opencv/modules/ocl/test/test_imgproc.cpp

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//  If you do not agree to this license, do not download, install,
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//
//                           License Agreement
//                For Open Source Computer Vision Library
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// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// @Authors
//    Niko Li, newlife20080214@gmail.com
//    Jia Haipeng, jiahaipeng95@gmail.com
//    Shengen Yan, yanshengen@gmail.com
//    Jiang Liyuan, lyuan001.good@163.com
//    Rock Li, Rock.Li@amd.com
//    Wu Zailong, bullet@yeah.net
//    Xu Pang, pangxu010@163.com
//
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#include "precomp.hpp"

#ifdef HAVE_OPENCL

using namespace cvtest;
using namespace testing;
using namespace std;

MatType nulltype = -1;

#define ONE_TYPE(type)  testing::ValuesIn(typeVector(type))
#define NULL_TYPE  testing::ValuesIn(typeVector(nulltype))

vector<MatType> typeVector(MatType type)
{
    vector<MatType> v;
    v.push_back(type);
    return v;
}

typedef struct
{
    short x;
    short y;
} COOR;

COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep, cv::Size size, int sp, int sr, int maxIter, float eps, int *tab)
{

    int isr2 = sr * sr;
    int c0, c1, c2, c3;
    int iter;
    uchar *ptr = NULL;
    uchar *pstart = NULL;
    int revx = 0, revy = 0;
    c0 = sptr[0];
    c1 = sptr[1];
    c2 = sptr[2];
    c3 = sptr[3];
    // iterate meanshift procedure
    for(iter = 0; iter < maxIter; iter++ )
    {
        int count = 0;
        int s0 = 0, s1 = 0, s2 = 0, sx = 0, sy = 0;

        //mean shift: process pixels in window (p-sigmaSp)x(p+sigmaSp)
        int minx = x0 - sp;
        int miny = y0 - sp;
        int maxx = x0 + sp;
        int maxy = y0 + sp;

        //deal with the image boundary
        if(minx < 0) minx = 0;
        if(miny < 0) miny = 0;
        if(maxx >= size.width) maxx = size.width - 1;
        if(maxy >= size.height) maxy = size.height - 1;
        if(iter == 0)
        {
            pstart = sptr;
        }
        else
        {
            pstart = pstart + revy * sstep + (revx << 2); //point to the new position
        }
        ptr = pstart;
        ptr = ptr + (miny - y0) * sstep + ((minx - x0) << 2); //point to the start in the row

        for( int y = miny; y <= maxy; y++, ptr += sstep - ((maxx - minx + 1) << 2))
        {
            int rowCount = 0;
            int x = minx;
#if CV_ENABLE_UNROLLED
            for( ; x + 4 <= maxx; x += 4, ptr += 16)
            {
                int t0, t1, t2;
                t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
                if(tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2)
                {
                    s0 += t0;
                    s1 += t1;
                    s2 += t2;
                    sx += x;
                    rowCount++;
                }
                t0 = ptr[4], t1 = ptr[5], t2 = ptr[6];
                if(tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2)
                {
                    s0 += t0;
                    s1 += t1;
                    s2 += t2;
                    sx += x + 1;
                    rowCount++;
                }
                t0 = ptr[8], t1 = ptr[9], t2 = ptr[10];
                if(tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2)
                {
                    s0 += t0;
                    s1 += t1;
                    s2 += t2;
                    sx += x + 2;
                    rowCount++;
                }
                t0 = ptr[12], t1 = ptr[13], t2 = ptr[14];
                if(tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2)
                {
                    s0 += t0;
                    s1 += t1;
                    s2 += t2;
                    sx += x + 3;
                    rowCount++;
                }
            }
#endif
            for(; x <= maxx; x++, ptr += 4)
            {
                int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
                if(tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2)
                {
                    s0 += t0;
                    s1 += t1;
                    s2 += t2;
                    sx += x;
                    rowCount++;
                }
            }
            if(rowCount == 0)
                continue;
            count += rowCount;
            sy += y * rowCount;
        }

        if( count == 0 )
            break;

        double icount = 1.0 / count;
        int x1 = cvFloor(sx * icount);
        int y1 = cvFloor(sy * icount);
        s0 = cvFloor(s0 * icount);
        s1 = cvFloor(s1 * icount);
        s2 = cvFloor(s2 * icount);

        bool stopFlag = (x0 == x1 && y0 == y1) || (abs(x1 - x0) + abs(y1 - y0) +
                        tab[s0-c0+255] + tab[s1-c1+255] + tab[s2-c2+255] <= eps);

        //revise the pointer corresponding to the new (y0,x0)
        revx = x1 - x0;
        revy = y1 - y0;

        x0 = x1;
        y0 = y1;
        c0 = s0;
        c1 = s1;
        c2 = s2;

        if( stopFlag )
            break;
    } //for iter

    dptr[0] = (uchar)c0;
    dptr[1] = (uchar)c1;
    dptr[2] = (uchar)c2;
    dptr[3] = (uchar)c3;

    COOR coor;
    coor.x = x0;
    coor.y = y0;
    return coor;
}

void meanShiftFiltering_(const Mat &src_roi, Mat &dst_roi, int sp, int sr, cv::TermCriteria crit)
{
    if( src_roi.empty() )
        CV_Error( CV_StsBadArg, "The input image is empty" );

    if( src_roi.depth() != CV_8U || src_roi.channels() != 4 )
        CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );

    CV_Assert( (src_roi.cols == dst_roi.cols) && (src_roi.rows == dst_roi.rows) );
    CV_Assert( !(dst_roi.step & 0x3) );

    if( !(crit.type & cv::TermCriteria::MAX_ITER) )
        crit.maxCount = 5;
    int maxIter = std::min(std::max(crit.maxCount, 1), 100);
    float eps;
    if( !(crit.type & cv::TermCriteria::EPS) )
        eps = 1.f;
    eps = (float)std::max(crit.epsilon, 0.0);

    int tab[512];
    for(int i = 0; i < 512; i++)
        tab[i] = (i - 255) * (i - 255);
    uchar *sptr = src_roi.data;
    uchar *dptr = dst_roi.data;
    int sstep = (int)src_roi.step;
    int dstep = (int)dst_roi.step;
    cv::Size size = src_roi.size();

    for(int i = 0; i < size.height; i++, sptr += sstep - (size.width << 2),
            dptr += dstep - (size.width << 2))
    {
        for(int j = 0; j < size.width; j++, sptr += 4, dptr += 4)
        {
            do_meanShift(j, i, sptr, dptr, sstep, size, sp, sr, maxIter, eps, tab);
        }
    }
}

void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp, int sr, cv::TermCriteria crit)
{

    if( src_roi.empty() )
        CV_Error( CV_StsBadArg, "The input image is empty" );
    if( src_roi.depth() != CV_8U || src_roi.channels() != 4 )
        CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
    CV_Assert( (src_roi.cols == dst_roi.cols) && (src_roi.rows == dst_roi.rows) &&
               (src_roi.cols == dstCoor_roi.cols) && (src_roi.rows == dstCoor_roi.rows));
    CV_Assert( !(dstCoor_roi.step & 0x3) );

    if( !(crit.type & cv::TermCriteria::MAX_ITER) )
        crit.maxCount = 5;
    int maxIter = std::min(std::max(crit.maxCount, 1), 100);
    float eps;
    if( !(crit.type & cv::TermCriteria::EPS) )
        eps = 1.f;
    eps = (float)std::max(crit.epsilon, 0.0);

    int tab[512];
    for(int i = 0; i < 512; i++)
        tab[i] = (i - 255) * (i - 255);
    uchar *sptr = src_roi.data;
    uchar *dptr = dst_roi.data;
    short *dCoorptr = (short *)dstCoor_roi.data;
    int sstep = (int)src_roi.step;
    int dstep = (int)dst_roi.step;
    int dCoorstep = (int)dstCoor_roi.step >> 1;
    cv::Size size = src_roi.size();

    for(int i = 0; i < size.height; i++, sptr += sstep - (size.width << 2),
            dptr += dstep - (size.width << 2), dCoorptr += dCoorstep - (size.width << 1))
    {
        for(int j = 0; j < size.width; j++, sptr += 4, dptr += 4, dCoorptr += 2)
        {
            *((COOR *)dCoorptr) = do_meanShift(j, i, sptr, dptr, sstep, size, sp, sr, maxIter, eps, tab);
        }
    }

}

PARAM_TEST_CASE(ImgprocTestBase, MatType, MatType, MatType, MatType, MatType, bool)
{
    int type1, type2, type3, type4, type5;
    cv::Scalar val;
    // set up roi
    int roicols;
    int roirows;
    int src1x;
    int src1y;
    int src2x;
    int src2y;
    int dstx;
    int dsty;
    int dst1x;
    int dst1y;
    int maskx;
    int masky;

    //mat
    cv::Mat mat1;
    cv::Mat mat2;
    cv::Mat mask;
    cv::Mat dst;
    cv::Mat dst1; //bak, for two outputs

    //mat with roi
    cv::Mat mat1_roi;
    cv::Mat mat2_roi;
    cv::Mat mask_roi;
    cv::Mat dst_roi;
    cv::Mat dst1_roi; //bak
    //std::vector<cv::ocl::Info> oclinfo;
    //ocl mat
    cv::ocl::oclMat clmat1;
    cv::ocl::oclMat clmat2;
    cv::ocl::oclMat clmask;
    cv::ocl::oclMat cldst;
    cv::ocl::oclMat cldst1; //bak

    //ocl mat with roi
    cv::ocl::oclMat clmat1_roi;
    cv::ocl::oclMat clmat2_roi;
    cv::ocl::oclMat clmask_roi;
    cv::ocl::oclMat cldst_roi;
    cv::ocl::oclMat cldst1_roi;

    virtual void SetUp()
    {
        type1 = GET_PARAM(0);
        type2 = GET_PARAM(1);
        type3 = GET_PARAM(2);
        type4 = GET_PARAM(3);
        type5 = GET_PARAM(4);
        cv::RNG &rng = TS::ptr()->get_rng();
        cv::Size size(MWIDTH, MHEIGHT);
        double min = 1, max = 20;
        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
        ////if you want to use undefault device, set it here
        ////setDevice(oclinfo[0]);

        if(type1 != nulltype)
        {
            mat1 = randomMat(rng, size, type1, min, max, false);
            clmat1 = mat1;
        }
        if(type2 != nulltype)
        {
            mat2 = randomMat(rng, size, type2, min, max, false);
            clmat2 = mat2;
        }
        if(type3 != nulltype)
        {
            dst  = randomMat(rng, size, type3, min, max, false);
            cldst = dst;
        }
        if(type4 != nulltype)
        {
            dst1 = randomMat(rng, size, type4, min, max, false);
            cldst1 = dst1;
        }
        if(type5 != nulltype)
        {
            mask = randomMat(rng, size, CV_8UC1, 0, 2,  false);
            cv::threshold(mask, mask, 0.5, 255., type5);
            clmask = mask;
        }
        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));
    }

    void random_roi()
    {     
#ifdef RANDOMROI
        //randomize ROI
		cv::RNG &rng = TS::ptr()->get_rng();
        roicols = rng.uniform(1, mat1.cols);
        roirows = rng.uniform(1, mat1.rows);
        src1x   = rng.uniform(0, mat1.cols - roicols);
        src1y   = rng.uniform(0, mat1.rows - roirows);
        src2x   = rng.uniform(0, mat2.cols - roicols);
        src2y   = rng.uniform(0, mat2.rows - roirows);
        dstx    = rng.uniform(0, dst.cols  - roicols);
        dsty    = rng.uniform(0, dst.rows  - roirows);
        dst1x    = rng.uniform(0, dst1.cols  - roicols);
        dst1y    = rng.uniform(0, dst1.rows  - roirows);
        maskx   = rng.uniform(0, mask.cols - roicols);
        masky   = rng.uniform(0, mask.rows - roirows);
#else
        roicols = mat1.cols;
        roirows = mat1.rows;
        src1x = 0;
        src1y = 0;
        src2x = 0;
        src2y = 0;
        dstx = 0;
        dsty = 0;
        dst1x = 0;
        dst1y = 0;
        maskx = 0;
        masky = 0;
#endif


        if(type1 != nulltype)
        {
            mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
            clmat1_roi = clmat1(Rect(src1x, src1y, roicols, roirows));
        }
        if(type2 != nulltype)
        {
            mat2_roi = mat2(Rect(src2x, src2y, roicols, roirows));
            clmat2_roi = clmat2(Rect(src2x, src2y, roicols, roirows));
        }
        if(type3 != nulltype)
        {
            dst_roi  = dst(Rect(dstx, dsty, roicols, roirows));
            cldst_roi = cldst(Rect(dstx, dsty, roicols, roirows));
        }
        if(type4 != nulltype)
        {
            dst1_roi = dst1(Rect(dst1x, dst1y, roicols, roirows));
            cldst1_roi = cldst1(Rect(dst1x, dst1y, roicols, roirows));
        }
        if(type5 != nulltype)
        {
            mask_roi = mask(Rect(maskx, masky, roicols, roirows));
            clmask_roi = clmask(Rect(maskx, masky, roicols, roirows));
        }
    }
};
////////////////////////////////equalizeHist//////////////////////////////////////////

struct equalizeHist : ImgprocTestBase {};

TEST_P(equalizeHist, Mat)
{
    if (mat1.type() != CV_8UC1 || mat1.type() != dst.type())
    {
        cout << "Unsupported type" << endl;
        EXPECT_DOUBLE_EQ(0.0, 0.0);
    }
    else
    {
        for(int j = 0; j < LOOP_TIMES; j++)
        {
            random_roi();
            cv::equalizeHist(mat1_roi, dst_roi);
            cv::ocl::equalizeHist(clmat1_roi, cldst_roi);
            cv::Mat cpu_cldst;
            cldst.download(cpu_cldst);
            char sss[1024];
            sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);
            EXPECT_MAT_NEAR(dst, cpu_cldst, 1.1, sss);
        }
    }
}





////////////////////////////////bilateralFilter////////////////////////////////////////////

struct bilateralFilter : ImgprocTestBase {};

TEST_P(bilateralFilter, Mat)
{
    double sigmacolor = 50.0;
    int radius = 9;
    int d = 2 * radius + 1;
    double sigmaspace = 20.0;
    int bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE/*,BORDER_REFLECT,BORDER_WRAP,BORDER_REFLECT_101*/};
    //const char* borderstr[]={"BORDER_CONSTANT", "BORDER_REPLICATE"/*, "BORDER_REFLECT","BORDER_WRAP","BORDER_REFLECT_101"*/};

    if (mat1.type() != CV_8UC1 || mat1.type() != dst.type())
    {
        cout << "Unsupported type" << endl;
        EXPECT_DOUBLE_EQ(0.0, 0.0);
    }
    else
    {
        for(int i = 0; i < sizeof(bordertype) / sizeof(int); i++)
            for(int j = 0; j < LOOP_TIMES; j++)
            {
                random_roi();
                cv::bilateralFilter(mat1_roi, dst_roi, d, sigmacolor, sigmaspace, bordertype[i]);
                cv::ocl::bilateralFilter(clmat1_roi, cldst_roi, d, sigmacolor, sigmaspace, bordertype[i]);

                cv::Mat cpu_cldst;
                cldst.download(cpu_cldst);
                char sss[1024];
                sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);

                EXPECT_MAT_NEAR(dst, cpu_cldst, 0.0, sss);
            }
    }
}



////////////////////////////////copyMakeBorder////////////////////////////////////////////

struct CopyMakeBorder : ImgprocTestBase {};

TEST_P(CopyMakeBorder, Mat)
{
    int bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE/*,BORDER_REFLECT,BORDER_WRAP,BORDER_REFLECT_101*/};
    //const char* borderstr[]={"BORDER_CONSTANT", "BORDER_REPLICATE"/*, "BORDER_REFLECT","BORDER_WRAP","BORDER_REFLECT_101"*/};

    if ((mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32SC1) || mat1.type() != dst.type())
    {
        cout << "Unsupported type" << endl;
        EXPECT_DOUBLE_EQ(0.0, 0.0);
    }
    else
    {
        for(int i = 0; i < sizeof(bordertype) / sizeof(int); i++)
            for(int j = 0; j < LOOP_TIMES; j++)
            {
                random_roi();
                cv::copyMakeBorder(mat1_roi, dst_roi, 7, 5, 5, 7, bordertype[i], cv::Scalar(1.0));
                cv::ocl::copyMakeBorder(clmat1_roi, cldst_roi, 7, 5, 5, 7,  bordertype[i], cv::Scalar(1.0));

                cv::Mat cpu_cldst;
                cldst.download(cpu_cldst);
                char sss[1024];
                sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);

                EXPECT_MAT_NEAR(dst, cpu_cldst, 0.0, sss);
            }
    }
}



////////////////////////////////cornerMinEigenVal//////////////////////////////////////////

struct cornerMinEigenVal : ImgprocTestBase {};

TEST_P(cornerMinEigenVal, Mat)
{
    for(int j = 0; j < LOOP_TIMES; j++)
    {

        random_roi();
        int blockSize = 7, apertureSize = 1 + 2 * (rand() % 4);
        //int borderType = cv::BORDER_CONSTANT;
        //int borderType = cv::BORDER_REPLICATE;
        int borderType = cv::BORDER_REFLECT;
        cv::cornerMinEigenVal(mat1_roi, dst_roi, blockSize, apertureSize, borderType);
        cv::ocl::cornerMinEigenVal(clmat1_roi, cldst_roi, blockSize, apertureSize, borderType);


        cv::Mat cpu_cldst;
        cldst.download(cpu_cldst);

        char sss[1024];
        sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);
        EXPECT_MAT_NEAR(dst, cpu_cldst, 1, sss);
    }
}



////////////////////////////////cornerHarris//////////////////////////////////////////

struct cornerHarris : ImgprocTestBase {};

TEST_P(cornerHarris, Mat)
{
    for(int j = 0; j < LOOP_TIMES; j++)
    {

        random_roi();
        int blockSize = 7, apertureSize = 3; //1 + 2 * (rand() % 4);
        double k = 2;
        //int borderType = cv::BORDER_CONSTANT;
        //int borderType = cv::BORDER_REPLICATE;
        int borderType = cv::BORDER_REFLECT;
        cv::cornerHarris(mat1_roi, dst_roi, blockSize, apertureSize, k, borderType);
        cv::ocl::cornerHarris(clmat1_roi, cldst_roi, blockSize, apertureSize, k, borderType);
        cv::Mat cpu_cldst;
        cldst.download(cpu_cldst);

        char sss[1024];
        sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);

        EXPECT_MAT_NEAR(dst, cpu_cldst, 1, sss);
    }
}


////////////////////////////////integral/////////////////////////////////////////////////

struct integral : ImgprocTestBase {};

TEST_P(integral, Mat)
{
    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();

        cv::ocl::integral(clmat1_roi, cldst_roi, cldst1_roi);
        cv::integral(mat1_roi, dst_roi, dst1_roi);

        cv::Mat cpu_cldst, cpu_cldst1;
        cldst.download(cpu_cldst);
        cldst1.download(cpu_cldst1);
        char sss[1024];
        sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,dst1x=%d,dst1y=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, dst1x, dst1y, maskx, masky, src2x, src2y);

        EXPECT_MAT_NEAR(dst, cpu_cldst, 0.0, sss);
        EXPECT_MAT_NEAR(dst1, cpu_cldst1, 0.0, sss);
    }
}


/////////////////////////////////////////////////////////////////////////////////////////////////
// warpAffine  & warpPerspective

PARAM_TEST_CASE(WarpTestBase, MatType, int)
{
    int type;
    cv::Size size;
    int interpolation;

    //src mat
    cv::Mat mat1;
    cv::Mat dst;

    // set up roi
    int src_roicols;
    int src_roirows;
    int dst_roicols;
    int dst_roirows;
    int src1x;
    int src1y;
    int dstx;
    int dsty;


    //src mat with roi
    cv::Mat mat1_roi;
    cv::Mat dst_roi;
    //std::vector<cv::ocl::Info> oclinfo;
    //ocl dst mat for testing
    cv::ocl::oclMat gdst_whole;

    //ocl mat with roi
    cv::ocl::oclMat gmat1;
    cv::ocl::oclMat gdst;

    virtual void SetUp()
    {
        type = GET_PARAM(0);
        //dsize = GET_PARAM(1);
        interpolation = GET_PARAM(1);

        cv::RNG &rng = TS::ptr()->get_rng();
        size = cv::Size(MWIDTH, MHEIGHT);

        mat1 = randomMat(rng, size, type, 5, 16, false);
        dst  = randomMat(rng, size, type, 5, 16, false);

        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
        ////if you want to use undefault device, set it here
        ////setDevice(oclinfo[0]);
    }

    void random_roi()
    {       
#ifdef RANDOMROI
        //randomize ROI
		cv::RNG &rng = TS::ptr()->get_rng();
        src_roicols = rng.uniform(1, mat1.cols);
        src_roirows = rng.uniform(1, mat1.rows);
        dst_roicols = rng.uniform(1, dst.cols);
        dst_roirows = rng.uniform(1, dst.rows);
        src1x   = rng.uniform(0, mat1.cols - src_roicols);
        src1y   = rng.uniform(0, mat1.rows - src_roirows);
        dstx    = rng.uniform(0, dst.cols  - dst_roicols);
        dsty    = rng.uniform(0, dst.rows  - dst_roirows);
#else
        src_roicols = mat1.cols;
        src_roirows = mat1.rows;
        dst_roicols = dst.cols;
        dst_roirows = dst.rows;
        src1x   = 0;
        src1y   = 0;
        dstx    = 0;
        dsty    = 0;
#endif


        mat1_roi = mat1(Rect(src1x, src1y, src_roicols, src_roirows));
        dst_roi  = dst(Rect(dstx, dsty, dst_roicols, dst_roirows));

        gdst_whole = dst;
        gdst = gdst_whole(Rect(dstx, dsty, dst_roicols, dst_roirows));


        gmat1 = mat1_roi;
    }

};

/////warpAffine

struct WarpAffine : WarpTestBase {};

TEST_P(WarpAffine, Mat)
{
    static const double coeffs[2][3] =
    {
        {cos(3.14 / 6), -sin(3.14 / 6), 100.0},
        {sin(3.14 / 6), cos(3.14 / 6), -100.0}
    };
    Mat M(2, 3, CV_64F, (void *)coeffs);

    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();

        cv::warpAffine(mat1_roi, dst_roi, M, size, interpolation);
        cv::ocl::warpAffine(gmat1, gdst, M, size, interpolation);

        cv::Mat cpu_dst;
        gdst_whole.download(cpu_dst);
        char sss[1024];
        sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, src1x, src1y, dstx, dsty);

        EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
    }

}


// warpPerspective

struct WarpPerspective : WarpTestBase {};

TEST_P(WarpPerspective, Mat)
{
    static const double coeffs[3][3] =
    {
        {cos(3.14 / 6), -sin(3.14 / 6), 100.0},
        {sin(3.14 / 6), cos(3.14 / 6), -100.0},
        {0.0, 0.0, 1.0}
    };
    Mat M(3, 3, CV_64F, (void *)coeffs);

    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();

        cv::warpPerspective(mat1_roi, dst_roi, M, size, interpolation);
        cv::ocl::warpPerspective(gmat1, gdst, M, size, interpolation);

        cv::Mat cpu_dst;
        gdst_whole.download(cpu_dst);
        char sss[1024];
        sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, src1x, src1y, dstx, dsty);

        EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
    }

}

/////////////////////////////////////////////////////////////////////////////////////////////////
// remap
//////////////////////////////////////////////////////////////////////////////////////////////////

PARAM_TEST_CASE(Remap, MatType, MatType, MatType, int, int)
{
    int srcType;
    // int dstType;
    int map1Type;
    int map2Type;
    cv::Scalar val;

    int interpolation;
    int bordertype;
    //Scalar& borderValue;

    cv::Mat src;
    cv::Mat dst;
    cv::Mat map1;
    cv::Mat map2;

    //std::vector<cv::ocl::Info> oclinfo;
    
    int src_roicols;
    int src_roirows;
    int dst_roicols;
    int dst_roirows;
    int map1_roicols;
    int map1_roirows;
    int map2_roicols;
    int map2_roirows;
    int srcx;
    int srcy;
    int dstx;
    int dsty;
    int map1x;
    int map1y;
    int map2x;
    int map2y;

    cv::Mat src_roi;
    cv::Mat dst_roi;
    cv::Mat map1_roi;
    cv::Mat map2_roi;

    //ocl mat for testing
    cv::ocl::oclMat gdst;
    cv::ocl::oclMat gsrc;
    cv::ocl::oclMat gmap1;
    cv::ocl::oclMat gmap2;

    //ocl mat with roi
    cv::ocl::oclMat gsrc_roi;
    cv::ocl::oclMat gdst_roi;
    cv::ocl::oclMat gmap1_roi;
    cv::ocl::oclMat gmap2_roi;

    virtual void SetUp()
    {
        srcType = GET_PARAM(0);
        //  dstType = GET_PARAM(1);
        map1Type = GET_PARAM(1);
        map2Type = GET_PARAM(2);
        interpolation = GET_PARAM(3);
        bordertype = GET_PARAM(4);
        // borderValue = GET_PARAM(6);

        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);

        cv::RNG& rng = TS::ptr()->get_rng();
        //cv::Size size = cv::Size(20, 20);
        cv::Size srcSize = cv::Size(100, 100);
        cv::Size dstSize = cv::Size(100, 100);
        cv::Size map1Size = cv::Size(100, 100);
        double min = 5, max = 16;

        if(srcType != nulltype)
        {
            src = randomMat(rng, srcSize, srcType, min, max, false);
            gsrc = src;
        }
        if((map1Type == CV_16SC2 && map2Type == nulltype) || (map1Type == CV_32FC2&& map2Type == nulltype))
        {
            map1 = randomMat(rng, map1Size, map1Type, min, max, false);
            gmap1 = map1;

        }
        else if (map1Type == CV_32FC1 && map2Type == CV_32FC1)
        {
            map1 = randomMat(rng, map1Size, map1Type, min, max, false);
            map2 = randomMat(rng, map1Size, map1Type, min, max, false);
            gmap1 = map1;
            gmap2 = map2;
        }

        else
            cout<<"The wrong input type"<<endl;

        dst = randomMat(rng, map1Size, srcType, min, max, false);
        gdst = dst;
    }
    void random_roi()
    {
        cv::RNG& rng = TS::ptr()->get_rng();

        dst_roicols = rng.uniform(1, dst.cols);
        dst_roirows = rng.uniform(1, dst.rows);

        src_roicols = rng.uniform(1, src.cols);
        src_roirows = rng.uniform(1, src.rows);

         
        srcx = rng.uniform(0, src.cols - src_roicols);
        srcy = rng.uniform(0, src.rows - src_roirows);
        dstx = rng.uniform(0, dst.cols - dst_roicols);
        dsty = rng.uniform(0, dst.rows - dst_roirows);
        map1_roicols = dst_roicols;
        map1_roirows = dst_roirows;
        map2_roicols = dst_roicols;
        map2_roirows = dst_roirows;
        map1x = dstx;
        map1y = dsty;
        map2x = dstx;
        map2y = dsty;

        switch (src.channels())
        {
            case 1:
                val = cv::Scalar(rng.uniform(0.0, 10.0), 0, 0, 0);
                break;
            case 2:
                val = cv::Scalar(rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), 0, 0);
                break;
            case 3:
                val = cv::Scalar(rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), 0);
                break;
            case 4:
                val = cv::Scalar(rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0), rng.uniform(0.0, 10.0));
                break;
        }
        if(srcType != nulltype)
        {
            src_roi = src(Rect(srcx,srcy,src_roicols,src_roirows));
            gsrc_roi = gsrc(Rect(srcx,srcy,src_roicols,src_roirows));
            gsrc_roi = src_roi;
        }
        if((map1Type == CV_16SC2 && map2Type == nulltype) || (map1Type == CV_32FC2&& map2Type == nulltype))
        {
            map1_roi = map1(Rect(map1x,map1y,map1_roicols,map1_roirows));
            gmap1_roi = map1_roi;
        }

        else if (map1Type == CV_32FC1 && map2Type == CV_32FC1)
        {
            map1_roi = map1(Rect(map1x,map1y,map1_roicols,map1_roirows));
            gmap1_roi = map1_roi;
            map2_roi = map2(Rect(map2x,map2y,map2_roicols,map2_roirows));
            gmap2_roi = map2_roi;
        }
        dst_roi = dst(Rect(dstx, dsty, dst_roicols, dst_roirows));
        gdst_roi = gdst(Rect(dstx,dsty,dst_roicols,dst_roirows));

   
    }
};

TEST_P(Remap, Mat)
{
    if((interpolation == 1 && map1Type == CV_16SC2) ||(interpolation == 1 && map1Type == CV_16SC1 && map2Type == CV_16SC1))
    {
        cout << "LINEAR don't support the map1Type and map2Type" << endl;
        return;                
    }
    int bordertype[] = {cv::BORDER_CONSTANT,cv::BORDER_REPLICATE/*,BORDER_REFLECT,BORDER_WRAP,BORDER_REFLECT_101*/};
    const char* borderstr[]={"BORDER_CONSTANT", "BORDER_REPLICATE"/*, "BORDER_REFLECT","BORDER_WRAP","BORDER_REFLECT_101"*/};
    // for(int i = 0; i < sizeof(bordertype)/sizeof(int); i++)
    for(int j=0; j<1; j++)
    {
        random_roi();
        cv::remap(src_roi, dst_roi, map1_roi, map2_roi, interpolation, bordertype[0], val);
        cv::ocl::remap(gsrc_roi, gdst_roi, gmap1_roi, gmap2_roi, interpolation, bordertype[0], val);
        cv::Mat cpu_dst;
        gdst_roi.download(cpu_dst);

        char sss[1024];
        sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, srcx, srcy, dstx, dsty);

   
        EXPECT_MAT_NEAR(dst_roi, cpu_dst, 1.0, sss);
 
    }
}



/////////////////////////////////////////////////////////////////////////////////////////////////
// resize

PARAM_TEST_CASE(Resize, MatType, cv::Size, double, double, int)
{
    int type;
    cv::Size dsize;
    double fx, fy;
    int interpolation;

    //src mat
    cv::Mat mat1;
    cv::Mat dst;

    // set up roi
    int src_roicols;
    int src_roirows;
    int dst_roicols;
    int dst_roirows;
    int src1x;
    int src1y;
    int dstx;
    int dsty;

    //std::vector<cv::ocl::Info> oclinfo;
    //src mat with roi
    cv::Mat mat1_roi;
    cv::Mat dst_roi;

    //ocl dst mat for testing
    cv::ocl::oclMat gdst_whole;

    //ocl mat with roi
    cv::ocl::oclMat gmat1;
    cv::ocl::oclMat gdst;

    virtual void SetUp()
    {
        type = GET_PARAM(0);
        dsize = GET_PARAM(1);
        fx = GET_PARAM(2);
        fy = GET_PARAM(3);
        interpolation = GET_PARAM(4);

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

        cv::Size size(MWIDTH, MHEIGHT);

        if(dsize == cv::Size() && !(fx > 0 && fy > 0))
        {
            cout << "invalid dsize and fx fy" << endl;
            return;
        }

        if(dsize == cv::Size())
        {
            dsize.width = (int)(size.width * fx);
            dsize.height = (int)(size.height * fy);
        }

        mat1 = randomMat(rng, size, type, 5, 16, false);
        dst  = randomMat(rng, dsize, type, 5, 16, false);

        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
        ////if you want to use undefault device, set it here
        ////setDevice(oclinfo[0]);
    }

    void random_roi()
    {        
#ifdef RANDOMROI
        //randomize ROI
		cv::RNG &rng = TS::ptr()->get_rng();
        src_roicols = rng.uniform(1, mat1.cols);
        src_roirows = rng.uniform(1, mat1.rows);
        dst_roicols = rng.uniform(1, dst.cols);
        dst_roirows = rng.uniform(1, dst.rows);
        src1x   = rng.uniform(0, mat1.cols - src_roicols);
        src1y   = rng.uniform(0, mat1.rows - src_roirows);
        dstx    = rng.uniform(0, dst.cols  - dst_roicols);
        dsty    = rng.uniform(0, dst.rows  - dst_roirows);
#else
        src_roicols = mat1.cols;
        src_roirows = mat1.rows;
        dst_roicols = dst.cols;
        dst_roirows = dst.rows;
        src1x   = 0;
        src1y   = 0;
        dstx    = 0;
        dsty    = 0;
#endif

        mat1_roi = mat1(Rect(src1x, src1y, src_roicols, src_roirows));
        dst_roi  = dst(Rect(dstx, dsty, dst_roicols, dst_roirows));

        gdst_whole = dst;
        gdst = gdst_whole(Rect(dstx, dsty, dst_roicols, dst_roirows));


        gmat1 = mat1_roi;
    }

};

TEST_P(Resize, Mat)
{
    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();

        // cv::resize(mat1_roi, dst_roi, dsize, fx, fy, interpolation);
        // cv::ocl::resize(gmat1, gdst, dsize, fx, fy, interpolation);

        cv::resize(mat1_roi, dst_roi, dsize, fx, fy, interpolation);
        cv::ocl::resize(gmat1, gdst, dsize, fx, fy, interpolation);

        cv::Mat cpu_dst;
        gdst_whole.download(cpu_dst);
        char sss[1024];
        sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, src1x, src1y, dstx, dsty);

        EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
    }

}


/////////////////////////////////////////////////////////////////////////////////////////////////
//threshold

PARAM_TEST_CASE(Threshold, MatType, ThreshOp)
{
    int type;
    int threshOp;

    //src mat
    cv::Mat mat1;
    cv::Mat dst;

    // set up roi
    int roicols;
    int roirows;
    int src1x;
    int src1y;
    int dstx;
    int dsty;

    //src mat with roi
    cv::Mat mat1_roi;
    cv::Mat dst_roi;
    //std::vector<cv::ocl::Info> oclinfo;
    //ocl dst mat for testing
    cv::ocl::oclMat gdst_whole;

    //ocl mat with roi
    cv::ocl::oclMat gmat1;
    cv::ocl::oclMat gdst;

    virtual void SetUp()
    {
        type = GET_PARAM(0);
        threshOp = GET_PARAM(1);

        cv::RNG &rng = TS::ptr()->get_rng();
        cv::Size size(MWIDTH, MHEIGHT);

        mat1 = randomMat(rng, size, type, 5, 16, false);
        dst  = randomMat(rng, size, type, 5, 16, false);

        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
        ////if you want to use undefault device, set it here
        ////setDevice(oclinfo[0]);
    }

    void random_roi()
    {       
#ifdef RANDOMROI
        //randomize ROI
		cv::RNG &rng = TS::ptr()->get_rng();
        roicols = rng.uniform(1, mat1.cols);
        roirows = rng.uniform(1, mat1.rows);
        src1x   = rng.uniform(0, mat1.cols - roicols);
        src1y   = rng.uniform(0, mat1.rows - roirows);
        dstx    = rng.uniform(0, dst.cols  - roicols);
        dsty    = rng.uniform(0, dst.rows  - roirows);
#else
        roicols = mat1.cols;
        roirows = mat1.rows;
        src1x   = 0;
        src1y   = 0;
        dstx    = 0;
        dsty    = 0;
#endif

        mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
        dst_roi  = dst(Rect(dstx, dsty, roicols, roirows));

        gdst_whole = dst;
        gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));


        gmat1 = mat1_roi;
    }

};

TEST_P(Threshold, Mat)
{
    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();
        double maxVal = randomDouble(20.0, 127.0);
        double thresh = randomDouble(0.0, maxVal);

        cv::threshold(mat1_roi, dst_roi, thresh, maxVal, threshOp);
        cv::ocl::threshold(gmat1, gdst, thresh, maxVal, threshOp);

        cv::Mat cpu_dst;
        gdst_whole.download(cpu_dst);

        //EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5)
        char sss[1024];
        sprintf(sss, "roicols=%d,roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x , src1y, dstx, dsty);

        EXPECT_MAT_NEAR(dst, cpu_dst, 1, sss);
    }

}

PARAM_TEST_CASE(meanShiftTestBase, MatType, MatType, int, int, cv::TermCriteria)
{
    int type, typeCoor;
    int sp, sr;
    cv::TermCriteria crit;
    //src mat
    cv::Mat src;
    cv::Mat dst;
    cv::Mat dstCoor;

    //set up roi
    int roicols;
    int roirows;
    int srcx;
    int srcy;
    int dstx;
    int dsty;

    //src mat with roi
    cv::Mat src_roi;
    cv::Mat dst_roi;
    cv::Mat dstCoor_roi;

    //ocl dst mat
    cv::ocl::oclMat gdst;
    cv::ocl::oclMat gdstCoor;

    //std::vector<cv::ocl::Info> oclinfo;
    //ocl mat with roi
    cv::ocl::oclMat gsrc_roi;
    cv::ocl::oclMat gdst_roi;
    cv::ocl::oclMat gdstCoor_roi;

    virtual void SetUp()
    {
        type     = GET_PARAM(0);
        typeCoor = GET_PARAM(1);
        sp       = GET_PARAM(2);
        sr       = GET_PARAM(3);
        crit     = GET_PARAM(4);

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

        // MWIDTH=256, MHEIGHT=256. defined in utility.hpp
        cv::Size size = cv::Size(MWIDTH, MHEIGHT);

        src = randomMat(rng, size, type, 5, 16, false);
        dst = randomMat(rng, size, type, 5, 16, false);
        dstCoor = randomMat(rng, size, typeCoor, 5, 16, false);

        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
        ////if you want to use undefault device, set it here
        ////setDevice(oclinfo[0]);
    }

    void random_roi()
    {
#ifdef RANDOMROI
        cv::RNG &rng = TS::ptr()->get_rng();

        //randomize ROI
        roicols = rng.uniform(1, src.cols);
        roirows = rng.uniform(1, src.rows);
        srcx = rng.uniform(0, src.cols - roicols);
        srcy = rng.uniform(0, src.rows - roirows);
        dstx = rng.uniform(0, dst.cols - roicols);
        dsty = rng.uniform(0, dst.rows - roirows);
#else
        roicols = src.cols;
        roirows = src.rows;
        srcx = 0;
        srcy = 0;
        dstx = 0;
        dsty = 0;
#endif
        src_roi = src(Rect(srcx, srcy, roicols, roirows));
        dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
        dstCoor_roi = dstCoor(Rect(dstx, dsty, roicols, roirows));

        gdst = dst;
        gdstCoor = dstCoor;

        gsrc_roi = src_roi;
        gdst_roi = gdst(Rect(dstx, dsty, roicols, roirows));  //gdst_roi
        gdstCoor_roi = gdstCoor(Rect(dstx, dsty, roicols, roirows));
    }
};

/////////////////////////meanShiftFiltering/////////////////////////////
struct meanShiftFiltering : meanShiftTestBase {};

TEST_P(meanShiftFiltering, Mat)
{

    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();

        cv::Mat cpu_gdst;
        gdst.download(cpu_gdst);

        meanShiftFiltering_(src_roi, dst_roi, sp, sr, crit);
        cv::ocl::meanShiftFiltering(gsrc_roi, gdst_roi, sp, sr, crit);

        gdst.download(cpu_gdst);

        char sss[1024];
        sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d,dstx=%d,dsty=%d\n", roicols, roirows, srcx, srcy, dstx, dsty);
        EXPECT_MAT_NEAR(dst, cpu_gdst, 0.0, sss);

    }
}

///////////////////////////meanShiftProc//////////////////////////////////
struct meanShiftProc : meanShiftTestBase {};

TEST_P(meanShiftProc, Mat)
{

    for(int j = 0; j < LOOP_TIMES; j++)
    {
        random_roi();

        cv::Mat cpu_gdst;
        cv::Mat cpu_gdstCoor;

        meanShiftProc_(src_roi, dst_roi, dstCoor_roi, sp, sr, crit);
        cv::ocl::meanShiftProc(gsrc_roi, gdst_roi, gdstCoor_roi, sp, sr, crit);

        gdst.download(cpu_gdst);
        gdstCoor.download(cpu_gdstCoor);

        char sss[1024];
        sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d,dstx=%d,dsty=%d\n", roicols, roirows, srcx, srcy, dstx, dsty);
        EXPECT_MAT_NEAR(dst, cpu_gdst, 0.0, sss);
        EXPECT_MAT_NEAR(dstCoor, cpu_gdstCoor, 0.0, sss);
    }
}

INSTANTIATE_TEST_CASE_P(ImgprocTestBase, equalizeHist, Combine(
                            ONE_TYPE(CV_8UC1),
                            NULL_TYPE,
                            ONE_TYPE(CV_8UC1),
                            NULL_TYPE,
                            NULL_TYPE,
                            Values(false))); // Values(false) is the reserved parameter

//INSTANTIATE_TEST_CASE_P(ImgprocTestBase, bilateralFilter, Combine(
//	ONE_TYPE(CV_8UC1),
//	NULL_TYPE,
//	ONE_TYPE(CV_8UC1),
//	NULL_TYPE,
//	NULL_TYPE,
//	Values(false))); // Values(false) is the reserved parameter
//
//
//INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine(
//	Values(CV_8UC1, CV_8UC4, CV_32SC1),
//	NULL_TYPE,
//	Values(CV_8UC1,CV_8UC4,CV_32SC1),
//	NULL_TYPE,
//	NULL_TYPE,
//	Values(false))); // Values(false) is the reserved parameter
//
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, cornerMinEigenVal, Combine(
	Values(CV_8UC1,CV_32FC1),
	NULL_TYPE,
	ONE_TYPE(CV_32FC1),
	NULL_TYPE,
	NULL_TYPE,
	Values(false))); // Values(false) is the reserved parameter

INSTANTIATE_TEST_CASE_P(ImgprocTestBase, cornerHarris, Combine(
	Values(CV_8UC1,CV_32FC1),
	NULL_TYPE,
	ONE_TYPE(CV_32FC1),
	NULL_TYPE,
	NULL_TYPE,
	Values(false))); // Values(false) is the reserved parameter


INSTANTIATE_TEST_CASE_P(ImgprocTestBase, integral, Combine(
                            ONE_TYPE(CV_8UC1),
                            NULL_TYPE,
                            ONE_TYPE(CV_32SC1),
                            ONE_TYPE(CV_32FC1),
                            NULL_TYPE,
                            Values(false))); // Values(false) is the reserved parameter

INSTANTIATE_TEST_CASE_P(Imgproc, WarpAffine, Combine(
                            Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
                            Values((MatType)cv::INTER_NEAREST, (MatType)cv::INTER_LINEAR,
                                    (MatType)cv::INTER_CUBIC, (MatType)(cv::INTER_NEAREST | cv::WARP_INVERSE_MAP),
                                    (MatType)(cv::INTER_LINEAR | cv::WARP_INVERSE_MAP), (MatType)(cv::INTER_CUBIC | cv::WARP_INVERSE_MAP))));


INSTANTIATE_TEST_CASE_P(Imgproc, WarpPerspective, Combine
                        (Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
                         Values((MatType)cv::INTER_NEAREST, (MatType)cv::INTER_LINEAR,
                                (MatType)cv::INTER_CUBIC, (MatType)(cv::INTER_NEAREST | cv::WARP_INVERSE_MAP),
                                (MatType)(cv::INTER_LINEAR | cv::WARP_INVERSE_MAP), (MatType)(cv::INTER_CUBIC | cv::WARP_INVERSE_MAP))));


INSTANTIATE_TEST_CASE_P(Imgproc, Resize, Combine(
                            Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),  Values(cv::Size()),
                            Values(0.5, 1.5, 2), Values(0.5, 1.5, 2), Values((MatType)cv::INTER_NEAREST, (MatType)cv::INTER_LINEAR)));


INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(
                            Values(CV_8UC1, CV_32FC1), Values(ThreshOp(cv::THRESH_BINARY),
                                    ThreshOp(cv::THRESH_BINARY_INV), ThreshOp(cv::THRESH_TRUNC),
                                    ThreshOp(cv::THRESH_TOZERO), ThreshOp(cv::THRESH_TOZERO_INV))));


INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftFiltering, Combine(
                            ONE_TYPE(CV_8UC4),
                            ONE_TYPE(CV_16SC2),
                            Values(5),
                            Values(6),
                            Values(cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1))
                        ));
                        

INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftProc, Combine(
       ONE_TYPE(CV_8UC4),
       ONE_TYPE(CV_16SC2),
       Values(5),
       Values(6),
       Values(cv::TermCriteria(cv::TermCriteria::COUNT+cv::TermCriteria::EPS, 5, 1))
));

INSTANTIATE_TEST_CASE_P(Imgproc, Remap, Combine(
            Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
            Values(CV_16SC2, CV_32FC2), NULL_TYPE,
            Values((int)cv::INTER_NEAREST, (int)cv::INTER_LINEAR), 
            Values((int)cv::BORDER_CONSTANT)));
#endif // HAVE_OPENCL