  
      def predict(self, face):
          """ Return encodings for given image from vgg_face """
          if face.shape[0] != self.input_size:
              face = self.resize_face(face)
          face = face[None, :, :, :3] - self.average_img
          preds = self.model.predict(face)
          return preds[0, :]
  
      def resize_face(self, 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
        """ </s> remove     def resize_face(self, face):
        """ Resize incoming face to model_input_size """
 </s> add     def _resize_face(self, face):
        """ Resize incoming face to model_input_size.

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

        Returns
        -------
        numpy.ndarray
            The face resized to model input size
        """ </s> remove         """ Find the cosine similarity between a source face and a test face """
 </s> add         """ Find the cosine similarity between two faces.

        Parameters
        ----------
        source_face: numpy.ndarray
            The first face to test against :attr:`test_face`
        test_face: numpy.ndarray
            The second face to test against :attr:`source_face`

        Returns
        -------
        float:
            The cosine similarity between the two faces
        """ </s> remove         clustering_method = self._get_clustering_method(num_predictions, dims)

 </s> add  </s> remove         self.model = self.get_model(git_model_id, model_filename, backend)
 </s> add         self.model = self._get_model(git_model_id, model_filename, backend)
            face = self._resize_face(face)
  
      def predict(self, face):
          """ Return encodings for given image from vgg_face """
          if face.shape[0] != self.input_size:
            face = self._resize_face(face)
          face = face[None, :, :, :3] - self.average_img
          preds = self.model.predict(face)
          return preds[0, :]
  
      def resize_face(self, face):
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