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Python core.build_assigner方法代码示例

本文整理汇总了Python中mmdet.core.build_assigner方法的典型用法代码示例。如果您正苦于以下问题:Python core.build_assigner方法的具体用法?Python core.build_assigner怎么用?Python core.build_assigner使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在mmdet.core的用法示例。


在下文中一共展示了core.build_assigner方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: init_assigner_sampler

# 需要导入模块: from mmdet import core [as 别名]
# 或者: from mmdet.core import build_assigner [as 别名]
def init_assigner_sampler(self):
        """Initialize assigner and sampler."""
        self.bbox_assigner = None
        self.bbox_sampler = None
        if self.train_cfg:
            self.bbox_assigner = build_assigner(self.train_cfg.assigner)
            self.bbox_sampler = build_sampler(
                self.train_cfg.sampler, context=self) 
开发者ID:open-mmlab,项目名称:mmdetection,代码行数:10,代码来源:standard_roi_head.py

示例2: _dummy_bbox_sampling

# 需要导入模块: from mmdet import core [as 别名]
# 或者: from mmdet.core import build_assigner [as 别名]
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 
开发者ID:open-mmlab,项目名称:mmdetection,代码行数:34,代码来源:test_heads.py

示例3: forward_train

# 需要导入模块: from mmdet import core [as 别名]
# 或者: from mmdet.core import build_assigner [as 别名]
def forward_train(self,
                      img,
                      img_metas,
                      gt_bboxes,
                      gt_labels,
                      gt_bboxes_ignore=None):
        if self.use_consistent_supervision:
            x, y = self.extract_feat(img)
            gt_bboxes_auxiliary = [gt.clone() for gt in gt_bboxes]
            gt_labels_auxiliary = [label.clone() for label in gt_labels]
        else:
            x = self.extract_feat(img)
        outs = self.bbox_head(x)
        loss_inputs = outs + (gt_bboxes, gt_labels, img_metas, self.train_cfg)

        losses = self.bbox_head.loss(
            *loss_inputs, gt_bboxes_ignore=gt_bboxes_ignore)
        if self.use_consistent_supervision:
            proposal_cfg = self.train_cfg.auxiliary.proposal
            proposal_inputs = outs + (img_metas, proposal_cfg)
            proposal_list = self.bbox_head.get_bboxes_auxiliary(*proposal_inputs)
        
            bbox_assigner = build_assigner(self.train_cfg.auxiliary.assigner)
            bbox_sampler = build_sampler(
                self.train_cfg.auxiliary.sampler, context=self)
            num_imgs = img.size(0)
            if gt_bboxes_ignore is None:
                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_auxiliary[i], gt_bboxes_ignore[i],
                    gt_labels_auxiliary[i])
                sampling_result = bbox_sampler.sample(
                    assign_result,
                    proposal_list[i],
                    gt_bboxes_auxiliary[i],
                    gt_labels_auxiliary[i],
                    feats=[lvl_feat[i][None] for lvl_feat in x])
                sampling_results.append(sampling_result)
            rois = bbox2roi([res.bboxes for res in sampling_results])
            bbox_feats_raw = self.auxiliary_bbox_roi_extractor(y[:self.auxiliary_bbox_roi_extractor.num_inputs], rois)
            cls_score_auxiliary, bbox_pred_auxiliary = self.auxiliary_bbox_head(bbox_feats_raw)

            bbox_targets = self.auxiliary_bbox_head.get_target(
                sampling_results, gt_bboxes, gt_labels, self.train_cfg.auxiliary.rcnn)
        
            loss_bbox_auxiliary = self.auxiliary_bbox_head.loss(cls_score_auxiliary, bbox_pred_auxiliary,
                                            *bbox_targets, alpha=0.25, num_level=3)   
            losses.update(loss_bbox_auxiliary) 

        return losses 
开发者ID:Gus-Guo,项目名称:AugFPN,代码行数:55,代码来源:single_stage.py


注:本文中的mmdet.core.build_assigner方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。