| """Link only files referenced by the selected training manifest into the data package.""" |
| import argparse |
| import json |
| from pathlib import Path |
|
|
| DATA_ROOT = Path(__file__).resolve().parents[1] |
| PREFIX = 'data/source/seamless_interaction/' |
| FIELDS = ('pose_file', 'audio_file', 'audio_file_listen', 'word_file', 'flame_file') |
|
|
|
|
| def link_training_data(manifest, dataset_root, data_root, flame_root=None): |
| dataset_root, data_root = Path(dataset_root).resolve(), Path(data_root).resolve() |
| rows = json.loads(Path(manifest).read_text())['data'] |
| sources = {} |
| for row in rows: |
| for field in FIELDS: |
| path = row[field] |
| assert path.startswith(PREFIX), f'Unexpected {field} path: {path}' |
| name = Path(path[len(PREFIX):]) |
| assert not name.is_absolute() and '..' not in name.parts, name |
| source = (Path(flame_root).resolve() / name.name |
| if field == 'flame_file' and flame_root else dataset_root / name) |
| assert name not in sources or sources[name] == source, name |
| sources[name] = source |
| for source in sources.values(): |
| assert source.is_file(), source |
| for name, source in sorted(sources.items()): |
| destination = data_root / 'source/seamless_interaction' / name |
| if destination.is_symlink(): |
| assert destination.resolve() == source.resolve(), destination |
| else: |
| assert not destination.exists(), destination |
| destination.parent.mkdir(parents=True, exist_ok=True) |
| destination.symlink_to(source) |
| return len(sources) |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument('--input', default=str(DATA_ROOT / 'manifests/train_selected81.json')) |
| parser.add_argument('--dataset-root', required=True, help='Downloaded Seamless Interaction root') |
| parser.add_argument('--flame-root', help='Directory of freshly extracted <pose_stem>_flame.npz labels') |
| parser.add_argument('--data-root', default=str(DATA_ROOT), help='Data package receiving source links') |
| args = parser.parse_args() |
| count = link_training_data(args.input, args.dataset_root, args.data_root, args.flame_root) |
| print(f'Linked {count} unique training files under {Path(args.data_root) / "source/seamless_interaction"}') |
|
|
|
|
| if __name__ == '__main__': |
| main() |
|
|
