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| # Copyright (c) OpenMMLab. All rights reserved. | |
| from typing import Optional, Union | |
| import torch | |
| from mmengine.config import ConfigDict | |
| from mmengine.structures import InstanceData | |
| from mmdet.registry import TASK_UTILS | |
| from .assign_result import AssignResult | |
| from .max_iou_assigner import MaxIoUAssigner | |
| class ApproxMaxIoUAssigner(MaxIoUAssigner): | |
| """Assign a corresponding gt bbox or background to each bbox. | |
| Each proposals will be assigned with an integer indicating the ground truth | |
| index. (semi-positive index: gt label (0-based), -1: background) | |
| - -1: negative sample, no assigned gt | |
| - semi-positive integer: positive sample, index (0-based) of assigned gt | |
| Args: | |
| pos_iou_thr (float): IoU threshold for positive bboxes. | |
| neg_iou_thr (float or tuple): IoU threshold for negative bboxes. | |
| min_pos_iou (float): Minimum iou for a bbox to be considered as a | |
| positive bbox. Positive samples can have smaller IoU than | |
| pos_iou_thr due to the 4th step (assign max IoU sample to each gt). | |
| gt_max_assign_all (bool): Whether to assign all bboxes with the same | |
| highest overlap with some gt to that gt. | |
| ignore_iof_thr (float): IoF threshold for ignoring bboxes (if | |
| `gt_bboxes_ignore` is specified). Negative values mean not | |
| ignoring any bboxes. | |
| ignore_wrt_candidates (bool): Whether to compute the iof between | |
| `bboxes` and `gt_bboxes_ignore`, or the contrary. | |
| match_low_quality (bool): Whether to allow quality matches. This is | |
| usually allowed for RPN and single stage detectors, but not allowed | |
| in the second stage. | |
| gpu_assign_thr (int): The upper bound of the number of GT for GPU | |
| assign. When the number of gt is above this threshold, will assign | |
| on CPU device. Negative values mean not assign on CPU. | |
| iou_calculator (:obj:`ConfigDict` or dict): Config of overlaps | |
| Calculator. | |
| """ | |
| def __init__( | |
| self, | |
| pos_iou_thr: float, | |
| neg_iou_thr: Union[float, tuple], | |
| min_pos_iou: float = .0, | |
| gt_max_assign_all: bool = True, | |
| ignore_iof_thr: float = -1, | |
| ignore_wrt_candidates: bool = True, | |
| match_low_quality: bool = True, | |
| gpu_assign_thr: int = -1, | |
| iou_calculator: Union[ConfigDict, dict] = dict(type='BboxOverlaps2D') | |
| ) -> None: | |
| self.pos_iou_thr = pos_iou_thr | |
| self.neg_iou_thr = neg_iou_thr | |
| self.min_pos_iou = min_pos_iou | |
| self.gt_max_assign_all = gt_max_assign_all | |
| self.ignore_iof_thr = ignore_iof_thr | |
| self.ignore_wrt_candidates = ignore_wrt_candidates | |
| self.gpu_assign_thr = gpu_assign_thr | |
| self.match_low_quality = match_low_quality | |
| self.iou_calculator = TASK_UTILS.build(iou_calculator) | |
| def assign(self, | |
| pred_instances: InstanceData, | |
| gt_instances: InstanceData, | |
| gt_instances_ignore: Optional[InstanceData] = None, | |
| **kwargs) -> AssignResult: | |
| """Assign gt to approxs. | |
| This method assign a gt bbox to each group of approxs (bboxes), | |
| each group of approxs is represent by a base approx (bbox) and | |
| will be assigned with -1, or a semi-positive number. | |
| background_label (-1) means negative sample, | |
| semi-positive number is the index (0-based) of assigned gt. | |
| The assignment is done in following steps, the order matters. | |
| 1. assign every bbox to background_label (-1) | |
| 2. use the max IoU of each group of approxs to assign | |
| 2. assign proposals whose iou with all gts < neg_iou_thr to background | |
| 3. for each bbox, if the iou with its nearest gt >= pos_iou_thr, | |
| assign it to that bbox | |
| 4. for each gt bbox, assign its nearest proposals (may be more than | |
| one) to itself | |
| Args: | |
| pred_instances (:obj:`InstanceData`): Instances of model | |
| predictions. It includes ``priors``, and the priors can | |
| be anchors or points, or the bboxes predicted by the | |
| previous stage, has shape (n, 4). ``approxs`` means the | |
| group of approxs aligned with ``priors``, has shape | |
| (n, num_approxs, 4). | |
| gt_instances (:obj:`InstanceData`): Ground truth of instance | |
| annotations. It usually includes ``bboxes``, with shape (k, 4), | |
| and ``labels``, with shape (k, ). | |
| gt_instances_ignore (:obj:`InstanceData`, optional): Instances | |
| to be ignored during training. It includes ``bboxes`` | |
| attribute data that is ignored during training and testing. | |
| Defaults to None. | |
| Returns: | |
| :obj:`AssignResult`: The assign result. | |
| """ | |
| squares = pred_instances.priors | |
| approxs = pred_instances.approxs | |
| gt_bboxes = gt_instances.bboxes | |
| gt_labels = gt_instances.labels | |
| gt_bboxes_ignore = None if gt_instances_ignore is None else \ | |
| gt_instances_ignore.get('bboxes', None) | |
| approxs_per_octave = approxs.size(1) | |
| num_squares = squares.size(0) | |
| num_gts = gt_bboxes.size(0) | |
| if num_squares == 0 or num_gts == 0: | |
| # No predictions and/or truth, return empty assignment | |
| overlaps = approxs.new(num_gts, num_squares) | |
| assign_result = self.assign_wrt_overlaps(overlaps, gt_labels) | |
| return assign_result | |
| # re-organize anchors by approxs_per_octave x num_squares | |
| approxs = torch.transpose(approxs, 0, 1).contiguous().view(-1, 4) | |
| assign_on_cpu = True if (self.gpu_assign_thr > 0) and ( | |
| num_gts > self.gpu_assign_thr) else False | |
| # compute overlap and assign gt on CPU when number of GT is large | |
| if assign_on_cpu: | |
| device = approxs.device | |
| approxs = approxs.cpu() | |
| gt_bboxes = gt_bboxes.cpu() | |
| if gt_bboxes_ignore is not None: | |
| gt_bboxes_ignore = gt_bboxes_ignore.cpu() | |
| if gt_labels is not None: | |
| gt_labels = gt_labels.cpu() | |
| all_overlaps = self.iou_calculator(approxs, gt_bboxes) | |
| overlaps, _ = all_overlaps.view(approxs_per_octave, num_squares, | |
| num_gts).max(dim=0) | |
| overlaps = torch.transpose(overlaps, 0, 1) | |
| if (self.ignore_iof_thr > 0 and gt_bboxes_ignore is not None | |
| and gt_bboxes_ignore.numel() > 0 and squares.numel() > 0): | |
| if self.ignore_wrt_candidates: | |
| ignore_overlaps = self.iou_calculator( | |
| squares, gt_bboxes_ignore, mode='iof') | |
| ignore_max_overlaps, _ = ignore_overlaps.max(dim=1) | |
| else: | |
| ignore_overlaps = self.iou_calculator( | |
| gt_bboxes_ignore, squares, mode='iof') | |
| ignore_max_overlaps, _ = ignore_overlaps.max(dim=0) | |
| overlaps[:, ignore_max_overlaps > self.ignore_iof_thr] = -1 | |
| assign_result = self.assign_wrt_overlaps(overlaps, gt_labels) | |
| if assign_on_cpu: | |
| assign_result.gt_inds = assign_result.gt_inds.to(device) | |
| assign_result.max_overlaps = assign_result.max_overlaps.to(device) | |
| if assign_result.labels is not None: | |
| assign_result.labels = assign_result.labels.to(device) | |
| return assign_result | |