              The center point of the Landmark's Extract Box
          """
          face = self._faces_at_frame_index(frame_index)[face_index]
          rot_mat = cv2.getRotationMatrix2D(tuple(center.astype("float32")), angle, 1.)
          face.landmarks_xy = cv2.transform(np.expand_dims(face.landmarks_xy, axis=0),
                                            rot_mat).squeeze()
          self._globals.tk_update.set(True)
  
      def landmarks_scale(self, frame_index, face_index, scale, center):
          """ Scale the landmarks on an Extract Box resize for the
          :class:`~lib.align.DetectedFace` object at the given frame and face indices from the
 
</s> remove         face.landmarks_xy = ((face.landmarks_xy - center) * scale) + center
 </s> add         face._landmarks_xy = ((face.landmarks_xy - center) * scale) + center </s> remove         face.x += shift_x
        face.y += shift_y
        face.landmarks_xy += (shift_x, shift_y)
 </s> add         face.left += shift_x
        face.top += shift_y
        face._landmarks_xy += (shift_x, shift_y) </s> remove         face.x = pnt_x
        face.w = width
        face.y = pnt_y
        face.h = height
        face.landmarks_xy = self._extractor.get_landmarks(frame_index, face_index, aligner)
 </s> add         face.left = pnt_x
        face.width = width
        face.top = pnt_y
        face.height = height
        face._landmarks_xy = self._extractor.get_landmarks(frame_index, face_index, aligner) </s> remove         numpy.ndarray: The mask affined to the original full frame of the given dimensions
 </s> add         :class:`numpy.ndarray`: The mask affined to the original full frame of the given dimensions </s> remove         key = "{}_{}".format(frame_index, face_index)
 </s> add         key = f"{frame_index}_{face_index}"
        face._landmarks_xy = cv2.transform(np.expand_dims(face.landmarks_xy, axis=0),
                                           rot_mat).squeeze()
              The center point of the Landmark's Extract Box
          """
          face = self._faces_at_frame_index(frame_index)[face_index]
          rot_mat = cv2.getRotationMatrix2D(tuple(center.astype("float32")), angle, 1.)
        face._landmarks_xy = cv2.transform(np.expand_dims(face.landmarks_xy, axis=0),
                                           rot_mat).squeeze()
        face._landmarks_xy = cv2.transform(np.expand_dims(face.landmarks_xy, axis=0),
                                           rot_mat).squeeze()
          self._globals.tk_update.set(True)
  
      def landmarks_scale(self, frame_index, face_index, scale, center):
          """ Scale the landmarks on an Extract Box resize for the
          :class:`~lib.align.DetectedFace` object at the given frame and face indices from the
keep keep keep keep replace replace keep keep keep keep keep
 lib.align updates:
  - alignments.py
    - Add typed dicts for imported alignments
    - Explicitly check for presence of thumb value in alignments dict
    - linting
  - detected_face.py
    - Typing
    - Linting
    - Legacy support for pre-aligned face
    - Update dependencies to new property names 
tools/manual/detected_faces.py