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# 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
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