root/modules/core/test/test_umat.cpp

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DEFINITIONS

This source file includes following definitions.
  1. PARAM_TEST_CASE
  2. TEST_P
  3. TEST_P
  4. TEST_P
  5. TEST_P
  6. TEST_P
  7. PARAM_TEST_CASE
  8. TEST_P
  9. PARAM_TEST_CASE
  10. TEST_P
  11. TEST_P
  12. TEST_P
  13. PARAM_TEST_CASE
  14. TEST_P
  15. PARAM_TEST_CASE
  16. TEST_P
  17. TEST
  18. checkDiff
  19. checkDiffF
  20. TestUMat
  21. run
  22. TEST
  23. TEST
  24. TEST
  25. TEST
  26. TEST
  27. TEST
  28. TEST
  29. TEST
  30. TEST
  31. processData
  32. getResult
  33. TEST
  34. TEST
  35. TEST
  36. TEST

/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"

using namespace cvtest;
using namespace testing;
using namespace cv;

namespace cvtest {
namespace ocl {

#define UMAT_TEST_SIZES testing::Values(cv::Size(1, 1), cv::Size(1,128), cv::Size(128, 1), \
    cv::Size(128, 128), cv::Size(640, 480), cv::Size(751, 373), cv::Size(1200, 1200))

/////////////////////////////// Basic Tests ////////////////////////////////

PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
{
    Mat a;
    UMat ua;
    int type;
    int depth;
    int cn;
    Size size;
    bool useRoi;
    Size roi_size;
    Rect roi;

    virtual void SetUp()
    {
        depth = GET_PARAM(0);
        cn = GET_PARAM(1);
        size = GET_PARAM(2);
        useRoi = GET_PARAM(3);
        type = CV_MAKE_TYPE(depth, cn);
        a = randomMat(size, type, -100, 100);
        a.copyTo(ua);
        int roi_shift_x = randomInt(0, size.width-1);
        int roi_shift_y = randomInt(0, size.height-1);
        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
        roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
    }
};

TEST_P(UMatBasicTests, createUMat)
{
    if(useRoi)
    {
        ua = UMat(ua, roi);
    }
    int dims = randomInt(2,6);
    int _sz[CV_MAX_DIM];
    for( int i = 0; i<dims; i++)
    {
        _sz[i] = randomInt(1,50);
    }
    int *sz = _sz;
    int new_depth = randomInt(CV_8S, CV_64F);
    int new_cn = randomInt(1,4);
    ua.create(dims, sz, CV_MAKE_TYPE(new_depth, new_cn));

    for(int i = 0; i<dims; i++)
    {
        ASSERT_EQ(ua.size[i], sz[i]);
    }
    ASSERT_EQ(ua.dims, dims);
    ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
    Size new_size = randomSize(1, 1000);
    ua.create(new_size, CV_MAKE_TYPE(new_depth, new_cn) );
    ASSERT_EQ( ua.size(), new_size);
    ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
    ASSERT_EQ( ua.dims, 2);
}

TEST_P(UMatBasicTests, swap)
{
    Mat b = randomMat(size, type, -100, 100);
    UMat ub;
    b.copyTo(ub);
    if(useRoi)
    {
        ua = UMat(ua,roi);
        ub = UMat(ub,roi);
    }
    UMat uc = ua, ud = ub;
    swap(ua,ub);
    EXPECT_MAT_NEAR(ub,uc, 0);
    EXPECT_MAT_NEAR(ud, ua, 0);
}

TEST_P(UMatBasicTests, base)
{
    const int align_mask = 3;
    roi.x &= ~align_mask;
    roi.y &= ~align_mask;
    roi.width = (roi.width + align_mask) & ~align_mask;
    roi &= Rect(0, 0, ua.cols, ua.rows);

    if(useRoi)
    {
        ua = UMat(ua,roi);
    }
    UMat ub = ua.clone();
    EXPECT_MAT_NEAR(ub,ua,0);

    ASSERT_EQ(ua.channels(), cn);
    ASSERT_EQ(ua.depth(), depth);
    ASSERT_EQ(ua.type(), type);
    ASSERT_EQ(ua.elemSize(), a.elemSize());
    ASSERT_EQ(ua.elemSize1(), a.elemSize1());
    ASSERT_EQ(ub.empty(), ub.cols*ub.rows == 0);
    ub.release();
    ASSERT_TRUE( ub.empty() );
    if(useRoi && a.size() != ua.size())
    {
        ASSERT_EQ(ua.isSubmatrix(), true);
    }
    else
    {
        ASSERT_EQ(ua.isSubmatrix(), false);
    }

    int dims = randomInt(2,6);
    int sz[CV_MAX_DIM];
    size_t total = 1;
    for(int i = 0; i<dims; i++)
    {
        sz[i] = randomInt(1,45);
        total *= (size_t)sz[i];
    }
    int new_type = CV_MAKE_TYPE(randomInt(CV_8S,CV_64F),randomInt(1,4));
    ub = UMat(dims, sz, new_type);
    ASSERT_EQ(ub.total(), total);
}

TEST_P(UMatBasicTests, DISABLED_copyTo)
{
    UMat roi_ua;
    Mat roi_a;
    int i;
    if(useRoi)
    {
        roi_ua = UMat(ua, roi);
        roi_a = Mat(a, roi);
        roi_a.copyTo(roi_ua);
        EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
        roi_ua.copyTo(roi_a);
        EXPECT_MAT_NEAR(roi_ua, roi_a, 0);
        roi_ua.copyTo(ua);
        EXPECT_MAT_NEAR(roi_ua, ua, 0);
        ua.copyTo(a);
        EXPECT_MAT_NEAR(ua, a, 0);
    }
    {
        UMat ub;
        ua.copyTo(ub);
        EXPECT_MAT_NEAR(ua, ub, 0);
    }
    {
        UMat ub;
        i = randomInt(0, ua.cols-1);
        a.col(i).copyTo(ub);
        EXPECT_MAT_NEAR(a.col(i), ub, 0);
    }
    {
        UMat ub;
        ua.col(i).copyTo(ub);
        EXPECT_MAT_NEAR(ua.col(i), ub, 0);
    }
    {
        Mat b;
        ua.col(i).copyTo(b);
        EXPECT_MAT_NEAR(ua.col(i), b, 0);
    }
    {
        UMat ub;
        i = randomInt(0, a.rows-1);
        ua.row(i).copyTo(ub);
        EXPECT_MAT_NEAR(ua.row(i), ub, 0);
    }
    {
        UMat ub;
        a.row(i).copyTo(ub);
        EXPECT_MAT_NEAR(a.row(i), ub, 0);
    }
    {
        Mat b;
        ua.row(i).copyTo(b);
        EXPECT_MAT_NEAR(ua.row(i), b, 0);
    }
}

TEST_P(UMatBasicTests, DISABLED_GetUMat)
{
    if(useRoi)
    {
        a = Mat(a, roi);
        ua = UMat(ua,roi);
    }
    {
        UMat ub;
        ub = a.getUMat(ACCESS_RW);
        EXPECT_MAT_NEAR(ub, ua, 0);
    }
    {
        Mat b;
        b = a.getUMat(ACCESS_RW).getMat(ACCESS_RW);
        EXPECT_MAT_NEAR(b, a, 0);
    }
    {
        Mat b;
        b = ua.getMat(ACCESS_RW);
        EXPECT_MAT_NEAR(b, a, 0);
    }
    {
        UMat ub;
        ub = ua.getMat(ACCESS_RW).getUMat(ACCESS_RW);
        EXPECT_MAT_NEAR(ub, ua, 0);
    }
}

INSTANTIATE_TEST_CASE_P(UMat, UMatBasicTests, Combine(testing::Values(CV_8U), testing::Values(1, 2),
    testing::Values(cv::Size(1, 1), cv::Size(1, 128), cv::Size(128, 1), cv::Size(128, 128), cv::Size(640, 480)), Bool()));

//////////////////////////////////////////////////////////////// Reshape ////////////////////////////////////////////////////////////////////////

PARAM_TEST_CASE(UMatTestReshape,  int, int, Size, bool)
{
    Mat a;
    UMat ua, ub;
    int type;
    int depth;
    int cn;
    Size size;
    bool useRoi;
    Size roi_size;
    virtual void SetUp()
    {
        depth = GET_PARAM(0);
        cn = GET_PARAM(1);
        size = GET_PARAM(2);
        useRoi = GET_PARAM(3);
        type = CV_MAKE_TYPE(depth, cn);
    }
};

TEST_P(UMatTestReshape, DISABLED_reshape)
{
    a = randomMat(size,type, -100, 100);
    a.copyTo(ua);
    if(useRoi)
    {
        int roi_shift_x = randomInt(0, size.width-1);
        int roi_shift_y = randomInt(0, size.height-1);
        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
        Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
        ua = UMat(ua, roi).clone();
        a = Mat(a, roi).clone();
    }

    int nChannels = randomInt(1,4);

    if ((ua.cols*ua.channels()*ua.rows)%nChannels != 0)
    {
        EXPECT_ANY_THROW(ua.reshape(nChannels));
    }
    else
    {
        ub = ua.reshape(nChannels);
        ASSERT_EQ(ub.channels(),nChannels);
        ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);

        EXPECT_MAT_NEAR(ua.reshape(nChannels), a.reshape(nChannels), 0);

        int new_rows = randomInt(1, INT_MAX);
        if ( ((int)ua.total()*ua.channels())%(new_rows*nChannels) != 0)
        {
            EXPECT_ANY_THROW (ua.reshape(nChannels, new_rows) );
        }
        else
        {
            EXPECT_NO_THROW ( ub = ua.reshape(nChannels, new_rows) );
            ASSERT_EQ(ub.channels(),nChannels);
            ASSERT_EQ(ub.rows, new_rows);
            ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);

            EXPECT_MAT_NEAR(ua.reshape(nChannels,new_rows), a.reshape(nChannels,new_rows), 0);
        }

        new_rows = (int)ua.total()*ua.channels()/(nChannels*randomInt(1, size.width*size.height));
        if (new_rows == 0) new_rows = 1;
        int new_cols = (int)ua.total()*ua.channels()/(new_rows*nChannels);
        int sz[] = {new_rows, new_cols};
        if( ((int)ua.total()*ua.channels()) % (new_rows*new_cols) != 0 )
        {
            EXPECT_ANY_THROW( ua.reshape(nChannels, ua.dims, sz) );
        }
        else
        {
            EXPECT_NO_THROW ( ub = ua.reshape(nChannels, ua.dims, sz) );
            ASSERT_EQ(ub.channels(),nChannels);
            ASSERT_EQ(ub.rows, new_rows);
            ASSERT_EQ(ub.cols, new_cols);
            ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);

            EXPECT_MAT_NEAR(ua.reshape(nChannels, ua.dims, sz), a.reshape(nChannels, a.dims, sz), 0);
        }
    }
}

INSTANTIATE_TEST_CASE_P(UMat, UMatTestReshape, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));

////////////////////////////////////////////////////////////////// ROI testing ///////////////////////////////////////////////////////////////

PARAM_TEST_CASE(UMatTestRoi, int, int, Size)
{
    Mat a, roi_a;
    UMat ua, roi_ua;
    int type;
    int depth;
    int cn;
    Size size;
    Size roi_size;
    virtual void SetUp()
    {
        depth = GET_PARAM(0);
        cn = GET_PARAM(1);
        size = GET_PARAM(2);
        type = CV_MAKE_TYPE(depth, cn);
    }
};

TEST_P(UMatTestRoi, createRoi)
{
    int roi_shift_x = randomInt(0, size.width-1);
    int roi_shift_y = randomInt(0, size.height-1);
    roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
    a = randomMat(size, type, -100, 100);
    Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
    roi_a = Mat(a, roi);
    a.copyTo(ua);
    roi_ua = UMat(ua, roi);

    EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
}

TEST_P(UMatTestRoi, locateRoi)
{
    int roi_shift_x = randomInt(0, size.width-1);
    int roi_shift_y = randomInt(0, size.height-1);
    roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
    a = randomMat(size, type, -100, 100);
    Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
    roi_a = Mat(a, roi);
    a.copyTo(ua);
    roi_ua = UMat(ua,roi);
    Size sz, usz;
    Point p, up;
    roi_a.locateROI(sz, p);
    roi_ua.locateROI(usz, up);
    ASSERT_EQ(sz, usz);
    ASSERT_EQ(p, up);
}

TEST_P(UMatTestRoi, adjustRoi)
{
    int roi_shift_x = randomInt(0, size.width-1);
    int roi_shift_y = randomInt(0, size.height-1);
    roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
    a = randomMat(size, type, -100, 100);
    Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
    a.copyTo(ua);
    roi_ua = UMat( ua, roi);
    int adjLeft = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
    int adjRight = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
    int adjTop = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
    int adjBot = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
    roi_ua.adjustROI(adjTop, adjBot, adjLeft, adjRight);
    roi_shift_x = std::max(0, roi.x-adjLeft);
    roi_shift_y = std::max(0, roi.y-adjTop);
    Rect new_roi( roi_shift_x, roi_shift_y, std::min(roi.width+adjRight+adjLeft, size.width-roi_shift_x), std::min(roi.height+adjBot+adjTop, size.height-roi_shift_y) );
    UMat test_roi = UMat(ua, new_roi);
    EXPECT_MAT_NEAR(roi_ua, test_roi, 0);
}

INSTANTIATE_TEST_CASE_P(UMat, UMatTestRoi, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES ));

/////////////////////////////////////////////////////////////// Size ////////////////////////////////////////////////////////////////////

PARAM_TEST_CASE(UMatTestSizeOperations, int, int, Size, bool)
{
    Mat a, b, roi_a, roi_b;
    UMat ua, ub, roi_ua, roi_ub;
    int type;
    int depth;
    int cn;
    Size size;
    Size roi_size;
    bool useRoi;
    virtual void SetUp()
    {
        depth = GET_PARAM(0);
        cn = GET_PARAM(1);
        size = GET_PARAM(2);
        useRoi = GET_PARAM(3);
        type = CV_MAKE_TYPE(depth, cn);
    }
};

TEST_P(UMatTestSizeOperations, copySize)
{
    Size s = randomSize(1,300);
    a = randomMat(size, type, -100, 100);
    b = randomMat(s, type, -100, 100);
    a.copyTo(ua);
    b.copyTo(ub);
    if(useRoi)
    {
        int roi_shift_x = randomInt(0, size.width-1);
        int roi_shift_y = randomInt(0, size.height-1);
        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
        Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
        ua = UMat(ua,roi);

        roi_shift_x = randomInt(0, s.width-1);
        roi_shift_y = randomInt(0, s.height-1);
        roi_size = Size(s.width - roi_shift_x, s.height - roi_shift_y);
        roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
        ub = UMat(ub, roi);
    }
    ua.copySize(ub);
    ASSERT_EQ(ua.size, ub.size);
}

INSTANTIATE_TEST_CASE_P(UMat, UMatTestSizeOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));

///////////////////////////////////////////////////////////////// UMat operations ////////////////////////////////////////////////////////////////////////////

PARAM_TEST_CASE(UMatTestUMatOperations, int, int, Size, bool)
{
    Mat a, b;
    UMat ua, ub;
    int type;
    int depth;
    int cn;
    Size size;
    Size roi_size;
    bool useRoi;
    virtual void SetUp()
    {
        depth = GET_PARAM(0);
        cn = GET_PARAM(1);
        size = GET_PARAM(2);
        useRoi = GET_PARAM(3);
        type = CV_MAKE_TYPE(depth, cn);
    }
};

TEST_P(UMatTestUMatOperations, diag)
{
    a = randomMat(size, type, -100, 100);
    a.copyTo(ua);
    Mat new_diag;
    if(useRoi)
    {
        int roi_shift_x = randomInt(0, size.width-1);
        int roi_shift_y = randomInt(0, size.height-1);
        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
        Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
        ua = UMat(ua,roi);
        a = Mat(a, roi);
    }
    int n = randomInt(0, ua.cols-1);
    ub = ua.diag(n);
    b = a.diag(n);
    EXPECT_MAT_NEAR(b, ub, 0);
    new_diag = randomMat(Size(ua.rows, 1), type, -100, 100);
    new_diag.copyTo(ub);
    ua = cv::UMat::diag(ub);
    EXPECT_MAT_NEAR(ua.diag(), new_diag.t(), 0);
}

INSTANTIATE_TEST_CASE_P(UMat, UMatTestUMatOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool()));

///////////////////////////////////////////////////////////////// OpenCL ////////////////////////////////////////////////////////////////////////////

TEST(UMat, BufferPoolGrowing)
{
#ifdef _DEBUG
    const int ITERATIONS = 100;
#else
    const int ITERATIONS = 200;
#endif
    const Size sz(1920, 1080);
    BufferPoolController* c = cv::ocl::getOpenCLAllocator()->getBufferPoolController();
    if (c)
    {
        size_t oldMaxReservedSize = c->getMaxReservedSize();
        c->freeAllReservedBuffers();
        c->setMaxReservedSize(sz.area() * 10);
        for (int i = 0; i < ITERATIONS; i++)
        {
            UMat um(Size(sz.width + i, sz.height + i), CV_8UC1);
            UMat um2(Size(sz.width + 2 * i, sz.height + 2 * i), CV_8UC1);
        }
        c->setMaxReservedSize(oldMaxReservedSize);
        c->freeAllReservedBuffers();
    }
    else
        std::cout << "Skipped, no OpenCL" << std::endl;
}

class CV_UMatTest :
        public cvtest::BaseTest
{
public:
    CV_UMatTest() {}
    ~CV_UMatTest() {}
protected:
    void run(int);

    struct test_excep
    {
        test_excep(const string& _s=string("")) : s(_s) { }
        string s;
    };

    bool TestUMat();

    void checkDiff(const Mat& m1, const Mat& m2, const string& s)
    {
        if (cvtest::norm(m1, m2, NORM_INF) != 0)
            throw test_excep(s);
    }
    void checkDiffF(const Mat& m1, const Mat& m2, const string& s)
    {
        if (cvtest::norm(m1, m2, NORM_INF) > 1e-5)
            throw test_excep(s);
    }
};

#define STR(a) STR2(a)
#define STR2(a) #a

#define CHECK_DIFF(a, b) checkDiff(a, b, "(" #a ")  !=  (" #b ")  at l." STR(__LINE__))
#define CHECK_DIFF_FLT(a, b) checkDiffF(a, b, "(" #a ")  !=(eps)  (" #b ")  at l." STR(__LINE__))


bool CV_UMatTest::TestUMat()
{
    try
    {
        Mat a(100, 100, CV_16SC2), b, c;
        randu(a, Scalar::all(-100), Scalar::all(100));
        Rect roi(1, 3, 5, 4);
        Mat ra(a, roi), rb, rc, rc0;
        UMat ua, ura, ub, urb, uc, urc;
        a.copyTo(ua);
        ua.copyTo(b);
        CHECK_DIFF(a, b);

        ura = ua(roi);
        ura.copyTo(rb);

        CHECK_DIFF(ra, rb);

        ra += Scalar::all(1.f);
        {
            Mat temp = ura.getMat(ACCESS_RW);
            temp += Scalar::all(1.f);
        }
        ra.copyTo(rb);
        CHECK_DIFF(ra, rb);

        b = a.clone();
        ra = a(roi);
        rb = b(roi);
        randu(b, Scalar::all(-100), Scalar::all(100));
        b.copyTo(ub);
        urb = ub(roi);

        /*std::cout << "==============================================\nbefore op (CPU):\n";
        std::cout << "ra: " << ra << std::endl;
        std::cout << "rb: " << rb << std::endl;*/

        ra.copyTo(ura);
        rb.copyTo(urb);
        ra.release();
        rb.release();
        ura.copyTo(ra);
        urb.copyTo(rb);

        /*std::cout << "==============================================\nbefore op (GPU):\n";
        std::cout << "ra: " << ra << std::endl;
        std::cout << "rb: " << rb << std::endl;*/

        cv::max(ra, rb, rc);
        cv::max(ura, urb, urc);
        urc.copyTo(rc0);

        /*std::cout << "==============================================\nafter op:\n";
        std::cout << "rc: " << rc << std::endl;
        std::cout << "rc0: " << rc0 << std::endl;*/

        CHECK_DIFF(rc0, rc);

        {
            UMat tmp = rc0.getUMat(ACCESS_WRITE);
            cv::max(ura, urb, tmp);
        }
        CHECK_DIFF(rc0, rc);

        ura.copyTo(urc);
        cv::max(urc, urb, urc);
        urc.copyTo(rc0);
        CHECK_DIFF(rc0, rc);

        rc = ra ^ rb;
        cv::bitwise_xor(ura, urb, urc);
        urc.copyTo(rc0);

        /*std::cout << "==============================================\nafter op:\n";
        std::cout << "ra: " << rc0 << std::endl;
        std::cout << "rc: " << rc << std::endl;*/

        CHECK_DIFF(rc0, rc);

        rc = ra + rb;
        cv::add(ura, urb, urc);
        urc.copyTo(rc0);

        CHECK_DIFF(rc0, rc);

        cv::subtract(ra, Scalar::all(5), rc);
        cv::subtract(ura, Scalar::all(5), urc);
        urc.copyTo(rc0);

        CHECK_DIFF(rc0, rc);
    }
    catch (const test_excep& e)
    {
        ts->printf(cvtest::TS::LOG, "%s\n", e.s.c_str());
        ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
        return false;
    }
    return true;
}

void CV_UMatTest::run( int /* start_from */)
{
    printf("Use OpenCL: %s\nHave OpenCL: %s\n",
           cv::ocl::useOpenCL() ? "TRUE" : "FALSE",
           cv::ocl::haveOpenCL() ? "TRUE" : "FALSE" );

    if (!TestUMat())
        return;

    ts->set_failed_test_info(cvtest::TS::OK);
}

TEST(Core_UMat, base) { CV_UMatTest test; test.safe_run(); }

TEST(Core_UMat, getUMat)
{
    {
        int a[3] = { 1, 2, 3 };
        Mat m = Mat(1, 1, CV_32SC3, a);
        UMat u = m.getUMat(ACCESS_READ);
        EXPECT_NE((void*)NULL, u.u);
    }

    {
        Mat m(10, 10, CV_8UC1), ref;
        for (int y = 0; y < m.rows; ++y)
        {
            uchar * const ptr = m.ptr<uchar>(y);
            for (int x = 0; x < m.cols; ++x)
                ptr[x] = (uchar)(x + y * 2);
        }

        ref = m.clone();
        Rect r(1, 1, 8, 8);
        ref(r).setTo(17);

        {
            UMat um = m(r).getUMat(ACCESS_WRITE);
            um.setTo(17);
        }

        double err = cvtest::norm(m, ref, NORM_INF);
        if (err > 0)
        {
            std::cout << "m: " << std::endl << m << std::endl;
            std::cout << "ref: " << std::endl << ref << std::endl;
        }
        EXPECT_EQ(0., err);
    }
}

TEST(UMat, Sync)
{
    UMat um(10, 10, CV_8UC1);

    {
        Mat m = um.getMat(ACCESS_WRITE);
        m.setTo(cv::Scalar::all(17));
    }

    um.setTo(cv::Scalar::all(19));

    EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
}

TEST(UMat, CopyToIfDeviceCopyIsObsolete)
{
    UMat um(7, 2, CV_8UC1);
    Mat m(um.size(), um.type());
    m.setTo(Scalar::all(0));

    {
        // make obsolete device copy of UMat
        Mat temp = um.getMat(ACCESS_WRITE);
        temp.setTo(Scalar::all(10));
    }

    m.copyTo(um);
    um.setTo(Scalar::all(17));

    EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), Mat(um.size(), um.type(), 17), NORM_INF));
}

TEST(UMat, setOpenCL)
{
    // save the current state
    bool useOCL = cv::ocl::useOpenCL();

    Mat m = (Mat_<uchar>(3,3)<<0,1,2,3,4,5,6,7,8);

    cv::ocl::setUseOpenCL(true);
    UMat um1;
    m.copyTo(um1);

    cv::ocl::setUseOpenCL(false);
    UMat um2;
    m.copyTo(um2);

    cv::ocl::setUseOpenCL(true);
    countNonZero(um1);
    countNonZero(um2);

    um1.copyTo(um2);
    EXPECT_MAT_NEAR(um1, um2, 0);
    EXPECT_MAT_NEAR(um1, m, 0);
    um2.copyTo(um1);
    EXPECT_MAT_NEAR(um1, m, 0);
    EXPECT_MAT_NEAR(um1, um2, 0);

    cv::ocl::setUseOpenCL(false);
    countNonZero(um1);
    countNonZero(um2);

    um1.copyTo(um2);
    EXPECT_MAT_NEAR(um1, um2, 0);
    EXPECT_MAT_NEAR(um1, m, 0);
    um2.copyTo(um1);
    EXPECT_MAT_NEAR(um1, um2, 0);
    EXPECT_MAT_NEAR(um1, m, 0);

    // reset state to the previous one
    cv::ocl::setUseOpenCL(useOCL);
}

TEST(UMat, ReadBufferRect)
{
    UMat m(1, 10000, CV_32FC2, Scalar::all(-1));
    Mat t(1, 9000, CV_32FC2, Scalar::all(-200)), t2(1, 9000, CV_32FC2, Scalar::all(-1));
    m.colRange(0, 9000).copyTo(t);

    EXPECT_MAT_NEAR(t, t2, 0);
}

// Use iGPU or OPENCV_OPENCL_DEVICE=:CPU: to catch problem
TEST(UMat, DISABLED_synchronization_map_unmap)
{
    class TestParallelLoopBody : public cv::ParallelLoopBody
    {
        UMat u_;
    public:
        TestParallelLoopBody(const UMat& u) : u_(u) { }
        void operator() (const cv::Range& range) const
        {
            printf("range: %d, %d -- begin\n", range.start, range.end);
            for (int i = 0; i < 10; i++)
            {
                printf("%d: %d map...\n", range.start, i);
                Mat m = u_.getMat(cv::ACCESS_READ);

                printf("%d: %d unmap...\n", range.start, i);
                m.release();
            }
            printf("range: %d, %d -- end\n", range.start, range.end);
        }
    };
    try
    {
        UMat u(1000, 1000, CV_32FC1);
        parallel_for_(cv::Range(0, 2), TestParallelLoopBody(u));
    }
    catch (const cv::Exception& e)
    {
        FAIL() << "Exception: " << e.what();
        ADD_FAILURE();
    }
    catch (...)
    {
        FAIL() << "Exception!";
    }
}

} } // namespace cvtest::ocl

TEST(UMat, DISABLED_bug_with_unmap)
{
    for (int i = 0; i < 20; i++)
    {
        try
        {
            Mat m = Mat(1000, 1000, CV_8UC1);
            UMat u = m.getUMat(ACCESS_READ);
            UMat dst;
            add(u, Scalar::all(0), dst); // start async operation
            u.release();
            m.release();
        }
        catch (const cv::Exception& e)
        {
            printf("i = %d... %s\n", i, e.what());
            ADD_FAILURE();
        }
        catch (...)
        {
            printf("i = %d...\n", i);
            ADD_FAILURE();
        }
    }
}

TEST(UMat, DISABLED_bug_with_unmap_in_class)
{
    class Logic
    {
    public:
        Logic() {}
        void processData(InputArray input)
        {
            Mat m = input.getMat();
            {
                Mat dst;
                m.convertTo(dst, CV_32FC1);
                // some additional CPU-based per-pixel processing into dst
                intermediateResult = dst.getUMat(ACCESS_READ);
                std::cout << "data processed..." << std::endl;
            } // problem is here: dst::~Mat()
            std::cout << "leave ProcessData()" << std::endl;
        }
        UMat getResult() const { return intermediateResult; }
    protected:
        UMat intermediateResult;
    };
    try
    {
        Mat m = Mat(1000, 1000, CV_8UC1);
        Logic l;
        l.processData(m);
        UMat result = l.getResult();
    }
    catch (const cv::Exception& e)
    {
        printf("exception... %s\n", e.what());
        ADD_FAILURE();
    }
    catch (...)
    {
        printf("exception... \n");
        ADD_FAILURE();
    }
}

TEST(UMat, Test_same_behaviour_read_and_read)
{
    bool exceptionDetected = false;
    try
    {
        UMat u(Size(10, 10), CV_8UC1);
        Mat m = u.getMat(ACCESS_READ);
        UMat dst;
        add(u, Scalar::all(1), dst);
    }
    catch (...)
    {
        exceptionDetected = true;
    }
    ASSERT_FALSE(exceptionDetected); // no data race, 2+ reads are valid
}

// VP: this test (and probably others from same_behaviour series) is not valid in my opinion.
TEST(UMat, DISABLED_Test_same_behaviour_read_and_write)
{
    bool exceptionDetected = false;
    try
    {
        UMat u(Size(10, 10), CV_8UC1);
        Mat m = u.getMat(ACCESS_READ);
        add(u, Scalar::all(1), u);
    }
    catch (...)
    {
        exceptionDetected = true;
    }
    ASSERT_TRUE(exceptionDetected); // data race
}

TEST(UMat, DISABLED_Test_same_behaviour_write_and_read)
{
    bool exceptionDetected = false;
    try
    {
        UMat u(Size(10, 10), CV_8UC1);
        Mat m = u.getMat(ACCESS_WRITE);
        UMat dst;
        add(u, Scalar::all(1), dst);
    }
    catch (...)
    {
        exceptionDetected = true;
    }
    ASSERT_TRUE(exceptionDetected); // data race
}

TEST(UMat, DISABLED_Test_same_behaviour_write_and_write)
{
    bool exceptionDetected = false;
    try
    {
        UMat u(Size(10, 10), CV_8UC1);
        Mat m = u.getMat(ACCESS_WRITE);
        add(u, Scalar::all(1), u);
    }
    catch (...)
    {
        exceptionDetected = true;
    }
    ASSERT_TRUE(exceptionDetected); // data race
}

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