/*M///////////////////////////////////////////////////////////////////////////////////////
//
//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
//  By downloading, copying, installing or using the software you agree to this license.
//  If you do not agree to this license, do not download, install,
//  copy or use the software.
//
//
//                           License Agreement
//                For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Multicore Ware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
//    Peng Xiao, pengxiao@multicorewareinc.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
//   * Redistribution's of source code must retain the above copyright notice,
//     this list of conditions and the following disclaimer.
//
//   * Redistribution's in binary form must reproduce the above copyright notice,
//     this list of conditions and the following disclaimer in the documentation
//     and/or other oclMaterials provided with the distribution.
//
//   * The name of the copyright holders may not be used to endorse or promote products
//     derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/

#include "precomp.hpp"
#include <ctime>

#if PERF_TEST_OCL

#ifdef HAVE_OPENCL

#define SHOW_CPU false
#define REPEAT   1000
#define COUNT_U  0 // count the uploading execution time for ocl mat structures
#define COUNT_D  0


// the following macro section tests the target function (kernel) performance
// upload is the code snippet for converting cv::mat to cv::ocl::oclMat
// downloading is the code snippet for converting cv::ocl::oclMat back to cv::mat
// change COUNT_U and COUNT_D to take downloading and uploading time into account
#define P_TEST_FULL( upload, kernel_call, download ) \
{ \
    std::cout<< "\n" #kernel_call "\n----------------------"; \
    {upload;} \
    R_TEST( kernel_call, 15 ); \
    double t = (double)cvGetTickCount(); \
    R_T( { \
            if( COUNT_U ) {upload;} \
            kernel_call; \
            if( COUNT_D ) {download;} \
            } ); \
    t = (double)cvGetTickCount() - t; \
    std::cout << "runtime is  " << t/((double)cvGetTickFrequency()* 1000.) << "ms" << std::endl; \
}


#define R_T2( test ) \
{ \
    std::cout<< "\n" #test "\n----------------------"; \
    R_TEST( test, 15 ) \
    clock_t st = clock(); \
    R_T( test ) \
    std::cout<< clock() - st << "ms\n"; \
}
#define R_T( test ) \
    R_TEST( test, REPEAT )
#define R_TEST( test, repeat ) \
    try{ \
        for( int i = 0; i < repeat; i ++ ) { test; } \
    } catch( ... ) { std::cout << "||||| Exception catched! |||||\n"; return; }

#define FILTER_TEST_IMAGE "C:/Windows/Web/Wallpaper/Landscapes/img9.jpg"
#define WARN_NRUN( name ) \
    std::cout << "Warning: " #name " is not runnable!\n";


void print_info();

// performance base class
struct PerfTest
{
    virtual void Run()   = 0;
    protected:
    virtual void SetUp() = 0;
};
///////////////////////////////////////
// Arithm
struct ArithmTestP : PerfTest
{
    int type;
    cv::Scalar val;

    cv::Size size;
    cv::Mat mat1, mat2;
    cv::Mat mask;
    cv::Mat dst;
    cv::ocl::oclMat oclRes, oclmat1, oclmat2;
    cv::ocl::oclMat oclmask;
    std::vector<cv::Mat> dstv;
    protected:
    ArithmTestP() : type( CV_8UC4 ) {}
    virtual void SetUp()
    {
        cv::RNG& rng = cvtest::TS::ptr()->get_rng();
        size = cv::Size( 3000, 3000 ); // big input image
        mat1 = cvtest::randomMat(rng, size, type, 1, 255, false);
        mat2 = cvtest::randomMat(rng, size, type, 1, 255, false);
        mask = cvtest::randomMat(rng, size, CV_8UC1, 0, 2,  false);

        cv::threshold(mask, mask, 0.5, 255., CV_8UC1);

        val = cv::Scalar(rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0));

        oclmat1 = cv::ocl::oclMat(mat1);
        oclmat2 = cv::ocl::oclMat(mat2);
        oclmask = cv::ocl::oclMat(mask);
    }
};

struct AddArrayP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::add(oclmat1, oclmat2, oclRes),
                oclRes.download(dst);
                );
    }
};

struct SubtractArrayP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::subtract(oclmat1, oclmat2, oclRes),
                oclRes.download(dst);
                );
    }
};

struct MultiplyArrayP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        clock_t start = clock();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::multiply(oclmat1, oclmat2, oclRes),
                oclRes.download(dst);
                );		
    }
};

struct DivideArrayP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::divide(oclmat1, oclmat2, oclRes),
                oclRes.download(dst);
                );
    }
};

struct ExpP : ArithmTestP
{
    void Run()
    {
        type = CV_32FC1;
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::exp(oclmat1, oclRes),
                oclRes.download(dst);
                );
    }
};

struct LogP : ArithmTestP
{
    void Run()
    {
        type = CV_32FC1;
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::log(oclmat1, oclRes),
                oclRes.download(dst);
                );
    }
};

struct CompareP : ArithmTestP
{
    virtual void Run()
    {
        type = CV_32FC1;
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::compare(oclmat1, oclmat2, oclRes, cv::CMP_EQ),
                oclRes.download(dst);
                );
    }
};

struct FlipP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::flip(oclmat1, oclRes, 0),
                oclRes.download(dst);
                );
    }
    protected:
    virtual void SetUp()
    {
        type = CV_8UC4;
        cv::RNG& rng = cvtest::TS::ptr()->get_rng();
        size = cv::Size(3000, 3000);
        mat1 = cvtest::randomMat(rng, size, type, 1, 255, false);
        oclmat1 = cv::ocl::oclMat(mat1);
    }
};

struct MagnitudeP : ArithmTestP
{
    virtual void Run()
    {
        type = CV_32F;
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::magnitude(oclmat1, oclmat1, oclRes),
                oclRes.download(dst);
                );
    }
};

struct LUTP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);ocllut  = cv::ocl::oclMat(lut),
                cv::ocl::LUT(oclmat1, ocllut, oclRes),
                oclRes.download(dst);
                );
    }
    protected:
    cv::Mat lut;
    cv::ocl::oclMat ocllut;
    virtual void SetUp()
    {
        type = CV_8UC1;
        cv::RNG& rng = cvtest::TS::ptr()->get_rng();
        size = cv::Size(3000, 3000);
        mat1 = cvtest::randomMat(rng, size, type, 1, 255, false);
        lut = cvtest::randomMat(rng, cv::Size(256, 1), CV_8UC1, 100, 200, false);
        oclmat1 = cv::ocl::oclMat(mat1);
        ocllut  = cv::ocl::oclMat(lut);
    }
};

struct MinMaxP : ArithmTestP
{
    double minVal_gold, minVal;
    double maxVal_gold, maxVal;

    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::minMax(oclmat1, &minVal, &maxVal, oclmat2),
                {};
                );
    }

    protected:
    virtual void SetUp()
    {
        type = CV_64F;

        cv::RNG& rng = cvtest::TS::ptr()->get_rng();

        size = cv::Size(3000, 3000);

        mat1 = cvtest::randomMat(rng, size, type, 0.0, 127.0, false);
        mat2 = cvtest::randomMat(rng, size, CV_8UC1, 0, 2, false);

        oclmat1 = cv::ocl::oclMat(mat1);
        oclmat2 = cv::ocl::oclMat(mat2);
    }
};

struct MinMaxLocP : MinMaxP
{
    cv::Point minLoc_gold;
    cv::Point maxLoc_gold;
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::minMaxLoc(oclmat1, &minVal, &maxVal, &minLoc_gold, &maxLoc_gold, oclmat2),
                {}
                );
    }
};

struct CountNonZeroP : ArithmTestP
{
    int n;
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                n = cv::ocl::countNonZero(oclmat1),
                {}
                );
    }
    protected:
    virtual void SetUp()
    {
        type = 6;

        cv::RNG& rng = cvtest::TS::ptr()->get_rng();

        size = cv::Size( 3000, 3000 );

        cv::Mat matBase = cvtest::randomMat(rng, size, CV_8U, 0.0, 1.0, false);
        matBase.convertTo(mat1, type);

        oclmat1 = cv::ocl::oclMat(mat1);
    }
};

struct SumP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        cv::Scalar n;
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                n = cv::ocl::sum(oclmat1),
                {}
                );
    }
};

struct BitwiseP : ArithmTestP
{
    protected:
        virtual void SetUp()
        {
            type = CV_8UC4;

            cv::RNG& rng = cvtest::TS::ptr()->get_rng();

            size = cv::Size( 3000, 3000 );

            mat1.create(size, type);
            mat2.create(size, type);

            for (int i = 0; i < mat1.rows; ++i)
            {
                cv::Mat row1(1, static_cast<int>(mat1.cols * mat1.elemSize()), CV_8U, (void*)mat1.ptr(i));
                rng.fill(row1, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));

                cv::Mat row2(1, static_cast<int>(mat2.cols * mat2.elemSize()), CV_8U, (void*)mat2.ptr(i));
                rng.fill(row2, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
            }
            oclmat1 = cv::ocl::oclMat(mat1);
            oclmat2 = cv::ocl::oclMat(mat2);
        }
};

struct BitwiseNotP : BitwiseP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::bitwise_not(oclmat1, oclRes),
                oclRes.download(dst)
                );
    }
};

struct BitwiseAndP : BitwiseP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::bitwise_and(oclmat1, oclmat2, oclRes),
                oclRes.download(dst)
                );
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::bitwise_and(oclmat1, val, oclRes),
                oclRes.download(dst)
                );
    }
};

struct BitwiseXorP : BitwiseP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::bitwise_xor(oclmat1, oclmat2, oclRes),
                oclRes.download(dst)
                );
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::bitwise_xor(oclmat1, val, oclRes),
                oclRes.download(dst)
                );

    }
};

struct BitwiseOrP : BitwiseP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::bitwise_or(oclmat1, oclmat2, oclRes),
                oclRes.download(dst)
                );
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::bitwise_or(oclmat1, val, oclRes),
                oclRes.download(dst)
                );
    }
};

struct TransposeP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::transpose(oclmat1, oclRes),
                oclRes.download(dst)
                );
    }
};

struct AbsdiffArrayP : ArithmTestP
{
    virtual void Run()
    {
        type = CV_32FC1;
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::absdiff(oclmat1, oclmat2, oclRes),
                oclRes.download(dst)
                );
    }
};

struct PhaseP : ArithmTestP
{
    virtual void Run()
    {
        type = CV_32F;
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1);oclmat2 = cv::ocl::oclMat(mat2),
                cv::ocl::phase(oclmat1,oclmat2,oclRes,1),
                oclRes.download(dst)
                );
    }
};

struct CartToPolarP : ArithmTestP
{
    cv::ocl::oclMat oclRes1;
    virtual void Run()
    {
        type = CV_64FC4;
        SetUp();
        clock_t start = clock();
        R_TEST(
                cv::ocl::cartToPolar(oclmat1,oclmat2,oclRes, oclRes1, 1);
                if( COUNT_D ) {oclRes.download(dst);oclRes1.download(dst);}
                , 5);
        std::cout<< "ocl::CartToPolar -- " << clock() - start << "ms\n";
    }
};

struct PolarToCartP : ArithmTestP
{
    cv::ocl::oclMat oclRes1;
    virtual void Run()
    {
        type = CV_64FC4;
        SetUp();
        clock_t start = clock();
        R_TEST(
                cv::ocl::polarToCart(oclmat1,oclmat2,oclRes, oclRes1, 1);
                if( COUNT_D ) {oclRes.download(dst);oclRes1.download(dst);}
                , 2);
        std::cout<< "ocl::polarToCart -- " << clock() - start << "ms\n";
    }
};

///////////////////////////////////////
// split & merge
struct SplitP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::split(oclmat1, dev_dst),
                {			
                dstv.resize(dev_dst.size());
                for (size_t i = 0; i < dev_dst.size(); ++i)
                {
                dev_dst[i].download(dstv[i]);
                }
                }
                );
    }
    protected:
    std::vector<cv::ocl::oclMat> dev_dst;
    virtual void SetUp()
    {
        size = cv::Size( 3000, 3000 );

        mat1.create(size, type);
        mat1.setTo(cv::Scalar(1.0, 2.0, 3.0, 4.0));

        oclmat1 = cv::ocl::oclMat(mat1);
    }
};

struct MergeP : SplitP
{
    virtual void Run()
    {
        SetUp();
        cv::ocl::split(oclmat1, dev_dst);
        cv::split(mat1, dstv);
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                cv::ocl::merge(dev_dst, oclmat2),
                oclmat2.download(dst)
                );
    }
};

struct SetToP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        static cv::Scalar s = cv::Scalar(1, 2, 3, 4);
        P_TEST_FULL(
                oclmat2 = cv::ocl::oclMat(mat2),
                oclmat1.setTo( s, oclmat2 ),
                oclmat1.download(dst);
                );
    }
    protected:
    virtual void SetUp()
    {
        type = CV_32FC4;
        size = cv::Size(3000, 3000);

        mat1.create(size, type);
        oclmat1.create(size, type);

        cv::RNG& rng = cvtest::TS::ptr()->get_rng();
        mat2 = cvtest::randomMat(rng, size, CV_8UC1, 0.0, 1.5, false);
        oclmat2 = cv::ocl::oclMat(mat2);
    }
};

struct CopyToP : SetToP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                oclmat1.copyTo( oclRes, oclmat2 ),
                oclRes.download(dst)
                );
    }
};

struct ConvertToP : ArithmTestP
{
    virtual void Run()
    {
        type = CV_32FC1;;
        SetUp();
        cv::RNG& rng = cvtest::TS::ptr()->get_rng();
        const double a = rng.uniform(0.0, 1.0);
        const double b = rng.uniform(-10.0, 10.0);

        int type2 = CV_32FC4;

        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat(mat1),
                oclmat1.convertTo( oclRes, type2 /*, a, b */ ), // fails when scaling factors a and b are specified
                oclRes.download(dst)
                );
    }
};

////////////////////////////////////////////
// Filters

struct FilterTestP : PerfTest
{
    protected:
        int ksize;
        int dx, dy;

        cv::Mat img_rgba;
        cv::Mat img_gray;

        cv::ocl::oclMat ocl_img_rgba;
        cv::ocl::oclMat ocl_img_gray;

        cv::ocl::oclMat dev_dst_rgba;
        cv::ocl::oclMat dev_dst_gray;

        cv::Mat dst_rgba;
        cv::Mat dst_gray;

        cv::Mat kernel;

        int bordertype;

        virtual void SetUp()
        {
            bordertype = (int)cv::BORDER_DEFAULT;
            ksize = 7;
            dx = ksize/2; dy = ksize/2;

            kernel = cv::Mat::ones(ksize, ksize, CV_8U);

            cv::Mat img = readImage(FILTER_TEST_IMAGE);
            ASSERT_FALSE(img.empty());

            cv::cvtColor(img, img_rgba, CV_BGR2BGRA);
            cv::cvtColor(img, img_gray, CV_BGR2GRAY);

            ocl_img_rgba = cv::ocl::oclMat(img_rgba);
            ocl_img_gray = cv::ocl::oclMat(img_gray);
        }
};

struct BlurP : FilterTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::blur(ocl_img_rgba, dev_dst_rgba, cv::Size(ksize, ksize), cv::Point(-1,-1), bordertype);
                cv::ocl::blur(ocl_img_gray, dev_dst_gray, cv::Size(ksize, ksize), cv::Point(-1,-1), bordertype);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct SobelP : FilterTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::Sobel(ocl_img_rgba, dev_dst_rgba, -1, dx, dy, ksize, 1, 0, bordertype);
                cv::ocl::Sobel(ocl_img_gray, dev_dst_gray, -1, dx, dy, ksize, 1, 0, bordertype);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct ScharrP : FilterTestP
{
    virtual void Run()
    {
        SetUp();
        dx = 0; dy = 1;
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::Scharr(ocl_img_rgba, dev_dst_rgba, -1, dx, dy, 1, 0, bordertype);
                cv::ocl::Scharr(ocl_img_gray, dev_dst_gray, -1, dx, dy, 1, 0, bordertype);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct GaussianBlurP : FilterTestP
{
    virtual void Run()
    {
        double sigma1 = 3, sigma2 = 3;
        SetUp();
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::GaussianBlur(ocl_img_rgba, dev_dst_rgba, cv::Size(ksize, ksize), sigma1, sigma2);
                cv::ocl::GaussianBlur(ocl_img_gray, dev_dst_gray, cv::Size(ksize, ksize), sigma1, sigma2);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct DilateP : FilterTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::dilate(ocl_img_rgba, dev_dst_rgba, kernel);
                cv::ocl::dilate(ocl_img_gray, dev_dst_gray, kernel);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct ErodeP : FilterTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::erode(ocl_img_rgba, dev_dst_rgba, kernel);
                cv::ocl::erode(ocl_img_gray, dev_dst_gray, kernel);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct MorphExP : FilterTestP
{
    virtual void Run()
    {
        SetUp();
        cv::ocl::oclMat okernel;
        P_TEST_FULL(
                {
                okernel      = cv::ocl::oclMat(kernel);
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::morphologyEx(ocl_img_rgba, dev_dst_rgba, 3, okernel);
                cv::ocl::morphologyEx(ocl_img_gray, dev_dst_gray, 3, okernel);
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

struct LaplacianP : FilterTestP
{
    void Run()
    {
        SetUp();
        P_TEST_FULL(
                {
                ocl_img_rgba = cv::ocl::oclMat(img_rgba);
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::Laplacian(ocl_img_rgba, dev_dst_rgba, -1, 3 );
                cv::ocl::Laplacian(ocl_img_gray, dev_dst_gray, -1, 3 );
                },
                {
                dev_dst_rgba.download(dst_rgba);
                dev_dst_gray.download(dst_gray);
                });
    }
};

////////////////////
// histograms
struct CalcHistP : PerfTest
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat = cv::ocl::oclMat( src ),
                cv::ocl::calcHist(oclmat, oclRes),
                oclRes.download(hist)
                );
    }
    protected:
    cv::Size size;
    cv::Mat src, hist;

    cv::ocl::oclMat oclmat;
    cv::ocl::oclMat oclRes;

    virtual void SetUp()
    {
        cv::RNG& rng = cvtest::TS::ptr()->get_rng();
        size = cv::Size(3000, 3000);
        src = cvtest::randomMat(rng, size, CV_8UC1, 0, 255, false);
        oclmat = cv::ocl::oclMat( src );
    }
};

struct EqualizeHistP : CalcHistP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat = cv::ocl::oclMat( src ),
                cv::ocl::equalizeHist(oclmat, oclRes),
                oclRes.download(hist)
                );
    }
};

struct ThresholdP : CalcHistP
{
    virtual void Run()
    {
        SetUp();
        int threshOp = (int)cv::THRESH_TOZERO_INV;;
        double maxVal = 200;
        double thresh = 125;

        clock_t start = clock();

        P_TEST_FULL(
                oclmat = cv::ocl::oclMat( src ),
                cv::ocl::threshold(oclmat, oclRes, thresh, maxVal, threshOp ),
                oclRes.download(hist)
                );
    }
};

struct ResizeP : ArithmTestP
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat( mat1 ),
                cv::ocl::resize(oclmat1, oclRes, cv::Size(), 2.0, 2.0),
                oclRes.download(dst)
                );
    }
};

struct CvtColorP : PerfTest
{
    virtual void Run()
    {
        SetUp();
        P_TEST_FULL(
                oclmat = cv::ocl::oclMat( img ),
                cv::ocl::cvtColor(oclmat, ocldst, cvtcode),
                ocldst.download(dst)
                );
    }
    protected:
    int type;
    int cvtcode;

    cv::Mat img, dst;
    cv::ocl::oclMat oclmat, ocldst;
    virtual void SetUp()
    {
        type = CV_8U;
        cvtcode = CV_BGR2GRAY;
        cv::Mat imgBase = readImage(FILTER_TEST_IMAGE);
        ASSERT_FALSE(imgBase.empty());

        imgBase.convertTo(img, type, type == CV_32F ? 1.0 / 255.0 : 1.0);
        oclmat = cv::ocl::oclMat( img );
    };
};


struct WarpAffineP : ArithmTestP
{
    void Run()
    {
        SetUp();
        const double aplha = CV_PI / 4;
        double mat[2][3] = { {std::cos(aplha), -std::sin(aplha), mat1.cols / 2},
            {std::sin(aplha),  std::cos(aplha), 0}};
        cv::Mat M(2, 3, CV_64F, (void*) mat);

        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat( mat1 ),
                cv::ocl::warpAffine( oclmat1, oclRes, M, cv::Size(1500, 1500) ),
                oclRes.download(dst)
                );
    }
};

struct WarpPerspectiveP : ArithmTestP
{
    void Run()
    {
        SetUp();
        const double aplha = CV_PI / 4;
        double mat[3][3] = { {std::cos(aplha), -std::sin(aplha), mat1.cols / 2},
            {std::sin(aplha),  std::cos(aplha), 0},
            {0.0,              0.0,             1.0}};
        cv::Mat M(3, 3, CV_64F, (void*) mat);

        P_TEST_FULL(
                oclmat1 = cv::ocl::oclMat( mat1 ),
                cv::ocl::warpPerspective( oclmat1, oclRes, M, cv::Size(1500, 1500) ),
                oclRes.download(dst)
                );
    }
};


struct CornerHarrisP : FilterTestP
{
    void Run()
    {
        SetUp();
        bordertype = 2;
        P_TEST_FULL(
                {
                ocl_img_gray = cv::ocl::oclMat(img_gray);
                },
                {
                cv::ocl::cornerHarris(ocl_img_gray, dev_dst_gray, 3, ksize, 0.5, bordertype );
                },
                {
                dev_dst_gray.download(dst_gray);
                });
    }
};

void test()
{
    clock_t start = clock();
    std::cout << ">>>>>>>> Performance test started <<<<<<<<\n";
    /*
       {
       AddArrayP AddArrayP;
       AddArrayP.Run();
       SubtractArrayP subarray;
       subarray.Run();
       MultiplyArrayP MultiplyArrayP;
       MultiplyArrayP.Run();
       DivideArrayP DivideArrayP;
       DivideArrayP.Run();
       }
       std::cout.flush();
       {
       CompareP comp;
       comp.Run();
       MagnitudeP magnitude;
       magnitude.Run();
       LUTP lut;
       lut.Run();
       FlipP FlipP;
       FlipP.Run();
       MinMaxP minmax;
       minmax.Run();
       MinMaxLocP minmaxloc;
       minmaxloc.Run();
       CountNonZeroP cnz;
       cnz.Run();
       SumP sum;
       sum.Run();
       }*/
      /* std::cout.flush();
       {
       BitwiseNotP bn;
       bn.Run();
       BitwiseOrP bo;
       bo.Run();
       BitwiseAndP ba;
       ba.Run();
       BitwiseXorP bx;
       bx.Run();
       }*/
       
    std::cout.flush();
    {
        //   TransposeP transpose;
        //  transpose.Run();
        // AbsdiffArrayP absdiff;
        // absdiff.Run();
        // SplitP split;
        // split.Run();
       // MergeP merge;
       // merge.Run();
        /*
           SetToP setto;
           setto.Run();
           CopyToP copyto;
           copyto.Run();
           ConvertToP convertto;
           convertto.Run();
           */
    }
    /*
       std::cout.flush();
       {
       BlurP blur;
       blur.Run();
       SobelP sobel;
       sobel.Run();
       ScharrP scharr;
       scharr.Run();
       GaussianBlurP gblur;
       gblur.Run();
       DilateP dilate;
       dilate.Run();
       ErodeP erode;
       erode.Run();
       }
       std::cout.flush();
       {
       MorphExP morphex;
       morphex.Run();
       CalcHistP calchist;
       calchist.Run();
       EqualizeHistP eqhist;
       eqhist.Run();
       ThresholdP threshold;
       threshold.Run();
       ResizeP resize;
       resize.Run();
       CvtColorP cvtcolor;
       cvtcolor.Run();
       }

       {
       LogP log;
       log.Run();
       ExpP exp;
       exp.Run();
       }

       std::cout.flush();
       {
    //PhaseP phase;
    //phase.Run();
    }
    std::cout.flush();
    {
    CartToPolarP ctop;
    ctop.Run();
    }
    std::cout.flush();
    {
    PolarToCartP ptoc;
    ptoc.Run();
    }
    {
    WarpAffineP warpA;
    warpA.Run();
    WarpPerspectiveP warpP;
    warpP.Run();	
    }

    {
    CornerHarrisP ch;
    ch.Run();
    }

    {
    LaplacianP laplacian;
    laplacian.Run();
    }


    */
        std::cout << ">>>>>>>> Performance test ended <<<<<<<<\ntotal - " << clock() - start << "ms\n";
    std::cout.flush();
}

void  run_perf_test()
{
    print_info();
    cvtest::TS::ptr()->init("ocl");
    test();
}

#endif // WITH_OPENCL

#endif // PREF_TEST_OCL