Datasets:
File size: 4,264 Bytes
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 | #!/usr/bin/env python
"""Build the browsable QC previews for one capture.
Reads (READ ONLY) the tracker's QC output:
<DEGAS_DATASET>/<PxCy>/hmt_seq_out/grid_f<frame:08d>.jpg 32-view contact sheet
<DEGAS_DATASET>/<PxCy>/hmt_seq_out/panels/f<frame>_cam<NN>.jpg 3-panel per view
Writes into the HF staging tree:
previews/<PxCy>_f<frame:08d>.jpg downscaled contact sheet, one per sampled frame
(this is the `image` column of the data viewer)
data/<PxCy>/preview.jpg one representative contact sheet for the capture
Usage:
python make_previews.py P1C1 --staging /mnt/sdb/degas_project/DREAMS-AVATAR-hf/staging
"""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
from PIL import Image
DATASET_ROOT = Path("/mnt/sdb/degas_project/DEGAS_DATASET")
Image.MAX_IMAGE_PIXELS = None
def _save_resized(src: Path, dst: Path, width: int, quality: int = 88) -> int:
im = Image.open(src).convert("RGB")
if im.width > width:
h = max(1, round(im.height * width / im.width))
im = im.resize((width, h), Image.LANCZOS)
dst.parent.mkdir(parents=True, exist_ok=True)
im.save(dst, "JPEG", quality=quality, optimize=True, progressive=True)
return dst.stat().st_size
def make_previews(capture: str, dataset_root: Path, staging: Path,
grid_width: int = 1920, hero_width: int = 2560) -> dict:
out_dir = dataset_root / capture / "hmt_seq_out"
grids = sorted(out_dir.glob("grid_f*.jpg"))
if not grids:
raise SystemExit(f"no grid_f*.jpg under {out_dir} -- has the tracker finished {capture}?")
prev_dir = staging / "previews"
rows = []
total = 0
for g in grids:
frame = int(g.stem.split("_f")[1])
dst = prev_dir / f"{capture}_f{frame:08d}.jpg"
total += _save_resized(g, dst, grid_width)
rows.append({"file_name": dst.name, "frame": frame})
# capture-level preview.jpg: the middle sampled frame
mid = grids[len(grids) // 2]
cap_prev = staging / "data" / capture / "preview.jpg"
_save_resized(mid, cap_prev, hero_width)
print(f"[previews] {capture}: {len(rows)} grids -> {prev_dir} "
f"({total / 2**20:.1f} MB), preview.jpg from {mid.name}", flush=True)
return {"capture": capture, "n_previews": len(rows), "rows": rows,
"preview_source": mid.name, "bytes": total}
def copy_showcase(capture: str, dataset_root: Path, staging: Path,
frame: int, cams: list[int], width: int = 2560) -> list[str]:
"""Copy the hand-picked 3-panel views used as the README hero images."""
panels = dataset_root / capture / "hmt_seq_out" / "panels"
out = []
for c in cams:
src = panels / f"f{frame:08d}_cam{c:02d}.jpg"
if not src.exists():
print(f"[showcase] MISSING {src}", file=sys.stderr)
continue
dst = staging / "assets" / "showcase" / f"{capture}_f{frame:08d}_cam{c:02d}.jpg"
_save_resized(src, dst, width, quality=92)
out.append(str(dst.relative_to(staging)))
print(f"[showcase] {src.name} -> {dst.relative_to(staging)}", flush=True)
return out
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument("capture")
ap.add_argument("--dataset-root", type=Path, default=DATASET_ROOT)
ap.add_argument("--staging", type=Path, required=True)
ap.add_argument("--grid-width", type=int, default=1920)
ap.add_argument("--showcase-frame", type=int, default=None,
help="also copy panels/f<frame>_cam<NN>.jpg into assets/showcase/")
ap.add_argument("--showcase-cams", type=int, nargs="*", default=[3, 6, 12])
a = ap.parse_args()
info = make_previews(a.capture, a.dataset_root, a.staging, a.grid_width)
if a.showcase_frame is not None:
info["showcase"] = copy_showcase(a.capture, a.dataset_root, a.staging,
a.showcase_frame, a.showcase_cams)
print(json.dumps({k: v for k, v in info.items() if k != "rows"}))
return 0
if __name__ == "__main__":
sys.exit(main())
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