def test_bottomup_evaluate(self):
        """test bottomup-style COCO metric evaluation."""
        # case1: score_mode='bbox', nms_mode='none'
        metric = KeypointPartitionMetric(
            metric=dict(
                type='CocoMetric',
                outfile_prefix=f'{self.tmp_dir.name}/test_bottomup',
                score_mode='bbox',
                nms_mode='none'),
            partitions=dict(
                body=range(17),
                foot=range(17, 23),
                face=range(23, 91),
                left_hand=range(91, 112),
                right_hand=range(112, 133),
                all=range(133)))
        metric.dataset_meta = self.dataset_meta_coco

        # process samples
        for data_batch, data_samples in self.bottomup_data_coco:
            metric.process(data_batch, data_samples)

        eval_results = metric.evaluate(size=len(self.bottomup_data_coco))
        for key in self.target_bbox_none.keys():
            self.assertAlmostEqual(
                eval_results[key], self.target_bbox_none[key], places=3)
        self._assert_outfiles('test_bottomup')
test bottomup-style COCO metric evaluation.
mmpose/tests/test_evaluation/test_metrics/test_keypoint_partition_metric.py