#!/usr/bin/env python3 """ Script to upload the bimanual bone dataset to Hugging Face """ import os import zipfile import tempfile from pathlib import Path from huggingface_hub import HfApi, create_repo import argparse def extract_and_upload_dataset(zip_path, repo_id, folder_name="so101"): """ Extract the zip file and upload to Hugging Face dataset repository """ api = HfApi() # Create the repository if it doesn't exist try: create_repo(repo_id=repo_id, repo_type="dataset", exist_ok=True) print(f"Repository {repo_id} is ready") except Exception as e: print(f"Repository creation/verification: {e}") # Create temporary directory for extraction with tempfile.TemporaryDirectory() as temp_dir: print(f"Extracting {zip_path} to temporary directory...") # Extract the zip file with zipfile.ZipFile(zip_path, 'r') as zip_ref: zip_ref.extractall(temp_dir) # Find the extracted content extracted_items = list(Path(temp_dir).iterdir()) if len(extracted_items) == 1 and extracted_items[0].is_dir(): # If there's a single directory, use its contents source_dir = extracted_items[0] else: # Otherwise use the temp directory itself source_dir = Path(temp_dir) # Create the target folder structure target_dir = source_dir / folder_name target_dir.mkdir(exist_ok=True) # Move all extracted content to the so101 folder for item in source_dir.iterdir(): if item.name != folder_name: import shutil shutil.move(str(item), str(target_dir / item.name)) print(f"Uploading dataset to {repo_id}...") print(f"Source directory: {source_dir}") print(f"Target folder: {folder_name}") # Upload the dataset with pull request api.upload_folder( folder_path=str(source_dir), repo_id=repo_id, repo_type="dataset", commit_message="Upload bimanual bone packing dataset with so101 folder structure", create_pr=True ) print("Dataset uploaded successfully!") def main(): parser = argparse.ArgumentParser(description="Upload bimanual bone dataset to Hugging Face") parser.add_argument("--zip-path", required=True, help="Path to the zip file") parser.add_argument("--repo-id", default="CHEWYSO/Chewy_Robotics_Bone_Bi-manual_Packing", help="Hugging Face repository ID") parser.add_argument("--folder-name", default="so101", help="Folder name to organize the dataset") args = parser.parse_args() if not os.path.exists(args.zip_path): print(f"Error: Zip file {args.zip_path} not found") return 1 extract_and_upload_dataset(args.zip_path, args.repo_id, args.folder_name) return 0 if __name__ == "__main__": exit(main())