Merge pull request #2221 from asmorkalov:ocv_test_install_custom

Added opencv_testing.sh.in file;
opencv_testing.sh installation guarded by OS check.

.gitignore

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

3rdparty/include/opencl/1.2/CL/cl.hpp

@@ -210,7 +210,7 @@
 #include <string>
 #endif 
 
-#if defined(linux) || defined(__APPLE__) || defined(__MACOSX)
+#if defined(__linux__) || defined(__APPLE__) || defined(__MACOSX)
 #include <alloca.h>
 
 #include <emmintrin.h>

3rdparty/libjasper/CMakeLists.txt

@@ -46,5 +46,5 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 if(NOT BUILD_SHARED_LIBS)
-  ocv_install_target(${JASPER_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main)
+  ocv_install_target(${JASPER_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
 endif()

3rdparty/libjpeg/CMakeLists.txt

@@ -39,5 +39,5 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 if(NOT BUILD_SHARED_LIBS)
-  ocv_install_target(${JPEG_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main)
+  ocv_install_target(${JPEG_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
 endif()

3rdparty/libpng/CMakeLists.txt

@@ -55,5 +55,5 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 if(NOT BUILD_SHARED_LIBS)
-  ocv_install_target(${PNG_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main)
+  ocv_install_target(${PNG_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
 endif()

3rdparty/libtiff/CMakeLists.txt

@@ -115,5 +115,5 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 if(NOT BUILD_SHARED_LIBS)
-  ocv_install_target(${TIFF_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main)
+  ocv_install_target(${TIFF_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
 endif()

3rdparty/openexr/CMakeLists.txt

@@ -62,7 +62,7 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 if(NOT BUILD_SHARED_LIBS)
-  ocv_install_target(IlmImf EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main)
+  ocv_install_target(IlmImf EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
 endif()
 
 set(OPENEXR_INCLUDE_PATHS ${OPENEXR_INCLUDE_PATHS} PARENT_SCOPE)

3rdparty/tbb/CMakeLists.txt

@@ -248,9 +248,9 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 ocv_install_target(tbb EXPORT OpenCVModules
-    RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main
-    LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT main
-    ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main
+    RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT libs
+    LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT libs
+    ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev
     )
 
 # get TBB version

3rdparty/zlib/CMakeLists.txt

@@ -95,5 +95,5 @@ if(ENABLE_SOLUTION_FOLDERS)
 endif()
 
 if(NOT BUILD_SHARED_LIBS)
-  ocv_install_target(${ZLIB_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT main)
+  ocv_install_target(${ZLIB_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
 endif()

CMakeLists.txt

@@ -197,7 +197,7 @@ OCV_OPTION(INSTALL_C_EXAMPLES       "Install C examples"        OFF )
 OCV_OPTION(INSTALL_PYTHON_EXAMPLES  "Install Python examples"   OFF )
 OCV_OPTION(INSTALL_ANDROID_EXAMPLES "Install Android examples"  OFF IF ANDROID )
 OCV_OPTION(INSTALL_TO_MANGLED_PATHS "Enables mangled install paths, that help with side by side installs." OFF IF (UNIX AND NOT ANDROID AND NOT IOS AND BUILD_SHARED_LIBS) )
-
+OCV_OPTION(INSTALL_TESTS            "Install accuracy and performance test binaries and test data" OFF)
 
 # OpenCV build options
 # ===================================================
@@ -275,6 +275,9 @@ endif()
 set(OPENCV_SAMPLES_BIN_INSTALL_PATH "${OpenCV_INSTALL_BINARIES_PREFIX}samples")
 
 set(OPENCV_BIN_INSTALL_PATH "${OpenCV_INSTALL_BINARIES_PREFIX}bin")
+if(NOT OPENCV_TEST_INSTALL_PATH)
+  set(OPENCV_TEST_INSTALL_PATH "${OPENCV_BIN_INSTALL_PATH}")
+endif()
 
 if(ANDROID)
   set(LIBRARY_OUTPUT_PATH         "${OpenCV_BINARY_DIR}/lib/${ANDROID_NDK_ABI_NAME}")
@@ -283,6 +286,7 @@ if(ANDROID)
   set(OPENCV_3P_LIB_INSTALL_PATH  sdk/native/3rdparty/libs/${ANDROID_NDK_ABI_NAME})
   set(OPENCV_CONFIG_INSTALL_PATH  sdk/native/jni)
   set(OPENCV_INCLUDE_INSTALL_PATH sdk/native/jni/include)
+  set(OPENCV_SAMPLES_SRC_INSTALL_PATH samples/native)
 else()
   set(LIBRARY_OUTPUT_PATH         "${OpenCV_BINARY_DIR}/lib")
   set(3P_LIBRARY_OUTPUT_PATH      "${OpenCV_BINARY_DIR}/3rdparty/lib${LIB_SUFFIX}")
@@ -293,9 +297,11 @@ else()
       set(OPENCV_LIB_INSTALL_PATH   "${OpenCV_INSTALL_BINARIES_PREFIX}lib${LIB_SUFFIX}")
     endif()
     set(OPENCV_3P_LIB_INSTALL_PATH  "${OpenCV_INSTALL_BINARIES_PREFIX}staticlib${LIB_SUFFIX}")
+    set(OPENCV_SAMPLES_SRC_INSTALL_PATH    samples/native)
   else()
     set(OPENCV_LIB_INSTALL_PATH     lib${LIB_SUFFIX})
     set(OPENCV_3P_LIB_INSTALL_PATH  share/OpenCV/3rdparty/${OPENCV_LIB_INSTALL_PATH})
+    set(OPENCV_SAMPLES_SRC_INSTALL_PATH    share/OpenCV/samples)
   endif()
   set(OPENCV_INCLUDE_INSTALL_PATH "include")
 
@@ -558,6 +564,19 @@ include(cmake/OpenCVGenConfig.cmake)
 # Generate Info.plist for the IOS framework
 include(cmake/OpenCVGenInfoPlist.cmake)
 
+# Generate environment setup file
+if(INSTALL_TESTS AND OPENCV_TEST_DATA_PATH AND UNIX AND NOT ANDROID)
+  configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/templates/opencv_testing.sh.in"
+                 "${CMAKE_BINARY_DIR}/unix-install/opencv_testing.sh" @ONLY)
+  install(FILES "${CMAKE_BINARY_DIR}/unix-install/opencv_testing.sh"
+          DESTINATION /etc/profile.d/ COMPONENT tests)
+  configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/templates/opencv_run_all_tests.sh.in"
+                 "${CMAKE_BINARY_DIR}/unix-install/opencv_run_all_tests.sh" @ONLY)
+  install(FILES "${CMAKE_BINARY_DIR}/unix-install/opencv_run_all_tests.sh"
+          PERMISSIONS OWNER_READ OWNER_WRITE GROUP_READ WORLD_READ OWNER_EXECUTE GROUP_EXECUTE WORLD_EXECUTE
+          DESTINATION ${OPENCV_TEST_INSTALL_PATH} COMPONENT tests)
+endif()
+
 # ----------------------------------------------------------------------------
 # Summary:
 # ----------------------------------------------------------------------------
@@ -975,3 +994,9 @@ ocv_finalize_status()
 if("${CMAKE_CURRENT_SOURCE_DIR}" STREQUAL "${CMAKE_CURRENT_BINARY_DIR}")
   message(WARNING "The source directory is the same as binary directory. \"make clean\" may damage the source tree")
 endif()
+
+# ----------------------------------------------------------------------------
+# CPack stuff
+# ----------------------------------------------------------------------------
+
+include(cmake/OpenCVPackaging.cmake)

LICENSE

@@ -1,16 +1,11 @@
-IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-
- By downloading, copying, installing or using the software you agree to this license.
- If you do not agree to this license, do not download, install,
- copy or use the software.
+By downloading, copying, installing or using the software you agree to this license.
+If you do not agree to this license, do not download, install,
+copy or use the software.
 
 
                           License Agreement
                For Open Source Computer Vision Library
-
-Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-Copyright (C) 2008-2011, Willow Garage Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
+                       (3-clause BSD License)
 
 Redistribution and use in source and binary forms, with or without modification,
 are permitted provided that the following conditions are met:
@@ -22,13 +17,14 @@ are permitted provided that the following conditions are met:
     this list of conditions and the following disclaimer in the documentation
     and/or other materials provided with the distribution.
 
-  * The name of the copyright holders may not be used to endorse or promote products
-    derived from this software without specific prior written permission.
+  * Neither the names of the copyright holders nor the names of the contributors
+    may be used to endorse or promote products derived from this software
+    without specific prior written permission.
 
 This software is provided by the copyright holders and contributors "as is" and
 any express or implied warranties, including, but not limited to, the implied
 warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall the Intel Corporation or contributors be liable for any direct,
+In no event shall copyright holders or contributors be liable for any direct,
 indirect, incidental, special, exemplary, or consequential damages
 (including, but not limited to, procurement of substitute goods or services;
 loss of use, data, or profits; or business interruption) however caused

apps/haartraining/CMakeLists.txt

@@ -71,14 +71,14 @@ set_target_properties(opencv_performance PROPERTIES
 
 if(INSTALL_CREATE_DISTRIB)
   if(BUILD_SHARED_LIBS)
-    install(TARGETS opencv_haartraining RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT main)
-    install(TARGETS opencv_createsamples RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT main)
-    install(TARGETS opencv_performance RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT main)
+    install(TARGETS opencv_haartraining RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
+    install(TARGETS opencv_createsamples RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
+    install(TARGETS opencv_performance RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
   endif()
 else()
-  install(TARGETS opencv_haartraining RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main)
-  install(TARGETS opencv_createsamples RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main)
-  install(TARGETS opencv_performance RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main)
+  install(TARGETS opencv_haartraining RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
+  install(TARGETS opencv_createsamples RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
+  install(TARGETS opencv_performance RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
 endif()
 
 if(ENABLE_SOLUTION_FOLDERS)

apps/haartraining/cvclassifier.h

@@ -338,7 +338,7 @@ typedef enum CvBoostType
     CV_LKCLASS  = 5, /* classification (K class problem)    */
     CV_LSREG    = 6, /* least squares regression            */
     CV_LADREG   = 7, /* least absolute deviation regression */
-    CV_MREG     = 8, /* M-regression (Huber loss)           */
+    CV_MREG     = 8  /* M-regression (Huber loss)           */
 } CvBoostType;
 
 /****************************************************************************************\

apps/traincascade/CMakeLists.txt

@@ -35,8 +35,8 @@ endif()
 
 if(INSTALL_CREATE_DISTRIB)
   if(BUILD_SHARED_LIBS)
-    install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT main)
+    install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
   endif()
 else()
-  install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main)
+  install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
 endif()

cmake/OpenCVDetectAndroidSDK.cmake

@@ -344,20 +344,20 @@ macro(add_android_project target path)
     add_custom_command(TARGET ${target} POST_BUILD COMMAND ${CMAKE_COMMAND} -E copy "${android_proj_bin_dir}/bin/${target}-debug.apk" "${OpenCV_BINARY_DIR}/bin/${target}.apk")
     if(INSTALL_ANDROID_EXAMPLES AND "${target}" MATCHES "^example-")
       #apk
-      install(FILES "${OpenCV_BINARY_DIR}/bin/${target}.apk" DESTINATION "samples" COMPONENT main)
+      install(FILES "${OpenCV_BINARY_DIR}/bin/${target}.apk" DESTINATION "samples" COMPONENT samples)
       get_filename_component(sample_dir "${path}" NAME)
       #java part
       list(REMOVE_ITEM android_proj_files ${ANDROID_MANIFEST_FILE})
       foreach(f ${android_proj_files} ${ANDROID_MANIFEST_FILE})
         get_filename_component(install_subdir "${f}" PATH)
-        install(FILES "${android_proj_bin_dir}/${f}" DESTINATION "samples/${sample_dir}/${install_subdir}" COMPONENT main)
+        install(FILES "${android_proj_bin_dir}/${f}" DESTINATION "samples/${sample_dir}/${install_subdir}" COMPONENT samples)
       endforeach()
       #jni part + eclipse files
       file(GLOB_RECURSE jni_files RELATIVE "${path}" "${path}/jni/*" "${path}/.cproject")
       ocv_list_filterout(jni_files "\\\\.svn")
       foreach(f ${jni_files} ".classpath" ".project" ".settings/org.eclipse.jdt.core.prefs")
         get_filename_component(install_subdir "${f}" PATH)
-        install(FILES "${path}/${f}" DESTINATION "samples/${sample_dir}/${install_subdir}" COMPONENT main)
+        install(FILES "${path}/${f}" DESTINATION "samples/${sample_dir}/${install_subdir}" COMPONENT samples)
       endforeach()
       #update proj
       if(android_proj_lib_deps_commands)
@@ -365,9 +365,9 @@ macro(add_android_project target path)
       endif()
       install(CODE "EXECUTE_PROCESS(COMMAND ${ANDROID_EXECUTABLE} --silent update project --path . --target \"${android_proj_sdk_target}\" --name \"${target}\" ${inst_lib_opt}
                                     WORKING_DIRECTORY \"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/samples/${sample_dir}\"
-                                   )"  COMPONENT main)
+                                   )"  COMPONENT dev)
       #empty 'gen'
-      install(CODE "MAKE_DIRECTORY(\"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/samples/${sample_dir}/gen\")" COMPONENT main)
+      install(CODE "MAKE_DIRECTORY(\"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/samples/${sample_dir}/gen\")" COMPONENT samples)
     endif()
   endif()
 endmacro()

cmake/OpenCVDetectPython.cmake

@@ -81,24 +81,39 @@ if(PYTHON_EXECUTABLE)
     SET(PYTHON_PACKAGES_PATH "${_PYTHON_PACKAGES_PATH}" CACHE PATH "Where to install the python packages.")
 
     if(NOT PYTHON_NUMPY_INCLUDE_DIR)
-      # Attempt to discover the NumPy include directory. If this succeeds, then build python API with NumPy
-      execute_process(COMMAND ${PYTHON_EXECUTABLE} -c "import os; os.environ['DISTUTILS_USE_SDK']='1'; import numpy.distutils; print numpy.distutils.misc_util.get_numpy_include_dirs()[0]"
-                      RESULT_VARIABLE PYTHON_NUMPY_PROCESS
-                      OUTPUT_VARIABLE PYTHON_NUMPY_INCLUDE_DIR
-                      OUTPUT_STRIP_TRAILING_WHITESPACE)
+      if(CMAKE_CROSSCOMPILING)
+        message(STATUS "Cannot probe for Python/Numpy support (because we are cross-compiling OpenCV)")
+        message(STATUS "If you want to enable Python/Numpy support, set the following variables:")
+        message(STATUS "  PYTHON_INCLUDE_PATH")
+        message(STATUS "  PYTHON_LIBRARIES")
+        message(STATUS "  PYTHON_NUMPY_INCLUDE_DIR")
+      else()
+        # Attempt to discover the NumPy include directory. If this succeeds, then build python API with NumPy
+        execute_process(COMMAND ${PYTHON_EXECUTABLE} -c "import os; os.environ['DISTUTILS_USE_SDK']='1'; import numpy.distutils; print numpy.distutils.misc_util.get_numpy_include_dirs()[0]"
+                        RESULT_VARIABLE PYTHON_NUMPY_PROCESS
+                        OUTPUT_VARIABLE PYTHON_NUMPY_INCLUDE_DIR
+                        OUTPUT_STRIP_TRAILING_WHITESPACE)
 
-      if(PYTHON_NUMPY_PROCESS EQUAL 0)
-        file(TO_CMAKE_PATH "${PYTHON_NUMPY_INCLUDE_DIR}" _PYTHON_NUMPY_INCLUDE_DIR)
-        set(PYTHON_NUMPY_INCLUDE_DIR ${_PYTHON_NUMPY_INCLUDE_DIR} CACHE PATH "Path to numpy headers")
+        if(NOT PYTHON_NUMPY_PROCESS EQUAL 0)
+          unset(PYTHON_NUMPY_INCLUDE_DIR)
+        endif()
       endif()
     endif()
 
     if(PYTHON_NUMPY_INCLUDE_DIR)
+      file(TO_CMAKE_PATH "${PYTHON_NUMPY_INCLUDE_DIR}" _PYTHON_NUMPY_INCLUDE_DIR)
+      set(PYTHON_NUMPY_INCLUDE_DIR ${_PYTHON_NUMPY_INCLUDE_DIR} CACHE PATH "Path to numpy headers")
       set(PYTHON_USE_NUMPY TRUE)
-      execute_process(COMMAND ${PYTHON_EXECUTABLE} -c "import numpy; print numpy.version.version"
+      if(CMAKE_CROSSCOMPILING)
+        if(NOT PYTHON_NUMPY_VERSION)
+          set(PYTHON_NUMPY_VERSION "undefined - cannot be probed because of the cross-compilation")
+        endif()
+      else()
+        execute_process(COMMAND ${PYTHON_EXECUTABLE} -c "import numpy; print numpy.version.version"
                         RESULT_VARIABLE PYTHON_NUMPY_PROCESS
                         OUTPUT_VARIABLE PYTHON_NUMPY_VERSION
                         OUTPUT_STRIP_TRAILING_WHITESPACE)
+      endif()
     endif()
   endif(NOT ANDROID AND NOT IOS)
 

cmake/OpenCVGenAndroidMK.cmake

@@ -116,5 +116,5 @@ if(ANDROID)
   set(OPENCV_3RDPARTY_LIBS_DIR_CONFIGCMAKE "\$(OPENCV_THIS_DIR)/../3rdparty/libs/\$(OPENCV_TARGET_ARCH_ABI)")
 
   configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/OpenCV.mk.in" "${CMAKE_BINARY_DIR}/unix-install/OpenCV.mk" IMMEDIATE @ONLY)
-  install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCV.mk DESTINATION ${OPENCV_CONFIG_INSTALL_PATH})
+  install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCV.mk DESTINATION ${OPENCV_CONFIG_INSTALL_PATH} COMPONENT dev)
 endif(ANDROID)

cmake/OpenCVGenConfig.cmake

@@ -109,18 +109,18 @@ if(UNIX) # ANDROID configuration is created here also
   #                <prefix>/(share|lib)/<name>*/                           (U)
   #                <prefix>/(share|lib)/<name>*/(cmake|CMake)/             (U)
   if(INSTALL_TO_MANGLED_PATHS)
-    install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig.cmake DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}-${OPENCV_VERSION}/)
-    install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig-version.cmake DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}-${OPENCV_VERSION}/)
-    install(EXPORT OpenCVModules DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}-${OPENCV_VERSION}/ FILE OpenCVModules${modules_file_suffix}.cmake)
+    install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig.cmake DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}-${OPENCV_VERSION}/ COMPONENT dev)
+    install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig-version.cmake DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}-${OPENCV_VERSION}/ COMPONENT dev)
+    install(EXPORT OpenCVModules DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}-${OPENCV_VERSION}/ FILE OpenCVModules${modules_file_suffix}.cmake COMPONENT dev)
   else()
-    install(FILES "${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig.cmake" DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/)
-    install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig-version.cmake DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/)
-    install(EXPORT OpenCVModules DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/ FILE OpenCVModules${modules_file_suffix}.cmake)
+    install(FILES "${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig.cmake" DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/ COMPONENT dev)
+    install(FILES ${CMAKE_BINARY_DIR}/unix-install/OpenCVConfig-version.cmake DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/ COMPONENT dev)
+    install(EXPORT OpenCVModules DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/ FILE OpenCVModules${modules_file_suffix}.cmake COMPONENT dev)
   endif()
 endif()
 
 if(ANDROID)
-  install(FILES "${OpenCV_SOURCE_DIR}/platforms/android/android.toolchain.cmake" DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/)
+  install(FILES "${OpenCV_SOURCE_DIR}/platforms/android/android.toolchain.cmake" DESTINATION ${OPENCV_CONFIG_INSTALL_PATH}/ COMPONENT dev)
 endif()
 
 # --------------------------------------------------------------------------------------------
@@ -134,12 +134,12 @@ if(WIN32)
   configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/OpenCVConfig.cmake.in" "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig.cmake" IMMEDIATE @ONLY)
   configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/OpenCVConfig-version.cmake.in" "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig-version.cmake" IMMEDIATE @ONLY)
   if(BUILD_SHARED_LIBS)
-    install(FILES "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig.cmake" DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}lib")
-    install(EXPORT OpenCVModules DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}lib" FILE OpenCVModules${modules_file_suffix}.cmake)
+    install(FILES "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig.cmake" DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}lib" COMPONENT dev)
+    install(EXPORT OpenCVModules DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}lib" FILE OpenCVModules${modules_file_suffix}.cmake COMPONENT dev)
   else()
-    install(FILES "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig.cmake" DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}staticlib")
-    install(EXPORT OpenCVModules DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}staticlib" FILE OpenCVModules${modules_file_suffix}.cmake)
+    install(FILES "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig.cmake" DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}staticlib" COMPONENT dev)
+    install(EXPORT OpenCVModules DESTINATION "${OpenCV_INSTALL_BINARIES_PREFIX}staticlib" FILE OpenCVModules${modules_file_suffix}.cmake COMPONENT dev)
   endif()
-  install(FILES "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig-version.cmake" DESTINATION "${CMAKE_INSTALL_PREFIX}")
-  install(FILES "${OpenCV_SOURCE_DIR}/cmake/OpenCVConfig.cmake" DESTINATION "${CMAKE_INSTALL_PREFIX}/")
+  install(FILES "${CMAKE_BINARY_DIR}/win-install/OpenCVConfig-version.cmake" DESTINATION "${CMAKE_INSTALL_PREFIX}" COMPONENT dev)
+  install(FILES "${OpenCV_SOURCE_DIR}/cmake/OpenCVConfig.cmake" DESTINATION "${CMAKE_INSTALL_PREFIX}/" COMPONENT dev)
 endif()

cmake/OpenCVGenHeaders.cmake

@@ -23,4 +23,4 @@ set(OPENCV_MODULE_DEFINITIONS_CONFIGMAKE "${OPENCV_MODULE_DEFINITIONS_CONFIGMAKE
 #endforeach()
 
 configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/opencv_modules.hpp.in" "${OPENCV_CONFIG_FILE_INCLUDE_DIR}/opencv2/opencv_modules.hpp")
-install(FILES "${OPENCV_CONFIG_FILE_INCLUDE_DIR}/opencv2/opencv_modules.hpp" DESTINATION ${OPENCV_INCLUDE_INSTALL_PATH}/opencv2 COMPONENT main)
+install(FILES "${OPENCV_CONFIG_FILE_INCLUDE_DIR}/opencv2/opencv_modules.hpp" DESTINATION ${OPENCV_INCLUDE_INSTALL_PATH}/opencv2 COMPONENT dev)

cmake/OpenCVGenPkgconfig.cmake

@@ -81,5 +81,5 @@ configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/opencv-XXX.pc.in"
                @ONLY IMMEDIATE)
 
 if(UNIX AND NOT ANDROID)
-  install(FILES ${CMAKE_BINARY_DIR}/unix-install/${OPENCV_PC_FILE_NAME} DESTINATION ${OPENCV_LIB_INSTALL_PATH}/pkgconfig)
+  install(FILES ${CMAKE_BINARY_DIR}/unix-install/${OPENCV_PC_FILE_NAME} DESTINATION ${OPENCV_LIB_INSTALL_PATH}/pkgconfig COMPONENT dev)
 endif()

cmake/OpenCVModule.cmake

@@ -577,9 +577,9 @@ macro(ocv_create_module)
   endif()
 
   ocv_install_target(${the_module} EXPORT OpenCVModules
-    RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main
-    LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT main
-    ARCHIVE DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT main
+    RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT libs
+    LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT libs
+    ARCHIVE DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT dev
     )
 
   # only "public" headers need to be installed
@@ -587,7 +587,7 @@ macro(ocv_create_module)
     foreach(hdr ${OPENCV_MODULE_${the_module}_HEADERS})
       string(REGEX REPLACE "^.*opencv2/" "opencv2/" hdr2 "${hdr}")
       if(hdr2 MATCHES "^(opencv2/.*)/[^/]+.h(..)?$")
-        install(FILES ${hdr} DESTINATION "${OPENCV_INCLUDE_INSTALL_PATH}/${CMAKE_MATCH_1}" COMPONENT main)
+        install(FILES ${hdr} DESTINATION "${OPENCV_INCLUDE_INSTALL_PATH}/${CMAKE_MATCH_1}" COMPONENT dev)
       endif()
     endforeach()
   endif()
@@ -711,6 +711,9 @@ function(ocv_add_perf_tests)
     else(OCV_DEPENDENCIES_FOUND)
       # TODO: warn about unsatisfied dependencies
     endif(OCV_DEPENDENCIES_FOUND)
+    if(INSTALL_TESTS)
+      install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_TEST_INSTALL_PATH} COMPONENT tests)
+    endif()
   endif()
 endfunction()
 
@@ -764,6 +767,10 @@ function(ocv_add_accuracy_tests)
     else(OCV_DEPENDENCIES_FOUND)
       # TODO: warn about unsatisfied dependencies
     endif(OCV_DEPENDENCIES_FOUND)
+
+    if(INSTALL_TESTS)
+      install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_TEST_INSTALL_PATH} COMPONENT tests)
+    endif()
   endif()
 endfunction()
 
@@ -795,7 +802,7 @@ function(ocv_add_samples)
         endif()
 
         if(WIN32)
-          install(TARGETS ${the_target} RUNTIME DESTINATION "samples/${module_id}" COMPONENT main)
+          install(TARGETS ${the_target} RUNTIME DESTINATION "samples/${module_id}" COMPONENT samples)
         endif()
       endforeach()
     endif()
@@ -804,8 +811,8 @@ function(ocv_add_samples)
   if(INSTALL_C_EXAMPLES AND NOT WIN32 AND EXISTS "${samples_path}")
     file(GLOB sample_files "${samples_path}/*")
     install(FILES ${sample_files}
-            DESTINATION share/OpenCV/samples/${module_id}
-            PERMISSIONS OWNER_READ GROUP_READ WORLD_READ)
+            DESTINATION ${OPENCV_SAMPLES_SRC_INSTALL_PATH}/${module_id}
+            PERMISSIONS OWNER_READ GROUP_READ WORLD_READ COMPONENT samples)
   endif()
 endfunction()
 

cmake/OpenCVPackaging.cmake

@@ -0,0 +1,110 @@
+if(EXISTS "${CMAKE_ROOT}/Modules/CPack.cmake")
+set(CPACK_set_DESTDIR "on")
+
+if(NOT OPENCV_CUSTOM_PACKAGE_INFO)
+  set(CPACK_PACKAGE_DESCRIPTION_SUMMARY "Open Computer Vision Library")
+  set(CPACK_PACKAGE_DESCRIPTION
+"OpenCV (Open Source Computer Vision Library) is an open source computer vision
+and machine learning software library. OpenCV was built to provide a common
+infrastructure for computer vision applications and to accelerate the use of
+machine perception in the commercial products. Being a BSD-licensed product,
+OpenCV makes it easy for businesses to utilize and modify the code.")
+  set(CPACK_PACKAGE_VENDOR "OpenCV Foundation")
+  set(CPACK_RESOURCE_FILE_LICENSE "${CMAKE_CURRENT_SOURCE_DIR}/LICENSE")
+  set(CPACK_PACKAGE_CONTACT "admin@opencv.org")
+  set(CPACK_PACKAGE_VERSION_MAJOR "${OPENCV_VERSION_MAJOR}")
+  set(CPACK_PACKAGE_VERSION_MINOR "${OPENCV_VERSION_MINOR}")
+  set(CPACK_PACKAGE_VERSION_PATCH "${OPENCV_VERSION_PATCH}")
+  set(CPACK_PACKAGE_VERSION "${OPENCV_VCSVERSION}")
+endif(NOT OPENCV_CUSTOM_PACKAGE_INFO)
+
+#arch
+if(X86)
+  set(CPACK_DEBIAN_ARCHITECTURE "i386")
+  set(CPACK_RPM_PACKAGE_ARCHITECTURE "i686")
+elseif(X86_64)
+  set(CPACK_DEBIAN_ARCHITECTURE "amd64")
+  set(CPACK_RPM_PACKAGE_ARCHITECTURE "x86_64")
+elseif(ARM)
+  set(CPACK_DEBIAN_ARCHITECTURE "armhf")
+  set(CPACK_RPM_PACKAGE_ARCHITECTURE "armhf")
+else()
+  set(CPACK_DEBIAN_ARCHITECTURE ${CMAKE_SYSTEM_PROCESSOR})
+  set(CPACK_RPM_PACKAGE_ARCHITECTURE ${CMAKE_SYSTEM_PROCESSOR})
+endif()
+
+if(CPACK_GENERATOR STREQUAL "DEB")
+  set(OPENCV_PACKAGE_ARCH_SUFFIX ${CPACK_DEBIAN_ARCHITECTURE})
+elseif(CPACK_GENERATOR STREQUAL "RPM")
+  set(OPENCV_PACKAGE_ARCH_SUFFIX ${CPACK_RPM_PACKAGE_ARCHITECTURE})
+else()
+  set(OPENCV_PACKAGE_ARCH_SUFFIX ${CMAKE_SYSTEM_PROCESSOR})
+endif()
+
+set(CPACK_PACKAGE_FILE_NAME "${CMAKE_PROJECT_NAME}-${OPENCV_VCSVERSION}-${OPENCV_PACKAGE_ARCH_SUFFIX}")
+set(CPACK_SOURCE_PACKAGE_FILE_NAME "${CMAKE_PROJECT_NAME}-${OPENCV_VCSVERSION}-${OPENCV_PACKAGE_ARCH_SUFFIX}")
+
+#rpm options
+set(CPACK_RPM_COMPONENT_INSTALL TRUE)
+set(CPACK_RPM_PACKAGE_SUMMARY ${CPACK_PACKAGE_DESCRIPTION_SUMMARY})
+set(CPACK_RPM_PACKAGE_DESCRIPTION ${CPACK_PACKAGE_DESCRIPTION})
+set(CPACK_RPM_PACKAGE_URL "http://opencv.org")
+set(CPACK_RPM_PACKAGE_LICENSE "BSD")
+
+#deb options
+set(CPACK_DEB_COMPONENT_INSTALL TRUE)
+set(CPACK_DEBIAN_PACKAGE_PRIORITY "optional")
+set(CPACK_DEBIAN_PACKAGE_SECTION "libs")
+set(CPACK_DEBIAN_PACKAGE_HOMEPAGE "http://opencv.org")
+
+#depencencies
+set(CPACK_DEBIAN_PACKAGE_SHLIBDEPS TRUE)
+set(CPACK_COMPONENT_samples_DEPENDS libs)
+set(CPACK_COMPONENT_dev_DEPENDS libs)
+set(CPACK_COMPONENT_docs_DEPENDS libs)
+set(CPACK_COMPONENT_java_DEPENDS libs)
+set(CPACK_COMPONENT_python_DEPENDS libs)
+set(CPACK_COMPONENT_tests_DEPENDS libs)
+
+if(HAVE_CUDA)
+  string(REPLACE "." "-" cuda_version_suffix ${CUDA_VERSION})
+  set(CPACK_DEB_libs_PACKAGE_DEPENDS "cuda-core-libs-${cuda_version_suffix}, cuda-extra-libs-${cuda_version_suffix}")
+  set(CPACK_COMPONENT_dev_DEPENDS libs)
+  set(CPACK_DEB_dev_PACKAGE_DEPENDS "cuda-headers-${cuda_version_suffix}")
+endif()
+
+if(NOT OPENCV_CUSTOM_PACKAGE_INFO)
+  set(CPACK_COMPONENT_libs_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}")
+  set(CPACK_COMPONENT_libs_DESCRIPTION "Open Computer Vision Library")
+
+  set(CPACK_COMPONENT_python_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}-python")
+  set(CPACK_COMPONENT_python_DESCRIPTION "Python bindings for Open Source Computer Vision Library")
+
+  set(CPACK_COMPONENT_java_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}-java")
+  set(CPACK_COMPONENT_java_DESCRIPTION "Java bindings for Open Source Computer Vision Library")
+
+  set(CPACK_COMPONENT_dev_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}-dev")
+  set(CPACK_COMPONENT_dev_DESCRIPTION "Development files for Open Source Computer Vision Library")
+
+  set(CPACK_COMPONENT_docs_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}-docs")
+  set(CPACK_COMPONENT_docs_DESCRIPTION "Documentation for Open Source Computer Vision Library")
+
+  set(CPACK_COMPONENT_samples_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}-samples")
+  set(CPACK_COMPONENT_samples_DESCRIPTION "Samples for Open Source Computer Vision Library")
+
+  set(CPACK_COMPONENT_tests_DISPLAY_NAME "lib${CMAKE_PROJECT_NAME}-tests")
+  set(CPACK_COMPONENT_tests_DESCRIPTION "Accuracy and performance tests for Open Source Computer Vision Library")
+endif(NOT OPENCV_CUSTOM_PACKAGE_INFO)
+
+if(NOT OPENCV_CUSTOM_PACKAGE_LAYOUT)
+  set(CPACK_libs_COMPONENT_INSTALL TRUE)
+  set(CPACK_dev_COMPONENT_INSTALL TRUE)
+  set(CPACK_docs_COMPONENT_INSTALL TRUE)
+  set(CPACK_python_COMPONENT_INSTALL TRUE)
+  set(CPACK_java_COMPONENT_INSTALL TRUE)
+  set(CPACK_samples_COMPONENT_INSTALL TRUE)
+endif(NOT OPENCV_CUSTOM_PACKAGE_LAYOUT)
+
+include(CPack)
+
+ENDif(EXISTS "${CMAKE_ROOT}/Modules/CPack.cmake")

cmake/templates/opencv_run_all_tests.sh.in

@@ -0,0 +1,24 @@
+#!/bin/sh
+
+OPENCV_TEST_PATH=@OPENCV_TEST_INSTALL_PATH@
+export OPENCV_TEST_DATA_PATH=@CMAKE_INSTALL_PREFIX@/share/OpenCV/testdata
+
+SUMMARY_STATUS=0
+for t in "$OPENCV_TEST_PATH/"opencv_test_* "$OPENCV_TEST_PATH/"opencv_perf_*;
+do
+  "$t" --perf_min_samples=1 --perf_force_samples=1 --gtest_output=xml:$t-`date --rfc-3339=date`.xml
+  TEST_STATUS=$?
+  if [ $TEST_STATUS -ne 0 ]; then
+    SUMMARY_STATUS=$TEST_STATUS
+  fi
+done
+
+rm -f /tmp/__opencv_temp.*
+
+if [ $SUMMARY_STATUS -eq 0 ]; then
+  echo "All OpenCV tests finished successfully"
+else
+  echo "OpenCV tests finished with status $SUMMARY_STATUS"
+fi
+
+return $SUMMARY_STATUS

cmake/templates/opencv_testing.sh.in

@@ -0,0 +1,2 @@
+# Environment setup for OpenCV testing
+export OPENCV_TEST_DATA_PATH=@CMAKE_INSTALL_PREFIX@/share/OpenCV/testdata

data/CMakeLists.txt

@@ -2,9 +2,17 @@ file(GLOB HAAR_CASCADES haarcascades/*.xml)
 file(GLOB LBP_CASCADES lbpcascades/*.xml)
 
 if(ANDROID)
-  install(FILES ${HAAR_CASCADES} DESTINATION sdk/etc/haarcascades COMPONENT main)
-  install(FILES ${LBP_CASCADES}  DESTINATION sdk/etc/lbpcascades  COMPONENT main)
+  install(FILES ${HAAR_CASCADES} DESTINATION sdk/etc/haarcascades COMPONENT libs)
+  install(FILES ${LBP_CASCADES}  DESTINATION sdk/etc/lbpcascades  COMPONENT libs)
 elseif(NOT WIN32)
-  install(FILES ${HAAR_CASCADES} DESTINATION share/OpenCV/haarcascades COMPONENT main)
-  install(FILES ${LBP_CASCADES}  DESTINATION share/OpenCV/lbpcascades  COMPONENT main)
+  install(FILES ${HAAR_CASCADES} DESTINATION share/OpenCV/haarcascades COMPONENT libs)
+  install(FILES ${LBP_CASCADES}  DESTINATION share/OpenCV/lbpcascades  COMPONENT libs)
 endif()
+
+if(INSTALL_TESTS AND OPENCV_TEST_DATA_PATH)
+  if(ANDROID)
+    install(DIRECTORY ${OPENCV_TEST_DATA_PATH} DESTINATION sdk/etc/testdata COMPONENT tests)
+  elseif(NOT WIN32)
+    install(DIRECTORY ${OPENCV_TEST_DATA_PATH} DESTINATION share/OpenCV/testdata COMPONENT tests)
+  endif()
+endif()

doc/CMakeLists.txt

@@ -143,11 +143,11 @@ if(BUILD_DOCS AND HAVE_SPHINX)
   endif()
 
   foreach(f ${DOC_LIST})
-    install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" COMPONENT main)
+    install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" COMPONENT docs)
   endforeach()
 
   foreach(f ${OPTIONAL_DOC_LIST})
-    install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" OPTIONAL)
+    install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" OPTIONAL COMPONENT docs)
   endforeach()
 
 endif()

doc/tutorials/introduction/android_binary_package/O4A_SDK.rst

@@ -66,7 +66,7 @@ The structure of package contents looks as follows:
     |               |_ armeabi-v7a
     |               |_ x86
     |
-    |_ license.txt
+    |_ LICENSE
     |_ README.android
 
 * :file:`sdk` folder contains OpenCV API and libraries for Android:

doc/tutorials/introduction/linux_install/linux_install.rst

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

include/CMakeLists.txt

@@ -1,7 +1,7 @@
 file(GLOB old_hdrs "opencv/*.h*")
 install(FILES ${old_hdrs}
     DESTINATION ${OPENCV_INCLUDE_INSTALL_PATH}/opencv
-    COMPONENT main)
+    COMPONENT dev)
 install(FILES "opencv2/opencv.hpp"
     DESTINATION ${OPENCV_INCLUDE_INSTALL_PATH}/opencv2
-    COMPONENT main)
+    COMPONENT dev)

modules/androidcamera/CMakeLists.txt

@@ -40,6 +40,6 @@ else()
     get_filename_component(wrapper_name "${wrapper}" NAME)
     install(FILES "${LIBRARY_OUTPUT_PATH}/${wrapper_name}"
             DESTINATION ${OPENCV_LIB_INSTALL_PATH}
-            COMPONENT main)
+            COMPONENT libs)
   endforeach()
 endif()

modules/androidcamera/camera_wrapper/CMakeLists.txt

@@ -63,4 +63,4 @@ if (NOT (CMAKE_BUILD_TYPE MATCHES "debug"))
 endif()
 
 
-install(TARGETS ${the_target} LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT main)
+install(TARGETS ${the_target} LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT libs)

modules/calib3d/test/test_chessboardgenerator.hpp

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

modules/contrib/src/adaptiveskindetector.cpp

@@ -53,7 +53,7 @@ void CvAdaptiveSkinDetector::initData(IplImage *src, int widthDivider, int heigh
     imgGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
     imgLastGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
     imgHSVFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 3);
-};
+}
 
 CvAdaptiveSkinDetector::CvAdaptiveSkinDetector(int samplingDivider, int morphingMethod)
 {
@@ -78,7 +78,7 @@ CvAdaptiveSkinDetector::CvAdaptiveSkinDetector(int samplingDivider, int morphing
     imgLastGrayFrame = NULL;
     imgSaturationFrame = NULL;
     imgHSVFrame = NULL;
-};
+}
 
 CvAdaptiveSkinDetector::~CvAdaptiveSkinDetector()
 {
@@ -91,7 +91,7 @@ CvAdaptiveSkinDetector::~CvAdaptiveSkinDetector()
     cvReleaseImage(&imgGrayFrame);
     cvReleaseImage(&imgLastGrayFrame);
     cvReleaseImage(&imgHSVFrame);
-};
+}
 
 void CvAdaptiveSkinDetector::process(IplImage *inputBGRImage, IplImage *outputHueMask)
 {
@@ -188,7 +188,7 @@ void CvAdaptiveSkinDetector::process(IplImage *inputBGRImage, IplImage *outputHu
 
     if (outputHueMask != NULL)
         cvCopy(imgFilteredFrame, outputHueMask);
-};
+}
 
 
 //------------------------- Histogram for Adaptive Skin Detector -------------------------//
@@ -200,12 +200,12 @@ CvAdaptiveSkinDetector::Histogram::Histogram()
     float *ranges[] = { range };
     fHistogram = cvCreateHist(1, histogramSize, CV_HIST_ARRAY, ranges, 1);
     cvClearHist(fHistogram);
-};
+}
 
 CvAdaptiveSkinDetector::Histogram::~Histogram()
 {
     cvReleaseHist(&fHistogram);
-};
+}
 
 int CvAdaptiveSkinDetector::Histogram::findCoverageIndex(double surfaceToCover, int defaultValue)
 {
@@ -219,7 +219,7 @@ int CvAdaptiveSkinDetector::Histogram::findCoverageIndex(double surfaceToCover,
         }
     }
     return defaultValue;
-};
+}
 
 void CvAdaptiveSkinDetector::Histogram::findCurveThresholds(int &x1, int &x2, double percent)
 {
@@ -242,7 +242,7 @@ void CvAdaptiveSkinDetector::Histogram::findCurveThresholds(int &x1, int &x2, do
         x2 = GSD_HUE_UT;
     else
         x2 += GSD_HUE_LT;
-};
+}
 
 void CvAdaptiveSkinDetector::Histogram::mergeWith(CvAdaptiveSkinDetector::Histogram *source, double weight)
 {
@@ -283,4 +283,4 @@ void CvAdaptiveSkinDetector::Histogram::mergeWith(CvAdaptiveSkinDetector::Histog
             }
         }
     }
-};
+}

modules/contrib/src/ba.cpp

@@ -938,7 +938,7 @@ static void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, C
 
 #endif
 
-};
+}
 static void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* estim, void* /*data*/) {
   //just do projections
   CvMat _Mi;
@@ -977,17 +977,17 @@ static void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, C
   cvTranspose( _mp2, estim );
   cvReleaseMat( &_mp );
   cvReleaseMat( &_mp2 );
-};
+}
 
 static void fjac_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data) {
   CvMat _point_params = point_params, _cam_params = cam_params, _Al = A, _Bl = B;
   fjac(i,j, &_point_params, &_cam_params, &_Al, &_Bl, data);
-};
+}
 
 static void func_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data)  {
   CvMat _point_params = point_params, _cam_params = cam_params, _estim = estim;
   func(i,j,&_point_params,&_cam_params,&_estim,data);
-};
+}
 
 void LevMarqSparse::bundleAdjust( vector<Point3d>& points, //positions of points in global coordinate system (input and output)
           const vector<vector<Point2d> >& imagePoints, //projections of 3d points for every camera

modules/contrib/src/facerec.cpp

@@ -873,7 +873,7 @@ CV_INIT_ALGORITHM(Eigenfaces, "FaceRecognizer.Eigenfaces",
                   obj.info()->addParam(obj, "labels", obj._labels, true);
                   obj.info()->addParam(obj, "eigenvectors", obj._eigenvectors, true);
                   obj.info()->addParam(obj, "eigenvalues", obj._eigenvalues, true);
-                  obj.info()->addParam(obj, "mean", obj._mean, true));
+                  obj.info()->addParam(obj, "mean", obj._mean, true))
 
 CV_INIT_ALGORITHM(Fisherfaces, "FaceRecognizer.Fisherfaces",
                   obj.info()->addParam(obj, "ncomponents", obj._num_components);
@@ -882,7 +882,7 @@ CV_INIT_ALGORITHM(Fisherfaces, "FaceRecognizer.Fisherfaces",
                   obj.info()->addParam(obj, "labels", obj._labels, true);
                   obj.info()->addParam(obj, "eigenvectors", obj._eigenvectors, true);
                   obj.info()->addParam(obj, "eigenvalues", obj._eigenvalues, true);
-                  obj.info()->addParam(obj, "mean", obj._mean, true));
+                  obj.info()->addParam(obj, "mean", obj._mean, true))
 
 CV_INIT_ALGORITHM(LBPH, "FaceRecognizer.LBPH",
                   obj.info()->addParam(obj, "radius", obj._radius);
@@ -891,7 +891,7 @@ CV_INIT_ALGORITHM(LBPH, "FaceRecognizer.LBPH",
                   obj.info()->addParam(obj, "grid_y", obj._grid_y);
                   obj.info()->addParam(obj, "threshold", obj._threshold);
                   obj.info()->addParam(obj, "histograms", obj._histograms, true);
-                  obj.info()->addParam(obj, "labels", obj._labels, true));
+                  obj.info()->addParam(obj, "labels", obj._labels, true))
 
 bool initModule_contrib()
 {

modules/contrib/src/fuzzymeanshifttracker.cpp

@@ -40,7 +40,7 @@ CvFuzzyPoint::CvFuzzyPoint(double _x, double _y)
 {
     x = _x;
     y = _y;
-};
+}
 
 bool CvFuzzyCurve::between(double x, double x1, double x2)
 {
@@ -50,37 +50,37 @@ bool CvFuzzyCurve::between(double x, double x1, double x2)
         return true;
 
     return false;
-};
+}
 
 CvFuzzyCurve::CvFuzzyCurve()
 {
     value = 0;
-};
+}
 
 CvFuzzyCurve::~CvFuzzyCurve()
 {
     // nothing to do
-};
+}
 
 void CvFuzzyCurve::setCentre(double _centre)
 {
     centre = _centre;
-};
+}
 
 double CvFuzzyCurve::getCentre()
 {
     return centre;
-};
+}
 
 void CvFuzzyCurve::clear()
 {
     points.clear();
-};
+}
 
 void CvFuzzyCurve::addPoint(double x, double y)
 {
     points.push_back(CvFuzzyPoint(x, y));
-};
+}
 
 double CvFuzzyCurve::calcValue(double param)
 {
@@ -101,41 +101,41 @@ double CvFuzzyCurve::calcValue(double param)
         }
     }
     return 0;
-};
+}
 
 double CvFuzzyCurve::getValue()
 {
     return value;
-};
+}
 
 void CvFuzzyCurve::setValue(double _value)
 {
     value = _value;
-};
+}
 
 
 CvFuzzyFunction::CvFuzzyFunction()
 {
     // nothing to do
-};
+}
 
 CvFuzzyFunction::~CvFuzzyFunction()
 {
     curves.clear();
-};
+}
 
 void CvFuzzyFunction::addCurve(CvFuzzyCurve *curve, double value)
 {
     curves.push_back(*curve);
     curve->setValue(value);
-};
+}
 
 void CvFuzzyFunction::resetValues()
 {
     int numCurves = (int)curves.size();
     for (int i = 0; i < numCurves; i++)
         curves[i].setValue(0);
-};
+}
 
 double CvFuzzyFunction::calcValue()
 {
@@ -152,7 +152,7 @@ double CvFuzzyFunction::calcValue()
         return s1/s2;
     else
         return 0;
-};
+}
 
 CvFuzzyCurve *CvFuzzyFunction::newCurve()
 {
@@ -160,14 +160,14 @@ CvFuzzyCurve *CvFuzzyFunction::newCurve()
     c = new CvFuzzyCurve();
     addCurve(c);
     return c;
-};
+}
 
 CvFuzzyRule::CvFuzzyRule()
 {
     fuzzyInput1 = NULL;
     fuzzyInput2 = NULL;
     fuzzyOutput = NULL;
-};
+}
 
 CvFuzzyRule::~CvFuzzyRule()
 {
@@ -179,14 +179,14 @@ CvFuzzyRule::~CvFuzzyRule()
 
     if (fuzzyOutput != NULL)
         delete fuzzyOutput;
-};
+}
 
 void CvFuzzyRule::setRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1)
 {
     fuzzyInput1 = c1;
     fuzzyInput2 = c2;
     fuzzyOutput = o1;
-};
+}
 
 double CvFuzzyRule::calcValue(double param1, double param2)
 {
@@ -202,31 +202,31 @@ double CvFuzzyRule::calcValue(double param1, double param2)
     }
     else
         return v1;
-};
+}
 
 CvFuzzyCurve *CvFuzzyRule::getOutputCurve()
 {
     return fuzzyOutput;
-};
+}
 
 CvFuzzyController::CvFuzzyController()
 {
     // nothing to do
-};
+}
 
 CvFuzzyController::~CvFuzzyController()
 {
     int size = (int)rules.size();
     for(int i = 0; i < size; i++)
         delete rules[i];
-};
+}
 
 void CvFuzzyController::addRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1)
 {
     CvFuzzyRule *f = new CvFuzzyRule();
     rules.push_back(f);
     f->setRule(c1, c2, o1);
-};
+}
 
 double CvFuzzyController::calcOutput(double param1, double param2)
 {
@@ -242,7 +242,7 @@ double CvFuzzyController::calcOutput(double param1, double param2)
     }
     v = list.calcValue();
     return v;
-};
+}
 
 CvFuzzyMeanShiftTracker::FuzzyResizer::FuzzyResizer()
 {
@@ -298,12 +298,12 @@ CvFuzzyMeanShiftTracker::FuzzyResizer::FuzzyResizer()
     fuzzyController.addRule(i1L, NULL, oS);
     fuzzyController.addRule(i1M, NULL, oZE);
     fuzzyController.addRule(i1H, NULL, oE);
-};
+}
 
 int CvFuzzyMeanShiftTracker::FuzzyResizer::calcOutput(double edgeDensity, double density)
 {
     return (int)fuzzyController.calcOutput(edgeDensity, density);
-};
+}
 
 CvFuzzyMeanShiftTracker::SearchWindow::SearchWindow()
 {
@@ -328,7 +328,7 @@ CvFuzzyMeanShiftTracker::SearchWindow::SearchWindow()
     depthLow = 0;
     depthHigh = 0;
     fuzzyResizer = NULL;
-};
+}
 
 CvFuzzyMeanShiftTracker::SearchWindow::~SearchWindow()
 {
@@ -354,7 +354,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::setSize(int _x, int _y, int _width,
 
     if (y + height > maxHeight)
         height = maxHeight - y;
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::initDepthValues(IplImage *maskImage, IplImage *depthMap)
 {
@@ -408,7 +408,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::initDepthValues(IplImage *maskImage,
         depthHigh = 32000;
         depthLow = 0;
     }
-};
+}
 
 bool CvFuzzyMeanShiftTracker::SearchWindow::shift()
 {
@@ -421,7 +421,7 @@ bool CvFuzzyMeanShiftTracker::SearchWindow::shift()
     {
         return false;
     }
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::extractInfo(IplImage *maskImage, IplImage *depthMap, bool initDepth)
 {
@@ -527,7 +527,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::extractInfo(IplImage *maskImage, Ipl
         ellipseAngle = 0;
         density = 0;
     }
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityLinear(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh) {
     int x1 = horizontalEdgeTop;
@@ -571,7 +571,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityLinear(in
     } else {
         resizeDw = - resizeDx;
     }
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsInnerDensity(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh)
 {
@@ -587,7 +587,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsInnerDensity(int &re
     resizeDy = (int)(py*dy);
     resizeDw = (int)((1-px)*dx);
     resizeDh = (int)((1-py)*dy);
-};
+}
 
 void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityFuzzy(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh)
 {
@@ -626,7 +626,7 @@ void CvFuzzyMeanShiftTracker::SearchWindow::getResizeAttribsEdgeDensityFuzzy(int
         resizeDy = int(-dy1);
         resizeDh = int(dy1+dy2);
     }
-};
+}
 
 bool CvFuzzyMeanShiftTracker::SearchWindow::meanShift(IplImage *maskImage, IplImage *depthMap, int maxIteration, bool initDepth)
 {
@@ -639,7 +639,7 @@ bool CvFuzzyMeanShiftTracker::SearchWindow::meanShift(IplImage *maskImage, IplIm
     } while (++numShifts < maxIteration);
 
     return false;
-};
+}
 
 void CvFuzzyMeanShiftTracker::findOptimumSearchWindow(SearchWindow &searchWindow, IplImage *maskImage, IplImage *depthMap, int maxIteration, int resizeMethod, bool initDepth)
 {
@@ -679,17 +679,17 @@ void CvFuzzyMeanShiftTracker::findOptimumSearchWindow(SearchWindow &searchWindow
 
         searchWindow.setSize(searchWindow.x + resizeDx, searchWindow.y + resizeDy, searchWindow.width + resizeDw, searchWindow.height + resizeDh);
     }
-};
+}
 
 CvFuzzyMeanShiftTracker::CvFuzzyMeanShiftTracker()
 {
     searchMode = tsSetWindow;
-};
+}
 
 CvFuzzyMeanShiftTracker::~CvFuzzyMeanShiftTracker()
 {
     // nothing to do
-};
+}
 
 void CvFuzzyMeanShiftTracker::track(IplImage *maskImage, IplImage *depthMap, int resizeMethod, bool resetSearch, int minKernelMass)
 {
@@ -717,4 +717,4 @@ void CvFuzzyMeanShiftTracker::track(IplImage *maskImage, IplImage *depthMap, int
             else
                 searchMode = tsTracking;
     }
-};
+}

modules/contrib/src/retina.cpp

@@ -85,7 +85,7 @@ Retina::Retina(const cv::Size inputSz, const bool colorMode, RETINA_COLORSAMPLIN
 {
     _retinaFilter = 0;
     _init(inputSz, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
-};
+}
 
 Retina::~Retina()
 {

modules/contrib/src/spinimages.cpp

@@ -718,7 +718,7 @@ void cv::SpinImageModel::defaultParams()
 
     T_GeometriccConsistency = 0.25f;
     T_GroupingCorespondances = 0.25f;
-};
+}
 
 Mat cv::SpinImageModel::packRandomScaledSpins(bool separateScale, size_t xCount, size_t yCount) const
 {

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

@@ -2401,7 +2401,7 @@ template<typename _Tp> inline SparseMat_<_Tp>::SparseMat_(const SparseMat& m)
     if( m.type() == DataType<_Tp>::type )
         *this = (const SparseMat_<_Tp>&)m;
     else
-        m.convertTo(this, DataType<_Tp>::type);
+        m.convertTo(*this, DataType<_Tp>::type);
 }
 
 template<typename _Tp> inline SparseMat_<_Tp>::SparseMat_(const SparseMat_<_Tp>& m)

modules/core/src/algorithm.cpp

@@ -647,7 +647,7 @@ void AlgorithmInfo::set(Algorithm* algo, const char* parameter, int argType, con
             || argType == Param::FLOAT || argType == Param::UNSIGNED_INT || argType == Param::UINT64 || argType == Param::UCHAR)
     {
         if ( !( p->type == Param::INT || p->type == Param::REAL || p->type == Param::BOOLEAN
-                || p->type == Param::UNSIGNED_INT || p->type == Param::UINT64 || p->type == Param::FLOAT || argType == Param::UCHAR
+                || p->type == Param::UNSIGNED_INT || p->type == Param::UINT64 || p->type == Param::FLOAT || p->type == Param::UCHAR
                 || (p->type == Param::SHORT && argType == Param::INT)) )
         {
             string message = getErrorMessageForWrongArgumentInSetter(algo->name(), parameter, p->type, argType);

modules/core/src/arithm.cpp

@@ -1272,8 +1272,8 @@ static void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
     bool haveScalar = false, swapped12 = false;
     int depth2 = src2.depth();
     if( src1.size != src2.size || src1.channels() != src2.channels() ||
-        ((kind1 == _InputArray::MATX || kind2 == _InputArray::MATX) &&
-         src1.cols == 1 && src2.rows == 4) )
+        (kind1 == _InputArray::MATX && (src1.size() == Size(1,4) || src1.size() == Size(1,1))) ||
+        (kind2 == _InputArray::MATX && (src2.size() == Size(1,4) || src2.size() == Size(1,1))) )
     {
         if( checkScalar(src1, src2.type(), kind1, kind2) )
         {

modules/core/src/convert.cpp

@@ -839,122 +839,122 @@ stype* dst, size_t dstep, Size size, double*) \
 }
 
 
-DEF_CVT_SCALE_ABS_FUNC(8u, cvtScaleAbs_, uchar, uchar, float);
-DEF_CVT_SCALE_ABS_FUNC(8s8u, cvtScaleAbs_, schar, uchar, float);
-DEF_CVT_SCALE_ABS_FUNC(16u8u, cvtScaleAbs_, ushort, uchar, float);
-DEF_CVT_SCALE_ABS_FUNC(16s8u, cvtScaleAbs_, short, uchar, float);
-DEF_CVT_SCALE_ABS_FUNC(32s8u, cvtScaleAbs_, int, uchar, float);
-DEF_CVT_SCALE_ABS_FUNC(32f8u, cvtScaleAbs_, float, uchar, float);
-DEF_CVT_SCALE_ABS_FUNC(64f8u, cvtScaleAbs_, double, uchar, float);
+DEF_CVT_SCALE_ABS_FUNC(8u, cvtScaleAbs_, uchar, uchar, float)
+DEF_CVT_SCALE_ABS_FUNC(8s8u, cvtScaleAbs_, schar, uchar, float)
+DEF_CVT_SCALE_ABS_FUNC(16u8u, cvtScaleAbs_, ushort, uchar, float)
+DEF_CVT_SCALE_ABS_FUNC(16s8u, cvtScaleAbs_, short, uchar, float)
+DEF_CVT_SCALE_ABS_FUNC(32s8u, cvtScaleAbs_, int, uchar, float)
+DEF_CVT_SCALE_ABS_FUNC(32f8u, cvtScaleAbs_, float, uchar, float)
+DEF_CVT_SCALE_ABS_FUNC(64f8u, cvtScaleAbs_, double, uchar, float)
 
-DEF_CVT_SCALE_FUNC(8u,     uchar, uchar, float);
-DEF_CVT_SCALE_FUNC(8s8u,   schar, uchar, float);
-DEF_CVT_SCALE_FUNC(16u8u,  ushort, uchar, float);
-DEF_CVT_SCALE_FUNC(16s8u,  short, uchar, float);
-DEF_CVT_SCALE_FUNC(32s8u,  int, uchar, float);
-DEF_CVT_SCALE_FUNC(32f8u,  float, uchar, float);
-DEF_CVT_SCALE_FUNC(64f8u,  double, uchar, float);
+DEF_CVT_SCALE_FUNC(8u,     uchar, uchar, float)
+DEF_CVT_SCALE_FUNC(8s8u,   schar, uchar, float)
+DEF_CVT_SCALE_FUNC(16u8u,  ushort, uchar, float)
+DEF_CVT_SCALE_FUNC(16s8u,  short, uchar, float)
+DEF_CVT_SCALE_FUNC(32s8u,  int, uchar, float)
+DEF_CVT_SCALE_FUNC(32f8u,  float, uchar, float)
+DEF_CVT_SCALE_FUNC(64f8u,  double, uchar, float)
 
-DEF_CVT_SCALE_FUNC(8u8s,   uchar, schar, float);
-DEF_CVT_SCALE_FUNC(8s,     schar, schar, float);
-DEF_CVT_SCALE_FUNC(16u8s,  ushort, schar, float);
-DEF_CVT_SCALE_FUNC(16s8s,  short, schar, float);
-DEF_CVT_SCALE_FUNC(32s8s,  int, schar, float);
-DEF_CVT_SCALE_FUNC(32f8s,  float, schar, float);
-DEF_CVT_SCALE_FUNC(64f8s,  double, schar, float);
+DEF_CVT_SCALE_FUNC(8u8s,   uchar, schar, float)
+DEF_CVT_SCALE_FUNC(8s,     schar, schar, float)
+DEF_CVT_SCALE_FUNC(16u8s,  ushort, schar, float)
+DEF_CVT_SCALE_FUNC(16s8s,  short, schar, float)
+DEF_CVT_SCALE_FUNC(32s8s,  int, schar, float)
+DEF_CVT_SCALE_FUNC(32f8s,  float, schar, float)
+DEF_CVT_SCALE_FUNC(64f8s,  double, schar, float)
 
-DEF_CVT_SCALE_FUNC(8u16u,  uchar, ushort, float);
-DEF_CVT_SCALE_FUNC(8s16u,  schar, ushort, float);
-DEF_CVT_SCALE_FUNC(16u,    ushort, ushort, float);
-DEF_CVT_SCALE_FUNC(16s16u, short, ushort, float);
-DEF_CVT_SCALE_FUNC(32s16u, int, ushort, float);
-DEF_CVT_SCALE_FUNC(32f16u, float, ushort, float);
-DEF_CVT_SCALE_FUNC(64f16u, double, ushort, float);
+DEF_CVT_SCALE_FUNC(8u16u,  uchar, ushort, float)
+DEF_CVT_SCALE_FUNC(8s16u,  schar, ushort, float)
+DEF_CVT_SCALE_FUNC(16u,    ushort, ushort, float)
+DEF_CVT_SCALE_FUNC(16s16u, short, ushort, float)
+DEF_CVT_SCALE_FUNC(32s16u, int, ushort, float)
+DEF_CVT_SCALE_FUNC(32f16u, float, ushort, float)
+DEF_CVT_SCALE_FUNC(64f16u, double, ushort, float)
 
-DEF_CVT_SCALE_FUNC(8u16s,  uchar, short, float);
-DEF_CVT_SCALE_FUNC(8s16s,  schar, short, float);
-DEF_CVT_SCALE_FUNC(16u16s, ushort, short, float);
-DEF_CVT_SCALE_FUNC(16s,    short, short, float);
-DEF_CVT_SCALE_FUNC(32s16s, int, short, float);
-DEF_CVT_SCALE_FUNC(32f16s, float, short, float);
-DEF_CVT_SCALE_FUNC(64f16s, double, short, float);
+DEF_CVT_SCALE_FUNC(8u16s,  uchar, short, float)
+DEF_CVT_SCALE_FUNC(8s16s,  schar, short, float)
+DEF_CVT_SCALE_FUNC(16u16s, ushort, short, float)
+DEF_CVT_SCALE_FUNC(16s,    short, short, float)
+DEF_CVT_SCALE_FUNC(32s16s, int, short, float)
+DEF_CVT_SCALE_FUNC(32f16s, float, short, float)
+DEF_CVT_SCALE_FUNC(64f16s, double, short, float)
 
-DEF_CVT_SCALE_FUNC(8u32s,  uchar, int, float);
-DEF_CVT_SCALE_FUNC(8s32s,  schar, int, float);
-DEF_CVT_SCALE_FUNC(16u32s, ushort, int, float);
-DEF_CVT_SCALE_FUNC(16s32s, short, int, float);
-DEF_CVT_SCALE_FUNC(32s,    int, int, double);
-DEF_CVT_SCALE_FUNC(32f32s, float, int, float);
-DEF_CVT_SCALE_FUNC(64f32s, double, int, double);
+DEF_CVT_SCALE_FUNC(8u32s,  uchar, int, float)
+DEF_CVT_SCALE_FUNC(8s32s,  schar, int, float)
+DEF_CVT_SCALE_FUNC(16u32s, ushort, int, float)
+DEF_CVT_SCALE_FUNC(16s32s, short, int, float)
+DEF_CVT_SCALE_FUNC(32s,    int, int, double)
+DEF_CVT_SCALE_FUNC(32f32s, float, int, float)
+DEF_CVT_SCALE_FUNC(64f32s, double, int, double)
 
-DEF_CVT_SCALE_FUNC(8u32f,  uchar, float, float);
-DEF_CVT_SCALE_FUNC(8s32f,  schar, float, float);
-DEF_CVT_SCALE_FUNC(16u32f, ushort, float, float);
-DEF_CVT_SCALE_FUNC(16s32f, short, float, float);
-DEF_CVT_SCALE_FUNC(32s32f, int, float, double);
-DEF_CVT_SCALE_FUNC(32f,    float, float, float);
-DEF_CVT_SCALE_FUNC(64f32f, double, float, double);
+DEF_CVT_SCALE_FUNC(8u32f,  uchar, float, float)
+DEF_CVT_SCALE_FUNC(8s32f,  schar, float, float)
+DEF_CVT_SCALE_FUNC(16u32f, ushort, float, float)
+DEF_CVT_SCALE_FUNC(16s32f, short, float, float)
+DEF_CVT_SCALE_FUNC(32s32f, int, float, double)
+DEF_CVT_SCALE_FUNC(32f,    float, float, float)
+DEF_CVT_SCALE_FUNC(64f32f, double, float, double)
 
-DEF_CVT_SCALE_FUNC(8u64f,  uchar, double, double);
-DEF_CVT_SCALE_FUNC(8s64f,  schar, double, double);
-DEF_CVT_SCALE_FUNC(16u64f, ushort, double, double);
-DEF_CVT_SCALE_FUNC(16s64f, short, double, double);
-DEF_CVT_SCALE_FUNC(32s64f, int, double, double);
-DEF_CVT_SCALE_FUNC(32f64f, float, double, double);
-DEF_CVT_SCALE_FUNC(64f,    double, double, double);
+DEF_CVT_SCALE_FUNC(8u64f,  uchar, double, double)
+DEF_CVT_SCALE_FUNC(8s64f,  schar, double, double)
+DEF_CVT_SCALE_FUNC(16u64f, ushort, double, double)
+DEF_CVT_SCALE_FUNC(16s64f, short, double, double)
+DEF_CVT_SCALE_FUNC(32s64f, int, double, double)
+DEF_CVT_SCALE_FUNC(32f64f, float, double, double)
+DEF_CVT_SCALE_FUNC(64f,    double, double, double)
 
-DEF_CPY_FUNC(8u,     uchar);
-DEF_CVT_FUNC(8s8u,   schar, uchar);
-DEF_CVT_FUNC(16u8u,  ushort, uchar);
-DEF_CVT_FUNC(16s8u,  short, uchar);
-DEF_CVT_FUNC(32s8u,  int, uchar);
-DEF_CVT_FUNC(32f8u,  float, uchar);
-DEF_CVT_FUNC(64f8u,  double, uchar);
+DEF_CPY_FUNC(8u,     uchar)
+DEF_CVT_FUNC(8s8u,   schar, uchar)
+DEF_CVT_FUNC(16u8u,  ushort, uchar)
+DEF_CVT_FUNC(16s8u,  short, uchar)
+DEF_CVT_FUNC(32s8u,  int, uchar)
+DEF_CVT_FUNC(32f8u,  float, uchar)
+DEF_CVT_FUNC(64f8u,  double, uchar)
 
-DEF_CVT_FUNC(8u8s,   uchar, schar);
-DEF_CVT_FUNC(16u8s,  ushort, schar);
-DEF_CVT_FUNC(16s8s,  short, schar);
-DEF_CVT_FUNC(32s8s,  int, schar);
-DEF_CVT_FUNC(32f8s,  float, schar);
-DEF_CVT_FUNC(64f8s,  double, schar);
+DEF_CVT_FUNC(8u8s,   uchar, schar)
+DEF_CVT_FUNC(16u8s,  ushort, schar)
+DEF_CVT_FUNC(16s8s,  short, schar)
+DEF_CVT_FUNC(32s8s,  int, schar)
+DEF_CVT_FUNC(32f8s,  float, schar)
+DEF_CVT_FUNC(64f8s,  double, schar)
 
-DEF_CVT_FUNC(8u16u,  uchar, ushort);
-DEF_CVT_FUNC(8s16u,  schar, ushort);
-DEF_CPY_FUNC(16u,    ushort);
-DEF_CVT_FUNC(16s16u, short, ushort);
-DEF_CVT_FUNC(32s16u, int, ushort);
-DEF_CVT_FUNC(32f16u, float, ushort);
-DEF_CVT_FUNC(64f16u, double, ushort);
+DEF_CVT_FUNC(8u16u,  uchar, ushort)
+DEF_CVT_FUNC(8s16u,  schar, ushort)
+DEF_CPY_FUNC(16u,    ushort)
+DEF_CVT_FUNC(16s16u, short, ushort)
+DEF_CVT_FUNC(32s16u, int, ushort)
+DEF_CVT_FUNC(32f16u, float, ushort)
+DEF_CVT_FUNC(64f16u, double, ushort)
 
-DEF_CVT_FUNC(8u16s,  uchar, short);
-DEF_CVT_FUNC(8s16s,  schar, short);
-DEF_CVT_FUNC(16u16s, ushort, short);
-DEF_CVT_FUNC(32s16s, int, short);
-DEF_CVT_FUNC(32f16s, float, short);
-DEF_CVT_FUNC(64f16s, double, short);
+DEF_CVT_FUNC(8u16s,  uchar, short)
+DEF_CVT_FUNC(8s16s,  schar, short)
+DEF_CVT_FUNC(16u16s, ushort, short)
+DEF_CVT_FUNC(32s16s, int, short)
+DEF_CVT_FUNC(32f16s, float, short)
+DEF_CVT_FUNC(64f16s, double, short)
 
-DEF_CVT_FUNC(8u32s,  uchar, int);
-DEF_CVT_FUNC(8s32s,  schar, int);
-DEF_CVT_FUNC(16u32s, ushort, int);
-DEF_CVT_FUNC(16s32s, short, int);
-DEF_CPY_FUNC(32s,    int);
-DEF_CVT_FUNC(32f32s, float, int);
-DEF_CVT_FUNC(64f32s, double, int);
+DEF_CVT_FUNC(8u32s,  uchar, int)
+DEF_CVT_FUNC(8s32s,  schar, int)
+DEF_CVT_FUNC(16u32s, ushort, int)
+DEF_CVT_FUNC(16s32s, short, int)
+DEF_CPY_FUNC(32s,    int)
+DEF_CVT_FUNC(32f32s, float, int)
+DEF_CVT_FUNC(64f32s, double, int)
 
-DEF_CVT_FUNC(8u32f,  uchar, float);
-DEF_CVT_FUNC(8s32f,  schar, float);
-DEF_CVT_FUNC(16u32f, ushort, float);
-DEF_CVT_FUNC(16s32f, short, float);
-DEF_CVT_FUNC(32s32f, int, float);
-DEF_CVT_FUNC(64f32f, double, float);
+DEF_CVT_FUNC(8u32f,  uchar, float)
+DEF_CVT_FUNC(8s32f,  schar, float)
+DEF_CVT_FUNC(16u32f, ushort, float)
+DEF_CVT_FUNC(16s32f, short, float)
+DEF_CVT_FUNC(32s32f, int, float)
+DEF_CVT_FUNC(64f32f, double, float)
 
-DEF_CVT_FUNC(8u64f,  uchar, double);
-DEF_CVT_FUNC(8s64f,  schar, double);
-DEF_CVT_FUNC(16u64f, ushort, double);
-DEF_CVT_FUNC(16s64f, short, double);
-DEF_CVT_FUNC(32s64f, int, double);
-DEF_CVT_FUNC(32f64f, float, double);
-DEF_CPY_FUNC(64s,    int64);
+DEF_CVT_FUNC(8u64f,  uchar, double)
+DEF_CVT_FUNC(8s64f,  schar, double)
+DEF_CVT_FUNC(16u64f, ushort, double)
+DEF_CVT_FUNC(16s64f, short, double)
+DEF_CVT_FUNC(32s64f, int, double)
+DEF_CVT_FUNC(32f64f, float, double)
+DEF_CPY_FUNC(64s,    int64)
 
 static BinaryFunc getCvtScaleAbsFunc(int depth)
 {

modules/core/src/copy.cpp

@@ -166,16 +166,16 @@ static void copyMask##suffix(const uchar* src, size_t sstep, const uchar* mask,
 }
 
 
-DEF_COPY_MASK(8u, uchar);
-DEF_COPY_MASK(16u, ushort);
-DEF_COPY_MASK(8uC3, Vec3b);
-DEF_COPY_MASK(32s, int);
-DEF_COPY_MASK(16uC3, Vec3s);
-DEF_COPY_MASK(32sC2, Vec2i);
-DEF_COPY_MASK(32sC3, Vec3i);
-DEF_COPY_MASK(32sC4, Vec4i);
-DEF_COPY_MASK(32sC6, Vec6i);
-DEF_COPY_MASK(32sC8, Vec8i);
+DEF_COPY_MASK(8u, uchar)
+DEF_COPY_MASK(16u, ushort)
+DEF_COPY_MASK(8uC3, Vec3b)
+DEF_COPY_MASK(32s, int)
+DEF_COPY_MASK(16uC3, Vec3s)
+DEF_COPY_MASK(32sC2, Vec2i)
+DEF_COPY_MASK(32sC3, Vec3i)
+DEF_COPY_MASK(32sC4, Vec4i)
+DEF_COPY_MASK(32sC6, Vec6i)
+DEF_COPY_MASK(32sC8, Vec8i)
 
 BinaryFunc copyMaskTab[] =
 {
@@ -232,10 +232,7 @@ void Mat::copyTo( OutputArray _dst ) const
             const uchar* sptr = data;
             uchar* dptr = dst.data;
 
-            // to handle the copying 1xn matrix => nx1 std vector.
-            Size sz = size() == dst.size() ?
-                getContinuousSize(*this, dst) :
-                getContinuousSize(*this);
+            Size sz = getContinuousSize(*this, dst);
             size_t len = sz.width*elemSize();
 
             for( ; sz.height--; sptr += step, dptr += dst.step )
@@ -286,6 +283,7 @@ void Mat::copyTo( OutputArray _dst, InputArray _mask ) const
 
     if( dims <= 2 )
     {
+        CV_Assert( size() == mask.size() );
         Size sz = getContinuousSize(*this, dst, mask, mcn);
         copymask(data, step, mask.data, mask.step, dst.data, dst.step, sz, &esz);
         return;

modules/core/src/gpumat.cpp

@@ -620,11 +620,19 @@ void cv::gpu::GpuMat::copyTo(GpuMat& m) const
 void cv::gpu::GpuMat::copyTo(GpuMat& mat, const GpuMat& mask) const
 {
     if (mask.empty())
+    {
         copyTo(mat);
+    }
     else
     {
+        uchar* data0 = mat.data;
+
         mat.create(size(), type());
 
+        // do not leave dst uninitialized
+        if (mat.data != data0)
+            mat.setTo(Scalar::all(0));
+
         gpuFuncTable()->copyWithMask(*this, mat, mask);
     }
 }

modules/core/src/system.cpp

@@ -982,7 +982,9 @@ public:
 };
 
 #ifdef WIN32
+#ifdef _MSC_VER
 #pragma warning(disable:4505) // unreferenced local function has been removed
+#endif
 
 #ifdef HAVE_WINRT
     // using C++11 thread attribute for local thread data
@@ -1129,17 +1131,24 @@ public:
         }
     }
 };
-static TLSContainerStorage tlsContainerStorage;
+
+// This is a wrapper function that will ensure 'tlsContainerStorage' is constructed on first use.
+// For more information: http://www.parashift.com/c++-faq/static-init-order-on-first-use.html
+static TLSContainerStorage& getTLSContainerStorage()
+{
+    static TLSContainerStorage *tlsContainerStorage = new TLSContainerStorage();
+    return *tlsContainerStorage;
+}
 
 TLSDataContainer::TLSDataContainer()
     : key_(-1)
 {
-    key_ = tlsContainerStorage.allocateKey(this);
+    key_ = getTLSContainerStorage().allocateKey(this);
 }
 
 TLSDataContainer::~TLSDataContainer()
 {
-    tlsContainerStorage.releaseKey(key_, this);
+    getTLSContainerStorage().releaseKey(key_, this);
     key_ = -1;
 }
 
@@ -1164,7 +1173,7 @@ TLSStorage::~TLSStorage()
         void*& data = tlsData_[i];
         if (data)
         {
-            tlsContainerStorage.destroyData(i, data);
+            getTLSContainerStorage().destroyData(i, data);
             data = NULL;
         }
     }

modules/core/test/test_arithm.cpp

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

modules/core/test/test_mat.cpp

@@ -897,3 +897,24 @@ TEST(Core_Mat, reshape_1942)
     );
     ASSERT_EQ(1, cn);
 }
+
+TEST(Core_Mat, copyNx1ToVector)
+{
+    cv::Mat_<uchar> src(5, 1);
+    cv::Mat_<uchar> ref_dst8;
+    cv::Mat_<ushort> ref_dst16;
+    std::vector<uchar> dst8;
+    std::vector<ushort> dst16;
+
+    src << 1, 2, 3, 4, 5;
+
+    src.copyTo(ref_dst8);
+    src.copyTo(dst8);
+
+    ASSERT_PRED_FORMAT2(cvtest::MatComparator(0, 0), ref_dst8, cv::Mat_<uchar>(dst8));
+
+    src.convertTo(ref_dst16, CV_16U);
+    src.convertTo(dst16, CV_16U);
+
+    ASSERT_PRED_FORMAT2(cvtest::MatComparator(0, 0), ref_dst16, cv::Mat_<ushort>(dst16));
+}

modules/features2d/src/features2d_init.cpp

@@ -59,23 +59,23 @@ Ptr<Feature2D> Feature2D::create( const string& feature2DType )
 
 CV_INIT_ALGORITHM(BRISK, "Feature2D.BRISK",
                    obj.info()->addParam(obj, "thres", obj.threshold);
-                   obj.info()->addParam(obj, "octaves", obj.octaves));
+                   obj.info()->addParam(obj, "octaves", obj.octaves))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
 CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
-                  obj.info()->addParam(obj, "bytes", obj.bytes_));
+                  obj.info()->addParam(obj, "bytes", obj.bytes_))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
 CV_INIT_ALGORITHM(FastFeatureDetector, "Feature2D.FAST",
                   obj.info()->addParam(obj, "threshold", obj.threshold);
-                  obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression));
+                  obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression))
 
 CV_INIT_ALGORITHM(FastFeatureDetector2, "Feature2D.FASTX",
                   obj.info()->addParam(obj, "threshold", obj.threshold);
                   obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression);
-                  obj.info()->addParam(obj, "type", obj.type));
+                  obj.info()->addParam(obj, "type", obj.type))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -84,7 +84,7 @@ CV_INIT_ALGORITHM(StarDetector, "Feature2D.STAR",
                   obj.info()->addParam(obj, "responseThreshold", obj.responseThreshold);
                   obj.info()->addParam(obj, "lineThresholdProjected", obj.lineThresholdProjected);
                   obj.info()->addParam(obj, "lineThresholdBinarized", obj.lineThresholdBinarized);
-                  obj.info()->addParam(obj, "suppressNonmaxSize", obj.suppressNonmaxSize));
+                  obj.info()->addParam(obj, "suppressNonmaxSize", obj.suppressNonmaxSize))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -97,7 +97,7 @@ CV_INIT_ALGORITHM(MSER, "Feature2D.MSER",
                   obj.info()->addParam(obj, "maxEvolution", obj.maxEvolution);
                   obj.info()->addParam(obj, "areaThreshold", obj.areaThreshold);
                   obj.info()->addParam(obj, "minMargin", obj.minMargin);
-                  obj.info()->addParam(obj, "edgeBlurSize", obj.edgeBlurSize));
+                  obj.info()->addParam(obj, "edgeBlurSize", obj.edgeBlurSize))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -109,7 +109,7 @@ CV_INIT_ALGORITHM(ORB, "Feature2D.ORB",
                   obj.info()->addParam(obj, "edgeThreshold", obj.edgeThreshold);
                   obj.info()->addParam(obj, "patchSize", obj.patchSize);
                   obj.info()->addParam(obj, "WTA_K", obj.WTA_K);
-                  obj.info()->addParam(obj, "scoreType", obj.scoreType));
+                  obj.info()->addParam(obj, "scoreType", obj.scoreType))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -117,7 +117,7 @@ CV_INIT_ALGORITHM(FREAK, "Feature2D.FREAK",
                   obj.info()->addParam(obj, "orientationNormalized", obj.orientationNormalized);
                   obj.info()->addParam(obj, "scaleNormalized", obj.scaleNormalized);
                   obj.info()->addParam(obj, "patternScale", obj.patternScale);
-                  obj.info()->addParam(obj, "nbOctave", obj.nOctaves));
+                  obj.info()->addParam(obj, "nbOctave", obj.nOctaves))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -126,7 +126,7 @@ CV_INIT_ALGORITHM(GFTTDetector, "Feature2D.GFTT",
                   obj.info()->addParam(obj, "qualityLevel", obj.qualityLevel);
                   obj.info()->addParam(obj, "minDistance", obj.minDistance);
                   obj.info()->addParam(obj, "useHarrisDetector", obj.useHarrisDetector);
-                  obj.info()->addParam(obj, "k", obj.k));
+                  obj.info()->addParam(obj, "k", obj.k))
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -146,7 +146,7 @@ CV_INIT_ALGORITHM(SimpleBlobDetector, "Feature2D.SimpleBlob",
                   obj.info()->addParam(obj, "maxInertiaRatio",  obj.params.maxInertiaRatio);
                   obj.info()->addParam(obj, "filterByConvexity", obj.params.filterByConvexity);
                   obj.info()->addParam(obj, "maxConvexity",     obj.params.maxConvexity);
-                  );
+                  )
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -167,7 +167,7 @@ CV_INIT_ALGORITHM(HarrisDetector, "Feature2D.HARRIS",
                   obj.info()->addParam(obj, "qualityLevel", obj.qualityLevel);
                   obj.info()->addParam(obj, "minDistance", obj.minDistance);
                   obj.info()->addParam(obj, "useHarrisDetector", obj.useHarrisDetector);
-                  obj.info()->addParam(obj, "k", obj.k));
+                  obj.info()->addParam(obj, "k", obj.k))
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////////////
 
@@ -178,21 +178,21 @@ CV_INIT_ALGORITHM(DenseFeatureDetector, "Feature2D.Dense",
                   obj.info()->addParam(obj, "initXyStep", obj.initXyStep);
                   obj.info()->addParam(obj, "initImgBound", obj.initImgBound);
                   obj.info()->addParam(obj, "varyXyStepWithScale", obj.varyXyStepWithScale);
-                  obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale));
+                  obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale))
 
 CV_INIT_ALGORITHM(GridAdaptedFeatureDetector, "Feature2D.Grid",
                   obj.info()->addParam<FeatureDetector>(obj, "detector", obj.detector, false, 0, 0); // Extra params added to avoid VS2013 fatal error in opencv2/core.hpp (decl. of addParam)
                   obj.info()->addParam(obj, "maxTotalKeypoints", obj.maxTotalKeypoints);
                   obj.info()->addParam(obj, "gridRows", obj.gridRows);
-                  obj.info()->addParam(obj, "gridCols", obj.gridCols));
+                  obj.info()->addParam(obj, "gridCols", obj.gridCols))
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////////////
 
 CV_INIT_ALGORITHM(BFMatcher, "DescriptorMatcher.BFMatcher",
                   obj.info()->addParam(obj, "normType", obj.normType);
-                  obj.info()->addParam(obj, "crossCheck", obj.crossCheck));
+                  obj.info()->addParam(obj, "crossCheck", obj.crossCheck))
 
-CV_INIT_ALGORITHM(FlannBasedMatcher, "DescriptorMatcher.FlannBasedMatcher",);
+CV_INIT_ALGORITHM(FlannBasedMatcher, "DescriptorMatcher.FlannBasedMatcher",)
 
 ///////////////////////////////////////////////////////////////////////////////////////////////////////////
 

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

@@ -414,12 +414,6 @@ public:
 
     void loadIndex(FILE* stream)
     {
-        load_value(stream, branching_);
-        load_value(stream, trees_);
-        load_value(stream, centers_init_);
-        load_value(stream, leaf_size_);
-        load_value(stream, memoryCounter);
-
         free_elements();
 
         if (root!=NULL) {
@@ -430,6 +424,12 @@ public:
             delete[] indices;
         }
 
+        load_value(stream, branching_);
+        load_value(stream, trees_);
+        load_value(stream, centers_init_);
+        load_value(stream, leaf_size_);
+        load_value(stream, memoryCounter);
+
         indices = new int*[trees_];
         root = new NodePtr[trees_];
         for (int i=0; i<trees_; ++i) {

modules/gpu/CMakeLists.txt

@@ -82,7 +82,7 @@ ocv_create_module(${cuda_link_libs})
 if(HAVE_CUDA)
   install(FILES src/nvidia/NPP_staging/NPP_staging.hpp  src/nvidia/core/NCV.hpp
     DESTINATION ${OPENCV_INCLUDE_INSTALL_PATH}/opencv2/${name}
-    COMPONENT main)
+    COMPONENT dev)
 endif()
 
 ocv_add_precompiled_headers(${the_module})

modules/gpu/include/opencv2/gpu/gpu.hpp

@@ -2443,7 +2443,7 @@ public:
         Uncompressed_YV12   = (('Y'<<24)|('V'<<16)|('1'<<8)|('2')),   // Y,V,U (4:2:0)
         Uncompressed_NV12   = (('N'<<24)|('V'<<16)|('1'<<8)|('2')),   // Y,UV  (4:2:0)
         Uncompressed_YUYV   = (('Y'<<24)|('U'<<16)|('Y'<<8)|('V')),   // YUYV/YUY2 (4:2:2)
-        Uncompressed_UYVY   = (('U'<<24)|('Y'<<16)|('V'<<8)|('Y')),   // UYVY (4:2:2)
+        Uncompressed_UYVY   = (('U'<<24)|('Y'<<16)|('V'<<8)|('Y'))    // UYVY (4:2:2)
     };
 
     enum ChromaFormat
@@ -2451,7 +2451,7 @@ public:
         Monochrome=0,
         YUV420,
         YUV422,
-        YUV444,
+        YUV444
     };
 
     struct FormatInfo

modules/gpu/perf/perf_imgproc.cpp

@@ -50,7 +50,7 @@ using namespace perf;
 // Remap
 
 enum { HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH };
-CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH);
+CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH)
 
 void generateMap(cv::Mat& map_x, cv::Mat& map_y, int remapMode)
 {
@@ -941,7 +941,7 @@ PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate8U,
 
         CPU_SANITY_CHECK(dst);
     }
-};
+}
 
 ////////////////////////////////////////////////////////////////////////////////
 // MatchTemplate32F
@@ -981,7 +981,7 @@ PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate32F,
 
         CPU_SANITY_CHECK(dst);
     }
-};
+}
 
 //////////////////////////////////////////////////////////////////////
 // MulSpectrums
@@ -1821,7 +1821,7 @@ PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles,
 //////////////////////////////////////////////////////////////////////
 // GeneralizedHough
 
-CV_FLAGS(GHMethod, GHT_POSITION, GHT_SCALE, GHT_ROTATION);
+CV_FLAGS(GHMethod, GHT_POSITION, GHT_SCALE, GHT_ROTATION)
 
 DEF_PARAM_TEST(Method_Sz, GHMethod, cv::Size);
 

modules/gpu/src/cuda/build_point_list.cu

@@ -0,0 +1,138 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#if !defined CUDA_DISABLER
+
+#include "opencv2/gpu/device/common.hpp"
+#include "opencv2/gpu/device/emulation.hpp"
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        __device__ static int g_counter;
+
+        template <int PIXELS_PER_THREAD>
+        __global__ void buildPointList(const PtrStepSzb src, unsigned int* list)
+        {
+            __shared__ unsigned int s_queues[4][32 * PIXELS_PER_THREAD];
+            __shared__ int s_qsize[4];
+            __shared__ int s_globStart[4];
+
+            const int x = blockIdx.x * blockDim.x * PIXELS_PER_THREAD + threadIdx.x;
+            const int y = blockIdx.y * blockDim.y + threadIdx.y;
+
+            if (threadIdx.x == 0)
+                s_qsize[threadIdx.y] = 0;
+            __syncthreads();
+
+            if (y < src.rows)
+            {
+                // fill the queue
+                const uchar* srcRow = src.ptr(y);
+                for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < src.cols; ++i, xx += blockDim.x)
+                {
+                    if (srcRow[xx])
+                    {
+                        const unsigned int val = (y << 16) | xx;
+                        const int qidx = Emulation::smem::atomicAdd(&s_qsize[threadIdx.y], 1);
+                        s_queues[threadIdx.y][qidx] = val;
+                    }
+                }
+            }
+
+            __syncthreads();
+
+            // let one thread reserve the space required in the global list
+            if (threadIdx.x == 0 && threadIdx.y == 0)
+            {
+                // find how many items are stored in each list
+                int totalSize = 0;
+                for (int i = 0; i < blockDim.y; ++i)
+                {
+                    s_globStart[i] = totalSize;
+                    totalSize += s_qsize[i];
+                }
+
+                // calculate the offset in the global list
+                const int globalOffset = atomicAdd(&g_counter, totalSize);
+                for (int i = 0; i < blockDim.y; ++i)
+                    s_globStart[i] += globalOffset;
+            }
+
+            __syncthreads();
+
+            // copy local queues to global queue
+            const int qsize = s_qsize[threadIdx.y];
+            int gidx = s_globStart[threadIdx.y] + threadIdx.x;
+            for(int i = threadIdx.x; i < qsize; i += blockDim.x, gidx += blockDim.x)
+                list[gidx] = s_queues[threadIdx.y][i];
+        }
+
+        int buildPointList_gpu(PtrStepSzb src, unsigned int* list)
+        {
+            const int PIXELS_PER_THREAD = 16;
+
+            void* counterPtr;
+            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
+
+            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
+
+            const dim3 block(32, 4);
+            const dim3 grid(divUp(src.cols, block.x * PIXELS_PER_THREAD), divUp(src.rows, block.y));
+
+            cudaSafeCall( cudaFuncSetCacheConfig(buildPointList<PIXELS_PER_THREAD>, cudaFuncCachePreferShared) );
+
+            buildPointList<PIXELS_PER_THREAD><<<grid, block>>>(src, list);
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+
+            int totalCount;
+            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
+
+            return totalCount;
+        }
+    }
+}}}
+
+#endif /* CUDA_DISABLER */

modules/gpu/src/cuda/generalized_hough.cu

@@ -40,654 +40,23 @@
 //
 //M*/
 
+#define CUDA_DISABLER
+
 #if !defined CUDA_DISABLER
 
 #include <thrust/device_ptr.h>
-#include <thrust/sort.h>
+#include <thrust/transform.h>
 
 #include "opencv2/gpu/device/common.hpp"
 #include "opencv2/gpu/device/emulation.hpp"
 #include "opencv2/gpu/device/vec_math.hpp"
 #include "opencv2/gpu/device/functional.hpp"
-#include "opencv2/gpu/device/limits.hpp"
-#include "opencv2/gpu/device/dynamic_smem.hpp"
 
 namespace cv { namespace gpu { namespace device
 {
     namespace hough
     {
-        __device__ int g_counter;
-
-        ////////////////////////////////////////////////////////////////////////
-        // buildPointList
-
-        template <int PIXELS_PER_THREAD>
-        __global__ void buildPointList(const PtrStepSzb src, unsigned int* list)
-        {
-            __shared__ unsigned int s_queues[4][32 * PIXELS_PER_THREAD];
-            __shared__ int s_qsize[4];
-            __shared__ int s_globStart[4];
-
-            const int x = blockIdx.x * blockDim.x * PIXELS_PER_THREAD + threadIdx.x;
-            const int y = blockIdx.y * blockDim.y + threadIdx.y;
-
-            if (threadIdx.x == 0)
-                s_qsize[threadIdx.y] = 0;
-            __syncthreads();
-
-            if (y < src.rows)
-            {
-                // fill the queue
-                const uchar* srcRow = src.ptr(y);
-                for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < src.cols; ++i, xx += blockDim.x)
-                {
-                    if (srcRow[xx])
-                    {
-                        const unsigned int val = (y << 16) | xx;
-                        const int qidx = Emulation::smem::atomicAdd(&s_qsize[threadIdx.y], 1);
-                        s_queues[threadIdx.y][qidx] = val;
-                    }
-                }
-            }
-
-            __syncthreads();
-
-            // let one thread reserve the space required in the global list
-            if (threadIdx.x == 0 && threadIdx.y == 0)
-            {
-                // find how many items are stored in each list
-                int totalSize = 0;
-                for (int i = 0; i < blockDim.y; ++i)
-                {
-                    s_globStart[i] = totalSize;
-                    totalSize += s_qsize[i];
-                }
-
-                // calculate the offset in the global list
-                const int globalOffset = atomicAdd(&g_counter, totalSize);
-                for (int i = 0; i < blockDim.y; ++i)
-                    s_globStart[i] += globalOffset;
-            }
-
-            __syncthreads();
-
-            // copy local queues to global queue
-            const int qsize = s_qsize[threadIdx.y];
-            int gidx = s_globStart[threadIdx.y] + threadIdx.x;
-            for(int i = threadIdx.x; i < qsize; i += blockDim.x, gidx += blockDim.x)
-                list[gidx] = s_queues[threadIdx.y][i];
-        }
-
-        int buildPointList_gpu(PtrStepSzb src, unsigned int* list)
-        {
-            const int PIXELS_PER_THREAD = 16;
-
-            void* counterPtr;
-            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
-
-            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
-
-            const dim3 block(32, 4);
-            const dim3 grid(divUp(src.cols, block.x * PIXELS_PER_THREAD), divUp(src.rows, block.y));
-
-            cudaSafeCall( cudaFuncSetCacheConfig(buildPointList<PIXELS_PER_THREAD>, cudaFuncCachePreferShared) );
-
-            buildPointList<PIXELS_PER_THREAD><<<grid, block>>>(src, list);
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-
-            int totalCount;
-            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
-
-            return totalCount;
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // linesAccum
-
-        __global__ void linesAccumGlobal(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
-        {
-            const int n = blockIdx.x;
-            const float ang = n * theta;
-
-            float sinVal;
-            float cosVal;
-            sincosf(ang, &sinVal, &cosVal);
-            sinVal *= irho;
-            cosVal *= irho;
-
-            const int shift = (numrho - 1) / 2;
-
-            int* accumRow = accum.ptr(n + 1);
-            for (int i = threadIdx.x; i < count; i += blockDim.x)
-            {
-                const unsigned int val = list[i];
-
-                const int x = (val & 0xFFFF);
-                const int y = (val >> 16) & 0xFFFF;
-
-                int r = __float2int_rn(x * cosVal + y * sinVal);
-                r += shift;
-
-                ::atomicAdd(accumRow + r + 1, 1);
-            }
-        }
-
-        __global__ void linesAccumShared(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
-        {
-            int* smem = DynamicSharedMem<int>();
-
-            for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
-                smem[i] = 0;
-
-            __syncthreads();
-
-            const int n = blockIdx.x;
-            const float ang = n * theta;
-
-            float sinVal;
-            float cosVal;
-            sincosf(ang, &sinVal, &cosVal);
-            sinVal *= irho;
-            cosVal *= irho;
-
-            const int shift = (numrho - 1) / 2;
-
-            for (int i = threadIdx.x; i < count; i += blockDim.x)
-            {
-                const unsigned int val = list[i];
-
-                const int x = (val & 0xFFFF);
-                const int y = (val >> 16) & 0xFFFF;
-
-                int r = __float2int_rn(x * cosVal + y * sinVal);
-                r += shift;
-
-                Emulation::smem::atomicAdd(&smem[r + 1], 1);
-            }
-
-            __syncthreads();
-
-            int* accumRow = accum.ptr(n + 1);
-            for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
-                accumRow[i] = smem[i];
-        }
-
-        void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20)
-        {
-            const dim3 block(has20 ? 1024 : 512);
-            const dim3 grid(accum.rows - 2);
-
-            size_t smemSize = (accum.cols - 1) * sizeof(int);
-
-            if (smemSize < sharedMemPerBlock - 1000)
-                linesAccumShared<<<grid, block, smemSize>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
-            else
-                linesAccumGlobal<<<grid, block>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
-
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // linesGetResult
-
-        __global__ void linesGetResult(const PtrStepSzi accum, float2* out, int* votes, const int maxSize, const float rho, const float theta, const int threshold, const int numrho)
-        {
-            const int r = blockIdx.x * blockDim.x + threadIdx.x;
-            const int n = blockIdx.y * blockDim.y + threadIdx.y;
-
-            if (r >= accum.cols - 2 || n >= accum.rows - 2)
-                return;
-
-            const int curVotes = accum(n + 1, r + 1);
-
-            if (curVotes > threshold &&
-                curVotes >  accum(n + 1, r) &&
-                curVotes >= accum(n + 1, r + 2) &&
-                curVotes >  accum(n, r + 1) &&
-                curVotes >= accum(n + 2, r + 1))
-            {
-                const float radius = (r - (numrho - 1) * 0.5f) * rho;
-                const float angle = n * theta;
-
-                const int ind = ::atomicAdd(&g_counter, 1);
-                if (ind < maxSize)
-                {
-                    out[ind] = make_float2(radius, angle);
-                    votes[ind] = curVotes;
-                }
-            }
-        }
-
-        int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort)
-        {
-            void* counterPtr;
-            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
-
-            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
-
-            const dim3 block(32, 8);
-            const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
-
-            cudaSafeCall( cudaFuncSetCacheConfig(linesGetResult, cudaFuncCachePreferL1) );
-
-            linesGetResult<<<grid, block>>>(accum, out, votes, maxSize, rho, theta, threshold, accum.cols - 2);
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-
-            int totalCount;
-            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
-
-            totalCount = ::min(totalCount, maxSize);
-
-            if (doSort && totalCount > 0)
-            {
-                thrust::device_ptr<float2> outPtr(out);
-                thrust::device_ptr<int> votesPtr(votes);
-                thrust::sort_by_key(votesPtr, votesPtr + totalCount, outPtr, thrust::greater<int>());
-            }
-
-            return totalCount;
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // houghLinesProbabilistic
-
-        texture<uchar, cudaTextureType2D, cudaReadModeElementType> tex_mask(false, cudaFilterModePoint, cudaAddressModeClamp);
-
-        __global__ void houghLinesProbabilistic(const PtrStepSzi accum,
-                                                int4* out, const int maxSize,
-                                                const float rho, const float theta,
-                                                const int lineGap, const int lineLength,
-                                                const int rows, const int cols)
-        {
-            const int r = blockIdx.x * blockDim.x + threadIdx.x;
-            const int n = blockIdx.y * blockDim.y + threadIdx.y;
-
-            if (r >= accum.cols - 2 || n >= accum.rows - 2)
-                return;
-
-            const int curVotes = accum(n + 1, r + 1);
-
-            if (curVotes >= lineLength &&
-                curVotes > accum(n, r) &&
-                curVotes > accum(n, r + 1) &&
-                curVotes > accum(n, r + 2) &&
-                curVotes > accum(n + 1, r) &&
-                curVotes > accum(n + 1, r + 2) &&
-                curVotes > accum(n + 2, r) &&
-                curVotes > accum(n + 2, r + 1) &&
-                curVotes > accum(n + 2, r + 2))
-            {
-                const float radius = (r - (accum.cols - 2 - 1) * 0.5f) * rho;
-                const float angle = n * theta;
-
-                float cosa;
-                float sina;
-                sincosf(angle, &sina, &cosa);
-
-                float2 p0 = make_float2(cosa * radius, sina * radius);
-                float2 dir = make_float2(-sina, cosa);
-
-                float2 pb[4] = {make_float2(-1, -1), make_float2(-1, -1), make_float2(-1, -1), make_float2(-1, -1)};
-                float a;
-
-                if (dir.x != 0)
-                {
-                    a = -p0.x / dir.x;
-                    pb[0].x = 0;
-                    pb[0].y = p0.y + a * dir.y;
-
-                    a = (cols - 1 - p0.x) / dir.x;
-                    pb[1].x = cols - 1;
-                    pb[1].y = p0.y + a * dir.y;
-                }
-                if (dir.y != 0)
-                {
-                    a = -p0.y / dir.y;
-                    pb[2].x = p0.x + a * dir.x;
-                    pb[2].y = 0;
-
-                    a = (rows - 1 - p0.y) / dir.y;
-                    pb[3].x = p0.x + a * dir.x;
-                    pb[3].y = rows - 1;
-                }
-
-                if (pb[0].x == 0 && (pb[0].y >= 0 && pb[0].y < rows))
-                {
-                    p0 = pb[0];
-                    if (dir.x < 0)
-                        dir = -dir;
-                }
-                else if (pb[1].x == cols - 1 && (pb[0].y >= 0 && pb[0].y < rows))
-                {
-                    p0 = pb[1];
-                    if (dir.x > 0)
-                        dir = -dir;
-                }
-                else if (pb[2].y == 0 && (pb[2].x >= 0 && pb[2].x < cols))
-                {
-                    p0 = pb[2];
-                    if (dir.y < 0)
-                        dir = -dir;
-                }
-                else if (pb[3].y == rows - 1 && (pb[3].x >= 0 && pb[3].x < cols))
-                {
-                    p0 = pb[3];
-                    if (dir.y > 0)
-                        dir = -dir;
-                }
-
-                float2 d;
-                if (::fabsf(dir.x) > ::fabsf(dir.y))
-                {
-                    d.x = dir.x > 0 ? 1 : -1;
-                    d.y = dir.y / ::fabsf(dir.x);
-                }
-                else
-                {
-                    d.x = dir.x / ::fabsf(dir.y);
-                    d.y = dir.y > 0 ? 1 : -1;
-                }
-
-                float2 line_end[2];
-                int gap;
-                bool inLine = false;
-
-                float2 p1 = p0;
-                if (p1.x < 0 || p1.x >= cols || p1.y < 0 || p1.y >= rows)
-                    return;
-
-                for (;;)
-                {
-                    if (tex2D(tex_mask, p1.x, p1.y))
-                    {
-                        gap = 0;
-
-                        if (!inLine)
-                        {
-                            line_end[0] = p1;
-                            line_end[1] = p1;
-                            inLine = true;
-                        }
-                        else
-                        {
-                            line_end[1] = p1;
-                        }
-                    }
-                    else if (inLine)
-                    {
-                        if (++gap > lineGap)
-                        {
-                            bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
-                                             ::abs(line_end[1].y - line_end[0].y) >= lineLength;
-
-                            if (good_line)
-                            {
-                                const int ind = ::atomicAdd(&g_counter, 1);
-                                if (ind < maxSize)
-                                    out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
-                            }
-
-                            gap = 0;
-                            inLine = false;
-                        }
-                    }
-
-                    p1 = p1 + d;
-                    if (p1.x < 0 || p1.x >= cols || p1.y < 0 || p1.y >= rows)
-                    {
-                        if (inLine)
-                        {
-                            bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
-                                             ::abs(line_end[1].y - line_end[0].y) >= lineLength;
-
-                            if (good_line)
-                            {
-                                const int ind = ::atomicAdd(&g_counter, 1);
-                                if (ind < maxSize)
-                                    out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
-                            }
-
-                        }
-                        break;
-                    }
-                }
-            }
-        }
-
-        int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi accum, int4* out, int maxSize, float rho, float theta, int lineGap, int lineLength)
-        {
-            void* counterPtr;
-            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
-
-            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
-
-            const dim3 block(32, 8);
-            const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
-
-            bindTexture(&tex_mask, mask);
-
-            houghLinesProbabilistic<<<grid, block>>>(accum,
-                                                     out, maxSize,
-                                                     rho, theta,
-                                                     lineGap, lineLength,
-                                                     mask.rows, mask.cols);
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-
-            int totalCount;
-            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
-
-            totalCount = ::min(totalCount, maxSize);
-
-            return totalCount;
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // circlesAccumCenters
-
-        __global__ void circlesAccumCenters(const unsigned int* list, const int count, const PtrStepi dx, const PtrStepi dy,
-                                            PtrStepi accum, const int width, const int height, const int minRadius, const int maxRadius, const float idp)
-        {
-            const int SHIFT = 10;
-            const int ONE = 1 << SHIFT;
-
-            const int tid = blockIdx.x * blockDim.x + threadIdx.x;
-
-            if (tid >= count)
-                return;
-
-            const unsigned int val = list[tid];
-
-            const int x = (val & 0xFFFF);
-            const int y = (val >> 16) & 0xFFFF;
-
-            const int vx = dx(y, x);
-            const int vy = dy(y, x);
-
-            if (vx == 0 && vy == 0)
-                return;
-
-            const float mag = ::sqrtf(vx * vx + vy * vy);
-
-            const int x0 = __float2int_rn((x * idp) * ONE);
-            const int y0 = __float2int_rn((y * idp) * ONE);
-
-            int sx = __float2int_rn((vx * idp) * ONE / mag);
-            int sy = __float2int_rn((vy * idp) * ONE / mag);
-
-            // Step from minRadius to maxRadius in both directions of the gradient
-            for (int k1 = 0; k1 < 2; ++k1)
-            {
-                int x1 = x0 + minRadius * sx;
-                int y1 = y0 + minRadius * sy;
-
-                for (int r = minRadius; r <= maxRadius; x1 += sx, y1 += sy, ++r)
-                {
-                    const int x2 = x1 >> SHIFT;
-                    const int y2 = y1 >> SHIFT;
-
-                    if (x2 < 0 || x2 >= width || y2 < 0 || y2 >= height)
-                        break;
-
-                    ::atomicAdd(accum.ptr(y2 + 1) + x2 + 1, 1);
-                }
-
-                sx = -sx;
-                sy = -sy;
-            }
-        }
-
-        void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp)
-        {
-            const dim3 block(256);
-            const dim3 grid(divUp(count, block.x));
-
-            cudaSafeCall( cudaFuncSetCacheConfig(circlesAccumCenters, cudaFuncCachePreferL1) );
-
-            circlesAccumCenters<<<grid, block>>>(list, count, dx, dy, accum, accum.cols - 2, accum.rows - 2, minRadius, maxRadius, idp);
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // buildCentersList
-
-        __global__ void buildCentersList(const PtrStepSzi accum, unsigned int* centers, const int threshold)
-        {
-            const int x = blockIdx.x * blockDim.x + threadIdx.x;
-            const int y = blockIdx.y * blockDim.y + threadIdx.y;
-
-            if (x < accum.cols - 2 && y < accum.rows - 2)
-            {
-                const int top = accum(y, x + 1);
-
-                const int left = accum(y + 1, x);
-                const int cur = accum(y + 1, x + 1);
-                const int right = accum(y + 1, x + 2);
-
-                const int bottom = accum(y + 2, x + 1);
-
-                if (cur > threshold && cur > top && cur >= bottom && cur >  left && cur >= right)
-                {
-                    const unsigned int val = (y << 16) | x;
-                    const int idx = ::atomicAdd(&g_counter, 1);
-                    centers[idx] = val;
-                }
-            }
-        }
-
-        int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold)
-        {
-            void* counterPtr;
-            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
-
-            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
-
-            const dim3 block(32, 8);
-            const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
-
-            cudaSafeCall( cudaFuncSetCacheConfig(buildCentersList, cudaFuncCachePreferL1) );
-
-            buildCentersList<<<grid, block>>>(accum, centers, threshold);
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-
-            int totalCount;
-            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
-
-            return totalCount;
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // circlesAccumRadius
-
-        __global__ void circlesAccumRadius(const unsigned int* centers, const unsigned int* list, const int count,
-                                           float3* circles, const int maxCircles, const float dp,
-                                           const int minRadius, const int maxRadius, const int histSize, const int threshold)
-        {
-            int* smem = DynamicSharedMem<int>();
-
-            for (int i = threadIdx.x; i < histSize + 2; i += blockDim.x)
-                smem[i] = 0;
-            __syncthreads();
-
-            unsigned int val = centers[blockIdx.x];
-
-            float cx = (val & 0xFFFF);
-            float cy = (val >> 16) & 0xFFFF;
-
-            cx = (cx + 0.5f) * dp;
-            cy = (cy + 0.5f) * dp;
-
-            for (int i = threadIdx.x; i < count; i += blockDim.x)
-            {
-                val = list[i];
-
-                const int x = (val & 0xFFFF);
-                const int y = (val >> 16) & 0xFFFF;
-
-                const float rad = ::sqrtf((cx - x) * (cx - x) + (cy - y) * (cy - y));
-                if (rad >= minRadius && rad <= maxRadius)
-                {
-                    const int r = __float2int_rn(rad - minRadius);
-
-                    Emulation::smem::atomicAdd(&smem[r + 1], 1);
-                }
-            }
-
-            __syncthreads();
-
-            for (int i = threadIdx.x; i < histSize; i += blockDim.x)
-            {
-                const int curVotes = smem[i + 1];
-
-                if (curVotes >= threshold && curVotes > smem[i] && curVotes >= smem[i + 2])
-                {
-                    const int ind = ::atomicAdd(&g_counter, 1);
-                    if (ind < maxCircles)
-                        circles[ind] = make_float3(cx, cy, i + minRadius);
-                }
-            }
-        }
-
-        int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
-                                   float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20)
-        {
-            void* counterPtr;
-            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
-
-            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
-
-            const dim3 block(has20 ? 1024 : 512);
-            const dim3 grid(centersCount);
-
-            const int histSize = maxRadius - minRadius + 1;
-            size_t smemSize = (histSize + 2) * sizeof(int);
-
-            circlesAccumRadius<<<grid, block, smemSize>>>(centers, list, count, circles, maxCircles, dp, minRadius, maxRadius, histSize, threshold);
-            cudaSafeCall( cudaGetLastError() );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-
-            int totalCount;
-            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
-
-            totalCount = ::min(totalCount, maxCircles);
-
-            return totalCount;
-        }
-
-        ////////////////////////////////////////////////////////////////////////
-        // Generalized Hough
+        __device__ static int g_counter;
 
         template <typename T, int PIXELS_PER_THREAD>
         __global__ void buildEdgePointList(const PtrStepSzb edges, const PtrStep<T> dx, const PtrStep<T> dy, unsigned int* coordList, float* thetaList)
@@ -1706,5 +1075,4 @@ namespace cv { namespace gpu { namespace device
     }
 }}}
 
-
 #endif /* CUDA_DISABLER */

modules/gpu/src/cuda/hough_circles.cu

@@ -0,0 +1,254 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#if !defined CUDA_DISABLER
+
+#include "opencv2/gpu/device/common.hpp"
+#include "opencv2/gpu/device/emulation.hpp"
+#include "opencv2/gpu/device/dynamic_smem.hpp"
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        __device__ static int g_counter;
+
+        ////////////////////////////////////////////////////////////////////////
+        // circlesAccumCenters
+
+        __global__ void circlesAccumCenters(const unsigned int* list, const int count, const PtrStepi dx, const PtrStepi dy,
+                                            PtrStepi accum, const int width, const int height, const int minRadius, const int maxRadius, const float idp)
+        {
+            const int SHIFT = 10;
+            const int ONE = 1 << SHIFT;
+
+            const int tid = blockIdx.x * blockDim.x + threadIdx.x;
+
+            if (tid >= count)
+                return;
+
+            const unsigned int val = list[tid];
+
+            const int x = (val & 0xFFFF);
+            const int y = (val >> 16) & 0xFFFF;
+
+            const int vx = dx(y, x);
+            const int vy = dy(y, x);
+
+            if (vx == 0 && vy == 0)
+                return;
+
+            const float mag = ::sqrtf(vx * vx + vy * vy);
+
+            const int x0 = __float2int_rn((x * idp) * ONE);
+            const int y0 = __float2int_rn((y * idp) * ONE);
+
+            int sx = __float2int_rn((vx * idp) * ONE / mag);
+            int sy = __float2int_rn((vy * idp) * ONE / mag);
+
+            // Step from minRadius to maxRadius in both directions of the gradient
+            for (int k1 = 0; k1 < 2; ++k1)
+            {
+                int x1 = x0 + minRadius * sx;
+                int y1 = y0 + minRadius * sy;
+
+                for (int r = minRadius; r <= maxRadius; x1 += sx, y1 += sy, ++r)
+                {
+                    const int x2 = x1 >> SHIFT;
+                    const int y2 = y1 >> SHIFT;
+
+                    if (x2 < 0 || x2 >= width || y2 < 0 || y2 >= height)
+                        break;
+
+                    ::atomicAdd(accum.ptr(y2 + 1) + x2 + 1, 1);
+                }
+
+                sx = -sx;
+                sy = -sy;
+            }
+        }
+
+        void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp)
+        {
+            const dim3 block(256);
+            const dim3 grid(divUp(count, block.x));
+
+            cudaSafeCall( cudaFuncSetCacheConfig(circlesAccumCenters, cudaFuncCachePreferL1) );
+
+            circlesAccumCenters<<<grid, block>>>(list, count, dx, dy, accum, accum.cols - 2, accum.rows - 2, minRadius, maxRadius, idp);
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+
+        ////////////////////////////////////////////////////////////////////////
+        // buildCentersList
+
+        __global__ void buildCentersList(const PtrStepSzi accum, unsigned int* centers, const int threshold)
+        {
+            const int x = blockIdx.x * blockDim.x + threadIdx.x;
+            const int y = blockIdx.y * blockDim.y + threadIdx.y;
+
+            if (x < accum.cols - 2 && y < accum.rows - 2)
+            {
+                const int top = accum(y, x + 1);
+
+                const int left = accum(y + 1, x);
+                const int cur = accum(y + 1, x + 1);
+                const int right = accum(y + 1, x + 2);
+
+                const int bottom = accum(y + 2, x + 1);
+
+                if (cur > threshold && cur > top && cur >= bottom && cur >  left && cur >= right)
+                {
+                    const unsigned int val = (y << 16) | x;
+                    const int idx = ::atomicAdd(&g_counter, 1);
+                    centers[idx] = val;
+                }
+            }
+        }
+
+        int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold)
+        {
+            void* counterPtr;
+            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
+
+            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
+
+            const dim3 block(32, 8);
+            const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
+
+            cudaSafeCall( cudaFuncSetCacheConfig(buildCentersList, cudaFuncCachePreferL1) );
+
+            buildCentersList<<<grid, block>>>(accum, centers, threshold);
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+
+            int totalCount;
+            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
+
+            return totalCount;
+        }
+
+        ////////////////////////////////////////////////////////////////////////
+        // circlesAccumRadius
+
+        __global__ void circlesAccumRadius(const unsigned int* centers, const unsigned int* list, const int count,
+                                           float3* circles, const int maxCircles, const float dp,
+                                           const int minRadius, const int maxRadius, const int histSize, const int threshold)
+        {
+            int* smem = DynamicSharedMem<int>();
+
+            for (int i = threadIdx.x; i < histSize + 2; i += blockDim.x)
+                smem[i] = 0;
+            __syncthreads();
+
+            unsigned int val = centers[blockIdx.x];
+
+            float cx = (val & 0xFFFF);
+            float cy = (val >> 16) & 0xFFFF;
+
+            cx = (cx + 0.5f) * dp;
+            cy = (cy + 0.5f) * dp;
+
+            for (int i = threadIdx.x; i < count; i += blockDim.x)
+            {
+                val = list[i];
+
+                const int x = (val & 0xFFFF);
+                const int y = (val >> 16) & 0xFFFF;
+
+                const float rad = ::sqrtf((cx - x) * (cx - x) + (cy - y) * (cy - y));
+                if (rad >= minRadius && rad <= maxRadius)
+                {
+                    const int r = __float2int_rn(rad - minRadius);
+
+                    Emulation::smem::atomicAdd(&smem[r + 1], 1);
+                }
+            }
+
+            __syncthreads();
+
+            for (int i = threadIdx.x; i < histSize; i += blockDim.x)
+            {
+                const int curVotes = smem[i + 1];
+
+                if (curVotes >= threshold && curVotes > smem[i] && curVotes >= smem[i + 2])
+                {
+                    const int ind = ::atomicAdd(&g_counter, 1);
+                    if (ind < maxCircles)
+                        circles[ind] = make_float3(cx, cy, i + minRadius);
+                }
+            }
+        }
+
+        int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
+                                   float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20)
+        {
+            void* counterPtr;
+            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
+
+            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
+
+            const dim3 block(has20 ? 1024 : 512);
+            const dim3 grid(centersCount);
+
+            const int histSize = maxRadius - minRadius + 1;
+            size_t smemSize = (histSize + 2) * sizeof(int);
+
+            circlesAccumRadius<<<grid, block, smemSize>>>(centers, list, count, circles, maxCircles, dp, minRadius, maxRadius, histSize, threshold);
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+
+            int totalCount;
+            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
+
+            totalCount = ::min(totalCount, maxCircles);
+
+            return totalCount;
+        }
+    }
+}}}
+
+#endif /* CUDA_DISABLER */

modules/gpu/src/cuda/hough_lines.cu

@@ -0,0 +1,212 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#if !defined CUDA_DISABLER
+
+#include <thrust/device_ptr.h>
+#include <thrust/sort.h>
+
+#include "opencv2/gpu/device/common.hpp"
+#include "opencv2/gpu/device/emulation.hpp"
+#include "opencv2/gpu/device/dynamic_smem.hpp"
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        __device__ static int g_counter;
+
+        ////////////////////////////////////////////////////////////////////////
+        // linesAccum
+
+        __global__ void linesAccumGlobal(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
+        {
+            const int n = blockIdx.x;
+            const float ang = n * theta;
+
+            float sinVal;
+            float cosVal;
+            sincosf(ang, &sinVal, &cosVal);
+            sinVal *= irho;
+            cosVal *= irho;
+
+            const int shift = (numrho - 1) / 2;
+
+            int* accumRow = accum.ptr(n + 1);
+            for (int i = threadIdx.x; i < count; i += blockDim.x)
+            {
+                const unsigned int val = list[i];
+
+                const int x = (val & 0xFFFF);
+                const int y = (val >> 16) & 0xFFFF;
+
+                int r = __float2int_rn(x * cosVal + y * sinVal);
+                r += shift;
+
+                ::atomicAdd(accumRow + r + 1, 1);
+            }
+        }
+
+        __global__ void linesAccumShared(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
+        {
+            int* smem = DynamicSharedMem<int>();
+
+            for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
+                smem[i] = 0;
+
+            __syncthreads();
+
+            const int n = blockIdx.x;
+            const float ang = n * theta;
+
+            float sinVal;
+            float cosVal;
+            sincosf(ang, &sinVal, &cosVal);
+            sinVal *= irho;
+            cosVal *= irho;
+
+            const int shift = (numrho - 1) / 2;
+
+            for (int i = threadIdx.x; i < count; i += blockDim.x)
+            {
+                const unsigned int val = list[i];
+
+                const int x = (val & 0xFFFF);
+                const int y = (val >> 16) & 0xFFFF;
+
+                int r = __float2int_rn(x * cosVal + y * sinVal);
+                r += shift;
+
+                Emulation::smem::atomicAdd(&smem[r + 1], 1);
+            }
+
+            __syncthreads();
+
+            int* accumRow = accum.ptr(n + 1);
+            for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
+                accumRow[i] = smem[i];
+        }
+
+        void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20)
+        {
+            const dim3 block(has20 ? 1024 : 512);
+            const dim3 grid(accum.rows - 2);
+
+            size_t smemSize = (accum.cols - 1) * sizeof(int);
+
+            if (smemSize < sharedMemPerBlock - 1000)
+                linesAccumShared<<<grid, block, smemSize>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
+            else
+                linesAccumGlobal<<<grid, block>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
+
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+
+        ////////////////////////////////////////////////////////////////////////
+        // linesGetResult
+
+        __global__ void linesGetResult(const PtrStepSzi accum, float2* out, int* votes, const int maxSize, const float rho, const float theta, const int threshold, const int numrho)
+        {
+            const int r = blockIdx.x * blockDim.x + threadIdx.x;
+            const int n = blockIdx.y * blockDim.y + threadIdx.y;
+
+            if (r >= accum.cols - 2 || n >= accum.rows - 2)
+                return;
+
+            const int curVotes = accum(n + 1, r + 1);
+
+            if (curVotes > threshold &&
+                curVotes >  accum(n + 1, r) &&
+                curVotes >= accum(n + 1, r + 2) &&
+                curVotes >  accum(n, r + 1) &&
+                curVotes >= accum(n + 2, r + 1))
+            {
+                const float radius = (r - (numrho - 1) * 0.5f) * rho;
+                const float angle = n * theta;
+
+                const int ind = ::atomicAdd(&g_counter, 1);
+                if (ind < maxSize)
+                {
+                    out[ind] = make_float2(radius, angle);
+                    votes[ind] = curVotes;
+                }
+            }
+        }
+
+        int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort)
+        {
+            void* counterPtr;
+            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
+
+            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
+
+            const dim3 block(32, 8);
+            const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
+
+            cudaSafeCall( cudaFuncSetCacheConfig(linesGetResult, cudaFuncCachePreferL1) );
+
+            linesGetResult<<<grid, block>>>(accum, out, votes, maxSize, rho, theta, threshold, accum.cols - 2);
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+
+            int totalCount;
+            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
+
+            totalCount = ::min(totalCount, maxSize);
+
+            if (doSort && totalCount > 0)
+            {
+                thrust::device_ptr<float2> outPtr(out);
+                thrust::device_ptr<int> votesPtr(votes);
+                thrust::sort_by_key(votesPtr, votesPtr + totalCount, outPtr, thrust::greater<int>());
+            }
+
+            return totalCount;
+        }
+    }
+}}}
+
+
+#endif /* CUDA_DISABLER */

modules/gpu/src/cuda/hough_segments.cu

@@ -0,0 +1,249 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#if !defined CUDA_DISABLER
+
+#include "opencv2/gpu/device/common.hpp"
+#include "opencv2/gpu/device/vec_math.hpp"
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        __device__ int g_counter;
+
+        texture<uchar, cudaTextureType2D, cudaReadModeElementType> tex_mask(false, cudaFilterModePoint, cudaAddressModeClamp);
+
+        __global__ void houghLinesProbabilistic(const PtrStepSzi accum,
+                                                int4* out, const int maxSize,
+                                                const float rho, const float theta,
+                                                const int lineGap, const int lineLength,
+                                                const int rows, const int cols)
+        {
+            const int r = blockIdx.x * blockDim.x + threadIdx.x;
+            const int n = blockIdx.y * blockDim.y + threadIdx.y;
+
+            if (r >= accum.cols - 2 || n >= accum.rows - 2)
+                return;
+
+            const int curVotes = accum(n + 1, r + 1);
+
+            if (curVotes >= lineLength &&
+                curVotes > accum(n, r) &&
+                curVotes > accum(n, r + 1) &&
+                curVotes > accum(n, r + 2) &&
+                curVotes > accum(n + 1, r) &&
+                curVotes > accum(n + 1, r + 2) &&
+                curVotes > accum(n + 2, r) &&
+                curVotes > accum(n + 2, r + 1) &&
+                curVotes > accum(n + 2, r + 2))
+            {
+                const float radius = (r - (accum.cols - 2 - 1) * 0.5f) * rho;
+                const float angle = n * theta;
+
+                float cosa;
+                float sina;
+                sincosf(angle, &sina, &cosa);
+
+                float2 p0 = make_float2(cosa * radius, sina * radius);
+                float2 dir = make_float2(-sina, cosa);
+
+                float2 pb[4] = {make_float2(-1, -1), make_float2(-1, -1), make_float2(-1, -1), make_float2(-1, -1)};
+                float a;
+
+                if (dir.x != 0)
+                {
+                    a = -p0.x / dir.x;
+                    pb[0].x = 0;
+                    pb[0].y = p0.y + a * dir.y;
+
+                    a = (cols - 1 - p0.x) / dir.x;
+                    pb[1].x = cols - 1;
+                    pb[1].y = p0.y + a * dir.y;
+                }
+                if (dir.y != 0)
+                {
+                    a = -p0.y / dir.y;
+                    pb[2].x = p0.x + a * dir.x;
+                    pb[2].y = 0;
+
+                    a = (rows - 1 - p0.y) / dir.y;
+                    pb[3].x = p0.x + a * dir.x;
+                    pb[3].y = rows - 1;
+                }
+
+                if (pb[0].x == 0 && (pb[0].y >= 0 && pb[0].y < rows))
+                {
+                    p0 = pb[0];
+                    if (dir.x < 0)
+                        dir = -dir;
+                }
+                else if (pb[1].x == cols - 1 && (pb[0].y >= 0 && pb[0].y < rows))
+                {
+                    p0 = pb[1];
+                    if (dir.x > 0)
+                        dir = -dir;
+                }
+                else if (pb[2].y == 0 && (pb[2].x >= 0 && pb[2].x < cols))
+                {
+                    p0 = pb[2];
+                    if (dir.y < 0)
+                        dir = -dir;
+                }
+                else if (pb[3].y == rows - 1 && (pb[3].x >= 0 && pb[3].x < cols))
+                {
+                    p0 = pb[3];
+                    if (dir.y > 0)
+                        dir = -dir;
+                }
+
+                float2 d;
+                if (::fabsf(dir.x) > ::fabsf(dir.y))
+                {
+                    d.x = dir.x > 0 ? 1 : -1;
+                    d.y = dir.y / ::fabsf(dir.x);
+                }
+                else
+                {
+                    d.x = dir.x / ::fabsf(dir.y);
+                    d.y = dir.y > 0 ? 1 : -1;
+                }
+
+                float2 line_end[2];
+                int gap;
+                bool inLine = false;
+
+                float2 p1 = p0;
+                if (p1.x < 0 || p1.x >= cols || p1.y < 0 || p1.y >= rows)
+                    return;
+
+                for (;;)
+                {
+                    if (tex2D(tex_mask, p1.x, p1.y))
+                    {
+                        gap = 0;
+
+                        if (!inLine)
+                        {
+                            line_end[0] = p1;
+                            line_end[1] = p1;
+                            inLine = true;
+                        }
+                        else
+                        {
+                            line_end[1] = p1;
+                        }
+                    }
+                    else if (inLine)
+                    {
+                        if (++gap > lineGap)
+                        {
+                            bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
+                                             ::abs(line_end[1].y - line_end[0].y) >= lineLength;
+
+                            if (good_line)
+                            {
+                                const int ind = ::atomicAdd(&g_counter, 1);
+                                if (ind < maxSize)
+                                    out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
+                            }
+
+                            gap = 0;
+                            inLine = false;
+                        }
+                    }
+
+                    p1 = p1 + d;
+                    if (p1.x < 0 || p1.x >= cols || p1.y < 0 || p1.y >= rows)
+                    {
+                        if (inLine)
+                        {
+                            bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
+                                             ::abs(line_end[1].y - line_end[0].y) >= lineLength;
+
+                            if (good_line)
+                            {
+                                const int ind = ::atomicAdd(&g_counter, 1);
+                                if (ind < maxSize)
+                                    out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
+                            }
+
+                        }
+                        break;
+                    }
+                }
+            }
+        }
+
+        int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi accum, int4* out, int maxSize, float rho, float theta, int lineGap, int lineLength)
+        {
+            void* counterPtr;
+            cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
+
+            cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
+
+            const dim3 block(32, 8);
+            const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
+
+            bindTexture(&tex_mask, mask);
+
+            houghLinesProbabilistic<<<grid, block>>>(accum,
+                                                     out, maxSize,
+                                                     rho, theta,
+                                                     lineGap, lineLength,
+                                                     mask.rows, mask.cols);
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+
+            int totalCount;
+            cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
+
+            totalCount = ::min(totalCount, maxSize);
+
+            return totalCount;
+        }
+    }
+}}}
+
+
+#endif /* CUDA_DISABLER */

modules/gpu/src/generalized_hough.cpp

@@ -40,6 +40,8 @@
 //
 //M*/
 
+#define CUDA_DISABLER
+
 #include "precomp.hpp"
 
 using namespace std;
@@ -48,16 +50,6 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
 
-void cv::gpu::HoughLines(const GpuMat&, GpuMat&, float, float, int, bool, int) { throw_nogpu(); }
-void cv::gpu::HoughLines(const GpuMat&, GpuMat&, HoughLinesBuf&, float, float, int, bool, int) { throw_nogpu(); }
-void cv::gpu::HoughLinesDownload(const GpuMat&, OutputArray, OutputArray) { throw_nogpu(); }
-
-void cv::gpu::HoughLinesP(const GpuMat&, GpuMat&, HoughLinesBuf&, float, float, int, int, int) { throw_nogpu(); }
-
-void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
-void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, HoughCirclesBuf&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
-void cv::gpu::HoughCirclesDownload(const GpuMat&, OutputArray) { throw_nogpu(); }
-
 Ptr<GeneralizedHough_GPU> cv::gpu::GeneralizedHough_GPU::create(int) { throw_nogpu(); return Ptr<GeneralizedHough_GPU>(); }
 cv::gpu::GeneralizedHough_GPU::~GeneralizedHough_GPU() {}
 void cv::gpu::GeneralizedHough_GPU::setTemplate(const GpuMat&, int, Point) { throw_nogpu(); }
@@ -77,299 +69,6 @@ namespace cv { namespace gpu { namespace device
     }
 }}}
 
-//////////////////////////////////////////////////////////
-// HoughLines
-
-namespace cv { namespace gpu { namespace device
-{
-    namespace hough
-    {
-        void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20);
-        int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort);
-    }
-}}}
-
-void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, float rho, float theta, int threshold, bool doSort, int maxLines)
-{
-    HoughLinesBuf buf;
-    HoughLines(src, lines, buf, rho, theta, threshold, doSort, maxLines);
-}
-
-void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort, int maxLines)
-{
-    using namespace cv::gpu::device::hough;
-
-    CV_Assert(src.type() == CV_8UC1);
-    CV_Assert(src.cols < std::numeric_limits<unsigned short>::max());
-    CV_Assert(src.rows < std::numeric_limits<unsigned short>::max());
-
-    ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.list);
-    unsigned int* srcPoints = buf.list.ptr<unsigned int>();
-
-    const int pointsCount = buildPointList_gpu(src, srcPoints);
-    if (pointsCount == 0)
-    {
-        lines.release();
-        return;
-    }
-
-    const int numangle = cvRound(CV_PI / theta);
-    const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
-    CV_Assert(numangle > 0 && numrho > 0);
-
-    ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, buf.accum);
-    buf.accum.setTo(Scalar::all(0));
-
-    DeviceInfo devInfo;
-    linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
-
-    ensureSizeIsEnough(2, maxLines, CV_32FC2, lines);
-
-    int linesCount = linesGetResult_gpu(buf.accum, lines.ptr<float2>(0), lines.ptr<int>(1), maxLines, rho, theta, threshold, doSort);
-    if (linesCount > 0)
-        lines.cols = linesCount;
-    else
-        lines.release();
-}
-
-void cv::gpu::HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines_, OutputArray h_votes_)
-{
-    if (d_lines.empty())
-    {
-        h_lines_.release();
-        if (h_votes_.needed())
-            h_votes_.release();
-        return;
-    }
-
-    CV_Assert(d_lines.rows == 2 && d_lines.type() == CV_32FC2);
-
-    h_lines_.create(1, d_lines.cols, CV_32FC2);
-    Mat h_lines = h_lines_.getMat();
-    d_lines.row(0).download(h_lines);
-
-    if (h_votes_.needed())
-    {
-        h_votes_.create(1, d_lines.cols, CV_32SC1);
-        Mat h_votes = h_votes_.getMat();
-        GpuMat d_votes(1, d_lines.cols, CV_32SC1, const_cast<int*>(d_lines.ptr<int>(1)));
-        d_votes.download(h_votes);
-    }
-}
-
-//////////////////////////////////////////////////////////
-// HoughLinesP
-
-namespace cv { namespace gpu { namespace device
-{
-    namespace hough
-    {
-        int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi accum, int4* out, int maxSize, float rho, float theta, int lineGap, int lineLength);
-    }
-}}}
-
-void cv::gpu::HoughLinesP(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int minLineLength, int maxLineGap, int maxLines)
-{
-    using namespace cv::gpu::device::hough;
-
-    CV_Assert( src.type() == CV_8UC1 );
-    CV_Assert( src.cols < std::numeric_limits<unsigned short>::max() );
-    CV_Assert( src.rows < std::numeric_limits<unsigned short>::max() );
-
-    ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.list);
-    unsigned int* srcPoints = buf.list.ptr<unsigned int>();
-
-    const int pointsCount = buildPointList_gpu(src, srcPoints);
-    if (pointsCount == 0)
-    {
-        lines.release();
-        return;
-    }
-
-    const int numangle = cvRound(CV_PI / theta);
-    const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
-    CV_Assert( numangle > 0 && numrho > 0 );
-
-    ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, buf.accum);
-    buf.accum.setTo(Scalar::all(0));
-
-    DeviceInfo devInfo;
-    linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
-
-    ensureSizeIsEnough(1, maxLines, CV_32SC4, lines);
-
-    int linesCount = houghLinesProbabilistic_gpu(src, buf.accum, lines.ptr<int4>(), maxLines, rho, theta, maxLineGap, minLineLength);
-
-    if (linesCount > 0)
-        lines.cols = linesCount;
-    else
-        lines.release();
-}
-
-//////////////////////////////////////////////////////////
-// HoughCircles
-
-namespace cv { namespace gpu { namespace device
-{
-    namespace hough
-    {
-        void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp);
-        int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold);
-        int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
-                                   float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20);
-    }
-}}}
-
-void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
-{
-    HoughCirclesBuf buf;
-    HoughCircles(src, circles, buf, method, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius, maxCircles);
-}
-
-void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method,
-                           float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
-{
-    using namespace cv::gpu::device::hough;
-
-    CV_Assert(src.type() == CV_8UC1);
-    CV_Assert(src.cols < std::numeric_limits<unsigned short>::max());
-    CV_Assert(src.rows < std::numeric_limits<unsigned short>::max());
-    CV_Assert(method == CV_HOUGH_GRADIENT);
-    CV_Assert(dp > 0);
-    CV_Assert(minRadius > 0 && maxRadius > minRadius);
-    CV_Assert(cannyThreshold > 0);
-    CV_Assert(votesThreshold > 0);
-    CV_Assert(maxCircles > 0);
-
-    const float idp = 1.0f / dp;
-
-    cv::gpu::Canny(src, buf.cannyBuf, buf.edges, std::max(cannyThreshold / 2, 1), cannyThreshold);
-
-    ensureSizeIsEnough(2, src.size().area(), CV_32SC1, buf.list);
-    unsigned int* srcPoints = buf.list.ptr<unsigned int>(0);
-    unsigned int* centers = buf.list.ptr<unsigned int>(1);
-
-    const int pointsCount = buildPointList_gpu(buf.edges, srcPoints);
-    if (pointsCount == 0)
-    {
-        circles.release();
-        return;
-    }
-
-    ensureSizeIsEnough(cvCeil(src.rows * idp) + 2, cvCeil(src.cols * idp) + 2, CV_32SC1, buf.accum);
-    buf.accum.setTo(Scalar::all(0));
-
-    circlesAccumCenters_gpu(srcPoints, pointsCount, buf.cannyBuf.dx, buf.cannyBuf.dy, buf.accum, minRadius, maxRadius, idp);
-
-    int centersCount = buildCentersList_gpu(buf.accum, centers, votesThreshold);
-    if (centersCount == 0)
-    {
-        circles.release();
-        return;
-    }
-
-    if (minDist > 1)
-    {
-        cv::AutoBuffer<ushort2> oldBuf_(centersCount);
-        cv::AutoBuffer<ushort2> newBuf_(centersCount);
-        int newCount = 0;
-
-        ushort2* oldBuf = oldBuf_;
-        ushort2* newBuf = newBuf_;
-
-        cudaSafeCall( cudaMemcpy(oldBuf, centers, centersCount * sizeof(ushort2), cudaMemcpyDeviceToHost) );
-
-        const int cellSize = cvRound(minDist);
-        const int gridWidth = (src.cols + cellSize - 1) / cellSize;
-        const int gridHeight = (src.rows + cellSize - 1) / cellSize;
-
-        std::vector< std::vector<ushort2> > grid(gridWidth * gridHeight);
-
-        const float minDist2 = minDist * minDist;
-
-        for (int i = 0; i < centersCount; ++i)
-        {
-            ushort2 p = oldBuf[i];
-
-            bool good = true;
-
-            int xCell = static_cast<int>(p.x / cellSize);
-            int yCell = static_cast<int>(p.y / cellSize);
-
-            int x1 = xCell - 1;
-            int y1 = yCell - 1;
-            int x2 = xCell + 1;
-            int y2 = yCell + 1;
-
-            // boundary check
-            x1 = std::max(0, x1);
-            y1 = std::max(0, y1);
-            x2 = std::min(gridWidth - 1, x2);
-            y2 = std::min(gridHeight - 1, y2);
-
-            for (int yy = y1; yy <= y2; ++yy)
-            {
-                for (int xx = x1; xx <= x2; ++xx)
-                {
-                    vector<ushort2>& m = grid[yy * gridWidth + xx];
-
-                    for(size_t j = 0; j < m.size(); ++j)
-                    {
-                        float dx = (float)(p.x - m[j].x);
-                        float dy = (float)(p.y - m[j].y);
-
-                        if (dx * dx + dy * dy < minDist2)
-                        {
-                            good = false;
-                            goto break_out;
-                        }
-                    }
-                }
-            }
-
-            break_out:
-
-            if(good)
-            {
-                grid[yCell * gridWidth + xCell].push_back(p);
-
-                newBuf[newCount++] = p;
-            }
-        }
-
-        cudaSafeCall( cudaMemcpy(centers, newBuf, newCount * sizeof(unsigned int), cudaMemcpyHostToDevice) );
-        centersCount = newCount;
-    }
-
-    ensureSizeIsEnough(1, maxCircles, CV_32FC3, circles);
-
-    const int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, circles.ptr<float3>(), maxCircles,
-                                                    dp, minRadius, maxRadius, votesThreshold, deviceSupports(FEATURE_SET_COMPUTE_20));
-
-    if (circlesCount > 0)
-        circles.cols = circlesCount;
-    else
-        circles.release();
-}
-
-void cv::gpu::HoughCirclesDownload(const GpuMat& d_circles, cv::OutputArray h_circles_)
-{
-    if (d_circles.empty())
-    {
-        h_circles_.release();
-        return;
-    }
-
-    CV_Assert(d_circles.rows == 1 && d_circles.type() == CV_32FC3);
-
-    h_circles_.create(1, d_circles.cols, CV_32FC3);
-    Mat h_circles = h_circles_.getMat();
-    d_circles.download(h_circles);
-}
-
-//////////////////////////////////////////////////////////
-// GeneralizedHough
-
 namespace cv { namespace gpu { namespace device
 {
     namespace hough

modules/gpu/src/hough_circles.cpp

@@ -0,0 +1,223 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace cv::gpu;
+
+#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
+
+void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
+void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, HoughCirclesBuf&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
+void cv::gpu::HoughCirclesDownload(const GpuMat&, OutputArray) { throw_nogpu(); }
+
+#else /* !defined (HAVE_CUDA) */
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        int buildPointList_gpu(PtrStepSzb src, unsigned int* list);
+    }
+}}}
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp);
+        int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold);
+        int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
+                                   float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20);
+    }
+}}}
+
+void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
+{
+    HoughCirclesBuf buf;
+    HoughCircles(src, circles, buf, method, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius, maxCircles);
+}
+
+void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method,
+                           float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
+{
+    using namespace cv::gpu::device::hough;
+
+    CV_Assert(src.type() == CV_8UC1);
+    CV_Assert(src.cols < std::numeric_limits<unsigned short>::max());
+    CV_Assert(src.rows < std::numeric_limits<unsigned short>::max());
+    CV_Assert(method == CV_HOUGH_GRADIENT);
+    CV_Assert(dp > 0);
+    CV_Assert(minRadius > 0 && maxRadius > minRadius);
+    CV_Assert(cannyThreshold > 0);
+    CV_Assert(votesThreshold > 0);
+    CV_Assert(maxCircles > 0);
+
+    const float idp = 1.0f / dp;
+
+    cv::gpu::Canny(src, buf.cannyBuf, buf.edges, std::max(cannyThreshold / 2, 1), cannyThreshold);
+
+    ensureSizeIsEnough(2, src.size().area(), CV_32SC1, buf.list);
+    unsigned int* srcPoints = buf.list.ptr<unsigned int>(0);
+    unsigned int* centers = buf.list.ptr<unsigned int>(1);
+
+    const int pointsCount = buildPointList_gpu(buf.edges, srcPoints);
+    if (pointsCount == 0)
+    {
+        circles.release();
+        return;
+    }
+
+    ensureSizeIsEnough(cvCeil(src.rows * idp) + 2, cvCeil(src.cols * idp) + 2, CV_32SC1, buf.accum);
+    buf.accum.setTo(Scalar::all(0));
+
+    circlesAccumCenters_gpu(srcPoints, pointsCount, buf.cannyBuf.dx, buf.cannyBuf.dy, buf.accum, minRadius, maxRadius, idp);
+
+    int centersCount = buildCentersList_gpu(buf.accum, centers, votesThreshold);
+    if (centersCount == 0)
+    {
+        circles.release();
+        return;
+    }
+
+    if (minDist > 1)
+    {
+        cv::AutoBuffer<ushort2> oldBuf_(centersCount);
+        cv::AutoBuffer<ushort2> newBuf_(centersCount);
+        int newCount = 0;
+
+        ushort2* oldBuf = oldBuf_;
+        ushort2* newBuf = newBuf_;
+
+        cudaSafeCall( cudaMemcpy(oldBuf, centers, centersCount * sizeof(ushort2), cudaMemcpyDeviceToHost) );
+
+        const int cellSize = cvRound(minDist);
+        const int gridWidth = (src.cols + cellSize - 1) / cellSize;
+        const int gridHeight = (src.rows + cellSize - 1) / cellSize;
+
+        std::vector< std::vector<ushort2> > grid(gridWidth * gridHeight);
+
+        const float minDist2 = minDist * minDist;
+
+        for (int i = 0; i < centersCount; ++i)
+        {
+            ushort2 p = oldBuf[i];
+
+            bool good = true;
+
+            int xCell = static_cast<int>(p.x / cellSize);
+            int yCell = static_cast<int>(p.y / cellSize);
+
+            int x1 = xCell - 1;
+            int y1 = yCell - 1;
+            int x2 = xCell + 1;
+            int y2 = yCell + 1;
+
+            // boundary check
+            x1 = std::max(0, x1);
+            y1 = std::max(0, y1);
+            x2 = std::min(gridWidth - 1, x2);
+            y2 = std::min(gridHeight - 1, y2);
+
+            for (int yy = y1; yy <= y2; ++yy)
+            {
+                for (int xx = x1; xx <= x2; ++xx)
+                {
+                    vector<ushort2>& m = grid[yy * gridWidth + xx];
+
+                    for(size_t j = 0; j < m.size(); ++j)
+                    {
+                        float dx = (float)(p.x - m[j].x);
+                        float dy = (float)(p.y - m[j].y);
+
+                        if (dx * dx + dy * dy < minDist2)
+                        {
+                            good = false;
+                            goto break_out;
+                        }
+                    }
+                }
+            }
+
+            break_out:
+
+            if(good)
+            {
+                grid[yCell * gridWidth + xCell].push_back(p);
+
+                newBuf[newCount++] = p;
+            }
+        }
+
+        cudaSafeCall( cudaMemcpy(centers, newBuf, newCount * sizeof(unsigned int), cudaMemcpyHostToDevice) );
+        centersCount = newCount;
+    }
+
+    ensureSizeIsEnough(1, maxCircles, CV_32FC3, circles);
+
+    const int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, circles.ptr<float3>(), maxCircles,
+                                                    dp, minRadius, maxRadius, votesThreshold, deviceSupports(FEATURE_SET_COMPUTE_20));
+
+    if (circlesCount > 0)
+        circles.cols = circlesCount;
+    else
+        circles.release();
+}
+
+void cv::gpu::HoughCirclesDownload(const GpuMat& d_circles, cv::OutputArray h_circles_)
+{
+    if (d_circles.empty())
+    {
+        h_circles_.release();
+        return;
+    }
+
+    CV_Assert(d_circles.rows == 1 && d_circles.type() == CV_32FC3);
+
+    h_circles_.create(1, d_circles.cols, CV_32FC3);
+    Mat h_circles = h_circles_.getMat();
+    d_circles.download(h_circles);
+}
+
+#endif /* !defined (HAVE_CUDA) */

modules/gpu/src/hough_lines.cpp

@@ -0,0 +1,142 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace cv::gpu;
+
+#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
+
+void cv::gpu::HoughLines(const GpuMat&, GpuMat&, float, float, int, bool, int) { throw_nogpu(); }
+void cv::gpu::HoughLines(const GpuMat&, GpuMat&, HoughLinesBuf&, float, float, int, bool, int) { throw_nogpu(); }
+void cv::gpu::HoughLinesDownload(const GpuMat&, OutputArray, OutputArray) { throw_nogpu(); }
+
+#else /* !defined (HAVE_CUDA) */
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        int buildPointList_gpu(PtrStepSzb src, unsigned int* list);
+    }
+}}}
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20);
+        int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort);
+    }
+}}}
+
+void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, float rho, float theta, int threshold, bool doSort, int maxLines)
+{
+    HoughLinesBuf buf;
+    HoughLines(src, lines, buf, rho, theta, threshold, doSort, maxLines);
+}
+
+void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort, int maxLines)
+{
+    using namespace cv::gpu::device::hough;
+
+    CV_Assert(src.type() == CV_8UC1);
+    CV_Assert(src.cols < std::numeric_limits<unsigned short>::max());
+    CV_Assert(src.rows < std::numeric_limits<unsigned short>::max());
+
+    ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.list);
+    unsigned int* srcPoints = buf.list.ptr<unsigned int>();
+
+    const int pointsCount = buildPointList_gpu(src, srcPoints);
+    if (pointsCount == 0)
+    {
+        lines.release();
+        return;
+    }
+
+    const int numangle = cvRound(CV_PI / theta);
+    const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
+    CV_Assert(numangle > 0 && numrho > 0);
+
+    ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, buf.accum);
+    buf.accum.setTo(Scalar::all(0));
+
+    DeviceInfo devInfo;
+    linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
+
+    ensureSizeIsEnough(2, maxLines, CV_32FC2, lines);
+
+    int linesCount = linesGetResult_gpu(buf.accum, lines.ptr<float2>(0), lines.ptr<int>(1), maxLines, rho, theta, threshold, doSort);
+    if (linesCount > 0)
+        lines.cols = linesCount;
+    else
+        lines.release();
+}
+
+void cv::gpu::HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines_, OutputArray h_votes_)
+{
+    if (d_lines.empty())
+    {
+        h_lines_.release();
+        if (h_votes_.needed())
+            h_votes_.release();
+        return;
+    }
+
+    CV_Assert(d_lines.rows == 2 && d_lines.type() == CV_32FC2);
+
+    h_lines_.create(1, d_lines.cols, CV_32FC2);
+    Mat h_lines = h_lines_.getMat();
+    d_lines.row(0).download(h_lines);
+
+    if (h_votes_.needed())
+    {
+        h_votes_.create(1, d_lines.cols, CV_32SC1);
+        Mat h_votes = h_votes_.getMat();
+        GpuMat d_votes(1, d_lines.cols, CV_32SC1, const_cast<int*>(d_lines.ptr<int>(1)));
+        d_votes.download(h_votes);
+    }
+}
+
+#endif /* !defined (HAVE_CUDA) */

modules/gpu/src/hough_segments.cpp

@@ -0,0 +1,110 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace cv::gpu;
+
+#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
+
+void cv::gpu::HoughLinesP(const GpuMat&, GpuMat&, HoughLinesBuf&, float, float, int, int, int) { throw_nogpu(); }
+
+#else /* !defined (HAVE_CUDA) */
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        int buildPointList_gpu(PtrStepSzb src, unsigned int* list);
+    }
+}}}
+
+namespace cv { namespace gpu { namespace device
+{
+    namespace hough
+    {
+        void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20);
+        int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi accum, int4* out, int maxSize, float rho, float theta, int lineGap, int lineLength);
+    }
+}}}
+
+void cv::gpu::HoughLinesP(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int minLineLength, int maxLineGap, int maxLines)
+{
+    using namespace cv::gpu::device::hough;
+
+    CV_Assert( src.type() == CV_8UC1 );
+    CV_Assert( src.cols < std::numeric_limits<unsigned short>::max() );
+    CV_Assert( src.rows < std::numeric_limits<unsigned short>::max() );
+
+    ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.list);
+    unsigned int* srcPoints = buf.list.ptr<unsigned int>();
+
+    const int pointsCount = buildPointList_gpu(src, srcPoints);
+    if (pointsCount == 0)
+    {
+        lines.release();
+        return;
+    }
+
+    const int numangle = cvRound(CV_PI / theta);
+    const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
+    CV_Assert( numangle > 0 && numrho > 0 );
+
+    ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, buf.accum);
+    buf.accum.setTo(Scalar::all(0));
+
+    DeviceInfo devInfo;
+    linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
+
+    ensureSizeIsEnough(1, maxLines, CV_32SC4, lines);
+
+    int linesCount = houghLinesProbabilistic_gpu(src, buf.accum, lines.ptr<int4>(), maxLines, rho, theta, maxLineGap, minLineLength);
+
+    if (linesCount > 0)
+        lines.cols = linesCount;
+    else
+        lines.release();
+}
+
+#endif /* !defined (HAVE_CUDA) */

modules/gpu/test/test_hough.cpp

@@ -189,7 +189,7 @@ PARAM_TEST_CASE(GeneralizedHough, cv::gpu::DeviceInfo, UseRoi)
 {
 };
 
-GPU_TEST_P(GeneralizedHough, POSITION)
+GPU_TEST_P(GeneralizedHough, DISABLED_POSITION)
 {
     const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
     cv::gpu::setDevice(devInfo.deviceID());

modules/highgui/CMakeLists.txt

@@ -315,7 +315,7 @@ if(WIN32 AND WITH_FFMPEG)
                        COMMENT "Copying ${ffmpeg_path} to the output directory")
   endif()
 
-  install(FILES "${ffmpeg_path}" DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT main RENAME "${ffmpeg_bare_name_ver}")
+  install(FILES "${ffmpeg_path}" DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT libs RENAME "${ffmpeg_bare_name_ver}")
 endif()
 
 ocv_add_accuracy_tests()

modules/highgui/src/bitstrm.hpp

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

modules/highgui/src/cap_ffmpeg_impl.hpp

@@ -2066,7 +2066,7 @@ enum
     VideoCodec_YV12   = (('Y'<<24)|('V'<<16)|('1'<<8)|('2')),   // Y,V,U (4:2:0)
     VideoCodec_NV12   = (('N'<<24)|('V'<<16)|('1'<<8)|('2')),   // Y,UV  (4:2:0)
     VideoCodec_YUYV   = (('Y'<<24)|('U'<<16)|('Y'<<8)|('V')),   // YUYV/YUY2 (4:2:2)
-    VideoCodec_UYVY   = (('U'<<24)|('Y'<<16)|('V'<<8)|('Y')),   // UYVY (4:2:2)
+    VideoCodec_UYVY   = (('U'<<24)|('Y'<<16)|('V'<<8)|('Y'))    // UYVY (4:2:2)
 };
 
 enum
@@ -2074,7 +2074,7 @@ enum
     VideoChromaFormat_Monochrome = 0,
     VideoChromaFormat_YUV420,
     VideoChromaFormat_YUV422,
-    VideoChromaFormat_YUV444,
+    VideoChromaFormat_YUV444
 };
 
 struct InputMediaStream_FFMPEG

modules/highgui/src/precomp.hpp

@@ -57,6 +57,14 @@
 #include <assert.h>
 
 #if defined WIN32 || defined WINCE
+    #if !defined _WIN32_WINNT
+        #ifdef HAVE_MSMF
+            #define _WIN32_WINNT 0x0600 // Windows Vista
+        #else
+            #define _WIN32_WINNT 0x0500 // Windows 2000
+        #endif
+    #endif
+
     #include <windows.h>
     #undef small
     #undef min

modules/highgui/src/window_w32.cpp

@@ -43,27 +43,11 @@
 
 #if defined WIN32 || defined _WIN32
 
-#define COMPILE_MULTIMON_STUBS // Required for multi-monitor support
-#ifndef _MULTIMON_USE_SECURE_CRT
-#  define _MULTIMON_USE_SECURE_CRT 0 // some MinGW platforms have no strncpy_s
-#endif
-
-#if defined SM_CMONITORS && !defined MONITOR_DEFAULTTONEAREST
-#  define MONITOR_DEFAULTTONULL       0x00000000
-#  define MONITOR_DEFAULTTOPRIMARY    0x00000001
-#  define MONITOR_DEFAULTTONEAREST    0x00000002
-#  define MONITORINFOF_PRIMARY        0x00000001
-#endif
-#ifndef __inout
-#  define __inout
-#endif
-
 #ifdef __GNUC__
 #  pragma GCC diagnostic ignored "-Wmissing-declarations"
 #endif
 
 #include <commctrl.h>
-#include <winuser.h>
 #include <stdlib.h>
 #include <string.h>
 #include <stdio.h>

modules/imgproc/doc/miscellaneous_transformations.rst

@@ -113,6 +113,8 @@ But in case of a non-linear transformation, an input RGB image should be normali
 
 If you use ``cvtColor`` with 8-bit images, the conversion will have some information lost. For many applications, this will not be noticeable but it is recommended to use 32-bit images in applications that need the full range of colors or that convert an image before an operation and then convert back.
 
+If conversion adds the alpha channel, its value will set to the maximum of corresponding channel range: 255 for ``CV_8U``, 65535 for ``CV_16U``, 1 for ``CV_32F``.
+
 The function can do the following transformations:
 
 *
@@ -127,7 +129,7 @@ The function can do the following transformations:
 
     .. math::
 
-        \text{Gray to RGB[A]:} \quad R  \leftarrow Y, G  \leftarrow Y, B  \leftarrow Y, A  \leftarrow 0
+        \text{Gray to RGB[A]:} \quad R  \leftarrow Y, G  \leftarrow Y, B  \leftarrow Y, A  \leftarrow \max (ChannelRange)
 
     The conversion from a RGB image to gray is done with:
 

modules/imgproc/perf/perf_filter2d.cpp

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

modules/imgproc/src/gcgraph.hpp

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

modules/imgproc/src/generalized_hough.cpp

@@ -300,7 +300,7 @@ namespace
                       obj.info()->addParam(obj, "votesThreshold", obj.votesThreshold, false, 0, 0,
                                            "The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected.");
                       obj.info()->addParam(obj, "dp", obj.dp, false, 0, 0,
-                                           "Inverse ratio of the accumulator resolution to the image resolution."));
+                                           "Inverse ratio of the accumulator resolution to the image resolution."))
 
     GHT_Ballard_Pos::GHT_Ballard_Pos()
     {
@@ -466,7 +466,7 @@ namespace
                       obj.info()->addParam(obj, "maxScale", obj.maxScale, false, 0, 0,
                                            "Maximal scale to detect.");
                       obj.info()->addParam(obj, "scaleStep", obj.scaleStep, false, 0, 0,
-                                           "Scale step."));
+                                           "Scale step."))
 
     GHT_Ballard_PosScale::GHT_Ballard_PosScale()
     {
@@ -631,7 +631,7 @@ namespace
                       obj.info()->addParam(obj, "maxAngle", obj.maxAngle, false, 0, 0,
                                            "Maximal rotation angle to detect in degrees.");
                       obj.info()->addParam(obj, "angleStep", obj.angleStep, false, 0, 0,
-                                           "Angle step in degrees."));
+                                           "Angle step in degrees."))
 
     GHT_Ballard_PosRotation::GHT_Ballard_PosRotation()
     {
@@ -878,7 +878,7 @@ namespace
                       obj.info()->addParam(obj, "dp", obj.dp, false, 0, 0,
                                            "Inverse ratio of the accumulator resolution to the image resolution.");
                       obj.info()->addParam(obj, "posThresh", obj.posThresh, false, 0, 0,
-                                           "Position threshold."));
+                                           "Position threshold."))
 
     GHT_Guil_Full::GHT_Guil_Full()
     {

modules/imgproc/src/imgwarp.cpp

@@ -2201,15 +2201,15 @@ struct RemapVec_8u
     int operator()( const Mat& _src, void* _dst, const short* XY,
                     const ushort* FXY, const void* _wtab, int width ) const
     {
-        int cn = _src.channels();
+        int cn = _src.channels(), x = 0, sstep = (int)_src.step;
 
-        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) )
+        if( (cn != 1 && cn != 3 && cn != 4) || !checkHardwareSupport(CV_CPU_SSE2) ||
+                sstep > 0x8000 )
             return 0;
 
         const uchar *S0 = _src.data, *S1 = _src.data + _src.step;
         const short* wtab = cn == 1 ? (const short*)_wtab : &BilinearTab_iC4[0][0][0];
         uchar* D = (uchar*)_dst;
-        int x = 0, sstep = (int)_src.step;
         __m128i delta = _mm_set1_epi32(INTER_REMAP_COEF_SCALE/2);
         __m128i xy2ofs = _mm_set1_epi32(cn + (sstep << 16));
         __m128i z = _mm_setzero_si128();

modules/imgproc/src/smooth.cpp

@@ -718,7 +718,7 @@ void cv::boxFilter( InputArray _src, OutputArray _dst, int ddepth,
         ddepth = sdepth;
     _dst.create( src.size(), CV_MAKETYPE(ddepth, cn) );
     Mat dst = _dst.getMat();
-    if( borderType != BORDER_CONSTANT && normalize )
+    if( borderType != BORDER_CONSTANT && normalize && (borderType & BORDER_ISOLATED) != 0 )
     {
         if( src.rows == 1 )
             ksize.height = 1;

modules/imgproc/test/test_cvtyuv.cpp

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

modules/imgproc/test/test_filter.cpp

@@ -1886,3 +1886,35 @@ protected:
 };
 
 TEST(Imgproc_Filtering, supportedFormats) { CV_FilterSupportedFormatsTest test; test.safe_run(); }
+
+TEST(Imgproc_Blur, borderTypes)
+{
+    Size kernelSize(3, 3);
+
+    /// ksize > src_roi.size()
+    Mat src(3, 3, CV_8UC1, cv::Scalar::all(255)), dst;
+    Mat src_roi = src(Rect(1, 1, 1, 1));
+    src_roi.setTo(cv::Scalar::all(0));
+
+    // should work like !BORDER_ISOLATED
+    blur(src_roi, dst, kernelSize, Point(-1, -1), BORDER_REPLICATE);
+    EXPECT_EQ(227, dst.at<uchar>(0, 0));
+
+    // should work like BORDER_ISOLATED
+    blur(src_roi, dst, kernelSize, Point(-1, -1), BORDER_REPLICATE | BORDER_ISOLATED);
+    EXPECT_EQ(0, dst.at<uchar>(0, 0));
+
+    /// ksize <= src_roi.size()
+    src = Mat(5, 5, CV_8UC1, cv::Scalar(255));
+    src_roi = src(Rect(1, 1, 3, 3));
+    src_roi.setTo(0);
+    src.at<uchar>(2, 2) = 255;
+
+    // should work like !BORDER_ISOLATED
+    blur(src_roi, dst, kernelSize, Point(-1, -1), BORDER_REPLICATE);
+    Mat expected_dst =
+            (Mat_<uchar>(3, 3) << 170, 113, 170, 113, 28, 113, 170, 113, 170);
+    EXPECT_EQ(expected_dst.type(), dst.type());
+    EXPECT_EQ(expected_dst.size(), dst.size());
+    EXPECT_DOUBLE_EQ(0.0, cvtest::norm(expected_dst, dst, NORM_INF));
+}

modules/java/CMakeLists.txt

@@ -175,7 +175,7 @@ foreach(java_file ${step3_input_files})
 
   if(ANDROID)
     get_filename_component(install_subdir "${java_file_name}" PATH)
-    install(FILES "${output_name}" DESTINATION "${JAVA_INSTALL_ROOT}/src/org/opencv/${install_subdir}" COMPONENT main)
+    install(FILES "${output_name}" DESTINATION "${JAVA_INSTALL_ROOT}/src/org/opencv/${install_subdir}" COMPONENT java)
   endif()
 endforeach()
 
@@ -189,7 +189,7 @@ if(ANDROID)
 
     if(NOT file MATCHES "jni/.+")
       get_filename_component(install_subdir "${file}" PATH)
-      install(FILES "${OpenCV_BINARY_DIR}/${file}" DESTINATION "${JAVA_INSTALL_ROOT}/${install_subdir}" COMPONENT main)
+      install(FILES "${OpenCV_BINARY_DIR}/${file}" DESTINATION "${JAVA_INSTALL_ROOT}/${install_subdir}" COMPONENT java)
     endif()
   endforeach()
 
@@ -225,11 +225,11 @@ if(ANDROID AND ANDROID_EXECUTABLE)
   list(APPEND copied_files ${lib_target_files} "${OpenCV_BINARY_DIR}/${ANDROID_MANIFEST_FILE}")
   list(APPEND step3_input_files "${CMAKE_CURRENT_BINARY_DIR}/${ANDROID_MANIFEST_FILE}")
 
-  install(FILES "${OpenCV_BINARY_DIR}/${ANDROID_PROJECT_PROPERTIES_FILE}" DESTINATION ${JAVA_INSTALL_ROOT} COMPONENT main)
-  install(FILES "${OpenCV_BINARY_DIR}/${ANDROID_MANIFEST_FILE}" DESTINATION ${JAVA_INSTALL_ROOT} COMPONENT main)
+  install(FILES "${OpenCV_BINARY_DIR}/${ANDROID_PROJECT_PROPERTIES_FILE}" DESTINATION ${JAVA_INSTALL_ROOT} COMPONENT java)
+  install(FILES "${OpenCV_BINARY_DIR}/${ANDROID_MANIFEST_FILE}" DESTINATION ${JAVA_INSTALL_ROOT} COMPONENT java)
   # creating empty 'gen' and 'res' folders
-  install(CODE "MAKE_DIRECTORY(\"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/${JAVA_INSTALL_ROOT}/gen\")" COMPONENT main)
-  install(CODE "MAKE_DIRECTORY(\"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/${JAVA_INSTALL_ROOT}/res\")" COMPONENT main)
+  install(CODE "MAKE_DIRECTORY(\"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/${JAVA_INSTALL_ROOT}/gen\")" COMPONENT java)
+  install(CODE "MAKE_DIRECTORY(\"\$ENV{DESTDIR}\${CMAKE_INSTALL_PREFIX}/${JAVA_INSTALL_ROOT}/res\")" COMPONENT java)
 endif(ANDROID AND ANDROID_EXECUTABLE)
 
 set(step3_depends ${step2_depends} ${step3_input_files} ${copied_files})
@@ -282,7 +282,7 @@ else(ANDROID)
   else(WIN32)
     set(JAR_INSTALL_DIR share/OpenCV/java)
   endif(WIN32)
-  install(FILES ${JAR_FILE} DESTINATION ${JAR_INSTALL_DIR} COMPONENT main)
+  install(FILES ${JAR_FILE} DESTINATION ${JAR_INSTALL_DIR} COMPONENT java)
 endif(ANDROID)
 
 # step 5: build native part
@@ -353,17 +353,17 @@ endif()
 
 if(ANDROID)
   ocv_install_target(${the_module} EXPORT OpenCVModules
-          LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT main
-          ARCHIVE DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT main)
+          LIBRARY DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT java
+          ARCHIVE DESTINATION ${OPENCV_LIB_INSTALL_PATH} COMPONENT java)
 else()
   if(NOT INSTALL_CREATE_DISTRIB)
     ocv_install_target(${the_module} EXPORT OpenCVModules
-            RUNTIME DESTINATION ${JAR_INSTALL_DIR} COMPONENT main
-            LIBRARY DESTINATION ${JAR_INSTALL_DIR} COMPONENT main)
+            RUNTIME DESTINATION ${JAR_INSTALL_DIR} COMPONENT java
+            LIBRARY DESTINATION ${JAR_INSTALL_DIR} COMPONENT java)
   else()
     ocv_install_target(${the_module} EXPORT OpenCVModules
-            RUNTIME DESTINATION ${JAR_INSTALL_DIR}/${OpenCV_ARCH} COMPONENT main
-            LIBRARY DESTINATION ${JAR_INSTALL_DIR}/${OpenCV_ARCH} COMPONENT main)
+            RUNTIME DESTINATION ${JAR_INSTALL_DIR}/${OpenCV_ARCH} COMPONENT java
+            LIBRARY DESTINATION ${JAR_INSTALL_DIR}/${OpenCV_ARCH} COMPONENT java)
   endif()
 endif()
 

modules/java/generator/src/cpp/VideoCapture.cpp

@@ -329,7 +329,10 @@ JNIEXPORT jstring JNICALL Java_org_opencv_highgui_VideoCapture_n_1getSupportedPr
         VideoCapture* me = (VideoCapture*) self; //TODO: check for NULL
         union {double prop; const char* name;} u;
         u.prop = me->get(CV_CAP_PROP_SUPPORTED_PREVIEW_SIZES_STRING);
-        return env->NewStringUTF(u.name);
+        // VideoCapture::get can return 0.0 or -1.0 if it doesn't support
+        // CV_CAP_PROP_SUPPORTED_PREVIEW_SIZES_STRING
+        if (u.prop != 0.0 && u.prop != -1.0)
+            return env->NewStringUTF(u.name);
     } catch(const std::exception &e) {
         throwJavaException(env, &e, method_name);
     } catch (...) {

modules/legacy/src/blobtrack.cpp

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

modules/legacy/src/enteringblobdetection.cpp

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

modules/legacy/src/vecfacetracking.cpp

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

modules/ml/doc/neural_networks.rst

@@ -240,6 +240,7 @@ This method applies the specified training algorithm to computing/adjusting the
 
 The RPROP training algorithm is parallelized with the TBB library.
 
+If you are using the default ``cvANN_MLP::SIGMOID_SYM`` activation function then the output should be in the range [-1,1], instead of [0,1], for optimal results.
 
 CvANN_MLP::predict
 ------------------
@@ -257,6 +258,8 @@ Predicts responses for input samples.
 
 The method returns a dummy value which should be ignored.
 
+If you are using the default ``cvANN_MLP::SIGMOID_SYM`` activation function with the default parameter values fparam1=0 and fparam2=0 then the function used is y = 1.7159*tanh(2/3 * x), so the output will range from [-1.7159, 1.7159], instead of [0,1].
+
 CvANN_MLP::get_layer_count
 --------------------------
 Returns the number of layers in the MLP.

modules/ml/src/ml_init.cpp

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

modules/ml/src/svm.cpp

@@ -2298,14 +2298,24 @@ void CvSVM::write_params( CvFileStorage* fs ) const
 }
 
 
+static bool isSvmModelApplicable(int sv_total, int var_all, int var_count, int class_count)
+{
+    return (sv_total > 0 && var_count > 0 && var_count <= var_all && class_count >= 0);
+}
+
+
 void CvSVM::write( CvFileStorage* fs, const char* name ) const
 {
     CV_FUNCNAME( "CvSVM::write" );
 
     __BEGIN__;
 
-    int i, var_count = get_var_count(), df_count, class_count;
+    int i, var_count = get_var_count(), df_count;
+    int class_count = class_labels ? class_labels->cols :
+                      params.svm_type == CvSVM::ONE_CLASS ? 1 : 0;
     const CvSVMDecisionFunc* df = decision_func;
+    if( !isSvmModelApplicable(sv_total, var_all, var_count, class_count) )
+        CV_ERROR( CV_StsParseError, "SVM model data is invalid, check sv_count, var_* and class_count tags" );
 
     cvStartWriteStruct( fs, name, CV_NODE_MAP, CV_TYPE_NAME_ML_SVM );
 
@@ -2314,9 +2324,6 @@ void CvSVM::write( CvFileStorage* fs, const char* name ) const
     cvWriteInt( fs, "var_all", var_all );
     cvWriteInt( fs, "var_count", var_count );
 
-    class_count = class_labels ? class_labels->cols :
-                  params.svm_type == CvSVM::ONE_CLASS ? 1 : 0;
-
     if( class_count )
     {
         cvWriteInt( fs, "class_count", class_count );
@@ -2454,7 +2461,6 @@ void CvSVM::read_params( CvFileStorage* fs, CvFileNode* svm_node )
     __END__;
 }
 
-
 void CvSVM::read( CvFileStorage* fs, CvFileNode* svm_node )
 {
     const double not_found_dbl = DBL_MAX;
@@ -2483,7 +2489,7 @@ void CvSVM::read( CvFileStorage* fs, CvFileNode* svm_node )
     var_count = cvReadIntByName( fs, svm_node, "var_count", var_all );
     class_count = cvReadIntByName( fs, svm_node, "class_count", 0 );
 
-    if( sv_total <= 0 || var_all <= 0 || var_count <= 0 || var_count > var_all || class_count < 0 )
+    if( !isSvmModelApplicable(sv_total, var_all, var_count, class_count) )
         CV_ERROR( CV_StsParseError, "SVM model data is invalid, check sv_count, var_* and class_count tags" );
 
     CV_CALL( class_labels = (CvMat*)cvReadByName( fs, svm_node, "class_labels" ));

modules/ml/test/test_save_load.cpp

@@ -155,6 +155,14 @@ TEST(ML_RTrees, save_load) { CV_SLMLTest test( CV_RTREES ); test.safe_run(); }
 TEST(ML_ERTrees, save_load) { CV_SLMLTest test( CV_ERTREES ); test.safe_run(); }
 
 
+TEST(ML_SVM, throw_exception_when_save_untrained_model)
+{
+    SVM svm;
+    string filename = tempfile("svm.xml");
+    ASSERT_THROW(svm.save(filename.c_str()), Exception);
+    remove(filename.c_str());
+}
+
 TEST(DISABLED_ML_SVM, linear_save_load)
 {
     CvSVM svm1, svm2, svm3;

modules/nonfree/src/nonfree_init.cpp

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

modules/ocl/include/opencv2/ocl/ocl.hpp

@@ -204,7 +204,7 @@ namespace cv
             CACHE_NONE    = 0,        // do not cache OpenCL binary
             CACHE_DEBUG   = 0x1 << 0, // cache OpenCL binary when built in debug mode
             CACHE_RELEASE = 0x1 << 1, // default behavior, only cache when built in release mode
-            CACHE_ALL     = CACHE_DEBUG | CACHE_RELEASE, // cache opencl binary
+            CACHE_ALL     = CACHE_DEBUG | CACHE_RELEASE // cache opencl binary
         };
         //! Enable or disable OpenCL program binary caching onto local disk
         // After a program (*.cl files in opencl/ folder) is built at runtime, we allow the

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

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

modules/ocl/perf/perf_haar.cpp

@@ -83,3 +83,69 @@ PERF_TEST(HaarFixture, Haar)
     else
         OCL_PERF_ELSE
 }
+
+using namespace std;
+using namespace cv;
+using namespace perf;
+using std::tr1::make_tuple;
+using std::tr1::get;
+
+typedef std::tr1::tuple<std::string, std::string, int> OCL_Cascade_Image_MinSize_t;
+typedef perf::TestBaseWithParam<OCL_Cascade_Image_MinSize_t> OCL_Cascade_Image_MinSize;
+
+PERF_TEST_P( OCL_Cascade_Image_MinSize, CascadeClassifier,
+             testing::Combine(
+                testing::Values( string("cv/cascadeandhog/cascades/haarcascade_frontalface_alt.xml") ),
+                testing::Values( string("cv/shared/lena.png"),
+                                 string("cv/cascadeandhog/images/bttf301.png")/*,
+                                 string("cv/cascadeandhog/images/class57.png")*/ ),
+                testing::Values(30, 64, 90) ) )
+{
+    const string cascasePath = get<0>(GetParam());
+    const string imagePath   = get<1>(GetParam());
+    const int min_size = get<2>(GetParam());
+    Size minSize(min_size, min_size);
+    vector<Rect> faces;
+
+    Mat img = imread(getDataPath(imagePath), IMREAD_GRAYSCALE);
+    ASSERT_TRUE(!img.empty()) << "Can't load source image: " << getDataPath(imagePath);
+    equalizeHist(img, img);
+    declare.in(img);
+
+    if (RUN_PLAIN_IMPL)
+    {
+        CascadeClassifier cc;
+        ASSERT_TRUE(cc.load(getDataPath(cascasePath))) << "Can't load cascade file: " << getDataPath(cascasePath);
+
+        while (next())
+        {
+            faces.clear();
+
+            startTimer();
+            cc.detectMultiScale(img, faces, 1.1, 3, 0, minSize);
+            stopTimer();
+        }
+    }
+    else if (RUN_OCL_IMPL)
+    {
+        ocl::oclMat uimg(img);
+        ocl::OclCascadeClassifier cc;
+        ASSERT_TRUE(cc.load(getDataPath(cascasePath))) << "Can't load cascade file: " << getDataPath(cascasePath);
+
+        while (next())
+        {
+            faces.clear();
+            ocl::finish();
+
+            startTimer();
+            cc.detectMultiScale(uimg, faces, 1.1, 3, 0, minSize);
+            stopTimer();
+        }
+    }
+    else
+        OCL_PERF_ELSE
+
+        //sort(faces.begin(), faces.end(), comparators::RectLess());
+        SANITY_CHECK_NOTHING();//(faces, min_size/5);
+        // using SANITY_CHECK_NOTHING() since OCL and PLAIN version may find different faces number
+}

modules/ocl/src/cl_runtime/cl_runtime.cpp

@@ -45,7 +45,7 @@
     #define CV_CL_GET_PROC_ADDRESS(name) WinGetProcAddress(name)
 #endif // _WIN32
 
-#if defined(linux)
+#if defined(__linux__)
     #include <dlfcn.h>
     #include <stdio.h>
 

modules/ocl/src/cl_runtime/clamdblas_runtime.cpp

@@ -27,7 +27,7 @@
     #define CV_CL_GET_PROC_ADDRESS(name) WinGetProcAddress(name)
 #endif // _WIN32
 
-#if defined(linux)
+#if defined(__linux__)
     #include <dlfcn.h>
     #include <stdio.h>
 

modules/ocl/src/cl_runtime/clamdfft_runtime.cpp

@@ -27,7 +27,7 @@
     #define CV_CL_GET_PROC_ADDRESS(name) WinGetProcAddress(name)
 #endif // _WIN32
 
-#if defined(linux)
+#if defined(__linux__)
     #include <dlfcn.h>
     #include <stdio.h>
 

modules/ocl/src/cl_runtime/generator/template/clamdblas_runtime.cpp.in

@@ -24,7 +24,7 @@
     #define CV_CL_GET_PROC_ADDRESS(name) WinGetProcAddress(name)
 #endif // _WIN32
 
-#if defined(linux)
+#if defined(__linux__)
     #include <dlfcn.h>
     #include <stdio.h>
 

modules/ocl/src/cl_runtime/generator/template/clamdfft_runtime.cpp.in

@@ -24,7 +24,7 @@
     #define CV_CL_GET_PROC_ADDRESS(name) WinGetProcAddress(name)
 #endif // _WIN32
 
-#if defined(linux)
+#if defined(__linux__)
     #include <dlfcn.h>
     #include <stdio.h>
 

modules/ocl/test/test_canny.cpp

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

modules/ocl/test/test_match_template.cpp

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

modules/ocl/test/test_objdetect.cpp

@@ -181,7 +181,7 @@ INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
                             testing::Values(MatType(CV_8UC1), MatType(CV_8UC4))));
 
 ///////////////////////////// Haar //////////////////////////////
-IMPLEMENT_PARAM_CLASS(CascadeName, std::string);
+IMPLEMENT_PARAM_CLASS(CascadeName, std::string)
 CascadeName cascade_frontalface_alt(std::string("haarcascade_frontalface_alt.xml"));
 CascadeName cascade_frontalface_alt2(std::string("haarcascade_frontalface_alt2.xml"));
 struct getRect

modules/ocl/test/utility.hpp

@@ -266,7 +266,7 @@ CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
 CV_ENUM(Border, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, BORDER_WRAP)
 CV_ENUM(TemplateMethod, TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED)
 
-CV_FLAGS(GemmFlags, GEMM_1_T, GEMM_2_T, GEMM_3_T);
+CV_FLAGS(GemmFlags, GEMM_1_T, GEMM_2_T, GEMM_3_T)
 CV_FLAGS(WarpFlags, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, WARP_INVERSE_MAP)
 CV_FLAGS(DftFlags, DFT_INVERSE, DFT_SCALE, DFT_ROWS, DFT_COMPLEX_OUTPUT, DFT_REAL_OUTPUT)
 

modules/python/CMakeLists.txt

@@ -108,17 +108,17 @@ endif()
 if(WIN32)
   set(PYTHON_INSTALL_ARCHIVE "")
 else()
-  set(PYTHON_INSTALL_ARCHIVE ARCHIVE DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT main)
+  set(PYTHON_INSTALL_ARCHIVE ARCHIVE DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT python)
 endif()
 
 if(NOT INSTALL_CREATE_DISTRIB)
   install(TARGETS ${the_module}
           ${PYTHON_INSTALL_CONFIGURATIONS}
-          RUNTIME DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT main
-          LIBRARY DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT main
+          RUNTIME DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT python
+          LIBRARY DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT python
           ${PYTHON_INSTALL_ARCHIVE}
           )
-  install(FILES src2/cv.py ${PYTHON_INSTALL_CONFIGURATIONS} DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT main)
+  install(FILES src2/cv.py ${PYTHON_INSTALL_CONFIGURATIONS} DESTINATION ${PYTHON_PACKAGES_PATH} COMPONENT python)
 else()
   if(DEFINED PYTHON_VERSION_MAJOR)
     set(__ver "${PYTHON_VERSION_MAJOR}.${PYTHON_VERSION_MINOR}")
@@ -127,7 +127,7 @@ else()
   endif()
   install(TARGETS ${the_module}
           CONFIGURATIONS Release
-          RUNTIME DESTINATION python/${__ver}/${OpenCV_ARCH} COMPONENT main
-          LIBRARY DESTINATION python/${__ver}/${OpenCV_ARCH} COMPONENT main
+          RUNTIME DESTINATION python/${__ver}/${OpenCV_ARCH} COMPONENT python
+          LIBRARY DESTINATION python/${__ver}/${OpenCV_ARCH} COMPONENT python
           )
 endif()

modules/superres/src/btv_l1.cpp

@@ -488,7 +488,7 @@ namespace
                       obj.info()->addParam(obj, "blurKernelSize", obj.blurKernelSize_, false, 0, 0, "Gaussian blur kernel size.");
                       obj.info()->addParam(obj, "blurSigma", obj.blurSigma_, false, 0, 0, "Gaussian blur sigma.");
                       obj.info()->addParam(obj, "temporalAreaRadius", obj.temporalAreaRadius_, false, 0, 0, "Radius of the temporal search area.");
-                      obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."));
+                      obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."))
 
     BTVL1::BTVL1()
     {

modules/superres/src/btv_l1_ocl.cpp

@@ -580,7 +580,7 @@ namespace
     obj.info()->addParam(obj, "blurKernelSize", obj.blurKernelSize_, false, 0, 0, "Gaussian blur kernel size.");
     obj.info()->addParam(obj, "blurSigma", obj.blurSigma_, false, 0, 0, "Gaussian blur sigma.");
     obj.info()->addParam(obj, "temporalAreaRadius", obj.temporalAreaRadius_, false, 0, 0, "Radius of the temporal search area.");
-    obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."));
+    obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm."))
 
     BTVL1_OCL::BTVL1_OCL()
     {