  .. autosummary::
     :nosignatures:
  
     ~lib.model.losses_tf.DSSIMObjective
     ~lib.model.losses_tf.PenalizedLoss
     ~lib.model.losses_tf.GeneralizedLoss
     ~lib.model.losses_tf.GMSDLoss
     ~lib.model.losses_tf.GradientLoss
     ~lib.model.losses_tf.LInfNorm
  
 
</s> remove         """ Load the alignments and convert to :class:`lib.faces_detect.DetectedFace` objects.
 </s> add         """ Load the alignments and convert to :class:`lib.align.DetectedFace` objects. </s> remove             The :class:`numpy.ndarray` aligned landmarks for keys "a" and "b"
 </s> add             The "a", "b" keys for each side, containing a sub-dictionary with the
            filename as key and :class:`lib.faces.detected_face.AlignedFace` object as value. </s> remove         retval = {side: self._transform_landmarks(side, detected_faces)
                  for side, detected_faces in self._detected_faces.items()}
        logger.trace(retval)
 </s> add         retval = dict()
        for side, detected_faces in self._detected_faces.items():
            centering = "legacy" if self._alignments_version[side] == 1.0 else "head"
            logger.debug("side: %s, centering: %s", side, centering)
            ret_side = dict()
            for fhash, face in detected_faces.items():
                face.load_aligned(None, size=self._training_size, centering=centering)
                for filename in self._hash_to_filenames(side, fhash):
                    ret_side[filename] = face.aligned
            retval[side] = ret_side </s> remove     def _transform_landmarks(self, side, detected_faces):
        """ Transform frame landmarks to their aligned face variant.

        Parameters
        ----------
        side: {"a" or "b"}
            The side currently being processed
        detected_faces: list
            A list of :class:`lib.faces_detect.DetectedFace` objects

        Returns
        -------
        dict
            The face filenames as keys with the aligned landmarks as value.
        """
        landmarks = dict()
        for face in detected_faces.values():
            face.load_aligned(None, size=self._training_size)
            for filename in self._hash_to_filenames(side, face.hash):
                landmarks[filename] = face.aligned_landmarks
        return landmarks

 </s> add 
  .. autosummary::
     :nosignatures:
  
     ~lib.model.losses_tf.DSSIMObjective

     ~lib.model.losses_tf.GeneralizedLoss
     ~lib.model.losses_tf.GMSDLoss
     ~lib.model.losses_tf.GradientLoss
     ~lib.model.losses_tf.LInfNorm
  
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 
docs/full/lib/model.rst