OpenCV_4.2.0/opencv_contrib-4.2.0/modules/cudaimgproc/test/test_histogram.cpp

285 lines
7.7 KiB
C++

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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, 3.0);
}
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, 3.0);
}
INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, EqualizeHist, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// 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