Update filters.py

filters.py

@@ -48,3 +48,27 @@ def canny_edge(image, lower_threshold: int=100, upper_threshold: int=200, conver
         gray = image
     edges = cv2.Canny(gray, lower_threshold, upper_threshold)
     return edges
+
+@registry.register("Sobel Edge", defaults={'dx': 1, 'dy': 0, 'kernel_size': 3, 'convert_to_gray': True}, min_vals={'dx': -1, 'dy': -1, 'kernel_size': 3}, max_vals={'dx': 1, 'dy': 1, 'kernel_size': 7}, step_vals={'dx': 1, 'dy': 1, 'kernel_size': 2})
+def sobel_edge(image, dx: int=1, dy: int=0, kernel_size: int=3, convert_to_gray: bool=True):
+    """
+    Applies the Sobel edge detector to detect horizontal or vertical edges.
+    
+    Args:
+        img (numpy.ndarray): Input image (BGR or grayscale)
+        dx (int): Order of derivative in x-direction (0 = no x-edge detection)
+        dy (int): Order of derivative in y-direction (0 = no y-edge detection)
+        kernel_size (int): Size of Sobel kernel (1, 3, 5, or 7)
+        convert_to_gray (bool): Convert to grayscale first
+        
+    Returns:
+        numpy.ndarray: Edge magnitude image
+    """
+    if convert_to_gray and len(image.shape) == 3:
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    else:
+        gray = image
+    sobel = cv2.Sobel(gray, cv2.CV_64F, dx, dy, ksize=kernel_size)
+    abs_sobel = cv2.convertScaleAbs(sobel)
+    
+    return abs_sobel