Test TX2 OpenCV cuda support

README.md

Run the docker image with

docker run -it --runtime nvidia -e DISPLAY --privileged IMAGE_NAME /bin/bash

./test.sh

test.cpp

#include <iostream>
#include <ctime>
#include <cmath>
#include "bits/time.h"

//#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/imgcodecs/imgcodecs.hpp>

#include <opencv2/core/cuda.hpp>
#include <opencv2/cudaarithm.hpp>
#include <opencv2/cudaimgproc.hpp>

#define TestCUDA true

int main()
{
    std::clock_t begin = std::clock();

    try {
        cv::Mat srcHost = cv::imread("image.png",CV_LOAD_IMAGE_GRAYSCALE);

        for(int i=0; i<1000; i++) {
            if(TestCUDA) {
                cv::cuda::GpuMat dst, src;
                src.upload(srcHost);

                //cv::cuda::threshold(src,dst,128.0,255.0, CV_THRESH_BINARY);
                cv::cuda::bilateralFilter(src,dst,3,1,1);

                cv::Mat resultHost;
                dst.download(resultHost);
            } else {
                cv::Mat dst;
                cv::bilateralFilter(srcHost,dst,3,1,1);
            }
        }

        //cv::imshow("Result",resultHost);
        //cv::waitKey();

    } catch(const cv::Exception& ex) {
        std::cout << "Error: " << ex.what() << std::endl;
    }

    std::clock_t end = std::clock();
    std::cout << double(end-begin) / CLOCKS_PER_SEC  << std::endl;
}

test.sh

#!/usr/bin/env bash
set -o xtrace

wget -O test.cpp https://gist.githubusercontent.com/awesomebytes/92e6ba2e24bad4ce24898e9b9fc4d703/raw/c54c2dd0e94155d242ddd5ea7188250a024ae8e7/test.cpp

wget -O image.png https://upload.wikimedia.org/wikipedia/en/7/7d/Lenna_%28test_image%29.png

nvcc `pkg-config opencv --cflags --libs` -o test test.cpp

./test