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import numpy as np
from skimage.metrics import structural_similarity as ssim
import gradio as gr
import cv2
def calculate_similarity(img1, img2):
if len(img1.shape) == 2:
img1 = cv2.cvtColor(img1, cv2.COLOR_GRAY2RGB)
if len(img2.shape) == 2:
img2 = cv2.cvtColor(img2, cv2.COLOR_GRAY2RGB)
max_height = max(img1.shape[0], img2.shape[0])
max_width = max(img1.shape[1], img2.shape[1])
img1_resized = cv2.resize(img1, (max_width, max_height))
img2_resized = cv2.resize(img2, (max_width, max_height))
similarity_score = ssim(img1_resized, img2_resized, multichannel=True)
return similarity_score
def image_similarity(img1, img2):
img1 = img1.astype(np.uint8)
img2 = img2.astype(np.uint8)
similarity_score = calculate_similarity(img1, img2)
result = f"Similarity Score: {similarity_score:.4f}"
return result
iface = gr.Interface(
fn=image_similarity,
inputs=[
gr.inputs.Image(type="numpy", label="Image 1"),
gr.inputs.Image(type="numpy", label="Image 2")
],
outputs="text",
title="Image Similarity Calculator",
description="Upload two images to compute their similarity."
)
iface.launch()
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