调试
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@ -428,11 +428,13 @@ class LoadImagesAndLabels(Dataset):
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# Check cache
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self.label_files = img2label_paths(self.im_files) # labels
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print('labelfile############',self.label_files)
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cache_path = (p if p.is_file() else Path(self.label_files[0]).parent).with_suffix('.cache')
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try:
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cache, exists = np.load(cache_path, allow_pickle=True).item(), True # load dict
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assert cache['version'] == self.cache_version # matches current version
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assert cache['hash'] == get_hash(self.label_files + self.im_files) # identical hash
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print('load_cache#########')
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except Exception:
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cache, exists = self.cache_labels(cache_path, prefix), False # run cache ops
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@ -447,6 +449,7 @@ class LoadImagesAndLabels(Dataset):
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# Read cache
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[cache.pop(k) for k in ('hash', 'version', 'msgs')] # remove items
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print('@@@@@@@@@@@@@@@@@@@@@')
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labels, shapes, self.segments = zip(*cache.values())
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nl = len(np.concatenate(labels, 0)) # number of labels
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assert nl > 0 or not augment, f'{prefix}All labels empty in {cache_path}, can not start training. {HELP_URL}'
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