| """Download multiple datasets from Hugging Face and COCO.""" |
|
|
| import argparse |
| import os |
| import sys |
| from huggingface_hub import snapshot_download |
|
|
|
|
| COCO_VAL_URL = "http://images.cocodataset.org/zips/val2014.zip" |
|
|
|
|
| def download_huggingface_dataset(repo_id: str, output_dir: str, use_auth_token: bool) -> str: |
| os.makedirs(output_dir, exist_ok=True) |
| print(f"Downloading Hugging Face dataset {repo_id} to '{output_dir}'...") |
| local_dir = snapshot_download( |
| repo_id=repo_id, |
| repo_type="dataset", |
| local_dir=output_dir, |
| use_auth_token=use_auth_token, |
| ) |
| print(f"Finished: {repo_id} -> {local_dir}\n") |
| return local_dir |
|
|
|
|
| def download_file(url: str, output_path: str) -> None: |
| try: |
| import requests |
| except ImportError: |
| import urllib.request |
|
|
| print("requests not found, falling back to urllib.request") |
| urllib.request.urlretrieve(url, output_path) |
| return |
|
|
| print(f"Downloading file from {url} to '{output_path}'...") |
| with requests.get(url, stream=True) as response: |
| response.raise_for_status() |
| total_size = int(response.headers.get("content-length", 0)) |
| downloaded = 0 |
| chunk_size = 8192 |
| with open(output_path, "wb") as f: |
| for chunk in response.iter_content(chunk_size=chunk_size): |
| if chunk: |
| f.write(chunk) |
| downloaded += len(chunk) |
| if total_size: |
| percent = downloaded * 100 / total_size |
| print(f"\rDownloaded {downloaded}/{total_size} bytes ({percent:.1f}%)", end="") |
| if total_size: |
| print() |
| print(f"Finished: {output_path}\n") |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description="Download VGMED, Medical Multimodal Evaluation Data, and COCO 2014 val images.") |
| parser.add_argument( |
| "--output-dir", |
| default="/home/jinhua/ExplainableVQA/benchmarks", |
| help="Base output directory for all downloads. Default: downloads", |
| ) |
| parser.add_argument( |
| "--use-auth-token", |
| action="store_true", |
| help="Use HF authentication token from HUGGINGFACE_HUB_TOKEN environment variable if required.", |
| ) |
| parser.add_argument( |
| "--skip-vgmed", |
| action="store_true", |
| help="Skip downloading guimeng-liu/VGMED.", |
| ) |
| parser.add_argument( |
| "--skip-med-eval", |
| action="store_true", |
| help="Skip downloading FreedomIntelligence/Medical_Multimodal_Evaluation_Data.", |
| ) |
| parser.add_argument( |
| "--skip-coco", |
| action="store_true", |
| help="Skip downloading COCO 2014 validation images.", |
| ) |
| parser.add_argument( |
| "--coco-url", |
| default=COCO_VAL_URL, |
| help="COCO 2014 val images download URL. Default is the official val2014 zip URL.", |
| ) |
| args = parser.parse_args() |
|
|
| base_dir = os.path.abspath(args.output_dir) |
| os.makedirs(base_dir, exist_ok=True) |
|
|
| if not args.skip_vgmed: |
| download_huggingface_dataset( |
| repo_id="guimeng-liu/VGMED", |
| output_dir=os.path.join(base_dir, "VGMED"), |
| use_auth_token=args.use_auth_token, |
| ) |
|
|
| if not args.skip_med_eval: |
| download_huggingface_dataset( |
| repo_id="FreedomIntelligence/Medical_Multimodal_Evaluation_Data", |
| output_dir=os.path.join(base_dir, "Medical_Multimodal_Evaluation_Data"), |
| use_auth_token=args.use_auth_token, |
| ) |
|
|
| if not args.skip_coco: |
| coco_target = os.path.join(base_dir, "val2014.zip") |
| download_file(args.coco_url, coco_target) |
|
|
| print("All requested downloads completed.") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
