How can I use the GPU for my code

Hi,
After installation of the jetpack. I tried to run some video processing examples on the Jetson TK1
it seems that all the examples on the elinux page doesn’t work for me due to compatibility, I downloaded also the openCV 3.3.1 an error appears saying that the utility.hpp file is missing? any solution for that, should I delete opencv3.3.1 and return to 2.4?
where I can find the complete list of opencv function for gpu implementation
I tried the following code using cmake, but it is very slow, How can I use GPU to accelerate these functions, any resources and help is very appreciated
I am new in this field, thanks in advance

#include "opencv2/objdetect/objdetect.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include "opencv2/imgproc/imgproc.hpp"

 #include <iostream>
 #include <stdio.h>

 using namespace std;
 using namespace cv;

 /** Function Headers */
 void detectAndDisplay( Mat frame );

 /** Global variables */
 String face_cascade_name = "haarcascade_frontalface_default.xml";
 String eyes_cascade_name = "haarcascade_eye.xml";
 CascadeClassifier face_cascade;
 CascadeClassifier eyes_cascade;
 string window_name = "Capture - Face detection";
 RNG rng(12345);

 /** @function main */
 int main( int argc, const char** argv )
 {
   CvCapture* capture;
   Mat frame;

   //-- 1. Load the cascades
   if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
   if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error2 loading\n"); return -1; };

   //-- 2. Read the video stream
   capture = cvCaptureFromCAM( -1 );
   if( capture )
   {
     while( true )
     {
   frame = cvQueryFrame( capture );

   //-- 3. Apply the classifier to the frame
       if( !frame.empty() )
       { detectAndDisplay( frame ); }
       else
       { printf(" --(!) No captured frame -- Break!"); break; }

       int c = waitKey(10);
       if( (char)c == 'c' ) { break; }
      }
   }
   return 0;
 }

/** @function detectAndDisplay */
void detectAndDisplay( Mat frame )
{
  std::vector<Rect> faces;
  Mat frame_gray;

  cvtColor( frame, frame_gray, CV_BGR2GRAY );
  equalizeHist( frame_gray, frame_gray );

  //-- Detect faces
  face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );

  for( size_t i = 0; i < faces.size(); i++ )
  {
    Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
    ellipse( frame, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );

    Mat faceROI = frame_gray( faces[i] );
    std::vector<Rect> eyes;

    //-- In each face, detect eyes
    eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );

    for( size_t j = 0; j < eyes.size(); j++ )
     {
       Point center( faces[i].x + eyes[j].x + eyes[j].width*0.5, faces[i].y + eyes[j].y + eyes[j].height*0.5 );
       int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
       circle( frame, center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
     }
  }
  //-- Show what you got
  imshow( window_name, frame );
 }

Hi k.sehairi,

Please run tegrastats while running this app in background to see if it is totally a cpu based program.

sudo ./tegrastats

There is also opencv forum. Maybe you can get more help there since you use a upstream opencv sample.
http://answers.opencv.org/questions/

thank you very much for your answer Mr. WayneWWW