Filter the None labels (#705)
* the value should be a list to unpacking * filter the None labels
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@@ -375,7 +375,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
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pbar = tqdm(self.label_files)
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pbar = tqdm(self.label_files)
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for i, file in enumerate(pbar):
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for i, file in enumerate(pbar):
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l = self.labels[i] # label
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l = self.labels[i] # label
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if l.shape[0]:
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if l is not None and l.shape[0]:
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assert l.shape[1] == 5, '> 5 label columns: %s' % file
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assert l.shape[1] == 5, '> 5 label columns: %s' % file
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assert (l >= 0).all(), 'negative labels: %s' % file
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assert (l >= 0).all(), 'negative labels: %s' % file
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assert (l[:, 1:] <= 1).all(), 'non-normalized or out of bounds coordinate labels: %s' % file
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assert (l[:, 1:] <= 1).all(), 'non-normalized or out of bounds coordinate labels: %s' % file
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