          mask = detected_face.mask[self._mask_type]
          mask.set_blur_and_threshold(**self._output["opts"])
          if not self._output["full_frame"] or self._input_is_faces:
              if self._input_is_faces:
                  face = detected_face.image
              else:
                  detected_face.load_aligned(detected_face.image)
                  face = detected_face.aligned_face
              mask = cv2.resize(detected_face.mask[self._mask_type].mask,
                                (face.shape[1], face.shape[0]),
 
</s> remove                 detected_face.load_aligned(detected_face.image)
                face = detected_face.aligned_face
 </s> add                 centering = "legacy" if self._alignments.version == 1.0 else "face"
                detected_face.load_aligned(detected_face.image, centering=centering)
                face = detected_face.aligned.face </s> remove             face = detected_face.image
 </s> add             face = np.array(detected_face.image)  # cv2 fails if this comes as imageio.core.Array </s> remove         mask, raw_mask = self._adjustments["mask"].run(detected_face, predicted_mask)
 </s> add         if self._centering == "legacy":
            crop_offset = reference_face.pose.offset["face"] * -1
        else:
            crop_offset = np.array((0, 0))
        mask, raw_mask = self._adjustments["mask"].run(detected_face, crop_offset, predicted_mask) </s> remove         mask = self._get_mask(detected_face, predicted_mask)
 </s> add         mask = self._get_mask(detected_face, predicted_mask, sub_crop_offset)
                face = AlignedFace(detected_face.landmarks_xy,
                                   image=detected_face.image,
                                   centering="face",
                                   size=detected_face.image.shape[0],
                                   is_aligned=True).face
          mask = detected_face.mask[self._mask_type]
          mask.set_blur_and_threshold(**self._output["opts"])
          if not self._output["full_frame"] or self._input_is_faces:
              if self._input_is_faces:
                face = AlignedFace(detected_face.landmarks_xy,
                                   image=detected_face.image,
                                   centering="face",
                                   size=detected_face.image.shape[0],
                                   is_aligned=True).face
              else:
                  detected_face.load_aligned(detected_face.image)
                  face = detected_face.aligned_face
              mask = cv2.resize(detected_face.mask[self._mask_type].mask,
                                (face.shape[1], face.shape[0]),
keep keep keep keep 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/mask/mask.py