opencv/modules/gpu/test/test_nvidia.cpp
Vladislav Vinogradov ade7394e77 refactored and fixed bugs in gpu warp functions (remap, resize, warpAffine, warpPerspective)
wrote more complicated tests for them
implemented own version of warpAffine and warpPerspective for different border interpolation types
refactored some gpu tests
2012-03-14 15:54:17 +00:00

170 lines
5.3 KiB
C++

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#include "precomp.hpp"
#ifdef HAVE_CUDA
using namespace cvtest;
using namespace testing;
enum OutputLevel
{
OutputLevelNone,
OutputLevelCompact,
OutputLevelFull
};
bool nvidia_NPPST_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NPPST_Squared_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NPPST_RectStdDev(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NPPST_Resize(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NPPST_Vector_Operations(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NPPST_Transpose(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NCV_Vector_Operations(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NCV_Haar_Cascade_Loader(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NCV_Haar_Cascade_Application(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NCV_Hypotheses_Filtration(const std::string& test_data_path, OutputLevel outputLevel);
bool nvidia_NCV_Visualization(const std::string& test_data_path, OutputLevel outputLevel);
struct NVidiaTest : TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
std::string path;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
path = std::string(TS::ptr()->get_data_path()) + "haarcascade/";
}
};
struct NPPST : NVidiaTest {};
struct NCV : NVidiaTest {};
OutputLevel nvidiaTestOutputLevel = OutputLevelNone;
TEST_P(NPPST, Integral)
{
bool res = nvidia_NPPST_Integral_Image(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, SquaredIntegral)
{
bool res = nvidia_NPPST_Squared_Integral_Image(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, RectStdDev)
{
bool res = nvidia_NPPST_RectStdDev(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, Resize)
{
bool res = nvidia_NPPST_Resize(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, VectorOperations)
{
bool res = nvidia_NPPST_Vector_Operations(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, Transpose)
{
bool res = nvidia_NPPST_Transpose(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, VectorOperations)
{
bool res = nvidia_NCV_Vector_Operations(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, HaarCascadeLoader)
{
bool res = nvidia_NCV_Haar_Cascade_Loader(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, HaarCascadeApplication)
{
bool res = nvidia_NCV_Haar_Cascade_Application(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, HypothesesFiltration)
{
bool res = nvidia_NCV_Hypotheses_Filtration(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, Visualization)
{
bool res = nvidia_NCV_Visualization(path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
INSTANTIATE_TEST_CASE_P(NVidia, NPPST, ALL_DEVICES);
INSTANTIATE_TEST_CASE_P(NVidia, NCV, ALL_DEVICES);
#endif // HAVE_CUDA