          """ Return the list of images or video file that is to be processed """
          if self.is_video:
              input_images = self.args.input_dir
          else:
              input_images = get_image_paths(self.args.input_dir)
  
          return input_images
  
      def load(self):
          """ Load an image and yield it with it's filename """
 
</s> remove     def get_input_images(self):
        """ Return the list of images or video file that is to be processed """
        if self.is_video:
            input_images = self.args.input_dir
 </s> add     def _get_input_images(self):
        """ Return the list of images or path to video file that is to be processed.

        Returns
        -------
        str or list
            Path to the video file if the input is a video otherwise list of image paths.
        """
        if self._is_video:
            input_images = self._args.input_dir </s> remove         """ Load an image and yield it with it's filename """
        iterator = self.load_video_frames if self.is_video else self.load_disk_frames
 </s> add         """ Generator to load frames from a folder of images or from a video file.

        Yields
        ------
        filename: str
            The filename of the current frame
        image: :class:`numpy.ndarray`
            A single frame
        """
        iterator = self._load_video_frames if self._is_video else self._load_disk_frames </s> remove             logger.info("Input Directory: %s", self.args.input_dir)
 </s> add             logger.info("Input Directory: %s", self._args.input_dir) </s> remove     def count_images(self):
        """ Number of images or frames """
        if self.is_video:
            retval = int(count_frames(self.args.input_dir, fast=True))
 </s> add     @property
    def is_video(self):
        """bool: ``True`` if the input is a video file otherwise ``False``. """
        return self._is_video

    @property
    def input_images(self):
        """str or list: Path to the video file if the input is a video otherwise list of
        image paths. """
        return self._input_images

    @property
    def images_found(self):
        """int: The number of frames that exist in the video file, or the folder of images. """
        return self._images_found

    def _count_images(self):
        """ Get the number of Frames from a video file or folder of images.

        Returns
        -------
        int
            The number of frames in the image source
        """
        if self._is_video:
            retval = int(count_frames(self._args.input_dir, fast=True)) </s> remove             retval = len(self.input_images)
 </s> add             retval = len(self._input_images)
            input_images = get_image_paths(self._args.input_dir)
          """ Return the list of images or video file that is to be processed """
          if self.is_video:
              input_images = self.args.input_dir
          else:
            input_images = get_image_paths(self._args.input_dir)
  
          return input_images
  
      def load(self):
          """ Load an image and yield it with it's filename """
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