def __call__(self, results):
        """Call function to apply test time augment transforms on results.

        Args:
            results (dict): Result dict contains the data to transform.

        Returns:
           dict[str: list]: The augmented data, where each value is wrapped
               into a list.
        """

        aug_data = []
        if self.img_scale is None and mmcv.is_list_of(self.img_ratios, float):
            h, w = results['img'].shape[:2]
            img_scale = [(int(w * ratio), int(h * ratio))
                         for ratio in self.img_ratios]
        else:
            img_scale = self.img_scale
        flip_aug = [False, True] if self.flip else [False]
        for scale in img_scale:
            for flip in flip_aug:
                for direction in self.flip_direction:
                    _results = results.copy()
                    _results['scale'] = scale
                    _results['flip'] = flip
                    _results['flip_direction'] = direction
                    data = self.transforms(_results)
                    aug_data.append(data)
        # list of dict to dict of list
        aug_data_dict = {key: [] for key in aug_data[0]}
        for data in aug_data:
            for key, val in data.items():
                aug_data_dict[key].append(val)
        return aug_data_dict
Call function to apply test time augment transforms on results.

        Args:
            results (dict): Result dict contains the data to transform.

        Returns:
           dict[str: list]: The augmented data, where each value is wrapped
               into a list.
        
ControlNet-v1-1-nightly/annotator/uniformer/mmseg/datasets/pipelines/test_time_aug.py