Update app.py

app.py

@@ -10,7 +10,7 @@ def preprocess_image(image, blur_value):
     blurred = cv2.GaussianBlur(gray, (blur_value, blur_value), 0)
     return blurred
 
-def compare_images(image1, image2, blur_value, technique):
+def compare_images(image1, image2, blur_value, technique, threshold_value):
     # Preprocess images
     gray1 = preprocess_image(image1, blur_value)
     gray2 = preprocess_image(image2, blur_value)
@@ -23,8 +23,8 @@ def compare_images(image1, image2, blur_value, technique):
         _, thresh = cv2.threshold(diff, 30, 255, cv2.THRESH_BINARY_INV)
     elif technique == "Otsu's Threshold":
         _, thresh = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)
-    else:  # Default to simple binary threshold
-        _, thresh = cv2.threshold(diff, 50, 255, cv2.THRESH_BINARY)
+    else:  # Simple Binary
+        _, thresh = cv2.threshold(diff, threshold_value, 255, cv2.THRESH_BINARY)
     
     # Find contours of differences
     contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
@@ -39,10 +39,15 @@ def compare_images(image1, image2, blur_value, technique):
     # Apply the mask to highlight the object added in the second image
     highlighted = cv2.bitwise_and(image2, mask)
     
-    # Show the raw difference in magenta
-    diff_colored = cv2.merge([np.zeros_like(diff), diff, diff])
+    # Overlay the difference in magenta over the first image
+    diff_colored = cv2.cvtColor(diff, cv2.COLOR_GRAY2BGR)
+    diff_colored[:, :, 1:] = 0  # Keep only red channel for magenta effect
+    overlayed = cv2.addWeighted(image1, 0.7, diff_colored, 0.3, 0)
     
-    return highlighted, diff_colored
+    return highlighted, overlayed
+
+def update_threshold_visibility(technique):
+    return gr.update(visible=(technique == "Simple Binary"))
 
 demo = gr.Interface(
     fn=compare_images,
@@ -50,14 +55,18 @@ demo = gr.Interface(
         gr.Image(type="numpy", label="Image Without Object"),
         gr.Image(type="numpy", label="Image With Object"),
         gr.Slider(minimum=1, maximum=15, step=2, value=5, label="Gaussian Blur"),
-        gr.Dropdown(["Adaptive Threshold", "Otsu's Threshold", "Simple Binary"], label="Thresholding Technique", value="Adaptive Threshold")
+        gr.Dropdown(["Adaptive Threshold", "Otsu's Threshold", "Simple Binary"], label="Thresholding Technique", value="Adaptive Threshold", interactive=True),
+        gr.Slider(minimum=0, maximum=255, step=1, value=50, label="Threshold Value", visible=False)
     ],
     outputs=[
         gr.Image(type="numpy", label="Highlighted Differences"),
-        gr.Image(type="numpy", label="Raw Difference (Magenta)")
+        gr.Image(type="numpy", label="Raw Difference Overlay (Magenta)")
     ],
     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 and show the real differences in magenta."
+    description="Upload two images: one without an object and one with an object. The app will highlight only the newly added object and show the real differences in magenta overlayed on the original image.",
+    live=True
 )
 
+demo.load(update_threshold_visibility, inputs=["Thresholding Technique"], outputs=["Threshold Value"])
+
 demo.launch()