          else:
              retval = item.mask
          return retval
  
      @staticmethod
      def _resize_masks(target_size, masks):
          """ Resize the masks to the target size """
          logger.trace("target size: %s, masks shape: %s", target_size, masks.shape)
          mask_size = masks.shape[1]
          if target_size == mask_size:
              logger.trace("Mask and targets the same size. Not resizing")
 
</s> remove         logger.trace("Input batch shape: %s, side: %s", batch.shape, side)
 </s> add         logger.trace("Input filenames: %s, batch shape: %s, side: %s",
                     filenames, batch.shape, side) </s> remove             Includes the key `landmarks` if landmarks are required for training, `masks` if masks
            are required for training, `masks_eye` if eye masks are required and `masks_mouth` if
            mouth masks are required. """
        retval = dict()
 </s> add             Includes the key `aligned_faces` holding aligned face information and the key
            `versions` indicating the alignments file versions that the faces have come from.
            In addition, the following optional keys are provided: `masks` if masks are required
            for training, `masks_eye` if eye masks are required and `masks_mouth` if mouth masks
            are required. """ </s> remove     def get_items(self, arguments):
        """ Set the correct items to process """
        retval = None
        if self.type == "frames":
            retval = Frames(arguments.frames_dir).items
        elif self.type == "faces":
            retval = Faces(arguments.faces_dir)
        return retval

 </s> add 
    @classmethod
    def _resize_masks(cls, target_size, masks):
          else:
              retval = item.mask
          return retval
  
    @classmethod
    def _resize_masks(cls, target_size, masks):
    @classmethod
    def _resize_masks(cls, target_size, masks):
          """ Resize the masks to the target size """
          logger.trace("target size: %s, masks shape: %s", target_size, masks.shape)
          mask_size = masks.shape[1]
          if target_size == mask_size:
              logger.trace("Mask and targets the same size. Not resizing")
keep keep keep keep 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 
lib/training_data.py