opencv/modules/gapi/test/common/gapi_imgproc_tests_inl.hpp

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2018 Intel Corporation


#ifndef OPENCV_GAPI_IMGPROC_TESTS_INL_HPP
#define OPENCV_GAPI_IMGPROC_TESTS_INL_HPP

#include "opencv2/gapi/imgproc.hpp"
#include "gapi_imgproc_tests.hpp"

namespace opencv_test
{
TEST_P(Filter2DTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0, borderType = 0, dtype = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, borderType, dtype, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, dtype, initOut);

    cv::Point anchor = {-1, -1};
    double delta = 0;

    cv::Mat kernel = cv::Mat(kernSize, kernSize, CV_32FC1 );
    cv::Scalar kernMean = cv::Scalar(1.0);
    cv::Scalar kernStddev = cv::Scalar(2.0/3);
    randn(kernel, kernMean, kernStddev);

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::filter2D(in, dtype, kernel, anchor, delta, borderType);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::filter2D(in_mat1, out_mat_ocv, dtype, kernel, anchor, delta, borderType);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        // TODO: Control this choice with test's especial parameter
    #if 1
        // Allow some rounding error
        if (CV_MAT_DEPTH(out_mat_gapi.type()) == CV_32F)
        {
            // 6 decimal digits is nearly best accuracy we can expect of FP32 arithmetic here
            EXPECT_EQ(0, cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) > 1e-6*cv::abs(out_mat_ocv)));
        }
        else
        {
            // allow wrong rounding if result fractional part is nearly 0.5,
            // assume there would be not more than 0.01% of such cases
            EXPECT_LE(cv::countNonZero(out_mat_gapi != out_mat_ocv), 1e-4*out_mat_ocv.total());
        }
    #else
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(BoxFilterTest, AccuracyTest)
{
    MatType type = 0;
    int filterSize = 0, borderType = 0, dtype = 0;
    cv::Size sz;
    double tolerance = 0.0;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, filterSize, sz, borderType, dtype, tolerance, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, dtype, initOut);

    cv::Point anchor = {-1, -1};
    bool normalize = true;

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::boxFilter(in, dtype, cv::Size(filterSize, filterSize), anchor, normalize, borderType);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::boxFilter(in_mat1, out_mat_ocv, dtype, cv::Size(filterSize, filterSize), anchor, normalize, borderType);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        // TODO: Control this choice with test's especial parameter
    #if 1
        // Allow some rounding error
        if (CV_MAT_DEPTH(out_mat_gapi.type()) == CV_32F)
        {
            // 6 decimal digits is nearly best accuracy we can expect of FP32 arithmetic here
            EXPECT_EQ(0, cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) > 1e-6*cv::abs(out_mat_ocv)));
        }
        else
        {
            // allow wrong rounding if result fractional part is nearly 0.5,
            // assume there would be not more than 0.01% of such cases
            EXPECT_LE(cv::countNonZero(out_mat_gapi != out_mat_ocv), 1e-4*out_mat_ocv.total());
        }
    #else
        cv::Mat absDiff;
        cv::absdiff(out_mat_gapi, out_mat_ocv, absDiff);
        EXPECT_EQ(0, cv::countNonZero(absDiff > tolerance));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(SepFilterTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0, dtype = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, dtype, initOut, compile_args) = GetParam();

    cv::Mat kernelX(kernSize, 1, CV_32F);
    cv::Mat kernelY(kernSize, 1, CV_32F);
    randu(kernelX, -1, 1);
    randu(kernelY, -1, 1);
    initMatsRandN(type, sz, dtype, initOut);

    cv::Point anchor = cv::Point(-1, -1);

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::sepFilter(in, dtype, kernelX, kernelY, anchor, cv::Scalar() );

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::sepFilter2D(in_mat1, out_mat_ocv, dtype, kernelX, kernelY );
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        // TODO: Control this choice with test's especial parameter
    #if 1
        // Expect some rounding error
        EXPECT_LE(cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) > 1e-5 * cv::abs(out_mat_ocv)),
                                                                         0.01 * out_mat_ocv.total());
    #else
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(BlurTest, AccuracyTest)
{
    MatType type = 0;
    int filterSize = 0, borderType = 0;
    cv::Size sz;
    double tolerance = 0.0;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, filterSize, sz, borderType, tolerance, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    cv::Point anchor = {-1, -1};

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::blur(in, cv::Size(filterSize, filterSize), anchor, borderType);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::blur(in_mat1, out_mat_ocv, cv::Size(filterSize, filterSize), anchor, borderType);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        cv::Mat absDiff;
        cv::absdiff(out_mat_gapi, out_mat_ocv, absDiff);
        EXPECT_EQ(0, cv::countNonZero(absDiff > tolerance));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(GaussianBlurTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    cv::Size kSize = cv::Size(kernSize, kernSize);
    double sigmaX = rand();

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::gaussianBlur(in, kSize, sigmaX);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::GaussianBlur(in_mat1, out_mat_ocv, kSize, sigmaX);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        // TODO: Control this choice with test's especial parameter
    #if 1
        // Expect some rounding error
        if (CV_MAT_DEPTH(out_mat_gapi.type()) == CV_32F ||
            CV_MAT_DEPTH(out_mat_gapi.type()) == CV_64F)
        {
            // Note that 1e-6 is nearly best accuracy we can expect of FP32 arithetic
            EXPECT_EQ(0, cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) >
                                                    1e-6*cv::abs(out_mat_ocv)));
        }
        else if (CV_MAT_DEPTH(out_mat_gapi.type()) == CV_8U)
        {
            // OpenCV uses 16-bits fixed-point for 8U data, so may produce wrong results
            EXPECT_LE(cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) > 1),
                                                          0.05*out_mat_ocv.total());
            EXPECT_LE(cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) > 2), 0);
        }
        else
        {
            EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        }
    #else
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(MedianBlurTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::medianBlur(in, kernSize);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::medianBlur(in_mat1, out_mat_ocv, kernSize);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(ErodeTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0, kernType = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, kernType, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    cv::Mat kernel = cv::getStructuringElement(kernType, cv::Size(kernSize, kernSize));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::erode(in, kernel);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::erode(in_mat1, out_mat_ocv, kernel);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(Erode3x3Test, AccuracyTest)
{
    MatType type = 0;
    int numIters = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, sz, initOut, numIters, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    cv::Mat kernel = cv::getStructuringElement(cv::MorphShapes::MORPH_RECT, cv::Size(3,3));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::erode3x3(in, numIters);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::erode(in_mat1, out_mat_ocv, kernel, cv::Point(-1, -1), numIters);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(DilateTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0, kernType = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, kernType, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    cv::Mat kernel = cv::getStructuringElement(kernType, cv::Size(kernSize, kernSize));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::dilate(in, kernel);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::dilate(in_mat1, out_mat_ocv, kernel);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(Dilate3x3Test, AccuracyTest)
{
    MatType type = 0;
    int numIters = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, sz, initOut, numIters, compile_args) = GetParam();
    initMatsRandN(type, sz, type, initOut);

    cv::Mat kernel = cv::getStructuringElement(cv::MorphShapes::MORPH_RECT, cv::Size(3,3));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::dilate3x3(in, numIters);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::dilate(in_mat1, out_mat_ocv, kernel, cv::Point(-1,-1), numIters);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}


TEST_P(SobelTest, AccuracyTest)
{
    MatType type = 0;
    int kernSize = 0, dtype = 0, dx = 0, dy = 0;
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, kernSize, sz, dtype, dx, dy, initOut, compile_args) = GetParam();
    initMatsRandN(type, sz, dtype, initOut);

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::Sobel(in, dtype, dx, dy, kernSize );

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::Sobel(in_mat1, out_mat_ocv, dtype, dx, dy, kernSize);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(EqHistTest, AccuracyTest)
{
    cv::Size sz;
    bool initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(sz, initOut, compile_args) = GetParam();
    initMatsRandN(CV_8UC1, sz, CV_8UC1, initOut);

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::equalizeHist(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::equalizeHist(in_mat1, out_mat_ocv);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(GetParam()));
    }
}

TEST_P(CannyTest, AccuracyTest)
{
    MatType type;
    int apSize = 0;
    double thrLow = 0.0, thrUp = 0.0;
    cv::Size sz;
    bool l2gr = false, initOut = false;
    cv::GCompileArgs compile_args;
    std::tie(type, sz, thrLow, thrUp, apSize, l2gr, initOut, compile_args) = GetParam();

    initMatsRandN(type, sz, CV_8UC1, initOut);

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::Canny(in, thrLow, thrUp, apSize, l2gr);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::Canny(in_mat1, out_mat_ocv, thrLow, thrUp, apSize, l2gr);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), sz);
    }
}

TEST_P(RGB2GrayTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC1, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::RGB2Gray(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_RGB2GRAY);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding if result's fractional part is nearly 0.5
        // - assume not more than 0.1% of pixels may deviate this way
        // - deviation must not exceed 1 unit anyway
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.001*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0);
    #else
        // insist of bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(BGR2GrayTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC1, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::BGR2Gray(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_BGR2GRAY);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding if result's fractional part is nearly 0.5
        // - assume not more than 0.1% of pixels may deviate this way
        // - deviation must not exceed 1 unit anyway
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.001*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0);
    #else
        // insist of bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(RGB2YUVTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::RGB2YUV(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_RGB2YUV);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding if result's fractional part is nearly 0.5
        // - assume not more than 15% of pixels may deviate this way
        // - deviation must not exceed 1 unit anyway
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.15*3*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0);
    #else
        // insist of bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(YUV2RGBTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::YUV2RGB(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_YUV2RGB);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding if result's fractional part is nearly 0.5
        // - assume not more than 1% of pixels may deviate this way
        // - deviation must not exceed 1 unit anyway
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.01*3*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0);
    #else
        // insist of bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(RGB2LabTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::RGB2Lab(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_RGB2Lab);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding, if result's fractional part is nearly 0.5
        // - assume not more than 25% of pixels may deviate this way
        // - not more than 1% of pixels may deviate by 1 unit
        // - deviation must not exceed 2 units anyway
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.25*3*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0.01*3*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 2), 1e-5*3*out_mat_ocv.total());
    #else
        // insist on bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(BGR2LUVTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::BGR2LUV(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_BGR2Luv);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding, if result's fractional part is nearly 0.5
        // - assume not more than 25% of pixels may deviate this way
        // - not more than 1% of pixels may deviate by 2+ units
        // - not more than 0.01% pixels may deviate by 5+ units
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.25   * 3 * out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0.01   * 3 * out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 5), 0.0001 * 3 * out_mat_ocv.total());
    #else
        // insist on bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(LUV2BGRTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::LUV2BGR(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_Luv2BGR);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(BGR2YUVTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::BGR2YUV(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_BGR2YUV);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}

TEST_P(YUV2BGRTest, AccuracyTest)
{
    auto param = GetParam();
    auto compile_args = std::get<2>(param);
    initMatsRandN(CV_8UC3, std::get<0>(param), CV_8UC3, std::get<1>(param));

    // G-API code //////////////////////////////////////////////////////////////
    cv::GMat in;
    auto out = cv::gapi::YUV2BGR(in);

    cv::GComputation c(in, out);
    c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
    // OpenCV code /////////////////////////////////////////////////////////////
    {
        cv::cvtColor(in_mat1, out_mat_ocv, cv::COLOR_YUV2BGR);
    }
    // Comparison //////////////////////////////////////////////////////////////
    {
    // TODO: control this choice with especial parameter of this test
    #if 1
        // allow faithful rounding, if result's fractional part is nearly 0.5
        // - assume not more than 25% of pixels may deviate this way
        // - not more than 1% of pixels may deviate by 1 unit
        // - deviation must not exceed 2 units anyway
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 0), 0.25*3*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 1), 0.01*3*out_mat_ocv.total());
        EXPECT_LE(cv::countNonZero(out_mat_gapi - out_mat_ocv > 2), 1e-5*3*out_mat_ocv.total());
    #else
        // insist on bit-exact results
        EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
    #endif
        EXPECT_EQ(out_mat_gapi.size(), std::get<0>(param));
    }
}
} // opencv_test

#endif //OPENCV_GAPI_IMGPROC_TESTS_INL_HPP