Datasets:
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aa991fc 358e603 aa991fc 01eab39 aa991fc 358e603 aa991fc 358e603 aa991fc 01eab39 aa991fc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 | #!/usr/bin/env python
"""Rebuild `previews/metadata.jsonl` -- the table the HF dataset viewer renders.
One row per (capture x sampled frame). The `file_name` column is resolved by the
`imagefolder` builder into an `image` feature, so Data Studio shows a browsable
thumbnail of every QC contact sheet next to its metadata.
Columns
file_name -> image 32-view QC contact sheet [raw | omni-600 | SMPL-X]
capture PxCy
subject / session Px / Cy
role train (C1) / test (C2) / cross_reenact_driving (P5,P6 C2)
frame frame id (0-based)
video_frame the same number: d=0, video index == smplx index
n_cams cameras in the capture
n_frames fitted frames in the capture
n_views_fit views actually used by the fit at this frame
n_face_views views with an accepted MediaPipe face at this frame
stages fit schedule at this frame (A+B+C+F cold / W warm)
joint_span_y_m vertical extent of the SMPL-X joints (sanity number, not height)
videos / smplx / cameras repo-relative paths to the full-res assets
Run after every capture is staged; it rescans the whole staging tree.
Usage:
python build_metadata.py --staging /mnt/sdb/degas_project/DREAMS-AVATAR-hf/staging
"""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
import numpy as np
sys.path.insert(0, str(Path(__file__).resolve().parent))
from load_capture import VIDEO_FRAME_OFFSET # noqa: E402 single source of truth for d
def build(staging: Path) -> dict:
prev_dir = staging / "previews"
data_dir = staging / "data"
captures = sorted(p.name for p in data_dir.iterdir() if p.is_dir()) if data_dir.is_dir() else []
if not captures:
raise SystemExit(f"no captures under {data_dir}")
rows = []
for cap in captures:
d = data_dir / cap
card = json.loads((d / "capture.json").read_text())
z = np.load(d / "smplx.npz", allow_pickle=False)
frames = z["frames"].astype(int)
idx_of = {int(f): i for i, f in enumerate(frames)}
joints = z["joints"]
n_views = z["n_views"]
n_face = z["n_face_views"]
stages = z["stages"]
imgs = sorted(prev_dir.glob(f"{cap}_f*.jpg"))
for img in imgs:
fr = int(img.stem.split("_f")[1])
i = idx_of.get(fr)
if i is None:
print(f"[metadata] WARN {img.name}: frame {fr} not in smplx.npz", file=sys.stderr)
continue
j = joints[i]
rows.append({
"file_name": img.name,
"capture": cap,
"subject": card["subject"],
"session": card["session"],
"role": card.get("role", ""),
"frame": fr,
"video_frame": fr + VIDEO_FRAME_OFFSET,
"n_cams": int(card["n_cams"]),
"n_frames": int(card.get("n_frames", len(frames))),
"n_views_fit": int(n_views[i]),
"n_face_views": int(n_face[i]),
"stages": str(stages[i]),
# vertical extent of the SMPL-X joints. A cheap "did the fit explode"
# number, NOT body height: it grows when the arms go above the head.
"joint_span_y_m": round(float(j[:, 1].max() - j[:, 1].min()), 4),
"videos": f"data/{cap}/videos",
"smplx": f"data/{cap}/smplx.npz",
"cameras": f"data/{cap}/cameras.json",
})
rows.sort(key=lambda r: (r["capture"], r["frame"]))
prev_dir.mkdir(parents=True, exist_ok=True)
out = prev_dir / "metadata.jsonl"
with out.open("w") as fh:
for r in rows:
fh.write(json.dumps(r) + "\n")
print(f"[metadata] {out}: {len(rows)} rows over {len(captures)} captures "
f"({', '.join(captures)})", flush=True)
return {"rows": len(rows), "captures": captures, "path": str(out)}
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument("--staging", type=Path, required=True)
a = ap.parse_args()
print(json.dumps(build(a.staging)))
return 0
if __name__ == "__main__":
sys.exit(main())
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