opencv/modules/cudaimgproc/test/test_histogram.cpp

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#include "test_precomp.hpp"

#ifdef HAVE_CUDA

namespace opencv_test { namespace {

///////////////////////////////////////////////////////////////////////////////////////////////////////
// HistEven

PARAM_TEST_CASE(HistEven, cv::cuda::DeviceInfo, cv::Size)
{
    cv::cuda::DeviceInfo devInfo;
    cv::Size size;

    virtual void SetUp()
    {
        devInfo = GET_PARAM(0);
        size = GET_PARAM(1);

        cv::cuda::setDevice(devInfo.deviceID());
    }
};

CUDA_TEST_P(HistEven, Accuracy)
{
    cv::Mat src = randomMat(size, CV_8UC1);

    int hbins = 30;
    float hranges[] = {50.0f, 200.0f};

    cv::cuda::GpuMat hist;
    cv::cuda::histEven(loadMat(src), hist, hbins, (int) hranges[0], (int) hranges[1]);

    cv::Mat hist_gold;

    int histSize[] = {hbins};
    const float* ranges[] = {hranges};
    int channels[] = {0};
    cv::calcHist(&src, 1, channels, cv::Mat(), hist_gold, 1, histSize, ranges);

    hist_gold = hist_gold.t();
    hist_gold.convertTo(hist_gold, CV_32S);

    EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
}

INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, HistEven, testing::Combine(
    ALL_DEVICES,
    DIFFERENT_SIZES));

///////////////////////////////////////////////////////////////////////////////////////////////////////
// CalcHist

PARAM_TEST_CASE(CalcHist, cv::cuda::DeviceInfo, cv::Size)
{
    cv::cuda::DeviceInfo devInfo;

    cv::Size size;

    virtual void SetUp()
    {
        devInfo = GET_PARAM(0);
        size = GET_PARAM(1);

        cv::cuda::setDevice(devInfo.deviceID());
    }
};

CUDA_TEST_P(CalcHist, Accuracy)
{
    cv::Mat src = randomMat(size, CV_8UC1);

    cv::cuda::GpuMat hist;
    cv::cuda::calcHist(loadMat(src), hist);

    cv::Mat hist_gold;

    const int hbins = 256;
    const float hranges[] = {0.0f, 256.0f};
    const int histSize[] = {hbins};
    const float* ranges[] = {hranges};
    const int channels[] = {0};

    cv::calcHist(&src, 1, channels, cv::Mat(), hist_gold, 1, histSize, ranges);
    hist_gold = hist_gold.reshape(1, 1);
    hist_gold.convertTo(hist_gold, CV_32S);

    EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
}

INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CalcHist, testing::Combine(
    ALL_DEVICES,
    DIFFERENT_SIZES));

PARAM_TEST_CASE(CalcHistWithMask, cv::cuda::DeviceInfo, cv::Size)
{
    cv::cuda::DeviceInfo devInfo;

    cv::Size size;

    virtual void SetUp()
    {
        devInfo = GET_PARAM(0);
        size = GET_PARAM(1);

        cv::cuda::setDevice(devInfo.deviceID());
    }
};

CUDA_TEST_P(CalcHistWithMask, Accuracy)
{
    cv::Mat src = randomMat(size, CV_8UC1);
    cv::Mat mask = randomMat(size, CV_8UC1);
    cv::Mat(mask, cv::Rect(0, 0, size.width / 2, size.height / 2)).setTo(0);

    cv::cuda::GpuMat hist;
    cv::cuda::calcHist(loadMat(src), loadMat(mask), hist);

    cv::Mat hist_gold;

    const int hbins = 256;
    const float hranges[] = {0.0f, 256.0f};
    const int histSize[] = {hbins};
    const float* ranges[] = {hranges};
    const int channels[] = {0};

    cv::calcHist(&src, 1, channels, mask, hist_gold, 1, histSize, ranges);
    hist_gold = hist_gold.reshape(1, 1);
    hist_gold.convertTo(hist_gold, CV_32S);

    EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
}

INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CalcHistWithMask, testing::Combine(
    ALL_DEVICES,
    DIFFERENT_SIZES));

///////////////////////////////////////////////////////////////////////////////////////////////////////
// EqualizeHist

PARAM_TEST_CASE(EqualizeHist, cv::cuda::DeviceInfo, cv::Size)
{
    cv::cuda::DeviceInfo devInfo;
    cv::Size size;

    virtual void SetUp()
    {
        devInfo = GET_PARAM(0);
        size = GET_PARAM(1);

        cv::cuda::setDevice(devInfo.deviceID());
    }
};

CUDA_TEST_P(EqualizeHist, Async)
{
    cv::Mat src = randomMat(size, CV_8UC1);

    cv::cuda::Stream stream;

    cv::cuda::GpuMat dst;
    cv::cuda::equalizeHist(loadMat(src), dst, stream);

    stream.waitForCompletion();

    cv::Mat dst_gold;
    cv::equalizeHist(src, dst_gold);

    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}

CUDA_TEST_P(EqualizeHist, Accuracy)
{
    cv::Mat src = randomMat(size, CV_8UC1);

    cv::cuda::GpuMat dst;
    cv::cuda::equalizeHist(loadMat(src), dst);

    cv::Mat dst_gold;
    cv::equalizeHist(src, dst_gold);

    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}

INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, EqualizeHist, testing::Combine(
    ALL_DEVICES,
    DIFFERENT_SIZES));

TEST(EqualizeHistIssue, Issue18035)
{
    std::vector<std::string> imgPaths;
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/3MP.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/5MP.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/airplane.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/baboon.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/box.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/box_in_scene.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/fruits.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/fruits_ecc.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/graffiti.png");
    imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/lena.png");

    for (int i = 0; i < imgPaths.size(); ++i)
    {
        std::string imgPath = imgPaths[i];
        cv::Mat src = cv::imread(imgPath, cv::IMREAD_GRAYSCALE);
        src = src / 30;

        cv::cuda::GpuMat d_src, dst;
        d_src.upload(src);
        cv::cuda::equalizeHist(d_src, dst);

        cv::Mat dst_gold;
        cv::equalizeHist(src, dst_gold);

        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
    }
}

PARAM_TEST_CASE(EqualizeHistExtreme, cv::cuda::DeviceInfo, cv::Size, int)
{
    cv::cuda::DeviceInfo devInfo;
    cv::Size size;
    int val;

    virtual void SetUp()
    {
        devInfo = GET_PARAM(0);
        size = GET_PARAM(1);
        val = GET_PARAM(2);

        cv::cuda::setDevice(devInfo.deviceID());
    }
};

CUDA_TEST_P(EqualizeHistExtreme, Case1)
{
    cv::Mat src(size, CV_8UC1, val);

    cv::cuda::GpuMat dst;
    cv::cuda::equalizeHist(loadMat(src), dst);

    cv::Mat dst_gold;
    cv::equalizeHist(src, dst_gold);

    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}

CUDA_TEST_P(EqualizeHistExtreme, Case2)
{
    cv::Mat src = randomMat(size, CV_8UC1, val);

    cv::cuda::GpuMat dst;
    cv::cuda::equalizeHist(loadMat(src), dst);

    cv::Mat dst_gold;
    cv::equalizeHist(src, dst_gold);

    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}

INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, EqualizeHistExtreme, testing::Combine(
    ALL_DEVICES,
    DIFFERENT_SIZES,
    testing::Range(0, 256)));

///////////////////////////////////////////////////////////////////////////////////////////////////////
// CLAHE

namespace
{
    IMPLEMENT_PARAM_CLASS(ClipLimit, double)
}

PARAM_TEST_CASE(CLAHE, cv::cuda::DeviceInfo, cv::Size, ClipLimit, MatType)
{
    cv::cuda::DeviceInfo devInfo;
    cv::Size size;
    double clipLimit;
    int type;

    virtual void SetUp()
    {
        devInfo = GET_PARAM(0);
        size = GET_PARAM(1);
        clipLimit = GET_PARAM(2);
        type = GET_PARAM(3);

        cv::cuda::setDevice(devInfo.deviceID());
    }
};

CUDA_TEST_P(CLAHE, Accuracy)
{
    cv::Mat src;
    if (type == CV_8UC1)
        src = randomMat(size, type);
    else if (type == CV_16UC1)
        src = randomMat(size, type, 0, 65535);

    cv::Ptr<cv::cuda::CLAHE> clahe = cv::cuda::createCLAHE(clipLimit);
    cv::cuda::GpuMat dst;
    clahe->apply(loadMat(src), dst);

    cv::Ptr<cv::CLAHE> clahe_gold = cv::createCLAHE(clipLimit);
    cv::Mat dst_gold;
    clahe_gold->apply(src, dst_gold);

    ASSERT_MAT_NEAR(dst_gold, dst, 1.0);
}

INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CLAHE, testing::Combine(
    ALL_DEVICES,
    DIFFERENT_SIZES,
    testing::Values(0.0, 5.0, 10.0, 20.0, 40.0),
    testing::Values(MatType(CV_8UC1), MatType(CV_16UC1))));


}} // namespace
#endif // HAVE_CUDA