修改unet工程格式

Python/Unet.py

@@ -31,15 +31,8 @@ if __name__ == '__main__':
     model = migraphx.parse_onnx("../Resource/Models/unet_13_256.onnx", map_input_dims=maxInput)
 
     # 获取模型输入/输出节点信息
-    print("inputs:")
     inputs = model.get_inputs()
-    for key,value in inputs.items():
-        print("{}:{}".format(key,value))
-
-    print("outputs:")
     outputs = model.get_outputs()
-    for key,value in outputs.items():
-        print("{}:{}".format(key,value))
 
     # 编译模型
     model.compile(migraphx.get_target("gpu"), device_id=0)   # device_id: 设置GPU设备，默认为0号设备

Src/Unet.cpp

@@ -28,7 +28,7 @@ ErrorCode Unet::Initialize(InitializationParameterOfSegmentation initParamOfSegm
 {
     // 读取配置文件
     std::string configFilePath=initParamOfSegmentationUnet.configFilePath;
-    if(Exists(configFilePath)==false)
+    if(!Exists(configFilePath))
     {
         LOG_ERROR(stdout, "no configuration file!\n");
         return CONFIG_FILE_NOT_EXIST;
@@ -49,7 +49,7 @@ ErrorCode Unet::Initialize(InitializationParameterOfSegmentation initParamOfSegm
     onnx_options.map_input_dims["inputs"]={1,3,256,256};
 
     // 加载模型
-    if(Exists(modelPath)==false)
+    if(!Exists(modelPath))
     {
         LOG_ERROR(stdout,"%s not exist!\n",modelPath.c_str());
         return MODEL_NOT_EXIST;
@@ -58,18 +58,8 @@ ErrorCode Unet::Initialize(InitializationParameterOfSegmentation initParamOfSegm
     LOG_INFO(stdout,"succeed to load model: %s\n",GetFileName(modelPath).c_str());
 
     // 获取模型输入/输出节点信息
-    std::cout<<"inputs:"<<std::endl;
     std::unordered_map<std::string, migraphx::shape> inputs=net.get_inputs();
-    for(auto i:inputs)
-    {
-        std::cout<<i.first<<":"<<i.second<<std::endl;
-    }
-    std::cout<<"outputs:"<<std::endl;
     std::unordered_map<std::string, migraphx::shape> outputs=net.get_outputs();
-    for(auto i:outputs)
-    {
-        std::cout<<i.first<<":"<<i.second<<std::endl;
-    }
     inputName=inputs.begin()->first;
     inputShape=inputs.begin()->second;
     int N=inputShape.lens()[0];

Src/main.cpp

@@ -24,11 +24,7 @@ int main()
    
     // 推理
     cv::Mat maskImage;   
-    double time1 = cv::getTickCount();
     unet.Segmentation(srcImage, maskImage);
-    double time2 = cv::getTickCount();
-    double elapsedTime = (time2 - time1) * 1000 / cv::getTickFrequency();
-    LOG_INFO(stdout, "inference time:%f ms\n", elapsedTime);
     LOG_INFO(stdout,"========== Segmentation Results ==========\n");
     LOG_INFO(stdout,"Segmentation results have been saved to ./Result.jpg\n");
     cv::imwrite("./Result.jpg", maskImage);