updates

detect.py

@@ -156,3 +156,8 @@ if __name__ == '__main__':
 
     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)

test.py

@@ -246,7 +246,7 @@ def test(data,
 if __name__ == '__main__':
     parser = argparse.ArgumentParser(prog='test.py')
     parser.add_argument('--weights', type=str, default='weights/yolov5s.pt', help='model.pt path')
-    parser.add_argument('--data', type=str, default='data/coco.yaml', help='*.data path')
+    parser.add_argument('--data', type=str, default='data/coco128.yaml', help='*.data path')
     parser.add_argument('--batch-size', type=int, default=32, help='size of each image batch')
     parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
     parser.add_argument('--conf-thres', type=float, default=0.001, help='object confidence threshold')