  
      def __init__(self, *args, **kwargs):
          super().__init__(*args, **kwargs)
          logger.info("Extracting and aligning face for Face Filter...")
          self.filter = self.load_face_filter(**kwargs)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      def load_face_filter(self, filter_lists, ref_threshold, aligner, detector,
                           multiprocess):
          """ Load faces to filter out of images """
 
</s> remove     def load_face_filter(self, filter_lists, ref_threshold, aligner, detector,
                         multiprocess):
        """ Load faces to filter out of images """
 </s> add     def _load_face_filter(self, filter_lists, ref_threshold, aligner, detector, multiprocess):
        """ Set up and load the :class:`~lib.face_filter.FaceFilter`.

        Parameters
        ----------
        filter_lists: dict
            The filter and nfilter image paths
        ref_threshold: float
            The reference threshold for a positive match
        aligner: str
            The aligner to use
        detector: str
            The detector to use
        multiprocess: bool
            Whether to run the extraction pipeline in single process mode or not

        Returns
        -------
        :class:`~lib.face_filter.FaceFilter`
            The face filter
        """ </s> remove     """ Filter in or out faces based on input image(s)
        Extract or Convert """
 </s> add     """ Filter in or out faces based on input image(s). Extract or Convert

    Parameters
    -----------
    args: tuple
        Unused
    kwargs: dict
        Keyword arguments for face filter:

        * **detector** (`str`) - The detector to use

        * **aligner** (`str`) - The aligner to use

        * **multiprocess** (`bool`) - Whether to run the extraction pipeline in single process \
        mode or not

        * **ref_threshold** (`float`) - The reference threshold for a positive match

        * **filter_lists** (`dict`) - The filter and nfilter image paths
    """ </s> remove         self.valid = True  # Set to False if invalid parameters passed in to disable
 </s> add         self._valid = True  # Set to False if invalid parameters passed in to disable </s> remove         self.args = arguments
        self.is_video = self.check_input_folder()
        self.input_images = self.get_input_images()
        self.images_found = self.count_images()
 </s> add         self._args = arguments
        self._is_video = self._check_input_folder()
        self._input_images = self._get_input_images()
        self._images_found = self._count_images() </s> remove     def random_choice(self):
        """ Return for random indices from the indices group """
        retval = [random.choice(indices) for indices in self.indices]
 </s> add     def sample_size(self):
        """ int: The number of samples to take from the input video/images """
        return self._sample_size

    @property
    def predicted_images(self):
        """ list: The predicted faces output from the Faceswap model """
        return self._predicted_images

    @property
    def alignments(self):
        """ :class:`~lib.alignments.Alignments`: The alignments for the preview faces """
        return self._alignments

    @property
    def predictor(self):
        """ :class:`~scripts.convert.Predict`: The Predictor for the Faceswap model """
        return self._predictor

    @property
    def _random_choice(self):
        """ list: Random indices from the :attr:`_indices` group """
        retval = [random.choice(indices) for indices in self._indices]
        self._filter = self._load_face_filter(**kwargs)
  
      def __init__(self, *args, **kwargs):
          super().__init__(*args, **kwargs)
          logger.info("Extracting and aligning face for Face Filter...")
        self._filter = self._load_face_filter(**kwargs)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      def load_face_filter(self, filter_lists, ref_threshold, aligner, detector,
                           multiprocess):
          """ Load faces to filter out of images """
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/fsmedia.py