  
          batch.update(retval)
          return batch
  
      def _get_adjusted_boxes(self, original_boxes):
          """ Obtain an array of adjusted bounding boxes based on the number of re-feed iterations
          that have been selected and the minimum dimension of the original bounding box.
  
          Parameters
          ----------
 
</s> remove         batch.update(retval)
 </s> add  </s> remove     def _process_input(self, batch):
 </s> add     def _process_input(self, batch: AlignerBatch) -> AlignerBatch: </s> remove     def get_center_scale(self, detected_faces):
        """ Get the center and set scale of bounding box """
 </s> add         Parameters
        ----------
        detected_faces: list
            List of :class:`~lib.align.DetectedFace` objects for the batch

        Returns
        -------
        :class:`numpy.ndarray`
            The center and scale of the bounding box
        """ </s> remove         for face, box in zip(batch["detected_faces"], original_boxes):
 </s> add         for face, box in zip(batch.detected_faces, original_boxes): </s> remove     def _process_output(self, batch):
 </s> add     def _process_output(self, batch: AlignerBatch) -> AlignerBatch:
    def _get_adjusted_boxes(self, original_boxes: np.ndarray) -> np.ndarray:
  
          batch.update(retval)
          return batch
  
    def _get_adjusted_boxes(self, original_boxes: np.ndarray) -> np.ndarray:
          """ Obtain an array of adjusted bounding boxes based on the number of re-feed iterations
          that have been selected and the minimum dimension of the original bounding box.
  
          Parameters
          ----------
keep keep keep keep replace keep keep keep keep keep
 Extract updates:
  - Default CPU detector to MTCNN
  - add basic Aligner false positive filters
  - Typing: align + plugins
  - Use specific AlignerBatch class for alignment
  - 
plugins/extract/align/_base.py