C++ TickMeter::reset方法代码示例

int main(int argc, const char* argv[])
{
    if (argc != 2)
        return -1;

    const std::string fname(argv[1]);

    cv::namedWindow("CPU", cv::WINDOW_NORMAL);
    cv::namedWindow("GPU", cv::WINDOW_OPENGL);
    cv::cuda::setGlDevice();

    cv::Mat frame;
    cv::VideoCapture reader(fname);

    cv::cuda::GpuMat d_frame;
    cv::Ptr<cv::cudacodec::VideoReader> d_reader = cv::cudacodec::createVideoReader(fname);

    TickMeter tm;
    std::vector<double> cpu_times;
    std::vector<double> gpu_times;

    for (;;)
    {
        tm.reset();
        tm.start();
        if (!reader.read(frame))
            break;
        tm.stop();
        cpu_times.push_back(tm.getTimeMilli());

        tm.reset();
        tm.start();
        if (!d_reader->nextFrame(d_frame))
            break;
        tm.stop();
        gpu_times.push_back(tm.getTimeMilli());

        cv::imshow("CPU", frame);
        cv::imshow("GPU", d_frame);

        if (cv::waitKey(3) > 0)
            break;
    }

    if (!cpu_times.empty() && !gpu_times.empty())
    {
        std::cout << std::endl << "Results:" << std::endl;

        std::sort(cpu_times.begin(), cpu_times.end());
        std::sort(gpu_times.begin(), gpu_times.end());

        double cpu_avg = std::accumulate(cpu_times.begin(), cpu_times.end(), 0.0) / cpu_times.size();
        double gpu_avg = std::accumulate(gpu_times.begin(), gpu_times.end(), 0.0) / gpu_times.size();

        std::cout << "CPU : Avg : " << cpu_avg << " ms FPS : " << 1000.0 / cpu_avg << std::endl;
        std::cout << "GPU : Avg : " << gpu_avg << " ms FPS : " << 1000.0 / gpu_avg << std::endl;
    }

    return 0;
}

int main(int argc, char** argv)
{
    if (argc != 3)
    {
        cerr << "Usage: stereo_multi_gpu <left_video> <right_video>" << endl;
        return -1;
    }

    const int numDevices = getCudaEnabledDeviceCount();
    if (numDevices != 2)
    {
        cerr << "Two GPUs are required" << endl;
        return -1;
    }

    for (int i = 0; i < numDevices; ++i)
    {
        DeviceInfo devInfo(i);
        if (!devInfo.isCompatible())
        {
            cerr << "CUDA module was't built for GPU #" << i << " ("
                 << devInfo.name() << ", CC " << devInfo.majorVersion()
                 << devInfo.minorVersion() << endl;
            return -1;
        }

        printShortCudaDeviceInfo(i);
    }

    VideoCapture leftVideo(argv[1]);
    VideoCapture rightVideo(argv[2]);

    if (!leftVideo.isOpened())
    {
         cerr << "Can't open " << argv[1] << " video file" << endl;
         return -1;
    }

    if (!rightVideo.isOpened())
    {
         cerr << "Can't open " << argv[2] << " video file" << endl;
         return -1;
    }

    cout << endl;
    cout << "This sample demonstrates working on one piece of data using two GPUs." << endl;
    cout << "It splits input into two parts and processes them separately on different GPUs." << endl;
    cout << endl;

    Mat leftFrame, rightFrame;
    CudaMem leftGrayFrame, rightGrayFrame;

    StereoSingleGpu gpu0Alg(0);
    StereoSingleGpu gpu1Alg(1);
    StereoMultiGpuThread multiThreadAlg;
    StereoMultiGpuStream multiStreamAlg;

    Mat disparityGpu0;
    Mat disparityGpu1;
    Mat disparityMultiThread;
    CudaMem disparityMultiStream;

    Mat disparityGpu0Show;
    Mat disparityGpu1Show;
    Mat disparityMultiThreadShow;
    Mat disparityMultiStreamShow;

    TickMeter tm;

    cout << "-------------------------------------------------------------------" << endl;
    cout << "| Frame | GPU 0 ms | GPU 1 ms | Multi Thread ms | Multi Stream ms |" << endl;
    cout << "-------------------------------------------------------------------" << endl;

    for (int i = 0;; ++i)
    {
        leftVideo >> leftFrame;
        rightVideo >> rightFrame;

        if (leftFrame.empty() || rightFrame.empty())
            break;

        if (leftFrame.size() != rightFrame.size())
        {
            cerr << "Frames have different sizes" << endl;
            return -1;
        }

        leftGrayFrame.create(leftFrame.size(), CV_8UC1);
        rightGrayFrame.create(leftFrame.size(), CV_8UC1);

        cvtColor(leftFrame, leftGrayFrame.createMatHeader(), COLOR_BGR2GRAY);
        cvtColor(rightFrame, rightGrayFrame.createMatHeader(), COLOR_BGR2GRAY);

        tm.reset(); tm.start();
        gpu0Alg.compute(leftGrayFrame.createMatHeader(), rightGrayFrame.createMatHeader(),
                        disparityGpu0);
        tm.stop();

        const double gpu0Time = tm.getTimeMilli();

//.........这里部分代码省略.........

//.........这里部分代码省略.........

            kpfn = kpfn+ ".yml";
            
            // Create filestorage item to read from and add to map.
            FileStorage store(kpfn, cv::FileStorage::READ);

            FileNode n1 = store["SurfKeypoints"];
            read(n1,SurfKeypoints);
            FileNode n2 = store["SiftKeypoints"];
            read(n2,SiftKeypoints);
            FileNode n3 = store["OrbKeypoints"];
            read(n3,OrbKeypoints);
            FileNode n4 = store["FastKeypoints"];
            read(n4,FastKeypoints);
            FileNode n5 = store["SurfDescriptors"];
            read(n5,SurfDescriptors);
            FileNode n6 = store["SiftDescriptors"];
            read(n6,SiftDescriptors);
            FileNode n7 = store["OrbDescriptors"];
            read(n7,OrbDescriptors);
            FileNode n8 = store["FastDescriptors"];
            read(n8,FastDescriptors);

            store.release();

            surfmap[ID] = SurfDescriptors;
            siftmap[ID] = SiftDescriptors;
            orbmap[ID]  = OrbDescriptors;
            fastmap[ID] = FastDescriptors;
        }
    }

    TickMeter tm;
    tm.reset();
    cout << "<\n  Analyzing Images ..." << endl;

    // We have a bunch of images, now we compute their grayscale and black and white.
    map<vector<float>, Mat> gsmap;
    map<vector<float>, Mat> bwmap;
    for (map<vector<float>, Mat>::iterator i = imagemap.begin(); i != imagemap.end(); ++i)
    {
        vector<float> ID = i->first;
        Mat Image = i-> second;
        GaussianBlur( Image, Image, Size(5,5), 0, 0, BORDER_DEFAULT );


        gsmap[ID] = averageImage::getPixSumFromImage(Image, divs);
        bwmap[ID] = averageImage::aboveBelow(gsmap[ID]);
    }
    Mat image = imread(image_name);
    Mat gsimage = averageImage::getPixSumFromImage(image, divs);
    Mat bwimage = averageImage::aboveBelow(gsimage);

    // cout << gsimage <<endl;
    imwrite("GS.png", gsimage);
    namedWindow("GSIMAGE (Line 319)");
    imshow("GSIMAGE (Line 319)", gsimage);
    waitKey(0);

    vector<KeyPoint> imgSurfKeypoints;
    vector<KeyPoint> imgSiftKeypoints;
    vector<KeyPoint> imgOrbKeypoints;
    vector<KeyPoint> imgFastKeypoints;
    Mat imgSurfDescriptors;
    Mat imgSiftDescriptors;
    Mat imgOrbDescriptors;

int main(int argc, const char* argv[])
{
    if (argc != 2)
    {
        std::cerr << "Usage : video_writer <input video file>" << std::endl;
        return -1;
    }

    const double FPS = 25.0;

    cv::VideoCapture reader(argv[1]);

    if (!reader.isOpened())
    {
        std::cerr << "Can't open input video file" << std::endl;
        return -1;
    }

    cv::cuda::printShortCudaDeviceInfo(cv::cuda::getDevice());

    cv::VideoWriter writer;
    cv::Ptr<cv::cudacodec::VideoWriter> d_writer;

    cv::Mat frame;
    cv::cuda::GpuMat d_frame;

    std::vector<double> cpu_times;
    std::vector<double> gpu_times;
    TickMeter tm;

    for (int i = 1;; ++i)
    {
        std::cout << "Read " << i << " frame" << std::endl;

        reader >> frame;

        if (frame.empty())
        {
            std::cout << "Stop" << std::endl;
            break;
        }

        if (!writer.isOpened())
        {
            std::cout << "Frame Size : " << frame.cols << "x" << frame.rows << std::endl;

            std::cout << "Open CPU Writer" << std::endl;

            if (!writer.open("output_cpu.avi", cv::VideoWriter::fourcc('X', 'V', 'I', 'D'), FPS, frame.size()))
                return -1;
        }

        if (d_writer.empty())
        {
            std::cout << "Open CUDA Writer" << std::endl;

            const cv::String outputFilename = "output_gpu.avi";
            d_writer = cv::cudacodec::createVideoWriter(outputFilename, frame.size(), FPS);
        }

        d_frame.upload(frame);

        std::cout << "Write " << i << " frame" << std::endl;

        tm.reset(); tm.start();
        writer.write(frame);
        tm.stop();
        cpu_times.push_back(tm.getTimeMilli());

        tm.reset(); tm.start();
        d_writer->write(d_frame);
        tm.stop();
        gpu_times.push_back(tm.getTimeMilli());
    }

    std::cout << std::endl << "Results:" << std::endl;

    std::sort(cpu_times.begin(), cpu_times.end());
    std::sort(gpu_times.begin(), gpu_times.end());

    double cpu_avg = std::accumulate(cpu_times.begin(), cpu_times.end(), 0.0) / cpu_times.size();
    double gpu_avg = std::accumulate(gpu_times.begin(), gpu_times.end(), 0.0) / gpu_times.size();

    std::cout << "CPU [XVID] : Avg : " << cpu_avg << " ms FPS : " << 1000.0 / cpu_avg << std::endl;
    std::cout << "GPU [H264] : Avg : " << gpu_avg << " ms FPS : " << 1000.0 / gpu_avg << std::endl;

    return 0;
}