          logger.trace("Building Faces Image")
          update_all = self.update_source
          self.faces_from_frames()
          if update_all:
              header = self.header_text()
              source = np.hstack([self.draw_rect(face) for face in self.faces["src"]])
              self.faces_source = np.vstack((header, source))
          self.faces_dest = np.hstack([self.draw_rect(face) for face in self.faces["dst"]])
          logger.debug("source row shape: %s, swapped row shape: %s",
                       self.faces_dest.shape, self.faces_source.shape)
  
      def faces_from_frames(self):
          """ Compile faces from the original images and return a row for each of source and dest """
 
</s> remove                      self.faces_dest.shape, self.faces_source.shape)
 </s> add                      self._faces_dest.shape, self._faces_source.shape) </s> remove         self.faces_from_frames()
 </s> add         self._faces_from_frames() </s> remove     def faces_from_frames(self):
        """ Compile faces from the original images and return a row for each of source and dest """
 </s> add     def _faces_from_frames(self):
        """ Extract the preview faces from the source frames and apply the requisite padding. """ </s> remove     def build_faces_image(self):
        """ Display associated faces """
 </s> add     def _build_faces_image(self):
        """ Compile the source and destination rows of the preview image. """ </s> remove             self.crop_source_faces()
        self.crop_destination_faces()
        logger.debug("Extracted faces from frames: %s", {k: len(v) for k, v in self.faces.items()})

    def crop_source_faces(self):
        """ Update the main faces dict with new source faces and matrices """
 </s> add             self._crop_source_faces()
        self._crop_destination_faces()
        logger.debug("Extracted faces from frames: %s",
                     {k: len(v) for k, v in self._faces.items()})

    def _crop_source_faces(self):
        """ Extract the source faces from the source frames, along with their filenames and the
        transformation matrix used to extract the faces. """
            header = self._header_text()
            source = np.hstack([self._draw_rect(face) for face in self._faces["src"]])
            self._faces_source = np.vstack((header, source))
        self._faces_dest = np.hstack([self._draw_rect(face) for face in self._faces["dst"]])
          logger.trace("Building Faces Image")
          update_all = self.update_source
          self.faces_from_frames()
          if update_all:
            header = self._header_text()
            source = np.hstack([self._draw_rect(face) for face in self._faces["src"]])
            self._faces_source = np.vstack((header, source))
        self._faces_dest = np.hstack([self._draw_rect(face) for face in self._faces["dst"]])
            header = self._header_text()
            source = np.hstack([self._draw_rect(face) for face in self._faces["src"]])
            self._faces_source = np.vstack((header, source))
        self._faces_dest = np.hstack([self._draw_rect(face) for face in self._faces["dst"]])
            header = self._header_text()
            source = np.hstack([self._draw_rect(face) for face in self._faces["src"]])
            self._faces_source = np.vstack((header, source))
        self._faces_dest = np.hstack([self._draw_rect(face) for face in self._faces["dst"]])
            header = self._header_text()
            source = np.hstack([self._draw_rect(face) for face in self._faces["src"]])
            self._faces_source = np.vstack((header, source))
        self._faces_dest = np.hstack([self._draw_rect(face) for face in self._faces["dst"]])
          logger.debug("source row shape: %s, swapped row shape: %s",
                       self.faces_dest.shape, self.faces_source.shape)
  
      def faces_from_frames(self):
          """ Compile faces from the original images and return a row for each of source and dest """
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 
tools/preview.py