Update app.py

app.py

@@ -67,11 +67,11 @@ def compare_images(image1, image2, blur_value, technique, threshold_value, metho
     cv2.drawContours(mask, filtered_contours, -1, (255, 255, 255), thickness=cv2.FILLED)
     highlighted = cv2.bitwise_and(image2, mask)
     
-    diff_colored = np.zeros_like(image1, dtype=np.uint8)
-    diff_colored[:, :, 0] = 0
-    diff_colored[:, :, 1] = 0
-    diff_colored[:, :, 2] = thresh
-    overlayed = cv2.addWeighted(image1, 0.7, diff_colored, 0.6, 0)
+    diff_colored = cv2.absdiff(image1, image2)
+    diff_colored[:, :, 0] = 0  # Remove blue
+    diff_colored[:, :, 1] = 0  # Remove green
+    
+    overlayed = cv2.addWeighted(image1, 0.6, diff_colored, 0.6, 0)
     
     blended_with_object = cv2.addWeighted(image1, 0.4, image2, 0.6, 0)
     blended_without_object = cv2.bitwise_and(image1, image1, mask=255 - thresh)
@@ -88,7 +88,7 @@ with gr.Blocks() as demo:
         img1 = gr.Image(type="numpy", label="Image Without Object")
         img2 = gr.Image(type="numpy", label="Image With Object")
     
-    blur_slider = gr.Slider(minimum=1, maximum=15, step=2, value=5, label="Gaussian Blur")
+    blur_slider = gr.Slider(minimum=1, maximum=15, step=1, value=5, label="Gaussian Blur")
     technique_dropdown = gr.Dropdown(["Adaptive Threshold", "Otsu's Threshold", "Simple Binary"], label="Thresholding Technique", value="Adaptive Threshold", interactive=True)
     threshold_slider = gr.Slider(minimum=0, maximum=255, step=1, value=50, label="Threshold Value", visible=False)
     method_dropdown = gr.Dropdown(["SSIM", "Background Subtraction", "Optical Flow", "Feature Matching"], label="Comparison Method", value="SSIM", interactive=True)
@@ -106,4 +106,4 @@ with gr.Blocks() as demo:
     btn = gr.Button("Process")
     btn.click(compare_images, inputs=[img1, img2, blur_slider, technique_dropdown, threshold_slider, method_dropdown], outputs=[output1, output2, output3, output4])
 
-demo.launch()
+demo.launch()