Added pixelize filter and reinitialized controls

- Introduced pixelize filter effect
- Reinitialized filter controls
- Updated dot_effect indentation
- Added pixel_size parameter defaults
- Improved image resizing logic

app.py

@@ -13,6 +13,10 @@ def create_app():
         controls = create_filter_controls()
         filter_names = list(registry.filters.keys())
         
+        # Re-initialize controls and filter_names after adding the new filter
+        controls = create_filter_controls()
+        filter_names = list(registry.filters.keys())
+
         filter_groups = {} # Store filter groups
 
         with gr.Row():

filters.py

@@ -62,18 +62,50 @@ def dot_effect(image, dot_size: int = 10, dot_spacing: int = 2, invert: bool = F
             if region.size > 0:
                 brightness = np.mean(region)
 
-                # Dynamic dot sizing based on brightness
-                relative_brightness = brightness / 255.0
-                if invert:
-                    relative_brightness = 1 - relative_brightness
-
-                # Draw circle with size proportional to brightness
-                radius = int((dot_size/2) * relative_brightness)
-                if radius > 0:
-                    cv2.circle(canvas,
-                               (x + dot_size//2, y + dot_size//2),
-                               radius,
-                               (dot_color),
-                               -1)
-
-    return canvas
+            # Dynamic dot sizing based on brightness
+            relative_brightness = brightness / 255.0
+            if invert:
+                relative_brightness = 1 - relative_brightness
+
+            # Draw circle with size proportional to brightness
+            radius = int((dot_size/2) * relative_brightness)
+            if radius > 0:
+                cv2.circle(canvas,
+                           (x + dot_size//2, y + dot_size//2),
+                           radius,
+                           (dot_color),
+                           -1)
+
+    return canvas
+
+@registry.register("Pixelize", defaults={
+    "pixel_size": 10,
+}, min_vals={
+    "pixel_size": 1,
+}, max_vals={
+    "pixel_size": 50,
+}, step_vals={
+    "pixel_size": 1,
+})
+def pixelize(image, pixel_size: int = 10):
+    """
+    ## Apply a pixelization effect to the image.
+
+    **Args:**
+    * `image` (numpy.ndarray): Input image (BGR or grayscale)
+    * `pixel_size` (int): Size of each pixel block
+
+    **Returns:**
+    * `numpy.ndarray`: Pixelized image
+    """
+    height, width = image.shape[:2]
+
+    # Resize the image to a smaller size
+    small_height = height // pixel_size
+    small_width = width // pixel_size
+    small_image = cv2.resize(image, (small_width, small_height), interpolation=cv2.INTER_LINEAR)
+
+    # Resize back to the original size with nearest neighbor interpolation
+    pixelized_image = cv2.resize(small_image, (width, height), interpolation=cv2.INTER_NEAREST)
+
+    return pixelized_image