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Download scripts/validate_metadata.py from mandipgoswami/rirmega: direct link, hf CLI and curl.
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https://huggingface.co/datasets/mandipgoswami/rirmega/resolve/refs%2Fpr%2F2/scripts/validate_metadata.py
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hf download hf://datasets/mandipgoswami/rirmega@refs/pr/2/scripts/validate_metadata.py
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curl -L -o validate_metadata.py https://huggingface.co/datasets/mandipgoswami/rirmega/resolve/refs%2Fpr%2F2/scripts/validate_metadata.py
3.12 kB
| # scripts/validate_metadata.py | |
| import csv, sys, pathlib | |
| # Two accepted schemas: | |
| REQUIRED_A = {"rir_id","file_path","sample_rate","rir_length","method", | |
| "src_x","src_y","src_z","mic_x","mic_y","mic_z", | |
| "distance","azimuth_deg","elevation_deg", | |
| "rt60_t20","rt60_t30","drr_db","room_l","room_w","room_h","vol_m3","split"} | |
| REQUIRED_B = {"id","split","fs","wav"} # compact schema | |
| def find_default_meta(): | |
| here = pathlib.Path(__file__).resolve().parents[1] | |
| candidates = [ | |
| here / "data" / "metadata" / "metadata.csv", | |
| here / "data" / "metadata.csv", | |
| ] | |
| for p in candidates: | |
| if p.exists(): | |
| return p | |
| return None | |
| def validate(path: pathlib.Path): | |
| with path.open(newline="", encoding="utf-8", errors="replace") as f: | |
| r = csv.DictReader(f) | |
| headers = { (h or "").strip().lstrip("\ufeff").lower() for h in (r.fieldnames or []) } | |
| if REQUIRED_A.issubset(headers): | |
| schema = "A" | |
| elif REQUIRED_B.issubset(headers): | |
| schema = "B" | |
| else: | |
| missingA = sorted(REQUIRED_A - headers) | |
| missingB = sorted(REQUIRED_B - headers) | |
| raise SystemExit( | |
| "metadata.csv does not match a known schema.\n" | |
| f"- Missing for Schema A: {missingA}\n" | |
| f"- Missing for Schema B: {missingB}\n" | |
| f"Headers seen: {sorted(headers)}" | |
| ) | |
| for i,row in enumerate(r, 1): | |
| if schema == "A": | |
| if not (row.get("file_path") or "").strip(): | |
| raise SystemExit(f"row {i}: empty file_path") | |
| try: | |
| if int(float(row["sample_rate"])) <= 0: | |
| raise ValueError | |
| except Exception: | |
| raise SystemExit(f"row {i}: invalid sample_rate -> {row.get('sample_rate')}") | |
| try: | |
| if int(float(row["rir_length"])) <= 0: | |
| raise ValueError | |
| except Exception: | |
| raise SystemExit(f"row {i}: invalid rir_length -> {row.get('rir_length')}") | |
| else: | |
| if not (row.get("wav") or "").strip(): | |
| raise SystemExit(f"row {i}: empty wav path") | |
| try: | |
| if int(float(row["fs"])) <= 0: | |
| raise ValueError | |
| except Exception: | |
| raise SystemExit(f"row {i}: invalid fs -> {row.get('fs')}") | |
| print(f"metadata OK ✅ ({schema=}) @ {path}") | |
| if __name__ == "__main__": | |
| # Accept optional path; fallback to default | |
| p = None | |
| if len(sys.argv) >= 2 and sys.argv[1].strip(): | |
| p = pathlib.Path(sys.argv[1]).expanduser().resolve() | |
| if not p.exists(): | |
| raise SystemExit(f"[ERR] Not found: {p}") | |
| else: | |
| p = find_default_meta() | |
| if p is None: | |
| raise SystemExit("Usage: python scripts/validate_metadata.py <path/to/metadata.csv>\n" | |
| "Could not auto-find data/metadata/metadata.csv") | |
| validate(p) | |