Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
#ifdef HAVE_CUDA
CV_ENUM(ThreshOp, cv::THRESH_BINARY, cv::THRESH_BINARY_INV, cv::THRESH_TRUNC, cv::THRESH_TOZERO, cv::THRESH_TOZERO_INV)
#define ALL_THRESH_OPS testing::Values(ThreshOp(cv::THRESH_BINARY), ThreshOp(cv::THRESH_BINARY_INV), ThreshOp(cv::THRESH_TRUNC), ThreshOp(cv::THRESH_TOZERO), ThreshOp(cv::THRESH_TOZERO_INV))
PARAM_TEST_CASE(Threshold, cv::gpu::DeviceInfo, cv::Size, MatType, ThreshOp, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int threshOp;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
threshOp = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
TEST_P(Threshold, Accuracy)
{
try
{
cv::Mat src = randomMat(size, type);
double maxVal = randomDouble(20.0, 127.0);
double thresh = randomDouble(0.0, maxVal);
cv::gpu::GpuMat dst = createMat(src.size(), src.type(), useRoi);
cv::gpu::threshold(loadMat(src, useRoi), dst, thresh, maxVal, threshOp);
cv::Mat dst_gold;
cv::threshold(src, dst_gold, thresh, maxVal, threshOp);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
catch (...)
{
cv::gpu::resetDevice();
throw;
}
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Threshold, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_16SC1), MatType(CV_32FC1)),
ALL_THRESH_OPS,
WHOLE_SUBMAT));
#endif // HAVE_CUDA