AI代码解释 #===mmdet/models/detectors/voxelnet.py/VoxelNet===defforward_train(self,points,img_metas,gt_bboxes_3d,gt_labels_3d,gt_bboxes_ignore=None):# 先进行点云的特征提取 x=self.extract_feat(points,img_metas)# 主要是调用 bbox_head 内部的 forward_train 方法,得到 head 输出 outs=self...
1]+gt_bboxes[:,3])*0.5).to(device)# 将gt的中心位置映射到特征图尺寸gt_bboxes_grid_x=torch.floor(gt_bboxes_cx/stride[0]).long()gt_bboxes_grid_y=torch.floor(gt_bboxes_cy/stride[1]).long()# 将w和h方向拉
losses=self.bbox_head.forward_train(x,img_metas,gt_bboxes,gt_labels,gt_bboxes_ignore)returnlosses defsimple_test(---):# 先运行backbone+neck进行特征提取 x=self.extract_feat(img)# head输出预测特征图 outs=self.bbox_head(x)# bbox解码和还原 bbox_list=self.bbox_head.get_bboxes(*outs...
dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'proposals', 'gt_bboxes', 'gt_labels']) ] test_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadProposals', num_max_proposals=None), dict( type='MultiScaleFlipAug', img_scale=(1333, 800), flip=Fal...
gt_bboxes_ignore[i], gt_labels[i]) sampling_result = bbox_sampler.sample( # sample函数 assign_result, proposal_list[i], gt_bboxes[i], gt_labels[i], feats=[lvl_feat[i][None] for lvl_feat in x]) sampling_results.append(sampling_result) ...
bbox_pred= self.fc_reg(x)ifself.with_regelseNonereturncls_score, bbox_preddef_get_target_single(self, pos_bboxes, neg_bboxes, pos_gt_bboxes, pos_gt_labels, cfg): num_pos=pos_bboxes.size(0) num_neg=neg_bboxes.size(0) ...
# 主要是调用 bbox_head 内部的 forward_train 方法,得到 head 输出outs = self.bbox_head(x)loss_inputs = outs + (gt_bboxes_3d, gt_labels_3d, img_metas)# 将 head 部分的输出和数据的 label 送入计算 losslosses = self.bbox_head.loss(*loss_inputs, gt_bboxes_ignore=gt_bboxes_...
增加:gt_bboxes, gt_bboxes_ignore, gt_labels, gt_masks, gt_semantic_seg, bbox_fields, mask_fields LoadProposals 增加:proposals 2.预处理 Resize 增加:flip 更新:img, *bbox_fields, *mask_fields, *seg_fields Pad 增加:pad_fixed_size, pad_size_divisor ...
2. 调整DenseHead结构: DenseHead的核心作用:在MMDetection中,DenseHead是单阶段模型的核心,包含抽象方法loss和get_bboxes。 接口调整:为了适应两阶段模型,DenseHead需要支持gt_labels=None和proposal_cfg。这意味着需要调整DenseHead的接口,使其能够处理没有真实标签的情况,并接受预选框配置。3. ...
LoadImageFromFile添加: img, img_shape, ori_shapeLoadAnnotations添加: gt_bboxes, gt_bboxes_ignore, gt_labels, gt_masks, gt_semantic_seg, bbox_fields, mask_fieldsLoadProposals添加: proposals预处理 Resize添加: scale, scale_idx, pad_shape, scale_factor, keep_ratio更新: img, img_shape, *b...