# #!/usr/bin/env python3
# """
# Script to upload multiple datasets to Hugging Face Hub
# Uploads all datasets except CTCdataset_COCO to ItsMaxNorm/CytoCTCs
# """

# import os
# import sys
# from pathlib import Path
# from huggingface_hub import HfApi, create_repo, upload_folder
# import argparse

# def upload_datasets_to_hf(base_path, repo_id, token=None):
#     """
#     Upload multiple dataset folders to Hugging Face Hub
    
#     Args:
#         base_path: Path to the directory containing dataset folders
#         repo_id: Hugging Face repository ID (e.g., "ItsMaxNorm/CytoCTCs")
#         token: Hugging Face API token (optional if already logged in via CLI)
#     """
#     # Initialize the Hugging Face API
#     api = HfApi(token=token)
    
#     # Define folders to upload (excluding CTCdataset_COCO)
#     folders_to_upload = ["Bacteria", "CTCDataset", "DEEPCELL"]
    
#     # Convert base_path to Path object
#     base_path = Path(base_path)
    
#     # Check if base path exists
#     if not base_path.exists():
#         print(f"Error: Base path {base_path} does not exist!")
#         return
    
#     # Try to create the repository (will not fail if it already exists)
#     try:
#         create_repo(repo_id, repo_type="dataset", token=token, exist_ok=True)
#         print(f"Repository {repo_id} is ready")
#     except Exception as e:
#         print(f"Note: {e}")
    
#     # Upload each folder
#     for folder_name in folders_to_upload:
#         folder_path = base_path / folder_name
        
#         if not folder_path.exists():
#             print(f"Warning: Folder {folder_path} does not exist, skipping...")
#             continue
        
#         if not folder_path.is_dir():
#             print(f"Warning: {folder_path} is not a directory, skipping...")
#             continue
        
#         print(f"\nUploading {folder_name}...")
        
#         try:
#             # Upload the folder to a subdirectory in the repo
#             upload_folder(
#                 folder_path=str(folder_path),
#                 path_in_repo=folder_name,  # This creates a subdirectory in the repo
#                 repo_id=repo_id,
#                 repo_type="dataset",
#                 token=token,
#                 ignore_patterns=["*.pyc", "__pycache__", ".git", ".DS_Store"]
#             )
#             print(f"✓ Successfully uploaded {folder_name}")
            
#         except Exception as e:
#             print(f"✗ Error uploading {folder_name}: {e}")
#             continue
    
#     print(f"\nAll uploads completed! Check your repository at: https://huggingface.co/datasets/{repo_id}")

# def main():
#     parser = argparse.ArgumentParser(description="Upload datasets to Hugging Face Hub")
#     parser.add_argument(
#         "--path",
#         type=str,
#         default="/l/users/sahal.mullappilly/Komal/documents/Cell",
#         help="Base path containing the dataset folders"
#     )
#     parser.add_argument(
#         "--repo",
#         type=str,
#         default="ItsMaxNorm/CytoCTCs",
#         help="Hugging Face repository ID"
#     )
#     parser.add_argument(
#         "--token",
#         type=str,
#         default=None,
#         help="Hugging Face API token (optional if logged in via CLI)"
#     )
    
#     args = parser.parse_args()
    
#     # If no token provided, try to get it from environment variable
#     if args.token is None:
#         args.token = os.environ.get("HF_TOKEN")
    
#     print(f"Starting upload process...")
#     print(f"Base path: {args.path}")
#     print(f"Repository: {args.repo}")
#     print(f"Folders to upload: Bacteria, CTCDataset, DEEPCELL, finetuning")
#     print(f"Excluding: CTCdataset_COCO")
#     print("-" * 50)
    
#     upload_datasets_to_hf(args.path, args.repo, args.token)

if __name__ == "__main__":
    from huggingface_hub import HfApi
    api = HfApi()

    api.upload_large_folder(
        folder_path="/l/users/sahal.mullappilly/Komal/documents/Cell",
        repo_id="ItsMaxNorm/CytoCTCs",
        repo_type="dataset",
    )