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This is the official implementation by the author for the paper "Dual-Branch Feature-Perception Architecture for Driver Emotion Recognition via Facial Expressions"

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driver_experssion

image

解压后:

fusion文件内的self_fusion是特征融合模块Cross CATA的代码,

main文件夹内是各种模型启动训练+推理测试的脚本代码

MobileNetV4-pytorch-main是LFP分支的代码

model是自己改的模块的代码,其中SCA和SHSA是SCSA块的diamond,Wavelet是小波变换块的代码(加在LFP的层3和4里面)

SHVIT-main是GFP代码

tools里主要是训练+验证+测试的脚本

image

接口说明: image

通过main文件夹中代码的data_path参数可以修改数据集路径,同时修改Trainer类的num_classes和class_names即可

**数据集格式:**标准分类数据格式 data根目录:

 train
   
 class1
   
 class2
   
 class3
   
 .......

val

 class1
   
 class2
   
 class3
   
 .......

test

 class1
   
 class2
   
 class3
   
 .......

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This is the official implementation by the author for the paper "Dual-Branch Feature-Perception Architecture for Driver Emotion Recognition via Facial Expressions"

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