File size: 971 Bytes
3f1bb3e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 |
import matplotlib.pyplot as plt
import requests, validators
import torch
import pathlib
import numpy as np
from PIL import Image
from transformers import DetrFeatureExtractor, DetrForSegmentation, MaskFormerImageProcessor, MaskFormerForInstanceSegmentation
from transformers.models.detr.feature_extraction_detr import rgb_to_id
TEST_IMAGE = Image.open(r"images/Test_Street_VisDrone.JPG")
MODEL_NAME_DETR = "facebook/detr-resnet-50-panoptic"
MODEL_NAME_MASKFORMER = "facebook/maskformer-swin-large-coco"
DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
#######
# Parameters
#######
image = TEST_IMAGE
model_name = MODEL_NAME_MASKFORMER
# Starting with MaskFormer
processor = MaskFormerImageProcessor.from_pretrained(model_name)
model = MaskFormerForInstanceSegmentation.from_pretrained(model_name)
model.to(DEVICE)
# img = np.array(TEST_IMAGE)
inputs = processor(images=image, return_tensors="pt")
inputs.to(DEVICE)
outputs = model(**inputs) |