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the code was refactored and old test system code was removed

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This commit is contained in:
ilya-lavrenov 2013-08-23 18:38:31 +04:00
parent 4c28a6f0f6
commit d02ccc9590
23 changed files with 547 additions and 2286 deletions
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161
modules/ocl/perf/main.cpp
View File

@ -42,153 +42,54 @@
#include "perf_precomp.hpp"
static int old_main(int argc, const char *argv[])
const char * impls[] =
{
const char *keys =
"{ h | help | false | print help message }"
"{ f | filter | | filter for test }"
"{ w | workdir | | set working directory }"
"{ l | list | false | show all tests }"
"{ d | device | 0 | device id }"
"{ c | cpu_ocl | false | use cpu as ocl device}"
"{ i | iters | 10 | iteration count }"
"{ m | warmup | 1 | gpu warm up iteration count}"
"{ t | xtop | 1.1 | xfactor top boundary}"
"{ b | xbottom | 0.9 | xfactor bottom boundary}"
"{ v | verify | false | only run gpu once to verify if problems occur}";
IMPL_OCL,
IMPL_PLAIN,
#ifdef HAVE_OPENCV_GPU
IMPL_GPU
#endif
};
int main(int argc, char ** argv)
{
const char * keys =
"{ h | help | false | print help message }"
"{ t | type | gpu | set device type:cpu or gpu}"
"{ p | platform | 0 | set platform id }"
"{ d | device | 0 | set device id }";
redirectError(cvErrorCallback);
CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Avaible options:" << endl;
cout << "Available options besides google test option:" << endl;
cmd.printParams();
return 0;
}
// get ocl devices
bool use_cpu = cmd.get<bool>("c");
vector<ocl::Info> oclinfo;
int num_devices = 0;
if(use_cpu)
num_devices = getDevice(oclinfo, ocl::CVCL_DEVICE_TYPE_CPU);
else
num_devices = getDevice(oclinfo);
if (num_devices < 1)
{
cerr << "no device found\n";
return -1;
}
// show device info
int devidx = 0;
for (size_t i = 0; i < oclinfo.size(); i++)
{
for (size_t j = 0; j < oclinfo[i].DeviceName.size(); j++)
{
cout << "device " << devidx++ << ": " << oclinfo[i].DeviceName[j] << endl;
}
}
string type = cmd.get<string>("type");
unsigned int pid = cmd.get<unsigned int>("platform");
int device = cmd.get<int>("device");
if (device < 0 || device >= num_devices)
int flag = type == "cpu" ? cv::ocl::CVCL_DEVICE_TYPE_CPU :
cv::ocl::CVCL_DEVICE_TYPE_GPU;
std::vector<cv::ocl::Info> oclinfo;
int devnums = cv::ocl::getDevice(oclinfo, flag);
if (devnums <= device || device < 0)
{
cerr << "Invalid device ID" << endl;
std::cout << "device invalid\n";
return -1;
}
// set this to overwrite binary cache every time the test starts
ocl::setBinaryDiskCache(ocl::CACHE_UPDATE);
if (cmd.get<bool>("verify"))
if (pid >= oclinfo.size())
{
TestSystem::instance().setNumIters(1);
TestSystem::instance().setGPUWarmupIters(0);
TestSystem::instance().setCPUIters(0);
std::cout << "platform invalid\n";
return -1;
}
devidx = 0;
for (size_t i = 0; i < oclinfo.size(); i++)
{
for (size_t j = 0; j < oclinfo[i].DeviceName.size(); j++, devidx++)
{
if (device == devidx)
{
ocl::setDevice(oclinfo[i], (int)j);
TestSystem::instance().setRecordName(oclinfo[i].DeviceName[j]);
cout << "use " << devidx << ": " <<oclinfo[i].DeviceName[j] << endl;
goto END_DEV;
}
}
}
END_DEV:
string filter = cmd.get<string>("filter");
string workdir = cmd.get<string>("workdir");
bool list = cmd.get<bool>("list");
int iters = cmd.get<int>("iters");
int wu_iters = cmd.get<int>("warmup");
double x_top = cmd.get<double>("xtop");
double x_bottom = cmd.get<double>("xbottom");
TestSystem::instance().setTopThreshold(x_top);
TestSystem::instance().setBottomThreshold(x_bottom);
if (!filter.empty())
{
TestSystem::instance().setTestFilter(filter);
}
if (!workdir.empty())
{
if (workdir[workdir.size() - 1] != '/' && workdir[workdir.size() - 1] != '\\')
{
workdir += '/';
}
TestSystem::instance().setWorkingDir(workdir);
}
if (list)
{
TestSystem::instance().setListMode(true);
}
TestSystem::instance().setNumIters(iters);
TestSystem::instance().setGPUWarmupIters(wu_iters);
TestSystem::instance().run();
return 0;
}
const char * impls[] =
{
"ocl",
"plain",
#ifdef HAVE_OPENCV_GPU
"gpu"
#endif
};
int main(int argc, char **argv)
{
// temp solution: if no '--gtest_' and '--perf_' args switch to old behavior
bool useGTest = false;
for(int i=1; i<argc; i++)
{
std::string arg( argv[i] );
if( arg.find("--gtest_")==0 || arg.find("--perf_")==0 )
useGTest = true;
// if (arg == "--perf_verify_sanity")
// argv[i] = (char*)"--perf_no_verify_sanity";
}
if( !useGTest )
return old_main(argc, (const char**)argv);
cv::ocl::setDevice(oclinfo[pid], device);
cv::ocl::setBinaryDiskCache(cv::ocl::CACHE_UPDATE);
CV_PERF_TEST_MAIN_INTERNALS(ocl, impls)
}

468
modules/ocl/perf/perf_arithm.cpp
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File diff suppressed because it is too large Load Diff

14
modules/ocl/perf/perf_blend.cpp
View File

@ -82,12 +82,9 @@ typedef TestBaseWithParam<Size> blendLinearFixture;
PERF_TEST_P(blendLinearFixture, blendLinear, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const int type = CV_8UC1;
const std::string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, CV_8UC1), dst;
Mat weights1(srcSize, CV_32FC1), weights2(srcSize, CV_32FC1);
@ -95,8 +92,7 @@ PERF_TEST_P(blendLinearFixture, blendLinear, OCL_TYPICAL_MAT_SIZES)
randu(weights1, 0.0f, 1.0f);
randu(weights2, 0.0f, 1.0f);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst;
ocl::oclMat oclWeights1(weights1), oclWeights2(weights2);
@ -107,16 +103,12 @@ PERF_TEST_P(blendLinearFixture, blendLinear, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

151
modules/ocl/perf/perf_brute_force_matcher.cpp
View File

@ -53,11 +53,10 @@ using namespace perf;
typedef TestBaseWithParam<Size> BruteForceMatcherFixture;
PERF_TEST_P(BruteForceMatcherFixture, match,
OCL_BFMATCHER_TYPICAL_MAT_SIZES)
PERF_TEST_P(BruteForceMatcherFixture, DISABLED_match,
OCL_BFMATCHER_TYPICAL_MAT_SIZES) // TODO too big difference between implementations
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
vector<DMatch> matches;
Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
@ -65,16 +64,15 @@ PERF_TEST_P(BruteForceMatcherFixture, match,
randu(query, 0.0f, 1.0f);
randu(train, 0.0f, 1.0f);
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
BFMatcher matcher(NORM_L2);
TEST_CYCLE() matcher.match(query, train, matches);
SANITY_CHECK_MATCHES(matches);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
// Init GPU matcher
ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
ocl::oclMat oclQuery(query), oclTrain(train);
@ -82,53 +80,14 @@ PERF_TEST_P(BruteForceMatcherFixture, match,
SANITY_CHECK_MATCHES(matches);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
//PERF_TEST_P(BruteForceMatcherFixture, matchSingle,
// OCL_BFMATCHER_TYPICAL_MAT_SIZES)
//{
// const Size srcSize = GetParam();
// const string impl = getSelectedImpl();
// Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
// Mat trainIdx, distance;
// randu(query, 0.0f, 1.0f);
// randu(train, 0.0f, 1.0f);
// if (impl == "plain")
// CV_TEST_FAIL_NO_IMPL();
// else if (impl == "ocl")
// {
// ocl::oclMat oclQuery(query), oclTrain(train), oclTrainIdx, oclDistance;
// TEST_CYCLE() oclMatcher->matchSingle(oclQuery, oclTrain, oclTrainIdx, oclDistance);
// oclTrainIdx.download(trainIdx);
// oclDistance.download(distance);
// SANITY_CHECK(trainIdx);
// SANITY_CHECK(distance);
// }
//#ifdef HAVE_OPENCV_GPU
// else if (impl == "gpu")
// CV_TEST_FAIL_NO_IMPL();
//#endif
// else
// CV_TEST_FAIL_NO_IMPL();
//}
PERF_TEST_P(BruteForceMatcherFixture, knnMatch,
OCL_BFMATCHER_TYPICAL_MAT_SIZES)
PERF_TEST_P(BruteForceMatcherFixture, DISABLED_knnMatch,
OCL_BFMATCHER_TYPICAL_MAT_SIZES) // TODO too many outliers
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
vector<vector<DMatch> > matches(2);
Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
@ -139,7 +98,7 @@ PERF_TEST_P(BruteForceMatcherFixture, knnMatch,
if (srcSize.height == 2000)
declare.time(8);
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
BFMatcher matcher (NORM_L2);
TEST_CYCLE() matcher.knnMatch(query, train, matches, 2);
@ -148,7 +107,7 @@ PERF_TEST_P(BruteForceMatcherFixture, knnMatch,
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
ocl::oclMat oclQuery(query), oclTrain(train);
@ -159,55 +118,14 @@ PERF_TEST_P(BruteForceMatcherFixture, knnMatch,
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
//PERF_TEST_P(BruteForceMatcherFixture, knnMatchSingle,
// OCL_BFMATCHER_TYPICAL_MAT_SIZES)
//{
// const Size srcSize = GetParam();
// const string impl = getSelectedImpl();
// Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
// Mat trainIdx, distance, allDist;
// randu(query, 0.0f, 1.0f);
// randu(train, 0.0f, 1.0f);
// if (impl == "plain")
// CV_TEST_FAIL_NO_IMPL();
// else if (impl == "ocl")
// {
// ocl::oclMat oclQuery(query), oclTrain(train), oclTrainIdx, oclDistance, oclAllDist;
// TEST_CYCLE() oclMatcher->knnMatchSingle(oclQuery, oclTrain, oclTrainIdx, oclDistance, oclAllDist, 2);
// oclTrainIdx.download(trainIdx);
// oclDistance.download(distance);
// oclAllDist.download(allDist);
// SANITY_CHECK(trainIdx);
// SANITY_CHECK(distance);
// SANITY_CHECK(allDist);
// }
//#ifdef HAVE_OPENCV_GPU
// else if (impl == "gpu")
// CV_TEST_FAIL_NO_IMPL();
//#endif
// else
// CV_TEST_FAIL_NO_IMPL();
//}
PERF_TEST_P(BruteForceMatcherFixture, DISABLED_radiusMatch,
OCL_BFMATCHER_TYPICAL_MAT_SIZES)
OCL_BFMATCHER_TYPICAL_MAT_SIZES) // TODO too many outliers
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
const float max_distance = 2.0f;
vector<vector<DMatch> > matches(2);
@ -218,7 +136,7 @@ PERF_TEST_P(BruteForceMatcherFixture, DISABLED_radiusMatch,
randu(query, 0.0f, 1.0f);
randu(train, 0.0f, 1.0f);
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
BFMatcher matcher (NORM_L2);
TEST_CYCLE() matcher.radiusMatch(query, matches, max_distance);
@ -227,7 +145,7 @@ PERF_TEST_P(BruteForceMatcherFixture, DISABLED_radiusMatch,
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
ocl::oclMat oclQuery(query), oclTrain(train);
ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
@ -238,49 +156,8 @@ PERF_TEST_P(BruteForceMatcherFixture, DISABLED_radiusMatch,
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
//PERF_TEST_P(BruteForceMatcherFixture, radiusMatchSingle,
// OCL_BFMATCHER_TYPICAL_MAT_SIZES)
//{
// const Size srcSize = GetParam();
// const string impl = getSelectedImpl();
// const float max_distance = 2.0f;
// Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
// Mat trainIdx, distance, nMatches;
// randu(query, 0.0f, 1.0f);
// randu(train, 0.0f, 1.0f);
// if (impl == "plain")
// CV_TEST_FAIL_NO_IMPL();
// else if (impl == "ocl")
// {
// ocl::oclMat oclQuery(query), oclTrain(train), oclTrainIdx, oclDistance, oclNMatches;
// TEST_CYCLE() oclMatcher->radiusMatchSingle(oclQuery, oclTrain, oclTrainIdx, oclDistance, oclNMatches, max_distance);
// oclTrainIdx.download(trainIdx);
// oclDistance.download(distance);
// oclNMatches.download(nMatches);
// SANITY_CHECK(trainIdx);
// SANITY_CHECK(distance);
// SANITY_CHECK(nMatches);
// }
//#ifdef HAVE_OPENCV_GPU
// else if (impl == "gpu")
// CV_TEST_FAIL_NO_IMPL();
//#endif
// else
// CV_TEST_FAIL_NO_IMPL();
//}
#undef OCL_BFMATCHER_TYPICAL_MAT_SIZES

15
modules/ocl/perf/perf_calib3d.cpp
View File

@ -48,7 +48,7 @@
///////////// StereoMatchBM ////////////////////////
PERF_TEST(StereoMatchBMFixture, DISABLED_StereoMatchBM)
PERF_TEST(StereoMatchBMFixture, DISABLED_StereoMatchBM) // TODO doesn't work properly
{
Mat left_image = imread(getDataPath("gpu/stereobm/aloe-L.png"), cv::IMREAD_GRAYSCALE);
Mat right_image = imread(getDataPath("gpu/stereobm/aloe-R.png"), cv::IMREAD_GRAYSCALE);
@ -58,13 +58,12 @@ PERF_TEST(StereoMatchBMFixture, DISABLED_StereoMatchBM)
ASSERT_TRUE(right_image.size() == left_image.size());
ASSERT_TRUE(right_image.size() == left_image.size());
const std::string impl = getSelectedImpl();
const int n_disp = 128, winSize = 19;
Mat disp(left_image.size(), CV_16SC1);
declare.in(left_image, right_image).out(disp);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclLeft(left_image), oclRight(right_image),
oclDisp(left_image.size(), CV_16SC1);
@ -76,7 +75,7 @@ PERF_TEST(StereoMatchBMFixture, DISABLED_StereoMatchBM)
SANITY_CHECK(disp);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
StereoBM bm(0, n_disp, winSize);
@ -84,10 +83,6 @@ PERF_TEST(StereoMatchBMFixture, DISABLED_StereoMatchBM)
SANITY_CHECK(disp);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
else
OCL_PERF_ELSE
}

17
modules/ocl/perf/perf_canny.cpp
View File

@ -49,34 +49,29 @@ using namespace perf;
///////////// Canny ////////////////////////
PERF_TEST(CannyFixture, Canny)
PERF_TEST(CannyFixture, DISABLED_Canny) // TODO difference between implmentations
{
Mat img = imread(getDataPath("gpu/stereobm/aloe-L.png"), cv::IMREAD_GRAYSCALE),
edges(img.size(), CV_8UC1);
ASSERT_TRUE(!img.empty()) << "can't open aloeL.jpg";
ASSERT_TRUE(!img.empty()) << "can't open aloe-L.png";
const std::string impl = getSelectedImpl();
declare.in(img).out(edges);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclImg(img), oclEdges(img.size(), CV_8UC1);
TEST_CYCLE() Canny(oclImg, oclEdges, 50.0, 100.0);
TEST_CYCLE() ocl::Canny(oclImg, oclEdges, 50.0, 100.0);
oclEdges.download(edges);
SANITY_CHECK(edges);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() Canny(img, edges, 50.0, 100.0);
SANITY_CHECK(edges);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

13
modules/ocl/perf/perf_color.cpp
View File

@ -54,12 +54,11 @@ typedef TestBaseWithParam<Size> cvtColorFixture;
PERF_TEST_P(cvtColorFixture, cvtColor, OCL_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
Mat src(srcSize, CV_8UC4), dst(srcSize, CV_8UC4);
declare.in(src).out(dst);
declare.in(src, WARMUP_RNG).out(dst);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(src.size(), CV_8UC4);
@ -68,16 +67,12 @@ PERF_TEST_P(cvtColorFixture, cvtColor, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::cvtColor(src, dst, CV_RGBA2GRAY, 4);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

22
modules/ocl/perf/perf_fft.cpp
View File

@ -51,37 +51,33 @@ using namespace perf;
typedef TestBaseWithParam<Size> dftFixture;
PERF_TEST_P(dftFixture, DISABLED_dft, OCL_TYPICAL_MAT_SIZES)
PERF_TEST_P(dftFixture, DISABLED_dft, OCL_TYPICAL_MAT_SIZES) // TODO not implemented
{
const std::string impl = getSelectedImpl();
Size srcSize = GetParam();
const Size srcSize = GetParam();
Mat src(srcSize, CV_32FC2), dst;
randu(src, 0.0f, 1.0f);
declare.in(src);
if (impl == "ocl")
if (srcSize == OCL_SIZE_4000)
declare.time(7.4);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst;
EXPECT_NO_THROW({
TEST_CYCLE() cv::ocl::dft(oclSrc, oclDst);
});
TEST_CYCLE() cv::ocl::dft(oclSrc, oclDst);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::dft(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

149
modules/ocl/perf/perf_filters.cpp
View File

@ -51,29 +51,23 @@ using std::tr1::tuple;
///////////// Blur////////////////////////
CV_ENUM(BlurMatType, CV_8UC1, CV_8UC4)
typedef tuple<Size, BlurMatType> BlurParams;
typedef TestBaseWithParam<BlurParams> BlurFixture;
typedef Size_MatType BlurFixture;
PERF_TEST_P(BlurFixture, Blur,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
BlurMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
BlurParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params), ksize(3, 3);
const int type = get<1>(params), bordertype = BORDER_CONSTANT;
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(5);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -83,44 +77,35 @@ PERF_TEST_P(BlurFixture, Blur,
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::blur(src, dst, ksize, Point(-1, -1), bordertype);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// Laplacian////////////////////////
typedef BlurMatType LaplacianMatType;
typedef tuple<Size, LaplacianMatType> LaplacianParams;
typedef TestBaseWithParam<LaplacianParams> LaplacianFixture;
typedef Size_MatType LaplacianFixture;
PERF_TEST_P(LaplacianFixture, Laplacian,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
LaplacianMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
LaplacianParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 3;
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(6);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -130,46 +115,36 @@ PERF_TEST_P(LaplacianFixture, Laplacian,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::Laplacian(src, dst, -1, ksize, 1);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// Erode ////////////////////
CV_ENUM(ErodeMatType, CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4)
typedef tuple<Size, ErodeMatType> ErodeParams;
typedef TestBaseWithParam<ErodeParams> ErodeFixture;
typedef Size_MatType ErodeFixture;
PERF_TEST_P(ErodeFixture, Erode,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ErodeMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4)))
{
// getting params
ErodeParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 3;
const Mat ker = getStructuringElement(MORPH_RECT, Size(ksize, ksize));
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst).in(ker);
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(5);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type), oclKer(ker);
@ -179,37 +154,28 @@ PERF_TEST_P(ErodeFixture, Erode,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::erode(src, dst, ker);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// Sobel ////////////////////////
typedef BlurMatType SobelMatType;
typedef tuple<Size, SobelMatType> SobelMatParams;
typedef TestBaseWithParam<SobelMatParams> SobelFixture;
typedef Size_MatType SobelFixture;
PERF_TEST_P(SobelFixture, Sobel,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
SobelMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
SobelMatParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), dx = 1, dy = 1;
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
@ -219,7 +185,7 @@ PERF_TEST_P(SobelFixture, Sobel,
else if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(20);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -229,37 +195,28 @@ PERF_TEST_P(SobelFixture, Sobel,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::Sobel(src, dst, -1, dx, dy);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// Scharr ////////////////////////
typedef BlurMatType ScharrMatType;
typedef tuple<Size, ScharrMatType> ScharrParams;
typedef TestBaseWithParam<ScharrParams> ScharrFixture;
typedef Size_MatType ScharrFixture;
PERF_TEST_P(ScharrFixture, Scharr,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ScharrMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
ScharrParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), dx = 1, dy = 0;
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
@ -269,7 +226,7 @@ PERF_TEST_P(ScharrFixture, Scharr,
else if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(21);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -279,43 +236,34 @@ PERF_TEST_P(ScharrFixture, Scharr,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::Scharr(src, dst, -1, dx, dy);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// GaussianBlur ////////////////////////
typedef ErodeMatType GaussianBlurMatType;
typedef tuple<Size, GaussianBlurMatType> GaussianBlurParams;
typedef TestBaseWithParam<GaussianBlurParams> GaussianBlurFixture;
typedef Size_MatType GaussianBlurFixture;
PERF_TEST_P(GaussianBlurFixture, GaussianBlur,
::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
GaussianBlurMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4)))
{
// getting params
GaussianBlurParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 7;
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
const double eps = src.depth() == CV_8U ? 1 + DBL_EPSILON : 3e-4;
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -325,37 +273,28 @@ PERF_TEST_P(GaussianBlurFixture, GaussianBlur,
SANITY_CHECK(dst, eps);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::GaussianBlur(src, dst, Size(ksize, ksize), 0);
SANITY_CHECK(dst, eps);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// filter2D////////////////////////
typedef BlurMatType filter2DMatType;
typedef tuple<Size, filter2DMatType> filter2DParams;
typedef TestBaseWithParam<filter2DParams> filter2DFixture;
typedef Size_MatType filter2DFixture;
PERF_TEST_P(filter2DFixture, filter2D,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
filter2DMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
filter2DParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 3;
const std::string impl = getSelectedImpl();
Mat src(srcSize, type), dst(srcSize, type), kernel(ksize, ksize, CV_32SC1);
declare.in(src, WARMUP_RNG).in(kernel).out(dst);
randu(kernel, -3.0, 3.0);
@ -363,7 +302,7 @@ PERF_TEST_P(filter2DFixture, filter2D,
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(8);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type), oclKernel(kernel);
@ -373,16 +312,12 @@ PERF_TEST_P(filter2DFixture, filter2D,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::filter2D(src, dst, -1, kernel);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

14
modules/ocl/perf/perf_gemm.cpp
View File

@ -51,11 +51,9 @@ using namespace perf;
typedef TestBaseWithParam<Size> gemmFixture;
PERF_TEST_P(gemmFixture, DISABLED_gemm, OCL_TYPICAL_MAT_SIZES)
PERF_TEST_P(gemmFixture, DISABLED_gemm, OCL_TYPICAL_MAT_SIZES) // TODO not implemented
{
// getting params
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
src3(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
@ -64,7 +62,7 @@ PERF_TEST_P(gemmFixture, DISABLED_gemm, OCL_TYPICAL_MAT_SIZES)
randu(src2, -10.0f, 10.0f);
randu(src3, -10.0f, 10.0f);
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2),
oclSrc3(src3), oclDst(srcSize, CV_32FC1);
@ -75,16 +73,12 @@ PERF_TEST_P(gemmFixture, DISABLED_gemm, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::gemm(src1, src2, 1.0, src3, 1.0, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

22
modules/ocl/perf/perf_gftt.cpp
View File

@ -60,22 +60,22 @@ PERF_TEST_P(GoodFeaturesToTrackFixture, GoodFeaturesToTrack,
string("gpu/stereobm/aloe-L.png")),
::testing::Range(0.0, 4.0, 3.0)))
{
std::vector<cv::Point2f> pts_gold;
// getting params
GoodFeaturesToTrackParams param = GetParam();
const string fileName = getDataPath(get<0>(param)), impl = getSelectedImpl();
const GoodFeaturesToTrackParams param = GetParam();
const string fileName = getDataPath(get<0>(param));
const int maxCorners = 2000;
const double qualityLevel = 0.01, minDistance = get<1>(param);
Mat frame = imread(fileName, IMREAD_GRAYSCALE);
declare.in(frame);
ASSERT_TRUE(!frame.empty()) << "no input image";
if (impl == "ocl")
vector<Point2f> pts_gold;
declare.in(frame);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclFrame(frame), pts_oclmat;
cv::ocl::GoodFeaturesToTrackDetector_OCL detector(maxCorners, qualityLevel, minDistance);
ocl::GoodFeaturesToTrackDetector_OCL detector(maxCorners, qualityLevel, minDistance);
TEST_CYCLE() detector(oclFrame, pts_oclmat);
@ -83,17 +83,13 @@ PERF_TEST_P(GoodFeaturesToTrackFixture, GoodFeaturesToTrack,
SANITY_CHECK(pts_gold);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::goodFeaturesToTrack(frame, pts_gold,
maxCorners, qualityLevel, minDistance);
SANITY_CHECK(pts_gold);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

12
modules/ocl/perf/perf_haar.cpp
View File

@ -88,14 +88,13 @@ public:
PERF_TEST(HaarFixture, Haar)
{
const std::string impl = getSelectedImpl();
vector<Rect> faces;
Mat img = imread(getDataPath("gpu/haarcascade/basketball1.png"), CV_LOAD_IMAGE_GRAYSCALE);
ASSERT_TRUE(!img.empty()) << "can't open basketball1.png";
declare.in(img);
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
CascadeClassifier faceCascade;
ASSERT_TRUE(faceCascade.load(getDataPath("gpu/haarcascade/haarcascade_frontalface_alt.xml")))
@ -106,7 +105,7 @@ PERF_TEST(HaarFixture, Haar)
SANITY_CHECK(faces, 4 + 1e-4);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
ocl::CascadeClassifier_GPU faceCascade;
ocl::oclMat oclImg(img);
@ -119,11 +118,6 @@ PERF_TEST(HaarFixture, Haar)
SANITY_CHECK(faces, 4 + 1e-4);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

17
modules/ocl/perf/perf_hog.cpp
View File

@ -54,22 +54,21 @@ PERF_TEST(HOGFixture, HOG)
Mat src = imread(getDataPath("gpu/hog/road.png"), cv::IMREAD_GRAYSCALE);
ASSERT_TRUE(!src.empty()) << "can't open input image road.png";
const std::string impl = getSelectedImpl();
std::vector<cv::Rect> found_locations;
vector<cv::Rect> found_locations;
declare.in(src).time(5);
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
cv::HOGDescriptor hog;
HOGDescriptor hog;
hog.setSVMDetector(hog.getDefaultPeopleDetector());
TEST_CYCLE() hog.detectMultiScale(src, found_locations);
SANITY_CHECK(found_locations, 1 + DBL_EPSILON);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
cv::ocl::HOGDescriptor ocl_hog;
ocl::HOGDescriptor ocl_hog;
ocl_hog.setSVMDetector(ocl_hog.getDefaultPeopleDetector());
ocl::oclMat oclSrc(src);
@ -77,10 +76,6 @@ PERF_TEST(HOGFixture, HOG)
SANITY_CHECK(found_locations, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

253
modules/ocl/perf/perf_imgproc.cpp
View File

@ -55,16 +55,12 @@ typedef TestBaseWithParam<Size> equalizeHistFixture;
PERF_TEST_P(equalizeHistFixture, equalizeHist, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_8UC1), dst(srcSize, CV_8UC1);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, src.type());
@ -74,45 +70,34 @@ PERF_TEST_P(equalizeHistFixture, equalizeHist, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::equalizeHist(src, dst);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
/////////// CopyMakeBorder //////////////////////
CV_ENUM(CopyMakeBorderMatType, CV_8UC1, CV_8UC4)
typedef tuple<Size, CopyMakeBorderMatType> CopyMakeBorderParams;
typedef TestBaseWithParam<CopyMakeBorderParams> CopyMakeBorderFixture;
typedef Size_MatType CopyMakeBorderFixture;
PERF_TEST_P(CopyMakeBorderFixture, CopyMakeBorder,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
CopyMakeBorderMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
CopyMakeBorderParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), borderType = BORDER_CONSTANT;
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst;
const Size dstSize = srcSize + Size(12, 12);
dst.create(dstSize, type);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
@ -122,40 +107,29 @@ PERF_TEST_P(CopyMakeBorderFixture, CopyMakeBorder,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::copyMakeBorder(src, dst, 7, 5, 5, 7, borderType, cv::Scalar(1.0));
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// cornerMinEigenVal ////////////////////////
CV_ENUM(cornerMinEigenValMatType, CV_8UC1, CV_32FC1)
typedef tuple<Size, cornerMinEigenValMatType> cornerMinEigenValParams;
typedef TestBaseWithParam<cornerMinEigenValParams> cornerMinEigenValFixture;
typedef Size_MatType cornerMinEigenValFixture;
PERF_TEST_P(cornerMinEigenValFixture, cornerMinEigenVal,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
cornerMinEigenValMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
{
// getting params
cornerMinEigenValParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), borderType = BORDER_REFLECT;
const int blockSize = 7, apertureSize = 1 + 2 * 3;
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
declare.in(src, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_4000 ? 20 : srcSize == OCL_SIZE_2000 ? 5 : 3);
@ -163,8 +137,7 @@ PERF_TEST_P(cornerMinEigenValFixture, cornerMinEigenVal,
const int depth = CV_MAT_DEPTH(type);
const ERROR_TYPE errorType = depth == CV_8U ? ERROR_ABSOLUTE : ERROR_RELATIVE;
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
@ -174,45 +147,34 @@ PERF_TEST_P(cornerMinEigenValFixture, cornerMinEigenVal,
SANITY_CHECK(dst, 1e-6, errorType);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::cornerMinEigenVal(src, dst, blockSize, apertureSize, borderType);
SANITY_CHECK(dst, 1e-6, errorType);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// cornerHarris ////////////////////////
typedef cornerMinEigenValMatType cornerHarrisMatType;
typedef tuple<Size, cornerHarrisMatType> cornerHarrisParams;
typedef TestBaseWithParam<cornerHarrisParams> cornerHarrisFixture;
typedef Size_MatType cornerHarrisFixture;
PERF_TEST_P(cornerHarrisFixture, cornerHarris,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
cornerHarrisMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
{
// getting params
cornerHarrisParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), borderType = BORDER_REFLECT;
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
randu(src, 0, 1);
declare.in(src).out(dst)
.time(srcSize == OCL_SIZE_4000 ? 20 : srcSize == OCL_SIZE_2000 ? 5 : 3);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
@ -222,36 +184,28 @@ PERF_TEST_P(cornerHarrisFixture, cornerHarris,
SANITY_CHECK(dst, 3e-5);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::cornerHarris(src, dst, 5, 7, 0.1, borderType);
SANITY_CHECK(dst, 3e-5);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// integral ////////////////////////
typedef TestBaseWithParam<Size> integralFixture;
PERF_TEST_P(integralFixture, DISABLED_integral, OCL_TYPICAL_MAT_SIZES)
PERF_TEST_P(integralFixture, DISABLED_integral, OCL_TYPICAL_MAT_SIZES) // TODO does not work properly
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_8UC1), dst;
declare.in(src, WARMUP_RNG);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst;
@ -261,29 +215,23 @@ PERF_TEST_P(integralFixture, DISABLED_integral, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::integral(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// WarpAffine ////////////////////////
typedef CopyMakeBorderMatType WarpAffineMatType;
typedef tuple<Size, WarpAffineMatType> WarpAffineParams;
typedef TestBaseWithParam<WarpAffineParams> WarpAffineFixture;
typedef Size_MatType WarpAffineFixture;
PERF_TEST_P(WarpAffineFixture, WarpAffine,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
WarpAffineMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
static const double coeffs[2][3] =
{
@ -293,18 +241,14 @@ PERF_TEST_P(WarpAffineFixture, WarpAffine,
Mat M(2, 3, CV_64F, (void *)coeffs);
const int interpolation = INTER_NEAREST;
// getting params
WarpAffineParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -314,29 +258,23 @@ PERF_TEST_P(WarpAffineFixture, WarpAffine,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::warpAffine(src, dst, M, srcSize, interpolation);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// WarpPerspective ////////////////////////
typedef CopyMakeBorderMatType WarpPerspectiveMatType;
typedef tuple<Size, WarpPerspectiveMatType> WarpPerspectiveParams;
typedef TestBaseWithParam<WarpPerspectiveParams> WarpPerspectiveFixture;
typedef Size_MatType WarpPerspectiveFixture;
PERF_TEST_P(WarpPerspectiveFixture, WarpPerspective,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
WarpPerspectiveMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
static const double coeffs[3][3] =
{
@ -347,19 +285,15 @@ PERF_TEST_P(WarpPerspectiveFixture, WarpPerspective,
Mat M(3, 3, CV_64F, (void *)coeffs);
const int interpolation = INTER_LINEAR;
// getting params
WarpPerspectiveParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_4000 ? 18 : srcSize == OCL_SIZE_2000 ? 5 : 2);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -369,42 +303,34 @@ PERF_TEST_P(WarpPerspectiveFixture, WarpPerspective,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::warpPerspective(src, dst, M, srcSize, interpolation);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// resize ////////////////////////
CV_ENUM(resizeInterType, INTER_NEAREST, INTER_LINEAR)
typedef CopyMakeBorderMatType resizeMatType;
typedef tuple<Size, resizeMatType, resizeInterType, double> resizeParams;
typedef tuple<Size, MatType, resizeInterType, double> resizeParams;
typedef TestBaseWithParam<resizeParams> resizeFixture;
PERF_TEST_P(resizeFixture, resize,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
resizeMatType::all(),
OCL_PERF_ENUM(CV_8UC1, CV_8UC4),
resizeInterType::all(),
::testing::Values(0.5, 2.0)))
{
// getting params
resizeParams params = GetParam();
const resizeParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), interType = get<2>(params);
double scale = get<3>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst;
const Size dstSize(cvRound(srcSize.width * scale), cvRound(srcSize.height * scale));
dst.create(dstSize, type);
@ -412,8 +338,7 @@ PERF_TEST_P(resizeFixture, resize,
if (interType == INTER_LINEAR && type == CV_8UC4 && OCL_SIZE_4000 == srcSize)
declare.time(11);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
@ -423,18 +348,14 @@ PERF_TEST_P(resizeFixture, resize,
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::resize(src, dst, Size(), scale, scale, interType);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// threshold////////////////////////
@ -448,19 +369,15 @@ PERF_TEST_P(ThreshFixture, threshold,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ThreshType::all()))
{
// getting params
ThreshParams params = GetParam();
const ThreshParams params = GetParam();
const Size srcSize = get<0>(params);
const int threshType = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_8U), dst(srcSize, CV_8U);
randu(src, 0, 100);
declare.in(src).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_8U);
@ -470,23 +387,19 @@ PERF_TEST_P(ThreshFixture, threshold,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::threshold(src, dst, 50.0, 0.0, threshType);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// meanShiftFiltering////////////////////////
typedef struct
typedef struct _COOR
{
short x;
short y;
@ -681,7 +594,6 @@ PERF_TEST_P(meanShiftFilteringFixture, meanShiftFiltering,
{
const Size srcSize = GetParam();
const int sp = 5, sr = 6;
const string impl = getSelectedImpl();
cv::TermCriteria crit(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1);
Mat src(srcSize, CV_8UC4), dst(srcSize, CV_8UC4);
@ -689,13 +601,13 @@ PERF_TEST_P(meanShiftFilteringFixture, meanShiftFiltering,
.time(srcSize == OCL_SIZE_4000 ?
56 : srcSize == OCL_SIZE_2000 ? 15 : 3.8);
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() meanShiftFiltering_(src, dst, sp, sr, crit);
SANITY_CHECK(dst);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_8UC4);
@ -705,12 +617,8 @@ PERF_TEST_P(meanShiftFilteringFixture, meanShiftFiltering,
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
static void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp, int sr, cv::TermCriteria crit)
@ -778,7 +686,6 @@ PERF_TEST_P(meanShiftProcFixture, meanShiftProc,
OCL_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
TermCriteria crit(TermCriteria::COUNT + TermCriteria::EPS, 5, 1);
Mat src(srcSize, CV_8UC4), dst1(srcSize, CV_8UC4),
@ -787,14 +694,14 @@ PERF_TEST_P(meanShiftProcFixture, meanShiftProc,
.time(srcSize == OCL_SIZE_4000 ?
56 : srcSize == OCL_SIZE_2000 ? 15 : 3.8);;
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() meanShiftProc_(src, dst1, dst2, 5, 6, crit);
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst1(srcSize, CV_8UC4),
oclDst2(srcSize, CV_16SC2);
@ -807,34 +714,26 @@ PERF_TEST_P(meanShiftProcFixture, meanShiftProc,
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// remap////////////////////////
CV_ENUM(RemapInterType, INTER_NEAREST, INTER_LINEAR)
typedef CopyMakeBorderMatType remapMatType;
typedef tuple<Size, remapMatType, RemapInterType> remapParams;
typedef tuple<Size, MatType, RemapInterType> remapParams;
typedef TestBaseWithParam<remapParams> remapFixture;
PERF_TEST_P(remapFixture, remap,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
remapMatType::all(),
OCL_PERF_ENUM(CV_8UC1, CV_8UC4),
RemapInterType::all()))
{
// getting params
remapParams params = GetParam();
const remapParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), interpolation = get<2>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
@ -859,8 +758,7 @@ PERF_TEST_P(remapFixture, remap,
const int borderMode = BORDER_CONSTANT;
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
ocl::oclMat oclXMap(xmap), oclYMap(ymap);
@ -871,18 +769,14 @@ PERF_TEST_P(remapFixture, remap,
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::remap(src, dst, xmap, ymap, interpolation, borderMode);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// CLAHE ////////////////////////
@ -891,11 +785,9 @@ typedef TestBaseWithParam<Size> CLAHEFixture;
PERF_TEST_P(CLAHEFixture, CLAHE, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_8UC1), dst;
const double clipLimit = 40.0;
declare.in(src, WARMUP_RNG);
@ -903,8 +795,7 @@ PERF_TEST_P(CLAHEFixture, CLAHE, OCL_TYPICAL_MAT_SIZES)
if (srcSize == OCL_SIZE_4000)
declare.time(11);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst;
cv::Ptr<cv::CLAHE> oclClahe = cv::ocl::createCLAHE(clipLimit);
@ -915,19 +806,15 @@ PERF_TEST_P(CLAHEFixture, CLAHE, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(clipLimit);
TEST_CYCLE() clahe->apply(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// columnSum////////////////////////
@ -946,19 +833,15 @@ static void columnSumPerfTest(const Mat & src, Mat & dst)
PERF_TEST_P(columnSumFixture, columnSum, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
declare.in(src, WARMUP_RNG).out(dst);
if (srcSize == OCL_SIZE_4000)
declare.time(5);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
@ -968,16 +851,12 @@ PERF_TEST_P(columnSumFixture, columnSum, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() columnSumPerfTest(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

38
modules/ocl/perf/perf_match_template.cpp
View File

@ -51,23 +51,16 @@ using std::tr1::get;
/////////// matchTemplate ////////////////////////
CV_ENUM(CV_TM_CCORRMatType, CV_32FC1, CV_32FC4)
typedef tuple<Size, CV_TM_CCORRMatType> CV_TM_CCORRParams;
typedef TestBaseWithParam<CV_TM_CCORRParams> CV_TM_CCORRFixture;
typedef Size_MatType CV_TM_CCORRFixture;
PERF_TEST_P(CV_TM_CCORRFixture, matchTemplate,
::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
CV_TM_CCORRMatType::all()))
OCL_PERF_ENUM(CV_32FC1, CV_32FC4)))
{
// getting params
CV_TM_CCORRParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params), templSize(5, 5);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), templ(templSize, type);
const Size dstSize(src.cols - templ.cols + 1, src.rows - templ.rows + 1);
Mat dst(dstSize, CV_32F);
@ -75,8 +68,7 @@ PERF_TEST_P(CV_TM_CCORRFixture, matchTemplate,
randu(templ, 0.0f, 1.0f);
declare.time(srcSize == OCL_SIZE_2000 ? 20 : 6).in(src, templ).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclTempl(templ), oclDst(dstSize, CV_32F);
@ -86,37 +78,29 @@ PERF_TEST_P(CV_TM_CCORRFixture, matchTemplate,
SANITY_CHECK(dst, 1e-4);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::matchTemplate(src, templ, dst, CV_TM_CCORR);
SANITY_CHECK(dst, 1e-4);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
typedef TestBaseWithParam<Size> CV_TM_CCORR_NORMEDFixture;
PERF_TEST_P(CV_TM_CCORR_NORMEDFixture, matchTemplate, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam(), templSize(5, 5);
const std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_8UC1), templ(templSize, CV_8UC1), dst;
const Size dstSize(src.cols - templ.cols + 1, src.rows - templ.rows + 1);
dst.create(dstSize, CV_8UC1);
declare.in(src, templ, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_2000 ? 10 : srcSize == OCL_SIZE_4000 ? 23 : 2);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclTempl(templ), oclDst(dstSize, CV_8UC1);
@ -126,16 +110,12 @@ PERF_TEST_P(CV_TM_CCORR_NORMEDFixture, matchTemplate, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(dst, 2e-2);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
SANITY_CHECK(dst, 2e-2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

70
modules/ocl/perf/perf_matrix_operation.cpp
View File

@ -51,30 +51,22 @@ using std::tr1::get;
///////////// ConvertTo////////////////////////
CV_ENUM(ConvertToMatType, CV_8UC1, CV_8UC4)
typedef tuple<Size, ConvertToMatType> ConvertToParams;
typedef TestBaseWithParam<ConvertToParams> ConvertToFixture;
typedef Size_MatType ConvertToFixture;
PERF_TEST_P(ConvertToFixture, ConvertTo,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ConvertToMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
ConvertToParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst;
const int dstType = CV_MAKE_TYPE(CV_32F, src.channels());
dst.create(srcSize, dstType);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, dstType);
@ -84,43 +76,32 @@ PERF_TEST_P(ConvertToFixture, ConvertTo,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() src.convertTo(dst, dstType);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// copyTo////////////////////////
typedef ConvertToMatType copyToMatType;
typedef tuple<Size, copyToMatType> copyToParams;
typedef TestBaseWithParam<copyToParams> copyToFixture;
typedef Size_MatType copyToFixture;
PERF_TEST_P(copyToFixture, copyTo,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
copyToMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
copyToParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
@ -130,44 +111,33 @@ PERF_TEST_P(copyToFixture, copyTo,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() src.copyTo(dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// setTo////////////////////////
typedef ConvertToMatType setToMatType;
typedef tuple<Size, setToMatType> setToParams;
typedef TestBaseWithParam<setToParams> setToFixture;
typedef Size_MatType setToFixture;
PERF_TEST_P(setToFixture, setTo,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
setToMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
setToParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const Scalar val(1, 2, 3, 4);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type);
declare.in(src);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(srcSize, type);
@ -176,16 +146,12 @@ PERF_TEST_P(setToFixture, setTo,
SANITY_CHECK(src);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() src.setTo(val);
SANITY_CHECK(src);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

26
modules/ocl/perf/perf_moments.cpp
View File

@ -52,50 +52,38 @@ using std::tr1::get;
///////////// Moments ////////////////////////
CV_ENUM(MomentsMatType, CV_8UC1, CV_16SC1, CV_32FC1, CV_64FC1)
typedef tuple<Size, MomentsMatType> MomentsParams;
typedef TestBaseWithParam<MomentsParams> MomentsFixture;
typedef Size_MatType MomentsFixture;
PERF_TEST_P(MomentsFixture, DISABLED_Moments,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
MomentsMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_16SC1, CV_32FC1, CV_64FC1))) // TODO does not work properly (see below)
{
// getting params
MomentsParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(7, 1, CV_64F);
const bool binaryImage = false;
cv::Moments mom;
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
TEST_CYCLE() mom = cv::ocl::ocl_moments(oclSrc, binaryImage);
TEST_CYCLE() mom = cv::ocl::ocl_moments(oclSrc, binaryImage); // TODO Use oclSrc
cv::HuMoments(mom, dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() mom = cv::moments(src, binaryImage);
cv::HuMoments(mom, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

15
modules/ocl/perf/perf_norm.cpp
View File

@ -53,21 +53,18 @@ using std::tr1::get;
typedef TestBaseWithParam<Size> normFixture;
PERF_TEST_P(normFixture, DISABLED_norm, OCL_TYPICAL_MAT_SIZES)
PERF_TEST_P(normFixture, DISABLED_norm, OCL_TYPICAL_MAT_SIZES) // TODO doesn't work properly
{
// getting params
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
double value = 0.0;
// creating src data
Mat src1(srcSize, CV_8UC1), src2(srcSize, CV_8UC1);
declare.in(src1, src2);
randu(src1, 0, 1);
randu(src2, 0, 1);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2);
@ -75,16 +72,12 @@ PERF_TEST_P(normFixture, DISABLED_norm, OCL_TYPICAL_MAT_SIZES)
SANITY_CHECK(value);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() value = cv::norm(src1, src2, NORM_INF);
SANITY_CHECK(value);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

318
modules/ocl/perf/perf_opticalflow.cpp
View File

@ -70,25 +70,25 @@ typedef tuple<int, tuple<string, string, LoadMode> > PyrLKOpticalFlowParamType;
typedef TestBaseWithParam<PyrLKOpticalFlowParamType> PyrLKOpticalFlowFixture;
PERF_TEST_P(PyrLKOpticalFlowFixture,
PyrLKOpticalFlow,
DISABLED_PyrLKOpticalFlow,
::testing::Combine(
::testing::Values(1000, 2000, 4000),
::testing::Values(
make_tuple<string, string, LoadMode>
(
string("gpu/opticalflow/rubberwhale1.png"),
string("gpu/opticalflow/rubberwhale1.png"),
string("gpu/opticalflow/rubberwhale2.png"),
LoadMode(IMREAD_COLOR)
)
// , make_tuple<string, string, LoadMode>
// (
// string("gpu/stereobm/aloe-L.png"),
// string("gpu/stereobm/aloe-R.png"),
// LoadMode(IMREAD_GRAYSCALE)
// )
, make_tuple<string, string, LoadMode>
(
string("gpu/stereobm/aloe-L.png"),
string("gpu/stereobm/aloe-R.png"),
LoadMode(IMREAD_GRAYSCALE)
)
)
)
)
) // TODO to big difference between implementations
{
PyrLKOpticalFlowParamType params = GetParam();
tuple<string, string, LoadMode> fileParam = get<1>(params);
@ -97,7 +97,6 @@ PERF_TEST_P(PyrLKOpticalFlowFixture,
const string fileName0 = get<0>(fileParam), fileName1 = get<1>(fileParam);
Mat frame0 = imread(getDataPath(fileName0), openMode);
Mat frame1 = imread(getDataPath(fileName1), openMode);
const string impl = getSelectedImpl();
ASSERT_FALSE(frame0.empty()) << "can't load " << fileName0;
ASSERT_FALSE(frame1.empty()) << "can't load " << fileName1;
@ -108,14 +107,12 @@ PERF_TEST_P(PyrLKOpticalFlowFixture,
else
grayFrame = frame0;
// initialization
vector<Point2f> pts, nextPts;
vector<unsigned char> status;
vector<float> err;
goodFeaturesToTrack(grayFrame, pts, pointsCount, 0.01, 0.0);
// selecting implementation
if (impl == "plain")
if (RUN_PLAIN_IMPL)
{
TEST_CYCLE()
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
@ -124,7 +121,7 @@ PERF_TEST_P(PyrLKOpticalFlowFixture,
SANITY_CHECK(status);
SANITY_CHECK(err);
}
else if (impl == "ocl")
else if (RUN_OCL_IMPL)
{
ocl::PyrLKOpticalFlow oclPyrLK;
ocl::oclMat oclFrame0(frame0), oclFrame1(frame1);
@ -142,228 +139,135 @@ PERF_TEST_P(PyrLKOpticalFlowFixture,
SANITY_CHECK(status);
SANITY_CHECK(err);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
// size_t mismatch = 0;
// for (int i = 0; i < (int)nextPts.size(); ++i)
// {
// if(status[i] != ocl_status.at<unsigned char>(0, i))
// {
// mismatch++;
// continue;
// }
// if(status[i])
// {
// Point2f gpu_rst = ocl_nextPts.at<Point2f>(0, i);
// Point2f cpu_rst = nextPts[i];
// if(fabs(gpu_rst.x - cpu_rst.x) >= 1. || fabs(gpu_rst.y - cpu_rst.y) >= 1.)
// mismatch++;
// }
// }
// double ratio = (double)mismatch / (double)nextPts.size();
// if(ratio < .02)
// TestSystem::instance().setAccurate(1, ratio);
// else
// TestSystem::instance().setAccurate(0, ratio);
OCL_PERF_ELSE
}
PERFTEST(tvl1flow)
PERF_TEST(tvl1flowFixture, tvl1flow)
{
cv::Mat frame0 = imread("rubberwhale1.png", cv::IMREAD_GRAYSCALE);
assert(!frame0.empty());
Mat frame0 = imread(getDataPath("gpu/opticalflow/rubberwhale1.png"), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty()) << "can't load rubberwhale1.png";
cv::Mat frame1 = imread("rubberwhale2.png", cv::IMREAD_GRAYSCALE);
assert(!frame1.empty());
Mat frame1 = imread(getDataPath("gpu/opticalflow/rubberwhale2.png"), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty()) << "can't load rubberwhale2.png";
cv::ocl::OpticalFlowDual_TVL1_OCL d_alg;
cv::ocl::oclMat d_flowx(frame0.size(), CV_32FC1);
cv::ocl::oclMat d_flowy(frame1.size(), CV_32FC1);
const Size srcSize = frame0.size();
const double eps = 1.2;
Mat flow(srcSize, CV_32FC2), flow1(srcSize, CV_32FC1), flow2(srcSize, CV_32FC1);
declare.in(frame0, frame1).out(flow1, flow2).time(159);
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
cv::Mat flow;
if (RUN_PLAIN_IMPL)
{
Ptr<DenseOpticalFlow> alg = createOptFlow_DualTVL1();
TEST_CYCLE() alg->calc(frame0, frame1, flow);
SUBTEST << frame0.cols << 'x' << frame0.rows << "; rubberwhale1.png; "<<frame1.cols<<'x'<<frame1.rows<<"; rubberwhale2.png";
alg->collectGarbage();
Mat flows[2] = { flow1, flow2 };
split(flow, flows);
alg->calc(frame0, frame1, flow);
SANITY_CHECK(flow1, eps);
SANITY_CHECK(flow2, eps);
}
else if (RUN_OCL_IMPL)
{
ocl::OpticalFlowDual_TVL1_OCL oclAlg;
ocl::oclMat oclFrame0(frame0), oclFrame1(frame1), oclFlow1(srcSize, CV_32FC1),
oclFlow2(srcSize, CV_32FC1);
CPU_ON;
alg->calc(frame0, frame1, flow);
CPU_OFF;
TEST_CYCLE() oclAlg(oclFrame0, oclFrame1, oclFlow1, oclFlow2);
cv::Mat gold[2];
cv::split(flow, gold);
oclAlg.collectGarbage();
cv::ocl::oclMat d0(frame0.size(), CV_32FC1);
d0.upload(frame0);
cv::ocl::oclMat d1(frame1.size(), CV_32FC1);
d1.upload(frame1);
oclFlow1.download(flow1);
oclFlow2.download(flow2);
WARMUP_ON;
d_alg(d0, d1, d_flowx, d_flowy);
WARMUP_OFF;
/*
double diff1 = 0.0, diff2 = 0.0;
if(ExceptedMatSimilar(gold[0], cv::Mat(d_flowx), 3e-3, diff1) == 1
&&ExceptedMatSimilar(gold[1], cv::Mat(d_flowy), 3e-3, diff2) == 1)
TestSystem::instance().setAccurate(1);
else
TestSystem::instance().setAccurate(0);
TestSystem::instance().setDiff(diff1);
TestSystem::instance().setDiff(diff2);
*/
GPU_ON;
d_alg(d0, d1, d_flowx, d_flowy);
d_alg.collectGarbage();
GPU_OFF;
cv::Mat flowx, flowy;
GPU_FULL_ON;
d0.upload(frame0);
d1.upload(frame1);
d_alg(d0, d1, d_flowx, d_flowy);
d_alg.collectGarbage();
d_flowx.download(flowx);
d_flowy.download(flowy);
GPU_FULL_OFF;
TestSystem::instance().ExceptedMatSimilar(gold[0], flowx, 3e-3);
TestSystem::instance().ExceptedMatSimilar(gold[1], flowy, 3e-3);
SANITY_CHECK(flow1, eps);
SANITY_CHECK(flow2, eps);
}
else
OCL_PERF_ELSE
}
///////////// FarnebackOpticalFlow ////////////////////////
PERFTEST(FarnebackOpticalFlow)
CV_ENUM(farneFlagType, 0, OPTFLOW_FARNEBACK_GAUSSIAN)
typedef tuple<tuple<int, double>, farneFlagType, bool> FarnebackOpticalFlowParams;
typedef TestBaseWithParam<FarnebackOpticalFlowParams> FarnebackOpticalFlowFixture;
PERF_TEST_P(FarnebackOpticalFlowFixture, FarnebackOpticalFlow,
::testing::Combine(
::testing::Values(make_tuple<int, double>(5, 1.1),
make_tuple<int, double>(7, 1.5)),
farneFlagType::all(),
::testing::Bool()))
{
cv::Mat frame0 = imread("rubberwhale1.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty());
Mat frame0 = imread(getDataPath("gpu/opticalflow/rubberwhale1.png"), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty()) << "can't load rubberwhale1.png";
cv::Mat frame1 = imread("rubberwhale2.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty());
Mat frame1 = imread(getDataPath("gpu/opticalflow/rubberwhale2.png"), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame1.empty()) << "can't load rubberwhale2.png";
cv::ocl::oclMat d_frame0(frame0), d_frame1(frame1);
const Size srcSize = frame0.size();
int polyNs[2] = { 5, 7 };
double polySigmas[2] = { 1.1, 1.5 };
int farneFlags[2] = { 0, cv::OPTFLOW_FARNEBACK_GAUSSIAN };
bool UseInitFlows[2] = { false, true };
double pyrScale = 0.5;
const FarnebackOpticalFlowParams params = GetParam();
const tuple<int, double> polyParams = get<0>(params);
const int polyN = get<0>(polyParams), flags = get<1>(params);
const double polySigma = get<1>(polyParams), pyrScale = 0.5;
const bool useInitFlow = get<2>(params);
const double eps = 1.5;
string farneFlagStrs[2] = { "BoxFilter", "GaussianBlur" };
string useInitFlowStrs[2] = { "", "UseInitFlow" };
Mat flowx(srcSize, CV_32FC1), flowy(srcSize, CV_32FC1), flow(srcSize, CV_32FC2);
declare.in(frame0, frame1).out(flowx, flowy);
for ( int i = 0; i < 2; ++i)
ocl::FarnebackOpticalFlow farn;
farn.pyrScale = pyrScale;
farn.polyN = polyN;
farn.polySigma = polySigma;
farn.flags = flags;
if (RUN_PLAIN_IMPL)
{
int polyN = polyNs[i];
double polySigma = polySigmas[i];
for ( int j = 0; j < 2; ++j)
if (useInitFlow)
{
int flags = farneFlags[j];
calcOpticalFlowFarneback(
frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
farn.flags |= OPTFLOW_USE_INITIAL_FLOW;
}
for ( int k = 0; k < 2; ++k)
{
bool useInitFlow = UseInitFlows[k];
SUBTEST << "polyN(" << polyN << "); " << farneFlagStrs[j] << "; " << useInitFlowStrs[k];
cv::ocl::FarnebackOpticalFlow farn;
farn.pyrScale = pyrScale;
farn.polyN = polyN;
farn.polySigma = polySigma;
farn.flags = flags;
cv::ocl::oclMat d_flowx, d_flowy;
cv::Mat flow, flowBuf, flowxBuf, flowyBuf;
WARMUP_ON;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
if (useInitFlow)
{
cv::Mat flowxy[] = {cv::Mat(d_flowx), cv::Mat(d_flowy)};
cv::merge(flowxy, 2, flow);
flow.copyTo(flowBuf);
flowxy[0].copyTo(flowxBuf);
flowxy[1].copyTo(flowyBuf);
farn.flags |= cv::OPTFLOW_USE_INITIAL_FLOW;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
}
WARMUP_OFF;
cv::calcOpticalFlowFarneback(
TEST_CYCLE()
calcOpticalFlowFarneback(
frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
std::vector<cv::Mat> flowxy;
cv::split(flow, flowxy);
Mat flowxy[2] = { flowx, flowy };
split(flow, flowxy);
Mat md_flowx = cv::Mat(d_flowx);
Mat md_flowy = cv::Mat(d_flowy);
TestSystem::instance().ExceptedMatSimilar(flowxy[0], md_flowx, 0.1);
TestSystem::instance().ExceptedMatSimilar(flowxy[1], md_flowy, 0.1);
if (useInitFlow)
{
cv::Mat flowx, flowy;
farn.flags = (flags | cv::OPTFLOW_USE_INITIAL_FLOW);
CPU_ON;
cv::calcOpticalFlowFarneback(
frame0, frame1, flowBuf, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
CPU_OFF;
GPU_ON;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
GPU_OFF;
GPU_FULL_ON;
d_frame0.upload(frame0);
d_frame1.upload(frame1);
d_flowx.upload(flowxBuf);
d_flowy.upload(flowyBuf);
farn(d_frame0, d_frame1, d_flowx, d_flowy);
d_flowx.download(flowx);
d_flowy.download(flowy);
GPU_FULL_OFF;
}
else
{
cv::Mat flow, flowx, flowy;
cv::ocl::oclMat d_flowx, d_flowy;
farn.flags = flags;
CPU_ON;
cv::calcOpticalFlowFarneback(
frame0, frame1, flow, farn.pyrScale, farn.numLevels, farn.winSize,
farn.numIters, farn.polyN, farn.polySigma, farn.flags);
CPU_OFF;
GPU_ON;
farn(d_frame0, d_frame1, d_flowx, d_flowy);
GPU_OFF;
GPU_FULL_ON;
d_frame0.upload(frame0);
d_frame1.upload(frame1);
farn(d_frame0, d_frame1, d_flowx, d_flowy);
d_flowx.download(flowx);
d_flowy.download(flowy);
GPU_FULL_OFF;
}
}
}
SANITY_CHECK(flowx, eps);
SANITY_CHECK(flowy, eps);
}
else if (RUN_OCL_IMPL)
{
ocl::oclMat oclFrame0(frame0), oclFrame1(frame1),
oclFlowx(srcSize, CV_32FC1), oclFlowy(srcSize, CV_32FC1);
if (useInitFlow)
{
farn(oclFrame0, oclFrame1, oclFlowx, oclFlowy);
farn.flags |= OPTFLOW_USE_INITIAL_FLOW;
}
TEST_CYCLE()
farn(oclFrame0, oclFrame1, oclFlowx, oclFlowy);
oclFlowx.download(flowx);
oclFlowy.download(flowy);
SANITY_CHECK(flowx, eps);
SANITY_CHECK(flowy, eps);
}
else
OCL_PERF_ELSE
}

449
modules/ocl/perf/perf_precomp.cpp
View File

@ -41,452 +41,3 @@
//M*/
#include "perf_precomp.hpp"
#if GTEST_OS_WINDOWS
#ifndef NOMINMAX
#define NOMINMAX
#endif
# include <windows.h>
#endif
// This program test most of the functions in ocl module and generate data metrix of x-factor in .csv files
// All images needed in this test are in samples/gpu folder.
// For haar template, haarcascade_frontalface_alt.xml shouold be in working directory
void TestSystem::run()
{
if (is_list_mode_)
{
for (vector<Runnable *>::iterator it = tests_.begin(); it != tests_.end(); ++it)
{
cout << (*it)->name() << endl;
}
return;
}
// Run test initializers
for (vector<Runnable *>::iterator it = inits_.begin(); it != inits_.end(); ++it)
{
if ((*it)->name().find(test_filter_, 0) != string::npos)
{
(*it)->run();
}
}
printHeading();
writeHeading();
// Run tests
for (vector<Runnable *>::iterator it = tests_.begin(); it != tests_.end(); ++it)
{
try
{
if ((*it)->name().find(test_filter_, 0) != string::npos)
{
cout << endl << (*it)->name() << ":\n";
setCurrentTest((*it)->name());
//fprintf(record_,"%s\n",(*it)->name().c_str());
(*it)->run();
finishCurrentSubtest();
}
}
catch (const Exception &)
{
// Message is printed via callback
resetCurrentSubtest();
}
catch (const runtime_error &e)
{
printError(e.what());
resetCurrentSubtest();
}
}
printSummary();
writeSummary();
}
void TestSystem::finishCurrentSubtest()
{
if (cur_subtest_is_empty_)
// There is no need to print subtest statistics
{
return;
}
double cpu_time = cpu_elapsed_ / getTickFrequency() * 1000.0;
double gpu_time = gpu_elapsed_ / getTickFrequency() * 1000.0;
double gpu_full_time = gpu_full_elapsed_ / getTickFrequency() * 1000.0;
double speedup = static_cast<double>(cpu_elapsed_) / std::max(1.0, gpu_elapsed_);
speedup_total_ += speedup;
double fullspeedup = static_cast<double>(cpu_elapsed_) / std::max(1.0, gpu_full_elapsed_);
speedup_full_total_ += fullspeedup;
if (speedup > top_)
{
speedup_faster_count_++;
}
else if (speedup < bottom_)
{
speedup_slower_count_++;
}
else
{
speedup_equal_count_++;
}
if (fullspeedup > top_)
{
speedup_full_faster_count_++;
}
else if (fullspeedup < bottom_)
{
speedup_full_slower_count_++;
}
else
{
speedup_full_equal_count_++;
}
// compute min, max and
std::sort(gpu_times_.begin(), gpu_times_.end());
double gpu_min = gpu_times_.front() / getTickFrequency() * 1000.0;
double gpu_max = gpu_times_.back() / getTickFrequency() * 1000.0;
double deviation = 0;
if (gpu_times_.size() > 1)
{
double sum = 0;
for (size_t i = 0; i < gpu_times_.size(); i++)
{
int64 diff = gpu_times_[i] - static_cast<int64>(gpu_elapsed_);
double diff_time = diff * 1000 / getTickFrequency();
sum += diff_time * diff_time;
}
deviation = std::sqrt(sum / gpu_times_.size());
}
printMetrics(is_accurate_, cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup);
writeMetrics(cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup, gpu_min, gpu_max, deviation);
num_subtests_called_++;
resetCurrentSubtest();
}
double TestSystem::meanTime(const vector<int64> &samples)
{
double sum = accumulate(samples.begin(), samples.end(), 0.);
return sum / samples.size();
}
void TestSystem::printHeading()
{
cout << endl;
cout<< setiosflags(ios_base::left);
#if 0
cout<<TAB<<setw(7)<< "Accu." << setw(10) << "CPU (ms)" << setw(10) << "GPU, ms"
<< setw(8) << "Speedup"<< setw(10)<<"GPUTotal" << setw(10) << "Total"
<< "Description\n";
cout<<TAB<<setw(7)<<""<<setw(10)<<""<<setw(10)<<""<<setw(8)<<""<<setw(10)<<"(ms)"<<setw(10)<<"Speedup\n";
#endif
cout<<TAB<< setw(10) << "CPU (ms)" << setw(10) << "GPU, ms"
<< setw(8) << "Speedup"<< setw(10)<<"GPUTotal" << setw(10) << "Total"
<< "Description\n";
cout<<TAB<<setw(10)<<""<<setw(10)<<""<<setw(8)<<""<<setw(10)<<"(ms)"<<setw(10)<<"Speedup\n";
cout << resetiosflags(ios_base::left);
}
void TestSystem::writeHeading()
{
if (!record_)
{
recordname_ += "_OCL.csv";
record_ = fopen(recordname_.c_str(), "w");
if(record_ == NULL)
{
cout<<".csv file open failed.\n";
exit(0);
}
}
fprintf(record_, "NAME,DESCRIPTION,ACCURACY,DIFFERENCE,CPU (ms),GPU (ms),SPEEDUP,GPUTOTAL (ms),TOTALSPEEDUP,GPU Min (ms),GPU Max (ms), Standard deviation (ms)\n");
fflush(record_);
}
void TestSystem::printSummary()
{
cout << setiosflags(ios_base::fixed);
cout << "\naverage GPU speedup: x"
<< setprecision(3) << speedup_total_ / std::max(1, num_subtests_called_)
<< endl;
cout << "\nGPU exceeded: "
<< setprecision(3) << speedup_faster_count_
<< "\nGPU passed: "
<< setprecision(3) << speedup_equal_count_
<< "\nGPU failed: "
<< setprecision(3) << speedup_slower_count_
<< endl;
cout << "\nGPU exceeded rate: "
<< setprecision(3) << (float)speedup_faster_count_ / std::max(1, num_subtests_called_) * 100
<< "%"
<< "\nGPU passed rate: "
<< setprecision(3) << (float)speedup_equal_count_ / std::max(1, num_subtests_called_) * 100
<< "%"
<< "\nGPU failed rate: "
<< setprecision(3) << (float)speedup_slower_count_ / std::max(1, num_subtests_called_) * 100
<< "%"
<< endl;
cout << "\naverage GPUTOTAL speedup: x"
<< setprecision(3) << speedup_full_total_ / std::max(1, num_subtests_called_)
<< endl;
cout << "\nGPUTOTAL exceeded: "
<< setprecision(3) << speedup_full_faster_count_
<< "\nGPUTOTAL passed: "
<< setprecision(3) << speedup_full_equal_count_
<< "\nGPUTOTAL failed: "
<< setprecision(3) << speedup_full_slower_count_
<< endl;
cout << "\nGPUTOTAL exceeded rate: "
<< setprecision(3) << (float)speedup_full_faster_count_ / std::max(1, num_subtests_called_) * 100
<< "%"
<< "\nGPUTOTAL passed rate: "
<< setprecision(3) << (float)speedup_full_equal_count_ / std::max(1, num_subtests_called_) * 100
<< "%"
<< "\nGPUTOTAL failed rate: "
<< setprecision(3) << (float)speedup_full_slower_count_ / std::max(1, num_subtests_called_) * 100
<< "%"
<< endl;
cout << resetiosflags(ios_base::fixed);
}
enum GTestColor {
COLOR_DEFAULT,
COLOR_RED,
COLOR_GREEN,
COLOR_YELLOW
};
#if GTEST_OS_WINDOWS&&!GTEST_OS_WINDOWS_MOBILE
// Returns the character attribute for the given color.
static WORD GetColorAttribute(GTestColor color) {
switch (color) {
case COLOR_RED: return FOREGROUND_RED;
case COLOR_GREEN: return FOREGROUND_GREEN;
case COLOR_YELLOW: return FOREGROUND_RED | FOREGROUND_GREEN;
default: return 0;
}
}
#else
static const char* GetAnsiColorCode(GTestColor color) {
switch (color) {
case COLOR_RED: return "1";
case COLOR_GREEN: return "2";
case COLOR_YELLOW: return "3";
default: return NULL;
};
}
#endif
static void printMetricsUti(double cpu_time, double gpu_time, double gpu_full_time, double speedup, double fullspeedup, std::stringstream& stream, std::stringstream& cur_subtest_description)
{
//cout <<TAB<< setw(7) << stream.str();
cout <<TAB;
stream.str("");
stream << cpu_time;
cout << setw(10) << stream.str();
stream.str("");
stream << gpu_time;
cout << setw(10) << stream.str();
stream.str("");
stream << "x" << setprecision(3) << speedup;
cout << setw(8) << stream.str();
stream.str("");
stream << gpu_full_time;
cout << setw(10) << stream.str();
stream.str("");
stream << "x" << setprecision(3) << fullspeedup;
cout << setw(10) << stream.str();
cout << cur_subtest_description.str();
cout << resetiosflags(ios_base::left) << endl;
}
void TestSystem::printMetrics(int is_accurate, double cpu_time, double gpu_time, double gpu_full_time, double speedup, double fullspeedup)
{
cout << setiosflags(ios_base::left);
stringstream stream;
std::stringstream &cur_subtest_description = getCurSubtestDescription();
#if GTEST_OS_WINDOWS&&!GTEST_OS_WINDOWS_MOBILE
WORD color;
const HANDLE stdout_handle = GetStdHandle(STD_OUTPUT_HANDLE);
// Gets the current text color.
CONSOLE_SCREEN_BUFFER_INFO buffer_info;
GetConsoleScreenBufferInfo(stdout_handle, &buffer_info);
const WORD old_color_attrs = buffer_info.wAttributes;
// We need to flush the stream buffers into the console before each
// SetConsoleTextAttribute call lest it affect the text that is already
// printed but has not yet reached the console.
fflush(stdout);
if(is_accurate == 1||is_accurate == -1)
{
color = old_color_attrs;
printMetricsUti(cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup, stream, cur_subtest_description);
}else
{
color = GetColorAttribute(COLOR_RED);
SetConsoleTextAttribute(stdout_handle,
color| FOREGROUND_INTENSITY);
printMetricsUti(cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup, stream, cur_subtest_description);
fflush(stdout);
// Restores the text color.
SetConsoleTextAttribute(stdout_handle, old_color_attrs);
}
#else
GTestColor color = COLOR_RED;
if(is_accurate == 1|| is_accurate == -1)
{
printMetricsUti(cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup, stream, cur_subtest_description);
}else
{
printf("\033[0;3%sm", GetAnsiColorCode(color));
printMetricsUti(cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup, stream, cur_subtest_description);
printf("\033[m"); // Resets the terminal to default.
}
#endif
}
void TestSystem::writeMetrics(double cpu_time, double gpu_time, double gpu_full_time, double speedup, double fullspeedup, double gpu_min, double gpu_max, double std_dev)
{
if (!record_)
{
recordname_ += ".csv";
record_ = fopen(recordname_.c_str(), "w");
}
string _is_accurate_;
if(is_accurate_ == 1)
_is_accurate_ = "Pass";
else if(is_accurate_ == 0)
_is_accurate_ = "Fail";
else if(is_accurate_ == -1)
_is_accurate_ = " ";
else
{
std::cout<<"is_accurate errer: "<<is_accurate_<<"\n";
exit(-1);
}
fprintf(record_, "%s,%s,%s,%.2f,%.3f,%.3f,%.3f,%.3f,%.3f,%.3f,%.3f,%.3f\n",
itname_changed_ ? itname_.c_str() : "",
cur_subtest_description_.str().c_str(),
_is_accurate_.c_str(),
accurate_diff_,
cpu_time, gpu_time, speedup, gpu_full_time, fullspeedup,
gpu_min, gpu_max, std_dev);
if (itname_changed_)
{
itname_changed_ = false;
}
fflush(record_);
}
void TestSystem::writeSummary()
{
if (!record_)
{
recordname_ += ".csv";
record_ = fopen(recordname_.c_str(), "w");
}
fprintf(record_, "\nAverage GPU speedup: %.3f\n"
"exceeded: %d (%.3f%%)\n"
"passed: %d (%.3f%%)\n"
"failed: %d (%.3f%%)\n"
"\nAverage GPUTOTAL speedup: %.3f\n"
"exceeded: %d (%.3f%%)\n"
"passed: %d (%.3f%%)\n"
"failed: %d (%.3f%%)\n",
speedup_total_ / std::max(1, num_subtests_called_),
speedup_faster_count_, (float)speedup_faster_count_ / std::max(1, num_subtests_called_) * 100,
speedup_equal_count_, (float)speedup_equal_count_ / std::max(1, num_subtests_called_) * 100,
speedup_slower_count_, (float)speedup_slower_count_ / std::max(1, num_subtests_called_) * 100,
speedup_full_total_ / std::max(1, num_subtests_called_),
speedup_full_faster_count_, (float)speedup_full_faster_count_ / std::max(1, num_subtests_called_) * 100,
speedup_full_equal_count_, (float)speedup_full_equal_count_ / std::max(1, num_subtests_called_) * 100,
speedup_full_slower_count_, (float)speedup_full_slower_count_ / std::max(1, num_subtests_called_) * 100
);
fflush(record_);
}
void TestSystem::printError(const std::string &msg)
{
if(msg != "CL_INVALID_BUFFER_SIZE")
{
cout << TAB << "[error: " << msg << "] " << cur_subtest_description_.str() << endl;
}
}
void gen(Mat &mat, int rows, int cols, int type, Scalar low, Scalar high)
{
mat.create(rows, cols, type);
RNG rng(0);
rng.fill(mat, RNG::UNIFORM, low, high);
}
string abspath(const string &relpath)
{
return TestSystem::instance().workingDir() + relpath;
}
int CV_CDECL cvErrorCallback(int /*status*/, const char * /*func_name*/,
const char *err_msg, const char * /*file_name*/,
int /*line*/, void * /*userdata*/)
{
TestSystem::instance().printError(err_msg);
return 0;
}
double checkNorm(const Mat &m)
{
return norm(m, NORM_INF);
}
double checkNorm(const Mat &m1, const Mat &m2)
{
return norm(m1, m2, NORM_INF);
}
double checkSimilarity(const Mat &m1, const Mat &m2)
{
Mat diff;
matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
return std::abs(diff.at<float>(0, 0) - 1.f);
}

479
modules/ocl/perf/perf_precomp.hpp
View File

@ -42,7 +42,6 @@
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# pragma GCC diagnostic ignored "-Wunused-function"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
@ -70,457 +69,37 @@
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/ts/ts.hpp"
#define OCL_SIZE_1000 cv::Size(1000, 1000)
#define OCL_SIZE_2000 cv::Size(2000, 2000)
#define OCL_SIZE_4000 cv::Size(4000, 4000)
#define OCL_TYPICAL_MAT_SIZES ::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000, OCL_SIZE_4000)
#define Min_Size 1000
#define Max_Size 4000
#define Multiple 2
#define TAB " "
using namespace std;
using namespace cv;
void gen(Mat &mat, int rows, int cols, int type, Scalar low, Scalar high);
void gen(Mat &mat, int rows, int cols, int type, int low, int high, int n);
string abspath(const string &relpath);
int CV_CDECL cvErrorCallback(int, const char *, const char *, const char *, int, void *);
//typedef struct
//{
// short x;
// short y;
//} COOR;
//COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep,
// cv::Size size, int sp, int sr, int maxIter, float eps, int *tab);
//void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi,
// int sp, int sr, cv::TermCriteria crit);
template<class T1, class T2>
int ExpectedEQ(T1 expected, T2 actual)
{
if(expected == actual)
return 1;
return 0;
}
template<class T1>
int EeceptDoubleEQ(T1 expected, T1 actual)
{
testing::internal::Double lhs(expected);
testing::internal::Double rhs(actual);
if (lhs.AlmostEquals(rhs))
{
return 1;
}
return 0;
}
template<class T>
int AssertEQ(T expected, T actual)
{
if(expected == actual)
{
return 1;
}
return 0;
}
int ExceptDoubleNear(double val1, double val2, double abs_error);
bool match_rect(cv::Rect r1, cv::Rect r2, int threshold);
double checkNorm(const cv::Mat &m);
double checkNorm(const cv::Mat &m1, const cv::Mat &m2);
double checkSimilarity(const cv::Mat &m1, const cv::Mat &m2);
int ExpectedMatNear(cv::Mat dst, cv::Mat cpu_dst, double eps);
int ExceptedMatSimilar(cv::Mat dst, cv::Mat cpu_dst, double eps);
class Runnable
{
public:
explicit Runnable(const std::string &runname): name_(runname) {}
virtual ~Runnable() {}
const std::string &name() const
{
return name_;
}
virtual void run() = 0;
private:
std::string name_;
};
class TestSystem
{
public:
static TestSystem &instance()
{
static TestSystem me;
return me;
}
void setWorkingDir(const std::string &val)
{
working_dir_ = val;
}
const std::string &workingDir() const
{
return working_dir_;
}
void setTestFilter(const std::string &val)
{
test_filter_ = val;
}
const std::string &testFilter() const
{
return test_filter_;
}
void setNumIters(int num_iters)
{
num_iters_ = num_iters;
}
void setGPUWarmupIters(int num_iters)
{
gpu_warmup_iters_ = num_iters;
}
void setCPUIters(int num_iters)
{
cpu_num_iters_ = num_iters;
}
void setTopThreshold(double top)
{
top_ = top;
}
void setBottomThreshold(double bottom)
{
bottom_ = bottom;
}
void addInit(Runnable *init)
{
inits_.push_back(init);
}
void addTest(Runnable *test)
{
tests_.push_back(test);
}
void run();
// It's public because OpenCV callback uses it
void printError(const std::string &msg);
std::stringstream &startNewSubtest()
{
finishCurrentSubtest();
return cur_subtest_description_;
}
bool stop() const
{
return cur_iter_idx_ >= num_iters_;
}
bool cpu_stop() const
{
return cur_iter_idx_ >= cpu_num_iters_;
}
int get_cur_iter_idx()
{
return cur_iter_idx_;
}
int get_cpu_num_iters()
{
return cpu_num_iters_;
}
bool warmupStop()
{
return cur_warmup_idx_++ >= gpu_warmup_iters_;
}
void warmupComplete()
{
cur_warmup_idx_ = 0;
}
void cpuOn()
{
cpu_started_ = cv::getTickCount();
}
void cpuOff()
{
int64 delta = cv::getTickCount() - cpu_started_;
cpu_times_.push_back(delta);
++cur_iter_idx_;
}
void cpuComplete()
{
cpu_elapsed_ += meanTime(cpu_times_);
cur_subtest_is_empty_ = false;
cur_iter_idx_ = 0;
}
void gpuOn()
{
gpu_started_ = cv::getTickCount();
}
void gpuOff()
{
int64 delta = cv::getTickCount() - gpu_started_;
gpu_times_.push_back(delta);
++cur_iter_idx_;
}
void gpuComplete()
{
gpu_elapsed_ += meanTime(gpu_times_);
cur_subtest_is_empty_ = false;
cur_iter_idx_ = 0;
}
void gpufullOn()
{
gpu_full_started_ = cv::getTickCount();
}
void gpufullOff()
{
int64 delta = cv::getTickCount() - gpu_full_started_;
gpu_full_times_.push_back(delta);
++cur_iter_idx_;
}
void gpufullComplete()
{
gpu_full_elapsed_ += meanTime(gpu_full_times_);
cur_subtest_is_empty_ = false;
cur_iter_idx_ = 0;
}
bool isListMode() const
{
return is_list_mode_;
}
void setListMode(bool value)
{
is_list_mode_ = value;
}
void setRecordName(const std::string &name)
{
recordname_ = name;
}
void setCurrentTest(const std::string &name)
{
itname_ = name;
itname_changed_ = true;
}
void setAccurate(int accurate, double diff)
{
is_accurate_ = accurate;
accurate_diff_ = diff;
}
void ExpectMatsNear(vector<Mat>& dst, vector<Mat>& cpu_dst, vector<double>& eps)
{
assert(dst.size() == cpu_dst.size());
assert(cpu_dst.size() == eps.size());
is_accurate_ = 1;
for(size_t i=0; i<dst.size(); i++)
{
double cur_diff = checkNorm(dst[i], cpu_dst[i]);
accurate_diff_ = max(accurate_diff_, cur_diff);
if(cur_diff > eps[i])
is_accurate_ = 0;
}
}
void ExpectedMatNear(cv::Mat& dst, cv::Mat& cpu_dst, double eps)
{
assert(dst.type() == cpu_dst.type());
assert(dst.size() == cpu_dst.size());
accurate_diff_ = checkNorm(dst, cpu_dst);
if(accurate_diff_ <= eps)
is_accurate_ = 1;
else
is_accurate_ = 0;
}
void ExceptedMatSimilar(cv::Mat& dst, cv::Mat& cpu_dst, double eps)
{
assert(dst.type() == cpu_dst.type());
assert(dst.size() == cpu_dst.size());
accurate_diff_ = checkSimilarity(cpu_dst, dst);
if(accurate_diff_ <= eps)
is_accurate_ = 1;
else
is_accurate_ = 0;
}
std::stringstream &getCurSubtestDescription()
{
return cur_subtest_description_;
}
private:
TestSystem():
cur_subtest_is_empty_(true), cpu_elapsed_(0),
gpu_elapsed_(0), gpu_full_elapsed_(0), speedup_total_(0.0),
num_subtests_called_(0),
speedup_faster_count_(0), speedup_slower_count_(0), speedup_equal_count_(0),
speedup_full_faster_count_(0), speedup_full_slower_count_(0), speedup_full_equal_count_(0), is_list_mode_(false),
num_iters_(10), cpu_num_iters_(2),
gpu_warmup_iters_(1), cur_iter_idx_(0), cur_warmup_idx_(0),
record_(0), recordname_("performance"), itname_changed_(true),
is_accurate_(-1), accurate_diff_(0.)
{
cpu_times_.reserve(num_iters_);
gpu_times_.reserve(num_iters_);
gpu_full_times_.reserve(num_iters_);
}
void finishCurrentSubtest();
void resetCurrentSubtest()
{
cpu_elapsed_ = 0;
gpu_elapsed_ = 0;
gpu_full_elapsed_ = 0;
cur_subtest_description_.str("");
cur_subtest_is_empty_ = true;
cur_iter_idx_ = 0;
cur_warmup_idx_ = 0;
cpu_times_.clear();
gpu_times_.clear();
gpu_full_times_.clear();
is_accurate_ = -1;
accurate_diff_ = 0.;
}
double meanTime(const std::vector<int64> &samples);
void printHeading();
void printSummary();
void printMetrics(int is_accurate, double cpu_time, double gpu_time = 0.0f, double gpu_full_time = 0.0f, double speedup = 0.0f, double fullspeedup = 0.0f);
void writeHeading();
void writeSummary();
void writeMetrics(double cpu_time, double gpu_time = 0.0f, double gpu_full_time = 0.0f,
double speedup = 0.0f, double fullspeedup = 0.0f,
double gpu_min = 0.0f, double gpu_max = 0.0f, double std_dev = 0.0f);
std::string working_dir_;
std::string test_filter_;
std::vector<Runnable *> inits_;
std::vector<Runnable *> tests_;
std::stringstream cur_subtest_description_;
bool cur_subtest_is_empty_;
int64 cpu_started_;
int64 gpu_started_;
int64 gpu_full_started_;
double cpu_elapsed_;
double gpu_elapsed_;
double gpu_full_elapsed_;
double speedup_total_;
double speedup_full_total_;
int num_subtests_called_;
int speedup_faster_count_;
int speedup_slower_count_;
int speedup_equal_count_;
int speedup_full_faster_count_;
int speedup_full_slower_count_;
int speedup_full_equal_count_;
bool is_list_mode_;
double top_;
double bottom_;
int num_iters_;
int cpu_num_iters_; //there's no need to set cpu running same times with gpu
int gpu_warmup_iters_; //gpu warm up times, default is 1
int cur_iter_idx_;
int cur_warmup_idx_; //current gpu warm up times
std::vector<int64> cpu_times_;
std::vector<int64> gpu_times_;
std::vector<int64> gpu_full_times_;
FILE *record_;
std::string recordname_;
std::string itname_;
bool itname_changed_;
int is_accurate_;
double accurate_diff_;
};
#define GLOBAL_INIT(name) \
struct name##_init: Runnable { \
name##_init(): Runnable(#name) { \
TestSystem::instance().addInit(this); \
} \
void run(); \
} name##_init_instance; \
void name##_init::run()
#define PERFTEST(name) \
struct name##_test: Runnable { \
name##_test(): Runnable(#name) { \
TestSystem::instance().addTest(this); \
} \
void run(); \
} name##_test_instance; \
void name##_test::run()
#define SUBTEST TestSystem::instance().startNewSubtest()
#define CPU_ON \
while (!TestSystem::instance().cpu_stop()) { \
TestSystem::instance().cpuOn()
#define CPU_OFF \
TestSystem::instance().cpuOff(); \
} TestSystem::instance().cpuComplete()
#define GPU_ON \
while (!TestSystem::instance().stop()) { \
TestSystem::instance().gpuOn()
#define GPU_OFF \
ocl::finish();\
TestSystem::instance().gpuOff(); \
} TestSystem::instance().gpuComplete()
#define GPU_FULL_ON \
while (!TestSystem::instance().stop()) { \
TestSystem::instance().gpufullOn()
#define GPU_FULL_OFF \
TestSystem::instance().gpufullOff(); \
} TestSystem::instance().gpufullComplete()
#define WARMUP_ON \
while (!TestSystem::instance().warmupStop()) {
#define WARMUP_OFF \
ocl::finish();\
} TestSystem::instance().warmupComplete()
#define OCL_SIZE_1000 Size(1000, 1000)
#define OCL_SIZE_2000 Size(2000, 2000)
#define OCL_SIZE_4000 Size(4000, 4000)
#define OCL_TYPICAL_MAT_SIZES ::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000, OCL_SIZE_4000)
#define OCL_PERF_ENUM(type, ...) ::testing::Values(type, ## __VA_ARGS__ )
#define IMPL_OCL "ocl"
#define IMPL_GPU "gpu"
#define IMPL_PLAIN "plain"
#define RUN_OCL_IMPL (IMPL_OCL == getSelectedImpl())
#define RUN_PLAIN_IMPL (IMPL_PLAIN == getSelectedImpl())
#ifdef HAVE_OPENCV_GPU
# define RUN_GPU_IMPL (IMPL_GPU == getSelectedImpl())
#endif
#ifdef HAVE_OPENCV_GPU
#define OCL_PERF_ELSE \
if (RUN_GPU_IMPL) \
CV_TEST_FAIL_NO_IMPL(); \
else \
CV_TEST_FAIL_NO_IMPL();
#else
#define OCL_PERF_ELSE \
CV_TEST_FAIL_NO_IMPL();
#endif
#endif

59
modules/ocl/perf/perf_pyramid.cpp
View File

@ -51,97 +51,74 @@ using std::tr1::get;
///////////// pyrDown //////////////////////
CV_ENUM(pyrDownMatType, CV_8UC1, CV_8UC4)
typedef tuple<Size, pyrDownMatType> pyrDownParams;
typedef TestBaseWithParam<pyrDownParams> pyrDownFixture;
typedef Size_MatType pyrDownFixture;
PERF_TEST_P(pyrDownFixture, pyrDown,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
pyrDownMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
pyrDownParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst;
Size dstSize((srcSize.height + 1) >> 1, (srcSize.width + 1) >> 1);
dst.create(dstSize, type);
declare.in(src).out(dst);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
TEST_CYCLE() cv::ocl::pyrDown(oclSrc, oclDst);
TEST_CYCLE() ocl::pyrDown(oclSrc, oclDst);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::pyrDown(src, dst);
TEST_CYCLE() pyrDown(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// pyrUp ////////////////////////
typedef pyrDownMatType pyrUpMatType;
typedef tuple<Size, pyrUpMatType> pyrUpParams;
typedef TestBaseWithParam<pyrUpParams> pyrUpFixture;
typedef Size_MatType pyrUpFixture;
PERF_TEST_P(pyrUpFixture, pyrUp,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
pyrUpMatType::all()))
OCL_PERF_ENUM(CV_8UC1, CV_8UC4)))
{
// getting params
pyrUpParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst;
Size dstSize(srcSize.height << 1, srcSize.width << 1);
dst.create(dstSize, type);
declare.in(src).out(dst);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
TEST_CYCLE() cv::ocl::pyrDown(oclSrc, oclDst);
TEST_CYCLE() ocl::pyrDown(oclSrc, oclDst);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::pyrDown(src, dst);
TEST_CYCLE() pyrDown(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}

51
modules/ocl/perf/perf_split_merge.cpp
View File

@ -51,23 +51,16 @@ using std::tr1::get;
///////////// Merge////////////////////////
CV_ENUM(MergeMatType, CV_8U, CV_32F)
typedef tuple<Size, MergeMatType> MergeParams;
typedef TestBaseWithParam<MergeParams> MergeFixture;
typedef Size_MatType MergeFixture;
PERF_TEST_P(MergeFixture, Merge,
::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
MergeMatType::all()))
OCL_PERF_ENUM(CV_8U, CV_32F)))
{
// getting params
MergeParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int depth = get<1>(params), channels = 3;
std::string impl = getSelectedImpl();
// creating src data
const int dstType = CV_MAKE_TYPE(depth, channels);
Mat dst(srcSize, dstType);
vector<Mat> src(channels);
@ -78,8 +71,7 @@ PERF_TEST_P(MergeFixture, Merge,
}
declare.out(dst);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclDst(srcSize, dstType);
vector<ocl::oclMat> oclSrc(src.size());
@ -92,50 +84,39 @@ PERF_TEST_P(MergeFixture, Merge,
SANITY_CHECK(dst);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::merge(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}
///////////// Split////////////////////////
typedef MergeMatType SplitMatType;
typedef tuple<Size, SplitMatType> SplitParams;
typedef TestBaseWithParam<SplitParams> SplitFixture;
typedef Size_MatType SplitFixture;
PERF_TEST_P(SplitFixture, Split,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
SplitMatType::all()))
OCL_PERF_ENUM(CV_8U, CV_32F)))
{
// getting params
MergeParams params = GetParam();
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int depth = get<1>(params), channels = 3;
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_MAKE_TYPE(depth, channels));
declare.in(src, WARMUP_RNG);
// select implementation
if (impl == "ocl")
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
vector<ocl::oclMat> oclDst(channels, ocl::oclMat(srcSize, CV_MAKE_TYPE(depth, 1)));
TEST_CYCLE() cv::ocl::split(oclSrc, oclDst);
AssertEQ(channels, 3);
ASSERT_EQ(3, channels);
Mat dst0, dst1, dst2;
oclDst[0].download(dst0);
oclDst[1].download(dst1);
@ -144,21 +125,17 @@ PERF_TEST_P(SplitFixture, Split,
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
else if (impl == "plain")
else if (RUN_PLAIN_IMPL)
{
vector<Mat> dst(channels, Mat(srcSize, CV_MAKE_TYPE(depth, 1)));
TEST_CYCLE() cv::split(src, dst);
AssertEQ(channels, 3);
ASSERT_EQ(3, channels);
Mat & dst0 = dst[0], & dst1 = dst[1], & dst2 = dst[2];
SANITY_CHECK(dst0);
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
OCL_PERF_ELSE
}