      logger.trace("interpolator: %s, inverse interpolator: %s", interpolators[0], interpolators[1])
      return interpolators
  
  
  def transform_image(image, matrix, size, padding=0):
      """ Perform transformation on an image, applying the given size and padding to the matrix.
  
      Parameters
      ----------
      image: :class:`numpy.ndarray`
 
</s> remove     logger.trace("interpolator: %s, inverse interpolator: %s", interpolators[0], interpolators[1])
 </s> add     logger.trace("interpolator: %s, inverse interpolator: %s",  # type: ignore
                 interpolators[0], interpolators[1]) </s> remove def get_matrix_scaling(matrix):
 </s> add def get_matrix_scaling(matrix: np.ndarray) -> Tuple[int, int]: </s> remove     logger.trace("image shape: %s, matrix: %s, size: %s. padding: %s",
 </s> add     logger.trace("image shape: %s, matrix: %s, size: %s. padding: %s",  # type: ignore </s> remove     def extract_face(self, image):
 </s> add     def extract_face(self, image: Optional[np.ndarray]) -> Optional[np.ndarray]: </s> remove         face.
 </s> add         face at the selected coverage ratio.
def transform_image(image: np.ndarray,
                    matrix: np.ndarray,
                    size: int,
                    padding: int = 0) -> np.ndarray:
      logger.trace("interpolator: %s, inverse interpolator: %s", interpolators[0], interpolators[1])
      return interpolators
  
  
def transform_image(image: np.ndarray,
                    matrix: np.ndarray,
                    size: int,
                    padding: int = 0) -> np.ndarray:
      """ Perform transformation on an image, applying the given size and padding to the matrix.
  
      Parameters
      ----------
      image: :class:`numpy.ndarray`
keep keep keep keep 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