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Commit e8a173bc authored by Kirill Kornyakov's avatar Kirill Kornyakov
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Merge branch 'master' of git://5.9.49.245/opencv

parents 9b8c4739 5047f2d6
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Showing with 98 additions and 48 deletions
cmake/OpenCVModule.cmake
View file @ e8a173bc
......@@ -581,7 +581,7 @@ function(ocv_add_perf_tests)
__ocv_parse_test_sources(PERF ${ARGN})
# opencv_highgui is required for imread/imwrite
set(perf_deps ${the_module} opencv_ts opencv_highgui ${OPENCV_PERF_${the_module}_DEPS})
set(perf_deps ${the_module} opencv_ts opencv_highgui ${OPENCV_PERF_${the_module}_DEPS} ${OPENCV_MODULE_opencv_ts_DEPS})
ocv_check_dependencies(${perf_deps})
if(OCV_DEPENDENCIES_FOUND)
......@@ -632,7 +632,7 @@ function(ocv_add_accuracy_tests)
__ocv_parse_test_sources(TEST ${ARGN})
# opencv_highgui is required for imread/imwrite
set(test_deps ${the_module} opencv_ts opencv_highgui ${OPENCV_TEST_${the_module}_DEPS})
set(test_deps ${the_module} opencv_ts opencv_highgui ${OPENCV_TEST_${the_module}_DEPS} ${OPENCV_MODULE_opencv_ts_DEPS})
ocv_check_dependencies(${test_deps})
if(OCV_DEPENDENCIES_FOUND)
......
modules/calib3d/perf/perf_pnp.cpp
View file @ e8a173bc
#include "perf_precomp.hpp"
#include "opencv2/core/internal.hpp"
using namespace std;
using namespace cv;
......@@ -48,7 +49,10 @@ PERF_TEST_P(PointsNum_Algo, solvePnP,
declare.in(points3d, points2d);
TEST_CYCLE_N(1000) solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
TEST_CYCLE_N(1000)
{
solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
}
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
......@@ -83,7 +87,10 @@ PERF_TEST(PointsNum_Algo, solveP3P)
declare.in(points3d, points2d);
TEST_CYCLE_N(1000) solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, CV_P3P);
TEST_CYCLE_N(1000)
{
solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, CV_P3P);
}
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
......@@ -117,9 +124,10 @@ PERF_TEST_P(PointsNum, SolvePnPRansac, testing::Values(4, 3*9, 7*13))
Mat rvec;
Mat tvec;
solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
declare.time(3.0);
#ifdef HAVE_TBB
// limit concurrency to get determenistic result
cv::Ptr<tbb::task_scheduler_init> one_thread = new tbb::task_scheduler_init(1);
#endif
TEST_CYCLE()
{
......
modules/calib3d/src/solvepnp.cpp
View file @ e8a173bc
......@@ -260,6 +260,8 @@ namespace cv
{
rvec.copyTo(initRvec);
tvec.copyTo(initTvec);
generator.state = theRNG().state; //to control it somehow...
}
private:
PnPSolver& operator=(const PnPSolver&);
......
modules/features2d/perf/perf_batchDistance.cpp
View file @ e8a173bc
......@@ -6,17 +6,15 @@ using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
CV_FLAGS(NormType, NORM_L1, NORM_L2, NORM_L2SQR, NORM_HAMMING, NORM_HAMMING2)
CV_ENUM(SourceType, CV_32F, CV_8U)
CV_ENUM(DestinationType, CV_32F, CV_32S)
CV_ENUM(NormType, NORM_L1, NORM_L2, NORM_L2SQR, NORM_HAMMING, NORM_HAMMING2)
typedef std::tr1::tuple<NormType, DestinationType, bool> Norm_Destination_CrossCheck_t;
typedef std::tr1::tuple<NormType, MatType, bool> Norm_Destination_CrossCheck_t;
typedef perf::TestBaseWithParam<Norm_Destination_CrossCheck_t> Norm_Destination_CrossCheck;
typedef std::tr1::tuple<NormType, bool> Norm_CrossCheck_t;
typedef perf::TestBaseWithParam<Norm_CrossCheck_t> Norm_CrossCheck;
typedef std::tr1::tuple<SourceType, bool> Source_CrossCheck_t;
typedef std::tr1::tuple<MatType, bool> Source_CrossCheck_t;
typedef perf::TestBaseWithParam<Source_CrossCheck_t> Source_CrossCheck;
void generateData( Mat& query, Mat& train, const int sourceType );
......@@ -29,27 +27,25 @@ PERF_TEST_P(Norm_Destination_CrossCheck, batchDistance_8U,
)
{
NormType normType = get<0>(GetParam());
DestinationType destinationType = get<1>(GetParam());
int destinationType = get<1>(GetParam());
bool isCrossCheck = get<2>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
int knn = 1;
generateData(queryDescriptors, trainDescriptors, CV_8U);
if(!isCrossCheck)
{
knn = 0;
}
declare.time(30);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, destinationType, (isCrossCheck) ? ndix : noArray(),
normType, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
PERF_TEST_P(Norm_CrossCheck, batchDistance_Dest_32S,
......@@ -60,25 +56,23 @@ PERF_TEST_P(Norm_CrossCheck, batchDistance_Dest_32S,
{
NormType normType = get<0>(GetParam());
bool isCrossCheck = get<1>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
int knn = 1;
generateData(queryDescriptors, trainDescriptors, CV_8U);
if(!isCrossCheck)
{
knn = 0;
}
declare.time(30);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, CV_32S, (isCrossCheck) ? ndix : noArray(),
normType, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
PERF_TEST_P(Source_CrossCheck, batchDistance_L2,
......@@ -87,27 +81,25 @@ PERF_TEST_P(Source_CrossCheck, batchDistance_L2,
)
)
{
SourceType sourceType = get<0>(GetParam());
int sourceType = get<0>(GetParam());
bool isCrossCheck = get<1>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
int knn = 1;
generateData(queryDescriptors, trainDescriptors, sourceType);
if(!isCrossCheck)
{
knn = 0;
}
declare.time(30);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, CV_32F, (isCrossCheck) ? ndix : noArray(),
NORM_L2, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
PERF_TEST_P(Norm_CrossCheck, batchDistance_32F,
......@@ -118,25 +110,23 @@ PERF_TEST_P(Norm_CrossCheck, batchDistance_32F,
{
NormType normType = get<0>(GetParam());
bool isCrossCheck = get<1>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
int knn = 1;
generateData(queryDescriptors, trainDescriptors, CV_32F);
if(!isCrossCheck)
{
knn = 0;
}
declare.time(30);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, CV_32F, (isCrossCheck) ? ndix : noArray(),
normType, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
void generateData( Mat& query, Mat& train, const int sourceType )
......
modules/features2d/perf/perf_fast.cpp
View file @ e8a173bc
......@@ -6,15 +6,23 @@ using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
typedef perf::TestBaseWithParam<std::string> fast;
enum { TYPE_5_8 =FastFeatureDetector::TYPE_5_8, TYPE_7_12 = FastFeatureDetector::TYPE_7_12, TYPE_9_16 = FastFeatureDetector::TYPE_9_16 };
CV_ENUM(FastType, TYPE_5_8, TYPE_7_12, TYPE_9_16)
typedef std::tr1::tuple<String, FastType> File_Type_t;
typedef perf::TestBaseWithParam<File_Type_t> fast;
#define FAST_IMAGES \
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png"
PERF_TEST_P(fast, detectForORB, testing::Values(FAST_IMAGES))
PERF_TEST_P(fast, detect, testing::Combine(
testing::Values(FAST_IMAGES),
testing::ValuesIn(FastType::all())
))
{
String filename = getDataPath(GetParam());
String filename = getDataPath(get<0>(GetParam()));
int type = get<1>(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
......@@ -22,13 +30,11 @@ PERF_TEST_P(fast, detectForORB, testing::Values(FAST_IMAGES))
declare.in(frame);
FastFeatureDetector fd(20, true, FastFeatureDetector::TYPE_5_8);
FastFeatureDetector fd(20, true, type);
vector<KeyPoint> points;
TEST_CYCLE() fd.detect(frame, points);
fd = FastFeatureDetector(20, true, FastFeatureDetector::TYPE_7_12);
TEST_CYCLE() fd.detect(frame, points);
fd = FastFeatureDetector(20, true, FastFeatureDetector::TYPE_9_16);
TEST_CYCLE() fd.detect(frame, points);
SANITY_CHECK_KEYPOINTS(points);
}
modules/features2d/perf/perf_orb.cpp
View file @ e8a173bc
......@@ -26,6 +26,8 @@ PERF_TEST_P(orb, detect, testing::Values(ORB_IMAGES))
vector<KeyPoint> points;
TEST_CYCLE() detector(frame, mask, points);
SANITY_CHECK_KEYPOINTS(points);
}
PERF_TEST_P(orb, extract, testing::Values(ORB_IMAGES))
......@@ -46,6 +48,8 @@ PERF_TEST_P(orb, extract, testing::Values(ORB_IMAGES))
Mat descriptors;
TEST_CYCLE() detector(frame, mask, points, descriptors, true);
SANITY_CHECK(descriptors);
}
PERF_TEST_P(orb, full, testing::Values(ORB_IMAGES))
......@@ -64,4 +68,7 @@ PERF_TEST_P(orb, full, testing::Values(ORB_IMAGES))
Mat descriptors;
TEST_CYCLE() detector(frame, mask, points, descriptors, false);
SANITY_CHECK_KEYPOINTS(points);
SANITY_CHECK(descriptors);
}
modules/ts/CMakeLists.txt
View file @ e8a173bc
......@@ -10,7 +10,8 @@ endif()
set(OPENCV_MODULE_IS_PART_OF_WORLD FALSE)
ocv_add_module(ts opencv_core)
ocv_add_module(ts opencv_core opencv_features2d)
ocv_glob_module_sources()
ocv_module_include_directories()
ocv_create_module()
......
modules/ts/include/opencv2/ts/ts_perf.hpp
View file @ e8a173bc
......@@ -2,6 +2,7 @@
#define __OPENCV_TS_PERF_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "ts_gtest.h"
#ifdef HAVE_TBB
......@@ -165,6 +166,7 @@ class CV_EXPORTS Regression
{
public:
static Regression& add(TestBase* test, const std::string& name, cv::InputArray array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
static Regression& addKeypoints(TestBase* test, const std::string& name, const std::vector<cv::KeyPoint>& array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
static void Init(const std::string& testSuitName, const std::string& ext = ".xml");
Regression& operator() (const std::string& name, cv::InputArray array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
......@@ -199,6 +201,7 @@ private:
};
#define SANITY_CHECK(array, ...) ::perf::Regression::add(this, #array, array , ## __VA_ARGS__)
#define SANITY_CHECK_KEYPOINTS(array, ...) ::perf::Regression::addKeypoints(this, #array, array , ## __VA_ARGS__)
/*****************************************************************************************\
......
modules/ts/src/ts_perf.cpp
View file @ e8a173bc
......@@ -103,6 +103,24 @@ Regression& Regression::add(TestBase* test, const std::string& name, cv::InputAr
return instance()(name, array, eps, err);
}
Regression& Regression::addKeypoints(TestBase* test, const std::string& name, const std::vector<cv::KeyPoint>& array, double eps, ERROR_TYPE err)
{
int len = (int)array.size();
cv::Mat pt (len, 1, CV_32FC2, (void*)&array[0].pt, sizeof(cv::KeyPoint));
cv::Mat size (len, 1, CV_32FC1, (void*)&array[0].size, sizeof(cv::KeyPoint));
cv::Mat angle (len, 1, CV_32FC1, (void*)&array[0].angle, sizeof(cv::KeyPoint));
cv::Mat response(len, 1, CV_32FC1, (void*)&array[0].response, sizeof(cv::KeyPoint));
cv::Mat octave (len, 1, CV_32SC1, (void*)&array[0].octave, sizeof(cv::KeyPoint));
cv::Mat class_id(len, 1, CV_32SC1, (void*)&array[0].class_id, sizeof(cv::KeyPoint));
return Regression::add(test, name + "-pt", pt, eps, ERROR_ABSOLUTE)
(name + "-size", size, eps, ERROR_ABSOLUTE)
(name + "-angle", angle, eps, ERROR_ABSOLUTE)
(name + "-response", response, eps, err)
(name + "-octave", octave, eps, ERROR_ABSOLUTE)
(name + "-class_id", class_id, eps, ERROR_ABSOLUTE);
}
void Regression::Init(const std::string& testSuitName, const std::string& ext)
{
instance().init(testSuitName, ext);
......@@ -490,6 +508,12 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
Regression& Regression::operator() (const std::string& name, cv::InputArray array, double eps, ERROR_TYPE err)
{
if(!array.empty() && array.depth() == CV_USRTYPE1)
{
ADD_FAILURE() << " Can not check regression for CV_USRTYPE1 data type for " << name;
return *this;
}
std::string nodename = getCurrentTestNodeName();
cv::FileNode n = rootIn[nodename];
......@@ -674,6 +698,8 @@ cv::Size TestBase::getSize(cv::InputArray a)
bool TestBase::next()
{
bool has_next = ++currentIter < nIters && totalTime < timeLimit;
cv::theRNG().state = param_seed; //this rng should generate same numbers for each run
#ifdef ANDROID
if (log_power_checkpoints)
{
......@@ -948,7 +974,6 @@ void TestBase::SetUp()
currentIter = (unsigned int)-1;
timeLimit = timeLimitDefault;
times.clear();
cv::theRNG().state = param_seed;//this rng should generate same numbers for each run
}
void TestBase::TearDown()
......
modules/video/perf/perf_optflowpyrlk.cpp
View file @ e8a173bc
......@@ -91,6 +91,10 @@ PERF_TEST_P(Path_Idx_Cn_NPoints_WSize, OpticalFlowPyrLK_full, testing::Combine(
Size(winSize, winSize), maxLevel, criteria,
flags, minEigThreshold);
}
SANITY_CHECK(outPoints);
SANITY_CHECK(status);
SANITY_CHECK(err, 1e-5);
}
typedef tr1::tuple<std::string, int, int, tr1::tuple<int,int>, int, bool> Path_Idx_Cn_NPoints_WSize_Deriv_t;
......@@ -166,6 +170,10 @@ PERF_TEST_P(Path_Idx_Cn_NPoints_WSize_Deriv, OpticalFlowPyrLK_self, testing::Com
Size(winSize, winSize), maxLevel, criteria,
flags, minEigThreshold);
}
SANITY_CHECK(outPoints);
SANITY_CHECK(status);
SANITY_CHECK(err, 1e-5);
}
CV_ENUM(PyrBorderMode, BORDER_DEFAULT, BORDER_TRANSPARENT);
......
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