Update app.py

app.py

@@ -1,7 +1,41 @@
 import gradio as gr
+import cv2
+import numpy as np
+from skimage.metrics import structural_similarity as ssim
 
-def greet(name):
-    return "Hello " + name + "!!"
+def compare_images(image1, image2):
+    # Convert images to grayscale
+    gray1 = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
+    gray2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
+    
+    # Compute SSIM between the two images
+    score, diff = ssim(gray1, gray2, full=True)
+    diff = (diff * 255).astype("uint8")
+    
+    # Threshold the difference image to get regions with major changes
+    _, thresh = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)
+    
+    # Find contours of differences
+    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    
+    # Create a mask to isolate only the significant added object
+    mask = np.zeros_like(image1)
+    cv2.drawContours(mask, contours, -1, (255, 255, 255), thickness=cv2.FILLED)
+    
+    # Apply the mask to highlight the object added in the second image
+    highlighted = cv2.bitwise_and(image2, mask)
+    
+    return highlighted
+
+demo = gr.Interface(
+    fn=compare_images,
+    inputs=[
+        gr.Image(type="numpy", label="Image Without Object"),
+        gr.Image(type="numpy", label="Image With Object")
+    ],
+    outputs=gr.Image(type="numpy", label="Highlighted Differences"),
+    title="Object Difference Highlighter",
+    description="Upload two images: one without an object and one with an object. The app will highlight only the newly added object."
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()