| from pathlib import Path |
| import argparse, hashlib, json |
| from datasets import load_dataset, Image as DatasetImage |
| from huggingface_hub import HfApi, hf_hub_download |
| REPO="fireviewer/flame_smoke_detection_box_not_precise" |
| def prepare(output, task="fire_smoke", revision=None): |
| revision=revision or HfApi().dataset_info(REPO).sha |
| out=Path(output); out.mkdir(parents=True,exist_ok=True) |
| wanted={}; totals={} |
| for split in ["train","validation","test"]: |
| p=hf_hub_download(REPO,f"annotations/merged/{task}/{split}.json",repo_type="dataset",revision=revision) |
| d=json.loads(Path(p).read_text()) |
| wanted[split]={im["sha256"]:im for im in d["images"]} |
| folder=out/split; (folder/"images").mkdir(parents=True,exist_ok=True) |
| for im in d["images"]: im["file_name"]="images/"+Path(im["file_name"]).name |
| (folder/"_annotations.coco.json").write_text(json.dumps(d,ensure_ascii=False),encoding="utf-8") |
| seen=set() |
| for row in load_dataset(REPO,"corpus",split=split,revision=revision,streaming=True).cast_column("image",DatasetImage(decode=False)): |
| h=row["sha256"] |
| if h not in wanted[split]: continue |
| image=row["image"] |
| if not isinstance(image,dict): raise RuntimeError("Image decoding must be disabled; cast the image column to datasets.Image(decode=False).") |
| blob=image["bytes"]; assert hashlib.sha256(blob).hexdigest()==h |
| dest=folder/wanted[split][h]["file_name"] |
| dest.write_bytes(blob); seen.add(h) |
| assert seen==set(wanted[split]),(split,len(seen),len(wanted[split])) |
| totals[split]=len(seen) |
| return totals, {"revision":revision,"task":task} |
| if __name__=="__main__": |
| p=argparse.ArgumentParser();p.add_argument("--output",required=True);p.add_argument("--task",choices=["fire_smoke","visible_flame","probable_fire"],default="fire_smoke");p.add_argument("--revision") |
| a=p.parse_args(); print(prepare(a.output,a.task,a.revision)) |
|
|
