Update app.py

app.py

@@ -10,7 +10,6 @@ import numpy as np
 import threading
 
 should_continue = True
-os.environ["GRADIO_CACHE_EXAMPLES"] = "lazy"
 
 @spaces.GPU(duration=120)
 def yolov9_inference(model_id, img_path=None, vid_path=None, tracking_algorithm = None):
@@ -31,7 +30,7 @@ def yolov9_inference(model_id, img_path=None, vid_path=None, tracking_algorithm
         img.save(img_path)
         input_path = img_path
         print(input_path)
-        output_path = run(weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='cpu', hide_conf= True)
+        output_path = run(weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='0', hide_conf= True)
     elif vid_path is not None:
         vid_name = 'output.mp4'
 
@@ -68,11 +67,12 @@ def yolov9_inference(model_id, img_path=None, vid_path=None, tracking_algorithm
         out.release()
         input_path = vid_name
         if tracking_algorithm == 'deep_sort':
-            output_path = run_deepsort(weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='cpu', draw_trails=True)
+            output_path = run_deepsort(weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='0', draw_trails=True)
         elif tracking_algorithm == 'strong_sort':
-            output_path = run_strongsort(yolo_weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='cpu', strong_sort_weights = "osnet_x0_25_msmt17.pt", hide_conf= True)
+            device_strongsort = torch.device('cuda:0')
+            output_path = run_strongsort(yolo_weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device=device_strongsort, strong_sort_weights = "osnet_x0_25_msmt17.pt", hide_conf= True)
         else: 
-            output_path =  run(weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='cpu', hide_conf= True)
+            output_path =  run(weights=model_id, imgsz=(image_size,image_size), conf_thres=conf_threshold, iou_thres=iou_threshold, source=input_path, device='0', hide_conf= True)
         # Assuming output_path is the path to the output file
     _, output_extension = os.path.splitext(output_path)
     if output_extension.lower() in img_extensions:
@@ -108,8 +108,8 @@ def app():
                     ],
                     value="None"
                 )
-                gr.Examples(['camera1_A_133.png'], inputs=img_path,label = "Image Example")
-                gr.Examples(['test.mp4'], inputs=vid_path, label = "Video Example")
+                gr.Examples(['camera1_A_133.png'], inputs=img_path,label = "Image Example", cache_examples = False)
+                gr.Examples(['test.mp4'], inputs=vid_path, label = "Video Example", cache_examples = False)
                 yolov9_infer = gr.Button(value="Inference")
             with gr.Column():
                 gr.HTML("<h2>Output</h2>")