Download preprocess/prepare_testset.py from tsinghua-ee/ELLSA2_data: direct link, hf CLI and curl.
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https://huggingface.co/datasets/tsinghua-ee/ELLSA2_data/resolve/main/preprocess/prepare_testset.py
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hf download hf://datasets/tsinghua-ee/ELLSA2_data/preprocess/prepare_testset.py
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2.42 kB
| """Materialize portable test manifests as inference and rendering jobs.""" | |
| import argparse | |
| import json | |
| from pathlib import Path | |
| import os | |
| ROOT = Path(os.environ.get("ELLSA2_DATA_ROOT", Path(__file__).resolve().parents[1])).expanduser().resolve() | |
| def read_manifest(): | |
| return [json.loads(s) for s in (ROOT / "testset/manifest.jsonl").read_text().splitlines() if s] | |
| def prepare(output_dir, test_id=None, limit=0): | |
| output_dir = Path(output_dir).resolve() | |
| output_dir.mkdir(parents=True, exist_ok=True) | |
| rows = read_manifest() | |
| if test_id: | |
| rows = [r for r in rows if r["group_id"] == test_id] | |
| assert rows, f"Unknown test id: {test_id}" | |
| rows = rows[:limit or None] | |
| jobs = [] | |
| render = [] | |
| for r in rows: | |
| gid = r["group_id"] | |
| motion = output_dir / (gid + ".npz") | |
| jobs.append({"group_id": gid, "audio_file": str(ROOT / r["audio20_target"]), | |
| "audio_file_listen": str(ROOT / r["audio20_partner"]), | |
| "word_file": str(ROOT / r["metadata20_target"]), | |
| "word_file_listen": str(ROOT / r["metadata20_partner"]), | |
| "motion_style_pose_path": str(ROOT / r["motion_style_pose_path"]), | |
| "motion_style_flame_path": str(ROOT / r["motion_style_flame_path"]) if r.get("motion_style_flame_path") else "", | |
| "motion_style_start": 0, "motion_style_length": 612, | |
| "output_path": str(motion), "sampling_seed": 0}) | |
| render.append({"group_id": gid, "system_id": "ELLSA2", "npz_path": str(motion), | |
| "wav_path": str(ROOT / r["audio20_target"]), | |
| "video_path": str(output_dir / "videos" / (gid + ".mp4")), | |
| "ready_path": str(output_dir / "render_ready" / (gid + ".ready")), | |
| "tmp_dir": str(output_dir / "render_tmp" / gid)}) | |
| job_file = output_dir / "inference_jobs.json" | |
| job_file.write_text(json.dumps({"data": jobs}, indent=2)) | |
| (output_dir / "render_jobs.json").write_text(json.dumps(render, indent=2)) | |
| return job_file | |
| def main(): | |
| p = argparse.ArgumentParser() | |
| p.add_argument("--output-dir", default="outputs/test") | |
| p.add_argument("--test-id") | |
| p.add_argument("--limit", type=int, default=0) | |
| args = p.parse_args() | |
| print(prepare(args.output_dir, args.test_id, args.limit)) | |
| if __name__ == "__main__": | |
| main() | |