import cv2
import numpy as np
from skimage.metrics import structural_similarity as ssim
import gradio as gr

# Function to calculate SSIM between two images
def calculate_similarity(img1, img2):
    img1 = cv2.cvtColor(img1, cv2.COLOR_RGB2GRAY)
    img2 = cv2.cvtColor(img2, cv2.COLOR_RGB2GRAY)
    return ssim(img1, img2)

# Function to compute similarity scores for all images
def compute_similarity(target_image, image_list):
    scores = []
    for image in image_list:
        similarity_score = calculate_similarity(target_image, image)
        scores.append(similarity_score)
    return scores

# Function to handle the Gradio interface
def image_similarity(target_image, image_list):
    target_image = target_image.astype(np.uint8)
    image_list = [image.astype(np.uint8) for image in image_list]
    scores = compute_similarity(target_image, image_list)
    results = list(zip(image_list, scores))
    results.sort(key=lambda x: x[1], reverse=True)  # Sort by similarity score
    return [str(result) for result in results]

# Prepare Gradio interface
iface = gr.Interface(
    fn=image_similarity,
    inputs=[
        gr.inputs.Image(type="numpy", label="Target Image"),
        gr.inputs.Image(type="numpy", label="Image List")
    ],
    outputs="text",
    title="Image Similarity Calculator",
    description="Upload an image and a list of images. Get similarity scores."
)

# Launch the interface
iface.launch()