              new_face = self._adjustments["seamless"].run(old_face, new_face, raw_mask)
          logger.trace("returning: new_face shape %s", new_face.shape)
          return new_face
  
      def _get_image_mask(self, new_face, detected_face, predicted_mask):
          """ Return any selected image mask and intersect with any box mask.
  
          Places the requested mask into the new face's Alpha channel, intersecting with any box
          mask that has already been applied.
  
 
</s> remove         new_face, raw_mask = self._get_image_mask(new_face, detected_face, predicted_mask)
 </s> add         new_face, raw_mask = self._get_image_mask(new_face,
                                                  detected_face,
                                                  predicted_mask,
                                                  reference_face) </s> remove     def _get_mask(self, detected_face, predicted_mask):
 </s> add     def _get_mask(self, detected_face, predicted_mask, sub_crop_offset): </s> remove     def _pre_warp_adjustments(self, new_face, detected_face, predicted_mask):
 </s> add     def _pre_warp_adjustments(self, new_face, detected_face, reference_face, predicted_mask): </s> remove         detected_face: :class:`lib.faces_detect.DetectedFace`
 </s> add         detected_face: :class:`lib.align.DetectedFace` </s> remove             new_face = self._pre_warp_adjustments(new_face, detected_face, predicted_mask)
 </s> add             new_face = self._pre_warp_adjustments(new_face,
                                                  detected_face,
                                                  reference_face,
                                                  predicted_mask)
    def _get_image_mask(self, new_face, detected_face, predicted_mask, reference_face):
              new_face = self._adjustments["seamless"].run(old_face, new_face, raw_mask)
          logger.trace("returning: new_face shape %s", new_face.shape)
          return new_face
  
    def _get_image_mask(self, new_face, detected_face, predicted_mask, reference_face):
          """ Return any selected image mask and intersect with any box mask.
  
          Places the requested mask into the new face's Alpha channel, intersecting with any box
          mask that has already been applied.
  
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 
lib/convert.py