      def get_indices(self):
          """ Returns a list of 'self.sample_size' evenly sized partition indices
              pertaining to the filtered file list """
          # Remove start and end values to get a list divisible by self.sample_size
          no_files = len(self.filelist)
          crop = no_files % self.sample_size
          top_tail = list(range(no_files))[
              crop // 2:no_files - (crop - (crop // 2))]
          # Partition the indices
          size = len(top_tail)
          retval = [top_tail[start:start + size // self.sample_size]
 
</s> remove     def get_indices(self):
        """ Returns a list of 'self.sample_size' evenly sized partition indices
            pertaining to the filtered file list """
 </s> add     def _get_indices(self):
        """ Get indices for each sample group.

        Obtain :attr:`self.sample_size` evenly sized groups of indices
        pertaining to the filtered :attr:`self._file_list`

        Returns
        -------
        list
            list of indices relating to the filtered file list, split into groups
        """ </s> remove         retval = [top_tail[start:start + size // self.sample_size]
                  for start in range(0, size, size // self.sample_size)]
 </s> add         retval = [top_tail[start:start + size // self._sample_size]
                  for start in range(0, size, size // self._sample_size)] </s> remove     def get_filelist(self):
        """ Return a list of files, filtering out those frames which do not contain faces """
 </s> add     def _get_filelist(self):
        """ Get a list of files for the input, filtering out those frames which do
        not contain faces.

        Returns
        -------
        list
            A list of filenames of frames that contain faces.
        """ </s> remove     def header_text(self):
        """ Create header text for output image """
        font_scale = self.size / 640
        height = self.size // 8
 </s> add     def _header_text(self):
        """ Create the header text displaying the frame name for each preview column.

        Returns
        -------
        :class:`numpy.ndarray`
            The header row of the preview image containing the frame names for each column
        """
        font_scale = self._size / 640
        height = self._size // 8 </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
        no_files = len(self._filelist)
        crop = no_files % self._sample_size
      def get_indices(self):
          """ Returns a list of 'self.sample_size' evenly sized partition indices
              pertaining to the filtered file list """
          # Remove start and end values to get a list divisible by self.sample_size
        no_files = len(self._filelist)
        crop = no_files % self._sample_size
        no_files = len(self._filelist)
        crop = no_files % self._sample_size
          top_tail = list(range(no_files))[
              crop // 2:no_files - (crop - (crop // 2))]
          # Partition the indices
          size = len(top_tail)
          retval = [top_tail[start:start + size // self.sample_size]
keep keep keep keep 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