| |
| """Validate generated proxy videos and write mechanics/visual evaluator manifests.""" |
| from __future__ import annotations |
|
|
| import argparse |
| import csv |
| import hashlib |
| import json |
| import os |
| from pathlib import Path |
|
|
|
|
| ROOT = Path(__file__).resolve().parents[1] |
|
|
|
|
| def sha256_file(path: Path) -> str: |
| digest = hashlib.sha256() |
| with path.open("rb") as handle: |
| for chunk in iter(lambda: handle.read(16 * 1024 * 1024), b""): |
| digest.update(chunk) |
| return digest.hexdigest() |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("--selection", type=Path, default=ROOT / "evaluation/proxy100/selection.json") |
| parser.add_argument("--run-name", required=True) |
| parser.add_argument("--checkpoint", type=Path, required=True) |
| parser.add_argument("--generated-root", type=Path, default=ROOT / "evaluation/proxy100/generated") |
| args = parser.parse_args() |
|
|
| selection = json.loads(args.selection.resolve().read_text(encoding="utf-8")) |
| output_dir = (args.generated_root / args.run_name).resolve() |
| mechanics_rows = [] |
| visual_rows = [] |
| missing = [] |
| for sample in selection["samples"]: |
| prediction = output_dir / sample["output_name"] |
| if not prediction.is_file() or prediction.stat().st_size == 0: |
| missing.append(str(prediction)) |
| continue |
| relative_prediction = prediction.relative_to(args.selection.resolve().parent).as_posix() |
| mechanics_rows.append({"id": sample["id"], "prediction": relative_prediction, "label": sample["label"]}) |
| if sample.get("reference_video"): |
| reference = ROOT / sample["reference_video"] |
| visual_rows.append( |
| { |
| "id": sample["id"], |
| "prediction": relative_prediction, |
| "reference": os.path.relpath(reference, args.selection.resolve().parent), |
| "label": sample["label"], |
| } |
| ) |
| if missing: |
| raise FileNotFoundError(f"Missing {len(missing)} generated videos; first: {missing[0]}") |
|
|
| mechanics_path = args.selection.resolve().parent / f"manifest_{args.run_name}_mechanics.csv" |
| with mechanics_path.open("w", newline="", encoding="utf-8") as handle: |
| writer = csv.DictWriter(handle, fieldnames=("id", "prediction", "label")) |
| writer.writeheader(); writer.writerows(mechanics_rows) |
| visual_path = args.selection.resolve().parent / f"manifest_{args.run_name}_visual.csv" |
| with visual_path.open("w", newline="", encoding="utf-8") as handle: |
| writer = csv.DictWriter(handle, fieldnames=("id", "prediction", "reference", "label")) |
| writer.writeheader(); writer.writerows(visual_rows) |
|
|
| provenance = { |
| "run_name": args.run_name, |
| "selection": str(args.selection.resolve().relative_to(ROOT)), |
| "checkpoint": str(args.checkpoint.resolve().relative_to(ROOT)), |
| "checkpoint_sha256": sha256_file(args.checkpoint.resolve()), |
| "mechanics_samples": len(mechanics_rows), |
| "visual_samples": len(visual_rows), |
| "mechanics_manifest": str(mechanics_path.relative_to(ROOT)), |
| "visual_manifest": str(visual_path.relative_to(ROOT)), |
| } |
| (args.selection.resolve().parent / f"provenance_{args.run_name}.json").write_text( |
| json.dumps(provenance, indent=2) + "\n", encoding="utf-8" |
| ) |
| print(json.dumps(provenance, indent=2)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
