import os
from PIL import Image, ImageChops, ImageDraw, ImageOps
from skimage.measure import label, regionprops
import numpy as np

def get_image_difference(image1, image2):
    diff = ImageChops.difference(image1, image2)
    np_diff = np.array(diff)
    num_nonzero = np.count_nonzero(np_diff)
    total_pixels = np_diff.size
    percentage_diff = (1 - (num_nonzero / total_pixels)) * 100
    return percentage_diff

def compare_images_in_sequence_2(images):
    count = 0
    for i in range(len(images) - 1):
        image1 = Image.open(images[i])
        for j in range(i + 1, len(images)):
            image2 = Image.open(images[j])
            similarity = get_image_difference(image1, image2)
            print(f"Similarity between in-sequence {images[i]} and {images[j]}: {similarity:.2f}%")

            image1 = ImageOps.grayscale(image1)
            image2 = ImageOps.grayscale(image2)

            diff = ImageChops.difference(image1, image2)
            binary_diff = np.array(diff) > 40

            labeled_diff = label(binary_diff)
            regions = regionprops(labeled_diff)

            significant_regions = [region for region in regions if 8 <= region.area <= 1000]

            if significant_regions:
                image1_rgb = image1.convert("RGB")
                image2_rgb = image2.convert("RGB")

                draw1 = ImageDraw.Draw(image1_rgb)
                draw2 = ImageDraw.Draw(image2_rgb)
                for region in significant_regions:
                    minr, minc, maxr, maxc = region.bbox
                    draw1.rectangle([minc, minr, maxc, maxr], outline='red', width=1)
                    draw2.rectangle([minc, minr, maxc, maxr], outline='red', width=1)

                combined_img = Image.new('RGB', (image1.width + image2.width, image1.height))
                combined_img.paste(image1_rgb, (0, 0))
                combined_img.paste(image2_rgb, (image1.width, 0))
                # combined_img.show(title=f'Image {i-1} and {i} combined')

                # if not dir 'output' exists, create it
                if not os.path.exists('output'):
                    os.makedirs('output')
                combined_img.save(f'output/combined_{i}_{j}_{count}.jpg')
                count = count + 1
                pass

def main(directory):
    all_images = [os.path.join(directory, f) for f in os.listdir(directory) if f.endswith('.JPG')]
    all_images.sort()

    sequences = []
    current_sequence = [all_images[0]]

    for i in range(1, len(all_images)):
        img1 = Image.open(all_images[i - 1])
        img2 = Image.open(all_images[i])

        similarity = get_image_difference(img1, img2)

        if similarity > 10:  # Images are in the same sequence
            current_sequence.append(all_images[i])
            # combined_img = Image.new('RGB', (img1.width + img2.width, img1.height))
            # combined_img.paste(img1, (0, 0))
            # combined_img.paste(img2, (img1.width, 0))
            # combined_img.show(title=f'Image {i-1} and {i} combined')
            pass
        else:  # Images are in different sequences
            sequences.append(current_sequence)
            current_sequence = [all_images[i]]

        # print(f'Difference between {all_images[i-1]} and {all_images[i]}: {similarity:.2f}%')

    sequences.append(current_sequence)  # Add the last sequence

    for seq in sequences:
        if len(seq) > 1:  # Only compare if there are at least two images in the sequence
            compare_images_in_sequence_2(seq)

if __name__ == '__main__':
    directory = 'images'
    main(directory)