          return box
  
      def run(self,
              detected_face: DetectedFace,
              sub_crop_offset: Optional[np.ndarray],
              centering: Literal["legacy", "face", "head"],
              predicted_mask: Optional[np.ndarray] = None) -> Tuple[np.ndarray, np.ndarray]:
          """ Obtain the requested mask type and perform any defined mask manipulations.
  
          Parameters
 
</s> remove                   sub_crop_offset: Optional[np.ndarray]) -> np.ndarray:
 </s> add                   source_offset: np.ndarray,
                  target_offset: np.ndarray) -> np.ndarray: </s> remove                          sub_crop_offset: Optional[np.ndarray]) -> np.ndarray:
 </s> add                          source_offset: np.ndarray,
                         target_offset: np.ndarray) -> np.ndarray: </s> remove                      "sub_crop_offset: %s, centering: '%s', predicted_mask: %s",
                     detected_face, sub_crop_offset, centering, predicted_mask is not None)
        mask = self._get_mask(detected_face, predicted_mask, centering, sub_crop_offset)
 </s> add                      "source_offset: %s, target_offset: %s, centering: '%s', predicted_mask: %s",
                     detected_face, source_offset, target_offset, centering,
                     predicted_mask is not None)
        mask = self._get_mask(detected_face,
                              predicted_mask,
                              centering,
                              source_offset,
                              target_offset) </s> remove         sub_crop_offset: :class:`numpy.ndarray`, optional
            The (x, y) offset to crop the mask from the center point.
 </s> add         source_offset: :class:`numpy.ndarray`
            The (x, y) offset for the mask at its stored centering
        target_offset: :class:`numpy.ndarray`
            The (x, y) offset for the mask at the requested target centering </s> remove         sub_crop_offset: :class:`numpy.ndarray`
            The (x, y) offset to crop the mask from the center point. Set to `None` if the mask
            does not need to be offset for alternative centering
 </s> add         source_offset: :class:`numpy.ndarray`
            The (x, y) offset for the mask at its stored centering
        target_offset: :class:`numpy.ndarray`
            The (x, y) offset for the mask at the requested target centering
            source_offset: np.ndarray,
            target_offset: np.ndarray,
          return box
  
      def run(self,
              detected_face: DetectedFace,
            source_offset: np.ndarray,
            target_offset: np.ndarray,
              centering: Literal["legacy", "face", "head"],
              predicted_mask: Optional[np.ndarray] = None) -> Tuple[np.ndarray, np.ndarray]:
          """ Obtain the requested mask type and perform any defined mask manipulations.
  
          Parameters
keep keep keep keep replace keep keep keep keep keep
 lib.detected_face.Mask
  - Add source + target offset and coverage to set_sub_crop method 
plugins/convert/mask/mask_blend.py