| |
| """Validate replayed RoboTwin GT RGB against the original RGB HDF5.""" |
| import argparse |
| from pathlib import Path |
| import cv2 |
| import h5py |
| import numpy as np |
|
|
|
|
| def decode(x): |
| return cv2.imdecode(np.frombuffer(x, np.uint8), cv2.IMREAD_COLOR) |
|
|
|
|
| def main(): |
| p = argparse.ArgumentParser() |
| p.add_argument("--original", type=Path, required=True) |
| p.add_argument("--ground-truth", type=Path, required=True) |
| p.add_argument("--camera", default="head_camera") |
| p.add_argument("--samples", type=int, default=8) |
| args = p.parse_args() |
| rows = [] |
| for src in sorted(args.original.glob("episode*.hdf5")): |
| dst = args.ground_truth / src.name |
| if not dst.exists(): |
| continue |
| with h5py.File(src, "r") as a, h5py.File(dst, "r") as b: |
| x = a[f"observation/{args.camera}/rgb"] |
| y = b[f"observation/{args.camera}/rgb"] |
| if len(x) != len(y): |
| rows.append((src.stem, len(x), len(y), np.inf)) |
| continue |
| ids = np.linspace(0, len(x) - 1, min(args.samples, len(x)), dtype=int) |
| errors = [] |
| for i in ids: |
| u, v = decode(x[i]), decode(y[i]) |
| errors.append(float(np.mean(np.abs(u.astype(np.float32) - v.astype(np.float32))))) |
| rows.append((src.stem, len(x), len(y), float(np.mean(errors)))) |
| if not rows: |
| raise SystemExit("no comparable episodes") |
| for row in rows: |
| print("episode=%s original=%d replay=%d mean_abs=%.4f" % row) |
| bad = [r for r in rows if not np.isfinite(r[3]) or r[3] > 5.0] |
| print(f"checked={len(rows)} bad={len(bad)}") |
| raise SystemExit(1 if bad else 0) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
