Added motion blur filter and fixed duplicate controls.

- Introduced motion blur filter with configurable kernel size
- Removed duplicate control initialization in app.py
- Updated filter registry with motion blur defaults
- Added kernel size validation for motion blur
- Improved code organization in filters.py

app.py

@@ -16,6 +16,8 @@ def create_app():
         # Re-initialize controls and filter_names after adding the new filter
         controls = create_filter_controls()
         filter_names = list(registry.filters.keys())
+        controls = create_filter_controls()
+        filter_names = list(registry.filters.keys())
 
         filter_groups = {} # Store filter groups
 

filters.py

@@ -108,4 +108,34 @@ def pixelize(image, pixel_size: int = 10):
     # 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
+    return pixelized_image
+
+@registry.register("Motion Blur", defaults={
+    "kernel_size": 10,
+}, min_vals={
+    "kernel_size": 1,
+}, max_vals={
+    "kernel_size": 50,
+}, step_vals={
+    "kernel_size": 1,
+})
+def motion_blur(image, kernel_size: int = 10):
+    """
+    ## Apply a motion blur effect to the image.
+
+    **Args:**
+    * `image` (numpy.ndarray): Input image (BGR or grayscale)
+    * `kernel_size` (int): Size of the kernel
+
+    **Returns:**
+    * `numpy.ndarray`: Motion blurred image
+    """
+    # Create a horizontal kernel
+    kernel = np.zeros((kernel_size, kernel_size))
+    kernel[kernel_size//2, :] = np.ones(kernel_size)
+    kernel = kernel / kernel_size
+
+    # Apply the kernel to the image
+    motion_blurred_image = cv2.filter2D(image, -1, kernel)
+
+    return motion_blurred_image