Merge branch 'master' into advanced_logging

test.py

@@ -26,6 +26,7 @@ def test(data,
     # Initialize/load model and set device
     if model is None:
         training = False
+        merge = opt.merge  # use Merge NMS
         device = torch_utils.select_device(opt.device, batch_size=batch_size)
 
         # Remove previous
@@ -34,10 +35,8 @@ def test(data,
 
         # Load model
         google_utils.attempt_download(weights)
-        model = torch.load(weights, map_location=device)['model'].float()  # load to FP32
-        torch_utils.model_info(model)
-        model.fuse()
-        model.to(device)
+        model = torch.load(weights, map_location=device)['model'].float().fuse().to(device)  # load to FP32
+        imgsz = check_img_size(imgsz, s=model.stride.max())  # check img_size
 
         # Multi-GPU disabled, incompatible with .half() https://github.com/ultralytics/yolov5/issues/99
         # if device.type != 'cpu' and torch.cuda.device_count() > 1:
@@ -62,7 +61,6 @@ def test(data,
 
     # Dataloader
     if dataloader is None:  # not training
-        merge = opt.merge  # use Merge NMS
         img = torch.zeros((1, 3, imgsz, imgsz), device=device)  # init img
         _ = model(img.half() if half else img) if device.type != 'cpu' else None  # run once
         path = data['test'] if opt.task == 'test' else data['val']  # path to val/test images
@@ -246,7 +244,6 @@ if __name__ == '__main__':
     parser.add_argument('--merge', action='store_true', help='use Merge NMS')
     parser.add_argument('--verbose', action='store_true', help='report mAP by class')
     opt = parser.parse_args()
-    opt.img_size = check_img_size(opt.img_size)
     opt.save_json = opt.save_json or opt.data.endswith('coco.yaml')
     opt.data = check_file(opt.data)  # check file
     print(opt)