update check_img_size() for model strides
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@@ -25,6 +25,7 @@ def detect(save_img=False):
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# torch.save(torch.load(weights, map_location=device), weights) # update model if SourceChangeWarning
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# model.fuse()
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model.to(device).eval()
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imgsz = check_img_size(imgsz, s=model.model[-1].stride.max()) # check img_size
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if half:
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model.half() # to FP16
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@@ -152,7 +153,6 @@ if __name__ == '__main__':
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parser.add_argument('--agnostic-nms', action='store_true', help='class-agnostic NMS')
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parser.add_argument('--augment', action='store_true', help='augmented inference')
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opt = parser.parse_args()
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opt.img_size = check_img_size(opt.img_size)
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print(opt)
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with torch.no_grad():
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@@ -34,6 +34,7 @@ def test(data,
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torch_utils.model_info(model)
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model.fuse()
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model.to(device)
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imgsz = check_img_size(imgsz, s=model.model[-1].stride.max()) # check img_size
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# Multi-GPU disabled, incompatible with .half() https://github.com/ultralytics/yolov5/issues/99
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# if device.type != 'cpu' and torch.cuda.device_count() > 1:
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@@ -242,7 +243,6 @@ if __name__ == '__main__':
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parser.add_argument('--merge', action='store_true', help='use Merge NMS')
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parser.add_argument('--verbose', action='store_true', help='report mAP by class')
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opt = parser.parse_args()
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opt.img_size = check_img_size(opt.img_size)
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opt.save_json = opt.save_json or opt.data.endswith('coco.yaml')
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opt.data = check_file(opt.data) # check file
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print(opt)
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