Download tools/load_sample.py from LinzhouLi/RealDenseFace-Ava256: direct link, hf CLI and curl.
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https://huggingface.co/datasets/LinzhouLi/RealDenseFace-Ava256/resolve/main/tools/load_sample.py
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hf download hf://datasets/LinzhouLi/RealDenseFace-Ava256/tools/load_sample.py
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curl -L -o load_sample.py https://huggingface.co/datasets/LinzhouLi/RealDenseFace-Ava256/resolve/main/tools/load_sample.py
2.1 kB
| """Read one observation directly from a downloaded dataset's tar archive.""" | |
| import argparse | |
| import io | |
| import json | |
| import tarfile | |
| from pathlib import Path | |
| import numpy as np | |
| import pyarrow.parquet as pq | |
| from PIL import Image | |
| def load_sample(root, subject, frame_id, camera_id): | |
| root = Path(root) | |
| records = pq.read_table(root / "metadata/subjects" / f"{subject}.parquet", filters=[ | |
| ("subject_id", "=", subject), ("frame_id", "=", frame_id), ("camera_id", "=", camera_id) | |
| ]).to_pylist() | |
| if len(records) != 1: | |
| raise ValueError(f"Expected one observation, got {len(records)}") | |
| record = records[0] | |
| with tarfile.open(root / record["archive_path"], "r:") as archive: | |
| with Image.open(io.BytesIO(archive.extractfile(record["image_member"]).read())) as image: | |
| rgb = np.asarray(image).copy() | |
| with Image.open(io.BytesIO(archive.extractfile(record["segmentation_member"]).read())) as image: | |
| segmentation = np.asarray(image).copy() | |
| with np.load(root / record["registration_path"], allow_pickle=False) as data: | |
| row = record["registration_row"] | |
| assert str(data["frame_ids"][row]) == frame_id | |
| geometry = {key: data[key][row].copy() for key in ( | |
| "identity", "expression", "pose", "translation", "v_offsets", "vertices_world", "joints_world" | |
| )} | |
| cameras = json.loads((root / "metadata/cameras.json").read_text()) | |
| return {"image": rgb, "segmentation": segmentation, "foreground": segmentation > 0, | |
| "camera": cameras[subject][camera_id], "metadata": record, **geometry} | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("--root", type=Path, required=True) | |
| parser.add_argument("--subject", required=True) | |
| parser.add_argument("--frame", required=True) | |
| parser.add_argument("--camera", required=True) | |
| args = parser.parse_args() | |
| sample = load_sample(args.root, args.subject, args.frame, args.camera) | |
| print({k: (list(v.shape) if isinstance(v, np.ndarray) else v) for k, v in sample.items()}) | |