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Tackling the error message mentioned in #1 #2

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Tackling the error message mentioned in #1 #2

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4 changes: 4 additions & 0 deletions data_pipeline/ntu_rgbd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,6 +51,10 @@ def make_dataset(root, has_skel, evaluation, split, subsample):
vid_names = os.listdir(os.path.join(root, rgb_folder_name))
vid_names = sorted(vid_names)

if len(vid_names) == 0:
raise BaseException('No files found. Make sure dataset is in: "{}"'.format(
root))

if evaluation == 'cross-subject' and split != 'test':
vid_names = [n for n in vid_names if int(n[9:12]) in train_cross_subject]
elif evaluation == 'cross-subject' and split == 'test':
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4 changes: 4 additions & 0 deletions data_pipeline/pku_mmd.py
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Expand Up @@ -46,6 +46,10 @@ def make_dataset(root, evaluation, mode, folder_name=rgb_folder_name, subsample_
vid_names_split = f[idx].split(', ')[:-1]
vid_names = sorted(list(set(vid_names).intersection(set(vid_names_split))))

if len(vid_names) == 0:
raise BaseException('No files found. Make sure dataset is in: "{}"'.format(
root))

if mode == 0 and subsample_rate:
# Subsample for training
vid_names = vid_names[::subsample_rate]
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