              setattr(self.converter.args, key, val)
          logger.debug("Updated Converter cli arguments")
  
      @staticmethod
      def feed_swapped_faces(patch_queue_in, samples):
          """ Feed swapped faces to the converter and trigger a run """
          logger.trace("feeding swapped faces to converter")
          for item in samples.predicted_images:
              patch_queue_in.put(item)
          logger.trace("fed %s swapped faces to converter", len(samples.predicted_images))
          logger.trace("Putting EOF to converter")
 
</s> remove             setattr(self.converter.args, key, val)
 </s> add             setattr(self._converter.cli_arguments, key, val) </s> remove     def patch_faces(self, queue_in, queue_out, sample_size):
        """ Patch faces """
 </s> add     def _patch_faces(self, queue_in, queue_out, sample_size):
        """ Patch faces.

        Run the convert process on the swapped faces and return the patched faces.

        patch_queue_in: :class:`queue.Queue`
            The input queue for the patching process
        queue_out: :class:`queue.Queue`
            The output queue from the patching process
        sample_size: int
            The number of samples to be displayed

        Returns
        -------
        list
            The swapped faces patched with the selected convert settings
        """ </s> remove     def update_converter_arguments(self):
        """ Update the converter arguments """
 </s> add     def _update_converter_arguments(self):
        """ Update the converter arguments to the currently selected values. """ </s> remove     def crop_destination_faces(self):
        """ Update the main faces dict with new destination faces based on source matrices """
 </s> add     def _crop_destination_faces(self):
        """ Extract the swapped faces from the swapped frames using the source face destination
        matrices. """ </s> remove             self.feed_swapped_faces(patch_queue_in, samples)
            with self.lock:
                self.update_converter_arguments()
                self.converter.reinitialize(config=self.current_config)
            swapped = self.patch_faces(patch_queue_in, patch_queue_out, samples.sample_size)
            with self.lock:
                self.display.destination = swapped
 </s> add             self._feed_swapped_faces(patch_queue_in, samples)
            with self._lock:
                self._update_converter_arguments()
                self._converter.reinitialize(config=self.current_config)
            swapped = self._patch_faces(patch_queue_in, patch_queue_out, samples.sample_size)
            with self._lock:
                self._display.destination = swapped
    def _feed_swapped_faces(patch_queue_in, samples):
        """ Feed swapped faces to the converter's in-queue.

        Parameters
        ----------
        patch_queue_in: :class:`queue.Queue`
            The input queue for the patching process
        samples: :class:`Samples`
            The Samples for display.
        """
              setattr(self.converter.args, key, val)
          logger.debug("Updated Converter cli arguments")
  
      @staticmethod
    def _feed_swapped_faces(patch_queue_in, samples):
        """ Feed swapped faces to the converter's in-queue.

        Parameters
        ----------
        patch_queue_in: :class:`queue.Queue`
            The input queue for the patching process
        samples: :class:`Samples`
            The Samples for display.
        """
    def _feed_swapped_faces(patch_queue_in, samples):
        """ Feed swapped faces to the converter's in-queue.

        Parameters
        ----------
        patch_queue_in: :class:`queue.Queue`
            The input queue for the patching process
        samples: :class:`Samples`
            The Samples for display.
        """
          logger.trace("feeding swapped faces to converter")
          for item in samples.predicted_images:
              patch_queue_in.put(item)
          logger.trace("fed %s swapped faces to converter", len(samples.predicted_images))
          logger.trace("Putting EOF to converter")
keep keep keep keep replace replace keep keep keep keep keep
 Smart Masks to Convert (#957)

- scripts.convert - Use Smart Masks for Convert
    * Make on-the-fly conversion an explicit option

- Move BlurMask to lib.faces_detect

- tools.preview - Fix for smart masks
    * Subclass from tk.Tk
    * Options to lib.gui.control_helper
    *variable cleanup

- lib.logger - Demote more tensorflow deprecation messages

- Documentation:
    * lib.faces_detect.BlurMask
    * plugins.convert.mask
    * lib.convert
    * scripts.convert
    * scripts.fsmedia
    * tools.preview 
tools/preview.py