from huggingface_hub import HfApi

# Create an API instance
api = HfApi()

# Start uploading the folder in the background (non-blocking)
future = api.upload_large_folder(
    repo_id="kalhar/images_dataset",          # Your repo ID
    folder_path="C:/Users/kalha/Documents/NEU 5330/Lab 1/computer-vision-dataset/image_dataset",  # Local folder to upload
    repo_type="dataset",                                 # Specify it's a dataset repo (if needed)
)

print("Upload started. Waiting for completion...")

# Optionally, you can check if the future is done
print("Upload done?", future.done())

# Block until the upload completes and get the result
result = future.result()
print("Folder uploaded successfully!")