Added perf tests

modules/imgproc/perf/perf_warp.cpp

-#include "perf_precomp.hpp"
-
-using namespace std;
-using namespace cv;
-using namespace perf;
-using namespace testing;
-using std::tr1::make_tuple;
-using std::tr1::get;
-
-enum{HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH};
-
-CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE);
-CV_ENUM(InterType, INTER_NEAREST, INTER_LINEAR);
-CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH);
-
-typedef TestBaseWithParam< tr1::tuple<Size, InterType, BorderMode> > TestWarpAffine;
-typedef TestBaseWithParam< tr1::tuple<Size, InterType, BorderMode> > TestWarpPerspective;
-typedef TestBaseWithParam< tr1::tuple<MatType, Size, InterType, BorderMode, RemapMode> > TestRemap;
-
-void update_map(const Mat& src, Mat& map_x, Mat& map_y, const int remapMode );
-
-PERF_TEST_P( TestWarpAffine, WarpAffine,
-             Combine(
-                Values( szVGA, sz720p, sz1080p ),
-                ValuesIn( InterType::all() ),
-                ValuesIn( BorderMode::all() )
-             )
-)
-{
-    Size sz;
-    int borderMode, interType;
-    sz         = get<0>(GetParam());
-    borderMode = get<1>(GetParam());
-    interType  = get<2>(GetParam());
-
-    Mat src, img = imread(getDataPath("cv/shared/fruits.jpg"));
-    cvtColor(img, src, COLOR_BGR2RGBA, 4);
-    Mat warpMat = getRotationMatrix2D(Point2f(src.cols/2.f, src.rows/2.f), 30., 2.2);
-    Mat dst(sz, CV_8UC4);
-
-    declare.in(src).out(dst);
-
-    TEST_CYCLE() warpAffine( src, dst, warpMat, sz, interType, borderMode, Scalar::all(150) );
-
-    SANITY_CHECK(dst);
-
-}
-
-PERF_TEST_P( TestWarpPerspective, WarpPerspective,
-             Combine(
-                Values( szVGA, sz720p, sz1080p ),
-                ValuesIn( InterType::all() ),
-                ValuesIn( BorderMode::all() )
-             )
-)
-{
-    Size sz;
-    int borderMode, interType;
-    sz         = get<0>(GetParam());
-    borderMode = get<1>(GetParam());
-    interType  = get<2>(GetParam());
-
-
-    Mat src, img = imread(getDataPath("cv/shared/fruits.jpg"));
-    cvtColor(img, src, COLOR_BGR2RGBA, 4);
-    Mat rotMat = getRotationMatrix2D(Point2f(src.cols/2.f, src.rows/2.f), 30., 2.2);
-    Mat warpMat(3, 3, CV_64FC1);
-    for(int r=0; r<2; r++)
-        for(int c=0; c<3; c++)
-            warpMat.at<double>(r, c) = rotMat.at<double>(r, c);
-    warpMat.at<double>(2, 0) = .3/sz.width;
-    warpMat.at<double>(2, 1) = .3/sz.height;
-    warpMat.at<double>(2, 2) = 1;
-    Mat dst(sz, CV_8UC4);
-
-    declare.in(src).out(dst);
-
-    TEST_CYCLE() warpPerspective( src, dst, warpMat, sz, interType, borderMode, Scalar::all(150) );
-
-    SANITY_CHECK(dst);
-}
-
-PERF_TEST_P( TestRemap, remap,
-             Combine(
-                 Values( TYPICAL_MAT_TYPES ),
-                 Values( szVGA, sz720p, sz1080p ),
-                 ValuesIn( InterType::all() ),
-                 ValuesIn( BorderMode::all() ),
-                 ValuesIn( RemapMode::all() )
-                 )
-             )
-{
-    int type = get<0>(GetParam());
-    Size size = get<1>(GetParam());
-    int interpolationType = get<2>(GetParam());
-    int borderMode = get<3>(GetParam());
-    int remapMode = get<4>(GetParam());
-    unsigned int height = size.height;
-    unsigned int width = size.width;
-    Mat source(height, width, type);
-    Mat destination;
-    Mat map_x(height, width, CV_32F);
-    Mat map_y(height, width, CV_32F);
-
-    declare.in(source, WARMUP_RNG);
-
-    update_map(source, map_x, map_y, remapMode);
-
-    TEST_CYCLE()
-    {
-        remap(source, destination, map_x, map_y, interpolationType, borderMode);
-    }
-
-    SANITY_CHECK(destination, 1);
-}
-
-void update_map(const Mat& src, Mat& map_x, Mat& map_y, const int remapMode )
-{
-    for( int j = 0; j < src.rows; j++ )
-    {
-        for( int i = 0; i < src.cols; i++ )
-        {
-            switch( remapMode )
-            {
-            case HALF_SIZE:
-                if( i > src.cols*0.25 && i < src.cols*0.75 && j > src.rows*0.25 && j < src.rows*0.75 )
-                {
-                    map_x.at<float>(j,i) = 2*( i - src.cols*0.25 ) + 0.5 ;
-                    map_y.at<float>(j,i) = 2*( j - src.rows*0.25 ) + 0.5 ;
-                }
-                else
-                {
-                    map_x.at<float>(j,i) = 0 ;
-                    map_y.at<float>(j,i) = 0 ;
-                }
-                break;
-            case UPSIDE_DOWN:
-                map_x.at<float>(j,i) = i ;
-                map_y.at<float>(j,i) = src.rows - j ;
-                break;
-            case REFLECTION_X:
-                map_x.at<float>(j,i) = src.cols - i ;
-                map_y.at<float>(j,i) = j ;
-                break;
-            case REFLECTION_BOTH:
-                map_x.at<float>(j,i) = src.cols - i ;
-                map_y.at<float>(j,i) = src.rows - j ;
-                break;
-            } // end of switch
-        }
-    }
-}
-
-PERF_TEST(Transform, getPerspectiveTransform)
-{
-    unsigned int size = 8;
-    Mat source(1, size/2, CV_32FC2);
-    Mat destination(1, size/2, CV_32FC2);
-    Mat transformCoefficient;
-
-    declare.in(source, destination, WARMUP_RNG);
-
-    TEST_CYCLE()
-    {
-        transformCoefficient = getPerspectiveTransform(source, destination);
-    }
-}
-
+#include "perf_precomp.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace perf;
+using namespace testing;
+using std::tr1::make_tuple;
+using std::tr1::get;
+
+enum{HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH};
+
+CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE);
+CV_ENUM(InterType, INTER_NEAREST, INTER_LINEAR);
+CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH);
+
+typedef TestBaseWithParam< tr1::tuple<Size, InterType, BorderMode> > TestWarpAffine;
+typedef TestBaseWithParam< tr1::tuple<Size, InterType, BorderMode> > TestWarpPerspective;
+typedef TestBaseWithParam< tr1::tuple<MatType, Size, InterType, BorderMode, RemapMode> > TestRemap;
+
+void update_map(const Mat& src, Mat& map_x, Mat& map_y, const int remapMode );
+
+PERF_TEST_P( TestWarpAffine, WarpAffine,
+             Combine(
+                Values( szVGA, sz720p, sz1080p ),
+                ValuesIn( InterType::all() ),
+                ValuesIn( BorderMode::all() )
+             )
+)
+{
+    Size sz;
+    int borderMode, interType;
+    sz         = get<0>(GetParam());
+    borderMode = get<1>(GetParam());
+    interType  = get<2>(GetParam());
+
+    Mat src, img = imread(getDataPath("cv/shared/fruits.jpg"));
+    cvtColor(img, src, COLOR_BGR2RGBA, 4);
+    Mat warpMat = getRotationMatrix2D(Point2f(src.cols/2.f, src.rows/2.f), 30., 2.2);
+    Mat dst(sz, CV_8UC4);
+
+    declare.in(src).out(dst);
+
+    TEST_CYCLE() warpAffine( src, dst, warpMat, sz, interType, borderMode, Scalar::all(150) );
+
+    SANITY_CHECK(dst);
+
+}
+
+PERF_TEST_P( TestWarpPerspective, WarpPerspective,
+             Combine(
+                Values( szVGA, sz720p, sz1080p ),
+                ValuesIn( InterType::all() ),
+                ValuesIn( BorderMode::all() )
+             )
+)
+{
+    Size sz;
+    int borderMode, interType;
+    sz         = get<0>(GetParam());
+    borderMode = get<1>(GetParam());
+    interType  = get<2>(GetParam());
+
+
+    Mat src, img = imread(getDataPath("cv/shared/fruits.jpg"));
+    cvtColor(img, src, COLOR_BGR2RGBA, 4);
+    Mat rotMat = getRotationMatrix2D(Point2f(src.cols/2.f, src.rows/2.f), 30., 2.2);
+    Mat warpMat(3, 3, CV_64FC1);
+    for(int r=0; r<2; r++)
+        for(int c=0; c<3; c++)
+            warpMat.at<double>(r, c) = rotMat.at<double>(r, c);
+    warpMat.at<double>(2, 0) = .3/sz.width;
+    warpMat.at<double>(2, 1) = .3/sz.height;
+    warpMat.at<double>(2, 2) = 1;
+    Mat dst(sz, CV_8UC4);
+
+    declare.in(src).out(dst);
+
+    TEST_CYCLE() warpPerspective( src, dst, warpMat, sz, interType, borderMode, Scalar::all(150) );
+
+    SANITY_CHECK(dst);
+}
+
+PERF_TEST_P( TestRemap, remap,
+             Combine(
+                 Values( TYPICAL_MAT_TYPES ),
+                 Values( szVGA, sz720p, sz1080p ),
+                 ValuesIn( InterType::all() ),
+                 ValuesIn( BorderMode::all() ),
+                 ValuesIn( RemapMode::all() )
+                 )
+             )
+{
+    int type = get<0>(GetParam());
+    Size size = get<1>(GetParam());
+    int interpolationType = get<2>(GetParam());
+    int borderMode = get<3>(GetParam());
+    int remapMode = get<4>(GetParam());
+    unsigned int height = size.height;
+    unsigned int width = size.width;
+    Mat source(height, width, type);
+    Mat destination;
+    Mat map_x(height, width, CV_32F);
+    Mat map_y(height, width, CV_32F);
+
+    declare.in(source, WARMUP_RNG);
+
+    update_map(source, map_x, map_y, remapMode);
+
+    TEST_CYCLE()
+    {
+        remap(source, destination, map_x, map_y, interpolationType, borderMode);
+    }
+
+    SANITY_CHECK(destination, 1);
+}
+
+void update_map(const Mat& src, Mat& map_x, Mat& map_y, const int remapMode )
+{
+    for( int j = 0; j < src.rows; j++ )
+    {
+        for( int i = 0; i < src.cols; i++ )
+        {
+            switch( remapMode )
+            {
+            case HALF_SIZE:
+                if( i > src.cols*0.25 && i < src.cols*0.75 && j > src.rows*0.25 && j < src.rows*0.75 )
+                {
+                    map_x.at<float>(j,i) = 2*( i - src.cols*0.25 ) + 0.5 ;
+                    map_y.at<float>(j,i) = 2*( j - src.rows*0.25 ) + 0.5 ;
+                }
+                else
+                {
+                    map_x.at<float>(j,i) = 0 ;
+                    map_y.at<float>(j,i) = 0 ;
+                }
+                break;
+            case UPSIDE_DOWN:
+                map_x.at<float>(j,i) = i ;
+                map_y.at<float>(j,i) = src.rows - j ;
+                break;
+            case REFLECTION_X:
+                map_x.at<float>(j,i) = src.cols - i ;
+                map_y.at<float>(j,i) = j ;
+                break;
+            case REFLECTION_BOTH:
+                map_x.at<float>(j,i) = src.cols - i ;
+                map_y.at<float>(j,i) = src.rows - j ;
+                break;
+            } // end of switch
+        }
+    }
+}
+
+PERF_TEST(Transform, getPerspectiveTransform)
+{
+    unsigned int size = 8;
+    Mat source(1, size/2, CV_32FC2);
+    Mat destination(1, size/2, CV_32FC2);
+    Mat transformCoefficient;
+
+    declare.in(source, destination, WARMUP_RNG);
+
+    TEST_CYCLE()
+    {
+        transformCoefficient = getPerspectiveTransform(source, destination);
+    }
+}
+

modules/stitching/perf/perf_stich.cpp

-#include "perf_precomp.hpp"
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/core/internal.hpp"
-#include "opencv2/flann/flann.hpp"
-#include "opencv2/opencv_modules.hpp"
-
-using namespace std;
-using namespace cv;
-using namespace perf;
-using std::tr1::make_tuple;
-using std::tr1::get;
-
-#define SURF_MATCH_CONFIDENCE 0.65f
-#define ORB_MATCH_CONFIDENCE  0.3f
-#define WORK_MEGAPIX 0.6
-
-typedef TestBaseWithParam<String> stitch;
-typedef TestBaseWithParam<String> match;
-
-#ifdef HAVE_OPENCV_NONFREE
-#define TEST_DETECTORS testing::Values("surf", "orb")
-#else
-#define TEST_DETECTORS testing::Values<String>("orb")
-#endif
-
-PERF_TEST_P(stitch, a123, TEST_DETECTORS)
-{
-    Mat pano;
-
-    vector<Mat> imgs;
-    imgs.push_back( imread( getDataPath("stitching/a1.jpg") ) );
-    imgs.push_back( imread( getDataPath("stitching/a2.jpg") ) );
-    imgs.push_back( imread( getDataPath("stitching/a3.jpg") ) );
-
-    Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
-            ? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
-            : (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
-
-    Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
-            ? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
-            : new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
-
-    declare.time(30 * 20).iterations(20);
-
-    while(next())
-    {
-        Stitcher stitcher = Stitcher::createDefault();
-        stitcher.setFeaturesFinder(featuresFinder);
-        stitcher.setFeaturesMatcher(featuresMatcher);
-        stitcher.setWarper(new SphericalWarper());
-        stitcher.setRegistrationResol(WORK_MEGAPIX);
-
-        startTimer();
-        stitcher.stitch(imgs, pano);
-        stopTimer();
-    }
-}
-
-PERF_TEST_P(stitch, b12, TEST_DETECTORS)
-{
-    Mat pano;
-
-    vector<Mat> imgs;
-    imgs.push_back( imread( getDataPath("stitching/b1.jpg") ) );
-    imgs.push_back( imread( getDataPath("stitching/b2.jpg") ) );
-
-    Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
-            ? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
-            : (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
-
-    Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
-            ? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
-            : new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
-
-    declare.time(30 * 20).iterations(20);
-
-    while(next())
-    {
-        Stitcher stitcher = Stitcher::createDefault();
-        stitcher.setFeaturesFinder(featuresFinder);
-        stitcher.setFeaturesMatcher(featuresMatcher);
-        stitcher.setWarper(new SphericalWarper());
-        stitcher.setRegistrationResol(WORK_MEGAPIX);
-
-        startTimer();
-        stitcher.stitch(imgs, pano);
-        stopTimer();
-    }
-}
-
-PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
-{
-    Mat img1, img1_full = imread( getDataPath("stitching/b1.jpg") );
-    Mat img2, img2_full = imread( getDataPath("stitching/b2.jpg") );
-    float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
-    float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
-    resize(img1_full, img1, Size(), scale1, scale1);
-    resize(img2_full, img2, Size(), scale2, scale2);
-
-    Ptr<detail::FeaturesFinder> finder;
-    Ptr<detail::FeaturesMatcher> matcher;
-    if (GetParam() == "surf")
-    {
-        finder = new detail::SurfFeaturesFinder();
-        matcher = new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
-    }
-    else if (GetParam() == "orb")
-    {
-        finder = new detail::OrbFeaturesFinder();
-        matcher = new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE);
-    }
-    else
-    {
-        FAIL() << "Unknown 2D features type: " << GetParam();
-    }
-
-    detail::ImageFeatures features1, features2;
-    (*finder)(img1, features1);
-    (*finder)(img2, features2);
-
-    detail::MatchesInfo pairwise_matches;
-
-    declare.in(features1.descriptors, features2.descriptors)
-            .iterations(100);
-
-    while(next())
-    {
-        cvflann::seed_random(42);//for predictive FlannBasedMatcher
-        startTimer();
-        (*matcher)(features1, features2, pairwise_matches);
-        stopTimer();
-        matcher->collectGarbage();
-    }
-}
+#include "perf_precomp.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/core/internal.hpp"
+#include "opencv2/flann/flann.hpp"
+#include "opencv2/opencv_modules.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace perf;
+using std::tr1::make_tuple;
+using std::tr1::get;
+
+#define SURF_MATCH_CONFIDENCE 0.65f
+#define ORB_MATCH_CONFIDENCE  0.3f
+#define WORK_MEGAPIX 0.6
+
+typedef TestBaseWithParam<String> stitch;
+typedef TestBaseWithParam<String> match;
+
+#ifdef HAVE_OPENCV_NONFREE
+#define TEST_DETECTORS testing::Values("surf", "orb")
+#else
+#define TEST_DETECTORS testing::Values<String>("orb")
+#endif
+
+PERF_TEST_P(stitch, a123, TEST_DETECTORS)
+{
+    Mat pano;
+
+    vector<Mat> imgs;
+    imgs.push_back( imread( getDataPath("stitching/a1.jpg") ) );
+    imgs.push_back( imread( getDataPath("stitching/a2.jpg") ) );
+    imgs.push_back( imread( getDataPath("stitching/a3.jpg") ) );
+
+    Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
+            ? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
+            : (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
+
+    Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
+            ? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
+            : new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
+
+    declare.time(30 * 20).iterations(20);
+
+    while(next())
+    {
+        Stitcher stitcher = Stitcher::createDefault();
+        stitcher.setFeaturesFinder(featuresFinder);
+        stitcher.setFeaturesMatcher(featuresMatcher);
+        stitcher.setWarper(new SphericalWarper());
+        stitcher.setRegistrationResol(WORK_MEGAPIX);
+
+        startTimer();
+        stitcher.stitch(imgs, pano);
+        stopTimer();
+    }
+}
+
+PERF_TEST_P(stitch, b12, TEST_DETECTORS)
+{
+    Mat pano;
+
+    vector<Mat> imgs;
+    imgs.push_back( imread( getDataPath("stitching/b1.jpg") ) );
+    imgs.push_back( imread( getDataPath("stitching/b2.jpg") ) );
+
+    Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
+            ? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
+            : (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
+
+    Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
+            ? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
+            : new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
+
+    declare.time(30 * 20).iterations(20);
+
+    while(next())
+    {
+        Stitcher stitcher = Stitcher::createDefault();
+        stitcher.setFeaturesFinder(featuresFinder);
+        stitcher.setFeaturesMatcher(featuresMatcher);
+        stitcher.setWarper(new SphericalWarper());
+        stitcher.setRegistrationResol(WORK_MEGAPIX);
+
+        startTimer();
+        stitcher.stitch(imgs, pano);
+        stopTimer();
+    }
+}
+
+PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
+{
+    Mat img1, img1_full = imread( getDataPath("stitching/b1.jpg") );
+    Mat img2, img2_full = imread( getDataPath("stitching/b2.jpg") );
+    float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
+    float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
+    resize(img1_full, img1, Size(), scale1, scale1);
+    resize(img2_full, img2, Size(), scale2, scale2);
+
+    Ptr<detail::FeaturesFinder> finder;
+    Ptr<detail::FeaturesMatcher> matcher;
+    if (GetParam() == "surf")
+    {
+        finder = new detail::SurfFeaturesFinder();
+        matcher = new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
+    }
+    else if (GetParam() == "orb")
+    {
+        finder = new detail::OrbFeaturesFinder();
+        matcher = new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE);
+    }
+    else
+    {
+        FAIL() << "Unknown 2D features type: " << GetParam();
+    }
+
+    detail::ImageFeatures features1, features2;
+    (*finder)(img1, features1);
+    (*finder)(img2, features2);
+
+    detail::MatchesInfo pairwise_matches;
+
+    declare.in(features1.descriptors, features2.descriptors)
+            .iterations(100);
+
+    while(next())
+    {
+        cvflann::seed_random(42);//for predictive FlannBasedMatcher
+        startTimer();
+        (*matcher)(features1, features2, pairwise_matches);
+        stopTimer();
+        matcher->collectGarbage();
+    }
+}