| 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() | |