Merge branch 'master' of https://github.com/Itseez/opencv into brief_cl

.gitignore

@@ -1,6 +1,7 @@
 *.autosave
 *.pyc
 *.user
+*~
 .*.swp
 .DS_Store
 .sw[a-z]

3rdparty/include/opencl/1.2/CL/cl_platform.h

@@ -332,13 +332,13 @@ typedef unsigned int cl_GLenum;
 /* Define basic vector types */
 #if defined( __VEC__ )
    #include <altivec.h>   /* may be omitted depending on compiler. AltiVec spec provides no way to detect whether the header is required. */
-   typedef vector unsigned char     __cl_uchar16;
+   typedef __vector unsigned char     __cl_uchar16;
-   typedef vector signed char       __cl_char16;
+   typedef __vector signed char       __cl_char16;
-   typedef vector unsigned short    __cl_ushort8;
+   typedef __vector unsigned short    __cl_ushort8;
-   typedef vector signed short      __cl_short8;
+   typedef __vector signed short      __cl_short8;
-   typedef vector unsigned int      __cl_uint4;
+   typedef __vector unsigned int      __cl_uint4;
-   typedef vector signed int        __cl_int4;
+   typedef __vector signed int        __cl_int4;
-   typedef vector float             __cl_float4;
+   typedef __vector float             __cl_float4;
    #define  __CL_UCHAR16__  1
    #define  __CL_CHAR16__   1
    #define  __CL_USHORT8__  1

apps/haartraining/cvclassifier.h

@@ -340,7 +340,7 @@ typedef enum CvBoostType
     CV_LKCLASS  = 5, /* classification (K class problem)    */
     CV_LSREG    = 6, /* least squares regression            */
     CV_LADREG   = 7, /* least absolute deviation regression */
-    CV_MREG     = 8, /* M-regression (Huber loss)           */
+    CV_MREG     = 8  /* M-regression (Huber loss)           */
 } CvBoostType;
 
 /****************************************************************************************\

doc/tutorials/introduction/linux_install/linux_install.rst

@@ -16,7 +16,7 @@ Required Packages
   * CMake 2.6 or higher;
   * Git;
   * GTK+2.x or higher, including headers (libgtk2.0-dev);
-  * pkgconfig;
+  * pkg-config;
   * Python 2.6 or later and Numpy 1.5 or later with developer packages (python-dev, python-numpy);
   * ffmpeg or libav development packages: libavcodec-dev, libavformat-dev, libswscale-dev;
   * [optional] libdc1394 2.x;

modules/bioinspired/src/retina.cpp

@@ -312,7 +312,7 @@ RetinaImpl::RetinaImpl(const cv::Size inputSz, const bool colorMode, int colorSa
 {
     _retinaFilter = 0;
     _init(inputSz, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
-};
+}
 
 RetinaImpl::~RetinaImpl()
 {

modules/calib3d/test/test_cameracalibration.cpp

@@ -337,7 +337,7 @@ void CV_CameraCalibrationTest::run( int start_from )
     int progress = 0;
     int values_read = -1;
 
-    sprintf( filepath, "%scameracalibration/", ts->get_data_path().c_str() );
+    sprintf( filepath, "%scv/cameracalibration/", ts->get_data_path().c_str() );
     sprintf( filename, "%sdatafiles.txt", filepath );
     datafile = fopen( filename, "r" );
     if( datafile == 0 )
@@ -1384,7 +1384,7 @@ void CV_StereoCalibrationTest::run( int )
     {
         char filepath[1000];
         char buf[1000];
-        sprintf( filepath, "%sstereo/case%d/stereo_calib.txt", ts->get_data_path().c_str(), testcase );
+        sprintf( filepath, "%scv/stereo/case%d/stereo_calib.txt", ts->get_data_path().c_str(), testcase );
         f = fopen(filepath, "rt");
         Size patternSize;
         vector<string> imglist;
@@ -1405,7 +1405,7 @@ void CV_StereoCalibrationTest::run( int )
                 buf[--len] = '\0';
             if( buf[0] == '#')
                 continue;
-            sprintf(filepath, "%sstereo/case%d/%s", ts->get_data_path().c_str(), testcase, buf );
+            sprintf(filepath, "%scv/stereo/case%d/%s", ts->get_data_path().c_str(), testcase, buf );
             imglist.push_back(string(filepath));
         }
         fclose(f);

modules/calib3d/test/test_chessboardgenerator.hpp

@@ -34,7 +34,7 @@ private:
     Mat rvec, tvec;
 };
 
-};
+}
 
 
 #endif

modules/calib3d/test/test_chesscorners.cpp

@@ -185,13 +185,13 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
     switch( pattern )
     {
         case CHESSBOARD:
-            folder = string(ts->get_data_path()) + "cameracalibration/";
+            folder = string(ts->get_data_path()) + "cv/cameracalibration/";
             break;
         case CIRCLES_GRID:
-            folder = string(ts->get_data_path()) + "cameracalibration/circles/";
+            folder = string(ts->get_data_path()) + "cv/cameracalibration/circles/";
             break;
         case ASYMMETRIC_CIRCLES_GRID:
-            folder = string(ts->get_data_path()) + "cameracalibration/asymmetric_circles/";
+            folder = string(ts->get_data_path()) + "cv/cameracalibration/asymmetric_circles/";
             break;
     }
 

modules/calib3d/test/test_chesscorners_timing.cpp

@@ -75,7 +75,7 @@ void CV_ChessboardDetectorTimingTest::run( int start_from )
     int  idx, max_idx;
     int  progress = 0;
 
-    sprintf( filepath, "%scameracalibration/", ts->get_data_path().c_str() );
+    sprintf( filepath, "%scv/cameracalibration/", ts->get_data_path().c_str() );
     sprintf( filename, "%schessboard_timing_list.dat", filepath );
     CvFileStorage* fs = cvOpenFileStorage( filename, 0, CV_STORAGE_READ );
     CvFileNode* board_list = fs ? cvGetFileNodeByName( fs, 0, "boards" ) : 0;

modules/calib3d/test/test_main.cpp

@@ -1,3 +1,3 @@
 #include "test_precomp.hpp"
 
-CV_TEST_MAIN("cv")
+CV_TEST_MAIN("")

modules/calib3d/test/test_stereomatching.cpp

@@ -398,7 +398,7 @@ protected:
 
 void CV_StereoMatchingTest::run(int)
 {
-    string dataPath = ts->get_data_path();
+    string dataPath = ts->get_data_path() + "cv/";
     string algorithmName = name;
     assert( !algorithmName.empty() );
     if( dataPath.empty() )

modules/contrib/src/adaptiveskindetector.cpp

@@ -55,7 +55,7 @@ void CvAdaptiveSkinDetector::initData(IplImage *src, int widthDivider, int heigh
     imgGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
     imgLastGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
     imgHSVFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 3);
-};
+}
 
 CvAdaptiveSkinDetector::CvAdaptiveSkinDetector(int samplingDivider, int morphingMethod)
 {
@@ -80,7 +80,7 @@ CvAdaptiveSkinDetector::CvAdaptiveSkinDetector(int samplingDivider, int morphing
     imgLastGrayFrame = NULL;
     imgSaturationFrame = NULL;
     imgHSVFrame = NULL;
-};
+}
 
 CvAdaptiveSkinDetector::~CvAdaptiveSkinDetector()
 {
@@ -93,7 +93,7 @@ CvAdaptiveSkinDetector::~CvAdaptiveSkinDetector()
     cvReleaseImage(&imgGrayFrame);
     cvReleaseImage(&imgLastGrayFrame);
     cvReleaseImage(&imgHSVFrame);
-};
+}
 
 void CvAdaptiveSkinDetector::process(IplImage *inputBGRImage, IplImage *outputHueMask)
 {
@@ -190,7 +190,7 @@ void CvAdaptiveSkinDetector::process(IplImage *inputBGRImage, IplImage *outputHu
 
     if (outputHueMask != NULL)
         cvCopy(imgFilteredFrame, outputHueMask);
-};
+}
 
 
 //------------------------- Histogram for Adaptive Skin Detector -------------------------//
@@ -202,12 +202,12 @@ CvAdaptiveSkinDetector::Histogram::Histogram()
     float *ranges[] = { range };
     fHistogram = cvCreateHist(1, histogramSize, CV_HIST_ARRAY, ranges, 1);
     cvClearHist(fHistogram);
-};
+}
 
 CvAdaptiveSkinDetector::Histogram::~Histogram()
 {
     cvReleaseHist(&fHistogram);
-};
+}
 
 int CvAdaptiveSkinDetector::Histogram::findCoverageIndex(double surfaceToCover, int defaultValue)
 {
@@ -221,7 +221,7 @@ int CvAdaptiveSkinDetector::Histogram::findCoverageIndex(double surfaceToCover,
         }
     }
     return defaultValue;
-};
+}
 
 void CvAdaptiveSkinDetector::Histogram::findCurveThresholds(int &x1, int &x2, double percent)
 {
@@ -244,7 +244,7 @@ void CvAdaptiveSkinDetector::Histogram::findCurveThresholds(int &x1, int &x2, do
         x2 = GSD_HUE_UT;
     else
         x2 += GSD_HUE_LT;
-};
+}
 
 void CvAdaptiveSkinDetector::Histogram::mergeWith(CvAdaptiveSkinDetector::Histogram *source, double weight)
 {
@@ -285,4 +285,4 @@ void CvAdaptiveSkinDetector::Histogram::mergeWith(CvAdaptiveSkinDetector::Histog
             }
         }
     }
-};
+}

modules/contrib/src/ba.cpp

@@ -940,7 +940,7 @@ static void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, C
 
 #endif
 
-};
+}
 static void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* estim, void* /*data*/) {
   //just do projections
   CvMat _Mi;
@@ -979,17 +979,17 @@ static void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, C
   cvTranspose( _mp2, estim );
   cvReleaseMat( &_mp );
   cvReleaseMat( &_mp2 );
-};
+}
 
 static void fjac_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data) {
   CvMat _point_params = point_params, _cam_params = cam_params, _Al = A, _Bl = B;
   fjac(i,j, &_point_params, &_cam_params, &_Al, &_Bl, data);
-};
+}
 
 static void func_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data)  {
   CvMat _point_params = point_params, _cam_params = cam_params, _estim = estim;
   func(i,j,&_point_params,&_cam_params,&_estim,data);
-};
+}
 
 void LevMarqSparse::bundleAdjust( std::vector<Point3d>& points, //positions of points in global coordinate system (input and output)
           const std::vector<std::vector<Point2d> >& imagePoints, //projections of 3d points for every camera

modules/contrib/src/facerec.cpp

@@ -872,7 +872,7 @@ CV_INIT_ALGORITHM(Eigenfaces, "FaceRecognizer.Eigenfaces",
                   obj.info()->addParam(obj, "labels", obj._labels, true);
                   obj.info()->addParam(obj, "eigenvectors", obj._eigenvectors, true);
                   obj.info()->addParam(obj, "eigenvalues", obj._eigenvalues, true);
-                  obj.info()->addParam(obj, "mean", obj._mean, true));
+                  obj.info()->addParam(obj, "mean", obj._mean, true))
 
 CV_INIT_ALGORITHM(Fisherfaces, "FaceRecognizer.Fisherfaces",
                   obj.info()->addParam(obj, "ncomponents", obj._num_components);
@@ -881,7 +881,7 @@ CV_INIT_ALGORITHM(Fisherfaces, "FaceRecognizer.Fisherfaces",
                   obj.info()->addParam(obj, "labels", obj._labels, true);
                   obj.info()->addParam(obj, "eigenvectors", obj._eigenvectors, true);
                   obj.info()->addParam(obj, "eigenvalues", obj._eigenvalues, true);
-                  obj.info()->addParam(obj, "mean", obj._mean, true));
+                  obj.info()->addParam(obj, "mean", obj._mean, true))
 
 CV_INIT_ALGORITHM(LBPH, "FaceRecognizer.LBPH",
                   obj.info()->addParam(obj, "radius", obj._radius);
@@ -890,7 +890,7 @@ CV_INIT_ALGORITHM(LBPH, "FaceRecognizer.LBPH",
                   obj.info()->addParam(obj, "grid_y", obj._grid_y);
                   obj.info()->addParam(obj, "threshold", obj._threshold);
                   obj.info()->addParam(obj, "histograms", obj._histograms, true);
-                  obj.info()->addParam(obj, "labels", obj._labels, true));
+                  obj.info()->addParam(obj, "labels", obj._labels, true))
 
 bool initModule_contrib()
 {

modules/contrib/src/fuzzymeanshifttracker.cpp

@@ -41,7 +41,7 @@ CvFuzzyPoint::CvFuzzyPoint(double _x, double _y)
 {
     x = _x;
     y = _y;
-};
+}
 
 bool CvFuzzyCurve::between(double x, double x1, double x2)
 {
@@ -51,37 +51,37 @@ bool CvFuzzyCurve::between(double x, double x1, double x2)
         return true;
 
     return false;
-};
+}
 
 CvFuzzyCurve::CvFuzzyCurve()
 {
     value = 0;
-};
+}
 
 CvFuzzyCurve::~CvFuzzyCurve()
 {
     // nothing to do
-};
+}
 
 void CvFuzzyCurve::setCentre(double _centre)
 {
     centre = _centre;
-};
+}
 
 double CvFuzzyCurve::getCentre()
 {
     return centre;
-};
+}
 
 void CvFuzzyCurve::clear()
 {
     points.clear();
-};
+}
 
 void CvFuzzyCurve::addPoint(double x, double y)
 {
     points.push_back(CvFuzzyPoint(x, y));
-};
+}
 
 double CvFuzzyCurve::calcValue(double param)
 {
@@ -102,41 +102,41 @@ double CvFuzzyCurve::calcValue(double param)
         }
     }
     return 0;
-};
+}
 
 double CvFuzzyCurve::getValue()
 {
     return value;
-};
+}
 
 void CvFuzzyCurve::setValue(double _value)
 {
     value = _value;
-};
+}
 
 
 CvFuzzyFunction::CvFuzzyFunction()
 {
     // nothing to do
-};
+}
 
 CvFuzzyFunction::~CvFuzzyFunction()
 {
     curves.clear();
-};
+}
 
 void CvFuzzyFunction::addCurve(CvFuzzyCurve *curve, double value)
 {
     curves.push_back(*curve);
     curve->setValue(value);
-};
+}
 
 void CvFuzzyFunction::resetValues()
 {
     int numCurves = (int)curves.size();
     for (int i = 0; i < numCurves; i++)
         curves[i].setValue(0);
-};
+}
 
 double CvFuzzyFunction::calcValue()
 {
@@ -153,7 +153,7 @@ double CvFuzzyFunction::calcValue()
         return s1/s2;
     else
         return 0;
-};
+}
 
 CvFuzzyCurve *CvFuzzyFunction::newCurve()
 {
@@ -161,14 +161,14 @@ CvFuzzyCurve *CvFuzzyFunction::newCurve()
     c = new CvFuzzyCurve();
     addCurve(c);
     return c;
-};
+}
 
 CvFuzzyRule::CvFuzzyRule()
 {
     fuzzyInput1 = NULL;
     fuzzyInput2 = NULL;
     fuzzyOutput = NULL;
-};
+}
 
 CvFuzzyRule::~CvFuzzyRule()
 {
@@ -180,14 +180,14 @@ CvFuzzyRule::~CvFuzzyRule()
 
     if (fuzzyOutput != NULL)
         delete fuzzyOutput;
-};
+}
 
 void CvFuzzyRule::setRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1)
 {
     fuzzyInput1 = c1;
     fuzzyInput2 = c2;
     fuzzyOutput = o1;
-};
+}
 
 double CvFuzzyRule::calcValue(double param1, double param2)
 {
@@ -203,31 +203,31 @@ double CvFuzzyRule::calcValue(double param1, double param2)
     }
     else
         return v1;
-};
+}
 
 CvFuzzyCurve *CvFuzzyRule::getOutputCurve()
 {
     return fuzzyOutput;
-};
+}
 
 CvFuzzyController::CvFuzzyController()
 {
     // nothing to do
-};
+}
 
 CvFuzzyController::~CvFuzzyController()
 {
     int size = (int)rules.size();
     for(int i = 0; i < size; i++)
         delete rules[i];
-};
+}
 
 void CvFuzzyController::addRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1)
 {
     CvFuzzyRule *f = new CvFuzzyRule();
     rules.push_back(f);
     f->setRule(c1, c2, o1);
-};
+}
 
 double CvFuzzyController::calcOutput(double param1, double param2)
 {
@@ -243,7 +243,7 @@ double CvFuzzyController::calcOutput(double param1, double param2)
     }
     v = list.calcValue();
     return v;
-};
+}
 
 CvFuzzyMeanShiftTracker::FuzzyResizer::FuzzyResizer()
 {
@@ -299,12 +299,12 @@ CvFuzzyMeanShiftTracker::FuzzyResizer::FuzzyResizer()
     fuzzyController.addRule(i1L, NULL, oS);
     fuzzyController.addRule(i1M, NULL, oZE);
     fuzzyController.addRule(i1H, NULL, oE);
-};
+}
 
 int CvFuzzyMeanShiftTracker::FuzzyResizer::calcOutput(double edgeDensity, double density)
 {
     return (int)fuzzyController.calcOutput(edgeDensity, density);
-};
+}
 
 CvFuzzyMeanShiftTracker::SearchWindow::SearchWindow()
 {
@@ -329,7 +329,7 @@ CvFuzzyMeanShiftTracker::SearchWindow::SearchWindow()
     depthLow = 0;
     depthHigh = 0;
     fuzzyResizer = NULL;
-};
+}
 
 CvFuzzyMeanShiftTracker::SearchWindow::~SearchWindow()
 {
@@ -355,7 +355,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::setSize(int _x, int _y, int _width,
 
     if (y + height > maxHeight)
         height = maxHeight - y;
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::initDepthValues(IplImage *maskImage, IplImage *depthMap)
 {
@@ -409,7 +409,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::initDepthValues(IplImage *maskImage,
         depthHigh = 32000;
         depthLow = 0;
     }
-};
+}
 
 bool CvFuzzyMeanShiftTracker::SearchWindow::shift()
 {
@@ -422,7 +422,7 @@ bool CvFuzzyMeanShiftTracker::SearchWindow::shift()
     {
         return false;
     }
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::extractInfo(IplImage *maskImage, IplImage *depthMap, bool initDepth)
 {
@@ -528,7 +528,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::extractInfo(IplImage *maskImage, Ipl
         ellipseAngle = 0;
         density = 0;
     }
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityLinear(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh) {
     int x1 = horizontalEdgeTop;
@@ -572,7 +572,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityLinear(in
     } else {
         resizeDw = - resizeDx;
     }
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsInnerDensity(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh)
 {
@@ -588,7 +588,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsInnerDensity(int &re
     resizeDy = (int)(py*dy);
     resizeDw = (int)((1-px)*dx);
     resizeDh = (int)((1-py)*dy);
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityFuzzy(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh)
 {
@@ -627,7 +627,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityFuzzy(int
         resizeDy = int(-dy1);
         resizeDh = int(dy1+dy2);
     }
-};
+}
 
 bool CvFuzzyMeanShiftTracker::SearchWindow::meanShift(IplImage *maskImage, IplImage *depthMap, int maxIteration, bool initDepth)
 {
@@ -640,7 +640,7 @@ bool CvFuzzyMeanShiftTracker::SearchWindow::meanShift(IplImage *maskImage, IplIm
     } while (++numShifts < maxIteration);
 
     return false;
-};
+}
 
 void CvFuzzyMeanShiftTracker::findOptimumSearchWindow(SearchWindow &searchWindow, IplImage *maskImage, IplImage *depthMap, int maxIteration, int resizeMethod, bool initDepth)
 {
@@ -680,17 +680,17 @@ void CvFuzzyMeanShiftTracker::findOptimumSearchWindow(SearchWindow &searchWindow
 
         searchWindow.setSize(searchWindow.x + resizeDx, searchWindow.y + resizeDy, searchWindow.width + resizeDw, searchWindow.height + resizeDh);
     }
-};
+}
 
 CvFuzzyMeanShiftTracker::CvFuzzyMeanShiftTracker()
 {
     searchMode = tsSetWindow;
-};
+}
 
 CvFuzzyMeanShiftTracker::~CvFuzzyMeanShiftTracker()
 {
     // nothing to do
-};
+}
 
 void CvFuzzyMeanShiftTracker::track(IplImage *maskImage, IplImage *depthMap, int resizeMethod, bool resetSearch, int minKernelMass)
 {
@@ -718,4 +718,4 @@ void CvFuzzyMeanShiftTracker::track(IplImage *maskImage, IplImage *depthMap, int
             else
                 searchMode = tsTracking;
     }
-};
+}

modules/contrib/src/spinimages.cpp

@@ -709,7 +709,7 @@ void cv::SpinImageModel::defaultParams()
 
     T_GeometriccConsistency = 0.25f;
     T_GroupingCorespondances = 0.25f;
-};
+}
 
 Mat cv::SpinImageModel::packRandomScaledSpins(bool separateScale, size_t xCount, size_t yCount) const
 {

modules/core/include/opencv2/core/mat.hpp

@@ -127,6 +127,7 @@ public:
     virtual int depth(int i=-1) const;
     virtual int channels(int i=-1) const;
     virtual bool isContinuous(int i=-1) const;
+    virtual bool isSubmatrix(int i=-1) const;
     virtual bool empty() const;
     virtual void copyTo(const _OutputArray& arr) const;
     virtual size_t offset(int i=-1) const;

modules/core/include/opencv2/core/mat.inl.hpp

@@ -186,6 +186,12 @@ inline _OutputArray::_OutputArray(const Mat& m)
 inline _OutputArray::_OutputArray(const std::vector<Mat>& vec)
 { init(FIXED_SIZE + STD_VECTOR_MAT + ACCESS_WRITE, &vec); }
 
+inline _OutputArray::_OutputArray(const UMat& m)
+{ init(FIXED_TYPE + FIXED_SIZE + UMAT + ACCESS_WRITE, &m); }
+
+inline _OutputArray::_OutputArray(const std::vector<UMat>& vec)
+{ init(FIXED_SIZE + STD_VECTOR_UMAT + ACCESS_WRITE, &vec); }
+
 inline _OutputArray::_OutputArray(const cuda::GpuMat& d_mat)
 { init(FIXED_TYPE + FIXED_SIZE + GPU_MAT + ACCESS_WRITE, &d_mat); }
 
@@ -1912,7 +1918,7 @@ SparseMat_<_Tp>::SparseMat_(const SparseMat& m)
     if( m.type() == DataType<_Tp>::type )
         *this = (const SparseMat_<_Tp>&)m;
     else
-        m.convertTo(this, DataType<_Tp>::type);
+        m.convertTo(*this, DataType<_Tp>::type);
 }
 
 template<typename _Tp> inline

modules/core/include/opencv2/core/operations.hpp

@@ -423,6 +423,12 @@ int print(const Mat& mtx, FILE* stream = stdout)
     return print(Formatter::get()->format(mtx), stream);
 }
 
+static inline
+int print(const UMat& mtx, FILE* stream = stdout)
+{
+    return print(Formatter::get()->format(mtx.getMat(ACCESS_READ)), stream);
+}
+
 template<typename _Tp> static inline
 int print(const std::vector<Point_<_Tp> >& vec, FILE* stream = stdout)
 {

modules/core/src/algorithm.cpp

@@ -628,7 +628,7 @@ void AlgorithmInfo::set(Algorithm* algo, const char* parameter, int argType, con
             || argType == Param::FLOAT || argType == Param::UNSIGNED_INT || argType == Param::UINT64 || argType == Param::UCHAR)
     {
         if ( !( p->type == Param::INT || p->type == Param::REAL || p->type == Param::BOOLEAN
-                || p->type == Param::UNSIGNED_INT || p->type == Param::UINT64 || p->type == Param::FLOAT || argType == Param::UCHAR) )
+                || p->type == Param::UNSIGNED_INT || p->type == Param::UINT64 || p->type == Param::FLOAT || p->type == Param::UCHAR) )
         {
             String message = getErrorMessageForWrongArgumentInSetter(algo->name(), parameter, p->type, argType);
             CV_Error(CV_StsBadArg, message);

modules/core/src/arithm.cpp

@@ -1434,8 +1434,8 @@ static void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
     bool haveScalar = false, swapped12 = false;
 
     if( dims1 != dims2 || sz1 != sz2 || cn != cn2 ||
-        ((kind1 == _InputArray::MATX || kind2 == _InputArray::MATX) &&
+        (kind1 == _InputArray::MATX && (sz1 == Size(1,4) || sz1 == Size(1,1))) ||
-         (sz1 == Size(1,4) || sz2 == Size(1,4))) )
+        (kind2 == _InputArray::MATX && (sz2 == Size(1,4) || sz2 == Size(1,1))) )
     {
         if( checkScalar(*psrc1, type2, kind1, kind2) )
         {

modules/core/src/convert.cpp

@@ -1040,122 +1040,122 @@ stype* dst, size_t dstep, Size size, double*) \
 }
 
 
-DEF_CVT_SCALE_ABS_FUNC(8u, cvtScaleAbs_, uchar, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(8u, cvtScaleAbs_, uchar, uchar, float)
-DEF_CVT_SCALE_ABS_FUNC(8s8u, cvtScaleAbs_, schar, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(8s8u, cvtScaleAbs_, schar, uchar, float)
-DEF_CVT_SCALE_ABS_FUNC(16u8u, cvtScaleAbs_, ushort, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(16u8u, cvtScaleAbs_, ushort, uchar, float)
-DEF_CVT_SCALE_ABS_FUNC(16s8u, cvtScaleAbs_, short, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(16s8u, cvtScaleAbs_, short, uchar, float)
-DEF_CVT_SCALE_ABS_FUNC(32s8u, cvtScaleAbs_, int, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(32s8u, cvtScaleAbs_, int, uchar, float)
-DEF_CVT_SCALE_ABS_FUNC(32f8u, cvtScaleAbs_, float, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(32f8u, cvtScaleAbs_, float, uchar, float)
-DEF_CVT_SCALE_ABS_FUNC(64f8u, cvtScaleAbs_, double, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(64f8u, cvtScaleAbs_, double, uchar, float)
 
-DEF_CVT_SCALE_FUNC(8u,     uchar, uchar, float);
+DEF_CVT_SCALE_FUNC(8u,     uchar, uchar, float)
-DEF_CVT_SCALE_FUNC(8s8u,   schar, uchar, float);
+DEF_CVT_SCALE_FUNC(8s8u,   schar, uchar, float)
-DEF_CVT_SCALE_FUNC(16u8u,  ushort, uchar, float);
+DEF_CVT_SCALE_FUNC(16u8u,  ushort, uchar, float)
-DEF_CVT_SCALE_FUNC(16s8u,  short, uchar, float);
+DEF_CVT_SCALE_FUNC(16s8u,  short, uchar, float)
-DEF_CVT_SCALE_FUNC(32s8u,  int, uchar, float);
+DEF_CVT_SCALE_FUNC(32s8u,  int, uchar, float)
-DEF_CVT_SCALE_FUNC(32f8u,  float, uchar, float);
+DEF_CVT_SCALE_FUNC(32f8u,  float, uchar, float)
-DEF_CVT_SCALE_FUNC(64f8u,  double, uchar, float);
+DEF_CVT_SCALE_FUNC(64f8u,  double, uchar, float)
 
-DEF_CVT_SCALE_FUNC(8u8s,   uchar, schar, float);
+DEF_CVT_SCALE_FUNC(8u8s,   uchar, schar, float)
-DEF_CVT_SCALE_FUNC(8s,     schar, schar, float);
+DEF_CVT_SCALE_FUNC(8s,     schar, schar, float)
-DEF_CVT_SCALE_FUNC(16u8s,  ushort, schar, float);
+DEF_CVT_SCALE_FUNC(16u8s,  ushort, schar, float)
-DEF_CVT_SCALE_FUNC(16s8s,  short, schar, float);
+DEF_CVT_SCALE_FUNC(16s8s,  short, schar, float)
-DEF_CVT_SCALE_FUNC(32s8s,  int, schar, float);
+DEF_CVT_SCALE_FUNC(32s8s,  int, schar, float)
-DEF_CVT_SCALE_FUNC(32f8s,  float, schar, float);
+DEF_CVT_SCALE_FUNC(32f8s,  float, schar, float)
-DEF_CVT_SCALE_FUNC(64f8s,  double, schar, float);
+DEF_CVT_SCALE_FUNC(64f8s,  double, schar, float)
 
-DEF_CVT_SCALE_FUNC(8u16u,  uchar, ushort, float);
+DEF_CVT_SCALE_FUNC(8u16u,  uchar, ushort, float)
-DEF_CVT_SCALE_FUNC(8s16u,  schar, ushort, float);
+DEF_CVT_SCALE_FUNC(8s16u,  schar, ushort, float)
-DEF_CVT_SCALE_FUNC(16u,    ushort, ushort, float);
+DEF_CVT_SCALE_FUNC(16u,    ushort, ushort, float)
-DEF_CVT_SCALE_FUNC(16s16u, short, ushort, float);
+DEF_CVT_SCALE_FUNC(16s16u, short, ushort, float)
-DEF_CVT_SCALE_FUNC(32s16u, int, ushort, float);
+DEF_CVT_SCALE_FUNC(32s16u, int, ushort, float)
-DEF_CVT_SCALE_FUNC(32f16u, float, ushort, float);
+DEF_CVT_SCALE_FUNC(32f16u, float, ushort, float)
-DEF_CVT_SCALE_FUNC(64f16u, double, ushort, float);
+DEF_CVT_SCALE_FUNC(64f16u, double, ushort, float)
 
-DEF_CVT_SCALE_FUNC(8u16s,  uchar, short, float);
+DEF_CVT_SCALE_FUNC(8u16s,  uchar, short, float)
-DEF_CVT_SCALE_FUNC(8s16s,  schar, short, float);
+DEF_CVT_SCALE_FUNC(8s16s,  schar, short, float)
-DEF_CVT_SCALE_FUNC(16u16s, ushort, short, float);
+DEF_CVT_SCALE_FUNC(16u16s, ushort, short, float)
-DEF_CVT_SCALE_FUNC(16s,    short, short, float);
+DEF_CVT_SCALE_FUNC(16s,    short, short, float)
-DEF_CVT_SCALE_FUNC(32s16s, int, short, float);
+DEF_CVT_SCALE_FUNC(32s16s, int, short, float)
-DEF_CVT_SCALE_FUNC(32f16s, float, short, float);
+DEF_CVT_SCALE_FUNC(32f16s, float, short, float)
-DEF_CVT_SCALE_FUNC(64f16s, double, short, float);
+DEF_CVT_SCALE_FUNC(64f16s, double, short, float)
 
-DEF_CVT_SCALE_FUNC(8u32s,  uchar, int, float);
+DEF_CVT_SCALE_FUNC(8u32s,  uchar, int, float)
-DEF_CVT_SCALE_FUNC(8s32s,  schar, int, float);
+DEF_CVT_SCALE_FUNC(8s32s,  schar, int, float)
-DEF_CVT_SCALE_FUNC(16u32s, ushort, int, float);
+DEF_CVT_SCALE_FUNC(16u32s, ushort, int, float)
-DEF_CVT_SCALE_FUNC(16s32s, short, int, float);
+DEF_CVT_SCALE_FUNC(16s32s, short, int, float)
-DEF_CVT_SCALE_FUNC(32s,    int, int, double);
+DEF_CVT_SCALE_FUNC(32s,    int, int, double)
-DEF_CVT_SCALE_FUNC(32f32s, float, int, float);
+DEF_CVT_SCALE_FUNC(32f32s, float, int, float)
-DEF_CVT_SCALE_FUNC(64f32s, double, int, double);
+DEF_CVT_SCALE_FUNC(64f32s, double, int, double)
 
-DEF_CVT_SCALE_FUNC(8u32f,  uchar, float, float);
+DEF_CVT_SCALE_FUNC(8u32f,  uchar, float, float)
-DEF_CVT_SCALE_FUNC(8s32f,  schar, float, float);
+DEF_CVT_SCALE_FUNC(8s32f,  schar, float, float)
-DEF_CVT_SCALE_FUNC(16u32f, ushort, float, float);
+DEF_CVT_SCALE_FUNC(16u32f, ushort, float, float)
-DEF_CVT_SCALE_FUNC(16s32f, short, float, float);
+DEF_CVT_SCALE_FUNC(16s32f, short, float, float)
-DEF_CVT_SCALE_FUNC(32s32f, int, float, double);
+DEF_CVT_SCALE_FUNC(32s32f, int, float, double)
-DEF_CVT_SCALE_FUNC(32f,    float, float, float);
+DEF_CVT_SCALE_FUNC(32f,    float, float, float)
-DEF_CVT_SCALE_FUNC(64f32f, double, float, double);
+DEF_CVT_SCALE_FUNC(64f32f, double, float, double)
 
-DEF_CVT_SCALE_FUNC(8u64f,  uchar, double, double);
+DEF_CVT_SCALE_FUNC(8u64f,  uchar, double, double)
-DEF_CVT_SCALE_FUNC(8s64f,  schar, double, double);
+DEF_CVT_SCALE_FUNC(8s64f,  schar, double, double)
-DEF_CVT_SCALE_FUNC(16u64f, ushort, double, double);
+DEF_CVT_SCALE_FUNC(16u64f, ushort, double, double)
-DEF_CVT_SCALE_FUNC(16s64f, short, double, double);
+DEF_CVT_SCALE_FUNC(16s64f, short, double, double)
-DEF_CVT_SCALE_FUNC(32s64f, int, double, double);
+DEF_CVT_SCALE_FUNC(32s64f, int, double, double)
-DEF_CVT_SCALE_FUNC(32f64f, float, double, double);
+DEF_CVT_SCALE_FUNC(32f64f, float, double, double)
-DEF_CVT_SCALE_FUNC(64f,    double, double, double);
+DEF_CVT_SCALE_FUNC(64f,    double, double, double)
 
-DEF_CPY_FUNC(8u,     uchar);
+DEF_CPY_FUNC(8u,     uchar)
-DEF_CVT_FUNC(8s8u,   schar, uchar);
+DEF_CVT_FUNC(8s8u,   schar, uchar)
-DEF_CVT_FUNC(16u8u,  ushort, uchar);
+DEF_CVT_FUNC(16u8u,  ushort, uchar)
-DEF_CVT_FUNC(16s8u,  short, uchar);
+DEF_CVT_FUNC(16s8u,  short, uchar)
-DEF_CVT_FUNC(32s8u,  int, uchar);
+DEF_CVT_FUNC(32s8u,  int, uchar)
-DEF_CVT_FUNC(32f8u,  float, uchar);
+DEF_CVT_FUNC(32f8u,  float, uchar)
-DEF_CVT_FUNC(64f8u,  double, uchar);
+DEF_CVT_FUNC(64f8u,  double, uchar)
 
-DEF_CVT_FUNC(8u8s,   uchar, schar);
+DEF_CVT_FUNC(8u8s,   uchar, schar)
-DEF_CVT_FUNC(16u8s,  ushort, schar);
+DEF_CVT_FUNC(16u8s,  ushort, schar)
-DEF_CVT_FUNC(16s8s,  short, schar);
+DEF_CVT_FUNC(16s8s,  short, schar)
-DEF_CVT_FUNC(32s8s,  int, schar);
+DEF_CVT_FUNC(32s8s,  int, schar)
-DEF_CVT_FUNC(32f8s,  float, schar);
+DEF_CVT_FUNC(32f8s,  float, schar)
-DEF_CVT_FUNC(64f8s,  double, schar);
+DEF_CVT_FUNC(64f8s,  double, schar)
 
-DEF_CVT_FUNC(8u16u,  uchar, ushort);
+DEF_CVT_FUNC(8u16u,  uchar, ushort)
-DEF_CVT_FUNC(8s16u,  schar, ushort);
+DEF_CVT_FUNC(8s16u,  schar, ushort)
-DEF_CPY_FUNC(16u,    ushort);
+DEF_CPY_FUNC(16u,    ushort)
-DEF_CVT_FUNC(16s16u, short, ushort);
+DEF_CVT_FUNC(16s16u, short, ushort)
-DEF_CVT_FUNC(32s16u, int, ushort);
+DEF_CVT_FUNC(32s16u, int, ushort)
-DEF_CVT_FUNC(32f16u, float, ushort);
+DEF_CVT_FUNC(32f16u, float, ushort)
-DEF_CVT_FUNC(64f16u, double, ushort);
+DEF_CVT_FUNC(64f16u, double, ushort)
 
-DEF_CVT_FUNC(8u16s,  uchar, short);
+DEF_CVT_FUNC(8u16s,  uchar, short)
-DEF_CVT_FUNC(8s16s,  schar, short);
+DEF_CVT_FUNC(8s16s,  schar, short)
-DEF_CVT_FUNC(16u16s, ushort, short);
+DEF_CVT_FUNC(16u16s, ushort, short)
-DEF_CVT_FUNC(32s16s, int, short);
+DEF_CVT_FUNC(32s16s, int, short)
-DEF_CVT_FUNC(32f16s, float, short);
+DEF_CVT_FUNC(32f16s, float, short)
-DEF_CVT_FUNC(64f16s, double, short);
+DEF_CVT_FUNC(64f16s, double, short)
 
-DEF_CVT_FUNC(8u32s,  uchar, int);
+DEF_CVT_FUNC(8u32s,  uchar, int)
-DEF_CVT_FUNC(8s32s,  schar, int);
+DEF_CVT_FUNC(8s32s,  schar, int)
-DEF_CVT_FUNC(16u32s, ushort, int);
+DEF_CVT_FUNC(16u32s, ushort, int)
-DEF_CVT_FUNC(16s32s, short, int);
+DEF_CVT_FUNC(16s32s, short, int)
-DEF_CPY_FUNC(32s,    int);
+DEF_CPY_FUNC(32s,    int)
-DEF_CVT_FUNC(32f32s, float, int);
+DEF_CVT_FUNC(32f32s, float, int)
-DEF_CVT_FUNC(64f32s, double, int);
+DEF_CVT_FUNC(64f32s, double, int)
 
-DEF_CVT_FUNC(8u32f,  uchar, float);
+DEF_CVT_FUNC(8u32f,  uchar, float)
-DEF_CVT_FUNC(8s32f,  schar, float);
+DEF_CVT_FUNC(8s32f,  schar, float)
-DEF_CVT_FUNC(16u32f, ushort, float);
+DEF_CVT_FUNC(16u32f, ushort, float)
-DEF_CVT_FUNC(16s32f, short, float);
+DEF_CVT_FUNC(16s32f, short, float)
-DEF_CVT_FUNC(32s32f, int, float);
+DEF_CVT_FUNC(32s32f, int, float)
-DEF_CVT_FUNC(64f32f, double, float);
+DEF_CVT_FUNC(64f32f, double, float)
 
-DEF_CVT_FUNC(8u64f,  uchar, double);
+DEF_CVT_FUNC(8u64f,  uchar, double)
-DEF_CVT_FUNC(8s64f,  schar, double);
+DEF_CVT_FUNC(8s64f,  schar, double)
-DEF_CVT_FUNC(16u64f, ushort, double);
+DEF_CVT_FUNC(16u64f, ushort, double)
-DEF_CVT_FUNC(16s64f, short, double);
+DEF_CVT_FUNC(16s64f, short, double)
-DEF_CVT_FUNC(32s64f, int, double);
+DEF_CVT_FUNC(32s64f, int, double)
-DEF_CVT_FUNC(32f64f, float, double);
+DEF_CVT_FUNC(32f64f, float, double)
-DEF_CPY_FUNC(64s,    int64);
+DEF_CPY_FUNC(64s,    int64)
 
 static BinaryFunc getCvtScaleAbsFunc(int depth)
 {

modules/core/src/copy.cpp

@@ -166,16 +166,16 @@ static void copyMask##suffix(const uchar* src, size_t sstep, const uchar* mask,
 }
 
 
-DEF_COPY_MASK(8u, uchar);
+DEF_COPY_MASK(8u, uchar)
-DEF_COPY_MASK(16u, ushort);
+DEF_COPY_MASK(16u, ushort)
-DEF_COPY_MASK(8uC3, Vec3b);
+DEF_COPY_MASK(8uC3, Vec3b)
-DEF_COPY_MASK(32s, int);
+DEF_COPY_MASK(32s, int)
-DEF_COPY_MASK(16uC3, Vec3s);
+DEF_COPY_MASK(16uC3, Vec3s)
-DEF_COPY_MASK(32sC2, Vec2i);
+DEF_COPY_MASK(32sC2, Vec2i)
-DEF_COPY_MASK(32sC3, Vec3i);
+DEF_COPY_MASK(32sC3, Vec3i)
-DEF_COPY_MASK(32sC4, Vec4i);
+DEF_COPY_MASK(32sC4, Vec4i)
-DEF_COPY_MASK(32sC6, Vec6i);
+DEF_COPY_MASK(32sC6, Vec6i)
-DEF_COPY_MASK(32sC8, Vec8i);
+DEF_COPY_MASK(32sC8, Vec8i)
 
 BinaryFunc copyMaskTab[] =
 {

modules/core/src/mathfuncs.cpp

@@ -2057,10 +2057,15 @@ static bool ocl_pow(InputArray _src, double power, OutputArray _dst)
     ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src),
             dstarg = ocl::KernelArg::WriteOnly(dst, cn);
 
-    if (depth == CV_32F)
+    if (issqrt)
-        k.args(srcarg, dstarg, (float)power);
+        k.args(srcarg, dstarg);
     else
-        k.args(srcarg, dstarg, power);
+    {
+        if (depth == CV_32F)
+            k.args(srcarg, dstarg, (float)power);
+        else
+            k.args(srcarg, dstarg, power);
+    }
 
     size_t globalsize[2] = { dst.cols *  cn, dst.rows };
     return k.run(2, globalsize, NULL, false);

modules/core/src/matrix.cpp

@@ -1808,6 +1808,37 @@ bool _InputArray::isContinuous(int i) const
     return false;
 }
 
+bool _InputArray::isSubmatrix(int i) const
+{
+    int k = kind();
+
+    if( k == MAT )
+        return i < 0 ? ((const Mat*)obj)->isSubmatrix() : false;
+
+    if( k == UMAT )
+        return i < 0 ? ((const UMat*)obj)->isSubmatrix() : false;
+
+    if( k == EXPR || k == MATX || k == STD_VECTOR || k == NONE || k == STD_VECTOR_VECTOR)
+        return false;
+
+    if( k == STD_VECTOR_MAT )
+    {
+        const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
+        CV_Assert((size_t)i < vv.size());
+        return vv[i].isSubmatrix();
+    }
+
+    if( k == STD_VECTOR_UMAT )
+    {
+        const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
+        CV_Assert((size_t)i < vv.size());
+        return vv[i].isSubmatrix();
+    }
+
+    CV_Error(CV_StsNotImplemented, "");
+    return false;
+}
+
 size_t _InputArray::offset(int i) const
 {
     int k = kind();

modules/core/src/system.cpp

@@ -849,7 +849,9 @@ public:
 };
 
 #ifdef WIN32
+#ifdef _MSC_VER
 #pragma warning(disable:4505) // unreferenced local function has been removed
+#endif
 
 #ifdef HAVE_WINRT
     // using C++11 thread attribute for local thread data

modules/core/src/umatrix.cpp

@@ -729,11 +729,12 @@ void UMat::convertTo(OutputArray _dst, int _type, double alpha, double beta) con
                              doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
         if (!k.empty())
         {
+            UMat src = *this;
             _dst.create( size(), _type );
             UMat dst = _dst.getUMat();
 
             float alphaf = (float)alpha, betaf = (float)beta;
-            k.args(ocl::KernelArg::ReadOnlyNoSize(*this), ocl::KernelArg::WriteOnly(dst, cn), alphaf, betaf);
+            k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst, cn), alphaf, betaf);
 
             size_t globalsize[2] = { dst.cols * cn, dst.rows };
             if (k.run(2, globalsize, NULL, false))

modules/core/test/test_arithm.cpp

@@ -115,7 +115,7 @@ struct BaseAddOp : public BaseElemWiseOp
 
 struct AddOp : public BaseAddOp
 {
-    AddOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {};
+    AddOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         if( mask.empty() )
@@ -128,7 +128,7 @@ struct AddOp : public BaseAddOp
 
 struct SubOp : public BaseAddOp
 {
-    SubOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, -1, Scalar::all(0)) {};
+    SubOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, -1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         if( mask.empty() )
@@ -141,7 +141,7 @@ struct SubOp : public BaseAddOp
 
 struct AddSOp : public BaseAddOp
 {
-    AddSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 0, Scalar::all(0)) {};
+    AddSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 0, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         if( mask.empty() )
@@ -154,7 +154,7 @@ struct AddSOp : public BaseAddOp
 
 struct SubRSOp : public BaseAddOp
 {
-    SubRSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, -1, 0, Scalar::all(0)) {};
+    SubRSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, -1, 0, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         if( mask.empty() )
@@ -167,7 +167,7 @@ struct SubRSOp : public BaseAddOp
 
 struct ScaleAddOp : public BaseAddOp
 {
-    ScaleAddOp() : BaseAddOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    ScaleAddOp() : BaseAddOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         scaleAdd(src[0], alpha, src[1], dst);
@@ -181,7 +181,7 @@ struct ScaleAddOp : public BaseAddOp
 
 struct AddWeightedOp : public BaseAddOp
 {
-    AddWeightedOp() : BaseAddOp(2, REAL_GAMMA, 1, 1, Scalar::all(0)) {};
+    AddWeightedOp() : BaseAddOp(2, REAL_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         addWeighted(src[0], alpha, src[1], beta, gamma[0], dst);
@@ -194,7 +194,7 @@ struct AddWeightedOp : public BaseAddOp
 
 struct MulOp : public BaseElemWiseOp
 {
-    MulOp() : BaseElemWiseOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    MulOp() : BaseElemWiseOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void getValueRange(int depth, double& minval, double& maxval)
     {
         minval = depth < CV_32S ? cvtest::getMinVal(depth) : depth == CV_32S ? -1000000 : -1000.;
@@ -218,7 +218,7 @@ struct MulOp : public BaseElemWiseOp
 
 struct DivOp : public BaseElemWiseOp
 {
-    DivOp() : BaseElemWiseOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    DivOp() : BaseElemWiseOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::divide(src[0], src[1], dst, alpha);
@@ -235,7 +235,7 @@ struct DivOp : public BaseElemWiseOp
 
 struct RecipOp : public BaseElemWiseOp
 {
-    RecipOp() : BaseElemWiseOp(1, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    RecipOp() : BaseElemWiseOp(1, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::divide(alpha, src[0], dst);
@@ -252,7 +252,7 @@ struct RecipOp : public BaseElemWiseOp
 
 struct AbsDiffOp : public BaseAddOp
 {
-    AbsDiffOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, -1, Scalar::all(0)) {};
+    AbsDiffOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, -1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         absdiff(src[0], src[1], dst);
@@ -265,7 +265,7 @@ struct AbsDiffOp : public BaseAddOp
 
 struct AbsDiffSOp : public BaseAddOp
 {
-    AbsDiffSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA, 1, 0, Scalar::all(0)) {};
+    AbsDiffSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA, 1, 0, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         absdiff(src[0], gamma, dst);
@@ -278,7 +278,7 @@ struct AbsDiffSOp : public BaseAddOp
 
 struct LogicOp : public BaseElemWiseOp
 {
-    LogicOp(char _opcode) : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)), opcode(_opcode) {};
+    LogicOp(char _opcode) : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)), opcode(_opcode) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         if( opcode == '&' )
@@ -309,7 +309,7 @@ struct LogicOp : public BaseElemWiseOp
 struct LogicSOp : public BaseElemWiseOp
 {
     LogicSOp(char _opcode)
-    : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+(_opcode != '~' ? SUPPORT_MASK : 0), 1, 1, Scalar::all(0)), opcode(_opcode) {};
+    : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+(_opcode != '~' ? SUPPORT_MASK : 0), 1, 1, Scalar::all(0)), opcode(_opcode) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         if( opcode == '&' )
@@ -341,7 +341,7 @@ struct LogicSOp : public BaseElemWiseOp
 
 struct MinOp : public BaseElemWiseOp
 {
-    MinOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    MinOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::min(src[0], src[1], dst);
@@ -358,7 +358,7 @@ struct MinOp : public BaseElemWiseOp
 
 struct MaxOp : public BaseElemWiseOp
 {
-    MaxOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    MaxOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::max(src[0], src[1], dst);
@@ -375,7 +375,7 @@ struct MaxOp : public BaseElemWiseOp
 
 struct MinSOp : public BaseElemWiseOp
 {
-    MinSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {};
+    MinSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::min(src[0], gamma[0], dst);
@@ -392,7 +392,7 @@ struct MinSOp : public BaseElemWiseOp
 
 struct MaxSOp : public BaseElemWiseOp
 {
-    MaxSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {};
+    MaxSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::max(src[0], gamma[0], dst);
@@ -409,7 +409,7 @@ struct MaxSOp : public BaseElemWiseOp
 
 struct CmpOp : public BaseElemWiseOp
 {
-    CmpOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    CmpOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void generateScalars(int depth, RNG& rng)
     {
         BaseElemWiseOp::generateScalars(depth, rng);
@@ -437,7 +437,7 @@ struct CmpOp : public BaseElemWiseOp
 
 struct CmpSOp : public BaseElemWiseOp
 {
-    CmpSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {};
+    CmpSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}
     void generateScalars(int depth, RNG& rng)
     {
         BaseElemWiseOp::generateScalars(depth, rng);
@@ -467,7 +467,7 @@ struct CmpSOp : public BaseElemWiseOp
 
 struct CopyOp : public BaseElemWiseOp
 {
-    CopyOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {};
+    CopyOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
     {
         src[0].copyTo(dst, mask);
@@ -490,7 +490,7 @@ struct CopyOp : public BaseElemWiseOp
 
 struct SetOp : public BaseElemWiseOp
 {
-    SetOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {};
+    SetOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>&, Mat& dst, const Mat& mask)
     {
         dst.setTo(gamma, mask);
@@ -651,7 +651,7 @@ static void inRangeS(const Mat& src, const Scalar& lb, const Scalar& rb, Mat& ds
 
 struct InRangeSOp : public BaseElemWiseOp
 {
-    InRangeSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA, 1, 1, Scalar::all(0)) {};
+    InRangeSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::inRange(src[0], gamma, gamma1, dst);
@@ -681,7 +681,7 @@ struct InRangeSOp : public BaseElemWiseOp
 
 struct InRangeOp : public BaseElemWiseOp
 {
-    InRangeOp() : BaseElemWiseOp(3, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    InRangeOp() : BaseElemWiseOp(3, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         Mat lb, rb;
@@ -707,7 +707,7 @@ struct InRangeOp : public BaseElemWiseOp
 
 struct ConvertScaleOp : public BaseElemWiseOp
 {
-    ConvertScaleOp() : BaseElemWiseOp(1, FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)), ddepth(0) { };
+    ConvertScaleOp() : BaseElemWiseOp(1, FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)), ddepth(0) { }
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         src[0].convertTo(dst, ddepth, alpha, gamma[0]);
@@ -742,7 +742,7 @@ struct ConvertScaleOp : public BaseElemWiseOp
 
 struct ConvertScaleAbsOp : public BaseElemWiseOp
 {
-    ConvertScaleAbsOp() : BaseElemWiseOp(1, FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {};
+    ConvertScaleAbsOp() : BaseElemWiseOp(1, FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>& src, Mat& dst, const Mat&)
     {
         cv::convertScaleAbs(src[0], dst, alpha, gamma[0]);
@@ -810,7 +810,7 @@ static void setIdentity(Mat& dst, const Scalar& s)
 
 struct FlipOp : public BaseElemWiseOp
 {
-    FlipOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    FlipOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void getRandomSize(RNG& rng, vector<int>& size)
     {
         cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size);
@@ -836,7 +836,7 @@ struct FlipOp : public BaseElemWiseOp
 
 struct TransposeOp : public BaseElemWiseOp
 {
-    TransposeOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    TransposeOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void getRandomSize(RNG& rng, vector<int>& size)
     {
         cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size);
@@ -857,7 +857,7 @@ struct TransposeOp : public BaseElemWiseOp
 
 struct SetIdentityOp : public BaseElemWiseOp
 {
-    SetIdentityOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA, 1, 1, Scalar::all(0)) {};
+    SetIdentityOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA, 1, 1, Scalar::all(0)) {}
     void getRandomSize(RNG& rng, vector<int>& size)
     {
         cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size);
@@ -878,7 +878,7 @@ struct SetIdentityOp : public BaseElemWiseOp
 
 struct SetZeroOp : public BaseElemWiseOp
 {
-    SetZeroOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    SetZeroOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     void op(const vector<Mat>&, Mat& dst, const Mat&)
     {
         dst = Scalar::all(0);
@@ -954,7 +954,7 @@ static void log(const Mat& src, Mat& dst)
 
 struct ExpOp : public BaseElemWiseOp
 {
-    ExpOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    ExpOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     int getRandomType(RNG& rng)
     {
         return cvtest::randomType(rng, _OutputArray::DEPTH_MASK_FLT, 1, ARITHM_MAX_CHANNELS);
@@ -981,7 +981,7 @@ struct ExpOp : public BaseElemWiseOp
 
 struct LogOp : public BaseElemWiseOp
 {
-    LogOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {};
+    LogOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}
     int getRandomType(RNG& rng)
     {
         return cvtest::randomType(rng, _OutputArray::DEPTH_MASK_FLT, 1, ARITHM_MAX_CHANNELS);
@@ -1564,3 +1564,19 @@ TEST(Core_round, CvRound)
     ASSERT_EQ(-2, cvRound(-2.5));
     ASSERT_EQ(-4, cvRound(-3.5));
 }
+
+
+typedef testing::TestWithParam<Size> Mul1;
+
+TEST_P(Mul1, One)
+{
+    Size size = GetParam();
+    cv::Mat src(size, CV_32FC1, cv::Scalar::all(2)), dst,
+            ref_dst(size, CV_32FC1, cv::Scalar::all(6));
+
+    cv::multiply(3, src, dst);
+
+    ASSERT_EQ(0, cv::norm(dst, ref_dst, cv::NORM_INF));
+}
+
+INSTANTIATE_TEST_CASE_P(Arithm, Mul1, testing::Values(Size(2, 2), Size(1, 1)));

modules/cudaimgproc/perf/perf_match_template.cpp

@@ -90,7 +90,7 @@ PERF_TEST_P(Sz_TemplateSz_Cn_Method, MatchTemplate8U,
 
         CPU_SANITY_CHECK(dst);
     }
-};
+}
 
 ////////////////////////////////////////////////////////////////////////////////
 // MatchTemplate32F

modules/features2d/src/features2d_init.cpp

@@ -58,19 +58,19 @@ Ptr<Feature2D> Feature2D::create( const String& feature2DType )
 
 CV_INIT_ALGORITHM(BRISK, "Feature2D.BRISK",
                    obj.info()->addParam(obj, "thres", obj.threshold);
-                   obj.info()->addParam(obj, "octaves", obj.octaves));
+                   obj.info()->addParam(obj, "octaves", obj.octaves))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
 CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
-                  obj.info()->addParam(obj, "bytes", obj.bytes_));
+                  obj.info()->addParam(obj, "bytes", obj.bytes_))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
 CV_INIT_ALGORITHM(FastFeatureDetector, "Feature2D.FAST",
                   obj.info()->addParam(obj, "threshold", obj.threshold);
                   obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression);
-                  obj.info()->addParam(obj, "type", obj.type));
+                  obj.info()->addParam(obj, "type", obj.type))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -79,7 +79,7 @@ CV_INIT_ALGORITHM(StarDetector, "Feature2D.STAR",
                   obj.info()->addParam(obj, "responseThreshold", obj.responseThreshold);
                   obj.info()->addParam(obj, "lineThresholdProjected", obj.lineThresholdProjected);
                   obj.info()->addParam(obj, "lineThresholdBinarized", obj.lineThresholdBinarized);
-                  obj.info()->addParam(obj, "suppressNonmaxSize", obj.suppressNonmaxSize));
+                  obj.info()->addParam(obj, "suppressNonmaxSize", obj.suppressNonmaxSize))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -92,7 +92,7 @@ CV_INIT_ALGORITHM(MSER, "Feature2D.MSER",
                   obj.info()->addParam(obj, "maxEvolution", obj.maxEvolution);
                   obj.info()->addParam(obj, "areaThreshold", obj.areaThreshold);
                   obj.info()->addParam(obj, "minMargin", obj.minMargin);
-                  obj.info()->addParam(obj, "edgeBlurSize", obj.edgeBlurSize));
+                  obj.info()->addParam(obj, "edgeBlurSize", obj.edgeBlurSize))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -104,7 +104,7 @@ CV_INIT_ALGORITHM(ORB, "Feature2D.ORB",
                   obj.info()->addParam(obj, "edgeThreshold", obj.edgeThreshold);
                   obj.info()->addParam(obj, "patchSize", obj.patchSize);
                   obj.info()->addParam(obj, "WTA_K", obj.WTA_K);
-                  obj.info()->addParam(obj, "scoreType", obj.scoreType));
+                  obj.info()->addParam(obj, "scoreType", obj.scoreType))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -112,7 +112,7 @@ CV_INIT_ALGORITHM(FREAK, "Feature2D.FREAK",
                   obj.info()->addParam(obj, "orientationNormalized", obj.orientationNormalized);
                   obj.info()->addParam(obj, "scaleNormalized", obj.scaleNormalized);
                   obj.info()->addParam(obj, "patternScale", obj.patternScale);
-                  obj.info()->addParam(obj, "nbOctave", obj.nOctaves));
+                  obj.info()->addParam(obj, "nbOctave", obj.nOctaves))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -121,7 +121,7 @@ CV_INIT_ALGORITHM(GFTTDetector, "Feature2D.GFTT",
                   obj.info()->addParam(obj, "qualityLevel", obj.qualityLevel);
                   obj.info()->addParam(obj, "minDistance", obj.minDistance);
                   obj.info()->addParam(obj, "useHarrisDetector", obj.useHarrisDetector);
-                  obj.info()->addParam(obj, "k", obj.k));
+                  obj.info()->addParam(obj, "k", obj.k))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -141,7 +141,7 @@ CV_INIT_ALGORITHM(SimpleBlobDetector, "Feature2D.SimpleBlob",
                   obj.info()->addParam(obj, "maxInertiaRatio",  obj.params.maxInertiaRatio);
                   obj.info()->addParam(obj, "filterByConvexity", obj.params.filterByConvexity);
                   obj.info()->addParam(obj, "maxConvexity",     obj.params.maxConvexity);
-                  );
+                  )
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -162,7 +162,7 @@ CV_INIT_ALGORITHM(HarrisDetector, "Feature2D.HARRIS",
                   obj.info()->addParam(obj, "qualityLevel", obj.qualityLevel);
                   obj.info()->addParam(obj, "minDistance", obj.minDistance);
                   obj.info()->addParam(obj, "useHarrisDetector", obj.useHarrisDetector);
-                  obj.info()->addParam(obj, "k", obj.k));
+                  obj.info()->addParam(obj, "k", obj.k))
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -173,21 +173,21 @@ CV_INIT_ALGORITHM(DenseFeatureDetector, "Feature2D.Dense",
                   obj.info()->addParam(obj, "initXyStep", obj.initXyStep);
                   obj.info()->addParam(obj, "initImgBound", obj.initImgBound);
                   obj.info()->addParam(obj, "varyXyStepWithScale", obj.varyXyStepWithScale);
-                  obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale));
+                  obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale))
 
 CV_INIT_ALGORITHM(GridAdaptedFeatureDetector, "Feature2D.Grid",
                   obj.info()->addParam<FeatureDetector>(obj, "detector", obj.detector, false, 0, 0); // Extra params added to avoid VS2013 fatal error in opencv2/core.hpp (decl. of addParam)
                   obj.info()->addParam(obj, "maxTotalKeypoints", obj.maxTotalKeypoints);
                   obj.info()->addParam(obj, "gridRows", obj.gridRows);
-                  obj.info()->addParam(obj, "gridCols", obj.gridCols));
+                  obj.info()->addParam(obj, "gridCols", obj.gridCols))
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////////////
 
 CV_INIT_ALGORITHM(BFMatcher, "DescriptorMatcher.BFMatcher",
                   obj.info()->addParam(obj, "normType", obj.normType);
-                  obj.info()->addParam(obj, "crossCheck", obj.crossCheck));
+                  obj.info()->addParam(obj, "crossCheck", obj.crossCheck))
 
-CV_INIT_ALGORITHM(FlannBasedMatcher, "DescriptorMatcher.FlannBasedMatcher",);
+CV_INIT_ALGORITHM(FlannBasedMatcher, "DescriptorMatcher.FlannBasedMatcher",)
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 

modules/flann/include/opencv2/flann/hierarchical_clustering_index.h

@@ -413,12 +413,6 @@ public:
 
     void loadIndex(FILE* stream)
     {
-        load_value(stream, branching_);
-        load_value(stream, trees_);
-        load_value(stream, centers_init_);
-        load_value(stream, leaf_size_);
-        load_value(stream, memoryCounter);
-
         free_elements();
 
         if (root!=NULL) {
@@ -429,6 +423,12 @@ public:
             delete[] indices;
         }
 
+        load_value(stream, branching_);
+        load_value(stream, trees_);
+        load_value(stream, centers_init_);
+        load_value(stream, leaf_size_);
+        load_value(stream, memoryCounter);
+
         indices = new int*[trees_];
         root = new NodePtr[trees_];
         for (int i=0; i<trees_; ++i) {

modules/highgui/doc/user_interface.rst

@@ -208,6 +208,26 @@ Sets mouse handler for the specified window
     :param userdata: The optional parameter passed to the callback.
 
 
+getMouseWheelDelta
+------------------
+Gets the mouse-wheel motion delta, when handling mouse-wheel events EVENT_MOUSEWHEEL and EVENT_MOUSEHWHEEL.
+
+.. ocv:function:: int getMouseWheelDelta(int flags)
+
+    :param flags: The mouse callback flags parameter.
+
+For regular mice with a scroll-wheel, delta will be a multiple of 120. The value 120 corresponds to a one notch rotation of the wheel or the threshold for action to be taken and one such action should occur for each delta.
+Some high-precision mice with higher-resolution freely-rotating wheels may generate smaller values.
+
+For EVENT_MOUSEWHEEL positive and negative values mean forward and backward scrolling, respectively.
+For EVENT_MOUSEHWHEEL, where available, positive and negative values mean right and left scrolling, respectively.
+
+With the C API, the macro CV_GET_WHEEL_DELTA(flags) can be used alternatively.
+
+.. note::
+
+    Mouse-wheel events are currently supported only on Windows.
+
 setTrackbarPos
 ------------------
 Sets the trackbar position.

modules/highgui/include/opencv2/highgui.hpp

@@ -76,7 +76,9 @@ enum { EVENT_MOUSEMOVE      = 0,
        EVENT_MBUTTONUP      = 6,
        EVENT_LBUTTONDBLCLK  = 7,
        EVENT_RBUTTONDBLCLK  = 8,
-       EVENT_MBUTTONDBLCLK  = 9
+       EVENT_MBUTTONDBLCLK  = 9,
+       EVENT_MOUSEWHEEL     = 10,
+       EVENT_MOUSEHWHEEL    = 11
      };
 
 enum { EVENT_FLAG_LBUTTON   = 1,
@@ -137,6 +139,8 @@ CV_EXPORTS_W double getWindowProperty(const String& winname, int prop_id);
 //! assigns callback for mouse events
 CV_EXPORTS void setMouseCallback(const String& winname, MouseCallback onMouse, void* userdata = 0);
 
+CV_EXPORTS int getMouseWheelDelta(int flags);
+
 CV_EXPORTS int createTrackbar(const String& trackbarname, const String& winname,
                               int* value, int count,
                               TrackbarCallback onChange = 0,

modules/highgui/include/opencv2/highgui/highgui_c.h

@@ -170,7 +170,9 @@ enum
     CV_EVENT_MBUTTONUP      =6,
     CV_EVENT_LBUTTONDBLCLK  =7,
     CV_EVENT_RBUTTONDBLCLK  =8,
-    CV_EVENT_MBUTTONDBLCLK  =9
+    CV_EVENT_MBUTTONDBLCLK  =9,
+    CV_EVENT_MOUSEWHEEL     =10,
+    CV_EVENT_MOUSEHWHEEL    =11
 };
 
 enum
@@ -183,6 +185,9 @@ enum
     CV_EVENT_FLAG_ALTKEY    =32
 };
 
+
+#define CV_GET_WHEEL_DELTA(flags) ((short)((flags >> 16) & 0xffff)) // upper 16 bits
+
 typedef void (CV_CDECL *CvMouseCallback )(int event, int x, int y, int flags, void* param);
 
 /* assign callback for mouse events */

modules/highgui/src/bitstrm.hpp

@@ -53,7 +53,7 @@ enum
     RBS_THROW_EOS=-123,  // <end of stream> exception code
     RBS_THROW_FORB=-124,  // <forrbidden huffman code> exception code
     RBS_HUFF_FORB=2047,  // forrbidden huffman code "value"
-    RBS_BAD_HEADER=-125, // invalid header
+    RBS_BAD_HEADER=-125 // invalid header
 };
 
 typedef unsigned long ulong;

modules/highgui/src/cap_ffmpeg_impl.hpp

@@ -2096,7 +2096,7 @@ enum
     VideoCodec_YV12   = (('Y'<<24)|('V'<<16)|('1'<<8)|('2')),   // Y,V,U (4:2:0)
     VideoCodec_NV12   = (('N'<<24)|('V'<<16)|('1'<<8)|('2')),   // Y,UV  (4:2:0)
     VideoCodec_YUYV   = (('Y'<<24)|('U'<<16)|('Y'<<8)|('V')),   // YUYV/YUY2 (4:2:2)
-    VideoCodec_UYVY   = (('U'<<24)|('Y'<<16)|('V'<<8)|('Y')),   // UYVY (4:2:2)
+    VideoCodec_UYVY   = (('U'<<24)|('Y'<<16)|('V'<<8)|('Y'))    // UYVY (4:2:2)
 };
 
 enum
@@ -2104,7 +2104,7 @@ enum
     VideoChromaFormat_Monochrome = 0,
     VideoChromaFormat_YUV420,
     VideoChromaFormat_YUV422,
-    VideoChromaFormat_YUV444,
+    VideoChromaFormat_YUV444
 };
 
 struct InputMediaStream_FFMPEG

modules/highgui/src/precomp.hpp

@@ -58,6 +58,14 @@
 #include <assert.h>
 
 #if defined WIN32 || defined WINCE
+    #if !defined _WIN32_WINNT
+        #ifdef HAVE_MSMF
+            #define _WIN32_WINNT 0x0600 // Windows Vista
+        #else
+            #define _WIN32_WINNT 0x0500 // Windows 2000
+        #endif
+    #endif
+
     #include <windows.h>
     #undef small
     #undef min

modules/highgui/src/window.cpp

@@ -216,6 +216,11 @@ void cv::setMouseCallback( const String& windowName, MouseCallback onMouse, void
     cvSetMouseCallback(windowName.c_str(), onMouse, param);
 }
 
+int cv::getMouseWheelDelta( int flags )
+{
+    return CV_GET_WHEEL_DELTA(flags);
+}
+
 int cv::startWindowThread()
 {
     return cvStartWindowThread();

modules/highgui/src/window_w32.cpp

@@ -40,30 +40,15 @@
 //M*/
 
 #include "precomp.hpp"
+#include <windowsx.h> // required for GET_X_LPARAM() and GET_Y_LPARAM() macros
 
 #if defined WIN32 || defined _WIN32
 
-#define COMPILE_MULTIMON_STUBS // Required for multi-monitor support
-#ifndef _MULTIMON_USE_SECURE_CRT
-#  define _MULTIMON_USE_SECURE_CRT 0 // some MinGW platforms have no strncpy_s
-#endif
-
-#if defined SM_CMONITORS && !defined MONITOR_DEFAULTTONEAREST
-#  define MONITOR_DEFAULTTONULL       0x00000000
-#  define MONITOR_DEFAULTTOPRIMARY    0x00000001
-#  define MONITOR_DEFAULTTONEAREST    0x00000002
-#  define MONITORINFOF_PRIMARY        0x00000001
-#endif
-#ifndef __inout
-#  define __inout
-#endif
-
 #ifdef __GNUC__
 #  pragma GCC diagnostic ignored "-Wmissing-declarations"
 #endif
 
 #include <commctrl.h>
-#include <winuser.h>
 #include <stdlib.h>
 #include <string.h>
 #include <stdio.h>
@@ -1377,6 +1362,39 @@ MainWindowProc( HWND hwnd, UINT uMsg, WPARAM wParam, LPARAM lParam )
             SetFocus(window->hwnd);
         break;
 
+    case WM_MOUSEWHEEL:
+    case WM_MOUSEHWHEEL:
+       if( window->on_mouse )
+       {
+          int flags = (wParam & MK_LBUTTON      ? CV_EVENT_FLAG_LBUTTON  : 0)|
+                      (wParam & MK_RBUTTON      ? CV_EVENT_FLAG_RBUTTON  : 0)|
+                      (wParam & MK_MBUTTON      ? CV_EVENT_FLAG_MBUTTON  : 0)|
+                      (wParam & MK_CONTROL      ? CV_EVENT_FLAG_CTRLKEY  : 0)|
+                      (wParam & MK_SHIFT        ? CV_EVENT_FLAG_SHIFTKEY : 0)|
+                      (GetKeyState(VK_MENU) < 0 ? CV_EVENT_FLAG_ALTKEY   : 0);
+          int event = (uMsg == WM_MOUSEWHEEL    ? CV_EVENT_MOUSEWHEEL    : CV_EVENT_MOUSEHWHEEL);
+
+          // Set the wheel delta of mouse wheel to be in the upper word of 'event'
+          int delta = GET_WHEEL_DELTA_WPARAM(wParam);
+          flags |= (delta << 16);
+
+          POINT pt;
+          pt.x = GET_X_LPARAM( lParam );
+          pt.y = GET_Y_LPARAM( lParam );
+          ::ScreenToClient(hwnd, &pt); // Convert screen coordinates to client coordinates.
+
+          RECT rect;
+          GetClientRect( window->hwnd, &rect );
+
+          SIZE size = {0,0};
+          icvGetBitmapData( window, &size, 0, 0 );
+
+          window->on_mouse( event, pt.x*size.cx/MAX(rect.right - rect.left,1),
+                                   pt.y*size.cy/MAX(rect.bottom - rect.top,1), flags,
+                                   window->on_mouse_param );
+       }
+       break;
+
     case WM_ERASEBKGND:
         {
             RECT cr, tr, wrc;
@@ -1474,8 +1492,8 @@ static LRESULT CALLBACK HighGUIProc( HWND hwnd, UINT uMsg, WPARAM wParam, LPARAM
             if( uMsg == WM_LBUTTONUP || uMsg == WM_RBUTTONUP || uMsg == WM_MBUTTONUP )
                 ReleaseCapture();
 
-            pt.x = LOWORD( lParam );
+            pt.x = GET_X_LPARAM( lParam );
-            pt.y = HIWORD( lParam );
+            pt.y = GET_Y_LPARAM( lParam );
 
             GetClientRect( window->hwnd, &rect );
             icvGetBitmapData( window, &size, 0, 0 );

modules/imgproc/perf/opencl/perf_blend.cpp

@@ -0,0 +1,82 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+///////////// BlendLinear ////////////////////////
+
+typedef Size_MatType BlendLinearFixture;
+
+OCL_PERF_TEST_P(BlendLinearFixture, BlendLinear, ::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_32FC1, CV_32FC4)))
+{
+    Size_MatType_t params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int srcType = get<1>(params);
+    const double eps = CV_MAT_DEPTH(srcType) <= CV_32S ? 1.0 : 0.2;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, srcType);
+
+    UMat src1(srcSize, srcType), src2(srcSize, srcType), dst(srcSize, srcType);
+    UMat weights1(srcSize, CV_32FC1), weights2(srcSize, CV_32FC1);
+
+    declare.in(src1, src2, WARMUP_RNG).in(weights1, weights2, WARMUP_READ).out(dst);
+    randu(weights1, 0, 1);
+    randu(weights2, 0, 1);
+
+    OCL_TEST_CYCLE() cv::blendLinear(src1, src2, weights1, weights2, dst);
+
+    SANITY_CHECK(dst, eps);
+}
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/opencl/perf_color.cpp

@@ -0,0 +1,104 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+using std::tr1::make_tuple;
+
+///////////// cvtColor////////////////////////
+
+CV_ENUM(ConversionTypes, COLOR_RGB2GRAY, COLOR_RGB2BGR, COLOR_RGB2YUV, COLOR_YUV2RGB, COLOR_RGB2YCrCb,
+        COLOR_YCrCb2RGB, COLOR_RGB2XYZ, COLOR_XYZ2RGB, COLOR_RGB2HSV, COLOR_HSV2RGB, COLOR_RGB2HLS,
+        COLOR_HLS2RGB, COLOR_BGR5652BGR, COLOR_BGR2BGR565, COLOR_RGBA2mRGBA, COLOR_mRGBA2RGBA, COLOR_YUV2RGB_NV12)
+
+typedef tuple<Size, tuple<ConversionTypes, int, int> > CvtColorParams;
+typedef TestBaseWithParam<CvtColorParams> CvtColorFixture;
+
+OCL_PERF_TEST_P(CvtColorFixture, CvtColor, testing::Combine(
+                OCL_TEST_SIZES,
+                testing::Values(
+                    make_tuple(ConversionTypes(COLOR_RGB2GRAY), 3, 1),
+                    make_tuple(ConversionTypes(COLOR_RGB2BGR), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_RGB2YUV), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_YUV2RGB), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_RGB2YCrCb), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_YCrCb2RGB), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_RGB2XYZ), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_XYZ2RGB), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_RGB2HSV), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_HSV2RGB), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_RGB2HLS), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_HLS2RGB), 3, 3),
+                    make_tuple(ConversionTypes(COLOR_BGR5652BGR), 2, 3),
+                    make_tuple(ConversionTypes(COLOR_BGR2BGR565), 3, 2),
+                    make_tuple(ConversionTypes(COLOR_RGBA2mRGBA), 4, 4),
+                    make_tuple(ConversionTypes(COLOR_mRGBA2RGBA), 4, 4),
+                    make_tuple(ConversionTypes(COLOR_YUV2RGB_NV12), 1, 3)
+                    )))
+{
+    CvtColorParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const tuple<int, int, int> conversionParams = get<1>(params);
+    const int code = get<0>(conversionParams), scn = get<1>(conversionParams),
+            dcn = get<2>(conversionParams);
+
+    UMat src(srcSize, CV_8UC(scn)), dst(srcSize, CV_8UC(scn));
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::cvtColor(src, dst, code, dcn);
+
+    SANITY_CHECK(dst, 1);
+}
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/opencl/perf_filters.cpp

@@ -0,0 +1,302 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+typedef tuple<Size, MatType, int> FilterParams;
+typedef TestBaseWithParam<FilterParams> FilterFixture;
+
+///////////// Blur ////////////////////////
+
+typedef FilterFixture BlurFixture;
+
+OCL_PERF_TEST_P(BlurFixture, Blur,
+                ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, OCL_PERF_ENUM(3, 5)))
+{
+    const FilterParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), ksize = get<2>(params), bordertype = BORDER_CONSTANT;
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-5;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::blur(src, dst, Size(ksize, ksize), Point(-1, -1), bordertype);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// Laplacian////////////////////////
+
+typedef FilterFixture LaplacianFixture;
+
+OCL_PERF_TEST_P(LaplacianFixture, Laplacian,
+                ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, OCL_PERF_ENUM(3, 5)))
+{
+    const FilterParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), ksize = get<2>(params);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-5;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::Laplacian(src, dst, -1, ksize, 1);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// Erode ////////////////////
+
+typedef FilterFixture ErodeFixture;
+
+OCL_PERF_TEST_P(ErodeFixture, Erode,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, OCL_PERF_ENUM(3, 5)))
+{
+    const FilterParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), ksize = get<2>(params);
+    const Mat ker = getStructuringElement(MORPH_RECT, Size(ksize, ksize));
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst).in(ker);
+
+    OCL_TEST_CYCLE() cv::erode(src, dst, ker);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// Dilate ////////////////////
+
+typedef FilterFixture DilateFixture;
+
+OCL_PERF_TEST_P(DilateFixture, Dilate,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, OCL_PERF_ENUM(3, 5)))
+{
+    const FilterParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), ksize = get<2>(params);
+    const Mat ker = getStructuringElement(MORPH_RECT, Size(ksize, ksize));
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst).in(ker);
+
+    OCL_TEST_CYCLE() cv::dilate(src, dst, ker);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// MorphologyEx ////////////////////////
+
+CV_ENUM(MorphOp, MORPH_OPEN, MORPH_CLOSE, MORPH_GRADIENT, MORPH_TOPHAT, MORPH_BLACKHAT)
+
+typedef tuple<Size, MatType, MorphOp, int> MorphologyExParams;
+typedef TestBaseWithParam<MorphologyExParams> MorphologyExFixture;
+
+OCL_PERF_TEST_P(MorphologyExFixture, MorphologyEx,
+                ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, MorphOp::all(), OCL_PERF_ENUM(3, 5)))
+{
+    const MorphologyExParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), op = get<2>(params), ksize = get<3>(params);
+    const Mat ker = getStructuringElement(MORPH_RECT, Size(ksize, ksize));
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst).in(ker);
+
+    OCL_TEST_CYCLE() cv::morphologyEx(src, dst, op, ker);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// Sobel ////////////////////////
+
+typedef Size_MatType SobelFixture;
+
+OCL_PERF_TEST_P(SobelFixture, Sobel,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
+{
+    const Size_MatType_t params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), dx = 1, dy = 1;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type, sizeof(float) * 2);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::Sobel(src, dst, -1, dx, dy);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// Scharr ////////////////////////
+
+typedef Size_MatType ScharrFixture;
+
+OCL_PERF_TEST_P(ScharrFixture, Scharr,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
+{
+    const Size_MatType_t params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), dx = 1, dy = 0;
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-5;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type, sizeof(float) * 2);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::Scharr(src, dst, -1, dx, dy);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// GaussianBlur ////////////////////////
+
+typedef FilterFixture GaussianBlurFixture;
+
+OCL_PERF_TEST_P(GaussianBlurFixture, GaussianBlur,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, OCL_PERF_ENUM(3, 5, 7)))
+{
+    const FilterParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), ksize = get<2>(params);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 + DBL_EPSILON : 3e-4;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::GaussianBlur(src, dst, Size(ksize, ksize), 0);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// Filter2D ////////////////////////
+
+typedef FilterFixture Filter2DFixture;
+
+OCL_PERF_TEST_P(Filter2DFixture, Filter2D,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, OCL_PERF_ENUM(3, 5)))
+{
+    const FilterParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), ksize = get<2>(params);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-5;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat 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);
+
+    OCL_TEST_CYCLE() cv::filter2D(src, dst, -1, kernel);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// Bilateral ////////////////////////
+
+typedef TestBaseWithParam<Size> BilateralFixture;
+
+OCL_PERF_TEST_P(BilateralFixture, Bilateral, OCL_TEST_SIZES)
+{
+    const Size srcSize = GetParam();
+    const int d = 7;
+    const double sigmacolor = 50.0, sigmaspace = 50.0;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, CV_8UC1);
+
+    UMat src(srcSize, CV_8UC1), dst(srcSize, CV_8UC1);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::bilateralFilter(src, dst, d, sigmacolor, sigmaspace);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// MedianBlur ////////////////////////
+
+typedef tuple<Size, int> MedianBlurParams;
+typedef TestBaseWithParam<MedianBlurParams> MedianBlurFixture;
+
+OCL_PERF_TEST_P(MedianBlurFixture, Bilateral, ::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(3, 5)))
+{
+    MedianBlurParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int ksize = get<1>(params);
+
+    checkDeviceMaxMemoryAllocSize(srcSize, CV_8UC1);
+
+    UMat src(srcSize, CV_8UC1), dst(srcSize, CV_8UC1);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::medianBlur(src, dst, ksize);
+
+    SANITY_CHECK(dst);
+}
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/opencl/perf_imgproc.cpp

@@ -0,0 +1,246 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+///////////// equalizeHist ////////////////////////
+
+typedef TestBaseWithParam<Size> EqualizeHistFixture;
+
+OCL_PERF_TEST_P(EqualizeHistFixture, EqualizeHist, OCL_TEST_SIZES)
+{
+    const Size srcSize = GetParam();
+    const double eps = 1;
+
+    UMat src(srcSize, CV_8UC1), dst(srcSize, CV_8UC1);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::equalizeHist(src, dst);
+
+    SANITY_CHECK(dst, eps);
+}
+
+/////////// CopyMakeBorder //////////////////////
+
+CV_ENUM(Border, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT, BORDER_WRAP, BORDER_REFLECT_101)
+
+typedef tuple<Size, MatType, Border> CopyMakeBorderParamType;
+typedef TestBaseWithParam<CopyMakeBorderParamType> CopyMakeBorderFixture;
+
+OCL_PERF_TEST_P(CopyMakeBorderFixture, CopyMakeBorder,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, Border::all()))
+{
+    const CopyMakeBorderParamType params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), borderType = get<2>(params);
+
+    UMat src(srcSize, type), dst;
+    const Size dstSize = srcSize + Size(12, 12);
+    dst.create(dstSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::copyMakeBorder(src, dst, 7, 5, 5, 7, borderType, cv::Scalar(1.0));
+
+    SANITY_CHECK(dst);
+}
+
+///////////// CornerMinEigenVal ////////////////////////
+
+typedef Size_MatType CornerMinEigenValFixture;
+
+OCL_PERF_TEST_P(CornerMinEigenValFixture, CornerMinEigenVal,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
+{
+    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;
+
+    UMat src(srcSize, type), dst(srcSize, CV_32FC1);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    const int depth = CV_MAT_DEPTH(type);
+    const ERROR_TYPE errorType = depth == CV_8U ? ERROR_ABSOLUTE : ERROR_RELATIVE;
+
+    OCL_TEST_CYCLE() cv::cornerMinEigenVal(src, dst, blockSize, apertureSize, borderType);
+
+    SANITY_CHECK(dst, 1e-6, errorType);
+}
+
+///////////// CornerHarris ////////////////////////
+
+typedef Size_MatType CornerHarrisFixture;
+
+OCL_PERF_TEST_P(CornerHarrisFixture, CornerHarris,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
+{
+    const Size_MatType_t params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), borderType = BORDER_REFLECT;
+
+    UMat src(srcSize, type), dst(srcSize, CV_32FC1);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::cornerHarris(src, dst, 5, 7, 0.1, borderType);
+
+    SANITY_CHECK(dst, 5e-5);
+}
+
+///////////// Integral ////////////////////////
+
+typedef tuple<Size, MatDepth> IntegralParams;
+typedef TestBaseWithParam<IntegralParams> IntegralFixture;
+
+OCL_PERF_TEST_P(IntegralFixture, Integral1, ::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_32S, CV_32F)))
+{
+    const IntegralParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int ddepth = get<1>(params);
+
+    UMat src(srcSize, CV_8UC1), dst(srcSize + Size(1, 1), ddepth);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::integral(src, dst, ddepth);
+
+    SANITY_CHECK(dst, 1e-6, ERROR_RELATIVE);
+}
+
+///////////// Threshold ////////////////////////
+
+CV_ENUM(ThreshType, THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO_INV)
+
+typedef tuple<Size, MatType, ThreshType> ThreshParams;
+typedef TestBaseWithParam<ThreshParams> ThreshFixture;
+
+OCL_PERF_TEST_P(ThreshFixture, Threshold,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, ThreshType::all()))
+{
+    const ThreshParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int srcType = get<1>(params);
+    const int threshType = get<2>(params);
+    const double maxValue = 220.0, threshold = 50;
+
+    UMat src(srcSize, srcType), dst(srcSize, srcType);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::threshold(src, dst, threshold, maxValue, threshType);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// CLAHE ////////////////////////
+
+typedef TestBaseWithParam<Size> CLAHEFixture;
+
+OCL_PERF_TEST_P(CLAHEFixture, CLAHE, OCL_TEST_SIZES)
+{
+    const Size srcSize = GetParam();
+
+    UMat src(srcSize, CV_8UC1), dst(srcSize, CV_8UC1);
+    const double clipLimit = 40.0;
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(clipLimit);
+    OCL_TEST_CYCLE() clahe->apply(src, dst);
+
+    SANITY_CHECK(dst);
+}
+
+///////////// SqrBoxFilter ////////////////////////
+
+typedef TestBaseWithParam<Size> SqrBoxFilterFixture;
+
+OCL_PERF_TEST_P(SqrBoxFilterFixture, SqrBoxFilter, OCL_TEST_SIZES)
+{
+    const Size srcSize = GetParam();
+
+    UMat src(srcSize, CV_8UC1), dst(srcSize, CV_32SC1);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::sqrBoxFilter(src, dst, CV_32S, Size(3, 3));
+
+    SANITY_CHECK(dst);
+}
+
+///////////// Canny ////////////////////////
+
+typedef tuple<int, bool> CannyParams;
+typedef TestBaseWithParam<CannyParams> CannyFixture;
+
+OCL_PERF_TEST_P(CannyFixture, Canny, ::testing::Combine(OCL_PERF_ENUM(3, 5), Bool()))
+{
+    const CannyParams params = GetParam();
+    int apertureSize = get<0>(params);
+    bool L2Grad = get<1>(params);
+
+    Mat _img = imread(getDataPath("gpu/stereobm/aloe-L.png"), cv::IMREAD_GRAYSCALE);
+    ASSERT_TRUE(!_img.empty()) << "can't open aloe-L.png";
+
+    UMat img;
+    _img.copyTo(img);
+    UMat edges(img.size(), CV_8UC1);
+
+    declare.in(img, WARMUP_RNG).out(edges);
+
+    OCL_TEST_CYCLE() cv::Canny(img, edges, 50.0, 100.0, apertureSize, L2Grad);
+
+    if (apertureSize == 3)
+        SANITY_CHECK(edges);
+    else
+        SANITY_CHECK_NOTHING();
+}
+
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/opencl/perf_imgwarp.cpp

@@ -0,0 +1,210 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+///////////// WarpAffine ////////////////////////
+
+CV_ENUM(InterType, INTER_NEAREST, INTER_LINEAR)
+
+typedef tuple<Size, MatType, InterType> WarpAffineParams;
+typedef TestBaseWithParam<WarpAffineParams> WarpAffineFixture;
+
+OCL_PERF_TEST_P(WarpAffineFixture, WarpAffine,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, InterType::all()))
+{
+    static const double coeffs[2][3] =
+    {
+        { cos(CV_PI / 6), -sin(CV_PI / 6), 100.0  },
+        { sin(CV_PI / 6), cos(CV_PI / 6) , -100.0 }
+    };
+    Mat M(2, 3, CV_64F, (void *)coeffs);
+
+    const WarpAffineParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), interpolation = get<2>(params);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-4;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::warpAffine(src, dst, M, srcSize, interpolation);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// WarpPerspective ////////////////////////
+
+typedef WarpAffineParams WarpPerspectiveParams;
+typedef TestBaseWithParam<WarpPerspectiveParams> WarpPerspectiveFixture;
+
+OCL_PERF_TEST_P(WarpPerspectiveFixture, WarpPerspective,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, InterType::all()))
+{
+    static const double coeffs[3][3] =
+    {
+        {cos(CV_PI / 6), -sin(CV_PI / 6), 100.0},
+        {sin(CV_PI / 6), cos(CV_PI / 6), -100.0},
+        {0.0, 0.0, 1.0}
+    };
+    Mat M(3, 3, CV_64F, (void *)coeffs);
+
+    const WarpPerspectiveParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), interpolation = get<2>(params);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-4;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::warpPerspective(src, dst, M, srcSize, interpolation);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// Resize ////////////////////////
+
+typedef tuple<Size, MatType, InterType, double> ResizeParams;
+typedef TestBaseWithParam<ResizeParams> ResizeFixture;
+
+OCL_PERF_TEST_P(ResizeFixture, Resize,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES,
+                               InterType::all(), ::testing::Values(0.5, 2.0)))
+{
+    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 Size dstSize(cvRound(srcSize.width * scale), cvRound(srcSize.height * scale));
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-4;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+    checkDeviceMaxMemoryAllocSize(dstSize, type);
+
+    UMat src(srcSize, type), dst(dstSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::resize(src, dst, Size(), scale, scale, interType);
+
+    SANITY_CHECK(dst, eps);
+}
+
+typedef tuple<Size, MatType, double> ResizeAreaParams;
+typedef TestBaseWithParam<ResizeAreaParams> ResizeAreaFixture;
+
+OCL_PERF_TEST_P(ResizeAreaFixture, Resize,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, ::testing::Values(0.3, 0.5, 0.6)))
+{
+    const ResizeAreaParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params);
+    double scale = get<2>(params);
+    const Size dstSize(cvRound(srcSize.width * scale), cvRound(srcSize.height * scale));
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-4;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+    checkDeviceMaxMemoryAllocSize(dstSize, type);
+
+    UMat src(srcSize, type), dst(dstSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::resize(src, dst, Size(), scale, scale, cv::INTER_AREA);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// Remap ////////////////////////
+
+typedef tuple<Size, MatType, InterType> RemapParams;
+typedef TestBaseWithParam<RemapParams> RemapFixture;
+
+OCL_PERF_TEST_P(RemapFixture, Remap,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES, InterType::all()))
+{
+    const RemapParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params), interpolation = get<2>(params), borderMode = BORDER_CONSTANT;
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-4;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+
+    UMat src(srcSize, type), dst(srcSize, type);
+    UMat xmap(srcSize, CV_32FC1), ymap(srcSize, CV_32FC1);
+
+    {
+        Mat _xmap = xmap.getMat(ACCESS_WRITE), _ymap = ymap.getMat(ACCESS_WRITE);
+        for (int i = 0; i < srcSize.height; ++i)
+        {
+            float * const xmap_row = _xmap.ptr<float>(i);
+            float * const ymap_row = _ymap.ptr<float>(i);
+
+            for (int j = 0; j < srcSize.width; ++j)
+            {
+                xmap_row[j] = (j - srcSize.width * 0.5f) * 0.75f + srcSize.width * 0.5f;
+                ymap_row[j] = (i - srcSize.height * 0.5f) * 0.75f + srcSize.height * 0.5f;
+            }
+        }
+    }
+    declare.in(src, WARMUP_RNG).in(xmap, ymap, WARMUP_READ).out(dst);
+
+    OCL_TEST_CYCLE() cv::remap(src, dst, xmap, ymap, interpolation, borderMode);
+
+    SANITY_CHECK(dst, eps);
+}
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/opencl/perf_moments.cpp

@@ -0,0 +1,78 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other Materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+///////////// Moments ////////////////////////
+
+typedef tuple<Size, bool> MomentsParams;
+typedef TestBaseWithParam<MomentsParams> MomentsFixture;
+
+OCL_PERF_TEST_P(MomentsFixture, Moments,
+    ::testing::Combine(OCL_TEST_SIZES, ::testing::Bool()))
+{
+    const MomentsParams params = GetParam();
+    const Size srcSize = get<0>(params);
+    const bool binaryImage = get<1>(params);
+
+    cv::Moments m;
+    UMat src(srcSize, CV_8UC1);
+    declare.in(src, WARMUP_RNG);
+
+    OCL_TEST_CYCLE() m = cv::moments(src, binaryImage);
+
+    SANITY_CHECK_MOMENTS(m, 1e-6, ERROR_RELATIVE);
+}
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/opencl/perf_pyramid.cpp

@@ -0,0 +1,105 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+///////////// PyrDown //////////////////////
+
+typedef Size_MatType PyrDownFixture;
+
+OCL_PERF_TEST_P(PyrDownFixture, PyrDown,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
+{
+    const Size_MatType_t params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params);
+    const Size dstSize((srcSize.height + 1) >> 1, (srcSize.width + 1) >> 1);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-5;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+    checkDeviceMaxMemoryAllocSize(dstSize, type);
+
+    UMat src(srcSize, type), dst(dstSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::pyrDown(src, dst);
+
+    SANITY_CHECK(dst, eps);
+}
+
+///////////// PyrUp ////////////////////////
+
+typedef Size_MatType PyrUpFixture;
+
+OCL_PERF_TEST_P(PyrUpFixture, PyrUp,
+            ::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
+{
+    const Size_MatType_t params = GetParam();
+    const Size srcSize = get<0>(params);
+    const int type = get<1>(params);
+    const Size dstSize(srcSize.height << 1, srcSize.width << 1);
+    const double eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : 1e-5;
+
+    checkDeviceMaxMemoryAllocSize(srcSize, type);
+    checkDeviceMaxMemoryAllocSize(dstSize, type);
+
+    UMat src(srcSize, type), dst(dstSize, type);
+    declare.in(src, WARMUP_RNG).out(dst);
+
+    OCL_TEST_CYCLE() cv::pyrDown(src, dst);
+
+    SANITY_CHECK(dst, eps);
+}
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/perf/perf_filter2d.cpp

@@ -8,7 +8,7 @@ using std::tr1::make_tuple;
 using std::tr1::get;
 
 
-CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT_101);
+CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT_101)
 
 typedef TestBaseWithParam< tr1::tuple<Size, int, BorderMode> > TestFilter2d;
 typedef TestBaseWithParam< tr1::tuple<string, int> > Image_KernelSize;

modules/imgproc/src/canny.cpp

@@ -40,6 +40,7 @@
 //M*/
 
 #include "precomp.hpp"
+#include "opencl_kernels.hpp"
 
 /*
 #if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
@@ -48,9 +49,11 @@
 #undef USE_IPP_CANNY
 #endif
 */
-#ifdef USE_IPP_CANNY
+
 namespace cv
 {
+
+#ifdef USE_IPP_CANNY
 static bool ippCanny(const Mat& _src, Mat& _dst, float low,  float high)
 {
     int size = 0, size1 = 0;
@@ -83,22 +86,165 @@ static bool ippCanny(const Mat& _src, Mat& _dst, float low,  float high)
         return false;
     return true;
 }
-}
 #endif
 
+static bool ocl_Canny(InputArray _src, OutputArray _dst, float low_thresh, float high_thresh,
+                      int aperture_size, bool L2gradient, int cn, const Size & size)
+{
+    UMat dx(size, CV_16SC(cn)), dy(size, CV_16SC(cn));
+
+    if (L2gradient)
+    {
+        low_thresh = std::min(32767.0f, low_thresh);
+        high_thresh = std::min(32767.0f, high_thresh);
+
+        if (low_thresh > 0) low_thresh *= low_thresh;
+        if (high_thresh > 0) high_thresh *= high_thresh;
+    }
+    int low = cvFloor(low_thresh), high = cvFloor(high_thresh);
+    Size esize(size.width + 2, size.height + 2);
+
+    UMat mag;
+    size_t globalsize[2] = { size.width * cn, size.height }, localsize[2] = { 16, 16 };
+
+    if (aperture_size == 3 && !_src.isSubmatrix())
+    {
+        // Sobel calculation
+        ocl::Kernel calcSobelRowPassKernel("calcSobelRowPass", ocl::imgproc::canny_oclsrc);
+        if (calcSobelRowPassKernel.empty())
+            return false;
+
+        UMat src = _src.getUMat(), dxBuf(size, CV_16SC(cn)), dyBuf(size, CV_16SC(cn));
+        calcSobelRowPassKernel.args(ocl::KernelArg::ReadOnly(src),
+                                    ocl::KernelArg::WriteOnlyNoSize(dxBuf),
+                                    ocl::KernelArg::WriteOnlyNoSize(dyBuf));
+
+        if (!calcSobelRowPassKernel.run(2, globalsize, localsize, false))
+            return false;
+
+        // magnitude calculation
+        ocl::Kernel magnitudeKernel("calcMagnitude_buf", ocl::imgproc::canny_oclsrc,
+                                    L2gradient ? " -D L2GRAD" : "");
+        if (magnitudeKernel.empty())
+            return false;
+
+        mag = UMat(esize, CV_32SC(cn), Scalar::all(0));
+        dx.create(size, CV_16SC(cn));
+        dy.create(size, CV_16SC(cn));
+
+        magnitudeKernel.args(ocl::KernelArg::ReadOnlyNoSize(dxBuf), ocl::KernelArg::ReadOnlyNoSize(dyBuf),
+                             ocl::KernelArg::WriteOnlyNoSize(dx), ocl::KernelArg::WriteOnlyNoSize(dy),
+                             ocl::KernelArg::WriteOnlyNoSize(mag, cn), size.height, size.width);
+
+        if (!magnitudeKernel.run(2, globalsize, localsize, false))
+            return false;
+    }
+    else
+    {
+        dx.create(size, CV_16SC(cn));
+        dy.create(size, CV_16SC(cn));
+
+        Sobel(_src, dx, CV_16SC1, 1, 0, aperture_size, 1, 0, BORDER_REPLICATE);
+        Sobel(_src, dy, CV_16SC1, 0, 1, aperture_size, 1, 0, BORDER_REPLICATE);
+
+        // magnitude calculation
+        ocl::Kernel magnitudeKernel("calcMagnitude", ocl::imgproc::canny_oclsrc,
+                                    L2gradient ? " -D L2GRAD" : "");
+        if (magnitudeKernel.empty())
+            return false;
+
+        mag = UMat(esize, CV_32SC(cn), Scalar::all(0));
+        magnitudeKernel.args(ocl::KernelArg::ReadOnlyNoSize(dx), ocl::KernelArg::ReadOnlyNoSize(dy),
+                             ocl::KernelArg::WriteOnlyNoSize(mag, cn), size.height, size.width);
+
+        if (!magnitudeKernel.run(2, globalsize, NULL, false))
+            return false;
+    }
+
+    // map calculation
+    ocl::Kernel calcMapKernel("calcMap", ocl::imgproc::canny_oclsrc);
+    if (calcMapKernel.empty())
+        return false;
+
+    UMat map(esize, CV_32SC(cn));
+    calcMapKernel.args(ocl::KernelArg::ReadOnlyNoSize(dx), ocl::KernelArg::ReadOnlyNoSize(dy),
+                       ocl::KernelArg::ReadOnlyNoSize(mag), ocl::KernelArg::WriteOnlyNoSize(map, cn),
+                       size.height, size.width, low, high);
+
+    if (!calcMapKernel.run(2, globalsize, localsize, false))
+        return false;
+
+    // local hysteresis thresholding
+    ocl::Kernel edgesHysteresisLocalKernel("edgesHysteresisLocal", ocl::imgproc::canny_oclsrc);
+    if (edgesHysteresisLocalKernel.empty())
+        return false;
+
+    UMat stack(1, size.area(), CV_16UC2), counter(1, 1, CV_32SC1, Scalar::all(0));
+    edgesHysteresisLocalKernel.args(ocl::KernelArg::ReadOnlyNoSize(map), ocl::KernelArg::PtrReadWrite(stack),
+                                    ocl::KernelArg::PtrReadWrite(counter), size.height, size.width);
+    if (!edgesHysteresisLocalKernel.run(2, globalsize, localsize, false))
+        return false;
+
+    // global hysteresis thresholding
+    UMat stack2(1, size.area(), CV_16UC2);
+    int count;
+
+    for ( ; ; )
+    {
+        ocl::Kernel edgesHysteresisGlobalKernel("edgesHysteresisGlobal", ocl::imgproc::canny_oclsrc);
+        if (edgesHysteresisGlobalKernel.empty())
+            return false;
+
+        {
+            Mat _counter = counter.getMat(ACCESS_RW);
+            count = _counter.at<int>(0, 0);
+            if (count == 0)
+                break;
+
+            _counter.at<int>(0, 0) = 0;
+        }
+
+        edgesHysteresisGlobalKernel.args(ocl::KernelArg::ReadOnlyNoSize(map), ocl::KernelArg::PtrReadWrite(stack),
+                                         ocl::KernelArg::PtrReadWrite(stack2), ocl::KernelArg::PtrReadWrite(counter),
+                                         size.height, size.width, count);
+
+#define divUp(total, grain) ((total + grain - 1) / grain)
+        size_t localsize2[2] = { 128, 1 }, globalsize2[2] = { std::min(count, 65535) * 128, divUp(count, 65535) };
+#undef divUp
+
+        if (!edgesHysteresisGlobalKernel.run(2, globalsize2, localsize2, false))
+            return false;
+
+        std::swap(stack, stack2);
+    }
+
+    // get edges
+    ocl::Kernel getEdgesKernel("getEdges", ocl::imgproc::canny_oclsrc);
+    if (getEdgesKernel.empty())
+        return false;
+
+    _dst.create(size, CV_8UC(cn));
+    UMat dst = _dst.getUMat();
+
+    getEdgesKernel.args(ocl::KernelArg::ReadOnlyNoSize(map), ocl::KernelArg::WriteOnly(dst));
+    return getEdgesKernel.run(2, globalsize, NULL, false);
+}
+
+}
+
 void cv::Canny( InputArray _src, OutputArray _dst,
                 double low_thresh, double high_thresh,
                 int aperture_size, bool L2gradient )
 {
-    Mat src = _src.getMat();
+    const int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
-    CV_Assert( src.depth() == CV_8U );
+    const Size size = _src.size();
 
-    _dst.create(src.size(), CV_8U);
+    CV_Assert( depth == CV_8U );
-    Mat dst = _dst.getMat();
+    _dst.create(size, CV_8U);
 
     if (!L2gradient && (aperture_size & CV_CANNY_L2_GRADIENT) == CV_CANNY_L2_GRADIENT)
     {
-        //backward compatibility
+        // backward compatibility
         aperture_size &= ~CV_CANNY_L2_GRADIENT;
         L2gradient = true;
     }
@@ -109,6 +255,12 @@ void cv::Canny( InputArray _src, OutputArray _dst,
     if (low_thresh > high_thresh)
         std::swap(low_thresh, high_thresh);
 
+    if (ocl::useOpenCL() && _dst.isUMat() && cn == 1 &&
+            ocl_Canny(_src, _dst, (float)low_thresh, (float)high_thresh, aperture_size, L2gradient, cn, size))
+        return;
+
+    Mat src = _src.getMat(), dst = _dst.getMat();
+
 #ifdef HAVE_TEGRA_OPTIMIZATION
     if (tegra::canny(src, dst, low_thresh, high_thresh, aperture_size, L2gradient))
         return;
@@ -120,12 +272,11 @@ void cv::Canny( InputArray _src, OutputArray _dst,
         return;
 #endif
 
-    const int cn = src.channels();
     Mat dx(src.rows, src.cols, CV_16SC(cn));
     Mat dy(src.rows, src.cols, CV_16SC(cn));
 
-    Sobel(src, dx, CV_16S, 1, 0, aperture_size, 1, 0, cv::BORDER_REPLICATE);
+    Sobel(src, dx, CV_16S, 1, 0, aperture_size, 1, 0, BORDER_REPLICATE);
-    Sobel(src, dy, CV_16S, 0, 1, aperture_size, 1, 0, cv::BORDER_REPLICATE);
+    Sobel(src, dy, CV_16S, 0, 1, aperture_size, 1, 0, BORDER_REPLICATE);
 
     if (L2gradient)
     {

modules/imgproc/src/color.cpp

@@ -2878,6 +2878,8 @@ static bool ocl_cvtColor( InputArray _src, OutputArray _dst, int code, int dcn )
 
         k.create("RGB2XYZ", ocl::imgproc::cvtcolor_oclsrc,
                  format("-D depth=%d -D scn=%d -D dcn=3 -D bidx=%d", depth, scn, bidx));
+        if (k.empty())
+            return false;
         k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst), ocl::KernelArg::PtrReadOnly(c));
         return k.run(2, globalsize, 0, false);
     }
@@ -2927,6 +2929,8 @@ static bool ocl_cvtColor( InputArray _src, OutputArray _dst, int code, int dcn )
 
         k.create("XYZ2RGB", ocl::imgproc::cvtcolor_oclsrc,
                  format("-D depth=%d -D scn=3 -D dcn=%d -D bidx=%d", depth, dcn, bidx));
+        if (k.empty())
+            return false;
         k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst), ocl::KernelArg::PtrReadOnly(c));
         return k.run(2, globalsize, 0, false);
     }
@@ -2981,6 +2985,8 @@ static bool ocl_cvtColor( InputArray _src, OutputArray _dst, int code, int dcn )
 
             k.create("RGB2HSV", ocl::imgproc::cvtcolor_oclsrc, format("-D depth=%d -D hrange=%d -D bidx=%d -D dcn=3 -D scn=%d",
                                                                       depth, hrange, bidx, scn));
+            if (k.empty())
+                return false;
 
             k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst),
                    ocl::KernelArg::PtrReadOnly(sdiv_data), hrange == 256 ? ocl::KernelArg::PtrReadOnly(hdiv_data256) :

modules/imgproc/src/gcgraph.hpp

@@ -380,6 +380,6 @@ bool GCGraph<TWeight>::inSourceSegment( int i )
 {
     CV_Assert( i>=0 && i<(int)vtcs.size() );
     return vtcs[i].t == 0;
-};
+}
 
 #endif

modules/imgproc/src/imgwarp.cpp

@@ -2565,15 +2565,15 @@ struct RemapVec_8u
     int operator()( const Mat& _src, void* _dst, const short* XY,
                     const ushort* FXY, const void* _wtab, int width ) const
     {
-        int cn = _src.channels();
+        int cn = _src.channels(), x = 0, sstep = (int)_src.step;
 
-        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) )
+        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) ||
+                sstep > 0x8000 )
             return 0;
 
         const uchar *S0 = _src.data, *S1 = _src.data + _src.step;
         const short* wtab = cn == 1 ? (const short*)_wtab : &BilinearTab_iC4[0][0][0];
         uchar* D = (uchar*)_dst;
-        int x = 0, sstep = (int)_src.step;
         __m128i delta = _mm_set1_epi32(INTER_REMAP_COEF_SCALE/2);
         __m128i xy2ofs = _mm_set1_epi32(cn + (sstep << 16));
         __m128i z = _mm_setzero_si128();

modules/imgproc/src/opencl/canny.cl

@@ -0,0 +1,514 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Peng Xiao, pengxiao@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+// Smoothing perpendicular to the derivative direction with a triangle filter
+// only support 3x3 Sobel kernel
+// h (-1) =  1, h (0) =  2, h (1) =  1
+// h'(-1) = -1, h'(0) =  0, h'(1) =  1
+// thus sobel 2D operator can be calculated as:
+// h'(x, y) = h'(x)h(y) for x direction
+//
+// src		input 8bit single channel image data
+// dx_buf	output dx buffer
+// dy_buf	output dy buffer
+
+__kernel void __attribute__((reqd_work_group_size(16, 16, 1)))
+calcSobelRowPass
+    (__global const uchar * src, int src_step, int src_offset, int rows, int cols,
+     __global uchar * dx_buf, int dx_buf_step, int dx_buf_offset,
+     __global uchar * dy_buf, int dy_buf_step, int dy_buf_offset)
+{
+    int gidx = get_global_id(0);
+    int gidy = get_global_id(1);
+
+    int lidx = get_local_id(0);
+    int lidy = get_local_id(1);
+
+    __local int smem[16][18];
+
+    smem[lidy][lidx + 1] = src[mad24(src_step, min(gidy, rows - 1), gidx + src_offset)];
+    if (lidx == 0)
+    {
+        smem[lidy][0]  = src[mad24(src_step, min(gidy, rows - 1), max(gidx - 1,  0)        + src_offset)];
+        smem[lidy][17] = src[mad24(src_step, min(gidy, rows - 1), min(gidx + 16, cols - 1) + src_offset)];
+    }
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (gidy < rows && gidx < cols)
+    {
+        *(__global short *)(dx_buf + mad24(gidy, dx_buf_step, gidx * (int)sizeof(short) + dx_buf_offset)) =
+            smem[lidy][lidx + 2] - smem[lidy][lidx];
+        *(__global short *)(dy_buf + mad24(gidy, dy_buf_step, gidx * (int)sizeof(short) + dy_buf_offset)) =
+            smem[lidy][lidx] + 2 * smem[lidy][lidx + 1] + smem[lidy][lidx + 2];
+    }
+}
+
+inline int calc(short x, short y)
+{
+#ifdef L2GRAD
+    return x * x + y * y;
+#else
+    return (x >= 0 ? x : -x) + (y >= 0 ? y : -y);
+#endif
+}
+
+// calculate the magnitude of the filter pass combining both x and y directions
+// This is the non-buffered version(non-3x3 sobel)
+//
+// dx_buf		dx buffer, calculated from calcSobelRowPass
+// dy_buf		dy buffer, calculated from calcSobelRowPass
+// dx			direvitive in x direction output
+// dy			direvitive in y direction output
+// mag			magnitude direvitive of xy output
+
+__kernel void calcMagnitude(__global const uchar * dxptr, int dx_step, int dx_offset,
+                            __global const uchar * dyptr, int dy_step, int dy_offset,
+                            __global uchar * magptr, int mag_step, int mag_offset, int rows, int cols)
+{
+    int x = get_global_id(0);
+    int y = get_global_id(1);
+
+    if (y < rows && x < cols)
+    {
+        int dx_index = mad24(dx_step, y, x * (int)sizeof(short) + dx_offset);
+        int dy_index = mad24(dy_step, y, x * (int)sizeof(short) + dy_offset);
+        int mag_index = mad24(mag_step, y + 1, (x + 1) * (int)sizeof(int) + mag_offset);
+
+        __global const short * dx = (__global const short *)(dxptr + dx_index);
+        __global const short * dy = (__global const short *)(dyptr + dy_index);
+        __global int * mag = (__global int *)(magptr + mag_index);
+
+        mag[0] = calc(dx[0], dy[0]);
+    }
+}
+
+// calculate the magnitude of the filter pass combining both x and y directions
+// This is the buffered version(3x3 sobel)
+//
+// dx_buf		dx buffer, calculated from calcSobelRowPass
+// dy_buf		dy buffer, calculated from calcSobelRowPass
+// dx			direvitive in x direction output
+// dy			direvitive in y direction output
+// mag			magnitude direvitive of xy output
+__kernel void __attribute__((reqd_work_group_size(16, 16, 1)))
+calcMagnitude_buf
+    (__global const short * dx_buf, int dx_buf_step, int dx_buf_offset,
+     __global const short * dy_buf, int dy_buf_step, int dy_buf_offset,
+     __global short * dx, int dx_step, int dx_offset,
+     __global short * dy, int dy_step, int dy_offset,
+     __global int * mag, int mag_step, int mag_offset,
+     int rows, int cols)
+{
+    dx_buf_step    /= sizeof(*dx_buf);
+    dx_buf_offset  /= sizeof(*dx_buf);
+    dy_buf_step    /= sizeof(*dy_buf);
+    dy_buf_offset  /= sizeof(*dy_buf);
+    dx_step    /= sizeof(*dx);
+    dx_offset  /= sizeof(*dx);
+    dy_step    /= sizeof(*dy);
+    dy_offset  /= sizeof(*dy);
+    mag_step   /= sizeof(*mag);
+    mag_offset /= sizeof(*mag);
+
+    int gidx = get_global_id(0);
+    int gidy = get_global_id(1);
+
+    int lidx = get_local_id(0);
+    int lidy = get_local_id(1);
+
+    __local short sdx[18][16];
+    __local short sdy[18][16];
+
+    sdx[lidy + 1][lidx] = dx_buf[gidx + min(gidy, rows - 1) * dx_buf_step + dx_buf_offset];
+    sdy[lidy + 1][lidx] = dy_buf[gidx + min(gidy, rows - 1) * dy_buf_step + dy_buf_offset];
+    if (lidy == 0)
+    {
+        sdx[0][lidx]  = dx_buf[gidx + min(max(gidy - 1, 0), rows - 1) * dx_buf_step + dx_buf_offset];
+        sdx[17][lidx] = dx_buf[gidx + min(gidy + 16, rows - 1)        * dx_buf_step + dx_buf_offset];
+
+        sdy[0][lidx]  = dy_buf[gidx + min(max(gidy - 1, 0), rows - 1) * dy_buf_step + dy_buf_offset];
+        sdy[17][lidx] = dy_buf[gidx + min(gidy + 16, rows - 1)        * dy_buf_step + dy_buf_offset];
+    }
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (gidx < cols && gidy < rows)
+    {
+        short x =  sdx[lidy][lidx] + 2 * sdx[lidy + 1][lidx] + sdx[lidy + 2][lidx];
+        short y = -sdy[lidy][lidx] + sdy[lidy + 2][lidx];
+
+        dx[gidx + gidy * dx_step + dx_offset] = x;
+        dy[gidx + gidy * dy_step + dy_offset] = y;
+
+        mag[(gidx + 1) + (gidy + 1) * mag_step + mag_offset] = calc(x, y);
+    }
+}
+
+
+//////////////////////////////////////////////////////////////////////////////////////////
+// 0.4142135623730950488016887242097 is tan(22.5)
+
+#define CANNY_SHIFT 15
+#define TG22        (int)(0.4142135623730950488016887242097f*(1<<CANNY_SHIFT) + 0.5f)
+
+// First pass of edge detection and non-maximum suppression
+// edgetype is set to for each pixel:
+// 0 - below low thres, not an edge
+// 1 - maybe an edge
+// 2 - is an edge, either magnitude is greater than high thres, or
+//     Given estimates of the image gradients, a search is then carried out
+//     to determine if the gradient magnitude assumes a local maximum in the gradient direction.
+//     if the rounded gradient angle is zero degrees (i.e. the edge is in the north-south direction) the point will be considered to be on the edge if its gradient magnitude is greater than the magnitudes in the west and east directions,
+//     if the rounded gradient angle is 90 degrees (i.e. the edge is in the east-west direction) the point will be considered to be on the edge if its gradient magnitude is greater than the magnitudes in the north and south directions,
+//     if the rounded gradient angle is 135 degrees (i.e. the edge is in the north east-south west direction) the point will be considered to be on the edge if its gradient magnitude is greater than the magnitudes in the north west and south east directions,
+//     if the rounded gradient angle is 45 degrees (i.e. the edge is in the north west-south east direction)the point will be considered to be on the edge if its gradient magnitude is greater than the magnitudes in the north east and south west directions.
+//
+// dx, dy		direvitives of x and y direction
+// mag			magnitudes calculated from calcMagnitude function
+// map			output containing raw edge types
+
+__kernel void __attribute__((reqd_work_group_size(16,16,1)))
+calcMap(
+    __global const uchar * dx, int dx_step, int dx_offset,
+    __global const uchar * dy, int dy_step, int dy_offset,
+    __global const uchar * mag, int mag_step, int mag_offset,
+    __global uchar * map, int map_step, int map_offset,
+    int rows, int cols, int low_thresh, int high_thresh)
+{
+    __local int smem[18][18];
+
+    int gidx = get_global_id(0);
+    int gidy = get_global_id(1);
+
+    int lidx = get_local_id(0);
+    int lidy = get_local_id(1);
+
+    int grp_idx = get_global_id(0) & 0xFFFFF0;
+    int grp_idy = get_global_id(1) & 0xFFFFF0;
+
+    int tid = lidx + lidy * 16;
+    int lx = tid % 18;
+    int ly = tid / 18;
+
+    mag += mag_offset;
+    if (ly < 14)
+        smem[ly][lx] = *(__global const int *)(mag +
+            mad24(mag_step, min(grp_idy + ly, rows - 1), (int)sizeof(int) * (grp_idx + lx)));
+    if (ly < 4 && grp_idy + ly + 14 <= rows && grp_idx + lx <= cols)
+        smem[ly + 14][lx] = *(__global const int *)(mag +
+            mad24(mag_step, min(grp_idy + ly + 14, rows - 1), (int)sizeof(int) * (grp_idx + lx)));
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (gidy < rows && gidx < cols)
+    {
+        // 0 - the pixel can not belong to an edge
+        // 1 - the pixel might belong to an edge
+        // 2 - the pixel does belong to an edge
+        int edge_type = 0;
+        int m = smem[lidy + 1][lidx + 1];
+
+        if (m > low_thresh)
+        {
+            short xs = *(__global const short *)(dx + mad24(gidy, dx_step, dx_offset + (int)sizeof(short) * gidx));
+            short ys = *(__global const short *)(dy + mad24(gidy, dy_step, dy_offset + (int)sizeof(short) * gidx));
+            int x = abs(xs), y = abs(ys);
+
+            int tg22x = x * TG22;
+            y <<= CANNY_SHIFT;
+
+            if (y < tg22x)
+            {
+                if (m > smem[lidy + 1][lidx] && m >= smem[lidy + 1][lidx + 2])
+                    edge_type = 1 + (int)(m > high_thresh);
+            }
+            else
+            {
+                int tg67x = tg22x + (x << (1 + CANNY_SHIFT));
+                if (y > tg67x)
+                {
+                    if (m > smem[lidy][lidx + 1]&& m >= smem[lidy + 2][lidx + 1])
+                        edge_type = 1 + (int)(m > high_thresh);
+                }
+                else
+                {
+                    int s = (xs ^ ys) < 0 ? -1 : 1;
+                    if (m > smem[lidy][lidx + 1 - s]&& m > smem[lidy + 2][lidx + 1 + s])
+                        edge_type = 1 + (int)(m > high_thresh);
+                }
+            }
+        }
+        *(__global int *)(map + mad24(map_step, gidy + 1, (gidx + 1) * (int)sizeof(int) + map_offset)) = edge_type;
+    }
+}
+
+#undef CANNY_SHIFT
+#undef TG22
+
+struct PtrStepSz
+{
+    __global uchar * ptr;
+    int step, rows, cols;
+};
+
+inline int get(struct PtrStepSz data, int y, int x)
+{
+    return *(__global int *)(data.ptr + mad24(data.step, y + 1, (int)sizeof(int) * (x + 1)));
+}
+
+inline void set(struct PtrStepSz data, int y, int x, int value)
+{
+    *(__global int *)(data.ptr + mad24(data.step, y + 1, (int)sizeof(int) * (x + 1))) = value;
+}
+
+// perform Hysteresis for pixel whose edge type is 1
+//
+// If candidate pixel (edge type is 1) has a neighbour pixel (in 3x3 area) with type 2, it is believed to be part of an edge and
+// marked as edge. Each thread will iterate for 16 times to connect local edges.
+// Candidate pixel being identified as edge will then be tested if there is nearby potiential edge points. If there is, counter will
+// be incremented by 1 and the point location is stored. These potiential candidates will be processed further in next kernel.
+//
+// map		raw edge type results calculated from calcMap.
+// stack	the potiential edge points found in this kernel call
+// counter	the number of potiential edge points
+
+__kernel void __attribute__((reqd_work_group_size(16,16,1)))
+edgesHysteresisLocal
+    (__global uchar * map_ptr, int map_step, int map_offset,
+     __global ushort2 * st, __global unsigned int * counter,
+    int rows, int cols)
+{
+    struct PtrStepSz map = { map_ptr + map_offset, map_step, rows + 1, cols + 1 };
+
+    __local int smem[18][18];
+
+    int2 blockIdx = (int2)(get_group_id(0), get_group_id(1));
+    int2 blockDim = (int2)(get_local_size(0), get_local_size(1));
+    int2 threadIdx = (int2)(get_local_id(0), get_local_id(1));
+
+    const int x = blockIdx.x * blockDim.x + threadIdx.x;
+    const int y = blockIdx.y * blockDim.y + threadIdx.y;
+
+    smem[threadIdx.y + 1][threadIdx.x + 1] = x < map.cols && y < map.rows ? get(map, y, x) : 0;
+    if (threadIdx.y == 0)
+        smem[0][threadIdx.x + 1] = x < map.cols ? get(map, y - 1, x) : 0;
+    if (threadIdx.y == blockDim.y - 1)
+        smem[blockDim.y + 1][threadIdx.x + 1] = y + 1 < map.rows ? get(map, y + 1, x) : 0;
+    if (threadIdx.x == 0)
+        smem[threadIdx.y + 1][0] = y < map.rows ? get(map, y, x - 1) : 0;
+    if (threadIdx.x == blockDim.x - 1)
+        smem[threadIdx.y + 1][blockDim.x + 1] = x + 1 < map.cols && y < map.rows ? get(map, y, x + 1) : 0;
+    if (threadIdx.x == 0 && threadIdx.y == 0)
+        smem[0][0] = y > 0 && x > 0 ? get(map, y - 1, x - 1) : 0;
+    if (threadIdx.x == blockDim.x - 1 && threadIdx.y == 0)
+        smem[0][blockDim.x + 1] = y > 0 && x + 1 < map.cols ? get(map, y - 1, x + 1) : 0;
+    if (threadIdx.x == 0 && threadIdx.y == blockDim.y - 1)
+        smem[blockDim.y + 1][0] = y + 1 < map.rows && x > 0 ? get(map, y + 1, x - 1) : 0;
+    if (threadIdx.x == blockDim.x - 1 && threadIdx.y == blockDim.y - 1)
+        smem[blockDim.y + 1][blockDim.x + 1] = y + 1 < map.rows && x + 1 < map.cols ? get(map, y + 1, x + 1) : 0;
+
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (x >= cols || y >= rows)
+        return;
+
+    int n;
+
+    #pragma unroll
+    for (int k = 0; k < 16; ++k)
+    {
+        n = 0;
+
+        if (smem[threadIdx.y + 1][threadIdx.x + 1] == 1)
+        {
+            n += smem[threadIdx.y    ][threadIdx.x    ] == 2;
+            n += smem[threadIdx.y    ][threadIdx.x + 1] == 2;
+            n += smem[threadIdx.y    ][threadIdx.x + 2] == 2;
+
+            n += smem[threadIdx.y + 1][threadIdx.x    ] == 2;
+            n += smem[threadIdx.y + 1][threadIdx.x + 2] == 2;
+
+            n += smem[threadIdx.y + 2][threadIdx.x    ] == 2;
+            n += smem[threadIdx.y + 2][threadIdx.x + 1] == 2;
+            n += smem[threadIdx.y + 2][threadIdx.x + 2] == 2;
+        }
+
+        if (n > 0)
+            smem[threadIdx.y + 1][threadIdx.x + 1] = 2;
+    }
+
+    const int e = smem[threadIdx.y + 1][threadIdx.x + 1];
+    set(map, y, x, e);
+    n = 0;
+
+    if (e == 2)
+    {
+        n += smem[threadIdx.y    ][threadIdx.x    ] == 1;
+        n += smem[threadIdx.y    ][threadIdx.x + 1] == 1;
+        n += smem[threadIdx.y    ][threadIdx.x + 2] == 1;
+
+        n += smem[threadIdx.y + 1][threadIdx.x    ] == 1;
+        n += smem[threadIdx.y + 1][threadIdx.x + 2] == 1;
+
+        n += smem[threadIdx.y + 2][threadIdx.x    ] == 1;
+        n += smem[threadIdx.y + 2][threadIdx.x + 1] == 1;
+        n += smem[threadIdx.y + 2][threadIdx.x + 2] == 1;
+    }
+
+    if (n > 0)
+    {
+        const int ind = atomic_inc(counter);
+        st[ind] = (ushort2)(x + 1, y + 1);
+    }
+}
+
+__constant int c_dx[8] = {-1,  0,  1, -1, 1, -1, 0, 1};
+__constant int c_dy[8] = {-1, -1, -1,  0, 0,  1, 1, 1};
+
+
+#define stack_size 512
+#define map_index mad24(map_step, pos.y, pos.x * (int)sizeof(int))
+
+__kernel void __attribute__((reqd_work_group_size(128, 1, 1)))
+edgesHysteresisGlobal(__global uchar * map, int map_step, int map_offset,
+    __global ushort2 * st1, __global ushort2 * st2, __global int * counter,
+    int rows, int cols, int count)
+{
+    map += map_offset;
+
+    int lidx = get_local_id(0);
+
+    int grp_idx = get_group_id(0);
+    int grp_idy = get_group_id(1);
+
+    __local unsigned int s_counter, s_ind;
+    __local ushort2 s_st[stack_size];
+
+    if (lidx == 0)
+        s_counter = 0;
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    int ind = mad24(grp_idy, (int)get_local_size(0), grp_idx);
+
+    if (ind < count)
+    {
+        ushort2 pos = st1[ind];
+        if (lidx < 8)
+        {
+            pos.x += c_dx[lidx];
+            pos.y += c_dy[lidx];
+            if (pos.x > 0 && pos.x <= cols && pos.y > 0 && pos.y <= rows && *(__global int *)(map + map_index) == 1)
+            {
+                *(__global int *)(map + map_index) = 2;
+                ind = atomic_inc(&s_counter);
+                s_st[ind] = pos;
+            }
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+
+        while (s_counter > 0 && s_counter <= stack_size - get_local_size(0))
+        {
+            const int subTaskIdx = lidx >> 3;
+            const int portion = min(s_counter, (uint)(get_local_size(0)>> 3));
+
+            if (subTaskIdx < portion)
+                pos = s_st[s_counter - 1 - subTaskIdx];
+            barrier(CLK_LOCAL_MEM_FENCE);
+
+            if (lidx == 0)
+                s_counter -= portion;
+            barrier(CLK_LOCAL_MEM_FENCE);
+
+            if (subTaskIdx < portion)
+            {
+                pos.x += c_dx[lidx & 7];
+                pos.y += c_dy[lidx & 7];
+                if (pos.x > 0 && pos.x <= cols && pos.y > 0 && pos.y <= rows && *(__global int *)(map + map_index) == 1)
+                {
+                    *(__global int *)(map + map_index) = 2;
+                    ind = atomic_inc(&s_counter);
+                    s_st[ind] = pos;
+                }
+            }
+            barrier(CLK_LOCAL_MEM_FENCE);
+        }
+
+        if (s_counter > 0)
+        {
+            if (lidx == 0)
+            {
+                ind = atomic_add(counter, s_counter);
+                s_ind = ind - s_counter;
+            }
+            barrier(CLK_LOCAL_MEM_FENCE);
+
+            ind = s_ind;
+            for (int i = lidx; i < (int)s_counter; i += get_local_size(0))
+                st2[ind + i] = s_st[i];
+        }
+    }
+}
+
+#undef map_index
+#undef stack_size
+
+// Get the edge result. egde type of value 2 will be marked as an edge point and set to 255. Otherwise 0.
+// map		edge type mappings
+// dst		edge output
+
+__kernel void getEdges(__global const uchar * mapptr, int map_step, int map_offset,
+                       __global uchar * dst, int dst_step, int dst_offset, int rows, int cols)
+{
+    int x = get_global_id(0);
+    int y = get_global_id(1);
+
+    if (y < rows && x < cols)
+    {
+        int map_index = mad24(map_step, y + 1, (x + 1) * (int)sizeof(int) + map_offset);
+        int dst_index = mad24(dst_step, y, x + dst_offset);
+
+        __global const int * map = (__global const int *)(mapptr + map_index);
+
+        dst[dst_index] = (uchar)(-(map[0] >> 1));
+    }
+}

modules/imgproc/src/opencl/resize.cl

@@ -50,7 +50,6 @@
 #define INTER_RESIZE_COEF_BITS 11
 #define INTER_RESIZE_COEF_SCALE (1 << INTER_RESIZE_COEF_BITS)
 #define CAST_BITS (INTER_RESIZE_COEF_BITS << 1)
-#define CAST_SCALE (1.0f/(1<<CAST_BITS))
 #define INC(x,l) min(x+1,l-1)
 
 #define PIXSIZE ((int)sizeof(PIXTYPE))

modules/imgproc/test/ocl/test_canny.cpp

@@ -0,0 +1,117 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Peng Xiao, pengxiao@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "test_precomp.hpp"
+#include "opencv2/ts/ocl_test.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace cvtest {
+namespace ocl {
+
+////////////////////////////////////////////////////////
+// Canny
+
+IMPLEMENT_PARAM_CLASS(AppertureSize, int)
+IMPLEMENT_PARAM_CLASS(L2gradient, bool)
+IMPLEMENT_PARAM_CLASS(UseRoi, bool)
+
+PARAM_TEST_CASE(Canny, AppertureSize, L2gradient, UseRoi)
+{
+    int apperture_size;
+    bool useL2gradient, use_roi;
+
+    TEST_DECLARE_INPUT_PARAMETER(src)
+    TEST_DECLARE_OUTPUT_PARAMETER(dst)
+
+    virtual void SetUp()
+    {
+        apperture_size = GET_PARAM(0);
+        useL2gradient = GET_PARAM(1);
+        use_roi = GET_PARAM(2);
+    }
+
+    void generateTestData()
+    {
+        Mat img = readImage("shared/fruits.png", IMREAD_GRAYSCALE);
+        ASSERT_FALSE(img.empty()) << "cann't load shared/fruits.png";
+
+        Size roiSize = img.size();
+        int type = img.type();
+        ASSERT_EQ(CV_8UC1, type);
+
+        Border srcBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
+        randomSubMat(src, src_roi, roiSize, srcBorder, type, 2, 100);
+        img.copyTo(src_roi);
+
+        Border dstBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
+        randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 5, 16);
+
+        UMAT_UPLOAD_INPUT_PARAMETER(src)
+        UMAT_UPLOAD_OUTPUT_PARAMETER(dst)
+    }
+};
+
+OCL_TEST_P(Canny, Accuracy)
+{
+    generateTestData();
+
+    const double low_thresh = 50.0, high_thresh = 100.0;
+
+    OCL_OFF(cv::Canny(src_roi, dst_roi, low_thresh, high_thresh, apperture_size, useL2gradient));
+    OCL_ON(cv::Canny(usrc_roi, udst_roi, low_thresh, high_thresh, apperture_size, useL2gradient));
+
+    EXPECT_MAT_SIMILAR(dst_roi, udst_roi, 1e-2);
+    EXPECT_MAT_SIMILAR(dst, udst, 1e-2);
+}
+
+OCL_INSTANTIATE_TEST_CASE_P(ImgProc, Canny, testing::Combine(
+                                testing::Values(AppertureSize(3), AppertureSize(5)),
+                                testing::Values(L2gradient(false), L2gradient(true)),
+                                testing::Values(UseRoi(false), UseRoi(true))));
+
+} } // namespace cvtest::ocl
+
+#endif // HAVE_OPENCL

modules/imgproc/test/test_cvtyuv.cpp

@@ -603,7 +603,7 @@ CV_ENUM(YUVCVTS, CV_YUV2RGB_NV12, CV_YUV2BGR_NV12, CV_YUV2RGB_NV21, CV_YUV2BGR_N
                  CV_YUV2RGBA_YUY2, CV_YUV2BGRA_YUY2, CV_YUV2RGBA_YVYU, CV_YUV2BGRA_YVYU,
                  CV_YUV2GRAY_420, CV_YUV2GRAY_UYVY, CV_YUV2GRAY_YUY2,
                  CV_YUV2BGR, CV_YUV2RGB, CV_RGB2YUV_YV12, CV_BGR2YUV_YV12, CV_RGBA2YUV_YV12,
-                 CV_BGRA2YUV_YV12, CV_RGB2YUV_I420, CV_BGR2YUV_I420, CV_RGBA2YUV_I420, CV_BGRA2YUV_I420);
+                 CV_BGRA2YUV_YV12, CV_RGB2YUV_I420, CV_BGR2YUV_I420, CV_RGBA2YUV_I420, CV_BGRA2YUV_I420)
 
 typedef ::testing::TestWithParam<YUVCVTS> Imgproc_ColorYUV;
 

modules/legacy/src/blobtrack.cpp

@@ -205,7 +205,7 @@ double CvVSModule::GetParam(const char* name)
         if(p->pInt) return p->pInt[0];
     }
     return 0;
-};
+}
 
 const char* CvVSModule::GetParamStr(const char* name)
 {

modules/legacy/src/enteringblobdetection.cpp

@@ -209,7 +209,7 @@ public:
     CvBlobDetectorSimple();
    ~CvBlobDetectorSimple();
     int DetectNewBlob(IplImage* pImg, IplImage* pFGMask, CvBlobSeq* pNewBlobList, CvBlobSeq* pOldBlobList);
-    void Release(){delete this;};
+    void Release(){delete this;}
 
 protected:
     IplImage*       m_pMaskBlobNew;
@@ -219,7 +219,7 @@ protected:
 };
 
 /* Blob detector creator (sole interface function for this file) */
-CvBlobDetector* cvCreateBlobDetectorSimple(){return new CvBlobDetectorSimple;};
+CvBlobDetector* cvCreateBlobDetectorSimple(){return new CvBlobDetectorSimple;}
 
 /* Constructor of BlobDetector: */
 CvBlobDetectorSimple::CvBlobDetectorSimple()

modules/legacy/src/vecfacetracking.cpp

@@ -52,7 +52,7 @@ enum
 {
     MOUTH = 0,
     LEYE = 1,
-    REYE = 2,
+    REYE = 2
 };
 
 #define MAX_LAYERS      64

modules/ml/src/ml_init.cpp

@@ -52,7 +52,7 @@ CV_INIT_ALGORITHM(EM, "StatModel.EM",
                   obj.info()->addParam(obj, "epsilon", obj.epsilon);
                   obj.info()->addParam(obj, "weights", obj.weights, true);
                   obj.info()->addParam(obj, "means", obj.means, true);
-                  obj.info()->addParam(obj, "covs", obj.covs, true));
+                  obj.info()->addParam(obj, "covs", obj.covs, true))
 
 bool initModule_ml(void)
 {

modules/nonfree/src/nonfree_init.cpp

@@ -52,7 +52,7 @@ CV_INIT_ALGORITHM(SURF, "Feature2D.SURF",
                   obj.info()->addParam(obj, "nOctaves", obj.nOctaves);
                   obj.info()->addParam(obj, "nOctaveLayers", obj.nOctaveLayers);
                   obj.info()->addParam(obj, "extended", obj.extended);
-                  obj.info()->addParam(obj, "upright", obj.upright));
+                  obj.info()->addParam(obj, "upright", obj.upright))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -61,7 +61,7 @@ CV_INIT_ALGORITHM(SIFT, "Feature2D.SIFT",
                   obj.info()->addParam(obj, "nOctaveLayers", obj.nOctaveLayers);
                   obj.info()->addParam(obj, "contrastThreshold", obj.contrastThreshold);
                   obj.info()->addParam(obj, "edgeThreshold", obj.edgeThreshold);
-                  obj.info()->addParam(obj, "sigma", obj.sigma));
+                  obj.info()->addParam(obj, "sigma", obj.sigma))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 

modules/objdetect/perf/opencl/perf_cascades.cpp

@@ -0,0 +1,61 @@
+#include "perf_precomp.hpp"
+#include <opencv2/imgproc.hpp>
+
+#include "opencv2/ts/ocl_perf.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace perf;
+using std::tr1::make_tuple;
+using std::tr1::get;
+
+typedef std::tr1::tuple<std::string, std::string, int> Cascade_Image_MinSize_t;
+typedef perf::TestBaseWithParam<Cascade_Image_MinSize_t> Cascade_Image_MinSize;
+
+#ifdef HAVE_OPENCL
+
+OCL_PERF_TEST_P(Cascade_Image_MinSize, CascadeClassifier,
+                 testing::Combine(
+                    testing::Values( string("cv/cascadeandhog/cascades/haarcascade_frontalface_alt.xml"),
+                                     string("cv/cascadeandhog/cascades/haarcascade_frontalface_alt_old.xml"),
+                                     string("cv/cascadeandhog/cascades/lbpcascade_frontalface.xml") ),
+                    testing::Values( string("cv/shared/lena.png"),
+                                     string("cv/cascadeandhog/images/bttf301.png"),
+                                     string("cv/cascadeandhog/images/class57.png") ),
+                    testing::Values(30, 64, 90) ) )
+{
+    const string cascasePath = get<0>(GetParam());
+    const string imagePath   = get<1>(GetParam());
+    int min_size = get<2>(GetParam());
+    Size minSize(min_size, min_size);
+
+    CascadeClassifier cc( getDataPath(cascasePath) );
+    if (cc.empty())
+        FAIL() << "Can't load cascade file: " << getDataPath(cascasePath);
+
+    Mat img = imread(getDataPath(imagePath), IMREAD_GRAYSCALE);
+    if (img.empty())
+        FAIL() << "Can't load source image: " << getDataPath(imagePath);
+
+    vector<Rect> faces;
+
+    equalizeHist(img, img);
+    declare.in(img).time(60);
+
+    UMat uimg = img.getUMat(ACCESS_READ);
+
+    while(next())
+    {
+        faces.clear();
+        cvtest::ocl::perf::safeFinish();
+
+        startTimer();
+        cc.detectMultiScale(uimg, faces, 1.1, 3, 0, minSize);
+        stopTimer();
+    }
+
+    sort(faces.begin(), faces.end(), comparators::RectLess());
+    SANITY_CHECK(faces, min_size/5);
+}
+
+#endif //HAVE_OPENCL

modules/objdetect/perf/perf_cascadeclassifier.cpp

@@ -1,56 +0,0 @@
-#include "perf_precomp.hpp"
-#include <opencv2/imgproc.hpp>
-
-using namespace std;
-using namespace cv;
-using namespace perf;
-using std::tr1::make_tuple;
-using std::tr1::get;
-
-typedef std::tr1::tuple<std::string, int> ImageName_MinSize_t;
-typedef perf::TestBaseWithParam<ImageName_MinSize_t> ImageName_MinSize;
-
-PERF_TEST_P(ImageName_MinSize, CascadeClassifierLBPFrontalFace,
-            testing::Combine(testing::Values( std::string("cv/shared/lena.png"),
-                                              std::string("cv/shared/1_itseez-0000289.png"),
-                                              std::string("cv/shared/1_itseez-0000492.png"),
-                                              std::string("cv/shared/1_itseez-0000573.png")),
-                             testing::Values(24, 30, 40, 50, 60, 70, 80, 90)
-                             )
-            )
-{
-    const string filename = get<0>(GetParam());
-    int min_size = get<1>(GetParam());
-    Size minSize(min_size, min_size);
-
-    CascadeClassifier cc(getDataPath("cv/cascadeandhog/cascades/lbpcascade_frontalface.xml"));
-    if (cc.empty())
-        FAIL() << "Can't load cascade file";
-
-    Mat img = imread(getDataPath(filename), 0);
-    if (img.empty())
-        FAIL() << "Can't load source image";
-
-    vector<Rect> faces;
-
-    equalizeHist(img, img);
-    declare.in(img);
-
-    while(next())
-    {
-        faces.clear();
-
-        startTimer();
-        cc.detectMultiScale(img, faces, 1.1, 3, 0, minSize);
-        stopTimer();
-    }
-    // for some reason OpenCL version detects the face, which CPU version does not detect, we just remove it
-    // TODO better solution: implement smart way of comparing two set of rectangles
-    if( filename == "cv/shared/1_itseez-0000492.png" && faces.size() == (size_t)3 )
-    {
-        faces.erase(faces.begin());
-    }
-
-    std::sort(faces.begin(), faces.end(), comparators::RectLess());
-    SANITY_CHECK(faces, 3.001 * faces.size());
-}

modules/ocl/include/opencv2/ocl.hpp

@@ -167,7 +167,7 @@ namespace cv
             CACHE_NONE    = 0,        // do not cache OpenCL binary
             CACHE_DEBUG   = 0x1 << 0, // cache OpenCL binary when built in debug mode
             CACHE_RELEASE = 0x1 << 1, // default behavior, only cache when built in release mode
-            CACHE_ALL     = CACHE_DEBUG | CACHE_RELEASE, // cache opencl binary
+            CACHE_ALL     = CACHE_DEBUG | CACHE_RELEASE // cache opencl binary
         };
         //! Enable or disable OpenCL program binary caching onto local disk
         // After a program (*.cl files in opencl/ folder) is built at runtime, we allow the

modules/ocl/include/opencv2/ocl/private/opencl_utils.hpp

@@ -108,7 +108,7 @@ inline cl_int getStringInfo(Functor f, ObjectType obj, cl_uint name, std::string
     }
 
     return CL_SUCCESS;
-};
+}
 
 } // namespace cl_utils
 

modules/ocl/test/test_canny.cpp

@@ -48,8 +48,8 @@
 
 ////////////////////////////////////////////////////////
 // Canny
-IMPLEMENT_PARAM_CLASS(AppertureSize, int);
+IMPLEMENT_PARAM_CLASS(AppertureSize, int)
-IMPLEMENT_PARAM_CLASS(L2gradient, bool);
+IMPLEMENT_PARAM_CLASS(L2gradient, bool)
 
 PARAM_TEST_CASE(Canny, AppertureSize, L2gradient)
 {

modules/ocl/test/test_match_template.cpp

@@ -50,7 +50,7 @@
 // MatchTemplate
 #define ALL_TEMPLATE_METHODS testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR), TemplateMethod(cv::TM_CCOEFF), TemplateMethod(cv::TM_SQDIFF_NORMED), TemplateMethod(cv::TM_CCORR_NORMED), TemplateMethod(cv::TM_CCOEFF_NORMED))
 
-IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size);
+IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size)
 
 #define MTEMP_SIZES testing::Values(cv::Size(128, 256), cv::Size(1024, 768))
 

modules/ocl/test/test_objdetect.cpp

@@ -180,7 +180,7 @@ INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
 
 
 ///////////////////////////// Haar //////////////////////////////
-IMPLEMENT_PARAM_CLASS(CascadeName, std::string);
+IMPLEMENT_PARAM_CLASS(CascadeName, std::string)
 CascadeName cascade_frontalface_alt(std::string("haarcascade_frontalface_alt.xml"));
 CascadeName cascade_frontalface_alt2(std::string("haarcascade_frontalface_alt2.xml"));
 

modules/ocl/test/utility.hpp

@@ -273,7 +273,7 @@ CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
 CV_ENUM(Border, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, BORDER_WRAP)
 CV_ENUM(TemplateMethod, TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED)
 
-CV_FLAGS(GemmFlags, GEMM_1_T, GEMM_2_T, GEMM_3_T);
+CV_FLAGS(GemmFlags, GEMM_1_T, GEMM_2_T, GEMM_3_T)
 CV_FLAGS(WarpFlags, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, WARP_INVERSE_MAP)
 CV_FLAGS(DftFlags, DFT_INVERSE, DFT_SCALE, DFT_ROWS, DFT_COMPLEX_OUTPUT, DFT_REAL_OUTPUT)
 

modules/superres/src/btv_l1.cpp

@@ -487,7 +487,7 @@ namespace
                       obj.info()->addParam(obj, "blurKernelSize", obj.blurKernelSize_, false, 0, 0, "Gaussian blur kernel size.");
                       obj.info()->addParam(obj, "blurSigma", obj.blurSigma_, false, 0, 0, "Gaussian blur sigma.");
                       obj.info()->addParam(obj, "temporalAreaRadius", obj.temporalAreaRadius_, false, 0, 0, "Radius of the temporal search area.");
-                      obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."));
+                      obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."))
 
     BTVL1::BTVL1()
     {

modules/superres/src/btv_l1_ocl.cpp

@@ -582,7 +582,7 @@ namespace
     obj.info()->addParam(obj, "blurKernelSize", obj.blurKernelSize_, false, 0, 0, "Gaussian blur kernel size.");
     obj.info()->addParam(obj, "blurSigma", obj.blurSigma_, false, 0, 0, "Gaussian blur sigma.");
     obj.info()->addParam(obj, "temporalAreaRadius", obj.temporalAreaRadius_, false, 0, 0, "Radius of the temporal search area.");
-    obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."));
+    obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."))
 
     BTVL1_OCL::BTVL1_OCL()
     {

modules/superres/src/optical_flow.cpp

@@ -148,7 +148,7 @@ namespace
                       obj.info()->addParam(obj, "numIters", obj.numIters_);
                       obj.info()->addParam(obj, "polyN", obj.polyN_);
                       obj.info()->addParam(obj, "polySigma", obj.polySigma_);
-                      obj.info()->addParam(obj, "flags", obj.flags_));
+                      obj.info()->addParam(obj, "flags", obj.flags_))
 
     Farneback::Farneback() : CpuOpticalFlow(CV_8UC1)
     {
@@ -218,7 +218,7 @@ namespace
                       obj.info()->addParam(obj, "upscaleAveragingRadius", obj.upscaleAveragingRadius_);
                       obj.info()->addParam(obj, "upscaleSigmaDist", obj.upscaleSigmaDist_);
                       obj.info()->addParam(obj, "upscaleSigmaColor", obj.upscaleSigmaColor_);
-                      obj.info()->addParam(obj, "speedUpThr", obj.speedUpThr_));
+                      obj.info()->addParam(obj, "speedUpThr", obj.speedUpThr_))
 
     Simple::Simple() : CpuOpticalFlow(CV_8UC3)
     {
@@ -301,7 +301,7 @@ namespace
                       obj.info()->addParam(obj, "warps", obj.warps_);
                       obj.info()->addParam(obj, "epsilon", obj.epsilon_);
                       obj.info()->addParam(obj, "iterations", obj.iterations_);
-                      obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow_));
+                      obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow_))
 
     DualTVL1::DualTVL1() : CpuOpticalFlow(CV_8UC1)
     {
@@ -472,7 +472,7 @@ namespace
                       obj.info()->addParam(obj, "scaleFactor", obj.scaleFactor_, false, 0, 0, "Pyramid scale factor");
                       obj.info()->addParam(obj, "innerIterations", obj.innerIterations_, false, 0, 0, "Number of lagged non-linearity iterations (inner loop)");
                       obj.info()->addParam(obj, "outerIterations", obj.outerIterations_, false, 0, 0, "Number of warping iterations (number of pyramid levels)");
-                      obj.info()->addParam(obj, "solverIterations", obj.solverIterations_, false, 0, 0, "Number of linear system solver iterations"));
+                      obj.info()->addParam(obj, "solverIterations", obj.solverIterations_, false, 0, 0, "Number of linear system solver iterations"))
 
     Brox_CUDA::Brox_CUDA() : GpuOpticalFlow(CV_32FC1), alg_(0.197f, 50.0f, 0.8f, 10, 77, 10)
     {
@@ -536,7 +536,7 @@ namespace
     CV_INIT_ALGORITHM(PyrLK_CUDA, "DenseOpticalFlowExt.PyrLK_CUDA",
                       obj.info()->addParam(obj, "winSize", obj.winSize_);
                       obj.info()->addParam(obj, "maxLevel", obj.maxLevel_);
-                      obj.info()->addParam(obj, "iterations", obj.iterations_));
+                      obj.info()->addParam(obj, "iterations", obj.iterations_))
 
     PyrLK_CUDA::PyrLK_CUDA() : GpuOpticalFlow(CV_8UC1)
     {
@@ -603,7 +603,7 @@ namespace
                       obj.info()->addParam(obj, "numIters", obj.numIters_);
                       obj.info()->addParam(obj, "polyN", obj.polyN_);
                       obj.info()->addParam(obj, "polySigma", obj.polySigma_);
-                      obj.info()->addParam(obj, "flags", obj.flags_));
+                      obj.info()->addParam(obj, "flags", obj.flags_))
 
     Farneback_CUDA::Farneback_CUDA() : GpuOpticalFlow(CV_8UC1)
     {
@@ -679,7 +679,7 @@ namespace
                       obj.info()->addParam(obj, "warps", obj.warps_);
                       obj.info()->addParam(obj, "epsilon", obj.epsilon_);
                       obj.info()->addParam(obj, "iterations", obj.iterations_);
-                      obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow_));
+                      obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow_))
 
     DualTVL1_CUDA::DualTVL1_CUDA() : GpuOpticalFlow(CV_8UC1)
     {
@@ -801,7 +801,7 @@ namespace
     CV_INIT_ALGORITHM(PyrLK_OCL, "DenseOpticalFlowExt.PyrLK_OCL",
         obj.info()->addParam(obj, "winSize", obj.winSize_);
     obj.info()->addParam(obj, "maxLevel", obj.maxLevel_);
-    obj.info()->addParam(obj, "iterations", obj.iterations_));
+    obj.info()->addParam(obj, "iterations", obj.iterations_))
 
     PyrLK_OCL::PyrLK_OCL() : oclOpticalFlow(CV_8UC1)
     {
@@ -870,7 +870,7 @@ namespace
     obj.info()->addParam(obj, "warps", obj.warps_);
     obj.info()->addParam(obj, "epsilon", obj.epsilon_);
     obj.info()->addParam(obj, "iterations", obj.iterations_);
-    obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow_));
+    obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow_))
 
     DualTVL1_OCL::DualTVL1_OCL() : oclOpticalFlow(CV_8UC1)
     {
@@ -947,7 +947,7 @@ namespace
     obj.info()->addParam(obj, "numIters", obj.numIters_);
     obj.info()->addParam(obj, "polyN", obj.polyN_);
     obj.info()->addParam(obj, "polySigma", obj.polySigma_);
-    obj.info()->addParam(obj, "flags", obj.flags_));
+    obj.info()->addParam(obj, "flags", obj.flags_))
 
     FarneBack_OCL::FarneBack_OCL() : oclOpticalFlow(CV_8UC1)
     {

modules/ts/include/opencv2/ts/ocl_perf.hpp

@@ -57,19 +57,33 @@ using std::tr1::tuple;
 
 #define OCL_PERF_STRATEGY PERF_STRATEGY_SIMPLE
 
+#define OCL_PERF_TEST(fixture, name) SIMPLE_PERF_TEST(fixture, name)
 #define OCL_PERF_TEST_P(fixture, name, params) SIMPLE_PERF_TEST_P(fixture, name, params)
 
-#define SIMPLE_PERF_TEST_P(fixture, name, params)\
+#define SIMPLE_PERF_TEST(fixture, name) \
-    class OCL##_##fixture##_##name : public fixture {\
+    class OCL##_##fixture##_##name : \
-    public:\
+        public ::perf::TestBase \
-        OCL##_##fixture##_##name() {}\
+    { \
-    protected:\
+    public: \
-        virtual void PerfTestBody();\
+        OCL##_##fixture##_##name() { } \
-    };\
+    protected: \
-    TEST_P(OCL##_##fixture##_##name, name){ declare.strategy(OCL_PERF_STRATEGY); RunPerfTestBody(); }\
+        virtual void PerfTestBody(); \
-    INSTANTIATE_TEST_CASE_P(/*none*/, OCL##_##fixture##_##name, params);\
+    }; \
+    TEST_F(OCL##_##fixture##_##name, name) { declare.strategy(OCL_PERF_STRATEGY); RunPerfTestBody(); } \
     void OCL##_##fixture##_##name::PerfTestBody()
 
+#define SIMPLE_PERF_TEST_P(fixture, name, params) \
+    class OCL##_##fixture##_##name : \
+        public fixture \
+    { \
+    public: \
+        OCL##_##fixture##_##name() { } \
+    protected: \
+        virtual void PerfTestBody(); \
+    }; \
+    TEST_P(OCL##_##fixture##_##name, name) { declare.strategy(OCL_PERF_STRATEGY); RunPerfTestBody(); } \
+    INSTANTIATE_TEST_CASE_P(/*none*/, OCL##_##fixture##_##name, params); \
+    void OCL##_##fixture##_##name::PerfTestBody()
 
 #define OCL_SIZE_1 szVGA
 #define OCL_SIZE_2 sz720p

modules/ts/include/opencv2/ts/ocl_test.hpp

@@ -96,18 +96,18 @@ extern int test_loop_times;
 
 #define EXPECT_MAT_NEAR(mat1, mat2, eps) \
 { \
-   ASSERT_EQ(mat1.type(), mat2.type()); \
+    ASSERT_EQ(mat1.type(), mat2.type()); \
-   ASSERT_EQ(mat1.size(), mat2.size()); \
+    ASSERT_EQ(mat1.size(), mat2.size()); \
-   EXPECT_LE(checkNorm(mat1, mat2), eps) \
+    EXPECT_LE(checkNorm(mat1, mat2), eps) \
-       << cv::format("Size: %d x %d", mat1.size().width, mat1.size().height) << std::endl; \
+        << "Size: " << mat1.size() << std::endl; \
 }
 
 #define EXPECT_MAT_NEAR_RELATIVE(mat1, mat2, eps) \
 { \
-   ASSERT_EQ(mat1.type(), mat2.type()); \
+    ASSERT_EQ(mat1.type(), mat2.type()); \
-   ASSERT_EQ(mat1.size(), mat2.size()); \
+    ASSERT_EQ(mat1.size(), mat2.size()); \
-   EXPECT_LE(checkNormRelative(mat1, mat2), eps) \
+    EXPECT_LE(checkNormRelative(mat1, mat2), eps) \
-       << cv::format("Size: %d x %d", mat1.size().width, mat1.size().height) << std::endl; \
+        << "Size: " << mat1.size() << std::endl; \
 }
 
 #define OCL_EXPECT_MATS_NEAR(name, eps) \
@@ -134,8 +134,8 @@ extern int test_loop_times;
 { \
     ASSERT_EQ(mat1.type(), mat2.type()); \
     ASSERT_EQ(mat1.size(), mat2.size()); \
-    EXPECT_LE(checkSimilarity(mat1, mat2), eps); \
+    EXPECT_LE(checkSimilarity(mat1, mat2), eps) \
-        << cv::format("Size: %d x %d", mat1.size().width, mat1.size().height) << std::endl; \
+        << "Size: " << mat1.size() << std::endl; \
 }
 
 using perf::MatDepth;

modules/ts/include/opencv2/ts/ts_perf.hpp

@@ -164,6 +164,7 @@ 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& addMoments(TestBase* test, const std::string& name, const cv::Moments & 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 Regression& addMatches(TestBase* test, const std::string& name, const std::vector<cv::DMatch>& array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
     static void Init(const std::string& testSuitName, const std::string& ext = ".xml");
@@ -201,6 +202,7 @@ private:
 };
 
 #define SANITY_CHECK(array, ...) ::perf::Regression::add(this, #array, array , ## __VA_ARGS__)
+#define SANITY_CHECK_MOMENTS(array, ...) ::perf::Regression::addMoments(this, #array, array , ## __VA_ARGS__)
 #define SANITY_CHECK_KEYPOINTS(array, ...) ::perf::Regression::addKeypoints(this, #array, array , ## __VA_ARGS__)
 #define SANITY_CHECK_MATCHES(array, ...) ::perf::Regression::addMatches(this, #array, array , ## __VA_ARGS__)
 #define SANITY_CHECK_NOTHING() this->setVerified();
@@ -253,7 +255,7 @@ enum PERF_STRATEGY
 {
     PERF_STRATEGY_DEFAULT = -1,
     PERF_STRATEGY_BASE = 0,
-    PERF_STRATEGY_SIMPLE = 1,
+    PERF_STRATEGY_SIMPLE = 1
 };
 
 

modules/ts/src/ts_perf.cpp

@@ -115,6 +115,14 @@ Regression& Regression::add(TestBase* test, const std::string& name, cv::InputAr
     return instance()(name, array, eps, err);
 }
 
+Regression& Regression::addMoments(TestBase* test, const std::string& name, const cv::Moments& array, double eps, ERROR_TYPE err)
+{
+    int len = (int)sizeof(cv::Moments) / sizeof(double);
+    cv::Mat m(1, len, CV_64F, (void*)&array);
+
+    return Regression::add(test, name, m, 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();

modules/video/perf/perf_optflowpyrlk.cpp

@@ -178,7 +178,7 @@ PERF_TEST_P(Path_Idx_Cn_NPoints_WSize_Deriv, OpticalFlowPyrLK_self, testing::Com
     SANITY_CHECK(err, 2);
 }
 
-CV_ENUM(PyrBorderMode, BORDER_DEFAULT, BORDER_TRANSPARENT);
+CV_ENUM(PyrBorderMode, BORDER_DEFAULT, BORDER_TRANSPARENT)
 typedef tr1::tuple<std::string, int, bool, PyrBorderMode, bool> Path_Win_Deriv_Border_Reuse_t;
 typedef TestBaseWithParam<Path_Win_Deriv_Border_Reuse_t> Path_Win_Deriv_Border_Reuse;
 

modules/video/src/kalman.cpp

@@ -127,4 +127,4 @@ const Mat& KalmanFilter::correct(const Mat& measurement)
     return statePost;
 }
 
-};
+}

modules/video/src/tvl1flow.cpp

@@ -947,7 +947,7 @@ CV_INIT_ALGORITHM(OpticalFlowDual_TVL1, "DenseOpticalFlow.DualTVL1",
                                        "inner iterations (between outlier filtering) used in the numerical scheme");
                   obj.info()->addParam(obj, "outerIterations", obj.outerIterations, false, 0, 0,
                                        "outer iterations (number of inner loops) used in the numerical scheme");
-                  obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow));
+                  obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow))
 
 } // namespace
 

samples/c/adaptiveskindetector.cpp

@@ -126,12 +126,12 @@ ASDFrameHolder::ASDFrameHolder( )
 {
     image = NULL;
     timeStamp = 0;
-};
+}
 
 ASDFrameHolder::~ASDFrameHolder( )
 {
     cvReleaseImage(&image);
-};
+}
 
 void ASDFrameHolder::assignFrame(IplImage *sourceImage, double frameTime)
 {
@@ -143,22 +143,22 @@ void ASDFrameHolder::assignFrame(IplImage *sourceImage, double frameTime)
 
     image = cvCloneImage(sourceImage);
     timeStamp = frameTime;
-};
+}
 
 IplImage *ASDFrameHolder::getImage()
 {
     return image;
-};
+}
 
 double ASDFrameHolder::getTimeStamp()
 {
     return timeStamp;
-};
+}
 
 void ASDFrameHolder::setImage(IplImage *sourceImage)
 {
     image = sourceImage;
-};
+}
 
 
 //-------------------- ASDFrameSequencer -----------------------//
@@ -166,26 +166,26 @@ void ASDFrameHolder::setImage(IplImage *sourceImage)
 ASDFrameSequencer::~ASDFrameSequencer()
 {
     close();
-};
+}
 
 IplImage *ASDFrameSequencer::getNextImage()
 {
     return NULL;
-};
+}
 
 void ASDFrameSequencer::close()
 {
 
-};
+}
 
 bool ASDFrameSequencer::isOpen()
 {
     return false;
-};
+}
 
 void ASDFrameSequencer::getFrameCaption(char* /*caption*/) {
     return;
-};
+}
 
 IplImage* ASDCVFrameSequencer::getNextImage()
 {
@@ -201,7 +201,7 @@ IplImage* ASDCVFrameSequencer::getNextImage()
     {
         return NULL;
     }
-};
+}
 
 void ASDCVFrameSequencer::close()
 {
@@ -209,12 +209,12 @@ void ASDCVFrameSequencer::close()
     {
         cvReleaseCapture(&capture);
     }
-};
+}
 
 bool ASDCVFrameSequencer::isOpen()
 {
     return (capture != NULL);
-};
+}
 
 
 //-------------------- ASDFrameSequencerWebCam -----------------------//
@@ -233,7 +233,7 @@ bool ASDFrameSequencerWebCam::open(int cameraIndex)
     {
         return true;
     }
-};
+}
 
 
 //-------------------- ASDFrameSequencerVideoFile -----------------------//
@@ -251,7 +251,7 @@ bool ASDFrameSequencerVideoFile::open(const char *fileName)
     {
         return true;
     }
-};
+}
 
 
 //-------------------- ASDFrameSequencerImageFile -----------------------//
@@ -263,11 +263,11 @@ void ASDFrameSequencerImageFile::open(const char *fileNameMask, int startIndex,
     nEndIndex = endIndex;
 
     std::sprintf(sFileNameMask, "%s", fileNameMask);
-};
+}
 
 void ASDFrameSequencerImageFile::getFrameCaption(char *caption) {
     std::sprintf(caption, sFileNameMask, nCurrentIndex);
-};
+}
 
 IplImage* ASDFrameSequencerImageFile::getNextImage()
 {
@@ -283,23 +283,23 @@ IplImage* ASDFrameSequencerImageFile::getNextImage()
     IplImage* img = cvLoadImage(fileName);
 
     return img;
-};
+}
 
 void ASDFrameSequencerImageFile::close()
 {
     nCurrentIndex = nEndIndex+1;
-};
+}
 
 bool ASDFrameSequencerImageFile::isOpen()
 {
     return (nCurrentIndex <= nEndIndex);
-};
+}
 
 static void putTextWithShadow(IplImage *img, const char *str, CvPoint point, CvFont *font, CvScalar color = CV_RGB(255, 255, 128))
 {
     cvPutText(img, str, cvPoint(point.x-1,point.y-1), font, CV_RGB(0, 0, 0));
     cvPutText(img, str, point, font, color);
-};
+}
 
 #define ASD_RGB_SET_PIXEL(pointer, r, g, b) { (*pointer) = (unsigned char)b; (*(pointer+1)) = (unsigned char)g; (*(pointer+2)) = (unsigned char)r; }
 
@@ -336,7 +336,7 @@ static void displayBuffer(IplImage *rgbDestImage, IplImage *buffer, int rValue,
         destY = 0;
         destX += dx;
     }
-};
+}
 
 int main(int argc, char** argv )
 {

samples/cpp/calibration_artificial.cpp

@@ -46,7 +46,7 @@ private:
     Point3f generateChessBoardCenter(const Mat& camMat, const Size& imgSize) const;
     Mat rvec, tvec;
 };
-};
+}
 
 
 

samples/cpp/kmeans.cpp

@@ -33,10 +33,10 @@ int main( int /*argc*/, char** /*argv*/ )
     {
         int k, clusterCount = rng.uniform(2, MAX_CLUSTERS+1);
         int i, sampleCount = rng.uniform(1, 1001);
-        Mat points(sampleCount, 1, CV_32FC2), labels;
+        Mat points(sampleCount, 2, CV_32F), labels;
 
         clusterCount = MIN(clusterCount, sampleCount);
-        Mat centers(clusterCount, 1, points.type());
+        Mat centers;
 
         /* generate random sample from multigaussian distribution */
         for( k = 0; k < clusterCount; k++ )

samples/cpp/tutorial_code/ImgProc/Threshold.cpp

@@ -14,7 +14,7 @@ using namespace cv;
 /// Global variables
 
 int threshold_value = 0;
-int threshold_type = 3;;
+int threshold_type = 3;
 int const max_value = 255;
 int const max_type = 4;
 int const max_BINARY_value = 255;