OpenCV 3.0.0 and OpenCL benchmark: Sobel edge detection

edit

I did a quick test with OpenCV 3.0.0 beta and I realised that the OpenCL version used my Intel HD Graphics instead of my NVidia GPU (see my comments).

I tested also with OpenCV 2.4.10 and it is possible to set the device for OpenCL: http://docs.opencv.org/modules/ocl/doc/introduction.html.

This is the code I use to test OpenCL with OpenCV 2.4.10:

#include <iostream>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/ocl/ocl.hpp>


int main(int argc, char**argv)
{
    int nBlurs = 50;

    bool use_opencl = false;
    if(argc > 1) {
        use_opencl = std::string(argv[1]) == "1";
    }

    std::cout << "use_opencl=" << use_opencl << std::endl;
    cv::VideoCapture cam;

    if (!cam.open(0)) {
        std::cout << "Problem connecting to cam " << std::endl;
        return -1;
    }
    else {
        std::cout << "Successfuly connected to camera " << std::endl;
    }

    cv::Mat frame;
    cv::Mat frameGray;
    cv::Mat frameSobelx;
    cv::Mat frameSobely;
    cv::Mat blurredSobel;

    char c;
    double total_time = 0.0;
    int cpt = 0;
    do
    {
        cam.read(frame);

        double t = (double) cv::getTickCount();
        if(use_opencl) {
            cv::ocl::oclMat frame_ocl, frameGray_ocl, frameSobelx_ocl, frameSobely_ocl, blurredSobel_ocl;
            frame_ocl.upload(frame);

            cv::ocl::cvtColor(frame_ocl, frameGray_ocl, cv::COLOR_BGR2GRAY);

            cv::ocl::Sobel(frameGray_ocl, frameSobelx_ocl, frameGray_ocl.depth(), 1, 0, 3);
            cv::ocl::Sobel(frameGray_ocl, frameSobely_ocl, frameGray_ocl.depth(), 0, 1, 3);

            cv::ocl::bitwise_or(frameSobelx_ocl, frameSobely_ocl, frameGray_ocl);

            for (int n = 0; n < nBlurs; n++) {
                cv::ocl::blur(frameGray_ocl, blurredSobel_ocl, cv::Size(3,3));
            }

            blurredSobel = blurredSobel_ocl;
        } else {
            cv::cvtColor(frame, frameGray, cv::COLOR_BGR2GRAY);

            cv::Sobel(frameGray, frameSobelx, frameGray.depth(), 1, 0, 3);
            cv::Sobel(frameGray, frameSobely, frameGray.depth(), 0, 1, 3);

            cv::bitwise_or(frameSobelx, frameSobely, frameGray);

            for (int n = 0; n < nBlurs; n++) {
                cv::blur(frameGray, blurredSobel, cv::Size(3,3));
            }
        }

        t = ((double) cv::getTickCount() - t) / cv::getTickFrequency();
        total_time += t;
        cpt++;
        std::cout << "Times passed in seconds: " << t << " ; FPS: " << (1/t) << " ; Average FPS=" << (cpt/total_time) << std::endl;

        cv::imshow("Sobel blurred Frame", blurredSobel);

        c = cv::waitKey(30);
    } while(c != 27);

    return 0;
}

My result (pass as an argument 1 to use the OpenCL version, otherwise it is the CPU version):

• CPU version=~24 FPS ; CPU load=~92%
• GPU version=~70 FPS ; CPU load=~8% ; GPU load=~7%

Also, you can use a program to monitor the GPU load (e.g. GPU-Z). Mine is about 7% when the program is running.

Edit: Additionnal information:

• Windows platform + Visual Studio 2010 + Release mode
• to set the GPU device: add the environment variable OPENCV_OPENCL_DEVICE with for example: :GPU:1

Edit2:

I retried with this time OpenCV 3.0.0 from master (as of 26/03/2015) and I built it with VS2010, 64 bits, release mode and without IPP. I manage to have with this configuration coherent results:

• setUseOpenCL(false): ~24 FPS ; ~8% for CPU load
• setUseOpenCL(true): ~200 FPS ; ~15% for CPU load ; ~< 10% for GPU load

To calculate the FPS, I measure only the time to process the image (without the time to acquire the image, without the time to display the image). I still have to set the ... (more)