文章目录
- 代码流程
- 训练中期融合模型fusion_pretrain.py
- 提取特征中期融合并决策main.py
代码流程
预处理preprocessing.py
训练中期融合模型fusion_pretrain,py
提取特征中期融合并决策main.py
训练中期融合模型fusion_pretrain.py
fusion_pretrain,py
调用engine_fusion_pretrain.py中的train_one_epoch
for data_iter_step,(samples,-) in enumerate (...)xyz_samples=samples[:,:,:,1152].to(device,...)rgb_samples=samples[:,:,1152,:].to(device,...)scores=...loss.value=loss.item()loss_scaler(...)
提取特征中期融合并决策main.py
features.py中的
class Features(torch.nn.module)...def __init__...self.deep_feature_extractor=Model(device=,rgb_backbonename=,xyz_b...,group_size=,num_group...)self.fusion=FeatureFusionBlock(1152,768,...)self.detect_fuser=linear_model.SGDOneClassSVM(...)def intepolate_point(self,rgb,xyz)...return xyz_feature_maps,center,xyzdef compute_s_s_mapdef calculate_metrics(self):......roc_auc_score(self.image_labels,self.image_preds)...calculate_au_pro(self.gts,self.predic)
m3dm.runner.py中的
def fit (self.class_name):for sample,_ in tqdm(train_loader,desc=f'extracting...')method.add_sample_to_mem_bank(sample)...method.run_late_fusion()
...with torch.no_grad():for sample,mask,label,rgb_patch in tqdm(test_loader,desc=f'extracting...')for method in self.methods.values():method.predict(sample,mask,label)...
)
)
)