"""
This script restores the original directory structure of an image dataset
from a locally saved Hugging Face Dataset.

It reads a dataset created by the `datasets` library's `save_to_disk` method,
iterates through each record, and uses the 'relative_path' column to
recreate the folder hierarchy and save each image file.

Usage:
    Run this script from the project's root directory.

    Syntax:
    python <path_to_script> <path_to_saved_dataset> <output_directory>


    ## Example:
    ### For stage 1 data decompression:
    python scripts/restore.py images/description_style_new data/selected/description_style_new


    ### For stage 2 data decompression:
    python scripts/restore.py images/stage_2_identity_matching data/selected/stage_2_identity_matching
    
    python scripts/restore.py images/stage_2_view_synthesis data/selected/stage_2_view_synthesis
    
    python scripts/restore.py images/stage_2_point_matching data/selected/stage_2_point_matching
    
    python scripts/restore.py images/stage_2_depth_estimation data/selected/stage_2_depth_estimation
    
    python scripts/restore.py images/stage_2_camera_pose data/selected/stage_2_camera_pose
"""

import os
import argparse
from datasets import load_from_disk
from tqdm import tqdm
from PIL import Image

def restore_images_from_dataset(dataset_path: str, output_path: str):
    """
    Loads a Hugging Face dataset from disk and restores the original image
    directory structure in a specified output folder.

    Args:
        dataset_path (str): The path to the saved Hugging Face dataset directory.
        output_path (str): The root directory where the images will be restored.
    """
    # 1. --- Load the dataset from disk ---
    print(f"Loading dataset from '{dataset_path}'...")
    try:
        dataset = load_from_disk(dataset_path)
    except FileNotFoundError:
        print(f"Error: No saved dataset found at '{dataset_path}'.")
        print("Please check the path and try again.")
        return

    print(f"Dataset loaded successfully. Found {len(dataset)} records.")

    # 2. --- Create the main output directory if it doesn't exist ---
    if not os.path.exists(output_path):
        print(f"Creating output directory: '{output_path}'")
        os.makedirs(output_path)

    # 3. --- Iterate, reconstruct paths, and save images ---
    print(f"Restoring images to '{output_path}'...")
    for record in tqdm(dataset, desc="Restoring images"):
        # The `record['image']` will be a PIL.Image.Image object
        image: Image.Image = record['image']
        relative_path: str = record['relative_path']

        # Create the full destination path for the image file
        # os.path.join handles path separators correctly for any OS
        destination_path = os.path.join(output_path, relative_path)

        # Get the directory part of the destination path
        destination_dir = os.path.dirname(destination_path)

        # Create the subdirectories if they don't exist
        # `exist_ok=True` prevents an error if the directory already exists
        os.makedirs(destination_dir, exist_ok=True)

        # Save the image to its restored path
        # The format is inferred from the file extension, but can be specified
        image.save(destination_path)

    print("\nImage restoration complete!")
    print(f"All images have been saved in '{os.path.abspath(output_path)}'.")


def main():
    parser = argparse.ArgumentParser(
        description="Restore an image folder structure from a saved "
                    "Hugging Face dataset."
    )
    parser.add_argument(
        'dataset_path',
        type=str,
        help="Path to the saved dataset directory (e.g., 'my-local-co3d-dataset')."
    )
    parser.add_argument(
        'output_path',
        type=str,
        help="Path to the root folder where images will be restored "
             "(e.g., 'data/restored')."
    )
    args = parser.parse_args()

    restore_images_from_dataset(args.dataset_path, args.output_path)


if __name__ == "__main__":
    main()