                - Containing 3 sub images: The original face, the masked face and the mask
                - The mask only
                - The masked face
          """
          mask = detected_face.mask[self._mask_type]
          mask.set_blur_and_threshold(**self._output["opts"])
          if not self._output["full_frame"] or self._input_is_faces:
              if self._input_is_faces:
                  face = AlignedFace(detected_face.landmarks_xy,
                                     image=detected_face.image,
 
</s> remove         numpy.ndarray:
 </s> add         -------
        :class:`numpy.ndarray`: </s> remove             mask = cv2.resize(detected_face.mask[self._mask_type].mask,
 </s> add             mask = cv2.resize(detected_face.mask[mask_type].mask, </s> remove                 detected_face.load_aligned(detected_face.image, centering=centering)
 </s> add                 detected_face.load_aligned(detected_face.image, centering=centering, force=True) </s> remove         filename = os.path.join(self._saver.location, "{}_{}_{}".format(
            os.path.splitext(frame)[0],
            idx,
            self._output["suffix"]))
 </s> add         if self._update_type == "output" and self._mask_type == "bisenet-fp":
            mask_types = [f"{self._mask_type}_{area}" for area in ("face", "head")]
        else:
            mask_types = [self._mask_type] </s> remove         image = self._create_image(detected_face)
        logger.trace("filename: '%s', image_shape: %s", filename, image.shape)
        self._saver.save(filename, image)
 </s> add 
        mask = detected_face.mask[mask_type]
                - Containing 3 sub images: The original face, the masked face and the mask
                - The mask only
                - The masked face
          """
        mask = detected_face.mask[mask_type]
          mask.set_blur_and_threshold(**self._output["opts"])
          if not self._output["full_frame"] or self._input_is_faces:
              if self._input_is_faces:
                  face = AlignedFace(detected_face.landmarks_xy,
                                     image=detected_face.image,
keep keep keep keep replace keep keep keep keep keep
 mask tool - Update to support masks that support multi-centering 
tools/mask/mask.py