| |
| """Export the Hugging Face VCR dataset back to the original r2c layout.""" |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import os |
| import shutil |
| from itertools import islice |
| from pathlib import Path |
|
|
| from datasets import load_dataset, load_from_disk |
| from huggingface_hub import hf_hub_download |
| from tqdm import tqdm |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("repo_id", help="Hugging Face dataset repo id, e.g. rowanz/vcr") |
| parser.add_argument("output_dir", type=Path, help="Directory to create in r2c-compatible layout") |
| parser.add_argument("--token", default=None, help="HF token for private/gated repos") |
| parser.add_argument("--limit", type=int, default=None, help="Optional per-split row limit for smoke tests") |
| parser.add_argument("--local-stage-dir", type=Path, default=None, help="Use a local vcr_hf.py stage directory instead of the Hub") |
| args = parser.parse_args() |
|
|
| args.output_dir.mkdir(parents=True, exist_ok=True) |
| images_dir = args.output_dir / "vcr1images" |
| images_dir.mkdir(parents=True, exist_ok=True) |
|
|
| for split in ("train", "val", "test"): |
| if args.local_stage_dir is None: |
| src = hf_hub_download( |
| repo_id=args.repo_id, |
| repo_type="dataset", |
| filename=f"original_annotations/{split}.jsonl", |
| token=args.token, |
| ) |
| else: |
| src = args.local_stage_dir / "original_annotations" / f"{split}.jsonl" |
| dst = args.output_dir / f"{split}.jsonl" |
| if args.limit is None: |
| shutil.copyfile(src, dst) |
| else: |
| with open(src, "r", encoding="utf-8") as f_in, open(dst, "w", encoding="utf-8") as f_out: |
| for i, line in enumerate(f_in): |
| if i >= args.limit: |
| break |
| f_out.write(line) |
|
|
| if args.local_stage_dir is None: |
| if args.limit is None: |
| split_expr = {s: s for s in ("train", "validation", "test")} |
| ds = load_dataset(args.repo_id, "image_examples", split=split_expr, token=args.token) |
| if not isinstance(ds, dict): |
| ds = {"train": ds} |
| else: |
| ds = { |
| split_name: load_dataset( |
| args.repo_id, |
| "image_examples", |
| split=split_name, |
| streaming=True, |
| token=args.token, |
| ) |
| for split_name in ("train", "validation", "test") |
| } |
| else: |
| local_ds = load_from_disk(args.local_stage_dir / "image_examples.dataset") |
| ds = {} |
| for split_name in ("train", "validation", "test"): |
| ds[split_name] = local_ds[split_name].select(range(min(args.limit, len(local_ds[split_name])))) if args.limit else local_ds[split_name] |
|
|
| seen: set[str] = set() |
| for split_name, split_ds in ds.items(): |
| rows = islice(split_ds, args.limit) if args.limit is not None else split_ds |
| for row in tqdm(rows, desc=f"export {split_name} images", total=args.limit): |
| img_fn = row["img_fn"] |
| metadata_fn = row["metadata_fn"] |
|
|
| if img_fn not in seen: |
| image = row["image"] |
| dst_img = images_dir / img_fn |
| dst_img.parent.mkdir(parents=True, exist_ok=True) |
| image.save(dst_img) |
| seen.add(img_fn) |
|
|
| if metadata_fn not in seen: |
| metadata = { |
| "boxes": row["boxes"], |
| "segms": json.loads(row["segms_json"]), |
| "names": row["objects"], |
| "width": row["width"], |
| "height": row["height"], |
| } |
| dst_meta = images_dir / metadata_fn |
| dst_meta.parent.mkdir(parents=True, exist_ok=True) |
| with open(dst_meta, "w", encoding="utf-8") as f: |
| json.dump(metadata, f, separators=(",", ":")) |
| seen.add(metadata_fn) |
|
|
| print(f"Wrote r2c-compatible VCR layout to {args.output_dir}", flush=True) |
| os._exit(0) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
