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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()
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