Merge pull request #11093 from alalek:cv_override_final

3rdparty/openexr/CMakeLists.txt

@@ -44,6 +44,7 @@ source_group("Src" FILES ${lib_srcs})
 
 ocv_warnings_disable(CMAKE_CXX_FLAGS -Wshadow -Wunused -Wsign-compare -Wundef -Wmissing-declarations -Wuninitialized -Wswitch -Wparentheses -Warray-bounds -Wextra
                                      -Wdeprecated-declarations -Wmisleading-indentation -Wdeprecated
+                                     -Wsuggest-override -Winconsistent-missing-override
 )
 ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4018 /wd4099 /wd4100 /wd4101 /wd4127 /wd4189 /wd4245 /wd4305 /wd4389 /wd4512 /wd4701 /wd4702 /wd4706 /wd4800) # vs2005
 ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4334) # vs2005 Win64

3rdparty/protobuf/CMakeLists.txt

@@ -20,6 +20,7 @@ else()
                                        -Wundef -Wtautological-undefined-compare -Wignored-qualifiers -Wextra
                                        -Wunused-function -Wunused-const-variable -Wshorten-64-to-32 -Wno-invalid-offsetof
                                        -Wenum-compare-switch
+                                       -Wsuggest-override -Winconsistent-missing-override
   )
 endif()
 if(CV_ICC)

apps/interactive-calibration/frameProcessor.hpp

@@ -61,10 +61,10 @@ protected:
 
 public:
     CalibProcessor(cv::Ptr<calibrationData> data, captureParameters& capParams);
-    virtual cv::Mat processFrame(const cv::Mat& frame);
-    virtual bool isProcessed() const;
-    virtual void resetState();
-    ~CalibProcessor();
+    virtual cv::Mat processFrame(const cv::Mat& frame) CV_OVERRIDE;
+    virtual bool isProcessed() const CV_OVERRIDE;
+    virtual void resetState() CV_OVERRIDE;
+    ~CalibProcessor() CV_OVERRIDE;
 };
 
 enum visualisationMode {Grid, Window};
@@ -84,9 +84,9 @@ protected:
     void drawGridPoints(const cv::Mat& frame);
 public:
     ShowProcessor(cv::Ptr<calibrationData> data, cv::Ptr<calibController> controller, TemplateType board);
-    virtual cv::Mat processFrame(const cv::Mat& frame);
-    virtual bool isProcessed() const;
-    virtual void resetState();
+    virtual cv::Mat processFrame(const cv::Mat& frame) CV_OVERRIDE;
+    virtual bool isProcessed() const CV_OVERRIDE;
+    virtual void resetState() CV_OVERRIDE;
 
     void setVisualizationMode(visualisationMode mode);
     void switchVisualizationMode();
@@ -95,7 +95,7 @@ public:
 
     void switchUndistort();
     void setUndistort(bool isEnabled);
-    ~ShowProcessor();
+    ~ShowProcessor() CV_OVERRIDE;
 };
 
 }

apps/traincascade/CMakeLists.txt

@@ -8,7 +8,9 @@ endif()
 project(traincascade)
 set(the_target opencv_traincascade)
 
-ocv_warnings_disable(CMAKE_CXX_FLAGS -Woverloaded-virtual)
+ocv_warnings_disable(CMAKE_CXX_FLAGS -Woverloaded-virtual
+                                     -Winconsistent-missing-override -Wsuggest-override
+)
 
 ocv_target_include_directories(${the_target} PRIVATE "${CMAKE_CURRENT_SOURCE_DIR}" "${OpenCV_SOURCE_DIR}/include/opencv")
 ocv_target_include_modules_recurse(${the_target} ${OPENCV_TRAINCASCADE_DEPS})

cmake/OpenCVCompilerOptions.cmake

@@ -103,6 +103,13 @@ if(CV_GCC OR CV_CLANG)
   add_extra_compiler_option(-Wsign-promo)
   add_extra_compiler_option(-Wuninitialized)
   add_extra_compiler_option(-Winit-self)
+  if(HAVE_CXX11)
+    if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
+      add_extra_compiler_option(-Wsuggest-override)
+    elseif(CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
+      add_extra_compiler_option(-Winconsistent-missing-override)
+    endif()
+  endif()
 
   if(ENABLE_NOISY_WARNINGS)
     add_extra_compiler_option(-Wcast-align)

cmake/OpenCVFindProtobuf.cmake

@@ -51,7 +51,7 @@ else()
       add_library(libprotobuf UNKNOWN IMPORTED)
       set_target_properties(libprotobuf PROPERTIES
         IMPORTED_LOCATION "${Protobuf_LIBRARY}"
-        INTERFACE_INCLUDE_DIRECTORIES "${Protobuf_INCLUDE_DIR}"
+        INTERFACE_INCLUDE_SYSTEM_DIRECTORIES "${Protobuf_INCLUDE_DIR}"
       )
       get_protobuf_version(Protobuf_VERSION "${Protobuf_INCLUDE_DIR}")
     endif()

cmake/OpenCVUtils.cmake

@@ -565,6 +565,24 @@ macro(ocv_append_build_options var_prefix pkg_prefix)
   endforeach()
 endmacro()
 
+function(ocv_append_source_files_cxx_compiler_options files_var)
+  set(__flags "${ARGN}")
+  ocv_check_flag_support(CXX "${__flags}" __HAVE_COMPILER_OPTIONS_VAR "")
+  if(${__HAVE_COMPILER_OPTIONS_VAR})
+    foreach(source ${${files_var}})
+      if("${source}" MATCHES "\\.(cpp|cc|cxx)$")
+        get_source_file_property(flags "${source}" COMPILE_FLAGS)
+        if(flags)
+          set(flags "${flags} ${__flags}")
+        else()
+          set(flags "${__flags}")
+        endif()
+        set_source_files_properties("${source}" PROPERTIES COMPILE_FLAGS "${flags}")
+      endif()
+    endforeach()
+  endif()
+endfunction()
+
 # Usage is similar to CMake 'pkg_check_modules' command
 # It additionally controls HAVE_${define} and ${define}_${modname}_FOUND variables
 macro(ocv_check_modules define)

modules/calib3d/src/five-point.cpp

@@ -34,10 +34,10 @@
 namespace cv
 {
 
-class EMEstimatorCallback : public PointSetRegistrator::Callback
+class EMEstimatorCallback CV_FINAL : public PointSetRegistrator::Callback
 {
 public:
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         Mat q1 = _m1.getMat(), q2 = _m2.getMat();
         Mat Q1 = q1.reshape(1, (int)q1.total());
@@ -370,7 +370,7 @@ protected:
     }
 
 
-    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
+    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
     {
         Mat X1 = _m1.getMat(), X2 = _m2.getMat(), model = _model.getMat();
         const Point2d* x1ptr = X1.ptr<Point2d>();

modules/calib3d/src/fundam.cpp

@@ -59,10 +59,10 @@ namespace cv
  * where \f$\lambda \in \mathbb{R} \f$.
  *
  */
-class HomographyEstimatorCallback : public PointSetRegistrator::Callback
+class HomographyEstimatorCallback CV_FINAL : public PointSetRegistrator::Callback
 {
 public:
-    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const
+    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const CV_OVERRIDE
     {
         Mat ms1 = _ms1.getMat(), ms2 = _ms2.getMat();
         if( haveCollinearPoints(ms1, count) || haveCollinearPoints(ms2, count) )
@@ -113,7 +113,7 @@ public:
      *            2 columns 1 channel
      * @param _model, CV_64FC1, 3x3, normalized, i.e., the last element is 1
      */
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat();
         int i, count = m1.checkVector(2);
@@ -188,7 +188,7 @@ public:
      * @param _model CV_64FC1, 3x3
      * @param _err, output, CV_32FC1, square of the L2 norm
      */
-    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
+    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat(), model = _model.getMat();
         int i, count = m1.checkVector(2);
@@ -211,7 +211,7 @@ public:
 };
 
 
-class HomographyRefineCallback : public LMSolver::Callback
+class HomographyRefineCallback CV_FINAL : public LMSolver::Callback
 {
 public:
     HomographyRefineCallback(InputArray _src, InputArray _dst)
@@ -220,7 +220,7 @@ public:
         dst = _dst.getMat();
     }
 
-    bool compute(InputArray _param, OutputArray _err, OutputArray _Jac) const
+    bool compute(InputArray _param, OutputArray _err, OutputArray _Jac) const CV_OVERRIDE
     {
         int i, count = src.checkVector(2);
         Mat param = _param.getMat();
@@ -700,16 +700,16 @@ static int run8Point( const Mat& _m1, const Mat& _m2, Mat& _fmatrix )
 }
 
 
-class FMEstimatorCallback : public PointSetRegistrator::Callback
+class FMEstimatorCallback CV_FINAL : public PointSetRegistrator::Callback
 {
 public:
-    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const
+    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const CV_OVERRIDE
     {
         Mat ms1 = _ms1.getMat(), ms2 = _ms2.getMat();
         return !haveCollinearPoints(ms1, count) && !haveCollinearPoints(ms2, count);
     }
 
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         double f[9*3];
         Mat m1 = _m1.getMat(), m2 = _m2.getMat();
@@ -725,7 +725,7 @@ public:
         return n;
     }
 
-    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
+    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
     {
         Mat __m1 = _m1.getMat(), __m2 = _m2.getMat(), __model = _model.getMat();
         int i, count = __m1.checkVector(2);

modules/calib3d/src/homography_decomp.cpp

@@ -99,25 +99,25 @@ private:
     cv::Matx33d _Hnorm;
 };
 
-class HomographyDecompZhang : public HomographyDecomp {
+class HomographyDecompZhang CV_FINAL : public HomographyDecomp {
 
 public:
     HomographyDecompZhang():HomographyDecomp() {}
     virtual ~HomographyDecompZhang() {}
 
 private:
-    virtual void decompose(std::vector<CameraMotion>& camMotions);
+    virtual void decompose(std::vector<CameraMotion>& camMotions) CV_OVERRIDE;
     bool findMotionFrom_tstar_n(const cv::Vec3d& tstar, const cv::Vec3d& n, CameraMotion& motion);
 };
 
-class HomographyDecompInria : public HomographyDecomp {
+class HomographyDecompInria CV_FINAL : public HomographyDecomp {
 
 public:
     HomographyDecompInria():HomographyDecomp() {}
     virtual ~HomographyDecompInria() {}
 
 private:
-    virtual void decompose(std::vector<CameraMotion>& camMotions);
+    virtual void decompose(std::vector<CameraMotion>& camMotions) CV_OVERRIDE;
     double oppositeOfMinor(const cv::Matx33d& M, const int row, const int col);
     void findRmatFrom_tstar_n(const cv::Vec3d& tstar, const cv::Vec3d& n, const double v, cv::Matx33d& R);
 };

modules/calib3d/src/levmarq.cpp

@@ -77,7 +77,7 @@
 namespace cv
 {
 
-class LMSolverImpl : public LMSolver
+class LMSolverImpl CV_FINAL : public LMSolver
 {
 public:
     LMSolverImpl() : maxIters(100) { init(); }
@@ -89,7 +89,7 @@ public:
         printInterval = 0;
     }
 
-    int run(InputOutputArray _param0) const
+    int run(InputOutputArray _param0) const CV_OVERRIDE
     {
         Mat param0 = _param0.getMat(), x, xd, r, rd, J, A, Ap, v, temp_d, d;
         int ptype = param0.type();
@@ -198,7 +198,7 @@ public:
         return iter;
     }
 
-    void setCallback(const Ptr<LMSolver::Callback>& _cb) { cb = _cb; }
+    void setCallback(const Ptr<LMSolver::Callback>& _cb) CV_OVERRIDE { cb = _cb; }
 
     Ptr<LMSolver::Callback> cb;
 

modules/calib3d/src/ptsetreg.cpp

@@ -161,7 +161,7 @@ public:
         return i == modelPoints && iters < maxAttempts;
     }
 
-    bool run(InputArray _m1, InputArray _m2, OutputArray _model, OutputArray _mask) const
+    bool run(InputArray _m1, InputArray _m2, OutputArray _model, OutputArray _mask) const CV_OVERRIDE
     {
         bool result = false;
         Mat m1 = _m1.getMat(), m2 = _m2.getMat();
@@ -257,7 +257,7 @@ public:
         return result;
     }
 
-    void setCallback(const Ptr<PointSetRegistrator::Callback>& _cb) { cb = _cb; }
+    void setCallback(const Ptr<PointSetRegistrator::Callback>& _cb) CV_OVERRIDE { cb = _cb; }
 
     Ptr<PointSetRegistrator::Callback> cb;
     int modelPoints;
@@ -274,7 +274,7 @@ public:
                               int _modelPoints=0, double _confidence=0.99, int _maxIters=1000)
     : RANSACPointSetRegistrator(_cb, _modelPoints, 0, _confidence, _maxIters) {}
 
-    bool run(InputArray _m1, InputArray _m2, OutputArray _model, OutputArray _mask) const
+    bool run(InputArray _m1, InputArray _m2, OutputArray _model, OutputArray _mask) const CV_OVERRIDE
     {
         const double outlierRatio = 0.45;
         bool result = false;
@@ -412,7 +412,7 @@ Ptr<PointSetRegistrator> createLMeDSPointSetRegistrator(const Ptr<PointSetRegist
 class Affine3DEstimatorCallback : public PointSetRegistrator::Callback
 {
 public:
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat();
         const Point3f* from = m1.ptr<Point3f>();
@@ -450,7 +450,7 @@ public:
         return 1;
     }
 
-    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
+    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat(), model = _model.getMat();
         const Point3f* from = m1.ptr<Point3f>();
@@ -477,7 +477,7 @@ public:
         }
     }
 
-    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const
+    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const CV_OVERRIDE
     {
         const float threshold = 0.996f;
         Mat ms1 = _ms1.getMat(), ms2 = _ms2.getMat();
@@ -527,7 +527,7 @@ public:
 class Affine2DEstimatorCallback : public PointSetRegistrator::Callback
 {
 public:
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat();
         const Point2f* from = m1.ptr<Point2f>();
@@ -587,7 +587,7 @@ public:
         return 1;
     }
 
-    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
+    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat(), model = _model.getMat();
         const Point2f* from = m1.ptr<Point2f>();
@@ -616,7 +616,7 @@ public:
         }
     }
 
-    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const
+    bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const CV_OVERRIDE
     {
         Mat ms1 = _ms1.getMat();
         Mat ms2 = _ms2.getMat();
@@ -640,7 +640,7 @@ public:
 class AffinePartial2DEstimatorCallback : public Affine2DEstimatorCallback
 {
 public:
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         Mat m1 = _m1.getMat(), m2 = _m2.getMat();
         const Point2f* from = m1.ptr<Point2f>();
@@ -696,7 +696,7 @@ public:
         dst = _dst.getMat();
     }
 
-    bool compute(InputArray _param, OutputArray _err, OutputArray _Jac) const
+    bool compute(InputArray _param, OutputArray _err, OutputArray _Jac) const CV_OVERRIDE
     {
         int i, count = src.checkVector(2);
         Mat param = _param.getMat();
@@ -754,7 +754,7 @@ public:
         dst = _dst.getMat();
     }
 
-    bool compute(InputArray _param, OutputArray _err, OutputArray _Jac) const
+    bool compute(InputArray _param, OutputArray _err, OutputArray _Jac) const CV_OVERRIDE
     {
         int i, count = src.checkVector(2);
         Mat param = _param.getMat();

modules/calib3d/src/rho.cpp

@@ -336,9 +336,9 @@ struct RHO_HEST_REFC : RHO_HEST{
     ~RHO_HEST_REFC();
 
     /* Methods to implement external interface */
-    inline int    initialize(void);
-    inline void   finalize(void);
-    inline int    ensureCapacity(unsigned N, double beta);
+    inline int    initialize(void) CV_OVERRIDE;
+    inline void   finalize(void) CV_OVERRIDE;
+    inline int    ensureCapacity(unsigned N, double beta) CV_OVERRIDE;
     unsigned      rhoHest(const float*   src,     /* Source points */
                           const float*   dst,     /* Destination points */
                           char*          inl,     /* Inlier mask */
@@ -351,7 +351,8 @@ struct RHO_HEST_REFC : RHO_HEST{
                           double         beta,    /* Works:    0.35 */
                           unsigned       flags,   /* Works:       0 */
                           const float*   guessH,  /* Extrinsic guess, NULL if none provided */
-                          float*         finalH); /* Final result. */
+                          float*         finalH   /* Final result. */
+    ) CV_OVERRIDE;
 
 
 

modules/calib3d/src/solvepnp.cpp

@@ -169,7 +169,7 @@ bool solvePnP( InputArray _opoints, InputArray _ipoints,
     return result;
 }
 
-class PnPRansacCallback : public PointSetRegistrator::Callback
+class PnPRansacCallback CV_FINAL : public PointSetRegistrator::Callback
 {
 
 public:
@@ -181,7 +181,7 @@ public:
 
     /* Pre: True */
     /* Post: compute _model with given points and return number of found models */
-    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const
+    int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
     {
         Mat opoints = _m1.getMat(), ipoints = _m2.getMat();
 
@@ -197,7 +197,7 @@ public:
 
     /* Pre: True */
     /* Post: fill _err with projection errors */
-    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const
+    void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
     {
 
         Mat opoints = _m1.getMat(), ipoints = _m2.getMat(), model = _model.getMat();

modules/calib3d/src/stereobm.cpp

@@ -889,7 +889,7 @@ struct PrefilterInvoker : public ParallelLoopBody
         state = _state;
     }
 
-    void operator()( const Range& range ) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         for( int i = range.start; i < range.end; i++ )
         {
@@ -974,7 +974,7 @@ struct FindStereoCorrespInvoker : public ParallelLoopBody
 #endif
     }
 
-    void operator()( const Range& range ) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         int cols = left->cols, rows = left->rows;
         int _row0 = std::min(cvRound(range.start * rows / nstripes), rows);
@@ -1046,7 +1046,7 @@ protected:
     bool useSIMD;
 };
 
-class StereoBMImpl : public StereoBM
+class StereoBMImpl CV_FINAL : public StereoBM
 {
 public:
     StereoBMImpl()
@@ -1059,7 +1059,7 @@ public:
         params = StereoBMParams(_numDisparities, _SADWindowSize);
     }
 
-    void compute( InputArray leftarr, InputArray rightarr, OutputArray disparr )
+    void compute( InputArray leftarr, InputArray rightarr, OutputArray disparr ) CV_OVERRIDE
     {
         CV_INSTRUMENT_REGION()
 
@@ -1201,49 +1201,49 @@ public:
             disp.convertTo(disp0, disp0.type(), 1./(1 << disp_shift), 0);
     }
 
-    int getMinDisparity() const { return params.minDisparity; }
-    void setMinDisparity(int minDisparity) { params.minDisparity = minDisparity; }
+    int getMinDisparity() const CV_OVERRIDE { return params.minDisparity; }
+    void setMinDisparity(int minDisparity) CV_OVERRIDE { params.minDisparity = minDisparity; }
 
-    int getNumDisparities() const { return params.numDisparities; }
-    void setNumDisparities(int numDisparities) { params.numDisparities = numDisparities; }
+    int getNumDisparities() const CV_OVERRIDE { return params.numDisparities; }
+    void setNumDisparities(int numDisparities) CV_OVERRIDE { params.numDisparities = numDisparities; }
 
-    int getBlockSize() const { return params.SADWindowSize; }
-    void setBlockSize(int blockSize) { params.SADWindowSize = blockSize; }
+    int getBlockSize() const CV_OVERRIDE { return params.SADWindowSize; }
+    void setBlockSize(int blockSize) CV_OVERRIDE { params.SADWindowSize = blockSize; }
 
-    int getSpeckleWindowSize() const { return params.speckleWindowSize; }
-    void setSpeckleWindowSize(int speckleWindowSize) { params.speckleWindowSize = speckleWindowSize; }
+    int getSpeckleWindowSize() const CV_OVERRIDE { return params.speckleWindowSize; }
+    void setSpeckleWindowSize(int speckleWindowSize) CV_OVERRIDE { params.speckleWindowSize = speckleWindowSize; }
 
-    int getSpeckleRange() const { return params.speckleRange; }
-    void setSpeckleRange(int speckleRange) { params.speckleRange = speckleRange; }
+    int getSpeckleRange() const CV_OVERRIDE { return params.speckleRange; }
+    void setSpeckleRange(int speckleRange) CV_OVERRIDE { params.speckleRange = speckleRange; }
 
-    int getDisp12MaxDiff() const { return params.disp12MaxDiff; }
-    void setDisp12MaxDiff(int disp12MaxDiff) { params.disp12MaxDiff = disp12MaxDiff; }
+    int getDisp12MaxDiff() const CV_OVERRIDE { return params.disp12MaxDiff; }
+    void setDisp12MaxDiff(int disp12MaxDiff) CV_OVERRIDE { params.disp12MaxDiff = disp12MaxDiff; }
 
-    int getPreFilterType() const { return params.preFilterType; }
-    void setPreFilterType(int preFilterType) { params.preFilterType = preFilterType; }
+    int getPreFilterType() const CV_OVERRIDE { return params.preFilterType; }
+    void setPreFilterType(int preFilterType) CV_OVERRIDE { params.preFilterType = preFilterType; }
 
-    int getPreFilterSize() const { return params.preFilterSize; }
-    void setPreFilterSize(int preFilterSize) { params.preFilterSize = preFilterSize; }
+    int getPreFilterSize() const CV_OVERRIDE { return params.preFilterSize; }
+    void setPreFilterSize(int preFilterSize) CV_OVERRIDE { params.preFilterSize = preFilterSize; }
 
-    int getPreFilterCap() const { return params.preFilterCap; }
-    void setPreFilterCap(int preFilterCap) { params.preFilterCap = preFilterCap; }
+    int getPreFilterCap() const CV_OVERRIDE { return params.preFilterCap; }
+    void setPreFilterCap(int preFilterCap) CV_OVERRIDE { params.preFilterCap = preFilterCap; }
 
-    int getTextureThreshold() const { return params.textureThreshold; }
-    void setTextureThreshold(int textureThreshold) { params.textureThreshold = textureThreshold; }
+    int getTextureThreshold() const CV_OVERRIDE { return params.textureThreshold; }
+    void setTextureThreshold(int textureThreshold) CV_OVERRIDE { params.textureThreshold = textureThreshold; }
 
-    int getUniquenessRatio() const { return params.uniquenessRatio; }
-    void setUniquenessRatio(int uniquenessRatio) { params.uniquenessRatio = uniquenessRatio; }
+    int getUniquenessRatio() const CV_OVERRIDE { return params.uniquenessRatio; }
+    void setUniquenessRatio(int uniquenessRatio) CV_OVERRIDE { params.uniquenessRatio = uniquenessRatio; }
 
-    int getSmallerBlockSize() const { return 0; }
-    void setSmallerBlockSize(int) {}
+    int getSmallerBlockSize() const CV_OVERRIDE { return 0; }
+    void setSmallerBlockSize(int) CV_OVERRIDE {}
 
-    Rect getROI1() const { return params.roi1; }
-    void setROI1(Rect roi1) { params.roi1 = roi1; }
+    Rect getROI1() const CV_OVERRIDE { return params.roi1; }
+    void setROI1(Rect roi1) CV_OVERRIDE { params.roi1 = roi1; }
 
-    Rect getROI2() const { return params.roi2; }
-    void setROI2(Rect roi2) { params.roi2 = roi2; }
+    Rect getROI2() const CV_OVERRIDE { return params.roi2; }
+    void setROI2(Rect roi2) CV_OVERRIDE { params.roi2 = roi2; }
 
-    void write(FileStorage& fs) const
+    void write(FileStorage& fs) const CV_OVERRIDE
     {
         writeFormat(fs);
         fs << "name" << name_
@@ -1260,7 +1260,7 @@ public:
         << "uniquenessRatio" << params.uniquenessRatio;
     }
 
-    void read(const FileNode& fn)
+    void read(const FileNode& fn) CV_OVERRIDE
     {
         FileNode n = fn["name"];
         CV_Assert( n.isString() && String(n) == name_ );

modules/calib3d/src/stereosgbm.cpp

@@ -871,7 +871,7 @@ struct CalcVerticalSums: public ParallelLoopBody
         useSIMD = hasSIMD128();
     }
 
-    void operator()( const Range& range ) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         static const CostType MAX_COST = SHRT_MAX;
         static const int ALIGN = 16;
@@ -1152,7 +1152,7 @@ struct CalcHorizontalSums: public ParallelLoopBody
         useSIMD = hasSIMD128();
     }
 
-    void operator()( const Range& range ) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         int y1 = range.start, y2 = range.end;
         size_t auxBufsSize = LrSize * sizeof(CostType) + width*(sizeof(CostType) + sizeof(DispType)) + 32;
@@ -1542,7 +1542,7 @@ struct SGBM3WayMainLoop : public ParallelLoopBody
 
     SGBM3WayMainLoop(Mat *_buffers, const Mat& _img1, const Mat& _img2, Mat* _dst_disp, const StereoSGBMParams& params, PixType* _clipTab, int _nstripes, int _stripe_overlap);
     void getRawMatchingCost(CostType* C, CostType* hsumBuf, CostType* pixDiff, PixType* tmpBuf, int y, int src_start_idx) const;
-    void operator () (const Range& range) const;
+    void operator () (const Range& range) const CV_OVERRIDE;
 };
 
 SGBM3WayMainLoop::SGBM3WayMainLoop(Mat *_buffers, const Mat& _img1, const Mat& _img2, Mat* _dst_disp, const StereoSGBMParams& params, PixType* _clipTab, int _nstripes, int _stripe_overlap):
@@ -2128,7 +2128,7 @@ static void computeDisparity3WaySGBM( const Mat& img1, const Mat& img2,
     delete[] dst_disp;
 }
 
-class StereoSGBMImpl : public StereoSGBM
+class StereoSGBMImpl CV_FINAL : public StereoSGBM
 {
 public:
     StereoSGBMImpl()
@@ -2147,7 +2147,7 @@ public:
                                    _mode );
     }
 
-    void compute( InputArray leftarr, InputArray rightarr, OutputArray disparr )
+    void compute( InputArray leftarr, InputArray rightarr, OutputArray disparr ) CV_OVERRIDE
     {
         CV_INSTRUMENT_REGION()
 
@@ -2172,40 +2172,40 @@ public:
                            StereoMatcher::DISP_SCALE*params.speckleRange, buffer);
     }
 
-    int getMinDisparity() const { return params.minDisparity; }
-    void setMinDisparity(int minDisparity) { params.minDisparity = minDisparity; }
+    int getMinDisparity() const CV_OVERRIDE { return params.minDisparity; }
+    void setMinDisparity(int minDisparity) CV_OVERRIDE { params.minDisparity = minDisparity; }
 
-    int getNumDisparities() const { return params.numDisparities; }
-    void setNumDisparities(int numDisparities) { params.numDisparities = numDisparities; }
+    int getNumDisparities() const CV_OVERRIDE { return params.numDisparities; }
+    void setNumDisparities(int numDisparities) CV_OVERRIDE { params.numDisparities = numDisparities; }
 
-    int getBlockSize() const { return params.SADWindowSize; }
-    void setBlockSize(int blockSize) { params.SADWindowSize = blockSize; }
+    int getBlockSize() const CV_OVERRIDE { return params.SADWindowSize; }
+    void setBlockSize(int blockSize) CV_OVERRIDE { params.SADWindowSize = blockSize; }
 
-    int getSpeckleWindowSize() const { return params.speckleWindowSize; }
-    void setSpeckleWindowSize(int speckleWindowSize) { params.speckleWindowSize = speckleWindowSize; }
+    int getSpeckleWindowSize() const CV_OVERRIDE { return params.speckleWindowSize; }
+    void setSpeckleWindowSize(int speckleWindowSize) CV_OVERRIDE { params.speckleWindowSize = speckleWindowSize; }
 
-    int getSpeckleRange() const { return params.speckleRange; }
-    void setSpeckleRange(int speckleRange) { params.speckleRange = speckleRange; }
+    int getSpeckleRange() const CV_OVERRIDE { return params.speckleRange; }
+    void setSpeckleRange(int speckleRange) CV_OVERRIDE { params.speckleRange = speckleRange; }
 
-    int getDisp12MaxDiff() const { return params.disp12MaxDiff; }
-    void setDisp12MaxDiff(int disp12MaxDiff) { params.disp12MaxDiff = disp12MaxDiff; }
+    int getDisp12MaxDiff() const CV_OVERRIDE { return params.disp12MaxDiff; }
+    void setDisp12MaxDiff(int disp12MaxDiff) CV_OVERRIDE { params.disp12MaxDiff = disp12MaxDiff; }
 
-    int getPreFilterCap() const { return params.preFilterCap; }
-    void setPreFilterCap(int preFilterCap) { params.preFilterCap = preFilterCap; }
+    int getPreFilterCap() const CV_OVERRIDE { return params.preFilterCap; }
+    void setPreFilterCap(int preFilterCap) CV_OVERRIDE { params.preFilterCap = preFilterCap; }
 
-    int getUniquenessRatio() const { return params.uniquenessRatio; }
-    void setUniquenessRatio(int uniquenessRatio) { params.uniquenessRatio = uniquenessRatio; }
+    int getUniquenessRatio() const CV_OVERRIDE { return params.uniquenessRatio; }
+    void setUniquenessRatio(int uniquenessRatio) CV_OVERRIDE { params.uniquenessRatio = uniquenessRatio; }
 
-    int getP1() const { return params.P1; }
-    void setP1(int P1) { params.P1 = P1; }
+    int getP1() const CV_OVERRIDE { return params.P1; }
+    void setP1(int P1) CV_OVERRIDE { params.P1 = P1; }
 
-    int getP2() const { return params.P2; }
-    void setP2(int P2) { params.P2 = P2; }
+    int getP2() const CV_OVERRIDE { return params.P2; }
+    void setP2(int P2) CV_OVERRIDE { params.P2 = P2; }
 
-    int getMode() const { return params.mode; }
-    void setMode(int mode) { params.mode = mode; }
+    int getMode() const CV_OVERRIDE { return params.mode; }
+    void setMode(int mode) CV_OVERRIDE { params.mode = mode; }
 
-    void write(FileStorage& fs) const
+    void write(FileStorage& fs) const CV_OVERRIDE
     {
         writeFormat(fs);
         fs << "name" << name_
@@ -2222,7 +2222,7 @@ public:
         << "mode" << params.mode;
     }
 
-    void read(const FileNode& fn)
+    void read(const FileNode& fn) CV_OVERRIDE
     {
         FileNode n = fn["name"];
         CV_Assert( n.isString() && String(n) == name_ );

modules/core/include/opencv2/core.hpp

@@ -124,7 +124,7 @@ public:
     /*!
      \return the error description and the context as a text string.
     */
-    virtual const char *what() const throw();
+    virtual const char *what() const throw() CV_OVERRIDE;
     void formatMessage();
 
     String msg; ///< the formatted error message

modules/core/include/opencv2/core/cvdef.h

@@ -453,6 +453,30 @@ Cv64suf;
 #endif
 
 
+/****************************************************************************************\
+*                                 C++11 override / final                                 *
+\****************************************************************************************/
+
+#ifndef CV_OVERRIDE
+#  ifdef CV_CXX11
+#    define CV_OVERRIDE override
+#  endif
+#endif
+#ifndef CV_OVERRIDE
+#  define CV_OVERRIDE
+#endif
+
+#ifndef CV_FINAL
+#  ifdef CV_CXX11
+#    define CV_FINAL final
+#  endif
+#endif
+#ifndef CV_FINAL
+#  define CV_FINAL
+#endif
+
+
+
 // Integer types portatibility
 #ifdef OPENCV_STDINT_HEADER
 #include OPENCV_STDINT_HEADER

modules/core/include/opencv2/core/private.hpp

@@ -165,6 +165,8 @@ template <typename T>
 T* allocSingleton(size_t count) { return static_cast<T*>(fastMalloc(sizeof(T) * count)); }
 }
 
+#if 1 // TODO: Remove in OpenCV 4.x
+
 // property implementation macros
 
 #define CV_IMPL_PROPERTY_RO(type, name, member) \
@@ -187,6 +189,8 @@ T* allocSingleton(size_t count) { return static_cast<T*>(fastMalloc(sizeof(T) *
 #define CV_WRAP_SAME_PROPERTY(type, name, internal_obj) CV_WRAP_PROPERTY(type, name, name, internal_obj)
 #define CV_WRAP_SAME_PROPERTY_S(type, name, internal_obj) CV_WRAP_PROPERTY_S(type, name, name, internal_obj)
 
+#endif
+
 /****************************************************************************************\
 *                     Structures and macros for integration with IPP                     *
 \****************************************************************************************/
@@ -233,8 +237,15 @@ T* allocSingleton(size_t count) { return static_cast<T*>(fastMalloc(sizeof(T) *
 #include "ipp.h"
 #endif
 #ifdef HAVE_IPP_IW
+#  if defined(__OPENCV_BUILD) && defined(__GNUC__) && __GNUC__ >= 5
+#  pragma GCC diagnostic push
+#  pragma GCC diagnostic ignored "-Wsuggest-override"
+#  endif
 #include "iw++/iw.hpp"
 #include "iw/iw_ll.h"
+#  if defined(__OPENCV_BUILD) && defined(__GNUC__) && __GNUC__ >= 5
+#  pragma GCC diagnostic pop
+#  endif
 #endif
 
 #if IPP_VERSION_X100 >= 201700

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

@@ -89,12 +89,12 @@ private:
 };
 
 template<typename Y, typename D>
-struct PtrOwnerImpl : PtrOwner
+struct PtrOwnerImpl CV_FINAL : PtrOwner
 {
     PtrOwnerImpl(Y* p, D d) : owned(p), deleter(d)
     {}
 
-    void deleteSelf()
+    void deleteSelf() CV_OVERRIDE
     {
         deleter(owned);
         delete this;

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

@@ -524,7 +524,7 @@ public:
         m_functor(functor)
     { }
 
-    virtual void operator() (const cv::Range& range) const
+    virtual void operator() (const cv::Range& range) const CV_OVERRIDE
     {
         m_functor(range);
     }
@@ -558,7 +558,8 @@ void Mat::forEach_impl(const Functor& operation) {
         virtual ~PixelOperationWrapper(){}
         // ! Overloaded virtual operator
         // convert range call to row call.
-        virtual void operator()(const Range &range) const {
+        virtual void operator()(const Range &range) const CV_OVERRIDE
+        {
             const int DIMS = mat->dims;
             const int COLS = mat->size[DIMS - 1];
             if (DIMS <= 2) {
@@ -711,8 +712,8 @@ public:
     inline void cleanup() { TLSDataContainer::cleanup(); }
 
 private:
-    virtual void* createDataInstance() const {return new T;}                // Wrapper to allocate data by template
-    virtual void  deleteDataInstance(void* pData) const {delete (T*)pData;} // Wrapper to release data by template
+    virtual void* createDataInstance() const CV_OVERRIDE {return new T;}                // Wrapper to allocate data by template
+    virtual void  deleteDataInstance(void* pData) const CV_OVERRIDE {delete (T*)pData;} // Wrapper to release data by template
 
     // Disable TLS copy operations
     TLSData(TLSData &) {}

modules/core/src/batch_distance.cpp

@@ -176,7 +176,7 @@ struct BatchDistInvoker : public ParallelLoopBody
         func = _func;
     }
 
-    void operator()(const Range& range) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         AutoBuffer<int> buf(src2->rows);
         int* bufptr = buf;

modules/core/src/bufferpool.impl.hpp

@@ -17,10 +17,10 @@ public:
     DummyBufferPoolController() { }
     virtual ~DummyBufferPoolController() { }
 
-    virtual size_t getReservedSize() const { return (size_t)-1; }
-    virtual size_t getMaxReservedSize() const { return (size_t)-1; }
-    virtual void setMaxReservedSize(size_t size) { (void)size; }
-    virtual void freeAllReservedBuffers() { }
+    virtual size_t getReservedSize() const CV_OVERRIDE { return (size_t)-1; }
+    virtual size_t getMaxReservedSize() const CV_OVERRIDE { return (size_t)-1; }
+    virtual void setMaxReservedSize(size_t size) CV_OVERRIDE { (void)size; }
+    virtual void freeAllReservedBuffers() CV_OVERRIDE { }
 };
 
 } // namespace

modules/core/src/conjugate_gradient.cpp

@@ -68,15 +68,15 @@ namespace cv
 
 #define SEC_METHOD_ITERATIONS 4
 #define INITIAL_SEC_METHOD_SIGMA 0.1
-    class ConjGradSolverImpl : public ConjGradSolver
+    class ConjGradSolverImpl CV_FINAL : public ConjGradSolver
     {
     public:
-        Ptr<Function> getFunction() const;
-        void setFunction(const Ptr<Function>& f);
-        TermCriteria getTermCriteria() const;
+        Ptr<Function> getFunction() const CV_OVERRIDE;
+        void setFunction(const Ptr<Function>& f) CV_OVERRIDE;
+        TermCriteria getTermCriteria() const CV_OVERRIDE;
         ConjGradSolverImpl();
-        void setTermCriteria(const TermCriteria& termcrit);
-        double minimize(InputOutputArray x);
+        void setTermCriteria(const TermCriteria& termcrit) CV_OVERRIDE;
+        double minimize(InputOutputArray x) CV_OVERRIDE;
     protected:
         Ptr<MinProblemSolver::Function> _Function;
         TermCriteria _termcrit;

modules/core/src/downhill_simplex.cpp

@@ -140,7 +140,7 @@ multiple lines in three dimensions as not all lines intersect in three dimension
 namespace cv
 {
 
-class DownhillSolverImpl : public DownhillSolver
+class DownhillSolverImpl CV_FINAL : public DownhillSolver
 {
 public:
     DownhillSolverImpl()
@@ -149,8 +149,8 @@ public:
         _step=Mat_<double>();
     }
 
-    void getInitStep(OutputArray step) const { _step.copyTo(step); }
-    void setInitStep(InputArray step)
+    void getInitStep(OutputArray step) const CV_OVERRIDE { _step.copyTo(step); }
+    void setInitStep(InputArray step) CV_OVERRIDE
     {
         // set dimensionality and make a deep copy of step
         Mat m = step.getMat();
@@ -161,13 +161,13 @@ public:
             transpose(m, _step);
     }
 
-    Ptr<MinProblemSolver::Function> getFunction() const { return _Function; }
+    Ptr<MinProblemSolver::Function> getFunction() const CV_OVERRIDE { return _Function; }
 
-    void setFunction(const Ptr<Function>& f) { _Function=f; }
+    void setFunction(const Ptr<Function>& f) CV_OVERRIDE { _Function=f; }
 
-    TermCriteria getTermCriteria() const { return _termcrit; }
+    TermCriteria getTermCriteria() const CV_OVERRIDE { return _termcrit; }
 
-    void setTermCriteria( const TermCriteria& termcrit )
+    void setTermCriteria( const TermCriteria& termcrit ) CV_OVERRIDE
     {
         CV_Assert( termcrit.type == (TermCriteria::MAX_ITER + TermCriteria::EPS) &&
                    termcrit.epsilon > 0 &&
@@ -175,7 +175,7 @@ public:
         _termcrit=termcrit;
     }
 
-    double minimize( InputOutputArray x_ )
+    double minimize( InputOutputArray x_ ) CV_OVERRIDE
     {
         dprintf(("hi from minimize\n"));
         CV_Assert( !_Function.empty() );

modules/core/src/dxt.cpp

@@ -1562,7 +1562,7 @@ public:
         *ok = true;
     }
 
-    virtual void operator()(const Range& range) const
+    virtual void operator()(const Range& range) const CV_OVERRIDE
     {
         IppStatus status;
         Ipp8u* pBuffer = 0;
@@ -1643,7 +1643,7 @@ public:
         *ok = true;
     }
 
-    virtual void operator()(const Range& range) const
+    virtual void operator()(const Range& range) const CV_OVERRIDE
     {
         IppStatus status;
         Ipp8u* pBuffer = 0;
@@ -2607,7 +2607,7 @@ inline DftDims determineDims(int rows, int cols, bool isRowWise, bool isContinuo
     return InvalidDim;
 }
 
-class OcvDftImpl : public hal::DFT2D
+class OcvDftImpl CV_FINAL : public hal::DFT2D
 {
 protected:
     Ptr<hal::DFT1D> contextA;
@@ -2779,7 +2779,7 @@ public:
         }
     }
 
-    void apply(const uchar * src, size_t src_step, uchar * dst, size_t dst_step)
+    void apply(const uchar * src, size_t src_step, uchar * dst, size_t dst_step) CV_OVERRIDE
     {
 #if defined USE_IPP_DFT
         if (useIpp)
@@ -3039,7 +3039,7 @@ protected:
     }
 };
 
-class OcvDftBasicImpl : public hal::DFT1D
+class OcvDftBasicImpl CV_FINAL : public hal::DFT1D
 {
 public:
     OcvDftOptions opt;
@@ -3194,7 +3194,7 @@ public:
         }
     }
 
-    void apply(const uchar *src, uchar *dst)
+    void apply(const uchar *src, uchar *dst) CV_OVERRIDE
     {
         opt.dft_func(opt, src, dst);
     }
@@ -3214,7 +3214,7 @@ struct ReplacementDFT1D : public hal::DFT1D
         isInitialized = (res == CV_HAL_ERROR_OK);
         return isInitialized;
     }
-    void apply(const uchar *src, uchar *dst)
+    void apply(const uchar *src, uchar *dst) CV_OVERRIDE
     {
         if (isInitialized)
         {
@@ -3244,7 +3244,7 @@ struct ReplacementDFT2D : public hal::DFT2D
         isInitialized = (res == CV_HAL_ERROR_OK);
         return isInitialized;
     }
-    void apply(const uchar *src, size_t src_step, uchar *dst, size_t dst_step)
+    void apply(const uchar *src, size_t src_step, uchar *dst, size_t dst_step) CV_OVERRIDE
     {
         if (isInitialized)
         {
@@ -3809,7 +3809,7 @@ public:
         *ok = true;
     }
 
-    virtual void operator()(const Range& range) const
+    virtual void operator()(const Range& range) const CV_OVERRIDE
     {
         if(*ok == false)
             return;
@@ -4048,7 +4048,7 @@ static bool ippi_DCT_32f(const uchar * src, size_t src_step, uchar * dst, size_t
 
 namespace cv {
 
-class OcvDctImpl : public hal::DCT2D
+class OcvDctImpl CV_FINAL : public hal::DCT2D
 {
 public:
     OcvDftOptions opt;
@@ -4100,7 +4100,7 @@ public:
             end_stage = 1;
         }
     }
-    void apply(const uchar *src, size_t src_step, uchar *dst, size_t dst_step)
+    void apply(const uchar *src, size_t src_step, uchar *dst, size_t dst_step) CV_OVERRIDE
     {
         CV_IPP_RUN(IPP_VERSION_X100 >= 700 && depth == CV_32F, ippi_DCT_32f(src, src_step, dst, dst_step, width, height, isInverse, isRowTransform))
 
@@ -4196,7 +4196,7 @@ struct ReplacementDCT2D : public hal::DCT2D
         isInitialized = (res == CV_HAL_ERROR_OK);
         return isInitialized;
     }
-    void apply(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step)
+    void apply(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) CV_OVERRIDE
     {
         if (isInitialized)
         {

modules/core/src/kmeans.cpp

@@ -65,7 +65,7 @@ public:
         tdist2(tdist2_), data(data_), dist(dist_), ci(ci_)
     { }
 
-    void operator()( const cv::Range& range ) const
+    void operator()( const cv::Range& range ) const CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         const int begin = range.start;
@@ -171,7 +171,7 @@ public:
     {
     }
 
-    void operator()( const Range& range ) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         const int begin = range.start;

modules/core/src/lut.cpp

@@ -328,7 +328,7 @@ public:
         *ok = (func != NULL);
     }
 
-    void operator()( const cv::Range& range ) const
+    void operator()( const cv::Range& range ) const CV_OVERRIDE
     {
         CV_DbgAssert(*ok);
 

modules/core/src/matrix.cpp

@@ -123,11 +123,11 @@ BufferPoolController* MatAllocator::getBufferPoolController(const char* id) cons
     return &dummy;
 }
 
-class StdMatAllocator : public MatAllocator
+class StdMatAllocator CV_FINAL : public MatAllocator
 {
 public:
     UMatData* allocate(int dims, const int* sizes, int type,
-                       void* data0, size_t* step, int /*flags*/, UMatUsageFlags /*usageFlags*/) const
+                       void* data0, size_t* step, int /*flags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
     {
         size_t total = CV_ELEM_SIZE(type);
         for( int i = dims-1; i >= 0; i-- )
@@ -154,13 +154,13 @@ public:
         return u;
     }
 
-    bool allocate(UMatData* u, int /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const
+    bool allocate(UMatData* u, int /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
     {
         if(!u) return false;
         return true;
     }
 
-    void deallocate(UMatData* u) const
+    void deallocate(UMatData* u) const CV_OVERRIDE
     {
         if(!u)
             return;

modules/core/src/matrix_expressions.cpp

@@ -14,53 +14,53 @@
 namespace cv
 {
 
-class MatOp_Identity : public MatOp
+class MatOp_Identity CV_FINAL : public MatOp
 {
 public:
     MatOp_Identity() {}
     virtual ~MatOp_Identity() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return true; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return true; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, const Mat& m);
 };
 
 static MatOp_Identity g_MatOp_Identity;
 
-class MatOp_AddEx : public MatOp
+class MatOp_AddEx CV_FINAL : public MatOp
 {
 public:
     MatOp_AddEx() {}
     virtual ~MatOp_AddEx() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return true; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return true; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
-    void add(const MatExpr& e1, const Scalar& s, MatExpr& res) const;
-    void subtract(const Scalar& s, const MatExpr& expr, MatExpr& res) const;
-    void multiply(const MatExpr& e1, double s, MatExpr& res) const;
-    void divide(double s, const MatExpr& e, MatExpr& res) const;
+    void add(const MatExpr& e1, const Scalar& s, MatExpr& res) const CV_OVERRIDE;
+    void subtract(const Scalar& s, const MatExpr& expr, MatExpr& res) const CV_OVERRIDE;
+    void multiply(const MatExpr& e1, double s, MatExpr& res) const CV_OVERRIDE;
+    void divide(double s, const MatExpr& e, MatExpr& res) const CV_OVERRIDE;
 
-    void transpose(const MatExpr& e1, MatExpr& res) const;
-    void abs(const MatExpr& expr, MatExpr& res) const;
+    void transpose(const MatExpr& e1, MatExpr& res) const CV_OVERRIDE;
+    void abs(const MatExpr& expr, MatExpr& res) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, const Mat& a, const Mat& b, double alpha, double beta, const Scalar& s=Scalar());
 };
 
 static MatOp_AddEx g_MatOp_AddEx;
 
-class MatOp_Bin : public MatOp
+class MatOp_Bin CV_FINAL : public MatOp
 {
 public:
     MatOp_Bin() {}
     virtual ~MatOp_Bin() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return true; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return true; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
-    void multiply(const MatExpr& e1, double s, MatExpr& res) const;
-    void divide(double s, const MatExpr& e, MatExpr& res) const;
+    void multiply(const MatExpr& e1, double s, MatExpr& res) const CV_OVERRIDE;
+    void divide(double s, const MatExpr& e, MatExpr& res) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, char op, const Mat& a, const Mat& b, double scale=1);
     static void makeExpr(MatExpr& res, char op, const Mat& a, const Scalar& s);
@@ -68,14 +68,14 @@ public:
 
 static MatOp_Bin g_MatOp_Bin;
 
-class MatOp_Cmp : public MatOp
+class MatOp_Cmp CV_FINAL : public MatOp
 {
 public:
     MatOp_Cmp() {}
     virtual ~MatOp_Cmp() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return true; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return true; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, int cmpop, const Mat& a, const Mat& b);
     static void makeExpr(MatExpr& res, int cmpop, const Mat& a, double alpha);
@@ -83,20 +83,20 @@ public:
 
 static MatOp_Cmp g_MatOp_Cmp;
 
-class MatOp_GEMM : public MatOp
+class MatOp_GEMM CV_FINAL : public MatOp
 {
 public:
     MatOp_GEMM() {}
     virtual ~MatOp_GEMM() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return false; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return false; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
-    void add(const MatExpr& e1, const MatExpr& e2, MatExpr& res) const;
-    void subtract(const MatExpr& e1, const MatExpr& e2, MatExpr& res) const;
-    void multiply(const MatExpr& e, double s, MatExpr& res) const;
+    void add(const MatExpr& e1, const MatExpr& e2, MatExpr& res) const CV_OVERRIDE;
+    void subtract(const MatExpr& e1, const MatExpr& e2, MatExpr& res) const CV_OVERRIDE;
+    void multiply(const MatExpr& e, double s, MatExpr& res) const CV_OVERRIDE;
 
-    void transpose(const MatExpr& expr, MatExpr& res) const;
+    void transpose(const MatExpr& expr, MatExpr& res) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, int flags, const Mat& a, const Mat& b,
                          double alpha=1, const Mat& c=Mat(), double beta=1);
@@ -104,63 +104,63 @@ public:
 
 static MatOp_GEMM g_MatOp_GEMM;
 
-class MatOp_Invert : public MatOp
+class MatOp_Invert CV_FINAL : public MatOp
 {
 public:
     MatOp_Invert() {}
     virtual ~MatOp_Invert() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return false; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return false; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
-    void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
+    void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, int method, const Mat& m);
 };
 
 static MatOp_Invert g_MatOp_Invert;
 
-class MatOp_T : public MatOp
+class MatOp_T CV_FINAL : public MatOp
 {
 public:
     MatOp_T() {}
     virtual ~MatOp_T() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return false; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return false; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
-    void multiply(const MatExpr& e1, double s, MatExpr& res) const;
-    void transpose(const MatExpr& expr, MatExpr& res) const;
+    void multiply(const MatExpr& e1, double s, MatExpr& res) const CV_OVERRIDE;
+    void transpose(const MatExpr& expr, MatExpr& res) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, const Mat& a, double alpha=1);
 };
 
 static MatOp_T g_MatOp_T;
 
-class MatOp_Solve : public MatOp
+class MatOp_Solve CV_FINAL : public MatOp
 {
 public:
     MatOp_Solve() {}
     virtual ~MatOp_Solve() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return false; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return false; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, int method, const Mat& a, const Mat& b);
 };
 
 static MatOp_Solve g_MatOp_Solve;
 
-class MatOp_Initializer : public MatOp
+class MatOp_Initializer CV_FINAL : public MatOp
 {
 public:
     MatOp_Initializer() {}
     virtual ~MatOp_Initializer() {}
 
-    bool elementWise(const MatExpr& /*expr*/) const { return false; }
-    void assign(const MatExpr& expr, Mat& m, int type=-1) const;
+    bool elementWise(const MatExpr& /*expr*/) const CV_OVERRIDE { return false; }
+    void assign(const MatExpr& expr, Mat& m, int type=-1) const CV_OVERRIDE;
 
-    void multiply(const MatExpr& e, double s, MatExpr& res) const;
+    void multiply(const MatExpr& e, double s, MatExpr& res) const CV_OVERRIDE;
 
     static void makeExpr(MatExpr& res, int method, Size sz, int type, double alpha=1);
     static void makeExpr(MatExpr& res, int method, int ndims, const int* sizes, int type, double alpha=1);

modules/core/src/ocl.cpp

@@ -4178,7 +4178,7 @@ public:
         CV_Assert(reservedEntries_.empty());
     }
 public:
-    virtual T allocate(size_t size)
+    virtual T allocate(size_t size) CV_OVERRIDE
     {
         AutoLock locker(mutex_);
         BufferEntry entry;
@@ -4193,7 +4193,7 @@ public:
         }
         return entry.clBuffer_;
     }
-    virtual void release(T buffer)
+    virtual void release(T buffer) CV_OVERRIDE
     {
         AutoLock locker(mutex_);
         BufferEntry entry;
@@ -4210,9 +4210,9 @@ public:
         }
     }
 
-    virtual size_t getReservedSize() const { return currentReservedSize; }
-    virtual size_t getMaxReservedSize() const { return maxReservedSize; }
-    virtual void setMaxReservedSize(size_t size)
+    virtual size_t getReservedSize() const CV_OVERRIDE { return currentReservedSize; }
+    virtual size_t getMaxReservedSize() const CV_OVERRIDE { return maxReservedSize; }
+    virtual void setMaxReservedSize(size_t size) CV_OVERRIDE
     {
         AutoLock locker(mutex_);
         size_t oldMaxReservedSize = maxReservedSize;
@@ -4236,7 +4236,7 @@ public:
             _checkSizeOfReservedEntries();
         }
     }
-    virtual void freeAllReservedBuffers()
+    virtual void freeAllReservedBuffers() CV_OVERRIDE
     {
         AutoLock locker(mutex_);
         typename std::list<BufferEntry>::const_iterator i = reservedEntries_.begin();
@@ -4257,7 +4257,7 @@ struct CLBufferEntry
     CLBufferEntry() : clBuffer_((cl_mem)NULL), capacity_(0) { }
 };
 
-class OpenCLBufferPoolImpl : public OpenCLBufferPoolBaseImpl<OpenCLBufferPoolImpl, CLBufferEntry, cl_mem>
+class OpenCLBufferPoolImpl CV_FINAL : public OpenCLBufferPoolBaseImpl<OpenCLBufferPoolImpl, CLBufferEntry, cl_mem>
 {
 public:
     typedef struct CLBufferEntry BufferEntry;
@@ -4303,7 +4303,7 @@ struct CLSVMBufferEntry
     size_t capacity_;
     CLSVMBufferEntry() : clBuffer_(NULL), capacity_(0) { }
 };
-class OpenCLSVMBufferPoolImpl : public OpenCLBufferPoolBaseImpl<OpenCLSVMBufferPoolImpl, CLSVMBufferEntry, void*>
+class OpenCLSVMBufferPoolImpl CV_FINAL : public OpenCLBufferPoolBaseImpl<OpenCLSVMBufferPoolImpl, CLSVMBufferEntry, void*>
 {
 public:
     typedef struct CLSVMBufferEntry BufferEntry;
@@ -4465,7 +4465,7 @@ private:
 #define CV_OPENCL_DATA_PTR_ALIGNMENT 16
 #endif
 
-class OpenCLAllocator : public MatAllocator
+class OpenCLAllocator CV_FINAL : public MatAllocator
 {
     mutable OpenCLBufferPoolImpl bufferPool;
     mutable OpenCLBufferPoolImpl bufferPoolHostPtr;
@@ -4525,7 +4525,7 @@ public:
     }
 
     UMatData* allocate(int dims, const int* sizes, int type,
-                       void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const
+                       void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const CV_OVERRIDE
     {
         if(!useOpenCL())
             return defaultAllocate(dims, sizes, type, data, step, flags, usageFlags);
@@ -4589,7 +4589,7 @@ public:
         return u;
     }
 
-    bool allocate(UMatData* u, int accessFlags, UMatUsageFlags usageFlags) const
+    bool allocate(UMatData* u, int accessFlags, UMatUsageFlags usageFlags) const CV_OVERRIDE
     {
         if(!u)
             return false;
@@ -4721,7 +4721,7 @@ public:
         }
     }*/
 
-    void deallocate(UMatData* u) const
+    void deallocate(UMatData* u) const CV_OVERRIDE
     {
         if(!u)
             return;
@@ -4905,7 +4905,7 @@ public:
     }
 
     // synchronized call (external UMatDataAutoLock, see UMat::getMat)
-    void map(UMatData* u, int accessFlags) const
+    void map(UMatData* u, int accessFlags) const CV_OVERRIDE
     {
         CV_Assert(u && u->handle);
 
@@ -4988,7 +4988,7 @@ public:
         }
     }
 
-    void unmap(UMatData* u) const
+    void unmap(UMatData* u) const CV_OVERRIDE
     {
         if(!u)
             return;
@@ -5133,7 +5133,7 @@ public:
 
     void download(UMatData* u, void* dstptr, int dims, const size_t sz[],
                   const size_t srcofs[], const size_t srcstep[],
-                  const size_t dststep[]) const
+                  const size_t dststep[]) const CV_OVERRIDE
     {
         if(!u)
             return;
@@ -5256,7 +5256,7 @@ public:
 
     void upload(UMatData* u, const void* srcptr, int dims, const size_t sz[],
                 const size_t dstofs[], const size_t dststep[],
-                const size_t srcstep[]) const
+                const size_t srcstep[]) const CV_OVERRIDE
     {
         if(!u)
             return;
@@ -5408,7 +5408,7 @@ public:
 
     void copy(UMatData* src, UMatData* dst, int dims, const size_t sz[],
               const size_t srcofs[], const size_t srcstep[],
-              const size_t dstofs[], const size_t dststep[], bool _sync) const
+              const size_t dstofs[], const size_t dststep[], bool _sync) const CV_OVERRIDE
     {
         if(!src || !dst)
             return;
@@ -5596,7 +5596,7 @@ public:
         }
     }
 
-    BufferPoolController* getBufferPoolController(const char* id) const {
+    BufferPoolController* getBufferPoolController(const char* id) const CV_OVERRIDE {
 #ifdef HAVE_OPENCL_SVM
         if ((svm::checkForceSVMUmatUsage() && (id == NULL || strcmp(id, "OCL") == 0)) || (id != NULL && strcmp(id, "SVM") == 0))
         {

modules/core/src/out.cpp

@@ -45,7 +45,7 @@
 
 namespace cv
 {
-    class FormattedImpl : public Formatted
+    class FormattedImpl CV_FINAL : public Formatted
     {
         enum { STATE_PROLOGUE, STATE_EPILOGUE, STATE_INTERLUDE,
                STATE_ROW_OPEN, STATE_ROW_CLOSE, STATE_CN_OPEN, STATE_CN_CLOSE, STATE_VALUE, STATE_FINISHED,
@@ -119,12 +119,12 @@ namespace cv
             }
         }
 
-        void reset()
+        void reset() CV_OVERRIDE
         {
             state = STATE_PROLOGUE;
         }
 
-        const char* next()
+        const char* next() CV_OVERRIDE
         {
             switch(state)
             {
@@ -258,17 +258,17 @@ namespace cv
     public:
         FormatterBase() : prec32f(8), prec64f(16), multiline(true) {}
 
-        void set32fPrecision(int p)
+        void set32fPrecision(int p) CV_OVERRIDE
         {
             prec32f = p;
         }
 
-        void set64fPrecision(int p)
+        void set64fPrecision(int p) CV_OVERRIDE
         {
             prec64f = p;
         }
 
-        void setMultiline(bool ml)
+        void setMultiline(bool ml) CV_OVERRIDE
         {
             multiline = ml;
         }
@@ -279,11 +279,11 @@ namespace cv
         int multiline;
     };
 
-    class DefaultFormatter : public FormatterBase
+    class DefaultFormatter CV_FINAL : public FormatterBase
     {
     public:
 
-        Ptr<Formatted> format(const Mat& mtx) const
+        Ptr<Formatted> format(const Mat& mtx) const CV_OVERRIDE
         {
             char braces[5] = {'\0', '\0', ';', '\0', '\0'};
             return makePtr<FormattedImpl>("[", "]", mtx, &*braces,
@@ -291,11 +291,11 @@ namespace cv
         }
     };
 
-    class MatlabFormatter : public FormatterBase
+    class MatlabFormatter CV_FINAL : public FormatterBase
     {
     public:
 
-        Ptr<Formatted> format(const Mat& mtx) const
+        Ptr<Formatted> format(const Mat& mtx) const CV_OVERRIDE
         {
             char braces[5] = {'\0', '\0', ';', '\0', '\0'};
             return makePtr<FormattedImpl>("", "", mtx, &*braces,
@@ -303,11 +303,11 @@ namespace cv
         }
     };
 
-    class PythonFormatter : public FormatterBase
+    class PythonFormatter CV_FINAL : public FormatterBase
     {
     public:
 
-        Ptr<Formatted> format(const Mat& mtx) const
+        Ptr<Formatted> format(const Mat& mtx) const CV_OVERRIDE
         {
             char braces[5] = {'[', ']', ',', '[', ']'};
             if (mtx.cols == 1)
@@ -317,11 +317,11 @@ namespace cv
         }
     };
 
-    class NumpyFormatter : public FormatterBase
+    class NumpyFormatter CV_FINAL : public FormatterBase
     {
     public:
 
-        Ptr<Formatted> format(const Mat& mtx) const
+        Ptr<Formatted> format(const Mat& mtx) const CV_OVERRIDE
         {
             static const char* numpyTypes[] =
             {
@@ -336,11 +336,11 @@ namespace cv
         }
     };
 
-    class CSVFormatter : public FormatterBase
+    class CSVFormatter CV_FINAL : public FormatterBase
     {
     public:
 
-        Ptr<Formatted> format(const Mat& mtx) const
+        Ptr<Formatted> format(const Mat& mtx) const CV_OVERRIDE
         {
             char braces[5] = {'\0', '\0', '\0', '\0', '\0'};
             return makePtr<FormattedImpl>(String(),
@@ -349,11 +349,11 @@ namespace cv
         }
     };
 
-    class CFormatter : public FormatterBase
+    class CFormatter CV_FINAL : public FormatterBase
     {
     public:
 
-        Ptr<Formatted> format(const Mat& mtx) const
+        Ptr<Formatted> format(const Mat& mtx) const CV_OVERRIDE
         {
             char braces[5] = {'\0', '\0', ',', '\0', '\0'};
             return makePtr<FormattedImpl>("{", "}", mtx, &*braces,

modules/core/src/parallel.cpp

@@ -238,7 +238,7 @@ namespace
         ~ParallelLoopBodyWrapper()
         {
         }
-        void operator()(const cv::Range& sr) const
+        void operator()(const cv::Range& sr) const CV_OVERRIDE
         {
 #ifdef OPENCV_TRACE
             // TODO CV_TRACE_NS::details::setCurrentRegion(rootRegion);

modules/core/src/trace.cpp

@@ -726,7 +726,7 @@ void TraceManagerThreadLocal::dumpStack(std::ostream& out, bool onlyFunctions) c
     out << ss.str();
 }
 
-class AsyncTraceStorage : public TraceStorage
+class AsyncTraceStorage CV_FINAL : public TraceStorage
 {
     mutable std::ofstream out;
 public:
@@ -744,7 +744,7 @@ public:
         out.close();
     }
 
-    bool put(const TraceMessage& msg) const
+    bool put(const TraceMessage& msg) const CV_OVERRIDE
     {
         if (msg.hasError)
             return false;
@@ -754,7 +754,7 @@ public:
     }
 };
 
-class SyncTraceStorage : public TraceStorage
+class SyncTraceStorage CV_FINAL : public TraceStorage
 {
     mutable std::ofstream out;
     mutable cv::Mutex mutex;
@@ -774,7 +774,7 @@ public:
         out.close();
     }
 
-    bool put(const TraceMessage& msg) const
+    bool put(const TraceMessage& msg) const CV_OVERRIDE
     {
         if (msg.hasError)
             return false;

modules/cudalegacy/src/calib3d.cpp

@@ -160,7 +160,7 @@ namespace
                   num_points(num_points_), subset_size(subset_size_), rot_matrices(rot_matrices_),
                   transl_vectors(transl_vectors_) {}
 
-        void operator()(const Range& range) const
+        void operator()(const Range& range) const CV_OVERRIDE
         {
             // Input data for generation of the current hypothesis
             std::vector<int> subset_indices(subset_size);

modules/dnn/CMakeLists.txt

@@ -87,6 +87,11 @@ if(WITH_INF_ENGINE AND HAVE_INF_ENGINE)
 endif()
 
 ocv_module_include_directories(${include_dirs})
+if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
+  ocv_append_source_files_cxx_compiler_options(fw_srcs "-Wno-suggest-override")  # GCC
+elseif(CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
+  ocv_append_source_files_cxx_compiler_options(fw_srcs "-Wno-inconsistent-missing-override")  # Clang
+endif()
 ocv_glob_module_sources(${sources_options} SOURCES ${fw_srcs})
 ocv_create_module(${libs})
 ocv_add_samples()

modules/dnn/include/opencv2/dnn/all_layers.hpp

@@ -152,8 +152,8 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
          * (i.e. @f$ x_{t}^{stream} @f$ is stored inside @p input[0][stream, ...]).
         */
 
-        int inputNameToIndex(String inputName);
-        int outputNameToIndex(const String& outputName);
+        int inputNameToIndex(String inputName) CV_OVERRIDE;
+        int outputNameToIndex(const String& outputName) CV_OVERRIDE;
     };
 
     /** @brief Classical recurrent layer

modules/dnn/src/caffe/caffe_io.hpp

@@ -91,7 +91,15 @@
 #define __OPENCV_DNN_CAFFE_IO_HPP__
 #ifdef HAVE_PROTOBUF
 
+#if defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wsuggest-override"
+#endif
 #include "opencv-caffe.pb.h"
+#if defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic pop
+#endif
+
 namespace caffe { using namespace opencv_caffe; } // avoid massive renames from caffe proto package
 
 namespace cv {

modules/dnn/src/dnn.cpp

@@ -283,12 +283,12 @@ public:
     ~OpenCLBackendWrapper() {}
 
     // Copies data from device to a host memory.
-    virtual void copyToHost()
+    virtual void copyToHost() CV_OVERRIDE
     {
         umat.copyTo(*host);
     }
 
-    virtual void setHostDirty()
+    virtual void setHostDirty() CV_OVERRIDE
     {
         hostDirty = true;
     };
@@ -395,11 +395,11 @@ struct LayerData
 //fake layer containing network input blobs
 struct DataLayer : public Layer
 {
-    void finalize(const std::vector<Mat*>&, std::vector<Mat>&) {}
-    void forward(std::vector<Mat*>&, std::vector<Mat>&, std::vector<Mat> &) {}
-    void forward(InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals) {}
+    void finalize(const std::vector<Mat*>&, std::vector<Mat>&) CV_OVERRIDE {}
+    void forward(std::vector<Mat*>&, std::vector<Mat>&, std::vector<Mat> &) CV_OVERRIDE {}
+    void forward(InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals) CV_OVERRIDE {}
 
-    int outputNameToIndex(const String& tgtName)
+    int outputNameToIndex(const String& tgtName) CV_OVERRIDE
     {
         int idx = (int)(std::find(outNames.begin(), outNames.end(), tgtName) - outNames.begin());
         return (idx < (int)outNames.size()) ? idx : -1;
@@ -413,7 +413,7 @@ struct DataLayer : public Layer
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == requiredOutputs);
         outputs.assign(inputs.begin(), inputs.end());

modules/dnn/src/layers/batch_norm_layer.cpp

@@ -23,7 +23,7 @@ namespace cv
 namespace dnn
 {
 
-class BatchNormLayerImpl : public BatchNormLayer
+class BatchNormLayerImpl CV_FINAL : public BatchNormLayer
 {
 public:
     Mat weights_, bias_;
@@ -90,7 +90,7 @@ public:
         }
     }
 
-    void getScaleShift(Mat& scale, Mat& shift) const
+    void getScaleShift(Mat& scale, Mat& shift) const CV_OVERRIDE
     {
         scale = weights_;
         shift = bias_;
@@ -99,7 +99,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         if (!useGlobalStats && inputs[0][0] != 1)
             CV_Error(Error::StsNotImplemented, "Batch normalization in training mode with batch size > 1");
@@ -107,7 +107,7 @@ public:
         return true;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() ||
@@ -176,7 +176,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -188,7 +188,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -219,7 +219,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node)
+    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node) CV_OVERRIDE
     {
         switch (node->backendId)
         {
@@ -251,7 +251,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Buffer<float> input = halideBuffer(inputs[0]);
@@ -278,7 +278,7 @@ public:
     }
 #endif  // HAVE_HALIDE
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -296,7 +296,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
 

modules/dnn/src/layers/blank_layer.cpp

@@ -45,7 +45,7 @@ namespace cv
 {
 namespace dnn
 {
-class BlankLayerImpl : public BlankLayer
+class BlankLayerImpl CV_FINAL : public BlankLayer
 {
 public:
     BlankLayerImpl(const LayerParams& params)
@@ -56,7 +56,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         Layer::getMemoryShapes(inputs, requiredOutputs, outputs, internals);
         return true;
@@ -83,7 +83,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -95,7 +95,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/concat_layer.cpp

@@ -54,7 +54,7 @@ namespace cv
 namespace dnn
 {
 
-class ConcatLayerImpl : public ConcatLayer
+class ConcatLayerImpl CV_FINAL : public ConcatLayer
 {
 public:
     ConcatLayerImpl(const LayerParams& params)
@@ -67,7 +67,7 @@ public:
     virtual bool getMemoryShapes(const std::vector<MatShape> &inputs,
                                  const int requiredOutputs,
                                  std::vector<MatShape> &outputs,
-                                 std::vector<MatShape> &internals) const
+                                 std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() > 0);
         outputs.resize(1, inputs[0]);
@@ -101,7 +101,7 @@ public:
         return false;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() && axis == 1 && !padding ||  // By channels
@@ -157,7 +157,7 @@ public:
 
         ChannelConcatInvoker()  : inputs(0), output(0), nstripes(0) {}
 
-        void operator()(const Range& r) const
+        void operator()(const Range& r) const CV_OVERRIDE
         {
             size_t planeSize = (size_t)output->size[2]*output->size[3];
             size_t nch = chptrs.size();
@@ -230,7 +230,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -242,7 +242,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -278,7 +278,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         std::vector<Halide::Buffer<> > inputBuffers = halideBuffers(input);
@@ -301,7 +301,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >& inputs)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >& inputs) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);

modules/dnn/src/layers/convolution_layer.cpp

@@ -79,14 +79,14 @@ public:
                   adjustPad.height < stride.height);
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
     }
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         CV_Assert(inputs.size() > 0);
 
@@ -123,7 +123,7 @@ public:
     virtual void applyHalideScheduler(Ptr<BackendNode>& node,
                                       const std::vector<Mat*> &inputs,
                                       const std::vector<Mat> &outputs,
-                                      int targetId) const
+                                      int targetId) const CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         if (targetId != DNN_TARGET_CPU)
@@ -165,7 +165,7 @@ public:
 #define IS_POWER_LAYER(layer) \
             (!layer.empty() && !layer->type.compare("Power"))
 //TODO: simultaneously convolution and bias addition for cache optimization
-class ConvolutionLayerImpl : public BaseConvolutionLayerImpl
+class ConvolutionLayerImpl CV_FINAL : public BaseConvolutionLayerImpl
 {
 public:
     enum { VEC_ALIGN = 8, DFT_TYPE = CV_32F };
@@ -194,7 +194,7 @@ public:
 #endif
     }
 
-    MatShape computeColRowShape(const MatShape &inpShape, const MatShape &outShape) const
+    MatShape computeColRowShape(const MatShape &inpShape, const MatShape &outShape) const CV_OVERRIDE
     {
         Size out(outShape[3], outShape[2]);
         int inpGroupCn = blobs[0].size[1];
@@ -205,7 +205,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(blobs.size() != 0);
         CV_Assert(!hasBias() || blobs[1].total() == (size_t)blobs[0].size[0]);
@@ -239,7 +239,7 @@ public:
         return false;
     }
 
-    virtual void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    virtual void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         BaseConvolutionLayerImpl::finalize(inputs, outputs);
 
@@ -278,7 +278,7 @@ public:
 #endif
     }
 
-    bool setActivation(const Ptr<ActivationLayer>& layer)
+    bool setActivation(const Ptr<ActivationLayer>& layer) CV_OVERRIDE
     {
         activ = layer;
         if (activ.empty())
@@ -312,7 +312,7 @@ public:
         return !activ.empty();
     }
 
-    virtual bool tryFuse(Ptr<Layer>& top)
+    virtual bool tryFuse(Ptr<Layer>& top) CV_OVERRIDE
     {
         Mat w, b;
         top->getScaleShift(w, b);
@@ -357,7 +357,7 @@ public:
         biasvec[outCn] = biasvec[outCn+1] = biasvec[outCn-1];
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Buffer<float> inputBuffer = halideBuffer(inputs[0]);
@@ -405,7 +405,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);
@@ -517,7 +517,7 @@ public:
             parallel_for_(Range(0, nstripes), p, nstripes);
         }
 
-        virtual void operator ()(const Range &r0) const
+        virtual void operator ()(const Range &r0) const CV_OVERRIDE
         {
             const int valign = ConvolutionLayerImpl::VEC_ALIGN;
             int ngroups = ngroups_, batchSize = input_->size[0]*ngroups;
@@ -937,7 +937,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -949,7 +949,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -993,7 +993,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == outputs.size());
 
@@ -1007,7 +1007,7 @@ public:
     }
 };
 
-class DeConvolutionLayerImpl : public BaseConvolutionLayerImpl
+class DeConvolutionLayerImpl CV_FINAL : public BaseConvolutionLayerImpl
 {
 public:
     Mat weightsMat, biasesMat;
@@ -1016,7 +1016,7 @@ public:
 
     DeConvolutionLayerImpl(const LayerParams& params) : BaseConvolutionLayerImpl(params) {}
 
-    MatShape computeColRowShape(const MatShape &inpShape, const MatShape &outShape) const
+    MatShape computeColRowShape(const MatShape &inpShape, const MatShape &outShape) const CV_OVERRIDE
     {
         int inpCn = inpShape[1];
         int inpH = inpShape[2];
@@ -1031,7 +1031,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(!hasBias() || blobs[1].total() == (size_t)numOutput);
         CV_Assert(inputs.size() != 0);
@@ -1080,7 +1080,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         BaseConvolutionLayerImpl::finalize(inputs, outputs);
         getConvPoolPaddings(Size(outputs[0].size[3], outputs[0].size[2]),
@@ -1102,7 +1102,7 @@ public:
             useAVX512 = CV_CPU_HAS_SUPPORT_AVX512_SKX;
         }
 
-        void operator()(const Range& range_) const
+        void operator()(const Range& range_) const CV_OVERRIDE
         {
             int stripeSize = (int)alignSize((b_->cols + nstripes_ - 1)/nstripes_, 16);
             Range range(range_.start*stripeSize, std::min(range_.end*stripeSize, b_->cols));
@@ -1277,7 +1277,7 @@ public:
             parallel_for_(Range(0, nstripes), t, nstripes);
         }
 
-        virtual void operator ()(const Range &r) const
+        virtual void operator ()(const Range &r) const CV_OVERRIDE
         {
             const float* data_col_ = data_col;
             float* data_im_ = data_im;
@@ -1423,7 +1423,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -1435,7 +1435,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -1489,7 +1489,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Buffer<float> inputBuffer = halideBuffer(inputs[0]);
@@ -1543,7 +1543,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == outputs.size());
 

modules/dnn/src/layers/crop_layer.cpp

@@ -48,7 +48,7 @@ namespace cv
 namespace dnn
 {
 
-class CropLayerImpl : public CropLayer
+class CropLayerImpl CV_FINAL : public CropLayer
 {
 public:
     CropLayerImpl(const LayerParams& params)
@@ -67,7 +67,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 2);
 
@@ -83,7 +83,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat *> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat *> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         CV_Assert(2 == inputs.size());
 
@@ -119,7 +119,7 @@ public:
         }
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -127,7 +127,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/detection_output_layer.cpp

@@ -93,7 +93,7 @@ static inline float caffe_norm_box_overlap(const util::NormalizedBBox& a, const
 
 } // namespace
 
-class DetectionOutputLayerImpl : public DetectionOutputLayer
+class DetectionOutputLayerImpl CV_FINAL : public DetectionOutputLayer
 {
 public:
     unsigned _numClasses;
@@ -193,7 +193,7 @@ public:
         setParamsFrom(params);
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && !_locPredTransposed;
@@ -202,7 +202,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() >= 3);
         CV_Assert(inputs[0][0] == inputs[1][0]);
@@ -367,7 +367,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -379,7 +379,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -862,7 +862,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;

modules/dnn/src/layers/elementwise_layers.cpp

@@ -82,7 +82,7 @@ public:
             nstripes_ = nstripes;
         }
 
-        void operator()(const Range &r) const
+        void operator()(const Range &r) const CV_OVERRIDE
         {
             int nstripes = nstripes_, nsamples = 1, outCn = 1;
             size_t planeSize = 1;
@@ -113,14 +113,14 @@ public:
 
     ElementWiseLayer(const Func &f=Func()) : run_parallel(false) { func = f; }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && this->type != "Sigmoid";
     }
 
-    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node)
+    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node) CV_OVERRIDE
     {
         switch (node->backendId)
         {
@@ -140,7 +140,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Buffer<float> input = halideBuffer(inputs[0]);
@@ -152,7 +152,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -166,13 +166,13 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         Layer::getMemoryShapes(inputs, requiredOutputs, outputs, internals);
         return true;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
 
@@ -183,7 +183,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
 
@@ -200,13 +200,13 @@ public:
         }
     }
 
-    void forwardSlice(const float* src, float* dst, int len, size_t planeSize, int cn0, int cn1) const
+    void forwardSlice(const float* src, float* dst, int len, size_t planeSize, int cn0, int cn1) const CV_OVERRIDE
     {
         func.apply(src, dst, len, planeSize, cn0, cn1);
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         long flops = 0;
         for (int i = 0; i < outputs.size(); i++)

modules/dnn/src/layers/eltwise_layer.cpp

@@ -54,7 +54,7 @@ namespace cv
 namespace dnn
 {
 
-class EltwiseLayerImpl : public EltwiseLayer
+class EltwiseLayerImpl CV_FINAL : public EltwiseLayer
 {
 public:
     enum EltwiseOp
@@ -94,7 +94,7 @@ public:
         }
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() ||
@@ -104,7 +104,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() >= 2);
         CV_Assert(coeffs.size() == 0 || coeffs.size() == inputs.size());
@@ -178,7 +178,7 @@ public:
             parallel_for_(Range(0, nstripes), p, nstripes);
         }
 
-        void operator()(const Range& r) const
+        void operator()(const Range& r) const CV_OVERRIDE
         {
             size_t total = dst->size[0]*planeSize;
             size_t stripeSize = (total + nstripes - 1)/nstripes;
@@ -338,7 +338,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -350,7 +350,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -361,7 +361,7 @@ public:
                             coeffs, op, activ.get(), nstripes);
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Var x("x"), y("y"), c("c"), n("n");
@@ -407,7 +407,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -429,7 +429,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         CV_Assert(inputs.size());
@@ -439,7 +439,7 @@ public:
         return flops;
     }
 
-    bool setActivation(const Ptr<ActivationLayer>& layer)
+    bool setActivation(const Ptr<ActivationLayer>& layer) CV_OVERRIDE
     {
         activ = layer;
         return !activ.empty();

modules/dnn/src/layers/flatten_layer.cpp

@@ -52,7 +52,7 @@ namespace cv
 namespace dnn
 {
 
-class FlattenLayerImpl : public FlattenLayer
+class FlattenLayerImpl CV_FINAL : public FlattenLayer
 {
 public:
     FlattenLayerImpl(const LayerParams &params)
@@ -62,7 +62,7 @@ public:
         setParamsFrom(params);
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
@@ -71,7 +71,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() > 0);
         for (size_t i = 1; i < inputs.size(); i++)
@@ -135,7 +135,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -148,7 +148,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -160,7 +160,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;

modules/dnn/src/layers/fully_connected_layer.cpp

@@ -56,7 +56,7 @@ namespace cv
 namespace dnn
 {
 
-class FullyConnectedLayerImpl : public InnerProductLayer
+class FullyConnectedLayerImpl CV_FINAL : public InnerProductLayer
 {
 public:
     enum { VEC_ALIGN = 8 };
@@ -106,7 +106,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &) const
+                         std::vector<MatShape> &) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1);
         CV_Assert(1 <= blobs.size() && blobs.size() <= 2);
@@ -125,14 +125,14 @@ public:
         return false;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() && axis == 1 ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && axis == 1;
     }
 
-    virtual bool setActivation(const Ptr<ActivationLayer>& layer)
+    virtual bool setActivation(const Ptr<ActivationLayer>& layer) CV_OVERRIDE
     {
         activ = layer;
         return !activ.empty();
@@ -168,7 +168,7 @@ public:
             parallel_for_(Range(0, nstripes), p, nstripes);
         }
 
-        void operator()(const Range& r) const
+        void operator()(const Range& r) const CV_OVERRIDE
         {
             int valign = FullyConnectedLayerImpl::VEC_ALIGN;
             int nsamples = srcMat->rows;
@@ -267,7 +267,7 @@ public:
     };
 
 #ifdef HAVE_OPENCL
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         innerProductOp.release();
     }
@@ -348,7 +348,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -360,7 +360,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &input, std::vector<Mat> &output, std::vector<Mat> &)
+    void forward(std::vector<Mat*> &input, std::vector<Mat> &output, std::vector<Mat> &) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -378,7 +378,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         int inW, inH, inC, inN, outC = blobs[0].size[0];
@@ -402,7 +402,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -421,7 +421,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)inputs; // suppress unused variable warning
         long flops = 0;

modules/dnn/src/layers/lrn_layer.cpp

@@ -59,7 +59,7 @@ namespace cv
 namespace dnn
 {
 
-class LRNLayerImpl : public LRNLayer
+class LRNLayerImpl CV_FINAL : public LRNLayer
 {
 public:
     LRNLayerImpl(const LayerParams& params)
@@ -88,7 +88,7 @@ public:
     Ptr<OCL4DNNLRN<float> > lrnOp;
 #endif
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() ||
@@ -96,7 +96,7 @@ public:
     }
 
 #ifdef HAVE_OPENCL
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         lrnOp.release();
     }
@@ -139,7 +139,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -153,7 +153,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -196,7 +196,7 @@ public:
             planeSize_ = planeSize; nsamples_ = nsamples; nstripes_ = nstripes;
         }
 
-        void operator()(const Range& r) const
+        void operator()(const Range& r) const CV_OVERRIDE
         {
             int nsamples = nsamples_, nstripes = nstripes_;
             size_t planeSize = planeSize_, planeSize_n = planeSize * nsamples;
@@ -303,7 +303,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         float alphaSize = alpha;
@@ -347,7 +347,7 @@ public:
     virtual void applyHalideScheduler(Ptr<BackendNode>& node,
                                       const std::vector<Mat*> &inputs,
                                       const std::vector<Mat> &outputs,
-                                      int targetId) const
+                                      int targetId) const CV_OVERRIDE
     {
 #ifdef  HAVE_HALIDE
         if (targetId != DNN_TARGET_CPU)
@@ -376,7 +376,7 @@ public:
 #endif  // HAVE_HALIDE
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -396,7 +396,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         CV_Assert(inputs.size() > 0);

modules/dnn/src/layers/max_unpooling_layer.cpp

@@ -21,7 +21,7 @@ namespace cv
 namespace dnn
 {
 
-class MaxUnpoolLayerImpl : public MaxUnpoolLayer
+class MaxUnpoolLayerImpl CV_FINAL : public MaxUnpoolLayer
 {
 public:
     MaxUnpoolLayerImpl(const LayerParams& params)
@@ -32,7 +32,7 @@ public:
         poolStride = Size(params.get<int>("pool_stride_w"), params.get<int>("pool_stride_h"));
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() &&
@@ -42,7 +42,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 2);
         CV_Assert(total(inputs[0]) == total(inputs[1]));
@@ -57,7 +57,7 @@ public:
         return false;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -65,7 +65,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -117,7 +117,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         // Meaningless operation if false because if kernel > stride

modules/dnn/src/layers/mvn_layer.cpp

@@ -54,7 +54,7 @@ namespace cv
 namespace dnn
 {
 
-class MVNLayerImpl : public MVNLayer
+class MVNLayerImpl CV_FINAL : public MVNLayer
 {
 public:
     MVNLayerImpl(const LayerParams& params)
@@ -71,7 +71,7 @@ public:
     Mat scale, shift;
     bool fuse_batch_norm;
 
-    virtual bool tryFuse(Ptr<Layer>& top)
+    virtual bool tryFuse(Ptr<Layer>& top) CV_OVERRIDE
     {
         if (preferableTarget == DNN_TARGET_OPENCL && !fuse_batch_norm)
         {
@@ -85,7 +85,7 @@ public:
     Ptr<ReLULayer> activ_relu;
     float relu_slope;
     bool fuse_relu;
-    bool setActivation(const Ptr<ActivationLayer>& layer)
+    bool setActivation(const Ptr<ActivationLayer>& layer) CV_OVERRIDE
     {
         if (!layer.empty() && preferableTarget == DNN_TARGET_OPENCL)
         {
@@ -244,7 +244,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -256,7 +256,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -295,7 +295,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         long flops = 0;

modules/dnn/src/layers/normalize_bbox_layer.cpp

@@ -45,7 +45,7 @@
 
 namespace cv { namespace dnn {
 
-class NormalizeBBoxLayerImpl : public NormalizeBBoxLayer
+class NormalizeBBoxLayerImpl CV_FINAL : public NormalizeBBoxLayer
 {
 public:
     NormalizeBBoxLayerImpl(const LayerParams& params)
@@ -60,7 +60,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1);
         Layer::getMemoryShapes(inputs, requiredOutputs, outputs, internals);
@@ -140,7 +140,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -152,7 +152,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/padding_layer.cpp

@@ -19,7 +19,7 @@ namespace cv
 namespace dnn
 {
 
-class PaddingLayerImpl : public PaddingLayer
+class PaddingLayerImpl CV_FINAL : public PaddingLayer
 {
 public:
     PaddingLayerImpl(const LayerParams &params)
@@ -45,7 +45,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1);
         const MatShape& inpShape = inputs[0];
@@ -61,7 +61,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         // Compute dstRanges.
         const MatSize& inpShape = inputs[0]->size;
@@ -85,13 +85,13 @@ public:
             dstRanges.push_back(Range::all());
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() && dstRanges.size() == 4;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -99,7 +99,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -145,7 +145,7 @@ public:
             CV_Error(Error::StsNotImplemented, "Unknown padding type: " + paddingType);
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         int inW, inH, inC, inN;

modules/dnn/src/layers/permute_layer.cpp

@@ -54,7 +54,7 @@ namespace cv
 {
 namespace dnn
 {
-class PermuteLayerImpl : public PermuteLayer
+class PermuteLayerImpl CV_FINAL : public PermuteLayer
 {
 public:
     void checkCurrentOrder(int currentOrder)
@@ -116,7 +116,7 @@ public:
         checkNeedForPermutation();
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
@@ -125,7 +125,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         if(!_needsPermute)
         {
@@ -172,7 +172,7 @@ public:
         _count = _oldStride[0] * shapeBefore[0];
     }
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         if(!_needsPermute)
         {
@@ -230,7 +230,7 @@ public:
 
         PermuteInvoker() : inp(0), out(0), order(0), nstripes(0) {}
 
-        void operator()(const Range& r) const
+        void operator()(const Range& r) const CV_OVERRIDE
         {
             int n0 = out->size[0], n1 = out->size[1], n2 = out->size[2], n3 = out->size[3];
 
@@ -308,7 +308,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -320,7 +320,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -380,7 +380,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;

modules/dnn/src/layers/pooling_layer.cpp

@@ -64,7 +64,7 @@ static inline int roundRoiSize(float v)
     return (int)(v + (v >= 0.f ? 0.5f : -0.5f));
 }
 
-class PoolingLayerImpl : public PoolingLayer
+class PoolingLayerImpl CV_FINAL : public PoolingLayer
 {
 public:
     PoolingLayerImpl(const LayerParams& params)
@@ -114,7 +114,7 @@ public:
     Ptr<OCL4DNNPool<float> > poolOp;
 #endif
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         CV_Assert(!inputs.empty());
 
@@ -133,7 +133,7 @@ public:
 #endif
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() &&
@@ -184,7 +184,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -196,7 +196,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -221,7 +221,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
         if (type == MAX)
             return initMaxPoolingHalide(inputs);
@@ -231,7 +231,7 @@ public:
             return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -313,7 +313,7 @@ public:
             parallel_for_(Range(0, nstripes), p, nstripes);
         }
 
-        void operator()(const Range& r) const
+        void operator()(const Range& r) const CV_OVERRIDE
         {
             int channels = dst->size[1], width = dst->size[3], height = dst->size[2];
             int inp_width = src->size[3], inp_height = src->size[2];
@@ -752,7 +752,7 @@ public:
     virtual void applyHalideScheduler(Ptr<BackendNode>& node,
                                       const std::vector<Mat*> &inputs,
                                       const std::vector<Mat> &outputs,
-                                      int targetId) const
+                                      int targetId) const CV_OVERRIDE
     {
 #ifdef  HAVE_HALIDE
         if (targetId != DNN_TARGET_CPU)
@@ -801,7 +801,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() != 0);
         Size in(inputs[0][3], inputs[0][2]), out;
@@ -858,7 +858,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)inputs; // suppress unused variable warning
         long flops = 0;

modules/dnn/src/layers/prior_box_layer.cpp

@@ -56,7 +56,7 @@ namespace cv
 namespace dnn
 {
 
-class PriorBoxLayerImpl : public PriorBoxLayer
+class PriorBoxLayerImpl CV_FINAL : public PriorBoxLayer
 {
 public:
     static bool getParameterDict(const LayerParams &params,
@@ -266,7 +266,7 @@ public:
         }
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && !_explicitSizes;
@@ -275,7 +275,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(!inputs.empty());
 
@@ -385,7 +385,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -397,7 +397,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -476,7 +476,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -516,7 +516,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         long flops = 0;

modules/dnn/src/layers/proposal_layer.cpp

@@ -9,7 +9,7 @@
 
 namespace cv { namespace dnn {
 
-class ProposalLayerImpl : public ProposalLayer
+class ProposalLayerImpl CV_FINAL : public ProposalLayer
 {
 public:
     ProposalLayerImpl(const LayerParams& params)
@@ -85,7 +85,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         // We need to allocate the following blobs:
         // - output priors from PriorBoxLayer
@@ -127,7 +127,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         std::vector<Mat*> layerInputs;
         std::vector<Mat> layerOutputs;
@@ -222,7 +222,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -234,7 +234,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/recurrent_layers.cpp

@@ -80,7 +80,7 @@ static void sigmoid(const Mat &src, Mat &dst)
     cv::pow(1 + dst, -1, dst);
 }
 
-class LSTMLayerImpl : public LSTMLayer
+class LSTMLayerImpl CV_FINAL : public LSTMLayer
 {
     int numTimeStamps, numSamples;
     bool allocated;
@@ -137,25 +137,25 @@ public:
         outTailShape.clear();
     }
 
-    void setUseTimstampsDim(bool use)
+    void setUseTimstampsDim(bool use) CV_OVERRIDE
     {
         CV_Assert(!allocated);
         useTimestampDim = use;
     }
 
-    void setProduceCellOutput(bool produce)
+    void setProduceCellOutput(bool produce) CV_OVERRIDE
     {
         CV_Assert(!allocated);
         produceCellOutput = produce;
     }
 
-    void setOutShape(const MatShape &outTailShape_)
+    void setOutShape(const MatShape &outTailShape_) CV_OVERRIDE
     {
         CV_Assert(!allocated || total(outTailShape) == total(outTailShape_));
         outTailShape = outTailShape_;
     }
 
-    void setWeights(const Mat &Wh, const Mat &Wx, const Mat &bias)
+    void setWeights(const Mat &Wh, const Mat &Wx, const Mat &bias) CV_OVERRIDE
     {
         CV_Assert(Wh.dims == 2 && Wx.dims == 2);
         CV_Assert(Wh.rows == Wx.rows);
@@ -172,7 +172,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(!usePeephole && blobs.size() == 3 || usePeephole && blobs.size() == 6);
         CV_Assert(inputs.size() == 1);
@@ -217,7 +217,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat*> &input, std::vector<Mat> &output)
+    void finalize(const std::vector<Mat*> &input, std::vector<Mat> &output) CV_OVERRIDE
     {
         CV_Assert(!usePeephole && blobs.size() == 3 || usePeephole && blobs.size() == 6);
         CV_Assert(input.size() == 1);
@@ -252,7 +252,7 @@ public:
         allocated = true;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -260,7 +260,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &input, std::vector<Mat> &output, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &input, std::vector<Mat> &output, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -384,12 +384,12 @@ public:
         produceH = false;
     }
 
-    void setProduceHiddenOutput(bool produce = false)
+    void setProduceHiddenOutput(bool produce = false) CV_OVERRIDE
     {
         produceH = produce;
     }
 
-    void setWeights(const Mat &W_xh, const Mat &b_h, const Mat &W_hh, const Mat &W_ho, const Mat &b_o)
+    void setWeights(const Mat &W_xh, const Mat &b_h, const Mat &W_hh, const Mat &W_ho, const Mat &b_o) CV_OVERRIDE
     {
         CV_Assert(W_hh.dims == 2 && W_xh.dims == 2);
         CV_Assert(W_hh.size[0] == W_xh.size[0] && W_hh.size[0] == W_hh.size[1] && (int)b_h.total() == W_xh.size[0]);
@@ -407,7 +407,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() >= 1 && inputs.size() <= 2);
 
@@ -433,7 +433,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat*> &input, std::vector<Mat> &output)
+    void finalize(const std::vector<Mat*> &input, std::vector<Mat> &output) CV_OVERRIDE
     {
         CV_Assert(input.size() >= 1 && input.size() <= 2);
 
@@ -473,7 +473,7 @@ public:
         }
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -481,7 +481,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &input, std::vector<Mat> &output, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &input, std::vector<Mat> &output, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/region_layer.cpp

@@ -54,7 +54,7 @@ namespace cv
 namespace dnn
 {
 
-class RegionLayerImpl : public RegionLayer
+class RegionLayerImpl CV_FINAL : public RegionLayer
 {
 public:
     int coords, classes, anchors, classfix;
@@ -85,7 +85,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() > 0);
         CV_Assert(inputs[0][3] == (1 + coords + classes)*anchors);
@@ -93,7 +93,7 @@ public:
         return false;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT;
     }
@@ -185,7 +185,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -197,7 +197,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -312,7 +312,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
 

modules/dnn/src/layers/reorg_layer.cpp

@@ -54,7 +54,7 @@ namespace cv
 namespace dnn
 {
 
-class ReorgLayerImpl : public ReorgLayer
+class ReorgLayerImpl CV_FINAL : public ReorgLayer
 {
     int reorgStride;
 public:
@@ -70,7 +70,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() > 0);
         outputs = std::vector<MatShape>(inputs.size(), shape(
@@ -85,7 +85,7 @@ public:
         return false;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT;
     }
@@ -129,7 +129,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -141,7 +141,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -174,7 +174,7 @@ public:
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
 

modules/dnn/src/layers/reshape_layer.cpp

@@ -144,7 +144,7 @@ static void computeShapeByReshapeMask(const MatShape &srcShape,
 }
 
 
-class ReshapeLayerImpl : public ReshapeLayer
+class ReshapeLayerImpl CV_FINAL : public ReshapeLayer
 {
 public:
     ReshapeLayerImpl(const LayerParams& params)
@@ -166,7 +166,7 @@ public:
         }
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
@@ -175,7 +175,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         outputs.clear();
 
@@ -214,7 +214,7 @@ public:
         return true;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -226,7 +226,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -239,7 +239,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;

modules/dnn/src/layers/resize_nearest_neighbor_layer.cpp

@@ -10,7 +10,7 @@
 
 namespace cv { namespace dnn {
 
-class ResizeNearestNeighborLayerImpl : public ResizeNearestNeighborLayer
+class ResizeNearestNeighborLayerImpl CV_FINAL : public ResizeNearestNeighborLayer
 {
 public:
     ResizeNearestNeighborLayerImpl(const LayerParams& params)
@@ -27,7 +27,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1, inputs[0].size() == 4);
         outputs.resize(1, inputs[0]);
@@ -37,7 +37,7 @@ public:
         return (outputs[0][2] == inputs[0][2]) && (outputs[0][3] == inputs[0][3]);
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -45,7 +45,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/scale_layer.cpp

@@ -20,7 +20,7 @@ namespace cv
 namespace dnn
 {
 
-class ScaleLayerImpl : public ScaleLayer
+class ScaleLayerImpl CV_FINAL : public ScaleLayer
 {
 public:
     ScaleLayerImpl(const LayerParams& params)
@@ -33,21 +33,21 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 2 && blobs.empty() || blobs.size() == 1 + hasBias);
         outputs.assign(1, inputs[0]);
         return true;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -55,7 +55,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -117,7 +117,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node)
+    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node) CV_OVERRIDE
     {
         switch (node->backendId)
         {
@@ -150,7 +150,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Buffer<float> input = halideBuffer(inputs[0]);
@@ -183,7 +183,7 @@ public:
     }
 #endif  // HAVE_HALIDE
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -201,14 +201,14 @@ public:
         return Ptr<BackendNode>();
     }
 
-    void getScaleShift(Mat& scale, Mat& shift) const
+    void getScaleShift(Mat& scale, Mat& shift) const CV_OVERRIDE
     {
         scale = !blobs.empty() ? blobs[0] : Mat();
         shift = hasBias ? blobs[1] : Mat();
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         long flops = 0;

modules/dnn/src/layers/shift_layer.cpp

@@ -18,7 +18,7 @@ namespace cv
 namespace dnn
 {
 
-class ShiftLayerImpl : public ShiftLayer
+class ShiftLayerImpl CV_FINAL : public ShiftLayer
 {
 public:
     ShiftLayerImpl(const LayerParams &params)
@@ -27,7 +27,7 @@ public:
         CV_Assert(blobs.size() == 1);
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
@@ -36,14 +36,14 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         Layer::getMemoryShapes(inputs, requiredOutputs, outputs, internals);
         internals.assign(1, shape(1, total(inputs[0], 2)));
         return true;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -51,7 +51,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    virtual void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    virtual void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -90,7 +90,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node)
+    virtual Ptr<BackendNode> tryAttach(const Ptr<BackendNode>& node) CV_OVERRIDE
     {
         switch (node->backendId)
         {
@@ -111,7 +111,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         // Inference Engine has no layer just for biases. Create a linear
@@ -136,14 +136,14 @@ public:
         return Ptr<BackendNode>();
     }
 
-    void getScaleShift(Mat& scale, Mat& shift) const
+    void getScaleShift(Mat& scale, Mat& shift) const CV_OVERRIDE
     {
         scale = Mat();
         shift = blobs[0];
     }
 
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
-                           const std::vector<MatShape> &outputs) const
+                           const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         long flops = 0;

modules/dnn/src/layers/slice_layer.cpp

@@ -53,7 +53,7 @@ namespace cv
 namespace dnn
 {
 
-class SliceLayerImpl : public SliceLayer
+class SliceLayerImpl CV_FINAL : public SliceLayer
 {
 public:
     SliceLayerImpl(const LayerParams& params)
@@ -110,7 +110,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                             const int requiredOutputs,
                             std::vector<MatShape> &outputs,
-                            std::vector<MatShape> &internals) const
+                            std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1);
         MatShape inpShape = inputs[0];
@@ -137,7 +137,7 @@ public:
         return false;
     }
 
-    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1);
         const MatSize& inpShape = inputs[0]->size;
@@ -217,7 +217,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -229,7 +229,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/layers/softmax_layer.cpp

@@ -58,7 +58,7 @@ namespace cv
 namespace dnn
 {
 
-class SoftMaxLayerImpl : public SoftmaxLayer
+class SoftMaxLayerImpl CV_FINAL : public SoftmaxLayer
 {
 public:
 
@@ -76,7 +76,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         bool inplace = Layer::getMemoryShapes(inputs, requiredOutputs, outputs, internals);
         MatShape shape = inputs[0];
@@ -86,7 +86,7 @@ public:
         return inplace;
     }
 
-    virtual bool supportBackend(int backendId)
+    virtual bool supportBackend(int backendId) CV_OVERRIDE
     {
         return backendId == DNN_BACKEND_DEFAULT ||
                backendId == DNN_BACKEND_HALIDE && haveHalide() && axisRaw == 1 ||
@@ -94,7 +94,7 @@ public:
     }
 
 #ifdef HAVE_OPENCL
-    virtual void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs)
+    virtual void finalize(const std::vector<Mat*> &inputs, std::vector<Mat> &outputs) CV_OVERRIDE
     {
         softmaxOp.release();
     }
@@ -190,7 +190,7 @@ public:
     }
 #endif
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -202,7 +202,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -290,7 +290,7 @@ public:
         }
     }
 
-    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs)
+    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
     {
 #ifdef HAVE_HALIDE
         Halide::Buffer<float> inputBuffer = halideBuffer(inputs[0]);
@@ -315,7 +315,7 @@ public:
         return Ptr<BackendNode>();
     }
 
-    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
         InferenceEngine::LayerParams lp;
@@ -330,7 +330,7 @@ public:
     }
 
     int64 getFLOPS(const std::vector<MatShape> &inputs,
-                  const std::vector<MatShape> &outputs) const
+                  const std::vector<MatShape> &outputs) const CV_OVERRIDE
     {
         (void)outputs; // suppress unused variable warning
         int64 flops = 0;

modules/dnn/src/layers/split_layer.cpp

@@ -48,7 +48,7 @@ namespace cv
 namespace dnn
 {
 
-class SplitLayerImpl : public SplitLayer
+class SplitLayerImpl CV_FINAL : public SplitLayer
 {
 public:
     SplitLayerImpl(const LayerParams &params)
@@ -69,7 +69,7 @@ public:
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,
                          std::vector<MatShape> &outputs,
-                         std::vector<MatShape> &internals) const
+                         std::vector<MatShape> &internals) const CV_OVERRIDE
     {
         CV_Assert(inputs.size() == 1);
 
@@ -78,7 +78,7 @@ public:
         return false;
     }
 
-    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
+    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());
@@ -86,7 +86,7 @@ public:
         Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
     }
 
-    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
         CV_TRACE_ARG_VALUE(name, "name", name.c_str());

modules/dnn/src/op_halide.hpp

@@ -9,7 +9,14 @@
 #define __OPENCV_DNN_OP_HALIDE_HPP__
 
 #ifdef HAVE_HALIDE
+#if defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wsuggest-override"
+#endif
 #include <Halide.h>
+#if defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic pop
+#endif
 #endif  // HAVE_HALIDE
 
 namespace cv
@@ -55,11 +62,11 @@ namespace dnn
 
         HalideBackendWrapper(const Ptr<BackendWrapper>& base, const MatShape& shape);
 
-        ~HalideBackendWrapper();
+        ~HalideBackendWrapper() CV_OVERRIDE;
 
-        virtual void copyToHost();
+        virtual void copyToHost() CV_OVERRIDE;
 
-        virtual void setHostDirty();
+        virtual void setHostDirty() CV_OVERRIDE;
 
         Halide::Buffer<float> buffer;
 

modules/dnn/src/op_inf_engine.cpp

@@ -131,6 +131,10 @@ void InfEngineBackendNet::getOutputsInfo(InferenceEngine::OutputsDataMap &output
 {
     outputs_ = outputs;
 }
+void InfEngineBackendNet::getOutputsInfo(InferenceEngine::OutputsDataMap &outputs_) const noexcept
+{
+    outputs_ = outputs;
+}
 
 // Returns input references that aren't connected to internal outputs.
 void InfEngineBackendNet::getInputsInfo(InferenceEngine::InputsDataMap &inputs_) noexcept

modules/dnn/src/op_inf_engine.hpp

@@ -9,7 +9,14 @@
 #define __OPENCV_DNN_OP_INF_ENGINE_HPP__
 
 #ifdef HAVE_INF_ENGINE
+#if defined(__GNUC__) && __GNUC__ >= 5
+//#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wsuggest-override"
+#endif
 #include <inference_engine.hpp>
+#if defined(__GNUC__) && __GNUC__ >= 5
+//#pragma GCC diagnostic pop
+#endif
 #endif  // HAVE_INF_ENGINE
 
 namespace cv { namespace dnn {
@@ -23,41 +30,43 @@ public:
 
     InfEngineBackendNet(InferenceEngine::CNNNetwork& net);
 
-    virtual void Release() noexcept;
+    virtual void Release() noexcept CV_OVERRIDE;
 
-    virtual InferenceEngine::Precision getPrecision() noexcept;
+    virtual InferenceEngine::Precision getPrecision() noexcept CV_OVERRIDE;
 
-    virtual void getOutputsInfo(InferenceEngine::OutputsDataMap &out) noexcept;
+    virtual void getOutputsInfo(InferenceEngine::OutputsDataMap &out) noexcept /*CV_OVERRIDE*/;
 
-    virtual void getInputsInfo(InferenceEngine::InputsDataMap &inputs) noexcept;
+    virtual void getOutputsInfo(InferenceEngine::OutputsDataMap &out) const noexcept /*CV_OVERRIDE*/;
 
-    virtual void getInputsInfo(InferenceEngine::InputsDataMap &inputs) const noexcept;
+    virtual void getInputsInfo(InferenceEngine::InputsDataMap &inputs) noexcept /*CV_OVERRIDE*/;
 
-    virtual InferenceEngine::InputInfo::Ptr getInput(const std::string &inputName) noexcept;
+    virtual void getInputsInfo(InferenceEngine::InputsDataMap &inputs) const noexcept /*CV_OVERRIDE*/;
 
-    virtual void getName(char *pName, size_t len) noexcept;
+    virtual InferenceEngine::InputInfo::Ptr getInput(const std::string &inputName) noexcept CV_OVERRIDE;
 
-    virtual size_t layerCount() noexcept;
+    virtual void getName(char *pName, size_t len) noexcept CV_OVERRIDE;
 
-    virtual InferenceEngine::DataPtr& getData(const char *dname) noexcept;
+    virtual size_t layerCount() noexcept CV_OVERRIDE;
 
-    virtual void addLayer(const InferenceEngine::CNNLayerPtr &layer) noexcept;
+    virtual InferenceEngine::DataPtr& getData(const char *dname) noexcept CV_OVERRIDE;
+
+    virtual void addLayer(const InferenceEngine::CNNLayerPtr &layer) noexcept CV_OVERRIDE;
 
     virtual InferenceEngine::StatusCode addOutput(const std::string &layerName,
                                                   size_t outputIndex = 0,
-                                                  InferenceEngine::ResponseDesc *resp = nullptr) noexcept;
+                                                  InferenceEngine::ResponseDesc *resp = nullptr) noexcept CV_OVERRIDE;
 
     virtual InferenceEngine::StatusCode getLayerByName(const char *layerName,
                                                        InferenceEngine::CNNLayerPtr &out,
-                                                       InferenceEngine::ResponseDesc *resp) noexcept;
+                                                       InferenceEngine::ResponseDesc *resp) noexcept CV_OVERRIDE;
 
-    virtual void setTargetDevice(InferenceEngine::TargetDevice device) noexcept;
+    virtual void setTargetDevice(InferenceEngine::TargetDevice device) noexcept CV_OVERRIDE;
 
-    virtual InferenceEngine::TargetDevice getTargetDevice() noexcept;
+    virtual InferenceEngine::TargetDevice getTargetDevice() noexcept CV_OVERRIDE;
 
-    virtual InferenceEngine::StatusCode setBatchSize(const size_t size) noexcept;
+    virtual InferenceEngine::StatusCode setBatchSize(const size_t size) noexcept CV_OVERRIDE;
 
-    virtual size_t getBatchSize() const noexcept;
+    virtual size_t getBatchSize() const noexcept CV_OVERRIDE;
 
     void init();
 
@@ -99,9 +108,9 @@ public:
 
     ~InfEngineBackendWrapper();
 
-    virtual void copyToHost();
+    virtual void copyToHost() CV_OVERRIDE;
 
-    virtual void setHostDirty();
+    virtual void setHostDirty() CV_OVERRIDE;
 
     InferenceEngine::DataPtr dataPtr;
     InferenceEngine::TBlob<float>::Ptr blob;
@@ -128,15 +137,15 @@ public:
     virtual bool getMemoryShapes(const std::vector<MatShape> &inputs,
                                  const int requiredOutputs,
                                  std::vector<MatShape> &outputs,
-                                 std::vector<MatShape> &internals) const;
+                                 std::vector<MatShape> &internals) const CV_OVERRIDE;
 
     virtual void forward(std::vector<Mat*> &input, std::vector<Mat> &output,
-                         std::vector<Mat> &internals);
+                         std::vector<Mat> &internals) CV_OVERRIDE;
 
     virtual void forward(InputArrayOfArrays inputs, OutputArrayOfArrays outputs,
-                         OutputArrayOfArrays internals);
+                         OutputArrayOfArrays internals) CV_OVERRIDE;
 
-    virtual bool supportBackend(int backendId);
+    virtual bool supportBackend(int backendId) CV_OVERRIDE;
 
 private:
     InferenceEngine::DataPtr output;

modules/dnn/src/tensorflow/tf_graph_simplifier.cpp

@@ -214,7 +214,7 @@ public:
     }
 
     virtual void finalize(tensorflow::GraphDef&, tensorflow::NodeDef* fusedNode,
-                          std::vector<tensorflow::NodeDef*>& inputNodes)
+                          std::vector<tensorflow::NodeDef*>& inputNodes) CV_OVERRIDE
     {
         Mat epsMat = getTensorContent(inputNodes.back()->attr().at("value").tensor());
         CV_Assert(epsMat.total() == 1, epsMat.type() == CV_32FC1);
@@ -249,7 +249,7 @@ public:
     }
 
     virtual void finalize(tensorflow::GraphDef& net, tensorflow::NodeDef* fusedNode,
-                          std::vector<tensorflow::NodeDef*>& inputNodes)
+                          std::vector<tensorflow::NodeDef*>& inputNodes) CV_OVERRIDE
     {
         Mat epsMat = getTensorContent(inputNodes.back()->attr().at("value").tensor());
         CV_Assert(epsMat.total() == 1, epsMat.type() == CV_32FC1);
@@ -343,7 +343,7 @@ public:
         setFusedNode("Relu6", input);
     }
 
-    virtual bool match(const tensorflow::GraphDef& net, int nodeId, std::vector<int>& matchedNodesIds)
+    virtual bool match(const tensorflow::GraphDef& net, int nodeId, std::vector<int>& matchedNodesIds) CV_OVERRIDE
     {
         if (!Subgraph::match(net, nodeId, matchedNodesIds))
             return false;
@@ -378,7 +378,7 @@ public:
     }
 
     virtual void finalize(tensorflow::GraphDef&, tensorflow::NodeDef* fusedNode,
-                          std::vector<tensorflow::NodeDef*>& inputNodes)
+                          std::vector<tensorflow::NodeDef*>& inputNodes) CV_OVERRIDE
     {
         std::vector<int> shape(numOutDims + 1);  // batch size in Keras is implicit.
         shape[0] = -1;

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -12,16 +12,12 @@ Implementation of Tensorflow models parser
 #include "../precomp.hpp"
 
 #ifdef HAVE_PROTOBUF
-#include "graph.pb.h"
+#include "tf_io.hpp"
 
 #include <iostream>
 #include <fstream>
 #include <algorithm>
 #include <string>
-#include <google/protobuf/message.h>
-#include <google/protobuf/text_format.h>
-#include <google/protobuf/io/zero_copy_stream_impl.h>
-#include "tf_io.hpp"
 #include "tf_graph_simplifier.hpp"
 #endif
 

modules/dnn/src/tensorflow/tf_io.cpp

@@ -23,8 +23,8 @@ Implementation of various functions which are related to Tensorflow models readi
 #include <fstream>
 #include <vector>
 
-#include "graph.pb.h"
 #include "tf_io.hpp"
+
 #include "../caffe/caffe_io.hpp"
 #include "../caffe/glog_emulator.hpp"
 

modules/dnn/src/tensorflow/tf_io.hpp

@@ -13,8 +13,20 @@ Declaration of various functions which are related to Tensorflow models reading.
 #define __OPENCV_DNN_TF_IO_HPP__
 #ifdef HAVE_PROTOBUF
 
+#if defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wsuggest-override"
+#endif
 #include "graph.pb.h"
 
+#include <google/protobuf/message.h>
+#include <google/protobuf/text_format.h>
+#include <google/protobuf/io/zero_copy_stream_impl.h>
+#if defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic pop
+#endif
+
+
 namespace cv {
 namespace dnn {
 

modules/features2d/include/opencv2/features2d.hpp

@@ -208,14 +208,14 @@ public:
 
     CV_WRAP void read( const String& fileName );
 
-    virtual void write( FileStorage&) const;
+    virtual void write( FileStorage&) const CV_OVERRIDE;
 
     // see corresponding cv::Algorithm method
-    CV_WRAP virtual void read( const FileNode&);
+    CV_WRAP virtual void read( const FileNode&) CV_OVERRIDE;
 
     //! Return true if detector object is empty
-    CV_WRAP virtual bool empty() const;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual bool empty() const CV_OVERRIDE;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 
     // see corresponding cv::Algorithm method
     CV_WRAP inline void write(const Ptr<FileStorage>& fs, const String& name = String()) const { Algorithm::write(fs, name); }
@@ -280,7 +280,7 @@ public:
     CV_WRAP static Ptr<BRISK> create(int thresh, int octaves, const std::vector<float> &radiusList,
         const std::vector<int> &numberList, float dMax=5.85f, float dMin=8.2f,
         const std::vector<int>& indexChange=std::vector<int>());
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @brief Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor
@@ -355,7 +355,7 @@ public:
 
     CV_WRAP virtual void setFastThreshold(int fastThreshold) = 0;
     CV_WRAP virtual int getFastThreshold() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @brief Maximally stable extremal region extractor
@@ -415,7 +415,7 @@ public:
 
     CV_WRAP virtual void setPass2Only(bool f) = 0;
     CV_WRAP virtual bool getPass2Only() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @overload */
@@ -471,7 +471,7 @@ public:
 
     CV_WRAP virtual void setType(int type) = 0;
     CV_WRAP virtual int getType() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @overload */
@@ -526,7 +526,7 @@ public:
 
     CV_WRAP virtual void setType(int type) = 0;
     CV_WRAP virtual int getType() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @brief Wrapping class for feature detection using the goodFeaturesToTrack function. :
@@ -555,7 +555,7 @@ public:
 
     CV_WRAP virtual void setK(double k) = 0;
     CV_WRAP virtual double getK() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @brief Class for extracting blobs from an image. :
@@ -622,7 +622,7 @@ public:
 
   CV_WRAP static Ptr<SimpleBlobDetector>
     create(const SimpleBlobDetector::Params &parameters = SimpleBlobDetector::Params());
-  CV_WRAP virtual String getDefaultName() const;
+  CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 //! @} features2d_main
@@ -679,7 +679,7 @@ public:
 
     CV_WRAP virtual void setDiffusivity(int diff) = 0;
     CV_WRAP virtual int getDiffusivity() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 /** @brief Class implementing the AKAZE keypoint detector and descriptor extractor, described in @cite ANB13.
@@ -747,7 +747,7 @@ public:
 
     CV_WRAP virtual void setDiffusivity(int diff) = 0;
     CV_WRAP virtual int getDiffusivity() const = 0;
-    CV_WRAP virtual String getDefaultName() const;
+    CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
 };
 
 //! @} features2d_main
@@ -857,11 +857,11 @@ public:
 
     /** @brief Clears the train descriptor collections.
      */
-    CV_WRAP virtual void clear();
+    CV_WRAP virtual void clear() CV_OVERRIDE;
 
     /** @brief Returns true if there are no train descriptors in the both collections.
      */
-    CV_WRAP virtual bool empty() const;
+    CV_WRAP virtual bool empty() const CV_OVERRIDE;
 
     /** @brief Returns true if the descriptor matcher supports masking permissible matches.
      */
@@ -991,9 +991,9 @@ public:
     }
     // Reads matcher object from a file node
     // see corresponding cv::Algorithm method
-    CV_WRAP virtual void read( const FileNode& );
+    CV_WRAP virtual void read( const FileNode& ) CV_OVERRIDE;
     // Writes matcher object to a file storage
-    virtual void write( FileStorage& ) const;
+    virtual void write( FileStorage& ) const CV_OVERRIDE;
 
     /** @brief Clones the matcher.
 
@@ -1086,7 +1086,7 @@ public:
 
     virtual ~BFMatcher() {}
 
-    virtual bool isMaskSupported() const { return true; }
+    virtual bool isMaskSupported() const CV_OVERRIDE { return true; }
 
     /** @brief Brute-force matcher create method.
     @param normType One of NORM_L1, NORM_L2, NORM_HAMMING, NORM_HAMMING2. L1 and L2 norms are
@@ -1102,12 +1102,12 @@ public:
      */
     CV_WRAP static Ptr<BFMatcher> create( int normType=NORM_L2, bool crossCheck=false ) ;
 
-    virtual Ptr<DescriptorMatcher> clone( bool emptyTrainData=false ) const;
+    virtual Ptr<DescriptorMatcher> clone( bool emptyTrainData=false ) const CV_OVERRIDE;
 protected:
     virtual void knnMatchImpl( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, int k,
-        InputArrayOfArrays masks=noArray(), bool compactResult=false );
+        InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE;
     virtual void radiusMatchImpl( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
-        InputArrayOfArrays masks=noArray(), bool compactResult=false );
+        InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE;
 
     int normType;
     bool crossCheck;
@@ -1128,29 +1128,29 @@ public:
     CV_WRAP FlannBasedMatcher( const Ptr<flann::IndexParams>& indexParams=makePtr<flann::KDTreeIndexParams>(),
                        const Ptr<flann::SearchParams>& searchParams=makePtr<flann::SearchParams>() );
 
-    virtual void add( InputArrayOfArrays descriptors );
-    virtual void clear();
+    virtual void add( InputArrayOfArrays descriptors ) CV_OVERRIDE;
+    virtual void clear() CV_OVERRIDE;
 
     // Reads matcher object from a file node
-    virtual void read( const FileNode& );
+    virtual void read( const FileNode& ) CV_OVERRIDE;
     // Writes matcher object to a file storage
-    virtual void write( FileStorage& ) const;
+    virtual void write( FileStorage& ) const CV_OVERRIDE;
 
-    virtual void train();
-    virtual bool isMaskSupported() const;
+    virtual void train() CV_OVERRIDE;
+    virtual bool isMaskSupported() const CV_OVERRIDE;
 
     CV_WRAP static Ptr<FlannBasedMatcher> create();
 
-    virtual Ptr<DescriptorMatcher> clone( bool emptyTrainData=false ) const;
+    virtual Ptr<DescriptorMatcher> clone( bool emptyTrainData=false ) const CV_OVERRIDE;
 protected:
     static void convertToDMatches( const DescriptorCollection& descriptors,
                                    const Mat& indices, const Mat& distances,
                                    std::vector<std::vector<DMatch> >& matches );
 
     virtual void knnMatchImpl( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, int k,
-        InputArrayOfArrays masks=noArray(), bool compactResult=false );
+        InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE;
     virtual void radiusMatchImpl( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
-        InputArrayOfArrays masks=noArray(), bool compactResult=false );
+        InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE;
 
     Ptr<flann::IndexParams> indexParams;
     Ptr<flann::SearchParams> searchParams;
@@ -1327,8 +1327,8 @@ public:
     virtual ~BOWKMeansTrainer();
 
     // Returns trained vocabulary (i.e. cluster centers).
-    CV_WRAP virtual Mat cluster() const;
-    CV_WRAP virtual Mat cluster( const Mat& descriptors ) const;
+    CV_WRAP virtual Mat cluster() const CV_OVERRIDE;
+    CV_WRAP virtual Mat cluster( const Mat& descriptors ) const CV_OVERRIDE;
 
 protected:
 

modules/features2d/src/agast.cpp

@@ -7941,14 +7941,14 @@ void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, boo
     AGAST(_img, keypoints, threshold, nonmax_suppression, AgastFeatureDetector::OAST_9_16);
 }
 
-class AgastFeatureDetector_Impl : public AgastFeatureDetector
+class AgastFeatureDetector_Impl CV_FINAL : public AgastFeatureDetector
 {
 public:
     AgastFeatureDetector_Impl( int _threshold, bool _nonmaxSuppression, int _type )
     : threshold(_threshold), nonmaxSuppression(_nonmaxSuppression), type((short)_type)
     {}
 
-    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask )
+    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE
     {
         CV_INSTRUMENT_REGION()
 
@@ -7986,14 +7986,14 @@ public:
         return 0;
     }
 
-    void setThreshold(int threshold_) { threshold = threshold_; }
-    int getThreshold() const { return threshold; }
+    void setThreshold(int threshold_) CV_OVERRIDE { threshold = threshold_; }
+    int getThreshold() const CV_OVERRIDE { return threshold; }
 
-    void setNonmaxSuppression(bool f) { nonmaxSuppression = f; }
-    bool getNonmaxSuppression() const { return nonmaxSuppression; }
+    void setNonmaxSuppression(bool f) CV_OVERRIDE { nonmaxSuppression = f; }
+    bool getNonmaxSuppression() const CV_OVERRIDE { return nonmaxSuppression; }
 
-    void setType(int type_) { type = type_; }
-    int getType() const { return type; }
+    void setType(int type_) CV_OVERRIDE { type = type_; }
+    int getType() const CV_OVERRIDE { return type; }
 
     int threshold;
     bool nonmaxSuppression;

modules/features2d/src/akaze.cpp

@@ -72,34 +72,34 @@ namespace cv
         {
         }
 
-        virtual ~AKAZE_Impl()
+        virtual ~AKAZE_Impl() CV_OVERRIDE
         {
 
         }
 
-        void setDescriptorType(int dtype) { descriptor = dtype; }
-        int getDescriptorType() const { return descriptor; }
+        void setDescriptorType(int dtype) CV_OVERRIDE { descriptor = dtype; }
+        int getDescriptorType() const CV_OVERRIDE { return descriptor; }
 
-        void setDescriptorSize(int dsize) { descriptor_size = dsize; }
-        int getDescriptorSize() const { return descriptor_size; }
+        void setDescriptorSize(int dsize) CV_OVERRIDE { descriptor_size = dsize; }
+        int getDescriptorSize() const CV_OVERRIDE { return descriptor_size; }
 
-        void setDescriptorChannels(int dch) { descriptor_channels = dch; }
-        int getDescriptorChannels() const { return descriptor_channels; }
+        void setDescriptorChannels(int dch) CV_OVERRIDE { descriptor_channels = dch; }
+        int getDescriptorChannels() const CV_OVERRIDE { return descriptor_channels; }
 
-        void setThreshold(double threshold_) { threshold = (float)threshold_; }
-        double getThreshold() const { return threshold; }
+        void setThreshold(double threshold_) CV_OVERRIDE { threshold = (float)threshold_; }
+        double getThreshold() const CV_OVERRIDE { return threshold; }
 
-        void setNOctaves(int octaves_) { octaves = octaves_; }
-        int getNOctaves() const { return octaves; }
+        void setNOctaves(int octaves_) CV_OVERRIDE { octaves = octaves_; }
+        int getNOctaves() const CV_OVERRIDE { return octaves; }
 
-        void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
-        int getNOctaveLayers() const { return sublevels; }
+        void setNOctaveLayers(int octaveLayers_) CV_OVERRIDE { sublevels = octaveLayers_; }
+        int getNOctaveLayers() const CV_OVERRIDE { return sublevels; }
 
-        void setDiffusivity(int diff_) { diffusivity = diff_; }
-        int getDiffusivity() const { return diffusivity; }
+        void setDiffusivity(int diff_) CV_OVERRIDE { diffusivity = diff_; }
+        int getDiffusivity() const CV_OVERRIDE { return diffusivity; }
 
         // returns the descriptor size in bytes
-        int descriptorSize() const
+        int descriptorSize() const CV_OVERRIDE
         {
             switch (descriptor)
             {
@@ -127,7 +127,7 @@ namespace cv
         }
 
         // returns the descriptor type
-        int descriptorType() const
+        int descriptorType() const CV_OVERRIDE
         {
             switch (descriptor)
             {
@@ -145,7 +145,7 @@ namespace cv
         }
 
         // returns the default norm type
-        int defaultNorm() const
+        int defaultNorm() const CV_OVERRIDE
         {
             switch (descriptor)
             {
@@ -165,7 +165,7 @@ namespace cv
         void detectAndCompute(InputArray image, InputArray mask,
                               std::vector<KeyPoint>& keypoints,
                               OutputArray descriptors,
-                              bool useProvidedKeypoints)
+                              bool useProvidedKeypoints) CV_OVERRIDE
         {
             CV_INSTRUMENT_REGION()
 
@@ -204,7 +204,7 @@ namespace cv
             }
         }
 
-        void write(FileStorage& fs) const
+        void write(FileStorage& fs) const CV_OVERRIDE
         {
             writeFormat(fs);
             fs << "descriptor" << descriptor;
@@ -216,7 +216,7 @@ namespace cv
             fs << "diffusivity" << diffusivity;
         }
 
-        void read(const FileNode& fn)
+        void read(const FileNode& fn) CV_OVERRIDE
         {
             descriptor = (int)fn["descriptor"];
             descriptor_channels = (int)fn["descriptor_channels"];

modules/features2d/src/blobdetector.cpp

@@ -64,8 +64,8 @@ public:
 
   explicit SimpleBlobDetectorImpl(const SimpleBlobDetector::Params &parameters = SimpleBlobDetector::Params());
 
-  virtual void read( const FileNode& fn );
-  virtual void write( FileStorage& fs ) const;
+  virtual void read( const FileNode& fn ) CV_OVERRIDE;
+  virtual void write( FileStorage& fs ) const CV_OVERRIDE;
 
 protected:
   struct CV_EXPORTS Center
@@ -75,7 +75,7 @@ protected:
       double confidence;
   };
 
-  virtual void detect( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask=noArray() );
+  virtual void detect( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask=noArray() ) CV_OVERRIDE;
   virtual void findBlobs(InputArray image, InputArray binaryImage, std::vector<Center> &centers) const;
 
   Params params;

modules/features2d/src/brisk.cpp

@@ -51,7 +51,7 @@
 namespace cv
 {
 
-class BRISK_Impl : public BRISK
+class BRISK_Impl CV_FINAL : public BRISK
 {
 public:
     explicit BRISK_Impl(int thresh=30, int octaves=3, float patternScale=1.0f);
@@ -65,17 +65,17 @@ public:
 
     virtual ~BRISK_Impl();
 
-    int descriptorSize() const
+    int descriptorSize() const CV_OVERRIDE
     {
         return strings_;
     }
 
-    int descriptorType() const
+    int descriptorType() const CV_OVERRIDE
     {
         return CV_8U;
     }
 
-    int defaultNorm() const
+    int defaultNorm() const CV_OVERRIDE
     {
         return NORM_HAMMING;
     }
@@ -90,7 +90,7 @@ public:
     void detectAndCompute( InputArray image, InputArray mask,
                      CV_OUT std::vector<KeyPoint>& keypoints,
                      OutputArray descriptors,
-                     bool useProvidedKeypoints );
+                     bool useProvidedKeypoints ) CV_OVERRIDE;
 
 protected:
 
@@ -151,11 +151,11 @@ private:
 
 
 // a layer in the Brisk detector pyramid
-class CV_EXPORTS BriskLayer
+class BriskLayer
 {
 public:
   // constructor arguments
-  struct CV_EXPORTS CommonParams
+  struct CommonParams
   {
     static const int HALFSAMPLE = 0;
     static const int TWOTHIRDSAMPLE = 1;
@@ -223,7 +223,7 @@ private:
   int pixel_9_16_[25];
 };
 
-class CV_EXPORTS BriskScaleSpace
+class BriskScaleSpace
 {
 public:
   // construct telling the octaves number:

modules/features2d/src/fast.avx2.cpp

@@ -50,7 +50,7 @@ namespace cv
 namespace opt_AVX2
 {
 
-class FAST_t_patternSize16_AVX2_Impl: public FAST_t_patternSize16_AVX2
+class FAST_t_patternSize16_AVX2_Impl CV_FINAL: public FAST_t_patternSize16_AVX2
 {
 public:
     FAST_t_patternSize16_AVX2_Impl(int _cols, int _threshold, bool _nonmax_suppression, const int* _pixel):
@@ -61,7 +61,7 @@ public:
         threshold = std::min(std::max(_threshold, 0), 255);
     }
 
-    virtual void process(int &j, const uchar* &ptr, uchar* curr, int* cornerpos, int &ncorners)
+    virtual void process(int &j, const uchar* &ptr, uchar* curr, int* cornerpos, int &ncorners) CV_OVERRIDE
     {
         static const __m256i delta256 = _mm256_broadcastsi128_si256(_mm_set1_epi8((char)(-128))), K16_256 = _mm256_broadcastsi128_si256(_mm_set1_epi8((char)8));
         const __m256i t256 = _mm256_broadcastsi128_si256(_mm_set1_epi8(t256c));
@@ -165,7 +165,7 @@ public:
         _mm256_zeroupper();
     }
 
-    virtual ~FAST_t_patternSize16_AVX2_Impl() {};
+    virtual ~FAST_t_patternSize16_AVX2_Impl() CV_OVERRIDE {};
 
 private:
     int cols;

modules/features2d/src/fast.cpp

@@ -515,14 +515,14 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
 }
 
 
-class FastFeatureDetector_Impl : public FastFeatureDetector
+class FastFeatureDetector_Impl CV_FINAL : public FastFeatureDetector
 {
 public:
     FastFeatureDetector_Impl( int _threshold, bool _nonmaxSuppression, int _type )
     : threshold(_threshold), nonmaxSuppression(_nonmaxSuppression), type((short)_type)
     {}
 
-    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask )
+    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE
     {
         CV_INSTRUMENT_REGION()
 
@@ -563,14 +563,14 @@ public:
         return 0;
     }
 
-    void setThreshold(int threshold_) { threshold = threshold_; }
-    int getThreshold() const { return threshold; }
+    void setThreshold(int threshold_) CV_OVERRIDE { threshold = threshold_; }
+    int getThreshold() const CV_OVERRIDE { return threshold; }
 
-    void setNonmaxSuppression(bool f) { nonmaxSuppression = f; }
-    bool getNonmaxSuppression() const { return nonmaxSuppression; }
+    void setNonmaxSuppression(bool f) CV_OVERRIDE { nonmaxSuppression = f; }
+    bool getNonmaxSuppression() const CV_OVERRIDE { return nonmaxSuppression; }
 
-    void setType(int type_) { type = type_; }
-    int getType() const { return type; }
+    void setType(int type_) CV_OVERRIDE { type = type_; }
+    int getType() const CV_OVERRIDE { return type; }
 
     int threshold;
     bool nonmaxSuppression;

modules/features2d/src/gftt.cpp

@@ -44,7 +44,7 @@
 namespace cv
 {
 
-class GFTTDetector_Impl : public GFTTDetector
+class GFTTDetector_Impl CV_FINAL : public GFTTDetector
 {
 public:
     GFTTDetector_Impl( int _nfeatures, double _qualityLevel,
@@ -55,28 +55,28 @@ public:
     {
     }
 
-    void setMaxFeatures(int maxFeatures) { nfeatures = maxFeatures; }
-    int getMaxFeatures() const { return nfeatures; }
+    void setMaxFeatures(int maxFeatures) CV_OVERRIDE { nfeatures = maxFeatures; }
+    int getMaxFeatures() const CV_OVERRIDE { return nfeatures; }
 
-    void setQualityLevel(double qlevel) { qualityLevel = qlevel; }
-    double getQualityLevel() const { return qualityLevel; }
+    void setQualityLevel(double qlevel) CV_OVERRIDE { qualityLevel = qlevel; }
+    double getQualityLevel() const CV_OVERRIDE { return qualityLevel; }
 
-    void setMinDistance(double minDistance_) { minDistance = minDistance_; }
-    double getMinDistance() const { return minDistance; }
+    void setMinDistance(double minDistance_) CV_OVERRIDE { minDistance = minDistance_; }
+    double getMinDistance() const CV_OVERRIDE { return minDistance; }
 
-    void setBlockSize(int blockSize_) { blockSize = blockSize_; }
-    int getBlockSize() const { return blockSize; }
+    void setBlockSize(int blockSize_) CV_OVERRIDE { blockSize = blockSize_; }
+    int getBlockSize() const CV_OVERRIDE { return blockSize; }
 
-    void setGradientSize(int gradientSize_) { gradSize = gradientSize_; }
-    int getGradientSize() { return gradSize; }
+    //void setGradientSize(int gradientSize_) { gradSize = gradientSize_; }
+    //int getGradientSize() { return gradSize; }
 
-    void setHarrisDetector(bool val) { useHarrisDetector = val; }
-    bool getHarrisDetector() const { return useHarrisDetector; }
+    void setHarrisDetector(bool val) CV_OVERRIDE { useHarrisDetector = val; }
+    bool getHarrisDetector() const CV_OVERRIDE { return useHarrisDetector; }
 
-    void setK(double k_) { k = k_; }
-    double getK() const { return k; }
+    void setK(double k_) CV_OVERRIDE { k = k_; }
+    double getK() const CV_OVERRIDE { return k; }
 
-    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask )
+    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE
     {
         CV_INSTRUMENT_REGION()
 

modules/features2d/src/kaze.cpp

@@ -53,7 +53,7 @@ http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla12eccv.pd
 namespace cv
 {
 
-    class KAZE_Impl : public KAZE
+    class KAZE_Impl CV_FINAL : public KAZE
     {
     public:
         KAZE_Impl(bool _extended, bool _upright, float _threshold, int _octaves,
@@ -67,40 +67,40 @@ namespace cv
         {
         }
 
-        virtual ~KAZE_Impl() {}
+        virtual ~KAZE_Impl() CV_OVERRIDE {}
 
-        void setExtended(bool extended_) { extended = extended_; }
-        bool getExtended() const { return extended; }
+        void setExtended(bool extended_) CV_OVERRIDE { extended = extended_; }
+        bool getExtended() const CV_OVERRIDE { return extended; }
 
-        void setUpright(bool upright_) { upright = upright_; }
-        bool getUpright() const { return upright; }
+        void setUpright(bool upright_) CV_OVERRIDE { upright = upright_; }
+        bool getUpright() const CV_OVERRIDE { return upright; }
 
-        void setThreshold(double threshold_) { threshold = (float)threshold_; }
-        double getThreshold() const { return threshold; }
+        void setThreshold(double threshold_) CV_OVERRIDE { threshold = (float)threshold_; }
+        double getThreshold() const CV_OVERRIDE { return threshold; }
 
-        void setNOctaves(int octaves_) { octaves = octaves_; }
-        int getNOctaves() const { return octaves; }
+        void setNOctaves(int octaves_) CV_OVERRIDE { octaves = octaves_; }
+        int getNOctaves() const CV_OVERRIDE { return octaves; }
 
-        void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
-        int getNOctaveLayers() const { return sublevels; }
+        void setNOctaveLayers(int octaveLayers_) CV_OVERRIDE { sublevels = octaveLayers_; }
+        int getNOctaveLayers() const CV_OVERRIDE { return sublevels; }
 
-        void setDiffusivity(int diff_) { diffusivity = diff_; }
-        int getDiffusivity() const { return diffusivity; }
+        void setDiffusivity(int diff_) CV_OVERRIDE { diffusivity = diff_; }
+        int getDiffusivity() const CV_OVERRIDE { return diffusivity; }
 
         // returns the descriptor size in bytes
-        int descriptorSize() const
+        int descriptorSize() const CV_OVERRIDE
         {
             return extended ? 128 : 64;
         }
 
         // returns the descriptor type
-        int descriptorType() const
+        int descriptorType() const CV_OVERRIDE
         {
             return CV_32F;
         }
 
         // returns the default norm type
-        int defaultNorm() const
+        int defaultNorm() const CV_OVERRIDE
         {
             return NORM_L2;
         }
@@ -108,7 +108,7 @@ namespace cv
         void detectAndCompute(InputArray image, InputArray mask,
                               std::vector<KeyPoint>& keypoints,
                               OutputArray descriptors,
-                              bool useProvidedKeypoints)
+                              bool useProvidedKeypoints) CV_OVERRIDE
         {
             CV_INSTRUMENT_REGION()
 
@@ -160,7 +160,7 @@ namespace cv
             }
         }
 
-        void write(FileStorage& fs) const
+        void write(FileStorage& fs) const CV_OVERRIDE
         {
             writeFormat(fs);
             fs << "extended" << (int)extended;
@@ -171,7 +171,7 @@ namespace cv
             fs << "diffusivity" << diffusivity;
         }
 
-        void read(const FileNode& fn)
+        void read(const FileNode& fn) CV_OVERRIDE
         {
             extended = (int)fn["extended"] != 0;
             upright = (int)fn["upright"] != 0;

modules/features2d/src/kaze/AKAZEFeatures.cpp

@@ -237,7 +237,7 @@ public:
     : Lt_(&Lt), Lf_(&Lf), Lstep_(&Lstep), step_size_(step_size)
   {}
 
-  void operator()(const Range& range) const
+  void operator()(const Range& range) const CV_OVERRIDE
   {
     nld_step_scalar_one_lane(*Lt_, *Lf_, *Lstep_, step_size_, range.start, range.end);
   }
@@ -603,7 +603,7 @@ public:
   {
   }
 
-  void operator()(const Range& range) const
+  void operator()(const Range& range) const CV_OVERRIDE
   {
     MatType Lxx, Lxy, Lyy;
 
@@ -725,7 +725,7 @@ public:
     : evolution_(&ev), keypoints_by_layers_(&kpts), dthreshold_(dthreshold)
   {}
 
-  void operator()(const Range& range) const
+  void operator()(const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -948,7 +948,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -974,7 +974,7 @@ public:
   {
   }
 
-  void operator()(const Range& range) const
+  void operator()(const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1000,7 +1000,7 @@ public:
   {
   }
 
-  void operator()(const Range& range) const
+  void operator()(const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1026,7 +1026,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1053,7 +1053,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1088,7 +1088,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1119,7 +1119,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1158,7 +1158,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {
@@ -1448,7 +1448,7 @@ public:
   {
   }
 
-  void operator() (const Range& range) const
+  void operator() (const Range& range) const CV_OVERRIDE
   {
     for (int i = range.start; i < range.end; i++)
     {

modules/features2d/src/kaze/KAZEFeatures.cpp

@@ -196,7 +196,7 @@ public:
     {
     }
 
-    void operator()(const Range& range) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         std::vector<TEvolution>& evolution = *evolution_;
         for (int i = range.start; i < range.end; i++)
@@ -239,7 +239,7 @@ public:
     {
     }
 
-    void operator()(const Range& range) const
+    void operator()(const Range& range) const CV_OVERRIDE
     {
         std::vector<TEvolution>& evolution = *evolution_;
         std::vector<std::vector<KeyPoint> >& kpts_par = *kpts_par_;
@@ -503,7 +503,7 @@ public:
     {
     }
 
-    void operator() (const Range& range) const
+    void operator() (const Range& range) const CV_OVERRIDE
     {
         std::vector<KeyPoint> &kpts      = *kpts_;
         Mat                   &desc      = *desc_;

modules/features2d/src/kaze/nldiffusion_functions.cpp

@@ -378,7 +378,7 @@ public:
 
     }
 
-    void operator()(const cv::Range& range) const
+    void operator()(const cv::Range& range) const CV_OVERRIDE
     {
         cv::Mat& Ld = *_Ld;
         const cv::Mat& c = *_c;

modules/features2d/src/mser.cpp

@@ -48,7 +48,7 @@ namespace cv
 
 using std::vector;
 
-class MSER_Impl : public MSER
+class MSER_Impl CV_FINAL : public MSER
 {
 public:
     struct Params
@@ -85,19 +85,19 @@ public:
 
     explicit MSER_Impl(const Params& _params) : params(_params) {}
 
-    virtual ~MSER_Impl() {}
+    virtual ~MSER_Impl() CV_OVERRIDE {}
 
-    void setDelta(int delta) { params.delta = delta; }
-    int getDelta() const { return params.delta; }
+    void setDelta(int delta) CV_OVERRIDE { params.delta = delta; }
+    int getDelta() const CV_OVERRIDE { return params.delta; }
 
-    void setMinArea(int minArea) { params.minArea = minArea; }
-    int getMinArea() const { return params.minArea; }
+    void setMinArea(int minArea) CV_OVERRIDE { params.minArea = minArea; }
+    int getMinArea() const CV_OVERRIDE { return params.minArea; }
 
-    void setMaxArea(int maxArea) { params.maxArea = maxArea; }
-    int getMaxArea() const { return params.maxArea; }
+    void setMaxArea(int maxArea) CV_OVERRIDE { params.maxArea = maxArea; }
+    int getMaxArea() const CV_OVERRIDE { return params.maxArea; }
 
-    void setPass2Only(bool f) { params.pass2Only = f; }
-    bool getPass2Only() const { return params.pass2Only; }
+    void setPass2Only(bool f) CV_OVERRIDE { params.pass2Only = f; }
+    bool getPass2Only() const CV_OVERRIDE { return params.pass2Only; }
 
     enum { DIR_SHIFT = 29, NEXT_MASK = ((1<<DIR_SHIFT)-1)  };
 
@@ -364,8 +364,8 @@ public:
 
     void detectRegions( InputArray image,
                         std::vector<std::vector<Point> >& msers,
-                        std::vector<Rect>& bboxes );
-    void detect( InputArray _src, vector<KeyPoint>& keypoints, InputArray _mask );
+                        std::vector<Rect>& bboxes ) CV_OVERRIDE;
+    void detect( InputArray _src, vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE;
 
     void preprocess1( const Mat& img, int* level_size )
     {

modules/features2d/src/orb.cpp

@@ -651,7 +651,7 @@ static inline float getScale(int level, int firstLevel, double scaleFactor)
 }
 
 
-class ORB_Impl : public ORB
+class ORB_Impl CV_FINAL : public ORB
 {
 public:
     explicit ORB_Impl(int _nfeatures, float _scaleFactor, int _nlevels, int _edgeThreshold,
@@ -661,43 +661,43 @@ public:
         scoreType(_scoreType), patchSize(_patchSize), fastThreshold(_fastThreshold)
     {}
 
-    void setMaxFeatures(int maxFeatures) { nfeatures = maxFeatures; }
-    int getMaxFeatures() const { return nfeatures; }
+    void setMaxFeatures(int maxFeatures) CV_OVERRIDE { nfeatures = maxFeatures; }
+    int getMaxFeatures() const CV_OVERRIDE { return nfeatures; }
 
-    void setScaleFactor(double scaleFactor_) { scaleFactor = scaleFactor_; }
-    double getScaleFactor() const { return scaleFactor; }
+    void setScaleFactor(double scaleFactor_) CV_OVERRIDE { scaleFactor = scaleFactor_; }
+    double getScaleFactor() const CV_OVERRIDE { return scaleFactor; }
 
-    void setNLevels(int nlevels_) { nlevels = nlevels_; }
-    int getNLevels() const { return nlevels; }
+    void setNLevels(int nlevels_) CV_OVERRIDE { nlevels = nlevels_; }
+    int getNLevels() const CV_OVERRIDE { return nlevels; }
 
-    void setEdgeThreshold(int edgeThreshold_) { edgeThreshold = edgeThreshold_; }
-    int getEdgeThreshold() const { return edgeThreshold; }
+    void setEdgeThreshold(int edgeThreshold_) CV_OVERRIDE { edgeThreshold = edgeThreshold_; }
+    int getEdgeThreshold() const CV_OVERRIDE { return edgeThreshold; }
 
-    void setFirstLevel(int firstLevel_) { CV_Assert(firstLevel_ >= 0);  firstLevel = firstLevel_; }
-    int getFirstLevel() const { return firstLevel; }
+    void setFirstLevel(int firstLevel_) CV_OVERRIDE { CV_Assert(firstLevel_ >= 0);  firstLevel = firstLevel_; }
+    int getFirstLevel() const CV_OVERRIDE { return firstLevel; }
 
-    void setWTA_K(int wta_k_) { wta_k = wta_k_; }
-    int getWTA_K() const { return wta_k; }
+    void setWTA_K(int wta_k_) CV_OVERRIDE { wta_k = wta_k_; }
+    int getWTA_K() const CV_OVERRIDE { return wta_k; }
 
-    void setScoreType(int scoreType_) { scoreType = scoreType_; }
-    int getScoreType() const { return scoreType; }
+    void setScoreType(int scoreType_) CV_OVERRIDE { scoreType = scoreType_; }
+    int getScoreType() const CV_OVERRIDE { return scoreType; }
 
-    void setPatchSize(int patchSize_) { patchSize = patchSize_; }
-    int getPatchSize() const { return patchSize; }
+    void setPatchSize(int patchSize_) CV_OVERRIDE { patchSize = patchSize_; }
+    int getPatchSize() const CV_OVERRIDE { return patchSize; }
 
-    void setFastThreshold(int fastThreshold_) { fastThreshold = fastThreshold_; }
-    int getFastThreshold() const { return fastThreshold; }
+    void setFastThreshold(int fastThreshold_) CV_OVERRIDE { fastThreshold = fastThreshold_; }
+    int getFastThreshold() const CV_OVERRIDE { return fastThreshold; }
 
     // returns the descriptor size in bytes
-    int descriptorSize() const;
+    int descriptorSize() const CV_OVERRIDE;
     // returns the descriptor type
-    int descriptorType() const;
+    int descriptorType() const CV_OVERRIDE;
     // returns the default norm type
-    int defaultNorm() const;
+    int defaultNorm() const CV_OVERRIDE;
 
     // Compute the ORB_Impl features and descriptors on an image
     void detectAndCompute( InputArray image, InputArray mask, std::vector<KeyPoint>& keypoints,
-                     OutputArray descriptors, bool useProvidedKeypoints=false );
+                     OutputArray descriptors, bool useProvidedKeypoints=false ) CV_OVERRIDE;
 
 protected:
 

modules/flann/include/opencv2/flann/any.h

@@ -54,50 +54,50 @@ struct base_any_policy
 template<typename T>
 struct typed_base_any_policy : base_any_policy
 {
-    virtual ::size_t get_size() { return sizeof(T); }
-    virtual const std::type_info& type() { return typeid(T); }
+    virtual ::size_t get_size() CV_OVERRIDE { return sizeof(T); }
+    virtual const std::type_info& type() CV_OVERRIDE { return typeid(T); }
 
 };
 
 template<typename T>
-struct small_any_policy : typed_base_any_policy<T>
+struct small_any_policy CV_FINAL : typed_base_any_policy<T>
 {
-    virtual void static_delete(void**) { }
-    virtual void copy_from_value(void const* src, void** dest)
+    virtual void static_delete(void**) CV_OVERRIDE { }
+    virtual void copy_from_value(void const* src, void** dest) CV_OVERRIDE
     {
         new (dest) T(* reinterpret_cast<T const*>(src));
     }
-    virtual void clone(void* const* src, void** dest) { *dest = *src; }
-    virtual void move(void* const* src, void** dest) { *dest = *src; }
-    virtual void* get_value(void** src) { return reinterpret_cast<void*>(src); }
-    virtual const void* get_value(void* const * src) { return reinterpret_cast<const void*>(src); }
-    virtual void print(std::ostream& out, void* const* src) { out << *reinterpret_cast<T const*>(src); }
+    virtual void clone(void* const* src, void** dest) CV_OVERRIDE { *dest = *src; }
+    virtual void move(void* const* src, void** dest) CV_OVERRIDE { *dest = *src; }
+    virtual void* get_value(void** src) CV_OVERRIDE { return reinterpret_cast<void*>(src); }
+    virtual const void* get_value(void* const * src) CV_OVERRIDE { return reinterpret_cast<const void*>(src); }
+    virtual void print(std::ostream& out, void* const* src) CV_OVERRIDE { out << *reinterpret_cast<T const*>(src); }
 };
 
 template<typename T>
-struct big_any_policy : typed_base_any_policy<T>
+struct big_any_policy CV_FINAL : typed_base_any_policy<T>
 {
-    virtual void static_delete(void** x)
+    virtual void static_delete(void** x) CV_OVERRIDE
     {
         if (* x) delete (* reinterpret_cast<T**>(x));
         *x = NULL;
     }
-    virtual void copy_from_value(void const* src, void** dest)
+    virtual void copy_from_value(void const* src, void** dest) CV_OVERRIDE
     {
         *dest = new T(*reinterpret_cast<T const*>(src));
     }
-    virtual void clone(void* const* src, void** dest)
+    virtual void clone(void* const* src, void** dest) CV_OVERRIDE
     {
         *dest = new T(**reinterpret_cast<T* const*>(src));
     }
-    virtual void move(void* const* src, void** dest)
+    virtual void move(void* const* src, void** dest) CV_OVERRIDE
     {
         (*reinterpret_cast<T**>(dest))->~T();
         **reinterpret_cast<T**>(dest) = **reinterpret_cast<T* const*>(src);
     }
-    virtual void* get_value(void** src) { return *src; }
-    virtual const void* get_value(void* const * src) { return *src; }
-    virtual void print(std::ostream& out, void* const* src) { out << *reinterpret_cast<T const*>(*src); }
+    virtual void* get_value(void** src) CV_OVERRIDE { return *src; }
+    virtual const void* get_value(void* const * src) CV_OVERRIDE { return *src; }
+    virtual void print(std::ostream& out, void* const* src) CV_OVERRIDE { out << *reinterpret_cast<T const*>(*src); }
 };
 
 template<> inline void big_any_policy<flann_centers_init_t>::print(std::ostream& out, void* const* src)

modules/flann/include/opencv2/flann/autotuned_index.h

@@ -100,7 +100,7 @@ public:
     /**
      *          Method responsible with building the index.
      */
-    virtual void buildIndex()
+    virtual void buildIndex() CV_OVERRIDE
     {
         std::ostringstream stream;
         bestParams_ = estimateBuildParams();
@@ -124,7 +124,7 @@ public:
     /**
      *  Saves the index to a stream
      */
-    virtual void saveIndex(FILE* stream)
+    virtual void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, (int)bestIndex_->getType());
         bestIndex_->saveIndex(stream);
@@ -134,7 +134,7 @@ public:
     /**
      *  Loads the index from a stream
      */
-    virtual void loadIndex(FILE* stream)
+    virtual void loadIndex(FILE* stream) CV_OVERRIDE
     {
         int index_type;
 
@@ -151,7 +151,7 @@ public:
     /**
      *      Method that searches for nearest-neighbors
      */
-    virtual void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    virtual void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         int checks = get_param<int>(searchParams,"checks",FLANN_CHECKS_AUTOTUNED);
         if (checks == FLANN_CHECKS_AUTOTUNED) {
@@ -163,7 +163,7 @@ public:
     }
 
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return bestIndex_->getParameters();
     }
@@ -182,7 +182,7 @@ public:
     /**
      *      Number of features in this index.
      */
-    virtual size_t size() const
+    virtual size_t size() const CV_OVERRIDE
     {
         return bestIndex_->size();
     }
@@ -190,7 +190,7 @@ public:
     /**
      *  The length of each vector in this index.
      */
-    virtual size_t veclen() const
+    virtual size_t veclen() const CV_OVERRIDE
     {
         return bestIndex_->veclen();
     }
@@ -198,7 +198,7 @@ public:
     /**
      * The amount of memory (in bytes) this index uses.
      */
-    virtual int usedMemory() const
+    virtual int usedMemory() const CV_OVERRIDE
     {
         return bestIndex_->usedMemory();
     }
@@ -206,7 +206,7 @@ public:
     /**
      * Algorithm name
      */
-    virtual flann_algorithm_t getType() const
+    virtual flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_AUTOTUNED;
     }

modules/flann/include/opencv2/flann/composite_index.h

@@ -101,7 +101,7 @@ public:
     /**
      * @return The index type
      */
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_COMPOSITE;
     }
@@ -109,7 +109,7 @@ public:
     /**
      * @return Size of the index
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return kdtree_index_->size();
     }
@@ -117,7 +117,7 @@ public:
     /**
      * \returns The dimensionality of the features in this index.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return kdtree_index_->veclen();
     }
@@ -125,7 +125,7 @@ public:
     /**
      * \returns The amount of memory (in bytes) used by the index.
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return kmeans_index_->usedMemory() + kdtree_index_->usedMemory();
     }
@@ -133,7 +133,7 @@ public:
     /**
      * \brief Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         Logger::info("Building kmeans tree...\n");
         kmeans_index_->buildIndex();
@@ -145,7 +145,7 @@ public:
      * \brief Saves the index to a stream
      * \param stream The stream to save the index to
      */
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         kmeans_index_->saveIndex(stream);
         kdtree_index_->saveIndex(stream);
@@ -155,7 +155,7 @@ public:
      * \brief Loads the index from a stream
      * \param stream The stream from which the index is loaded
      */
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         kmeans_index_->loadIndex(stream);
         kdtree_index_->loadIndex(stream);
@@ -164,7 +164,7 @@ public:
     /**
      * \returns The index parameters
      */
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }
@@ -172,7 +172,7 @@ public:
     /**
      * \brief Method that searches for nearest-neighbours
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         kmeans_index_->findNeighbors(result, vec, searchParams);
         kdtree_index_->findNeighbors(result, vec, searchParams);

modules/flann/include/opencv2/flann/flann_base.hpp

@@ -128,7 +128,7 @@ public:
     /**
      * Builds the index.
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         if (!loaded_) {
             nnIndex_->buildIndex();
@@ -150,7 +150,7 @@ public:
      * \brief Saves the index to a stream
      * \param stream The stream to save the index to
      */
-    virtual void saveIndex(FILE* stream)
+    virtual void saveIndex(FILE* stream) CV_OVERRIDE
     {
         nnIndex_->saveIndex(stream);
     }
@@ -159,7 +159,7 @@ public:
      * \brief Loads the index from a stream
      * \param stream The stream from which the index is loaded
      */
-    virtual void loadIndex(FILE* stream)
+    virtual void loadIndex(FILE* stream) CV_OVERRIDE
     {
         nnIndex_->loadIndex(stream);
     }
@@ -167,7 +167,7 @@ public:
     /**
      * \returns number of features in this index.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return nnIndex_->veclen();
     }
@@ -175,7 +175,7 @@ public:
     /**
      * \returns The dimensionality of the features in this index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return nnIndex_->size();
     }
@@ -183,7 +183,7 @@ public:
     /**
      * \returns The index type (kdtree, kmeans,...)
      */
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return nnIndex_->getType();
     }
@@ -191,7 +191,7 @@ public:
     /**
      * \returns The amount of memory (in bytes) used by the index.
      */
-    virtual int usedMemory() const
+    virtual int usedMemory() const CV_OVERRIDE
     {
         return nnIndex_->usedMemory();
     }
@@ -200,7 +200,7 @@ public:
     /**
      * \returns The index parameters
      */
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return nnIndex_->getParameters();
     }
@@ -213,7 +213,7 @@ public:
      * \param[in] knn Number of nearest neighbors to return
      * \param[in] params Search parameters
      */
-    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
+    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params) CV_OVERRIDE
     {
         nnIndex_->knnSearch(queries, indices, dists, knn, params);
     }
@@ -227,7 +227,7 @@ public:
      * \param[in] params Search parameters
      * \returns Number of neighbors found
      */
-    int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params)
+    int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params) CV_OVERRIDE
     {
         return nnIndex_->radiusSearch(query, indices, dists, radius, params);
     }
@@ -235,7 +235,7 @@ public:
     /**
      * \brief Method that searches for nearest-neighbours
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         nnIndex_->findNeighbors(result, vec, searchParams);
     }

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

@@ -435,7 +435,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -443,7 +443,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return veclen_;
     }
@@ -453,7 +453,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return pool.usedMemory+pool.wastedMemory+memoryCounter;
     }
@@ -461,7 +461,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         if (branching_<2) {
             throw FLANNException("Branching factor must be at least 2");
@@ -480,13 +480,13 @@ public:
     }
 
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_HIERARCHICAL;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, branching_);
         save_value(stream, trees_);
@@ -501,7 +501,7 @@ public:
     }
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         free_elements();
 
@@ -544,7 +544,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     searchParams = parameters that influence the search algorithm (checks)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
 
         int maxChecks = get_param(searchParams,"checks",32);
@@ -569,7 +569,7 @@ public:
 
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return params;
     }

modules/flann/include/opencv2/flann/kdtree_index.h

@@ -120,7 +120,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         /* Construct the randomized trees. */
         for (int i = 0; i < trees_; i++) {
@@ -136,13 +136,13 @@ public:
     }
 
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_KDTREE;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, trees_);
         for (int i=0; i<trees_; ++i) {
@@ -152,7 +152,7 @@ public:
 
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, trees_);
         if (tree_roots_!=NULL) {
@@ -170,7 +170,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -178,7 +178,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return veclen_;
     }
@@ -187,7 +187,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return int(pool_.usedMemory+pool_.wastedMemory+dataset_.rows*sizeof(int));  // pool memory and vind array memory
     }
@@ -201,7 +201,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     maxCheck = the maximum number of restarts (in a best-bin-first manner)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         int maxChecks = get_param(searchParams,"checks", 32);
         float epsError = 1+get_param(searchParams,"eps",0.0f);
@@ -214,7 +214,7 @@ public:
         }
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }

modules/flann/include/opencv2/flann/kdtree_single_index.h

@@ -114,7 +114,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         computeBoundingBox(root_bbox_);
         root_node_ = divideTree(0, (int)size_, root_bbox_ );   // construct the tree
@@ -133,13 +133,13 @@ public:
         }
     }
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_KDTREE_SINGLE;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, size_);
         save_value(stream, dim_);
@@ -154,7 +154,7 @@ public:
     }
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, size_);
         load_value(stream, dim_);
@@ -179,7 +179,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -187,7 +187,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return dim_;
     }
@@ -196,7 +196,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return (int)(pool_.usedMemory+pool_.wastedMemory+dataset_.rows*sizeof(int));  // pool memory and vind array memory
     }
@@ -210,7 +210,7 @@ public:
      * \param[in] knn Number of nearest neighbors to return
      * \param[in] params Search parameters
      */
-    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
+    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params) CV_OVERRIDE
     {
         assert(queries.cols == veclen());
         assert(indices.rows >= queries.rows);
@@ -225,7 +225,7 @@ public:
         }
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }
@@ -239,7 +239,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     maxCheck = the maximum number of restarts (in a best-bin-first manner)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         float epsError = 1+get_param(searchParams,"eps",0.0f);
 

modules/flann/include/opencv2/flann/kmeans_index.h

@@ -266,7 +266,7 @@ public:
 
 public:
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_KMEANS;
     }
@@ -291,7 +291,7 @@ public:
         {
         }
 
-        void operator()(const cv::Range& range) const
+        void operator()(const cv::Range& range) const CV_OVERRIDE
         {
             const int begin = range.start;
             const int end = range.end;
@@ -398,7 +398,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -406,7 +406,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return veclen_;
     }
@@ -421,7 +421,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return pool_.usedMemory+pool_.wastedMemory+memoryCounter_;
     }
@@ -429,7 +429,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         if (branching_<2) {
             throw FLANNException("Branching factor must be at least 2");
@@ -448,7 +448,7 @@ public:
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, branching_);
         save_value(stream, iterations_);
@@ -460,7 +460,7 @@ public:
     }
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, branching_);
         load_value(stream, iterations_);
@@ -495,7 +495,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     searchParams = parameters that influence the search algorithm (checks, cb_index)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
 
         int maxChecks = get_param(searchParams,"checks",32);
@@ -554,7 +554,7 @@ public:
         return clusterCount;
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }

modules/flann/include/opencv2/flann/linear_index.h

@@ -63,47 +63,47 @@ public:
     LinearIndex(const LinearIndex&);
     LinearIndex& operator=(const LinearIndex&);
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_LINEAR;
     }
 
 
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return dataset_.rows;
     }
 
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return dataset_.cols;
     }
 
 
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return 0;
     }
 
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         /* nothing to do here for linear search */
     }
 
-    void saveIndex(FILE*)
+    void saveIndex(FILE*) CV_OVERRIDE
     {
         /* nothing to do here for linear search */
     }
 
 
-    void loadIndex(FILE*)
+    void loadIndex(FILE*) CV_OVERRIDE
     {
         /* nothing to do here for linear search */
 
         index_params_["algorithm"] = getType();
     }
 
-    void findNeighbors(ResultSet<DistanceType>& resultSet, const ElementType* vec, const SearchParams& /*searchParams*/)
+    void findNeighbors(ResultSet<DistanceType>& resultSet, const ElementType* vec, const SearchParams& /*searchParams*/) CV_OVERRIDE
     {
         ElementType* data = dataset_.data;
         for (size_t i = 0; i < dataset_.rows; ++i, data += dataset_.cols) {
@@ -112,7 +112,7 @@ public:
         }
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }

modules/flann/include/opencv2/flann/lsh_index.h

@@ -107,7 +107,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         tables_.resize(table_number_);
         for (unsigned int i = 0; i < table_number_; ++i) {
@@ -119,13 +119,13 @@ public:
         }
     }
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_LSH;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream,table_number_);
         save_value(stream,key_size_);
@@ -133,7 +133,7 @@ public:
         save_value(stream, dataset_);
     }
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, table_number_);
         load_value(stream, key_size_);
@@ -151,7 +151,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return dataset_.rows;
     }
@@ -159,7 +159,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return feature_size_;
     }
@@ -168,13 +168,13 @@ public:
      * Computes the index memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return (int)(dataset_.rows * sizeof(int));
     }
 
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }
@@ -187,7 +187,7 @@ public:
      * \param[in] knn Number of nearest neighbors to return
      * \param[in] params Search parameters
      */
-    virtual void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
+    virtual void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params) CV_OVERRIDE
     {
         assert(queries.cols == veclen());
         assert(indices.rows >= queries.rows);
@@ -217,7 +217,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     maxCheck = the maximum number of restarts (in a best-bin-first manner)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& /*searchParams*/)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& /*searchParams*/) CV_OVERRIDE
     {
         getNeighbors(vec, result);
     }

modules/flann/include/opencv2/flann/result_set.h

@@ -109,13 +109,13 @@ public:
         return count;
     }
 
-    bool full() const
+    bool full() const CV_OVERRIDE
     {
         return count == capacity;
     }
 
 
-    void addPoint(DistanceType dist, int index)
+    void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         if (dist >= worst_distance_) return;
         int i;
@@ -139,7 +139,7 @@ public:
         worst_distance_ = dists[capacity-1];
     }
 
-    DistanceType worstDist() const
+    DistanceType worstDist() const CV_OVERRIDE
     {
         return worst_distance_;
     }
@@ -176,13 +176,13 @@ public:
         return count;
     }
 
-    bool full() const
+    bool full() const CV_OVERRIDE
     {
         return count == capacity;
     }
 
 
-    void addPoint(DistanceType dist, int index)
+    void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         if (dist >= worst_distance_) return;
         int i;
@@ -215,7 +215,7 @@ public:
         worst_distance_ = dists[capacity-1];
     }
 
-    DistanceType worstDist() const
+    DistanceType worstDist() const CV_OVERRIDE
     {
         return worst_distance_;
     }
@@ -310,7 +310,7 @@ public:
     /** Check the status of the set
      * @return true if we have k NN
      */
-    inline bool full() const
+    inline bool full() const CV_OVERRIDE
     {
         return is_full_;
     }
@@ -365,7 +365,7 @@ public:
      * If we don't have enough neighbors, it returns the max possible value
      * @return
      */
-    inline DistanceType worstDist() const
+    inline DistanceType worstDist() const CV_OVERRIDE
     {
         return worst_distance_;
     }
@@ -402,7 +402,7 @@ public:
      * @param dist distance for that neighbor
      * @param index index of that neighbor
      */
-    inline void addPoint(DistanceType dist, int index)
+    inline void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         // Don't do anything if we are worse than the worst
         if (dist >= worst_distance_) return;
@@ -422,7 +422,7 @@ public:
 
     /** Remove all elements in the set
      */
-    void clear()
+    void clear() CV_OVERRIDE
     {
         dist_indices_.clear();
         worst_distance_ = std::numeric_limits<DistanceType>::max();
@@ -461,14 +461,14 @@ public:
      * @param dist distance for that neighbor
      * @param index index of that neighbor
      */
-    void addPoint(DistanceType dist, int index)
+    void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         if (dist <= radius_) dist_indices_.insert(DistIndex(dist, index));
     }
 
     /** Remove all elements in the set
      */
-    inline void clear()
+    inline void clear() CV_OVERRIDE
     {
         dist_indices_.clear();
     }
@@ -477,7 +477,7 @@ public:
     /** Check the status of the set
      * @return alwys false
      */
-    inline bool full() const
+    inline bool full() const CV_OVERRIDE
     {
         return true;
     }
@@ -486,7 +486,7 @@ public:
      * If we don't have enough neighbors, it returns the max possible value
      * @return
      */
-    inline DistanceType worstDist() const
+    inline DistanceType worstDist() const CV_OVERRIDE
     {
         return radius_;
     }