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@@ -27,15 +27,19 @@ def create(name, pretrained, channels, classes): |
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Returns: |
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pytorch model |
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""" |
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config = os.path.join(os.path.dirname(__file__), 'models', '%s.yaml' % name) # model.yaml path |
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model = Model(config, channels, classes) |
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if pretrained: |
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ckpt = '%s.pt' % name # checkpoint filename |
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google_utils.attempt_download(ckpt) # download if not found locally |
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state_dict = torch.load(ckpt, map_location=torch.device('cpu'))['model'].float().state_dict() # to FP32 |
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state_dict = {k: v for k, v in state_dict.items() if model.state_dict()[k].shape == v.shape} # filter |
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model.load_state_dict(state_dict, strict=False) # load |
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return model |
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try: |
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config = os.path.join(os.path.dirname(__file__), 'models', '%s.yaml' % name) # model.yaml path |
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model = Model(config, channels, classes) |
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if pretrained: |
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ckpt = '%s.pt' % name # checkpoint filename |
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google_utils.attempt_download(ckpt) # download if not found locally |
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state_dict = torch.load(ckpt, map_location=torch.device('cpu'))['model'].float().state_dict() # to FP32 |
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state_dict = {k: v for k, v in state_dict.items() if model.state_dict()[k].shape == v.shape} # filter |
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model.load_state_dict(state_dict, strict=False) # load |
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return model |
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except Exception as e: |
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help_url = 'https://github.com/ultralytics/yolov5/issues/36' |
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print('%s\nCache is out of date. Delete cache and retry. See %s for help.' % (e, help_url)) |
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def yolov5s(pretrained=False, channels=3, classes=80): |