              logger.trace("original matrix: %s, new matrix: %s", self._matrices["legacy"], matrix)
          return self._matrices[self._centering]
  
      @property
      def _head_size(self):
          """ int: The size of the full head extract image calculated from the required
          centering. """
          with self._cache["head_size"][1]:
              if self._centering not in self._cache["head_size"][0]:
                  self._cache["head_size"][0][self._centering] = get_centered_size(self._centering,
                                                                                   "head",
                                                                                   self.size)
          return self._cache["head_size"][0][self._centering]
  
      @property
      def pose(self):
          """ :class:`lib.align.PoseEstimate`: The estimated pose in 3D space. """
          with self._cache["pose"][1]:
              if self._cache["pose"][0] is None:
                  lms = cv2.transform(np.expand_dims(self._frame_landmarks, axis=1),
                                      self._matrices["legacy"]).squeeze()
 
</s> remove             logger.trace("original matrix: %s, new matrix: %s", self._matrices["legacy"], matrix)
 </s> add             logger.trace("original matrix: %s, new matrix: %s",  # type: ignore
                         self._matrices["legacy"], matrix) </s> remove         with self._cache["pose"][1]:
            if self._cache["pose"][0] is None:
 </s> add         with self._cache.lock("pose"):
            if self._cache.pose is None: </s> remove         if self._matrices[self._centering] is None:
 </s> add         if not np.any(self._matrices[self._centering]): </s> remove                 self._cache["pose"][0] = PoseEstimate(lms)
        return self._cache["pose"][0]
 </s> add                 self._cache.pose = PoseEstimate(lms)
        return self._cache.pose </s> remove     def size(self):
 </s> add     def centering(self) -> Literal["legacy", "head", "face"]:
        """ str: The centering of the Aligned Face. One of `"legacy"`, `"head"`, `"face"`. """
        return self._centering

    @property
    def size(self) -> int:
    def pose(self) -> "PoseEstimate":
              logger.trace("original matrix: %s, new matrix: %s", self._matrices["legacy"], matrix)
          return self._matrices[self._centering]
  
      @property
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
    def pose(self) -> "PoseEstimate":
          """ :class:`lib.align.PoseEstimate`: The estimated pose in 3D space. """
          with self._cache["pose"][1]:
              if self._cache["pose"][0] is None:
                  lms = cv2.transform(np.expand_dims(self._frame_landmarks, axis=1),
                                      self._matrices["legacy"]).squeeze()
keep keep keep keep replace replace replace replace replace replace replace replace replace replace replace replace keep keep keep keep keep
 lib.align.aligned_face updates
  - Typing
  - Legacy support for pre-aligned faces
  - Coverage support for pre-aligned faces
  - Standardized retrieval of sub-crops 
lib/align/aligned_face.py