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