Added smooth edges function

app.py

@@ -121,7 +121,7 @@ def crop_signature(original_image_path, mask, padding=32):
         cropped_mask = binary_mask[y_padded:y_padded+h_padded, x_padded:x_padded+w_padded]
 
         # Apply smoothing and denoising to the cropped mask
-        smooth_denoised_mask = smooth_and_denoise(cropped_mask)
+        smooth_denoised_mask = smooth_edges(cropped_mask)
 
         # Create an RGBA image with a black background and the denoised mask as the alpha channel
         mask_image = Image.new('RGBA', (w_padded, h_padded), (0, 0, 0))
@@ -200,6 +200,29 @@ def smooth_and_denoise(mask):
     return denoised_mask
 
 
+def smooth_edges(mask):
+    """
+    Smooth edges of a binary mask using morphological operations.
+    :param mask: The binary mask of the signature.
+    :return: Mask with smoothed edges.
+    """
+    # Convert mask to uint8 type if it isn't already
+    mask = mask.astype(np.uint8)
+    
+    # Define a kernel for morphological operations
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
+    
+    # Use morphological close operation to close small holes in the mask
+    closing = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel, iterations=2)
+    
+    # Use morphological open operation to remove noise
+    opening = cv2.morphologyEx(closing, cv2.MORPH_OPEN, kernel, iterations=2)
+    
+    # Dilate the mask to make the signature slightly thicker
+    dilated = cv2.dilate(opening, kernel, iterations=1)
+    
+    return dilated
+
     
 def predict(net,  inputs_val, shapes_val, hypar, device):
     '''