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import argparse |
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import pickle |
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from collections import OrderedDict |
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from ultralytics import YOLO |
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def parse_args(): |
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parser = argparse.ArgumentParser() |
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parser.add_argument('-w', |
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'--weights', |
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type=str, |
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required=True, |
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help='YOLOv8 pytorch weights') |
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parser.add_argument('-o', |
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'--output', |
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type=str, |
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required=True, |
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help='Output file') |
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args = parser.parse_args() |
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return args |
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args = parse_args() |
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model = YOLO(args.weights) |
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model.model.fuse() |
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YOLOv8 = model.model.model |
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strides = YOLOv8[-1].stride.detach().cpu().numpy() |
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reg_max = YOLOv8[-1].dfl.conv.weight.shape[1] |
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state_dict = OrderedDict(GD=model.model.yaml['depth_multiple'], |
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GW=model.model.yaml['width_multiple'], |
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strides=strides, |
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reg_max=reg_max) |
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for name, value in YOLOv8.state_dict().items(): |
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value = value.detach().cpu().numpy() |
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i = int(name.split('.')[0]) |
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layer = YOLOv8[i] |
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module_name = layer.type.split('.')[-1] |
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stem = module_name + '.' + name |
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state_dict[stem] = value |
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with open(args.output, 'wb') as f: |
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pickle.dump(state_dict, f) |
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