def _evaluate_cityscapes()

in modified_mmseg/datasets/cityscapes.py [0:0]
32 lines of code
6 McCabe index (conditional complexity)

    def _evaluate_cityscapes(self, results, logger, imgfile_prefix):
        """Evaluation in Cityscapes protocol.
        Args:
            results (list): Testing results of the dataset.
            logger (logging.Logger | str | None): Logger used for printing
                related information during evaluation. Default: None.
            imgfile_prefix (str | None): The prefix of output image file
        Returns:
            dict[str: float]: Cityscapes evaluation results.
        """
        try:
            import cityscapesscripts.evaluation.evalPixelLevelSemanticLabeling as CSEval  # noqa
        except ImportError:
            raise ImportError('Please run "pip install cityscapesscripts" to '
                              'install cityscapesscripts first.')
        msg = 'Evaluating in Cityscapes style'
        if logger is None:
            msg = '\n' + msg
        print_log(msg, logger=logger)

        result_files, tmp_dir = self.format_results(results, imgfile_prefix)

        if tmp_dir is None:
            result_dir = imgfile_prefix
        else:
            result_dir = tmp_dir.name

        eval_results = dict()
        print_log(f'Evaluating results under {result_dir} ...', logger=logger)

        CSEval.args.evalInstLevelScore = True
        CSEval.args.predictionPath = osp.abspath(result_dir)
        CSEval.args.evalPixelAccuracy = True
        CSEval.args.JSONOutput = False

        seg_map_list = []
        pred_list = []

        # when evaluating with official cityscapesscripts,
        # **_gtFine_labelIds.png is used
        for seg_map in mmcv.scandir(
                self.ann_dir, 'gtFine_labelIds.png', recursive=True):
            seg_map_list.append(osp.join(self.ann_dir, seg_map))
            pred_list.append(CSEval.getPrediction(CSEval.args, seg_map))

        eval_results.update(
            CSEval.evaluateImgLists(pred_list, seg_map_list, CSEval.args))

        if tmp_dir is not None:
            tmp_dir.cleanup()

        return eval_results