Измерение времени выполнения функции, выполняющейся в while l oop в C ++ (windows)

Question

всем, у меня есть проект на платформе windows, и я хочу измерить время выполнения нескольких функций через некоторое время l oop (рисунок 3), поэтому я создаю класс (называемый Benchmark, рисунок 1 заголовок и рисунок 2 - это исходный код), которые делают это, однако он выполняет время на каждом шаге (рис. 4), но я хочу знать, сколько времени программа тратит полностью на каждую функцию. Любая идея, пожалуйста.

// Benchmrak.cpp
#define time Now() std::chrono::high_resolution_clock::now();
#define duration(a) std::chrono::duration_cast<std::chrono::nanoseconds (a).count();
Benchmark:: Benchmark(std::string caller, bool start_running=false ) :_caller(caller), _elapsed(0), _running(false),average (0),count(0)
{
if (start_running ) start(); 
}

//-------------------------------------------------------
Benchmark:: ~Benchmark()
{
  stop();
 //average_time();
  disp ();

}

//-------------------------------------------------------

void Benchmark:: start() 
{
 if (!_running) //=if (runing==false)
 {
     _start_time=timeNow();
     _running = true;
 }
}

//-------------------------------------------------------
void Benchmark:: stop() 
{

 if (_running ) 
 {
     stop_time=timeNow(); 
     _elapsed= duration(stop_time - _start_time);
     average =_elapsed;
     _running = false;
       count   ;
 }
}
void Benchmark:: disp() 
{ 

 std::cout<<std::fixed<<std::setprecision(4);
 std::cout<<"Time taking for "<<_caller<<" is : "<< _elapsed /1.e9 <<"s\n"; 

// in another file.Cpp contain while loop
 while( _continue )
 {
     //std::cout<<"Image number "<<m_imgIdx<<std::endl;
     //read image
     AbbeTIFFReader_getSampleData( m_tiff, mat.data, 0);
     _continue = AbbeTIFFReader_readNext( m_tiff );

     cv::add ( mat, matConcatenated, matConcatenated, cv::noArray(),CV_32FC1 );

     Benchmark tim_1 ("LocalMean",true);
     //local mean
     cv::Mat mat_LocalMean = m_substractLocalMean(mat,15);  //1st function
     tim_1.stop();
     //wavelet
     double stdDev =0;
     Benchmark tim_2("matWavel et",true);
     cv::Mat matWavelet = m_WaveletFiltering (mat_LocalMean,stdDev); //2nd function
     tim_2.stop();

     //fast    
      Benchmark tim_3 ("fastLoc",true);        
      m_fastLoc(matWavelet,stdDev,1.,9,50); //3rd function
     tim_3.stop();
     tim_1.disp ();
     tim_2.disp ();
     tim_3.disp ();


      m_imgIdx  ;
// the exution 
 }`*********** iam in startLocalization function *************
void Localization::startLocalization()
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s
Time taking for LocalMean is : 0.0000s
Time taking for matWavel et is : 0.0000s
Time taking for fastLoc is : 0.0010s