Merge pull request #2393 from ilya-lavrenov:coverity

modules/calib3d/src/calibinit.cpp

@@ -1998,7 +1998,7 @@ bool cv::findCirclesGrid( InputArray _image, Size patternSize,
       {
         isFound = boxFinder.findHoles();
       }
-      catch (cv::Exception)
+      catch (const cv::Exception &)
       {
 
       }

modules/calib3d/src/circlesgrid.cpp

@@ -218,6 +218,7 @@ void CirclesGridClusterFinder::findCorners(const std::vector<cv::Point2f> &hull2
 
 void CirclesGridClusterFinder::findOutsideCorners(const std::vector<cv::Point2f> &corners, std::vector<cv::Point2f> &outsideCorners)
 {
+  CV_Assert(!corners.empty());
   outsideCorners.clear();
   //find two pairs of the most nearest corners
   int i, j, n = (int)corners.size();

modules/calib3d/src/compat_ptsetreg.cpp

@@ -57,6 +57,7 @@ CvLevMarq::CvLevMarq()
     criteria = cvTermCriteria(0,0,0);
     iters = 0;
     completeSymmFlag = false;
+    errNorm = prevErrNorm = DBL_MAX;
 }
 
 CvLevMarq::CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria0, bool _completeSymmFlag )
@@ -101,7 +102,7 @@ void CvLevMarq::init( int nparams, int nerrs, CvTermCriteria criteria0, bool _co
         J.reset(cvCreateMat( nerrs, nparams, CV_64F ));
         err.reset(cvCreateMat( nerrs, 1, CV_64F ));
     }
-    prevErrNorm = DBL_MAX;
+    errNorm = prevErrNorm = DBL_MAX;
     lambdaLg10 = -3;
     criteria = criteria0;
     if( criteria.type & CV_TERMCRIT_ITER )

modules/calib3d/src/epnp.h

@@ -74,7 +74,6 @@ class epnp {
   int number_of_correspondences;
 
   double cws[4][3], ccs[4][3];
-  double cws_determinant;
   int max_nr;
   double * A1, * A2;
 };

modules/calib3d/src/ptsetreg.cpp

@@ -260,7 +260,6 @@ public:
 
     Ptr<PointSetRegistrator::Callback> cb;
     int modelPoints;
-    int maxBasicSolutions;
     bool checkPartialSubsets;
     double threshold;
     double confidence;

modules/calib3d/test/test_cameracalibration.cpp

@@ -1393,6 +1393,7 @@ void CV_StereoCalibrationTest::run( int )
         {
             ts->printf( cvtest::TS::LOG, "The file %s can not be opened or has invalid content\n", filepath.c_str() );
             ts->set_failed_test_info( f ? cvtest::TS::FAIL_INVALID_TEST_DATA : cvtest::TS::FAIL_MISSING_TEST_DATA );
+            fclose(f);
             return;
         }
 

modules/calib3d/test/test_cameracalibration_artificial.cpp

@@ -85,7 +85,8 @@ Mat calcRvec(const vector<Point3f>& points, const Size& cornerSize)
 class CV_CalibrateCameraArtificialTest : public cvtest::BaseTest
 {
 public:
-    CV_CalibrateCameraArtificialTest()
+    CV_CalibrateCameraArtificialTest() :
+        r(0)
     {
     }
     ~CV_CalibrateCameraArtificialTest() {}

modules/calib3d/test/test_chesscorners.cpp

@@ -309,8 +309,9 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
         progress = update_progress( progress, idx, max_idx, 0 );
     }
 
+    if (count != 0)
         sum_error /= count;
-    ts->printf(cvtest::TS::LOG, "Average error is %f\n", sum_error);
+    ts->printf(cvtest::TS::LOG, "Average error is %f (%d patterns have been found)\n", sum_error, count);
 }
 
 double calcErrorMinError(const Size& cornSz, const vector<Point2f>& corners_found, const vector<Point2f>& corners_generated)

modules/calib3d/test/test_chesscorners_badarg.cpp

@@ -89,7 +89,14 @@ protected:
     }
 };
 
-CV_ChessboardDetectorBadArgTest::CV_ChessboardDetectorBadArgTest() {}
+CV_ChessboardDetectorBadArgTest::CV_ChessboardDetectorBadArgTest()
+{
+    cpp = false;
+    flags = 0;
+    out_corners = NULL;
+    out_corner_count = NULL;
+    drawCorners = was_found = false;
+}
 
 /* ///////////////////// chess_corner_test ///////////////////////// */
 void CV_ChessboardDetectorBadArgTest::run( int /*start_from */)

modules/calib3d/test/test_cornerssubpix.cpp

@@ -211,6 +211,7 @@ void CV_ChessboardSubpixelTest::run( int )
 
         progress = update_progress( progress, i-1, runs_count, 0 );
     }
+    ASSERT_NE(0, count);
     sum_dist /= count;
     ts->printf(cvtest::TS::LOG, "Average error after findCornerSubpix: %f\n", sum_dist);
 

modules/calib3d/test/test_fundam.cpp

@@ -808,6 +808,7 @@ CV_FundamentalMatTest::CV_FundamentalMatTest()
     method = 0;
     img_size = 10;
     cube_size = 10;
+    dims = 0;
     min_f = 1;
     max_f = 3;
     sigma = 0;//0.1;
@@ -1086,7 +1087,6 @@ protected:
     int img_size;
     int cube_size;
     int dims;
-    int e_result;
     double min_f, max_f;
     double sigma;
 };
@@ -1124,9 +1124,10 @@ CV_EssentialMatTest::CV_EssentialMatTest()
     method = 0;
     img_size = 10;
     cube_size = 10;
+    dims = 0;
     min_f = 1;
     max_f = 3;
-
+    sigma = 0;
 }
 
 

modules/calib3d/test/test_undistort.cpp

@@ -75,6 +75,9 @@ CV_DefaultNewCameraMatrixTest::CV_DefaultNewCameraMatrixTest()
     test_array[INPUT].push_back(NULL);
     test_array[OUTPUT].push_back(NULL);
     test_array[REF_OUTPUT].push_back(NULL);
+
+    matrix_type = 0;
+    center_principal_point = false;
 }
 
 void CV_DefaultNewCameraMatrixTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
@@ -200,6 +203,9 @@ CV_UndistortPointsTest::CV_UndistortPointsTest()
     test_array[OUTPUT].push_back(NULL); // distorted dst points
     test_array[TEMP].push_back(NULL); // dst points
     test_array[REF_OUTPUT].push_back(NULL);
+
+    useCPlus = useDstMat = false;
+    zero_new_cam = zero_distortion = zero_R = false;
 }
 
 void CV_UndistortPointsTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
@@ -605,6 +611,11 @@ CV_InitUndistortRectifyMapTest::CV_InitUndistortRectifyMapTest()
     test_array[INPUT].push_back(NULL); // new camera matrix
     test_array[OUTPUT].push_back(NULL); // distorted dst points
     test_array[REF_OUTPUT].push_back(NULL);
+
+    useCPlus = false;
+    zero_distortion = zero_new_cam = zero_R = false;
+    _mapx = _mapy = NULL;
+    mat_type = 0;
 }
 
 void CV_InitUndistortRectifyMapTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )

modules/calib3d/test/test_undistort_badarg.cpp

@@ -78,6 +78,8 @@ private:
 
 CV_UndistortPointsBadArgTest::CV_UndistortPointsBadArgTest ()
 {
+    useCPlus = false;
+    _camera_mat = matR = matP = _distortion_coeffs = _src_points = _dst_points = NULL;
 }
 
 void CV_UndistortPointsBadArgTest::run_func()
@@ -311,6 +313,8 @@ private:
 
 CV_InitUndistortRectifyMapBadArgTest::CV_InitUndistortRectifyMapBadArgTest ()
 {
+    useCPlus = false;
+    _camera_mat = matR = _new_camera_mat = _distortion_coeffs = _mapx = _mapy = NULL;
 }
 
 void CV_InitUndistortRectifyMapBadArgTest::run_func()
@@ -431,6 +435,8 @@ private:
 
 CV_UndistortBadArgTest::CV_UndistortBadArgTest ()
 {
+    useCPlus = false;
+    _camera_mat = _new_camera_mat = _distortion_coeffs = _src = _dst = NULL;
 }
 
 void CV_UndistortBadArgTest::run_func()

modules/contrib/include/opencv2/contrib.hpp

@@ -55,7 +55,7 @@ class CV_EXPORTS Octree
 public:
     struct Node
     {
-        Node() {}
+        Node() { memset(this, 0, sizeof(Node)); }
         int begin, end;
         float x_min, x_max, y_min, y_max, z_min, z_max;
         int maxLevels;

modules/core/include/opencv2/core/utility.hpp

@@ -340,6 +340,8 @@ class CV_EXPORTS CommandLineParser
     CommandLineParser(const CommandLineParser& parser);
     CommandLineParser& operator = (const CommandLineParser& parser);
 
+    ~CommandLineParser();
+
     String getPathToApplication() const;
 
     template <typename T>

modules/core/src/command_line_parser.cpp

@@ -237,6 +237,11 @@ CommandLineParser::CommandLineParser(int argc, const char* const argv[], const S
     impl->sort_params();
 }
 
+CommandLineParser::~CommandLineParser()
+{
+    if (CV_XADD(&impl->refcount, -1) == 1)
+        delete impl;
+}
 
 CommandLineParser::CommandLineParser(const CommandLineParser& parser)
 {

modules/core/src/copy.cpp

@@ -353,7 +353,7 @@ Mat& Mat::operator = (const Scalar& s)
 
 Mat& Mat::setTo(InputArray _value, InputArray _mask)
 {
-    if( !data )
+    if( empty() )
         return *this;
 
     Mat value = _value.getMat(), mask = _mask.getMat();
@@ -632,6 +632,7 @@ int cv::borderInterpolate( int p, int len, int borderType )
     }
     else if( borderType == BORDER_WRAP )
     {
+        CV_Assert(len > 0);
         if( p < 0 )
             p -= ((p-len+1)/len)*len;
         if( p >= len )

modules/core/src/ocl.cpp

@@ -2641,9 +2641,9 @@ KernelArg KernelArg::Constant(const Mat& m)
 
 struct Kernel::Impl
 {
-    Impl(const char* kname, const Program& prog)
+    Impl(const char* kname, const Program& prog) :
+        refcount(1), e(0), nu(0)
     {
-        e = 0; refcount = 1;
         cl_program ph = (cl_program)prog.ptr();
         cl_int retval = 0;
         handle = ph != 0 ?

modules/core/src/system.cpp

@@ -426,6 +426,7 @@ String format( const char* fmt, ... )
         String s(len, '\0');
         va_start(va, fmt);
         len = vsnprintf((char*)s.c_str(), len + 1, fmt, va);
+        (void)len;
         va_end(va);
         return s;
     }

modules/core/test/test_arithm.cpp

@@ -18,7 +18,7 @@ struct BaseElemWiseOp
     BaseElemWiseOp(int _ninputs, int _flags, double _alpha, double _beta,
                    Scalar _gamma=Scalar::all(0), int _context=1)
     : ninputs(_ninputs), flags(_flags), alpha(_alpha), beta(_beta), gamma(_gamma), context(_context) {}
-    BaseElemWiseOp() { flags = 0; alpha = beta = 0; gamma = Scalar::all(0); }
+    BaseElemWiseOp() { flags = 0; alpha = beta = 0; gamma = Scalar::all(0); ninputs = 0; context = 1; }
     virtual ~BaseElemWiseOp() {}
     virtual void op(const vector<Mat>&, Mat&, const Mat&) {}
     virtual void refop(const vector<Mat>&, Mat&, const Mat&) {}
@@ -89,7 +89,6 @@ struct BaseElemWiseOp
     double alpha;
     double beta;
     Scalar gamma;
-    int maxErr;
     int context;
 };
 
@@ -409,7 +408,7 @@ 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)) { cmpop = 0; }
     void generateScalars(int depth, RNG& rng)
     {
         BaseElemWiseOp::generateScalars(depth, rng);
@@ -437,7 +436,7 @@ 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)) { cmpop = 0; }
     void generateScalars(int depth, RNG& rng)
     {
         BaseElemWiseOp::generateScalars(depth, rng);
@@ -467,7 +466,7 @@ 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);
@@ -484,7 +483,6 @@ struct CopyOp : public BaseElemWiseOp
     {
         return 0;
     }
-    int cmpop;
 };
 
 
@@ -810,7 +808,7 @@ 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)) { flipcode = 0; }
     void getRandomSize(RNG& rng, vector<int>& size)
     {
         cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size);

modules/core/test/test_math.cpp

@@ -617,6 +617,7 @@ Core_GEMMTest::Core_GEMMTest() : Core_MatrixTest( 5, 1, false, false, 2 )
 {
     test_case_count = 100;
     max_log_array_size = 10;
+    tabc_flag = 0;
     alpha = beta = 0;
 }
 
@@ -821,6 +822,8 @@ protected:
 
 Core_TransformTest::Core_TransformTest() : Core_MatrixTest( 3, 1, true, false, 4 )
 {
+    scale = 1;
+    diagMtx = false;
 }
 
 
@@ -1154,7 +1157,7 @@ protected:
 
 
 Core_CovarMatrixTest::Core_CovarMatrixTest() : Core_MatrixTest( 1, 1, true, false, 1 ),
-flags(0), t_flag(0), are_images(false)
+    flags(0), t_flag(0), len(0), count(0), are_images(false)
 {
     test_case_count = 100;
     test_array[INPUT_OUTPUT].push_back(NULL);

modules/features2d/src/bagofwords.cpp

@@ -44,7 +44,7 @@
 namespace cv
 {
 
-BOWTrainer::BOWTrainer()
+BOWTrainer::BOWTrainer() : size(0)
 {}
 
 BOWTrainer::~BOWTrainer()

modules/features2d/src/brisk.cpp

@@ -224,6 +224,8 @@ BRISK::BRISK(std::vector<float> &radiusList, std::vector<int> &numberList, float
                                                    std::vector<int> indexChange)
 {
   generateKernel(radiusList, numberList, dMax, dMin, indexChange);
+  threshold = 20;
+  octaves = 3;
 }
 
 void

modules/imgproc/src/accum.cpp

@@ -408,7 +408,7 @@ static bool ocl_accumulate( InputArray _src, InputArray _src2, InputOutputArray
             argidx = k.set(argidx, alpha);
     }
     if (haveMask)
-        argidx = k.set(argidx, maskarg);
+        k.set(argidx, maskarg);
 
     size_t globalsize[2] = { src.cols, src.rows };
     return k.run(2, globalsize, NULL, false);

modules/imgproc/src/clahe.cpp

@@ -83,11 +83,9 @@ namespace clahe
         idx = k.set(idx, tile_size);
         idx = k.set(idx, tilesX);
         idx = k.set(idx, clipLimit);
-        idx = k.set(idx, lutScale);
+        k.set(idx, lutScale);
 
-        if (!k.run(2, globalThreads, localThreads, false))
+        return k.run(2, globalThreads, localThreads, false);
-            return false;
-        return true;
     }
 
     static bool transform(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _lut,
@@ -118,11 +116,9 @@ namespace clahe
         idx = k.set(idx, src.rows);
         idx = k.set(idx, tile_size);
         idx = k.set(idx, tilesX);
-        idx = k.set(idx, tilesY);
+        k.set(idx, tilesY);
 
-        if (!k.run(2, globalThreads, localThreads, false))
+        return k.run(2, globalThreads, localThreads, false);
-            return false;
-        return true;
     }
 }
 

modules/imgproc/src/deriv.cpp

@@ -540,8 +540,6 @@ void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
         int wtype = CV_MAKETYPE(wdepth, src.channels());
         Mat kd, ks;
         getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );
-        if( ddepth < 0 )
-            ddepth = src.depth();
         int dtype = CV_MAKETYPE(ddepth, src.channels());
 
         int dy0 = std::min(std::max((int)(STRIPE_SIZE/(getElemSize(src.type())*src.cols)), 1), src.rows);

modules/imgproc/src/filter.cpp

@@ -1405,7 +1405,11 @@ struct SymmColumnVec_32f16s
 
 struct RowVec_32f
 {
-    RowVec_32f() {}
+    RowVec_32f()
+    {
+        haveSSE = checkHardwareSupport(CV_CPU_SSE);
+    }
+
     RowVec_32f( const Mat& _kernel )
     {
         kernel = _kernel;

modules/imgproc/test/test_color.cpp

@@ -99,6 +99,8 @@ CV_ColorCvtBaseTest::CV_ColorCvtBaseTest( bool _custom_inv_transform, bool _allo
 
     test_cpp = false;
     hue_range = 0;
+    blue_idx = 0;
+    inplace = false;
 }
 
 

modules/ml/src/precomp.hpp

@@ -351,7 +351,7 @@ namespace cv
 {
     struct DTreeBestSplitFinder
     {
-        DTreeBestSplitFinder(){ tree = 0; node = 0; }
+        DTreeBestSplitFinder(){ splitSize = 0, tree = 0; node = 0; }
         DTreeBestSplitFinder( CvDTree* _tree, CvDTreeNode* _node);
         DTreeBestSplitFinder( const DTreeBestSplitFinder& finder, Split );
         virtual ~DTreeBestSplitFinder() {}

modules/objdetect/src/erfilter.cpp

@@ -294,7 +294,7 @@ void ERFilterNM::er_tree_extract( InputArray image )
         push_new_component = false;
 
         // explore the (remaining) edges to the neighbors to the current pixel
-        for (current_edge = current_edge; current_edge < 4; current_edge++)
+        for ( ; current_edge < 4; current_edge++)
         {
 
             int neighbour_pixel = current_pixel;
@@ -1949,7 +1949,6 @@ private:
     double (dissimilarity::*distfn) (const int_fast32_t, const int_fast32_t) const;
 
     auto_array_ptr<double> precomputed;
-    double * precomputed2;
 
     double * V;
     const double * V_data;

modules/objdetect/test/test_cascadeandhog.cpp

@@ -574,7 +574,7 @@ public:
         Size winStride = Size(), Size padding = Size(),
         const vector<Point>& locations = vector<Point>()) const;
 
-    virtual void compute(const Mat& img, vector<float>& descriptors,
+    virtual void compute(InputArray img, vector<float>& descriptors,
         Size winStride = Size(), Size padding = Size(),
         const vector<Point>& locations = vector<Point>()) const;
 
@@ -1107,9 +1107,11 @@ void HOGDescriptorTester::detect(const Mat& img, vector<Point>& hits, double hit
     detect(img, hits, weightsV, hitThreshold, winStride, padding, locations);
 }
 
-void HOGDescriptorTester::compute(const Mat& img, vector<float>& descriptors,
+void HOGDescriptorTester::compute(InputArray _img, vector<float>& descriptors,
     Size winStride, Size padding, const vector<Point>& locations) const
 {
+    Mat img = _img.getMat();
+
     if( winStride == Size() )
         winStride = cellSize;
     Size cacheStride(gcd(winStride.width, blockStride.width),

modules/shape/src/scd_def.hpp

@@ -120,7 +120,6 @@ public:
 
 private:
     float minMatchCost;
-    float betaAdditional;
 protected:
     void buildCostMatrix(const cv::Mat& descriptors1, const cv::Mat& descriptors2,
                                      cv::Mat& costMatrix, cv::Ptr<cv::HistogramCostExtractor>& comparer) const;

modules/ts/src/ts_func.cpp

@@ -2897,7 +2897,7 @@ static std::ostream& operator << (std::ostream& out, const MatPart& m)
 }
 
 MatComparator::MatComparator(double _maxdiff, int _context)
-    : maxdiff(_maxdiff), context(_context) {}
+    : maxdiff(_maxdiff), realmaxdiff(DBL_MAX), context(_context) {}
 
 ::testing::AssertionResult
 MatComparator::operator()(const char* expr1, const char* expr2,

modules/ts/src/ts_perf.cpp

@@ -855,6 +855,9 @@ int64 TestBase::_calibrate()
 #endif
 TestBase::TestBase(): testStrategy(PERF_STRATEGY_DEFAULT), declare(this)
 {
+    lastTime = totalTime = timeLimit = 0;
+    nIters = currentIter = runsPerIteration = 0;
+    verified = false;
 }
 #ifdef _MSC_VER
 # pragma warning(pop)

modules/video/src/bgfg_gaussmix2.cpp

@@ -779,7 +779,7 @@ bool BackgroundSubtractorMOG2Impl::ocl_apply(InputArray _image, OutputArray _fgm
     idxArg = kernel_apply.set(idxArg, varMax);
     idxArg = kernel_apply.set(idxArg, fVarInit);
     idxArg = kernel_apply.set(idxArg, fTau);
-    idxArg = kernel_apply.set(idxArg, nShadowDetection);
+    kernel_apply.set(idxArg, nShadowDetection);
 
     size_t globalsize[] = {frame.cols, frame.rows, 1};
 
@@ -805,7 +805,7 @@ bool BackgroundSubtractorMOG2Impl::ocl_getBackgroundImage(OutputArray _backgroun
     idxArg = kernel_getBg.set(idxArg, ocl::KernelArg::ReadOnlyNoSize(u_weight));
     idxArg = kernel_getBg.set(idxArg, ocl::KernelArg::ReadOnlyNoSize(u_mean));
     idxArg = kernel_getBg.set(idxArg, ocl::KernelArg::WriteOnlyNoSize(dst));
-    idxArg = kernel_getBg.set(idxArg, backgroundRatio);
+    kernel_getBg.set(idxArg, backgroundRatio);
 
     size_t globalsize[2] = {u_bgmodelUsedModes.cols, u_bgmodelUsedModes.rows};
 

modules/video/src/optflowgf.cpp

@@ -857,7 +857,7 @@ private:
         idxArg = kernel.set(idxArg, dst.cols);
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_gKer));
         idxArg = kernel.set(idxArg, (int)ksizeHalf);
-        idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
+        kernel.set(idxArg, (void *)NULL, smem_size);
         return kernel.run(2, globalsize, localsize, false);
     }
     bool gaussianBlur5Ocl(const UMat &src, int ksizeHalf, UMat &dst)
@@ -883,7 +883,7 @@ private:
         idxArg = kernel.set(idxArg, src.cols);
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_gKer));
         idxArg = kernel.set(idxArg, (int)ksizeHalf);
-        idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
+        kernel.set(idxArg, (void *)NULL, smem_size);
         return kernel.run(2, globalsize, localsize, false);
     }
     bool polynomialExpansionOcl(const UMat &src, UMat &dst)
@@ -919,12 +919,7 @@ private:
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_xg));
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_xxg));
         idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
-#if 0
+        kernel.set(idxArg, (void *)m_ig, 4 * sizeof(float));
-        if (useDouble)
-            idxArg = kernel.set(idxArg, (void *)m_igd, 4 * sizeof(double));
-        else
-#endif
-            idxArg = kernel.set(idxArg, (void *)m_ig, 4 * sizeof(float));
         return kernel.run(2, globalsize, localsize, false);
     }
     bool boxFilter5Ocl(const UMat &src, int ksizeHalf, UMat &dst)
@@ -951,7 +946,7 @@ private:
         idxArg = kernel.set(idxArg, height);
         idxArg = kernel.set(idxArg, src.cols);
         idxArg = kernel.set(idxArg, (int)ksizeHalf);
-        idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
+        kernel.set(idxArg, (void *)NULL, smem_size);
         return kernel.run(2, globalsize, localsize, false);
     }
 
@@ -976,7 +971,7 @@ private:
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(flowy));
         idxArg = kernel.set(idxArg, (int)(flowy.step / flowy.elemSize()));
         idxArg = kernel.set(idxArg, (int)flowy.rows);
-        idxArg = kernel.set(idxArg, (int)flowy.cols);
+        kernel.set(idxArg, (int)flowy.cols);
         return kernel.run(2, globalsize, localsize, false);
     }
     bool updateMatricesOcl(const UMat &flowx, const UMat &flowy, const UMat &R0, const UMat &R1, UMat &M)
@@ -1004,7 +999,7 @@ private:
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(R1));
         idxArg = kernel.set(idxArg, (int)(R1.step / R1.elemSize()));
         idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(M));
-        idxArg = kernel.set(idxArg, (int)(M.step / M.elemSize()));
+        kernel.set(idxArg, (int)(M.step / M.elemSize()));
         return kernel.run(2, globalsize, localsize, false);
     }
 

modules/video/src/simpleflow.cpp

@@ -429,6 +429,7 @@ static inline float extrapolateValueInRect(int height, int width,
   if (r == height && c == 0) { return v21;}
   if (r == height && c == width) { return v22;}
 
+  CV_Assert(height > 0 && width > 0);
   float qr = float(r) / height;
   float pr = 1.0f - qr;
   float qc = float(c) / width;