              image_mask = np.concatenate(image_mask, alpha, axis=2)
              frame = np.concatenate(frame, alpha, axis=2)
  
          if self.args.sharpen_image is not None and self.args.sharpen_image.lower() != "none":
              np.clip(masked, 0.0, 255.0, out=masked)
              if self.args.sharpen_image == "box_filter":
                  kernel = np.ones((3, 3)) * (-1)
                  kernel[1, 1] = 9
                  masked = cv2.filter2D(masked, -1, kernel)  # pylint: disable=no-member
              elif self.args.sharpen_image == "gaussian_filter":
 
</s> remove                 masked = cv2.filter2D(masked, -1, kernel)  # pylint: disable=no-member
 </s> add                 new_image = cv2.filter2D(new_image, -1, kernel)  # pylint: disable=no-member </s> remove                 blur = cv2.GaussianBlur(masked, (0, 0), 3.0)  # pylint: disable=no-member
                masked = cv2.addWeighted(masked,  # pylint: disable=no-member
 </s> add                 blur = cv2.GaussianBlur(new_image, (0, 0), 3.0)  # pylint: disable=no-member
                new_image = cv2.addWeighted(new_image,  # pylint: disable=no-member </s> remove         masked = new_image  # * image_mask
 </s> add  </s> remove             np.clip(masked, 0.0, 255.0, out=masked)
            masked = self.color_hist_match(masked, frame, image_mask)
 </s> add             np.clip(new_image, 0.0, 255.0, out=new_image)
            new_image = self.color_hist_match(new_image, frame, image_mask) </s> remove             foreground = masked * image_mask
 </s> add             foreground = new_image * image_mask
            np.clip(new_image, 0.0, 255.0, out=new_image)
              image_mask = np.concatenate(image_mask, alpha, axis=2)
              frame = np.concatenate(frame, alpha, axis=2)
  
          if self.args.sharpen_image is not None and self.args.sharpen_image.lower() != "none":
            np.clip(new_image, 0.0, 255.0, out=new_image)
              if self.args.sharpen_image == "box_filter":
                  kernel = np.ones((3, 3)) * (-1)
                  kernel[1, 1] = 9
                  masked = cv2.filter2D(masked, -1, kernel)  # pylint: disable=no-member
              elif self.args.sharpen_image == "gaussian_filter":
keep keep keep keep replace keep keep keep keep keep
 auto smooth edges size and clarify naming 
plugins/convert/masked.py