tree-distribution-shift / tools /export_coco.py
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Export all splits (incl density splits) using streaming
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import argparse
from pathlib import Path
import orjson
from datasets import load_dataset, get_dataset_split_names
def export_split(ds, out_dir: Path, split_name: str):
images_dir = out_dir / split_name / "images"
ann_dir = out_dir / split_name / "annotations"
images_dir.mkdir(parents=True, exist_ok=True)
ann_dir.mkdir(parents=True, exist_ok=True)
images = []
annotations = []
categories = None
ann_id = 1
for i, ex in enumerate(ds, 1):
image_id = int(ex["image_id"])
filename = ex["filename"]
width = int(ex["width"])
height = int(ex["height"])
(images_dir / filename).write_bytes(ex["image_bytes"])
images.append(
{"id": image_id, "file_name": filename, "width": width, "height": height}
)
annos = orjson.loads(ex["coco_annotations"])
if categories is None:
categories = orjson.loads(ex["coco_categories"])
for a in annos:
a = dict(a)
a["id"] = ann_id
ann_id += 1
annotations.append(a)
if i % 1000 == 0:
print(f"[{split_name}] exported {i} images...")
coco = {"images": images, "annotations": annotations, "categories": categories or []}
(ann_dir / f"instances_{split_name}.json").write_bytes(orjson.dumps(coco))
print(f"[{split_name}] images={len(images)} annotations={len(annotations)}")
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--repo", required=True, help="HF dataset repo id (e.g. aadityabuilds/tree-distribution-shift)")
ap.add_argument("--config", required=True, help="Config name (e.g. in_state_train_Karnataka__ood_Rajasthan)")
ap.add_argument("--out", required=True, help="Output directory (writes <out>/<config>/...)")
ap.add_argument("--revision", default=None, help="Optional HF revision/commit sha")
args = ap.parse_args()
out_dir = Path(args.out) / args.config
out_dir.mkdir(parents=True, exist_ok=True)
# Discover splits from the Hub (so we don't hardcode)
splits = get_dataset_split_names(args.repo, args.config, revision=args.revision)
print("Splits:", splits)
for split in splits:
# streaming=True avoids huge RAM mmap / pyarrow pressure
ds = load_dataset(
args.repo,
args.config,
split=split,
streaming=True,
revision=args.revision,
)
export_split(ds, out_dir, split)
print(f"COCO export written to: {out_dir}")
if __name__ == "__main__":
main()