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@@ -72,7 +72,7 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary |
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# Hyperparameters |
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if isinstance(hyp, str): |
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with open(hyp) as f: |
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with open(hyp, errors='ignore') as f: |
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hyp = yaml.safe_load(f) # load hyps dict |
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LOGGER.info(colorstr('hyperparameters: ') + ', '.join(f'{k}={v}' for k, v in hyp.items())) |
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@@ -488,7 +488,7 @@ def main(opt, callbacks=Callbacks()): |
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if opt.resume and not check_wandb_resume(opt) and not opt.evolve: # resume an interrupted run |
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ckpt = opt.resume if isinstance(opt.resume, str) else get_latest_run() # specified or most recent path |
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assert os.path.isfile(ckpt), 'ERROR: --resume checkpoint does not exist' |
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with open(Path(ckpt).parent.parent / 'opt.yaml') as f: |
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with open(Path(ckpt).parent.parent / 'opt.yaml', errors='ignore') as f: |
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opt = argparse.Namespace(**yaml.safe_load(f)) # replace |
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opt.cfg, opt.weights, opt.resume = '', ckpt, True # reinstate |
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LOGGER.info(f'Resuming training from {ckpt}') |
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@@ -552,7 +552,7 @@ def main(opt, callbacks=Callbacks()): |
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'mixup': (1, 0.0, 1.0), # image mixup (probability) |
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'copy_paste': (1, 0.0, 1.0)} # segment copy-paste (probability) |
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with open(opt.hyp) as f: |
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with open(opt.hyp, errors='ignore') as f: |
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hyp = yaml.safe_load(f) # load hyps dict |
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if 'anchors' not in hyp: # anchors commented in hyp.yaml |
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hyp['anchors'] = 3 |