#!/usr/bin/python3
import argparse
from skimage.metrics import structural_similarity as ssim
import cv2

def are_images_similar(image_path1, image_path2, similarity_threshold=0.95):
    # Load both images in grayscale mode
    image1 = cv2.imread(image_path1, cv2.IMREAD_GRAYSCALE)
    image2 = cv2.imread(image_path2, cv2.IMREAD_GRAYSCALE)

    # Check if images are the same size
    if image1.shape != image2.shape:
        print("Images have different dimensions.")
        return False

    # Calculate the SSIM between the two images
    score, _ = ssim(image1, image2, full=True)

    # Return True if the score is above the similarity threshold
    return score >= similarity_threshold

def main():
    # Set up argument parser
    parser = argparse.ArgumentParser(description="Compare two images for similarity.")
    parser.add_argument("image1_path", type=str, help="Path to the first image file")
    parser.add_argument("image2_path", type=str, help="Path to the second image file")

    # Parse arguments
    args = parser.parse_args()

    # Compare images
    if are_images_similar(args.image1_path, args.image2_path):
        print(f"\nFound similar videos:\n{args.image1_path} and {args.image2_path}\n")

if __name__ == "__main__":
    main()