Skip to content

O
opencv
Commit b7e6b5af authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
Browse files
Options

fixed tests (call resetDevice, if there was a gpu failure)

parent 0773ab4d
Expand all Hide whitespace changes
Inline Side-by-side
Showing with 283 additions and 237 deletions
modules/gpu/perf/perf_core.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/perf/perf_imgproc.cpp
View file @ b7e6b5af
......@@ -581,13 +581,12 @@ PERF_TEST_P(Sz, ImgProc_CalcHist, GPU_TYPICAL_MAT_SIZES)
{
cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat d_hist;
cv::gpu::GpuMat d_buf;
cv::gpu::calcHist(d_src, d_hist, d_buf);
cv::gpu::calcHist(d_src, d_hist);
TEST_CYCLE()
{
cv::gpu::calcHist(d_src, d_hist, d_buf);
cv::gpu::calcHist(d_src, d_hist);
}
GPU_SANITY_CHECK(d_hist);
......@@ -1706,10 +1705,30 @@ PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidGetLayer, Combine(GPU_TYPICAL_MAT_S
}
}
namespace {
struct Vec3fComparator
{
bool operator()(const cv::Vec3f& a, const cv::Vec3f b) const
{
if(a[0] != b[0]) return a[0] < b[0];
else if(a[1] != b[1]) return a[1] < b[1];
else return a[2] < b[2];
}
};
struct Vec2fComparator
{
bool operator()(const cv::Vec2f& a, const cv::Vec2f b) const
{
if(a[0] != b[0]) return a[0] < b[0];
else return a[1] < b[1];
}
};
}
//////////////////////////////////////////////////////////////////////
// HoughLines
PERF_TEST_P(Sz, DISABLED_ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
PERF_TEST_P(Sz, ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
{
declare.time(30.0);
......@@ -1744,7 +1763,11 @@ PERF_TEST_P(Sz, DISABLED_ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
cv::gpu::HoughLines(d_src, d_lines, d_buf, rho, theta, threshold);
}
GPU_SANITY_CHECK(d_lines);
cv::Mat h_lines(d_lines);
cv::Vec2f* begin = (cv::Vec2f*)(h_lines.ptr<char>(0));
cv::Vec2f* end = (cv::Vec2f*)(h_lines.ptr<char>(0) + (h_lines.cols) * 2 * sizeof(float));
std::sort(begin, end, Vec2fComparator());
SANITY_CHECK(h_lines);
}
else
{
......@@ -1756,7 +1779,8 @@ PERF_TEST_P(Sz, DISABLED_ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
cv::HoughLines(src, lines, rho, theta, threshold);
}
CPU_SANITY_CHECK(lines);
std::sort(lines.begin(), lines.end(), Vec2fComparator());
SANITY_CHECK(lines);
}
}
......@@ -1804,7 +1828,11 @@ PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles, Combine(GPU_TYPICAL_MAT_SIZES,
cv::gpu::HoughCircles(d_src, d_circles, d_buf, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);
}
GPU_SANITY_CHECK(d_circles);
cv::Mat h_circles(d_circles);
cv::Vec3f* begin = (cv::Vec3f*)(h_circles.ptr<char>(0));
cv::Vec3f* end = (cv::Vec3f*)(h_circles.ptr<char>(0) + (h_circles.cols) * 3 * sizeof(float));
std::sort(begin, end, Vec3fComparator());
SANITY_CHECK(h_circles);
}
else
{
......@@ -1817,7 +1845,8 @@ PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles, Combine(GPU_TYPICAL_MAT_SIZES,
cv::HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);
}
CPU_SANITY_CHECK(circles);
std::sort(circles.begin(), circles.end(), Vec3fComparator());
SANITY_CHECK(circles);
}
}
......
modules/gpu/perf/perf_objdetect.cpp
View file @ b7e6b5af
......@@ -89,7 +89,6 @@ PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gp
SANITY_CHECK(found_locations);
}
///////////////////////////////////////////////////////////////
// HaarClassifier
......@@ -181,4 +180,4 @@ PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
}
}
} // namespace
} // namespace
\ No newline at end of file
modules/gpu/test/interpolation.hpp
View file @ b7e6b5af
......@@ -42,6 +42,9 @@
#ifndef __OPENCV_TEST_INTERPOLATION_HPP__
#define __OPENCV_TEST_INTERPOLATION_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
if (border_type == cv::BORDER_CONSTANT)
......@@ -113,7 +116,7 @@ template <typename T> struct CubicInterpolator
for (float cx = xmin; cx <= xmax; cx += 1.0f)
{
const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy);
sum += w * readVal<T>(src, cvFloor(cy), cvFloor(cx), c, border_type, borderVal);
sum += w * readVal<T>(src, (int) floorf(cy), (int) floorf(cx), c, border_type, borderVal);
wsum += w;
}
}
......
modules/gpu/test/nvidia/TestHaarCascadeApplication.cpp
View file @ b7e6b5af
......@@ -13,10 +13,50 @@
#include <float.h>
#if defined(__GNUC__) && !defined(__APPLE__)
#if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
#include <fpu_control.h>
#endif
namespace
{
// http://www.christian-seiler.de/projekte/fpmath/
class FpuControl
{
public:
FpuControl();
~FpuControl();
private:
#if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
fpu_control_t fpu_oldcw, fpu_cw;
#elif defined(_WIN32) && !defined(_WIN64)
unsigned int fpu_oldcw, fpu_cw;
#endif
};
FpuControl::FpuControl()
{
#if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
_FPU_GETCW(fpu_oldcw);
fpu_cw = (fpu_oldcw & ~_FPU_EXTENDED & ~_FPU_DOUBLE & ~_FPU_SINGLE) | _FPU_SINGLE;
_FPU_SETCW(fpu_cw);
#elif defined(_WIN32) && !defined(_WIN64)
_controlfp_s(&fpu_cw, 0, 0);
fpu_oldcw = fpu_cw;
_controlfp_s(&fpu_cw, _PC_24, _MCW_PC);
#endif
}
FpuControl::~FpuControl()
{
#if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
_FPU_SETCW(fpu_oldcw);
#elif defined(_WIN32) && !defined(_WIN64)
_controlfp_s(&fpu_cw, fpu_oldcw, _MCW_PC);
#endif
}
}
#include "TestHaarCascadeApplication.h"
#include "NCVHaarObjectDetection.hpp"
......@@ -47,12 +87,8 @@ bool TestHaarCascadeApplication::init()
return true;
}
bool TestHaarCascadeApplication::process()
{
#if defined(__APPLE)
return true;
#endif
NCVStatus ncvStat;
bool rcode = false;
......@@ -205,44 +241,19 @@ bool TestHaarCascadeApplication::process()
}
ncvAssertReturn(cudaSuccess == cudaStreamSynchronize(0), false);
#if !defined(__APPLE__)
#if defined(__GNUC__)
//http://www.christian-seiler.de/projekte/fpmath/
fpu_control_t fpu_oldcw, fpu_cw;
_FPU_GETCW(fpu_oldcw); // store old cw
fpu_cw = (fpu_oldcw & ~_FPU_EXTENDED & ~_FPU_DOUBLE & ~_FPU_SINGLE) | _FPU_SINGLE;
_FPU_SETCW(fpu_cw);
// calculations here
ncvStat = ncvApplyHaarClassifierCascade_host(
h_integralImage, h_rectStdDev, h_pixelMask,
detectionsOnThisScale_h,
haar, h_HaarStages, h_HaarNodes, h_HaarFeatures, false,
searchRoiU, 1, 1.0f);
ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
_FPU_SETCW(fpu_oldcw); // restore old cw
#else
#ifndef _WIN64
Ncv32u fpu_oldcw, fpu_cw;
_controlfp_s(&fpu_cw, 0, 0);
fpu_oldcw = fpu_cw;
_controlfp_s(&fpu_cw, _PC_24, _MCW_PC);
#endif
ncvStat = ncvApplyHaarClassifierCascade_host(
h_integralImage, h_rectStdDev, h_pixelMask,
detectionsOnThisScale_h,
haar, h_HaarStages, h_HaarNodes, h_HaarFeatures, false,
searchRoiU, 1, 1.0f);
ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
#ifndef _WIN64
_controlfp_s(&fpu_cw, fpu_oldcw, _MCW_PC);
#endif
#endif
{
// calculations here
FpuControl fpu;
(void) fpu;
ncvStat = ncvApplyHaarClassifierCascade_host(
h_integralImage, h_rectStdDev, h_pixelMask,
detectionsOnThisScale_h,
haar, h_HaarStages, h_HaarNodes, h_HaarFeatures, false,
searchRoiU, 1, 1.0f);
ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
}
#endif
NCV_SKIP_COND_END
int devId;
......@@ -302,4 +313,4 @@ bool TestHaarCascadeApplication::deinit()
return true;
}
#endif /* CUDA_DISABLER */
\ No newline at end of file
#endif /* CUDA_DISABLER */
modules/gpu/test/nvidia/main_nvidia.cpp
View file @ b7e6b5af
......@@ -25,7 +25,7 @@
#include "NCVAutoTestLister.hpp"
#include "NCVTestSourceProvider.hpp"
#include <main_test_nvidia.h>
#include "main_test_nvidia.h"
static std::string path;
......@@ -97,7 +97,7 @@ void generateRectStdDevTests(NCVAutoTestLister &testLister, NCVTestSourceProvide
template <class T>
void generateResizeTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<T> &src)
{
for (Ncv32u i=1; i<480; i+=3)
for (Ncv32u i=2; i<10; ++i)
{
char testName[80];
sprintf(testName, "TestResize_VGA_s%d", i);
......@@ -105,7 +105,7 @@ void generateResizeTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<T>
testLister.add(new TestResize<T>(testName, src, 640, 480, i, false));
}
for (Ncv32u i=1; i<1080; i+=5)
for (Ncv32u i=2; i<10; ++i)
{
char testName[80];
sprintf(testName, "TestResize_1080_s%d", i);
......@@ -117,7 +117,7 @@ void generateResizeTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<T>
void generateNPPSTVectorTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<Ncv32u> &src, Ncv32u maxLength)
{
//compaction
for (Ncv32f _i=256.0; _i<maxLength; _i*=1.1f)
for (Ncv32f _i=256.0; _i<maxLength; _i*=1.5f)
{
Ncv32u i = (Ncv32u)_i;
char testName[80];
......@@ -132,13 +132,13 @@ void generateNPPSTVectorTests(NCVAutoTestLister &testLister, NCVTestSourceProvid
testLister.add(new TestCompact(testName, src, i, 0xC001C0DE, 0));
testLister.add(new TestCompact(testName, src, i, 0xC001C0DE, 100));
}
for (Ncv32u i=256*256-256; i<256*256+257; i++)
for (Ncv32u i=256*256-10; i<256*256+10; i++)
{
char testName[80];
sprintf(testName, "Compaction%d", i);
testLister.add(new TestCompact(testName, src, i, 0xFFFFFFFF, 40));
}
for (Ncv32u i=256*256*256-10; i<256*256*256+10; i++)
for (Ncv32u i=256*256*256-2; i<256*256*256+2; i++)
{
char testName[80];
sprintf(testName, "Compaction%d", i);
......@@ -212,7 +212,7 @@ void generateDrawRectsTests(NCVAutoTestLister &testLister,
void generateVectorTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<Ncv32u> &src, Ncv32u maxLength)
{
//growth
for (Ncv32f _i=10.0; _i<maxLength; _i*=1.1f)
for (Ncv32f _i=10.0; _i<maxLength; _i*=1.5f)
{
Ncv32u i = (Ncv32u)_i;
char testName[80];
......@@ -253,16 +253,16 @@ void generateHaarApplicationTests(NCVAutoTestLister &testLister, NCVTestSourcePr
Ncv32u maxWidth, Ncv32u maxHeight)
{
(void)maxHeight;
for (Ncv32u i=20; i<512; i+=11)
for (Ncv32u i=100; i<512; i+=41)
{
for (Ncv32u j=20; j<128; j+=5)
for (Ncv32u j=100; j<128; j+=25)
{
char testName[80];
sprintf(testName, "HaarAppl%d_%d", i, j);
testLister.add(new TestHaarCascadeApplication(testName, src, path + "haarcascade_frontalface_alt.xml", j, i));
}
}
for (Ncv32f _i=20.0; _i<maxWidth; _i*=1.1f)
for (Ncv32f _i=20.0; _i<maxWidth; _i*=1.5f)
{
Ncv32u i = (Ncv32u)_i;
char testName[80];
......@@ -276,6 +276,8 @@ static void devNullOutput(const std::string& msg)
(void)msg;
}
}
bool nvidia_NPPST_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel)
{
path = test_data_path.c_str();
......@@ -283,17 +285,15 @@ bool nvidia_NPPST_Integral_Image(const std::string& test_data_path, OutputLevel
NCVAutoTestLister testListerII("NPPST Integral Image", outputLevel);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
NCVTestSourceProvider<Ncv32f> testSrcRandom_32f(2010, -1.0f, 1.0f, 4096, 4096);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
NCVTestSourceProvider<Ncv32f> testSrcRandom_32f(2010, -1.0f, 1.0f, 2048, 2048);
generateIntegralTests<Ncv8u, Ncv32u>(testListerII, testSrcRandom_8u, 4096, 4096);
generateIntegralTests<Ncv32f, Ncv32f>(testListerII, testSrcRandom_32f, 4096, 4096);
generateIntegralTests<Ncv8u, Ncv32u>(testListerII, testSrcRandom_8u, 2048, 2048);
generateIntegralTests<Ncv32f, Ncv32f>(testListerII, testSrcRandom_32f, 2048, 2048);
return testListerII.invoke();
}
}
bool nvidia_NPPST_Squared_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel)
{
path = test_data_path;
......@@ -301,9 +301,9 @@ bool nvidia_NPPST_Squared_Integral_Image(const std::string& test_data_path, Outp
NCVAutoTestLister testListerSII("NPPST Squared Integral Image", outputLevel);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
generateSquaredIntegralTests(testListerSII, testSrcRandom_8u, 4096, 4096);
generateSquaredIntegralTests(testListerSII, testSrcRandom_8u, 2048, 2048);
return testListerSII.invoke();
}
......@@ -315,9 +315,9 @@ bool nvidia_NPPST_RectStdDev(const std::string& test_data_path, OutputLevel outp
NCVAutoTestLister testListerRStdDev("NPPST RectStdDev", outputLevel);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
generateRectStdDevTests(testListerRStdDev, testSrcRandom_8u, 4096, 4096);
generateRectStdDevTests(testListerRStdDev, testSrcRandom_8u, 2048, 2048);
return testListerRStdDev.invoke();
}
......@@ -329,8 +329,8 @@ bool nvidia_NPPST_Resize(const std::string& test_data_path, OutputLevel outputLe
NCVAutoTestLister testListerResize("NPPST Resize", outputLevel);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 2048, 2048);
generateResizeTests(testListerResize, testSrcRandom_32u);
generateResizeTests(testListerResize, testSrcRandom_64u);
......@@ -345,9 +345,9 @@ bool nvidia_NPPST_Vector_Operations(const std::string& test_data_path, OutputLev
NCVAutoTestLister testListerNPPSTVectorOperations("NPPST Vector Operations", outputLevel);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
generateNPPSTVectorTests(testListerNPPSTVectorOperations, testSrcRandom_32u, 4096*4096);
generateNPPSTVectorTests(testListerNPPSTVectorOperations, testSrcRandom_32u, 2048*2048);
return testListerNPPSTVectorOperations.invoke();
}
......@@ -359,8 +359,8 @@ bool nvidia_NPPST_Transpose(const std::string& test_data_path, OutputLevel outpu
NCVAutoTestLister testListerTranspose("NPPST Transpose", outputLevel);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 2048, 2048);
generateTransposeTests(testListerTranspose, testSrcRandom_32u);
generateTransposeTests(testListerTranspose, testSrcRandom_64u);
......@@ -375,9 +375,9 @@ bool nvidia_NCV_Vector_Operations(const std::string& test_data_path, OutputLevel
NCVAutoTestLister testListerVectorOperations("Vector Operations", outputLevel);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
generateVectorTests(testListerVectorOperations, testSrcRandom_32u, 4096*4096);
generateVectorTests(testListerVectorOperations, testSrcRandom_32u, 2048*2048);
return testListerVectorOperations.invoke();
......@@ -404,7 +404,7 @@ bool nvidia_NCV_Haar_Cascade_Application(const std::string& test_data_path, Outp
NCVTestSourceProvider<Ncv8u> testSrcFacesVGA_8u(path + "group_1_640x480_VGA.pgm");
generateHaarApplicationTests(testListerHaarAppl, testSrcFacesVGA_8u, 1280, 720);
generateHaarApplicationTests(testListerHaarAppl, testSrcFacesVGA_8u, 640, 480);
return testListerHaarAppl.invoke();
}
......@@ -416,9 +416,9 @@ bool nvidia_NCV_Hypotheses_Filtration(const std::string& test_data_path, OutputL
NCVAutoTestLister testListerHypFiltration("Hypotheses Filtration", outputLevel);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
generateHypothesesFiltrationTests(testListerHypFiltration, testSrcRandom_32u, 1024);
generateHypothesesFiltrationTests(testListerHypFiltration, testSrcRandom_32u, 512);
return testListerHypFiltration.invoke();
}
......@@ -430,13 +430,13 @@ bool nvidia_NCV_Visualization(const std::string& test_data_path, OutputLevel out
NCVAutoTestLister testListerVisualize("Visualization", outputLevel);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, RAND_MAX, 4096, 4096);
NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, RAND_MAX, 2048, 2048);
generateDrawRectsTests(testListerVisualize, testSrcRandom_8u, testSrcRandom_32u, 4096, 4096);
generateDrawRectsTests(testListerVisualize, testSrcRandom_32u, testSrcRandom_32u, 4096, 4096);
generateDrawRectsTests(testListerVisualize, testSrcRandom_8u, testSrcRandom_32u, 2048, 2048);
generateDrawRectsTests(testListerVisualize, testSrcRandom_32u, testSrcRandom_32u, 2048, 2048);
return testListerVisualize.invoke();
}
#endif /* CUDA_DISABLER */
\ No newline at end of file
#endif /* CUDA_DISABLER */
modules/gpu/test/test_bgfg.cpp 0 → 100644
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_calib3d.cpp
View file @ b7e6b5af
......@@ -43,8 +43,6 @@
#ifdef HAVE_CUDA
namespace {
//////////////////////////////////////////////////////////////////////////
// StereoBM
......@@ -60,7 +58,7 @@ struct StereoBM : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(StereoBM, Regression)
GPU_TEST_P(StereoBM, Regression)
{
cv::Mat left_image = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
......@@ -95,7 +93,7 @@ struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(StereoBeliefPropagation, Regression)
GPU_TEST_P(StereoBeliefPropagation, Regression)
{
cv::Mat left_image = readImage("stereobp/aloe-L.png");
cv::Mat right_image = readImage("stereobp/aloe-R.png");
......@@ -133,7 +131,7 @@ struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(StereoConstantSpaceBP, Regression)
GPU_TEST_P(StereoConstantSpaceBP, Regression)
{
cv::Mat left_image = readImage("csstereobp/aloe-L.png");
cv::Mat right_image = readImage("csstereobp/aloe-R.png");
......@@ -177,7 +175,7 @@ struct TransformPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(TransformPoints, Accuracy)
GPU_TEST_P(TransformPoints, Accuracy)
{
cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
......@@ -225,7 +223,7 @@ struct ProjectPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(ProjectPoints, Accuracy)
GPU_TEST_P(ProjectPoints, Accuracy)
{
cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
......@@ -275,7 +273,7 @@ struct SolvePnPRansac : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(SolvePnPRansac, Accuracy)
GPU_TEST_P(SolvePnPRansac, Accuracy)
{
cv::Mat object = randomMat(cv::Size(5000, 1), CV_32FC3, 0, 100);
cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1);
......@@ -324,7 +322,7 @@ PARAM_TEST_CASE(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, MatDepth, Use
}
};
TEST_P(ReprojectImageTo3D, Accuracy)
GPU_TEST_P(ReprojectImageTo3D, Accuracy)
{
cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
......@@ -344,6 +342,4 @@ INSTANTIATE_TEST_CASE_P(GPU_Calib3D, ReprojectImageTo3D, testing::Combine(
testing::Values(MatDepth(CV_8U), MatDepth(CV_16S)),
WHOLE_SUBMAT));
} // namespace
#endif // HAVE_CUDA
modules/gpu/test/test_color.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_copy_make_border.cpp
View file @ b7e6b5af
......@@ -43,9 +43,10 @@
#ifdef HAVE_CUDA
namespace {
IMPLEMENT_PARAM_CLASS(Border, int)
namespace
{
IMPLEMENT_PARAM_CLASS(Border, int)
}
PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border, BorderType, UseRoi)
{
......@@ -69,7 +70,7 @@ PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border,
}
};
TEST_P(CopyMakeBorder, Accuracy)
GPU_TEST_P(CopyMakeBorder, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Scalar val = randomScalar(0, 255);
......@@ -99,6 +100,4 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CopyMakeBorder, testing::Combine(
ALL_BORDER_TYPES,
WHOLE_SUBMAT));
} // namespace
#endif // HAVE_CUDA
modules/gpu/test/test_core.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_denoising.cpp
View file @ b7e6b5af
......@@ -69,7 +69,7 @@ PARAM_TEST_CASE(BilateralFilter, cv::gpu::DeviceInfo, cv::Size, MatType)
}
};
TEST_P(BilateralFilter, Accuracy)
GPU_TEST_P(BilateralFilter, Accuracy)
{
cv::Mat src = randomMat(size, type);
......@@ -105,7 +105,7 @@ struct BruteForceNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(BruteForceNonLocalMeans, Regression)
GPU_TEST_P(BruteForceNonLocalMeans, Regression)
{
using cv::gpu::GpuMat;
......@@ -134,8 +134,6 @@ TEST_P(BruteForceNonLocalMeans, Regression)
INSTANTIATE_TEST_CASE_P(GPU_Denoising, BruteForceNonLocalMeans, ALL_DEVICES);
////////////////////////////////////////////////////////
// Fast Force Non local means
......@@ -150,7 +148,7 @@ struct FastNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(FastNonLocalMeans, Regression)
GPU_TEST_P(FastNonLocalMeans, Regression)
{
using cv::gpu::GpuMat;
......@@ -167,8 +165,8 @@ TEST_P(FastNonLocalMeans, Regression)
fnlmd.labMethod(GpuMat(bgr), dbgr, 20, 10);
#if 0
//dumpImage("denoising/fnlm_denoised_lena_bgr.png", cv::Mat(dbgr));
//dumpImage("denoising/fnlm_denoised_lena_gray.png", cv::Mat(dgray));
dumpImage("denoising/fnlm_denoised_lena_bgr.png", cv::Mat(dbgr));
dumpImage("denoising/fnlm_denoised_lena_gray.png", cv::Mat(dgray));
#endif
cv::Mat bgr_gold = readImage("denoising/fnlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
......@@ -181,5 +179,4 @@ TEST_P(FastNonLocalMeans, Regression)
INSTANTIATE_TEST_CASE_P(GPU_Denoising, FastNonLocalMeans, ALL_DEVICES);
#endif // HAVE_CUDA
modules/gpu/test/test_features2d.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_filters.cpp
View file @ b7e6b5af
......@@ -43,27 +43,30 @@
#ifdef HAVE_CUDA
namespace {
IMPLEMENT_PARAM_CLASS(KSize, cv::Size)
cv::Mat getInnerROI(cv::InputArray m_, cv::Size ksize)
namespace
{
cv::Mat m = getMat(m_);
cv::Rect roi(ksize.width, ksize.height, m.cols - 2 * ksize.width, m.rows - 2 * ksize.height);
return m(roi);
}
IMPLEMENT_PARAM_CLASS(KSize, cv::Size)
IMPLEMENT_PARAM_CLASS(Anchor, cv::Point)
IMPLEMENT_PARAM_CLASS(Deriv_X, int)
IMPLEMENT_PARAM_CLASS(Deriv_Y, int)
IMPLEMENT_PARAM_CLASS(Iterations, int)
cv::Mat getInnerROI(cv::InputArray m, int ksize)
{
return getInnerROI(m, cv::Size(ksize, ksize));
cv::Mat getInnerROI(cv::InputArray m_, cv::Size ksize)
{
cv::Mat m = getMat(m_);
cv::Rect roi(ksize.width, ksize.height, m.cols - 2 * ksize.width, m.rows - 2 * ksize.height);
return m(roi);
}
cv::Mat getInnerROI(cv::InputArray m, int ksize)
{
return getInnerROI(m, cv::Size(ksize, ksize));
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// Blur
IMPLEMENT_PARAM_CLASS(Anchor, cv::Point)
PARAM_TEST_CASE(Blur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
......@@ -86,7 +89,7 @@ PARAM_TEST_CASE(Blur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, Use
}
};
TEST_P(Blur, Accuracy)
GPU_TEST_P(Blur, Accuracy)
{
cv::Mat src = randomMat(size, type);
......@@ -110,36 +113,39 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Blur, testing::Combine(
/////////////////////////////////////////////////////////////////////////////////////////////////
// Sobel
IMPLEMENT_PARAM_CLASS(Deriv_X, int)
IMPLEMENT_PARAM_CLASS(Deriv_Y, int)
PARAM_TEST_CASE(Sobel, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Deriv_X, Deriv_Y, BorderType, UseRoi)
PARAM_TEST_CASE(Sobel, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, KSize, Deriv_X, Deriv_Y, BorderType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int depth;
int cn;
cv::Size ksize;
int dx;
int dy;
int borderType;
bool useRoi;
int type;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
ksize = GET_PARAM(3);
dx = GET_PARAM(4);
dy = GET_PARAM(5);
borderType = GET_PARAM(6);
useRoi = GET_PARAM(7);
depth = GET_PARAM(2);
cn = GET_PARAM(3);
ksize = GET_PARAM(4);
dx = GET_PARAM(5);
dy = GET_PARAM(6);
borderType = GET_PARAM(7);
useRoi = GET_PARAM(8);
cv::gpu::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(Sobel, Accuracy)
GPU_TEST_P(Sobel, Accuracy)
{
if (dx == 0 && dy == 0)
return;
......@@ -152,13 +158,14 @@ TEST_P(Sobel, Accuracy)
cv::Mat dst_gold;
cv::Sobel(src, dst_gold, -1, dx, dy, ksize.width, 1.0, 0.0, borderType);
EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
}
INSTANTIATE_TEST_CASE_P(GPU_Filter, Sobel, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32F)),
IMAGE_CHANNELS,
testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7))),
testing::Values(Deriv_X(0), Deriv_X(1), Deriv_X(2)),
testing::Values(Deriv_Y(0), Deriv_Y(1), Deriv_Y(2)),
......@@ -171,31 +178,37 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Sobel, testing::Combine(
/////////////////////////////////////////////////////////////////////////////////////////////////
// Scharr
PARAM_TEST_CASE(Scharr, cv::gpu::DeviceInfo, cv::Size, MatType, Deriv_X, Deriv_Y, BorderType, UseRoi)
PARAM_TEST_CASE(Scharr, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, Deriv_X, Deriv_Y, BorderType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int depth;
int cn;
int dx;
int dy;
int borderType;
bool useRoi;
int type;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
dx = GET_PARAM(3);
dy = GET_PARAM(4);
borderType = GET_PARAM(5);
useRoi = GET_PARAM(6);
depth = GET_PARAM(2);
cn = GET_PARAM(3);
dx = GET_PARAM(4);
dy = GET_PARAM(5);
borderType = GET_PARAM(6);
useRoi = GET_PARAM(7);
cv::gpu::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(Scharr, Accuracy)
GPU_TEST_P(Scharr, Accuracy)
{
if (dx + dy != 1)
return;
......@@ -208,13 +221,14 @@ TEST_P(Scharr, Accuracy)
cv::Mat dst_gold;
cv::Scharr(src, dst_gold, -1, dx, dy, 1.0, 0.0, borderType);
EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
EXPECT_MAT_NEAR(getInnerROI(dst_gold, cv::Size(3, 3)), getInnerROI(dst, cv::Size(3, 3)), CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
}
INSTANTIATE_TEST_CASE_P(GPU_Filter, Scharr, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32F)),
IMAGE_CHANNELS,
testing::Values(Deriv_X(0), Deriv_X(1)),
testing::Values(Deriv_Y(0), Deriv_Y(1)),
testing::Values(BorderType(cv::BORDER_REFLECT101),
......@@ -226,29 +240,35 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Scharr, testing::Combine(
/////////////////////////////////////////////////////////////////////////////////////////////////
// GaussianBlur
PARAM_TEST_CASE(GaussianBlur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, BorderType, UseRoi)
PARAM_TEST_CASE(GaussianBlur, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, KSize, BorderType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int depth;
int cn;
cv::Size ksize;
int borderType;
bool useRoi;
int type;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
ksize = GET_PARAM(3);
borderType = GET_PARAM(4);
useRoi = GET_PARAM(5);
depth = GET_PARAM(2);
cn = GET_PARAM(3);
ksize = GET_PARAM(4);
borderType = GET_PARAM(5);
useRoi = GET_PARAM(6);
cv::gpu::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(GaussianBlur, Accuracy)
GPU_TEST_P(GaussianBlur, Accuracy)
{
cv::Mat src = randomMat(size, type);
double sigma1 = randomDouble(0.1, 1.0);
......@@ -281,7 +301,8 @@ TEST_P(GaussianBlur, Accuracy)
INSTANTIATE_TEST_CASE_P(GPU_Filter, GaussianBlur, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32F)),
IMAGE_CHANNELS,
testing::Values(KSize(cv::Size(3, 3)),
KSize(cv::Size(5, 5)),
KSize(cv::Size(7, 7)),
......@@ -326,7 +347,7 @@ PARAM_TEST_CASE(Laplacian, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, UseRoi
}
};
TEST_P(Laplacian, Accuracy)
GPU_TEST_P(Laplacian, Accuracy)
{
cv::Mat src = randomMat(size, type);
......@@ -349,8 +370,6 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Laplacian, testing::Combine(
/////////////////////////////////////////////////////////////////////////////////////////////////
// Erode
IMPLEMENT_PARAM_CLASS(Iterations, int)
PARAM_TEST_CASE(Erode, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iterations, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
......@@ -373,7 +392,7 @@ PARAM_TEST_CASE(Erode, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iteration
}
};
TEST_P(Erode, Accuracy)
GPU_TEST_P(Erode, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
......@@ -422,7 +441,7 @@ PARAM_TEST_CASE(Dilate, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iteratio
}
};
TEST_P(Dilate, Accuracy)
GPU_TEST_P(Dilate, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
......@@ -476,7 +495,7 @@ PARAM_TEST_CASE(MorphEx, cv::gpu::DeviceInfo, cv::Size, MatType, MorphOp, Anchor
}
};
TEST_P(MorphEx, Accuracy)
GPU_TEST_P(MorphEx, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
......@@ -530,7 +549,7 @@ PARAM_TEST_CASE(Filter2D, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor,
}
};
TEST_P(Filter2D, Accuracy)
GPU_TEST_P(Filter2D, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
......@@ -553,6 +572,4 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Filter2D, testing::Combine(
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT)),
WHOLE_SUBMAT));
} // namespace
#endif // HAVE_CUDA
modules/gpu/test/test_global_motion.cpp
View file @ b7e6b5af
......@@ -51,7 +51,7 @@ struct CompactPoints : testing::TestWithParam<gpu::DeviceInfo>
virtual void SetUp() { gpu::setDevice(GetParam().deviceID()); }
};
TEST_P(CompactPoints, CanCompactizeSmallInput)
GPU_TEST_P(CompactPoints, CanCompactizeSmallInput)
{
Mat src0(1, 3, CV_32FC2);
src0.at<Point2f>(0,0) = Point2f(0,0);
......
modules/gpu/test/test_gpumat.cpp
View file @ b7e6b5af
......@@ -44,8 +44,6 @@
#ifdef HAVE_CUDA
namespace {
////////////////////////////////////////////////////////////////////////////////
// SetTo
......@@ -67,7 +65,7 @@ PARAM_TEST_CASE(SetTo, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
}
};
TEST_P(SetTo, Zero)
GPU_TEST_P(SetTo, Zero)
{
cv::Scalar zero = cv::Scalar::all(0);
......@@ -77,7 +75,7 @@ TEST_P(SetTo, Zero)
EXPECT_MAT_NEAR(cv::Mat::zeros(size, type), mat, 0.0);
}
TEST_P(SetTo, SameVal)
GPU_TEST_P(SetTo, SameVal)
{
cv::Scalar val = cv::Scalar::all(randomDouble(0.0, 255.0));
......@@ -102,7 +100,7 @@ TEST_P(SetTo, SameVal)
}
}
TEST_P(SetTo, DifferentVal)
GPU_TEST_P(SetTo, DifferentVal)
{
cv::Scalar val = randomScalar(0.0, 255.0);
......@@ -127,7 +125,7 @@ TEST_P(SetTo, DifferentVal)
}
}
TEST_P(SetTo, Masked)
GPU_TEST_P(SetTo, Masked)
{
cv::Scalar val = randomScalar(0.0, 255.0);
cv::Mat mat_gold = randomMat(size, type);
......@@ -184,7 +182,7 @@ PARAM_TEST_CASE(CopyTo, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
}
};
TEST_P(CopyTo, WithOutMask)
GPU_TEST_P(CopyTo, WithOutMask)
{
cv::Mat src = randomMat(size, type);
......@@ -195,7 +193,7 @@ TEST_P(CopyTo, WithOutMask)
EXPECT_MAT_NEAR(src, dst, 0.0);
}
TEST_P(CopyTo, Masked)
GPU_TEST_P(CopyTo, Masked)
{
cv::Mat src = randomMat(size, type);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
......@@ -255,7 +253,7 @@ PARAM_TEST_CASE(ConvertTo, cv::gpu::DeviceInfo, cv::Size, MatDepth, MatDepth, Us
}
};
TEST_P(ConvertTo, WithOutScaling)
GPU_TEST_P(ConvertTo, WithOutScaling)
{
cv::Mat src = randomMat(size, depth1);
......@@ -285,7 +283,7 @@ TEST_P(ConvertTo, WithOutScaling)
}
}
TEST_P(ConvertTo, WithScaling)
GPU_TEST_P(ConvertTo, WithScaling)
{
cv::Mat src = randomMat(size, depth1);
double a = randomDouble(0.0, 1.0);
......@@ -324,6 +322,4 @@ INSTANTIATE_TEST_CASE_P(GPU_GpuMat, ConvertTo, testing::Combine(
ALL_DEPTH,
WHOLE_SUBMAT));
} // namespace
#endif // HAVE_CUDA
modules/gpu/test/test_hough.cpp
View file @ b7e6b5af
......@@ -43,8 +43,6 @@
#ifdef HAVE_CUDA
namespace {
///////////////////////////////////////////////////////////////////////////////////////////////////////
// HoughLines
......@@ -79,7 +77,7 @@ PARAM_TEST_CASE(HoughLines, cv::gpu::DeviceInfo, cv::Size, UseRoi)
}
};
TEST_P(HoughLines, Accuracy)
GPU_TEST_P(HoughLines, Accuracy)
{
const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
......@@ -87,7 +85,7 @@ TEST_P(HoughLines, Accuracy)
const bool useRoi = GET_PARAM(2);
const float rho = 1.0f;
const float theta = 1.5f * CV_PI / 180.0f;
const float theta = (float) (1.5 * CV_PI / 180.0);
const int threshold = 100;
cv::Mat src(size, CV_8UC1);
......@@ -124,7 +122,7 @@ PARAM_TEST_CASE(HoughCircles, cv::gpu::DeviceInfo, cv::Size, UseRoi)
}
};
TEST_P(HoughCircles, Accuracy)
GPU_TEST_P(HoughCircles, Accuracy)
{
const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
......@@ -188,7 +186,7 @@ PARAM_TEST_CASE(GeneralizedHough, cv::gpu::DeviceInfo, UseRoi)
{
};
TEST_P(GeneralizedHough, POSITION)
GPU_TEST_P(GeneralizedHough, POSITION)
{
const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
......@@ -251,6 +249,4 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, GeneralizedHough, testing::Combine(
ALL_DEVICES,
WHOLE_SUBMAT));
} // namespace
#endif // HAVE_CUDA
modules/gpu/test/test_imgproc.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_labeling.cpp
View file @ b7e6b5af
......@@ -43,8 +43,8 @@
#ifdef HAVE_CUDA
namespace {
namespace
{
struct GreedyLabeling
{
struct dot
......@@ -82,7 +82,7 @@ namespace {
int cc = -1;
int* dist_labels = (int*)labels.data;
int pitch = labels.step1();
int pitch = (int) labels.step1();
unsigned char* source = (unsigned char*)image.data;
int width = image.cols;
......@@ -166,7 +166,7 @@ struct Labeling : testing::TestWithParam<cv::gpu::DeviceInfo>
}
};
TEST_P(Labeling, ConnectedComponents)
GPU_TEST_P(Labeling, DISABLED_ConnectedComponents)
{
cv::Mat image;
cvtColor(loat_image(), image, CV_BGR2GRAY);
......@@ -186,11 +186,11 @@ TEST_P(Labeling, ConnectedComponents)
cv::gpu::connectivityMask(cv::gpu::GpuMat(image), mask, cv::Scalar::all(0), cv::Scalar::all(2));
ASSERT_NO_THROW(cv::gpu::labelComponents(mask, components));
cv::gpu::labelComponents(mask, components);
host.checkCorrectness(cv::Mat(components));
}
INSTANTIATE_TEST_CASE_P(ConnectedComponents, Labeling, ALL_DEVICES);
INSTANTIATE_TEST_CASE_P(GPU_ConnectedComponents, Labeling, ALL_DEVICES);
#endif // HAVE_CUDA
modules/gpu/test/test_nvidia.cpp
View file @ b7e6b5af
......@@ -41,11 +41,9 @@
#include "test_precomp.hpp"
#if defined HAVE_CUDA
OutputLevel nvidiaTestOutputLevel = OutputLevelNone;
#endif
#ifdef HAVE_CUDA
#if defined HAVE_CUDA && !defined(CUDA_DISABLER)
OutputLevel nvidiaTestOutputLevel = OutputLevelNone;
using namespace cvtest;
using namespace testing;
......@@ -69,77 +67,77 @@ struct NVidiaTest : TestWithParam<cv::gpu::DeviceInfo>
struct NPPST : NVidiaTest {};
struct NCV : NVidiaTest {};
//TEST_P(NPPST, Integral)
//{
// bool res = nvidia_NPPST_Integral_Image(path, nvidiaTestOutputLevel);
GPU_TEST_P(NPPST, Integral)
{
bool res = nvidia_NPPST_Integral_Image(_path, nvidiaTestOutputLevel);
// ASSERT_TRUE(res);
//}
ASSERT_TRUE(res);
}
TEST_P(NPPST, SquaredIntegral)
GPU_TEST_P(NPPST, SquaredIntegral)
{
bool res = nvidia_NPPST_Squared_Integral_Image(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, RectStdDev)
GPU_TEST_P(NPPST, RectStdDev)
{
bool res = nvidia_NPPST_RectStdDev(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, Resize)
GPU_TEST_P(NPPST, Resize)
{
bool res = nvidia_NPPST_Resize(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, VectorOperations)
GPU_TEST_P(NPPST, VectorOperations)
{
bool res = nvidia_NPPST_Vector_Operations(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NPPST, Transpose)
GPU_TEST_P(NPPST, Transpose)
{
bool res = nvidia_NPPST_Transpose(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, VectorOperations)
GPU_TEST_P(NCV, VectorOperations)
{
bool res = nvidia_NCV_Vector_Operations(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, HaarCascadeLoader)
GPU_TEST_P(NCV, HaarCascadeLoader)
{
bool res = nvidia_NCV_Haar_Cascade_Loader(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, HaarCascadeApplication)
GPU_TEST_P(NCV, HaarCascadeApplication)
{
bool res = nvidia_NCV_Haar_Cascade_Application(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, HypothesesFiltration)
GPU_TEST_P(NCV, HypothesesFiltration)
{
bool res = nvidia_NCV_Hypotheses_Filtration(_path, nvidiaTestOutputLevel);
ASSERT_TRUE(res);
}
TEST_P(NCV, Visualization)
GPU_TEST_P(NCV, Visualization)
{
// this functionality doesn't used in gpu module
bool res = nvidia_NCV_Visualization(_path, nvidiaTestOutputLevel);
......
modules/gpu/test/test_objdetect.cpp
View file @ b7e6b5af
......@@ -43,8 +43,6 @@
#ifdef HAVE_CUDA
namespace {
//#define DUMP
struct HOG : testing::TestWithParam<cv::gpu::DeviceInfo>, cv::gpu::HOGDescriptor
......@@ -176,7 +174,7 @@ struct HOG : testing::TestWithParam<cv::gpu::DeviceInfo>, cv::gpu::HOGDescriptor
};
// desabled while resize does not fixed
TEST_P(HOG, DISABLED_Detect)
GPU_TEST_P(HOG, Detect)
{
cv::Mat img_rgb = readImage("hog/road.png");
ASSERT_FALSE(img_rgb.empty());
......@@ -201,7 +199,7 @@ TEST_P(HOG, DISABLED_Detect)
f.close();
}
TEST_P(HOG, GetDescriptors)
GPU_TEST_P(HOG, GetDescriptors)
{
// Load image (e.g. train data, composed from windows)
cv::Mat img_rgb = readImage("hog/train_data.png");
......@@ -288,6 +286,7 @@ TEST_P(HOG, GetDescriptors)
INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, HOG, ALL_DEVICES);
//============== caltech hog tests =====================//
struct CalTech : public ::testing::TestWithParam<std::tr1::tuple<cv::gpu::DeviceInfo, std::string> >
{
cv::gpu::DeviceInfo devInfo;
......@@ -303,7 +302,7 @@ struct CalTech : public ::testing::TestWithParam<std::tr1::tuple<cv::gpu::Device
}
};
TEST_P(CalTech, HOG)
GPU_TEST_P(CalTech, HOG)
{
cv::gpu::GpuMat d_img(img);
cv::Mat markedImage(img.clone());
......@@ -350,7 +349,7 @@ PARAM_TEST_CASE(LBP_Read_classifier, cv::gpu::DeviceInfo, int)
}
};
TEST_P(LBP_Read_classifier, Accuracy)
GPU_TEST_P(LBP_Read_classifier, Accuracy)
{
cv::gpu::CascadeClassifier_GPU classifier;
std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
......@@ -372,7 +371,7 @@ PARAM_TEST_CASE(LBP_classify, cv::gpu::DeviceInfo, int)
}
};
TEST_P(LBP_classify, Accuracy)
GPU_TEST_P(LBP_classify, Accuracy)
{
std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
std::string imagePath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/er.png";
......@@ -422,6 +421,4 @@ TEST_P(LBP_classify, Accuracy)
INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify,
testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
} // namespace
#endif // HAVE_CUDA
modules/gpu/test/test_optflow.cpp 0 → 100644
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_precomp.hpp
View file @ b7e6b5af
......@@ -51,6 +51,7 @@
#define __OPENCV_TEST_PRECOMP_HPP__
#include <cmath>
#include <ctime>
#include <cstdio>
#include <iostream>
#include <fstream>
......
modules/gpu/test/test_pyramids.cpp
View file @ b7e6b5af
......@@ -64,7 +64,7 @@ PARAM_TEST_CASE(PyrDown, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
}
};
TEST_P(PyrDown, Accuracy)
GPU_TEST_P(PyrDown, Accuracy)
{
cv::Mat src = randomMat(size, type);
......@@ -104,7 +104,7 @@ PARAM_TEST_CASE(PyrUp, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
}
};
TEST_P(PyrUp, Accuracy)
GPU_TEST_P(PyrUp, Accuracy)
{
cv::Mat src = randomMat(size, type);
......
modules/gpu/test/test_remap.cpp
View file @ b7e6b5af
......@@ -152,7 +152,7 @@ PARAM_TEST_CASE(Remap, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, Bo
}
};
TEST_P(Remap, Accuracy)
GPU_TEST_P(Remap, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Scalar val = randomScalar(0.0, 255.0);
......
modules/gpu/test/test_resize.cpp
View file @ b7e6b5af
......@@ -136,7 +136,7 @@ PARAM_TEST_CASE(Resize, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpol
}
};
TEST_P(Resize, Accuracy)
GPU_TEST_P(Resize, Accuracy)
{
cv::Mat src = randomMat(size, type);
......@@ -157,8 +157,8 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
WHOLE_SUBMAT));
/////////////////
PARAM_TEST_CASE(ResizeSameAsHost, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpolation, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
......@@ -182,7 +182,7 @@ PARAM_TEST_CASE(ResizeSameAsHost, cv::gpu::DeviceInfo, cv::Size, MatType, double
};
// downscaling only: used for classifiers
TEST_P(ResizeSameAsHost, Accuracy)
GPU_TEST_P(ResizeSameAsHost, Accuracy)
{
cv::Mat src = randomMat(size, type);
......@@ -224,7 +224,7 @@ PARAM_TEST_CASE(ResizeNPP, cv::gpu::DeviceInfo, MatType, double, Interpolation)
}
};
TEST_P(ResizeNPP, Accuracy)
GPU_TEST_P(ResizeNPP, Accuracy)
{
cv::Mat src = readImageType("stereobp/aloe-L.png", type);
ASSERT_FALSE(src.empty());
......
modules/gpu/test/test_threshold.cpp
View file @ b7e6b5af
......@@ -66,7 +66,7 @@ PARAM_TEST_CASE(Threshold, cv::gpu::DeviceInfo, cv::Size, MatType, ThreshOp, Use
}
};
TEST_P(Threshold, Accuracy)
GPU_TEST_P(Threshold, Accuracy)
{
cv::Mat src = randomMat(size, type);
double maxVal = randomDouble(20.0, 127.0);
......
modules/gpu/test/test_video.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_warp_affine.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/test_warp_perspective.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/utility.cpp
View file @ b7e6b5af
This diff is collapsed.
modules/gpu/test/utility.hpp
View file @ b7e6b5af
This diff is collapsed.
modules/ts/include/opencv2/ts/ts.hpp
View file @ b7e6b5af
#ifndef __OPENCV_GTESTCV_HPP__
#define __OPENCV_GTESTCV_HPP__
#if HAVE_CVCONFIG_H
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif
#ifndef GTEST_CREATE_SHARED_LIBRARY
......
modules/ts/src/ts_perf.cpp
View file @ b7e6b5af
#include "precomp.hpp"
#ifdef HAVE_CUDA
#include "opencv2/core/gpumat.hpp"
#endif
#ifdef ANDROID
# include <sys/time.h>
#endif
......@@ -1160,6 +1164,10 @@ void TestBase::RunPerfTestBody()
catch(cv::Exception e)
{
metrics.terminationReason = performance_metrics::TERM_EXCEPTION;
#ifdef HAVE_CUDA
if (e.code == CV_GpuApiCallError)
cv::gpu::resetDevice();
#endif
FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n Actual: it throws cv::Exception:\n " << e.what();
}
catch(std::exception e)
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment