import mmcv import warnings from copy import deepcopy from mmdet.datasets.builder import PIPELINES from mmdet.datasets.pipelines import Compose @PIPELINES.register_module() class MultiScaleFlipAug3D(object): """Test-time augmentation with multiple scales and flipping. Args: transforms (list[dict]): Transforms to apply in each augmentation. img_scale (tuple | list[tuple]: Images scales for resizing. pts_scale_ratio (float | list[float]): Points scale ratios for resizing. flip (bool): Whether apply flip augmentation. Default: False. flip_direction (str | list[str]): Flip augmentation directions for images, options are "horizontal" and "vertical". If flip_direction is list, multiple flip augmentations will be applied. It has no effect when flip == False. Default: "horizontal". pcd_horizontal_flip (bool): Whether apply horizontal flip augmentation to point cloud. Default: True. Note that it works only when 'flip' is turned on. pcd_vertical_flip (bool): Whether apply vertical flip augmentation to point cloud. Default: True. Note that it works only when 'flip' is turned on. """ def __init__(self, transforms, img_scale, pts_scale_ratio, flip=False, flip_direction='horizontal', pcd_horizontal_flip=False, pcd_vertical_flip=False): self.transforms = Compose(transforms) self.img_scale = img_scale if isinstance(img_scale, list) else [img_scale] self.pts_scale_ratio = pts_scale_ratio \ if isinstance(pts_scale_ratio, list) else[float(pts_scale_ratio)] assert mmcv.is_list_of(self.img_scale, tuple) assert mmcv.is_list_of(self.pts_scale_ratio, float) self.flip = flip self.pcd_horizontal_flip = pcd_horizontal_flip self.pcd_vertical_flip = pcd_vertical_flip self.flip_direction = flip_direction if isinstance( flip_direction, list) else [flip_direction] assert mmcv.is_list_of(self.flip_direction, str) if not self.flip and self.flip_direction != ['horizontal']: warnings.warn( 'flip_direction has no effect when flip is set to False') if (self.flip and not any([(t['type'] == 'RandomFlip3D' or t['type'] == 'RandomFlip') for t in transforms])): warnings.warn( 'flip has no effect when RandomFlip is not in transforms') def __call__(self, results): aug_data = [] flip_aug = [False, True] if self.flip else [False] pcd_horizontal_flip_aug = [False, True] \ if self.flip and self.pcd_horizontal_flip else [False] pcd_vertical_flip_aug = [False, True] \ if self.flip and self.pcd_vertical_flip else [False] for scale in self.img_scale: for pts_scale_ratio in self.pts_scale_ratio: for flip in flip_aug: for pcd_horizontal_flip in pcd_horizontal_flip_aug: for pcd_vertical_flip in pcd_vertical_flip_aug: for direction in self.flip_direction: # results.copy will cause bug # since it is shallow copy _results = deepcopy(results) _results['scale'] = scale _results['flip'] = flip _results['pcd_scale_factor'] = \ pts_scale_ratio _results['flip_direction'] = direction _results['pcd_horizontal_flip'] = \ pcd_horizontal_flip _results['pcd_vertical_flip'] = \ pcd_vertical_flip 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 def __repr__(self): repr_str = self.__class__.__name__ repr_str += f'(transforms={self.transforms}, ' repr_str += f'img_scale={self.img_scale}, flip={self.flip}, ' repr_str += f'pts_scale_ratio={self.pts_scale_raio}, ' repr_str += f'flip_direction={self.flip_direction})' return repr_str