              ``True`` if landmarks are being adjusted on a zoomed image otherwise ``False``
          """
          face = self._faces_at_frame_index(frame_index)[face_index]
          if is_zoomed:
              if not np.any(face.aligned_landmarks):  # This will be None on a resize
                  face.load_aligned(None, size=min(self._globals.frame_display_dims))
              landmark = face.aligned_landmarks[landmark_index]
              landmark += (shift_x, shift_y)
              matrix = AlignerExtract.transform_matrix(face.aligned["matrix"],
                                                       face.aligned["size"],
                                                       face.aligned["padding"])
              matrix = cv2.invertAffineTransform(matrix)
 
</s> remove             matrix = AlignerExtract.transform_matrix(face.aligned["matrix"],
                                                     face.aligned["size"],
                                                     face.aligned["padding"])
 </s> add             matrix = aligned.adjusted_matrix </s> remove             detected_face.load_aligned(src_img, self._size)
            matrix = detected_face.aligned["matrix"]
 </s> add             detected_face.load_aligned(src_img, size=self._size, centering=self._centering)
            matrix = detected_face.aligned.matrix </s> remove         ``False`` if the standard random warp method should be used. If ``True`` then
        the key `landmarks` must be provided in the alignments dictionary.
 </s> add         ``False`` if the standard random warp method should be used.
            aligned = AlignedFace(face.landmarks_xy,
                                  centering="face",
                                  size=min(self._globals.frame_display_dims))
            landmark = aligned.landmarks[landmark_index]
              ``True`` if landmarks are being adjusted on a zoomed image otherwise ``False``
          """
          face = self._faces_at_frame_index(frame_index)[face_index]
          if is_zoomed:
            aligned = AlignedFace(face.landmarks_xy,
                                  centering="face",
                                  size=min(self._globals.frame_display_dims))
            landmark = aligned.landmarks[landmark_index]
            aligned = AlignedFace(face.landmarks_xy,
                                  centering="face",
                                  size=min(self._globals.frame_display_dims))
            landmark = aligned.landmarks[landmark_index]
            aligned = AlignedFace(face.landmarks_xy,
                                  centering="face",
                                  size=min(self._globals.frame_display_dims))
            landmark = aligned.landmarks[landmark_index]
              landmark += (shift_x, shift_y)
              matrix = AlignerExtract.transform_matrix(face.aligned["matrix"],
                                                       face.aligned["size"],
                                                       face.aligned["padding"])
              matrix = cv2.invertAffineTransform(matrix)
keep keep keep keep replace replace replace keep keep keep keep keep
 Extract - Increase area and move centering (#1095)

* Extract
  - Implement aligner re-feeding
  - Add extract type to pipeline.ExtractMedia
  - Add pose annotation to debug
* Convert
  - implement centering
  - remove usage of feed and reference face properties
  - Remove distributed option from convert
  - Force update of alignments file on legacy receive
* Train
  - Resize preview image to model output size
  - Force legacy centering if centering does not exist in model's state file
  - Enable training on legacy face sets

* Alignments Tool
  - Update draw to include head/pose
  - Remove DFL drop + linting
  - Remove remove-frames job
  - remove align-eyes option
  - Update legacy masks to new extract type
  - Exit if attempting to merge version 1.0 alignments files with version 2.0 alignments files
  - Re-generate thumbnails on legacy upgrade
* Mask Tool
  - Update for new extract + bugfix full frame
* Manual Tool
  - Update to new extraction method
   - Disable legacy alignments,
   - extract box bugfix
   - extract faces - size to 512 and center on head
* Preview Tool
  - Display based on model centering
* Sort Tool
  - Use alignments for sort by face

* lib.aligner
  - Add Pose Class
  - Add AlignedFace Class
  - center _MEAN_FACE on x
  - Add meta information with versioning to alignments file
  - lib.aligner.get_align_matrix to use landmarks not face
  - Refactor aligned faces in lib.faces_detect
* lib.logger
  - larger file log padding
* lib.config
  - Fix global changeable_items
* lib.face_filter
  - Use new extracted face images
* lib.image
  - bump thumbnail default size to 96px 
tools/manual/detected_faces.py