          consecutive_no_faces = 0
          batch = list()
          is_plaidml = GPUStats().is_plaidml
          while True:
              item = self.in_queue.get()
              if item != "EOF":
                  logger.trace("Got from queue: '%s'", item["filename"])
                  faces_count = len(item["detected_faces"])
  
                  # Safety measure. If a large stream of frames appear that do not have faces,
 
</s> remove                 # If self.batchsize number of frames appear, force the current batch through
 </s> add                 # If self._batchsize number of frames appear, force the current batch through </s> remove                 self.faces_count += faces_count
 </s> add                 self._faces_count += faces_count </s> remove     def predict_faces(self):
        """ Get detected faces from images """
 </s> add     def _launch_predictor(self):
        """ Launch the prediction process in a background thread.

        Starts the prediction thread and returns the thread.

        Returns
        -------
        :class:`~lib.multithreading.MultiThread`
            The started Faceswap model prediction thread.
        """
        thread = MultiThread(self._predict_faces, thread_count=1)
        thread.start()
        return thread

    def _predict_faces(self):
        """ Run Prediction on the Faceswap model in a background thread.

        Reads from the :attr:`self._in_queue`, prepares images for prediction
        then puts the predictions back to the :attr:`self.out_queue`
        """ </s> remove             item = self.save_queue.get()
 </s> add             item = self._queues["save"].get() </s> remove                     self.verify_output = True
 </s> add                     self._verify_output = True
            item = self._in_queue.get()
          consecutive_no_faces = 0
          batch = list()
          is_plaidml = GPUStats().is_plaidml
          while True:
            item = self._in_queue.get()
              if item != "EOF":
                  logger.trace("Got from queue: '%s'", item["filename"])
                  faces_count = len(item["detected_faces"])
  
                  # Safety measure. If a large stream of frames appear that do not have faces,
keep keep keep keep 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 
scripts/convert.py