  import operator
  from argparse import Namespace
  from concurrent import futures
  from shutil import copyfile
  
  import numpy as np
  import cv2
  from tqdm import tqdm
  
  # faceswap imports
 
</s> remove logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
 </s> add logger = logging.getLogger(__name__) </s> remove "L|'color-gray': Sort images by the average intensity of the converted grayscale color channel.\n"
"L|'color-luma': Sort images by the average intensity of the converted Y color channel. Bright lighting and oversaturated images will be ranked first.\n"
"L|'color-green': Sort images by the average intensity of the converted Cg color channel. Green images will be ranked first and red images will be last.\n"
"L|'color-orange': Sort images by the average intensity of the converted Co color channel. Orange images will be ranked first and blue images will be last.\n"
"L|'size': Sort images by their size in the original frame. Faces closer to the camera and from higher resolution sources will be sorted first, whilst faces further from the camera and from lower resolution sources will be sorted last.\n"
"L|'black-pixels': Sort images by their number of black pixels. Useful when faces are near borders and a large part of the image is black.\n"
 </s> add "L|'color-gray': Sort images by the average intensity of the converted "
"grayscale color channel.\n"
"L|'color-luma': Sort images by the average intensity of the converted Y "
"color channel. Bright lighting and oversaturated images will be ranked "
"first.\n"
"L|'color-green': Sort images by the average intensity of the converted Cg "
"color channel. Green images will be ranked first and red images will be "
"last.\n"
"L|'color-orange': Sort images by the average intensity of the converted Co "
"color channel. Orange images will be ranked first and blue images will be "
"last.\n"
"L|'size': Sort images by their size in the original frame. Faces closer to "
"the camera and from higher resolution sources will be sorted first, whilst "
"faces further from the camera and from lower resolution sources will be "
"sorted last.\n"
"L|'black-pixels': Sort images by their number of black pixels. Useful when "
"faces are near borders and a large part of the image is black.\n" </s> remove             alignments = metadata["alignments"]
 </s> add             alignments = metadata["itxt"]["alignments"] </s> remove class Sort():
 </s> add class Sort():  # pylint:disable=too-few-public-methods
    """ Sorts folders of faces based on input criteria

    Wrapper for the sort process to run in either batch mode or single use mode

    Parameters
    ----------
    arguments: :class:`argparse.Namespace`
        The arguments to be passed to the extraction process as generated from Faceswap's command
        line arguments
    """
    def __init__(self, arguments: Namespace) -> None:
        self._args = arguments
        self._input_locations = self._get_input_locations()

    def _get_input_locations(self) -> List[str]:
        """ Obtain the full path to input locations. Will be a list of locations if batch mode is
        selected, or a containing a single location if batch mode is not selected.

        Returns
        -------
        list:
            The list of input location paths
        """
        if not self._args.batch_mode:
            return [self._args.input_dir]

        retval = [os.path.join(self._args.input_dir, fname)
                  for fname in os.listdir(self._args.input_dir)
                  if os.path.isdir(os.path.join(self._args.input_dir, fname))]
        logger.info("Input locations: %s", retval)
        return retval

    def _output_for_input(self, input_location: str) -> str:
        """ Obtain the path to an output folder for faces for a given input location.

        If not running in batch mode, then the user supplied output location will be returned,
        otherwise a sub-folder within the user supplied output location will be returned based on
        the input filename

        Parameters
        ----------
        input_location: str
            The full path to an input video or folder of images
        """
        if not self._args.batch_mode or self._args.output_dir is None:
            return self._args.output_dir

        retval = os.path.join(self._args.output_dir, os.path.basename(input_location))
        logger.info("Returning output: '%s' for input: '%s'", retval, input_location)
        return retval

    def process(self) -> None:
        """ The entry point for triggering the Sort Process.

        Should only be called from  :class:`lib.cli.launcher.ScriptExecutor`
        """
        logger.info('Starting, this may take a while...')
        inputs = self._input_locations
        if self._args.batch_mode:
            logger.info("Batch mode selected processing: %s", self._input_locations)
        for job_no, location in enumerate(self._input_locations):
            if self._args.batch_mode:
                logger.info("Processing job %s of %s: '%s'", job_no + 1, len(inputs), location)
                arguments = Namespace(**self._args.__dict__)
                arguments.input_dir = location
                arguments.output_dir = self._output_for_input(location)
            else:
                arguments = self._args
            sort = _Sort(arguments)
            sort.process()


class _Sort():
from typing import List
  import operator
  from argparse import Namespace
  from concurrent import futures
  from shutil import copyfile
from typing import List
  
  import numpy as np
  import cv2
  from tqdm import tqdm
  
  # faceswap imports
keep keep keep add keep keep keep keep keep keep
 Sort - Add Batch Mode. Speed up yaw sort 
tools/sort/sort.py