          self._output_faces = []
          self._additional_keys = []
          logger.debug("Initialized %s", self.__class__.__name__)
  
      def set_normalize_method(self, method):
          """ Set the normalization method for feeding faces into the aligner.
  
          Parameters
          ----------
          method: {"none", "clahe", "hist", "mean"}
 
</s> remove         self._faces_per_filename = {}  # Tracking for recompiling face batches
        self._rollover = None  # Items that are rolled over from the previous batch in get_batch
        self._output_faces = []
        self._additional_keys = []
 </s> add         self._faces_per_filename: Dict[str, int] = {}  # Tracking for recompiling batches
        self._rollover: Optional[ExtractMedia] = None  # batch rollover items
        self._output_faces: List[DetectedFace] = []
        self._filter = AlignedFilter(min_scale=self.config["aligner_min_scale"],
                                     max_scale=self.config["aligner_max_scale"],
                                     distance=self.config["aligner_distance"]) </s> remove     def set_aligner_normalization_method(self, method: str) -> None:
 </s> add     def set_aligner_normalization_method(self, method: Optional[Literal["none",
                                                                        "clahe",
                                                                        "hist",
                                                                        "mean"]]) -> None: </s> remove         self._normalize_method = method
 </s> add         self._normalize_method = cast(Optional[Literal["clahe", "hist", "mean"]], method) </s> remove     def _normalize_faces(self, faces):
 </s> add     def _normalize_faces(self, faces: List[np.ndarray]) -> List[np.ndarray]:
    def set_normalize_method(self,
                             method: Optional[Literal["none", "clahe", "hist", "mean"]]) -> None:
          self._output_faces = []
          self._additional_keys = []
          logger.debug("Initialized %s", self.__class__.__name__)
  
    def set_normalize_method(self,
                             method: Optional[Literal["none", "clahe", "hist", "mean"]]) -> None:
          """ Set the normalization method for feeding faces into the aligner.
  
          Parameters
          ----------
          method: {"none", "clahe", "hist", "mean"}
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