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| # Copyright (c) OpenMMLab. All rights reserved. | |
| from typing import Optional, Sequence, Union | |
| from torch import Tensor | |
| from mmdet.registry import TASK_UTILS | |
| from mmdet.structures.bbox import (BaseBoxes, HorizontalBoxes, bbox2distance, | |
| distance2bbox, get_box_tensor) | |
| from .base_bbox_coder import BaseBBoxCoder | |
| class DistancePointBBoxCoder(BaseBBoxCoder): | |
| """Distance Point BBox coder. | |
| This coder encodes gt bboxes (x1, y1, x2, y2) into (top, bottom, left, | |
| right) and decode it back to the original. | |
| Args: | |
| clip_border (bool, optional): Whether clip the objects outside the | |
| border of the image. Defaults to True. | |
| """ | |
| def __init__(self, clip_border: Optional[bool] = True, **kwargs) -> None: | |
| super().__init__(**kwargs) | |
| self.clip_border = clip_border | |
| def encode(self, | |
| points: Tensor, | |
| gt_bboxes: Union[Tensor, BaseBoxes], | |
| max_dis: Optional[float] = None, | |
| eps: float = 0.1) -> Tensor: | |
| """Encode bounding box to distances. | |
| Args: | |
| points (Tensor): Shape (N, 2), The format is [x, y]. | |
| gt_bboxes (Tensor or :obj:`BaseBoxes`): Shape (N, 4), The format | |
| is "xyxy" | |
| max_dis (float): Upper bound of the distance. Default None. | |
| eps (float): a small value to ensure target < max_dis, instead <=. | |
| Default 0.1. | |
| Returns: | |
| Tensor: Box transformation deltas. The shape is (N, 4). | |
| """ | |
| gt_bboxes = get_box_tensor(gt_bboxes) | |
| assert points.size(0) == gt_bboxes.size(0) | |
| assert points.size(-1) == 2 | |
| assert gt_bboxes.size(-1) == 4 | |
| return bbox2distance(points, gt_bboxes, max_dis, eps) | |
| def decode( | |
| self, | |
| points: Tensor, | |
| pred_bboxes: Tensor, | |
| max_shape: Optional[Union[Sequence[int], Tensor, | |
| Sequence[Sequence[int]]]] = None | |
| ) -> Union[Tensor, BaseBoxes]: | |
| """Decode distance prediction to bounding box. | |
| Args: | |
| points (Tensor): Shape (B, N, 2) or (N, 2). | |
| pred_bboxes (Tensor): Distance from the given point to 4 | |
| boundaries (left, top, right, bottom). Shape (B, N, 4) | |
| or (N, 4) | |
| max_shape (Sequence[int] or torch.Tensor or Sequence[ | |
| Sequence[int]],optional): Maximum bounds for boxes, specifies | |
| (H, W, C) or (H, W). If priors shape is (B, N, 4), then | |
| the max_shape should be a Sequence[Sequence[int]], | |
| and the length of max_shape should also be B. | |
| Default None. | |
| Returns: | |
| Union[Tensor, :obj:`BaseBoxes`]: Boxes with shape (N, 4) or | |
| (B, N, 4) | |
| """ | |
| assert points.size(0) == pred_bboxes.size(0) | |
| assert points.size(-1) == 2 | |
| assert pred_bboxes.size(-1) == 4 | |
| if self.clip_border is False: | |
| max_shape = None | |
| bboxes = distance2bbox(points, pred_bboxes, max_shape) | |
| if self.use_box_type: | |
| bboxes = HorizontalBoxes(bboxes) | |
| return bboxes | |