def main():
args = parse_args()
if args.seed is not None:
print(f'Set random seed to {args.seed}')
set_random_seed(args.seed)
if args.format == 'rawframes':
frame_info = parse_directory(args.src_folder,
rgb_prefix=args.rgb_prefix,
flow_x_prefix=args.flow_x_prefix,
flow_y_prefix=args.flow_y_prefix,
level=args.level)
elif args.format == 'videos':
if args.level == 1:
# search for one-level directory
video_list = glob.glob(osp.join(args.src_folder, '*'))
elif args.level == 2:
# search for two-level directory
video_list = glob.glob(osp.join(args.src_folder, '*', '*'))
else:
raise ValueError(f'level must be 1 or 2, but got {args.level}')
frame_info = {}
for video in video_list:
video_path = osp.relpath(video, args.src_folder)
# video_id: (video_relative_path, -1, -1)
frame_info[osp.splitext(video_path)[0]] = (video_path, -1, -1)
else:
raise NotImplementedError('only rawframes and videos are supported')
if args.dataset == 'ucf101':
splits = parse_ucf101_splits(args.level)
elif args.dataset == 'sthv1':
splits = parse_sthv1_splits(args.level)
elif args.dataset == 'sthv2':
splits = parse_sthv2_splits(args.level)
elif args.dataset == 'mit':
splits = parse_mit_splits()
elif args.dataset == 'mmit':
splits = parse_mmit_splits()
elif args.dataset in ['kinetics400', 'kinetics600', 'kinetics700']:
splits = parse_kinetics_splits(args.level, args.dataset)
elif args.dataset == 'hmdb51':
splits = parse_hmdb51_split(args.level)
elif args.dataset == 'jester':
splits = parse_jester_splits(args.level)
elif args.dataset == 'diving48':
splits = parse_diving48_splits()
else:
raise ValueError(
f"Supported datasets are 'ucf101, sthv1, sthv2', 'jester', "
f"'mmit', 'mit', 'kinetics400', 'kinetics600', 'kinetics700', but "
f'got {args.dataset}')
assert len(splits) == args.num_split
out_path = args.out_root_path + args.dataset
if len(splits) > 1:
for i, split in enumerate(splits):
file_lists = build_file_list(split,
frame_info,
shuffle=args.shuffle)
train_name = f'{args.dataset}_train_split_{i+1}_{args.format}.txt'
val_name = f'{args.dataset}_val_split_{i+1}_{args.format}.txt'
if args.output_format == 'txt':
with open(osp.join(out_path, train_name), 'w') as f:
f.writelines(file_lists[0][0])
with open(osp.join(out_path, val_name), 'w') as f:
f.writelines(file_lists[0][1])
elif args.output_format == 'json':
train_list = lines2dictlist(file_lists[0][0], args.format)
val_list = lines2dictlist(file_lists[0][1], args.format)
train_name = train_name.replace('.txt', '.json')
val_name = val_name.replace('.txt', '.json')
with open(osp.join(out_path, train_name), 'w') as f:
json.dump(train_list, f)
with open(osp.join(out_path, val_name), 'w') as f:
json.dump(val_list, f)
else:
lists = build_file_list(splits[0], frame_info, shuffle=args.shuffle)
if args.subset == 'train':
ind = 0
elif args.subset == 'val':
ind = 1
elif args.subset == 'test':
ind = 2
else:
raise ValueError(f"subset must be in ['train', 'val', 'test'], "
f'but got {args.subset}.')
filename = f'{args.dataset}_{args.subset}_list_{args.format}.txt'
if args.output_format == 'txt':
with open(osp.join(out_path, filename), 'w') as f:
f.writelines(lists[0][ind])
elif args.output_format == 'json':
data_list = lines2dictlist(lists[0][ind], args.format)
filename = filename.replace('.txt', '.json')
with open(osp.join(out_path, filename), 'w') as f:
json.dump(data_list, f)
def main():
args = parse_args()
if args.level == 2:
# search for two-level directory
def key_func(x):
return '/'.join(x.split('/')[-2:])
else:
# Only search for one-level directory
def key_func(x):
return x.split('/')[-1]
if args.format == 'rawframes':
frame_info = parse_directory(args.src_folder,
key_func=key_func,
rgb_prefix=args.rgb_prefix,
flow_x_prefix=args.flow_x_prefix,
flow_y_prefix=args.flow_y_prefix,
level=args.level)
elif args.format == 'videos':
if args.level == 1:
# search for one-level directory
video_list = glob.glob(osp.join(args.src_folder, '*'))
elif args.level == 2:
# search for two-level directory
video_list = glob.glob(osp.join(args.src_folder, '*', '*'))
else:
raise ValueError(f'level must be 1 or 2, but got {args.level}')
frame_info = {}
for video in video_list:
video_path = osp.relpath(video, args.src_folder)
# video_id: (video_relative_path, -1, -1)
frame_info['.'.join(video_path.split('.')[:-1])] = (video_path, -1,
-1)
else:
raise NotImplementedError('only rawframes and videos are supported')
if args.dataset == 'ucf101':
splits = parse_ucf101_splits(args.level)
elif args.dataset == 'sthv1':
splits = parse_sthv1_splits(args.level)
elif args.dataset == 'sthv2':
splits = parse_sthv2_splits(args.level)
elif args.dataset == 'mit':
splits = parse_mit_splits(args.level)
elif args.dataset == 'mmit':
splits = parse_mmit_splits(args.level)
elif args.dataset == 'kinetics400':
splits = parse_kinetics_splits(args.level)
else:
raise ValueError(
f"Supported datasets are 'ucf101, sthv1, sthv2',"
f"'mmit', 'mit', 'kinetics400' but got {args.dataset}")
assert len(splits) == args.num_split
out_path = args.out_root_path + args.dataset
if len(splits) > 1:
for i, split in enumerate(splits):
file_lists = build_file_list(split,
frame_info,
shuffle=args.shuffle)
filename = f'{args.dataset}_train_split_{i+1}_{args.format}.txt'
with open(osp.join(out_path, filename), 'w') as f:
f.writelines(file_lists[0][0])
filename = f'{args.dataset}_val_split_{i+1}_{args.format}.txt'
with open(osp.join(out_path, filename), 'w') as f:
f.writelines(file_lists[0][1])
else:
lists = build_file_list(splits[0], frame_info, shuffle=args.shuffle)
filename = f'{args.dataset}_{args.subset}_list_{args.format}.txt'
if args.subset == 'train':
ind = 0
elif args.subset == 'val':
ind = 1
elif args.subset == 'test':
ind = 2
else:
raise ValueError(f"subset must be in ['train', 'val', 'test'], "
f'but got {args.subset}.')
with open(osp.join(out_path, filename), 'w') as f:
f.writelines(lists[0][ind])