19314 (21973/36182) [2025-04-30 03:28:15,088 INFO hook.py line 650 1619929] Train: [459/512][200/242] Data 0.015 (0.017) Batch 1.496 (1.429) Remain 05:06:30 loss: 4.6868 Lr: 3.92091e-05 Mem R(MA/MR): 20482 (21973/36182) [2025-04-30 03:29:12,396 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2317 loss_mask: 0.0305 loss_dice: 1.7400 loss_score: 0.0000 loss_bbox: 0.0454 loss_sp_cls: 0.6829 loss: 4.3933 [2025-04-30 03:29:14,441 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:30:51,072 INFO hook.py line 650 1619929] Train: [460/512][50/242] Data 0.015 (0.016) Batch 1.648 (1.464) Remain 05:11:41 loss: 4.2340 Lr: 3.89577e-05 Mem R(MA/MR): 25704 (21973/36182) [2025-04-30 03:32:03,217 INFO hook.py line 650 1619929] Train: [460/512][100/242] Data 0.016 (0.016) Batch 1.539 (1.453) Remain 05:08:11 loss: 4.2151 Lr: 3.88209e-05 Mem R(MA/MR): 25718 (21973/36182) [2025-04-30 03:33:17,226 INFO hook.py line 650 1619929] Train: [460/512][150/242] Data 0.017 (0.017) Batch 1.525 (1.462) Remain 05:08:55 loss: 4.7501 Lr: 3.86842e-05 Mem R(MA/MR): 25718 (21973/36182) [2025-04-30 03:34:30,823 INFO hook.py line 650 1619929] Train: [460/512][200/242] Data 0.015 (0.016) Batch 1.455 (1.465) Remain 05:08:13 loss: 4.0493 Lr: 3.85473e-05 Mem R(MA/MR): 25718 (21973/36182) [2025-04-30 03:35:28,842 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2328 loss_mask: 0.0304 loss_dice: 1.7398 loss_score: 0.0000 loss_bbox: 0.0454 loss_sp_cls: 0.6884 loss: 4.4059 [2025-04-30 03:35:34,141 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:37:10,608 INFO hook.py line 650 1619929] Train: [461/512][50/242] Data 0.021 (0.021) Batch 1.476 (1.545) Remain 05:22:43 loss: 3.9153 Lr: 3.82954e-05 Mem R(MA/MR): 24272 (21973/36182) [2025-04-30 03:38:23,914 INFO hook.py line 650 1619929] Train: [461/512][100/242] Data 0.016 (0.019) Batch 1.599 (1.504) Remain 05:13:00 loss: 4.5111 Lr: 3.81585e-05 Mem R(MA/MR): 24272 (21973/36182) [2025-04-30 03:39:39,603 INFO hook.py line 650 1619929] Train: [461/512][150/242] Data 0.018 (0.019) Batch 1.583 (1.508) Remain 05:12:24 loss: 4.6658 Lr: 3.80214e-05 Mem R(MA/MR): 24272 (21973/36182) [2025-04-30 03:40:52,956 INFO hook.py line 650 1619929] Train: [461/512][200/242] Data 0.016 (0.019) Batch 1.379 (1.497) Remain 05:09:02 loss: 4.0001 Lr: 3.78843e-05 Mem R(MA/MR): 24272 (21973/36182) [2025-04-30 03:41:49,510 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2315 loss_mask: 0.0304 loss_dice: 1.7319 loss_score: 0.0000 loss_bbox: 0.0455 loss_sp_cls: 0.6843 loss: 4.3854 [2025-04-30 03:41:52,073 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:43:23,002 INFO hook.py line 650 1619929] Train: [462/512][50/242] Data 0.016 (0.017) Batch 1.251 (1.523) Remain 05:11:56 loss: 5.3430 Lr: 3.76319e-05 Mem R(MA/MR): 21334 (21973/36182) [2025-04-30 03:44:33,229 INFO hook.py line 650 1619929] Train: [462/512][100/242] Data 0.016 (0.017) Batch 1.453 (1.462) Remain 04:58:14 loss: 5.0648 Lr: 3.74947e-05 Mem R(MA/MR): 22846 (21973/36182) [2025-04-30 03:45:45,428 INFO hook.py line 650 1619929] Train: [462/512][150/242] Data 0.017 (0.017) Batch 1.521 (1.456) Remain 04:55:48 loss: 4.1941 Lr: 3.73574e-05 Mem R(MA/MR): 26348 (21973/36182) [2025-04-30 03:46:57,137 INFO hook.py line 650 1619929] Train: [462/512][200/242] Data 0.014 (0.017) Batch 1.486 (1.450) Remain 04:53:29 loss: 5.3203 Lr: 3.72200e-05 Mem R(MA/MR): 28342 (21973/36182) [2025-04-30 03:47:55,425 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2308 loss_mask: 0.0306 loss_dice: 1.7327 loss_score: 0.0000 loss_bbox: 0.0449 loss_sp_cls: 0.6870 loss: 4.3837 [2025-04-30 03:47:56,912 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:49:36,732 INFO hook.py line 650 1619929] Train: [463/512][50/242] Data 0.019 (0.022) Batch 1.547 (1.607) Remain 05:22:40 loss: 4.6979 Lr: 3.69671e-05 Mem R(MA/MR): 22064 (21973/36182) [2025-04-30 03:50:56,015 INFO hook.py line 650 1619929] Train: [463/512][100/242] Data 0.018 (0.021) Batch 1.843 (1.596) Remain 05:19:10 loss: 4.3594 Lr: 3.68296e-05 Mem R(MA/MR): 24560 (21973/36182) [2025-04-30 03:52:10,597 INFO hook.py line 650 1619929] Train: [463/512][150/242] Data 0.016 (0.020) Batch 1.414 (1.560) Remain 05:10:47 loss: 3.9358 Lr: 3.66920e-05 Mem R(MA/MR): 24564 (21973/36182) [2025-04-30 03:53:21,751 INFO hook.py line 650 1619929] Train: [463/512][200/242] Data 0.014 (0.019) Batch 1.220 (1.526) Remain 05:02:34 loss: 4.0108 Lr: 3.65544e-05 Mem R(MA/MR): 24564 (21973/36182) [2025-04-30 03:54:17,450 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2284 loss_mask: 0.0295 loss_dice: 1.7316 loss_score: 0.0000 loss_bbox: 0.0459 loss_sp_cls: 0.6799 loss: 4.3757 [2025-04-30 03:54:18,907 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 03:55:54,324 INFO hook.py line 650 1619929] Train: [464/512][50/242] Data 0.016 (0.017) Batch 1.377 (1.475) Remain 04:50:19 loss: 2.6322 Lr: 3.63010e-05 Mem R(MA/MR): 22276 (21973/36182) [2025-04-30 03:57:06,254 INFO hook.py line 650 1619929] Train: [464/512][100/242] Data 0.017 (0.017) Batch 1.506 (1.456) Remain 04:45:23 loss: 3.8332 Lr: 3.61632e-05 Mem R(MA/MR): 24110 (21973/36182) [2025-04-30 03:58:19,456 INFO hook.py line 650 1619929] Train: [464/512][150/242] Data 0.016 (0.017) Batch 1.368 (1.459) Remain 04:44:41 loss: 3.7575 Lr: 3.60253e-05 Mem R(MA/MR): 26678 (21973/36182) [2025-04-30 03:59:31,769 INFO hook.py line 650 1619929] Train: [464/512][200/242] Data 0.016 (0.017) Batch 1.321 (1.456) Remain 04:42:51 loss: 3.8229 Lr: 3.58874e-05 Mem R(MA/MR): 26678 (21973/36182) [2025-04-30 04:00:29,769 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2245 loss_mask: 0.0299 loss_dice: 1.7089 loss_score: 0.0000 loss_bbox: 0.0453 loss_sp_cls: 0.6738 loss: 4.3219 [2025-04-30 04:00:32,612 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 04:00:34,888 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.3638 Process Time: 0.252 Mem R(MA/MR): 4520 (21973/36182) [2025-04-30 04:00:36,622 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8541 Process Time: 0.567 Mem R(MA/MR): 7064 (21973/36182) [2025-04-30 04:00:37,968 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2985 Process Time: 0.405 Mem R(MA/MR): 9638 (21973/36182) [2025-04-30 04:00:46,094 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.9813 Process Time: 1.214 Mem R(MA/MR): 19936 (21973/36182) [2025-04-30 04:00:47,315 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3881 Process Time: 0.393 Mem R(MA/MR): 6686 (21973/36182) [2025-04-30 04:00:48,655 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0086 Process Time: 0.424 Mem R(MA/MR): 11304 (21973/36182) [2025-04-30 04:00:49,239 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0443 Process Time: 0.184 Mem R(MA/MR): 6326 (21973/36182) [2025-04-30 04:00:49,689 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3902 Process Time: 0.138 Mem R(MA/MR): 4544 (21973/36182) [2025-04-30 04:00:50,670 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8665 Process Time: 0.250 Mem R(MA/MR): 11448 (21973/36182) [2025-04-30 04:00:52,359 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.1530 Process Time: 0.295 Mem R(MA/MR): 9530 (21973/36182) [2025-04-30 04:00:54,437 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.9619 Process Time: 0.335 Mem R(MA/MR): 18444 (21973/36182) [2025-04-30 04:00:57,052 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3445 Process Time: 0.622 Mem R(MA/MR): 15170 (21973/36182) [2025-04-30 04:00:58,288 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.5428 Process Time: 0.411 Mem R(MA/MR): 8758 (21973/36182) [2025-04-30 04:00:58,712 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9810 Process Time: 0.211 Mem R(MA/MR): 4852 (21973/36182) [2025-04-30 04:01:01,371 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.3441 Process Time: 0.366 Mem R(MA/MR): 16500 (21973/36182) [2025-04-30 04:01:02,952 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6474 Process Time: 0.399 Mem R(MA/MR): 14310 (21973/36182) [2025-04-30 04:01:03,624 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.8372 Process Time: 0.200 Mem R(MA/MR): 6612 (21973/36182) [2025-04-30 04:01:04,423 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6711 Process Time: 0.253 Mem R(MA/MR): 8132 (21973/36182) [2025-04-30 04:01:05,480 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.4216 Process Time: 0.168 Mem R(MA/MR): 5938 (21973/36182) [2025-04-30 04:01:07,076 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.6119 Process Time: 0.468 Mem R(MA/MR): 11530 (21973/36182) [2025-04-30 04:01:15,353 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.3065 Process Time: 0.970 Mem R(MA/MR): 23776 (21973/36182) [2025-04-30 04:01:15,972 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.2693 Process Time: 0.191 Mem R(MA/MR): 6852 (21973/36182) [2025-04-30 04:01:25,078 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.2961 Process Time: 0.382 Mem R(MA/MR): 10002 (21973/36182) [2025-04-30 04:01:25,627 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.3177 Process Time: 0.152 Mem R(MA/MR): 5524 (21973/36182) [2025-04-30 04:01:26,578 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0569 Process Time: 0.302 Mem R(MA/MR): 9082 (21973/36182) [2025-04-30 04:01:32,362 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.0297 Process Time: 0.863 Mem R(MA/MR): 30878 (21973/36182) [2025-04-30 04:01:35,061 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5085 Process Time: 0.611 Mem R(MA/MR): 10070 (21973/36182) [2025-04-30 04:01:36,295 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0142 Process Time: 0.352 Mem R(MA/MR): 8932 (21973/36182) [2025-04-30 04:01:40,663 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.1615 Process Time: 0.281 Mem R(MA/MR): 16616 (21973/36182) [2025-04-30 04:01:41,643 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1822 Process Time: 0.355 Mem R(MA/MR): 7728 (21973/36182) [2025-04-30 04:01:45,559 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.4998 Process Time: 0.556 Mem R(MA/MR): 20562 (21973/36182) [2025-04-30 04:01:46,030 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.4171 Process Time: 0.185 Mem R(MA/MR): 4238 (21973/36182) [2025-04-30 04:01:49,799 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.8996 Process Time: 0.417 Mem R(MA/MR): 24896 (21973/36182) [2025-04-30 04:01:51,066 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6132 Process Time: 0.428 Mem R(MA/MR): 9958 (21973/36182) [2025-04-30 04:01:52,919 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0361 Process Time: 0.394 Mem R(MA/MR): 14106 (21973/36182) [2025-04-30 04:01:53,478 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.4361 Process Time: 0.200 Mem R(MA/MR): 6544 (21973/36182) [2025-04-30 04:01:56,615 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5101 Process Time: 0.423 Mem R(MA/MR): 28252 (21973/36182) [2025-04-30 04:01:58,293 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.9521 Process Time: 0.451 Mem R(MA/MR): 10858 (21973/36182) [2025-04-30 04:01:58,986 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1364 Process Time: 0.318 Mem R(MA/MR): 5646 (21973/36182) [2025-04-30 04:02:00,420 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.6600 Process Time: 0.567 Mem R(MA/MR): 10190 (21973/36182) [2025-04-30 04:02:01,340 INFO hook.py line 449 1619929] Test: [41/50] Loss 4.4130 Process Time: 0.281 Mem R(MA/MR): 8942 (21973/36182) [2025-04-30 04:02:01,785 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.6198 Process Time: 0.140 Mem R(MA/MR): 5694 (21973/36182) [2025-04-30 04:02:02,238 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8022 Process Time: 0.191 Mem R(MA/MR): 5704 (21973/36182) [2025-04-30 04:02:02,811 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3514 Process Time: 0.161 Mem R(MA/MR): 7008 (21973/36182) [2025-04-30 04:02:03,483 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7624 Process Time: 0.237 Mem R(MA/MR): 5480 (21973/36182) [2025-04-30 04:02:05,276 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.2947 Process Time: 0.282 Mem R(MA/MR): 14504 (21973/36182) [2025-04-30 04:02:12,290 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.8136 Process Time: 0.692 Mem R(MA/MR): 20362 (21973/36182) [2025-04-30 04:02:22,314 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.6643 Process Time: 1.611 Mem R(MA/MR): 35560 (21973/36182) [2025-04-30 04:02:23,117 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9137 Process Time: 0.235 Mem R(MA/MR): 5840 (21973/36182) [2025-04-30 04:02:25,179 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.3556 Process Time: 0.272 Mem R(MA/MR): 13600 (21973/36182) [2025-04-30 04:02:28,924 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 04:02:28,924 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 04:02:28,924 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] table : 0.295 0.608 0.722 0.847 0.610 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] door : 0.488 0.786 0.929 0.909 0.759 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] ceiling lamp : 0.586 0.770 0.877 0.868 0.729 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] cabinet : 0.349 0.511 0.557 0.507 0.552 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] blinds : 0.567 0.777 0.837 0.842 0.696 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] curtain : 0.332 0.539 0.716 0.562 0.750 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] chair : 0.681 0.824 0.849 0.788 0.779 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] storage cabinet: 0.205 0.271 0.396 0.448 0.520 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] office chair : 0.584 0.605 0.606 0.717 0.688 [2025-04-30 04:02:28,924 INFO hook.py line 395 1619929] bookshelf : 0.155 0.289 0.606 0.714 0.455 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] whiteboard : 0.549 0.682 0.764 0.957 0.629 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] window : 0.136 0.301 0.630 0.415 0.429 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] box : 0.201 0.325 0.525 0.604 0.337 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] monitor : 0.617 0.749 0.809 0.929 0.743 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] shelf : 0.122 0.271 0.507 0.429 0.300 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] heater : 0.470 0.773 0.839 0.906 0.763 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] kitchen cabinet: 0.133 0.421 0.644 0.591 0.520 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] sofa : 0.488 0.707 0.886 0.889 0.667 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] bed : 0.159 0.510 0.706 0.625 0.625 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] trash can : 0.522 0.680 0.723 0.779 0.815 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] book : 0.015 0.038 0.102 0.207 0.109 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] plant : 0.381 0.718 0.825 0.923 0.667 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] blanket : 0.415 0.541 0.585 0.857 0.545 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] computer tower : 0.286 0.419 0.596 0.667 0.429 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] refrigerator : 0.236 0.379 0.483 1.000 0.333 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] jacket : 0.095 0.330 0.493 0.500 0.545 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] sink : 0.475 0.742 0.887 0.800 0.727 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] bag : 0.125 0.179 0.276 0.333 0.296 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] picture : 0.158 0.330 0.403 0.737 0.359 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] pillow : 0.539 0.679 0.697 0.909 0.526 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] towel : 0.191 0.332 0.518 0.436 0.447 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] suitcase : 0.446 0.505 0.505 1.000 0.429 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] backpack : 0.411 0.599 0.599 1.000 0.538 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] crate : 0.089 0.317 0.492 0.833 0.455 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] keyboard : 0.575 0.758 0.812 0.879 0.744 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] toilet : 0.871 1.000 1.000 1.000 1.000 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] printer : 0.209 0.290 0.301 1.000 0.222 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] poster : 0.001 0.005 0.007 0.033 0.222 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] painting : 0.056 0.056 0.062 0.111 1.000 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] microwave : 0.649 0.731 0.985 0.857 0.750 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] shoes : 0.137 0.205 0.552 0.500 0.317 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] socket : 0.198 0.451 0.660 0.768 0.450 [2025-04-30 04:02:28,925 INFO hook.py line 395 1619929] bottle : 0.116 0.198 0.305 0.371 0.313 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] bucket : 0.008 0.014 0.026 0.200 0.143 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] cushion : 0.120 0.153 0.236 0.194 1.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] basket : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] telephone : 0.335 0.615 0.658 0.889 0.471 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] laptop : 0.419 0.641 0.756 0.625 0.625 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] plant pot : 0.112 0.328 0.473 0.727 0.500 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] exhaust fan : 0.234 0.400 0.400 1.000 0.400 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] cup : 0.238 0.359 0.433 0.882 0.341 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] coat hanger : 0.273 0.750 0.750 1.000 0.750 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] light switch : 0.228 0.469 0.622 0.833 0.462 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] speaker : 0.271 0.362 0.362 0.857 0.545 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.500 1.000 0.333 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] smoke detector : 0.612 0.780 0.780 1.000 0.750 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] power strip : 0.029 0.045 0.075 0.286 0.200 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.056 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] mouse : 0.473 0.670 0.736 0.880 0.688 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] toilet paper : 0.293 0.384 0.494 0.700 0.412 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] paper towel : 0.012 0.016 0.125 0.250 0.125 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] clock : 0.481 0.667 0.667 1.000 0.667 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] tap : 0.143 0.303 0.700 0.625 0.556 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.018 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] soap dispenser : 0.477 0.755 0.755 0.800 0.800 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] bowl : 0.148 0.333 0.333 1.000 0.333 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] whiteboard eraser: 0.204 0.462 0.478 0.625 0.833 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] toilet brush : 0.428 0.707 0.901 1.000 0.667 [2025-04-30 04:02:28,926 INFO hook.py line 395 1619929] spray bottle : 0.011 0.016 0.018 0.125 0.250 [2025-04-30 04:02:28,927 INFO hook.py line 395 1619929] headphones : 0.348 0.633 0.662 1.000 0.500 [2025-04-30 04:02:28,927 INFO hook.py line 395 1619929] stapler : 0.006 0.019 0.079 0.111 0.333 [2025-04-30 04:02:28,927 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:02:28,927 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 04:02:28,927 INFO hook.py line 404 1619929] average : 0.268 0.408 0.493 0.618 0.469 [2025-04-30 04:02:28,927 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 04:02:28,927 INFO hook.py line 480 1619929] Total Process Time: 20.056 s [2025-04-30 04:02:28,927 INFO hook.py line 481 1619929] Average Process Time: 404.154 ms [2025-04-30 04:02:28,927 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 04:02:28,950 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 04:02:28,952 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:04:03,948 INFO hook.py line 650 1619929] Train: [465/512][50/242] Data 0.019 (0.017) Batch 1.428 (1.481) Remain 04:45:28 loss: 2.7461 Lr: 3.56335e-05 Mem R(MA/MR): 21402 (21973/36182) [2025-04-30 04:05:17,287 INFO hook.py line 650 1619929] Train: [465/512][100/242] Data 0.014 (0.017) Batch 1.451 (1.474) Remain 04:42:50 loss: 5.4352 Lr: 3.54954e-05 Mem R(MA/MR): 23088 (21973/36182) [2025-04-30 04:06:29,404 INFO hook.py line 650 1619929] Train: [465/512][150/242] Data 0.018 (0.017) Batch 1.475 (1.463) Remain 04:39:34 loss: 4.5271 Lr: 3.53573e-05 Mem R(MA/MR): 26880 (21973/36182) [2025-04-30 04:07:43,492 INFO hook.py line 650 1619929] Train: [465/512][200/242] Data 0.016 (0.021) Batch 1.596 (1.468) Remain 04:39:15 loss: 4.5257 Lr: 3.52191e-05 Mem R(MA/MR): 29418 (21973/36182) [2025-04-30 04:08:42,904 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2259 loss_mask: 0.0303 loss_dice: 1.7155 loss_score: 0.0000 loss_bbox: 0.0459 loss_sp_cls: 0.6817 loss: 4.3488 [2025-04-30 04:08:47,007 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:10:26,395 INFO hook.py line 650 1619929] Train: [466/512][50/242] Data 0.017 (0.017) Batch 1.647 (1.490) Remain 04:41:14 loss: 5.1542 Lr: 3.49674e-05 Mem R(MA/MR): 23998 (21973/36182) [2025-04-30 04:11:38,802 INFO hook.py line 650 1619929] Train: [466/512][100/242] Data 0.017 (0.016) Batch 1.460 (1.468) Remain 04:35:55 loss: 5.1764 Lr: 3.48290e-05 Mem R(MA/MR): 28474 (21973/36182) [2025-04-30 04:12:52,489 INFO hook.py line 650 1619929] Train: [466/512][150/242] Data 0.018 (0.017) Batch 1.458 (1.470) Remain 04:35:02 loss: 3.8406 Lr: 3.46906e-05 Mem R(MA/MR): 30498 (21973/36182) [2025-04-30 04:14:04,982 INFO hook.py line 650 1619929] Train: [466/512][200/242] Data 0.015 (0.017) Batch 1.440 (1.465) Remain 04:32:51 loss: 4.6233 Lr: 3.45521e-05 Mem R(MA/MR): 30498 (21973/36182) [2025-04-30 04:15:02,683 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2296 loss_mask: 0.0301 loss_dice: 1.7230 loss_score: 0.0000 loss_bbox: 0.0456 loss_sp_cls: 0.6822 loss: 4.3661 [2025-04-30 04:15:04,107 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:16:39,204 INFO hook.py line 650 1619929] Train: [467/512][50/242] Data 0.020 (0.017) Batch 1.762 (1.464) Remain 04:30:22 loss: 4.9356 Lr: 3.42971e-05 Mem R(MA/MR): 21552 (21973/36182) [2025-04-30 04:17:52,831 INFO hook.py line 650 1619929] Train: [467/512][100/242] Data 0.017 (0.017) Batch 1.641 (1.468) Remain 04:29:58 loss: 4.8267 Lr: 3.41584e-05 Mem R(MA/MR): 21552 (21973/36182) [2025-04-30 04:19:06,620 INFO hook.py line 650 1619929] Train: [467/512][150/242] Data 0.017 (0.017) Batch 1.427 (1.471) Remain 04:29:13 loss: 4.0324 Lr: 3.40197e-05 Mem R(MA/MR): 23210 (21973/36182) [2025-04-30 04:20:18,565 INFO hook.py line 650 1619929] Train: [467/512][200/242] Data 0.014 (0.017) Batch 1.264 (1.463) Remain 04:26:30 loss: 4.3208 Lr: 3.38809e-05 Mem R(MA/MR): 25556 (21973/36182) [2025-04-30 04:21:18,002 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2323 loss_mask: 0.0304 loss_dice: 1.7314 loss_score: 0.0000 loss_bbox: 0.0459 loss_sp_cls: 0.6854 loss: 4.3907 [2025-04-30 04:21:21,367 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:22:57,204 INFO hook.py line 650 1619929] Train: [468/512][50/242] Data 0.017 (0.016) Batch 1.413 (1.444) Remain 04:20:56 loss: 3.6015 Lr: 3.36281e-05 Mem R(MA/MR): 17766 (21973/36182) [2025-04-30 04:24:09,989 INFO hook.py line 650 1619929] Train: [468/512][100/242] Data 0.017 (0.017) Batch 1.444 (1.450) Remain 04:20:47 loss: 3.9372 Lr: 3.34891e-05 Mem R(MA/MR): 20618 (21973/36182) [2025-04-30 04:25:23,651 INFO hook.py line 650 1619929] Train: [468/512][150/242] Data 0.016 (0.017) Batch 1.375 (1.458) Remain 04:20:59 loss: 3.7436 Lr: 3.33501e-05 Mem R(MA/MR): 20618 (21973/36182) [2025-04-30 04:26:38,205 INFO hook.py line 650 1619929] Train: [468/512][200/242] Data 0.015 (0.016) Batch 1.402 (1.466) Remain 04:21:16 loss: 4.5535 Lr: 3.32110e-05 Mem R(MA/MR): 20618 (21973/36182) [2025-04-30 04:27:36,385 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2384 loss_mask: 0.0313 loss_dice: 1.7517 loss_score: 0.0000 loss_bbox: 0.0462 loss_sp_cls: 0.6866 loss: 4.4407 [2025-04-30 04:27:41,259 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:29:19,935 INFO hook.py line 650 1619929] Train: [469/512][50/242] Data 0.016 (0.017) Batch 1.558 (1.485) Remain 04:22:13 loss: 5.1055 Lr: 3.29548e-05 Mem R(MA/MR): 26950 (21973/36182) [2025-04-30 04:30:31,806 INFO hook.py line 650 1619929] Train: [469/512][100/242] Data 0.016 (0.016) Batch 1.426 (1.460) Remain 04:16:43 loss: 4.8753 Lr: 3.28156e-05 Mem R(MA/MR): 26956 (21973/36182) [2025-04-30 04:31:42,716 INFO hook.py line 650 1619929] Train: [469/512][150/242] Data 0.017 (0.016) Batch 1.483 (1.446) Remain 04:12:59 loss: 4.4667 Lr: 3.26762e-05 Mem R(MA/MR): 28676 (21973/36182) [2025-04-30 04:32:55,348 INFO hook.py line 650 1619929] Train: [469/512][200/242] Data 0.015 (0.016) Batch 1.446 (1.448) Remain 04:12:05 loss: 4.6037 Lr: 3.25368e-05 Mem R(MA/MR): 31260 (21973/36182) [2025-04-30 04:33:52,274 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2311 loss_mask: 0.0308 loss_dice: 1.7483 loss_score: 0.0000 loss_bbox: 0.0461 loss_sp_cls: 0.6863 loss: 4.4210 [2025-04-30 04:33:55,744 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:35:32,472 INFO hook.py line 650 1619929] Train: [470/512][50/242] Data 0.016 (0.017) Batch 1.504 (1.452) Remain 04:10:34 loss: 3.4959 Lr: 3.22801e-05 Mem R(MA/MR): 21522 (21973/36182) [2025-04-30 04:36:44,898 INFO hook.py line 650 1619929] Train: [470/512][100/242] Data 0.017 (0.017) Batch 1.522 (1.450) Remain 04:09:04 loss: 3.8633 Lr: 3.21404e-05 Mem R(MA/MR): 21526 (21973/36182) [2025-04-30 04:37:56,211 INFO hook.py line 650 1619929] Train: [470/512][150/242] Data 0.016 (0.016) Batch 1.421 (1.442) Remain 04:06:28 loss: 2.9902 Lr: 3.20008e-05 Mem R(MA/MR): 21526 (21973/36182) [2025-04-30 04:39:10,486 INFO hook.py line 650 1619929] Train: [470/512][200/242] Data 0.015 (0.016) Batch 1.434 (1.453) Remain 04:07:09 loss: 4.1525 Lr: 3.18610e-05 Mem R(MA/MR): 21546 (21973/36182) [2025-04-30 04:40:06,691 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2313 loss_mask: 0.0307 loss_dice: 1.7537 loss_score: 0.0000 loss_bbox: 0.0457 loss_sp_cls: 0.6880 loss: 4.4259 [2025-04-30 04:40:10,168 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:41:44,846 INFO hook.py line 650 1619929] Train: [471/512][50/242] Data 0.015 (0.016) Batch 1.355 (1.460) Remain 04:06:08 loss: 4.5574 Lr: 3.16037e-05 Mem R(MA/MR): 20660 (21973/36182) [2025-04-30 04:42:55,972 INFO hook.py line 650 1619929] Train: [471/512][100/242] Data 0.018 (0.016) Batch 1.436 (1.441) Remain 04:01:39 loss: 4.4674 Lr: 3.14638e-05 Mem R(MA/MR): 22488 (21973/36182) [2025-04-30 04:44:10,257 INFO hook.py line 650 1619929] Train: [471/512][150/242] Data 0.016 (0.016) Batch 1.507 (1.456) Remain 04:03:00 loss: 4.0335 Lr: 3.13237e-05 Mem R(MA/MR): 22488 (21973/36182) [2025-04-30 04:45:24,128 INFO hook.py line 650 1619929] Train: [471/512][200/242] Data 0.014 (0.016) Batch 1.427 (1.461) Remain 04:02:42 loss: 3.9472 Lr: 3.11837e-05 Mem R(MA/MR): 24616 (21973/36182) [2025-04-30 04:46:21,545 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2288 loss_mask: 0.0308 loss_dice: 1.7376 loss_score: 0.0000 loss_bbox: 0.0462 loss_sp_cls: 0.6820 loss: 4.3932 [2025-04-30 04:46:23,932 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:47:56,270 INFO hook.py line 650 1619929] Train: [472/512][50/242] Data 0.016 (0.016) Batch 1.458 (1.492) Remain 04:05:28 loss: 4.0520 Lr: 3.09257e-05 Mem R(MA/MR): 22868 (21973/36182) [2025-04-30 04:49:08,062 INFO hook.py line 650 1619929] Train: [472/512][100/242] Data 0.015 (0.016) Batch 1.429 (1.463) Remain 03:59:29 loss: 3.9719 Lr: 3.07855e-05 Mem R(MA/MR): 26262 (21973/36182) [2025-04-30 04:50:19,787 INFO hook.py line 650 1619929] Train: [472/512][150/242] Data 0.016 (0.017) Batch 1.335 (1.453) Remain 03:56:41 loss: 2.9182 Lr: 3.06451e-05 Mem R(MA/MR): 28814 (21973/36182) [2025-04-30 04:51:30,273 INFO hook.py line 650 1619929] Train: [472/512][200/242] Data 0.015 (0.017) Batch 1.401 (1.442) Remain 03:53:41 loss: 3.7872 Lr: 3.05047e-05 Mem R(MA/MR): 28814 (21973/36182) [2025-04-30 04:52:28,396 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2290 loss_mask: 0.0307 loss_dice: 1.7325 loss_score: 0.0000 loss_bbox: 0.0462 loss_sp_cls: 0.6779 loss: 4.3837 [2025-04-30 04:52:28,773 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 04:52:31,205 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.3046 Process Time: 0.384 Mem R(MA/MR): 4334 (21973/36182) [2025-04-30 04:52:33,258 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.4317 Process Time: 0.871 Mem R(MA/MR): 7180 (21973/36182) [2025-04-30 04:52:35,489 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5542 Process Time: 1.002 Mem R(MA/MR): 9678 (21973/36182) [2025-04-30 04:52:43,530 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3230 Process Time: 1.192 Mem R(MA/MR): 19588 (21973/36182) [2025-04-30 04:52:44,579 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.0457 Process Time: 0.409 Mem R(MA/MR): 7038 (21973/36182) [2025-04-30 04:52:46,278 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6824 Process Time: 0.540 Mem R(MA/MR): 11148 (21973/36182) [2025-04-30 04:52:46,849 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1373 Process Time: 0.168 Mem R(MA/MR): 6292 (21973/36182) [2025-04-30 04:52:47,261 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4810 Process Time: 0.114 Mem R(MA/MR): 4384 (21973/36182) [2025-04-30 04:52:48,111 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6559 Process Time: 0.234 Mem R(MA/MR): 11364 (21973/36182) [2025-04-30 04:52:49,675 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4446 Process Time: 0.301 Mem R(MA/MR): 9446 (21973/36182) [2025-04-30 04:52:52,568 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.7549 Process Time: 0.823 Mem R(MA/MR): 18664 (21973/36182) [2025-04-30 04:52:55,053 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.9030 Process Time: 0.539 Mem R(MA/MR): 15172 (21973/36182) [2025-04-30 04:52:56,059 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.3926 Process Time: 0.278 Mem R(MA/MR): 8618 (21973/36182) [2025-04-30 04:52:56,442 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9218 Process Time: 0.174 Mem R(MA/MR): 4648 (21973/36182) [2025-04-30 04:52:59,285 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.6137 Process Time: 0.301 Mem R(MA/MR): 16260 (21973/36182) [2025-04-30 04:53:01,724 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.8291 Process Time: 0.943 Mem R(MA/MR): 14334 (21973/36182) [2025-04-30 04:53:02,450 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.4305 Process Time: 0.214 Mem R(MA/MR): 6708 (21973/36182) [2025-04-30 04:53:03,457 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6937 Process Time: 0.366 Mem R(MA/MR): 8098 (21973/36182) [2025-04-30 04:53:04,687 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.8038 Process Time: 0.228 Mem R(MA/MR): 6004 (21973/36182) [2025-04-30 04:53:06,234 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.5491 Process Time: 0.314 Mem R(MA/MR): 11446 (21973/36182) [2025-04-30 04:53:14,960 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.4751 Process Time: 0.528 Mem R(MA/MR): 23738 (21973/36182) [2025-04-30 04:53:15,522 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4207 Process Time: 0.182 Mem R(MA/MR): 6922 (21973/36182) [2025-04-30 04:53:25,571 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.9749 Process Time: 0.509 Mem R(MA/MR): 10132 (21973/36182) [2025-04-30 04:53:26,498 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9844 Process Time: 0.431 Mem R(MA/MR): 5300 (21973/36182) [2025-04-30 04:53:27,967 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.6357 Process Time: 0.665 Mem R(MA/MR): 9216 (21973/36182) [2025-04-30 04:53:34,658 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.9922 Process Time: 1.058 Mem R(MA/MR): 31222 (21973/36182) [2025-04-30 04:53:37,525 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.8562 Process Time: 0.684 Mem R(MA/MR): 9844 (21973/36182) [2025-04-30 04:53:38,777 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.6973 Process Time: 0.325 Mem R(MA/MR): 8828 (21973/36182) [2025-04-30 04:53:43,543 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8840 Process Time: 0.403 Mem R(MA/MR): 16462 (21973/36182) [2025-04-30 04:53:44,938 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3098 Process Time: 0.598 Mem R(MA/MR): 7824 (21973/36182) [2025-04-30 04:53:49,072 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8985 Process Time: 0.785 Mem R(MA/MR): 20248 (21973/36182) [2025-04-30 04:53:49,358 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2286 Process Time: 0.126 Mem R(MA/MR): 3980 (21973/36182) [2025-04-30 04:53:53,026 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.8092 Process Time: 0.382 Mem R(MA/MR): 24752 (21973/36182) [2025-04-30 04:53:55,276 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4680 Process Time: 0.905 Mem R(MA/MR): 9764 (21973/36182) [2025-04-30 04:53:57,558 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7805 Process Time: 0.485 Mem R(MA/MR): 13972 (21973/36182) [2025-04-30 04:53:58,285 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0505 Process Time: 0.161 Mem R(MA/MR): 6524 (21973/36182) [2025-04-30 04:54:01,919 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8795 Process Time: 0.491 Mem R(MA/MR): 28416 (21973/36182) [2025-04-30 04:54:04,440 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.1210 Process Time: 0.770 Mem R(MA/MR): 10624 (21973/36182) [2025-04-30 04:54:05,389 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1408 Process Time: 0.324 Mem R(MA/MR): 5434 (21973/36182) [2025-04-30 04:54:06,995 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.4040 Process Time: 0.574 Mem R(MA/MR): 10006 (21973/36182) [2025-04-30 04:54:08,008 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.8913 Process Time: 0.208 Mem R(MA/MR): 8932 (21973/36182) [2025-04-30 04:54:08,501 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.4976 Process Time: 0.143 Mem R(MA/MR): 5476 (21973/36182) [2025-04-30 04:54:09,005 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8303 Process Time: 0.180 Mem R(MA/MR): 5508 (21973/36182) [2025-04-30 04:54:09,756 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.2453 Process Time: 0.275 Mem R(MA/MR): 7024 (21973/36182) [2025-04-30 04:54:10,333 INFO hook.py line 449 1619929] Test: [45/50] Loss 5.2712 Process Time: 0.155 Mem R(MA/MR): 5258 (21973/36182) [2025-04-30 04:54:12,560 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.4578 Process Time: 0.541 Mem R(MA/MR): 14348 (21973/36182) [2025-04-30 04:54:21,091 INFO hook.py line 449 1619929] Test: [47/50] Loss 7.2446 Process Time: 1.253 Mem R(MA/MR): 20168 (21973/36182) [2025-04-30 04:54:31,635 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.4201 Process Time: 1.890 Mem R(MA/MR): 35234 (21973/36182) [2025-04-30 04:54:32,658 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.7848 Process Time: 0.297 Mem R(MA/MR): 5580 (21973/36182) [2025-04-30 04:54:34,806 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.7199 Process Time: 0.430 Mem R(MA/MR): 13434 (21973/36182) [2025-04-30 04:54:39,602 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 04:54:39,603 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 04:54:39,603 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] table : 0.294 0.602 0.782 0.752 0.625 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] door : 0.444 0.757 0.892 0.894 0.747 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] ceiling lamp : 0.575 0.777 0.881 0.866 0.751 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] cabinet : 0.321 0.503 0.575 0.618 0.507 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] blinds : 0.501 0.727 0.792 0.692 0.783 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] curtain : 0.278 0.466 0.639 0.450 0.750 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] chair : 0.670 0.793 0.830 0.914 0.693 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] storage cabinet: 0.230 0.348 0.488 0.588 0.400 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] office chair : 0.611 0.663 0.676 0.731 0.792 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] bookshelf : 0.267 0.698 0.719 0.857 0.545 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] whiteboard : 0.535 0.696 0.747 1.000 0.600 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] window : 0.141 0.276 0.584 0.391 0.374 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] box : 0.213 0.387 0.541 0.645 0.392 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] monitor : 0.629 0.761 0.821 0.915 0.771 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] shelf : 0.128 0.290 0.480 0.579 0.367 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] heater : 0.400 0.685 0.725 0.960 0.632 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] kitchen cabinet: 0.146 0.371 0.637 0.600 0.480 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] sofa : 0.453 0.556 0.875 0.700 0.583 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] bed : 0.298 0.602 0.985 0.833 0.625 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] trash can : 0.522 0.684 0.700 0.764 0.846 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] book : 0.020 0.042 0.069 0.196 0.101 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] plant : 0.378 0.550 0.722 0.917 0.611 [2025-04-30 04:54:39,603 INFO hook.py line 395 1619929] blanket : 0.550 0.701 0.758 1.000 0.545 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] computer tower : 0.285 0.458 0.680 0.700 0.500 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] refrigerator : 0.210 0.352 0.432 1.000 0.333 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] jacket : 0.088 0.387 0.468 0.600 0.545 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] sink : 0.508 0.780 0.873 0.857 0.818 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] bag : 0.104 0.210 0.286 0.583 0.259 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] picture : 0.118 0.263 0.372 0.484 0.385 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] pillow : 0.600 0.807 0.849 0.923 0.632 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] towel : 0.207 0.328 0.495 0.583 0.368 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] suitcase : 0.415 0.551 0.551 1.000 0.429 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] backpack : 0.450 0.606 0.606 0.889 0.615 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] crate : 0.040 0.163 0.420 0.417 0.455 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] keyboard : 0.492 0.630 0.741 0.727 0.615 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] toilet : 0.872 1.000 1.000 1.000 1.000 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] printer : 0.381 0.537 0.556 1.000 0.444 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] microwave : 0.538 0.708 0.875 0.857 0.750 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] shoes : 0.126 0.216 0.578 0.516 0.390 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] socket : 0.189 0.477 0.701 0.717 0.471 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] bottle : 0.128 0.217 0.325 0.422 0.325 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] bucket : 0.053 0.081 0.081 0.286 0.286 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] cushion : 0.078 0.134 0.236 0.250 0.333 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] basket : 0.008 0.018 0.018 0.250 0.143 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] telephone : 0.411 0.706 0.696 1.000 0.706 [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 04:54:39,604 INFO hook.py line 395 1619929] laptop : 0.305 0.531 0.635 0.500 0.625 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] plant pot : 0.164 0.340 0.576 0.667 0.500 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] exhaust fan : 0.186 0.337 0.337 0.750 0.400 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] cup : 0.238 0.331 0.376 0.929 0.295 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] coat hanger : 0.236 0.750 0.750 1.000 0.750 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] light switch : 0.263 0.529 0.626 0.850 0.523 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] speaker : 0.370 0.435 0.493 0.800 0.364 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] kettle : 0.241 0.333 0.333 1.000 0.333 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] smoke detector : 0.662 0.833 0.833 1.000 0.833 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] power strip : 0.074 0.133 0.190 0.600 0.300 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] mouse : 0.516 0.759 0.764 0.862 0.781 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] cutting board : 0.306 0.500 0.500 1.000 0.500 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] toilet paper : 0.278 0.412 0.479 1.000 0.412 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] paper towel : 0.070 0.143 0.250 1.000 0.125 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] clock : 0.441 0.528 0.528 0.667 0.667 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] tap : 0.172 0.389 0.700 0.500 0.667 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] soap dispenser : 0.502 0.800 0.963 1.000 0.800 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] bowl : 0.185 0.333 0.333 1.000 0.333 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] whiteboard eraser: 0.125 0.346 0.346 0.571 0.667 [2025-04-30 04:54:39,605 INFO hook.py line 395 1619929] toilet brush : 0.418 0.667 0.833 1.000 0.667 [2025-04-30 04:54:39,606 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,606 INFO hook.py line 395 1619929] headphones : 0.407 0.792 1.000 0.667 1.000 [2025-04-30 04:54:39,606 INFO hook.py line 395 1619929] stapler : 0.013 0.065 0.024 0.182 0.667 [2025-04-30 04:54:39,606 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 04:54:39,606 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 04:54:39,606 INFO hook.py line 404 1619929] average : 0.275 0.425 0.508 0.640 0.470 [2025-04-30 04:54:39,606 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 04:54:39,606 INFO hook.py line 480 1619929] Total Process Time: 25.156 s [2025-04-30 04:54:39,606 INFO hook.py line 481 1619929] Average Process Time: 505.545 ms [2025-04-30 04:54:39,606 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 04:54:39,625 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 04:54:39,630 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 04:56:12,557 INFO hook.py line 650 1619929] Train: [473/512][50/242] Data 0.016 (0.016) Batch 1.433 (1.459) Remain 03:54:11 loss: 3.8186 Lr: 3.02461e-05 Mem R(MA/MR): 19796 (21973/36182) [2025-04-30 04:57:24,057 INFO hook.py line 650 1619929] Train: [473/512][100/242] Data 0.017 (0.016) Batch 1.568 (1.444) Remain 03:50:34 loss: 4.3390 Lr: 3.01055e-05 Mem R(MA/MR): 21670 (21973/36182) [2025-04-30 04:58:37,471 INFO hook.py line 650 1619929] Train: [473/512][150/242] Data 0.016 (0.022) Batch 1.418 (1.452) Remain 03:50:40 loss: 3.4867 Lr: 2.99648e-05 Mem R(MA/MR): 21682 (21973/36182) [2025-04-30 04:59:50,289 INFO hook.py line 650 1619929] Train: [473/512][200/242] Data 0.013 (0.021) Batch 1.352 (1.453) Remain 03:49:37 loss: 4.8762 Lr: 2.98240e-05 Mem R(MA/MR): 24130 (21973/36182) [2025-04-30 05:00:48,146 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2261 loss_mask: 0.0308 loss_dice: 1.7195 loss_score: 0.0000 loss_bbox: 0.0456 loss_sp_cls: 0.6811 loss: 4.3515 [2025-04-30 05:00:52,455 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:02:27,272 INFO hook.py line 650 1619929] Train: [474/512][50/242] Data 0.017 (0.017) Batch 1.619 (1.486) Remain 03:52:28 loss: 4.4296 Lr: 2.95648e-05 Mem R(MA/MR): 21710 (21973/36182) [2025-04-30 05:03:41,379 INFO hook.py line 650 1619929] Train: [474/512][100/242] Data 0.017 (0.017) Batch 1.337 (1.484) Remain 03:50:56 loss: 4.7956 Lr: 2.94238e-05 Mem R(MA/MR): 25040 (21973/36182) [2025-04-30 05:04:52,280 INFO hook.py line 650 1619929] Train: [474/512][150/242] Data 0.018 (0.017) Batch 1.464 (1.461) Remain 03:46:14 loss: 3.4801 Lr: 2.92827e-05 Mem R(MA/MR): 25040 (21973/36182) [2025-04-30 05:06:05,258 INFO hook.py line 650 1619929] Train: [474/512][200/242] Data 0.015 (0.017) Batch 1.435 (1.461) Remain 03:44:56 loss: 3.8913 Lr: 2.91416e-05 Mem R(MA/MR): 27106 (21973/36182) [2025-04-30 05:07:03,934 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2253 loss_mask: 0.0303 loss_dice: 1.7131 loss_score: 0.0000 loss_bbox: 0.0457 loss_sp_cls: 0.6793 loss: 4.3412 [2025-04-30 05:07:08,040 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:08:49,098 INFO hook.py line 650 1619929] Train: [475/512][50/242] Data 0.020 (0.021) Batch 1.684 (1.559) Remain 03:57:40 loss: 4.7402 Lr: 2.88817e-05 Mem R(MA/MR): 23926 (21973/36182) [2025-04-30 05:10:04,327 INFO hook.py line 650 1619929] Train: [475/512][100/242] Data 0.018 (0.020) Batch 1.317 (1.531) Remain 03:52:06 loss: 3.9448 Lr: 2.87404e-05 Mem R(MA/MR): 25754 (21973/36182) [2025-04-30 05:11:19,635 INFO hook.py line 650 1619929] Train: [475/512][150/242] Data 0.016 (0.019) Batch 1.322 (1.523) Remain 03:49:33 loss: 3.7768 Lr: 2.85989e-05 Mem R(MA/MR): 25754 (21973/36182) [2025-04-30 05:12:34,045 INFO hook.py line 650 1619929] Train: [475/512][200/242] Data 0.014 (0.019) Batch 1.359 (1.514) Remain 03:46:58 loss: 4.4350 Lr: 2.84574e-05 Mem R(MA/MR): 25754 (21973/36182) [2025-04-30 05:13:30,113 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2300 loss_mask: 0.0304 loss_dice: 1.7293 loss_score: 0.0000 loss_bbox: 0.0457 loss_sp_cls: 0.6873 loss: 4.3838 [2025-04-30 05:13:33,690 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:15:12,350 INFO hook.py line 650 1619929] Train: [476/512][50/242] Data 0.015 (0.017) Batch 1.311 (1.507) Remain 03:43:36 loss: 4.7047 Lr: 2.81968e-05 Mem R(MA/MR): 24070 (21973/36182) [2025-04-30 05:16:26,540 INFO hook.py line 650 1619929] Train: [476/512][100/242] Data 0.016 (0.017) Batch 1.448 (1.495) Remain 03:40:36 loss: 3.4336 Lr: 2.80551e-05 Mem R(MA/MR): 24070 (21973/36182) [2025-04-30 05:17:40,196 INFO hook.py line 650 1619929] Train: [476/512][150/242] Data 0.017 (0.017) Batch 1.425 (1.488) Remain 03:38:16 loss: 4.6400 Lr: 2.79133e-05 Mem R(MA/MR): 24070 (21973/36182) [2025-04-30 05:18:51,986 INFO hook.py line 650 1619929] Train: [476/512][200/242] Data 0.016 (0.017) Batch 1.548 (1.474) Remain 03:35:06 loss: 3.9769 Lr: 2.77714e-05 Mem R(MA/MR): 24070 (21973/36182) [2025-04-30 05:19:49,991 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2231 loss_mask: 0.0301 loss_dice: 1.7099 loss_score: 0.0000 loss_bbox: 0.0451 loss_sp_cls: 0.6720 loss: 4.3222 [2025-04-30 05:19:50,179 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:21:22,400 INFO hook.py line 650 1619929] Train: [477/512][50/242] Data 0.015 (0.017) Batch 1.447 (1.470) Remain 03:32:12 loss: 4.2709 Lr: 2.75101e-05 Mem R(MA/MR): 22656 (21973/36182) [2025-04-30 05:22:35,390 INFO hook.py line 650 1619929] Train: [477/512][100/242] Data 0.016 (0.016) Batch 1.586 (1.465) Remain 03:30:13 loss: 3.8266 Lr: 2.73680e-05 Mem R(MA/MR): 29436 (21973/36182) [2025-04-30 05:23:47,927 INFO hook.py line 650 1619929] Train: [477/512][150/242] Data 0.017 (0.016) Batch 1.560 (1.460) Remain 03:28:20 loss: 4.6947 Lr: 2.72258e-05 Mem R(MA/MR): 29436 (21973/36182) [2025-04-30 05:25:00,714 INFO hook.py line 650 1619929] Train: [477/512][200/242] Data 0.015 (0.017) Batch 1.216 (1.459) Remain 03:26:58 loss: 3.9280 Lr: 2.70835e-05 Mem R(MA/MR): 29436 (21973/36182) [2025-04-30 05:25:57,116 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2239 loss_mask: 0.0300 loss_dice: 1.7046 loss_score: 0.0000 loss_bbox: 0.0460 loss_sp_cls: 0.6721 loss: 4.3217 [2025-04-30 05:26:01,089 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:27:35,568 INFO hook.py line 650 1619929] Train: [478/512][50/242] Data 0.017 (0.017) Batch 1.366 (1.428) Remain 03:20:19 loss: 3.9343 Lr: 2.68215e-05 Mem R(MA/MR): 22630 (21973/36182) [2025-04-30 05:28:48,084 INFO hook.py line 650 1619929] Train: [478/512][100/242] Data 0.016 (0.017) Batch 1.395 (1.439) Remain 03:20:46 loss: 4.1338 Lr: 2.66789e-05 Mem R(MA/MR): 22660 (21973/36182) [2025-04-30 05:30:01,473 INFO hook.py line 650 1619929] Train: [478/512][150/242] Data 0.017 (0.017) Batch 1.390 (1.449) Remain 03:20:55 loss: 4.1025 Lr: 2.65363e-05 Mem R(MA/MR): 22660 (21973/36182) [2025-04-30 05:31:15,928 INFO hook.py line 650 1619929] Train: [478/512][200/242] Data 0.015 (0.017) Batch 1.381 (1.459) Remain 03:21:07 loss: 4.3573 Lr: 2.63936e-05 Mem R(MA/MR): 22662 (21973/36182) [2025-04-30 05:32:14,146 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2176 loss_mask: 0.0295 loss_dice: 1.6974 loss_score: 0.0000 loss_bbox: 0.0450 loss_sp_cls: 0.6655 loss: 4.2828 [2025-04-30 05:32:17,745 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:33:55,043 INFO hook.py line 650 1619929] Train: [479/512][50/242] Data 0.020 (0.022) Batch 1.329 (1.537) Remain 03:29:30 loss: 4.3036 Lr: 2.61309e-05 Mem R(MA/MR): 27080 (21973/36182) [2025-04-30 05:35:12,157 INFO hook.py line 650 1619929] Train: [479/512][100/242] Data 0.017 (0.021) Batch 1.422 (1.540) Remain 03:28:35 loss: 4.4992 Lr: 2.59879e-05 Mem R(MA/MR): 27082 (21973/36182) [2025-04-30 05:36:28,113 INFO hook.py line 650 1619929] Train: [479/512][150/242] Data 0.018 (0.020) Batch 1.597 (1.533) Remain 03:26:21 loss: 4.5931 Lr: 2.58449e-05 Mem R(MA/MR): 29092 (21973/36182) [2025-04-30 05:37:40,494 INFO hook.py line 650 1619929] Train: [479/512][200/242] Data 0.015 (0.019) Batch 1.446 (1.511) Remain 03:22:11 loss: 4.5208 Lr: 2.57018e-05 Mem R(MA/MR): 29098 (21973/36182) [2025-04-30 05:38:37,473 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2212 loss_mask: 0.0297 loss_dice: 1.7004 loss_score: 0.0000 loss_bbox: 0.0450 loss_sp_cls: 0.6714 loss: 4.2991 [2025-04-30 05:38:38,371 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:40:15,328 INFO hook.py line 650 1619929] Train: [480/512][50/242] Data 0.016 (0.018) Batch 1.434 (1.477) Remain 03:15:18 loss: 3.4584 Lr: 2.54382e-05 Mem R(MA/MR): 19630 (21973/36182) [2025-04-30 05:41:30,304 INFO hook.py line 650 1619929] Train: [480/512][100/242] Data 0.015 (0.018) Batch 1.358 (1.488) Remain 03:15:37 loss: 4.5135 Lr: 2.52948e-05 Mem R(MA/MR): 20232 (21973/36182) [2025-04-30 05:42:43,293 INFO hook.py line 650 1619929] Train: [480/512][150/242] Data 0.018 (0.018) Batch 1.306 (1.479) Remain 03:13:07 loss: 3.9525 Lr: 2.51514e-05 Mem R(MA/MR): 20234 (21973/36182) [2025-04-30 05:43:56,628 INFO hook.py line 650 1619929] Train: [480/512][200/242] Data 0.015 (0.018) Batch 1.396 (1.476) Remain 03:11:29 loss: 4.2574 Lr: 2.50078e-05 Mem R(MA/MR): 20234 (21973/36182) [2025-04-30 05:44:54,671 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2213 loss_mask: 0.0300 loss_dice: 1.7162 loss_score: 0.0000 loss_bbox: 0.0452 loss_sp_cls: 0.6743 loss: 4.3319 [2025-04-30 05:44:59,470 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 05:45:01,827 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1149 Process Time: 0.299 Mem R(MA/MR): 3908 (21973/36182) [2025-04-30 05:45:03,618 INFO hook.py line 449 1619929] Test: [2/50] Loss 6.0397 Process Time: 0.585 Mem R(MA/MR): 6752 (21973/36182) [2025-04-30 05:45:05,482 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5096 Process Time: 0.770 Mem R(MA/MR): 9286 (21973/36182) [2025-04-30 05:45:13,986 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.1863 Process Time: 1.577 Mem R(MA/MR): 19412 (21973/36182) [2025-04-30 05:45:14,956 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4146 Process Time: 0.365 Mem R(MA/MR): 6826 (21973/36182) [2025-04-30 05:45:16,432 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.1999 Process Time: 0.474 Mem R(MA/MR): 10790 (21973/36182) [2025-04-30 05:45:17,123 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.4863 Process Time: 0.238 Mem R(MA/MR): 5910 (21973/36182) [2025-04-30 05:45:17,586 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.7511 Process Time: 0.150 Mem R(MA/MR): 3940 (21973/36182) [2025-04-30 05:45:18,742 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6215 Process Time: 0.418 Mem R(MA/MR): 11092 (21973/36182) [2025-04-30 05:45:20,289 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.2083 Process Time: 0.409 Mem R(MA/MR): 9016 (21973/36182) [2025-04-30 05:45:22,819 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.8169 Process Time: 0.497 Mem R(MA/MR): 18328 (21973/36182) [2025-04-30 05:45:25,787 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.8592 Process Time: 0.750 Mem R(MA/MR): 15024 (21973/36182) [2025-04-30 05:45:27,058 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.6903 Process Time: 0.393 Mem R(MA/MR): 8232 (21973/36182) [2025-04-30 05:45:27,530 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2765 Process Time: 0.192 Mem R(MA/MR): 4254 (21973/36182) [2025-04-30 05:45:30,465 INFO hook.py line 449 1619929] Test: [15/50] Loss 11.8313 Process Time: 0.336 Mem R(MA/MR): 16098 (21973/36182) [2025-04-30 05:45:32,473 INFO hook.py line 449 1619929] Test: [16/50] Loss 7.0228 Process Time: 0.652 Mem R(MA/MR): 14096 (21973/36182) [2025-04-30 05:45:33,421 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3048 Process Time: 0.373 Mem R(MA/MR): 6352 (21973/36182) [2025-04-30 05:45:34,518 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6010 Process Time: 0.370 Mem R(MA/MR): 7718 (21973/36182) [2025-04-30 05:45:35,625 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0453 Process Time: 0.175 Mem R(MA/MR): 5450 (21973/36182) [2025-04-30 05:45:37,082 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.1765 Process Time: 0.227 Mem R(MA/MR): 10974 (21973/36182) [2025-04-30 05:45:45,617 INFO hook.py line 449 1619929] Test: [21/50] Loss 9.1280 Process Time: 0.723 Mem R(MA/MR): 23654 (21973/36182) [2025-04-30 05:45:46,252 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.8137 Process Time: 0.202 Mem R(MA/MR): 6244 (21973/36182) [2025-04-30 05:45:56,174 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.0814 Process Time: 0.331 Mem R(MA/MR): 9732 (21973/36182) [2025-04-30 05:45:56,814 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7598 Process Time: 0.219 Mem R(MA/MR): 4888 (21973/36182) [2025-04-30 05:45:57,975 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9249 Process Time: 0.395 Mem R(MA/MR): 8684 (21973/36182) [2025-04-30 05:46:04,957 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.0919 Process Time: 1.299 Mem R(MA/MR): 31122 (21973/36182) [2025-04-30 05:46:07,157 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.7201 Process Time: 0.258 Mem R(MA/MR): 9466 (21973/36182) [2025-04-30 05:46:08,329 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9681 Process Time: 0.258 Mem R(MA/MR): 8458 (21973/36182) [2025-04-30 05:46:13,455 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.4362 Process Time: 0.814 Mem R(MA/MR): 16488 (21973/36182) [2025-04-30 05:46:14,626 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1795 Process Time: 0.374 Mem R(MA/MR): 7336 (21973/36182) [2025-04-30 05:46:18,405 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.4975 Process Time: 0.652 Mem R(MA/MR): 19934 (21973/36182) [2025-04-30 05:46:18,822 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1889 Process Time: 0.201 Mem R(MA/MR): 3558 (21973/36182) [2025-04-30 05:46:23,017 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.2832 Process Time: 0.561 Mem R(MA/MR): 24430 (21973/36182) [2025-04-30 05:46:24,539 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4271 Process Time: 0.676 Mem R(MA/MR): 9304 (21973/36182) [2025-04-30 05:46:27,031 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.8512 Process Time: 0.627 Mem R(MA/MR): 13696 (21973/36182) [2025-04-30 05:46:27,918 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9361 Process Time: 0.221 Mem R(MA/MR): 6172 (21973/36182) [2025-04-30 05:46:32,120 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.2705 Process Time: 0.895 Mem R(MA/MR): 28020 (21973/36182) [2025-04-30 05:46:33,971 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.2248 Process Time: 0.489 Mem R(MA/MR): 10126 (21973/36182) [2025-04-30 05:46:34,924 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1577 Process Time: 0.323 Mem R(MA/MR): 5076 (21973/36182) [2025-04-30 05:46:36,244 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7994 Process Time: 0.398 Mem R(MA/MR): 9606 (21973/36182) [2025-04-30 05:46:37,296 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.4368 Process Time: 0.248 Mem R(MA/MR): 8512 (21973/36182) [2025-04-30 05:46:37,779 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3961 Process Time: 0.139 Mem R(MA/MR): 5000 (21973/36182) [2025-04-30 05:46:38,262 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8400 Process Time: 0.152 Mem R(MA/MR): 5078 (21973/36182) [2025-04-30 05:46:38,970 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.8406 Process Time: 0.259 Mem R(MA/MR): 6648 (21973/36182) [2025-04-30 05:46:39,762 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6185 Process Time: 0.325 Mem R(MA/MR): 4792 (21973/36182) [2025-04-30 05:46:42,181 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.3873 Process Time: 0.412 Mem R(MA/MR): 14092 (21973/36182) [2025-04-30 05:46:50,876 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1423 Process Time: 1.080 Mem R(MA/MR): 19892 (21973/36182) [2025-04-30 05:47:01,104 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2143 Process Time: 1.943 Mem R(MA/MR): 35152 (21973/36182) [2025-04-30 05:47:01,799 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0211 Process Time: 0.194 Mem R(MA/MR): 5198 (21973/36182) [2025-04-30 05:47:03,980 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2887 Process Time: 0.365 Mem R(MA/MR): 13278 (21973/36182) [2025-04-30 05:47:08,082 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 05:47:08,082 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 05:47:08,082 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] table : 0.275 0.593 0.734 0.823 0.581 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] door : 0.469 0.742 0.903 0.884 0.772 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] ceiling lamp : 0.608 0.810 0.892 0.903 0.773 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] cabinet : 0.318 0.490 0.520 0.583 0.522 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] blinds : 0.609 0.826 0.851 0.833 0.870 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] curtain : 0.445 0.607 0.842 0.875 0.583 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] chair : 0.645 0.778 0.820 0.758 0.758 [2025-04-30 05:47:08,082 INFO hook.py line 395 1619929] storage cabinet: 0.225 0.322 0.473 0.619 0.520 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] office chair : 0.601 0.652 0.655 0.655 0.750 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] bookshelf : 0.321 0.705 0.705 0.750 0.818 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] whiteboard : 0.562 0.789 0.794 0.962 0.714 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] window : 0.112 0.280 0.633 0.533 0.352 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] box : 0.218 0.398 0.554 0.605 0.398 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] monitor : 0.663 0.846 0.887 0.908 0.843 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] shelf : 0.168 0.314 0.496 0.524 0.367 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] heater : 0.384 0.668 0.720 0.862 0.658 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] kitchen cabinet: 0.163 0.376 0.689 0.469 0.600 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] sofa : 0.436 0.563 0.928 0.778 0.583 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] bed : 0.331 0.625 0.905 1.000 0.625 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] trash can : 0.559 0.727 0.790 0.794 0.831 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] book : 0.024 0.049 0.080 0.312 0.090 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] plant : 0.437 0.650 0.765 0.857 0.667 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] blanket : 0.487 0.665 0.684 0.692 0.818 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] computer tower : 0.312 0.498 0.652 0.625 0.595 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] refrigerator : 0.220 0.370 0.454 1.000 0.333 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] jacket : 0.047 0.187 0.389 0.353 0.545 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] sink : 0.506 0.824 0.900 0.826 0.864 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] bag : 0.102 0.150 0.222 0.310 0.333 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] picture : 0.143 0.360 0.430 0.762 0.410 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] pillow : 0.608 0.799 0.837 0.929 0.684 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] towel : 0.199 0.299 0.480 0.438 0.368 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] suitcase : 0.415 0.468 0.472 1.000 0.429 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] backpack : 0.436 0.596 0.596 0.889 0.615 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] crate : 0.051 0.249 0.455 0.800 0.364 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] keyboard : 0.483 0.616 0.712 0.920 0.590 [2025-04-30 05:47:08,083 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] toilet : 0.875 0.889 1.000 1.000 0.889 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] printer : 0.251 0.332 0.370 0.750 0.333 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.003 0.040 0.111 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] painting : 0.045 0.045 0.056 0.091 1.000 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] microwave : 0.630 0.858 1.000 0.875 0.875 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] shoes : 0.131 0.241 0.583 0.636 0.341 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] socket : 0.193 0.484 0.684 0.761 0.500 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] bottle : 0.141 0.269 0.355 0.500 0.337 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] bucket : 0.027 0.043 0.043 0.222 0.286 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] cushion : 0.031 0.054 0.155 0.188 0.500 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] basket : 0.028 0.036 0.226 0.500 0.143 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] shoe rack : 0.111 0.500 0.500 1.000 0.500 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] telephone : 0.435 0.721 0.723 1.000 0.647 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] laptop : 0.375 0.592 0.725 0.833 0.625 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] plant pot : 0.140 0.318 0.436 0.727 0.500 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] exhaust fan : 0.190 0.306 0.306 0.833 0.333 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] cup : 0.241 0.402 0.442 0.944 0.386 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] coat hanger : 0.253 0.750 0.908 1.000 0.750 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] light switch : 0.266 0.532 0.643 0.814 0.538 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] speaker : 0.424 0.467 0.619 1.000 0.364 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] kettle : 0.242 0.264 0.264 0.667 0.333 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] smoke detector : 0.633 0.833 0.833 1.000 0.833 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] power strip : 0.041 0.057 0.089 0.400 0.200 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.083 0.000 0.000 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,084 INFO hook.py line 395 1619929] mouse : 0.493 0.689 0.723 0.870 0.625 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] toilet paper : 0.302 0.421 0.562 0.875 0.412 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] paper towel : 0.024 0.031 0.125 0.500 0.125 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] clock : 0.519 0.667 0.667 1.000 0.667 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] pan : 0.028 0.250 0.250 1.000 0.250 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] tap : 0.197 0.462 0.763 0.556 0.556 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] soap dispenser : 0.496 0.755 0.893 0.800 0.800 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] bowl : 0.093 0.192 0.192 0.400 0.667 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] tissue box : 0.035 0.062 0.083 0.250 0.500 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] whiteboard eraser: 0.124 0.334 0.346 0.750 0.500 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] toilet brush : 0.506 0.726 0.913 1.000 0.667 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] headphones : 0.394 0.708 0.708 0.500 1.000 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] stapler : 0.001 0.011 0.089 0.067 0.333 [2025-04-30 05:47:08,085 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 05:47:08,085 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 05:47:08,085 INFO hook.py line 404 1619929] average : 0.280 0.423 0.510 0.636 0.495 [2025-04-30 05:47:08,085 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 05:47:08,086 INFO hook.py line 480 1619929] Total Process Time: 24.283 s [2025-04-30 05:47:08,086 INFO hook.py line 481 1619929] Average Process Time: 489.463 ms [2025-04-30 05:47:08,086 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 05:47:08,120 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 05:47:08,126 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:48:45,454 INFO hook.py line 650 1619929] Train: [481/512][50/242] Data 0.016 (0.037) Batch 1.420 (1.501) Remain 03:12:32 loss: 4.1105 Lr: 2.47435e-05 Mem R(MA/MR): 21810 (21973/36182) [2025-04-30 05:49:58,728 INFO hook.py line 650 1619929] Train: [481/512][100/242] Data 0.017 (0.026) Batch 1.489 (1.483) Remain 03:08:55 loss: 4.2907 Lr: 2.45997e-05 Mem R(MA/MR): 24286 (21973/36182) [2025-04-30 05:51:11,166 INFO hook.py line 650 1619929] Train: [481/512][150/242] Data 0.019 (0.023) Batch 1.455 (1.471) Remain 03:06:13 loss: 5.0571 Lr: 2.44558e-05 Mem R(MA/MR): 24286 (21973/36182) [2025-04-30 05:52:24,329 INFO hook.py line 650 1619929] Train: [481/512][200/242] Data 0.015 (0.021) Batch 1.530 (1.469) Remain 03:04:44 loss: 5.3552 Lr: 2.43118e-05 Mem R(MA/MR): 24286 (21973/36182) [2025-04-30 05:53:20,486 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2230 loss_mask: 0.0296 loss_dice: 1.7007 loss_score: 0.0000 loss_bbox: 0.0448 loss_sp_cls: 0.6719 loss: 4.3003 [2025-04-30 05:53:22,779 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 05:54:58,131 INFO hook.py line 650 1619929] Train: [482/512][50/242] Data 0.016 (0.017) Batch 1.579 (1.474) Remain 03:03:04 loss: 4.5129 Lr: 2.40465e-05 Mem R(MA/MR): 20548 (21973/36182) [2025-04-30 05:56:10,249 INFO hook.py line 650 1619929] Train: [482/512][100/242] Data 0.016 (0.017) Batch 1.518 (1.458) Remain 02:59:50 loss: 3.5009 Lr: 2.39023e-05 Mem R(MA/MR): 24896 (21973/36182) [2025-04-30 05:57:21,675 INFO hook.py line 650 1619929] Train: [482/512][150/242] Data 0.016 (0.017) Batch 1.424 (1.448) Remain 02:57:24 loss: 4.8218 Lr: 2.37579e-05 Mem R(MA/MR): 29256 (21973/36182) [2025-04-30 05:58:31,586 INFO hook.py line 650 1619929] Train: [482/512][200/242] Data 0.014 (0.017) Batch 1.424 (1.435) Remain 02:54:39 loss: 4.4942 Lr: 2.36134e-05 Mem R(MA/MR): 29256 (21973/36182) [2025-04-30 05:59:28,926 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2195 loss_mask: 0.0293 loss_dice: 1.7013 loss_score: 0.0000 loss_bbox: 0.0450 loss_sp_cls: 0.6690 loss: 4.2943 [2025-04-30 05:59:32,569 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:01:10,894 INFO hook.py line 650 1619929] Train: [483/512][50/242] Data 0.016 (0.019) Batch 1.586 (1.558) Remain 03:07:16 loss: 5.0237 Lr: 2.33474e-05 Mem R(MA/MR): 21112 (21973/36182) [2025-04-30 06:02:24,560 INFO hook.py line 650 1619929] Train: [483/512][100/242] Data 0.016 (0.018) Batch 1.565 (1.515) Remain 03:00:44 loss: 4.8113 Lr: 2.32026e-05 Mem R(MA/MR): 21112 (21973/36182) [2025-04-30 06:03:36,149 INFO hook.py line 650 1619929] Train: [483/512][150/242] Data 0.016 (0.018) Batch 1.385 (1.486) Remain 02:56:08 loss: 6.6267 Lr: 2.30578e-05 Mem R(MA/MR): 24018 (21973/36182) [2025-04-30 06:04:48,413 INFO hook.py line 650 1619929] Train: [483/512][200/242] Data 0.015 (0.018) Batch 1.436 (1.476) Remain 02:53:40 loss: 4.6346 Lr: 2.29128e-05 Mem R(MA/MR): 24018 (21973/36182) [2025-04-30 06:05:45,841 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2194 loss_mask: 0.0298 loss_dice: 1.6994 loss_score: 0.0000 loss_bbox: 0.0450 loss_sp_cls: 0.6726 loss: 4.2924 [2025-04-30 06:05:50,268 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:07:26,715 INFO hook.py line 650 1619929] Train: [484/512][50/242] Data 0.015 (0.017) Batch 1.354 (1.485) Remain 02:52:30 loss: 4.0737 Lr: 2.26459e-05 Mem R(MA/MR): 23360 (21973/36182) [2025-04-30 06:08:38,969 INFO hook.py line 650 1619929] Train: [484/512][100/242] Data 0.016 (0.017) Batch 1.409 (1.465) Remain 02:48:52 loss: 3.7173 Lr: 2.25006e-05 Mem R(MA/MR): 25378 (21973/36182) [2025-04-30 06:09:50,723 INFO hook.py line 650 1619929] Train: [484/512][150/242] Data 0.016 (0.017) Batch 1.440 (1.455) Remain 02:46:29 loss: 4.9336 Lr: 2.23553e-05 Mem R(MA/MR): 25378 (21973/36182) [2025-04-30 06:11:01,082 INFO hook.py line 650 1619929] Train: [484/512][200/242] Data 0.014 (0.017) Batch 1.339 (1.443) Remain 02:43:55 loss: 4.2447 Lr: 2.22098e-05 Mem R(MA/MR): 25390 (21973/36182) [2025-04-30 06:11:58,327 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2212 loss_mask: 0.0299 loss_dice: 1.7019 loss_score: 0.0000 loss_bbox: 0.0452 loss_sp_cls: 0.6712 loss: 4.3015 [2025-04-30 06:12:02,088 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:13:34,517 INFO hook.py line 650 1619929] Train: [485/512][50/242] Data 0.017 (0.017) Batch 1.444 (1.493) Remain 02:47:21 loss: 3.7637 Lr: 2.19419e-05 Mem R(MA/MR): 22488 (21973/36182) [2025-04-30 06:14:46,929 INFO hook.py line 650 1619929] Train: [485/512][100/242] Data 0.016 (0.017) Batch 1.442 (1.470) Remain 02:43:33 loss: 4.3383 Lr: 2.17962e-05 Mem R(MA/MR): 24334 (21973/36182) [2025-04-30 06:16:00,003 INFO hook.py line 650 1619929] Train: [485/512][150/242] Data 0.017 (0.017) Batch 1.478 (1.467) Remain 02:42:00 loss: 3.6952 Lr: 2.16503e-05 Mem R(MA/MR): 25262 (21973/36182) [2025-04-30 06:17:12,498 INFO hook.py line 650 1619929] Train: [485/512][200/242] Data 0.016 (0.017) Batch 1.406 (1.463) Remain 02:40:18 loss: 3.5417 Lr: 2.15044e-05 Mem R(MA/MR): 25262 (21973/36182) [2025-04-30 06:18:09,153 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2191 loss_mask: 0.0298 loss_dice: 1.6961 loss_score: 0.0000 loss_bbox: 0.0453 loss_sp_cls: 0.6675 loss: 4.2904 [2025-04-30 06:18:12,306 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:19:44,462 INFO hook.py line 650 1619929] Train: [486/512][50/242] Data 0.017 (0.018) Batch 1.549 (1.487) Remain 02:40:38 loss: 4.3523 Lr: 2.12384e-05 Mem R(MA/MR): 20870 (21973/36182) [2025-04-30 06:20:58,387 INFO hook.py line 650 1619929] Train: [486/512][100/242] Data 0.017 (0.017) Batch 1.359 (1.482) Remain 02:38:57 loss: 3.1250 Lr: 2.10921e-05 Mem R(MA/MR): 20870 (21973/36182) [2025-04-30 06:22:09,985 INFO hook.py line 650 1619929] Train: [486/512][150/242] Data 0.017 (0.017) Batch 1.450 (1.465) Remain 02:35:53 loss: 5.2506 Lr: 2.09457e-05 Mem R(MA/MR): 22704 (21973/36182) [2025-04-30 06:23:23,222 INFO hook.py line 650 1619929] Train: [486/512][200/242] Data 0.015 (0.017) Batch 1.411 (1.465) Remain 02:34:40 loss: 4.2477 Lr: 2.07992e-05 Mem R(MA/MR): 24848 (21973/36182) [2025-04-30 06:24:22,223 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2211 loss_mask: 0.0295 loss_dice: 1.6978 loss_score: 0.0000 loss_bbox: 0.0456 loss_sp_cls: 0.6685 loss: 4.3024 [2025-04-30 06:24:26,378 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:26:00,082 INFO hook.py line 650 1619929] Train: [487/512][50/242] Data 0.017 (0.018) Batch 1.402 (1.431) Remain 02:28:51 loss: 4.3245 Lr: 2.05294e-05 Mem R(MA/MR): 23428 (21973/36182) [2025-04-30 06:27:11,451 INFO hook.py line 650 1619929] Train: [487/512][100/242] Data 0.017 (0.017) Batch 1.352 (1.429) Remain 02:27:28 loss: 3.4179 Lr: 2.03825e-05 Mem R(MA/MR): 25200 (21973/36182) [2025-04-30 06:28:23,147 INFO hook.py line 650 1619929] Train: [487/512][150/242] Data 0.017 (0.017) Batch 1.455 (1.431) Remain 02:26:27 loss: 3.9870 Lr: 2.02356e-05 Mem R(MA/MR): 27076 (21973/36182) [2025-04-30 06:29:36,320 INFO hook.py line 650 1619929] Train: [487/512][200/242] Data 0.016 (0.017) Batch 1.336 (1.439) Remain 02:26:06 loss: 3.7483 Lr: 2.00885e-05 Mem R(MA/MR): 27080 (21973/36182) [2025-04-30 06:30:32,164 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2204 loss_mask: 0.0292 loss_dice: 1.6850 loss_score: 0.0000 loss_bbox: 0.0452 loss_sp_cls: 0.6697 loss: 4.2773 [2025-04-30 06:30:34,815 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:32:08,909 INFO hook.py line 650 1619929] Train: [488/512][50/242] Data 0.017 (0.017) Batch 1.483 (1.443) Remain 02:24:17 loss: 4.0503 Lr: 1.98176e-05 Mem R(MA/MR): 27290 (21973/36182) [2025-04-30 06:33:24,428 INFO hook.py line 650 1619929] Train: [488/512][100/242] Data 0.017 (0.017) Batch 1.453 (1.478) Remain 02:26:32 loss: 4.5730 Lr: 1.96702e-05 Mem R(MA/MR): 29256 (21973/36182) [2025-04-30 06:34:36,902 INFO hook.py line 650 1619929] Train: [488/512][150/242] Data 0.016 (0.017) Batch 1.382 (1.468) Remain 02:24:21 loss: 4.0774 Lr: 1.95226e-05 Mem R(MA/MR): 29256 (21973/36182) [2025-04-30 06:35:47,546 INFO hook.py line 650 1619929] Train: [488/512][200/242] Data 0.015 (0.016) Batch 1.465 (1.454) Remain 02:21:46 loss: 4.2397 Lr: 1.93750e-05 Mem R(MA/MR): 29276 (21973/36182) [2025-04-30 06:36:45,649 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2172 loss_mask: 0.0296 loss_dice: 1.6822 loss_score: 0.0000 loss_bbox: 0.0449 loss_sp_cls: 0.6624 loss: 4.2549 [2025-04-30 06:36:49,576 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 06:36:52,141 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0237 Process Time: 0.539 Mem R(MA/MR): 3690 (21973/36182) [2025-04-30 06:36:53,991 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.4743 Process Time: 0.714 Mem R(MA/MR): 6504 (21973/36182) [2025-04-30 06:36:55,590 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.6424 Process Time: 0.670 Mem R(MA/MR): 8948 (21973/36182) [2025-04-30 06:37:03,689 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.7215 Process Time: 1.360 Mem R(MA/MR): 19242 (21973/36182) [2025-04-30 06:37:04,732 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6681 Process Time: 0.384 Mem R(MA/MR): 6332 (21973/36182) [2025-04-30 06:37:06,098 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0786 Process Time: 0.370 Mem R(MA/MR): 10622 (21973/36182) [2025-04-30 06:37:07,115 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0814 Process Time: 0.415 Mem R(MA/MR): 5652 (21973/36182) [2025-04-30 06:37:07,667 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4249 Process Time: 0.169 Mem R(MA/MR): 3704 (21973/36182) [2025-04-30 06:37:08,646 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.2409 Process Time: 0.319 Mem R(MA/MR): 10920 (21973/36182) [2025-04-30 06:37:10,203 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8410 Process Time: 0.319 Mem R(MA/MR): 8806 (21973/36182) [2025-04-30 06:37:13,006 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.6432 Process Time: 0.729 Mem R(MA/MR): 18510 (21973/36182) [2025-04-30 06:37:15,864 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.8915 Process Time: 0.838 Mem R(MA/MR): 14798 (21973/36182) [2025-04-30 06:37:17,021 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.3973 Process Time: 0.363 Mem R(MA/MR): 7998 (21973/36182) [2025-04-30 06:37:17,617 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1721 Process Time: 0.240 Mem R(MA/MR): 4032 (21973/36182) [2025-04-30 06:37:20,918 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.6399 Process Time: 0.369 Mem R(MA/MR): 15860 (21973/36182) [2025-04-30 06:37:22,571 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.2643 Process Time: 0.306 Mem R(MA/MR): 13964 (21973/36182) [2025-04-30 06:37:23,388 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3372 Process Time: 0.234 Mem R(MA/MR): 6158 (21973/36182) [2025-04-30 06:37:24,498 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9772 Process Time: 0.412 Mem R(MA/MR): 7454 (21973/36182) [2025-04-30 06:37:26,077 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9044 Process Time: 0.356 Mem R(MA/MR): 5192 (21973/36182) [2025-04-30 06:37:28,059 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.2441 Process Time: 0.468 Mem R(MA/MR): 10832 (21973/36182) [2025-04-30 06:37:37,406 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.2527 Process Time: 0.853 Mem R(MA/MR): 23778 (21973/36182) [2025-04-30 06:37:37,926 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.6427 Process Time: 0.177 Mem R(MA/MR): 6148 (21973/36182) [2025-04-30 06:37:47,612 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.2379 Process Time: 0.311 Mem R(MA/MR): 9516 (21973/36182) [2025-04-30 06:37:48,324 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8238 Process Time: 0.287 Mem R(MA/MR): 4628 (21973/36182) [2025-04-30 06:37:49,336 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1598 Process Time: 0.273 Mem R(MA/MR): 8440 (21973/36182) [2025-04-30 06:37:56,100 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.3861 Process Time: 1.493 Mem R(MA/MR): 30780 (21973/36182) [2025-04-30 06:37:58,351 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4574 Process Time: 0.237 Mem R(MA/MR): 9362 (21973/36182) [2025-04-30 06:37:59,607 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.2650 Process Time: 0.356 Mem R(MA/MR): 8150 (21973/36182) [2025-04-30 06:38:04,766 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.2603 Process Time: 0.402 Mem R(MA/MR): 16530 (21973/36182) [2025-04-30 06:38:06,022 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3633 Process Time: 0.353 Mem R(MA/MR): 7120 (21973/36182) [2025-04-30 06:38:10,108 INFO hook.py line 449 1619929] Test: [31/50] Loss 6.8507 Process Time: 0.500 Mem R(MA/MR): 20110 (21973/36182) [2025-04-30 06:38:10,701 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2433 Process Time: 0.297 Mem R(MA/MR): 3496 (21973/36182) [2025-04-30 06:38:15,137 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.7536 Process Time: 0.602 Mem R(MA/MR): 24462 (21973/36182) [2025-04-30 06:38:16,559 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.3525 Process Time: 0.508 Mem R(MA/MR): 8952 (21973/36182) [2025-04-30 06:38:18,807 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3493 Process Time: 0.575 Mem R(MA/MR): 13420 (21973/36182) [2025-04-30 06:38:19,650 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0777 Process Time: 0.355 Mem R(MA/MR): 5916 (21973/36182) [2025-04-30 06:38:23,306 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5812 Process Time: 0.723 Mem R(MA/MR): 28226 (21973/36182) [2025-04-30 06:38:24,922 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.7332 Process Time: 0.386 Mem R(MA/MR): 10012 (21973/36182) [2025-04-30 06:38:25,627 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3768 Process Time: 0.317 Mem R(MA/MR): 4806 (21973/36182) [2025-04-30 06:38:26,871 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.2197 Process Time: 0.333 Mem R(MA/MR): 9328 (21973/36182) [2025-04-30 06:38:27,956 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.3436 Process Time: 0.284 Mem R(MA/MR): 8192 (21973/36182) [2025-04-30 06:38:28,515 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9548 Process Time: 0.165 Mem R(MA/MR): 4810 (21973/36182) [2025-04-30 06:38:29,005 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7003 Process Time: 0.185 Mem R(MA/MR): 4820 (21973/36182) [2025-04-30 06:38:29,934 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.3299 Process Time: 0.438 Mem R(MA/MR): 6426 (21973/36182) [2025-04-30 06:38:30,562 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.6059 Process Time: 0.170 Mem R(MA/MR): 4568 (21973/36182) [2025-04-30 06:38:32,826 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.8116 Process Time: 0.361 Mem R(MA/MR): 13972 (21973/36182) [2025-04-30 06:38:41,160 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.9425 Process Time: 1.036 Mem R(MA/MR): 19776 (21973/36182) [2025-04-30 06:38:51,732 INFO hook.py line 449 1619929] Test: [48/50] Loss 13.3073 Process Time: 1.840 Mem R(MA/MR): 35002 (21973/36182) [2025-04-30 06:38:52,593 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.4425 Process Time: 0.227 Mem R(MA/MR): 5092 (21973/36182) [2025-04-30 06:38:54,670 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1795 Process Time: 0.321 Mem R(MA/MR): 13010 (21973/36182) [2025-04-30 06:38:58,389 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 06:38:58,389 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 06:38:58,389 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] table : 0.287 0.604 0.750 0.819 0.632 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] door : 0.460 0.756 0.908 0.967 0.747 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] ceiling lamp : 0.581 0.787 0.897 0.838 0.773 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] cabinet : 0.359 0.494 0.555 0.642 0.507 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] blinds : 0.557 0.727 0.811 0.655 0.826 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] curtain : 0.286 0.499 0.607 0.500 0.667 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] chair : 0.695 0.829 0.852 0.804 0.807 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] storage cabinet: 0.225 0.363 0.492 0.765 0.520 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] office chair : 0.579 0.592 0.608 0.680 0.708 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] bookshelf : 0.372 0.656 0.698 0.875 0.636 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] whiteboard : 0.583 0.771 0.822 0.962 0.714 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] window : 0.144 0.329 0.713 0.442 0.462 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] box : 0.207 0.364 0.534 0.494 0.442 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] monitor : 0.631 0.774 0.819 0.962 0.729 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] shelf : 0.171 0.322 0.404 0.818 0.300 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] heater : 0.441 0.705 0.840 0.857 0.789 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] kitchen cabinet: 0.161 0.307 0.621 0.478 0.440 [2025-04-30 06:38:58,389 INFO hook.py line 395 1619929] sofa : 0.426 0.595 0.884 0.800 0.667 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] bed : 0.275 0.522 0.798 0.714 0.625 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] trash can : 0.561 0.710 0.739 0.818 0.831 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] book : 0.020 0.045 0.076 0.211 0.101 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] plant : 0.439 0.630 0.698 1.000 0.556 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] blanket : 0.544 0.617 0.617 0.875 0.636 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] tv : 0.929 1.000 1.000 1.000 1.000 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] computer tower : 0.300 0.449 0.661 0.595 0.524 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] refrigerator : 0.242 0.404 0.404 0.667 0.444 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] jacket : 0.079 0.336 0.420 0.412 0.636 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] sink : 0.489 0.773 0.874 0.895 0.773 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] bag : 0.095 0.151 0.205 0.364 0.296 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] picture : 0.150 0.317 0.371 0.484 0.385 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] pillow : 0.575 0.740 0.741 0.765 0.684 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] towel : 0.192 0.321 0.517 0.520 0.342 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] suitcase : 0.369 0.429 0.429 1.000 0.429 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] backpack : 0.426 0.584 0.584 0.889 0.615 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] crate : 0.083 0.279 0.534 0.571 0.364 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] keyboard : 0.541 0.747 0.802 0.789 0.769 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] toilet : 0.857 0.889 1.000 1.000 0.889 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] printer : 0.413 0.492 0.497 1.000 0.444 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] painting : 0.045 0.045 0.056 0.091 1.000 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] microwave : 0.699 0.835 0.845 1.000 0.750 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] shoes : 0.142 0.307 0.564 0.929 0.317 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] socket : 0.204 0.473 0.673 0.726 0.493 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] bottle : 0.130 0.202 0.341 0.440 0.265 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] bucket : 0.000 0.004 0.010 0.050 0.143 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] cushion : 0.090 0.240 0.240 0.357 0.833 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] basket : 0.056 0.143 0.143 1.000 0.143 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] telephone : 0.318 0.536 0.562 0.818 0.529 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] laptop : 0.299 0.540 0.680 0.714 0.625 [2025-04-30 06:38:58,390 INFO hook.py line 395 1619929] plant pot : 0.155 0.341 0.462 0.600 0.562 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] exhaust fan : 0.212 0.362 0.362 0.857 0.400 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] cup : 0.233 0.375 0.415 0.882 0.341 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] coat hanger : 0.308 0.750 0.750 1.000 0.750 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] light switch : 0.270 0.565 0.653 0.846 0.508 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] speaker : 0.258 0.294 0.360 0.556 0.455 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] kettle : 0.316 0.425 0.425 0.600 0.500 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] smoke detector : 0.697 0.899 0.901 0.913 0.875 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] power strip : 0.042 0.051 0.064 0.286 0.200 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] mouse : 0.440 0.673 0.722 0.808 0.656 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] cutting board : 0.333 0.500 0.500 1.000 0.500 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] toilet paper : 0.286 0.471 0.529 1.000 0.471 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] paper towel : 0.135 0.143 0.144 1.000 0.125 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] clock : 0.519 0.667 0.667 1.000 0.667 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] tap : 0.220 0.445 0.722 0.500 0.556 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] soap dispenser : 0.487 0.755 0.755 0.800 0.800 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] bowl : 0.318 0.528 0.528 0.667 0.667 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] whiteboard eraser: 0.161 0.401 0.403 0.667 0.667 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] toilet brush : 0.544 0.755 0.930 1.000 0.667 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] headphones : 0.278 0.500 0.662 1.000 0.500 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] stapler : 0.035 0.122 0.194 0.333 0.667 [2025-04-30 06:38:58,391 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 06:38:58,391 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 06:38:58,391 INFO hook.py line 404 1619929] average : 0.287 0.430 0.501 0.639 0.492 [2025-04-30 06:38:58,391 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 06:38:58,392 INFO hook.py line 480 1619929] Total Process Time: 23.937 s [2025-04-30 06:38:58,392 INFO hook.py line 481 1619929] Average Process Time: 477.523 ms [2025-04-30 06:38:58,392 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 06:38:58,412 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 06:38:58,416 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:40:37,351 INFO hook.py line 650 1619929] Train: [489/512][50/242] Data 0.016 (0.017) Batch 1.453 (1.516) Remain 02:25:26 loss: 4.3416 Lr: 1.91029e-05 Mem R(MA/MR): 25342 (21973/36182) [2025-04-30 06:41:50,070 INFO hook.py line 650 1619929] Train: [489/512][100/242] Data 0.016 (0.017) Batch 1.367 (1.484) Remain 02:21:10 loss: 4.9114 Lr: 1.89549e-05 Mem R(MA/MR): 25352 (21973/36182) [2025-04-30 06:43:01,704 INFO hook.py line 650 1619929] Train: [489/512][150/242] Data 0.017 (0.017) Batch 1.591 (1.467) Remain 02:18:17 loss: 4.6597 Lr: 1.88068e-05 Mem R(MA/MR): 27480 (21973/36182) [2025-04-30 06:44:16,366 INFO hook.py line 650 1619929] Train: [489/512][200/242] Data 0.015 (0.020) Batch 1.284 (1.473) Remain 02:17:42 loss: 4.1047 Lr: 1.86585e-05 Mem R(MA/MR): 27480 (21973/36182) [2025-04-30 06:45:13,532 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2192 loss_mask: 0.0295 loss_dice: 1.6913 loss_score: 0.0000 loss_bbox: 0.0447 loss_sp_cls: 0.6644 loss: 4.2718 [2025-04-30 06:45:18,830 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:46:56,204 INFO hook.py line 650 1619929] Train: [490/512][50/242] Data 0.016 (0.018) Batch 1.345 (1.525) Remain 02:20:10 loss: 6.4840 Lr: 1.83853e-05 Mem R(MA/MR): 20930 (21973/36182) [2025-04-30 06:48:09,171 INFO hook.py line 650 1619929] Train: [490/512][100/242] Data 0.016 (0.017) Batch 1.513 (1.491) Remain 02:15:49 loss: 5.9727 Lr: 1.82366e-05 Mem R(MA/MR): 22616 (21973/36182) [2025-04-30 06:49:20,968 INFO hook.py line 650 1619929] Train: [490/512][150/242] Data 0.016 (0.017) Batch 1.511 (1.472) Remain 02:12:53 loss: 4.6942 Lr: 1.80879e-05 Mem R(MA/MR): 22616 (21973/36182) [2025-04-30 06:50:33,037 INFO hook.py line 650 1619929] Train: [490/512][200/242] Data 0.017 (0.017) Batch 1.418 (1.464) Remain 02:10:58 loss: 3.5507 Lr: 1.79389e-05 Mem R(MA/MR): 26378 (21973/36182) [2025-04-30 06:51:29,635 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2180 loss_mask: 0.0295 loss_dice: 1.7033 loss_score: 0.0000 loss_bbox: 0.0452 loss_sp_cls: 0.6701 loss: 4.2908 [2025-04-30 06:51:34,646 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:53:04,262 INFO hook.py line 650 1619929] Train: [491/512][50/242] Data 0.016 (0.020) Batch 1.420 (1.485) Remain 02:10:29 loss: 3.3159 Lr: 1.76645e-05 Mem R(MA/MR): 23988 (21973/36182) [2025-04-30 06:54:22,057 INFO hook.py line 650 1619929] Train: [491/512][100/242] Data 0.021 (0.021) Batch 1.524 (1.521) Remain 02:12:27 loss: 3.7225 Lr: 1.75152e-05 Mem R(MA/MR): 23988 (21973/36182) [2025-04-30 06:55:38,436 INFO hook.py line 650 1619929] Train: [491/512][150/242] Data 0.020 (0.021) Batch 1.418 (1.523) Remain 02:11:22 loss: 4.4049 Lr: 1.73658e-05 Mem R(MA/MR): 23988 (21973/36182) [2025-04-30 06:56:51,797 INFO hook.py line 650 1619929] Train: [491/512][200/242] Data 0.015 (0.020) Batch 1.444 (1.509) Remain 02:08:53 loss: 4.1701 Lr: 1.72162e-05 Mem R(MA/MR): 23988 (21973/36182) [2025-04-30 06:57:49,309 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2172 loss_mask: 0.0294 loss_dice: 1.6906 loss_score: 0.0000 loss_bbox: 0.0444 loss_sp_cls: 0.6619 loss: 4.2623 [2025-04-30 06:57:53,145 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 06:59:28,675 INFO hook.py line 650 1619929] Train: [492/512][50/242] Data 0.018 (0.019) Batch 1.355 (1.511) Remain 02:06:45 loss: 3.8631 Lr: 1.69405e-05 Mem R(MA/MR): 20362 (21973/36182) [2025-04-30 07:00:46,191 INFO hook.py line 650 1619929] Train: [492/512][100/242] Data 0.018 (0.019) Batch 1.535 (1.531) Remain 02:07:09 loss: 4.1510 Lr: 1.67905e-05 Mem R(MA/MR): 24886 (21973/36182) [2025-04-30 07:02:04,067 INFO hook.py line 650 1619929] Train: [492/512][150/242] Data 0.019 (0.019) Batch 1.436 (1.540) Remain 02:06:36 loss: 4.4417 Lr: 1.66403e-05 Mem R(MA/MR): 24886 (21973/36182) [2025-04-30 07:03:21,094 INFO hook.py line 650 1619929] Train: [492/512][200/242] Data 0.014 (0.019) Batch 1.465 (1.540) Remain 02:05:20 loss: 3.7563 Lr: 1.64900e-05 Mem R(MA/MR): 24886 (21973/36182) [2025-04-30 07:04:20,038 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2169 loss_mask: 0.0294 loss_dice: 1.6871 loss_score: 0.0000 loss_bbox: 0.0451 loss_sp_cls: 0.6643 loss: 4.2636 [2025-04-30 07:04:24,091 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:06:01,591 INFO hook.py line 650 1619929] Train: [493/512][50/242] Data 0.016 (0.017) Batch 1.583 (1.485) Remain 01:58:31 loss: 4.2215 Lr: 1.62130e-05 Mem R(MA/MR): 20264 (21973/36182) [2025-04-30 07:07:14,117 INFO hook.py line 650 1619929] Train: [493/512][100/242] Data 0.017 (0.017) Batch 1.406 (1.467) Remain 01:55:53 loss: 4.0790 Lr: 1.60623e-05 Mem R(MA/MR): 20268 (21973/36182) [2025-04-30 07:08:26,234 INFO hook.py line 650 1619929] Train: [493/512][150/242] Data 0.018 (0.017) Batch 1.454 (1.459) Remain 01:54:01 loss: 3.8385 Lr: 1.59113e-05 Mem R(MA/MR): 20268 (21973/36182) [2025-04-30 07:09:38,467 INFO hook.py line 650 1619929] Train: [493/512][200/242] Data 0.015 (0.017) Batch 1.303 (1.455) Remain 01:52:31 loss: 4.2163 Lr: 1.57603e-05 Mem R(MA/MR): 23074 (21973/36182) [2025-04-30 07:10:37,176 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2178 loss_mask: 0.0294 loss_dice: 1.6886 loss_score: 0.0000 loss_bbox: 0.0452 loss_sp_cls: 0.6670 loss: 4.2676 [2025-04-30 07:10:41,427 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:12:17,982 INFO hook.py line 650 1619929] Train: [494/512][50/242] Data 0.015 (0.017) Batch 1.361 (1.476) Remain 01:51:53 loss: 4.2449 Lr: 1.54819e-05 Mem R(MA/MR): 21080 (21973/36182) [2025-04-30 07:13:29,157 INFO hook.py line 650 1619929] Train: [494/512][100/242] Data 0.015 (0.017) Batch 1.403 (1.449) Remain 01:48:37 loss: 3.5650 Lr: 1.53303e-05 Mem R(MA/MR): 24388 (21973/36182) [2025-04-30 07:14:41,914 INFO hook.py line 650 1619929] Train: [494/512][150/242] Data 0.017 (0.017) Batch 1.543 (1.451) Remain 01:47:34 loss: 4.3201 Lr: 1.51817e-05 Mem R(MA/MR): 24408 (21973/36182) [2025-04-30 07:15:53,411 INFO hook.py line 650 1619929] Train: [494/512][200/242] Data 0.014 (0.016) Batch 1.443 (1.446) Remain 01:45:58 loss: 4.0592 Lr: 1.50298e-05 Mem R(MA/MR): 24408 (21973/36182) [2025-04-30 07:16:50,627 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2147 loss_mask: 0.0293 loss_dice: 1.6744 loss_score: 0.0000 loss_bbox: 0.0443 loss_sp_cls: 0.6574 loss: 4.2274 [2025-04-30 07:16:54,801 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:18:28,688 INFO hook.py line 650 1619929] Train: [495/512][50/242] Data 0.016 (0.016) Batch 1.399 (1.463) Remain 01:44:58 loss: 3.6421 Lr: 1.47499e-05 Mem R(MA/MR): 21396 (21973/36182) [2025-04-30 07:19:39,630 INFO hook.py line 650 1619929] Train: [495/512][100/242] Data 0.015 (0.016) Batch 1.315 (1.440) Remain 01:42:08 loss: 3.4277 Lr: 1.45976e-05 Mem R(MA/MR): 21396 (21973/36182) [2025-04-30 07:20:52,052 INFO hook.py line 650 1619929] Train: [495/512][150/242] Data 0.015 (0.016) Batch 1.440 (1.443) Remain 01:41:08 loss: 4.1484 Lr: 1.44450e-05 Mem R(MA/MR): 21396 (21973/36182) [2025-04-30 07:22:04,850 INFO hook.py line 650 1619929] Train: [495/512][200/242] Data 0.015 (0.016) Batch 1.379 (1.446) Remain 01:40:10 loss: 4.0173 Lr: 1.42923e-05 Mem R(MA/MR): 21396 (21973/36182) [2025-04-30 07:23:02,734 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2151 loss_mask: 0.0295 loss_dice: 1.6940 loss_score: 0.0000 loss_bbox: 0.0444 loss_sp_cls: 0.6609 loss: 4.2621 [2025-04-30 07:23:06,229 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:24:42,628 INFO hook.py line 650 1619929] Train: [496/512][50/242] Data 0.017 (0.018) Batch 1.476 (1.533) Remain 01:43:52 loss: 4.2118 Lr: 1.40108e-05 Mem R(MA/MR): 23472 (21973/36182) [2025-04-30 07:25:57,120 INFO hook.py line 650 1619929] Train: [496/512][100/242] Data 0.017 (0.017) Batch 1.688 (1.511) Remain 01:41:05 loss: 4.2043 Lr: 1.38576e-05 Mem R(MA/MR): 25244 (21973/36182) [2025-04-30 07:27:12,909 INFO hook.py line 650 1619929] Train: [496/512][150/242] Data 0.017 (0.017) Batch 1.613 (1.513) Remain 01:39:55 loss: 5.3108 Lr: 1.37042e-05 Mem R(MA/MR): 27796 (21973/36182) [2025-04-30 07:28:25,880 INFO hook.py line 650 1619929] Train: [496/512][200/242] Data 0.014 (0.017) Batch 1.308 (1.499) Remain 01:37:47 loss: 4.2181 Lr: 1.35506e-05 Mem R(MA/MR): 27806 (21973/36182) [2025-04-30 07:29:21,819 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2169 loss_mask: 0.0296 loss_dice: 1.6828 loss_score: 0.0000 loss_bbox: 0.0448 loss_sp_cls: 0.6666 loss: 4.2563 [2025-04-30 07:29:27,301 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 07:29:29,841 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0119 Process Time: 0.532 Mem R(MA/MR): 4380 (21973/36182) [2025-04-30 07:29:31,470 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.5647 Process Time: 0.474 Mem R(MA/MR): 7246 (21973/36182) [2025-04-30 07:29:33,062 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3372 Process Time: 0.633 Mem R(MA/MR): 9778 (21973/36182) [2025-04-30 07:29:42,280 INFO hook.py line 449 1619929] Test: [4/50] Loss 4.6946 Process Time: 1.321 Mem R(MA/MR): 19948 (21973/36182) [2025-04-30 07:29:43,543 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5500 Process Time: 0.583 Mem R(MA/MR): 7112 (21973/36182) [2025-04-30 07:29:45,061 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6896 Process Time: 0.450 Mem R(MA/MR): 11302 (21973/36182) [2025-04-30 07:29:45,781 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8728 Process Time: 0.297 Mem R(MA/MR): 6388 (21973/36182) [2025-04-30 07:29:46,208 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.0957 Process Time: 0.122 Mem R(MA/MR): 4436 (21973/36182) [2025-04-30 07:29:47,014 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.9143 Process Time: 0.197 Mem R(MA/MR): 11522 (21973/36182) [2025-04-30 07:29:48,702 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.6911 Process Time: 0.402 Mem R(MA/MR): 9526 (21973/36182) [2025-04-30 07:29:51,103 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.7305 Process Time: 0.428 Mem R(MA/MR): 18970 (21973/36182) [2025-04-30 07:29:54,057 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1737 Process Time: 0.737 Mem R(MA/MR): 15590 (21973/36182) [2025-04-30 07:29:55,193 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7073 Process Time: 0.401 Mem R(MA/MR): 8706 (21973/36182) [2025-04-30 07:29:55,545 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1872 Process Time: 0.156 Mem R(MA/MR): 4702 (21973/36182) [2025-04-30 07:29:58,461 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.1723 Process Time: 0.387 Mem R(MA/MR): 16700 (21973/36182) [2025-04-30 07:30:00,603 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3084 Process Time: 0.603 Mem R(MA/MR): 14630 (21973/36182) [2025-04-30 07:30:01,950 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.7426 Process Time: 0.586 Mem R(MA/MR): 6718 (21973/36182) [2025-04-30 07:30:02,844 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1202 Process Time: 0.282 Mem R(MA/MR): 8112 (21973/36182) [2025-04-30 07:30:04,190 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9250 Process Time: 0.153 Mem R(MA/MR): 5964 (21973/36182) [2025-04-30 07:30:06,053 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.7889 Process Time: 0.387 Mem R(MA/MR): 11488 (21973/36182) [2025-04-30 07:30:15,741 INFO hook.py line 449 1619929] Test: [21/50] Loss 7.9303 Process Time: 0.760 Mem R(MA/MR): 23738 (21973/36182) [2025-04-30 07:30:16,683 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7029 Process Time: 0.424 Mem R(MA/MR): 6868 (21973/36182) [2025-04-30 07:30:28,495 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.2594 Process Time: 0.441 Mem R(MA/MR): 10224 (21973/36182) [2025-04-30 07:30:29,089 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9680 Process Time: 0.232 Mem R(MA/MR): 5392 (21973/36182) [2025-04-30 07:30:30,103 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9179 Process Time: 0.255 Mem R(MA/MR): 9240 (21973/36182) [2025-04-30 07:30:36,324 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.2287 Process Time: 1.033 Mem R(MA/MR): 31626 (21973/36182) [2025-04-30 07:30:38,767 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.5047 Process Time: 0.508 Mem R(MA/MR): 9962 (21973/36182) [2025-04-30 07:30:40,080 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.6909 Process Time: 0.312 Mem R(MA/MR): 8866 (21973/36182) [2025-04-30 07:30:45,325 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.1897 Process Time: 0.397 Mem R(MA/MR): 17094 (21973/36182) [2025-04-30 07:30:46,414 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.8300 Process Time: 0.349 Mem R(MA/MR): 7670 (21973/36182) [2025-04-30 07:30:50,180 INFO hook.py line 449 1619929] Test: [31/50] Loss 6.5800 Process Time: 0.406 Mem R(MA/MR): 20806 (21973/36182) [2025-04-30 07:30:50,473 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2423 Process Time: 0.137 Mem R(MA/MR): 4074 (21973/36182) [2025-04-30 07:30:54,319 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.9509 Process Time: 0.462 Mem R(MA/MR): 24856 (21973/36182) [2025-04-30 07:30:55,812 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5191 Process Time: 0.591 Mem R(MA/MR): 9794 (21973/36182) [2025-04-30 07:30:57,629 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0390 Process Time: 0.358 Mem R(MA/MR): 13994 (21973/36182) [2025-04-30 07:30:58,181 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0949 Process Time: 0.188 Mem R(MA/MR): 6616 (21973/36182) [2025-04-30 07:31:01,523 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.0940 Process Time: 0.436 Mem R(MA/MR): 28548 (21973/36182) [2025-04-30 07:31:03,881 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.7247 Process Time: 0.794 Mem R(MA/MR): 10790 (21973/36182) [2025-04-30 07:31:04,358 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1625 Process Time: 0.184 Mem R(MA/MR): 5566 (21973/36182) [2025-04-30 07:31:05,467 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7250 Process Time: 0.338 Mem R(MA/MR): 10136 (21973/36182) [2025-04-30 07:31:06,356 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5408 Process Time: 0.201 Mem R(MA/MR): 9062 (21973/36182) [2025-04-30 07:31:06,829 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3444 Process Time: 0.136 Mem R(MA/MR): 5538 (21973/36182) [2025-04-30 07:31:07,232 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.4995 Process Time: 0.152 Mem R(MA/MR): 5570 (21973/36182) [2025-04-30 07:31:07,929 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.6572 Process Time: 0.265 Mem R(MA/MR): 7174 (21973/36182) [2025-04-30 07:31:08,512 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.4361 Process Time: 0.175 Mem R(MA/MR): 5284 (21973/36182) [2025-04-30 07:31:10,557 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.6326 Process Time: 0.394 Mem R(MA/MR): 14496 (21973/36182) [2025-04-30 07:31:19,129 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.1157 Process Time: 1.038 Mem R(MA/MR): 20406 (21973/36182) [2025-04-30 07:31:30,069 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.6636 Process Time: 2.268 Mem R(MA/MR): 35808 (21973/36182) [2025-04-30 07:31:31,024 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.9998 Process Time: 0.329 Mem R(MA/MR): 5768 (21973/36182) [2025-04-30 07:31:33,417 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1760 Process Time: 0.444 Mem R(MA/MR): 13628 (21973/36182) [2025-04-30 07:31:37,279 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 07:31:37,280 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 07:31:37,280 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] table : 0.290 0.607 0.739 0.818 0.596 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] door : 0.504 0.802 0.928 0.923 0.759 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] ceiling lamp : 0.579 0.751 0.853 0.845 0.724 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] cabinet : 0.332 0.447 0.554 0.525 0.478 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] blinds : 0.579 0.822 0.842 0.900 0.783 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] curtain : 0.301 0.547 0.739 0.583 0.583 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] chair : 0.667 0.807 0.838 0.840 0.754 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] storage cabinet: 0.241 0.316 0.465 0.526 0.400 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] office chair : 0.577 0.608 0.608 0.723 0.708 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] bookshelf : 0.336 0.617 0.701 0.643 0.818 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] whiteboard : 0.598 0.766 0.766 0.867 0.743 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] window : 0.148 0.370 0.667 0.577 0.495 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] box : 0.216 0.373 0.540 0.638 0.370 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] monitor : 0.649 0.793 0.831 0.964 0.757 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] shelf : 0.165 0.337 0.456 0.625 0.333 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] heater : 0.449 0.763 0.801 0.906 0.763 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] kitchen cabinet: 0.131 0.343 0.642 0.611 0.440 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] sofa : 0.514 0.640 0.805 0.875 0.583 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] bed : 0.330 0.625 0.808 1.000 0.625 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] trash can : 0.557 0.710 0.746 0.846 0.846 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] book : 0.025 0.046 0.075 0.263 0.094 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] plant : 0.424 0.637 0.752 1.000 0.556 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] blanket : 0.433 0.509 0.544 0.875 0.636 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] computer tower : 0.302 0.454 0.696 0.850 0.405 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] refrigerator : 0.242 0.473 0.475 1.000 0.444 [2025-04-30 07:31:37,280 INFO hook.py line 395 1619929] jacket : 0.052 0.104 0.321 0.333 0.273 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] sink : 0.483 0.765 0.876 0.850 0.773 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] bag : 0.099 0.170 0.235 0.381 0.296 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] picture : 0.165 0.311 0.364 0.706 0.308 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] pillow : 0.553 0.708 0.726 0.812 0.684 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] towel : 0.201 0.322 0.543 0.519 0.368 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] suitcase : 0.397 0.476 0.476 1.000 0.429 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] backpack : 0.443 0.539 0.539 0.667 0.615 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] crate : 0.069 0.207 0.507 0.455 0.455 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] keyboard : 0.556 0.742 0.802 0.857 0.769 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] toilet : 0.864 0.889 1.000 1.000 0.889 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] printer : 0.350 0.422 0.445 1.000 0.333 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.071 0.125 1.000 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] microwave : 0.656 0.875 1.000 1.000 0.875 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] shoes : 0.107 0.240 0.639 0.714 0.366 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] socket : 0.193 0.461 0.687 0.636 0.550 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] bottle : 0.118 0.201 0.328 0.538 0.253 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] bucket : 0.031 0.053 0.053 0.500 0.143 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] cushion : 0.062 0.110 0.200 0.174 0.667 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] basket : 0.099 0.143 0.160 1.000 0.143 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] shoe rack : 0.014 0.125 0.500 0.500 0.500 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] telephone : 0.395 0.662 0.698 1.000 0.588 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] laptop : 0.304 0.678 0.678 0.750 0.750 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] plant pot : 0.125 0.246 0.517 0.474 0.562 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] exhaust fan : 0.156 0.298 0.298 0.714 0.333 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] cup : 0.212 0.357 0.387 0.933 0.318 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] coat hanger : 0.093 0.208 0.750 0.667 0.500 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] light switch : 0.245 0.514 0.632 0.744 0.492 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] speaker : 0.565 0.624 0.717 0.875 0.636 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] table lamp : 0.667 1.000 1.000 1.000 1.000 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] kettle : 0.259 0.333 0.333 1.000 0.333 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] smoke detector : 0.666 0.853 0.856 0.840 0.875 [2025-04-30 07:31:37,281 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] power strip : 0.046 0.096 0.122 0.375 0.300 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] paper bag : 0.069 0.071 0.071 0.143 1.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] mouse : 0.511 0.740 0.744 1.000 0.625 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] toilet paper : 0.252 0.427 0.466 1.000 0.412 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] paper towel : 0.046 0.065 0.158 0.333 0.250 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] tap : 0.151 0.255 0.556 0.750 0.333 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] soap dispenser : 0.581 0.800 0.800 1.000 0.800 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] bowl : 0.066 0.083 0.083 0.500 0.333 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] tissue box : 0.069 0.125 0.500 0.500 0.500 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] whiteboard eraser: 0.183 0.422 0.422 0.556 0.833 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] toilet brush : 0.407 0.709 0.930 1.000 0.667 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] spray bottle : 0.007 0.009 0.009 0.071 0.250 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] headphones : 0.532 1.000 1.000 1.000 1.000 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] stapler : 0.001 0.013 0.019 0.077 0.333 [2025-04-30 07:31:37,282 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:31:37,282 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 07:31:37,282 INFO hook.py line 404 1619929] average : 0.289 0.425 0.516 0.647 0.508 [2025-04-30 07:31:37,282 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 07:31:37,282 INFO hook.py line 480 1619929] Total Process Time: 23.137 s [2025-04-30 07:31:37,283 INFO hook.py line 481 1619929] Average Process Time: 461.320 ms [2025-04-30 07:31:37,283 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 07:31:37,304 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 07:31:37,305 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:33:12,221 INFO hook.py line 650 1619929] Train: [497/512][50/242] Data 0.017 (0.017) Batch 1.443 (1.480) Remain 01:34:17 loss: 4.5549 Lr: 1.32674e-05 Mem R(MA/MR): 22522 (21973/36182) [2025-04-30 07:34:26,339 INFO hook.py line 650 1619929] Train: [497/512][100/242] Data 0.016 (0.017) Batch 1.561 (1.481) Remain 01:33:07 loss: 4.2607 Lr: 1.31132e-05 Mem R(MA/MR): 24414 (21973/36182) [2025-04-30 07:35:39,403 INFO hook.py line 650 1619929] Train: [497/512][150/242] Data 0.017 (0.023) Batch 1.437 (1.475) Remain 01:31:28 loss: 4.6460 Lr: 1.29589e-05 Mem R(MA/MR): 24414 (21973/36182) [2025-04-30 07:36:51,097 INFO hook.py line 650 1619929] Train: [497/512][200/242] Data 0.015 (0.021) Batch 1.449 (1.464) Remain 01:29:36 loss: 4.4885 Lr: 1.28043e-05 Mem R(MA/MR): 24414 (21973/36182) [2025-04-30 07:37:47,813 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2178 loss_mask: 0.0297 loss_dice: 1.6960 loss_score: 0.0000 loss_bbox: 0.0450 loss_sp_cls: 0.6657 loss: 4.2802 [2025-04-30 07:37:51,438 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 07:37:53,733 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1951 Process Time: 0.251 Mem R(MA/MR): 4948 (21973/36182) [2025-04-30 07:37:55,386 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6057 Process Time: 0.523 Mem R(MA/MR): 7560 (21973/36182) [2025-04-30 07:37:57,138 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1357 Process Time: 0.595 Mem R(MA/MR): 10230 (21973/36182) [2025-04-30 07:38:05,695 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3694 Process Time: 1.401 Mem R(MA/MR): 20072 (21973/36182) [2025-04-30 07:38:06,881 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4866 Process Time: 0.421 Mem R(MA/MR): 7180 (21973/36182) [2025-04-30 07:38:08,268 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0423 Process Time: 0.445 Mem R(MA/MR): 11876 (21973/36182) [2025-04-30 07:38:09,105 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.8743 Process Time: 0.323 Mem R(MA/MR): 6766 (21973/36182) [2025-04-30 07:38:09,553 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5439 Process Time: 0.133 Mem R(MA/MR): 4982 (21973/36182) [2025-04-30 07:38:10,452 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.4732 Process Time: 0.274 Mem R(MA/MR): 11962 (21973/36182) [2025-04-30 07:38:12,125 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.3819 Process Time: 0.375 Mem R(MA/MR): 9980 (21973/36182) [2025-04-30 07:38:14,559 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.3545 Process Time: 0.528 Mem R(MA/MR): 19028 (21973/36182) [2025-04-30 07:38:17,020 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.5419 Process Time: 0.481 Mem R(MA/MR): 15710 (21973/36182) [2025-04-30 07:38:18,151 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1693 Process Time: 0.289 Mem R(MA/MR): 9286 (21973/36182) [2025-04-30 07:38:18,482 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1474 Process Time: 0.136 Mem R(MA/MR): 5208 (21973/36182) [2025-04-30 07:38:21,439 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.7201 Process Time: 0.334 Mem R(MA/MR): 16970 (21973/36182) [2025-04-30 07:38:23,371 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3846 Process Time: 0.602 Mem R(MA/MR): 14868 (21973/36182) [2025-04-30 07:38:24,411 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.6637 Process Time: 0.366 Mem R(MA/MR): 7090 (21973/36182) [2025-04-30 07:38:25,270 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.6184 Process Time: 0.250 Mem R(MA/MR): 8654 (21973/36182) [2025-04-30 07:38:26,705 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2061 Process Time: 0.202 Mem R(MA/MR): 6384 (21973/36182) [2025-04-30 07:38:28,446 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.5987 Process Time: 0.300 Mem R(MA/MR): 12056 (21973/36182) [2025-04-30 07:38:38,061 INFO hook.py line 449 1619929] Test: [21/50] Loss 10.0108 Process Time: 0.838 Mem R(MA/MR): 24360 (21973/36182) [2025-04-30 07:38:38,909 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7490 Process Time: 0.261 Mem R(MA/MR): 7152 (21973/36182) [2025-04-30 07:38:49,908 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.3856 Process Time: 0.372 Mem R(MA/MR): 10542 (21973/36182) [2025-04-30 07:38:50,713 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7883 Process Time: 0.292 Mem R(MA/MR): 5980 (21973/36182) [2025-04-30 07:38:52,016 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1190 Process Time: 0.440 Mem R(MA/MR): 9674 (21973/36182) [2025-04-30 07:39:00,120 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.7355 Process Time: 1.567 Mem R(MA/MR): 31908 (21973/36182) [2025-04-30 07:39:03,040 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.3704 Process Time: 0.457 Mem R(MA/MR): 10600 (21973/36182) [2025-04-30 07:39:04,446 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9496 Process Time: 0.386 Mem R(MA/MR): 9380 (21973/36182) [2025-04-30 07:39:10,092 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.4883 Process Time: 0.534 Mem R(MA/MR): 17336 (21973/36182) [2025-04-30 07:39:11,068 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1544 Process Time: 0.288 Mem R(MA/MR): 7910 (21973/36182) [2025-04-30 07:39:14,766 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.9410 Process Time: 0.663 Mem R(MA/MR): 20984 (21973/36182) [2025-04-30 07:39:15,076 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2278 Process Time: 0.128 Mem R(MA/MR): 4340 (21973/36182) [2025-04-30 07:39:19,216 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3762 Process Time: 0.581 Mem R(MA/MR): 25310 (21973/36182) [2025-04-30 07:39:20,577 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5753 Process Time: 0.565 Mem R(MA/MR): 10138 (21973/36182) [2025-04-30 07:39:22,598 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7155 Process Time: 0.447 Mem R(MA/MR): 14560 (21973/36182) [2025-04-30 07:39:23,080 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1253 Process Time: 0.167 Mem R(MA/MR): 6946 (21973/36182) [2025-04-30 07:39:26,915 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8536 Process Time: 0.885 Mem R(MA/MR): 28754 (21973/36182) [2025-04-30 07:39:28,709 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.9630 Process Time: 0.531 Mem R(MA/MR): 10994 (21973/36182) [2025-04-30 07:39:29,215 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3225 Process Time: 0.191 Mem R(MA/MR): 6096 (21973/36182) [2025-04-30 07:39:30,246 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.4598 Process Time: 0.238 Mem R(MA/MR): 10414 (21973/36182) [2025-04-30 07:39:31,341 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.4589 Process Time: 0.285 Mem R(MA/MR): 9376 (21973/36182) [2025-04-30 07:39:31,874 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.6689 Process Time: 0.172 Mem R(MA/MR): 6122 (21973/36182) [2025-04-30 07:39:32,347 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7135 Process Time: 0.185 Mem R(MA/MR): 6170 (21973/36182) [2025-04-30 07:39:32,963 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.4634 Process Time: 0.181 Mem R(MA/MR): 7464 (21973/36182) [2025-04-30 07:39:33,503 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3916 Process Time: 0.145 Mem R(MA/MR): 5556 (21973/36182) [2025-04-30 07:39:35,850 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.8014 Process Time: 0.449 Mem R(MA/MR): 15022 (21973/36182) [2025-04-30 07:39:43,361 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.6888 Process Time: 0.874 Mem R(MA/MR): 20236 (21973/36182) [2025-04-30 07:39:53,070 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.7632 Process Time: 1.429 Mem R(MA/MR): 34750 (21973/36182) [2025-04-30 07:39:53,637 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0985 Process Time: 0.165 Mem R(MA/MR): 6510 (21973/36182) [2025-04-30 07:39:56,296 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.3604 Process Time: 0.617 Mem R(MA/MR): 14054 (21973/36182) [2025-04-30 07:40:01,020 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 07:40:01,020 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 07:40:01,020 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] table : 0.292 0.622 0.732 0.851 0.632 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] door : 0.470 0.755 0.895 0.877 0.722 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] ceiling lamp : 0.592 0.775 0.861 0.903 0.718 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] cabinet : 0.345 0.500 0.543 0.471 0.597 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] blinds : 0.626 0.835 0.857 0.905 0.826 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] curtain : 0.465 0.636 0.789 0.526 0.833 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] chair : 0.618 0.758 0.795 0.786 0.709 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] storage cabinet: 0.192 0.284 0.448 0.647 0.440 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] office chair : 0.571 0.588 0.621 0.714 0.729 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] bookshelf : 0.356 0.681 0.681 0.875 0.636 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] whiteboard : 0.558 0.725 0.766 0.893 0.714 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] window : 0.165 0.348 0.660 0.544 0.407 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] box : 0.224 0.378 0.555 0.506 0.453 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] monitor : 0.647 0.789 0.849 0.902 0.786 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] shelf : 0.129 0.275 0.534 0.800 0.267 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] heater : 0.462 0.756 0.784 0.879 0.763 [2025-04-30 07:40:01,020 INFO hook.py line 395 1619929] kitchen cabinet: 0.149 0.350 0.710 0.625 0.400 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] sofa : 0.544 0.687 0.805 0.875 0.583 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] bed : 0.182 0.437 0.761 0.800 0.500 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] trash can : 0.558 0.708 0.741 0.831 0.831 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] book : 0.019 0.043 0.081 0.295 0.086 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] plant : 0.446 0.593 0.741 1.000 0.556 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] blanket : 0.503 0.679 0.688 0.875 0.636 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] tv : 0.922 1.000 1.000 1.000 1.000 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] computer tower : 0.320 0.504 0.648 0.826 0.452 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] refrigerator : 0.257 0.471 0.479 0.800 0.444 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] jacket : 0.035 0.071 0.310 0.211 0.364 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] sink : 0.459 0.821 0.881 0.944 0.773 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] bag : 0.083 0.124 0.170 0.556 0.185 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] picture : 0.139 0.334 0.395 0.867 0.333 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] pillow : 0.483 0.635 0.665 0.733 0.579 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] towel : 0.216 0.346 0.508 0.722 0.342 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] suitcase : 0.385 0.429 0.429 1.000 0.429 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] backpack : 0.387 0.585 0.585 1.000 0.538 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] crate : 0.057 0.259 0.492 0.800 0.364 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] keyboard : 0.472 0.646 0.704 0.917 0.564 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] toilet : 0.868 0.889 1.000 1.000 0.889 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] printer : 0.188 0.211 0.260 0.375 0.333 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.002 0.036 0.111 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.071 0.125 1.000 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] microwave : 0.580 0.750 0.875 1.000 0.750 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] shoes : 0.123 0.266 0.667 0.500 0.415 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] socket : 0.199 0.479 0.679 0.661 0.514 [2025-04-30 07:40:01,021 INFO hook.py line 395 1619929] bottle : 0.128 0.213 0.344 0.512 0.265 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] bucket : 0.021 0.033 0.033 0.167 0.286 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] cushion : 0.032 0.036 0.148 0.120 0.500 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] basket : 0.032 0.036 0.064 0.500 0.143 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] telephone : 0.363 0.582 0.619 0.769 0.588 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] laptop : 0.347 0.626 0.626 1.000 0.500 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] plant pot : 0.126 0.394 0.557 0.778 0.438 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] exhaust fan : 0.189 0.314 0.319 0.600 0.400 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] cup : 0.229 0.401 0.433 0.704 0.432 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] coat hanger : 0.259 0.750 0.908 1.000 0.750 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] light switch : 0.245 0.498 0.623 0.717 0.508 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] speaker : 0.448 0.497 0.681 0.714 0.455 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] table lamp : 0.667 1.000 1.000 1.000 1.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] smoke detector : 0.660 0.829 0.829 0.952 0.833 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] power strip : 0.043 0.115 0.185 0.308 0.400 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.083 0.000 0.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] mouse : 0.499 0.752 0.753 0.852 0.719 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] toilet paper : 0.264 0.412 0.518 1.000 0.412 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] paper towel : 0.125 0.125 0.150 1.000 0.125 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] clock : 0.659 0.764 0.764 0.750 1.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] tap : 0.114 0.231 0.578 0.571 0.444 [2025-04-30 07:40:01,022 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] soap dispenser : 0.529 0.800 0.938 1.000 0.800 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] bowl : 0.194 0.333 0.333 1.000 0.333 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] tissue box : 0.069 0.125 0.500 0.500 0.500 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] whiteboard eraser: 0.161 0.391 0.394 0.667 0.667 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] toilet brush : 0.517 0.755 0.941 1.000 0.667 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] headphones : 0.532 1.000 1.000 1.000 1.000 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] stapler : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,023 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:40:01,023 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 07:40:01,023 INFO hook.py line 404 1619929] average : 0.283 0.423 0.514 0.642 0.475 [2025-04-30 07:40:01,023 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 07:40:01,023 INFO hook.py line 480 1619929] Total Process Time: 22.561 s [2025-04-30 07:40:01,023 INFO hook.py line 481 1619929] Average Process Time: 455.306 ms [2025-04-30 07:40:01,023 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 07:40:01,075 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 07:40:01,078 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:41:36,185 INFO hook.py line 650 1619929] Train: [498/512][50/242] Data 0.018 (0.017) Batch 1.737 (1.528) Remain 01:31:09 loss: 4.5199 Lr: 1.25193e-05 Mem R(MA/MR): 21038 (21973/36182) [2025-04-30 07:42:51,479 INFO hook.py line 650 1619929] Train: [498/512][100/242] Data 0.017 (0.025) Batch 1.630 (1.517) Remain 01:29:13 loss: 4.3534 Lr: 1.23641e-05 Mem R(MA/MR): 21038 (21973/36182) [2025-04-30 07:44:03,635 INFO hook.py line 650 1619929] Train: [498/512][150/242] Data 0.016 (0.022) Batch 1.358 (1.492) Remain 01:26:30 loss: 3.7965 Lr: 1.22087e-05 Mem R(MA/MR): 21042 (21973/36182) [2025-04-30 07:45:15,083 INFO hook.py line 650 1619929] Train: [498/512][200/242] Data 0.016 (0.021) Batch 1.280 (1.476) Remain 01:24:21 loss: 4.6360 Lr: 1.20531e-05 Mem R(MA/MR): 21068 (21973/36182) [2025-04-30 07:46:12,814 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2166 loss_mask: 0.0288 loss_dice: 1.6723 loss_score: 0.0000 loss_bbox: 0.0457 loss_sp_cls: 0.6656 loss: 4.2426 [2025-04-30 07:46:14,778 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 07:46:17,142 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2120 Process Time: 0.301 Mem R(MA/MR): 4960 (21973/36182) [2025-04-30 07:46:19,169 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.9226 Process Time: 0.834 Mem R(MA/MR): 7732 (21973/36182) [2025-04-30 07:46:21,182 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.4506 Process Time: 0.859 Mem R(MA/MR): 10328 (21973/36182) [2025-04-30 07:46:29,996 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3994 Process Time: 1.432 Mem R(MA/MR): 20164 (21973/36182) [2025-04-30 07:46:31,090 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5136 Process Time: 0.472 Mem R(MA/MR): 7650 (21973/36182) [2025-04-30 07:46:32,535 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6831 Process Time: 0.468 Mem R(MA/MR): 11748 (21973/36182) [2025-04-30 07:46:33,061 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1054 Process Time: 0.169 Mem R(MA/MR): 6768 (21973/36182) [2025-04-30 07:46:33,482 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5472 Process Time: 0.123 Mem R(MA/MR): 4968 (21973/36182) [2025-04-30 07:46:34,296 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8107 Process Time: 0.196 Mem R(MA/MR): 12028 (21973/36182) [2025-04-30 07:46:35,921 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4481 Process Time: 0.397 Mem R(MA/MR): 10058 (21973/36182) [2025-04-30 07:46:38,535 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.8897 Process Time: 0.582 Mem R(MA/MR): 19152 (21973/36182) [2025-04-30 07:46:41,005 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.7112 Process Time: 0.428 Mem R(MA/MR): 15842 (21973/36182) [2025-04-30 07:46:42,293 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1655 Process Time: 0.447 Mem R(MA/MR): 9290 (21973/36182) [2025-04-30 07:46:42,726 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.3450 Process Time: 0.180 Mem R(MA/MR): 5240 (21973/36182) [2025-04-30 07:46:45,764 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4363 Process Time: 0.351 Mem R(MA/MR): 16996 (21973/36182) [2025-04-30 07:46:47,880 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4317 Process Time: 0.710 Mem R(MA/MR): 14912 (21973/36182) [2025-04-30 07:46:48,560 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3040 Process Time: 0.214 Mem R(MA/MR): 7268 (21973/36182) [2025-04-30 07:46:49,615 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1134 Process Time: 0.460 Mem R(MA/MR): 8676 (21973/36182) [2025-04-30 07:46:50,832 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0350 Process Time: 0.233 Mem R(MA/MR): 6318 (21973/36182) [2025-04-30 07:46:52,462 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.9313 Process Time: 0.259 Mem R(MA/MR): 11956 (21973/36182) [2025-04-30 07:47:01,558 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.7092 Process Time: 0.971 Mem R(MA/MR): 24456 (21973/36182) [2025-04-30 07:47:02,190 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.9015 Process Time: 0.179 Mem R(MA/MR): 7294 (21973/36182) [2025-04-30 07:47:13,755 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.9945 Process Time: 0.551 Mem R(MA/MR): 10802 (21973/36182) [2025-04-30 07:47:14,429 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7841 Process Time: 0.197 Mem R(MA/MR): 5748 (21973/36182) [2025-04-30 07:47:15,453 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8988 Process Time: 0.277 Mem R(MA/MR): 9866 (21973/36182) [2025-04-30 07:47:21,686 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.4076 Process Time: 0.770 Mem R(MA/MR): 31652 (21973/36182) [2025-04-30 07:47:23,860 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.6449 Process Time: 0.363 Mem R(MA/MR): 10158 (21973/36182) [2025-04-30 07:47:25,492 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9417 Process Time: 0.597 Mem R(MA/MR): 9374 (21973/36182) [2025-04-30 07:47:30,706 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.7162 Process Time: 0.363 Mem R(MA/MR): 17394 (21973/36182) [2025-04-30 07:47:31,999 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3437 Process Time: 0.428 Mem R(MA/MR): 8216 (21973/36182) [2025-04-30 07:47:35,579 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.5830 Process Time: 0.511 Mem R(MA/MR): 21088 (21973/36182) [2025-04-30 07:47:36,181 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3379 Process Time: 0.185 Mem R(MA/MR): 4398 (21973/36182) [2025-04-30 07:47:40,306 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.1839 Process Time: 0.605 Mem R(MA/MR): 25218 (21973/36182) [2025-04-30 07:47:41,417 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5551 Process Time: 0.384 Mem R(MA/MR): 10102 (21973/36182) [2025-04-30 07:47:43,368 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7480 Process Time: 0.367 Mem R(MA/MR): 14556 (21973/36182) [2025-04-30 07:47:43,887 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.1631 Process Time: 0.175 Mem R(MA/MR): 7148 (21973/36182) [2025-04-30 07:47:47,905 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5078 Process Time: 0.876 Mem R(MA/MR): 28982 (21973/36182) [2025-04-30 07:47:49,280 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8703 Process Time: 0.276 Mem R(MA/MR): 11226 (21973/36182) [2025-04-30 07:47:50,014 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3656 Process Time: 0.341 Mem R(MA/MR): 6016 (21973/36182) [2025-04-30 07:47:51,124 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.7224 Process Time: 0.317 Mem R(MA/MR): 10526 (21973/36182) [2025-04-30 07:47:52,238 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.7516 Process Time: 0.430 Mem R(MA/MR): 9430 (21973/36182) [2025-04-30 07:47:52,757 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.5236 Process Time: 0.170 Mem R(MA/MR): 5886 (21973/36182) [2025-04-30 07:47:53,265 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8795 Process Time: 0.182 Mem R(MA/MR): 6106 (21973/36182) [2025-04-30 07:47:53,911 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.9408 Process Time: 0.222 Mem R(MA/MR): 7724 (21973/36182) [2025-04-30 07:47:54,652 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5903 Process Time: 0.216 Mem R(MA/MR): 5672 (21973/36182) [2025-04-30 07:47:56,641 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.7612 Process Time: 0.310 Mem R(MA/MR): 14960 (21973/36182) [2025-04-30 07:48:04,061 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7471 Process Time: 0.694 Mem R(MA/MR): 20702 (21973/36182) [2025-04-30 07:48:14,339 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.2093 Process Time: 1.698 Mem R(MA/MR): 35564 (21973/36182) [2025-04-30 07:48:14,943 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1717 Process Time: 0.183 Mem R(MA/MR): 6188 (21973/36182) [2025-04-30 07:48:17,010 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.1195 Process Time: 0.257 Mem R(MA/MR): 14204 (21973/36182) [2025-04-30 07:48:20,911 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 07:48:20,911 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 07:48:20,912 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] table : 0.297 0.604 0.759 0.796 0.603 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] door : 0.478 0.752 0.914 0.905 0.722 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] ceiling lamp : 0.593 0.778 0.865 0.835 0.757 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] cabinet : 0.342 0.452 0.523 0.447 0.567 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] blinds : 0.575 0.808 0.829 0.905 0.826 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] curtain : 0.392 0.690 0.770 0.692 0.750 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] chair : 0.659 0.797 0.834 0.797 0.754 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] storage cabinet: 0.202 0.331 0.448 0.542 0.520 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] office chair : 0.581 0.613 0.613 0.714 0.729 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] bookshelf : 0.187 0.323 0.529 0.500 0.636 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] whiteboard : 0.578 0.789 0.789 0.867 0.743 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] window : 0.127 0.330 0.678 0.456 0.451 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] box : 0.216 0.395 0.554 0.652 0.414 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] monitor : 0.651 0.813 0.826 0.966 0.814 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] shelf : 0.158 0.366 0.546 0.500 0.367 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] heater : 0.452 0.716 0.759 0.962 0.658 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] kitchen cabinet: 0.188 0.446 0.681 0.571 0.480 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] sofa : 0.488 0.581 0.793 0.778 0.583 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] bed : 0.232 0.538 0.837 0.833 0.625 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] trash can : 0.547 0.723 0.745 0.763 0.892 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] book : 0.025 0.051 0.085 0.225 0.094 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] plant : 0.440 0.631 0.784 1.000 0.556 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] blanket : 0.554 0.641 0.693 0.875 0.636 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] tv : 0.912 1.000 1.000 1.000 1.000 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] computer tower : 0.291 0.476 0.625 0.667 0.476 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] refrigerator : 0.184 0.414 0.414 1.000 0.333 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] jacket : 0.082 0.268 0.362 0.500 0.455 [2025-04-30 07:48:20,912 INFO hook.py line 395 1619929] sink : 0.473 0.749 0.870 0.739 0.773 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] bag : 0.057 0.091 0.176 0.209 0.333 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] picture : 0.139 0.296 0.407 0.800 0.308 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] pillow : 0.503 0.637 0.705 0.722 0.684 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] towel : 0.193 0.287 0.451 0.520 0.342 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] suitcase : 0.414 0.537 0.542 1.000 0.429 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] backpack : 0.415 0.520 0.520 0.778 0.538 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] crate : 0.074 0.243 0.545 0.800 0.364 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] keyboard : 0.528 0.681 0.761 0.920 0.590 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] toilet : 0.868 1.000 1.000 1.000 1.000 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] printer : 0.343 0.454 0.481 0.800 0.444 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] poster : 0.000 0.003 0.004 0.053 0.111 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] painting : 0.039 0.042 0.042 0.083 1.000 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] microwave : 0.585 0.667 0.875 0.833 0.625 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] shoes : 0.105 0.245 0.619 0.667 0.390 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] socket : 0.198 0.467 0.681 0.611 0.550 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] bottle : 0.089 0.199 0.356 0.460 0.277 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] bucket : 0.008 0.017 0.040 0.087 0.286 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] cushion : 0.074 0.112 0.208 0.333 0.333 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] basket : 0.011 0.024 0.052 0.333 0.143 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] telephone : 0.385 0.651 0.656 0.909 0.588 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] laptop : 0.270 0.506 0.567 0.625 0.625 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] plant pot : 0.181 0.326 0.471 0.615 0.500 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] exhaust fan : 0.202 0.355 0.362 0.750 0.400 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] cup : 0.269 0.378 0.407 0.607 0.386 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] coat hanger : 0.269 0.750 0.750 1.000 0.750 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] light switch : 0.266 0.528 0.664 0.773 0.523 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] speaker : 0.515 0.557 0.641 1.000 0.455 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] kettle : 0.242 0.264 0.264 0.667 0.333 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] smoke detector : 0.692 0.861 0.862 0.909 0.833 [2025-04-30 07:48:20,913 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] power strip : 0.041 0.067 0.106 0.333 0.300 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.042 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] mouse : 0.502 0.694 0.795 0.955 0.656 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] cutting board : 0.333 0.500 0.500 1.000 0.500 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] toilet paper : 0.255 0.412 0.494 1.000 0.412 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.166 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] tap : 0.098 0.176 0.444 0.667 0.222 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] soap dispenser : 0.588 0.800 0.800 1.000 0.800 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] bowl : 0.037 0.083 0.083 0.500 0.333 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] whiteboard eraser: 0.202 0.446 0.446 0.625 0.833 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] toilet brush : 0.468 0.715 0.930 1.000 0.667 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] headphones : 0.365 0.662 0.708 1.000 0.500 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] stapler : 0.009 0.019 0.021 0.111 0.333 [2025-04-30 07:48:20,914 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:48:20,914 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 07:48:20,914 INFO hook.py line 404 1619929] average : 0.286 0.424 0.505 0.613 0.481 [2025-04-30 07:48:20,914 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 07:48:20,915 INFO hook.py line 480 1619929] Total Process Time: 22.210 s [2025-04-30 07:48:20,915 INFO hook.py line 481 1619929] Average Process Time: 447.114 ms [2025-04-30 07:48:20,915 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 07:48:20,957 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 07:48:20,962 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:50:00,626 INFO hook.py line 650 1619929] Train: [499/512][50/242] Data 0.016 (0.036) Batch 1.352 (1.501) Remain 01:23:29 loss: 4.4034 Lr: 1.17662e-05 Mem R(MA/MR): 21774 (21973/36182) [2025-04-30 07:51:14,223 INFO hook.py line 650 1619929] Train: [499/512][100/242] Data 0.016 (0.026) Batch 1.396 (1.486) Remain 01:21:25 loss: 3.8110 Lr: 1.16099e-05 Mem R(MA/MR): 21774 (21973/36182) [2025-04-30 07:52:29,398 INFO hook.py line 650 1619929] Train: [499/512][150/242] Data 0.017 (0.023) Batch 1.540 (1.492) Remain 01:20:30 loss: 4.7552 Lr: 1.14535e-05 Mem R(MA/MR): 25396 (21973/36182) [2025-04-30 07:53:42,971 INFO hook.py line 650 1619929] Train: [499/512][200/242] Data 0.014 (0.021) Batch 1.302 (1.487) Remain 01:18:59 loss: 4.2162 Lr: 1.12967e-05 Mem R(MA/MR): 27934 (21973/36182) [2025-04-30 07:54:40,685 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2125 loss_mask: 0.0295 loss_dice: 1.6857 loss_score: 0.0000 loss_bbox: 0.0445 loss_sp_cls: 0.6687 loss: 4.2473 [2025-04-30 07:54:45,051 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 07:54:47,322 INFO hook.py line 449 1619929] Test: [1/50] Loss 2.7559 Process Time: 0.260 Mem R(MA/MR): 5020 (21973/36182) [2025-04-30 07:54:49,096 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8530 Process Time: 0.644 Mem R(MA/MR): 7818 (21973/36182) [2025-04-30 07:54:50,794 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2782 Process Time: 0.667 Mem R(MA/MR): 10408 (21973/36182) [2025-04-30 07:54:58,793 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.7311 Process Time: 1.172 Mem R(MA/MR): 20430 (21973/36182) [2025-04-30 07:55:00,030 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.2416 Process Time: 0.379 Mem R(MA/MR): 7724 (21973/36182) [2025-04-30 07:55:01,770 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8469 Process Time: 0.548 Mem R(MA/MR): 11902 (21973/36182) [2025-04-30 07:55:02,723 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.7644 Process Time: 0.416 Mem R(MA/MR): 6980 (21973/36182) [2025-04-30 07:55:03,256 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3644 Process Time: 0.137 Mem R(MA/MR): 5052 (21973/36182) [2025-04-30 07:55:04,259 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8515 Process Time: 0.285 Mem R(MA/MR): 12044 (21973/36182) [2025-04-30 07:55:05,893 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4958 Process Time: 0.264 Mem R(MA/MR): 10120 (21973/36182) [2025-04-30 07:55:08,976 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.3514 Process Time: 0.647 Mem R(MA/MR): 19438 (21973/36182) [2025-04-30 07:55:12,302 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.7455 Process Time: 1.014 Mem R(MA/MR): 15888 (21973/36182) [2025-04-30 07:55:13,594 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.3509 Process Time: 0.448 Mem R(MA/MR): 9370 (21973/36182) [2025-04-30 07:55:14,021 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2268 Process Time: 0.167 Mem R(MA/MR): 5376 (21973/36182) [2025-04-30 07:55:16,789 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.7377 Process Time: 0.316 Mem R(MA/MR): 17060 (21973/36182) [2025-04-30 07:55:18,757 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.5216 Process Time: 0.581 Mem R(MA/MR): 15092 (21973/36182) [2025-04-30 07:55:19,590 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2661 Process Time: 0.307 Mem R(MA/MR): 7330 (21973/36182) [2025-04-30 07:55:20,623 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.3859 Process Time: 0.410 Mem R(MA/MR): 8782 (21973/36182) [2025-04-30 07:55:21,943 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2990 Process Time: 0.277 Mem R(MA/MR): 6520 (21973/36182) [2025-04-30 07:55:23,429 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.7172 Process Time: 0.306 Mem R(MA/MR): 11936 (21973/36182) [2025-04-30 07:55:31,612 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.4115 Process Time: 0.562 Mem R(MA/MR): 24404 (21973/36182) [2025-04-30 07:55:32,472 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5614 Process Time: 0.341 Mem R(MA/MR): 7332 (21973/36182) [2025-04-30 07:55:44,142 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.1646 Process Time: 0.380 Mem R(MA/MR): 10876 (21973/36182) [2025-04-30 07:55:44,996 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7358 Process Time: 0.369 Mem R(MA/MR): 5984 (21973/36182) [2025-04-30 07:55:45,980 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8456 Process Time: 0.303 Mem R(MA/MR): 9778 (21973/36182) [2025-04-30 07:55:52,840 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.5663 Process Time: 1.364 Mem R(MA/MR): 32176 (21973/36182) [2025-04-30 07:55:54,770 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.3401 Process Time: 0.286 Mem R(MA/MR): 10522 (21973/36182) [2025-04-30 07:55:55,971 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.7869 Process Time: 0.300 Mem R(MA/MR): 9430 (21973/36182) [2025-04-30 07:56:01,225 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8537 Process Time: 0.598 Mem R(MA/MR): 17544 (21973/36182) [2025-04-30 07:56:02,107 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.8944 Process Time: 0.252 Mem R(MA/MR): 8252 (21973/36182) [2025-04-30 07:56:05,654 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.3439 Process Time: 0.525 Mem R(MA/MR): 21236 (21973/36182) [2025-04-30 07:56:06,123 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.4451 Process Time: 0.163 Mem R(MA/MR): 4678 (21973/36182) [2025-04-30 07:56:10,298 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3132 Process Time: 0.634 Mem R(MA/MR): 25560 (21973/36182) [2025-04-30 07:56:11,451 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4216 Process Time: 0.382 Mem R(MA/MR): 10378 (21973/36182) [2025-04-30 07:56:13,771 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.6277 Process Time: 0.513 Mem R(MA/MR): 14650 (21973/36182) [2025-04-30 07:56:14,708 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8591 Process Time: 0.289 Mem R(MA/MR): 7228 (21973/36182) [2025-04-30 07:56:18,680 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9916 Process Time: 0.688 Mem R(MA/MR): 28778 (21973/36182) [2025-04-30 07:56:20,205 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.0453 Process Time: 0.378 Mem R(MA/MR): 11298 (21973/36182) [2025-04-30 07:56:20,956 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1586 Process Time: 0.364 Mem R(MA/MR): 6152 (21973/36182) [2025-04-30 07:56:21,962 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.4983 Process Time: 0.268 Mem R(MA/MR): 10748 (21973/36182) [2025-04-30 07:56:23,100 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5338 Process Time: 0.391 Mem R(MA/MR): 9606 (21973/36182) [2025-04-30 07:56:23,672 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2914 Process Time: 0.214 Mem R(MA/MR): 6122 (21973/36182) [2025-04-30 07:56:24,130 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5245 Process Time: 0.162 Mem R(MA/MR): 6200 (21973/36182) [2025-04-30 07:56:24,738 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.9870 Process Time: 0.218 Mem R(MA/MR): 7804 (21973/36182) [2025-04-30 07:56:25,559 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.4142 Process Time: 0.316 Mem R(MA/MR): 5926 (21973/36182) [2025-04-30 07:56:27,488 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.1044 Process Time: 0.341 Mem R(MA/MR): 15066 (21973/36182) [2025-04-30 07:56:34,022 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.2943 Process Time: 0.454 Mem R(MA/MR): 20882 (21973/36182) [2025-04-30 07:56:44,043 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.3917 Process Time: 1.858 Mem R(MA/MR): 35956 (21973/36182) [2025-04-30 07:56:45,246 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1675 Process Time: 0.553 Mem R(MA/MR): 6392 (21973/36182) [2025-04-30 07:56:48,100 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0879 Process Time: 0.621 Mem R(MA/MR): 14342 (21973/36182) [2025-04-30 07:56:52,461 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 07:56:52,461 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 07:56:52,461 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] table : 0.297 0.636 0.763 0.828 0.603 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] door : 0.438 0.745 0.900 0.866 0.734 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] ceiling lamp : 0.564 0.746 0.831 0.821 0.735 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] cabinet : 0.344 0.470 0.554 0.593 0.478 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] blinds : 0.542 0.732 0.781 0.895 0.739 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] curtain : 0.331 0.599 0.725 0.500 0.833 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] chair : 0.676 0.813 0.861 0.823 0.742 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] storage cabinet: 0.241 0.361 0.479 0.483 0.560 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] office chair : 0.529 0.565 0.566 0.694 0.708 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] bookshelf : 0.282 0.566 0.716 0.778 0.636 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] whiteboard : 0.560 0.748 0.748 0.926 0.714 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] window : 0.120 0.282 0.610 0.515 0.385 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] box : 0.223 0.402 0.556 0.540 0.448 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] monitor : 0.636 0.810 0.824 0.982 0.786 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] shelf : 0.167 0.325 0.511 0.643 0.300 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] heater : 0.444 0.733 0.772 0.931 0.711 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] kitchen cabinet: 0.109 0.270 0.597 0.389 0.560 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] sofa : 0.560 0.642 0.903 0.643 0.750 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] bed : 0.248 0.553 0.926 1.000 0.500 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] trash can : 0.587 0.760 0.772 0.846 0.846 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] book : 0.026 0.050 0.094 0.231 0.094 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] plant : 0.435 0.696 0.811 1.000 0.667 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] blanket : 0.441 0.542 0.618 0.875 0.636 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] tv : 0.916 1.000 1.000 1.000 1.000 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] computer tower : 0.299 0.445 0.645 0.750 0.429 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] refrigerator : 0.234 0.436 0.436 1.000 0.333 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] jacket : 0.100 0.323 0.515 0.571 0.364 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] sink : 0.435 0.746 0.853 0.810 0.773 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] bag : 0.064 0.092 0.129 0.316 0.222 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] picture : 0.127 0.304 0.416 0.765 0.333 [2025-04-30 07:56:52,462 INFO hook.py line 395 1619929] pillow : 0.439 0.619 0.631 0.632 0.632 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] towel : 0.185 0.299 0.499 0.632 0.316 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] suitcase : 0.395 0.519 0.519 0.667 0.571 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] backpack : 0.383 0.538 0.538 1.000 0.538 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] crate : 0.067 0.245 0.500 0.412 0.636 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] keyboard : 0.473 0.639 0.721 0.735 0.641 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] toilet : 0.866 1.000 1.000 1.000 1.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] printer : 0.369 0.402 0.425 1.000 0.333 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] painting : 0.042 0.045 0.045 0.091 1.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] microwave : 0.629 0.826 0.957 0.778 0.875 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] shoes : 0.105 0.232 0.580 0.722 0.317 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] socket : 0.191 0.451 0.666 0.654 0.500 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] bottle : 0.144 0.219 0.368 0.453 0.289 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] bucket : 0.029 0.049 0.049 0.500 0.143 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] cushion : 0.061 0.149 0.234 0.267 0.667 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] basket : 0.056 0.143 0.165 1.000 0.143 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] telephone : 0.368 0.602 0.603 0.833 0.588 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] laptop : 0.411 0.778 0.778 0.857 0.750 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] plant pot : 0.208 0.371 0.446 0.667 0.500 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] exhaust fan : 0.175 0.319 0.319 0.667 0.400 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] cup : 0.261 0.360 0.469 0.727 0.364 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] coat hanger : 0.259 0.750 0.884 1.000 0.750 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] light switch : 0.231 0.489 0.645 0.727 0.492 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] speaker : 0.589 0.643 0.770 1.000 0.545 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] kettle : 0.210 0.264 0.264 0.667 0.333 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] smoke detector : 0.621 0.780 0.783 1.000 0.708 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] power strip : 0.047 0.079 0.140 0.375 0.300 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,463 INFO hook.py line 395 1619929] mouse : 0.585 0.793 0.828 0.960 0.750 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] toilet paper : 0.264 0.412 0.412 1.000 0.412 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] paper towel : 0.115 0.250 0.250 1.000 0.250 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] tap : 0.141 0.299 0.637 0.500 0.444 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] soap dispenser : 0.531 0.800 1.000 1.000 0.800 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] bowl : 0.068 0.083 0.083 0.500 0.333 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] tissue box : 0.065 0.083 0.125 0.333 0.500 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] whiteboard eraser: 0.213 0.498 0.536 0.750 0.500 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] toilet brush : 0.490 0.667 0.833 1.000 0.667 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] headphones : 0.316 0.578 0.708 1.000 0.500 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] stapler : 0.002 0.011 0.061 0.067 0.333 [2025-04-30 07:56:52,464 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 07:56:52,464 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 07:56:52,464 INFO hook.py line 404 1619929] average : 0.285 0.425 0.513 0.633 0.484 [2025-04-30 07:56:52,464 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 07:56:52,464 INFO hook.py line 480 1619929] Total Process Time: 23.333 s [2025-04-30 07:56:52,464 INFO hook.py line 481 1619929] Average Process Time: 470.885 ms [2025-04-30 07:56:52,465 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 07:56:52,509 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 07:56:52,513 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 07:58:28,775 INFO hook.py line 650 1619929] Train: [500/512][50/242] Data 0.015 (0.037) Batch 1.392 (1.485) Remain 01:16:37 loss: 4.2400 Lr: 1.10077e-05 Mem R(MA/MR): 23372 (21973/36182) [2025-04-30 07:59:41,494 INFO hook.py line 650 1619929] Train: [500/512][100/242] Data 0.016 (0.026) Batch 1.397 (1.469) Remain 01:14:35 loss: 4.5672 Lr: 1.08503e-05 Mem R(MA/MR): 25210 (21973/36182) [2025-04-30 08:00:54,623 INFO hook.py line 650 1619929] Train: [500/512][150/242] Data 0.016 (0.023) Batch 1.514 (1.467) Remain 01:13:14 loss: 3.5056 Lr: 1.06926e-05 Mem R(MA/MR): 25210 (21973/36182) [2025-04-30 08:02:07,370 INFO hook.py line 650 1619929] Train: [500/512][200/242] Data 0.016 (0.022) Batch 1.404 (1.464) Remain 01:11:52 loss: 4.3865 Lr: 1.05347e-05 Mem R(MA/MR): 27204 (21973/36182) [2025-04-30 08:03:07,481 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2153 loss_mask: 0.0288 loss_dice: 1.6845 loss_score: 0.0000 loss_bbox: 0.0451 loss_sp_cls: 0.6697 loss: 4.2574 [2025-04-30 08:03:11,906 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:03:14,223 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0831 Process Time: 0.350 Mem R(MA/MR): 4748 (21973/36182) [2025-04-30 08:03:15,637 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.7706 Process Time: 0.373 Mem R(MA/MR): 7588 (21973/36182) [2025-04-30 08:03:17,274 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5052 Process Time: 0.607 Mem R(MA/MR): 10268 (21973/36182) [2025-04-30 08:03:24,951 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.1531 Process Time: 0.837 Mem R(MA/MR): 20052 (21973/36182) [2025-04-30 08:03:25,745 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.7400 Process Time: 0.253 Mem R(MA/MR): 7506 (21973/36182) [2025-04-30 08:03:27,375 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5035 Process Time: 0.413 Mem R(MA/MR): 11620 (21973/36182) [2025-04-30 08:03:28,480 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.6767 Process Time: 0.469 Mem R(MA/MR): 6560 (21973/36182) [2025-04-30 08:03:28,961 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4187 Process Time: 0.136 Mem R(MA/MR): 4768 (21973/36182) [2025-04-30 08:03:29,991 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.1405 Process Time: 0.318 Mem R(MA/MR): 11768 (21973/36182) [2025-04-30 08:03:31,665 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.3736 Process Time: 0.280 Mem R(MA/MR): 10038 (21973/36182) [2025-04-30 08:03:34,748 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.7355 Process Time: 0.700 Mem R(MA/MR): 19046 (21973/36182) [2025-04-30 08:03:38,091 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9500 Process Time: 0.780 Mem R(MA/MR): 15842 (21973/36182) [2025-04-30 08:03:39,172 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.3797 Process Time: 0.239 Mem R(MA/MR): 9342 (21973/36182) [2025-04-30 08:03:39,851 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2533 Process Time: 0.309 Mem R(MA/MR): 5294 (21973/36182) [2025-04-30 08:03:43,335 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.9912 Process Time: 0.507 Mem R(MA/MR): 17000 (21973/36182) [2025-04-30 08:03:45,407 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4265 Process Time: 0.461 Mem R(MA/MR): 14946 (21973/36182) [2025-04-30 08:03:46,249 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.5233 Process Time: 0.271 Mem R(MA/MR): 7136 (21973/36182) [2025-04-30 08:03:47,210 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9434 Process Time: 0.271 Mem R(MA/MR): 8728 (21973/36182) [2025-04-30 08:03:48,639 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2797 Process Time: 0.277 Mem R(MA/MR): 6010 (21973/36182) [2025-04-30 08:03:50,292 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.4810 Process Time: 0.276 Mem R(MA/MR): 11824 (21973/36182) [2025-04-30 08:04:01,149 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.2640 Process Time: 1.272 Mem R(MA/MR): 23912 (21973/36182) [2025-04-30 08:04:01,935 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7834 Process Time: 0.313 Mem R(MA/MR): 7354 (21973/36182) [2025-04-30 08:04:12,899 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.9620 Process Time: 0.442 Mem R(MA/MR): 10630 (21973/36182) [2025-04-30 08:04:13,472 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8152 Process Time: 0.196 Mem R(MA/MR): 5778 (21973/36182) [2025-04-30 08:04:14,364 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8055 Process Time: 0.200 Mem R(MA/MR): 9750 (21973/36182) [2025-04-30 08:04:20,993 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.8947 Process Time: 1.048 Mem R(MA/MR): 31990 (21973/36182) [2025-04-30 08:04:23,672 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.1131 Process Time: 0.518 Mem R(MA/MR): 10278 (21973/36182) [2025-04-30 08:04:24,960 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.2346 Process Time: 0.290 Mem R(MA/MR): 9416 (21973/36182) [2025-04-30 08:04:30,953 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.5543 Process Time: 0.767 Mem R(MA/MR): 17298 (21973/36182) [2025-04-30 08:04:31,893 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2717 Process Time: 0.263 Mem R(MA/MR): 7968 (21973/36182) [2025-04-30 08:04:35,936 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.3035 Process Time: 0.449 Mem R(MA/MR): 20894 (21973/36182) [2025-04-30 08:04:36,629 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1072 Process Time: 0.199 Mem R(MA/MR): 4260 (21973/36182) [2025-04-30 08:04:41,130 INFO hook.py line 449 1619929] Test: [33/50] Loss 13.3623 Process Time: 0.657 Mem R(MA/MR): 25058 (21973/36182) [2025-04-30 08:04:42,333 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6327 Process Time: 0.410 Mem R(MA/MR): 10244 (21973/36182) [2025-04-30 08:04:44,436 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.4474 Process Time: 0.339 Mem R(MA/MR): 14354 (21973/36182) [2025-04-30 08:04:45,157 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0925 Process Time: 0.232 Mem R(MA/MR): 6706 (21973/36182) [2025-04-30 08:04:49,111 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8979 Process Time: 0.721 Mem R(MA/MR): 28390 (21973/36182) [2025-04-30 08:04:50,664 INFO hook.py line 449 1619929] Test: [38/50] Loss 5.0914 Process Time: 0.347 Mem R(MA/MR): 11332 (21973/36182) [2025-04-30 08:04:51,283 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3909 Process Time: 0.225 Mem R(MA/MR): 5868 (21973/36182) [2025-04-30 08:04:52,737 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5915 Process Time: 0.500 Mem R(MA/MR): 10510 (21973/36182) [2025-04-30 08:04:53,947 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5652 Process Time: 0.370 Mem R(MA/MR): 9490 (21973/36182) [2025-04-30 08:04:54,977 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3951 Process Time: 0.367 Mem R(MA/MR): 5858 (21973/36182) [2025-04-30 08:04:55,483 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6632 Process Time: 0.180 Mem R(MA/MR): 5944 (21973/36182) [2025-04-30 08:04:56,230 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.7502 Process Time: 0.253 Mem R(MA/MR): 7488 (21973/36182) [2025-04-30 08:04:56,935 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.7969 Process Time: 0.210 Mem R(MA/MR): 5660 (21973/36182) [2025-04-30 08:04:59,328 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.7352 Process Time: 0.452 Mem R(MA/MR): 14776 (21973/36182) [2025-04-30 08:05:07,346 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7697 Process Time: 0.853 Mem R(MA/MR): 20798 (21973/36182) [2025-04-30 08:05:17,597 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.6293 Process Time: 1.711 Mem R(MA/MR): 35736 (21973/36182) [2025-04-30 08:05:18,486 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.2279 Process Time: 0.315 Mem R(MA/MR): 6018 (21973/36182) [2025-04-30 08:05:20,812 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.8255 Process Time: 0.390 Mem R(MA/MR): 13934 (21973/36182) [2025-04-30 08:05:25,418 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:05:25,418 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:05:25,418 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:05:25,418 INFO hook.py line 395 1619929] table : 0.311 0.661 0.744 0.837 0.640 [2025-04-30 08:05:25,418 INFO hook.py line 395 1619929] door : 0.499 0.785 0.915 0.882 0.759 [2025-04-30 08:05:25,418 INFO hook.py line 395 1619929] ceiling lamp : 0.571 0.744 0.812 0.837 0.707 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] cabinet : 0.348 0.472 0.536 0.552 0.552 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] blinds : 0.576 0.701 0.853 0.789 0.652 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] curtain : 0.447 0.539 0.817 0.533 0.667 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] chair : 0.666 0.811 0.831 0.909 0.697 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] storage cabinet: 0.234 0.325 0.497 0.448 0.520 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] office chair : 0.599 0.640 0.643 0.720 0.750 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] bookshelf : 0.246 0.486 0.589 0.533 0.727 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] whiteboard : 0.567 0.761 0.778 0.920 0.657 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] window : 0.142 0.325 0.656 0.596 0.341 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] box : 0.217 0.370 0.559 0.603 0.387 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] monitor : 0.659 0.795 0.837 0.932 0.786 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] shelf : 0.170 0.349 0.469 0.769 0.333 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] heater : 0.456 0.794 0.850 0.967 0.763 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] kitchen cabinet: 0.123 0.300 0.666 0.455 0.600 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] sofa : 0.471 0.629 0.825 0.667 0.667 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] bed : 0.330 0.625 0.969 1.000 0.625 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] trash can : 0.556 0.711 0.747 0.841 0.815 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] book : 0.017 0.040 0.073 0.306 0.082 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] plant : 0.426 0.642 0.743 1.000 0.611 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] blanket : 0.552 0.672 0.672 0.875 0.636 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] tv : 0.916 1.000 1.000 1.000 1.000 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] computer tower : 0.292 0.493 0.659 0.833 0.476 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] refrigerator : 0.191 0.382 0.471 1.000 0.333 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] jacket : 0.074 0.181 0.381 0.269 0.636 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] sink : 0.488 0.768 0.852 0.850 0.773 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] bag : 0.090 0.121 0.138 0.444 0.148 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] picture : 0.133 0.326 0.378 0.812 0.333 [2025-04-30 08:05:25,419 INFO hook.py line 395 1619929] pillow : 0.590 0.761 0.761 0.917 0.579 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] towel : 0.180 0.275 0.445 0.440 0.289 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] suitcase : 0.417 0.472 0.476 1.000 0.429 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] backpack : 0.434 0.578 0.578 1.000 0.538 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] crate : 0.072 0.223 0.511 0.500 0.455 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] keyboard : 0.540 0.713 0.815 0.800 0.718 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] toilet : 0.860 1.000 1.000 1.000 1.000 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] printer : 0.392 0.428 0.452 0.667 0.444 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] poster : 0.000 0.001 0.001 0.015 0.111 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] microwave : 0.537 0.717 0.845 1.000 0.625 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] shoes : 0.106 0.230 0.504 0.609 0.341 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] socket : 0.183 0.439 0.652 0.673 0.486 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] bottle : 0.137 0.241 0.341 0.466 0.325 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] bucket : 0.039 0.057 0.057 0.231 0.429 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] cushion : 0.084 0.098 0.210 0.231 0.500 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] basket : 0.044 0.143 0.143 1.000 0.143 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] telephone : 0.366 0.638 0.653 0.900 0.529 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] laptop : 0.321 0.655 0.775 0.833 0.625 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] plant pot : 0.225 0.470 0.465 0.714 0.625 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] exhaust fan : 0.194 0.347 0.347 0.750 0.400 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] cup : 0.206 0.309 0.373 0.556 0.341 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] coat hanger : 0.106 0.208 0.750 0.667 0.500 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] light switch : 0.247 0.543 0.653 0.861 0.477 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] speaker : 0.355 0.365 0.457 0.800 0.364 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] kettle : 0.278 0.333 0.333 1.000 0.333 [2025-04-30 08:05:25,420 INFO hook.py line 395 1619929] smoke detector : 0.660 0.829 0.829 1.000 0.792 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] power strip : 0.051 0.099 0.102 0.429 0.300 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.083 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] mouse : 0.548 0.762 0.804 0.880 0.688 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] toilet paper : 0.264 0.412 0.454 1.000 0.412 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] paper towel : 0.017 0.031 0.104 0.500 0.125 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.396 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] tap : 0.172 0.497 0.778 0.800 0.444 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] soap dispenser : 0.544 0.800 0.800 1.000 0.800 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] bowl : 0.067 0.083 0.083 0.500 0.333 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] whiteboard eraser: 0.176 0.434 0.434 0.667 0.667 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] toilet brush : 0.512 0.715 0.889 1.000 0.667 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] spray bottle : 0.005 0.008 0.008 0.062 0.250 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] headphones : 0.500 1.000 1.000 1.000 1.000 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] stapler : 0.001 0.012 0.021 0.071 0.333 [2025-04-30 08:05:25,421 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:05:25,421 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:05:25,421 INFO hook.py line 404 1619929] average : 0.288 0.427 0.512 0.640 0.474 [2025-04-30 08:05:25,421 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:05:25,422 INFO hook.py line 480 1619929] Total Process Time: 22.617 s [2025-04-30 08:05:25,422 INFO hook.py line 481 1619929] Average Process Time: 454.435 ms [2025-04-30 08:05:25,422 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:05:25,474 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 08:05:25,480 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:07:00,145 INFO hook.py line 650 1619929] Train: [501/512][50/242] Data 0.015 (0.017) Batch 1.344 (1.481) Remain 01:10:27 loss: 4.5810 Lr: 1.02433e-05 Mem R(MA/MR): 20516 (21973/36182) [2025-04-30 08:08:13,040 INFO hook.py line 650 1619929] Train: [501/512][100/242] Data 0.019 (0.017) Batch 1.512 (1.469) Remain 01:08:39 loss: 4.2529 Lr: 1.00846e-05 Mem R(MA/MR): 20516 (21973/36182) [2025-04-30 08:09:25,428 INFO hook.py line 650 1619929] Train: [501/512][150/242] Data 0.016 (0.017) Batch 1.425 (1.462) Remain 01:07:06 loss: 3.9018 Lr: 9.92566e-06 Mem R(MA/MR): 20516 (21973/36182) [2025-04-30 08:10:37,330 INFO hook.py line 650 1619929] Train: [501/512][200/242] Data 0.015 (0.022) Batch 1.412 (1.456) Remain 01:05:36 loss: 4.1423 Lr: 9.76640e-06 Mem R(MA/MR): 22510 (21973/36182) [2025-04-30 08:11:34,244 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2149 loss_mask: 0.0292 loss_dice: 1.6814 loss_score: 0.0000 loss_bbox: 0.0452 loss_sp_cls: 0.6644 loss: 4.2485 [2025-04-30 08:11:39,382 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:11:41,666 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2841 Process Time: 0.291 Mem R(MA/MR): 4846 (21973/36182) [2025-04-30 08:11:43,601 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6502 Process Time: 0.639 Mem R(MA/MR): 7730 (21973/36182) [2025-04-30 08:11:45,146 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3878 Process Time: 0.521 Mem R(MA/MR): 10242 (21973/36182) [2025-04-30 08:11:53,095 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.8433 Process Time: 1.200 Mem R(MA/MR): 20326 (21973/36182) [2025-04-30 08:11:54,044 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.5023 Process Time: 0.280 Mem R(MA/MR): 7612 (21973/36182) [2025-04-30 08:11:55,566 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.5605 Process Time: 0.569 Mem R(MA/MR): 11654 (21973/36182) [2025-04-30 08:11:56,400 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1037 Process Time: 0.306 Mem R(MA/MR): 6864 (21973/36182) [2025-04-30 08:11:56,980 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2146 Process Time: 0.189 Mem R(MA/MR): 4896 (21973/36182) [2025-04-30 08:11:58,052 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.0590 Process Time: 0.321 Mem R(MA/MR): 11782 (21973/36182) [2025-04-30 08:11:59,813 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.0658 Process Time: 0.239 Mem R(MA/MR): 9972 (21973/36182) [2025-04-30 08:12:03,120 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.6026 Process Time: 0.906 Mem R(MA/MR): 19270 (21973/36182) [2025-04-30 08:12:05,877 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9320 Process Time: 0.426 Mem R(MA/MR): 15788 (21973/36182) [2025-04-30 08:12:07,310 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.3881 Process Time: 0.391 Mem R(MA/MR): 9214 (21973/36182) [2025-04-30 08:12:07,775 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0362 Process Time: 0.174 Mem R(MA/MR): 5208 (21973/36182) [2025-04-30 08:12:11,161 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.7792 Process Time: 0.475 Mem R(MA/MR): 16912 (21973/36182) [2025-04-30 08:12:13,308 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.2014 Process Time: 0.609 Mem R(MA/MR): 14728 (21973/36182) [2025-04-30 08:12:14,536 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.5399 Process Time: 0.511 Mem R(MA/MR): 7182 (21973/36182) [2025-04-30 08:12:15,466 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0326 Process Time: 0.264 Mem R(MA/MR): 8592 (21973/36182) [2025-04-30 08:12:16,666 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.4073 Process Time: 0.155 Mem R(MA/MR): 6340 (21973/36182) [2025-04-30 08:12:18,253 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.1807 Process Time: 0.232 Mem R(MA/MR): 11888 (21973/36182) [2025-04-30 08:12:28,293 INFO hook.py line 449 1619929] Test: [21/50] Loss 9.6183 Process Time: 1.706 Mem R(MA/MR): 24256 (21973/36182) [2025-04-30 08:12:29,144 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.6628 Process Time: 0.454 Mem R(MA/MR): 7408 (21973/36182) [2025-04-30 08:12:40,701 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.9471 Process Time: 0.678 Mem R(MA/MR): 10708 (21973/36182) [2025-04-30 08:12:41,389 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.5089 Process Time: 0.247 Mem R(MA/MR): 5836 (21973/36182) [2025-04-30 08:12:42,368 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9893 Process Time: 0.258 Mem R(MA/MR): 9582 (21973/36182) [2025-04-30 08:12:49,075 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.4215 Process Time: 1.043 Mem R(MA/MR): 32296 (21973/36182) [2025-04-30 08:12:51,812 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4674 Process Time: 0.597 Mem R(MA/MR): 10324 (21973/36182) [2025-04-30 08:12:53,048 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0835 Process Time: 0.246 Mem R(MA/MR): 9348 (21973/36182) [2025-04-30 08:12:58,503 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.2308 Process Time: 0.393 Mem R(MA/MR): 17230 (21973/36182) [2025-04-30 08:12:59,528 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2737 Process Time: 0.266 Mem R(MA/MR): 8208 (21973/36182) [2025-04-30 08:13:03,788 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8477 Process Time: 0.359 Mem R(MA/MR): 21202 (21973/36182) [2025-04-30 08:13:04,289 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1139 Process Time: 0.267 Mem R(MA/MR): 4520 (21973/36182) [2025-04-30 08:13:09,718 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.9025 Process Time: 1.111 Mem R(MA/MR): 25296 (21973/36182) [2025-04-30 08:13:10,904 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6107 Process Time: 0.374 Mem R(MA/MR): 10288 (21973/36182) [2025-04-30 08:13:13,138 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3916 Process Time: 0.365 Mem R(MA/MR): 14414 (21973/36182) [2025-04-30 08:13:13,887 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.7207 Process Time: 0.265 Mem R(MA/MR): 7058 (21973/36182) [2025-04-30 08:13:18,413 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5796 Process Time: 1.068 Mem R(MA/MR): 28856 (21973/36182) [2025-04-30 08:13:20,140 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8433 Process Time: 0.465 Mem R(MA/MR): 11160 (21973/36182) [2025-04-30 08:13:20,789 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2345 Process Time: 0.280 Mem R(MA/MR): 5944 (21973/36182) [2025-04-30 08:13:22,045 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.8857 Process Time: 0.325 Mem R(MA/MR): 10590 (21973/36182) [2025-04-30 08:13:23,810 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.8576 Process Time: 0.860 Mem R(MA/MR): 9476 (21973/36182) [2025-04-30 08:13:24,376 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.4512 Process Time: 0.180 Mem R(MA/MR): 5982 (21973/36182) [2025-04-30 08:13:25,059 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9569 Process Time: 0.305 Mem R(MA/MR): 6000 (21973/36182) [2025-04-30 08:13:25,722 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.6138 Process Time: 0.193 Mem R(MA/MR): 7620 (21973/36182) [2025-04-30 08:13:26,473 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3125 Process Time: 0.269 Mem R(MA/MR): 5732 (21973/36182) [2025-04-30 08:13:28,791 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.7230 Process Time: 0.485 Mem R(MA/MR): 14850 (21973/36182) [2025-04-30 08:13:36,660 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.0889 Process Time: 0.366 Mem R(MA/MR): 20870 (21973/36182) [2025-04-30 08:13:46,881 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.7663 Process Time: 1.424 Mem R(MA/MR): 36100 (21973/36182) [2025-04-30 08:13:47,676 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.3404 Process Time: 0.280 Mem R(MA/MR): 6138 (21973/36182) [2025-04-30 08:13:50,648 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0407 Process Time: 0.696 Mem R(MA/MR): 14050 (21973/36182) [2025-04-30 08:13:55,254 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:13:55,254 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:13:55,254 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] table : 0.281 0.620 0.778 0.830 0.610 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] door : 0.464 0.782 0.909 0.910 0.772 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] ceiling lamp : 0.582 0.753 0.855 0.876 0.702 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] cabinet : 0.356 0.489 0.545 0.613 0.567 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] blinds : 0.570 0.759 0.812 0.792 0.826 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] curtain : 0.400 0.629 0.754 0.600 0.750 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] chair : 0.676 0.815 0.851 0.766 0.832 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] storage cabinet: 0.202 0.369 0.492 0.722 0.520 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] office chair : 0.533 0.542 0.542 0.711 0.667 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] bookshelf : 0.267 0.623 0.630 0.778 0.636 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] whiteboard : 0.566 0.748 0.773 0.926 0.714 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] window : 0.135 0.322 0.669 0.561 0.407 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] box : 0.214 0.370 0.525 0.569 0.387 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] monitor : 0.686 0.821 0.865 0.935 0.829 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] shelf : 0.154 0.288 0.489 0.727 0.267 [2025-04-30 08:13:55,254 INFO hook.py line 395 1619929] heater : 0.427 0.720 0.747 0.900 0.711 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] kitchen cabinet: 0.124 0.323 0.598 0.480 0.480 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] sofa : 0.556 0.669 0.873 0.692 0.750 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] bed : 0.338 0.625 0.974 1.000 0.625 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] trash can : 0.565 0.713 0.746 0.792 0.877 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] book : 0.026 0.047 0.088 0.309 0.079 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] plant : 0.440 0.611 0.698 1.000 0.611 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] blanket : 0.538 0.625 0.685 0.875 0.636 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] computer tower : 0.298 0.463 0.658 0.741 0.476 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] refrigerator : 0.216 0.390 0.396 1.000 0.333 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] jacket : 0.071 0.139 0.415 0.240 0.545 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] sink : 0.418 0.714 0.950 0.882 0.682 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] bag : 0.075 0.129 0.195 0.391 0.333 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] picture : 0.139 0.337 0.416 0.652 0.385 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] pillow : 0.626 0.775 0.788 0.812 0.684 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] towel : 0.207 0.325 0.512 0.424 0.368 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] suitcase : 0.355 0.475 0.486 0.500 0.571 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] backpack : 0.407 0.647 0.647 1.000 0.615 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] crate : 0.034 0.113 0.493 0.429 0.273 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] keyboard : 0.523 0.715 0.789 0.848 0.718 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] toilet : 0.856 1.000 1.000 1.000 1.000 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] printer : 0.298 0.313 0.329 0.400 0.444 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.002 0.033 0.111 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] microwave : 0.645 0.717 0.985 1.000 0.625 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] shoes : 0.120 0.265 0.616 0.636 0.341 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] socket : 0.186 0.465 0.660 0.646 0.521 [2025-04-30 08:13:55,255 INFO hook.py line 395 1619929] bottle : 0.123 0.219 0.330 0.443 0.325 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] bucket : 0.051 0.075 0.075 0.214 0.429 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] cushion : 0.065 0.141 0.252 0.300 0.500 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] basket : 0.016 0.036 0.058 0.500 0.143 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] telephone : 0.345 0.617 0.678 0.833 0.588 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] laptop : 0.359 0.612 0.779 1.000 0.500 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] plant pot : 0.158 0.316 0.476 0.615 0.500 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] exhaust fan : 0.188 0.337 0.337 0.750 0.400 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] cup : 0.246 0.369 0.405 0.875 0.318 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] coat hanger : 0.278 0.750 0.677 1.000 0.750 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] light switch : 0.228 0.479 0.647 0.853 0.446 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] speaker : 0.380 0.511 0.607 0.833 0.455 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.792 1.000 0.500 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] smoke detector : 0.652 0.817 0.819 0.905 0.792 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] power strip : 0.062 0.116 0.173 0.500 0.300 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] mouse : 0.524 0.755 0.775 0.885 0.719 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] toilet paper : 0.265 0.412 0.471 1.000 0.412 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] paper towel : 0.154 0.177 0.177 0.500 0.250 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] tap : 0.209 0.399 0.725 0.500 0.556 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] jar : 0.001 0.012 0.028 0.333 0.071 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] soap dispenser : 0.530 0.800 1.000 1.000 0.800 [2025-04-30 08:13:55,256 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] bowl : 0.333 0.333 0.333 1.000 0.333 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] tissue box : 0.051 0.125 0.500 0.500 0.500 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] whiteboard eraser: 0.224 0.486 0.501 0.800 0.667 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] toilet brush : 0.520 0.738 0.913 1.000 0.667 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] headphones : 0.407 0.792 1.000 0.667 1.000 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] stapler : 0.005 0.049 0.075 0.143 0.667 [2025-04-30 08:13:55,257 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:13:55,257 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:13:55,257 INFO hook.py line 404 1619929] average : 0.288 0.427 0.523 0.634 0.484 [2025-04-30 08:13:55,257 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:13:55,257 INFO hook.py line 480 1619929] Total Process Time: 24.523 s [2025-04-30 08:13:55,257 INFO hook.py line 481 1619929] Average Process Time: 494.536 ms [2025-04-30 08:13:55,257 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:13:55,314 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 08:13:55,317 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:15:30,595 INFO hook.py line 650 1619929] Train: [502/512][50/242] Data 0.017 (0.017) Batch 1.407 (1.495) Remain 01:05:06 loss: 3.8821 Lr: 9.47259e-06 Mem R(MA/MR): 21366 (21973/36182) [2025-04-30 08:16:44,225 INFO hook.py line 650 1619929] Train: [502/512][100/242] Data 0.015 (0.017) Batch 1.566 (1.484) Remain 01:03:21 loss: 5.1659 Lr: 9.31249e-06 Mem R(MA/MR): 21366 (21973/36182) [2025-04-30 08:17:58,043 INFO hook.py line 650 1619929] Train: [502/512][150/242] Data 0.016 (0.023) Batch 1.328 (1.481) Remain 01:02:00 loss: 5.1171 Lr: 9.15208e-06 Mem R(MA/MR): 25040 (21973/36182) [2025-04-30 08:19:07,824 INFO hook.py line 650 1619929] Train: [502/512][200/242] Data 0.015 (0.022) Batch 1.392 (1.459) Remain 00:59:53 loss: 4.3196 Lr: 8.99136e-06 Mem R(MA/MR): 25042 (21973/36182) [2025-04-30 08:20:05,387 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2126 loss_mask: 0.0290 loss_dice: 1.6743 loss_score: 0.0000 loss_bbox: 0.0447 loss_sp_cls: 0.6581 loss: 4.2258 [2025-04-30 08:20:05,851 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:20:08,136 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0092 Process Time: 0.289 Mem R(MA/MR): 4634 (21973/36182) [2025-04-30 08:20:09,846 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.4622 Process Time: 0.570 Mem R(MA/MR): 7448 (21973/36182) [2025-04-30 08:20:11,475 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2944 Process Time: 0.640 Mem R(MA/MR): 10174 (21973/36182) [2025-04-30 08:20:19,883 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.6437 Process Time: 1.076 Mem R(MA/MR): 20032 (21973/36182) [2025-04-30 08:20:20,948 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4570 Process Time: 0.362 Mem R(MA/MR): 7348 (21973/36182) [2025-04-30 08:20:22,796 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8796 Process Time: 0.532 Mem R(MA/MR): 11584 (21973/36182) [2025-04-30 08:20:23,638 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0143 Process Time: 0.308 Mem R(MA/MR): 6438 (21973/36182) [2025-04-30 08:20:24,165 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.1158 Process Time: 0.151 Mem R(MA/MR): 4644 (21973/36182) [2025-04-30 08:20:25,160 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7806 Process Time: 0.284 Mem R(MA/MR): 11724 (21973/36182) [2025-04-30 08:20:26,993 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5783 Process Time: 0.335 Mem R(MA/MR): 9916 (21973/36182) [2025-04-30 08:20:30,061 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.9361 Process Time: 0.677 Mem R(MA/MR): 19106 (21973/36182) [2025-04-30 08:20:32,813 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1778 Process Time: 0.440 Mem R(MA/MR): 15652 (21973/36182) [2025-04-30 08:20:34,070 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7265 Process Time: 0.342 Mem R(MA/MR): 9158 (21973/36182) [2025-04-30 08:20:34,475 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0871 Process Time: 0.144 Mem R(MA/MR): 5206 (21973/36182) [2025-04-30 08:20:37,850 INFO hook.py line 449 1619929] Test: [15/50] Loss 13.2420 Process Time: 0.337 Mem R(MA/MR): 16612 (21973/36182) [2025-04-30 08:20:40,017 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0299 Process Time: 0.607 Mem R(MA/MR): 14874 (21973/36182) [2025-04-30 08:20:40,841 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2433 Process Time: 0.251 Mem R(MA/MR): 6698 (21973/36182) [2025-04-30 08:20:41,839 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1501 Process Time: 0.326 Mem R(MA/MR): 8524 (21973/36182) [2025-04-30 08:20:43,156 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2815 Process Time: 0.177 Mem R(MA/MR): 5992 (21973/36182) [2025-04-30 08:20:44,791 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.4668 Process Time: 0.240 Mem R(MA/MR): 11690 (21973/36182) [2025-04-30 08:20:54,102 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.4451 Process Time: 1.183 Mem R(MA/MR): 23898 (21973/36182) [2025-04-30 08:20:54,747 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7019 Process Time: 0.275 Mem R(MA/MR): 6972 (21973/36182) [2025-04-30 08:21:04,271 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.1420 Process Time: 0.437 Mem R(MA/MR): 10450 (21973/36182) [2025-04-30 08:21:05,082 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7901 Process Time: 0.332 Mem R(MA/MR): 5640 (21973/36182) [2025-04-30 08:21:06,317 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.1283 Process Time: 0.397 Mem R(MA/MR): 9618 (21973/36182) [2025-04-30 08:21:13,917 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.3083 Process Time: 1.204 Mem R(MA/MR): 31686 (21973/36182) [2025-04-30 08:21:16,528 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4092 Process Time: 0.383 Mem R(MA/MR): 10144 (21973/36182) [2025-04-30 08:21:17,786 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.1571 Process Time: 0.261 Mem R(MA/MR): 9270 (21973/36182) [2025-04-30 08:21:23,678 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8592 Process Time: 0.642 Mem R(MA/MR): 17046 (21973/36182) [2025-04-30 08:21:24,727 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3325 Process Time: 0.327 Mem R(MA/MR): 7876 (21973/36182) [2025-04-30 08:21:28,679 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.6408 Process Time: 0.760 Mem R(MA/MR): 20840 (21973/36182) [2025-04-30 08:21:28,961 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1958 Process Time: 0.116 Mem R(MA/MR): 4324 (21973/36182) [2025-04-30 08:21:33,007 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.9596 Process Time: 0.515 Mem R(MA/MR): 25176 (21973/36182) [2025-04-30 08:21:34,427 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6698 Process Time: 0.559 Mem R(MA/MR): 10156 (21973/36182) [2025-04-30 08:21:36,346 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.3279 Process Time: 0.371 Mem R(MA/MR): 14114 (21973/36182) [2025-04-30 08:21:37,002 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2070 Process Time: 0.286 Mem R(MA/MR): 6544 (21973/36182) [2025-04-30 08:21:40,665 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.6655 Process Time: 0.766 Mem R(MA/MR): 28504 (21973/36182) [2025-04-30 08:21:42,427 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.7203 Process Time: 0.451 Mem R(MA/MR): 11108 (21973/36182) [2025-04-30 08:21:42,910 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.4298 Process Time: 0.194 Mem R(MA/MR): 5772 (21973/36182) [2025-04-30 08:21:43,955 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.4865 Process Time: 0.277 Mem R(MA/MR): 10408 (21973/36182) [2025-04-30 08:21:44,894 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.6875 Process Time: 0.320 Mem R(MA/MR): 9378 (21973/36182) [2025-04-30 08:21:45,590 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.7111 Process Time: 0.307 Mem R(MA/MR): 5764 (21973/36182) [2025-04-30 08:21:46,049 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5990 Process Time: 0.168 Mem R(MA/MR): 5822 (21973/36182) [2025-04-30 08:21:46,641 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.2152 Process Time: 0.196 Mem R(MA/MR): 7404 (21973/36182) [2025-04-30 08:21:47,415 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5734 Process Time: 0.350 Mem R(MA/MR): 5564 (21973/36182) [2025-04-30 08:21:49,520 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.6914 Process Time: 0.507 Mem R(MA/MR): 14654 (21973/36182) [2025-04-30 08:21:56,568 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7427 Process Time: 0.726 Mem R(MA/MR): 20458 (21973/36182) [2025-04-30 08:22:06,648 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.8861 Process Time: 1.819 Mem R(MA/MR): 35434 (21973/36182) [2025-04-30 08:22:07,831 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.2004 Process Time: 0.299 Mem R(MA/MR): 6194 (21973/36182) [2025-04-30 08:22:10,247 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0730 Process Time: 0.562 Mem R(MA/MR): 13870 (21973/36182) [2025-04-30 08:22:14,058 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:22:14,058 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:22:14,058 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] table : 0.294 0.649 0.775 0.809 0.654 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] door : 0.448 0.775 0.898 0.870 0.759 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] ceiling lamp : 0.586 0.782 0.875 0.819 0.773 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] cabinet : 0.378 0.527 0.601 0.591 0.582 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] blinds : 0.598 0.859 0.830 0.870 0.870 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] curtain : 0.399 0.522 0.707 0.600 0.500 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] chair : 0.671 0.807 0.840 0.812 0.762 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] storage cabinet: 0.237 0.398 0.527 0.750 0.480 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] office chair : 0.603 0.632 0.632 0.712 0.771 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] bookshelf : 0.401 0.591 0.607 0.571 0.727 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] whiteboard : 0.572 0.770 0.809 0.962 0.714 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] window : 0.136 0.321 0.628 0.513 0.440 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] box : 0.206 0.369 0.516 0.644 0.370 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] monitor : 0.648 0.806 0.849 0.964 0.757 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] shelf : 0.148 0.294 0.402 0.625 0.333 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] heater : 0.442 0.819 0.864 0.879 0.763 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] kitchen cabinet: 0.100 0.293 0.756 0.455 0.400 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] sofa : 0.530 0.625 0.809 0.875 0.583 [2025-04-30 08:22:14,058 INFO hook.py line 395 1619929] bed : 0.200 0.553 0.938 1.000 0.500 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] trash can : 0.584 0.724 0.738 0.869 0.815 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] book : 0.025 0.047 0.076 0.294 0.075 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] plant : 0.387 0.552 0.765 0.688 0.611 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] blanket : 0.601 0.760 0.760 0.875 0.636 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] tv : 0.922 1.000 1.000 1.000 1.000 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] computer tower : 0.336 0.508 0.637 0.649 0.571 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] refrigerator : 0.227 0.453 0.461 0.667 0.444 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] jacket : 0.046 0.169 0.416 0.294 0.455 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] sink : 0.392 0.645 0.814 0.867 0.591 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] bag : 0.085 0.119 0.200 0.500 0.259 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] picture : 0.135 0.301 0.395 0.484 0.385 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] pillow : 0.628 0.852 0.895 0.933 0.737 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] towel : 0.209 0.353 0.521 0.362 0.553 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] suitcase : 0.392 0.476 0.481 1.000 0.429 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] backpack : 0.494 0.615 0.615 1.000 0.615 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] crate : 0.059 0.211 0.492 0.800 0.364 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] keyboard : 0.536 0.691 0.813 0.839 0.667 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] toilet : 0.877 1.000 1.000 1.000 1.000 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] printer : 0.341 0.404 0.426 1.000 0.333 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.003 0.037 0.111 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] painting : 0.056 0.062 0.062 0.125 1.000 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] microwave : 0.640 0.875 1.000 1.000 0.875 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] shoes : 0.106 0.210 0.652 0.583 0.341 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] socket : 0.201 0.465 0.690 0.638 0.529 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] bottle : 0.142 0.252 0.387 0.535 0.277 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] bucket : 0.004 0.004 0.018 0.056 0.143 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] cushion : 0.035 0.102 0.249 0.250 0.333 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] basket : 0.012 0.036 0.036 0.500 0.143 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] telephone : 0.346 0.548 0.550 0.750 0.529 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] laptop : 0.337 0.590 0.745 0.714 0.625 [2025-04-30 08:22:14,059 INFO hook.py line 395 1619929] plant pot : 0.149 0.352 0.572 0.643 0.562 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] exhaust fan : 0.181 0.337 0.337 0.750 0.400 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] cup : 0.257 0.368 0.419 0.696 0.364 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] coat hanger : 0.132 0.500 0.750 1.000 0.500 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] light switch : 0.241 0.472 0.625 0.586 0.523 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] speaker : 0.461 0.529 0.624 0.857 0.545 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] smoke detector : 0.677 0.858 0.860 0.909 0.833 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] power strip : 0.052 0.151 0.170 0.600 0.300 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] mouse : 0.517 0.726 0.805 0.952 0.625 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] cutting board : 0.028 0.250 0.250 1.000 0.250 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] toilet paper : 0.258 0.464 0.464 0.889 0.471 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] paper towel : 0.000 0.000 0.198 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.042 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] tap : 0.165 0.372 0.593 0.667 0.444 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] soap dispenser : 0.531 0.800 0.800 1.000 0.800 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] bowl : 0.296 0.333 0.528 1.000 0.333 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] tissue box : 0.011 0.050 0.062 0.200 0.500 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] whiteboard eraser: 0.203 0.474 0.474 0.800 0.667 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] toilet brush : 0.493 0.718 0.907 1.000 0.667 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] spray bottle : 0.006 0.008 0.008 0.067 0.250 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] headphones : 0.556 1.000 1.000 1.000 1.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] stapler : 0.038 0.124 0.195 0.231 1.000 [2025-04-30 08:22:14,060 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:22:14,060 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:22:14,060 INFO hook.py line 404 1619929] average : 0.287 0.431 0.518 0.637 0.493 [2025-04-30 08:22:14,060 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:22:14,061 INFO hook.py line 480 1619929] Total Process Time: 23.079 s [2025-04-30 08:22:14,061 INFO hook.py line 481 1619929] Average Process Time: 465.098 ms [2025-04-30 08:22:14,061 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:22:14,108 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 08:22:14,110 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:23:49,525 INFO hook.py line 650 1619929] Train: [503/512][50/242] Data 0.016 (0.017) Batch 1.514 (1.462) Remain 00:57:45 loss: 4.2390 Lr: 8.69480e-06 Mem R(MA/MR): 28024 (21973/36182) [2025-04-30 08:25:03,379 INFO hook.py line 650 1619929] Train: [503/512][100/242] Data 0.019 (0.017) Batch 1.515 (1.470) Remain 00:56:50 loss: 4.3510 Lr: 8.53315e-06 Mem R(MA/MR): 28024 (21973/36182) [2025-04-30 08:26:17,614 INFO hook.py line 650 1619929] Train: [503/512][150/242] Data 0.017 (0.022) Batch 1.486 (1.475) Remain 00:55:48 loss: 4.5491 Lr: 8.37116e-06 Mem R(MA/MR): 30582 (21973/36182) [2025-04-30 08:27:30,508 INFO hook.py line 650 1619929] Train: [503/512][200/242] Data 0.015 (0.021) Batch 1.596 (1.471) Remain 00:54:24 loss: 4.9164 Lr: 8.20882e-06 Mem R(MA/MR): 30582 (21973/36182) [2025-04-30 08:28:29,680 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2123 loss_mask: 0.0287 loss_dice: 1.6651 loss_score: 0.0000 loss_bbox: 0.0447 loss_sp_cls: 0.6671 loss: 4.2131 [2025-04-30 08:28:33,020 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:28:35,374 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0921 Process Time: 0.314 Mem R(MA/MR): 4978 (21973/36182) [2025-04-30 08:28:37,163 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6799 Process Time: 0.553 Mem R(MA/MR): 7848 (21973/36182) [2025-04-30 08:28:38,858 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.6317 Process Time: 0.641 Mem R(MA/MR): 10316 (21973/36182) [2025-04-30 08:28:46,356 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.1520 Process Time: 0.746 Mem R(MA/MR): 20522 (21973/36182) [2025-04-30 08:28:47,510 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4411 Process Time: 0.337 Mem R(MA/MR): 7756 (21973/36182) [2025-04-30 08:28:49,194 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.3567 Process Time: 0.503 Mem R(MA/MR): 11836 (21973/36182) [2025-04-30 08:28:50,103 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1281 Process Time: 0.314 Mem R(MA/MR): 6996 (21973/36182) [2025-04-30 08:28:50,740 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2102 Process Time: 0.203 Mem R(MA/MR): 5020 (21973/36182) [2025-04-30 08:28:51,685 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8759 Process Time: 0.259 Mem R(MA/MR): 11978 (21973/36182) [2025-04-30 08:28:53,346 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4300 Process Time: 0.303 Mem R(MA/MR): 10086 (21973/36182) [2025-04-30 08:28:56,111 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.2025 Process Time: 0.418 Mem R(MA/MR): 19484 (21973/36182) [2025-04-30 08:28:59,147 INFO hook.py line 449 1619929] Test: [12/50] Loss 6.9254 Process Time: 0.589 Mem R(MA/MR): 15988 (21973/36182) [2025-04-30 08:29:00,723 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.8935 Process Time: 0.518 Mem R(MA/MR): 9372 (21973/36182) [2025-04-30 08:29:01,246 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.0962 Process Time: 0.222 Mem R(MA/MR): 5360 (21973/36182) [2025-04-30 08:29:04,565 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.7669 Process Time: 0.353 Mem R(MA/MR): 17044 (21973/36182) [2025-04-30 08:29:06,365 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3119 Process Time: 0.366 Mem R(MA/MR): 15026 (21973/36182) [2025-04-30 08:29:07,120 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.4425 Process Time: 0.200 Mem R(MA/MR): 7280 (21973/36182) [2025-04-30 08:29:08,225 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.7484 Process Time: 0.322 Mem R(MA/MR): 8750 (21973/36182) [2025-04-30 08:29:09,715 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2609 Process Time: 0.235 Mem R(MA/MR): 6576 (21973/36182) [2025-04-30 08:29:11,616 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.0694 Process Time: 0.463 Mem R(MA/MR): 12108 (21973/36182) [2025-04-30 08:29:20,829 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.3167 Process Time: 1.025 Mem R(MA/MR): 24372 (21973/36182) [2025-04-30 08:29:21,861 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.7105 Process Time: 0.538 Mem R(MA/MR): 7398 (21973/36182) [2025-04-30 08:29:31,897 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.8866 Process Time: 0.497 Mem R(MA/MR): 10820 (21973/36182) [2025-04-30 08:29:32,768 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.4448 Process Time: 0.356 Mem R(MA/MR): 5924 (21973/36182) [2025-04-30 08:29:34,110 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.8673 Process Time: 0.526 Mem R(MA/MR): 9836 (21973/36182) [2025-04-30 08:29:42,562 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.5283 Process Time: 2.175 Mem R(MA/MR): 32252 (21973/36182) [2025-04-30 08:29:45,151 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.1823 Process Time: 0.382 Mem R(MA/MR): 10484 (21973/36182) [2025-04-30 08:29:46,474 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.5209 Process Time: 0.296 Mem R(MA/MR): 9538 (21973/36182) [2025-04-30 08:29:51,986 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.8011 Process Time: 0.398 Mem R(MA/MR): 17636 (21973/36182) [2025-04-30 08:29:53,341 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3128 Process Time: 0.374 Mem R(MA/MR): 8222 (21973/36182) [2025-04-30 08:29:57,363 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.9300 Process Time: 0.748 Mem R(MA/MR): 21244 (21973/36182) [2025-04-30 08:29:57,906 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.0596 Process Time: 0.288 Mem R(MA/MR): 4644 (21973/36182) [2025-04-30 08:30:01,941 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.5574 Process Time: 0.583 Mem R(MA/MR): 25566 (21973/36182) [2025-04-30 08:30:03,285 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.3649 Process Time: 0.496 Mem R(MA/MR): 10460 (21973/36182) [2025-04-30 08:30:05,124 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0540 Process Time: 0.324 Mem R(MA/MR): 14678 (21973/36182) [2025-04-30 08:30:05,593 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.9623 Process Time: 0.172 Mem R(MA/MR): 7228 (21973/36182) [2025-04-30 08:30:08,845 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5945 Process Time: 0.433 Mem R(MA/MR): 28814 (21973/36182) [2025-04-30 08:30:10,664 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.5592 Process Time: 0.454 Mem R(MA/MR): 11304 (21973/36182) [2025-04-30 08:30:11,502 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.3580 Process Time: 0.442 Mem R(MA/MR): 6128 (21973/36182) [2025-04-30 08:30:12,943 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5126 Process Time: 0.445 Mem R(MA/MR): 10782 (21973/36182) [2025-04-30 08:30:13,986 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.4719 Process Time: 0.259 Mem R(MA/MR): 9572 (21973/36182) [2025-04-30 08:30:14,531 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3196 Process Time: 0.156 Mem R(MA/MR): 6110 (21973/36182) [2025-04-30 08:30:14,961 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7623 Process Time: 0.137 Mem R(MA/MR): 6144 (21973/36182) [2025-04-30 08:30:15,671 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.8411 Process Time: 0.208 Mem R(MA/MR): 7738 (21973/36182) [2025-04-30 08:30:16,310 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5513 Process Time: 0.170 Mem R(MA/MR): 5880 (21973/36182) [2025-04-30 08:30:18,634 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5175 Process Time: 0.413 Mem R(MA/MR): 15024 (21973/36182) [2025-04-30 08:30:26,947 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.7655 Process Time: 1.175 Mem R(MA/MR): 21060 (21973/36182) [2025-04-30 08:30:37,556 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2975 Process Time: 2.460 Mem R(MA/MR): 36194 (21973/36194) [2025-04-30 08:30:38,716 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.7677 Process Time: 0.389 Mem R(MA/MR): 6398 (21973/36194) [2025-04-30 08:30:41,263 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2828 Process Time: 0.478 Mem R(MA/MR): 14224 (21973/36194) [2025-04-30 08:30:44,953 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:30:44,953 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:30:44,953 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:30:44,953 INFO hook.py line 395 1619929] table : 0.284 0.602 0.735 0.808 0.618 [2025-04-30 08:30:44,953 INFO hook.py line 395 1619929] door : 0.463 0.749 0.886 0.922 0.747 [2025-04-30 08:30:44,953 INFO hook.py line 395 1619929] ceiling lamp : 0.573 0.745 0.836 0.847 0.735 [2025-04-30 08:30:44,953 INFO hook.py line 395 1619929] cabinet : 0.347 0.465 0.536 0.567 0.507 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] blinds : 0.564 0.760 0.814 0.857 0.783 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] curtain : 0.324 0.470 0.658 0.667 0.500 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] chair : 0.669 0.809 0.850 0.802 0.779 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] storage cabinet: 0.219 0.349 0.436 0.560 0.560 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] office chair : 0.608 0.649 0.649 0.712 0.771 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] bookshelf : 0.249 0.433 0.679 0.778 0.636 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] whiteboard : 0.576 0.773 0.791 0.929 0.743 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] window : 0.141 0.306 0.649 0.487 0.418 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] box : 0.222 0.387 0.539 0.638 0.370 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] monitor : 0.648 0.809 0.836 1.000 0.771 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] shelf : 0.146 0.309 0.392 0.667 0.333 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] heater : 0.435 0.780 0.821 0.861 0.816 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] kitchen cabinet: 0.194 0.465 0.662 0.577 0.600 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] sofa : 0.530 0.606 0.870 0.875 0.583 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] bed : 0.252 0.574 0.788 0.833 0.625 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] trash can : 0.591 0.756 0.770 0.838 0.877 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] book : 0.025 0.047 0.093 0.296 0.090 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] plant : 0.438 0.637 0.759 1.000 0.556 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] blanket : 0.549 0.620 0.674 0.857 0.545 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] tv : 0.914 1.000 1.000 1.000 1.000 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] computer tower : 0.297 0.515 0.670 0.778 0.500 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] refrigerator : 0.237 0.444 0.444 1.000 0.444 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] jacket : 0.057 0.148 0.322 0.600 0.273 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] sink : 0.459 0.756 0.809 0.857 0.818 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] bag : 0.112 0.167 0.218 0.500 0.222 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] picture : 0.152 0.318 0.370 0.615 0.410 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] pillow : 0.605 0.792 0.821 0.875 0.737 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] towel : 0.211 0.343 0.518 0.538 0.368 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] suitcase : 0.408 0.539 0.539 0.556 0.714 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] backpack : 0.502 0.669 0.748 0.818 0.692 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] crate : 0.066 0.197 0.588 0.316 0.545 [2025-04-30 08:30:44,954 INFO hook.py line 395 1619929] keyboard : 0.525 0.708 0.748 0.900 0.692 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] toilet : 0.866 1.000 1.000 1.000 1.000 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] printer : 0.253 0.290 0.413 0.500 0.333 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] poster : 0.000 0.003 0.004 0.050 0.111 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] microwave : 0.536 0.602 0.875 0.833 0.625 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] shoes : 0.092 0.209 0.564 0.500 0.366 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] socket : 0.193 0.487 0.679 0.750 0.514 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] bottle : 0.157 0.251 0.351 0.605 0.277 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] bucket : 0.026 0.041 0.061 0.167 0.286 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] cushion : 0.060 0.088 0.247 0.188 0.500 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] basket : 0.011 0.024 0.046 0.333 0.143 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] telephone : 0.341 0.588 0.590 1.000 0.471 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] laptop : 0.391 0.764 0.764 0.750 0.750 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] plant pot : 0.143 0.323 0.424 0.778 0.438 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] exhaust fan : 0.203 0.362 0.362 0.857 0.400 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] cup : 0.258 0.402 0.461 0.889 0.364 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] coat hanger : 0.278 0.750 0.750 1.000 0.750 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] light switch : 0.235 0.505 0.631 0.816 0.477 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] speaker : 0.350 0.384 0.459 0.583 0.636 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] kettle : 0.221 0.264 0.264 0.667 0.333 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] smoke detector : 0.659 0.825 0.825 0.909 0.833 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] power strip : 0.065 0.118 0.158 0.500 0.300 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] paper bag : 0.083 0.083 0.125 0.167 1.000 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] mouse : 0.385 0.617 0.636 0.944 0.531 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] cutting board : 0.068 0.250 0.250 1.000 0.250 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] toilet paper : 0.269 0.417 0.537 0.778 0.412 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] paper towel : 0.118 0.177 0.177 0.500 0.250 [2025-04-30 08:30:44,955 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] clock : 0.441 0.528 0.528 0.667 0.667 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.521 0.000 0.000 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] tap : 0.211 0.489 0.876 0.667 0.667 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] soap dispenser : 0.529 0.800 0.800 1.000 0.800 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] bowl : 0.068 0.083 0.083 0.500 0.333 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] whiteboard eraser: 0.185 0.450 0.478 0.556 0.833 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] toilet brush : 0.466 0.667 0.833 1.000 0.667 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] spray bottle : 0.005 0.007 0.008 0.053 0.250 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] headphones : 0.440 0.792 1.000 0.667 1.000 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] stapler : 0.003 0.011 0.058 0.067 0.333 [2025-04-30 08:30:44,956 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:30:44,956 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:30:44,956 INFO hook.py line 404 1619929] average : 0.282 0.425 0.511 0.622 0.497 [2025-04-30 08:30:44,956 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:30:44,956 INFO hook.py line 480 1619929] Total Process Time: 24.659 s [2025-04-30 08:30:44,956 INFO hook.py line 481 1619929] Average Process Time: 496.829 ms [2025-04-30 08:30:44,956 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:30:44,997 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 08:30:45,002 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:32:21,602 INFO hook.py line 650 1619929] Train: [504/512][50/242] Data 0.018 (0.017) Batch 1.726 (1.504) Remain 00:53:21 loss: 5.1072 Lr: 7.90918e-06 Mem R(MA/MR): 21498 (21973/36194) [2025-04-30 08:33:36,728 INFO hook.py line 650 1619929] Train: [504/512][100/242] Data 0.017 (0.027) Batch 1.561 (1.503) Remain 00:52:04 loss: 4.1215 Lr: 7.74580e-06 Mem R(MA/MR): 24454 (21973/36194) [2025-04-30 08:34:49,639 INFO hook.py line 650 1619929] Train: [504/512][150/242] Data 0.016 (0.024) Batch 1.389 (1.488) Remain 00:50:17 loss: 4.0317 Lr: 7.58204e-06 Mem R(MA/MR): 26226 (21973/36194) [2025-04-30 08:36:02,458 INFO hook.py line 650 1619929] Train: [504/512][200/242] Data 0.014 (0.022) Batch 1.510 (1.480) Remain 00:48:47 loss: 3.8724 Lr: 7.42117e-06 Mem R(MA/MR): 28054 (21973/36194) [2025-04-30 08:36:59,468 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2167 loss_mask: 0.0289 loss_dice: 1.6783 loss_score: 0.0000 loss_bbox: 0.0447 loss_sp_cls: 0.6645 loss: 4.2448 [2025-04-30 08:36:59,547 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:37:02,027 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2073 Process Time: 0.520 Mem R(MA/MR): 4718 (21973/36194) [2025-04-30 08:37:03,634 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6403 Process Time: 0.509 Mem R(MA/MR): 7480 (21973/36194) [2025-04-30 08:37:05,663 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1172 Process Time: 0.883 Mem R(MA/MR): 10088 (21973/36194) [2025-04-30 08:37:13,662 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.2635 Process Time: 0.856 Mem R(MA/MR): 20058 (21973/36194) [2025-04-30 08:37:14,631 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3868 Process Time: 0.373 Mem R(MA/MR): 7438 (21973/36194) [2025-04-30 08:37:16,290 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8518 Process Time: 0.379 Mem R(MA/MR): 11622 (21973/36194) [2025-04-30 08:37:16,857 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.9991 Process Time: 0.187 Mem R(MA/MR): 6520 (21973/36194) [2025-04-30 08:37:17,325 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.4751 Process Time: 0.155 Mem R(MA/MR): 4760 (21973/36194) [2025-04-30 08:37:18,176 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7334 Process Time: 0.248 Mem R(MA/MR): 11778 (21973/36194) [2025-04-30 08:37:19,711 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.2233 Process Time: 0.305 Mem R(MA/MR): 9828 (21973/36194) [2025-04-30 08:37:22,162 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.2205 Process Time: 0.420 Mem R(MA/MR): 19044 (21973/36194) [2025-04-30 08:37:24,772 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1236 Process Time: 0.612 Mem R(MA/MR): 15878 (21973/36194) [2025-04-30 08:37:26,019 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7281 Process Time: 0.420 Mem R(MA/MR): 9096 (21973/36194) [2025-04-30 08:37:26,419 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2228 Process Time: 0.151 Mem R(MA/MR): 5082 (21973/36194) [2025-04-30 08:37:29,796 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.6661 Process Time: 0.320 Mem R(MA/MR): 16862 (21973/36194) [2025-04-30 08:37:32,080 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4615 Process Time: 0.807 Mem R(MA/MR): 14834 (21973/36194) [2025-04-30 08:37:32,945 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3143 Process Time: 0.274 Mem R(MA/MR): 7044 (21973/36194) [2025-04-30 08:37:34,031 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1640 Process Time: 0.414 Mem R(MA/MR): 8482 (21973/36194) [2025-04-30 08:37:35,307 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.8912 Process Time: 0.230 Mem R(MA/MR): 6048 (21973/36194) [2025-04-30 08:37:37,051 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.2965 Process Time: 0.407 Mem R(MA/MR): 11820 (21973/36194) [2025-04-30 08:37:46,193 INFO hook.py line 449 1619929] Test: [21/50] Loss 9.5655 Process Time: 0.619 Mem R(MA/MR): 23936 (21973/36194) [2025-04-30 08:37:46,918 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4481 Process Time: 0.252 Mem R(MA/MR): 7122 (21973/36194) [2025-04-30 08:37:57,760 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.2697 Process Time: 0.465 Mem R(MA/MR): 10552 (21973/36194) [2025-04-30 08:37:58,583 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.9145 Process Time: 0.217 Mem R(MA/MR): 5496 (21973/36194) [2025-04-30 08:37:59,557 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.2225 Process Time: 0.274 Mem R(MA/MR): 9532 (21973/36194) [2025-04-30 08:38:06,002 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.3767 Process Time: 1.124 Mem R(MA/MR): 31692 (21973/36194) [2025-04-30 08:38:08,414 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.1282 Process Time: 0.457 Mem R(MA/MR): 10232 (21973/36194) [2025-04-30 08:38:09,667 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.0411 Process Time: 0.339 Mem R(MA/MR): 9236 (21973/36194) [2025-04-30 08:38:15,008 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.3473 Process Time: 0.511 Mem R(MA/MR): 17308 (21973/36194) [2025-04-30 08:38:15,930 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.9978 Process Time: 0.259 Mem R(MA/MR): 7954 (21973/36194) [2025-04-30 08:38:20,324 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.9357 Process Time: 0.707 Mem R(MA/MR): 20488 (21973/36194) [2025-04-30 08:38:20,859 INFO hook.py line 449 1619929] Test: [32/50] Loss 3.9627 Process Time: 0.216 Mem R(MA/MR): 4192 (21973/36194) [2025-04-30 08:38:25,081 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.8039 Process Time: 0.508 Mem R(MA/MR): 24982 (21973/36194) [2025-04-30 08:38:26,211 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5689 Process Time: 0.352 Mem R(MA/MR): 9890 (21973/36194) [2025-04-30 08:38:28,218 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.8093 Process Time: 0.453 Mem R(MA/MR): 14416 (21973/36194) [2025-04-30 08:38:28,746 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2618 Process Time: 0.200 Mem R(MA/MR): 6914 (21973/36194) [2025-04-30 08:38:32,822 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8558 Process Time: 1.023 Mem R(MA/MR): 28666 (21973/36194) [2025-04-30 08:38:34,336 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.6776 Process Time: 0.345 Mem R(MA/MR): 10892 (21973/36194) [2025-04-30 08:38:34,828 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2230 Process Time: 0.197 Mem R(MA/MR): 5834 (21973/36194) [2025-04-30 08:38:36,033 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.9565 Process Time: 0.360 Mem R(MA/MR): 10374 (21973/36194) [2025-04-30 08:38:37,212 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.3641 Process Time: 0.446 Mem R(MA/MR): 9228 (21973/36194) [2025-04-30 08:38:37,768 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.7133 Process Time: 0.174 Mem R(MA/MR): 5682 (21973/36194) [2025-04-30 08:38:38,292 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.9040 Process Time: 0.256 Mem R(MA/MR): 5856 (21973/36194) [2025-04-30 08:38:39,022 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1993 Process Time: 0.259 Mem R(MA/MR): 7476 (21973/36194) [2025-04-30 08:38:39,585 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.5785 Process Time: 0.140 Mem R(MA/MR): 5444 (21973/36194) [2025-04-30 08:38:41,483 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.7296 Process Time: 0.235 Mem R(MA/MR): 14938 (21973/36194) [2025-04-30 08:38:49,940 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.4405 Process Time: 0.939 Mem R(MA/MR): 20668 (21973/36194) [2025-04-30 08:39:00,187 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.5436 Process Time: 1.872 Mem R(MA/MR): 35890 (21973/36194) [2025-04-30 08:39:01,329 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9861 Process Time: 0.462 Mem R(MA/MR): 5976 (21973/36194) [2025-04-30 08:39:03,806 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5628 Process Time: 0.552 Mem R(MA/MR): 14050 (21973/36194) [2025-04-30 08:39:08,602 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:39:08,602 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:39:08,602 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] table : 0.296 0.642 0.756 0.883 0.610 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] door : 0.472 0.740 0.892 0.906 0.734 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] ceiling lamp : 0.569 0.747 0.852 0.811 0.735 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] cabinet : 0.338 0.485 0.566 0.561 0.552 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] blinds : 0.573 0.759 0.811 0.850 0.739 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] curtain : 0.440 0.712 0.734 0.875 0.583 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] chair : 0.659 0.805 0.834 0.797 0.770 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] storage cabinet: 0.202 0.353 0.427 0.706 0.480 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] office chair : 0.661 0.712 0.712 0.717 0.792 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] bookshelf : 0.245 0.605 0.605 0.667 0.727 [2025-04-30 08:39:08,602 INFO hook.py line 395 1619929] whiteboard : 0.556 0.738 0.803 0.893 0.714 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] window : 0.144 0.336 0.711 0.500 0.396 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] box : 0.211 0.376 0.547 0.522 0.453 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] monitor : 0.679 0.837 0.867 0.966 0.814 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] shelf : 0.176 0.348 0.510 0.714 0.333 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] heater : 0.438 0.794 0.843 0.967 0.763 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] kitchen cabinet: 0.122 0.273 0.636 0.526 0.400 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] sofa : 0.489 0.715 0.801 1.000 0.667 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] bed : 0.234 0.574 0.761 0.833 0.625 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] trash can : 0.599 0.772 0.752 0.848 0.862 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] book : 0.024 0.046 0.078 0.222 0.097 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] plant : 0.434 0.556 0.650 1.000 0.556 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] blanket : 0.496 0.597 0.636 0.857 0.545 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] tv : 0.934 1.000 1.000 1.000 1.000 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] computer tower : 0.334 0.511 0.657 0.706 0.571 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] refrigerator : 0.230 0.404 0.404 0.667 0.444 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] jacket : 0.135 0.262 0.499 0.300 0.545 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] sink : 0.427 0.702 0.855 0.727 0.727 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] bag : 0.088 0.121 0.167 0.500 0.222 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] picture : 0.162 0.318 0.388 0.765 0.333 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] pillow : 0.548 0.739 0.739 0.923 0.632 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] towel : 0.214 0.309 0.529 0.519 0.368 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] suitcase : 0.432 0.505 0.505 1.000 0.429 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] backpack : 0.466 0.589 0.589 1.000 0.538 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] crate : 0.025 0.076 0.467 0.235 0.364 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] keyboard : 0.504 0.701 0.785 0.867 0.667 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] toilet : 0.868 1.000 1.000 1.000 1.000 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] printer : 0.272 0.309 0.329 0.500 0.333 [2025-04-30 08:39:08,603 INFO hook.py line 395 1619929] poster : 0.001 0.006 0.008 0.111 0.111 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] painting : 0.038 0.038 0.050 0.077 1.000 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] microwave : 0.590 0.774 0.950 1.000 0.625 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] shoes : 0.119 0.227 0.560 0.667 0.341 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] socket : 0.188 0.463 0.677 0.692 0.529 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] bottle : 0.075 0.184 0.366 0.382 0.313 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] bucket : 0.007 0.007 0.007 0.100 0.143 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] cushion : 0.039 0.085 0.171 0.250 0.333 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] basket : 0.009 0.024 0.024 0.333 0.143 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] telephone : 0.344 0.583 0.599 0.769 0.588 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] laptop : 0.407 0.708 0.809 1.000 0.500 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] plant pot : 0.132 0.316 0.495 0.727 0.500 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] exhaust fan : 0.206 0.362 0.362 0.857 0.400 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] cup : 0.240 0.397 0.419 0.800 0.364 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] coat hanger : 0.264 0.750 0.750 1.000 0.750 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] light switch : 0.242 0.505 0.633 0.745 0.538 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] speaker : 0.560 0.611 0.700 0.875 0.636 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] kettle : 0.221 0.264 0.264 0.667 0.333 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] smoke detector : 0.675 0.850 0.855 0.905 0.792 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] power strip : 0.068 0.106 0.151 0.500 0.300 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] paper bag : 0.054 0.056 0.062 0.111 1.000 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] mouse : 0.508 0.708 0.769 1.000 0.625 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] cutting board : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] toilet paper : 0.261 0.447 0.600 0.889 0.471 [2025-04-30 08:39:08,604 INFO hook.py line 395 1619929] paper towel : 0.166 0.198 0.198 0.667 0.250 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.396 0.000 0.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] tap : 0.119 0.296 0.651 0.444 0.444 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] soap dispenser : 0.602 0.800 0.800 1.000 0.800 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] bowl : 0.333 0.333 0.333 1.000 0.333 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] tissue box : 0.011 0.050 0.062 0.200 0.500 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] whiteboard eraser: 0.147 0.399 0.405 0.667 0.667 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] toilet brush : 0.462 0.667 0.833 1.000 0.667 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] headphones : 0.556 1.000 1.000 1.000 1.000 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] stapler : 0.008 0.034 0.040 0.100 0.667 [2025-04-30 08:39:08,605 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:39:08,605 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:39:08,605 INFO hook.py line 404 1619929] average : 0.290 0.431 0.508 0.632 0.497 [2025-04-30 08:39:08,605 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:39:08,606 INFO hook.py line 480 1619929] Total Process Time: 22.684 s [2025-04-30 08:39:08,606 INFO hook.py line 481 1619929] Average Process Time: 452.320 ms [2025-04-30 08:39:08,606 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:39:08,655 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 08:39:08,660 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:40:44,902 INFO hook.py line 650 1619929] Train: [505/512][50/242] Data 0.016 (0.039) Batch 1.489 (1.530) Remain 00:48:05 loss: 4.4569 Lr: 7.11808e-06 Mem R(MA/MR): 20848 (21973/36194) [2025-04-30 08:41:58,207 INFO hook.py line 650 1619929] Train: [505/512][100/242] Data 0.018 (0.027) Batch 1.575 (1.497) Remain 00:45:48 loss: 4.0239 Lr: 6.95276e-06 Mem R(MA/MR): 22734 (21973/36194) [2025-04-30 08:43:10,551 INFO hook.py line 650 1619929] Train: [505/512][150/242] Data 0.017 (0.024) Batch 1.646 (1.480) Remain 00:44:03 loss: 3.6656 Lr: 6.78699e-06 Mem R(MA/MR): 24800 (21973/36194) [2025-04-30 08:44:22,599 INFO hook.py line 650 1619929] Train: [505/512][200/242] Data 0.016 (0.022) Batch 1.368 (1.470) Remain 00:42:32 loss: 3.4770 Lr: 6.62078e-06 Mem R(MA/MR): 24800 (21973/36194) [2025-04-30 08:45:20,215 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2151 loss_mask: 0.0293 loss_dice: 1.6604 loss_score: 0.0000 loss_bbox: 0.0443 loss_sp_cls: 0.6633 loss: 4.2133 [2025-04-30 08:45:23,974 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:45:26,298 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.2536 Process Time: 0.286 Mem R(MA/MR): 4364 (21973/36194) [2025-04-30 08:45:27,923 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6519 Process Time: 0.448 Mem R(MA/MR): 7238 (21973/36194) [2025-04-30 08:45:29,564 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.6581 Process Time: 0.619 Mem R(MA/MR): 9706 (21973/36194) [2025-04-30 08:45:37,979 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.0591 Process Time: 1.185 Mem R(MA/MR): 19828 (21973/36194) [2025-04-30 08:45:38,792 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.2207 Process Time: 0.327 Mem R(MA/MR): 7050 (21973/36194) [2025-04-30 08:45:40,553 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0885 Process Time: 0.689 Mem R(MA/MR): 11230 (21973/36194) [2025-04-30 08:45:41,531 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.7613 Process Time: 0.448 Mem R(MA/MR): 6366 (21973/36194) [2025-04-30 08:45:42,077 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.0118 Process Time: 0.165 Mem R(MA/MR): 4404 (21973/36194) [2025-04-30 08:45:43,087 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7367 Process Time: 0.278 Mem R(MA/MR): 11474 (21973/36194) [2025-04-30 08:45:45,045 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4157 Process Time: 0.383 Mem R(MA/MR): 9446 (21973/36194) [2025-04-30 08:45:48,217 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0100 Process Time: 0.749 Mem R(MA/MR): 18854 (21973/36194) [2025-04-30 08:45:50,896 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.5360 Process Time: 0.335 Mem R(MA/MR): 15372 (21973/36194) [2025-04-30 08:45:52,210 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0793 Process Time: 0.394 Mem R(MA/MR): 8716 (21973/36194) [2025-04-30 08:45:52,637 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1102 Process Time: 0.158 Mem R(MA/MR): 4738 (21973/36194) [2025-04-30 08:45:55,982 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.7800 Process Time: 0.499 Mem R(MA/MR): 16588 (21973/36194) [2025-04-30 08:45:57,961 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.0312 Process Time: 0.540 Mem R(MA/MR): 14628 (21973/36194) [2025-04-30 08:45:58,673 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2030 Process Time: 0.183 Mem R(MA/MR): 6684 (21973/36194) [2025-04-30 08:45:59,998 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.8277 Process Time: 0.399 Mem R(MA/MR): 8152 (21973/36194) [2025-04-30 08:46:01,422 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.7892 Process Time: 0.268 Mem R(MA/MR): 5878 (21973/36194) [2025-04-30 08:46:03,121 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.2228 Process Time: 0.296 Mem R(MA/MR): 11440 (21973/36194) [2025-04-30 08:46:13,333 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.2525 Process Time: 1.362 Mem R(MA/MR): 23784 (21973/36194) [2025-04-30 08:46:14,019 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4737 Process Time: 0.286 Mem R(MA/MR): 6722 (21973/36194) [2025-04-30 08:46:24,766 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.7774 Process Time: 0.669 Mem R(MA/MR): 10178 (21973/36194) [2025-04-30 08:46:25,226 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8636 Process Time: 0.132 Mem R(MA/MR): 5330 (21973/36194) [2025-04-30 08:46:26,373 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9237 Process Time: 0.439 Mem R(MA/MR): 9234 (21973/36194) [2025-04-30 08:46:32,828 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.6712 Process Time: 1.150 Mem R(MA/MR): 31836 (21973/36194) [2025-04-30 08:46:35,200 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4339 Process Time: 0.537 Mem R(MA/MR): 10012 (21973/36194) [2025-04-30 08:46:36,273 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9592 Process Time: 0.213 Mem R(MA/MR): 8840 (21973/36194) [2025-04-30 08:46:41,191 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6703 Process Time: 0.577 Mem R(MA/MR): 16968 (21973/36194) [2025-04-30 08:46:42,285 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.2150 Process Time: 0.357 Mem R(MA/MR): 7628 (21973/36194) [2025-04-30 08:46:45,836 INFO hook.py line 449 1619929] Test: [31/50] Loss 6.9523 Process Time: 0.459 Mem R(MA/MR): 20614 (21973/36194) [2025-04-30 08:46:46,299 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3473 Process Time: 0.167 Mem R(MA/MR): 4016 (21973/36194) [2025-04-30 08:46:50,120 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.5260 Process Time: 0.492 Mem R(MA/MR): 24822 (21973/36194) [2025-04-30 08:46:51,268 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4972 Process Time: 0.391 Mem R(MA/MR): 9770 (21973/36194) [2025-04-30 08:46:53,353 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.0951 Process Time: 0.360 Mem R(MA/MR): 14048 (21973/36194) [2025-04-30 08:46:53,959 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.7538 Process Time: 0.214 Mem R(MA/MR): 6508 (21973/36194) [2025-04-30 08:46:58,067 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8252 Process Time: 0.863 Mem R(MA/MR): 28210 (21973/36194) [2025-04-30 08:46:59,696 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.5447 Process Time: 0.370 Mem R(MA/MR): 10684 (21973/36194) [2025-04-30 08:47:00,248 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.0889 Process Time: 0.212 Mem R(MA/MR): 5480 (21973/36194) [2025-04-30 08:47:01,421 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5730 Process Time: 0.301 Mem R(MA/MR): 10072 (21973/36194) [2025-04-30 08:47:02,499 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5269 Process Time: 0.261 Mem R(MA/MR): 8952 (21973/36194) [2025-04-30 08:47:03,108 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3474 Process Time: 0.254 Mem R(MA/MR): 5462 (21973/36194) [2025-04-30 08:47:03,676 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6814 Process Time: 0.223 Mem R(MA/MR): 5502 (21973/36194) [2025-04-30 08:47:04,447 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.5357 Process Time: 0.270 Mem R(MA/MR): 7076 (21973/36194) [2025-04-30 08:47:05,223 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.4487 Process Time: 0.286 Mem R(MA/MR): 5234 (21973/36194) [2025-04-30 08:47:07,683 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.4204 Process Time: 0.468 Mem R(MA/MR): 14476 (21973/36194) [2025-04-30 08:47:16,283 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.9321 Process Time: 0.714 Mem R(MA/MR): 20274 (21973/36194) [2025-04-30 08:47:26,945 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.9889 Process Time: 1.760 Mem R(MA/MR): 35666 (21973/36194) [2025-04-30 08:47:27,799 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.8585 Process Time: 0.307 Mem R(MA/MR): 5782 (21973/36194) [2025-04-30 08:47:30,239 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0170 Process Time: 0.473 Mem R(MA/MR): 13638 (21973/36194) [2025-04-30 08:47:34,018 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:47:34,018 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:47:34,018 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] table : 0.284 0.618 0.758 0.810 0.625 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] door : 0.475 0.774 0.910 0.894 0.747 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] ceiling lamp : 0.581 0.771 0.863 0.865 0.740 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] cabinet : 0.368 0.499 0.562 0.557 0.507 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] blinds : 0.532 0.736 0.825 0.810 0.739 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] curtain : 0.382 0.577 0.729 0.727 0.667 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] chair : 0.686 0.815 0.847 0.784 0.758 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] storage cabinet: 0.203 0.325 0.464 0.536 0.600 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] office chair : 0.687 0.730 0.730 0.727 0.833 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] bookshelf : 0.217 0.646 0.646 0.643 0.818 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] whiteboard : 0.564 0.728 0.819 0.957 0.629 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] window : 0.148 0.321 0.641 0.589 0.363 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] box : 0.211 0.380 0.533 0.583 0.409 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] monitor : 0.643 0.806 0.861 0.948 0.786 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] shelf : 0.124 0.276 0.493 0.526 0.333 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] heater : 0.465 0.799 0.820 0.933 0.737 [2025-04-30 08:47:34,018 INFO hook.py line 395 1619929] kitchen cabinet: 0.128 0.331 0.704 0.565 0.520 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] sofa : 0.469 0.572 0.883 0.700 0.583 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] bed : 0.320 0.625 0.911 1.000 0.625 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] trash can : 0.582 0.745 0.761 0.836 0.862 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] book : 0.024 0.046 0.084 0.216 0.090 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] plant : 0.471 0.693 0.807 1.000 0.667 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] blanket : 0.564 0.676 0.770 0.875 0.636 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] tv : 0.886 1.000 1.000 1.000 1.000 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] computer tower : 0.259 0.490 0.634 0.875 0.500 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] refrigerator : 0.213 0.379 0.385 1.000 0.333 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] jacket : 0.036 0.108 0.370 0.217 0.455 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] sink : 0.471 0.695 0.891 0.800 0.727 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] bag : 0.101 0.134 0.204 0.500 0.259 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] picture : 0.124 0.269 0.389 0.560 0.359 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] pillow : 0.618 0.810 0.810 0.929 0.684 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] towel : 0.201 0.327 0.441 0.469 0.395 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] suitcase : 0.409 0.481 0.481 1.000 0.429 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] backpack : 0.299 0.377 0.488 0.600 0.462 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] crate : 0.055 0.195 0.513 0.417 0.455 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] keyboard : 0.547 0.693 0.776 0.750 0.692 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] toilet : 0.880 1.000 1.000 1.000 1.000 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] printer : 0.263 0.283 0.296 1.000 0.222 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.003 0.040 0.111 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] painting : 0.063 0.071 0.071 0.143 1.000 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] microwave : 0.506 0.586 0.875 1.000 0.500 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] shoes : 0.120 0.309 0.628 0.667 0.439 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] socket : 0.196 0.477 0.665 0.716 0.521 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] bottle : 0.141 0.211 0.349 0.338 0.313 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] bucket : 0.064 0.086 0.088 0.211 0.571 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] cushion : 0.075 0.084 0.206 0.222 0.333 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] basket : 0.019 0.024 0.024 0.333 0.143 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] telephone : 0.485 0.731 0.734 1.000 0.706 [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:47:34,019 INFO hook.py line 395 1619929] laptop : 0.421 0.689 0.744 0.583 0.875 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] plant pot : 0.152 0.402 0.588 0.588 0.625 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] exhaust fan : 0.201 0.355 0.355 0.750 0.400 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] cup : 0.255 0.419 0.458 0.760 0.432 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] coat hanger : 0.215 0.750 0.750 1.000 0.750 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] light switch : 0.219 0.462 0.627 0.750 0.462 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] speaker : 0.503 0.529 0.621 0.833 0.455 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] table lamp : 0.667 1.000 1.000 1.000 1.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] kettle : 0.357 0.425 0.425 0.600 0.500 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] smoke detector : 0.672 0.860 0.862 0.909 0.833 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] power strip : 0.057 0.101 0.131 0.429 0.300 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] mouse : 0.438 0.637 0.720 0.905 0.594 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] toilet paper : 0.293 0.440 0.570 1.000 0.412 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] paper towel : 0.008 0.016 0.177 0.250 0.125 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.342 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] tap : 0.185 0.353 0.734 0.500 0.444 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.018 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] soap dispenser : 0.530 0.697 0.697 0.800 0.800 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] bowl : 0.068 0.083 0.083 0.500 0.333 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] whiteboard eraser: 0.168 0.384 0.391 0.667 0.667 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] toilet brush : 0.424 0.629 0.899 0.800 0.667 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] spray bottle : 0.005 0.007 0.007 0.056 0.250 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] headphones : 0.333 1.000 1.000 1.000 1.000 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] stapler : 0.007 0.064 0.097 0.182 0.667 [2025-04-30 08:47:34,020 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:47:34,020 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:47:34,020 INFO hook.py line 404 1619929] average : 0.286 0.431 0.522 0.619 0.503 [2025-04-30 08:47:34,020 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:47:34,021 INFO hook.py line 480 1619929] Total Process Time: 23.213 s [2025-04-30 08:47:34,021 INFO hook.py line 481 1619929] Average Process Time: 467.891 ms [2025-04-30 08:47:34,021 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:47:34,048 INFO hook.py line 685 1619929] Currently Best AP50: 0.432 [2025-04-30 08:47:34,053 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:49:10,816 INFO hook.py line 650 1619929] Train: [506/512][50/242] Data 0.016 (0.038) Batch 1.374 (1.510) Remain 00:41:22 loss: 3.3661 Lr: 6.31372e-06 Mem R(MA/MR): 22408 (21973/36194) [2025-04-30 08:50:23,526 INFO hook.py line 650 1619929] Train: [506/512][100/242] Data 0.016 (0.027) Batch 1.338 (1.481) Remain 00:39:20 loss: 3.9637 Lr: 6.14614e-06 Mem R(MA/MR): 24450 (21973/36194) [2025-04-30 08:51:33,880 INFO hook.py line 650 1619929] Train: [506/512][150/242] Data 0.016 (0.023) Batch 1.362 (1.456) Remain 00:37:27 loss: 4.1957 Lr: 5.97806e-06 Mem R(MA/MR): 24450 (21973/36194) [2025-04-30 08:52:46,815 INFO hook.py line 650 1619929] Train: [506/512][200/242] Data 0.016 (0.022) Batch 1.548 (1.457) Remain 00:36:16 loss: 4.9022 Lr: 5.80945e-06 Mem R(MA/MR): 24450 (21973/36194) [2025-04-30 08:53:45,240 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2151 loss_mask: 0.0294 loss_dice: 1.6786 loss_score: 0.0000 loss_bbox: 0.0449 loss_sp_cls: 0.6663 loss: 4.2462 [2025-04-30 08:53:47,612 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 08:53:50,158 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1419 Process Time: 0.383 Mem R(MA/MR): 4734 (21973/36194) [2025-04-30 08:53:51,719 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.6527 Process Time: 0.444 Mem R(MA/MR): 7486 (21973/36194) [2025-04-30 08:53:53,435 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2492 Process Time: 0.669 Mem R(MA/MR): 10266 (21973/36194) [2025-04-30 08:54:00,953 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4705 Process Time: 0.840 Mem R(MA/MR): 19682 (21973/36194) [2025-04-30 08:54:01,872 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.6104 Process Time: 0.286 Mem R(MA/MR): 7160 (21973/36194) [2025-04-30 08:54:03,356 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.7700 Process Time: 0.505 Mem R(MA/MR): 11800 (21973/36194) [2025-04-30 08:54:04,202 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0133 Process Time: 0.359 Mem R(MA/MR): 6774 (21973/36194) [2025-04-30 08:54:04,660 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.3475 Process Time: 0.138 Mem R(MA/MR): 4726 (21973/36194) [2025-04-30 08:54:05,759 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.6322 Process Time: 0.410 Mem R(MA/MR): 12024 (21973/36194) [2025-04-30 08:54:07,327 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.7554 Process Time: 0.340 Mem R(MA/MR): 9586 (21973/36194) [2025-04-30 08:54:09,838 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0915 Process Time: 0.536 Mem R(MA/MR): 19046 (21973/36194) [2025-04-30 08:54:12,218 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3027 Process Time: 0.462 Mem R(MA/MR): 15692 (21973/36194) [2025-04-30 08:54:13,555 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0269 Process Time: 0.333 Mem R(MA/MR): 8810 (21973/36194) [2025-04-30 08:54:13,984 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1615 Process Time: 0.164 Mem R(MA/MR): 4984 (21973/36194) [2025-04-30 08:54:16,805 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.6656 Process Time: 0.429 Mem R(MA/MR): 16938 (21973/36194) [2025-04-30 08:54:18,426 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4318 Process Time: 0.319 Mem R(MA/MR): 14900 (21973/36194) [2025-04-30 08:54:19,048 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3700 Process Time: 0.189 Mem R(MA/MR): 7076 (21973/36194) [2025-04-30 08:54:19,986 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.8683 Process Time: 0.296 Mem R(MA/MR): 8240 (21973/36194) [2025-04-30 08:54:21,366 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9320 Process Time: 0.217 Mem R(MA/MR): 6356 (21973/36194) [2025-04-30 08:54:23,288 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.2809 Process Time: 0.466 Mem R(MA/MR): 12066 (21973/36194) [2025-04-30 08:54:33,441 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.6861 Process Time: 1.149 Mem R(MA/MR): 23982 (21973/36194) [2025-04-30 08:54:34,120 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5092 Process Time: 0.231 Mem R(MA/MR): 7150 (21973/36194) [2025-04-30 08:54:44,008 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.7316 Process Time: 0.437 Mem R(MA/MR): 10554 (21973/36194) [2025-04-30 08:54:44,627 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7127 Process Time: 0.185 Mem R(MA/MR): 5246 (21973/36194) [2025-04-30 08:54:45,795 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0423 Process Time: 0.383 Mem R(MA/MR): 9710 (21973/36194) [2025-04-30 08:54:53,206 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.9927 Process Time: 1.340 Mem R(MA/MR): 31374 (21973/36194) [2025-04-30 08:54:55,389 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4191 Process Time: 0.298 Mem R(MA/MR): 10366 (21973/36194) [2025-04-30 08:54:56,622 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.8364 Process Time: 0.297 Mem R(MA/MR): 9010 (21973/36194) [2025-04-30 08:55:01,960 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.5490 Process Time: 0.555 Mem R(MA/MR): 17074 (21973/36194) [2025-04-30 08:55:02,880 INFO hook.py line 449 1619929] Test: [30/50] Loss 5.9642 Process Time: 0.248 Mem R(MA/MR): 7850 (21973/36194) [2025-04-30 08:55:06,811 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.2761 Process Time: 0.631 Mem R(MA/MR): 20502 (21973/36194) [2025-04-30 08:55:07,306 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1309 Process Time: 0.152 Mem R(MA/MR): 4154 (21973/36194) [2025-04-30 08:55:11,028 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.9981 Process Time: 0.460 Mem R(MA/MR): 24636 (21973/36194) [2025-04-30 08:55:12,085 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6960 Process Time: 0.351 Mem R(MA/MR): 10096 (21973/36194) [2025-04-30 08:55:13,855 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.1080 Process Time: 0.318 Mem R(MA/MR): 14542 (21973/36194) [2025-04-30 08:55:14,363 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.5139 Process Time: 0.194 Mem R(MA/MR): 6938 (21973/36194) [2025-04-30 08:55:18,072 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8709 Process Time: 0.839 Mem R(MA/MR): 28590 (21973/36194) [2025-04-30 08:55:20,010 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.8975 Process Time: 0.499 Mem R(MA/MR): 10940 (21973/36194) [2025-04-30 08:55:20,577 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2328 Process Time: 0.199 Mem R(MA/MR): 5718 (21973/36194) [2025-04-30 08:55:21,784 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5520 Process Time: 0.332 Mem R(MA/MR): 10392 (21973/36194) [2025-04-30 08:55:23,160 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.3866 Process Time: 0.481 Mem R(MA/MR): 9126 (21973/36194) [2025-04-30 08:55:23,803 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.7516 Process Time: 0.210 Mem R(MA/MR): 5754 (21973/36194) [2025-04-30 08:55:24,307 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7613 Process Time: 0.169 Mem R(MA/MR): 5796 (21973/36194) [2025-04-30 08:55:24,964 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.7886 Process Time: 0.208 Mem R(MA/MR): 7468 (21973/36194) [2025-04-30 08:55:25,728 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3291 Process Time: 0.218 Mem R(MA/MR): 5268 (21973/36194) [2025-04-30 08:55:28,132 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.7272 Process Time: 0.443 Mem R(MA/MR): 15116 (21973/36194) [2025-04-30 08:55:36,915 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.4677 Process Time: 1.053 Mem R(MA/MR): 20372 (21973/36194) [2025-04-30 08:55:49,034 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.8432 Process Time: 1.772 Mem R(MA/MR): 34822 (21973/36194) [2025-04-30 08:55:49,933 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9975 Process Time: 0.277 Mem R(MA/MR): 6140 (21973/36194) [2025-04-30 08:55:52,214 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.8956 Process Time: 0.377 Mem R(MA/MR): 14254 (21973/36194) [2025-04-30 08:55:56,037 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 08:55:56,037 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 08:55:56,037 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] table : 0.305 0.638 0.766 0.817 0.625 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] door : 0.464 0.766 0.900 0.906 0.734 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] ceiling lamp : 0.574 0.755 0.845 0.840 0.751 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] cabinet : 0.345 0.506 0.538 0.625 0.522 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] blinds : 0.611 0.793 0.841 0.741 0.870 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] curtain : 0.380 0.617 0.719 0.529 0.750 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] chair : 0.668 0.799 0.829 0.947 0.656 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] storage cabinet: 0.219 0.335 0.439 0.600 0.480 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] office chair : 0.606 0.634 0.634 0.692 0.750 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] bookshelf : 0.360 0.710 0.715 0.889 0.727 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] whiteboard : 0.571 0.787 0.787 0.893 0.714 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] window : 0.146 0.301 0.639 0.434 0.396 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] box : 0.209 0.362 0.532 0.558 0.398 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] monitor : 0.646 0.812 0.852 0.966 0.814 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] shelf : 0.165 0.347 0.511 0.667 0.333 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] heater : 0.457 0.796 0.803 0.882 0.789 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] kitchen cabinet: 0.182 0.417 0.661 0.632 0.480 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] sofa : 0.494 0.557 0.819 0.778 0.583 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] bed : 0.261 0.625 0.923 1.000 0.625 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] trash can : 0.562 0.729 0.743 0.857 0.831 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] book : 0.022 0.044 0.088 0.488 0.075 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] plant : 0.461 0.648 0.729 1.000 0.611 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] blanket : 0.522 0.737 0.745 0.875 0.636 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] tv : 0.922 1.000 1.000 1.000 1.000 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] computer tower : 0.279 0.438 0.636 0.636 0.500 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] refrigerator : 0.220 0.379 0.379 1.000 0.333 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] jacket : 0.079 0.259 0.514 0.455 0.455 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] sink : 0.484 0.835 0.928 0.857 0.818 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] bag : 0.067 0.092 0.176 0.400 0.222 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] picture : 0.141 0.277 0.353 0.619 0.333 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] pillow : 0.546 0.728 0.728 0.923 0.632 [2025-04-30 08:55:56,038 INFO hook.py line 395 1619929] towel : 0.191 0.308 0.496 0.348 0.421 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] suitcase : 0.389 0.463 0.477 0.571 0.571 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] backpack : 0.425 0.583 0.583 0.875 0.538 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] crate : 0.072 0.219 0.542 0.500 0.455 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] keyboard : 0.517 0.702 0.742 0.897 0.667 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] toilet : 0.867 1.000 1.000 1.000 1.000 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] printer : 0.539 0.603 0.629 0.750 0.667 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] poster : 0.000 0.004 0.006 0.071 0.111 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] microwave : 0.527 0.706 0.845 1.000 0.625 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] shoes : 0.098 0.266 0.601 0.654 0.415 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] socket : 0.195 0.472 0.686 0.782 0.486 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] bottle : 0.133 0.253 0.354 0.565 0.313 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] bucket : 0.027 0.027 0.060 0.167 0.286 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] cushion : 0.079 0.156 0.258 0.300 0.500 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] basket : 0.079 0.143 0.163 1.000 0.143 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] shoe rack : 0.014 0.125 0.500 0.500 0.500 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] telephone : 0.331 0.538 0.560 0.667 0.588 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] laptop : 0.372 0.609 0.750 0.714 0.625 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] plant pot : 0.119 0.247 0.383 0.636 0.438 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] exhaust fan : 0.200 0.355 0.362 0.750 0.400 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] cup : 0.228 0.360 0.422 0.727 0.364 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] coat hanger : 0.317 0.750 0.677 1.000 0.750 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] light switch : 0.256 0.528 0.622 0.745 0.538 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] speaker : 0.467 0.499 0.589 0.778 0.636 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] table lamp : 0.667 1.000 1.000 1.000 1.000 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] smoke detector : 0.649 0.815 0.818 0.905 0.792 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] power strip : 0.065 0.099 0.113 0.300 0.300 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] mouse : 0.472 0.694 0.753 0.840 0.656 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] cutting board : 0.042 0.062 0.062 0.500 0.250 [2025-04-30 08:55:56,039 INFO hook.py line 395 1619929] toilet paper : 0.231 0.404 0.503 0.875 0.412 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] paper towel : 0.125 0.125 0.125 1.000 0.125 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] tap : 0.172 0.431 0.778 0.833 0.556 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] soap dispenser : 0.532 0.800 0.800 1.000 0.800 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] bowl : 0.231 0.472 0.472 0.500 0.667 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] tissue box : 0.056 0.125 0.500 0.500 0.500 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] whiteboard eraser: 0.152 0.373 0.411 0.750 0.500 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] toilet brush : 0.416 0.667 0.833 1.000 0.667 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] headphones : 0.310 0.792 1.000 0.667 1.000 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] stapler : 0.006 0.009 0.043 0.056 0.333 [2025-04-30 08:55:56,040 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 08:55:56,040 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 08:55:56,040 INFO hook.py line 404 1619929] average : 0.288 0.436 0.519 0.634 0.492 [2025-04-30 08:55:56,040 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 08:55:56,040 INFO hook.py line 480 1619929] Total Process Time: 22.091 s [2025-04-30 08:55:56,040 INFO hook.py line 481 1619929] Average Process Time: 443.026 ms [2025-04-30 08:55:56,040 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 08:55:56,087 INFO hook.py line 680 1619929] Best validation AP50 updated to: 0.436 [2025-04-30 08:55:56,092 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 08:55:56,092 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 08:57:32,752 INFO hook.py line 650 1619929] Train: [507/512][50/242] Data 0.017 (0.017) Batch 1.497 (1.533) Remain 00:35:49 loss: 4.0597 Lr: 5.49777e-06 Mem R(MA/MR): 26360 (21973/36194) [2025-04-30 08:58:49,133 INFO hook.py line 650 1619929] Train: [507/512][100/242] Data 0.018 (0.017) Batch 1.585 (1.530) Remain 00:34:28 loss: 5.1660 Lr: 5.32756e-06 Mem R(MA/MR): 28316 (21973/36194) [2025-04-30 09:00:02,669 INFO hook.py line 650 1619929] Train: [507/512][150/242] Data 0.018 (0.017) Batch 1.543 (1.510) Remain 00:32:46 loss: 5.0036 Lr: 5.15674e-06 Mem R(MA/MR): 28316 (21973/36194) [2025-04-30 09:01:17,398 INFO hook.py line 650 1619929] Train: [507/512][200/242] Data 0.014 (0.021) Batch 1.305 (1.506) Remain 00:31:25 loss: 5.2538 Lr: 4.98529e-06 Mem R(MA/MR): 28316 (21973/36194) [2025-04-30 09:02:14,853 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2157 loss_mask: 0.0292 loss_dice: 1.6822 loss_score: 0.0000 loss_bbox: 0.0441 loss_sp_cls: 0.6652 loss: 4.2446 [2025-04-30 09:02:18,635 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 09:02:20,981 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0142 Process Time: 0.316 Mem R(MA/MR): 4454 (21973/36194) [2025-04-30 09:02:22,580 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.7552 Process Time: 0.413 Mem R(MA/MR): 7274 (21973/36194) [2025-04-30 09:02:24,451 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3051 Process Time: 0.795 Mem R(MA/MR): 10012 (21973/36194) [2025-04-30 09:02:32,841 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.4336 Process Time: 1.040 Mem R(MA/MR): 20104 (21973/36194) [2025-04-30 09:02:33,720 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3773 Process Time: 0.343 Mem R(MA/MR): 7172 (21973/36194) [2025-04-30 09:02:35,218 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.9137 Process Time: 0.475 Mem R(MA/MR): 11338 (21973/36194) [2025-04-30 09:02:36,036 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.6067 Process Time: 0.376 Mem R(MA/MR): 6420 (21973/36194) [2025-04-30 09:02:36,587 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2370 Process Time: 0.202 Mem R(MA/MR): 4488 (21973/36194) [2025-04-30 09:02:37,565 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8298 Process Time: 0.335 Mem R(MA/MR): 11518 (21973/36194) [2025-04-30 09:02:39,214 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.8206 Process Time: 0.398 Mem R(MA/MR): 9556 (21973/36194) [2025-04-30 09:02:41,670 INFO hook.py line 449 1619929] Test: [11/50] Loss 12.0125 Process Time: 0.498 Mem R(MA/MR): 18856 (21973/36194) [2025-04-30 09:02:44,367 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.5819 Process Time: 0.662 Mem R(MA/MR): 15588 (21973/36194) [2025-04-30 09:02:45,640 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.2974 Process Time: 0.378 Mem R(MA/MR): 8788 (21973/36194) [2025-04-30 09:02:46,047 INFO hook.py line 449 1619929] Test: [14/50] Loss 2.9652 Process Time: 0.141 Mem R(MA/MR): 4836 (21973/36194) [2025-04-30 09:02:49,558 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.5118 Process Time: 0.547 Mem R(MA/MR): 16552 (21973/36194) [2025-04-30 09:02:51,425 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.6292 Process Time: 0.450 Mem R(MA/MR): 14446 (21973/36194) [2025-04-30 09:02:52,477 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.2716 Process Time: 0.435 Mem R(MA/MR): 6784 (21973/36194) [2025-04-30 09:02:53,379 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.0804 Process Time: 0.256 Mem R(MA/MR): 8176 (21973/36194) [2025-04-30 09:02:55,093 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0448 Process Time: 0.360 Mem R(MA/MR): 6070 (21973/36194) [2025-04-30 09:02:56,879 INFO hook.py line 449 1619929] Test: [20/50] Loss 9.8271 Process Time: 0.317 Mem R(MA/MR): 11522 (21973/36194) [2025-04-30 09:03:06,013 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.8272 Process Time: 1.053 Mem R(MA/MR): 23920 (21973/36194) [2025-04-30 09:03:06,721 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4795 Process Time: 0.288 Mem R(MA/MR): 7004 (21973/36194) [2025-04-30 09:03:17,313 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.6980 Process Time: 0.302 Mem R(MA/MR): 10292 (21973/36194) [2025-04-30 09:03:17,857 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.6701 Process Time: 0.168 Mem R(MA/MR): 5384 (21973/36194) [2025-04-30 09:03:19,002 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9299 Process Time: 0.456 Mem R(MA/MR): 9410 (21973/36194) [2025-04-30 09:03:26,167 INFO hook.py line 449 1619929] Test: [26/50] Loss 11.9210 Process Time: 1.524 Mem R(MA/MR): 31880 (21973/36194) [2025-04-30 09:03:28,623 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4500 Process Time: 0.355 Mem R(MA/MR): 10084 (21973/36194) [2025-04-30 09:03:30,045 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.1041 Process Time: 0.425 Mem R(MA/MR): 8948 (21973/36194) [2025-04-30 09:03:35,546 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.4841 Process Time: 0.461 Mem R(MA/MR): 17050 (21973/36194) [2025-04-30 09:03:36,636 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1719 Process Time: 0.367 Mem R(MA/MR): 7748 (21973/36194) [2025-04-30 09:03:40,784 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.8915 Process Time: 0.924 Mem R(MA/MR): 20832 (21973/36194) [2025-04-30 09:03:41,055 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2972 Process Time: 0.111 Mem R(MA/MR): 4122 (21973/36194) [2025-04-30 09:03:44,867 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.1175 Process Time: 0.374 Mem R(MA/MR): 24904 (21973/36194) [2025-04-30 09:03:45,996 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.3385 Process Time: 0.299 Mem R(MA/MR): 9872 (21973/36194) [2025-04-30 09:03:48,595 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.9013 Process Time: 0.710 Mem R(MA/MR): 14028 (21973/36194) [2025-04-30 09:03:49,247 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.0266 Process Time: 0.259 Mem R(MA/MR): 6664 (21973/36194) [2025-04-30 09:03:53,559 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.5002 Process Time: 1.095 Mem R(MA/MR): 28564 (21973/36194) [2025-04-30 09:03:55,966 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.6739 Process Time: 0.561 Mem R(MA/MR): 10816 (21973/36194) [2025-04-30 09:03:56,646 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2867 Process Time: 0.286 Mem R(MA/MR): 5588 (21973/36194) [2025-04-30 09:03:58,222 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.3407 Process Time: 0.589 Mem R(MA/MR): 10214 (21973/36194) [2025-04-30 09:03:59,406 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.3211 Process Time: 0.313 Mem R(MA/MR): 9068 (21973/36194) [2025-04-30 09:04:00,002 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.1391 Process Time: 0.191 Mem R(MA/MR): 5566 (21973/36194) [2025-04-30 09:04:00,449 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.8396 Process Time: 0.157 Mem R(MA/MR): 5614 (21973/36194) [2025-04-30 09:04:01,088 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.1636 Process Time: 0.177 Mem R(MA/MR): 7210 (21973/36194) [2025-04-30 09:04:02,178 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.1727 Process Time: 0.466 Mem R(MA/MR): 5352 (21973/36194) [2025-04-30 09:04:04,783 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.6307 Process Time: 0.602 Mem R(MA/MR): 14502 (21973/36194) [2025-04-30 09:04:13,511 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1693 Process Time: 1.148 Mem R(MA/MR): 20592 (21973/36194) [2025-04-30 09:04:24,777 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.1702 Process Time: 2.007 Mem R(MA/MR): 35500 (21973/36194) [2025-04-30 09:04:25,304 INFO hook.py line 449 1619929] Test: [49/50] Loss 2.9169 Process Time: 0.158 Mem R(MA/MR): 5690 (21973/36194) [2025-04-30 09:04:27,450 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2120 Process Time: 0.349 Mem R(MA/MR): 13734 (21973/36194) [2025-04-30 09:04:31,192 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 09:04:31,192 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 09:04:31,192 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] table : 0.293 0.627 0.753 0.821 0.640 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] door : 0.462 0.740 0.883 0.897 0.772 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] ceiling lamp : 0.579 0.757 0.856 0.888 0.702 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] cabinet : 0.341 0.456 0.544 0.620 0.463 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] blinds : 0.620 0.851 0.829 0.800 0.870 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] curtain : 0.471 0.644 0.812 0.636 0.583 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] chair : 0.665 0.791 0.831 0.772 0.779 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] storage cabinet: 0.291 0.400 0.579 0.688 0.440 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] office chair : 0.598 0.615 0.629 0.729 0.729 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] bookshelf : 0.255 0.645 0.639 0.727 0.727 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] whiteboard : 0.534 0.760 0.760 1.000 0.714 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] window : 0.135 0.323 0.661 0.585 0.418 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] box : 0.227 0.379 0.544 0.624 0.376 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] monitor : 0.624 0.811 0.827 0.966 0.800 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] shelf : 0.176 0.359 0.537 0.769 0.333 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] heater : 0.375 0.728 0.794 0.964 0.711 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] kitchen cabinet: 0.136 0.372 0.662 0.667 0.400 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] sofa : 0.531 0.631 0.878 0.778 0.583 [2025-04-30 09:04:31,192 INFO hook.py line 395 1619929] bed : 0.159 0.425 0.776 0.667 0.500 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] trash can : 0.568 0.746 0.760 0.867 0.800 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] book : 0.025 0.051 0.099 0.161 0.105 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] plant : 0.463 0.655 0.762 1.000 0.611 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] blanket : 0.507 0.698 0.698 0.889 0.727 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] tv : 0.896 1.000 1.000 1.000 1.000 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] computer tower : 0.285 0.453 0.627 0.667 0.524 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] refrigerator : 0.255 0.482 0.486 1.000 0.444 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] jacket : 0.062 0.184 0.462 0.267 0.727 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] sink : 0.336 0.559 0.755 0.789 0.682 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] bag : 0.081 0.122 0.146 0.600 0.222 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] picture : 0.128 0.268 0.385 0.538 0.359 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] pillow : 0.644 0.845 0.865 0.882 0.789 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] towel : 0.203 0.314 0.485 0.565 0.342 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] suitcase : 0.373 0.493 0.505 0.750 0.429 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] backpack : 0.526 0.669 0.669 0.818 0.692 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] crate : 0.060 0.230 0.479 0.800 0.364 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] keyboard : 0.515 0.700 0.791 0.829 0.744 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] toilet : 0.866 1.000 1.000 1.000 1.000 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] printer : 0.307 0.361 0.419 0.500 0.444 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.003 0.036 0.111 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] painting : 0.042 0.042 0.050 0.083 1.000 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] microwave : 0.528 0.631 0.815 1.000 0.500 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] shoes : 0.160 0.287 0.537 0.684 0.317 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] socket : 0.192 0.481 0.656 0.739 0.464 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] bottle : 0.141 0.249 0.385 0.455 0.301 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] bucket : 0.007 0.007 0.007 0.100 0.143 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] cushion : 0.077 0.115 0.214 0.172 0.833 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] basket : 0.020 0.036 0.058 0.500 0.143 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] telephone : 0.281 0.571 0.683 0.714 0.588 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] laptop : 0.359 0.656 0.789 0.667 0.750 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] plant pot : 0.165 0.392 0.434 0.818 0.562 [2025-04-30 09:04:31,193 INFO hook.py line 395 1619929] exhaust fan : 0.253 0.420 0.420 0.875 0.467 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] cup : 0.209 0.348 0.408 1.000 0.318 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] coat hanger : 0.157 0.750 0.944 1.000 0.750 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] light switch : 0.231 0.476 0.595 0.763 0.446 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] speaker : 0.532 0.604 0.669 1.000 0.455 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] table lamp : 0.667 1.000 1.000 1.000 1.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] kettle : 0.278 0.333 0.333 1.000 0.333 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] smoke detector : 0.624 0.783 0.783 0.905 0.792 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] power strip : 0.068 0.102 0.142 0.500 0.300 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.042 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] paper bag : 0.042 0.042 0.050 0.083 1.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] mouse : 0.459 0.663 0.716 1.000 0.594 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] cutting board : 0.292 0.396 0.396 0.667 0.500 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] toilet paper : 0.302 0.412 0.493 1.000 0.412 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] paper towel : 0.111 0.125 0.166 1.000 0.125 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] tap : 0.143 0.293 0.667 0.385 0.556 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.018 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] soap dispenser : 0.532 0.800 0.800 1.000 0.800 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] bowl : 0.048 0.056 0.083 0.333 0.333 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] tissue box : 0.006 0.050 0.083 0.200 0.500 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] whiteboard eraser: 0.162 0.396 0.413 0.750 0.500 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] toilet brush : 0.438 0.629 0.899 0.800 0.667 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] headphones : 0.509 1.000 1.000 1.000 1.000 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] stapler : 0.009 0.045 0.021 0.125 0.667 [2025-04-30 09:04:31,194 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:04:31,194 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 09:04:31,194 INFO hook.py line 404 1619929] average : 0.286 0.436 0.517 0.642 0.516 [2025-04-30 09:04:31,194 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 09:04:31,195 INFO hook.py line 480 1619929] Total Process Time: 24.914 s [2025-04-30 09:04:31,195 INFO hook.py line 481 1619929] Average Process Time: 501.989 ms [2025-04-30 09:04:31,195 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 09:04:31,243 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 09:04:31,248 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 09:06:07,567 INFO hook.py line 650 1619929] Train: [508/512][50/242] Data 0.018 (0.017) Batch 1.612 (1.508) Remain 00:29:09 loss: 4.1204 Lr: 4.66808e-06 Mem R(MA/MR): 24164 (21973/36194) [2025-04-30 09:07:20,540 INFO hook.py line 650 1619929] Train: [508/512][100/242] Data 0.016 (0.017) Batch 1.567 (1.483) Remain 00:27:26 loss: 4.8394 Lr: 4.49468e-06 Mem R(MA/MR): 24170 (21973/36194) [2025-04-30 09:08:36,916 INFO hook.py line 650 1619929] Train: [508/512][150/242] Data 0.015 (0.024) Batch 1.562 (1.498) Remain 00:26:28 loss: 4.8108 Lr: 4.32054e-06 Mem R(MA/MR): 26164 (21973/36194) [2025-04-30 09:09:49,544 INFO hook.py line 650 1619929] Train: [508/512][200/242] Data 0.016 (0.022) Batch 1.469 (1.487) Remain 00:25:01 loss: 4.8549 Lr: 4.14561e-06 Mem R(MA/MR): 28764 (21973/36194) [2025-04-30 09:10:49,027 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2126 loss_mask: 0.0294 loss_dice: 1.6803 loss_score: 0.0000 loss_bbox: 0.0448 loss_sp_cls: 0.6575 loss: 4.2323 [2025-04-30 09:10:50,698 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 09:10:53,197 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1826 Process Time: 0.422 Mem R(MA/MR): 4292 (21973/36194) [2025-04-30 09:10:54,912 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8434 Process Time: 0.563 Mem R(MA/MR): 7288 (21973/36194) [2025-04-30 09:10:56,561 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.5430 Process Time: 0.641 Mem R(MA/MR): 9554 (21973/36194) [2025-04-30 09:11:04,340 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.0470 Process Time: 0.825 Mem R(MA/MR): 19694 (21973/36194) [2025-04-30 09:11:05,534 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3614 Process Time: 0.307 Mem R(MA/MR): 6906 (21973/36194) [2025-04-30 09:11:07,190 INFO hook.py line 449 1619929] Test: [6/50] Loss 5.0917 Process Time: 0.549 Mem R(MA/MR): 11578 (21973/36194) [2025-04-30 09:11:07,915 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.6620 Process Time: 0.276 Mem R(MA/MR): 6464 (21973/36194) [2025-04-30 09:11:08,474 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.1626 Process Time: 0.188 Mem R(MA/MR): 4304 (21973/36194) [2025-04-30 09:11:09,398 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8369 Process Time: 0.216 Mem R(MA/MR): 11778 (21973/36194) [2025-04-30 09:11:11,364 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.5466 Process Time: 0.429 Mem R(MA/MR): 9346 (21973/36194) [2025-04-30 09:11:14,408 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.3837 Process Time: 0.660 Mem R(MA/MR): 18824 (21973/36194) [2025-04-30 09:11:17,004 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0388 Process Time: 0.336 Mem R(MA/MR): 15340 (21973/36194) [2025-04-30 09:11:18,163 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.9422 Process Time: 0.229 Mem R(MA/MR): 8630 (21973/36194) [2025-04-30 09:11:18,789 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2791 Process Time: 0.149 Mem R(MA/MR): 4968 (21973/36194) [2025-04-30 09:11:22,150 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.6610 Process Time: 0.427 Mem R(MA/MR): 16700 (21973/36194) [2025-04-30 09:11:24,196 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4555 Process Time: 0.565 Mem R(MA/MR): 14698 (21973/36194) [2025-04-30 09:11:24,974 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1544 Process Time: 0.220 Mem R(MA/MR): 6804 (21973/36194) [2025-04-30 09:11:25,926 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.4612 Process Time: 0.223 Mem R(MA/MR): 8094 (21973/36194) [2025-04-30 09:11:27,250 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.0575 Process Time: 0.181 Mem R(MA/MR): 6060 (21973/36194) [2025-04-30 09:11:28,930 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.4065 Process Time: 0.298 Mem R(MA/MR): 11858 (21973/36194) [2025-04-30 09:11:38,344 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.8684 Process Time: 1.351 Mem R(MA/MR): 23992 (21973/36194) [2025-04-30 09:11:39,117 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5439 Process Time: 0.245 Mem R(MA/MR): 6772 (21973/36194) [2025-04-30 09:11:49,530 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.8994 Process Time: 0.434 Mem R(MA/MR): 10288 (21973/36194) [2025-04-30 09:11:50,224 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8678 Process Time: 0.237 Mem R(MA/MR): 5520 (21973/36194) [2025-04-30 09:11:51,226 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9246 Process Time: 0.303 Mem R(MA/MR): 8990 (21973/36194) [2025-04-30 09:11:57,801 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.1958 Process Time: 1.179 Mem R(MA/MR): 31770 (21973/36194) [2025-04-30 09:12:00,647 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.7087 Process Time: 0.754 Mem R(MA/MR): 10310 (21973/36194) [2025-04-30 09:12:01,949 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.8648 Process Time: 0.404 Mem R(MA/MR): 8734 (21973/36194) [2025-04-30 09:12:07,080 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.3272 Process Time: 0.450 Mem R(MA/MR): 17014 (21973/36194) [2025-04-30 09:12:08,142 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3590 Process Time: 0.355 Mem R(MA/MR): 7572 (21973/36194) [2025-04-30 09:12:11,763 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.7549 Process Time: 0.423 Mem R(MA/MR): 20424 (21973/36194) [2025-04-30 09:12:12,138 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3037 Process Time: 0.131 Mem R(MA/MR): 3876 (21973/36194) [2025-04-30 09:12:16,155 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.2463 Process Time: 0.501 Mem R(MA/MR): 24612 (21973/36194) [2025-04-30 09:12:17,765 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5571 Process Time: 0.649 Mem R(MA/MR): 10086 (21973/36194) [2025-04-30 09:12:19,726 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3416 Process Time: 0.488 Mem R(MA/MR): 14258 (21973/36194) [2025-04-30 09:12:20,341 INFO hook.py line 449 1619929] Test: [36/50] Loss 6.0221 Process Time: 0.263 Mem R(MA/MR): 6660 (21973/36194) [2025-04-30 09:12:23,809 INFO hook.py line 449 1619929] Test: [37/50] Loss 14.0682 Process Time: 0.662 Mem R(MA/MR): 28362 (21973/36194) [2025-04-30 09:12:25,301 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.6982 Process Time: 0.339 Mem R(MA/MR): 10996 (21973/36194) [2025-04-30 09:12:25,912 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.4038 Process Time: 0.254 Mem R(MA/MR): 5636 (21973/36194) [2025-04-30 09:12:27,298 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5468 Process Time: 0.527 Mem R(MA/MR): 10410 (21973/36194) [2025-04-30 09:12:28,618 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.6717 Process Time: 0.546 Mem R(MA/MR): 8756 (21973/36194) [2025-04-30 09:12:29,139 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3137 Process Time: 0.161 Mem R(MA/MR): 5666 (21973/36194) [2025-04-30 09:12:29,557 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7334 Process Time: 0.159 Mem R(MA/MR): 5706 (21973/36194) [2025-04-30 09:12:30,131 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.7882 Process Time: 0.196 Mem R(MA/MR): 7120 (21973/36194) [2025-04-30 09:12:30,706 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3574 Process Time: 0.180 Mem R(MA/MR): 5458 (21973/36194) [2025-04-30 09:12:32,674 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.5534 Process Time: 0.419 Mem R(MA/MR): 14750 (21973/36194) [2025-04-30 09:12:40,358 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.1657 Process Time: 1.017 Mem R(MA/MR): 20146 (21973/36194) [2025-04-30 09:12:50,722 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.3478 Process Time: 1.598 Mem R(MA/MR): 35722 (21973/36194) [2025-04-30 09:12:51,561 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1283 Process Time: 0.298 Mem R(MA/MR): 5770 (21973/36194) [2025-04-30 09:12:54,081 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.5271 Process Time: 0.343 Mem R(MA/MR): 14012 (21973/36194) [2025-04-30 09:12:57,961 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 09:12:57,961 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 09:12:57,961 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] table : 0.290 0.609 0.756 0.796 0.603 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] door : 0.494 0.781 0.882 0.910 0.772 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] ceiling lamp : 0.579 0.770 0.848 0.876 0.740 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] cabinet : 0.360 0.532 0.588 0.586 0.612 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] blinds : 0.593 0.835 0.846 0.944 0.739 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] curtain : 0.335 0.541 0.708 0.571 0.667 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] chair : 0.672 0.800 0.840 0.894 0.656 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] storage cabinet: 0.250 0.339 0.437 0.565 0.520 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] office chair : 0.636 0.663 0.664 0.714 0.729 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] bookshelf : 0.303 0.723 0.723 0.750 0.818 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] whiteboard : 0.582 0.781 0.792 0.923 0.686 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] window : 0.134 0.322 0.674 0.494 0.451 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] box : 0.213 0.371 0.536 0.638 0.370 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] monitor : 0.659 0.810 0.841 0.950 0.814 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] shelf : 0.166 0.320 0.416 0.750 0.300 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] heater : 0.449 0.761 0.795 0.929 0.684 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] kitchen cabinet: 0.148 0.428 0.728 0.480 0.480 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] sofa : 0.446 0.636 0.903 0.692 0.750 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] bed : 0.353 0.625 0.974 1.000 0.625 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] trash can : 0.583 0.768 0.784 0.789 0.923 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] book : 0.029 0.052 0.086 0.266 0.079 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] plant : 0.456 0.606 0.689 0.917 0.611 [2025-04-30 09:12:57,961 INFO hook.py line 395 1619929] blanket : 0.433 0.575 0.674 0.857 0.545 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] tv : 0.912 1.000 1.000 1.000 1.000 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] computer tower : 0.302 0.491 0.653 0.769 0.476 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] refrigerator : 0.197 0.452 0.454 0.800 0.444 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] jacket : 0.059 0.181 0.422 0.333 0.455 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] sink : 0.466 0.776 0.934 0.810 0.773 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] bag : 0.083 0.101 0.153 0.417 0.185 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] picture : 0.141 0.324 0.394 0.552 0.410 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] pillow : 0.553 0.738 0.754 0.857 0.632 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] towel : 0.220 0.343 0.486 0.609 0.368 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] suitcase : 0.378 0.439 0.439 0.750 0.429 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] backpack : 0.459 0.669 0.669 0.818 0.692 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] crate : 0.035 0.094 0.475 0.500 0.273 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] keyboard : 0.561 0.746 0.803 0.962 0.641 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] toilet : 0.866 1.000 1.000 1.000 1.000 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] printer : 0.306 0.335 0.343 0.500 0.444 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.011 0.036 0.111 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] painting : 0.050 0.050 0.056 0.100 1.000 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] microwave : 0.548 0.690 0.956 1.000 0.625 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] shoes : 0.126 0.198 0.487 0.481 0.317 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] socket : 0.183 0.457 0.669 0.649 0.514 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] bottle : 0.117 0.219 0.323 0.462 0.289 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] bucket : 0.019 0.019 0.020 0.095 0.286 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] cushion : 0.024 0.031 0.152 0.094 0.500 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] basket : 0.012 0.018 0.046 0.250 0.143 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] telephone : 0.320 0.575 0.583 1.000 0.471 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] laptop : 0.420 0.708 0.785 0.857 0.750 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] plant pot : 0.166 0.335 0.585 0.778 0.438 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] exhaust fan : 0.204 0.362 0.362 0.857 0.400 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] cup : 0.264 0.410 0.463 0.704 0.432 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] coat hanger : 0.126 0.321 0.750 0.500 0.750 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] light switch : 0.221 0.496 0.596 0.625 0.538 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] speaker : 0.465 0.513 0.678 0.600 0.545 [2025-04-30 09:12:57,962 INFO hook.py line 395 1619929] table lamp : 0.833 1.000 1.000 1.000 1.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] kettle : 0.167 0.167 0.167 1.000 0.167 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] smoke detector : 0.627 0.788 0.788 1.000 0.750 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] power strip : 0.041 0.068 0.089 0.214 0.300 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] mouse : 0.509 0.733 0.735 0.957 0.688 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] cutting board : 0.167 0.250 0.250 1.000 0.250 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] toilet paper : 0.265 0.412 0.464 1.000 0.412 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] paper towel : 0.138 0.198 0.198 0.667 0.250 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] tap : 0.137 0.305 0.683 0.571 0.444 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] jar : 0.016 0.071 0.071 1.000 0.071 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] soap dispenser : 0.564 0.800 0.800 1.000 0.800 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] bowl : 0.423 0.528 0.528 0.667 0.667 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] whiteboard eraser: 0.181 0.425 0.434 0.500 0.833 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] toilet brush : 0.447 0.629 0.803 0.800 0.667 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] headphones : 0.556 1.000 1.000 1.000 1.000 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] stapler : 0.003 0.013 0.070 0.077 0.333 [2025-04-30 09:12:57,963 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:12:57,963 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 09:12:57,963 INFO hook.py line 404 1619929] average : 0.291 0.428 0.522 0.616 0.489 [2025-04-30 09:12:57,963 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 09:12:57,964 INFO hook.py line 480 1619929] Total Process Time: 22.568 s [2025-04-30 09:12:57,964 INFO hook.py line 481 1619929] Average Process Time: 451.976 ms [2025-04-30 09:12:57,964 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 09:12:58,009 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 09:12:58,011 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 09:14:32,120 INFO hook.py line 650 1619929] Train: [509/512][50/242] Data 0.017 (0.016) Batch 1.463 (1.475) Remain 00:22:34 loss: 3.6653 Lr: 3.82156e-06 Mem R(MA/MR): 23886 (21973/36194) [2025-04-30 09:15:45,360 INFO hook.py line 650 1619929] Train: [509/512][100/242] Data 0.016 (0.017) Batch 1.488 (1.470) Remain 00:21:15 loss: 4.5467 Lr: 3.64417e-06 Mem R(MA/MR): 23898 (21973/36194) [2025-04-30 09:16:59,314 INFO hook.py line 650 1619929] Train: [509/512][150/242] Data 0.017 (0.023) Batch 1.517 (1.473) Remain 00:20:04 loss: 4.5964 Lr: 3.46582e-06 Mem R(MA/MR): 23898 (21973/36194) [2025-04-30 09:18:12,596 INFO hook.py line 650 1619929] Train: [509/512][200/242] Data 0.015 (0.022) Batch 1.387 (1.471) Remain 00:18:49 loss: 4.8123 Lr: 3.28644e-06 Mem R(MA/MR): 23904 (21973/36194) [2025-04-30 09:19:09,839 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2126 loss_mask: 0.0292 loss_dice: 1.6649 loss_score: 0.0000 loss_bbox: 0.0442 loss_sp_cls: 0.6589 loss: 4.2131 [2025-04-30 09:19:12,401 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 09:19:14,714 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1854 Process Time: 0.297 Mem R(MA/MR): 4564 (21973/36194) [2025-04-30 09:19:16,340 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.5981 Process Time: 0.472 Mem R(MA/MR): 7140 (21973/36194) [2025-04-30 09:19:18,053 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1797 Process Time: 0.658 Mem R(MA/MR): 9762 (21973/36194) [2025-04-30 09:19:25,415 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.1106 Process Time: 0.645 Mem R(MA/MR): 19908 (21973/36194) [2025-04-30 09:19:26,063 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.3140 Process Time: 0.177 Mem R(MA/MR): 6734 (21973/36194) [2025-04-30 09:19:27,456 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4943 Process Time: 0.450 Mem R(MA/MR): 11420 (21973/36194) [2025-04-30 09:19:28,051 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.0711 Process Time: 0.237 Mem R(MA/MR): 6376 (21973/36194) [2025-04-30 09:19:28,572 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.1393 Process Time: 0.151 Mem R(MA/MR): 4598 (21973/36194) [2025-04-30 09:19:29,497 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.8814 Process Time: 0.267 Mem R(MA/MR): 11644 (21973/36194) [2025-04-30 09:19:30,897 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.1798 Process Time: 0.269 Mem R(MA/MR): 9550 (21973/36194) [2025-04-30 09:19:33,681 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.3026 Process Time: 0.745 Mem R(MA/MR): 18614 (21973/36194) [2025-04-30 09:19:35,961 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.0771 Process Time: 0.285 Mem R(MA/MR): 15334 (21973/36194) [2025-04-30 09:19:37,129 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.0877 Process Time: 0.304 Mem R(MA/MR): 8866 (21973/36194) [2025-04-30 09:19:37,639 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1417 Process Time: 0.197 Mem R(MA/MR): 4836 (21973/36194) [2025-04-30 09:19:40,427 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4921 Process Time: 0.351 Mem R(MA/MR): 16592 (21973/36194) [2025-04-30 09:19:42,042 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.1672 Process Time: 0.322 Mem R(MA/MR): 14390 (21973/36194) [2025-04-30 09:19:42,768 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.1038 Process Time: 0.223 Mem R(MA/MR): 6672 (21973/36194) [2025-04-30 09:19:43,658 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.4063 Process Time: 0.283 Mem R(MA/MR): 8252 (21973/36194) [2025-04-30 09:19:44,786 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.6142 Process Time: 0.177 Mem R(MA/MR): 5938 (21973/36194) [2025-04-30 09:19:46,150 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.3752 Process Time: 0.236 Mem R(MA/MR): 11636 (21973/36194) [2025-04-30 09:19:55,101 INFO hook.py line 449 1619929] Test: [21/50] Loss 8.4628 Process Time: 0.610 Mem R(MA/MR): 23780 (21973/36194) [2025-04-30 09:19:55,593 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5366 Process Time: 0.150 Mem R(MA/MR): 6694 (21973/36194) [2025-04-30 09:20:05,724 INFO hook.py line 449 1619929] Test: [23/50] Loss 17.9572 Process Time: 0.303 Mem R(MA/MR): 10162 (21973/36194) [2025-04-30 09:20:06,497 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.6819 Process Time: 0.303 Mem R(MA/MR): 5562 (21973/36194) [2025-04-30 09:20:07,611 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0258 Process Time: 0.353 Mem R(MA/MR): 9356 (21973/36194) [2025-04-30 09:20:15,191 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.2404 Process Time: 1.320 Mem R(MA/MR): 32030 (21973/36194) [2025-04-30 09:20:18,379 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.1234 Process Time: 0.809 Mem R(MA/MR): 10222 (21973/36194) [2025-04-30 09:20:19,643 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.4172 Process Time: 0.245 Mem R(MA/MR): 9004 (21973/36194) [2025-04-30 09:20:25,665 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.1777 Process Time: 0.605 Mem R(MA/MR): 16886 (21973/36194) [2025-04-30 09:20:27,079 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3371 Process Time: 0.390 Mem R(MA/MR): 7480 (21973/36194) [2025-04-30 09:20:31,244 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.2847 Process Time: 0.478 Mem R(MA/MR): 20636 (21973/36194) [2025-04-30 09:20:31,719 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.1391 Process Time: 0.199 Mem R(MA/MR): 3954 (21973/36194) [2025-04-30 09:20:36,361 INFO hook.py line 449 1619929] Test: [33/50] Loss 12.3528 Process Time: 0.670 Mem R(MA/MR): 24950 (21973/36194) [2025-04-30 09:20:37,326 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6462 Process Time: 0.251 Mem R(MA/MR): 9948 (21973/36194) [2025-04-30 09:20:39,118 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7013 Process Time: 0.277 Mem R(MA/MR): 14210 (21973/36194) [2025-04-30 09:20:39,670 INFO hook.py line 449 1619929] Test: [36/50] Loss 4.8676 Process Time: 0.169 Mem R(MA/MR): 6518 (21973/36194) [2025-04-30 09:20:43,074 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.9987 Process Time: 0.519 Mem R(MA/MR): 28592 (21973/36194) [2025-04-30 09:20:44,754 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.7045 Process Time: 0.440 Mem R(MA/MR): 10940 (21973/36194) [2025-04-30 09:20:45,681 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1775 Process Time: 0.317 Mem R(MA/MR): 5714 (21973/36194) [2025-04-30 09:20:46,712 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.5785 Process Time: 0.271 Mem R(MA/MR): 10290 (21973/36194) [2025-04-30 09:20:47,785 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.2193 Process Time: 0.199 Mem R(MA/MR): 9112 (21973/36194) [2025-04-30 09:20:48,292 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.6083 Process Time: 0.153 Mem R(MA/MR): 5732 (21973/36194) [2025-04-30 09:20:48,736 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7735 Process Time: 0.158 Mem R(MA/MR): 5738 (21973/36194) [2025-04-30 09:20:49,461 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.8391 Process Time: 0.248 Mem R(MA/MR): 7064 (21973/36194) [2025-04-30 09:20:50,153 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.4043 Process Time: 0.219 Mem R(MA/MR): 5338 (21973/36194) [2025-04-30 09:20:52,520 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.9683 Process Time: 0.540 Mem R(MA/MR): 14628 (21973/36194) [2025-04-30 09:21:00,629 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7755 Process Time: 1.172 Mem R(MA/MR): 20156 (21973/36194) [2025-04-30 09:21:10,854 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.3739 Process Time: 1.936 Mem R(MA/MR): 35650 (21973/36194) [2025-04-30 09:21:11,609 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1021 Process Time: 0.233 Mem R(MA/MR): 5994 (21973/36194) [2025-04-30 09:21:13,807 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.0734 Process Time: 0.264 Mem R(MA/MR): 13934 (21973/36194) [2025-04-30 09:21:17,606 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 09:21:17,606 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 09:21:17,606 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] table : 0.296 0.625 0.745 0.885 0.566 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] door : 0.463 0.743 0.879 0.882 0.759 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] ceiling lamp : 0.588 0.776 0.871 0.817 0.762 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] cabinet : 0.343 0.486 0.545 0.574 0.582 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] blinds : 0.602 0.856 0.817 0.864 0.826 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] curtain : 0.515 0.686 0.852 0.800 0.667 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] chair : 0.678 0.796 0.834 0.717 0.811 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] storage cabinet: 0.257 0.372 0.567 0.469 0.600 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] office chair : 0.573 0.602 0.619 0.694 0.708 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] bookshelf : 0.261 0.445 0.610 0.500 0.727 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] whiteboard : 0.538 0.726 0.777 0.926 0.714 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] window : 0.139 0.312 0.643 0.429 0.495 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] box : 0.205 0.365 0.540 0.618 0.376 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] monitor : 0.633 0.806 0.825 0.949 0.800 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] shelf : 0.150 0.266 0.490 0.474 0.300 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] heater : 0.414 0.743 0.808 0.929 0.684 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] kitchen cabinet: 0.121 0.293 0.655 0.571 0.480 [2025-04-30 09:21:17,606 INFO hook.py line 395 1619929] sofa : 0.481 0.562 0.909 0.778 0.583 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] bed : 0.310 0.559 0.794 1.000 0.500 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] trash can : 0.542 0.677 0.717 0.812 0.800 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] book : 0.018 0.044 0.087 0.354 0.086 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] plant : 0.451 0.698 0.739 1.000 0.667 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] blanket : 0.607 0.790 0.790 0.889 0.727 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] tv : 0.912 1.000 1.000 1.000 1.000 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] computer tower : 0.290 0.499 0.632 0.634 0.619 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] refrigerator : 0.193 0.404 0.419 0.667 0.444 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] jacket : 0.061 0.174 0.447 0.333 0.545 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] sink : 0.405 0.637 0.855 0.696 0.727 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] bag : 0.083 0.171 0.189 0.364 0.296 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] picture : 0.126 0.297 0.432 0.652 0.385 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] pillow : 0.574 0.765 0.839 0.800 0.632 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] towel : 0.198 0.349 0.492 0.533 0.421 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] suitcase : 0.428 0.505 0.505 1.000 0.429 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] backpack : 0.455 0.537 0.638 0.667 0.615 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] crate : 0.073 0.232 0.544 0.800 0.364 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] keyboard : 0.532 0.691 0.809 0.763 0.744 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] toilet : 0.875 1.000 1.000 1.000 1.000 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] printer : 0.245 0.281 0.367 0.750 0.333 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] painting : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] microwave : 0.653 0.717 1.000 1.000 0.625 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] shoes : 0.112 0.198 0.584 0.600 0.293 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] socket : 0.196 0.467 0.689 0.737 0.521 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] bottle : 0.116 0.203 0.337 0.358 0.349 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] bucket : 0.013 0.022 0.022 0.143 0.286 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] cushion : 0.075 0.124 0.213 0.200 0.500 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] basket : 0.010 0.018 0.024 0.250 0.143 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] telephone : 0.398 0.676 0.701 0.846 0.647 [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 09:21:17,607 INFO hook.py line 395 1619929] laptop : 0.387 0.665 0.665 0.750 0.750 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] plant pot : 0.198 0.396 0.508 0.611 0.688 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] exhaust fan : 0.206 0.362 0.362 0.857 0.400 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] cup : 0.256 0.394 0.436 0.667 0.409 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] coat hanger : 0.190 0.500 0.750 1.000 0.500 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] light switch : 0.251 0.505 0.646 0.795 0.538 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] speaker : 0.382 0.431 0.521 0.778 0.636 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] kettle : 0.242 0.356 0.356 0.600 0.500 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] smoke detector : 0.653 0.821 0.821 0.909 0.833 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] power strip : 0.021 0.035 0.086 0.222 0.200 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.042 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] mouse : 0.493 0.686 0.754 0.815 0.688 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] cutting board : 0.361 0.500 0.500 1.000 0.500 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] toilet paper : 0.242 0.412 0.483 1.000 0.412 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] paper towel : 0.125 0.125 0.166 1.000 0.125 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] tap : 0.117 0.285 0.568 0.571 0.444 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] jar : 0.001 0.005 0.089 0.143 0.071 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] soap dispenser : 0.532 0.800 0.938 1.000 0.800 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] bowl : 0.065 0.083 0.083 0.500 0.333 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] tissue box : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] whiteboard eraser: 0.233 0.533 0.539 0.667 0.667 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] toilet brush : 0.475 0.667 0.833 1.000 0.667 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] spray bottle : 0.006 0.008 0.008 0.062 0.250 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] headphones : 0.500 1.000 1.000 1.000 1.000 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] stapler : 0.010 0.043 0.046 0.125 0.667 [2025-04-30 09:21:17,608 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:21:17,608 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 09:21:17,608 INFO hook.py line 404 1619929] average : 0.287 0.423 0.512 0.616 0.490 [2025-04-30 09:21:17,608 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 09:21:17,609 INFO hook.py line 480 1619929] Total Process Time: 20.547 s [2025-04-30 09:21:17,609 INFO hook.py line 481 1619929] Average Process Time: 413.281 ms [2025-04-30 09:21:17,609 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 09:21:17,655 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 09:21:17,660 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 09:22:52,225 INFO hook.py line 650 1619929] Train: [510/512][50/242] Data 0.017 (0.017) Batch 1.506 (1.499) Remain 00:16:53 loss: 3.7377 Lr: 2.95347e-06 Mem R(MA/MR): 21486 (21973/36194) [2025-04-30 09:24:05,384 INFO hook.py line 650 1619929] Train: [510/512][100/242] Data 0.015 (0.027) Batch 1.375 (1.480) Remain 00:15:26 loss: 3.0460 Lr: 2.77076e-06 Mem R(MA/MR): 21486 (21973/36194) [2025-04-30 09:25:17,192 INFO hook.py line 650 1619929] Train: [510/512][150/242] Data 0.016 (0.024) Batch 1.625 (1.465) Remain 00:14:04 loss: 4.1852 Lr: 2.58671e-06 Mem R(MA/MR): 23314 (21973/36194) [2025-04-30 09:26:29,368 INFO hook.py line 650 1619929] Train: [510/512][200/242] Data 0.015 (0.022) Batch 1.556 (1.460) Remain 00:12:47 loss: 4.5613 Lr: 2.40119e-06 Mem R(MA/MR): 25872 (21973/36194) [2025-04-30 09:27:27,520 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2136 loss_mask: 0.0287 loss_dice: 1.6658 loss_score: 0.0000 loss_bbox: 0.0448 loss_sp_cls: 0.6585 loss: 4.2149 [2025-04-30 09:27:28,987 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 09:27:31,181 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.1020 Process Time: 0.256 Mem R(MA/MR): 4216 (21973/36194) [2025-04-30 09:27:33,152 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.7552 Process Time: 0.777 Mem R(MA/MR): 7024 (21973/36194) [2025-04-30 09:27:34,987 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.1495 Process Time: 0.685 Mem R(MA/MR): 9558 (21973/36194) [2025-04-30 09:27:43,757 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3379 Process Time: 1.496 Mem R(MA/MR): 19450 (21973/36194) [2025-04-30 09:27:44,721 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4206 Process Time: 0.326 Mem R(MA/MR): 7072 (21973/36194) [2025-04-30 09:27:46,171 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.6817 Process Time: 0.378 Mem R(MA/MR): 11120 (21973/36194) [2025-04-30 09:27:46,900 INFO hook.py line 449 1619929] Test: [7/50] Loss 6.1138 Process Time: 0.358 Mem R(MA/MR): 6050 (21973/36194) [2025-04-30 09:27:47,381 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.5249 Process Time: 0.147 Mem R(MA/MR): 4254 (21973/36194) [2025-04-30 09:27:48,280 INFO hook.py line 449 1619929] Test: [9/50] Loss 3.2531 Process Time: 0.251 Mem R(MA/MR): 11276 (21973/36194) [2025-04-30 09:27:49,863 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.3723 Process Time: 0.309 Mem R(MA/MR): 9298 (21973/36194) [2025-04-30 09:27:52,842 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.7763 Process Time: 0.552 Mem R(MA/MR): 18422 (21973/36194) [2025-04-30 09:27:55,625 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.2137 Process Time: 0.466 Mem R(MA/MR): 15288 (21973/36194) [2025-04-30 09:27:56,852 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7192 Process Time: 0.304 Mem R(MA/MR): 8524 (21973/36194) [2025-04-30 09:27:57,336 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2040 Process Time: 0.210 Mem R(MA/MR): 4590 (21973/36194) [2025-04-30 09:28:00,778 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4436 Process Time: 0.340 Mem R(MA/MR): 16354 (21973/36194) [2025-04-30 09:28:02,853 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4180 Process Time: 0.549 Mem R(MA/MR): 14314 (21973/36194) [2025-04-30 09:28:03,667 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.0250 Process Time: 0.258 Mem R(MA/MR): 6524 (21973/36194) [2025-04-30 09:28:04,589 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1665 Process Time: 0.248 Mem R(MA/MR): 8012 (21973/36194) [2025-04-30 09:28:05,808 INFO hook.py line 449 1619929] Test: [19/50] Loss 6.2454 Process Time: 0.145 Mem R(MA/MR): 5542 (21973/36194) [2025-04-30 09:28:07,486 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.3453 Process Time: 0.262 Mem R(MA/MR): 11318 (21973/36194) [2025-04-30 09:28:15,988 INFO hook.py line 449 1619929] Test: [21/50] Loss 9.1118 Process Time: 0.959 Mem R(MA/MR): 23920 (21973/36194) [2025-04-30 09:28:16,930 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.4378 Process Time: 0.403 Mem R(MA/MR): 6614 (21973/36194) [2025-04-30 09:28:29,134 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.3770 Process Time: 0.616 Mem R(MA/MR): 10082 (21973/36194) [2025-04-30 09:28:29,684 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.7394 Process Time: 0.171 Mem R(MA/MR): 5002 (21973/36194) [2025-04-30 09:28:30,563 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0992 Process Time: 0.193 Mem R(MA/MR): 9058 (21973/36194) [2025-04-30 09:28:36,995 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.9639 Process Time: 0.887 Mem R(MA/MR): 31544 (21973/36194) [2025-04-30 09:28:39,459 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.6160 Process Time: 0.263 Mem R(MA/MR): 9662 (21973/36194) [2025-04-30 09:28:40,827 INFO hook.py line 449 1619929] Test: [28/50] Loss 5.9694 Process Time: 0.379 Mem R(MA/MR): 8702 (21973/36194) [2025-04-30 09:28:46,381 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.0508 Process Time: 0.376 Mem R(MA/MR): 16750 (21973/36194) [2025-04-30 09:28:47,237 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.1513 Process Time: 0.242 Mem R(MA/MR): 7580 (21973/36194) [2025-04-30 09:28:50,723 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.4532 Process Time: 0.411 Mem R(MA/MR): 20260 (21973/36194) [2025-04-30 09:28:51,251 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.2242 Process Time: 0.227 Mem R(MA/MR): 4028 (21973/36194) [2025-04-30 09:28:55,243 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.8515 Process Time: 0.520 Mem R(MA/MR): 24480 (21973/36194) [2025-04-30 09:28:56,132 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.4844 Process Time: 0.218 Mem R(MA/MR): 9704 (21973/36194) [2025-04-30 09:28:57,821 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.9751 Process Time: 0.277 Mem R(MA/MR): 13768 (21973/36194) [2025-04-30 09:28:58,347 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.4277 Process Time: 0.213 Mem R(MA/MR): 6440 (21973/36194) [2025-04-30 09:29:02,045 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.3792 Process Time: 0.580 Mem R(MA/MR): 28324 (21973/36194) [2025-04-30 09:29:04,064 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.9476 Process Time: 0.463 Mem R(MA/MR): 10462 (21973/36194) [2025-04-30 09:29:04,538 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.1186 Process Time: 0.170 Mem R(MA/MR): 5298 (21973/36194) [2025-04-30 09:29:05,677 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.3729 Process Time: 0.274 Mem R(MA/MR): 9832 (21973/36194) [2025-04-30 09:29:06,630 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.4781 Process Time: 0.205 Mem R(MA/MR): 8742 (21973/36194) [2025-04-30 09:29:07,154 INFO hook.py line 449 1619929] Test: [42/50] Loss 5.9066 Process Time: 0.157 Mem R(MA/MR): 5352 (21973/36194) [2025-04-30 09:29:07,685 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.5089 Process Time: 0.211 Mem R(MA/MR): 5384 (21973/36194) [2025-04-30 09:29:08,466 INFO hook.py line 449 1619929] Test: [44/50] Loss 7.6384 Process Time: 0.312 Mem R(MA/MR): 6986 (21973/36194) [2025-04-30 09:29:09,132 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3155 Process Time: 0.156 Mem R(MA/MR): 4954 (21973/36194) [2025-04-30 09:29:11,362 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.2641 Process Time: 0.362 Mem R(MA/MR): 14382 (21973/36194) [2025-04-30 09:29:19,179 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7331 Process Time: 0.711 Mem R(MA/MR): 20048 (21973/36194) [2025-04-30 09:29:29,604 INFO hook.py line 449 1619929] Test: [48/50] Loss 12.2077 Process Time: 1.866 Mem R(MA/MR): 35392 (21973/36194) [2025-04-30 09:29:30,251 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.1722 Process Time: 0.177 Mem R(MA/MR): 5630 (21973/36194) [2025-04-30 09:29:32,740 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.6457 Process Time: 0.518 Mem R(MA/MR): 13548 (21973/36194) [2025-04-30 09:29:36,558 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 09:29:36,558 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 09:29:36,558 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] table : 0.306 0.643 0.779 0.848 0.618 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] door : 0.444 0.745 0.882 0.908 0.747 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] ceiling lamp : 0.589 0.765 0.869 0.843 0.740 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] cabinet : 0.358 0.525 0.556 0.606 0.597 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] blinds : 0.613 0.797 0.850 0.895 0.739 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] curtain : 0.403 0.543 0.747 0.600 0.750 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] chair : 0.655 0.788 0.829 0.782 0.762 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] storage cabinet: 0.232 0.325 0.480 0.538 0.560 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] office chair : 0.580 0.621 0.622 0.667 0.750 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] bookshelf : 0.269 0.450 0.609 0.778 0.636 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] whiteboard : 0.561 0.775 0.774 1.000 0.714 [2025-04-30 09:29:36,558 INFO hook.py line 395 1619929] window : 0.126 0.282 0.621 0.522 0.396 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] box : 0.211 0.374 0.533 0.497 0.420 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] monitor : 0.655 0.805 0.875 0.948 0.786 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] shelf : 0.169 0.351 0.543 0.769 0.333 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] heater : 0.386 0.701 0.769 0.839 0.684 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] kitchen cabinet: 0.106 0.336 0.671 0.611 0.440 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] sofa : 0.504 0.627 0.883 0.778 0.583 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] bed : 0.262 0.559 0.896 1.000 0.500 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] trash can : 0.523 0.670 0.699 0.786 0.846 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] book : 0.022 0.044 0.088 0.310 0.082 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] plant : 0.448 0.702 0.755 1.000 0.667 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] blanket : 0.477 0.550 0.638 0.857 0.545 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] tv : 0.880 1.000 1.000 1.000 1.000 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] computer tower : 0.293 0.476 0.626 0.636 0.500 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] refrigerator : 0.185 0.374 0.379 1.000 0.333 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] jacket : 0.103 0.210 0.467 0.333 0.545 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] sink : 0.494 0.794 0.935 0.783 0.818 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] bag : 0.066 0.101 0.126 0.462 0.222 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] picture : 0.137 0.316 0.392 0.684 0.333 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] pillow : 0.598 0.803 0.818 0.765 0.684 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] towel : 0.203 0.338 0.516 0.733 0.289 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] suitcase : 0.416 0.522 0.522 0.667 0.571 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] backpack : 0.529 0.715 0.715 0.833 0.769 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] crate : 0.059 0.172 0.459 0.417 0.455 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] keyboard : 0.463 0.644 0.772 0.862 0.641 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] toilet : 0.877 1.000 1.000 1.000 1.000 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] printer : 0.224 0.236 0.296 0.308 0.444 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] poster : 0.000 0.002 0.002 0.031 0.111 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] painting : 0.062 0.062 0.071 0.125 1.000 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] microwave : 0.526 0.717 0.858 1.000 0.625 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] shoes : 0.127 0.250 0.596 0.600 0.366 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] socket : 0.194 0.479 0.663 0.697 0.493 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] bottle : 0.126 0.211 0.362 0.431 0.301 [2025-04-30 09:29:36,559 INFO hook.py line 395 1619929] bucket : 0.030 0.041 0.041 0.167 0.429 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] cushion : 0.060 0.098 0.170 0.156 0.833 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] basket : 0.079 0.143 0.143 1.000 0.143 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] telephone : 0.371 0.649 0.654 0.846 0.647 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] laptop : 0.348 0.566 0.702 1.000 0.500 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] plant pot : 0.226 0.371 0.491 0.692 0.562 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] exhaust fan : 0.269 0.420 0.420 0.875 0.467 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] cup : 0.236 0.393 0.418 0.810 0.386 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] coat hanger : 0.134 0.750 0.750 1.000 0.750 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] light switch : 0.207 0.435 0.593 0.652 0.462 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] speaker : 0.459 0.533 0.653 0.857 0.545 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] kettle : 0.296 0.333 0.333 1.000 0.333 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] smoke detector : 0.654 0.821 0.823 0.870 0.833 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] power strip : 0.040 0.052 0.062 0.333 0.200 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] paper bag : 0.056 0.056 0.071 0.111 1.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] mouse : 0.548 0.752 0.756 1.000 0.656 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] cutting board : 0.139 0.250 0.250 1.000 0.250 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] toilet paper : 0.328 0.430 0.476 1.000 0.412 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] paper towel : 0.034 0.061 0.166 0.400 0.250 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.250 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] tap : 0.184 0.413 0.865 0.545 0.667 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] soap dispenser : 0.525 0.800 0.800 1.000 0.800 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] bowl : 0.138 0.222 0.528 0.500 0.667 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] tissue box : 0.046 0.083 0.500 0.333 0.500 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] whiteboard eraser: 0.279 0.652 0.659 0.800 0.667 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] toilet brush : 0.462 0.667 0.913 1.000 0.667 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] spray bottle : 0.005 0.008 0.008 0.062 0.250 [2025-04-30 09:29:36,560 INFO hook.py line 395 1619929] headphones : 0.278 0.500 1.000 1.000 0.500 [2025-04-30 09:29:36,561 INFO hook.py line 395 1619929] stapler : 0.009 0.039 0.017 0.111 0.667 [2025-04-30 09:29:36,561 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:29:36,561 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 09:29:36,561 INFO hook.py line 404 1619929] average : 0.284 0.420 0.525 0.633 0.511 [2025-04-30 09:29:36,561 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 09:29:36,561 INFO hook.py line 480 1619929] Total Process Time: 20.834 s [2025-04-30 09:29:36,561 INFO hook.py line 481 1619929] Average Process Time: 419.969 ms [2025-04-30 09:29:36,561 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 09:29:36,602 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 09:29:36,607 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 09:31:16,124 INFO hook.py line 650 1619929] Train: [511/512][50/242] Data 0.015 (0.037) Batch 1.384 (1.531) Remain 00:11:04 loss: 3.9480 Lr: 2.05551e-06 Mem R(MA/MR): 20802 (21973/36194) [2025-04-30 09:32:29,313 INFO hook.py line 650 1619929] Train: [511/512][100/242] Data 0.017 (0.026) Batch 1.659 (1.496) Remain 00:09:34 loss: 4.5678 Lr: 1.86495e-06 Mem R(MA/MR): 20802 (21973/36194) [2025-04-30 09:33:42,036 INFO hook.py line 650 1619929] Train: [511/512][150/242] Data 0.016 (0.023) Batch 1.528 (1.482) Remain 00:08:14 loss: 4.3232 Lr: 1.67221e-06 Mem R(MA/MR): 21308 (21973/36194) [2025-04-30 09:34:55,406 INFO hook.py line 650 1619929] Train: [511/512][200/242] Data 0.014 (0.021) Batch 1.312 (1.478) Remain 00:06:59 loss: 3.1340 Lr: 1.47695e-06 Mem R(MA/MR): 25242 (21973/36194) [2025-04-30 09:35:52,050 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2125 loss_mask: 0.0290 loss_dice: 1.6711 loss_score: 0.0000 loss_bbox: 0.0446 loss_sp_cls: 0.6593 loss: 4.2180 [2025-04-30 09:35:57,277 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 09:35:59,573 INFO hook.py line 449 1619929] Test: [1/50] Loss 3.0602 Process Time: 0.299 Mem R(MA/MR): 4990 (21973/36194) [2025-04-30 09:36:01,163 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8460 Process Time: 0.472 Mem R(MA/MR): 8126 (21973/36194) [2025-04-30 09:36:02,711 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.2206 Process Time: 0.522 Mem R(MA/MR): 10422 (21973/36194) [2025-04-30 09:36:11,215 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.1504 Process Time: 1.499 Mem R(MA/MR): 20472 (21973/36194) [2025-04-30 09:36:11,949 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.8103 Process Time: 0.197 Mem R(MA/MR): 7788 (21973/36194) [2025-04-30 09:36:13,418 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.8907 Process Time: 0.481 Mem R(MA/MR): 12180 (21973/36194) [2025-04-30 09:36:14,321 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.7801 Process Time: 0.383 Mem R(MA/MR): 6976 (21973/36194) [2025-04-30 09:36:14,880 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2804 Process Time: 0.207 Mem R(MA/MR): 4968 (21973/36194) [2025-04-30 09:36:15,925 INFO hook.py line 449 1619929] Test: [9/50] Loss 2.7620 Process Time: 0.418 Mem R(MA/MR): 12268 (21973/36194) [2025-04-30 09:36:17,389 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4366 Process Time: 0.262 Mem R(MA/MR): 10244 (21973/36194) [2025-04-30 09:36:20,022 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.5392 Process Time: 0.594 Mem R(MA/MR): 19728 (21973/36194) [2025-04-30 09:36:22,512 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.1785 Process Time: 0.442 Mem R(MA/MR): 16482 (21973/36194) [2025-04-30 09:36:23,727 INFO hook.py line 449 1619929] Test: [13/50] Loss 7.1129 Process Time: 0.344 Mem R(MA/MR): 9528 (21973/36194) [2025-04-30 09:36:24,115 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.1785 Process Time: 0.171 Mem R(MA/MR): 5882 (21973/36194) [2025-04-30 09:36:27,038 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.3951 Process Time: 0.333 Mem R(MA/MR): 17624 (21973/36194) [2025-04-30 09:36:28,530 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.3276 Process Time: 0.242 Mem R(MA/MR): 15622 (21973/36194) [2025-04-30 09:36:29,436 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.4142 Process Time: 0.368 Mem R(MA/MR): 7692 (21973/36194) [2025-04-30 09:36:30,328 INFO hook.py line 449 1619929] Test: [18/50] Loss 3.1364 Process Time: 0.238 Mem R(MA/MR): 9002 (21973/36194) [2025-04-30 09:36:31,712 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9388 Process Time: 0.254 Mem R(MA/MR): 6510 (21973/36194) [2025-04-30 09:36:33,383 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.5932 Process Time: 0.405 Mem R(MA/MR): 12236 (21973/36194) [2025-04-30 09:36:42,095 INFO hook.py line 449 1619929] Test: [21/50] Loss 9.2967 Process Time: 0.752 Mem R(MA/MR): 24196 (21973/36194) [2025-04-30 09:36:42,697 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.5557 Process Time: 0.185 Mem R(MA/MR): 7720 (21973/36194) [2025-04-30 09:36:53,501 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.3043 Process Time: 0.372 Mem R(MA/MR): 11186 (21973/36194) [2025-04-30 09:36:54,145 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.8954 Process Time: 0.282 Mem R(MA/MR): 6252 (21973/36194) [2025-04-30 09:36:55,355 INFO hook.py line 449 1619929] Test: [25/50] Loss 2.9922 Process Time: 0.434 Mem R(MA/MR): 9484 (21973/36194) [2025-04-30 09:37:01,967 INFO hook.py line 449 1619929] Test: [26/50] Loss 12.4102 Process Time: 1.355 Mem R(MA/MR): 31594 (21973/36194) [2025-04-30 09:37:04,473 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.2006 Process Time: 0.309 Mem R(MA/MR): 10336 (21973/36194) [2025-04-30 09:37:05,672 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.3234 Process Time: 0.301 Mem R(MA/MR): 9096 (21973/36194) [2025-04-30 09:37:10,841 INFO hook.py line 449 1619929] Test: [29/50] Loss 6.9609 Process Time: 0.461 Mem R(MA/MR): 17752 (21973/36194) [2025-04-30 09:37:11,796 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3881 Process Time: 0.338 Mem R(MA/MR): 8518 (21973/36194) [2025-04-30 09:37:15,982 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.0499 Process Time: 0.726 Mem R(MA/MR): 21028 (21973/36194) [2025-04-30 09:37:16,360 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.6169 Process Time: 0.131 Mem R(MA/MR): 4800 (21973/36194) [2025-04-30 09:37:20,397 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.1685 Process Time: 0.390 Mem R(MA/MR): 25412 (21973/36194) [2025-04-30 09:37:21,583 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.6953 Process Time: 0.379 Mem R(MA/MR): 9912 (21973/36194) [2025-04-30 09:37:23,768 INFO hook.py line 449 1619929] Test: [35/50] Loss 7.7489 Process Time: 0.546 Mem R(MA/MR): 14772 (21973/36194) [2025-04-30 09:37:24,465 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2478 Process Time: 0.312 Mem R(MA/MR): 7044 (21973/36194) [2025-04-30 09:37:28,034 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.8414 Process Time: 0.561 Mem R(MA/MR): 28764 (21973/36194) [2025-04-30 09:37:29,642 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.9354 Process Time: 0.547 Mem R(MA/MR): 11206 (21973/36194) [2025-04-30 09:37:30,301 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2469 Process Time: 0.240 Mem R(MA/MR): 6358 (21973/36194) [2025-04-30 09:37:31,442 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.4663 Process Time: 0.318 Mem R(MA/MR): 10654 (21973/36194) [2025-04-30 09:37:32,850 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.4358 Process Time: 0.453 Mem R(MA/MR): 9318 (21973/36194) [2025-04-30 09:37:33,413 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.2454 Process Time: 0.159 Mem R(MA/MR): 6418 (21973/36194) [2025-04-30 09:37:33,953 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.7872 Process Time: 0.215 Mem R(MA/MR): 6420 (21973/36194) [2025-04-30 09:37:34,667 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3933 Process Time: 0.255 Mem R(MA/MR): 8050 (21973/36194) [2025-04-30 09:37:35,286 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.4792 Process Time: 0.135 Mem R(MA/MR): 6194 (21973/36194) [2025-04-30 09:37:37,403 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.8153 Process Time: 0.262 Mem R(MA/MR): 15292 (21973/36194) [2025-04-30 09:37:45,134 INFO hook.py line 449 1619929] Test: [47/50] Loss 6.3631 Process Time: 0.765 Mem R(MA/MR): 20952 (21973/36194) [2025-04-30 09:37:54,746 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.7699 Process Time: 1.678 Mem R(MA/MR): 35934 (21973/36194) [2025-04-30 09:37:55,322 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0318 Process Time: 0.146 Mem R(MA/MR): 6508 (21973/36194) [2025-04-30 09:37:57,438 INFO hook.py line 449 1619929] Test: [50/50] Loss 4.9119 Process Time: 0.329 Mem R(MA/MR): 14284 (21973/36194) [2025-04-30 09:38:01,214 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 09:38:01,214 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 09:38:01,214 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] table : 0.291 0.633 0.752 0.840 0.618 [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] door : 0.491 0.768 0.911 0.871 0.772 [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] ceiling lamp : 0.585 0.790 0.869 0.857 0.762 [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] cabinet : 0.331 0.507 0.546 0.585 0.567 [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] blinds : 0.568 0.788 0.815 0.947 0.783 [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] curtain : 0.406 0.513 0.692 0.538 0.583 [2025-04-30 09:38:01,214 INFO hook.py line 395 1619929] chair : 0.625 0.766 0.801 0.787 0.725 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] storage cabinet: 0.207 0.341 0.470 0.560 0.560 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] office chair : 0.599 0.643 0.643 0.696 0.812 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] bookshelf : 0.337 0.642 0.669 0.727 0.727 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] whiteboard : 0.594 0.757 0.791 0.926 0.714 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] window : 0.124 0.286 0.611 0.455 0.440 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] box : 0.214 0.374 0.527 0.568 0.392 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] monitor : 0.659 0.805 0.853 0.949 0.800 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] shelf : 0.167 0.344 0.460 0.625 0.333 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] heater : 0.432 0.770 0.771 0.935 0.763 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] kitchen cabinet: 0.101 0.258 0.682 0.448 0.520 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] sofa : 0.530 0.671 0.890 0.875 0.583 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] bed : 0.290 0.625 0.974 1.000 0.625 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] trash can : 0.571 0.719 0.733 0.857 0.831 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] book : 0.027 0.049 0.079 0.208 0.097 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] plant : 0.428 0.711 0.795 1.000 0.667 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] blanket : 0.459 0.605 0.663 0.875 0.636 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] tv : 0.896 1.000 1.000 1.000 1.000 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] computer tower : 0.324 0.495 0.752 0.641 0.595 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] refrigerator : 0.239 0.428 0.431 0.667 0.444 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] jacket : 0.124 0.264 0.519 0.300 0.545 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] sink : 0.398 0.714 0.901 0.720 0.818 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] bag : 0.106 0.155 0.200 0.667 0.222 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] picture : 0.129 0.272 0.412 0.538 0.359 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] pillow : 0.512 0.711 0.737 0.765 0.684 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] towel : 0.193 0.315 0.477 0.733 0.289 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] suitcase : 0.415 0.487 0.487 1.000 0.429 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] backpack : 0.509 0.769 0.769 1.000 0.769 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] crate : 0.067 0.176 0.504 0.417 0.455 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] keyboard : 0.528 0.728 0.757 0.933 0.718 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] toilet : 0.849 0.889 1.000 1.000 0.889 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] printer : 0.455 0.499 0.526 0.625 0.556 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] poster : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] painting : 0.051 0.056 0.062 0.111 1.000 [2025-04-30 09:38:01,215 INFO hook.py line 395 1619929] microwave : 0.634 0.816 1.000 0.857 0.750 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] shoes : 0.136 0.250 0.598 0.538 0.341 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] socket : 0.196 0.475 0.666 0.723 0.486 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] bottle : 0.122 0.226 0.340 0.463 0.301 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] bucket : 0.006 0.006 0.006 0.083 0.143 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] cushion : 0.045 0.076 0.178 0.176 0.500 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] basket : 0.015 0.024 0.042 0.333 0.143 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] shoe rack : 0.056 0.500 0.500 1.000 0.500 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] telephone : 0.401 0.685 0.700 0.909 0.588 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] laptop : 0.397 0.678 0.763 0.750 0.750 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] plant pot : 0.174 0.377 0.516 0.750 0.562 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] exhaust fan : 0.188 0.337 0.337 0.750 0.400 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] cup : 0.245 0.383 0.440 0.800 0.364 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] coat hanger : 0.143 0.346 0.750 0.600 0.750 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] light switch : 0.217 0.481 0.618 0.727 0.492 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] speaker : 0.475 0.642 0.729 0.667 0.727 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 0.500 1.000 0.500 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] kettle : 0.303 0.356 0.382 0.600 0.500 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] smoke detector : 0.651 0.827 0.827 0.909 0.833 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] power strip : 0.029 0.114 0.130 0.375 0.300 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] paper bag : 0.061 0.062 0.071 0.125 1.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] mouse : 0.481 0.645 0.670 1.000 0.625 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] cutting board : 0.194 0.250 0.250 1.000 0.250 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] toilet paper : 0.289 0.412 0.457 1.000 0.412 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] paper towel : 0.009 0.021 0.158 0.333 0.125 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] clock : 0.852 1.000 1.000 1.000 1.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.123 0.000 0.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] tap : 0.172 0.367 0.556 1.000 0.333 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] soap dispenser : 0.465 0.637 0.637 0.667 0.800 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] bowl : 0.059 0.083 0.083 0.500 0.333 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] tissue box : 0.033 0.050 0.062 0.200 0.500 [2025-04-30 09:38:01,216 INFO hook.py line 395 1619929] whiteboard eraser: 0.206 0.486 0.501 0.800 0.667 [2025-04-30 09:38:01,217 INFO hook.py line 395 1619929] toilet brush : 0.459 0.732 0.907 1.000 0.667 [2025-04-30 09:38:01,217 INFO hook.py line 395 1619929] spray bottle : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,217 INFO hook.py line 395 1619929] headphones : 0.446 1.000 1.000 1.000 1.000 [2025-04-30 09:38:01,217 INFO hook.py line 395 1619929] stapler : 0.005 0.037 0.052 0.105 0.667 [2025-04-30 09:38:01,217 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:38:01,217 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 09:38:01,217 INFO hook.py line 404 1619929] average : 0.286 0.429 0.513 0.622 0.517 [2025-04-30 09:38:01,217 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 09:38:01,217 INFO hook.py line 480 1619929] Total Process Time: 21.465 s [2025-04-30 09:38:01,217 INFO hook.py line 481 1619929] Average Process Time: 431.969 ms [2025-04-30 09:38:01,217 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 09:38:01,384 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 09:38:01,390 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 09:39:32,935 INFO hook.py line 650 1619929] Train: [512/512][50/242] Data 0.019 (0.017) Batch 1.455 (1.508) Remain 00:04:49 loss: 3.9924 Lr: 1.10964e-06 Mem R(MA/MR): 23222 (21973/36194) [2025-04-30 09:40:46,361 INFO hook.py line 650 1619929] Train: [512/512][100/242] Data 0.021 (0.017) Batch 1.497 (1.488) Remain 00:03:31 loss: 4.4945 Lr: 9.04423e-07 Mem R(MA/MR): 23222 (21973/36194) [2025-04-30 09:42:01,699 INFO hook.py line 650 1619929] Train: [512/512][150/242] Data 0.018 (0.017) Batch 1.528 (1.494) Remain 00:02:17 loss: 4.7171 Lr: 6.93839e-07 Mem R(MA/MR): 25562 (21973/36194) [2025-04-30 09:43:15,941 INFO hook.py line 650 1619929] Train: [512/512][200/242] Data 0.014 (0.017) Batch 1.498 (1.492) Remain 00:01:02 loss: 4.0534 Lr: 4.75757e-07 Mem R(MA/MR): 25574 (21973/36194) [2025-04-30 09:44:14,659 INFO misc.py line 135 1619929] Train result: loss_cls: 0.2126 loss_mask: 0.0290 loss_dice: 1.6816 loss_score: 0.0000 loss_bbox: 0.0445 loss_sp_cls: 0.6611 loss: 4.2381 [2025-04-30 09:44:17,796 INFO hook.py line 408 1619929] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>> [2025-04-30 09:44:20,300 INFO hook.py line 449 1619929] Test: [1/50] Loss 2.9476 Process Time: 0.371 Mem R(MA/MR): 4106 (21973/36194) [2025-04-30 09:44:22,122 INFO hook.py line 449 1619929] Test: [2/50] Loss 5.8406 Process Time: 0.647 Mem R(MA/MR): 6968 (21973/36194) [2025-04-30 09:44:23,933 INFO hook.py line 449 1619929] Test: [3/50] Loss 7.3257 Process Time: 0.720 Mem R(MA/MR): 9458 (21973/36194) [2025-04-30 09:44:32,189 INFO hook.py line 449 1619929] Test: [4/50] Loss 5.3378 Process Time: 0.977 Mem R(MA/MR): 19376 (21973/36194) [2025-04-30 09:44:33,241 INFO hook.py line 449 1619929] Test: [5/50] Loss 5.4989 Process Time: 0.356 Mem R(MA/MR): 6850 (21973/36194) [2025-04-30 09:44:34,833 INFO hook.py line 449 1619929] Test: [6/50] Loss 4.4724 Process Time: 0.405 Mem R(MA/MR): 11070 (21973/36194) [2025-04-30 09:44:35,730 INFO hook.py line 449 1619929] Test: [7/50] Loss 5.9024 Process Time: 0.343 Mem R(MA/MR): 6096 (21973/36194) [2025-04-30 09:44:36,367 INFO hook.py line 449 1619929] Test: [8/50] Loss 5.2708 Process Time: 0.185 Mem R(MA/MR): 4140 (21973/36194) [2025-04-30 09:44:37,355 INFO hook.py line 449 1619929] Test: [9/50] Loss 4.0838 Process Time: 0.295 Mem R(MA/MR): 11128 (21973/36194) [2025-04-30 09:44:39,028 INFO hook.py line 449 1619929] Test: [10/50] Loss 4.4842 Process Time: 0.262 Mem R(MA/MR): 9216 (21973/36194) [2025-04-30 09:44:42,285 INFO hook.py line 449 1619929] Test: [11/50] Loss 11.6194 Process Time: 0.964 Mem R(MA/MR): 18556 (21973/36194) [2025-04-30 09:44:45,426 INFO hook.py line 449 1619929] Test: [12/50] Loss 7.3757 Process Time: 0.861 Mem R(MA/MR): 15298 (21973/36194) [2025-04-30 09:44:46,509 INFO hook.py line 449 1619929] Test: [13/50] Loss 6.7619 Process Time: 0.251 Mem R(MA/MR): 8466 (21973/36194) [2025-04-30 09:44:46,861 INFO hook.py line 449 1619929] Test: [14/50] Loss 3.2230 Process Time: 0.126 Mem R(MA/MR): 4446 (21973/36194) [2025-04-30 09:44:49,785 INFO hook.py line 449 1619929] Test: [15/50] Loss 12.4066 Process Time: 0.423 Mem R(MA/MR): 16378 (21973/36194) [2025-04-30 09:44:51,766 INFO hook.py line 449 1619929] Test: [16/50] Loss 6.4493 Process Time: 0.452 Mem R(MA/MR): 14388 (21973/36194) [2025-04-30 09:44:52,417 INFO hook.py line 449 1619929] Test: [17/50] Loss 5.3029 Process Time: 0.202 Mem R(MA/MR): 6432 (21973/36194) [2025-04-30 09:44:53,329 INFO hook.py line 449 1619929] Test: [18/50] Loss 2.9130 Process Time: 0.301 Mem R(MA/MR): 7870 (21973/36194) [2025-04-30 09:44:54,626 INFO hook.py line 449 1619929] Test: [19/50] Loss 5.9433 Process Time: 0.268 Mem R(MA/MR): 5626 (21973/36194) [2025-04-30 09:44:56,014 INFO hook.py line 449 1619929] Test: [20/50] Loss 10.3125 Process Time: 0.238 Mem R(MA/MR): 11208 (21973/36194) [2025-04-30 09:45:04,464 INFO hook.py line 449 1619929] Test: [21/50] Loss 10.2321 Process Time: 0.858 Mem R(MA/MR): 23796 (21973/36194) [2025-04-30 09:45:05,616 INFO hook.py line 449 1619929] Test: [22/50] Loss 5.6000 Process Time: 0.574 Mem R(MA/MR): 6488 (21973/36194) [2025-04-30 09:45:16,492 INFO hook.py line 449 1619929] Test: [23/50] Loss 18.9483 Process Time: 0.691 Mem R(MA/MR): 9972 (21973/36194) [2025-04-30 09:45:17,191 INFO hook.py line 449 1619929] Test: [24/50] Loss 4.5138 Process Time: 0.222 Mem R(MA/MR): 5080 (21973/36194) [2025-04-30 09:45:18,167 INFO hook.py line 449 1619929] Test: [25/50] Loss 3.0414 Process Time: 0.251 Mem R(MA/MR): 8910 (21973/36194) [2025-04-30 09:45:25,058 INFO hook.py line 449 1619929] Test: [26/50] Loss 10.6994 Process Time: 1.403 Mem R(MA/MR): 31474 (21973/36194) [2025-04-30 09:45:28,290 INFO hook.py line 449 1619929] Test: [27/50] Loss 6.4137 Process Time: 0.574 Mem R(MA/MR): 9722 (21973/36194) [2025-04-30 09:45:29,350 INFO hook.py line 449 1619929] Test: [28/50] Loss 6.5098 Process Time: 0.201 Mem R(MA/MR): 8566 (21973/36194) [2025-04-30 09:45:34,363 INFO hook.py line 449 1619929] Test: [29/50] Loss 5.6320 Process Time: 0.391 Mem R(MA/MR): 16672 (21973/36194) [2025-04-30 09:45:35,323 INFO hook.py line 449 1619929] Test: [30/50] Loss 6.3013 Process Time: 0.314 Mem R(MA/MR): 7438 (21973/36194) [2025-04-30 09:45:39,080 INFO hook.py line 449 1619929] Test: [31/50] Loss 7.0791 Process Time: 0.443 Mem R(MA/MR): 20424 (21973/36194) [2025-04-30 09:45:39,322 INFO hook.py line 449 1619929] Test: [32/50] Loss 4.3088 Process Time: 0.104 Mem R(MA/MR): 3770 (21973/36194) [2025-04-30 09:45:43,416 INFO hook.py line 449 1619929] Test: [33/50] Loss 11.7233 Process Time: 0.457 Mem R(MA/MR): 24586 (21973/36194) [2025-04-30 09:45:45,299 INFO hook.py line 449 1619929] Test: [34/50] Loss 3.5109 Process Time: 0.545 Mem R(MA/MR): 9494 (21973/36194) [2025-04-30 09:45:47,492 INFO hook.py line 449 1619929] Test: [35/50] Loss 8.3691 Process Time: 0.441 Mem R(MA/MR): 13876 (21973/36194) [2025-04-30 09:45:48,000 INFO hook.py line 449 1619929] Test: [36/50] Loss 5.2288 Process Time: 0.164 Mem R(MA/MR): 6362 (21973/36194) [2025-04-30 09:45:52,388 INFO hook.py line 449 1619929] Test: [37/50] Loss 13.7477 Process Time: 1.054 Mem R(MA/MR): 28264 (21973/36194) [2025-04-30 09:45:54,262 INFO hook.py line 449 1619929] Test: [38/50] Loss 4.7407 Process Time: 0.418 Mem R(MA/MR): 10426 (21973/36194) [2025-04-30 09:45:54,721 INFO hook.py line 449 1619929] Test: [39/50] Loss 6.2266 Process Time: 0.144 Mem R(MA/MR): 5236 (21973/36194) [2025-04-30 09:45:55,856 INFO hook.py line 449 1619929] Test: [40/50] Loss 3.6185 Process Time: 0.228 Mem R(MA/MR): 9804 (21973/36194) [2025-04-30 09:45:56,985 INFO hook.py line 449 1619929] Test: [41/50] Loss 3.5481 Process Time: 0.360 Mem R(MA/MR): 8702 (21973/36194) [2025-04-30 09:45:57,547 INFO hook.py line 449 1619929] Test: [42/50] Loss 6.3871 Process Time: 0.168 Mem R(MA/MR): 5242 (21973/36194) [2025-04-30 09:45:58,034 INFO hook.py line 449 1619929] Test: [43/50] Loss 4.6683 Process Time: 0.155 Mem R(MA/MR): 5270 (21973/36194) [2025-04-30 09:45:58,902 INFO hook.py line 449 1619929] Test: [44/50] Loss 8.3182 Process Time: 0.397 Mem R(MA/MR): 6850 (21973/36194) [2025-04-30 09:45:59,845 INFO hook.py line 449 1619929] Test: [45/50] Loss 4.3612 Process Time: 0.429 Mem R(MA/MR): 5026 (21973/36194) [2025-04-30 09:46:02,585 INFO hook.py line 449 1619929] Test: [46/50] Loss 11.3974 Process Time: 0.762 Mem R(MA/MR): 14136 (21973/36194) [2025-04-30 09:46:11,177 INFO hook.py line 449 1619929] Test: [47/50] Loss 5.7000 Process Time: 0.937 Mem R(MA/MR): 20172 (21973/36194) [2025-04-30 09:46:22,418 INFO hook.py line 449 1619929] Test: [48/50] Loss 11.2894 Process Time: 2.271 Mem R(MA/MR): 35334 (21973/36194) [2025-04-30 09:46:23,037 INFO hook.py line 449 1619929] Test: [49/50] Loss 3.0638 Process Time: 0.217 Mem R(MA/MR): 5476 (21973/36194) [2025-04-30 09:46:25,378 INFO hook.py line 449 1619929] Test: [50/50] Loss 5.2052 Process Time: 0.471 Mem R(MA/MR): 13458 (21973/36194) [2025-04-30 09:46:29,227 INFO hook.py line 372 1619929] ################################################################## [2025-04-30 09:46:29,228 INFO hook.py line 380 1619929] what : AP AP_50% AP_25% Prec_50% Rec_50% [2025-04-30 09:46:29,228 INFO hook.py line 381 1619929] ################################################################## [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] table : 0.288 0.623 0.755 0.785 0.618 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] door : 0.472 0.745 0.908 0.868 0.747 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] ceiling lamp : 0.584 0.780 0.878 0.849 0.746 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] cabinet : 0.356 0.537 0.568 0.613 0.567 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] blinds : 0.629 0.838 0.858 0.864 0.826 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] curtain : 0.456 0.547 0.793 0.636 0.583 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] chair : 0.656 0.788 0.834 0.862 0.689 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] storage cabinet: 0.249 0.403 0.504 0.577 0.600 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] office chair : 0.581 0.617 0.633 0.691 0.792 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] bookshelf : 0.216 0.513 0.595 0.533 0.727 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] whiteboard : 0.551 0.716 0.768 0.774 0.686 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] window : 0.130 0.297 0.586 0.487 0.429 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] box : 0.202 0.361 0.516 0.589 0.365 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] monitor : 0.648 0.807 0.891 0.932 0.786 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] shelf : 0.152 0.314 0.458 0.667 0.333 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] heater : 0.487 0.799 0.840 0.967 0.763 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] kitchen cabinet: 0.133 0.420 0.695 0.464 0.520 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] sofa : 0.488 0.576 0.894 0.778 0.583 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] bed : 0.330 0.625 0.875 1.000 0.625 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] trash can : 0.576 0.741 0.755 0.846 0.846 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] book : 0.019 0.043 0.076 0.188 0.112 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] plant : 0.437 0.591 0.696 1.000 0.556 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] blanket : 0.515 0.692 0.692 0.818 0.818 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] tv : 0.922 1.000 1.000 1.000 1.000 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] computer tower : 0.320 0.528 0.705 0.800 0.571 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] refrigerator : 0.226 0.367 0.472 1.000 0.333 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] jacket : 0.050 0.194 0.527 0.400 0.364 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] sink : 0.368 0.643 0.822 0.750 0.682 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] bag : 0.085 0.196 0.241 0.500 0.370 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] picture : 0.146 0.316 0.409 0.552 0.410 [2025-04-30 09:46:29,228 INFO hook.py line 395 1619929] pillow : 0.597 0.801 0.818 0.750 0.789 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] towel : 0.197 0.350 0.521 0.706 0.316 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] suitcase : 0.423 0.523 0.532 1.000 0.429 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] backpack : 0.422 0.669 0.669 0.750 0.692 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] crate : 0.058 0.173 0.577 0.750 0.273 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] keyboard : 0.424 0.579 0.685 0.857 0.615 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] rack : nan nan nan nan nan [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] toilet : 0.877 1.000 1.000 1.000 1.000 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] printer : 0.393 0.423 0.436 0.667 0.444 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] poster : 0.000 0.001 0.002 0.023 0.111 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] painting : 0.036 0.038 0.045 0.077 1.000 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] microwave : 0.501 0.575 0.845 1.000 0.500 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] shoes : 0.103 0.240 0.588 0.682 0.366 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] socket : 0.180 0.433 0.635 0.673 0.471 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] bottle : 0.135 0.219 0.365 0.545 0.289 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] bucket : 0.025 0.041 0.041 0.333 0.143 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] cushion : 0.082 0.119 0.208 0.231 0.500 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] basket : 0.021 0.024 0.038 0.333 0.143 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] shoe rack : 0.000 0.000 0.500 0.000 0.000 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] telephone : 0.377 0.623 0.717 0.800 0.706 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] file folder : nan nan nan nan nan [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] laptop : 0.303 0.638 0.653 0.800 0.500 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] plant pot : 0.200 0.419 0.517 0.875 0.438 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] exhaust fan : 0.212 0.364 0.388 0.700 0.467 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] cup : 0.267 0.402 0.427 0.944 0.386 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] coat hanger : 0.135 0.396 0.677 0.667 0.500 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] light switch : 0.227 0.515 0.641 0.879 0.446 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] speaker : 0.445 0.488 0.646 0.600 0.545 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] table lamp : 0.500 0.500 1.000 1.000 0.500 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] kettle : 0.259 0.333 0.333 1.000 0.333 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] smoke detector : 0.669 0.855 0.857 0.909 0.833 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] container : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] power strip : 0.045 0.059 0.071 0.400 0.200 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] slippers : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:46:29,229 INFO hook.py line 395 1619929] paper bag : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] mouse : 0.514 0.691 0.770 0.950 0.594 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] cutting board : 0.167 0.250 0.250 1.000 0.250 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] toilet paper : 0.276 0.412 0.471 1.000 0.412 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] paper towel : 0.097 0.125 0.125 1.000 0.125 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] pot : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] clock : 0.798 0.903 0.903 0.750 1.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] pan : 0.000 0.000 0.062 0.000 0.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] tap : 0.166 0.332 0.729 0.667 0.444 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] jar : 0.000 0.000 0.071 0.000 0.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] soap dispenser : 0.532 0.800 0.800 1.000 0.800 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] binder : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] bowl : 0.460 0.667 0.667 1.000 0.667 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] tissue box : 0.035 0.062 0.083 0.250 0.500 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] whiteboard eraser: 0.174 0.413 0.434 0.500 0.833 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] toilet brush : 0.445 0.667 0.833 1.000 0.667 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] spray bottle : 0.005 0.007 0.007 0.059 0.250 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] headphones : 0.468 1.000 1.000 1.000 1.000 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] stapler : 0.014 0.046 0.093 0.125 0.667 [2025-04-30 09:46:29,230 INFO hook.py line 395 1619929] marker : 0.000 0.000 0.000 0.000 0.000 [2025-04-30 09:46:29,230 INFO hook.py line 397 1619929] ------------------------------------------------------------------ [2025-04-30 09:46:29,230 INFO hook.py line 404 1619929] average : 0.287 0.424 0.524 0.635 0.490 [2025-04-30 09:46:29,230 INFO hook.py line 405 1619929] ################################################################## [2025-04-30 09:46:29,230 INFO hook.py line 480 1619929] Total Process Time: 24.289 s [2025-04-30 09:46:29,231 INFO hook.py line 481 1619929] Average Process Time: 488.124 ms [2025-04-30 09:46:29,231 INFO hook.py line 482 1619929] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<< [2025-04-30 09:46:29,277 INFO hook.py line 685 1619929] Currently Best AP50: 0.436 [2025-04-30 09:46:29,281 INFO hook.py line 694 1619929] Saving checkpoint to: exp/scannetpp/insseg-sm-spunet-v2-3/model/model_last.pth [2025-04-30 09:46:29,950 INFO hook.py line 487 1619929] Best AP50: 0.4359