          self.input_size = 224
          # Average image provided in https://github.com/ox-vgg/vgg_face2
          self.average_img = np.array([91.4953, 103.8827, 131.0912])
  
          self.model = self.get_model(git_model_id, model_filename, backend)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      # <<< GET MODEL >>> #
      @staticmethod
      def get_model(git_model_id, model_filename, backend):
 
</s> remove     def get_model(git_model_id, model_filename, backend):
        """ Check if model is available, if not, download and unzip it """
 </s> add     def _get_model(git_model_id, model_filename, backend):
        """ Check if model is available, if not, download and unzip it

        Parameters
        ----------
        git_model_id: int
            The second digit in the github tag that identifies this model. See
            https://github.com/deepfakes-models/faceswap-models for more information
        model_filename: str
            The name of the model to be loaded (see :class:`lib.utils.GetModel` for more
            information)
        backend: ['GPU', 'CPU']
            Whether to run inference on a GPU or on the CPU

        See Also
        --------
        lib.utils.GetModel: The model downloading and allocation class.
        """ </s> remove             str: 'linkage' or 'vector'
 </s> add             bool:
                ``True`` if vector_linkage should be used. ``False`` if linkage should be used </s> remove         linkage_required = (((item_count ** 2) * np_float) / 1.7) / divider
 </s> add         linkage_required = (((item_count ** 2) * np_float) / 1.8) / divider </s> remove             face = self.resize_face(face)
 </s> add             face = self._resize_face(face) </s> remove         """ Return encodings for given image from vgg_face """
 </s> add         """ Return encodings for given image from vgg_face2.

        Parameters
        ----------
        face: numpy.ndarray
            The face to be fed through the predictor. Should be in BGR channel order

        Returns
        -------
        numpy.ndarray
            The encodings for the face
        """
        self.model = self._get_model(git_model_id, model_filename, backend)
          self.input_size = 224
          # Average image provided in https://github.com/ox-vgg/vgg_face2
          self.average_img = np.array([91.4953, 103.8827, 131.0912])
  
        self.model = self._get_model(git_model_id, model_filename, backend)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      # <<< GET MODEL >>> #
      @staticmethod
      def get_model(git_model_id, model_filename, backend):
keep keep keep keep replace keep keep keep keep keep
 bugfix: tools.preview - Fix for new icons
bugfix: lib.vgg_face2_keras - Remove debug code
documentation: lib.vgg_face2_keras 
lib/vgg_face2_keras.py