import os import zipfile import requests import argparse from huggingface_hub import HfApi # Parameters repo_id = "dappu97/Coil100-Augmented/coil-100-augmented-binary" # Replace with your Hugging Face repo ID temp_zip_folder = "./temp_zips" # Temporary folder to store downloaded ZIPs # Initialize Hugging Face API api = HfApi() # Step 1: List and download all ZIP files from the Hugging Face repository def download_zip_files(repo_id, temp_zip_folder): files = api.list_repo_files(repo_id, repo_type="dataset") zip_files = [file for file in files if file.endswith(".zip")] for zip_file in zip_files: url = f"https://huggingface.co/datasets/{repo_id}/resolve/main/{zip_file}" local_path = os.path.join(temp_zip_folder, zip_file) os.makedirs(os.path.dirname(local_path), exist_ok=True) print(f"Downloading {zip_file}...") response = requests.get(url, stream=True) if response.status_code == 200: with open(local_path, "wb") as f: f.write(response.content) print(f"Downloaded {zip_file} to {local_path}.") else: print(f"Failed to download {zip_file}. HTTP status code: {response.status_code}") # Step 2: Extract all ZIP files and save images in a single folder def extract_zip_files(temp_zip_folder, output_folder): os.makedirs(temp_zip_folder, exist_ok=True) for zip_file in os.listdir(temp_zip_folder): zip_path = os.path.join(temp_zip_folder, zip_file) if not zipfile.is_zipfile(zip_path): continue # Skip non-ZIP files print(f"Extracting {zip_file}...") with zipfile.ZipFile(zip_path, "r") as z: for file_name in z.namelist(): # Extract only files (skip directories) if not file_name.endswith("/"): file_data = z.read(file_name) output_path = os.path.join(output_folder, os.path.basename(file_name)) with open(output_path, "wb") as f: f.write(file_data) if __name__ == '__main__': parser = argparse.ArgumentParser(description="Download and unzip ZIP files from a Hugging Face dataset.") parser.add_argument("output_folder", help="Path to the folder where extracted files will be saved.") args = parser.parse_args() # Folder to save all images output_folder = args.output_folder # Create output directories os.makedirs(output_folder, exist_ok=True) os.makedirs(temp_zip_folder, exist_ok=True) # Download and extract the dataset download_zip_files(repo_id, temp_zip_folder) extract_zip_files(os.path.join(temp_zip_folder, "coil-100-augmented-binary"), output_folder) print(f"All images have been saved to {output_folder}.")