release: OpenCV 4.0.0-alpha (version++)

Merge pull request #12585 from alalek:move_cuda_modules
cuda: move CUDA modules to opencv_contrib: https://github.com/opencv/opencv_contrib/pull/1781
2026-07-24 12:53:04 +04:00 · 2018-09-19 19:30:30 +03:00 · 2018-09-19 19:30:02 +03:00 · 2018-09-19 18:57:00 +03:00 · 2018-09-19 15:49:47 +00:00 · 2018-09-19 15:07:58 +00:00
1391 changed files with 55130 additions and 148562 deletions
@@ -2,6 +2,14 @@
 If you have a question rather than reporting a bug please go to http://answers.opencv.org where you get much faster responses.
 If you need further assistance please read [How To Contribute](https://github.com/opencv/opencv/wiki/How_to_contribute).

+Please:
+
+* Read the documentation to test with the latest developer build.
+* Check if other person has already created the same issue to avoid duplicates. You can comment on it if there already is an issue.
+* Try to be as detailed as possible in your report.
+* Report only one problem per created issue.
+
+
 This is a template helping you to create an issue which can be processed as quickly as possible. This is the bug reporting section for the OpenCV library.
 -->

@@ -27,4 +35,4 @@ This is a template helping you to create an issue which can be processed as quic
    // C++ code example
    ```
 or attach as .txt or .zip file
-->
+-->
@@ -1,9 +1,9 @@
-# Binaries branch name: ffmpeg/3.4_20180608
-# Binaries were created for OpenCV: f5ddbbf65937d8f44e481e4ee1082961821f5c62
-ocv_update(FFMPEG_BINARIES_COMMIT "8041bd6f5ad37045c258904ba3030bb3442e3911")
-ocv_update(FFMPEG_FILE_HASH_BIN32 "fa5a2a4e2f37defcb95bde8ed145c2b3")
-ocv_update(FFMPEG_FILE_HASH_BIN64 "2cc08fc4fef8199fe80e0f126684834f")
-ocv_update(FFMPEG_FILE_HASH_CMAKE "3b90f67f4b429e77d3da36698cef700c")
+# Binaries branch name: ffmpeg/master_20180918
+# Binaries were created for OpenCV: e628fd7bce2b5d64c36b5bdc55a37c0ae78bc907
+ocv_update(FFMPEG_BINARIES_COMMIT "c88df798e9dc3d63840f913714563a730245464a")
+ocv_update(FFMPEG_FILE_HASH_BIN32 "48c95ce37d5aa6b15b3ad116e331ebc1")
+ocv_update(FFMPEG_FILE_HASH_BIN64 "d33eca57ae1cfd6287b975b98125f7a3")
+ocv_update(FFMPEG_FILE_HASH_CMAKE "5fd49e1b84e9f402ca155e27c92d2ce9")

 function(download_win_ffmpeg script_var)
  set(${script_var} "" PARENT_SCOPE)
@@ -335,7 +335,7 @@ ITT_INLINE long __itt_interlocked_increment(volatile long* ptr)
 #ifdef SDL_STRNCPY_S
 #define __itt_fstrcpyn(s1, b, s2, l) SDL_STRNCPY_S(s1, b, s2, l)
 #else
-#define __itt_fstrcpyn(s1, b, s2, l) strncpy(s1, s2, l)
+#define __itt_fstrcpyn(s1, b, s2, l) strncpy(s1, s2, b)
 #endif /* SDL_STRNCPY_S */

 #define __itt_fstrdup(s)          strdup(s)
@@ -47,6 +47,10 @@ ocv_warnings_disable(CMAKE_CXX_FLAGS -Wshadow -Wunused -Wsign-compare -Wundef -W
                                     -Wsuggest-override -Winconsistent-missing-override
                                     -Wimplicit-fallthrough
 )
+if(CV_GCC AND CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 8.0)
+  ocv_warnings_disable(CMAKE_CXX_FLAGS -Wclass-memaccess)
+endif()
+
 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
 ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4244) # vs2008
@@ -431,7 +431,7 @@ int ovx_hal_warpAffine(int atype, const uchar *a, size_t astep, int aw, int ah,
    return CV_HAL_ERROR_OK;
 }

-int ovx_hal_warpPerspectve(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[9], int interpolation, int borderType, const double borderValue[4])
+int ovx_hal_warpPerspective(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[9], int interpolation, int borderType, const double borderValue[4])
 {
    if (skipSmallImages<VX_KERNEL_WARP_PERSPECTIVE>(aw, ah))
        return CV_HAL_ERROR_NOT_IMPLEMENTED;
@@ -27,7 +27,7 @@ int ovx_hal_mul(const T *a, size_t astep, const T *b, size_t bstep, T *c, size_t
 int ovx_hal_merge8u(const uchar **src_data, uchar *dst_data, int len, int cn);
 int ovx_hal_resize(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, double inv_scale_x, double inv_scale_y, int interpolation);
 int ovx_hal_warpAffine(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[6], int interpolation, int borderType, const double borderValue[4]);
-int ovx_hal_warpPerspectve(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[9], int interpolation, int borderType, const double borderValue[4]);
+int ovx_hal_warpPerspective(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[9], int interpolation, int borderType, const double borderValue[4]);

 struct cvhalFilter2D;
 int ovx_hal_filterInit(cvhalFilter2D **filter_context, uchar *kernel_data, size_t kernel_step, int kernel_type, int kernel_width, int kernel_height,
@@ -97,7 +97,7 @@ int ovx_hal_integral(int depth, int sdepth, int, const uchar * a, size_t astep,
 //#undef cv_hal_warpAffine
 //#define cv_hal_warpAffine ovx_hal_warpAffine
 //#undef cv_hal_warpPerspective
-//#define cv_hal_warpPerspective ovx_hal_warpPerspectve
+//#define cv_hal_warpPerspective ovx_hal_warpPerspective

 #undef cv_hal_filterInit
 #define cv_hal_filterInit ovx_hal_filterInit
@@ -29,6 +29,9 @@ if(CV_ICC)
      -wd265 -wd858 -wd873 -wd2196
  )
 endif()
+if(CV_GCC AND CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 8.0)
+  ocv_warnings_disable(CMAKE_CXX_FLAGS -Wclass-memaccess)
+endif()

 # Easier to support different versions of protobufs
 function(append_if_exist OUTPUT_LIST)
@@ -149,7 +149,6 @@ endif()
 # ----------------------------------------------------------------------------
 # Detect compiler and target platform architecture
 # ----------------------------------------------------------------------------
-OCV_OPTION(ENABLE_CXX11 "Enable C++11 compilation mode" "${OPENCV_CXX11}")
 include(cmake/OpenCVDetectCXXCompiler.cmake)
 ocv_cmake_hook(POST_DETECT_COMPILER)

@@ -253,8 +252,8 @@ OCV_OPTION(WITH_WIN32UI        "Build with Win32 UI Backend support"         ON
 OCV_OPTION(WITH_QUICKTIME      "Use QuickTime for Video I/O"                 OFF  IF APPLE )
 OCV_OPTION(WITH_QTKIT          "Use QTKit Video I/O backend"                 OFF  IF APPLE )
 OCV_OPTION(WITH_TBB            "Include Intel TBB support"                   OFF  IF (NOT IOS AND NOT WINRT) )
+OCV_OPTION(WITH_HPX            "Include Ste||ar Group HPX support"           OFF)
 OCV_OPTION(WITH_OPENMP         "Include OpenMP support"                      OFF)
-OCV_OPTION(WITH_CSTRIPES       "Include C= support"                          OFF  IF (WIN32 AND NOT WINRT)  )
 OCV_OPTION(WITH_PTHREADS_PF    "Use pthreads-based parallel_for"             ON   IF (NOT WIN32 OR MINGW) )
 OCV_OPTION(WITH_TIFF           "Include TIFF support"                        ON   IF (NOT IOS) )
 OCV_OPTION(WITH_UNICAP         "Include Unicap support (GPL)"                OFF  IF (UNIX AND NOT APPLE AND NOT ANDROID) )
@@ -271,18 +270,19 @@ OCV_OPTION(WITH_OPENCLAMDFFT   "Include AMD OpenCL FFT library support"      ON
 OCV_OPTION(WITH_OPENCLAMDBLAS  "Include AMD OpenCL BLAS library support"     ON   IF (NOT ANDROID AND NOT IOS AND NOT WINRT) )
 OCV_OPTION(WITH_DIRECTX        "Include DirectX support"                     ON   IF (WIN32 AND NOT WINRT) )
 OCV_OPTION(WITH_INTELPERC      "Include Intel Perceptual Computing support"  OFF  IF (WIN32 AND NOT WINRT) )
-OCV_OPTION(WITH_MATLAB         "Include Matlab support"                      ON   IF (NOT ANDROID AND NOT IOS AND NOT WINRT))
+OCV_OPTION(WITH_LIBREALSENSE   "Include Intel librealsense support"          OFF  IF (NOT WITH_INTELPERC) )
 OCV_OPTION(WITH_VA             "Include VA support"                          OFF  IF (UNIX AND NOT ANDROID) )
 OCV_OPTION(WITH_VA_INTEL       "Include Intel VA-API/OpenCL support"         OFF  IF (UNIX AND NOT ANDROID) )
 OCV_OPTION(WITH_MFX            "Include Intel Media SDK support"             OFF   IF ((UNIX AND NOT ANDROID) OR (WIN32 AND NOT WINRT AND NOT MINGW)) )
 OCV_OPTION(WITH_GDAL           "Include GDAL Support"                        OFF  IF (NOT ANDROID AND NOT IOS AND NOT WINRT) )
-OCV_OPTION(WITH_GPHOTO2        "Include gPhoto2 library support"             ON   IF (UNIX AND NOT ANDROID AND NOT IOS) )
+OCV_OPTION(WITH_GPHOTO2        "Include gPhoto2 library support"             OFF  IF (UNIX AND NOT ANDROID AND NOT IOS) )
 OCV_OPTION(WITH_LAPACK         "Include Lapack library support"              (NOT CV_DISABLE_OPTIMIZATION)  IF (NOT ANDROID AND NOT IOS) )
 OCV_OPTION(WITH_ITT            "Include Intel ITT support"                   ON   IF (NOT APPLE_FRAMEWORK) )
 OCV_OPTION(WITH_PROTOBUF       "Enable libprotobuf"                          ON )
 OCV_OPTION(WITH_IMGCODEC_HDR   "Include HDR support"                         ON)
 OCV_OPTION(WITH_IMGCODEC_SUNRASTER "Include SUNRASTER support"               ON)
 OCV_OPTION(WITH_IMGCODEC_PXM   "Include PNM (PBM,PGM,PPM) and PAM formats support" ON)
+OCV_OPTION(WITH_IMGCODEC_PFM   "Include PFM formats support"                 ON)

 # OpenCV build components
 # ===================================================
@@ -373,8 +373,6 @@ endif()

 if(ANDROID OR WIN32)
  ocv_update(OPENCV_DOC_INSTALL_PATH doc)
-else()
-  ocv_update(OPENCV_DOC_INSTALL_PATH share/OpenCV/doc)
 endif()

 if(WIN32 AND CMAKE_HOST_SYSTEM_NAME MATCHES Windows)
@@ -414,8 +412,6 @@ if(ANDROID)
  ocv_update(OPENCV_TEST_DATA_INSTALL_PATH "sdk/etc/testdata")
 elseif(WIN32)
  ocv_update(OPENCV_TEST_DATA_INSTALL_PATH "testdata")
-else()
-  ocv_update(OPENCV_TEST_DATA_INSTALL_PATH "share/OpenCV/testdata")
 endif()

 if(ANDROID)
@@ -428,6 +424,7 @@ if(ANDROID)
  ocv_update(OPENCV_INCLUDE_INSTALL_PATH sdk/native/jni/include)
  ocv_update(OPENCV_SAMPLES_SRC_INSTALL_PATH samples/native)
  ocv_update(OPENCV_OTHER_INSTALL_PATH   sdk/etc)
+  ocv_update(OPENCV_LICENSES_INSTALL_PATH "${OPENCV_OTHER_INSTALL_PATH}/licenses")
 else()
  set(LIBRARY_OUTPUT_PATH                "${OpenCV_BINARY_DIR}/lib")
  ocv_update(3P_LIBRARY_OUTPUT_PATH      "${OpenCV_BINARY_DIR}/3rdparty/lib${LIB_SUFFIX}")
@@ -443,42 +440,40 @@ else()
    ocv_update(OPENCV_JAR_INSTALL_PATH java)
    ocv_update(OPENCV_OTHER_INSTALL_PATH   etc)
    ocv_update(OPENCV_CONFIG_INSTALL_PATH  ".")
+    ocv_update(OPENCV_INCLUDE_INSTALL_PATH "include")
+    ocv_update(OPENCV_LICENSES_INSTALL_PATH "${OPENCV_OTHER_INSTALL_PATH}/licenses")
  else()
+    # Note: layout differs from OpenCV 3.4
    include(GNUInstallDirs)
-    ocv_update(OPENCV_LIB_INSTALL_PATH     ${CMAKE_INSTALL_LIBDIR}${LIB_SUFFIX})
-    ocv_update(OPENCV_3P_LIB_INSTALL_PATH  share/OpenCV/3rdparty/${OPENCV_LIB_INSTALL_PATH})
-    ocv_update(OPENCV_SAMPLES_SRC_INSTALL_PATH    share/OpenCV/samples)
-    ocv_update(OPENCV_JAR_INSTALL_PATH share/OpenCV/java)
-    ocv_update(OPENCV_OTHER_INSTALL_PATH   share/OpenCV)
-
-    if(NOT DEFINED OPENCV_CONFIG_INSTALL_PATH)
-      math(EXPR SIZEOF_VOID_P_BITS "8 * ${CMAKE_SIZEOF_VOID_P}")
-      if(LIB_SUFFIX AND NOT SIZEOF_VOID_P_BITS EQUAL LIB_SUFFIX)
-        ocv_update(OPENCV_CONFIG_INSTALL_PATH ${CMAKE_INSTALL_LIBDIR}${LIB_SUFFIX}/cmake/opencv)
-      else()
-        ocv_update(OPENCV_CONFIG_INSTALL_PATH share/OpenCV)
-      endif()
-    endif()
+    ocv_update(OPENCV_INCLUDE_INSTALL_PATH       "${CMAKE_INSTALL_INCLUDEDIR}/opencv4")
+    ocv_update(OPENCV_LIB_INSTALL_PATH           "${CMAKE_INSTALL_LIBDIR}${LIB_SUFFIX}")
+    ocv_update(OPENCV_CONFIG_INSTALL_PATH        "${OPENCV_LIB_INSTALL_PATH}/cmake/opencv4")
+    ocv_update(OPENCV_3P_LIB_INSTALL_PATH        "${OPENCV_LIB_INSTALL_PATH}/opencv4/3rdparty")
+    ocv_update(OPENCV_SAMPLES_SRC_INSTALL_PATH   "${CMAKE_INSTALL_DATAROOTDIR}/opencv4/samples")
+    ocv_update(OPENCV_DOC_INSTALL_PATH           "${CMAKE_INSTALL_DATAROOTDIR}/doc/opencv4")
+    ocv_update(OPENCV_JAR_INSTALL_PATH           "${CMAKE_INSTALL_DATAROOTDIR}/java/opencv4")
+    ocv_update(OPENCV_TEST_DATA_INSTALL_PATH     "${CMAKE_INSTALL_DATAROOTDIR}/opencv4/testdata")
+    ocv_update(OPENCV_OTHER_INSTALL_PATH         "${CMAKE_INSTALL_DATAROOTDIR}/opencv4")
+    ocv_update(OPENCV_LICENSES_INSTALL_PATH      "${CMAKE_INSTALL_DATAROOTDIR}/licenses/opencv4")
  endif()
-  ocv_update(OPENCV_INCLUDE_INSTALL_PATH "include")
 endif()

 ocv_update(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/${OPENCV_LIB_INSTALL_PATH}")
 set(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE)

 if(INSTALL_TO_MANGLED_PATHS)
-  set(OPENCV_INCLUDE_INSTALL_PATH ${OPENCV_INCLUDE_INSTALL_PATH}/opencv-${OPENCV_VERSION})
  foreach(v
+      OPENCV_INCLUDE_INSTALL_PATH
+      # file names include version (.so/.dll): OPENCV_LIB_INSTALL_PATH
+      OPENCV_CONFIG_INSTALL_PATH
      OPENCV_3P_LIB_INSTALL_PATH
      OPENCV_SAMPLES_SRC_INSTALL_PATH
-      OPENCV_CONFIG_INSTALL_PATH
      OPENCV_DOC_INSTALL_PATH
-      OPENCV_JAR_INSTALL_PATH
+      # JAR file name includes version: OPENCV_JAR_INSTALL_PATH
      OPENCV_TEST_DATA_INSTALL_PATH
      OPENCV_OTHER_INSTALL_PATH
    )
-    string(REPLACE "OpenCV" "OpenCV-${OPENCV_VERSION}" ${v} "${${v}}")
-    string(REPLACE "opencv" "opencv-${OPENCV_VERSION}" ${v} "${${v}}")
+    string(REGEX REPLACE "opencv[0-9]*" "opencv-${OPENCV_VERSION}" ${v} "${${v}}")
  endforeach()
 endif()

@@ -693,11 +688,6 @@ if(WITH_DIRECTX)
  include(cmake/OpenCVDetectDirectX.cmake)
 endif()

-# --- Matlab/Octave ---
-if(WITH_MATLAB)
-  include(cmake/OpenCVFindMatlab.cmake)
-endif()
-
 if(WITH_VTK)
  include(cmake/OpenCVDetectVTK.cmake)
 endif()
@@ -1015,9 +1005,6 @@ string(STRIP "${OPENCV_COMPILER_STR}" OPENCV_COMPILER_STR)
 status("")
 status("  C/C++:")
 status("    Built as dynamic libs?:" BUILD_SHARED_LIBS THEN YES ELSE NO)
-if(ENABLE_CXX11 OR HAVE_CXX11)
-status("    C++11:" HAVE_CXX11 THEN YES ELSE NO)
-endif()
 status("    C++ Compiler:"           ${OPENCV_COMPILER_STR})
 status("    C++ flags (Release):"    ${CMAKE_CXX_FLAGS} ${CMAKE_CXX_FLAGS_RELEASE})
 status("    C++ flags (Debug):"      ${CMAKE_CXX_FLAGS} ${CMAKE_CXX_FLAGS_DEBUG})
@@ -1231,6 +1218,10 @@ if(WITH_IMGCODEC_PXM OR DEFINED HAVE_IMGCODEC_PXM)
  status("    PXM:" HAVE_IMGCODEC_PXM THEN "YES" ELSE "NO")
 endif()

+if(WITH_IMGCODEC_PFM OR DEFINED HAVE_IMGCODEC_PFM)
+  status("    PFM:" HAVE_IMGCODEC_PFM THEN "YES" ELSE "NO")
+endif()
+
 # ========================== VIDEO IO ==========================
 status("")
 status("  Video I/O:")
@@ -1352,7 +1343,7 @@ endif()
 # Order is similar to CV_PARALLEL_FRAMEWORK in core/src/parallel.cpp
 ocv_build_features_string(parallel_status EXCLUSIVE
  IF HAVE_TBB THEN "TBB (ver ${TBB_VERSION_MAJOR}.${TBB_VERSION_MINOR} interface ${TBB_INTERFACE_VERSION})"
-  IF HAVE_CSTRIPES THEN "C="
+  IF HAVE_HPX THEN "HPX"
  IF HAVE_OPENMP THEN "OpenMP"
  IF HAVE_GCD THEN "GCD"
  IF WINRT OR HAVE_CONCURRENCY THEN "Concurrency"
@@ -1396,7 +1387,7 @@ if(WITH_VA OR HAVE_VA)
 endif()

 if(WITH_VA_INTEL OR HAVE_VA_INTEL)
-  status("    Intel VA-API/OpenCL:"  HAVE_VA_INTEL       THEN "YES (MSDK: ${VA_INTEL_MSDK_ROOT}  OpenCL: ${VA_INTEL_IOCL_ROOT})" ELSE NO)
+  status("    Intel VA-API/OpenCL:"  HAVE_VA_INTEL       THEN "YES (OpenCL: ${VA_INTEL_IOCL_ROOT})" ELSE NO)
 endif()

 if(WITH_LAPACK OR HAVE_LAPACK)
@@ -1407,8 +1398,22 @@ if(WITH_HALIDE OR HAVE_HALIDE)
  status("    Halide:"     HAVE_HALIDE      THEN "YES (${HALIDE_LIBRARIES} ${HALIDE_INCLUDE_DIRS})" ELSE NO)
 endif()

-if(WITH_INF_ENGINE OR HAVE_INF_ENGINE)
-  status("    Inference Engine:"     HAVE_INF_ENGINE     THEN "YES (${INF_ENGINE_LIBRARIES} ${INF_ENGINE_INCLUDE_DIRS})" ELSE NO)
+if(WITH_INF_ENGINE OR INF_ENGINE_TARGET)
+  if(INF_ENGINE_TARGET)
+    set(__msg "YES (${INF_ENGINE_RELEASE} / ${INF_ENGINE_VERSION})")
+    get_target_property(_lib ${INF_ENGINE_TARGET} IMPORTED_LOCATION)
+    if(NOT _lib)
+      get_target_property(_lib_rel ${INF_ENGINE_TARGET} IMPORTED_IMPLIB_RELEASE)
+      get_target_property(_lib_dbg ${INF_ENGINE_TARGET} IMPORTED_IMPLIB_DEBUG)
+      set(_lib "${_lib_rel} / ${_lib_dbg}")
+    endif()
+    get_target_property(_inc ${INF_ENGINE_TARGET} INTERFACE_INCLUDE_DIRECTORIES)
+    status("    Inference Engine:" "${__msg}")
+    status("                libs:" "${_lib}")
+    status("            includes:" "${_inc}")
+  else()
+    status("    Inference Engine:"     "NO")
+  endif()
 endif()

 if(WITH_EIGEN OR HAVE_EIGEN)
@@ -1502,15 +1507,7 @@ if(BUILD_JAVA OR BUILD_opencv_java)
  status("    Java tests:"    BUILD_TESTS AND opencv_test_java_BINARY_DIR                                 THEN YES ELSE NO)
 endif()

-# ========================= matlab =========================
-if(WITH_MATLAB OR MATLAB_FOUND)
-  status("")
-  status("  Matlab:" MATLAB_FOUND THEN "YES" ELSE "NO")
-  if(MATLAB_FOUND)
-    status("    mex:"         MATLAB_MEX_SCRIPT  THEN  "${MATLAB_MEX_SCRIPT}"   ELSE NO)
-    status("    Compiler/generator:" MEX_WORKS   THEN  "Working"                ELSE "Not working (bindings will not be generated)")
-  endif()
-endif()
+ocv_cmake_hook(STATUS_DUMP_EXTRA)

 # ========================== auxiliary ==========================
 status("")
@@ -2,8 +2,8 @@

 ### Resources

-* Homepage: <http://opencv.org>
-* Docs: <http://docs.opencv.org/master/>
+* Homepage: <https://opencv.org>
+* Docs: <https://docs.opencv.org/master/>
 * Q&A forum: <http://answers.opencv.org>
 * Issue tracking: <https://github.com/opencv/opencv/issues>

@@ -54,6 +54,10 @@
 #include "opencv2/highgui.hpp"
 #include "opencv2/calib3d.hpp"

+#if defined __GNUC__ && __GNUC__ >= 8
+#pragma GCC diagnostic ignored "-Wclass-memaccess"
+#endif
+
 using namespace cv;

 #ifndef PATH_MAX
@@ -1040,12 +1044,10 @@ void cvCreateTrainingSamples( const char* filename,
        output = fopen( filename, "wb" );
        if( output != NULL )
        {
-            int hasbg;
            int i;
            int inverse;

-            hasbg = 0;
-            hasbg = (bgfilename != NULL && icvInitBackgroundReaders( bgfilename,
+            const int hasbg = (bgfilename != NULL && icvInitBackgroundReaders( bgfilename,
                     Size( winwidth,winheight ) ) );

            Mat sample( winheight, winwidth, CV_8UC1 );
@@ -1372,7 +1374,7 @@ int icvGetTraininDataFromVec( Mat& img, CvVecFile& userdata )

    size_t elements_read = fread( &tmp, sizeof( tmp ), 1, userdata.input );
    CV_Assert(elements_read == 1);
-    elements_read = fread( vector, sizeof( short ), userdata.vecsize, userdata.input );
+    elements_read = fread(vector.data(), sizeof(short), userdata.vecsize, userdata.input);
    CV_Assert(elements_read == (size_t)userdata.vecsize);

    if( feof( userdata.input ) || userdata.last++ >= userdata.count )
@@ -224,8 +224,10 @@ void calib::calibDataController::filterFrames()
        cv::Mat newErrorsVec = cv::Mat((int)numberOfFrames - 1, 1, CV_64F);
        std::copy(mCalibData->perViewErrors.ptr<double>(0),
                  mCalibData->perViewErrors.ptr<double>((int)worstElemIndex), newErrorsVec.ptr<double>(0));
-        std::copy(mCalibData->perViewErrors.ptr<double>((int)worstElemIndex + 1), mCalibData->perViewErrors.ptr<double>((int)numberOfFrames),
+        if((int)worstElemIndex < (int)numberOfFrames-1) {
+            std::copy(mCalibData->perViewErrors.ptr<double>((int)worstElemIndex + 1), mCalibData->perViewErrors.ptr<double>((int)numberOfFrames),
                    newErrorsVec.ptr<double>((int)worstElemIndex));
+        }
        mCalibData->perViewErrors = newErrorsVec;
    }
 }
@@ -103,7 +103,7 @@ bool CalibProcessor::detectAndParseChAruco(const cv::Mat &frame)
        return true;
    }
 #else
-    (void)frame;
+    CV_UNUSED(frame);
 #endif
    return false;
 }
@@ -16,7 +16,7 @@ void calib::Euler(const cv::Mat& src, cv::Mat& dst, int argType)
 {
    if((src.rows == 3) && (src.cols == 3))
    {
-        //convert rotaion matrix to 3 angles (pitch, yaw, roll)
+        //convert rotation matrix to 3 angles (pitch, yaw, roll)
        dst = cv::Mat(3, 1, CV_64F);
        double pitch, yaw, roll;

@@ -55,7 +55,7 @@ void calib::Euler(const cv::Mat& src, cv::Mat& dst, int argType)
    else if( (src.cols == 1 && src.rows == 3) ||
             (src.cols == 3 && src.rows == 1 ) )
    {
-        //convert vector which contains 3 angles (pitch, yaw, roll) to rotaion matrix
+        //convert vector which contains 3 angles (pitch, yaw, roll) to rotation matrix
        double pitch, yaw, roll;
        if(src.cols == 1 && src.rows == 3)
        {
@@ -165,7 +165,7 @@ void CvHOGEvaluator::integralHistogram(const Mat &img, vector<Mat> &histogram, M
    Mat qangle(gradSize, CV_8U);

    AutoBuffer<int> mapbuf(gradSize.width + gradSize.height + 4);
-    int* xmap = (int*)mapbuf + 1;
+    int* xmap = mapbuf.data() + 1;
    int* ymap = xmap + gradSize.width + 2;

    const int borderType = (int)BORDER_REPLICATE;
@@ -177,7 +177,7 @@ void CvHOGEvaluator::integralHistogram(const Mat &img, vector<Mat> &histogram, M

    int width = gradSize.width;
    AutoBuffer<float> _dbuf(width*4);
-    float* dbuf = _dbuf;
+    float* dbuf = _dbuf.data();
    Mat Dx(1, width, CV_32F, dbuf);
    Mat Dy(1, width, CV_32F, dbuf + width);
    Mat Mag(1, width, CV_32F, dbuf + width*2);
@@ -30,7 +30,6 @@ using cv::ParallelLoopBody;
 #include "boost.h"
 #include "cascadeclassifier.h"
 #include <queue>
-#include "cxmisc.h"

 #include "cvconfig.h"

@@ -383,7 +382,7 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id
            int ci = get_var_type(vi);
            CV_Assert( ci < 0 );

-            int *src_idx_buf = (int*)(uchar*)inn_buf;
+            int *src_idx_buf = (int*)inn_buf.data();
            float *src_val_buf = (float*)(src_idx_buf + sample_count);
            int* sample_indices_buf = (int*)(src_val_buf + sample_count);
            const int* src_idx = 0;
@@ -423,7 +422,7 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id
        }

        // subsample cv_lables
-        const int* src_lbls = get_cv_labels(data_root, (int*)(uchar*)inn_buf);
+        const int* src_lbls = get_cv_labels(data_root, (int*)inn_buf.data());
        if (is_buf_16u)
        {
            unsigned short* udst = (unsigned short*)(buf->data.s + root->buf_idx*get_length_subbuf() +
@@ -440,7 +439,7 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id
        }

        // subsample sample_indices
-        const int* sample_idx_src = get_sample_indices(data_root, (int*)(uchar*)inn_buf);
+        const int* sample_idx_src = get_sample_indices(data_root, (int*)inn_buf.data());
        if (is_buf_16u)
        {
            unsigned short* sample_idx_dst = (unsigned short*)(buf->data.s + root->buf_idx*get_length_subbuf() +
@@ -543,7 +542,7 @@ void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluat
    featureEvaluator = _featureEvaluator;

    max_c_count = MAX( 2, featureEvaluator->getMaxCatCount() );
-    _resp = featureEvaluator->getCls();
+    _resp = cvMat(featureEvaluator->getCls());
    responses = &_resp;
    // TODO: check responses: elements must be 0 or 1

@@ -815,7 +814,7 @@ struct FeatureIdxOnlyPrecalc : ParallelLoopBody
    void operator()( const Range& range ) const
    {
        cv::AutoBuffer<float> valCache(sample_count);
-        float* valCachePtr = (float*)valCache;
+        float* valCachePtr = valCache.data();
        for ( int fi = range.start; fi < range.end; fi++)
        {
            for( int si = 0; si < sample_count; si++ )
@@ -1084,7 +1083,7 @@ void CvCascadeBoostTree::split_node_data( CvDTreeNode* node )
    CvMat* buf = data->buf;
    size_t length_buf_row = data->get_length_subbuf();
    cv::AutoBuffer<uchar> inn_buf(n*(3*sizeof(int)+sizeof(float)));
-    int* tempBuf = (int*)(uchar*)inn_buf;
+    int* tempBuf = (int*)inn_buf.data();
    bool splitInputData;

    complete_node_dir(node);
@@ -1398,7 +1397,7 @@ void CvCascadeBoost::update_weights( CvBoostTree* tree )
    int inn_buf_size = ((params.boost_type == LOGIT) || (params.boost_type == GENTLE) ? n*sizeof(int) : 0) +
                       ( !tree ? n*sizeof(int) : 0 );
    cv::AutoBuffer<uchar> inn_buf(inn_buf_size);
-    uchar* cur_inn_buf_pos = (uchar*)inn_buf;
+    uchar* cur_inn_buf_pos = inn_buf.data();
    if ( (params.boost_type == LOGIT) || (params.boost_type == GENTLE) )
    {
        step = CV_IS_MAT_CONT(data->responses_copy->type) ?
@@ -2033,7 +2033,8 @@ typedef CvANN_MLP NeuralNet_MLP;
 typedef CvGBTreesParams GradientBoostingTreeParams;
 typedef CvGBTrees GradientBoostingTrees;

-template<> void DefaultDeleter<CvDTreeSplit>::operator ()(CvDTreeSplit* obj) const;
+template<> struct DefaultDeleter<CvDTreeSplit>{ void operator ()(CvDTreeSplit* obj) const; };
+
 }

 #endif // __cplusplus
@@ -168,7 +168,7 @@ CvBoostTree::try_split_node( CvDTreeNode* node )
        // store the responses for the corresponding training samples
        double* weak_eval = ensemble->get_weak_response()->data.db;
        cv::AutoBuffer<int> inn_buf(node->sample_count);
-        const int* labels = data->get_cv_labels( node, (int*)inn_buf );
+        const int* labels = data->get_cv_labels(node, inn_buf.data());
        int i, count = node->sample_count;
        double value = node->value;

@@ -191,7 +191,7 @@ CvBoostTree::calc_node_dir( CvDTreeNode* node )
    if( data->get_var_type(vi) >= 0 ) // split on categorical var
    {
        cv::AutoBuffer<int> inn_buf(n);
-        const int* cat_labels = data->get_cat_var_data( node, vi, (int*)inn_buf );
+        const int* cat_labels = data->get_cat_var_data(node, vi, inn_buf.data());
        const int* subset = node->split->subset;
        double sum = 0, sum_abs = 0;

@@ -210,7 +210,7 @@ CvBoostTree::calc_node_dir( CvDTreeNode* node )
    else // split on ordered var
    {
        cv::AutoBuffer<uchar> inn_buf(2*n*sizeof(int)+n*sizeof(float));
-        float* values_buf = (float*)(uchar*)inn_buf;
+        float* values_buf = (float*)inn_buf.data();
        int* sorted_indices_buf = (int*)(values_buf + n);
        int* sample_indices_buf = sorted_indices_buf + n;
        const float* values = 0;
@@ -260,7 +260,7 @@ CvBoostTree::find_split_ord_class( CvDTreeNode* node, int vi, float init_quality
    cv::AutoBuffer<uchar> inn_buf;
    if( !_ext_buf )
        inn_buf.allocate(n*(3*sizeof(int)+sizeof(float)));
-    uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
+    uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
    float* values_buf = (float*)ext_buf;
    int* sorted_indices_buf = (int*)(values_buf + n);
    int* sample_indices_buf = sorted_indices_buf + n;
@@ -369,7 +369,7 @@ CvBoostTree::find_split_cat_class( CvDTreeNode* node, int vi, float init_quality
    cv::AutoBuffer<uchar> inn_buf((2*mi+3)*sizeof(double) + mi*sizeof(double*));
    if( !_ext_buf)
        inn_buf.allocate( base_size + 2*n*sizeof(int) );
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;

    int* cat_labels_buf = (int*)ext_buf;
@@ -490,7 +490,7 @@ CvBoostTree::find_split_ord_reg( CvDTreeNode* node, int vi, float init_quality,
    cv::AutoBuffer<uchar> inn_buf;
    if( !_ext_buf )
        inn_buf.allocate(2*n*(sizeof(int)+sizeof(float)));
-    uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
+    uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();

    float* values_buf = (float*)ext_buf;
    int* indices_buf = (int*)(values_buf + n);
@@ -559,7 +559,7 @@ CvBoostTree::find_split_cat_reg( CvDTreeNode* node, int vi, float init_quality,
    cv::AutoBuffer<uchar> inn_buf(base_size);
    if( !_ext_buf )
        inn_buf.allocate(base_size + n*(2*sizeof(int) + sizeof(float)));
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;

    int* cat_labels_buf = (int*)ext_buf;
@@ -652,7 +652,7 @@ CvBoostTree::find_surrogate_split_ord( CvDTreeNode* node, int vi, uchar* _ext_bu
    cv::AutoBuffer<uchar> inn_buf;
    if( !_ext_buf )
        inn_buf.allocate(n*(2*sizeof(int)+sizeof(float)));
-    uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
+    uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
    float* values_buf = (float*)ext_buf;
    int* indices_buf = (int*)(values_buf + n);
    int* sample_indices_buf = indices_buf + n;
@@ -733,7 +733,7 @@ CvBoostTree::find_surrogate_split_cat( CvDTreeNode* node, int vi, uchar* _ext_bu
    cv::AutoBuffer<uchar> inn_buf(base_size);
    if( !_ext_buf )
        inn_buf.allocate(base_size + n*sizeof(int));
-    uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
+    uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
    int* cat_labels_buf = (int*)ext_buf;
    const int* cat_labels = data->get_cat_var_data(node, vi, cat_labels_buf);

@@ -797,7 +797,7 @@ CvBoostTree::calc_node_value( CvDTreeNode* node )
    int i, n = node->sample_count;
    const double* weights = ensemble->get_weights()->data.db;
    cv::AutoBuffer<uchar> inn_buf(n*(sizeof(int) + ( data->is_classifier ? sizeof(int) : sizeof(int) + sizeof(float))));
-    int* labels_buf = (int*)(uchar*)inn_buf;
+    int* labels_buf = (int*)inn_buf.data();
    const int* labels = data->get_cv_labels(node, labels_buf);
    double* subtree_weights = ensemble->get_subtree_weights()->data.db;
    double rcw[2] = {0,0};
@@ -1147,7 +1147,7 @@ CvBoost::update_weights( CvBoostTree* tree )
            _buf_size += data->get_length_subbuf()*(sizeof(float)+sizeof(uchar));
    }
    inn_buf.allocate(_buf_size);
-    uchar* cur_buf_pos = (uchar*)inn_buf;
+    uchar* cur_buf_pos = inn_buf.data();

    if ( (params.boost_type == LOGIT) || (params.boost_type == GENTLE) )
    {
@@ -2122,12 +2122,12 @@ CvBoost::train( const Mat& _train_data, int _tflag,
               const Mat& _missing_mask,
               CvBoostParams _params, bool _update )
 {
-    train_data_hdr = _train_data;
+    train_data_hdr = cvMat(_train_data);
    train_data_mat = _train_data;
-    responses_hdr = _responses;
+    responses_hdr = cvMat(_responses);
    responses_mat = _responses;

-    CvMat vidx = _var_idx, sidx = _sample_idx, vtype = _var_type, mmask = _missing_mask;
+    CvMat vidx = cvMat(_var_idx), sidx = cvMat(_sample_idx), vtype = cvMat(_var_type), mmask = cvMat(_missing_mask);

    return train(&train_data_hdr, _tflag, &responses_hdr, vidx.data.ptr ? &vidx : 0,
          sidx.data.ptr ? &sidx : 0, vtype.data.ptr ? &vtype : 0,
@@ -2138,7 +2138,7 @@ float
 CvBoost::predict( const Mat& _sample, const Mat& _missing,
                  const Range& slice, bool raw_mode, bool return_sum ) const
 {
-    CvMat sample = _sample, mmask = _missing;
+    CvMat sample = cvMat(_sample), mmask = cvMat(_missing);
    /*if( weak_responses )
    {
        int weak_count = cvSliceLength( slice, weak );
@@ -780,7 +780,7 @@ CvDTreeNode* CvDTreeTrainData::subsample_data( const CvMat* _subsample_idx )
            if( ci >= 0 || vi >= var_count )
            {
                int num_valid = 0;
-                const int* src = CvDTreeTrainData::get_cat_var_data( data_root, vi, (int*)(uchar*)inn_buf );
+                const int* src = CvDTreeTrainData::get_cat_var_data(data_root, vi, (int*)inn_buf.data());

                if (is_buf_16u)
                {
@@ -810,7 +810,7 @@ CvDTreeNode* CvDTreeTrainData::subsample_data( const CvMat* _subsample_idx )
            }
            else
            {
-                int *src_idx_buf = (int*)(uchar*)inn_buf;
+                int *src_idx_buf = (int*)inn_buf.data();
                float *src_val_buf = (float*)(src_idx_buf + sample_count);
                int* sample_indices_buf = (int*)(src_val_buf + sample_count);
                const int* src_idx = 0;
@@ -870,7 +870,7 @@ CvDTreeNode* CvDTreeTrainData::subsample_data( const CvMat* _subsample_idx )
            }
        }
        // sample indices subsampling
-        const int* sample_idx_src = get_sample_indices(data_root, (int*)(uchar*)inn_buf);
+        const int* sample_idx_src = get_sample_indices(data_root, (int*)inn_buf.data());
        if (is_buf_16u)
        {
            unsigned short* sample_idx_dst = (unsigned short*)(buf->data.s + root->buf_idx*get_length_subbuf() +
@@ -943,7 +943,7 @@ void CvDTreeTrainData::get_vectors( const CvMat* _subsample_idx,
        {
            float* dst = values + vi;
            uchar* m = missing ? missing + vi : 0;
-            const int* src = get_cat_var_data(data_root, vi, (int*)(uchar*)inn_buf);
+            const int* src = get_cat_var_data(data_root, vi, (int*)inn_buf.data());

            for( i = 0; i < count; i++, dst += var_count )
            {
@@ -962,7 +962,7 @@ void CvDTreeTrainData::get_vectors( const CvMat* _subsample_idx,
            float* dst = values + vi;
            uchar* m = missing ? missing + vi : 0;
            int count1 = data_root->get_num_valid(vi);
-            float *src_val_buf = (float*)(uchar*)inn_buf;
+            float *src_val_buf = (float*)inn_buf.data();
            int* src_idx_buf = (int*)(src_val_buf + sample_count);
            int* sample_indices_buf = src_idx_buf + sample_count;
            const float *src_val = 0;
@@ -999,7 +999,7 @@ void CvDTreeTrainData::get_vectors( const CvMat* _subsample_idx,
    {
        if( is_classifier )
        {
-            const int* src = get_class_labels(data_root, (int*)(uchar*)inn_buf);
+            const int* src = get_class_labels(data_root, (int*)inn_buf.data());
            for( i = 0; i < count; i++ )
            {
                int idx = sidx ? sidx[i] : i;
@@ -1010,7 +1010,7 @@ void CvDTreeTrainData::get_vectors( const CvMat* _subsample_idx,
        }
        else
        {
-            float* val_buf = (float*)(uchar*)inn_buf;
+            float* val_buf = (float*)inn_buf.data();
            int* sample_idx_buf = (int*)(val_buf + sample_count);
            const float* _values = get_ord_responses(data_root, val_buf, sample_idx_buf);
            for( i = 0; i < count; i++ )
@@ -1592,12 +1592,12 @@ bool CvDTree::train( const Mat& _train_data, int _tflag,
                    const Mat& _sample_idx, const Mat& _var_type,
                    const Mat& _missing_mask, CvDTreeParams _params )
 {
-    train_data_hdr = _train_data;
+    train_data_hdr = cvMat(_train_data);
    train_data_mat = _train_data;
-    responses_hdr = _responses;
+    responses_hdr = cvMat(_responses);
    responses_mat = _responses;

-    CvMat vidx=_var_idx, sidx=_sample_idx, vtype=_var_type, mmask=_missing_mask;
+    CvMat vidx=cvMat(_var_idx), sidx=cvMat(_sample_idx), vtype=cvMat(_var_type), mmask=cvMat(_missing_mask);

    return train(&train_data_hdr, _tflag, &responses_hdr, vidx.data.ptr ? &vidx : 0, sidx.data.ptr ? &sidx : 0,
                 vtype.data.ptr ? &vtype : 0, mmask.data.ptr ? &mmask : 0, _params);
@@ -1780,7 +1780,7 @@ double CvDTree::calc_node_dir( CvDTreeNode* node )
    if( data->get_var_type(vi) >= 0 ) // split on categorical var
    {
        cv::AutoBuffer<int> inn_buf(n*(!data->have_priors ? 1 : 2));
-        int* labels_buf = (int*)inn_buf;
+        int* labels_buf = inn_buf.data();
        const int* labels = data->get_cat_var_data( node, vi, labels_buf );
        const int* subset = node->split->subset;
        if( !data->have_priors )
@@ -1824,7 +1824,7 @@ double CvDTree::calc_node_dir( CvDTreeNode* node )
        int split_point = node->split->ord.split_point;
        int n1 = node->get_num_valid(vi);
        cv::AutoBuffer<uchar> inn_buf(n*(sizeof(int)*(data->have_priors ? 3 : 2) + sizeof(float)));
-        float* val_buf = (float*)(uchar*)inn_buf;
+        float* val_buf = (float*)inn_buf.data();
        int* sorted_buf = (int*)(val_buf + n);
        int* sample_idx_buf = sorted_buf + n;
        const float* val = 0;
@@ -1880,10 +1880,7 @@ double CvDTree::calc_node_dir( CvDTreeNode* node )
 namespace cv
 {

-template<> void DefaultDeleter<CvDTreeSplit>::operator ()(CvDTreeSplit* obj) const
-{
-    fastFree(obj);
-}
+void DefaultDeleter<CvDTreeSplit>::operator ()(CvDTreeSplit* obj) const { fastFree(obj); }

 DTreeBestSplitFinder::DTreeBestSplitFinder( CvDTree* _tree, CvDTreeNode* _node)
 {
@@ -1929,16 +1926,16 @@ void DTreeBestSplitFinder::operator()(const BlockedRange& range)
        if( data->is_classifier )
        {
            if( ci >= 0 )
-                res = tree->find_split_cat_class( node, vi, bestSplit->quality, split, (uchar*)inn_buf );
+                res = tree->find_split_cat_class( node, vi, bestSplit->quality, split, inn_buf.data() );
            else
-                res = tree->find_split_ord_class( node, vi, bestSplit->quality, split, (uchar*)inn_buf );
+                res = tree->find_split_ord_class( node, vi, bestSplit->quality, split, inn_buf.data() );
        }
        else
        {
            if( ci >= 0 )
-                res = tree->find_split_cat_reg( node, vi, bestSplit->quality, split, (uchar*)inn_buf );
+                res = tree->find_split_cat_reg( node, vi, bestSplit->quality, split, inn_buf.data() );
            else
-                res = tree->find_split_ord_reg( node, vi, bestSplit->quality, split, (uchar*)inn_buf );
+                res = tree->find_split_ord_reg( node, vi, bestSplit->quality, split, inn_buf.data() );
        }

        if( res && bestSplit->quality < split->quality )
@@ -1982,7 +1979,7 @@ CvDTreeSplit* CvDTree::find_split_ord_class( CvDTreeNode* node, int vi,
    cv::AutoBuffer<uchar> inn_buf(base_size);
    if( !_ext_buf )
      inn_buf.allocate(base_size + n*(3*sizeof(int)+sizeof(float)));
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;
    float* values_buf = (float*)ext_buf;
    int* sorted_indices_buf = (int*)(values_buf + n);
@@ -2096,7 +2093,7 @@ void CvDTree::cluster_categories( const int* vectors, int n, int m,
    int iters = 0, max_iters = 100;
    int i, j, idx;
    cv::AutoBuffer<double> buf(n + k);
-    double *v_weights = buf, *c_weights = buf + n;
+    double *v_weights = buf.data(), *c_weights = buf.data() + n;
    bool modified = true;
    RNG* r = data->rng;

@@ -2201,7 +2198,7 @@ CvDTreeSplit* CvDTree::find_split_cat_class( CvDTreeNode* node, int vi, float in
    cv::AutoBuffer<uchar> inn_buf(base_size);
    if( !_ext_buf )
        inn_buf.allocate(base_size + 2*n*sizeof(int));
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;

    int* lc = (int*)base_buf;
@@ -2383,7 +2380,7 @@ CvDTreeSplit* CvDTree::find_split_ord_reg( CvDTreeNode* node, int vi, float init
    cv::AutoBuffer<uchar> inn_buf;
    if( !_ext_buf )
        inn_buf.allocate(2*n*(sizeof(int) + sizeof(float)));
-    uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
+    uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
    float* values_buf = (float*)ext_buf;
    int* sorted_indices_buf = (int*)(values_buf + n);
    int* sample_indices_buf = sorted_indices_buf + n;
@@ -2443,7 +2440,7 @@ CvDTreeSplit* CvDTree::find_split_cat_reg( CvDTreeNode* node, int vi, float init
    cv::AutoBuffer<uchar> inn_buf(base_size);
    if( !_ext_buf )
        inn_buf.allocate(base_size + n*(2*sizeof(int) + sizeof(float)));
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;
    int* labels_buf = (int*)ext_buf;
    const int* labels = data->get_cat_var_data(node, vi, labels_buf);
@@ -2534,7 +2531,7 @@ CvDTreeSplit* CvDTree::find_surrogate_split_ord( CvDTreeNode* node, int vi, ucha
    cv::AutoBuffer<uchar> inn_buf;
    if( !_ext_buf )
        inn_buf.allocate( n*(sizeof(int)*(data->have_priors ? 3 : 2) + sizeof(float)) );
-    uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
+    uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
    float* values_buf = (float*)ext_buf;
    int* sorted_indices_buf = (int*)(values_buf + n);
    int* sample_indices_buf = sorted_indices_buf + n;
@@ -2658,7 +2655,7 @@ CvDTreeSplit* CvDTree::find_surrogate_split_cat( CvDTreeNode* node, int vi, ucha
    cv::AutoBuffer<uchar> inn_buf(base_size);
    if( !_ext_buf )
        inn_buf.allocate(base_size + n*(sizeof(int) + (data->have_priors ? sizeof(int) : 0)));
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;

    int* labels_buf = (int*)ext_buf;
@@ -2758,7 +2755,7 @@ void CvDTree::calc_node_value( CvDTreeNode* node )
    int base_size = data->is_classifier ? m*cv_n*sizeof(int) : 2*cv_n*sizeof(double)+cv_n*sizeof(int);
    int ext_size = n*(sizeof(int) + (data->is_classifier ? sizeof(int) : sizeof(int)+sizeof(float)));
    cv::AutoBuffer<uchar> inn_buf(base_size + ext_size);
-    uchar* base_buf = (uchar*)inn_buf;
+    uchar* base_buf = inn_buf.data();
    uchar* ext_buf = base_buf + base_size;

    int* cv_labels_buf = (int*)ext_buf;
@@ -2961,7 +2958,7 @@ void CvDTree::complete_node_dir( CvDTreeNode* node )

            if( data->get_var_type(vi) >= 0 ) // split on categorical var
            {
-                int* labels_buf = (int*)(uchar*)inn_buf;
+                int* labels_buf = (int*)inn_buf.data();
                const int* labels = data->get_cat_var_data(node, vi, labels_buf);
                const int* subset = split->subset;

@@ -2980,7 +2977,7 @@ void CvDTree::complete_node_dir( CvDTreeNode* node )
            }
            else // split on ordered var
            {
-                float* values_buf = (float*)(uchar*)inn_buf;
+                float* values_buf = (float*)inn_buf.data();
                int* sorted_indices_buf = (int*)(values_buf + n);
                int* sample_indices_buf = sorted_indices_buf + n;
                const float* values = 0;
@@ -3042,7 +3039,7 @@ void CvDTree::split_node_data( CvDTreeNode* node )
    CvMat* buf = data->buf;
    size_t length_buf_row = data->get_length_subbuf();
    cv::AutoBuffer<uchar> inn_buf(n*(3*sizeof(int) + sizeof(float)));
-    int* temp_buf = (int*)(uchar*)inn_buf;
+    int* temp_buf = (int*)inn_buf.data();

    complete_node_dir(node);

@@ -3734,7 +3731,7 @@ CvDTreeNode* CvDTree::predict( const CvMat* _sample,

 CvDTreeNode* CvDTree::predict( const Mat& _sample, const Mat& _missing, bool preprocessed_input ) const
 {
-    CvMat sample = _sample, mmask = _missing;
+    CvMat sample = cvMat(_sample), mmask = cvMat(_missing);
    return predict(&sample, mmask.data.ptr ? &mmask : 0, preprocessed_input);
 }

@@ -141,7 +141,7 @@
 #   -- Same as CUDA_ADD_EXECUTABLE except that a library is created.
 #
 #   CUDA_BUILD_CLEAN_TARGET()
-#   -- Creates a convience target that deletes all the dependency files
+#   -- Creates a convenience target that deletes all the dependency files
 #      generated.  You should make clean after running this target to ensure the
 #      dependency files get regenerated.
 #
@@ -473,7 +473,7 @@ else()
 endif()

 # Propagate the host flags to the host compiler via -Xcompiler
-option(CUDA_PROPAGATE_HOST_FLAGS "Propage C/CXX_FLAGS and friends to the host compiler via -Xcompile" ON)
+option(CUDA_PROPAGATE_HOST_FLAGS "Propagate C/CXX_FLAGS and friends to the host compiler via -Xcompile" ON)

 # Enable CUDA_SEPARABLE_COMPILATION
 option(CUDA_SEPARABLE_COMPILATION "Compile CUDA objects with separable compilation enabled.  Requires CUDA 5.0+" OFF)
@@ -700,12 +700,21 @@ macro(ocv_compiler_optimization_fill_cpu_config)
    list(APPEND __dispatch_modes ${CPU_DISPATCH_${OPT}_FORCE} ${OPT})
  endforeach()
  list(REMOVE_DUPLICATES __dispatch_modes)
-  set(OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE "")
  foreach(OPT ${__dispatch_modes})
    set(OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE "${OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE}
 #define CV_CPU_DISPATCH_COMPILE_${OPT} 1")
  endforeach()

+  set(OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE "${OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE}
+\n\n#define CV_CPU_DISPATCH_FEATURES 0 \\")
+  foreach(OPT ${__dispatch_modes})
+    if(NOT DEFINED CPU_${OPT}_FEATURE_ALIAS OR NOT "x${CPU_${OPT}_FEATURE_ALIAS}" STREQUAL "x")
+      set(OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE "${OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE}
+    , CV_CPU_${OPT} \\")
+    endif()
+  endforeach()
+  set(OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE "${OPENCV_CPU_DISPATCH_DEFINITIONS_CONFIGMAKE}\n")
+
  set(OPENCV_CPU_CONTROL_DEFINITIONS_CONFIGMAKE "// AUTOGENERATED, DO NOT EDIT\n")
  foreach(OPT ${CPU_ALL_OPTIMIZATIONS})
    if(NOT DEFINED CPU_${OPT}_FEATURE_ALIAS OR NOT "x${CPU_${OPT}_FEATURE_ALIAS}" STREQUAL "x")
@@ -740,7 +749,7 @@ macro(ocv_compiler_optimization_fill_cpu_config)
 ")


-  set(__file "${CMAKE_SOURCE_DIR}/modules/core/include/opencv2/core/cv_cpu_helper.h")
+  set(__file "${OpenCV_SOURCE_DIR}/modules/core/include/opencv2/core/cv_cpu_helper.h")
  if(EXISTS "${__file}")
    file(READ "${__file}" __content)
  endif()
@@ -752,24 +761,24 @@ macro(ocv_compiler_optimization_fill_cpu_config)
  endif()
 endmacro()

-macro(ocv_add_dispatched_file filename)
+macro(__ocv_add_dispatched_file filename target_src_var src_directory dst_directory precomp_hpp optimizations_var)
  if(NOT OPENCV_INITIAL_PASS)
    set(__codestr "
-#include \"${CMAKE_CURRENT_LIST_DIR}/src/precomp.hpp\"
-#include \"${CMAKE_CURRENT_LIST_DIR}/src/${filename}.simd.hpp\"
+#include \"${src_directory}/${precomp_hpp}\"
+#include \"${src_directory}/${filename}.simd.hpp\"
 ")

-    set(__declarations_str "#define CV_CPU_SIMD_FILENAME \"${CMAKE_CURRENT_LIST_DIR}/src/${filename}.simd.hpp\"")
+    set(__declarations_str "#define CV_CPU_SIMD_FILENAME \"${src_directory}/${filename}.simd.hpp\"")
    set(__dispatch_modes "BASELINE")

-    set(__optimizations "${ARGN}")
+    set(__optimizations "${${optimizations_var}}")
    if(CV_DISABLE_OPTIMIZATION OR NOT CV_ENABLE_INTRINSICS)
      set(__optimizations "")
    endif()

    foreach(OPT ${__optimizations})
      string(TOLOWER "${OPT}" OPT_LOWER)
-      set(__file "${CMAKE_CURRENT_BINARY_DIR}/${filename}.${OPT_LOWER}.cpp")
+      set(__file "${CMAKE_CURRENT_BINARY_DIR}/${dst_directory}${filename}.${OPT_LOWER}.cpp")
      if(EXISTS "${__file}")
        file(READ "${__file}" __content)
      else()
@@ -782,7 +791,11 @@ macro(ocv_add_dispatched_file filename)
      endif()

      if(";${CPU_DISPATCH};" MATCHES "${OPT}" OR __CPU_DISPATCH_INCLUDE_ALL)
-        list(APPEND OPENCV_MODULE_${the_module}_SOURCES_DISPATCHED "${__file}")
+        if(EXISTS "${src_directory}/${filename}.${OPT_LOWER}.cpp")
+          message(STATUS "Using overrided ${OPT} source: ${src_directory}/${filename}.${OPT_LOWER}.cpp")
+        else()
+          list(APPEND ${target_src_var} "${__file}")
+        endif()
      endif()

      set(__declarations_str "${__declarations_str}
@@ -794,9 +807,11 @@ macro(ocv_add_dispatched_file filename)

    set(__declarations_str "${__declarations_str}
 #define CV_CPU_DISPATCH_MODES_ALL ${__dispatch_modes}
+
+#undef CV_CPU_SIMD_FILENAME
 ")

-    set(__file "${CMAKE_CURRENT_BINARY_DIR}/${filename}.simd_declarations.hpp")
+    set(__file "${CMAKE_CURRENT_BINARY_DIR}/${dst_directory}${filename}.simd_declarations.hpp")
    if(EXISTS "${__file}")
      file(READ "${__file}" __content)
    endif()
@@ -808,6 +823,17 @@ macro(ocv_add_dispatched_file filename)
  endif()
 endmacro()

+macro(ocv_add_dispatched_file filename)
+  set(__optimizations "${ARGN}")
+  if(" ${ARGV1}" STREQUAL " TEST")
+    list(REMOVE_AT __optimizations 0)
+    __ocv_add_dispatched_file("${filename}" "OPENCV_MODULE_${the_module}_TEST_SOURCES_DISPATCHED" "${CMAKE_CURRENT_LIST_DIR}/test" "test/" "test_precomp.hpp" __optimizations)
+  else()
+    __ocv_add_dispatched_file("${filename}" "OPENCV_MODULE_${the_module}_SOURCES_DISPATCHED" "${CMAKE_CURRENT_LIST_DIR}/src" "" "precomp.hpp" __optimizations)
+  endif()
+endmacro()
+
+
 # Workaround to support code which always require all code paths
 macro(ocv_add_dispatched_file_force_all)
  set(__CPU_DISPATCH_INCLUDE_ALL 1)
@@ -125,8 +125,8 @@ if(CV_GCC OR CV_CLANG)
    )
      add_extra_compiler_option(-Wimplicit-fallthrough=3)
    endif()
-    if(CV_GCC AND CMAKE_CXX_COMPILER_VERSION VERSION_EQUAL 7.2.0)
-      add_extra_compiler_option(-Wno-strict-overflow) # Issue is fixed in GCC 7.2.1
+    if(CV_GCC AND CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 7.0)
+      add_extra_compiler_option(-Wno-strict-overflow) # Issue appears when compiling surf.cpp from opencv_contrib/modules/xfeatures2d
    endif()
  endif()
  add_extra_compiler_option(-fdiagnostics-show-option)
@@ -1,11 +0,0 @@
-if(WIN32)
-    find_path( CSTRIPES_LIB_DIR
-               NAMES "C=.lib"
-               DOC "The path to C= lib and dll")
-    if(CSTRIPES_LIB_DIR)
-        ocv_include_directories("${CSTRIPES_LIB_DIR}/..")
-        link_directories("${CSTRIPES_LIB_DIR}")
-        set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} "C=")
-        set(HAVE_CSTRIPES 1)
-    endif()
-endif()
@@ -3,19 +3,28 @@ if(WIN32 AND NOT MSVC)
  return()
 endif()

-if(NOT APPLE AND CV_CLANG)
+if(NOT UNIX AND CV_CLANG)
  message(STATUS "CUDA compilation is disabled (due to Clang unsupported on your platform).")
  return()
 endif()

-set(CMAKE_MODULE_PATH "${OpenCV_SOURCE_DIR}/cmake" ${CMAKE_MODULE_PATH})

-if(ANDROID)
-  set(CUDA_TARGET_OS_VARIANT "Android")
+if(((NOT CMAKE_VERSION VERSION_LESS "3.9.0")  # requires https://gitlab.kitware.com/cmake/cmake/merge_requests/663
+      OR OPENCV_CUDA_FORCE_EXTERNAL_CMAKE_MODULE)
+    AND NOT OPENCV_CUDA_FORCE_BUILTIN_CMAKE_MODULE)
+  ocv_update(CUDA_LINK_LIBRARIES_KEYWORD "LINK_PRIVATE")
+  find_host_package(CUDA "${MIN_VER_CUDA}" QUIET)
+else()
+  # Use OpenCV's patched "FindCUDA" module
+  set(CMAKE_MODULE_PATH "${OpenCV_SOURCE_DIR}/cmake" ${CMAKE_MODULE_PATH})
+
+  if(ANDROID)
+    set(CUDA_TARGET_OS_VARIANT "Android")
+  endif()
+  find_host_package(CUDA "${MIN_VER_CUDA}" QUIET)
+
+  list(REMOVE_AT CMAKE_MODULE_PATH 0)
 endif()
-find_host_package(CUDA "${MIN_VER_CUDA}" QUIET)
-
-list(REMOVE_AT CMAKE_MODULE_PATH 0)

 if(CUDA_FOUND)
  set(HAVE_CUDA 1)
@@ -61,6 +70,12 @@ if(CUDA_FOUND)
    unset(CUDA_ARCH_PTX CACHE)
  endif()

+  SET(DETECT_ARCHS_COMMAND "${CUDA_NVCC_EXECUTABLE}" ${CUDA_NVCC_FLAGS} "${OpenCV_SOURCE_DIR}/cmake/checks/OpenCVDetectCudaArch.cu" "--run")
+  if(WIN32 AND CMAKE_LINKER) #Workaround for VS cl.exe not being in the env. path
+    get_filename_component(host_compiler_bindir ${CMAKE_LINKER} DIRECTORY)
+    SET(DETECT_ARCHS_COMMAND ${DETECT_ARCHS_COMMAND} "-ccbin" "${host_compiler_bindir}")
+  endif()
+
  set(__cuda_arch_ptx "")
  if(CUDA_GENERATION STREQUAL "Fermi")
    set(__cuda_arch_bin "2.0")
@@ -73,10 +88,11 @@ if(CUDA_FOUND)
  elseif(CUDA_GENERATION STREQUAL "Volta")
    set(__cuda_arch_bin "7.0")
  elseif(CUDA_GENERATION STREQUAL "Auto")
-    execute_process( COMMAND "${CUDA_NVCC_EXECUTABLE}" ${CUDA_NVCC_FLAGS} "${OpenCV_SOURCE_DIR}/cmake/checks/OpenCVDetectCudaArch.cu" "--run"
+    execute_process( COMMAND ${DETECT_ARCHS_COMMAND}
                     WORKING_DIRECTORY "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/"
                     RESULT_VARIABLE _nvcc_res OUTPUT_VARIABLE _nvcc_out
                     ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
+    string(REGEX REPLACE ".*\n" "" _nvcc_out "${_nvcc_out}") #Strip leading warning messages, if any
    if(NOT _nvcc_res EQUAL 0)
      message(STATUS "Automatic detection of CUDA generation failed. Going to build for all known architectures.")
    else()
@@ -90,10 +106,11 @@ if(CUDA_FOUND)
      set(__cuda_arch_bin "3.2")
      set(__cuda_arch_ptx "")
    elseif(AARCH64)
-      execute_process( COMMAND "${CUDA_NVCC_EXECUTABLE}" ${CUDA_NVCC_FLAGS} "${OpenCV_SOURCE_DIR}/cmake/checks/OpenCVDetectCudaArch.cu" "--run"
+      execute_process( COMMAND ${DETECT_ARCHS_COMMAND}
                       WORKING_DIRECTORY "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/"
                       RESULT_VARIABLE _nvcc_res OUTPUT_VARIABLE _nvcc_out
                       ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
+      string(REGEX REPLACE ".*\n" "" _nvcc_out "${_nvcc_out}") #Strip leading warning messages, if any
      if(NOT _nvcc_res EQUAL 0)
        message(STATUS "Automatic detection of CUDA generation failed. Going to build for all known architectures.")
        set(__cuda_arch_bin "5.3 6.2 7.0")
@@ -179,6 +196,13 @@ if(CUDA_FOUND)
    foreach(var CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_RELEASE CMAKE_CXX_FLAGS_DEBUG)
      set(${var}_backup_in_cuda_compile_ "${${var}}")

+      if (CV_CLANG)
+        # we remove -Winconsistent-missing-override and -Qunused-arguments
+        # just in case we are compiling CUDA with gcc but OpenCV with clang
+        string(REPLACE "-Winconsistent-missing-override" "" ${var} "${${var}}")
+        string(REPLACE "-Qunused-arguments" "" ${var} "${${var}}")
+      endif()
+
      # we remove /EHa as it generates warnings under windows
      string(REPLACE "/EHa" "" ${var} "${${var}}")

@@ -224,7 +248,7 @@ if(CUDA_FOUND)
    endif()

    if(UNIX OR APPLE)
-      set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} -Xcompiler -fPIC)
+      set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} -Xcompiler -fPIC --std=c++11)
    endif()
    if(APPLE)
      set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} -Xcompiler -fno-finite-math-only)
@@ -166,14 +166,11 @@ if(CMAKE_VERSION VERSION_LESS "3.1")
  endforeach()
 endif()

-if(ENABLE_CXX11)
-  #cmake_minimum_required(VERSION 3.1.0 FATAL_ERROR)
-  set(CMAKE_CXX_STANDARD 11)
-  set(CMAKE_CXX_STANDARD_REQUIRED TRUE)
-  set(CMAKE_CXX_EXTENSIONS OFF) # use -std=c++11 instead of -std=gnu++11
-  if(CMAKE_CXX11_COMPILE_FEATURES)
-    set(HAVE_CXX11 ON)
-  endif()
+set(CMAKE_CXX_STANDARD 11)
+set(CMAKE_CXX_STANDARD_REQUIRED TRUE)
+set(CMAKE_CXX_EXTENSIONS OFF) # use -std=c++11 instead of -std=gnu++11
+if(CMAKE_CXX11_COMPILE_FEATURES)
+  set(HAVE_CXX11 ON)
 endif()
 if(NOT HAVE_CXX11)
  ocv_check_compiler_flag(CXX "" HAVE_CXX11 "${OpenCV_SOURCE_DIR}/cmake/checks/cxx11.cpp")
@@ -185,3 +182,6 @@ if(NOT HAVE_CXX11)
    endif()
  endif()
 endif()
+if(NOT HAVE_CXX11)
+  message(FATAL_ERROR "OpenCV 4.x requires C++11")
+endif()
@@ -1,71 +1,87 @@
 # The script detects Intel(R) Inference Engine installation
 #
-# Parameters:
-# INTEL_CVSDK_DIR - Path to Inference Engine root folder
-# IE_PLUGINS_PATH - Path to folder with Inference Engine plugins
+# Cache variables:
+# INF_ENGINE_OMP_DIR - directory with OpenMP library to link with (needed by some versions of IE)
+# INF_ENGINE_RELEASE - a number reflecting IE source interface (linked with OpenVINO release)
 #
-# On return this will define:
+# Detect parameters:
+# 1. Native cmake IE package:
+#    - enironment variable InferenceEngine_DIR is set to location of cmake module
+# 2. Custom location:
+#    - INF_ENGINE_INCLUDE_DIRS - headers search location
+#    - INF_ENGINE_LIB_DIRS     - library search location
+# 3. OpenVINO location:
+#    - environment variable INTEL_CVSDK_DIR is set to location of OpenVINO installation dir
+#    - INF_ENGINE_PLATFORM - part of name of library directory representing its platform (default ubuntu_16.04)
 #
-# HAVE_INF_ENGINE          - True if Intel Inference Engine was found
-# INF_ENGINE_INCLUDE_DIRS  - Inference Engine include folder
-# INF_ENGINE_LIBRARIES     - Inference Engine libraries and it's dependencies
+# Result:
+# INF_ENGINE_TARGET - set to name of imported library target representing InferenceEngine
 #
-macro(ie_fail)
-    set(HAVE_INF_ENGINE FALSE)
-    return()
-endmacro()

 if(NOT HAVE_CXX11)
-    ie_fail()
+    message(WARNING "DL Inference engine requires C++11. You can turn it on via ENABLE_CXX11=ON CMake flag.")
+    return()
 endif()

-if(NOT INF_ENGINE_ROOT_DIR OR NOT EXISTS "${INF_ENGINE_ROOT_DIR}/include/inference_engine.hpp")
-    set(ie_root_paths "${INF_ENGINE_ROOT_DIR}")
-    if(DEFINED ENV{INTEL_CVSDK_DIR})
-        list(APPEND ie_root_paths "$ENV{INTEL_CVSDK_DIR}")
-        list(APPEND ie_root_paths "$ENV{INTEL_CVSDK_DIR}/inference_engine")
-    endif()
-    if(DEFINED INTEL_CVSDK_DIR)
-        list(APPEND ie_root_paths "${INTEL_CVSDK_DIR}")
-        list(APPEND ie_root_paths "${INTEL_CVSDK_DIR}/inference_engine")
-    endif()
+# =======================

-    if(NOT ie_root_paths)
-        list(APPEND ie_root_paths "/opt/intel/deeplearning_deploymenttoolkit/deployment_tools/inference_engine")
-    endif()
+function(add_custom_ie_build _inc _lib _lib_rel _lib_dbg _msg)
+  if(NOT _inc OR NOT (_lib OR _lib_rel OR _lib_dbg))
+    return()
+  endif()
+  add_library(inference_engine UNKNOWN IMPORTED)
+  set_target_properties(inference_engine PROPERTIES
+    IMPORTED_LOCATION "${_lib}"
+    IMPORTED_IMPLIB_RELEASE "${_lib_rel}"
+    IMPORTED_IMPLIB_DEBUG "${_lib_dbg}"
+    INTERFACE_INCLUDE_DIRECTORIES "${_inc}"
+  )
+  find_library(omp_lib iomp5 PATHS "${INF_ENGINE_OMP_DIR}" NO_DEFAULT_PATH)
+  if(NOT omp_lib)
+    message(WARNING "OpenMP for IE have not been found. Set INF_ENGINE_OMP_DIR variable if you experience build errors.")
+  else()
+    set_target_properties(inference_engine PROPERTIES IMPORTED_LINK_INTERFACE_LIBRARIES "${omp_lib}")
+  endif()
+  set(INF_ENGINE_VERSION "Unknown" CACHE STRING "")
+  set(INF_ENGINE_TARGET inference_engine PARENT_SCOPE)
+  message(STATUS "Detected InferenceEngine: ${_msg}")
+endfunction()

-    find_path(INF_ENGINE_ROOT_DIR include/inference_engine.hpp PATHS ${ie_root_paths})
+# ======================
+
+find_package(InferenceEngine QUIET)
+if(InferenceEngine_FOUND)
+  set(INF_ENGINE_TARGET IE::inference_engine)
+  set(INF_ENGINE_VERSION "${InferenceEngine_VERSION}" CACHE STRING "")
+  message(STATUS "Detected InferenceEngine: cmake package")
 endif()

-set(INF_ENGINE_INCLUDE_DIRS "${INF_ENGINE_ROOT_DIR}/include" CACHE PATH "Path to Inference Engine include directory")
-
-if(NOT INF_ENGINE_ROOT_DIR
-    OR NOT EXISTS "${INF_ENGINE_ROOT_DIR}"
-    OR NOT EXISTS "${INF_ENGINE_ROOT_DIR}/include/inference_engine.hpp"
-)
-    ie_fail()
+if(NOT INF_ENGINE_TARGET AND INF_ENGINE_LIB_DIRS AND INF_ENGINE_INCLUDE_DIRS)
+  find_path(ie_custom_inc "inference_engine.hpp" PATHS "${INF_ENGINE_INCLUDE_DIRS}" NO_DEFAULT_PATH)
+  find_library(ie_custom_lib "inference_engine" PATHS "${INF_ENGINE_LIB_DIRS}" NO_DEFAULT_PATH)
+  find_library(ie_custom_lib_rel "inference_engine" PATHS "${INF_ENGINE_LIB_DIRS}/Release" NO_DEFAULT_PATH)
+  find_library(ie_custom_lib_dbg "inference_engine" PATHS "${INF_ENGINE_LIB_DIRS}/Debug" NO_DEFAULT_PATH)
+  add_custom_ie_build("${ie_custom_inc}" "${ie_custom_lib}" "${ie_custom_lib_rel}" "${ie_custom_lib_dbg}" "INF_ENGINE_{INCLUDE,LIB}_DIRS")
 endif()

-set(INF_ENGINE_LIBRARIES "")
+set(_loc "$ENV{INTEL_CVSDK_DIR}")
+if(NOT INF_ENGINE_TARGET AND _loc)
+  set(INF_ENGINE_PLATFORM "ubuntu_16.04" CACHE STRING "InferenceEngine platform (library dir)")
+  find_path(ie_custom_env_inc "inference_engine.hpp" PATHS "${_loc}/deployment_tools/inference_engine/include" NO_DEFAULT_PATH)
+  find_library(ie_custom_env_lib "inference_engine" PATHS "${_loc}/deployment_tools/inference_engine/lib/${INF_ENGINE_PLATFORM}/intel64" NO_DEFAULT_PATH)
+  find_library(ie_custom_env_lib_rel "inference_engine" PATHS "${_loc}/deployment_tools/inference_engine/lib/intel64/Release" NO_DEFAULT_PATH)
+  find_library(ie_custom_env_lib_dbg "inference_engine" PATHS "${_loc}/deployment_tools/inference_engine/lib/intel64/Debug" NO_DEFAULT_PATH)
+  add_custom_ie_build("${ie_custom_env_inc}" "${ie_custom_env_lib}" "${ie_custom_env_lib_rel}" "${ie_custom_env_lib_dbg}" "OpenVINO (${_loc})")
+endif()

-set(ie_lib_list inference_engine)
+# Add more features to the target

-link_directories(
-  ${INTEL_CVSDK_DIR}/inference_engine/external/mkltiny_lnx/lib
-  ${INTEL_CVSDK_DIR}/inference_engine/external/cldnn/lib
-)
-
-foreach(lib ${ie_lib_list})
-    find_library(${lib}
-        NAMES ${lib}
-        # For inference_engine
-        HINTS ${IE_PLUGINS_PATH}
-        HINTS "$ENV{IE_PLUGINS_PATH}"
-    )
-    if(NOT ${lib})
-        ie_fail()
-    endif()
-    list(APPEND INF_ENGINE_LIBRARIES ${${lib}})
-endforeach()
-
-set(HAVE_INF_ENGINE TRUE)
+if(INF_ENGINE_TARGET)
+  if(NOT INF_ENGINE_RELEASE)
+    message(WARNING "InferenceEngine version have not been set, 2018R3 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
+  endif()
+  set(INF_ENGINE_RELEASE "2018030000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
+  set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
+    INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
+  )
+endif()
@@ -254,10 +254,12 @@ find_python(3.4 "${MIN_VER_PYTHON3}" PYTHON3_LIBRARY PYTHON3_INCLUDE_DIR

 if(PYTHON_DEFAULT_EXECUTABLE)
    set(PYTHON_DEFAULT_AVAILABLE "TRUE")
-elseif(PYTHON2INTERP_FOUND) # Use Python 2 as default Python interpreter
+elseif(PYTHON2_EXECUTABLE AND PYTHON2INTERP_FOUND)
+    # Use Python 2 as default Python interpreter
    set(PYTHON_DEFAULT_AVAILABLE "TRUE")
    set(PYTHON_DEFAULT_EXECUTABLE "${PYTHON2_EXECUTABLE}")
-elseif(PYTHON3INTERP_FOUND) # Use Python 3 as fallback Python interpreter (if there is no Python 2)
+elseif(PYTHON3_EXECUTABLE AND PYTHON3INTERP_FOUND)
+    # Use Python 3 as fallback Python interpreter (if there is no Python 2)
    set(PYTHON_DEFAULT_AVAILABLE "TRUE")
    set(PYTHON_DEFAULT_EXECUTABLE "${PYTHON3_EXECUTABLE}")
 endif()
@@ -52,5 +52,18 @@ if(HAVE_QT AND ${VTK_VERSION} VERSION_GREATER "6.0.0" AND NOT ${VTK_QT_VERSION}
  endif()
 endif()

+try_compile(VTK_COMPILE_STATUS
+    "${OpenCV_BINARY_DIR}"
+    "${OpenCV_SOURCE_DIR}/cmake/checks/vtk_test.cpp"
+    CMAKE_FLAGS "-DINCLUDE_DIRECTORIES:STRING=${VTK_INCLUDE_DIRS}"
+    LINK_LIBRARIES ${VTK_LIBRARIES}
+    OUTPUT_VARIABLE OUTPUT
+)
+
+if(NOT ${VTK_COMPILE_STATUS})
+  message(STATUS "VTK support is disabled. Compilation of the sample code has failed.")
+  return()
+endif()
+
 set(HAVE_VTK ON)
 message(STATUS "Found VTK ${VTK_VERSION} (${VTK_USE_FILE})")
@@ -20,16 +20,19 @@ if(DEFINED ENV{OPENCV_DOWNLOAD_PATH})
 endif()
 set(OPENCV_DOWNLOAD_PATH "${OpenCV_SOURCE_DIR}/.cache" CACHE PATH "${HELP_OPENCV_DOWNLOAD_PATH}")
 set(OPENCV_DOWNLOAD_LOG "${OpenCV_BINARY_DIR}/CMakeDownloadLog.txt")
+set(OPENCV_DOWNLOAD_WITH_CURL "${OpenCV_BINARY_DIR}/download_with_curl.sh")
+set(OPENCV_DOWNLOAD_WITH_WGET "${OpenCV_BINARY_DIR}/download_with_wget.sh")

-# Init download cache directory and log file
+# Init download cache directory and log file and helper scripts
 if(NOT EXISTS "${OPENCV_DOWNLOAD_PATH}")
  file(MAKE_DIRECTORY ${OPENCV_DOWNLOAD_PATH})
 endif()
 if(NOT EXISTS "${OPENCV_DOWNLOAD_PATH}/.gitignore")
  file(WRITE "${OPENCV_DOWNLOAD_PATH}/.gitignore" "*\n")
 endif()
-file(WRITE "${OPENCV_DOWNLOAD_LOG}" "use_cache \"${OPENCV_DOWNLOAD_PATH}\"\n")
-
+file(WRITE "${OPENCV_DOWNLOAD_LOG}" "#use_cache \"${OPENCV_DOWNLOAD_PATH}\"\n")
+file(REMOVE "${OPENCV_DOWNLOAD_WITH_CURL}")
+file(REMOVE "${OPENCV_DOWNLOAD_WITH_WGET}")

 function(ocv_download)
  cmake_parse_arguments(DL "UNPACK;RELATIVE_URL" "FILENAME;HASH;DESTINATION_DIR;ID;STATUS" "URL" ${ARGN})
@@ -103,7 +106,7 @@ function(ocv_download)
  endif()

  # Log all calls to file
-  ocv_download_log("do_${mode} \"${DL_FILENAME}\" \"${DL_HASH}\" \"${DL_URL}\" \"${DL_DESTINATION_DIR}\"")
+  ocv_download_log("#do_${mode} \"${DL_FILENAME}\" \"${DL_HASH}\" \"${DL_URL}\" \"${DL_DESTINATION_DIR}\"")
  # ... and to console
  set(__msg_prefix "")
  if(DL_ID)
@@ -191,6 +194,9 @@ function(ocv_download)
 For details please refer to the download log file:
 ${OPENCV_DOWNLOAD_LOG}
 ")
+      # write helper scripts for failed downloads
+      file(APPEND "${OPENCV_DOWNLOAD_WITH_CURL}" "curl --output \"${CACHE_CANDIDATE}\" \"${DL_URL}\"\n")
+      file(APPEND "${OPENCV_DOWNLOAD_WITH_WGET}" "wget -O \"${CACHE_CANDIDATE}\" \"${DL_URL}\"\n")
      return()
    endif()

@@ -1,45 +0,0 @@
-# Main variables:
-# IPP_A_LIBRARIES and IPP_A_INCLUDE to use IPP Async
-# HAVE_IPP_A for conditional compilation OpenCV with/without IPP Async
-
-# IPP_ASYNC_ROOT - root of IPP Async installation
-
-if(X86_64)
-    find_path(
-    IPP_A_INCLUDE_DIR
-    NAMES ipp_async_defs.h
-    PATHS $ENV{IPP_ASYNC_ROOT}
-    PATH_SUFFIXES include
-    DOC "Path to Intel IPP Async interface headers")
-
-    find_file(
-    IPP_A_LIBRARIES
-    NAMES ipp_async_preview.lib
-    PATHS $ENV{IPP_ASYNC_ROOT}
-    PATH_SUFFIXES lib/intel64
-    DOC "Path to Intel IPP Async interface libraries")
-
-else()
-    find_path(
-    IPP_A_INCLUDE_DIR
-    NAMES ipp_async_defs.h
-    PATHS $ENV{IPP_ASYNC_ROOT}
-    PATH_SUFFIXES include
-    DOC "Path to Intel IPP Async interface headers")
-
-    find_file(
-    IPP_A_LIBRARIES
-    NAMES ipp_async_preview.lib
-    PATHS $ENV{IPP_ASYNC_ROOT}
-    PATH_SUFFIXES lib/ia32
-    DOC "Path to Intel IPP Async interface libraries")
-endif()
-
-if(IPP_A_INCLUDE_DIR AND IPP_A_LIBRARIES)
-    set(HAVE_IPP_A TRUE)
-else()
-    set(HAVE_IPP_A FALSE)
-    message(WARNING "Intel IPP Async library directory (set by IPP_A_LIBRARIES_DIR variable) is not found or does not have Intel IPP Async libraries.")
-endif()
-
-mark_as_advanced(FORCE IPP_A_LIBRARIES IPP_A_INCLUDE_DIR)
@@ -0,0 +1,15 @@
+# Main variables:
+# LIBREALSENSE_LIBRARIES and LIBREALSENSE_INCLUDE to link Intel librealsense modules
+# HAVE_LIBREALSENSE for conditional compilation OpenCV with/without librealsense
+
+find_path(LIBREALSENSE_INCLUDE_DIR "librealsense2/rs.hpp" PATHS "$ENV{LIBREALSENSE_INCLUDE}" DOC "Path to librealsense interface headers")
+find_library(LIBREALSENSE_LIBRARIES "realsense2" PATHS "$ENV{LIBREALSENSE_LIB}" DOC "Path to librealsense interface libraries")
+
+if(LIBREALSENSE_INCLUDE_DIR AND LIBREALSENSE_LIBRARIES)
+    set(HAVE_LIBREALSENSE TRUE)
+else()
+    set(HAVE_LIBREALSENSE FALSE)
+    message( WARNING, " librealsense include directory (set by LIBREALSENSE_INCLUDE_DIR variable) is not found or does not have librealsense include files." )
+endif() #if(LIBREALSENSE_INCLUDE_DIR AND LIBREALSENSE_LIBRARIES)
+
+mark_as_advanced(FORCE LIBREALSENSE_LIBRARIES LIBREALSENSE_INCLUDE_DIR)
@@ -268,3 +268,8 @@ if(WITH_IMGCODEC_PXM)
 elseif(DEFINED WITH_IMGCODEC_PXM)
  set(HAVE_IMGCODEC_PXM OFF)
 endif()
+if(WITH_IMGCODEC_PFM)
+  set(HAVE_IMGCODEC_PFM ON)
+elseif(DEFINED WITH_IMGCODEC_PFM)
+  set(HAVE_IMGCODEC_PFM OFF)
+endif()
@@ -7,6 +7,13 @@ if(WITH_TBB)
  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVDetectTBB.cmake")
 endif(WITH_TBB)

+# --- HPX ---
+if(WITH_HPX)
+  find_package(HPX REQUIRED)
+  ocv_include_directories(${HPX_INCLUDE_DIRS})
+  set(HAVE_HPX TRUE)
+endif(WITH_HPX)
+
 # --- IPP ---
 if(WITH_IPP)
  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVFindIPP.cmake")
@@ -28,17 +35,6 @@ if(WITH_IPP)
  endif()
 endif()

-# --- IPP Async ---
-
-if(WITH_IPP_A)
-  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVFindIPPAsync.cmake")
-  if(IPP_A_INCLUDE_DIR AND IPP_A_LIBRARIES)
-    ocv_include_directories(${IPP_A_INCLUDE_DIR})
-    link_directories(${IPP_A_LIBRARIES})
-    set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${IPP_A_LIBRARIES})
-   endif()
-endif(WITH_IPP_A)
-
 # --- CUDA ---
 if(WITH_CUDA)
  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVDetectCUDA.cmake")
@@ -104,22 +100,15 @@ if(WITH_CLP)
  endif()
 endif(WITH_CLP)

-# --- C= ---
-if(WITH_CSTRIPES AND NOT HAVE_TBB)
-  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVDetectCStripes.cmake")
-else()
-  set(HAVE_CSTRIPES 0)
-endif()
-
 # --- GCD ---
-if(APPLE AND NOT HAVE_TBB AND NOT HAVE_CSTRIPES)
+if(APPLE AND NOT HAVE_TBB)
  set(HAVE_GCD 1)
 else()
  set(HAVE_GCD 0)
 endif()

 # --- Concurrency ---
-if(MSVC AND NOT HAVE_TBB AND NOT HAVE_CSTRIPES)
+if(MSVC AND NOT HAVE_TBB)
  set(_fname "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/concurrencytest.cpp")
  file(WRITE "${_fname}" "#if _MSC_VER < 1600\n#error\n#endif\nint main() { return 0; }\n")
  try_compile(HAVE_CONCURRENCY "${CMAKE_BINARY_DIR}" "${_fname}")
@@ -310,6 +310,11 @@ if(APPLE)
  endif()
 endif(APPLE)

+# --- Intel librealsense ---
+if(WITH_LIBREALSENSE)
+  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVFindLibRealsense.cmake")
+endif(WITH_LIBREALSENSE)
+
 # --- Intel Perceptual Computing SDK ---
 if(WITH_INTELPERC)
  include("${OpenCV_SOURCE_DIR}/cmake/OpenCVFindIntelPerCSDK.cmake")
@@ -1,199 +0,0 @@
-# ----- Find Matlab/Octave -----
-#
-# OpenCVFindMatlab.cmake attempts to locate the install path of Matlab in order
-# to extract the mex headers, libraries and shell scripts. If found
-# successfully, the following variables will be defined
-#
-#   MATLAB_FOUND:       true/false
-#   MATLAB_ROOT_DIR:    Root of Matlab installation
-#   MATLAB_BIN:         The main Matlab "executable" (shell script)
-#   MATLAB_MEX_SCRIPT:  The mex script used to compile mex files
-#   MATLAB_INCLUDE_DIRS:Path to "mex.h"
-#   MATLAB_LIBRARY_DIRS:Path to mex and matrix libraries
-#   MATLAB_LIBRARIES:   The Matlab libs, usually mx, mex, mat
-#   MATLAB_MEXEXT:      The mex library extension. It will be one of:
-#                         mexwin32, mexwin64,  mexglx, mexa64, mexmac,
-#                         mexmaci,  mexmaci64, mexsol, mexs64
-#   MATLAB_ARCH:        The installation architecture. It is **usually**
-#                       the MEXEXT with the preceding "mex" removed,
-#                       though it's different for linux distros.
-#
-# There doesn't appear to be an elegant way to detect all versions of Matlab
-# across different platforms. If you know the matlab path and want to avoid
-# the search, you can define the path to the Matlab root when invoking cmake:
-#
-#   cmake -DMATLAB_ROOT_DIR='/PATH/TO/ROOT_DIR' ..
-
-
-
-# ----- set_library_presuffix -----
-#
-# Matlab tends to use some non-standard prefixes and suffixes on its libraries.
-# For example, libmx.dll on Windows (Windows does not add prefixes) and
-# mkl.dylib on OS X (OS X uses "lib" prefixes).
-# On some versions of Windows the .dll suffix also appears to not be checked.
-#
-# This function modifies the library prefixes and suffixes used by
-# find_library when finding Matlab libraries. It does not affect scopes
-# outside of this file.
-function(set_libarch_prefix_suffix)
-  if (UNIX AND NOT APPLE)
-    set(CMAKE_FIND_LIBRARY_PREFIXES "lib" PARENT_SCOPE)
-    set(CMAKE_FIND_LIBRARY_SUFFIXES ".so" ".a" PARENT_SCOPE)
-  elseif (APPLE)
-    set(CMAKE_FIND_LIBRARY_PREFIXES "lib" PARENT_SCOPE)
-    set(CMAKE_FIND_LIBRARY_SUFFIXES ".dylib" ".a" PARENT_SCOPE)
-  elseif (WIN32)
-    set(CMAKE_FIND_LIBRARY_PREFIXES "lib" PARENT_SCOPE)
-    set(CMAKE_FIND_LIBRARY_SUFFIXES ".lib" ".dll" PARENT_SCOPE)
-  endif()
-endfunction()
-
-
-
-# ----- locate_matlab_root -----
-#
-# Attempt to find the path to the Matlab installation. If successful, sets
-# the absolute path in the variable MATLAB_ROOT_DIR
-function(locate_matlab_root)
-
-  # --- UNIX/APPLE ---
-  if (UNIX)
-    # possible root locations, in order of likelihood
-    set(SEARCH_DIRS_ /Applications /usr/local /opt/local /usr /opt)
-    foreach (DIR_ ${SEARCH_DIRS_})
-      file(GLOB MATLAB_ROOT_DIR_ ${DIR_}/MATLAB/R* ${DIR_}/MATLAB_R*)
-      if (MATLAB_ROOT_DIR_)
-        # sort in order from highest to lowest
-        # normally it's in the format MATLAB_R[20XX][A/B]
-        # TODO: numerical rather than lexicographic sort. However,
-        # CMake does not support floating-point MATH(EXPR ...) at this time.
-        list(SORT MATLAB_ROOT_DIR_)
-        list(REVERSE MATLAB_ROOT_DIR_)
-        list(GET MATLAB_ROOT_DIR_ 0 MATLAB_ROOT_DIR_)
-        set(MATLAB_ROOT_DIR ${MATLAB_ROOT_DIR_} PARENT_SCOPE)
-        return()
-      endif()
-    endforeach()
-
-  # --- WINDOWS ---
-  elseif (WIN32)
-    # 1. search the path environment variable
-    find_program(MATLAB_ROOT_DIR_ matlab PATHS ENV PATH)
-    if (MATLAB_ROOT_DIR_)
-      # get the root directory from the full path
-      # /path/to/matlab/rootdir/bin/matlab.exe
-      get_filename_component(MATLAB_ROOT_DIR_ ${MATLAB_ROOT_DIR_} PATH)
-      get_filename_component(MATLAB_ROOT_DIR_ ${MATLAB_ROOT_DIR_} PATH)
-      set(MATLAB_ROOT_DIR ${MATLAB_ROOT_DIR_} PARENT_SCOPE)
-      return()
-    endif()
-
-    # 2. search the registry
-    # determine the available Matlab versions
-    set(REG_EXTENSION_ "SOFTWARE\\Mathworks\\MATLAB")
-    set(REG_ROOTS_ "HKEY_LOCAL_MACHINE" "HKEY_CURRENT_USER")
-    foreach(REG_ROOT_ ${REG_ROOTS_})
-      execute_process(COMMAND reg query "${REG_ROOT_}\\${REG_EXTENSION_}" OUTPUT_VARIABLE QUERY_RESPONSE_ ERROR_VARIABLE UNUSED_)
-      if (QUERY_RESPONSE_)
-        string(REGEX MATCHALL "[0-9]\\.[0-9]" VERSION_STRINGS_ ${QUERY_RESPONSE_})
-        list(APPEND VERSIONS_ ${VERSION_STRINGS_})
-      endif()
-    endforeach()
-
-    # select the highest version
-    list(APPEND VERSIONS_ "0.0")
-    list(SORT VERSIONS_)
-    list(REVERSE VERSIONS_)
-    list(GET VERSIONS_ 0 VERSION_)
-
-    # request the MATLABROOT from the registry
-    foreach(REG_ROOT_ ${REG_ROOTS_})
-      get_filename_component(QUERY_RESPONSE_ [${REG_ROOT_}\\${REG_EXTENSION_}\\${VERSION_};MATLABROOT] ABSOLUTE)
-      if (NOT ${QUERY_RESPONSE_} MATCHES "registry$")
-        set(MATLAB_ROOT_DIR ${QUERY_RESPONSE_} PARENT_SCOPE)
-        return()
-      endif()
-    endforeach()
-  endif()
-endfunction()
-
-
-
-# ----- locate_matlab_components -----
-#
-# Given a directory MATLAB_ROOT_DIR, attempt to find the Matlab components
-# (include directory and libraries) under the root. If everything is found,
-# sets the variable MATLAB_FOUND to TRUE
-function(locate_matlab_components MATLAB_ROOT_DIR)
-  # get the mex extension
-  find_file(MATLAB_MEXEXT_SCRIPT_ NAMES mexext mexext.bat PATHS ${MATLAB_ROOT_DIR}/bin NO_DEFAULT_PATH)
-  execute_process(COMMAND ${MATLAB_MEXEXT_SCRIPT_}
-                  OUTPUT_VARIABLE MATLAB_MEXEXT_
-                  OUTPUT_STRIP_TRAILING_WHITESPACE)
-  if (NOT MATLAB_MEXEXT_)
-    return()
-  endif()
-
-  # map the mexext to an architecture extension
-  set(ARCHITECTURES_ "maci64" "maci" "glnxa64" "glnx64" "sol64" "sola64" "win32" "win64" )
-  foreach(ARCHITECTURE_ ${ARCHITECTURES_})
-    if(EXISTS ${MATLAB_ROOT_DIR}/bin/${ARCHITECTURE_})
-      set(MATLAB_ARCH_ ${ARCHITECTURE_})
-      break()
-    endif()
-  endforeach()
-
-  # get the path to the libraries
-  set(MATLAB_LIBRARY_DIRS_ ${MATLAB_ROOT_DIR}/bin/${MATLAB_ARCH_})
-
-  # get the libraries
-  set_libarch_prefix_suffix()
-  find_library(MATLAB_LIB_MX_  mx  PATHS ${MATLAB_LIBRARY_DIRS_} NO_DEFAULT_PATH)
-  find_library(MATLAB_LIB_MEX_ mex PATHS ${MATLAB_LIBRARY_DIRS_} NO_DEFAULT_PATH)
-  find_library(MATLAB_LIB_MAT_ mat PATHS ${MATLAB_LIBRARY_DIRS_} NO_DEFAULT_PATH)
-  set(MATLAB_LIBRARIES_ ${MATLAB_LIB_MX_} ${MATLAB_LIB_MEX_} ${MATLAB_LIB_MAT_})
-
-  # get the include path
-  find_path(MATLAB_INCLUDE_DIRS_ mex.h ${MATLAB_ROOT_DIR}/extern/include)
-
-  # get the mex shell script
-  find_program(MATLAB_MEX_SCRIPT_ NAMES mex mex.bat PATHS ${MATLAB_ROOT_DIR}/bin NO_DEFAULT_PATH)
-
-  # get the Matlab executable
-  find_program(MATLAB_BIN_ NAMES matlab PATHS ${MATLAB_ROOT_DIR}/bin NO_DEFAULT_PATH)
-
-  # export into parent scope
-  if (MATLAB_MEX_SCRIPT_ AND MATLAB_LIBRARIES_ AND MATLAB_INCLUDE_DIRS_)
-    set(MATLAB_BIN          ${MATLAB_BIN_}          PARENT_SCOPE)
-    set(MATLAB_MEX_SCRIPT   ${MATLAB_MEX_SCRIPT_}   PARENT_SCOPE)
-    set(MATLAB_INCLUDE_DIRS ${MATLAB_INCLUDE_DIRS_} PARENT_SCOPE)
-    set(MATLAB_LIBRARIES    ${MATLAB_LIBRARIES_}    PARENT_SCOPE)
-    set(MATLAB_LIBRARY_DIRS ${MATLAB_LIBRARY_DIRS_} PARENT_SCOPE)
-    set(MATLAB_MEXEXT       ${MATLAB_MEXEXT_}       PARENT_SCOPE)
-    set(MATLAB_ARCH         ${MATLAB_ARCH_}         PARENT_SCOPE)
-  endif()
-endfunction()
-
-
-
-# ----------------------------------------------------------------------------
-# FIND MATLAB COMPONENTS
-# ----------------------------------------------------------------------------
-if (NOT MATLAB_FOUND)
-
-  # attempt to find the Matlab root folder
-  if (NOT MATLAB_ROOT_DIR)
-    locate_matlab_root()
-  endif()
-
-  # given the matlab root folder, find the library locations
-  if (MATLAB_ROOT_DIR)
-    locate_matlab_components(${MATLAB_ROOT_DIR})
-  endif()
-  find_package_handle_standard_args(Matlab DEFAULT_MSG
-                                           MATLAB_MEX_SCRIPT   MATLAB_INCLUDE_DIRS
-                                           MATLAB_ROOT_DIR     MATLAB_LIBRARIES
-                                           MATLAB_LIBRARY_DIRS MATLAB_MEXEXT
-                                           MATLAB_ARCH         MATLAB_BIN)
-endif()
@@ -50,7 +50,8 @@ else()
      add_library(libprotobuf UNKNOWN IMPORTED)
      set_target_properties(libprotobuf PROPERTIES
        IMPORTED_LOCATION "${Protobuf_LIBRARY}"
-        INTERFACE_INCLUDE_SYSTEM_DIRECTORIES "${Protobuf_INCLUDE_DIR}"
+        INTERFACE_INCLUDE_DIRECTORIES "${Protobuf_INCLUDE_DIR}"
+        INTERFACE_SYSTEM_INCLUDE_DIRECTORIES "${Protobuf_INCLUDE_DIR}"
      )
      get_protobuf_version(Protobuf_VERSION "${Protobuf_INCLUDE_DIR}")
    endif()
@@ -12,7 +12,9 @@ endif()

 if(VA_INCLUDE_DIR)
    set(HAVE_VA TRUE)
-    set(VA_LIBRARIES "-lva" "-lva-drm")
+    if(NOT DEFINED VA_LIBRARIES)
+      set(VA_LIBRARIES "va" "va-drm")
+    endif()
 else()
    set(HAVE_VA FALSE)
    message(WARNING "libva installation is not found.")
@@ -1,30 +1,16 @@
 # Main variables:
-# VA_INTEL_MSDK_INCLUDE_DIR and VA_INTEL_IOCL_INCLUDE_DIR to use VA_INTEL
+# VA_INTEL_IOCL_INCLUDE_DIR to use VA_INTEL
 # HAVE_VA_INTEL for conditional compilation OpenCV with/without VA_INTEL

-# VA_INTEL_MSDK_ROOT - root of Intel MSDK installation
 # VA_INTEL_IOCL_ROOT - root of Intel OCL installation

 if(UNIX AND NOT ANDROID)
-    if($ENV{VA_INTEL_MSDK_ROOT})
-        set(VA_INTEL_MSDK_ROOT $ENV{VA_INTEL_MSDK_ROOT})
-    else()
-        set(VA_INTEL_MSDK_ROOT "/opt/intel/mediasdk")
-    endif()
-
    if($ENV{VA_INTEL_IOCL_ROOT})
        set(VA_INTEL_IOCL_ROOT $ENV{VA_INTEL_IOCL_ROOT})
    else()
        set(VA_INTEL_IOCL_ROOT "/opt/intel/opencl")
    endif()

-    find_path(
-    VA_INTEL_MSDK_INCLUDE_DIR
-    NAMES mfxdefs.h
-    PATHS ${VA_INTEL_MSDK_ROOT}
-    PATH_SUFFIXES include
-    DOC "Path to Intel MSDK headers")
-
    find_path(
    VA_INTEL_IOCL_INCLUDE_DIR
    NAMES CL/va_ext.h
@@ -33,12 +19,14 @@ if(UNIX AND NOT ANDROID)
    DOC "Path to Intel OpenCL headers")
 endif()

-if(VA_INTEL_MSDK_INCLUDE_DIR AND VA_INTEL_IOCL_INCLUDE_DIR)
+if(VA_INTEL_IOCL_INCLUDE_DIR)
    set(HAVE_VA_INTEL TRUE)
-    set(VA_INTEL_LIBRARIES "-lva" "-lva-drm")
+    if(NOT DEFINED VA_INTEL_LIBRARIES)
+      set(VA_INTEL_LIBRARIES "va" "va-drm")
+    endif()
 else()
    set(HAVE_VA_INTEL FALSE)
-    message(WARNING "Intel MSDK & OpenCL installation is not found.")
+    message(WARNING "Intel OpenCL installation is not found.")
 endif()

-mark_as_advanced(FORCE VA_INTEL_MSDK_INCLUDE_DIR VA_INTEL_IOCL_INCLUDE_DIR)
+mark_as_advanced(FORCE VA_INTEL_IOCL_INCLUDE_DIR)
@@ -48,7 +48,7 @@ if(ANDROID)
  string(REPLACE "opencv_" "" OPENCV_MODULES_CONFIGMAKE "${OPENCV_MODULES_CONFIGMAKE}")

  if(BUILD_FAT_JAVA_LIB)
-    set(OPENCV_LIBS_CONFIGMAKE java3)
+    set(OPENCV_LIBS_CONFIGMAKE java4)
  else()
    set(OPENCV_LIBS_CONFIGMAKE "${OPENCV_MODULES_CONFIGMAKE}")
  endif()
@@ -33,7 +33,7 @@ endif()
 # -------------------------------------------------------------------------------------------
 #  Part 1/3: ${BIN_DIR}/OpenCVConfig.cmake              -> For use *without* "make install"
 # -------------------------------------------------------------------------------------------
-set(OpenCV_INCLUDE_DIRS_CONFIGCMAKE "\"${OPENCV_CONFIG_FILE_INCLUDE_DIR}\" \"${OpenCV_SOURCE_DIR}/include\" \"${OpenCV_SOURCE_DIR}/include/opencv\"")
+set(OpenCV_INCLUDE_DIRS_CONFIGCMAKE "\"${OPENCV_CONFIG_FILE_INCLUDE_DIR}\" \"${OpenCV_SOURCE_DIR}/include\"")

 foreach(m ${OPENCV_MODULES_BUILD})
  if(EXISTS "${OPENCV_MODULE_${m}_LOCATION}/include")
@@ -68,7 +68,7 @@ configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/OpenCVConfig-version.cmake.
 #  Part 2/3: ${BIN_DIR}/unix-install/OpenCVConfig.cmake -> For use *with* "make install"
 # -------------------------------------------------------------------------------------------
 file(RELATIVE_PATH OpenCV_INSTALL_PATH_RELATIVE_CONFIGCMAKE "${CMAKE_INSTALL_PREFIX}/${OPENCV_CONFIG_INSTALL_PATH}/" ${CMAKE_INSTALL_PREFIX})
-set(OpenCV_INCLUDE_DIRS_CONFIGCMAKE "\"\${OpenCV_INSTALL_PATH}/${OPENCV_INCLUDE_INSTALL_PATH}\" \"\${OpenCV_INSTALL_PATH}/${OPENCV_INCLUDE_INSTALL_PATH}/opencv\"")
+set(OpenCV_INCLUDE_DIRS_CONFIGCMAKE "\"\${OpenCV_INSTALL_PATH}/${OPENCV_INCLUDE_INSTALL_PATH}\"")

 if(USE_IPPICV)
  file(RELATIVE_PATH IPPICV_INSTALL_PATH_RELATIVE_CONFIGCMAKE "${CMAKE_INSTALL_PREFIX}" "${IPPICV_INSTALL_PATH}")
@@ -43,9 +43,9 @@ endmacro()
 if(NOT DEFINED CMAKE_HELPER_SCRIPT)

 if(INSTALL_TO_MANGLED_PATHS)
-  set(OPENCV_PC_FILE_NAME "opencv-${OPENCV_VERSION}.pc")
+  ocv_update(OPENCV_PC_FILE_NAME "opencv-${OPENCV_VERSION}.pc")
 else()
-  set(OPENCV_PC_FILE_NAME opencv.pc)
+  ocv_update(OPENCV_PC_FILE_NAME opencv4.pc)
 endif()

 # build the list of opencv libs and dependencies for all modules
@@ -1,4 +1,4 @@
-set(MIN_VER_CMAKE 2.8.12.2)
+set(MIN_VER_CMAKE 3.5.1)
 set(MIN_VER_CUDA 6.5)
 set(MIN_VER_PYTHON2 2.6)
 set(MIN_VER_PYTHON3 3.2)
@@ -296,28 +296,29 @@ endfunction()
 # Calls 'add_subdirectory' for each location.
 # Note: both input lists should have same length.
 # Usage: _add_modules_1(<list with paths> <list with names>)
-function(_add_modules_1 paths names)
-  list(LENGTH ${paths} len)
-  if(len EQUAL 0)
-    return()
+macro(_add_modules_1 paths names)
+  ocv_debug_message("_add_modules_1(paths=${paths}, names=${names}, ... " ${ARGN} ")")
+  list(LENGTH ${paths} __len)
+  if(NOT __len EQUAL 0)
+    list(LENGTH ${names} __len_verify)
+    if(NOT __len EQUAL __len_verify)
+      message(FATAL_ERROR "Bad configuration! ${__len} != ${__len_verify}")
+    endif()
+    math(EXPR __len "${__len} - 1")
+    foreach(i RANGE ${__len})
+      list(GET ${paths} ${i} __path)
+      list(GET ${names} ${i} __name)
+      #message(STATUS "First pass: ${__name} => ${__path}")
+      include("${__path}/cmake/init.cmake" OPTIONAL)
+      add_subdirectory("${__path}" "${CMAKE_CURRENT_BINARY_DIR}/.firstpass/${__name}")
+    endforeach()
  endif()
-  list(LENGTH ${names} len_verify)
-  if(NOT len EQUAL len_verify)
-    message(FATAL_ERROR "Bad configuration! ${len} != ${len_verify}")
-  endif()
-  math(EXPR len "${len} - 1")
-  foreach(i RANGE ${len})
-    list(GET ${paths} ${i} path)
-    list(GET ${names} ${i} name)
-    #message(STATUS "First pass: ${name} => ${path}")
-    include("${path}/cmake/init.cmake" OPTIONAL)
-    add_subdirectory("${path}" "${CMAKE_CURRENT_BINARY_DIR}/.firstpass/${name}")
-  endforeach()
-endfunction()
+endmacro()

 # Calls 'add_subdirectory' for each module name.
 # Usage: _add_modules_2([<module> ...])
-function(_add_modules_2)
+macro(_add_modules_2)
+  ocv_debug_message("_add_modules_2(" ${ARGN} ")")
  foreach(m ${ARGN})
    set(the_module "${m}")
    ocv_cmake_hook(PRE_MODULES_CREATE_${the_module})
@@ -333,7 +334,8 @@ function(_add_modules_2)
    endif()
    ocv_cmake_hook(POST_MODULES_CREATE_${the_module})
  endforeach()
-endfunction()
+  unset(the_module)
+endmacro()

 # Check if list of input items is unique.
 # Usage: _assert_uniqueness(<failure message> <element> [<element> ...])
@@ -1132,9 +1134,14 @@ function(ocv_add_perf_tests)
      source_group("Src" FILES "${${the_target}_pch}")
      ocv_add_executable(${the_target} ${OPENCV_PERF_${the_module}_SOURCES} ${${the_target}_pch})
      ocv_target_include_modules(${the_target} ${perf_deps} "${perf_path}")
-      ocv_target_link_libraries(${the_target} LINK_PRIVATE ${perf_deps} ${OPENCV_MODULE_${the_module}_DEPS} ${OPENCV_LINKER_LIBS})
+      ocv_target_link_libraries(${the_target} LINK_PRIVATE ${perf_deps} ${OPENCV_MODULE_${the_module}_DEPS} ${OPENCV_LINKER_LIBS} ${OPENCV_PERF_${the_module}_DEPS})
      add_dependencies(opencv_perf_tests ${the_target})

+      if(HAVE_HPX)
+        message("Linking HPX to Perf test of module ${name}")
+        ocv_target_link_libraries(${the_target} LINK_PRIVATE "${HPX_LIBRARIES}")
+      endif()
+
      set_target_properties(${the_target} PROPERTIES LABELS "${OPENCV_MODULE_${the_module}_LABEL};PerfTest")
      set_source_files_properties(${OPENCV_PERF_${the_module}_SOURCES} ${${the_target}_pch}
        PROPERTIES LABELS "${OPENCV_MODULE_${the_module}_LABEL};PerfTest")
@@ -1175,7 +1182,7 @@ function(ocv_add_perf_tests)
 endfunction()

 # this is a command for adding OpenCV accuracy/regression tests to the module
-# ocv_add_accuracy_tests([FILES <source group name> <list of sources>] [DEPENDS_ON] <list of extra dependencies>)
+# ocv_add_accuracy_tests(<list of extra dependencies>)
 function(ocv_add_accuracy_tests)
  ocv_debug_message("ocv_add_accuracy_tests(" ${ARGN} ")")

@@ -1202,6 +1209,9 @@ function(ocv_add_accuracy_tests)
        set(OPENCV_TEST_${the_module}_SOURCES ${test_srcs} ${test_hdrs})
      endif()

+      if(OPENCV_MODULE_${the_module}_TEST_SOURCES_DISPATCHED)
+        list(APPEND OPENCV_TEST_${the_module}_SOURCES ${OPENCV_MODULE_${the_module}_TEST_SOURCES_DISPATCHED})
+      endif()
      ocv_compiler_optimization_process_sources(OPENCV_TEST_${the_module}_SOURCES OPENCV_TEST_${the_module}_DEPS ${the_target})

      if(NOT BUILD_opencv_world)
@@ -1211,9 +1221,17 @@ function(ocv_add_accuracy_tests)
      source_group("Src" FILES "${${the_target}_pch}")
      ocv_add_executable(${the_target} ${OPENCV_TEST_${the_module}_SOURCES} ${${the_target}_pch})
      ocv_target_include_modules(${the_target} ${test_deps} "${test_path}")
-      ocv_target_link_libraries(${the_target} LINK_PRIVATE ${test_deps} ${OPENCV_MODULE_${the_module}_DEPS} ${OPENCV_LINKER_LIBS})
+      if(EXISTS "${CMAKE_CURRENT_BINARY_DIR}/test")
+        ocv_target_include_directories(${the_target} "${CMAKE_CURRENT_BINARY_DIR}/test")
+      endif()
+      ocv_target_link_libraries(${the_target} LINK_PRIVATE ${test_deps} ${OPENCV_MODULE_${the_module}_DEPS} ${OPENCV_LINKER_LIBS} ${OPENCV_TEST_${the_module}_DEPS})
      add_dependencies(opencv_tests ${the_target})

+      if(HAVE_HPX)
+        message("Linking HPX to Perf test of module ${name}")
+        ocv_target_link_libraries(${the_target} LINK_PRIVATE "${HPX_LIBRARIES}")
+      endif()
+
      set_target_properties(${the_target} PROPERTIES LABELS "${OPENCV_MODULE_${the_module}_LABEL};AccuracyTest")
      set_source_files_properties(${OPENCV_TEST_${the_module}_SOURCES} ${${the_target}_pch}
        PROPERTIES LABELS "${OPENCV_MODULE_${the_module}_LABEL};AccuracyTest")
@@ -362,7 +362,7 @@ MACRO(ADD_NATIVE_PRECOMPILED_HEADER _targetName _input)
          endif()
        endforeach()

-        #also inlude ${oldProps} to have the same compile options
+        #also include ${oldProps} to have the same compile options
        GET_TARGET_PROPERTY(oldProps ${_targetName} COMPILE_FLAGS)
        if (oldProps MATCHES NOTFOUND)
            SET(oldProps "")
@@ -121,8 +121,10 @@ macro(ocv_assert)
 endmacro()

 macro(ocv_debug_message)
-#  string(REPLACE ";" " " __msg "${ARGN}")
-#  message(STATUS "${__msg}")
+  if(OPENCV_CMAKE_DEBUG_MESSAGES)
+    string(REPLACE ";" " " __msg "${ARGN}")
+    message(STATUS "${__msg}")
+  endif()
 endmacro()

 macro(ocv_check_environment_variables)
@@ -259,7 +261,7 @@ function(ocv_include_directories)
    ocv_is_opencv_directory(__is_opencv_dir "${dir}")
    if(__is_opencv_dir)
      list(APPEND __add_before "${dir}")
-    elseif(CV_GCC AND NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS "6.0" AND
+    elseif(((CV_GCC AND NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS "6.0") OR CV_CLANG) AND
           dir MATCHES "/usr/include$")
      # workaround for GCC 6.x bug
    else()
@@ -1087,7 +1089,7 @@ function(ocv_install_3rdparty_licenses library)
    get_filename_component(name "${filename}" NAME)
    install(
      FILES "${filename}"
-      DESTINATION "${OPENCV_OTHER_INSTALL_PATH}/licenses"
+      DESTINATION "${OPENCV_LICENSES_INSTALL_PATH}"
      COMPONENT licenses
      RENAME "${library}-${name}"
      OPTIONAL)
@@ -1,14 +1,25 @@
-#include <stdio.h>
+#include <iostream>
+#include <sstream>
+#include <list>
+
 int main()
 {
+    std::ostringstream arch;
+    std::list<std::string> archs;
+
    int count = 0;
-    if (cudaSuccess != cudaGetDeviceCount(&count)){return -1;}
-    if (count == 0) {return -1;}
+    if (cudaSuccess != cudaGetDeviceCount(&count)){ return -1; }
+    if (count == 0) { return -1; }
    for (int device = 0; device < count; ++device)
    {
        cudaDeviceProp prop;
-        if (cudaSuccess != cudaGetDeviceProperties(&prop, device)){ continue;}
-        printf("%d.%d ", prop.major, prop.minor);
+        if (cudaSuccess != cudaGetDeviceProperties(&prop, device)){ continue; }
+        arch << prop.major << "." << prop.minor;
+        archs.push_back(arch.str());
+        arch.str("");
    }
+    archs.unique(); #Some devices might have the same arch
+    for (std::list<std::string>::iterator it=archs.begin(); it!=archs.end(); ++it)
+        std::cout << *it << " ";
    return 0;
 }
@@ -0,0 +1,9 @@
+#include <vtkSmartPointer.h>
+#include <vtkTransform.h>
+#include <vtkMath.h>
+
+int main()
+{
+  vtkSmartPointer<vtkTransform> transform = vtkSmartPointer<vtkTransform>::New();
+  return 0;
+}
@@ -260,7 +260,7 @@ endif()
 set(OpenCV_LIBRARIES ${OpenCV_LIBS})

 #
-# Some macroses for samples
+# Some macros for samples
 #
 macro(ocv_check_dependencies)
  set(OCV_DEPENDENCIES_FOUND TRUE)
@@ -46,9 +46,6 @@
 /* Cocoa API */
 #cmakedefine HAVE_COCOA

-/* C= */
-#cmakedefine HAVE_CSTRIPES
-
 /* NVIDIA CUDA Basic Linear Algebra Subprograms (BLAS) API*/
 #cmakedefine HAVE_CUBLAS

@@ -106,9 +103,6 @@
 #cmakedefine HAVE_IPP_ICV
 #cmakedefine HAVE_IPP_IW

-/* Intel IPP Async */
-#cmakedefine HAVE_IPP_A
-
 /* JPEG-2000 codec */
 #cmakedefine HAVE_JASPER

@@ -150,6 +144,9 @@
 /* OpenNI library */
 #cmakedefine HAVE_OPENNI2

+/* librealsense library */
+#cmakedefine HAVE_LIBREALSENSE
+
 /* PNG codec */
 #cmakedefine HAVE_PNG

@@ -174,6 +171,9 @@
 /* Intel Threading Building Blocks */
 #cmakedefine HAVE_TBB

+/* Ste||ar Group High Performance ParallelX */
+#cmakedefine HAVE_HPX
+
 /* TIFF codec */
 #cmakedefine HAVE_TIFF

@@ -227,7 +227,6 @@ SEARCH_INCLUDES        = YES
 INCLUDE_PATH           =
 INCLUDE_FILE_PATTERNS  =
 PREDEFINED             = __cplusplus=1 \
-                         HAVE_IPP_A=1 \
                         CVAPI(x)=x \
                         CV_DOXYGEN= \
                         CV_EXPORTS= \
@@ -241,6 +240,9 @@ PREDEFINED             = __cplusplus=1 \
                         CV_PROP_RW= \
                         CV_WRAP= \
                         CV_WRAP_AS(x)= \
+                         CV_WRAP_MAPPABLE(x)= \
+                         CV_WRAP_PHANTOM(x)= \
+                         CV_WRAP_DEFAULT(x)= \
                         CV_CDECL= \
                         CV_Func = \
                         CV_DO_PRAGMA(x)= \
@@ -29,7 +29,7 @@ What happens in background ?
    objects). Everything inside rectangle is unknown. Similarly any user input specifying
    foreground and background are considered as hard-labelling which means they won't change in
    the process.
-   Computer does an initial labelling depeding on the data we gave. It labels the foreground and
+-   Computer does an initial labelling depending on the data we gave. It labels the foreground and
    background pixels (or it hard-labels)
 -   Now a Gaussian Mixture Model(GMM) is used to model the foreground and background.
 -   Depending on the data we gave, GMM learns and create new pixel distribution. That is, the
@@ -129,7 +129,7 @@ function onOpenCvReady() {
 </html>
@endcode

-@note You have to call delete method of cv.Mat to free memory allocated in Emscripten's heap. Please refer to [Memeory management of Emscripten](https://kripken.github.io/emscripten-site/docs/porting/connecting_cpp_and_javascript/embind.html#memory-management) for details.
+@note You have to call delete method of cv.Mat to free memory allocated in Emscripten's heap. Please refer to [Memory management of Emscripten](https://kripken.github.io/emscripten-site/docs/porting/connecting_cpp_and_javascript/embind.html#memory-management) for details.

 Try it
 ------
@@ -1016,3 +1016,56 @@
  year = {2017},
  organization = {IEEE}
 }
+@ARTICLE{gonzalez,
+  title={Digital Image Fundamentals, Digital Imaging Processing},
+  author={Gonzalez, Rafael C and others},
+  year={1987},
+  publisher={Addison Wesley Publishing Company}
+}
+@ARTICLE{gruzman,
+  title={Цифровая обработка изображений в информационных системах},
+  author={Грузман, И.С. and Киричук, В.С. and Косых, В.П. and Перетягин, Г.И. and Спектор, А.А.},
+  year={2000},
+  publisher={Изд-во НГТУ Новосибирск}
+}
+@INPROCEEDINGS{duda2018,
+    title = {Accurate Detection and Localization of Checkerboard Corners for Calibration},
+    year = {2018},
+    booktitle = {29th British Machine Vision Conference. British Machine Vision Conference (BMVC-29), September 3-6, Newcastle, United Kingdom},
+    publisher = {BMVA Press},
+    author = {Alexander Duda and Udo Frese},
+}
+
+@book{jahne2000computer,
+  title={Computer vision and applications: a guide for students and practitioners},
+  author={Jahne, Bernd},
+  year={2000},
+  publisher={Elsevier}
+}
+
+@book{bigun2006vision,
+  title={Vision with direction},
+  author={Bigun, Josef},
+  year={2006},
+  publisher={Springer}
+}
+
+@inproceedings{van1995estimators,
+  title={Estimators for orientation and anisotropy in digitized images},
+  author={Van Vliet, Lucas J and Verbeek, Piet W},
+  booktitle={ASCI},
+  volume={95},
+  pages={16--18},
+  year={1995}
+}
+
+@article{yang1996structure,
+  title={Structure adaptive anisotropic image filtering},
+  author={Yang, Guang-Zhong and Burger, Peter and Firmin, David N and Underwood, SR},
+  journal={Image and Vision Computing},
+  volume={14},
+  number={2},
+  pages={135--145},
+  year={1996},
+  publisher={Elsevier}
+}
@@ -20,20 +20,20 @@ A simple example on extending C++ functions to Python can be found in official P
 documentation[1]. So extending all functions in OpenCV to Python by writing their wrapper functions
 manually is a time-consuming task. So OpenCV does it in a more intelligent way. OpenCV generates
 these wrapper functions automatically from the C++ headers using some Python scripts which are
-located in modules/python/src2. We will look into what they do.
+located in `modules/python/src2`. We will look into what they do.

-First, modules/python/CMakeFiles.txt is a CMake script which checks the modules to be extended to
+First, `modules/python/CMakeFiles.txt` is a CMake script which checks the modules to be extended to
 Python. It will automatically check all the modules to be extended and grab their header files.
 These header files contain list of all classes, functions, constants etc. for that particular
 modules.

-Second, these header files are passed to a Python script, modules/python/src2/gen2.py. This is the
-Python bindings generator script. It calls another Python script modules/python/src2/hdr_parser.py.
+Second, these header files are passed to a Python script, `modules/python/src2/gen2.py`. This is the
+Python bindings generator script. It calls another Python script `modules/python/src2/hdr_parser.py`.
 This is the header parser script. This header parser splits the complete header file into small
 Python lists. So these lists contain all details about a particular function, class etc. For
 example, a function will be parsed to get a list containing function name, return type, input
-arguments, argument types etc. Final list contains details of all the functions, structs, classes
-etc. in that header file.
+arguments, argument types etc. Final list contains details of all the functions, enums, structs,
+classes etc. in that header file.

 But header parser doesn't parse all the functions/classes in the header file. The developer has to
 specify which functions should be exported to Python. For that, there are certain macros added to
@@ -44,15 +44,15 @@ macros will be given in next session.

 So header parser returns a final big list of parsed functions. Our generator script (gen2.py) will
 create wrapper functions for all the functions/classes/enums/structs parsed by header parser (You
-can find these header files during compilation in the build/modules/python/ folder as
+can find these header files during compilation in the `build/modules/python/` folder as
 pyopencv_generated_\*.h files). But there may be some basic OpenCV datatypes like Mat, Vec4i,
 Size. They need to be extended manually. For example, a Mat type should be extended to Numpy array,
 Size should be extended to a tuple of two integers etc. Similarly, there may be some complex
 structs/classes/functions etc. which need to be extended manually. All such manual wrapper functions
-are placed in modules/python/src2/cv2.cpp.
+are placed in `modules/python/src2/cv2.cpp`.

 So now only thing left is the compilation of these wrapper files which gives us **cv2** module. So
-when you call a function, say res = equalizeHist(img1,img2) in Python, you pass two numpy arrays and
+when you call a function, say `res = equalizeHist(img1,img2)` in Python, you pass two numpy arrays and
 you expect another numpy array as the output. So these numpy arrays are converted to cv::Mat and
 then calls the equalizeHist() function in C++. Final result, res will be converted back into a Numpy
 array. So in short, almost all operations are done in C++ which gives us almost same speed as that
@@ -67,19 +67,19 @@ Header parser parse the header files based on some wrapper macros added to funct
 Enumeration constants don't need any wrapper macros. They are automatically wrapped. But remaining
 functions, classes etc. need wrapper macros.

-Functions are extended using CV_EXPORTS_W macro. An example is shown below.
+Functions are extended using `CV_EXPORTS_W` macro. An example is shown below.
@code{.cpp}
 CV_EXPORTS_W void equalizeHist( InputArray src, OutputArray dst );
@endcode
 Header parser can understand the input and output arguments from keywords like
 InputArray, OutputArray etc. But sometimes, we may need to hardcode inputs and outputs. For that,
-macros like CV_OUT, CV_IN_OUT etc. are used.
+macros like `CV_OUT`, `CV_IN_OUT` etc. are used.
@code{.cpp}
 CV_EXPORTS_W void minEnclosingCircle( InputArray points,
                                     CV_OUT Point2f& center, CV_OUT float& radius );
@endcode
-For large classes also, CV_EXPORTS_W is used. To extend class methods, CV_WRAP is used.
-Similarly, CV_PROP is used for class fields.
+For large classes also, `CV_EXPORTS_W` is used. To extend class methods, `CV_WRAP` is used.
+Similarly, `CV_PROP` is used for class fields.
@code{.cpp}
 class CV_EXPORTS_W CLAHE : public Algorithm
 {
@@ -90,9 +90,9 @@ public:
    CV_WRAP virtual double getClipLimit() const = 0;
 }
@endcode
-Overloaded functions can be extended using CV_EXPORTS_AS. But we need to pass a new name so that
+Overloaded functions can be extended using `CV_EXPORTS_AS`. But we need to pass a new name so that
 each function will be called by that name in Python. Take the case of integral function below. Three
-functions are available, so each one is named with a suffix in Python. Similarly CV_WRAP_AS can be
+functions are available, so each one is named with a suffix in Python. Similarly `CV_WRAP_AS` can be
 used to wrap overloaded methods.
@code{.cpp}
 //! computes the integral image
@@ -107,9 +107,9 @@ CV_EXPORTS_AS(integral3) void integral( InputArray src, OutputArray sum,
                                        OutputArray sqsum, OutputArray tilted,
                                        int sdepth = -1, int sqdepth = -1 );
@endcode
-Small classes/structs are extended using CV_EXPORTS_W_SIMPLE. These structs are passed by value
-to C++ functions. Examples are KeyPoint, Match etc. Their methods are extended by CV_WRAP and
-fields are extended by CV_PROP_RW.
+Small classes/structs are extended using `CV_EXPORTS_W_SIMPLE`. These structs are passed by value
+to C++ functions. Examples are `KeyPoint`, `Match` etc. Their methods are extended by `CV_WRAP` and
+fields are extended by `CV_PROP_RW`.
@code{.cpp}
 class CV_EXPORTS_W_SIMPLE DMatch
 {
@@ -125,8 +125,8 @@ public:
    CV_PROP_RW float distance;
 };
@endcode
-Some other small classes/structs can be exported using CV_EXPORTS_W_MAP where it is exported to a
-Python native dictionary. Moments() is an example of it.
+Some other small classes/structs can be exported using `CV_EXPORTS_W_MAP` where it is exported to a
+Python native dictionary. `Moments()` is an example of it.
@code{.cpp}
 class CV_EXPORTS_W_MAP Moments
 {
@@ -142,6 +142,41 @@ public:
 So these are the major extension macros available in OpenCV. Typically, a developer has to put
 proper macros in their appropriate positions. Rest is done by generator scripts. Sometimes, there
 may be an exceptional cases where generator scripts cannot create the wrappers. Such functions need
-to be handled manually, to do this write your own pyopencv_*.hpp extending headers and put them into
+to be handled manually, to do this write your own `pyopencv_*.hpp` extending headers and put them into
 misc/python subdirectory of your module. But most of the time, a code written according to OpenCV
-coding guidelines will be automatically wrapped by generator scripts.
+coding guidelines will be automatically wrapped by generator scripts.
+
+More advanced cases involves providing Python with additional features that does not exist
+in the C++ interface such as extra methods, type mappings, or to provide default arguments.
+We will take `UMat` datatype as an example of such cases later on.
+First, to provide Python-specific methods, `CV_WRAP_PHANTOM` is utilized in a similar manner to
+`CV_WRAP`, except that it takes the method header as its argument, and you would need to provide
+the method body in your own `pyopencv_*.hpp` extension. `UMat::queue()` and `UMat::context()` are
+an example of such phantom methods that does not exist in C++ interface, but are needed to handle
+OpenCL functionalities at the Python side.
+Second, if an already-existing datatype(s) is mappable to your class, it is highly preferable to
+indicate such capacity using `CV_WRAP_MAPPABLE` with the source type as its argument,
+rather than crafting your own binding function(s). This is the case of `UMat` which maps from `Mat`.
+Finally, if a default argument is needed, but it is not provided in the native C++ interface,
+you can provide it for Python side as the argument of `CV_WRAP_DEFAULT`. As per the `UMat::getMat`
+example below:
+@code{.cpp}
+class CV_EXPORTS_W UMat
+{
+public:
+    //! Mat is mappable to UMat.
+    // You would need to provide `static bool cv_mappable_to(const Ptr<Mat>& src, Ptr<UMat>& dst)`
+    CV_WRAP_MAPPABLE(Ptr<Mat>);
+
+    /! returns the OpenCL queue used by OpenCV UMat.
+    // You would need to provide the method body in the binder code
+    CV_WRAP_PHANTOM(static void* queue());
+
+    //! returns the OpenCL context used by OpenCV UMat
+    // You would need to provide the method body in the binder code
+    CV_WRAP_PHANTOM(static void* context());
+
+    //! The wrapped method become equvalent to `get(int flags = ACCESS_RW)`
+    CV_WRAP_AS(get) Mat getMat(int flags CV_WRAP_DEFAULT(ACCESS_RW)) const;
+};
+@endcode
@@ -153,15 +153,15 @@ padding etc. This function takes following arguments:

 -   **borderType** - Flag defining what kind of border to be added. It can be following types:
    -   **cv.BORDER_CONSTANT** - Adds a constant colored border. The value should be given
-            as next argument.
-        -   **cv.BORDER_REFLECT** - Border will be mirror reflection of the border elements,
-            like this : *fedcba|abcdefgh|hgfedcb*
-        -   **cv.BORDER_REFLECT_101** or **cv.BORDER_DEFAULT** - Same as above, but with a
-            slight change, like this : *gfedcb|abcdefgh|gfedcba*
-        -   **cv.BORDER_REPLICATE** - Last element is replicated throughout, like this:
-            *aaaaaa|abcdefgh|hhhhhhh*
-        -   **cv.BORDER_WRAP** - Can't explain, it will look like this :
-            *cdefgh|abcdefgh|abcdefg*
+        as next argument.
+    -   **cv.BORDER_REFLECT** - Border will be mirror reflection of the border elements,
+        like this : *fedcba|abcdefgh|hgfedcb*
+    -   **cv.BORDER_REFLECT_101** or **cv.BORDER_DEFAULT** - Same as above, but with a
+        slight change, like this : *gfedcb|abcdefgh|gfedcba*
+    -   **cv.BORDER_REPLICATE** - Last element is replicated throughout, like this:
+        *aaaaaa|abcdefgh|hhhhhhh*
+    -   **cv.BORDER_WRAP** - Can't explain, it will look like this :
+        *cdefgh|abcdefgh|abcdefg*

 -   **value** - Color of border if border type is cv.BORDER_CONSTANT

@@ -37,6 +37,7 @@ cv.namedWindow('image')

 # create trackbars for color change
 cv.createTrackbar('R','image',0,255,nothing)
+
 cv.createTrackbar('G','image',0,255,nothing)
 cv.createTrackbar('B','image',0,255,nothing)

@@ -37,7 +37,7 @@ So what happens in background ?
    objects). Everything inside rectangle is unknown. Similarly any user input specifying
    foreground and background are considered as hard-labelling which means they won't change in
    the process.
-   Computer does an initial labelling depeding on the data we gave. It labels the foreground and
+-   Computer does an initial labelling depending on the data we gave. It labels the foreground and
    background pixels (or it hard-labels)
 -   Now a Gaussian Mixture Model(GMM) is used to model the foreground and background.
 -   Depending on the data we gave, GMM learns and create new pixel distribution. That is, the
@@ -36,7 +36,7 @@ gives us a feature vector containing 64 values. This is the feature vector we us

 Finally, as in the previous case, we start by splitting our big dataset into individual cells. For
 every digit, 250 cells are reserved for training data and remaining 250 data is reserved for
-testing. Full code is given below, you also can download it from [here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py):
+testing. Full code is given below, you also can download it from [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py):

@include samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py

@@ -77,13 +77,13 @@ Source code

 You may also find the source code in the `samples/cpp/tutorial_code/calib3d/camera_calibration/`
 folder of the OpenCV source library or [download it from here
-](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). The program has a
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). The program has a
 single argument: the name of its configuration file. If none is given then it will try to open the
 one named "default.xml". [Here's a sample configuration file
-](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
 configuration file you may choose to use camera as an input, a video file or an image list. If you
 opt for the last one, you will need to create a configuration file where you enumerate the images to
-use. Here's [an example of this ](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
+use. Here's [an example of this ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
 The important part to remember is that the images need to be specified using the absolute path or
 the relative one from your application's working directory. You may find all this in the samples
 directory mentioned above.
@@ -16,7 +16,7 @@ In this tutorial is explained how to build a real time application to estimate t
 order to track a textured object with six degrees of freedom given a 2D image and its 3D textured
 model.

-The application will have the followings parts:
+The application will have the following parts:

 -   Read 3D textured object model and object mesh.
 -   Take input from Camera or Video.
@@ -426,16 +426,16 @@ Here is explained in detail the code for the real time application:
    @endcode
    OpenCV provides four PnP methods: ITERATIVE, EPNP, P3P and DLS. Depending on the application type,
    the estimation method will be different. In the case that we want to make a real time application,
-    the more suitable methods are EPNP and P3P due to that are faster than ITERATIVE and DLS at
+    the more suitable methods are EPNP and P3P since they are faster than ITERATIVE and DLS at
    finding an optimal solution. However, EPNP and P3P are not especially robust in front of planar
-    surfaces and sometimes the pose estimation seems to have a mirror effect. Therefore, in this this
-    tutorial is used ITERATIVE method due to the object to be detected has planar surfaces.
+    surfaces and sometimes the pose estimation seems to have a mirror effect. Therefore, in this
+    tutorial an ITERATIVE method is used due to the object to be detected has planar surfaces.

-    The OpenCV RANSAC implementation wants you to provide three parameters: the maximum number of
-    iterations until stop the algorithm, the maximum allowed distance between the observed and
-    computed point projections to consider it an inlier and the confidence to obtain a good result.
+    The OpenCV RANSAC implementation wants you to provide three parameters: 1) the maximum number of
+    iterations until the algorithm stops, 2) the maximum allowed distance between the observed and
+    computed point projections to consider it an inlier and 3) the confidence to obtain a good result.
    You can tune these parameters in order to improve your algorithm performance. Increasing the
-    number of iterations you will have a more accurate solution, but will take more time to find a
+    number of iterations will have a more accurate solution, but will take more time to find a
    solution. Increasing the reprojection error will reduce the computation time, but your solution
    will be unaccurate. Decreasing the confidence your algorithm will be faster, but the obtained
    solution will be unaccurate.
@@ -33,19 +33,19 @@ Source Code

@add_toggle_cpp
 Download the source code from
-[here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
@include cpp/tutorial_code/core/AddingImages/AddingImages.cpp
@end_toggle

@add_toggle_java
 Download the source code from
-[here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/java/tutorial_code/core/AddingImages/AddingImages.java).
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/AddingImages/AddingImages.java).
@include java/tutorial_code/core/AddingImages/AddingImages.java
@end_toggle

@add_toggle_python
 Download the source code from
-[here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/python/tutorial_code/core/AddingImages/adding_images.py).
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/AddingImages/adding_images.py).
@include python/tutorial_code/core/AddingImages/adding_images.py
@end_toggle

@@ -69,7 +69,7 @@ We need two source images (\f$f_{0}(x)\f$ and \f$f_{1}(x)\f$). So, we load them
@snippet python/tutorial_code/core/AddingImages/adding_images.py load
@end_toggle

-We used the following images: [LinuxLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/data/LinuxLogo.jpg) and [WindowsLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/data/WindowsLogo.jpg)
+We used the following images: [LinuxLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/LinuxLogo.jpg) and [WindowsLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/WindowsLogo.jpg)

@warning Since we are *adding* *src1* and *src2*, they both have to be of the same size
 (width and height) and type.
@@ -1,6 +1,9 @@
 Changing the contrast and brightness of an image! {#tutorial_basic_linear_transform}
 =================================================

+@prev_tutorial{tutorial_adding_images}
+@next_tutorial{tutorial_discrete_fourier_transform}
+
 Goal
 ----

@@ -53,48 +56,143 @@ Theory
 Code
 ----

+@add_toggle_cpp
+-   **Downloadable code**: Click
+    [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp)
+
 -   The following code performs the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ :
-@include BasicLinearTransforms.cpp
+    @include samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp
+@end_toggle
+
+@add_toggle_java
+-   **Downloadable code**: Click
+    [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java)
+
+-   The following code performs the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ :
+    @include samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java
+@end_toggle
+
+@add_toggle_python
+-   **Downloadable code**: Click
+    [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py)
+
+-   The following code performs the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ :
+    @include samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py
+@end_toggle

 Explanation
 -----------

-#  We begin by creating parameters to save \f$\alpha\f$ and \f$\beta\f$ to be entered by the user:
-    @snippet BasicLinearTransforms.cpp basic-linear-transform-parameters
+-   We load an image using @ref cv::imread and save it in a Mat object:

-#  We load an image using @ref cv::imread and save it in a Mat object:
-    @snippet BasicLinearTransforms.cpp basic-linear-transform-load
-#  Now, since we will make some transformations to this image, we need a new Mat object to store
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp basic-linear-transform-load
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java basic-linear-transform-load
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py basic-linear-transform-load
+@end_toggle
+
+-   Now, since we will make some transformations to this image, we need a new Mat object to store
    it. Also, we want this to have the following features:

    -   Initial pixel values equal to zero
    -   Same size and type as the original image
-    @snippet BasicLinearTransforms.cpp basic-linear-transform-output
-    We observe that @ref cv::Mat::zeros returns a Matlab-style zero initializer based on
-    *image.size()* and *image.type()*

-#  Now, to perform the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ we will access to each
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp basic-linear-transform-output
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java basic-linear-transform-output
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py basic-linear-transform-output
+@end_toggle
+
+We observe that @ref cv::Mat::zeros returns a Matlab-style zero initializer based on
+*image.size()* and *image.type()*
+
+-   We ask now the values of \f$\alpha\f$ and \f$\beta\f$ to be entered by the user:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp basic-linear-transform-parameters
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java basic-linear-transform-parameters
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py basic-linear-transform-parameters
+@end_toggle
+
+-   Now, to perform the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ we will access to each
    pixel in image. Since we are operating with BGR images, we will have three values per pixel (B,
    G and R), so we will also access them separately. Here is the piece of code:
-    @snippet BasicLinearTransforms.cpp basic-linear-transform-operation
-    Notice the following:
-    -   To access each pixel in the images we are using this syntax: *image.at\<Vec3b\>(y,x)[c]*
-        where *y* is the row, *x* is the column and *c* is R, G or B (0, 1 or 2).
-    -   Since the operation \f$\alpha \cdot p(i,j) + \beta\f$ can give values out of range or not
-        integers (if \f$\alpha\f$ is float), we use cv::saturate_cast to make sure the
-        values are valid.

-#  Finally, we create windows and show the images, the usual way.
-    @snippet BasicLinearTransforms.cpp basic-linear-transform-display
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp basic-linear-transform-operation
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java basic-linear-transform-operation
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py basic-linear-transform-operation
+@end_toggle
+
+Notice the following (**C++ code only**):
+-   To access each pixel in the images we are using this syntax: *image.at\<Vec3b\>(y,x)[c]*
+    where *y* is the row, *x* is the column and *c* is R, G or B (0, 1 or 2).
+-   Since the operation \f$\alpha \cdot p(i,j) + \beta\f$ can give values out of range or not
+    integers (if \f$\alpha\f$ is float), we use cv::saturate_cast to make sure the
+    values are valid.
+
+-   Finally, we create windows and show the images, the usual way.
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp basic-linear-transform-display
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java basic-linear-transform-display
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py basic-linear-transform-display
+@end_toggle

@note
    Instead of using the **for** loops to access each pixel, we could have simply used this command:
-    @code{.cpp}
-    image.convertTo(new_image, -1, alpha, beta);
-    @endcode
-    where @ref cv::Mat::convertTo would effectively perform *new_image = a*image + beta\*. However, we
-    wanted to show you how to access each pixel. In any case, both methods give the same result but
-    convertTo is more optimized and works a lot faster.
+
+@add_toggle_cpp
+@code{.cpp}
+image.convertTo(new_image, -1, alpha, beta);
+@endcode
+@end_toggle
+
+@add_toggle_java
+@code{.java}
+image.convertTo(newImage, -1, alpha, beta);
+@endcode
+@end_toggle
+
+@add_toggle_python
+@code{.py}
+new_image = cv.convertScaleAbs(image, alpha=alpha, beta=beta)
+@endcode
+@end_toggle
+
+where @ref cv::Mat::convertTo would effectively perform *new_image = a*image + beta\*. However, we
+wanted to show you how to access each pixel. In any case, both methods give the same result but
+convertTo is more optimized and works a lot faster.

 Result
 ------
@@ -185,10 +283,31 @@ and are not intended to be used as a replacement of a raster graphics editor!**

 ### Code

-Code for the tutorial is [here](https://github.com/opencv/opencv/blob/3.4/samples/cpp/tutorial_code/ImgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.cpp).
+@add_toggle_cpp
+Code for the tutorial is [here](https://github.com/opencv/opencv/blob/master/samples/cpp/tutorial_code/ImgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.cpp).
+@end_toggle
+
+@add_toggle_java
+Code for the tutorial is [here](https://github.com/opencv/opencv/blob/master/samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/ChangingContrastBrightnessImageDemo.java).
+@end_toggle
+
+@add_toggle_python
+Code for the tutorial is [here](https://github.com/opencv/opencv/blob/master/samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.py).
+@end_toggle
+
 Code for the gamma correction:

-@snippet changing_contrast_brightness_image.cpp changing-contrast-brightness-gamma-correction
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.cpp changing-contrast-brightness-gamma-correction
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/ChangingContrastBrightnessImageDemo.java changing-contrast-brightness-gamma-correction
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.py changing-contrast-brightness-gamma-correction
+@end_toggle

 A look-up table is used to improve the performance of the computation as only 256 values needs to be calculated once.

@@ -1,7 +1,7 @@
 Discrete Fourier Transform {#tutorial_discrete_fourier_transform}
 ==========================

-@prev_tutorial{tutorial_random_generator_and_text}
+@prev_tutorial{tutorial_basic_linear_transform}
@next_tutorial{tutorial_file_input_output_with_xml_yml}

 Goal
@@ -19,7 +19,7 @@ Source code

@add_toggle_cpp
 You can [download this from here
-](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
 find it in the
 `samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp` of the
 OpenCV source code library.
@@ -27,7 +27,7 @@ OpenCV source code library.

@add_toggle_java
 You can [download this from here
-](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java) or
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java) or
 find it in the
 `samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java` of the
 OpenCV source code library.
@@ -35,7 +35,7 @@ OpenCV source code library.

@add_toggle_python
 You can [download this from here
-](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py) or
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py) or
 find it in the
 `samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py` of the
 OpenCV source code library.
@@ -222,7 +222,7 @@ An application idea would be to determine the geometrical orientation present in
 example, let us find out if a text is horizontal or not? Looking at some text you'll notice that the
 text lines sort of form also horizontal lines and the letters form sort of vertical lines. These two
 main components of a text snippet may be also seen in case of the Fourier transform. Let us use
-[this horizontal ](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/data/imageTextN.png) and [this rotated](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/data/imageTextR.png)
+[this horizontal ](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/imageTextN.png) and [this rotated](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/imageTextR.png)
 image about a text.

 In case of the horizontal text:
@@ -1,6 +1,9 @@
 File Input and Output using XML and YAML files {#tutorial_file_input_output_with_xml_yml}
 ==============================================

+@prev_tutorial{tutorial_discrete_fourier_transform}
+@next_tutorial{tutorial_interoperability_with_OpenCV_1}
+
 Goal
 ----

@@ -16,7 +19,7 @@ Source code
 -----------

 You can [download this from here
-](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
 `samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp` of the OpenCV source code
 library.

@@ -1,6 +1,9 @@
 How to scan images, lookup tables and time measurement with OpenCV {#tutorial_how_to_scan_images}
 ==================================================================

+@prev_tutorial{tutorial_mat_the_basic_image_container}
+@next_tutorial{tutorial_mat_mask_operations}
+
 Goal
 ----

@@ -51,7 +54,7 @@ three major ways of going through an image pixel by pixel. To make things a litt
 will make the scanning for each image using all of these methods, and print out how long it took.

 You can download the full source code [here
-](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
 the samples directory of OpenCV at the cpp tutorial code for the core section. Its basic usage is:
@code{.bash}
 how_to_scan_images imageName.jpg intValueToReduce [G]
@@ -1,13 +1,15 @@
 How to use the OpenCV parallel_for_ to parallelize your code {#tutorial_how_to_use_OpenCV_parallel_for_}
 ==================================================================

+@prev_tutorial{tutorial_interoperability_with_OpenCV_1}
+
 Goal
 ----

 The goal of this tutorial is to show you how to use the OpenCV `parallel_for_` framework to easily
 parallelize your code. To illustrate the concept, we will write a program to draw a Mandelbrot set
 exploiting almost all the CPU load available.
-The full tutorial code is [here](https://github.com/opencv/opencv/blob/3.4/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
+The full tutorial code is [here](https://github.com/opencv/opencv/blob/master/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
 If you want more information about multithreading, you will have to refer to a reference book or course as this tutorial is intended
 to remain simple.

@@ -175,7 +177,7 @@ C++ 11 standard allows to simplify the parallel implementation by get rid of the
 Results
 -----------

-You can find the full tutorial code [here](https://github.com/opencv/opencv/blob/3.4/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
+You can find the full tutorial code [here](https://github.com/opencv/opencv/blob/master/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
 The performance of the parallel implementation depends of the type of CPU you have. For instance, on 4 cores / 8 threads
 CPU, you can expect a speed-up of around 6.9X. There are many factors to explain why we do not achieve a speed-up of almost 8X.
 Main reasons should be mostly due to:
@@ -1,143 +0,0 @@
-Intel® IPP Asynchronous C/C++ library in OpenCV {#tutorial_how_to_use_ippa_conversion}
-===============================================
-
-Goal
----
-
-The tutorial demonstrates the [Intel® IPP Asynchronous
-C/C++](http://software.intel.com/en-us/intel-ipp-preview) library usage with OpenCV. The code
-example below illustrates implementation of the Sobel operation, accelerated with Intel® IPP
-Asynchronous C/C++ functions. In this code example, @ref cv::hpp::getMat and @ref cv::hpp::getHpp
-functions are used for data conversion between
-[hppiMatrix](http://software.intel.com/en-us/node/501660) and Mat matrices.
-
-Code
----
-
-You may also find the source code in the
-`samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp` file of the OpenCV source library or
-download it from [here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
-
-@include cpp/tutorial_code/core/ippasync/ippasync_sample.cpp
-
-Explanation
-----------
-
-#  Create parameters for OpenCV:
-    @code{.cpp}
-    VideoCapture cap;
-    Mat image, gray, result;
-    @endcode
-    and IPP Async:
-    @code{.cpp}
-    hppiMatrix* src,* dst;
-    hppAccel accel = 0;
-    hppAccelType accelType;
-    hppStatus sts;
-    hppiVirtualMatrix * virtMatrix;
-    @endcode
-#  Load input image or video. How to open and read video stream you can see in the
-    @ref tutorial_video_input_psnr_ssim tutorial.
-    @code{.cpp}
-    if( useCamera )
-    {
-       printf("used camera\n");
-       cap.open(0);
-    }
-    else
-    {
-       printf("used image %s\n", file.c_str());
-       cap.open(file.c_str());
-    }
-
-    if( !cap.isOpened() )
-    {
-       printf("can not open camera or video file\n");
-       return -1;
-    }
-    @endcode
-#  Create accelerator instance using
-    [hppCreateInstance](http://software.intel.com/en-us/node/501686):
-    @code{.cpp}
-    accelType = sAccel == "cpu" ? HPP_ACCEL_TYPE_CPU:
-                sAccel == "gpu" ? HPP_ACCEL_TYPE_GPU:
-                                  HPP_ACCEL_TYPE_ANY;
-
-    //Create accelerator instance
-    sts = hppCreateInstance(accelType, 0, &accel);
-    CHECK_STATUS(sts, "hppCreateInstance");
-    @endcode
-#  Create an array of virtual matrices using
-    [hppiCreateVirtualMatrices](http://software.intel.com/en-us/node/501700) function.
-    @code{.cpp}
-    virtMatrix = hppiCreateVirtualMatrices(accel, 1);
-    @endcode
-#  Prepare a matrix for input and output data:
-    @code{.cpp}
-    cap >> image;
-    if(image.empty())
-       break;
-
-    cvtColor( image, gray, COLOR_BGR2GRAY );
-
-    result.create( image.rows, image.cols, CV_8U);
-    @endcode
-#  Convert Mat to [hppiMatrix](http://software.intel.com/en-us/node/501660) using @ref cv::hpp::getHpp
-    and call [hppiSobel](http://software.intel.com/en-us/node/474701) function.
-    @code{.cpp}
-    //convert Mat to hppiMatrix
-    src = getHpp(gray, accel);
-    dst = getHpp(result, accel);
-
-    sts = hppiSobel(accel,src, HPP_MASK_SIZE_3X3,HPP_NORM_L1,virtMatrix[0]);
-    CHECK_STATUS(sts,"hppiSobel");
-
-    sts = hppiConvert(accel, virtMatrix[0], 0, HPP_RND_MODE_NEAR, dst, HPP_DATA_TYPE_8U);
-    CHECK_STATUS(sts,"hppiConvert");
-
-    // Wait for tasks to complete
-    sts = hppWait(accel, HPP_TIME_OUT_INFINITE);
-    CHECK_STATUS(sts, "hppWait");
-    @endcode
-    We use [hppiConvert](http://software.intel.com/en-us/node/501746) because
-    [hppiSobel](http://software.intel.com/en-us/node/474701) returns destination matrix with
-    HPP_DATA_TYPE_16S data type for source matrix with HPP_DATA_TYPE_8U type. You should check
-    hppStatus after each call IPP Async function.
-
-#  Create windows and show the images, the usual way.
-    @code{.cpp}
-    imshow("image", image);
-    imshow("rez", result);
-
-    waitKey(15);
-    @endcode
-#  Delete hpp matrices.
-    @code{.cpp}
-    sts =  hppiFreeMatrix(src);
-    CHECK_DEL_STATUS(sts,"hppiFreeMatrix");
-
-    sts =  hppiFreeMatrix(dst);
-    CHECK_DEL_STATUS(sts,"hppiFreeMatrix");
-    @endcode
-#  Delete virtual matrices and accelerator instance.
-    @code{.cpp}
-    if (virtMatrix)
-    {
-       sts = hppiDeleteVirtualMatrices(accel, virtMatrix);
-       CHECK_DEL_STATUS(sts,"hppiDeleteVirtualMatrices");
-    }
-
-    if (accel)
-    {
-       sts = hppDeleteInstance(accel);
-       CHECK_DEL_STATUS(sts, "hppDeleteInstance");
-    }
-    @endcode
-
-Result
------
-
-After compiling the code above we can execute it giving an image or video path and accelerator type
-as an argument. For this tutorial we use baboon.png image as input. The result is below.
-
-![](images/How_To_Use_IPPA_Result.jpg)
@@ -1,6 +1,9 @@
 Interoperability with OpenCV 1 {#tutorial_interoperability_with_OpenCV_1}
 ==============================

+@prev_tutorial{tutorial_file_input_output_with_xml_yml}
+@next_tutorial{tutorial_how_to_use_OpenCV_parallel_for_}
+
 Goal
 ----

@@ -85,7 +88,7 @@ L = Mat(pI);
 A case study
 ------------

-Now that you have the basics done [here's](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
+Now that you have the basics done [here's](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
 an example that mixes the usage of the C interface with the C++ one. You will also find it in the
 sample directory of the OpenCV source code library at the
 `samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp` .
@@ -132,7 +135,7 @@ output:

 You may observe a runtime instance of this on the [YouTube
 here](https://www.youtube.com/watch?v=qckm-zvo31w) and you can [download the source code from here
-](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
+](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
 or find it in the
 `samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp`
 of the OpenCV source code library.
@@ -33,7 +33,7 @@ Code

@add_toggle_cpp
 You can download this source code from [here
-](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
 OpenCV source code libraries sample directory at
 `samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.
@include samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp
@@ -41,7 +41,7 @@ OpenCV source code libraries sample directory at

@add_toggle_java
 You can download this source code from [here
-](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java) or look in the
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java) or look in the
 OpenCV source code libraries sample directory at
 `samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java`.
@include samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java
@@ -49,7 +49,7 @@ OpenCV source code libraries sample directory at

@add_toggle_python
 You can download this source code from [here
-](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py) or look in the
+](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py) or look in the
 OpenCV source code libraries sample directory at
 `samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py`.
@include samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py
@@ -1,31 +1,59 @@
 Operations with images {#tutorial_mat_operations}
 ======================

+@prev_tutorial{tutorial_mat_mask_operations}
+@next_tutorial{tutorial_adding_images}
+
 Input/Output
 ------------

 ### Images

 Load an image from a file:
-@code{.cpp}
-    Mat img = imread(filename)
-@endcode
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Load an image from a file
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Load an image from a file
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Load an image from a file
+@end_toggle

 If you read a jpg file, a 3 channel image is created by default. If you need a grayscale image, use:

-@code{.cpp}
-    Mat img = imread(filename, IMREAD_GRAYSCALE);
-@endcode
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Load an image from a file in grayscale
+@end_toggle

-@note format of the file is determined by its content (first few bytes) Save an image to a file:
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Load an image from a file in grayscale
+@end_toggle

-@code{.cpp}
-    imwrite(filename, img);
-@endcode
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Load an image from a file in grayscale
+@end_toggle

-@note format of the file is determined by its extension.
+@note Format of the file is determined by its content (first few bytes). To save an image to a file:

-@note use imdecode and imencode to read and write image from/to memory rather than a file.
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Save image
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Save image
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Save image
+@end_toggle
+
+@note Format of the file is determined by its extension.
+
+@note Use cv::imdecode and cv::imencode to read and write an image from/to memory rather than a file.

 Basic operations with images
 ----------------------------
@@ -35,49 +63,65 @@ Basic operations with images
 In order to get pixel intensity value, you have to know the type of an image and the number of
 channels. Here is an example for a single channel grey scale image (type 8UC1) and pixel coordinates
 x and y:
-@code{.cpp}
-    Scalar intensity = img.at<uchar>(y, x);
-@endcode
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Pixel access 1
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Pixel access 1
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Pixel access 1
+@end_toggle
+
+C++ version only:
 intensity.val[0] contains a value from 0 to 255. Note the ordering of x and y. Since in OpenCV
 images are represented by the same structure as matrices, we use the same convention for both
 cases - the 0-based row index (or y-coordinate) goes first and the 0-based column index (or
-x-coordinate) follows it. Alternatively, you can use the following notation:
-@code{.cpp}
-    Scalar intensity = img.at<uchar>(Point(x, y));
-@endcode
+x-coordinate) follows it. Alternatively, you can use the following notation (**C++ only**):
+
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Pixel access 2
+
 Now let us consider a 3 channel image with BGR color ordering (the default format returned by
 imread):
-@code{.cpp}
-    Vec3b intensity = img.at<Vec3b>(y, x);
-    uchar blue = intensity.val[0];
-    uchar green = intensity.val[1];
-    uchar red = intensity.val[2];
-@endcode
+
+**C++ code**
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Pixel access 3
+
+**Python Python**
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Pixel access 3
+
 You can use the same method for floating-point images (for example, you can get such an image by
-running Sobel on a 3 channel image):
-@code{.cpp}
-    Vec3f intensity = img.at<Vec3f>(y, x);
-    float blue = intensity.val[0];
-    float green = intensity.val[1];
-    float red = intensity.val[2];
-@endcode
+running Sobel on a 3 channel image) (**C++ only**):
+
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Pixel access 4
+
 The same method can be used to change pixel intensities:
-@code{.cpp}
-    img.at<uchar>(y, x) = 128;
-@endcode
-There are functions in OpenCV, especially from calib3d module, such as projectPoints, that take an
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Pixel access 5
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Pixel access 5
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Pixel access 5
+@end_toggle
+
+There are functions in OpenCV, especially from calib3d module, such as cv::projectPoints, that take an
 array of 2D or 3D points in the form of Mat. Matrix should contain exactly one column, each row
 corresponds to a point, matrix type should be 32FC2 or 32FC3 correspondingly. Such a matrix can be
-easily constructed from `std::vector`:
-@code{.cpp}
-    vector<Point2f> points;
-    //... fill the array
-    Mat pointsMat = Mat(points);
-@endcode
-One can access a point in this matrix using the same method Mat::at :
-@code{.cpp}
-Point2f point = pointsMat.at<Point2f>(i, 0);
-@endcode
+easily constructed from `std::vector` (**C++ only**):
+
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Mat from points vector
+
+One can access a point in this matrix using the same method `Mat::at` (**C++ only**):
+
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Point access

 ### Memory management and reference counting

@@ -85,91 +129,141 @@ Mat is a structure that keeps matrix/image characteristics (rows and columns num
 and a pointer to data. So nothing prevents us from having several instances of Mat corresponding to
 the same data. A Mat keeps a reference count that tells if data has to be deallocated when a
 particular instance of Mat is destroyed. Here is an example of creating two matrices without copying
-data:
-@code{.cpp}
-    std::vector<Point3f> points;
-    // .. fill the array
-    Mat pointsMat = Mat(points).reshape(1);
-@endcode
-As a result we get a 32FC1 matrix with 3 columns instead of 32FC3 matrix with 1 column. pointsMat
+data (**C++ only**):
+
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Reference counting 1
+
+As a result, we get a 32FC1 matrix with 3 columns instead of 32FC3 matrix with 1 column. `pointsMat`
 uses data from points and will not deallocate the memory when destroyed. In this particular
-instance, however, developer has to make sure that lifetime of points is longer than of pointsMat.
+instance, however, developer has to make sure that lifetime of `points` is longer than of `pointsMat`
 If we need to copy the data, this is done using, for example, cv::Mat::copyTo or cv::Mat::clone:
-@code{.cpp}
-    Mat img = imread("image.jpg");
-    Mat img1 = img.clone();
-@endcode
-To the contrary with C API where an output image had to be created by developer, an empty output Mat
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Reference counting 2
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Reference counting 2
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Reference counting 2
+@end_toggle
+
+To the contrary with C API where an output image had to be created by the developer, an empty output Mat
 can be supplied to each function. Each implementation calls Mat::create for a destination matrix.
 This method allocates data for a matrix if it is empty. If it is not empty and has the correct size
-and type, the method does nothing. If, however, size or type are different from input arguments, the
+and type, the method does nothing. If however, size or type are different from the input arguments, the
 data is deallocated (and lost) and a new data is allocated. For example:
-@code{.cpp}
-    Mat img = imread("image.jpg");
-    Mat sobelx;
-    Sobel(img, sobelx, CV_32F, 1, 0);
-@endcode
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Reference counting 3
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Reference counting 3
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Reference counting 3
+@end_toggle

 ### Primitive operations

 There is a number of convenient operators defined on a matrix. For example, here is how we can make
-a black image from an existing greyscale image \`img\`:
-@code{.cpp}
-    img = Scalar(0);
-@endcode
+a black image from an existing greyscale image `img`
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Set image to black
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Set image to black
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Set image to black
+@end_toggle
+
 Selecting a region of interest:
-@code{.cpp}
-    Rect r(10, 10, 100, 100);
-    Mat smallImg = img(r);
-@endcode
-A conversion from Mat to C API data structures:
-@code{.cpp}
-    Mat img = imread("image.jpg");
-    IplImage img1 = img;
-    CvMat m = img;
-@endcode
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Select ROI
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Select ROI
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Select ROI
+@end_toggle
+
+A conversion from Mat to C API data structures (**C++ only**):
+
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp C-API conversion

 Note that there is no data copying here.

-Conversion from color to grey scale:
-@code{.cpp}
-    Mat img = imread("image.jpg"); // loading a 8UC3 image
-    Mat grey;
-    cvtColor(img, grey, COLOR_BGR2GRAY);
-@endcode
+Conversion from color to greyscale:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp BGR to Gray
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java BGR to Gray
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py BGR to Gray
+@end_toggle
+
 Change image type from 8UC1 to 32FC1:
-@code{.cpp}
-    src.convertTo(dst, CV_32F);
-@endcode
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp Convert to CV_32F
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java Convert to CV_32F
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py Convert to CV_32F
+@end_toggle

 ### Visualizing images

 It is very useful to see intermediate results of your algorithm during development process. OpenCV
 provides a convenient way of visualizing images. A 8U image can be shown using:
-@code{.cpp}
-    Mat img = imread("image.jpg");

-    namedWindow("image", WINDOW_AUTOSIZE);
-    imshow("image", img);
-    waitKey();
-@endcode
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp imshow 1
+@end_toggle
+
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java imshow 1
+@end_toggle
+
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py imshow 1
+@end_toggle

 A call to waitKey() starts a message passing cycle that waits for a key stroke in the "image"
 window. A 32F image needs to be converted to 8U type. For example:
-@code{.cpp}
-    Mat img = imread("image.jpg");
-    Mat grey;
-    cvtColor(img, grey, COLOR_BGR2GRAY);

-    Mat sobelx;
-    Sobel(grey, sobelx, CV_32F, 1, 0);
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp imshow 2
+@end_toggle

-    double minVal, maxVal;
-    minMaxLoc(sobelx, &minVal, &maxVal); //find minimum and maximum intensities
-    Mat draw;
-    sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal * 255.0/(maxVal - minVal));
+@add_toggle_java
+@snippet samples/java/tutorial_code/core/mat_operations/MatOperations.java imshow 2
+@end_toggle

-    namedWindow("image", WINDOW_AUTOSIZE);
-    imshow("image", draw);
-    waitKey();
-@endcode
+@add_toggle_python
+@snippet samples/python/tutorial_code/core/mat_operations/mat_operations.py imshow 2
+@end_toggle
+
+@note Here cv::namedWindow is not necessary since it is immediately followed by cv::imshow.
+Nevertheless, it can be used to change the window properties or when using cv::createTrackbar
@@ -1,6 +1,8 @@
 Mat - The Basic Image Container {#tutorial_mat_the_basic_image_container}
 ===============================

+@next_tutorial{tutorial_how_to_scan_images}
+
 Goal
 ----

@@ -260,7 +262,7 @@ OpenCV offers support for output of other common OpenCV data structures too via
    ![](images/MatBasicContainerOut15.png)

 Most of the samples here have been included in a small console application. You can download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
 or in the core section of the cpp samples.

 You can also find a quick video demonstration of this on
@@ -36,6 +36,10 @@ understanding how to manipulate the images on a pixel level.

 -   @subpage tutorial_mat_operations

+    *Languages:* C++, Java, Python
+
+    *Compatibility:* \> OpenCV 2.0
+
    Reading/writing images from file, accessing pixels, primitive operations, visualizing images.

 -   @subpage tutorial_adding_images
@@ -50,29 +54,13 @@ understanding how to manipulate the images on a pixel level.

 -   @subpage tutorial_basic_linear_transform

-    *Compatibility:* \> OpenCV 2.0
-
-    *Author:* Ana Huamán
-
-    We will learn how to change our image appearance!
-
-   @subpage tutorial_basic_geometric_drawing
-
    *Languages:* C++, Java, Python

    *Compatibility:* \> OpenCV 2.0

    *Author:* Ana Huamán

-    We will learn how to draw simple geometry with OpenCV!
-
-   @subpage tutorial_random_generator_and_text
-
-    *Compatibility:* \> OpenCV 2.0
-
-    *Author:* Ana Huamán
-
-    We will draw some *fancy-looking* stuff using OpenCV!
+    We will learn how to change our image appearance!

 -   @subpage tutorial_discrete_fourier_transform

@@ -105,15 +93,6 @@ understanding how to manipulate the images on a pixel level.
    Look here to shed light on all this questions.


-   @subpage tutorial_how_to_use_ippa_conversion
-
-    *Compatibility:* \> OpenCV 2.0
-
-    *Author:* Elena Gvozdeva
-
-    You will see how to use the IPP Async with OpenCV.
-
-
 -   @subpage tutorial_how_to_use_OpenCV_parallel_for_

    *Compatibility:* \>= OpenCV 2.4.3
@@ -12,7 +12,7 @@ Tutorial was written for the following versions of corresponding software:

 - Download and install Android Studio from https://developer.android.com/studio.

- Get the latest pre-built OpenCV for Android release from https://github.com/opencv/opencv/releases and unpack it (for example, `opencv-3.4.2-android-sdk.zip`).
+- Get the latest pre-built OpenCV for Android release from https://github.com/opencv/opencv/releases and unpack it (for example, `opencv-3.4.3-android-sdk.zip`).

 - Download MobileNet object detection model from https://github.com/chuanqi305/MobileNet-SSD. We need a configuration file `MobileNetSSD_deploy.prototxt` and weights `MobileNetSSD_deploy.caffemodel`.

@@ -216,7 +216,7 @@ a centric one.
@snippet dnn/edge_detection.py Register

 That's it! We've replaced an implemented OpenCV's layer to a custom one.
-You may find a full script in the [source code](https://github.com/opencv/opencv/tree/3.4/samples/dnn/edge_detection.py).
+You may find a full script in the [source code](https://github.com/opencv/opencv/tree/master/samples/dnn/edge_detection.py).

 <table border="0">
 <tr>
@@ -13,7 +13,7 @@ We will demonstrate results of this example on the following picture.
 Source Code
 -----------

-We will be using snippets from the example application, that can be downloaded [here](https://github.com/opencv/opencv/blob/3.4/samples/dnn/classification.cpp).
+We will be using snippets from the example application, that can be downloaded [here](https://github.com/opencv/opencv/blob/master/samples/dnn/classification.cpp).

@include dnn/classification.cpp

@@ -25,7 +25,7 @@ Explanation
   [bvlc_googlenet.caffemodel](http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel)

   Also you need file with names of [ILSVRC2012](http://image-net.org/challenges/LSVRC/2012/browse-synsets) classes:
-   [classification_classes_ILSVRC2012.txt](https://github.com/opencv/opencv/tree/3.4/samples/dnn/classification_classes_ILSVRC2012.txt).
+   [classification_classes_ILSVRC2012.txt](https://github.com/opencv/opencv/tree/master/samples/dnn/classification_classes_ILSVRC2012.txt).

   Put these files into working dir of this program example.

@@ -68,8 +68,6 @@ MSBuild.exe /m:4 /t:Build /p:Configuration=Release .\\ALL_BUILD.vcxproj
 ## Build OpenCV with Halide backend
 When you build OpenCV add the following configuration flags:

- `ENABLE_CXX11` - enable C++11 standard
-
 - `WITH_HALIDE` - enable Halide linkage

 - `HALIDE_ROOT_DIR` - path to Halide build directory
@@ -19,8 +19,8 @@ Source Code
 -----------

 Use a universal sample for object detection models written
-[in C++](https://github.com/opencv/opencv/blob/3.4/samples/dnn/object_detection.cpp) and
-[in Python](https://github.com/opencv/opencv/blob/3.4/samples/dnn/object_detection.py) languages
+[in C++](https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.cpp) and
+[in Python](https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.py) languages

 Usage examples
 --------------
@@ -32,7 +32,7 @@ You can find the images (*graf1.png*, *graf3.png*) and homography (*H1to3p.xml*)

@add_toggle_cpp
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)

 -   **Code at glance:**
    @include samples/cpp/tutorial_code/features2D/AKAZE_match.cpp
@@ -40,7 +40,7 @@ You can find the images (*graf1.png*, *graf3.png*) and homography (*H1to3p.xml*)

@add_toggle_java
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java)
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java)

 -   **Code at glance:**
    @include samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java
@@ -48,7 +48,7 @@ You can find the images (*graf1.png*, *graf3.png*) and homography (*H1to3p.xml*)

@add_toggle_python
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py)
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py)

 -   **Code at glance:**
    @include samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py
@@ -24,19 +24,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java)
@include samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py)
@include samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py
@end_toggle

@@ -22,19 +22,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
@include samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
@include samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py
@end_toggle

@@ -45,19 +45,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java)
@include samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py)
@include samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py
@end_toggle

@@ -20,19 +20,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java)
@include samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py)
@include samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py
@end_toggle

@@ -12,8 +12,8 @@ For detailed explanations about the theory, please refer to a computer vision co
 *   An Invitation to 3-D Vision: From Images to Geometric Models, @cite Ma:2003:IVI
 *   Computer Vision: Algorithms and Applications, @cite RS10

-The tutorial code can be found [here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/Homography).
-The images used in this tutorial can be found [here](https://github.com/opencv/opencv/tree/3.4/samples/data) (`left*.jpg`).
+The tutorial code can be found [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/Homography).
+The images used in this tutorial can be found [here](https://github.com/opencv/opencv/tree/master/samples/data) (`left*.jpg`).

 Basic theory {#tutorial_homography_Basic_theory}
 ------------
@@ -17,19 +17,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java)
@include samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py
@end_toggle

@@ -21,21 +21,21 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)

@include samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java)

@include samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py)

@include samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py
@end_toggle
@@ -16,19 +16,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java)
@include samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py
@end_toggle

@@ -120,19 +120,19 @@ Code

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java)
@include samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py
@end_toggle

@@ -24,7 +24,7 @@ The source code

 You may also find the source code and the video file in the
 `samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity` directory of the OpenCV
-source library or download it from [here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
+source library or download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
 The full source code is quite long (due to the controlling of the application via the command line
 arguments and performance measurement). Therefore, to avoid cluttering up these sections with those
 you'll find here only the functions itself.
@@ -27,19 +27,19 @@ Let's modify the program made in the tutorial @ref tutorial_adding_images. We wi

@add_toggle_cpp
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp)
@include cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp
@end_toggle

@add_toggle_java
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/highgui/trackbar/AddingImagesTrackbar.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/highgui/trackbar/AddingImagesTrackbar.java)
@include java/tutorial_code/highgui/trackbar/AddingImagesTrackbar.java
@end_toggle

@add_toggle_python
 This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py)
@include python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py
@end_toggle

@@ -0,0 +1,91 @@
+Anisotropic image segmentation by a gradient structure tensor {#tutorial_anisotropic_image_segmentation_by_a_gst}
+==========================
+
+Goal
+----
+
+In this tutorial you will learn:
+
+-   what the gradient structure tensor is
+-   how to estimate orientation and coherency of an anisotropic image by a gradient structure tensor
+-   how to segment an anisotropic image with a single local orientation by a gradient structure tensor
+
+Theory
+------
+
+@note The explanation is based on the books @cite jahne2000computer, @cite bigun2006vision and @cite van1995estimators. Good physical explanation of a gradient structure tensor is given in @cite yang1996structure. Also, you can refer to a wikipedia page [Structure tensor].
+@note A anisotropic image on this page is a real world  image.
+
+### What is the gradient structure tensor?
+
+In mathematics, the gradient structure tensor (also referred to as the second-moment matrix, the second order moment tensor, the inertia tensor, etc.) is a matrix derived from the gradient of a function. It summarizes the predominant directions of the gradient in a specified neighborhood of a point, and the degree to which those directions are coherent (coherency). The gradient structure tensor is widely used in image processing and computer vision for 2D/3D image segmentation, motion detection, adaptive filtration, local image features detection, etc.
+
+Important features of anisotropic images include orientation and coherency of a local anisotropy. In this paper we will show how to estimate orientation and coherency, and how to segment an anisotropic image with a single local orientation by a gradient structure tensor.
+
+The gradient structure tensor of an image is a 2x2 symmetric matrix. Eigenvectors of the gradient structure tensor indicate local orientation, whereas eigenvalues give coherency (a measure of anisotropism).
+
+The gradient structure tensor \f$J\f$ of an image \f$Z\f$ can be written as:
+
+\f[J = \begin{bmatrix}
+J_{11} & J_{12}  \\
+J_{12} & J_{22}
+\end{bmatrix}\f]
+
+where \f$J_{11} = M[Z_{x}^{2}]\f$, \f$J_{22} = M[Z_{y}^{2}]\f$, \f$J_{12} = M[Z_{x}Z_{y}]\f$ - components of the tensor, \f$M[]\f$ is a symbol of mathematical expectation (we can consider this operation as averaging in a window w), \f$Z_{x}\f$ and \f$Z_{y}\f$ are partial derivatives of an image \f$Z\f$ with respect to \f$x\f$ and \f$y\f$.
+
+The eigenvalues of the tensor can be found in the below formula:
+\f[\lambda_{1,2} = J_{11} + J_{22} \pm \sqrt{(J_{11} - J_{22})^{2} + 4J_{12}^{2}}\f]
+where \f$\lambda_1\f$ - largest eigenvalue, \f$\lambda_2\f$ - smallest eigenvalue.
+
+### How to estimate orientation and coherency of an anisotropic image by gradient structure tensor?
+
+The orientation of an anisotropic image:
+\f[\alpha = 0.5arctg\frac{2J_{12}}{J_{22} - J_{11}}\f]
+
+Coherency:
+\f[C = \frac{\lambda_1 - \lambda_2}{\lambda_1 + \lambda_2}\f]
+
+The coherency ranges from 0 to 1. For ideal local orientation (\f$\lambda_2\f$ = 0, \f$\lambda_1\f$ > 0) it is one, for an isotropic gray value structure (\f$\lambda_1\f$ = \f$\lambda_2\f$ > 0) it is zero.
+
+Source code
+-----------
+
+You can find source code in the `samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp` of the OpenCV source code library.
+
+@include cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp
+
+Explanation
+-----------
+An anisotropic image segmentation algorithm consists of a gradient structure tensor calculation, an orientation calculation, a coherency calculation and an orientation and coherency thresholding:
+@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp main
+
+A function calcGST() calculates orientation and coherency by using a gradient structure tensor. An input parameter w defines a window size:
+@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp calcGST
+
+The below code applies a thresholds LowThr and HighThr to image orientation and a threshold C_Thr to image coherency calculated by the previous function. LowThr and HighThr define orientation range:
+@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp thresholding
+
+And finally we combine thresholding results:
+@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp combining
+
+Result
+------
+
+Below you can see the real anisotropic image with single direction:
+![Anisotropic image with the single direction](images/gst_input.jpg)
+
+Below you can see the orientation and coherency of the anisotropic image:
+![Orientation](images/gst_orientation.jpg)
+![Coherency](images/gst_coherency.jpg)
+
+Below you can see the segmentation result:
+![Segmentation result](images/gst_result.jpg)
+
+The result has been computed with w = 52, C_Thr = 0.43, LowThr = 35, HighThr = 57. We can see that the algorithm selected only the areas with one single direction.
+
+References
+------
+- [Structure tensor] - structure tensor description on the wikipedia
+
+<!-- invisible references list -->
+[Structure tensor]: https://en.wikipedia.org/wiki/Structure_tensor
@@ -1,7 +1,6 @@
 Basic Drawing {#tutorial_basic_geometric_drawing}
 =============

-@prev_tutorial{tutorial_basic_linear_transform}
@next_tutorial{tutorial_random_generator_and_text}

 Goals
@@ -82,20 +81,20 @@ Code

@add_toggle_cpp
 -   This code is in your OpenCV sample folder. Otherwise you can grab it from
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
-    @include samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp)
+    @include samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp
@end_toggle

@add_toggle_java
 -   This code is in your OpenCV sample folder. Otherwise you can grab it from
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java)
-    @include samples/java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java)
+    @include samples/java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java
@end_toggle

@add_toggle_python
 -   This code is in your OpenCV sample folder. Otherwise you can grab it from
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py)
-    @include samples/python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py)
+    @include samples/python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py
@end_toggle

 Explanation
@@ -104,42 +103,42 @@ Explanation
 Since we plan to draw two examples (an atom and a rook), we have to create two images and two
 windows to display them.
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp create_images
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp create_images
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java create_images
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java create_images
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py create_images
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py create_images
@end_toggle

 We created functions to draw different geometric shapes. For instance, to draw the atom we used
 **MyEllipse** and **MyFilledCircle**:
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp draw_atom
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp draw_atom
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java draw_atom
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java draw_atom
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py draw_atom
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py draw_atom
@end_toggle

 And to draw the rook we employed **MyLine**, **rectangle** and a **MyPolygon**:
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp draw_rook
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp draw_rook
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java draw_rook
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java draw_rook
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py draw_rook
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py draw_rook
@end_toggle


@@ -149,15 +148,15 @@ Let's check what is inside each of these functions:

 <H4>MyLine</H4>
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp my_line
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp my_line
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java my_line
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java my_line
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py my_line
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py my_line
@end_toggle

 -   As we can see, **MyLine** just call the function **line()** , which does the following:
@@ -170,15 +169,15 @@ Let's check what is inside each of these functions:

 <H4>MyEllipse</H4>
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp my_ellipse
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp my_ellipse
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java my_ellipse
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java my_ellipse
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py my_ellipse
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py my_ellipse
@end_toggle

 -   From the code above, we can observe that the function **ellipse()** draws an ellipse such
@@ -194,15 +193,15 @@ Let's check what is inside each of these functions:

 <H4>MyFilledCircle</H4>
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp my_filled_circle
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp my_filled_circle
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java my_filled_circle
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java my_filled_circle
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py my_filled_circle
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py my_filled_circle
@end_toggle

 -   Similar to the ellipse function, we can observe that *circle* receives as arguments:
@@ -215,15 +214,15 @@ Let's check what is inside each of these functions:

 <H4>MyPolygon</H4>
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp my_polygon
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp my_polygon
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java my_polygon
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java my_polygon
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py my_polygon
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py my_polygon
@end_toggle

 -   To draw a filled polygon we use the function **fillPoly()** . We note that:
@@ -235,15 +234,15 @@ Let's check what is inside each of these functions:

 <H4>rectangle</H4>
@add_toggle_cpp
-@snippet cpp/tutorial_code/core/Matrix/Drawing_1.cpp rectangle
+@snippet cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp rectangle
@end_toggle

@add_toggle_java
-@snippet java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java rectangle
+@snippet java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java rectangle
@end_toggle

@add_toggle_python
-@snippet python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py rectangle
+@snippet python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py rectangle
@end_toggle

 -   Finally we have the @ref cv::rectangle function (we did not create a special function for
@@ -1,6 +1,9 @@
 Eroding and Dilating {#tutorial_erosion_dilatation}
 ====================

+@prev_tutorial{tutorial_gausian_median_blur_bilateral_filter}
+@next_tutorial{tutorial_opening_closing_hats}
+
 Goal
 ----

@@ -62,19 +65,19 @@ Code

@add_toggle_cpp
 This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
@include samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp
@end_toggle

@add_toggle_java
 This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/ImgProc/erosion_dilatation/MorphologyDemo1.java)
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/erosion_dilatation/MorphologyDemo1.java)
@include samples/java/tutorial_code/ImgProc/erosion_dilatation/MorphologyDemo1.java
@end_toggle

@add_toggle_python
 This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py)
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py)
@include samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py
@end_toggle

@@ -1,6 +1,7 @@
 Smoothing Images {#tutorial_gausian_median_blur_bilateral_filter}
 ================

+@prev_tutorial{tutorial_random_generator_and_text}
@next_tutorial{tutorial_erosion_dilatation}

 Goal
@@ -97,7 +98,7 @@ Code

@add_toggle_cpp
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)

 -   **Code at glance:**
    @include samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp
@@ -105,7 +106,7 @@ Code

@add_toggle_java
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/java/tutorial_code/ImgProc/Smoothing/Smoothing.java)
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/Smoothing/Smoothing.java)

 -   **Code at glance:**
    @include samples/java/tutorial_code/ImgProc/Smoothing/Smoothing.java
@@ -113,7 +114,7 @@ Code

@add_toggle_python
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/python/tutorial_code/imgProc/Smoothing/smoothing.py)
+    [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/Smoothing/smoothing.py)

 -   **Code at glance:**
    @include samples/python/tutorial_code/imgProc/Smoothing/smoothing.py
@@ -220,7 +221,7 @@ already known by now.
 Results
 -------

-   The code opens an image (in this case [lena.jpg](https://raw.githubusercontent.com/opencv/opencv/3.4/samples/data/lena.jpg))
+-   The code opens an image (in this case [lena.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/lena.jpg))
    and display it under the effects of the 4 filters explained.
 -   Here is a snapshot of the image smoothed using *medianBlur*:

@@ -1,6 +1,9 @@
 Back Projection {#tutorial_back_projection}
 ===============

+@prev_tutorial{tutorial_histogram_comparison}
+@next_tutorial{tutorial_template_matching}
+
 Goal
 ----

@@ -71,13 +74,13 @@ Code
@add_toggle_cpp
 -   **Downloadable code**:
    -   Click
-        [here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
+        [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
        for the basic version (explained in this tutorial).
    -   For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
        skin area) you can check the [improved
-        demo](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
+        demo](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
    -   ...or you can always check out the classical
-        [camshiftdemo](https://github.com/opencv/opencv/tree/3.4/samples/cpp/camshiftdemo.cpp)
+        [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
        in samples.

 -   **Code at glance:**
@@ -87,13 +90,13 @@ Code
@add_toggle_java
 -   **Downloadable code**:
    -   Click
-        [here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo1.java)
+        [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo1.java)
        for the basic version (explained in this tutorial).
    -   For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
        skin area) you can check the [improved
-        demo](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo2.java)
+        demo](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo2.java)
    -   ...or you can always check out the classical
-        [camshiftdemo](https://github.com/opencv/opencv/tree/3.4/samples/cpp/camshiftdemo.cpp)
+        [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
        in samples.

 -   **Code at glance:**
@@ -103,13 +106,13 @@ Code
@add_toggle_python
 -   **Downloadable code**:
    -   Click
-        [here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo1.py)
+        [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo1.py)
        for the basic version (explained in this tutorial).
    -   For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
        skin area) you can check the [improved
-        demo](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo2.py)
+        demo](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo2.py)
    -   ...or you can always check out the classical
-        [camshiftdemo](https://github.com/opencv/opencv/tree/3.4/samples/cpp/camshiftdemo.cpp)
+        [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
        in samples.

 -   **Code at glance:**
--- a/Show More
+++ b/Show More