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#include "test_precomp.hpp"

namespace opencv_test { namespace {

BIGDATA_TEST(Imgproc_Threshold, huge)
{
    Mat m(65000, 40000, CV_8U);
    ASSERT_FALSE(m.isContinuous());

    uint64 i, n = (uint64)m.rows*m.cols;
    for( i = 0; i < n; i++ )
        m.data[i] = (uchar)(i & 255);

    cv::threshold(m, m, 127, 255, cv::THRESH_BINARY);
    int nz = cv::countNonZero(m);  // FIXIT 'int' is not enough here (overflow is possible with other inputs)
    ASSERT_EQ((uint64)nz, n / 2);
}

TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_16085)
{
    Size sz(16, 16);
    Mat input(sz, CV_32F, Scalar::all(2));
    Mat result;
    cv::threshold(input, result, 2.0, 0.0, THRESH_TOZERO);
    EXPECT_EQ(0, cv::norm(result, NORM_INF));
}

TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258)
{
    Size sz(16, 16);
    float val = nextafterf(16.0f, 0.0f);  // 0x417fffff, all bits in mantissa are 1
    Mat input(sz, CV_32F, Scalar::all(val));
    Mat result;
    cv::threshold(input, result, val, 0.0, THRESH_TOZERO);
    EXPECT_EQ(0, cv::norm(result, NORM_INF));
}

TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258_Min)
{
    Size sz(16, 16);
    float min_val = -std::numeric_limits<float>::max();
    Mat input(sz, CV_32F, Scalar::all(min_val));
    Mat result;
    cv::threshold(input, result, min_val, 0.0, THRESH_TOZERO);
    EXPECT_EQ(0, cv::norm(result, NORM_INF));
}

TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258_Max)
{
    Size sz(16, 16);
    float max_val = std::numeric_limits<float>::max();
    Mat input(sz, CV_32F, Scalar::all(max_val));
    Mat result;
    cv::threshold(input, result, max_val, 0.0, THRESH_TOZERO);
    EXPECT_EQ(0, cv::norm(result, NORM_INF));
}

}} // namespace