| """materialize.py —— 把 parquet 展开成目录树（按字节原样写出，不重编码）。 |
| |
| 目录形状（与原 GenImage 一致，方便直接喂 ImageFolder）： |
| |
| <out>/<generator>/<split>/ai/<class_name>/*.PNG # 假图 |
| <out>/nature/<split>/<class_name>/*.JPEG # 真图池，全局只有一份 |
| |
| 用法： |
| python scripts/materialize.py --root . --out ./data |
| python scripts/materialize.py --root . --out ./data --config tiny |
| python scripts/materialize.py --root . --out ./data --splits test --generators ADM nature |
| python scripts/materialize.py --root . --out ./data --dry-run |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import sys |
| from pathlib import Path |
|
|
| import pyarrow.parquet as pq |
|
|
|
|
| def image_bytes(cell): |
| """兼容两种写法：struct{bytes,path} 或裸 binary。""" |
| if isinstance(cell, dict): |
| return cell.get("bytes") |
| if isinstance(cell, (bytes, bytearray, memoryview)): |
| return bytes(cell) |
| return None |
|
|
|
|
| def guess_ext(orig_path: str, fmt: str) -> str: |
| suf = Path(orig_path).suffix |
| if suf: |
| return suf.lower() |
| return {"PNG": ".png", "JPEG": ".jpg"}.get(fmt, ".bin") |
|
|
|
|
| def main() -> None: |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--root", required=True, help="仓库根目录（含 data/ 与 meta/）") |
| ap.add_argument("--out", required=True, help="输出目录树") |
| ap.add_argument("--config", default="default", choices=["default", "tiny"]) |
| ap.add_argument("--splits", nargs="*", default=None) |
| ap.add_argument("--generators", nargs="*", default=None) |
| ap.add_argument("--limit", type=int, default=None, help="每个 (生成器, split) 最多导出多少张") |
| ap.add_argument("--dry-run", action="store_true") |
| args = ap.parse_args() |
|
|
| root = Path(args.root) |
| sub = "data" if args.config == "default" else "tiny" |
| files = sorted((root / sub).glob("*.parquet")) |
| if not files: |
| sys.exit(f"[!] {root / sub} 下没有 parquet，检查 --root / --config") |
|
|
| out = Path(args.out) |
| total = written = 0 |
| counts: dict[tuple, int] = {} |
|
|
| for f in files: |
| pf = pq.ParquetFile(f) |
| for batch in pf.iter_batches(batch_size=128): |
| d = batch.to_pydict() |
| for i in range(batch.num_rows): |
| split = d["split"][i] |
| gen = d["generator"][i] |
| if args.splits and split not in args.splits: |
| continue |
| if args.generators and gen not in args.generators: |
| continue |
| key = (gen, split) |
| if args.limit and counts.get(key, 0) >= args.limit: |
| continue |
|
|
| label = int(d["label"][i]) |
| cls = str(d["class_name"][i] or f"class_{d['class_id'][i]}").replace("/", "_") |
| orig = d["image_path"][i] |
| stem = Path(orig).stem |
| ext = guess_ext(orig, d["format"][i]) |
| branch = "ai" if label == 1 else "nature" |
| dst = out / gen / split / branch / cls / f"{stem}{ext}" |
| total += 1 |
| if args.dry_run: |
| continue |
| dst.parent.mkdir(parents=True, exist_ok=True) |
| b = image_bytes(d["image"][i]) |
| if b is None: |
| continue |
| dst.write_bytes(b) |
| written += 1 |
| counts[key] = counts.get(key, 0) + 1 |
| print(f"\r 处理 {f.name} … 已导出 {written:,}", end="", flush=True) |
|
|
| print() |
| if args.dry_run: |
| print(f"[dry-run] 将导出 {total:,} 张到 {out}") |
| return |
| print(f"完成：{written:,} 张 -> {out.resolve()}") |
| for (gen, split), n in sorted(counts.items()): |
| print(f" {gen:10s} {split:6s} {n:>7,}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
