update detect.py

detect.py

@@ -123,10 +123,11 @@ def detect(save_img=False):
                         if isinstance(vid_writer, cv2.VideoWriter):
                             vid_writer.release()  # release previous video writer
 
+                        fourcc = 'mp4v'  # output video codec
                         fps = vid_cap.get(cv2.CAP_PROP_FPS)
                         w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
                         h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-                        vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*opt.fourcc), fps, (w, h))
+                        vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*fourcc), fps, (w, h))
                     vid_writer.write(im0)
 
     if save_txt or save_img:
@@ -145,20 +146,20 @@ if __name__ == '__main__':
     parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
     parser.add_argument('--conf-thres', type=float, default=0.4, help='object confidence threshold')
     parser.add_argument('--iou-thres', type=float, default=0.5, help='IOU threshold for NMS')
-    parser.add_argument('--fourcc', type=str, default='mp4v', help='output video codec (verify ffmpeg support)')
     parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
     parser.add_argument('--view-img', action='store_true', help='display results')
     parser.add_argument('--save-txt', action='store_true', help='save results to *.txt')
     parser.add_argument('--classes', nargs='+', type=int, help='filter by class')
     parser.add_argument('--agnostic-nms', action='store_true', help='class-agnostic NMS')
     parser.add_argument('--augment', action='store_true', help='augmented inference')
+    parser.add_argument('--update', action='store_true', help='update all models')
     opt = parser.parse_args()
     print(opt)
 
     with torch.no_grad():
-        detect()
-
-        # # Update all models
-        # for opt.weights in ['yolov5s.pt', 'yolov5m.pt', 'yolov5l.pt', 'yolov5x.pt', 'yolov3-spp.pt']:
-        #     detect()
-        #     create_pretrained(opt.weights, opt.weights)
+        if opt.update:  # update all models (to fix SourceChangeWarning)
+            for opt.weights in ['yolov5s.pt', 'yolov5m.pt', 'yolov5l.pt', 'yolov5x.pt', 'yolov3-spp.pt']:
+                detect()
+                create_pretrained(opt.weights, opt.weights)
+        else:
+            detect()