|
- # Copyright (c) OpenMMLab. All rights reserved.
- import torch
-
- from mmdet.core import build_assigner, build_sampler
-
-
- def _dummy_bbox_sampling(proposal_list, gt_bboxes, gt_labels):
- """Create sample results that can be passed to BBoxHead.get_targets."""
- num_imgs = 1
- feat = torch.rand(1, 1, 3, 3)
- assign_config = dict(
- type='MaxIoUAssigner',
- pos_iou_thr=0.5,
- neg_iou_thr=0.5,
- min_pos_iou=0.5,
- ignore_iof_thr=-1)
- sampler_config = dict(
- type='RandomSampler',
- num=512,
- pos_fraction=0.25,
- neg_pos_ub=-1,
- add_gt_as_proposals=True)
- bbox_assigner = build_assigner(assign_config)
- bbox_sampler = build_sampler(sampler_config)
- gt_bboxes_ignore = [None for _ in range(num_imgs)]
- sampling_results = []
- for i in range(num_imgs):
- assign_result = bbox_assigner.assign(proposal_list[i], gt_bboxes[i],
- gt_bboxes_ignore[i], gt_labels[i])
- sampling_result = bbox_sampler.sample(
- assign_result,
- proposal_list[i],
- gt_bboxes[i],
- gt_labels[i],
- feats=feat)
- sampling_results.append(sampling_result)
-
- return sampling_results
|
