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35 lines
856 B
35 lines
856 B
2 years ago
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import torch
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from ultralytics.yolo.utils.checks import check_yaml
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from ultralytics.yolo.utils.modeling.tasks import DetectionModel
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def test_model_parser():
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cfg = check_yaml("../assets/dummy_model.yaml") # check YAML
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# Create model
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model = DetectionModel(cfg)
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print(model)
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'''
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# Options
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if opt.line_profile: # profile layer by layer
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model(im, profile=True)
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elif opt.profile: # profile forward-backward
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results = profile(input=im, ops=[model], n=3)
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elif opt.test: # test all models
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for cfg in Path(ROOT / 'models').rglob('yolo*.yaml'):
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try:
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_ = Model(cfg)
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except Exception as e:
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print(f'Error in {cfg}: {e}')
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else: # report fused model summary
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model.fuse()
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'''
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if __name__ == "__main__":
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test_model_parser()
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