                  return data
              data = super().load()
              return data
  
          skip_existing = bool(hasattr(self.args, 'skip_existing')
                               and self.args.skip_existing)
          skip_faces = bool(hasattr(self.args, 'skip_faces')
                            and self.args.skip_faces)
  
          if not skip_existing and not skip_faces:
              logger.debug("No skipping selected. Returning empty dictionary")
              return data
  
 
</s> remove         if not self.is_extract:
 </s> add         if not self._is_extract: </s> remove         """ Override  parent loader to handle skip existing on extract """
 </s> add         """ Override the parent :func:`~lib.alignments.Alignments.load` to handle skip existing
        frames and faces on extract.

        If skip existing has been selected, existing alignments are loaded and returned to the
        calling script.

        Returns
        -------
        dict
            Any alignments that have already been extracted if skip existing has been selected
            otherwise an empty dictionary
        """ </s> remove     """ Holds the full frames/images """
 </s> add     """ Handles the loading of frames from a folder of images or a video file for extract
    and convert processes.

    Parameters
    ----------
    arguments: :class:`argparse.Namespace`
        The command line arguments that were passed to Faceswap
    """ </s> remove                     # raise an error on numeric datatypes so return 0
 </s> add                     # raise an error on numeric data types so return 0 </s> remove         face_hashes = self.get_face_hashes()
 </s> add         face_hashes = self._get_face_hashes()
        skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
        skip_faces = hasattr(self._args, 'skip_faces') and self._args.skip_faces
                  return data
              data = super().load()
              return data
  
        skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
        skip_faces = hasattr(self._args, 'skip_faces') and self._args.skip_faces
        skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
        skip_faces = hasattr(self._args, 'skip_faces') and self._args.skip_faces
        skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
        skip_faces = hasattr(self._args, 'skip_faces') and self._args.skip_faces
        skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
        skip_faces = hasattr(self._args, 'skip_faces') and self._args.skip_faces
  
          if not skip_existing and not skip_faces:
              logger.debug("No skipping selected. Returning empty dictionary")
              return data
  
keep keep keep keep replace replace 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 
scripts/fsmedia.py