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#include "perf_precomp.hpp"

using namespace std;
using namespace testing;
using namespace perf;

typedef pair<string, string> pair_string;

DEF_PARAM_TEST_1(ImagePair, pair_string);

//////////////////////////////////////////////////////
// BroxOpticalFlow

PERF_TEST_P(ImagePair, BroxOpticalFlow,
            Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
    declare.time(300);

    cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame0.empty());

    cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame1.empty());

    frame0.convertTo(frame0, CV_32FC1, 1.0 / 255.0);
    frame1.convertTo(frame1, CV_32FC1, 1.0 / 255.0);

    if (PERF_RUN_CUDA())
    {
        const cv::cuda::GpuMat d_frame0(frame0);
        const cv::cuda::GpuMat d_frame1(frame1);
        cv::cuda::GpuMat u;
        cv::cuda::GpuMat v;

        cv::cuda::BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
                                        10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);

        TEST_CYCLE() d_flow(d_frame0, d_frame1, u, v);

        CUDA_SANITY_CHECK(u, 1e-1);
        CUDA_SANITY_CHECK(v, 1e-1);
    }
    else
    {
        FAIL_NO_CPU();
    }
}

//////////////////////////////////////////////////////
// PyrLKOpticalFlowSparse

DEF_PARAM_TEST(ImagePair_Gray_NPts_WinSz_Levels_Iters, pair_string, bool, int, int, int, int);

PERF_TEST_P(ImagePair_Gray_NPts_WinSz_Levels_Iters, PyrLKOpticalFlowSparse,
            Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
                    Bool(),
                    Values(8000),
                    Values(21),
                    Values(1, 3),
                    Values(1, 30)))
{
    declare.time(20.0);

    const pair_string imagePair = GET_PARAM(0);
    const bool useGray = GET_PARAM(1);
    const int points = GET_PARAM(2);
    const int winSize = GET_PARAM(3);
    const int levels = GET_PARAM(4);
    const int iters = GET_PARAM(5);

    const cv::Mat frame0 = readImage(imagePair.first, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
    ASSERT_FALSE(frame0.empty());

    const cv::Mat frame1 = readImage(imagePair.second, useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
    ASSERT_FALSE(frame1.empty());

    cv::Mat gray_frame;
    if (useGray)
        gray_frame = frame0;
    else
        cv::cvtColor(frame0, gray_frame, cv::COLOR_BGR2GRAY);

    cv::Mat pts;
    cv::goodFeaturesToTrack(gray_frame, pts, points, 0.01, 0.0);

    if (PERF_RUN_CUDA())
    {
        const cv::cuda::GpuMat d_pts(pts.reshape(2, 1));

        cv::cuda::PyrLKOpticalFlow d_pyrLK;
        d_pyrLK.winSize = cv::Size(winSize, winSize);
        d_pyrLK.maxLevel = levels - 1;
        d_pyrLK.iters = iters;

        const cv::cuda::GpuMat d_frame0(frame0);
        const cv::cuda::GpuMat d_frame1(frame1);
        cv::cuda::GpuMat nextPts;
        cv::cuda::GpuMat status;

        TEST_CYCLE() d_pyrLK.sparse(d_frame0, d_frame1, d_pts, nextPts, status);

        CUDA_SANITY_CHECK(nextPts);
        CUDA_SANITY_CHECK(status);
    }
    else
    {
        cv::Mat nextPts;
        cv::Mat status;

        TEST_CYCLE()
        {
            cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, cv::noArray(),
                                     cv::Size(winSize, winSize), levels - 1,
                                     cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, iters, 0.01));
        }

        CPU_SANITY_CHECK(nextPts);
        CPU_SANITY_CHECK(status);
    }
}

//////////////////////////////////////////////////////
// PyrLKOpticalFlowDense

DEF_PARAM_TEST(ImagePair_WinSz_Levels_Iters, pair_string, int, int, int);

PERF_TEST_P(ImagePair_WinSz_Levels_Iters, PyrLKOpticalFlowDense,
            Combine(Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")),
                    Values(3, 5, 7, 9, 13, 17, 21),
                    Values(1, 3),
                    Values(1, 10)))
{
    declare.time(30);

    const pair_string imagePair = GET_PARAM(0);
    const int winSize = GET_PARAM(1);
    const int levels = GET_PARAM(2);
    const int iters = GET_PARAM(3);

    const cv::Mat frame0 = readImage(imagePair.first, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame0.empty());

    const cv::Mat frame1 = readImage(imagePair.second, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame1.empty());

    if (PERF_RUN_CUDA())
    {
        const cv::cuda::GpuMat d_frame0(frame0);
        const cv::cuda::GpuMat d_frame1(frame1);
        cv::cuda::GpuMat u;
        cv::cuda::GpuMat v;

        cv::cuda::PyrLKOpticalFlow d_pyrLK;
        d_pyrLK.winSize = cv::Size(winSize, winSize);
        d_pyrLK.maxLevel = levels - 1;
        d_pyrLK.iters = iters;

        TEST_CYCLE() d_pyrLK.dense(d_frame0, d_frame1, u, v);

        CUDA_SANITY_CHECK(u);
        CUDA_SANITY_CHECK(v);
    }
    else
    {
        FAIL_NO_CPU();
    }
}

//////////////////////////////////////////////////////
// FarnebackOpticalFlow

PERF_TEST_P(ImagePair, FarnebackOpticalFlow,
            Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
    declare.time(10);

    const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame0.empty());

    const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame1.empty());

    const int numLevels = 5;
    const double pyrScale = 0.5;
    const int winSize = 13;
    const int numIters = 10;
    const int polyN = 5;
    const double polySigma = 1.1;
    const int flags = 0;

    if (PERF_RUN_CUDA())
    {
        const cv::cuda::GpuMat d_frame0(frame0);
        const cv::cuda::GpuMat d_frame1(frame1);
        cv::cuda::GpuMat u;
        cv::cuda::GpuMat v;

        cv::cuda::FarnebackOpticalFlow d_farneback;
        d_farneback.numLevels = numLevels;
        d_farneback.pyrScale = pyrScale;
        d_farneback.winSize = winSize;
        d_farneback.numIters = numIters;
        d_farneback.polyN = polyN;
        d_farneback.polySigma = polySigma;
        d_farneback.flags = flags;

        TEST_CYCLE() d_farneback(d_frame0, d_frame1, u, v);

        CUDA_SANITY_CHECK(u, 1e-4);
        CUDA_SANITY_CHECK(v, 1e-4);
    }
    else
    {
        cv::Mat flow;

        TEST_CYCLE() cv::calcOpticalFlowFarneback(frame0, frame1, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags);

        CPU_SANITY_CHECK(flow);
    }
}

//////////////////////////////////////////////////////
// OpticalFlowDual_TVL1

PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1,
            Values<pair_string>(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png")))
{
    declare.time(20);

    const cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame0.empty());

    const cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(frame1.empty());

    if (PERF_RUN_CUDA())
    {
        const cv::cuda::GpuMat d_frame0(frame0);
        const cv::cuda::GpuMat d_frame1(frame1);
        cv::cuda::GpuMat u;
        cv::cuda::GpuMat v;

        cv::cuda::OpticalFlowDual_TVL1_CUDA d_alg;

        TEST_CYCLE() d_alg(d_frame0, d_frame1, u, v);

        CUDA_SANITY_CHECK(u, 1e-1);
        CUDA_SANITY_CHECK(v, 1e-1);
    }
    else
    {
        cv::Mat flow;

        cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
        alg->set("medianFiltering", 1);
        alg->set("innerIterations", 1);
        alg->set("outerIterations", 300);
        TEST_CYCLE() alg->calc(frame0, frame1, flow);

        CPU_SANITY_CHECK(flow);
    }
}