modified according to CUDA 4.0 API updates

modules/gpu/CMakeLists.txt_cuda32

@@ -1,236 +0,0 @@
-set(name "gpu")
-
-set(the_target "opencv_${name}")
-project(${the_target})
-
-set(DEPS "opencv_core" "opencv_imgproc" "opencv_objdetect" "opencv_features2d" "opencv_flann" "opencv_calib3d") #"opencv_features2d" "opencv_flann" "opencv_objdetect" - only headers needed 
-set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} opencv_gpu)
-
-include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include"                    
-					"${CMAKE_CURRENT_SOURCE_DIR}/src/cuda"                    
-					"${CMAKE_CURRENT_SOURCE_DIR}/src"
-					"${CMAKE_CURRENT_BINARY_DIR}")
-
-file(GLOB lib_srcs "src/*.cpp")
-file(GLOB lib_int_hdrs "src/*.h*")
-file(GLOB lib_cuda "src/cuda/*.cu*")
-file(GLOB lib_cuda_hdrs "src/cuda/*.h*")
-source_group("Src\\Host" FILES ${lib_srcs} ${lib_int_hdrs})
-source_group("Src\\Cuda" FILES ${lib_cuda} ${lib_cuda_hdrs})
-
-file(GLOB lib_hdrs "include/opencv2/${name}/*.h*")
-source_group("Include" FILES ${lib_hdrs})
-
-#file(GLOB lib_device_hdrs "include/opencv2/${name}/device/*.h*")
-file(GLOB lib_device_hdrs "src/opencv2/gpu/device/*.h*")
-source_group("Device" FILES ${lib_device_hdrs})
-
-if (HAVE_CUDA)
-    file(GLOB_RECURSE ncv_srcs "src/nvidia/*.cpp")	
-    file(GLOB_RECURSE ncv_cuda "src/nvidia/*.cu")
-    file(GLOB_RECURSE ncv_hdrs "src/nvidia/*.hpp" "src/nvidia/*.h")
-    
-    source_group("Src\\NVidia" FILES ${ncv_srcs} ${ncv_hdrs} ${ncv_cuda})
-    include_directories("src/nvidia/core" "src/nvidia/NPP_staging")
-endif()
-
-if (HAVE_CUDA)		
-    get_filename_component(_path_to_findnpp "${CMAKE_CURRENT_LIST_FILE}" PATH)
-    set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${_path_to_findnpp})
-    find_package(NPP 3.2.16 REQUIRED)
-    message(STATUS "NPP detected: " ${NPP_VERSION})
-       
-    include_directories(${CUDA_INCLUDE_DIRS} ${CUDA_NPP_INCLUDES})
-
-    if (UNIX OR APPLE)
-        set (CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS}  "-Xcompiler;-fPIC;")
-        #set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}" "-fPIC")
-    endif()
-
-    #set (CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} "-keep")
-    #set (CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} "-Xcompiler;/EHsc-;")
-
-    string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-    string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
-    string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
-
-    if(MSVC)
-        #string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-        #string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
-        #string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
-        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4211 /wd4201 /wd4100 /wd4505 /wd4408")
-
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
-    endif()
-	
-	if (OPENCV_BUILD_SHARED_LIB) 
-		set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} "-Xcompiler;-DCVAPI_EXPORTS")
-	endif()
-    
-    CUDA_COMPILE(cuda_objs ${lib_cuda} ${ncv_cuda})
-    #CUDA_BUILD_CLEAN_TARGET()
-endif()
-
-foreach(d ${DEPS})
-	if(${d} MATCHES "opencv_")
-		string(REPLACE "opencv_" "${CMAKE_CURRENT_SOURCE_DIR}/../" d_dir ${d})
-		include_directories("${d_dir}/include")
-	endif()
-endforeach()
-
-add_library(${the_target} ${lib_srcs} ${lib_hdrs} ${lib_int_hdrs} ${lib_cuda} ${lib_cuda_hdrs} ${lib_device_hdrs} ${ncv_srcs} ${ncv_hdrs} ${ncv_cuda} ${cuda_objs})
-
-if(PCHSupport_FOUND)
-	set(pch_header ${CMAKE_CURRENT_SOURCE_DIR}/src/precomp.hpp)
-	if(${CMAKE_GENERATOR} MATCHES "Visual*" OR ${CMAKE_GENERATOR} MATCHES "Xcode*")
-		if(${CMAKE_GENERATOR} MATCHES "Visual*")
-			set(${the_target}_pch "src/precomp.cpp")
-		endif()
-		add_native_precompiled_header(${the_target} ${pch_header})
-	elseif(CMAKE_COMPILER_IS_GNUCXX AND ${CMAKE_GENERATOR} MATCHES ".*Makefiles")
-		add_precompiled_header(${the_target} ${pch_header})
-	endif()
-endif()
-
-# For dynamic link numbering convenions
-set_target_properties(${the_target} PROPERTIES
-	VERSION ${OPENCV_VERSION}
-	SOVERSION ${OPENCV_SOVERSION}
-	OUTPUT_NAME "${the_target}${OPENCV_DLLVERSION}"
-	)
-
-if(ENABLE_SOLUTION_FOLDERS)
-	set_target_properties(${the_target} PROPERTIES FOLDER "modules")
-endif()	
-	
-if (OPENCV_BUILD_SHARED_LIB) 
-	if (MSVC)
-		set_target_properties(${the_target} PROPERTIES DEFINE_SYMBOL CVAPI_EXPORTS)
-	else()
-		add_definitions(-DCVAPI_EXPORTS)	   
-	endif()	
-endif()
-
-# Additional target properties
-set_target_properties(${the_target} PROPERTIES
-	DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-	ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/lib/"
-	RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
-	INSTALL_NAME_DIR "${CMAKE_INSTALL_PREFIX}/lib"
-	)
-
-# Add the required libraries for linking:
-target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${IPP_LIBS} ${DEPS} )
-
-if (HAVE_CUDA)
-	target_link_libraries(${the_target} ${CUDA_LIBRARIES} ${CUDA_NPP_LIBRARIES})    
-    CUDA_ADD_CUFFT_TO_TARGET(${the_target})
-endif()
-
-if(MSVC)
-	if(CMAKE_CROSSCOMPILING)
-		set_target_properties(${the_target} PROPERTIES LINK_FLAGS "/NODEFAULTLIB:secchk")
-	endif()
-    
-	set_target_properties(${the_target} PROPERTIES LINK_FLAGS "/NODEFAULTLIB:libc")
-endif()
-
-# Dependencies of this target:
-add_dependencies(${the_target} ${DEPS})
-
-install(TARGETS ${the_target}
-	RUNTIME DESTINATION bin COMPONENT main
-	LIBRARY DESTINATION lib COMPONENT main
-	ARCHIVE DESTINATION lib COMPONENT main)
-
-install(FILES ${lib_hdrs}
-	DESTINATION include/opencv2/${name}
-	COMPONENT main)
-
-install(FILES src/nvidia/NPP_staging/NPP_staging.hpp  src/nvidia/core/NCV.hpp
-	DESTINATION include/opencv2/${name}
-	COMPONENT main)
-
-#install(FILES ${lib_device_hdrs}
-#	DESTINATION include/opencv2/${name}/device
-#	COMPONENT main)
-
-
-################################################################################################################
-################################      GPU Module Tests     #####################################################
-################################################################################################################
-
-# Test files processing is in the separated directory to avoid 'Src' source 
-# filter creation in Visual Studio 
-if(BUILD_TESTS AND EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/test)
-    set(the_test_target "opencv_test_${name}")   
-    
-    include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include"
-                        "${CMAKE_CURRENT_SOURCE_DIR}/test"
-                        "${CMAKE_CURRENT_BINARY_DIR}")                      
-    
-    set(test_deps opencv_${name} opencv_ts opencv_highgui opencv_calib3d ${DEPS})
-    foreach(d ${test_deps})
-        if(${d} MATCHES "opencv_")
-            if(${d} MATCHES "opencv_lapack")
-            else()
-                string(REPLACE "opencv_" "${CMAKE_CURRENT_SOURCE_DIR}/../" d_dir ${d})
-                include_directories("${d_dir}/include")
-            endif()
-        endif()
-    endforeach()
-    
-    file(GLOB test_srcs "test/*.cpp")
-    file(GLOB test_hdrs "test/*.h*")
-	
-	source_group("Src" FILES ${test_hdrs} ${test_srcs})
-    if(HAVE_CUDA)
-            include_directories(${CUDA_INCLUDE_DIRS} ${CMAKE_SOURCE_DIR}/modules/gpu/src/nvidia ${CMAKE_SOURCE_DIR}/modules/gpu/src/nvidia/core ${CMAKE_SOURCE_DIR}/modules/gpu/src/nvidia/NPP_staging)
-    
-            file(GLOB nvidia "test/nvidia/*.cpp" "test/nvidia/*.h*")            
-            source_group("Src\\NVidia" FILES ${nvidia})
-    endif()
-    
-    
-    add_executable(${the_test_target} ${test_srcs} ${test_hdrs} ${nvidia})
-    
-    if(PCHSupport_FOUND)
-        set(pch_header ${CMAKE_CURRENT_SOURCE_DIR}/test/test_precomp.hpp)
-        if(${CMAKE_GENERATOR} MATCHES "Visual*" OR ${CMAKE_GENERATOR} MATCHES "Xcode*")
-            if(${CMAKE_GENERATOR} MATCHES "Visual*")
-                set(${the_test_target}_pch "test/test_precomp.cpp")
-            endif()            
-            add_native_precompiled_header(${the_test_target} ${pch_header})
-        elseif(CMAKE_COMPILER_IS_GNUCXX AND ${CMAKE_GENERATOR} MATCHES ".*Makefiles")
-            add_precompiled_header(${the_test_target} ${pch_header})
-        endif()
-    endif()
-    
-    # Additional target properties
-    set_target_properties(${the_test_target} PROPERTIES
-        DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-        RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
-        )
-	
-	if(ENABLE_SOLUTION_FOLDERS)
-		set_target_properties(${the_test_target} PROPERTIES FOLDER "tests")
-	endif()			
-    
-    add_dependencies(${the_test_target} ${test_deps})
-    
-    # Add the required libraries for linking:
-    target_link_libraries(${the_test_target} ${OPENCV_LINKER_LIBS} ${test_deps})
-    
-    enable_testing()
-    get_target_property(LOC ${the_test_target} LOCATION)
-    add_test(${the_test_target} "${LOC}")
-    
-    if(WIN32)
-        install(TARGETS ${the_test_target} RUNTIME DESTINATION bin COMPONENT main)
-    endif()
-endif()

modules/gpu/CMakeLists.txt_cuda4.0

@@ -1,240 +0,0 @@
-set(name "gpu")
-
-set(the_target "opencv_${name}")
-project(${the_target})
-
-set(DEPS "opencv_core" "opencv_imgproc" "opencv_objdetect" "opencv_features2d" "opencv_flann" "opencv_calib3d") #"opencv_features2d" "opencv_flann" "opencv_objdetect" - only headers needed 
-set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} opencv_gpu)
-
-include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include"                    
-					"${CMAKE_CURRENT_SOURCE_DIR}/src/cuda"                    
-					"${CMAKE_CURRENT_SOURCE_DIR}/src"
-					"${CMAKE_CURRENT_BINARY_DIR}")
-
-file(GLOB lib_srcs "src/*.cpp")
-file(GLOB lib_int_hdrs "src/*.h*")
-file(GLOB lib_cuda "src/cuda/*.cu*")
-file(GLOB lib_cuda_hdrs "src/cuda/*.h*")
-source_group("Src\\Host" FILES ${lib_srcs} ${lib_int_hdrs})
-source_group("Src\\Cuda" FILES ${lib_cuda} ${lib_cuda_hdrs})
-
-file(GLOB lib_hdrs "include/opencv2/${name}/*.h*")
-source_group("Include" FILES ${lib_hdrs})
-
-#file(GLOB lib_device_hdrs "include/opencv2/${name}/device/*.h*")
-file(GLOB lib_device_hdrs "src/opencv2/gpu/device/*.h*")
-source_group("Device" FILES ${lib_device_hdrs})
-
-if (HAVE_CUDA)
-    file(GLOB_RECURSE ncv_srcs "src/nvidia/*.cpp")	
-    file(GLOB_RECURSE ncv_cuda "src/nvidia/*.cu")
-    file(GLOB_RECURSE ncv_hdrs "src/nvidia/*.hpp" "src/nvidia/*.h")
-    
-    source_group("Src\\NVidia" FILES ${ncv_srcs} ${ncv_hdrs} ${ncv_cuda})
-    include_directories("src/nvidia/core" "src/nvidia/NPP_staging")
-endif()
-
-if (HAVE_CUDA)		
-    #get_filename_component(_path_to_findnpp "${CMAKE_CURRENT_LIST_FILE}" PATH)
-    #set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${_path_to_findnpp})
-    #find_package(NPP 3.2.16 REQUIRED)
-    #message(STATUS "NPP detected: " ${NPP_VERSION})
-       
-    include_directories(${CUDA_INCLUDE_DIRS})
-
-    if (UNIX OR APPLE)
-        set (CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS}  "-Xcompiler;-fPIC;")
-        #set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}" "-fPIC")
-    endif()
-
-    #set (CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} "-keep")
-    #set (CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} "-Xcompiler;/EHsc-;")
-
-    string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-    string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
-    string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
-
-    if(MSVC)
-        #string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-        #string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
-        #string(REPLACE "/W4" "/W3" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
-        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4211 /wd4201 /wd4100 /wd4505 /wd4408")
-
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
-        string(REPLACE "/EHsc-" "/EHs" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
-    endif()
-	
-	if (OPENCV_BUILD_SHARED_LIB) 
-		set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} "-Xcompiler;-DCVAPI_EXPORTS")
-	endif()
-    
-    CUDA_COMPILE(cuda_objs ${lib_cuda} ${ncv_cuda})
-    #CUDA_BUILD_CLEAN_TARGET()
-endif()
-
-foreach(d ${DEPS})
-	if(${d} MATCHES "opencv_")
-		string(REPLACE "opencv_" "${CMAKE_CURRENT_SOURCE_DIR}/../" d_dir ${d})
-		include_directories("${d_dir}/include")
-	endif()
-endforeach()
-
-add_library(${the_target} ${lib_srcs} ${lib_hdrs} ${lib_int_hdrs} ${lib_cuda} ${lib_cuda_hdrs} ${lib_device_hdrs} ${ncv_srcs} ${ncv_hdrs} ${ncv_cuda} ${cuda_objs})
-
-if(PCHSupport_FOUND)
-	set(pch_header ${CMAKE_CURRENT_SOURCE_DIR}/src/precomp.hpp)
-	if(${CMAKE_GENERATOR} MATCHES "Visual*" OR ${CMAKE_GENERATOR} MATCHES "Xcode*")
-		if(${CMAKE_GENERATOR} MATCHES "Visual*")
-			set(${the_target}_pch "src/precomp.cpp")
-		endif()
-		add_native_precompiled_header(${the_target} ${pch_header})
-	elseif(CMAKE_COMPILER_IS_GNUCXX AND ${CMAKE_GENERATOR} MATCHES ".*Makefiles")
-		add_precompiled_header(${the_target} ${pch_header})
-	endif()
-endif()
-
-# For dynamic link numbering convenions
-set_target_properties(${the_target} PROPERTIES
-	VERSION ${OPENCV_VERSION}
-	SOVERSION ${OPENCV_SOVERSION}
-	OUTPUT_NAME "${the_target}${OPENCV_DLLVERSION}"
-	)
-
-if(ENABLE_SOLUTION_FOLDERS)
-	set_target_properties(${the_target} PROPERTIES FOLDER "modules")
-endif()	
-	
-if (OPENCV_BUILD_SHARED_LIB) 
-	if (MSVC)
-		set_target_properties(${the_target} PROPERTIES DEFINE_SYMBOL CVAPI_EXPORTS)
-	else()
-		add_definitions(-DCVAPI_EXPORTS)	   
-	endif()	
-endif()
-
-# Additional target properties
-set_target_properties(${the_target} PROPERTIES
-	DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-	ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/lib/"
-	RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
-	INSTALL_NAME_DIR "${CMAKE_INSTALL_PREFIX}/lib"
-	)
-
-# Add the required libraries for linking:
-target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${IPP_LIBS} ${DEPS} )
-
-if (HAVE_CUDA)
-	target_link_libraries(${the_target} ${CUDA_LIBRARIES})    
-    CUDA_ADD_CUFFT_TO_TARGET(${the_target})
-	
-	unset(CUDA_npp_LIBRARY CACHE)
-	find_cuda_helper_libs(npp)
-	target_link_libraries(${the_target} ${CUDA_npp_LIBRARY})    		
-endif()
-
-if(MSVC)
-	if(CMAKE_CROSSCOMPILING)
-		set_target_properties(${the_target} PROPERTIES LINK_FLAGS "/NODEFAULTLIB:secchk")
-	endif()
-    
-	set_target_properties(${the_target} PROPERTIES LINK_FLAGS "/NODEFAULTLIB:libc")
-endif()
-
-# Dependencies of this target:
-add_dependencies(${the_target} ${DEPS})
-
-install(TARGETS ${the_target}
-	RUNTIME DESTINATION bin COMPONENT main
-	LIBRARY DESTINATION lib COMPONENT main
-	ARCHIVE DESTINATION lib COMPONENT main)
-
-install(FILES ${lib_hdrs}
-	DESTINATION include/opencv2/${name}
-	COMPONENT main)
-
-install(FILES src/nvidia/NPP_staging/NPP_staging.hpp  src/nvidia/core/NCV.hpp
-	DESTINATION include/opencv2/${name}
-	COMPONENT main)
-
-#install(FILES ${lib_device_hdrs}
-#	DESTINATION include/opencv2/${name}/device
-#	COMPONENT main)
-
-
-################################################################################################################
-################################      GPU Module Tests     #####################################################
-################################################################################################################
-
-# Test files processing is in the separated directory to avoid 'Src' source 
-# filter creation in Visual Studio 
-if(BUILD_TESTS AND EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/test)
-    set(the_test_target "opencv_test_${name}")   
-    
-    include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include"
-                        "${CMAKE_CURRENT_SOURCE_DIR}/test"
-                        "${CMAKE_CURRENT_BINARY_DIR}")                      
-    
-    set(test_deps opencv_${name} opencv_ts opencv_highgui opencv_calib3d ${DEPS})
-    foreach(d ${test_deps})
-        if(${d} MATCHES "opencv_")
-            if(${d} MATCHES "opencv_lapack")
-            else()
-                string(REPLACE "opencv_" "${CMAKE_CURRENT_SOURCE_DIR}/../" d_dir ${d})
-                include_directories("${d_dir}/include")
-            endif()
-        endif()
-    endforeach()
-    
-    file(GLOB test_srcs "test/*.cpp")
-    file(GLOB test_hdrs "test/*.h*")
-	
-	source_group("Src" FILES ${test_hdrs} ${test_srcs})
-    if(HAVE_CUDA)
-            include_directories(${CUDA_INCLUDE_DIRS} ${CMAKE_SOURCE_DIR}/modules/gpu/src/nvidia ${CMAKE_SOURCE_DIR}/modules/gpu/src/nvidia/core ${CMAKE_SOURCE_DIR}/modules/gpu/src/nvidia/NPP_staging)
-    
-            file(GLOB nvidia "test/nvidia/*.cpp" "test/nvidia/*.h*")            
-            source_group("Src\\NVidia" FILES ${nvidia})
-    endif()
-    
-    
-    add_executable(${the_test_target} ${test_srcs} ${test_hdrs} ${nvidia})
-    
-    if(PCHSupport_FOUND)
-        set(pch_header ${CMAKE_CURRENT_SOURCE_DIR}/test/test_precomp.hpp)
-        if(${CMAKE_GENERATOR} MATCHES "Visual*" OR ${CMAKE_GENERATOR} MATCHES "Xcode*")
-            if(${CMAKE_GENERATOR} MATCHES "Visual*")
-                set(${the_test_target}_pch "test/test_precomp.cpp")
-            endif()            
-            add_native_precompiled_header(${the_test_target} ${pch_header})
-        elseif(CMAKE_COMPILER_IS_GNUCXX AND ${CMAKE_GENERATOR} MATCHES ".*Makefiles")
-            add_precompiled_header(${the_test_target} ${pch_header})
-        endif()
-    endif()
-    
-    # Additional target properties
-    set_target_properties(${the_test_target} PROPERTIES
-        DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-        RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin/"
-        )
-	
-	if(ENABLE_SOLUTION_FOLDERS)
-		set_target_properties(${the_test_target} PROPERTIES FOLDER "tests")
-	endif()			
-    
-    add_dependencies(${the_test_target} ${test_deps})
-    
-    # Add the required libraries for linking:
-    target_link_libraries(${the_test_target} ${OPENCV_LINKER_LIBS} ${test_deps})
-    
-    enable_testing()
-    get_target_property(LOC ${the_test_target} LOCATION)
-    add_test(${the_test_target} "${LOC}")
-    
-    if(WIN32)
-        install(TARGETS ${the_test_target} RUNTIME DESTINATION bin COMPONENT main)
-    endif()
-endif()

modules/gpu/FindNPP.cmake

@@ -1,125 +0,0 @@
-###############################################################################
-#
-# FindNPP.cmake
-#
-# CUDA_NPP_LIBRARY_ROOT_DIR   -- Path to the NPP dorectory.
-# CUDA_NPP_INCLUDES           -- NPP Include directories.
-# CUDA_NPP_LIBRARIES          -- NPP libraries.
-# NPP_VERSION                 -- NPP version in format "major.minor.build".
-#
-# If not found automatically, please set CUDA_NPP_LIBRARY_ROOT_DIR 
-# in CMake or set enviroment varivabe $CUDA_NPP_ROOT
-#
-# Author: Anatoly Baksheev, Itseez Ltd.
-# 
-# The MIT License
-#
-# License for the specific language governing rights and limitations under
-# Permission is hereby granted, free of charge, to any person obtaining a
-# copy of this software and associated documentation files (the "Software"),
-# to deal in the Software without restriction, including without limitation
-# the rights to use, copy, modify, merge, publish, distribute, sublicense,
-# and/or sell copies of the Software, and to permit persons to whom the
-# Software is furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included
-# in all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
-# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
-# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
-# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-# DEALINGS IN THE SOFTWARE.
-#
-###############################################################################
-
-cmake_policy(PUSH)
-cmake_minimum_required(VERSION 2.8.0)
-cmake_policy(POP)
-
-if(NOT "${CUDA_NPP_LIBRARY_ROOT_DIR}" STREQUAL "${CUDA_NPP_LIBRARY_ROOT_DIR_INTERNAL}")
-    unset(CUDA_NPP_INCLUDES CACHE)
-    unset(CUDA_NPP_LIBRARIES CACHE)  
-endif()
-
-if(CMAKE_SIZEOF_VOID_P EQUAL 4)			
-    if (UNIX OR APPLE)
-        set(NPP_SUFFIX "32")				
-    else()
-        set(NPP_SUFFIX "-mt")
-    endif()
-else(CMAKE_SIZEOF_VOID_P EQUAL 4)
-    if (UNIX OR APPLE)
-        set(NPP_SUFFIX "64")				
-    else()
-        set(NPP_SUFFIX "-mt-x64")			
-    endif()
-endif(CMAKE_SIZEOF_VOID_P EQUAL 4)
-
-if(NOT CUDA_NPP_LIBRARY_ROOT_DIR OR CUDA_NPP_LIBRARY_ROOT_DIR STREQUAL "")
-    unset(CUDA_NPP_LIBRARY_ROOT_DIR CACHE)	
-    find_path(CUDA_NPP_LIBRARY_ROOT_DIR "common/npp/include/npp.h" PATHS ENV CUDA_NPP_ROOT DOC "NPP root directory.")	
-    MESSAGE(STATUS "NPP root directory: " ${CUDA_NPP_LIBRARY_ROOT_DIR})
-endif()
-
-# Search includes in our own paths.
-find_path(CUDA_NPP_INCLUDES npp.h PATHS "${CUDA_NPP_LIBRARY_ROOT_DIR}/common/npp/include")
-# Search default search paths, after we search our own set of paths.
-find_path(CUDA_NPP_INCLUDES device_functions.h)
-mark_as_advanced(CUDA_NPP_INCLUDES)
-
-# Find NPP library
-find_library(CUDA_NPP_LIBRARIES
-    NAMES "npp" "npp${NPP_SUFFIX}" "libnpp${NPP_SUFFIX}"
-    PATHS "${CUDA_NPP_LIBRARY_ROOT_DIR}"    
-    PATH_SUFFIXES "common/lib" "common/npp/lib"
-    DOC "NPP library"	
-    )	
-
-# Search default search paths, after we search our own set of paths.
-find_library(CUDA_NPP_LIBRARIES NAMES npp${NPP_SUFFIX} libnpp${NPP_SUFFIX} DOC "NPP library")
-mark_as_advanced(CUDA_NPP_LIBRARIES)
-
-if(EXISTS ${CUDA_NPP_INCLUDES}/nppversion.h)
-    file( STRINGS ${CUDA_NPP_INCLUDES}/nppversion.h npp_major REGEX "#define NPP_VERSION_MAJOR.*")
-    file( STRINGS ${CUDA_NPP_INCLUDES}/nppversion.h npp_minor REGEX "#define NPP_VERSION_MINOR.*")
-    file( STRINGS ${CUDA_NPP_INCLUDES}/nppversion.h npp_build REGEX "#define NPP_VERSION_BUILD.*")
-
-    string( REGEX REPLACE "#define NPP_VERSION_MAJOR[ \t]+|//.*" "" npp_major ${npp_major})
-    string( REGEX REPLACE "#define NPP_VERSION_MINOR[ \t]+|//.*" "" npp_minor ${npp_minor})
-    string( REGEX REPLACE "#define NPP_VERSION_BUILD[ \t]+|//.*" "" npp_build ${npp_build})
-
-    string( REGEX MATCH "[0-9]+" npp_major ${npp_major} ) 
-    string( REGEX MATCH "[0-9]+" npp_minor ${npp_minor} ) 
-    string( REGEX MATCH "[0-9]+" npp_build ${npp_build} ) 	
-    set( NPP_VERSION "${npp_major}.${npp_minor}.${npp_build}")	
-endif()
-
-if(NOT EXISTS ${CUDA_NPP_LIBRARIES} OR NOT EXISTS ${CUDA_NPP_INCLUDES}/npp.h)
-    set(CUDA_NPP_FOUND FALSE)	
-    message(FATAL_ERROR "NPP headers/libraries are not found. Please specify CUDA_NPP_LIBRARY_ROOT_DIR in CMake or set $CUDA_NPP_ROOT.")	
-endif()
-
-include( FindPackageHandleStandardArgs ) 
-find_package_handle_standard_args( NPP 
-    REQUIRED_VARS 
-        CUDA_NPP_INCLUDES 
-        CUDA_NPP_LIBRARIES 
-    #Need cmake 2.8.3 to uncomment this. 
-    #VERSION_VAR			
-        NPP_VERSION)
-
-if(APPLE)
-    # We need to add the path to cudart to the linker using rpath, since the library name for the cuda libraries is prepended with @rpath.
-    get_filename_component(_cuda_path_to_npp "${CUDA_NPP_LIBRARIES}" PATH)
-    if(_cuda_path_to_npp)
-        list(APPEND CUDA_NPP_LIBRARIES "-Wl,-rpath,${_cuda_path_to_npp}")
-    endif()
-endif()
-
-set(CUDA_NPP_FOUND TRUE)
-set(CUDA_NPP_LIBRARY_ROOT_DIR_INTERNAL "${CUDA_NPP_LIBRARY_ROOT_DIR}" CACHE INTERNAL "This is the value of the last time CUDA_NPP_LIBRARY_ROOT_DIR was set successfully." FORCE)
-
-

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

@@ -447,12 +447,21 @@ namespace cv
 
             // converts matrix type, ex from float to uchar depending on type
             void enqueueConvert(const GpuMat& src, GpuMat& dst, int type, double a = 1, double b = 0);
+
+            static Stream& Null();
+
+            operator bool() const;
+
         private:
             void create();
             void release();
+
             struct Impl;
             Impl *impl;
+
             friend struct StreamAccessor;
+            
+            explicit Stream(Impl* impl);
         };
 
 
@@ -460,168 +469,130 @@ namespace cv
 
         //! transposes the matrix
         //! supports matrix with element size = 1, 4 and 8 bytes (CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, etc)
-        CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst);
+        CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst, Stream& stream = Stream::Null());
 
         //! reverses the order of the rows, columns or both in a matrix
         //! supports CV_8UC1, CV_8UC4 types
-        CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode);
+        CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode, Stream& stream = Stream::Null());
 
         //! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i))
         //! destination array will have the depth type as lut and the same channels number as source
         //! supports CV_8UC1, CV_8UC3 types
-        CV_EXPORTS void LUT(const GpuMat& src, const Mat& lut, GpuMat& dst);
+        CV_EXPORTS void LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& stream = Stream::Null());
 
         //! makes multi-channel array out of several single-channel arrays
-        CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst);
+        CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst, Stream& stream = Stream::Null());
 
         //! makes multi-channel array out of several single-channel arrays
-        CV_EXPORTS void merge(const vector<GpuMat>& src, GpuMat& dst);
+        CV_EXPORTS void merge(const vector<GpuMat>& src, GpuMat& dst, Stream& stream = Stream::Null());
-
-        //! makes multi-channel array out of several single-channel arrays (async version)
-        CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst, const Stream& stream);
-
-        //! makes multi-channel array out of several single-channel arrays (async version)
-        CV_EXPORTS void merge(const vector<GpuMat>& src, GpuMat& dst, const Stream& stream);
 
         //! copies each plane of a multi-channel array to a dedicated array
-        CV_EXPORTS void split(const GpuMat& src, GpuMat* dst);
+        CV_EXPORTS void split(const GpuMat& src, GpuMat* dst, Stream& stream = Stream::Null());
 
         //! copies each plane of a multi-channel array to a dedicated array
-        CV_EXPORTS void split(const GpuMat& src, vector<GpuMat>& dst);
+        CV_EXPORTS void split(const GpuMat& src, vector<GpuMat>& dst, Stream& stream = Stream::Null());
-
-        //! copies each plane of a multi-channel array to a dedicated array (async version)
-        CV_EXPORTS void split(const GpuMat& src, GpuMat* dst, const Stream& stream);
-
-        //! copies each plane of a multi-channel array to a dedicated array (async version)
-        CV_EXPORTS void split(const GpuMat& src, vector<GpuMat>& dst, const Stream& stream);
 
         //! computes magnitude of complex (x(i).re, x(i).im) vector
         //! supports only CV_32FC2 type
-        CV_EXPORTS void magnitude(const GpuMat& x, GpuMat& magnitude);
+        CV_EXPORTS void magnitude(const GpuMat& x, GpuMat& magnitude, Stream& stream = Stream::Null());
 
         //! computes squared magnitude of complex (x(i).re, x(i).im) vector
         //! supports only CV_32FC2 type
-        CV_EXPORTS void magnitudeSqr(const GpuMat& x, GpuMat& magnitude);
+        CV_EXPORTS void magnitudeSqr(const GpuMat& x, GpuMat& magnitude, Stream& stream = Stream::Null());
 
         //! computes magnitude of each (x(i), y(i)) vector
         //! supports only floating-point source
-        CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
+        CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, const Stream& stream);
 
         //! computes squared magnitude of each (x(i), y(i)) vector
         //! supports only floating-point source
-        CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
+        CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, const Stream& stream);
 
         //! computes angle (angle(i)) of each (x(i), y(i)) vector
         //! supports only floating-point source
-        CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false);
+        CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees, const Stream& stream);
 
         //! converts Cartesian coordinates to polar
         //! supports only floating-point source
-        CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false);
+        CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees, const Stream& stream);
 
         //! converts polar coordinates to Cartesian
         //! supports only floating-point source
-        CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false);
+        CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, const Stream& stream);
 
 
         //////////////////////////// Per-element operations ////////////////////////////////////
 
         //! adds one matrix to another (c = a + b)
         //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types
-        CV_EXPORTS void add(const GpuMat& a, const GpuMat& b, GpuMat& c);
+        CV_EXPORTS void add(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
         //! adds scalar to a matrix (c = a + s)
         //! supports CV_32FC1 and CV_32FC2 type
-        CV_EXPORTS void add(const GpuMat& a, const Scalar& sc, GpuMat& c);
+        CV_EXPORTS void add(const GpuMat& a, const Scalar& sc, GpuMat& c, Stream& stream = Stream::Null());
 
         //! subtracts one matrix from another (c = a - b)
         //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types
-        CV_EXPORTS void subtract(const GpuMat& a, const GpuMat& b, GpuMat& c);
+        CV_EXPORTS void subtract(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
         //! subtracts scalar from a matrix (c = a - s)
         //! supports CV_32FC1 and CV_32FC2 type
-        CV_EXPORTS void subtract(const GpuMat& a, const Scalar& sc, GpuMat& c);
+        CV_EXPORTS void subtract(const GpuMat& a, const Scalar& sc, GpuMat& c, Stream& stream = Stream::Null());
 
         //! computes element-wise product of the two arrays (c = a * b)
         //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types
-        CV_EXPORTS void multiply(const GpuMat& a, const GpuMat& b, GpuMat& c);
+        CV_EXPORTS void multiply(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
         //! multiplies matrix to a scalar (c = a * s)
         //! supports CV_32FC1 and CV_32FC2 type
-        CV_EXPORTS void multiply(const GpuMat& a, const Scalar& sc, GpuMat& c);
+        CV_EXPORTS void multiply(const GpuMat& a, const Scalar& sc, GpuMat& c, Stream& stream = Stream::Null());
 
         //! computes element-wise quotient of the two arrays (c = a / b)
         //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types
-        CV_EXPORTS void divide(const GpuMat& a, const GpuMat& b, GpuMat& c);
+        CV_EXPORTS void divide(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
         //! computes element-wise quotient of matrix and scalar (c = a / s)
         //! supports CV_32FC1 and CV_32FC2 type
-        CV_EXPORTS void divide(const GpuMat& a, const Scalar& sc, GpuMat& c);
+        CV_EXPORTS void divide(const GpuMat& a, const Scalar& sc, GpuMat& c, Stream& stream = Stream::Null());
 
         //! computes exponent of each matrix element (b = e**a)
         //! supports only CV_32FC1 type
-        CV_EXPORTS void exp(const GpuMat& a, GpuMat& b);
+        CV_EXPORTS void exp(const GpuMat& a, GpuMat& b, Stream& stream = Stream::Null());
 
         //! computes natural logarithm of absolute value of each matrix element: b = log(abs(a))
         //! supports only CV_32FC1 type
-        CV_EXPORTS void log(const GpuMat& a, GpuMat& b);
+        CV_EXPORTS void log(const GpuMat& a, GpuMat& b, Stream& stream = Stream::Null());
 
         //! computes element-wise absolute difference of two arrays (c = abs(a - b))
         //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types
-        CV_EXPORTS void absdiff(const GpuMat& a, const GpuMat& b, GpuMat& c);
+        CV_EXPORTS void absdiff(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
         //! computes element-wise absolute difference of array and scalar (c = abs(a - s))
         //! supports only CV_32FC1 type
-        CV_EXPORTS void absdiff(const GpuMat& a, const Scalar& s, GpuMat& c);
+        CV_EXPORTS void absdiff(const GpuMat& a, const Scalar& s, GpuMat& c, Stream& stream = Stream::Null());
 
         //! compares elements of two arrays (c = a <cmpop> b)
         //! supports CV_8UC4, CV_32FC1 types
-        CV_EXPORTS void compare(const GpuMat& a, const GpuMat& b, GpuMat& c, int cmpop);
+        CV_EXPORTS void compare(const GpuMat& a, const GpuMat& b, GpuMat& c, int cmpop, Stream& stream = Stream::Null());
 
         //! performs per-elements bit-wise inversion
-        CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat());
+        CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, const Stream& stream);
 
         //! calculates per-element bit-wise disjunction of two arrays
-        CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
+        CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
 
         //! calculates per-element bit-wise conjunction of two arrays
-        CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
+        CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
 
         //! calculates per-element bit-wise "exclusive or" operation
-        CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
+        CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
 
         //! computes per-element minimum of two arrays (dst = min(src1, src2))
-        CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
+        CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
-        //! Async version
-        CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
 
         //! computes per-element minimum of array and scalar (dst = min(src1, src2))
-        CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst);
+        CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
-        //! Async version
-        CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream);
 
         //! computes per-element maximum of two arrays (dst = max(src1, src2))
-        CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
+        CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
-        //! Async version
-        CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
 
         //! computes per-element maximum of array and scalar (dst = max(src1, src2))
-        CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst);
+        CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
-        //! Async version
-        CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream);
 
 
         ////////////////////////////// Image processing //////////////////////////////
@@ -645,68 +616,60 @@ namespace cv
         //! Does coloring of disparity image: [0..ndisp) -> [0..240, 1, 1] in HSV.
         //! Supported types of input disparity: CV_8U, CV_16S.
         //! Output disparity has CV_8UC4 type in BGRA format (alpha = 255).
-        CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp);
+        CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, const Stream& stream);
 
         //! Reprojects disparity image to 3D space.
         //! Supports CV_8U and CV_16S types of input disparity.
         //! The output is a 4-channel floating-point (CV_32FC4) matrix.
         //! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
         //! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
-        CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q);
+        CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const Stream& stream);
 
         //! converts image from one color space to another
-        CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0);
+        CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn, const Stream& stream);
 
         //! applies fixed threshold to the image
-        CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type);
+        CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, Stream& stream = Stream::Null());
-        //! async version
-        CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, const Stream& stream);
 
         //! resizes the image
         //! Supports INTER_NEAREST, INTER_LINEAR
         //! supports CV_8UC1, CV_8UC4 types
-        CV_EXPORTS void resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx=0, double fy=0, int interpolation = INTER_LINEAR);
+        CV_EXPORTS void resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx=0, double fy=0, int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
 
         //! warps the image using affine transformation
         //! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
-        CV_EXPORTS void warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR);
+        CV_EXPORTS void warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR, Stream& stream = Stream::Null());
 
         //! warps the image using perspective transformation
         //! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
-        CV_EXPORTS void warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR);
+        CV_EXPORTS void warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR, Stream& stream = Stream::Null());
 
         //! rotate 8bit single or four channel image
         //! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
         //! supports CV_8UC1, CV_8UC4 types
-        CV_EXPORTS void rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift = 0, double yShift = 0, int interpolation = INTER_LINEAR);
+        CV_EXPORTS void rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift = 0, double yShift = 0, int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
 
         //! copies 2D array to a larger destination array and pads borders with user-specifiable constant
         //! supports CV_8UC1, CV_8UC4, CV_32SC1 and CV_32FC1 types
-        CV_EXPORTS void copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, const Scalar& value = Scalar());
+        CV_EXPORTS void copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, const Scalar& value = Scalar(), Stream& stream = Stream::Null());
 
         //! computes the integral image
         //! sum will have CV_32S type, but will contain unsigned int values
         //! supports only CV_8UC1 source type
-        CV_EXPORTS void integral(const GpuMat& src, GpuMat& sum);
+        CV_EXPORTS void integral(const GpuMat& src, GpuMat& sum, Stream& stream = Stream::Null());
 
         //! buffered version
-        CV_EXPORTS void integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer);
+        CV_EXPORTS void integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, Stream& stream = Stream::Null());
 
         //! computes the integral image and integral for the squared image
         //! sum will have CV_32S type, sqsum - CV32F type
         //! supports only CV_8UC1 source type
-        CV_EXPORTS void integral(const GpuMat& src, GpuMat& sum, GpuMat& sqsum);
+        CV_EXPORTS void integral(const GpuMat& src, GpuMat& sum, GpuMat& sqsum, Stream& stream = Stream::Null());
 
         //! computes squared integral image
         //! result matrix will have 64F type, but will contain 64U values
         //! supports source images of 8UC1 type only
-        CV_EXPORTS void sqrIntegral(const GpuMat& src, GpuMat& sqsum);
+        CV_EXPORTS void sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& stream = Stream::Null());
 
         //! computes vertical sum, supports only CV_32FC1 images
         CV_EXPORTS void columnSum(const GpuMat& src, GpuMat& sum);
@@ -714,14 +677,7 @@ namespace cv
         //! computes the standard deviation of integral images
         //! supports only CV_32SC1 source type and CV_32FC1 sqr type
         //! output will have CV_32FC1 type
-        CV_EXPORTS void rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, const Rect& rect);
+        CV_EXPORTS void rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, const Rect& rect, Stream& stream = Stream::Null());
-
-        // applies Canny edge detector and produces the edge map
-        // disabled until fix crash
-        //CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double threshold1, double threshold2, int apertureSize = 3);
-        //CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, GpuMat& buffer, double threshold1, double threshold2, int apertureSize = 3);
-        //CV_EXPORTS void Canny(const GpuMat& srcDx, const GpuMat& srcDy, GpuMat& edges, double threshold1, double threshold2, int apertureSize = 3);
-        //CV_EXPORTS void Canny(const GpuMat& srcDx, const GpuMat& srcDy, GpuMat& edges, GpuMat& buffer, double threshold1, double threshold2, int apertureSize = 3);
 
         //! computes Harris cornerness criteria at each image pixel
         CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, double k, int borderType=BORDER_REFLECT101);
@@ -792,7 +748,7 @@ namespace cv
         //! performs linear blending of two images
         //! to avoid accuracy errors sum of weigths shouldn't be very close to zero
         CV_EXPORTS void blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat& weights1, const GpuMat& weights2, 
-                                    GpuMat& result);
+            GpuMat& result, Stream& stream = Stream::Null());
 
         ////////////////////////////// Matrix reductions //////////////////////////////
 
@@ -863,17 +819,11 @@ namespace cv
         ///////////////////////////// Calibration 3D //////////////////////////////////
 
         CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
-                                        GpuMat& dst);
+                                        GpuMat& dst, Stream& stream = Stream::Null());
-
-        CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
-                                        GpuMat& dst, const Stream& stream);
-
-        CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
-                                      const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst);
 
         CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
                                       const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst, 
-                                      const Stream& stream);
+                                      Stream& stream = Stream::Null());
 
         CV_EXPORTS void solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
                                        const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false,
@@ -893,7 +843,7 @@ namespace cv
         public:
             BaseRowFilter_GPU(int ksize_, int anchor_) : ksize(ksize_), anchor(anchor_) {}
             virtual ~BaseRowFilter_GPU() {}
-            virtual void operator()(const GpuMat& src, GpuMat& dst) = 0;
+            virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null()) = 0;
             int ksize, anchor;
         };
 
@@ -908,7 +858,7 @@ namespace cv
         public:
             BaseColumnFilter_GPU(int ksize_, int anchor_) : ksize(ksize_), anchor(anchor_) {}
             virtual ~BaseColumnFilter_GPU() {}
-            virtual void operator()(const GpuMat& src, GpuMat& dst) = 0;
+            virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null()) = 0;
             int ksize, anchor;
         };
 
@@ -922,7 +872,7 @@ namespace cv
         public:
             BaseFilter_GPU(const Size& ksize_, const Point& anchor_) : ksize(ksize_), anchor(anchor_) {}
             virtual ~BaseFilter_GPU() {}
-            virtual void operator()(const GpuMat& src, GpuMat& dst) = 0;
+            virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null()) = 0;
             Size ksize;
             Point anchor;
         };
@@ -938,7 +888,7 @@ namespace cv
         public:
             virtual ~FilterEngine_GPU() {}
 
-            virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1)) = 0;
+            virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1), Stream& stream = Stream::Null()) = 0;
         };
 
         //! returns the non-separable filter engine with the specified filter
@@ -1027,47 +977,47 @@ namespace cv
 
         //! smooths the image using the normalized box filter
         //! supports CV_8UC1, CV_8UC4 types
-        CV_EXPORTS void boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize, Point anchor = Point(-1,-1));
+        CV_EXPORTS void boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize, Point anchor = Point(-1,-1), Stream& stream = Stream::Null());
 
         //! a synonym for normalized box filter
-        static inline void blur(const GpuMat& src, GpuMat& dst, Size ksize, Point anchor = Point(-1,-1)) { boxFilter(src, dst, -1, ksize, anchor); }
+        static inline void blur(const GpuMat& src, GpuMat& dst, Size ksize, Point anchor = Point(-1,-1), Stream& stream = Stream::Null()) { boxFilter(src, dst, -1, ksize, anchor, stream); }
 
         //! erodes the image (applies the local minimum operator)
-        CV_EXPORTS void erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1);
+        CV_EXPORTS void erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1, Stream& stream = Stream::Null());
 
         //! dilates the image (applies the local maximum operator)
-        CV_EXPORTS void dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1);
+        CV_EXPORTS void dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1, Stream& stream = Stream::Null());
 
         //! applies an advanced morphological operation to the image
-        CV_EXPORTS void morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1);
+        CV_EXPORTS void morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1, Stream& stream = Stream::Null());
 
         //! applies non-separable 2D linear filter to the image
-        CV_EXPORTS void filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor=Point(-1,-1));
+        CV_EXPORTS void filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor=Point(-1,-1), Stream& stream = Stream::Null());
 
         //! applies separable 2D linear filter to the image
         CV_EXPORTS void sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernelX, const Mat& kernelY,
-            Point anchor = Point(-1,-1), int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1);
+            Point anchor = Point(-1,-1), int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1, Stream& stream = Stream::Null());
 
         //! applies generalized Sobel operator to the image
         CV_EXPORTS void Sobel(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, int ksize = 3, double scale = 1,
-            int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1);
+            int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1, Stream& stream = Stream::Null());
 
         //! applies the vertical or horizontal Scharr operator to the image
         CV_EXPORTS void Scharr(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, double scale = 1,
-            int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1);
+            int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1, Stream& stream = Stream::Null());
 
         //! smooths the image using Gaussian filter.
         CV_EXPORTS void GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double sigma1, double sigma2 = 0,
-            int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1);
+            int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1, Stream& stream = Stream::Null());
 
         //! applies Laplacian operator to the image
         //! supports only ksize = 1 and ksize = 3
-        CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1);
+        CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1, Stream& stream = Stream::Null());
 
         //////////////////////////////// Image Labeling ////////////////////////////////
 
         //!performs labeling via graph cuts
-        CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf);
+        CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf, Stream& stream = Stream::Null());
 
         ////////////////////////////////// Histograms //////////////////////////////////
 
@@ -1076,23 +1026,23 @@ namespace cv
         //! Calculates histogram with evenly distributed bins for signle channel source.
         //! Supports CV_8UC1, CV_16UC1 and CV_16SC1 source types.
         //! Output hist will have one row and histSize cols and CV_32SC1 type.
-        CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel);
+        CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
         //! Calculates histogram with evenly distributed bins for four-channel source.
         //! All channels of source are processed separately.
         //! Supports CV_8UC4, CV_16UC4 and CV_16SC4 source types.
         //! Output hist[i] will have one row and histSize[i] cols and CV_32SC1 type.
-        CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4]);
+        CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
         //! Calculates histogram with bins determined by levels array.
         //! levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
         //! Supports CV_8UC1, CV_16UC1, CV_16SC1 and CV_32FC1 source types.
         //! Output hist will have one row and (levels.cols-1) cols and CV_32SC1 type.
-        CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels);
+        CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, Stream& stream = Stream::Null());
         //! Calculates histogram with bins determined by levels array.
         //! All levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
         //! All channels of source are processed separately.
         //! Supports CV_8UC4, CV_16UC4, CV_16SC4 and CV_32FC4 source types.
         //! Output hist[i] will have one row and (levels[i].cols-1) cols and CV_32SC1 type.
-        CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4]);
+        CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], Stream& stream = Stream::Null());
 
         //////////////////////////////// StereoBM_GPU ////////////////////////////////
 
@@ -1110,10 +1060,7 @@ namespace cv
 
             //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair
             //! Output disparity has CV_8U type.
-            void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity);
+            void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
-
-            //! async version
-            void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream & stream);
 
             //! Some heuristics that tries to estmate
             // if current GPU will be faster than CPU in this algorithm.
@@ -1165,15 +1112,11 @@ namespace cv
 
             //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair,
             //! if disparity is empty output type will be CV_16S else output type will be disparity.type().
-            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
+            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
-
-            //! async version
-            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
 
 
             //! version for user specified data term
-            void operator()(const GpuMat& data, GpuMat& disparity);
+            void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream = Stream::Null());
-            void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream);
 
             int ndisp;
 
@@ -1194,7 +1137,7 @@ namespace cv
 
         /////////////////////////// StereoConstantSpaceBP ///////////////////////////
         // "A Constant-Space Belief Propagation Algorithm for Stereo Matching"
-        // Qingxiong Yang, Liang Wang<EFBFBD>, Narendra Ahuja
+        // Qingxiong Yang, Liang Wang, Narendra Ahuja
         // http://vision.ai.uiuc.edu/~qyang6/
 
         class CV_EXPORTS StereoConstantSpaceBP
@@ -1224,10 +1167,7 @@ namespace cv
 
             //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair,
             //! if disparity is empty output type will be CV_16S else output type will be disparity.type().
-            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
+            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
-
-            //! async version
-            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
 
             int ndisp;
 
@@ -1280,10 +1220,7 @@ namespace cv
 
             //! the disparity map refinement operator. Refine disparity map using joint bilateral filtering given a single color image.
             //! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type.
-            void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst);
+            void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream = Stream::Null());
-
-            //! async version
-            void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream);
 
         private:
             int ndisp;
@@ -1406,7 +1343,7 @@ namespace cv
             // distance.at<float>(0, queryIdx) will contain distance
             void matchSingle(const GpuMat& queryDescs, const GpuMat& trainDescs,
                 GpuMat& trainIdx, GpuMat& distance,
-                const GpuMat& mask = GpuMat());
+                const GpuMat& mask = GpuMat(), Stream& stream = Stream::Null());
 
             // Download trainIdx and distance to CPU vector with DMatch
             static void matchDownload(const GpuMat& trainIdx, const GpuMat& distance, std::vector<DMatch>& matches);
@@ -1425,7 +1362,7 @@ namespace cv
             // distance.at<float>(0, queryIdx) will contain distance
             void matchCollection(const GpuMat& queryDescs, const GpuMat& trainCollection,
                 GpuMat& trainIdx, GpuMat& imgIdx, GpuMat& distance,
-                const GpuMat& maskCollection);
+                const GpuMat& maskCollection, Stream& stream = Stream::Null());
 
             // Download trainIdx, imgIdx and distance to CPU vector with DMatch
             static void matchDownload(const GpuMat& trainIdx, const GpuMat& imgIdx, const GpuMat& distance,
@@ -1443,7 +1380,7 @@ namespace cv
             // allDist.at<float>(queryIdx, trainIdx) will contain FLT_MAX, if trainIdx is one from k best,
             // otherwise it will contain distance between queryIdx and trainIdx descriptors
             void knnMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
-                GpuMat& trainIdx, GpuMat& distance, GpuMat& allDist, int k, const GpuMat& mask = GpuMat());
+                GpuMat& trainIdx, GpuMat& distance, GpuMat& allDist, int k, const GpuMat& mask = GpuMat(), Stream& stream = Stream::Null());
 
             // Download trainIdx and distance to CPU vector with DMatch
             // compactResult is used when mask is not empty. If compactResult is false matches
@@ -1478,7 +1415,7 @@ namespace cv
             // Matches doesn't sorted.
             void radiusMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
                 GpuMat& trainIdx, GpuMat& nMatches, GpuMat& distance, float maxDistance,
-                const GpuMat& mask = GpuMat());
+                const GpuMat& mask = GpuMat(), Stream& stream = Stream::Null());
 
             // Download trainIdx, nMatches and distance to CPU vector with DMatch.
             // matches will be sorted in increasing order of distances.

modules/gpu/src/arithm.cpp

@@ -48,37 +48,36 @@ using namespace std;
 
 #if !defined (HAVE_CUDA)
 
-void cv::gpu::transpose(const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::transpose(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::flip(const GpuMat&, GpuMat&, int) { throw_nogpu(); }
+void cv::gpu::flip(const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
-void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::exp(const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::exp(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::log(const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::log(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::magnitude(const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::magnitude(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::magnitudeSqr(const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::magnitudeSqr(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::magnitude(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::magnitude(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::magnitude(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::magnitudeSqr(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::magnitudeSqr(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::phase(const GpuMat&, const GpuMat&, GpuMat&, bool, Stream&) { throw_nogpu(); }
-void cv::gpu::magnitudeSqr(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, Stream&) { throw_nogpu(); }
-void cv::gpu::phase(const GpuMat&, const GpuMat&, GpuMat&, bool) { throw_nogpu(); }
+void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, Stream&) { throw_nogpu(); }
-void cv::gpu::phase(const GpuMat&, const GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
-void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool) { throw_nogpu(); }
-void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
-void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool) { throw_nogpu(); }
-void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
 
 ////////////////////////////////////////////////////////////////////////
 // transpose
 
-void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
+void cv::gpu::transpose(const GpuMat& src, GpuMat& dst, Stream& s)
 {
     CV_Assert(src.elemSize() == 1 || src.elemSize() == 4 || src.elemSize() == 8);
 
     dst.create( src.cols, src.rows, src.type() );
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
     if (src.elemSize() == 1)
     {
+        NppStreamHandler h(stream);
+
         NppiSize sz;
         sz.width  = src.cols;
         sz.height = src.rows;
@@ -87,6 +86,8 @@ void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
     }
     else if (src.elemSize() == 4)
     {
+        NppStStreamHandler h(stream);
+
         NcvSize32u sz;
         sz.width  = src.cols;
         sz.height = src.rows;
@@ -96,6 +97,8 @@ void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
     }
     else // if (src.elemSize() == 8)
     {
+        NppStStreamHandler h(stream);
+
         NcvSize32u sz;
         sz.width  = src.cols;
         sz.height = src.rows;
@@ -104,13 +107,14 @@ void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
             dst.ptr<Ncv64u>(), dst.step, sz) );		
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
 // flip
 
-void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
+void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode, Stream& s)
 {
     CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
 
@@ -120,6 +124,10 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
     sz.width  = src.cols;
     sz.height = src.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     if (src.type() == CV_8UC1)
     {
         nppSafeCall( nppiMirror_8u_C1R(src.ptr<Npp8u>(), src.step,
@@ -133,13 +141,14 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
             (flipCode == 0 ? NPP_HORIZONTAL_AXIS : (flipCode > 0 ? NPP_VERTICAL_AXIS : NPP_BOTH_AXIS))) );
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
 // LUT
 
-void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst)
+void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& s)
 {
     class LevelsInit
     {
@@ -172,6 +181,10 @@ void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst)
     Mat nppLut;
     lut.convertTo(nppLut, CV_32S);
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     if (src.type() == CV_8UC1)
     {
         nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, nppLut.ptr<Npp32s>(), lvls.pLevels, 256) );
@@ -192,13 +205,14 @@ void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst)
         nppSafeCall( nppiLUT_Linear_8u_C3R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, pValues3, lvls.pLevels3, lvls.nValues3) );
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
 // exp
 
-void cv::gpu::exp(const GpuMat& src, GpuMat& dst)
+void cv::gpu::exp(const GpuMat& src, GpuMat& dst, Stream& s)
 {
     CV_Assert(src.type() == CV_32FC1);
 
@@ -208,15 +222,20 @@ void cv::gpu::exp(const GpuMat& src, GpuMat& dst)
     sz.width = src.cols;
     sz.height = src.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     nppSafeCall( nppiExp_32f_C1R(src.ptr<Npp32f>(), src.step, dst.ptr<Npp32f>(), dst.step, sz) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
 // log
 
-void cv::gpu::log(const GpuMat& src, GpuMat& dst)
+void cv::gpu::log(const GpuMat& src, GpuMat& dst, Stream& s)
 {
     CV_Assert(src.type() == CV_32FC1);
 
@@ -226,9 +245,14 @@ void cv::gpu::log(const GpuMat& src, GpuMat& dst)
     sz.width = src.cols;
     sz.height = src.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     nppSafeCall( nppiLn_32f_C1R(src.ptr<Npp32f>(), src.step, dst.ptr<Npp32f>(), dst.step, sz) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
@@ -238,7 +262,7 @@ namespace
 {
     typedef NppStatus (*nppMagnitude_t)(const Npp32fc* pSrc, int nSrcStep, Npp32f* pDst, int nDstStep, NppiSize oSizeROI);
 
-    inline void npp_magnitude(const GpuMat& src, GpuMat& dst, nppMagnitude_t func)
+    inline void npp_magnitude(const GpuMat& src, GpuMat& dst, nppMagnitude_t func, cudaStream_t stream)
     {
         CV_Assert(src.type() == CV_32FC2);
 
@@ -248,20 +272,23 @@ namespace
         sz.width = src.cols;
         sz.height = src.rows;
 
+        NppStreamHandler h(stream);
+
         nppSafeCall( func(src.ptr<Npp32fc>(), src.step, dst.ptr<Npp32f>(), dst.step, sz) );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 }
 
-void cv::gpu::magnitude(const GpuMat& src, GpuMat& dst)
+void cv::gpu::magnitude(const GpuMat& src, GpuMat& dst, Stream& stream)
 {
-    ::npp_magnitude(src, dst, nppiMagnitude_32fc32f_C1R);
+    ::npp_magnitude(src, dst, nppiMagnitude_32fc32f_C1R, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::magnitudeSqr(const GpuMat& src, GpuMat& dst)
+void cv::gpu::magnitudeSqr(const GpuMat& src, GpuMat& dst, Stream& stream)
 {
-    ::npp_magnitude(src, dst, nppiMagnitudeSqr_32fc32f_C1R);
+    ::npp_magnitude(src, dst, nppiMagnitudeSqr_32fc32f_C1R, StreamAccessor::getStream(stream));
 }
 
 ////////////////////////////////////////////////////////////////////////
@@ -310,52 +337,27 @@ namespace
     }
 }
 
-void cv::gpu::magnitude(const GpuMat& x, const GpuMat& y, GpuMat& dst)
+void cv::gpu::magnitude(const GpuMat& x, const GpuMat& y, GpuMat& dst, Stream& stream)
-{
-    ::cartToPolar_caller(x, y, &dst, false, 0, false, 0);
-}
-
-void cv::gpu::magnitude(const GpuMat& x, const GpuMat& y, GpuMat& dst, const Stream& stream)
 {
     ::cartToPolar_caller(x, y, &dst, false, 0, false, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& dst)
+void cv::gpu::magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& dst, Stream& stream)
-{
-    ::cartToPolar_caller(x, y, &dst, true, 0, false, 0);
-}
-
-void cv::gpu::magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& dst, const Stream& stream)
 {
     ::cartToPolar_caller(x, y, &dst, true, 0, false, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees)
+void cv::gpu::phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees, Stream& stream)
-{
-    ::cartToPolar_caller(x, y, 0, false, &angle, angleInDegrees, 0);
-}
-
-void cv::gpu::phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees, const Stream& stream)
 {
     ::cartToPolar_caller(x, y, 0, false, &angle, angleInDegrees, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& mag, GpuMat& angle, bool angleInDegrees)
+void cv::gpu::cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& mag, GpuMat& angle, bool angleInDegrees, Stream& stream)
-{
-    ::cartToPolar_caller(x, y, &mag, false, &angle, angleInDegrees, 0);
-}
-
-void cv::gpu::cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& mag, GpuMat& angle, bool angleInDegrees, const Stream& stream)
 {
     ::cartToPolar_caller(x, y, &mag, false, &angle, angleInDegrees, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees)
+void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, Stream& stream)
-{
-    ::polarToCart_caller(magnitude, angle, x, y, angleInDegrees, 0);
-}
-
-void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, const Stream& stream)
 {
     ::polarToCart_caller(magnitude, angle, x, y, angleInDegrees, StreamAccessor::getStream(stream));
 }

modules/gpu/src/bilateral_filter.cpp

@@ -51,7 +51,6 @@ using namespace std;
 cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int, int, int) { throw_nogpu(); }
 cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int, int, int, float, float, float) { throw_nogpu(); }
 
-void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
 void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
@@ -101,7 +100,7 @@ namespace
     template <typename T>
     void bilateral_filter_operator(int ndisp, int radius, int iters, float edge_threshold,float max_disc_threshold, 
                                    GpuMat& table_color, GpuMat& table_space, 
-                                   const GpuMat& disp, const GpuMat& img, GpuMat& dst, cudaStream_t stream)
+                                   const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream)
     {
         short edge_disc = max<short>(short(1), short(ndisp * edge_threshold + 0.5));
         short max_disc = short(ndisp * max_disc_threshold + 0.5);
@@ -109,14 +108,19 @@ namespace
         bf::load_constants(table_color.ptr<float>(), table_space, ndisp, radius, edge_disc, max_disc);
 
         if (&dst != &disp)
+        {
+            if (stream)
+                stream.enqueueCopy(disp, dst);
+            else
                 disp.copyTo(dst);
+        }
 
-        bf::bilateral_filter_gpu((DevMem2D_<T>)dst, img, img.channels(), iters, stream);
+        bf::bilateral_filter_gpu((DevMem2D_<T>)dst, img, img.channels(), iters, StreamAccessor::getStream(stream));
     }
 
     typedef void (*bilateral_filter_operator_t)(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, 
                                                 GpuMat& table_color, GpuMat& table_space, 
-                                                const GpuMat& disp, const GpuMat& img, GpuMat& dst, cudaStream_t stream);
+                                                const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream);
     
     const bilateral_filter_operator_t operators[] = 
         {bilateral_filter_operator<unsigned char>, 0, 0, bilateral_filter_operator<short>, 0, 0, 0, 0};
@@ -139,18 +143,11 @@ cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp_, int radi
     calc_space_weighted_filter(table_space, radius * 2 + 1, radius + 1.0f);
 }
 
-void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat& disp, const GpuMat& img, GpuMat& dst)
-{
-    CV_DbgAssert(0 < ndisp && 0 < radius && 0 < iters);
-    CV_Assert(disp.rows == img.rows && disp.cols == img.cols && (disp.type() == CV_8U || disp.type() == CV_16S) && (img.type() == CV_8UC1 || img.type() == CV_8UC3));
-    operators[disp.type()](ndisp, radius, iters, edge_threshold, max_disc_threshold, table_color, table_space, disp, img, dst, 0);
-}
-
 void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream)
 {
     CV_DbgAssert(0 < ndisp && 0 < radius && 0 < iters);
     CV_Assert(disp.rows == img.rows && disp.cols == img.cols && (disp.type() == CV_8U || disp.type() == CV_16S) && (img.type() == CV_8UC1 || img.type() == CV_8UC3));
-    operators[disp.type()](ndisp, radius, iters, edge_threshold, max_disc_threshold, table_color, table_space, disp, img, dst, StreamAccessor::getStream(stream));
+    operators[disp.type()](ndisp, radius, iters, edge_threshold, max_disc_threshold, table_color, table_space, disp, img, dst, stream);
 }
 
 #endif /* !defined (HAVE_CUDA) */

modules/gpu/src/blend.cpp

@@ -48,8 +48,7 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA)
 
-void cv::gpu::blendLinear(const GpuMat&, const GpuMat&, const GpuMat&, const GpuMat&, 
+void cv::gpu::blendLinear(const GpuMat&, const GpuMat&, const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-                          GpuMat&) { throw_nogpu(); }
 
 #else
 
@@ -57,14 +56,14 @@ namespace cv { namespace gpu
 {
     template <typename T>
     void blendLinearCaller(int rows, int cols, int cn, const PtrStep_<T> img1, const PtrStep_<T> img2, 
-                           const PtrStep_<float> weights1, const PtrStep_<float> weights2, PtrStep_<T> result);
+                           const PtrStep_<float> weights1, const PtrStep_<float> weights2, PtrStep_<T> result, cudaStream_t stream);
 
     void blendLinearCaller8UC4(int rows, int cols, const PtrStep img1, const PtrStep img2, 
-                               const PtrStepf weights1, const PtrStepf weights2, PtrStep result);
+                               const PtrStepf weights1, const PtrStepf weights2, PtrStep result, cudaStream_t stream);
 }}
 
 void cv::gpu::blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat& weights1, const GpuMat& weights2, 
-                          GpuMat& result)
+                          GpuMat& result, Stream& stream)
 {
     CV_Assert(img1.size() == img2.size());
     CV_Assert(img1.type() == img2.type());
@@ -83,12 +82,12 @@ void cv::gpu::blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat&
     {
     case CV_8U:
         if (cn != 4)
-            blendLinearCaller<uchar>(size.height, size.width, cn, img1, img2, weights1, weights2, result);
+            blendLinearCaller<uchar>(size.height, size.width, cn, img1, img2, weights1, weights2, result, StreamAccessor::getStream(stream));
         else
-            blendLinearCaller8UC4(size.height, size.width, img1, img2, weights1, weights2, result);
+            blendLinearCaller8UC4(size.height, size.width, img1, img2, weights1, weights2, result, StreamAccessor::getStream(stream));
         break;
     case CV_32F:
-        blendLinearCaller<float>(size.height, size.width, cn, img1, img2, weights1, weights2, result);
+        blendLinearCaller<float>(size.height, size.width, cn, img1, img2, weights1, weights2, result, StreamAccessor::getStream(stream));
         break;
     default:
         CV_Error(CV_StsUnsupportedFormat, "bad image depth in linear blending function");

modules/gpu/src/brute_force_matcher.cpp

@@ -54,18 +54,18 @@ const vector<GpuMat>& cv::gpu::BruteForceMatcher_GPU_base::getTrainDescriptors()
 void cv::gpu::BruteForceMatcher_GPU_base::clear() { throw_nogpu(); }
 bool cv::gpu::BruteForceMatcher_GPU_base::empty() const { throw_nogpu(); return true; }
 bool cv::gpu::BruteForceMatcher_GPU_base::isMaskSupported() const { throw_nogpu(); return true; }
-void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat&, const GpuMat&, vector<DMatch>&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat&, const GpuMat&, vector<DMatch>&, const GpuMat&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::makeGpuCollection(GpuMat&, GpuMat&, const vector<GpuMat>&) { throw_nogpu(); }
-void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat&, const GpuMat&, const GpuMat&, std::vector<DMatch>&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat&, std::vector<DMatch>&, const std::vector<GpuMat>&) { throw_nogpu(); }
-void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, int, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, int, const GpuMat&, Stream&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::knnMatchDownload(const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, bool) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, int, const GpuMat&, bool) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, std::vector< std::vector<DMatch> >&, int, const std::vector<GpuMat>&, bool) { throw_nogpu(); }
-void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, float, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, float, const GpuMat&, Stream&) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::radiusMatchDownload(const GpuMat&, const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, bool) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, float, const GpuMat&, bool) { throw_nogpu(); }
 void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, std::vector< std::vector<DMatch> >&, float, const std::vector<GpuMat>&, bool) { throw_nogpu(); }
@@ -77,47 +77,47 @@ namespace cv { namespace gpu { namespace bfmatcher
     template <typename T>
     void matchSingleL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
     template <typename T>
     void matchSingleL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
     template <typename T>
     void matchSingleHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, 
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
     template <typename T>
     void matchCollectionL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
     template <typename T>
     void matchCollectionL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
     template <typename T>
     void matchCollectionHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection, 
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
 
     template <typename T>
     void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
     template <typename T>
     void knnMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
     template <typename T>
     void knnMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
 
     template <typename T>
     void radiusMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
     template <typename T>
     void radiusMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
     template <typename T>
     void radiusMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
 }}}
 
 namespace
@@ -168,7 +168,7 @@ bool cv::gpu::BruteForceMatcher_GPU_base::isMaskSupported() const
 // Match
 
 void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs, const GpuMat& trainDescs,
-    GpuMat& trainIdx, GpuMat& distance, const GpuMat& mask)
+    GpuMat& trainIdx, GpuMat& distance, const GpuMat& mask, Stream& stream)
 {
     if (queryDescs.empty() || trainDescs.empty())
         return;
@@ -177,7 +177,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs,
 
     typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12);
+        bool cc_12, cudaStream_t stream);
 
     static const match_caller_t match_callers[3][8] =
     {
@@ -213,7 +213,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs,
 
     // For single train there is no need to save imgIdx, so we just save imgIdx to trainIdx.
     // trainIdx store after imgIdx, so we doesn't lose it value.
-    func(queryDescs, trainDescs, mask, trainIdx, trainIdx, distance, cc_12);
+    func(queryDescs, trainDescs, mask, trainIdx, trainIdx, distance, cc_12, StreamAccessor::getStream(stream));
 }
 
 void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat& trainIdx, const GpuMat& distance,
@@ -301,7 +301,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::makeGpuCollection(GpuMat& trainCollect
 }
 
 void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDescs, const GpuMat& trainCollection,
-    GpuMat& trainIdx, GpuMat& imgIdx, GpuMat& distance, const GpuMat& maskCollection)
+    GpuMat& trainIdx, GpuMat& imgIdx, GpuMat& distance, const GpuMat& maskCollection, Stream& stream)
 {
     if (queryDescs.empty() || trainCollection.empty())
         return;
@@ -310,7 +310,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDes
 
     typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
-        const DevMem2Df& distance, bool cc_12);
+        const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
 
     static const match_caller_t match_callers[3][8] =
     {
@@ -344,7 +344,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDes
 
     bool cc_12 = TargetArchs::builtWith(FEATURE_SET_COMPUTE_12) && DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
 
-    func(queryDescs, trainCollection, maskCollection, trainIdx, imgIdx, distance, cc_12);
+    func(queryDescs, trainCollection, maskCollection, trainIdx, imgIdx, distance, cc_12, StreamAccessor::getStream(stream));
 }
 
 void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat& trainIdx, const GpuMat& imgIdx,
@@ -403,7 +403,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat& queryDescs, vector
 // KnnMatch
 
 void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
-    GpuMat& trainIdx, GpuMat& distance, GpuMat& allDist, int k, const GpuMat& mask)
+    GpuMat& trainIdx, GpuMat& distance, GpuMat& allDist, int k, const GpuMat& mask, Stream& stream)
 {
     if (queryDescs.empty() || trainDescs.empty())
         return;
@@ -411,7 +411,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
     using namespace cv::gpu::bfmatcher;
 
     typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
 
     static const match_caller_t match_callers[3][8] =
     {
@@ -436,16 +436,24 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
     const int nTrain = trainDescs.rows;
 
     trainIdx.create(nQuery, k, CV_32S);
-    trainIdx.setTo(Scalar::all(-1));
     distance.create(nQuery, k, CV_32F);
-
     ensureSizeIsEnough(nQuery, nTrain, CV_32FC1, allDist);
+
+    if (stream)
+    {
+        stream.enqueueMemSet(trainIdx, Scalar::all(-1));
+        stream.enqueueMemSet(allDist, Scalar::all(numeric_limits<float>::max()));
+    }
+    else
+    {
+        trainIdx.setTo(Scalar::all(-1));
         allDist.setTo(Scalar::all(numeric_limits<float>::max()));
+    }
 
     match_caller_t func = match_callers[distType][queryDescs.depth()];
     CV_Assert(func != 0);
 
-    func(queryDescs, trainDescs, k, mask, trainIdx, distance, allDist);
+    func(queryDescs, trainDescs, k, mask, trainIdx, distance, allDist, StreamAccessor::getStream(stream));
 }
 
 void cv::gpu::BruteForceMatcher_GPU_base::knnMatchDownload(const GpuMat& trainIdx, const GpuMat& distance,
@@ -547,7 +555,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs,
 // RadiusMatch
 
 void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
-    GpuMat& trainIdx, GpuMat& nMatches, GpuMat& distance, float maxDistance, const GpuMat& mask)
+    GpuMat& trainIdx, GpuMat& nMatches, GpuMat& distance, float maxDistance, const GpuMat& mask, Stream& stream)
 {
     if (queryDescs.empty() || trainDescs.empty())
         return;
@@ -555,7 +563,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs,
     using namespace cv::gpu::bfmatcher;
 
     typedef void (*radiusMatch_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
 
     static const radiusMatch_caller_t radiusMatch_callers[3][8] =
     {
@@ -583,17 +591,21 @@ void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs,
     CV_Assert(trainIdx.empty() || (trainIdx.rows == nQuery && trainIdx.size() == distance.size()));
 
     ensureSizeIsEnough(1, nQuery, CV_32SC1, nMatches);
-    nMatches.setTo(Scalar::all(0));
     if (trainIdx.empty())
     {
         trainIdx.create(nQuery, nTrain, CV_32SC1);
         distance.create(nQuery, nTrain, CV_32FC1);
     }
 
+    if (stream)
+        stream.enqueueMemSet(nMatches, Scalar::all(0));
+    else
+        nMatches.setTo(Scalar::all(0));
+
     radiusMatch_caller_t func = radiusMatch_callers[distType][queryDescs.depth()];
     CV_Assert(func != 0);
 
-    func(queryDescs, trainDescs, maxDistance, mask, trainIdx, nMatches.ptr<unsigned int>(), distance);
+    func(queryDescs, trainDescs, maxDistance, mask, trainIdx, nMatches.ptr<unsigned int>(), distance, StreamAccessor::getStream(stream));
 }
 
 void cv::gpu::BruteForceMatcher_GPU_base::radiusMatchDownload(const GpuMat& trainIdx, const GpuMat& nMatches,

modules/gpu/src/calib3d.cpp

@@ -44,20 +44,11 @@
 
 #if !defined(HAVE_CUDA)
 
-void cv::gpu::transformPoints(const GpuMat&, const Mat&, const Mat&,
+void cv::gpu::transformPoints(const GpuMat&, const Mat&, const Mat&, GpuMat&, Stream&) { throw_nogpu(); }
-                              GpuMat&) { throw_nogpu(); }
 
-void cv::gpu::transformPoints(const GpuMat&, const Mat&, const Mat&,
+void cv::gpu::projectPoints(const GpuMat&, const Mat&, const Mat&, const Mat&, const Mat&, GpuMat&, Stream&) { throw_nogpu(); }
-                              GpuMat&, const Stream&) { throw_nogpu(); }
 
-void cv::gpu::projectPoints(const GpuMat&, const Mat&, const Mat&,
+void cv::gpu::solvePnPRansac(const Mat&, const Mat&, const Mat&, const Mat&, Mat&, Mat&, bool, int, float, int, vector<int>*) { throw_nogpu(); }
-                            const Mat&, const Mat&, GpuMat&) { throw_nogpu(); }
-
-void cv::gpu::projectPoints(const GpuMat&, const Mat&, const Mat&,
-                            const Mat&, const Mat&, GpuMat&, const Stream&) { throw_nogpu(); }
-
-void cv::gpu::solvePnPRansac(const Mat&, const Mat&, const Mat&, const Mat&, 
-                             Mat&, Mat&, bool, int, float, int, vector<int>*) { throw_nogpu(); }
 
 #else
 
@@ -66,14 +57,12 @@ using namespace cv::gpu;
 
 namespace cv { namespace gpu { namespace transform_points 
 {
-    void call(const DevMem2D_<float3> src, const float* rot, const float* transl,
+    void call(const DevMem2D_<float3> src, const float* rot, const float* transl, DevMem2D_<float3> dst, cudaStream_t stream);
-              DevMem2D_<float3> dst, cudaStream_t stream);
 }}}
 
 namespace
 {
-    void transformPointsCaller(const GpuMat& src, const Mat& rvec, const Mat& tvec,
+    void transformPointsCaller(const GpuMat& src, const Mat& rvec, const Mat& tvec, GpuMat& dst, cudaStream_t stream)
-                               GpuMat& dst, cudaStream_t stream)
     {
         CV_Assert(src.rows == 1 && src.cols > 0 && src.type() == CV_32FC3);
         CV_Assert(rvec.size() == Size(3, 1) && rvec.type() == CV_32F);
@@ -88,30 +77,20 @@ namespace
     }
 }
 
-void cv::gpu::transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
+void cv::gpu::transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec, GpuMat& dst, Stream& stream)
-                              GpuMat& dst)
-{
-    ::transformPointsCaller(src, rvec, tvec, dst, 0);
-}
-
-void cv::gpu::transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
-                              GpuMat& dst, const Stream& stream)
 {
     ::transformPointsCaller(src, rvec, tvec, dst, StreamAccessor::getStream(stream));
 }
 
 namespace cv { namespace gpu { namespace project_points 
 {
-    void call(const DevMem2D_<float3> src, const float* rot, const float* transl,
+    void call(const DevMem2D_<float3> src, const float* rot, const float* transl, const float* proj, DevMem2D_<float2> dst, cudaStream_t stream);
-              const float* proj, DevMem2D_<float2> dst, cudaStream_t stream);
 }}}
 
 
 namespace
 {
-    void projectPointsCaller(const GpuMat& src, const Mat& rvec, const Mat& tvec,
+    void projectPointsCaller(const GpuMat& src, const Mat& rvec, const Mat& tvec, const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst, cudaStream_t stream)
-                             const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst,
-                             cudaStream_t stream)
     {
         CV_Assert(src.rows == 1 && src.cols > 0 && src.type() == CV_32FC3);
         CV_Assert(rvec.size() == Size(3, 1) && rvec.type() == CV_32F);
@@ -124,20 +103,11 @@ namespace
         Rodrigues(rvec, rot);
 
         dst.create(src.size(), CV_32FC2);
-        project_points::call(src, rot.ptr<float>(), tvec.ptr<float>(),
+        project_points::call(src, rot.ptr<float>(), tvec.ptr<float>(), camera_mat.ptr<float>(), dst,stream);
-                             camera_mat.ptr<float>(), dst,stream);
     }
 }
 
-void cv::gpu::projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
+void cv::gpu::projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec, const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst, Stream& stream)
-                            const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst)
-{
-    ::projectPointsCaller(src, rvec, tvec, camera_mat, dist_coef, dst, 0);
-}
-
-void cv::gpu::projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
-                            const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst,
-                            const Stream& stream)
 {
     ::projectPointsCaller(src, rvec, tvec, camera_mat, dist_coef, dst, StreamAccessor::getStream(stream));
 }

modules/gpu/src/color.cpp

@@ -47,8 +47,7 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA)
 
-void cv::gpu::cvtColor(const GpuMat&, GpuMat&, int, int) { throw_nogpu(); }
+void cv::gpu::cvtColor(const GpuMat&, GpuMat&, int, int, Stream&) { throw_nogpu(); }
-void cv::gpu::cvtColor(const GpuMat&, GpuMat&, int, int, const Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
 
@@ -455,12 +454,7 @@ namespace
     }
 }
 
-void cv::gpu::cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn)
+void cv::gpu::cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn, Stream& stream)
-{
-    cvtColor_caller(src, dst, code, dcn, 0);
-}
-
-void cv::gpu::cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn, const Stream& stream)
 {
     cvtColor_caller(src, dst, code, dcn, StreamAccessor::getStream(stream));
 }

modules/gpu/src/cuda/blend.cu

@@ -68,19 +68,22 @@ namespace cv { namespace gpu
 
     template <typename T>
     void blendLinearCaller(int rows, int cols, int cn, const PtrStep_<T> img1, const PtrStep_<T> img2, 
-                           const PtrStepf weights1, const PtrStepf weights2, PtrStep_<T> result)
+                           const PtrStepf weights1, const PtrStepf weights2, PtrStep_<T> result, cudaStream_t stream)
     {
         dim3 threads(16, 16);
         dim3 grid(divUp(cols * cn, threads.x), divUp(rows, threads.y));
         
-        blendLinearKernel<<<grid, threads>>>(rows, cols * cn, cn, img1, img2, weights1, weights2, result);
+        blendLinearKernel<<<grid, threads, 0, stream>>>(rows, cols * cn, cn, img1, img2, weights1, weights2, result);
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaGetLastError() );
+
+        if (stream == 0)
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
     template void blendLinearCaller<uchar>(int, int, int, const PtrStep, const PtrStep, 
-                                           const PtrStepf, const PtrStepf, PtrStep);
+                                           const PtrStepf, const PtrStepf, PtrStep, cudaStream_t stream);
     template void blendLinearCaller<float>(int, int, int, const PtrStepf, const PtrStepf, 
-                                           const PtrStepf, const PtrStepf, PtrStepf);
+                                           const PtrStepf, const PtrStepf, PtrStepf, cudaStream_t stream);
 
 
     __global__ void blendLinearKernel8UC4(int rows, int cols, const PtrStep img1, const PtrStep img2,
@@ -105,13 +108,16 @@ namespace cv { namespace gpu
 
 
     void blendLinearCaller8UC4(int rows, int cols, const PtrStep img1, const PtrStep img2, 
-                               const PtrStepf weights1, const PtrStepf weights2, PtrStep result)
+                               const PtrStepf weights1, const PtrStepf weights2, PtrStep result, cudaStream_t stream)
     {
         dim3 threads(16, 16);
         dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
         
-        blendLinearKernel8UC4<<<grid, threads>>>(rows, cols, img1, img2, weights1, weights2, result);
+        blendLinearKernel8UC4<<<grid, threads, 0, stream>>>(rows, cols, img1, img2, weights1, weights2, result);
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaGetLastError() );
+
+        if (stream == 0)
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 }}

modules/gpu/src/cuda/brute_force_matcher.cu

@@ -589,7 +589,7 @@ namespace cv { namespace gpu { namespace bfmatcher
 
     template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename T, typename Train, typename Mask>
     void matchSimple_caller(const DevMem2D_<T>& queryDescs, const Train& train, 
-        const Mask& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance)
+        const Mask& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, cudaStream_t stream)
     {
         StaticAssert<BLOCK_DIM_Y <= 64>::check(); // blockDimY vals must reduce by warp
 
@@ -597,14 +597,15 @@ namespace cv { namespace gpu { namespace bfmatcher
         dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
 
         match<BLOCK_DIM_X, BLOCK_DIM_Y, ReduceDescCalculatorSimple<BLOCK_DIM_X, T>, Dist, T>
-            <<<grid, threads>>>(queryDescs, train, mask, trainIdx.data, imgIdx.data, distance.data);
+            <<<grid, threads, 0, stream>>>(queryDescs, train, mask, trainIdx.data, imgIdx.data, distance.data);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     template <int BLOCK_DIM_X, int BLOCK_DIM_Y, int MAX_DESCRIPTORS_LEN, bool DESC_LEN_EQ_MAX_LEN, typename Dist, typename T, typename Train, typename Mask>
     void matchCached_caller(const DevMem2D_<T>& queryDescs, const Train& train, 
-        const Mask& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance)
+        const Mask& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, cudaStream_t stream)
     {
         StaticAssert<BLOCK_DIM_Y <= 64>::check();                                // blockDimY vals must reduce by warp
         StaticAssert<BLOCK_DIM_X * BLOCK_DIM_Y >= MAX_DESCRIPTORS_LEN>::check(); // block size must be greter than descriptors length
@@ -614,10 +615,11 @@ namespace cv { namespace gpu { namespace bfmatcher
         dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
 
         match<BLOCK_DIM_X, BLOCK_DIM_Y, ReduceDescCalculatorCached<BLOCK_DIM_X, MAX_DESCRIPTORS_LEN, DESC_LEN_EQ_MAX_LEN, T, typename Dist::ValueType>, Dist, T>
-              <<<grid, threads>>>(queryDescs, train, mask, trainIdx.data, imgIdx.data, distance.data);
+              <<<grid, threads, 0, stream>>>(queryDescs, train, mask, trainIdx.data, imgIdx.data, distance.data);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     
     ///////////////////////////////////////////////////////////////////////////////
@@ -626,167 +628,165 @@ namespace cv { namespace gpu { namespace bfmatcher
     template <typename Dist, typename T, typename Train, typename Mask>
     void matchDispatcher(const DevMem2D_<T>& queryDescs, const Train& train, 
         const Mask& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
-        bool cc_12)
+        bool cc_12, cudaStream_t stream)
     {
         if (queryDescs.cols < 64)
-            matchCached_caller<16, 16, 64, false, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchCached_caller<16, 16, 64, false, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
         else if (queryDescs.cols == 64)
-            matchCached_caller<16, 16, 64, true, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchCached_caller<16, 16, 64, true, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
         else if (queryDescs.cols < 128)
-            matchCached_caller<16, 16, 128, false, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchCached_caller<16, 16, 128, false, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
         else if (queryDescs.cols == 128)
-            matchCached_caller<16, 16, 128, true, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchCached_caller<16, 16, 128, true, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
         else if (queryDescs.cols < 256)
-            matchCached_caller<16, 16, 256, false, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchCached_caller<16, 16, 256, false, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
         else if (queryDescs.cols == 256 && cc_12)
-            matchCached_caller<16, 16, 256, true, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchCached_caller<16, 16, 256, true, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
         else
-            matchSimple_caller<16, 16, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance);
+            matchSimple_caller<16, 16, Dist>(queryDescs, train, mask, trainIdx, imgIdx, distance, stream);
-
-        cudaSafeCall( cudaThreadSynchronize() );
     }
 
     template <typename T>
     void matchSingleL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, 
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
-        bool cc_12)
+        bool cc_12, cudaStream_t stream)
     {
         SingleTrain<T> train((DevMem2D_<T>)trainDescs);
         if (mask.data)
         {
             SingleMask m(mask);
-            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, m, trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, m, trainIdx, imgIdx, distance, cc_12, stream);
         }
         else
         {
-            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12, stream);
         }
     }
 
-    template void matchSingleL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
 
     template <typename T>
     void matchSingleL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, 
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12)
+        bool cc_12, cudaStream_t stream)
     {
         SingleTrain<T> train((DevMem2D_<T>)trainDescs);
         if (mask.data)
         {
             SingleMask m(mask);
-            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, m, trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, m, trainIdx, imgIdx, distance, cc_12, stream);
         }
         else
         {
-            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12, stream);
         }
     }
 
-    template void matchSingleL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
 
     template <typename T>
     void matchSingleHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, 
         const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, 
-        bool cc_12)
+        bool cc_12, cudaStream_t stream)
     {
         SingleTrain<T> train((DevMem2D_<T>)trainDescs);
         if (mask.data)
         {
             SingleMask m(mask);
-            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, m, trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, m, trainIdx, imgIdx, distance, cc_12, stream);
         }
         else
         {
-            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12, stream);
         }
     }
 
-    template void matchSingleHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchSingleHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchSingleHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
 
     template <typename T>
     void matchCollectionL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection, 
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, 
-        const DevMem2Df& distance, bool cc_12)
+        const DevMem2Df& distance, bool cc_12, cudaStream_t stream)
     {
         TrainCollection<T> train((DevMem2D_<T>*)trainCollection.ptr(), trainCollection.cols, queryDescs.cols);
         if (maskCollection.data)
         {
             MaskCollection mask(maskCollection.data);
-            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, mask, trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, mask, trainIdx, imgIdx, distance, cc_12, stream);
         }
         else
         {
-            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12, stream);
         }
     }
 
-    template void matchCollectionL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
 
     template <typename T>
     void matchCollectionL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection, 
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, 
-        const DevMem2Df& distance, bool cc_12)
+        const DevMem2Df& distance, bool cc_12, cudaStream_t stream)
     {
         TrainCollection<T> train((DevMem2D_<T>*)trainCollection.ptr(), trainCollection.cols, queryDescs.cols);
         if (maskCollection.data)
         {
             MaskCollection mask(maskCollection.data);
-            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, mask, trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, mask, trainIdx, imgIdx, distance, cc_12, stream);
         }
         else
         {
-            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12, stream);
         }
     }
 
-    template void matchCollectionL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
 
     template <typename T>
     void matchCollectionHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection, 
         const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, 
-        const DevMem2Df& distance, bool cc_12)
+        const DevMem2Df& distance, bool cc_12, cudaStream_t stream)
     {
         TrainCollection<T> train((DevMem2D_<T>*)trainCollection.ptr(), trainCollection.cols, queryDescs.cols);
         if (maskCollection.data)
         {
             MaskCollection mask(maskCollection.data);
-            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, mask, trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, mask, trainIdx, imgIdx, distance, cc_12, stream);
         }
         else
         {
-            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12);
+            matchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, train, WithOutMask(), trainIdx, imgIdx, distance, cc_12, stream);
         }
     }
 
-    template void matchCollectionHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
-    template void matchCollectionHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12);
+    template void matchCollectionHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance, bool cc_12, cudaStream_t stream);
     
 ///////////////////////////////////////////////////////////////////////////////////
 //////////////////////////////////// Knn Match ////////////////////////////////////
@@ -833,16 +833,17 @@ namespace cv { namespace gpu { namespace bfmatcher
 
     template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename T, typename Mask>
     void calcDistance_caller(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, 
-        const Mask& mask, const DevMem2Df& distance)
+        const Mask& mask, const DevMem2Df& distance, cudaStream_t stream)
     {
         dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
         dim3 grid(queryDescs.rows, divUp(trainDescs.rows, BLOCK_DIM_Y), 1);
 
-        calcDistance<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, T><<<grid, threads>>>(
+        calcDistance<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, T><<<grid, threads, 0, stream>>>(
             queryDescs, trainDescs, mask, distance);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
         
     ///////////////////////////////////////////////////////////////////////////////
@@ -1010,105 +1011,106 @@ namespace cv { namespace gpu { namespace bfmatcher
     // find knn match kernel caller
 
     template <int BLOCK_SIZE>
-    void findKnnMatch_caller(int knn, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist)
+    void findKnnMatch_caller(int knn, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
     {
         dim3 threads(BLOCK_SIZE, 1, 1);
         dim3 grid(trainIdx.rows, 1, 1);
 
         for (int i = 0; i < knn; ++i)
         {
-            findBestMatch<BLOCK_SIZE><<<grid, threads>>>(allDist, i, trainIdx, distance);
+            findBestMatch<BLOCK_SIZE><<<grid, threads, 0, stream>>>(allDist, i, trainIdx, distance);
             cudaSafeCall( cudaGetLastError() );
         }
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     
     ///////////////////////////////////////////////////////////////////////////////
     // knn match caller
 
     template <typename Dist, typename T, typename Mask>
-    void calcDistanceDispatcher(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, const Mask& mask, const DevMem2Df& allDist)
+    void calcDistanceDispatcher(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, const Mask& mask, const DevMem2Df& allDist, cudaStream_t stream)
     {
-        calcDistance_caller<16, 16, Dist>(queryDescs, trainDescs, mask, allDist);
+        calcDistance_caller<16, 16, Dist>(queryDescs, trainDescs, mask, allDist, stream);
     }
 
-    void findKnnMatchDispatcher(int knn, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist)
+    void findKnnMatchDispatcher(int knn, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
     {
-        findKnnMatch_caller<256>(knn, trainIdx, distance, allDist);
+        findKnnMatch_caller<256>(knn, trainIdx, distance, allDist, stream);
     }
 
     template <typename T>
     void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist)
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
     {
         if (mask.data)
         {
-            calcDistanceDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, SingleMask(mask), allDist);
+            calcDistanceDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, SingleMask(mask), allDist, stream);
         }
         else
         {
-            calcDistanceDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, WithOutMask(), allDist);
+            calcDistanceDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, WithOutMask(), allDist, stream);
         }
 
-        findKnnMatchDispatcher(knn, trainIdx, distance, allDist);
+        findKnnMatchDispatcher(knn, trainIdx, distance, allDist, stream);
     }
 
-    template void knnMatchL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
 
     template <typename T>
     void knnMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist)
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
     {
         if (mask.data)
         {
             calcDistanceDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                SingleMask(mask), allDist);
+                SingleMask(mask), allDist, stream);
         }
         else
         {
             calcDistanceDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                WithOutMask(), allDist);
+                WithOutMask(), allDist, stream);
         }
 
-        findKnnMatchDispatcher(knn, trainIdx, distance, allDist);
+        findKnnMatchDispatcher(knn, trainIdx, distance, allDist, stream);
     }
 
-    template void knnMatchL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
 
     template <typename T>
     void knnMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist)
+        const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
     {
         if (mask.data)
         {
             calcDistanceDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                SingleMask(mask), allDist);
+                SingleMask(mask), allDist, stream);
         }
         else
         {
             calcDistanceDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                WithOutMask(), allDist);
+                WithOutMask(), allDist, stream);
         }
 
-        findKnnMatchDispatcher(knn, trainIdx, distance, allDist);
+        findKnnMatchDispatcher(knn, trainIdx, distance, allDist, stream);
     }
 
-    template void knnMatchHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
-    template void knnMatchHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
+    template void knnMatchHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
 
 ///////////////////////////////////////////////////////////////////////////////////
 /////////////////////////////////// Radius Match //////////////////////////////////
@@ -1166,16 +1168,17 @@ namespace cv { namespace gpu { namespace bfmatcher
     template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename T, typename Mask>
     void radiusMatch_caller(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, 
         float maxDistance, const Mask& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, 
-        const DevMem2Df& distance)
+        const DevMem2Df& distance, cudaStream_t stream)
     {
         dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
         dim3 grid(queryDescs.rows, divUp(trainDescs.rows, BLOCK_DIM_Y), 1);
 
-        radiusMatch<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, T><<<grid, threads>>>(
+        radiusMatch<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, T><<<grid, threads, 0, stream>>>(
             queryDescs, trainDescs, maxDistance, mask, trainIdx, nMatches, distance);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     
     ///////////////////////////////////////////////////////////////////////////////
@@ -1184,77 +1187,77 @@ namespace cv { namespace gpu { namespace bfmatcher
     template <typename Dist, typename T, typename Mask>
     void radiusMatchDispatcher(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, 
         float maxDistance, const Mask& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, 
-        const DevMem2Df& distance)
+        const DevMem2Df& distance, cudaStream_t stream)
     {
         radiusMatch_caller<16, 16, Dist>(queryDescs, trainDescs, maxDistance, mask, 
-            trainIdx, nMatches, distance);
+            trainIdx, nMatches, distance, stream);
     }
 
     template <typename T>
     void radiusMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance)
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream)
     {
         if (mask.data)
         {
             radiusMatchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                maxDistance, SingleMask(mask), trainIdx, nMatches, distance);
+                maxDistance, SingleMask(mask), trainIdx, nMatches, distance, stream);
         }
         else
         {
             radiusMatchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                maxDistance, WithOutMask(), trainIdx, nMatches, distance);
+                maxDistance, WithOutMask(), trainIdx, nMatches, distance, stream);
         }
     }
 
-    template void radiusMatchL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL1_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
 
     template <typename T>
     void radiusMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance)
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream)
     {
         if (mask.data)
         {
             radiusMatchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                maxDistance, SingleMask(mask), trainIdx, nMatches, distance);
+                maxDistance, SingleMask(mask), trainIdx, nMatches, distance, stream);
         }
         else
         {
             radiusMatchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                maxDistance, WithOutMask(), trainIdx, nMatches, distance);
+                maxDistance, WithOutMask(), trainIdx, nMatches, distance, stream);
         }
     }
 
-    template void radiusMatchL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL2_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
 
     template <typename T>
     void radiusMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
-        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance)
+        const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream)
     {
         if (mask.data)
         {
             radiusMatchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                maxDistance, SingleMask(mask), trainIdx, nMatches, distance);
+                maxDistance, SingleMask(mask), trainIdx, nMatches, distance, stream);
         }
         else
         {
             radiusMatchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, 
-                maxDistance, WithOutMask(), trainIdx, nMatches, distance);
+                maxDistance, WithOutMask(), trainIdx, nMatches, distance, stream);
         }
     }
 
-    template void radiusMatchHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
-    template void radiusMatchHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
+    template void radiusMatchHamming_gpu<int   >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance, const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance, cudaStream_t stream);
 }}}

modules/gpu/src/cuda/calib3d.cu

@@ -184,7 +184,9 @@ namespace cv { namespace gpu
 
             computeHypothesisScoresKernel<<<grid, threads, smem_size>>>(
                     num_points, object, image, dist_threshold, hypothesis_scores);
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall( cudaGetLastError() );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     } // namespace solvepnp_ransac
 

modules/gpu/src/cuda/element_operations.cu

@@ -64,19 +64,19 @@ namespace cv { namespace gpu { namespace mathfunc
     };
 
     template <typename T1, typename T2>
-    inline void compare_ne(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst)
+    inline void compare_ne(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream)
     {
         NotEqual<T1, T2> op;
-        transform(static_cast< DevMem2D_<T1> >(src1), static_cast< DevMem2D_<T2> >(src2), dst, op, 0);
+        transform(static_cast< DevMem2D_<T1> >(src1), static_cast< DevMem2D_<T2> >(src2), dst, op, stream);
     }
 
-    void compare_ne_8uc4(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst)
+    void compare_ne_8uc4(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream)
     {
-        compare_ne<uint, uint>(src1, src2, dst);
+        compare_ne<uint, uint>(src1, src2, dst, stream);
     }
-    void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst)
+    void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream)
     {
-        compare_ne<float, float>(src1, src2, dst);
+        compare_ne<float, float>(src1, src2, dst, stream);
     }
 
 
@@ -133,7 +133,7 @@ namespace cv { namespace gpu { namespace mathfunc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0) 
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 
@@ -165,7 +165,7 @@ namespace cv { namespace gpu { namespace mathfunc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0) 
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 
@@ -256,7 +256,7 @@ namespace cv { namespace gpu { namespace mathfunc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0) 
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 
@@ -290,7 +290,7 @@ namespace cv { namespace gpu { namespace mathfunc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0) 
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 

modules/gpu/src/cuda/filters.cu

@@ -129,7 +129,7 @@ namespace filter_krnls
 namespace cv { namespace gpu { namespace filters
 {
     template <int ksize, typename T, typename D, template<typename> class B>
-    void linearRowFilter_caller(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor)
+    void linearRowFilter_caller(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor, cudaStream_t stream)
     {
         dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y);
         dim3 grid(divUp(src.cols, BLOCK_DIM_X), divUp(src.rows, BLOCK_DIM_Y));
@@ -143,16 +143,17 @@ namespace cv { namespace gpu { namespace filters
                            "try bigger image or another border extrapolation mode", __FILE__, __LINE__);
         }
 
-        filter_krnls::linearRowFilter<ksize, T, D><<<grid, threads>>>(src, dst, anchor, b);
+        filter_krnls::linearRowFilter<ksize, T, D><<<grid, threads, 0, stream>>>(src, dst, anchor, b);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template <typename T, typename D>
-    void linearRowFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type)
+    void linearRowFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream)
     {
-        typedef void (*caller_t)(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor);
+        typedef void (*caller_t)(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor, cudaStream_t stream);
         static const caller_t callers[3][17] = 
         {
             {
@@ -216,15 +217,15 @@ namespace cv { namespace gpu { namespace filters
         
         loadLinearKernel(kernel, ksize);
 
-        callers[brd_type][ksize]((DevMem2D_<T>)src, (DevMem2D_<D>)dst, anchor);
+        callers[brd_type][ksize]((DevMem2D_<T>)src, (DevMem2D_<D>)dst, anchor, stream);
     }
 
-    template void linearRowFilter_gpu<uchar , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearRowFilter_gpu<uchar , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearRowFilter_gpu<uchar4, float4>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearRowFilter_gpu<uchar4, float4>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearRowFilter_gpu<short , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);;
+    template void linearRowFilter_gpu<short , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearRowFilter_gpu<short2, float2>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearRowFilter_gpu<short2, float2>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearRowFilter_gpu<int   , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearRowFilter_gpu<int   , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearRowFilter_gpu<float , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearRowFilter_gpu<float , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
 }}}
 
 namespace filter_krnls
@@ -269,7 +270,7 @@ namespace filter_krnls
 namespace cv { namespace gpu { namespace filters
 {
     template <int ksize, typename T, typename D, template<typename> class B>
-    void linearColumnFilter_caller(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor)
+    void linearColumnFilter_caller(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor, cudaStream_t stream)
     {
         dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y);
         dim3 grid(divUp(src.cols, BLOCK_DIM_X), divUp(src.rows, BLOCK_DIM_Y));
@@ -282,16 +283,17 @@ namespace cv { namespace gpu { namespace filters
                            "try bigger image or another border extrapolation mode", __FILE__, __LINE__);
         }
 
-        filter_krnls::linearColumnFilter<ksize, T, D><<<grid, threads>>>(src, dst, anchor, b);
+        filter_krnls::linearColumnFilter<ksize, T, D><<<grid, threads, 0, stream>>>(src, dst, anchor, b);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template <typename T, typename D>
-    void linearColumnFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type)
+    void linearColumnFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream)
     {
-        typedef void (*caller_t)(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor);
+        typedef void (*caller_t)(const DevMem2D_<T>& src, const DevMem2D_<D>& dst, int anchor, cudaStream_t stream);
         static const caller_t callers[3][17] = 
         {
             {
@@ -355,15 +357,15 @@ namespace cv { namespace gpu { namespace filters
         
         loadLinearKernel(kernel, ksize);
 
-        callers[brd_type][ksize]((DevMem2D_<T>)src, (DevMem2D_<D>)dst, anchor);
+        callers[brd_type][ksize]((DevMem2D_<T>)src, (DevMem2D_<D>)dst, anchor, stream);
     }
 
-    template void linearColumnFilter_gpu<float , uchar >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearColumnFilter_gpu<float , uchar >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearColumnFilter_gpu<float4, uchar4>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearColumnFilter_gpu<float4, uchar4>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearColumnFilter_gpu<float , short >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearColumnFilter_gpu<float , short >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearColumnFilter_gpu<float2, short2>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearColumnFilter_gpu<float2, short2>(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearColumnFilter_gpu<float , int   >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearColumnFilter_gpu<float , int   >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
-    template void linearColumnFilter_gpu<float , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    template void linearColumnFilter_gpu<float , float >(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
 }}}
 
 /////////////////////////////////////////////////////////////////////////////////////////////////
@@ -541,7 +543,7 @@ namespace cv { namespace gpu { namespace bf
         }
 
         if (stream != 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     void bilateral_filter_gpu(const DevMem2D& disp, const DevMem2D& img, int channels, int iters, cudaStream_t stream)

modules/gpu/src/cuda/hog.cu

@@ -220,7 +220,7 @@ void compute_hists(int nbins, int block_stride_x, int block_stride_y,
         img_block_width, grad, qangle, scale, block_hists);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -324,7 +324,7 @@ void normalize_hists(int nbins, int block_stride_x, int block_stride_y,
 
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -418,7 +418,7 @@ void classify_hists(int win_height, int win_width, int block_stride_y, int block
         block_hists, coefs, free_coef, threshold, labels);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 //----------------------------------------------------------------------------
@@ -463,7 +463,7 @@ void extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, i
         img_block_width, win_block_stride_x, win_block_stride_y, block_hists, descriptors);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -512,7 +512,7 @@ void extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, i
         img_block_width, win_block_stride_x, win_block_stride_y, block_hists, descriptors);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 //----------------------------------------------------------------------------
@@ -636,7 +636,8 @@ void compute_gradients_8UC4(int nbins, int height, int width, const DevMem2D& im
         compute_gradients_8UC4_kernel<nthreads, 0><<<gdim, bdim>>>(height, width, img, angle_scale, grad, qangle);
 
     cudaSafeCall( cudaGetLastError() );
-    cudaSafeCall(cudaThreadSynchronize());
+
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 template <int nthreads, int correct_gamma>
@@ -707,7 +708,8 @@ void compute_gradients_8UC1(int nbins, int height, int width, const DevMem2D& im
         compute_gradients_8UC1_kernel<nthreads, 0><<<gdim, bdim>>>(height, width, img, angle_scale, grad, qangle);
 
     cudaSafeCall( cudaGetLastError() );
-    cudaSafeCall(cudaThreadSynchronize());
+
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -765,7 +767,9 @@ static void resize_for_hog(const DevMem2D& src, DevMem2D dst, TEX& tex)
 
     resize_for_hog_kernel<<<grid, threads>>>(sx, sy, (DevMem2D_<T>)dst, colOfs);
     cudaSafeCall( cudaGetLastError() );
-    cudaSafeCall( cudaThreadSynchronize() );
+
+    cudaSafeCall( cudaDeviceSynchronize() );
+
     cudaSafeCall( cudaUnbindTexture(tex) );
 }
 

modules/gpu/src/cuda/imgproc.cu

@@ -139,7 +139,7 @@ namespace cv { namespace gpu { namespace imgproc
         remap_1c<<<grid, threads>>>(xmap.data, ymap.data, xmap.step, dst.data, dst.step, dst.cols, dst.rows);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );  
+        cudaSafeCall( cudaDeviceSynchronize() );  
         cudaSafeCall( cudaUnbindTexture(tex_remap) );
     }
     
@@ -153,7 +153,7 @@ namespace cv { namespace gpu { namespace imgproc
         remap_3c<<<grid, threads>>>(src.data, src.step, xmap.data, ymap.data, xmap.step, dst.data, dst.step, dst.cols, dst.rows);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() ); 
+        cudaSafeCall( cudaDeviceSynchronize() ); 
     }
 
 /////////////////////////////////// MeanShiftfiltering ///////////////////////////////////////////////
@@ -263,7 +263,7 @@ namespace cv { namespace gpu { namespace imgproc
         meanshift_kernel<<< grid, threads >>>( dst.data, dst.step, dst.cols, dst.rows, sp, sr, maxIter, eps );
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
         cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );        
     }
     extern "C" void meanShiftProc_gpu(const DevMem2D& src, DevMem2D dstr, DevMem2D dstsp, int sp, int sr, int maxIter, float eps) 
@@ -279,7 +279,7 @@ namespace cv { namespace gpu { namespace imgproc
         meanshiftproc_kernel<<< grid, threads >>>( dstr.data, dstr.step, dstsp.data, dstsp.step, dstr.cols, dstr.rows, sp, sr, maxIter, eps );
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
         cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );        
     }
 
@@ -397,7 +397,7 @@ namespace cv { namespace gpu { namespace imgproc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() ); 
+            cudaSafeCall( cudaDeviceSynchronize() ); 
     }
 
     void drawColorDisp_gpu(const DevMem2D_<short>& src, const DevMem2D& dst, int ndisp, const cudaStream_t& stream)
@@ -411,7 +411,7 @@ namespace cv { namespace gpu { namespace imgproc
         cudaSafeCall( cudaGetLastError() );
         
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 /////////////////////////////////// reprojectImageTo3D ///////////////////////////////////////////////
@@ -462,7 +462,7 @@ namespace cv { namespace gpu { namespace imgproc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     void reprojectImageTo3D_gpu(const DevMem2D& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream)
@@ -502,7 +502,7 @@ namespace cv { namespace gpu { namespace imgproc
         extractCovData_kernel<<<grid, threads>>>(Dx.cols, Dx.rows, Dx, Dy, dst);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 /////////////////////////////////////////// Corner Harris /////////////////////////////////////////////////
@@ -611,7 +611,8 @@ namespace cv { namespace gpu { namespace imgproc
 
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
+
         cudaSafeCall(cudaUnbindTexture(harrisDxTex));
         cudaSafeCall(cudaUnbindTexture(harrisDyTex));
     }
@@ -727,7 +728,8 @@ namespace cv { namespace gpu { namespace imgproc
 
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall(cudaDeviceSynchronize());
+
         cudaSafeCall(cudaUnbindTexture(minEigenValDxTex));
         cudaSafeCall(cudaUnbindTexture(minEigenValDyTex));
     }
@@ -763,7 +765,7 @@ namespace cv { namespace gpu { namespace imgproc
         column_sumKernel_32F<<<grid, threads>>>(src.cols, src.rows, src, dst);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     //////////////////////////////////////////////////////////////////////////
@@ -791,7 +793,7 @@ namespace cv { namespace gpu { namespace imgproc
         mulSpectrumsKernel<<<grid, threads>>>(a, b, c);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     //////////////////////////////////////////////////////////////////////////
@@ -820,7 +822,7 @@ namespace cv { namespace gpu { namespace imgproc
         mulSpectrumsKernel_CONJ<<<grid, threads>>>(a, b, c);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     //////////////////////////////////////////////////////////////////////////
@@ -850,7 +852,7 @@ namespace cv { namespace gpu { namespace imgproc
         mulAndScaleSpectrumsKernel<<<grid, threads>>>(a, b, scale, c);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     //////////////////////////////////////////////////////////////////////////
@@ -880,7 +882,7 @@ namespace cv { namespace gpu { namespace imgproc
         mulAndScaleSpectrumsKernel_CONJ<<<grid, threads>>>(a, b, scale, c);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     /////////////////////////////////////////////////////////////////////////
@@ -904,7 +906,9 @@ namespace cv { namespace gpu { namespace imgproc
         dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
 
         downsampleKernel<<<grid, threads>>>(src, rows, cols, k, dst);
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaGetLastError() );
+
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void downsampleCaller(const PtrStep src, int rows, int cols, int k, PtrStep dst);

modules/gpu/src/cuda/internal_shared.hpp

@@ -46,6 +46,8 @@
 #include "opencv2/gpu/devmem2d.hpp"
 #include "safe_call.hpp"
 #include "cuda_runtime.h"
+#include "npp.h"
+#include "NPP_staging.hpp"
 
 namespace cv
 {
@@ -106,6 +108,41 @@ namespace cv
             cudaSafeCall( cudaGetTextureReference(&tex, name) ); 
             cudaSafeCall( cudaUnbindTexture(tex) );
         }
+
+        class NppStreamHandler
+        {
+        public:
+            inline explicit NppStreamHandler(cudaStream_t newStream = 0)
+            {
+                oldStream = nppGetStream();
+                nppSetStream(newStream);
+            }
+
+            inline ~NppStreamHandler()
+            {
+                nppSetStream(oldStream);
+            }
+
+        private:
+            cudaStream_t oldStream;
+        };
+
+        class NppStStreamHandler
+        {
+        public:
+            inline explicit NppStStreamHandler(cudaStream_t newStream = 0)
+            {
+                oldStream = nppStSetActiveCUDAstream(newStream);
+            }
+
+            inline ~NppStStreamHandler()
+            {
+                nppStSetActiveCUDAstream(oldStream);
+            }
+
+        private:
+            cudaStream_t oldStream;
+        };
     }
 }
 

modules/gpu/src/cuda/match_template.cu

@@ -134,7 +134,7 @@ void matchTemplateNaive_CCORR_32F(const DevMem2D image, const DevMem2D templ,
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -165,7 +165,7 @@ void matchTemplateNaive_CCORR_8U(const DevMem2D image, const DevMem2D templ,
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -228,7 +228,7 @@ void matchTemplateNaive_SQDIFF_32F(const DevMem2D image, const DevMem2D templ,
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -259,7 +259,7 @@ void matchTemplateNaive_SQDIFF_8U(const DevMem2D image, const DevMem2D templ,
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -309,7 +309,7 @@ void matchTemplatePrepared_SQDIFF_8U(
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -360,7 +360,7 @@ void matchTemplatePrepared_SQDIFF_NORMED_8U(
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -392,7 +392,7 @@ void matchTemplatePrepared_CCOFF_8U(
             w, h, (float)templ_sum / (w * h), image_sum, result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -434,7 +434,7 @@ void matchTemplatePrepared_CCOFF_8UC2(
             image_sum_r, image_sum_g, result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -490,7 +490,7 @@ void matchTemplatePrepared_CCOFF_8UC3(
             image_sum_r, image_sum_g, image_sum_b, result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -556,7 +556,7 @@ void matchTemplatePrepared_CCOFF_8UC4(
             result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -602,7 +602,7 @@ void matchTemplatePrepared_CCOFF_NORMED_8U(
             image_sum, image_sqsum, result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -665,7 +665,7 @@ void matchTemplatePrepared_CCOFF_NORMED_8UC2(
             result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -742,7 +742,7 @@ void matchTemplatePrepared_CCOFF_NORMED_8UC3(
             result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -833,7 +833,7 @@ void matchTemplatePrepared_CCOFF_NORMED_8UC4(
             result);
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -877,7 +877,7 @@ void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -919,7 +919,7 @@ void extractFirstChannel_32F(const DevMem2D image, DevMem2Df result, int cn)
     }
     cudaSafeCall( cudaGetLastError() );
 
-    cudaSafeCall(cudaThreadSynchronize());
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 

modules/gpu/src/cuda/mathfunc.cu

@@ -153,7 +153,7 @@ namespace cv { namespace gpu { namespace mathfunc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     void cartToPolar_gpu(const DevMem2Df& x, const DevMem2Df& y, const DevMem2Df& mag, bool magSqr, const DevMem2Df& angle, bool angleInDegrees, cudaStream_t stream)
@@ -202,7 +202,7 @@ namespace cv { namespace gpu { namespace mathfunc
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     void polarToCart_gpu(const DevMem2Df& mag, const DevMem2Df& angle, const DevMem2Df& x, const DevMem2Df& y, bool angleInDegrees, cudaStream_t stream)

modules/gpu/src/cuda/matrix_operations.cu

@@ -87,7 +87,7 @@ namespace cv { namespace gpu { namespace matrix_operations {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall ( cudaThreadSynchronize() );        
+            cudaSafeCall ( cudaDeviceSynchronize() );
     }
 
     void copy_to_with_mask(const DevMem2D& mat_src, DevMem2D mat_dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream)
@@ -199,7 +199,7 @@ namespace cv { namespace gpu { namespace matrix_operations {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall ( cudaThreadSynchronize() );
+            cudaSafeCall ( cudaDeviceSynchronize() );
     }
 
     template void set_to_gpu<uchar >(const DevMem2D& mat, const uchar* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
@@ -222,7 +222,7 @@ namespace cv { namespace gpu { namespace matrix_operations {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall ( cudaThreadSynchronize() );
+            cudaSafeCall ( cudaDeviceSynchronize() );
     }
 
     template void set_to_gpu<uchar >(const DevMem2D& mat, const uchar* scalar, int channels, cudaStream_t stream);

modules/gpu/src/cuda/matrix_reductions.cu

@@ -275,7 +275,7 @@ namespace cv { namespace gpu { namespace mathfunc
         minMaxKernel<256, T, Mask8U><<<grid, threads>>>(src, Mask8U(mask), minval_buf, maxval_buf);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
@@ -306,7 +306,7 @@ namespace cv { namespace gpu { namespace mathfunc
         minMaxKernel<256, T, MaskTrue><<<grid, threads>>>(src, MaskTrue(), minval_buf, maxval_buf);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
@@ -363,7 +363,7 @@ namespace cv { namespace gpu { namespace mathfunc
         minMaxPass2Kernel<256, T><<<1, 256>>>(minval_buf, maxval_buf, grid.x * grid.y);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall(cudaDeviceSynchronize());
 
         T minval_, maxval_;
         cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
@@ -395,7 +395,7 @@ namespace cv { namespace gpu { namespace mathfunc
         minMaxPass2Kernel<256, T><<<1, 256>>>(minval_buf, maxval_buf, grid.x * grid.y);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
@@ -609,7 +609,7 @@ namespace cv { namespace gpu { namespace mathfunc
                                                            minloc_buf, maxloc_buf);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
@@ -650,7 +650,7 @@ namespace cv { namespace gpu { namespace mathfunc
                                                              minloc_buf, maxloc_buf);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall(cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost));
@@ -724,7 +724,7 @@ namespace cv { namespace gpu { namespace mathfunc
         minMaxLocPass2Kernel<256, T><<<1, 256>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall(cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost));
@@ -766,7 +766,7 @@ namespace cv { namespace gpu { namespace mathfunc
         minMaxLocPass2Kernel<256, T><<<1, 256>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         T minval_, maxval_;
         cudaSafeCall(cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost));
@@ -895,7 +895,7 @@ namespace cv { namespace gpu { namespace mathfunc
         countNonZeroKernel<256, T><<<grid, threads>>>(src, count_buf);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         uint count;
         cudaSafeCall(cudaMemcpy(&count, count_buf, sizeof(int), cudaMemcpyDeviceToHost));
@@ -942,7 +942,7 @@ namespace cv { namespace gpu { namespace mathfunc
         countNonZeroPass2Kernel<256, T><<<1, 256>>>(count_buf, grid.x * grid.y);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         uint count;
         cudaSafeCall(cudaMemcpy(&count, count_buf, sizeof(int), cudaMemcpyDeviceToHost));
@@ -1493,7 +1493,7 @@ namespace cv { namespace gpu { namespace mathfunc
 
             break;
         }
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         R result[4] = {0, 0, 0, 0};
         cudaSafeCall(cudaMemcpy(&result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
@@ -1543,7 +1543,7 @@ namespace cv { namespace gpu { namespace mathfunc
         }
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         R result[4] = {0, 0, 0, 0};
         cudaSafeCall(cudaMemcpy(&result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
@@ -1615,7 +1615,7 @@ namespace cv { namespace gpu { namespace mathfunc
 
             break;
         }
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         R result[4] = {0, 0, 0, 0};
         cudaSafeCall(cudaMemcpy(result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
@@ -1665,7 +1665,7 @@ namespace cv { namespace gpu { namespace mathfunc
         }
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         R result[4] = {0, 0, 0, 0};
         cudaSafeCall(cudaMemcpy(result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
@@ -1737,7 +1737,7 @@ namespace cv { namespace gpu { namespace mathfunc
 
             break;
         }
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         R result[4] = {0, 0, 0, 0};
         cudaSafeCall(cudaMemcpy(result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));
@@ -1787,7 +1787,7 @@ namespace cv { namespace gpu { namespace mathfunc
         }
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall(cudaThreadSynchronize());
+        cudaSafeCall( cudaDeviceSynchronize() );
 
         R result[4] = {0, 0, 0, 0};
         cudaSafeCall(cudaMemcpy(result, buf.ptr(0), sizeof(R) * cn, cudaMemcpyDeviceToHost));

modules/gpu/src/cuda/split_merge.cu

@@ -236,7 +236,7 @@ namespace cv { namespace gpu { namespace split_merge {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 
@@ -253,7 +253,7 @@ namespace cv { namespace gpu { namespace split_merge {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 
@@ -271,7 +271,7 @@ namespace cv { namespace gpu { namespace split_merge {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 
@@ -445,7 +445,7 @@ namespace cv { namespace gpu { namespace split_merge {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 
@@ -462,7 +462,7 @@ namespace cv { namespace gpu { namespace split_merge {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 
@@ -480,7 +480,7 @@ namespace cv { namespace gpu { namespace split_merge {
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall(cudaThreadSynchronize());
+            cudaSafeCall(cudaDeviceSynchronize());
     }
 
 

modules/gpu/src/cuda/stereobm.cu

@@ -328,7 +328,7 @@ template<int RADIUS> void kernel_caller(const DevMem2D& left, const DevMem2D& ri
     cudaSafeCall( cudaGetLastError() );
 
     if (stream == 0)
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
 };
 
 typedef void (*kernel_caller_t)(const DevMem2D& left, const DevMem2D& right, const DevMem2D& disp, int maxdisp, cudaStream_t & stream);
@@ -407,7 +407,7 @@ extern "C" void prefilter_xsobel(const DevMem2D& input, const DevMem2D& output,
     cudaSafeCall( cudaGetLastError() );
 
     if (stream == 0)   
-		cudaSafeCall( cudaThreadSynchronize() );    
+        cudaSafeCall( cudaDeviceSynchronize() );    
 
     cudaSafeCall( cudaUnbindTexture (texForSobel ) );
 }
@@ -532,9 +532,9 @@ extern "C" void postfilter_textureness(const DevMem2D& input, int winsz, float a
     cudaSafeCall( cudaGetLastError() );
 
     if (stream == 0)
-		cudaSafeCall( cudaThreadSynchronize() );		
+        cudaSafeCall( cudaDeviceSynchronize() );
-    cudaSafeCall( cudaUnbindTexture (texForTF) );
 
+    cudaSafeCall( cudaUnbindTexture (texForTF) );
 }
 
 }}}

modules/gpu/src/cuda/stereobp.cu

@@ -175,7 +175,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     template <> void comp_data_gpu<uchar, float>(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream)
     {
@@ -189,7 +189,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template <> void comp_data_gpu<uchar3, short>(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream)
@@ -204,7 +204,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     template <> void comp_data_gpu<uchar3, float>(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream)
     {
@@ -218,7 +218,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template <> void comp_data_gpu<uchar4, short>(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream)
@@ -233,7 +233,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     template <> void comp_data_gpu<uchar4, float>(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream)
     {
@@ -247,7 +247,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 ///////////////////////////////////////////////////////////////
@@ -287,7 +287,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void data_step_down_gpu<short>(int dst_cols, int dst_rows, int src_rows, const DevMem2D& src, const DevMem2D& dst, cudaStream_t stream);
@@ -337,7 +337,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void level_up_messages_gpu<short>(int dst_idx, int dst_cols, int dst_rows, int src_rows, DevMem2D* mus, DevMem2D* mds, DevMem2D* mls, DevMem2D* mrs, cudaStream_t stream);
@@ -457,7 +457,7 @@ namespace cv { namespace gpu { namespace bp
             cudaSafeCall( cudaGetLastError() );
 
             if (stream == 0)
-                cudaSafeCall( cudaThreadSynchronize() );
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     }
 
@@ -520,7 +520,7 @@ namespace cv { namespace gpu { namespace bp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void output_gpu<short>(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data, const DevMem2D_<short>& disp, cudaStream_t stream);

modules/gpu/src/cuda/stereocsbp.cu

@@ -385,7 +385,7 @@ namespace cv { namespace gpu { namespace csbp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
 
         dim3 threads(32, 8, 1);
         dim3 grid(1, 1, 1);
@@ -401,7 +401,7 @@ namespace cv { namespace gpu { namespace csbp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void init_data_cost(int rows, int cols, short* disp_selected_pyr, short* data_cost_selected, size_t msg_step,
@@ -586,7 +586,7 @@ namespace cv { namespace gpu { namespace csbp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void compute_data_cost(const short* disp_selected_pyr, short* data_cost, size_t msg_step1, size_t msg_step2,
@@ -713,7 +713,7 @@ namespace cv { namespace gpu { namespace csbp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
 
@@ -815,7 +815,7 @@ namespace cv { namespace gpu { namespace csbp
             cudaSafeCall( cudaGetLastError() );
 
             if (stream == 0)
-                cudaSafeCall( cudaThreadSynchronize() );
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     
@@ -885,7 +885,7 @@ namespace cv { namespace gpu { namespace csbp
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template void compute_disp(const short* u, const short* d, const short* l, const short* r, const short* data_cost_selected, const short* disp_selected, size_t msg_step, 

modules/gpu/src/cuda/surf.cu

@@ -181,7 +181,7 @@ namespace cv { namespace gpu { namespace surf
         icvCalcLayerDetAndTrace<<<grid, threads>>>(det, trace);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     ////////////////////////////////////////////////////////////////////////
@@ -338,7 +338,7 @@ namespace cv { namespace gpu { namespace surf
 
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     ////////////////////////////////////////////////////////////////////////
@@ -483,7 +483,7 @@ namespace cv { namespace gpu { namespace surf
         icvInterpolateKeypoint<<<grid, threads>>>(det, maxPosBuffer, featureX, featureY, featureLaplacian, featureSize, featureHessian, featureCounter);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     ////////////////////////////////////////////////////////////////////////
@@ -674,7 +674,7 @@ namespace cv { namespace gpu { namespace surf
         icvCalcOrientation<<<grid, threads>>>(featureX, featureY, featureSize, featureDir);
         cudaSafeCall( cudaGetLastError() );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     ////////////////////////////////////////////////////////////////////////
@@ -986,24 +986,24 @@ namespace cv { namespace gpu { namespace surf
             compute_descriptors64<<<dim3(nFeatures, 16, 1), dim3(6, 6, 1)>>>(descriptors, featureX, featureY, featureSize, featureDir);
             cudaSafeCall( cudaGetLastError() );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
 
             normalize_descriptors<64><<<dim3(nFeatures, 1, 1), dim3(64, 1, 1)>>>(descriptors);
             cudaSafeCall( cudaGetLastError() );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
         else
         {
             compute_descriptors128<<<dim3(nFeatures, 16, 1), dim3(6, 6, 1)>>>(descriptors, featureX, featureY, featureSize, featureDir);            
             cudaSafeCall( cudaGetLastError() );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
 
             normalize_descriptors<128><<<dim3(nFeatures, 1, 1), dim3(128, 1, 1)>>>(descriptors);            
             cudaSafeCall( cudaGetLastError() );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     }
 }}}

modules/gpu/src/cudastream.cpp

@@ -64,6 +64,8 @@ void cv::gpu::Stream::enqueueCopy(const GpuMat& /*src*/, GpuMat& /*dst*/) { thro
 void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }
 void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }
 void cv::gpu::Stream::enqueueConvert(const GpuMat& /*src*/, GpuMat& /*dst*/, int /*type*/, double /*a*/, double /*b*/) { throw_nogpu(); }
+Stream& cv::gpu::Stream::Null() { throw_nogpu(); static Stream s; return s; }
+cv::gpu::Stream::operator bool() const { throw_nogpu(); return false; }
 
 #else /* !defined (HAVE_CUDA) */
 
@@ -117,7 +119,7 @@ namespace
     }
 }
 
-CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream) { return stream.impl->stream; };
+CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream) { return stream.impl ? stream.impl->stream : 0; };
 
 void cv::gpu::Stream::create()
 {
@@ -188,18 +190,35 @@ void cv::gpu::Stream::enqueueUpload(const CudaMem& src, GpuMat& dst){ devcopy(sr
 void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst)  { devcopy(src, dst, impl->stream,   cudaMemcpyHostToDevice); }
 void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }
 
-void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val)
+void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar s)
 {
     CV_Assert((src.depth() != CV_64F) || 
         (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
 
+    if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
+    {
+        cudaSafeCall( cudaMemset2DAsync(src.data, src.step, 0, src.cols * src.elemSize(), src.rows, impl->stream) );
+        return;
+    }
+    if (src.depth() == CV_8U)
+    {
+        int cn = src.channels();
+
+        if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
+        {
+            int val = saturate_cast<uchar>(s[0]);
+            cudaSafeCall( cudaMemset2DAsync(src.data, src.step, val, src.cols * src.elemSize(), src.rows, impl->stream) );
+            return;
+        }
+    }
+
     typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, cudaStream_t stream);
     static const set_caller_t set_callers[] =
     {
         kernelSet<uchar>, kernelSet<schar>, kernelSet<ushort>, kernelSet<short>,
         kernelSet<int>, kernelSet<float>, kernelSet<double>
     };
-    set_callers[src.depth()](src, val, impl->stream);
+    set_callers[src.depth()](src, s, impl->stream);
 }
 
 void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val, const GpuMat& mask)
@@ -246,5 +265,17 @@ void cv::gpu::Stream::enqueueConvert(const GpuMat& src, GpuMat& dst, int rtype,
     matrix_operations::convert_gpu(psrc->reshape(1), sdepth, dst.reshape(1), ddepth, alpha, beta, impl->stream);
 }
 
+cv::gpu::Stream::operator bool() const
+{
+    return impl && impl->stream;
+}
+
+cv::gpu::Stream::Stream(Impl* impl_) : impl(impl_) {}
+
+cv::gpu::Stream& cv::gpu::Stream::Null()
+{
+    static Stream s((Impl*)0);
+    return s;
+}
 
 #endif /* !defined (HAVE_CUDA) */

modules/gpu/src/element_operations.cpp

@@ -47,35 +47,26 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA)
 
-void cv::gpu::add(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::add(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::add(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::add(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::subtract(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::subtract(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::subtract(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::subtract(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::multiply(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::multiply(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::multiply(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::multiply(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::divide(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::divide(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::divide(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::divide(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::absdiff(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::absdiff(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::absdiff(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::absdiff(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::compare(const GpuMat&, const GpuMat&, GpuMat&, int) { throw_nogpu(); }
+void cv::gpu::compare(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::min(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::max(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int, Stream&) {throw_nogpu(); return 0.0;}
-void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
-void cv::gpu::min(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
-void cv::gpu::min(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
-void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
-void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
-void cv::gpu::max(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
-void cv::gpu::max(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
-double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int) {throw_nogpu(); return 0.0;}
-double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int, const Stream&) {throw_nogpu(); return 0.0;}
 
 #else
 
@@ -90,7 +81,7 @@ namespace
 
     void nppArithmCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst,
                          npp_arithm_8u_t npp_func_8uc1, npp_arithm_8u_t npp_func_8uc4,
-                         npp_arithm_32s_t npp_func_32sc1, npp_arithm_32f_t npp_func_32fc1)
+                         npp_arithm_32s_t npp_func_32sc1, npp_arithm_32f_t npp_func_32fc1, cudaStream_t stream)
     {
         CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
         CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1);
@@ -100,6 +91,8 @@ namespace
         sz.width  = src1.cols;
         sz.height = src1.rows;
 
+        NppStreamHandler h(stream);
+
         switch (src1.type())
         {
         case CV_8UC1:
@@ -118,7 +111,8 @@ namespace
             CV_Assert(!"Unsupported source type");
         }
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 
     template<int SCN> struct NppArithmScalarFunc;
@@ -135,7 +129,7 @@ namespace
 
     template<typename NppArithmScalarFunc<1>::func_ptr func> struct NppArithmScalar<1, func>
     {
-        static void calc(const GpuMat& src, const Scalar& sc, GpuMat& dst)
+        static void calc(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream)
         {
             dst.create(src.size(), src.type());
 
@@ -143,14 +137,17 @@ namespace
             sz.width  = src.cols;
             sz.height = src.rows;
 
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<Npp32f>(), src.step, (Npp32f)sc[0], dst.ptr<Npp32f>(), dst.step, sz) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     template<typename NppArithmScalarFunc<2>::func_ptr func> struct NppArithmScalar<2, func>
     {
-        static void calc(const GpuMat& src, const Scalar& sc, GpuMat& dst)
+        static void calc(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream)
         {
             dst.create(src.size(), src.type());
 
@@ -162,78 +159,81 @@ namespace
             nValue.re = (Npp32f)sc[0];
             nValue.im = (Npp32f)sc[1];
 
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<Npp32fc>(), src.step, nValue, dst.ptr<Npp32fc>(), dst.step, sz) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 }
 
-void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
+void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
 {
-    nppArithmCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, nppiAdd_32s_C1R, nppiAdd_32f_C1R);
+    nppArithmCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, nppiAdd_32s_C1R, nppiAdd_32f_C1R, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
+void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
 {
-    nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R);
+    nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
+void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
 {
-    nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R);
+    nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
+void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
 {
-    nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R);
+    nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::add(const GpuMat& src, const Scalar& sc, GpuMat& dst)
+void cv::gpu::add(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
 {
-    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst);
+    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream);
     static const caller_t callers[] = {0, NppArithmScalar<1, nppiAddC_32f_C1R>::calc, NppArithmScalar<2, nppiAddC_32fc_C1R>::calc};
 
     CV_Assert(src.type() == CV_32FC1 || src.type() == CV_32FC2);
 
-    callers[src.channels()](src, sc, dst);
+    callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst)
+void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
 {
-    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst);
+    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream);
     static const caller_t callers[] = {0, NppArithmScalar<1, nppiSubC_32f_C1R>::calc, NppArithmScalar<2, nppiSubC_32fc_C1R>::calc};
 
     CV_Assert(src.type() == CV_32FC1 || src.type() == CV_32FC2);
 
-    callers[src.channels()](src, sc, dst);
+    callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst)
+void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
 {
-    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst);
+    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream);
     static const caller_t callers[] = {0, NppArithmScalar<1, nppiMulC_32f_C1R>::calc, NppArithmScalar<2, nppiMulC_32fc_C1R>::calc};
 
     CV_Assert(src.type() == CV_32FC1 || src.type() == CV_32FC2);
 
-    callers[src.channels()](src, sc, dst);
+    callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst)
+void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
 {
-    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst);
+    typedef void (*caller_t)(const GpuMat& src, const Scalar& sc, GpuMat& dst, cudaStream_t stream);
     static const caller_t callers[] = {0, NppArithmScalar<1, nppiDivC_32f_C1R>::calc, NppArithmScalar<2, nppiDivC_32fc_C1R>::calc};
 
     CV_Assert(src.type() == CV_32FC1 || src.type() == CV_32FC2);
 
-    callers[src.channels()](src, sc, dst);
+    callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream));
 }
 
 
 //////////////////////////////////////////////////////////////////////////////
 // Absolute difference
 
-void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
+void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s)
 {
     CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
 
@@ -245,6 +245,10 @@ void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
     sz.width  = src1.cols;
     sz.height = src1.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     switch (src1.type())
     {
     case CV_8UC1:
@@ -263,22 +267,28 @@ void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
         CV_Assert(!"Unsupported source type");
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
-void cv::gpu::absdiff(const GpuMat& src, const Scalar& s, GpuMat& dst)
+void cv::gpu::absdiff(const GpuMat& src1, const Scalar& src2, GpuMat& dst, Stream& s)
 {
-    CV_Assert(src.type() == CV_32FC1);
+    CV_Assert(src1.type() == CV_32FC1);
 
-    dst.create( src.size(), src.type() );
+    dst.create( src1.size(), src1.type() );
 
     NppiSize sz;
-    sz.width  = src.cols;
+    sz.width  = src1.cols;
-    sz.height = src.rows;
+    sz.height = src1.rows;
 
-    nppSafeCall( nppiAbsDiffC_32f_C1R(src.ptr<Npp32f>(), src.step, dst.ptr<Npp32f>(), dst.step, sz, (Npp32f)s[0]) );
+    cudaStream_t stream = StreamAccessor::getStream(s);
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    NppStreamHandler h(stream);
+
+    nppSafeCall( nppiAbsDiffC_32f_C1R(src1.ptr<Npp32f>(), src1.step, dst.ptr<Npp32f>(), dst.step, sz, (Npp32f)src2[0]) );
+
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
@@ -287,11 +297,11 @@ void cv::gpu::absdiff(const GpuMat& src, const Scalar& s, GpuMat& dst)
 
 namespace cv { namespace gpu { namespace mathfunc
 {
-    void compare_ne_8uc4(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst);
+    void compare_ne_8uc4(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream);
-    void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst);
+    void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream);
 }}}
 
-void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int cmpop)
+void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int cmpop, Stream& s)
 {
     CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
 
@@ -305,34 +315,42 @@ void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int c
     sz.width  = src1.cols;
     sz.height = src1.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
     if (src1.type() == CV_8UC4)
     {
         if (cmpop != CMP_NE)
         {
+            NppStreamHandler h(stream);
+
             nppSafeCall( nppiCompare_8u_C4R(src1.ptr<Npp8u>(), src1.step,
                 src2.ptr<Npp8u>(), src2.step,
                 dst.ptr<Npp8u>(), dst.step, sz, nppCmpOp[cmpop]) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
         else
         {
-            mathfunc::compare_ne_8uc4(src1, src2, dst);
+            mathfunc::compare_ne_8uc4(src1, src2, dst, stream);
         }
     }
     else
     {
         if (cmpop != CMP_NE)
         {
+            NppStreamHandler h(stream);
+
             nppSafeCall( nppiCompare_32f_C1R(src1.ptr<Npp32f>(), src1.step,
                 src2.ptr<Npp32f>(), src2.step,
                 dst.ptr<Npp8u>(), dst.step, sz, nppCmpOp[cmpop]) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
         else
         {
-            mathfunc::compare_ne_32f(src1, src2, dst);
+            mathfunc::compare_ne_32f(src1, src2, dst, stream);
         }
     }
 }
@@ -383,16 +401,7 @@ namespace
 }
 
 
-void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask)
+void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, Stream& stream)
-{
-    if (mask.empty())
-        ::bitwiseNotCaller(src, dst, 0);
-    else
-        ::bitwiseNotCaller(src, dst, mask, 0);
-}
-
-
-void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, const Stream& stream)
 {
     if (mask.empty())
         ::bitwiseNotCaller(src, dst, StreamAccessor::getStream(stream));
@@ -519,16 +528,7 @@ namespace
 }
 
 
-void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
+void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& stream)
-{
-    if (mask.empty())
-        ::bitwiseOrCaller(src1, src2, dst, 0);
-    else
-        ::bitwiseOrCaller(src1, src2, dst, mask, 0);
-}
-
-
-void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
 {
     if (mask.empty())
         ::bitwiseOrCaller(src1, src2, dst, StreamAccessor::getStream(stream));
@@ -537,16 +537,7 @@ void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, co
 }
 
 
-void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
+void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& stream)
-{
-    if (mask.empty())
-        ::bitwiseAndCaller(src1, src2, dst, 0);
-    else
-        ::bitwiseAndCaller(src1, src2, dst, mask, 0);
-}
-
-
-void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
 {
     if (mask.empty())
         ::bitwiseAndCaller(src1, src2, dst, StreamAccessor::getStream(stream));
@@ -555,16 +546,7 @@ void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, c
 }
 
 
-void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
+void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& stream)
-{
-    if (mask.empty())
-        ::bitwiseXorCaller(src1, src2, dst, 0);
-    else
-        ::bitwiseXorCaller(src1, src2, dst, mask, 0);
-}
-
-
-void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
 {
     if (mask.empty())
         ::bitwiseXorCaller(src1, src2, dst, StreamAccessor::getStream(stream));
@@ -624,22 +606,7 @@ namespace
     }
 }
 
-void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) 
+void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) 
-{
-    CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
-    CV_Assert((src1.depth() != CV_64F) || 
-        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
-
-    typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
-    static const func_t funcs[] = 
-    {
-        min_caller<uchar>, min_caller<schar>, min_caller<ushort>, min_caller<short>, min_caller<int>, 
-        min_caller<float>, min_caller<double>
-    };
-    funcs[src1.depth()](src1, src2, dst, 0);
-}
-
-void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream) 
 { 
     CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
     CV_Assert((src1.depth() != CV_64F) || 
@@ -653,22 +620,7 @@ void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Str
     };
     funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
 }
-
+void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream) 
-void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst) 
-{
-    CV_Assert((src1.depth() != CV_64F) || 
-        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
-
-    typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
-    static const func_t funcs[] = 
-    {
-        min_caller<uchar>, min_caller<schar>, min_caller<ushort>, min_caller<short>, min_caller<int>, 
-        min_caller<float>, min_caller<double>
-    };
-    funcs[src1.depth()](src1, src2, dst, 0);
-}
-
-void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream) 
 {
     CV_Assert((src1.depth() != CV_64F) || 
         (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
@@ -682,22 +634,7 @@ void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& st
     funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) 
+void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream) 
-{ 
-    CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
-    CV_Assert((src1.depth() != CV_64F) || 
-        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
-
-    typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
-    static const func_t funcs[] = 
-    {
-        max_caller<uchar>, max_caller<schar>, max_caller<ushort>, max_caller<short>, max_caller<int>, 
-        max_caller<float>, max_caller<double>
-    };
-    funcs[src1.depth()](src1, src2, dst, 0);
-}
-
-void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream) 
 { 
     CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
     CV_Assert((src1.depth() != CV_64F) || 
@@ -712,21 +649,7 @@ void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Str
     funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst) 
+void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream) 
-{
-    CV_Assert((src1.depth() != CV_64F) || 
-        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
-
-    typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
-    static const func_t funcs[] = 
-    {
-        max_caller<uchar>, max_caller<schar>, max_caller<ushort>, max_caller<short>, max_caller<int>, 
-        max_caller<float>, max_caller<double>
-    };
-    funcs[src1.depth()](src1, src2, dst, 0);
-}
-
-void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream) 
 {
     CV_Assert((src1.depth() != CV_64F) || 
         (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
@@ -760,10 +683,14 @@ namespace
     }
 }
 
-double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type)
+double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& s)
 {
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
     if (src.type() == CV_32FC1 && type == THRESH_TRUNC)
     {
+        NppStreamHandler h(stream);
+
         dst.create(src.size(), src.type());
 
         NppiSize sz;
@@ -773,7 +700,8 @@ double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double
         nppSafeCall( nppiThreshold_32f_C1R(src.ptr<Npp32f>(), src.step,
             dst.ptr<Npp32f>(), dst.step, sz, static_cast<Npp32f>(thresh), NPP_CMP_GREATER) );
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
     else
     {
@@ -801,37 +729,10 @@ double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double
             maxVal = cvRound(maxVal);
         }
 
-        callers[src.depth()](src, dst, thresh, maxVal, type, 0);
+        callers[src.depth()](src, dst, thresh, maxVal, type, stream);
     }
 
     return thresh;
 }
 
-double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, const Stream& stream)
-{
-    typedef void (*caller_t)(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, 
-        cudaStream_t stream);
-
-    static const caller_t callers[] = 
-    {
-        threshold_caller<unsigned char>, threshold_caller<signed char>, 
-        threshold_caller<unsigned short>, threshold_caller<short>, 
-        threshold_caller<int>, threshold_caller<float>, threshold_caller<double>
-    };
-
-    CV_Assert(src.channels() == 1 && src.depth() <= CV_64F);
-    CV_Assert(type <= THRESH_TOZERO_INV);
-
-    dst.create(src.size(), src.type());
-
-    if (src.depth() != CV_32F)
-    {
-        thresh = cvFloor(thresh);
-        maxVal = cvRound(maxVal);
-    }
-
-    callers[src.depth()](src, dst, thresh, maxVal, type, StreamAccessor::getStream(stream));
-    return thresh;
-}
-
 #endif

modules/gpu/src/filtering.cpp

@@ -66,16 +66,16 @@ Ptr<FilterEngine_GPU> cv::gpu::createGaussianFilter_GPU(int, Size, double, doubl
 Ptr<BaseFilter_GPU> cv::gpu::getMaxFilter_GPU(int, int, const Size&, Point) { throw_nogpu(); return Ptr<BaseFilter_GPU>(0); }
 Ptr<BaseFilter_GPU> cv::gpu::getMinFilter_GPU(int, int, const Size&, Point) { throw_nogpu(); return Ptr<BaseFilter_GPU>(0); }
 
-void cv::gpu::boxFilter(const GpuMat&, GpuMat&, int, Size, Point) { throw_nogpu(); }
+void cv::gpu::boxFilter(const GpuMat&, GpuMat&, int, Size, Point, Stream&) { throw_nogpu(); }
-void cv::gpu::erode( const GpuMat&, GpuMat&, const Mat&, Point, int) { throw_nogpu(); }
+void cv::gpu::erode( const GpuMat&, GpuMat&, const Mat&, Point, int, Stream&) { throw_nogpu(); }
-void cv::gpu::dilate( const GpuMat&, GpuMat&, const Mat&, Point, int) { throw_nogpu(); }
+void cv::gpu::dilate( const GpuMat&, GpuMat&, const Mat&, Point, int, Stream&) { throw_nogpu(); }
-void cv::gpu::morphologyEx( const GpuMat&, GpuMat&, int, const Mat&, Point, int) { throw_nogpu(); }
+void cv::gpu::morphologyEx( const GpuMat&, GpuMat&, int, const Mat&, Point, int, Stream&) { throw_nogpu(); }
-void cv::gpu::filter2D(const GpuMat&, GpuMat&, int, const Mat&, Point) { throw_nogpu(); }
+void cv::gpu::filter2D(const GpuMat&, GpuMat&, int, const Mat&, Point, Stream&) { throw_nogpu(); }
-void cv::gpu::sepFilter2D(const GpuMat&, GpuMat&, int, const Mat&, const Mat&, Point, int, int) { throw_nogpu(); }
+void cv::gpu::sepFilter2D(const GpuMat&, GpuMat&, int, const Mat&, const Mat&, Point, int, int, Stream&) { throw_nogpu(); }
-void cv::gpu::Sobel(const GpuMat&, GpuMat&, int, int, int, int, double, int, int) { throw_nogpu(); }
+void cv::gpu::Sobel(const GpuMat&, GpuMat&, int, int, int, int, double, int, int, Stream&) { throw_nogpu(); }
-void cv::gpu::Scharr(const GpuMat&, GpuMat&, int, int, int, double, int, int) { throw_nogpu(); }
+void cv::gpu::Scharr(const GpuMat&, GpuMat&, int, int, int, double, int, int, Stream&) { throw_nogpu(); }
-void cv::gpu::GaussianBlur(const GpuMat&, GpuMat&, Size, double, double, int, int) { throw_nogpu(); }
+void cv::gpu::GaussianBlur(const GpuMat&, GpuMat&, Size, double, double, int, int, Stream&) { throw_nogpu(); }
-void cv::gpu::Laplacian(const GpuMat&, GpuMat&, int, int, double) { throw_nogpu(); }
+void cv::gpu::Laplacian(const GpuMat&, GpuMat&, int, int, double, Stream&) { throw_nogpu(); }
 
 #else
 
@@ -137,21 +137,25 @@ namespace
             filter2D(filter2D_), srcType(srcType_), dstType(dstType_)
         {}
 
-        virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1))
+        virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1), Stream& stream = Stream::Null())
         {
             CV_Assert(src.type() == srcType);
 
             Size src_size = src.size();
 
             dst.create(src_size, dstType);
-            dst = Scalar(0.0);
+
+            if (stream)
+                stream.enqueueMemSet(dst, Scalar::all(0.0));
+            else
+                dst.setTo(Scalar::all(0.0));
 
             normalizeROI(roi, filter2D->ksize, filter2D->anchor, src_size);
 
             GpuMat srcROI = src(roi);
             GpuMat dstROI = dst(roi);
 
-            (*filter2D)(srcROI, dstROI);
+            (*filter2D)(srcROI, dstROI, stream);
         }
 
         Ptr<BaseFilter_GPU> filter2D;
@@ -181,16 +185,25 @@ namespace
             anchor = Point(rowFilter->anchor, columnFilter->anchor);
         }
 
-        virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1))
+        virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1), Stream& stream = Stream::Null())
         {
             CV_Assert(src.type() == srcType);
 
             Size src_size = src.size();
 
             dst.create(src_size, dstType);
-            dst = Scalar(0.0);
             dstBuf.create(src_size, bufType);
+
+            if (stream)
+            {
+                stream.enqueueMemSet(dst, Scalar::all(0));
+                stream.enqueueMemSet(dstBuf, Scalar::all(0));
+            }
+            else
+            {
+                dst = Scalar(0.0);
                 dstBuf = Scalar(0.0);
+            }
 
             normalizeROI(roi, ksize, anchor, src_size);
 
@@ -198,8 +211,8 @@ namespace
             GpuMat dstROI = dst(roi);
             GpuMat dstBufROI = dstBuf(roi);
             
-            (*rowFilter)(srcROI, dstBufROI);
+            (*rowFilter)(srcROI, dstBufROI, stream);
-            (*columnFilter)(dstBufROI, dstROI);
+            (*columnFilter)(dstBufROI, dstROI, stream);
         }
 
         Ptr<BaseRowFilter_GPU> rowFilter;
@@ -229,15 +242,20 @@ namespace
     public:
         NppRowSumFilter(int ksize_, int anchor_) : BaseRowFilter_GPU(ksize_, anchor_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
             sz.height = src.rows;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( nppiSumWindowRow_8u32f_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp32f>(), dst.step, sz, ksize, anchor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 }
@@ -258,15 +276,20 @@ namespace
     public:
         NppColumnSumFilter(int ksize_, int anchor_) : BaseColumnFilter_GPU(ksize_, anchor_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
             sz.height = src.rows;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( nppiSumWindowColumn_8u32f_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp32f>(), dst.step, sz, ksize, anchor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 }
@@ -293,7 +316,7 @@ namespace
     public:
         NPPBoxFilter(const Size& ksize_, const Point& anchor_, nppFilterBox_t func_) : BaseFilter_GPU(ksize_, anchor_), func(func_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
@@ -305,9 +328,14 @@ namespace
             oAnchor.x = anchor.x;
             oAnchor.y = anchor.y;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+            
             nppSafeCall( func(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, oKernelSize, oAnchor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
 
         nppFilterBox_t func;
@@ -331,7 +359,7 @@ Ptr<FilterEngine_GPU> cv::gpu::createBoxFilter_GPU(int srcType, int dstType, con
     return createFilter2D_GPU(boxFilter, srcType, dstType);
 }
 
-void cv::gpu::boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize, Point anchor)
+void cv::gpu::boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize, Point anchor, Stream& stream)
 {
     int sdepth = src.depth(), cn = src.channels();
     if( ddepth < 0 )
@@ -340,7 +368,7 @@ void cv::gpu::boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize,
     dst.create(src.size(), CV_MAKETYPE(ddepth, cn));
 
     Ptr<FilterEngine_GPU> f = createBoxFilter_GPU(src.type(), dst.type(), ksize, anchor);
-    f->apply(src, dst);
+    f->apply(src, dst, Rect(0,0,-1,-1), stream);
 }
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -356,7 +384,7 @@ namespace
         NPPMorphFilter(const Size& ksize_, const Point& anchor_, const GpuMat& kernel_, nppMorfFilter_t func_) : 
             BaseFilter_GPU(ksize_, anchor_), kernel(kernel_), func(func_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
@@ -368,9 +396,14 @@ namespace
             oAnchor.x = anchor.x;
             oAnchor.y = anchor.y;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, kernel.ptr<Npp8u>(), oKernelSize, oAnchor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
 
         GpuMat kernel;
@@ -404,16 +437,16 @@ namespace
         MorphologyFilterEngine_GPU(const Ptr<BaseFilter_GPU>& filter2D_, int type, int iters_) : 
           Filter2DEngine_GPU(filter2D_, type, type), iters(iters_) {}
 
-        virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1))
+        virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1), Stream& stream = Stream::Null())
         {
             if (iters > 1)
                 morfBuf.create(src.size(), src.type());
 
-            Filter2DEngine_GPU::apply(src, dst);
+            Filter2DEngine_GPU::apply(src, dst, roi, stream);
             for(int i = 1; i < iters; ++i)
             {
                 dst.swap(morfBuf);
-                Filter2DEngine_GPU::apply(morfBuf, dst);
+                Filter2DEngine_GPU::apply(morfBuf, dst, roi, stream);
             }
         }
 
@@ -435,7 +468,7 @@ Ptr<FilterEngine_GPU> cv::gpu::createMorphologyFilter_GPU(int op, int type, cons
 
 namespace
 {
-    void morphOp(int op, const GpuMat& src, GpuMat& dst, const Mat& _kernel, Point anchor, int iterations)
+    void morphOp(int op, const GpuMat& src, GpuMat& dst, const Mat& _kernel, Point anchor, int iterations, Stream& stream)
     {
         Mat kernel;
         Size ksize = _kernel.data ? _kernel.size() : Size(3, 3);
@@ -444,6 +477,9 @@ namespace
 
         if (iterations == 0 || _kernel.rows * _kernel.cols == 1)
         {
+            if (stream)
+                stream.enqueueCopy(src, dst);
+            else
                 src.copyTo(dst);
             return;
         }
@@ -468,49 +504,49 @@ namespace
 
         Ptr<FilterEngine_GPU> f = createMorphologyFilter_GPU(op, src.type(), kernel, anchor, iterations);
 
-        f->apply(src, dst);
+        f->apply(src, dst, Rect(0,0,-1,-1), stream);
     }
 }
 
-void cv::gpu::erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor, int iterations)
+void cv::gpu::erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor, int iterations, Stream& stream)
 {
-    morphOp(MORPH_ERODE, src, dst, kernel, anchor, iterations);
+    morphOp(MORPH_ERODE, src, dst, kernel, anchor, iterations, stream);
 }
 
-void cv::gpu::dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor, int iterations)
+void cv::gpu::dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor, int iterations, Stream& stream)
 {
-    morphOp(MORPH_DILATE, src, dst, kernel, anchor, iterations);
+    morphOp(MORPH_DILATE, src, dst, kernel, anchor, iterations, stream);
 }
 
-void cv::gpu::morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor, int iterations)
+void cv::gpu::morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor, int iterations, Stream& stream)
 {
     GpuMat temp;
     switch( op )
     {
-    case MORPH_ERODE:   erode( src, dst, kernel, anchor, iterations); break;    
+    case MORPH_ERODE:   erode( src, dst, kernel, anchor, iterations, stream); break;
-    case MORPH_DILATE: dilate( src, dst, kernel, anchor, iterations); break;    
+    case MORPH_DILATE: dilate( src, dst, kernel, anchor, iterations, stream); break;
     case MORPH_OPEN:
-        erode( src, temp, kernel, anchor, iterations);
+        erode( src, temp, kernel, anchor, iterations, stream);
-        dilate( temp, dst, kernel, anchor, iterations);
+        dilate( temp, dst, kernel, anchor, iterations, stream);
         break;
     case CV_MOP_CLOSE:
-        dilate( src, temp, kernel, anchor, iterations);
+        dilate( src, temp, kernel, anchor, iterations, stream);
-         erode( temp, dst, kernel, anchor, iterations);
+         erode( temp, dst, kernel, anchor, iterations, stream);
         break;
     case CV_MOP_GRADIENT:
-         erode( src, temp, kernel, anchor, iterations);
+         erode( src, temp, kernel, anchor, iterations, stream);
-        dilate( src, dst, kernel, anchor, iterations);        
+        dilate( src, dst, kernel, anchor, iterations, stream);
-        subtract(dst, temp, dst);
+        subtract(dst, temp, dst, stream);
         break;
     case CV_MOP_TOPHAT:
-        erode( src, dst, kernel, anchor, iterations);
+        erode( src, dst, kernel, anchor, iterations, stream);
-        dilate( dst, temp, kernel, anchor, iterations);        
+        dilate( dst, temp, kernel, anchor, iterations, stream);
-        subtract(src, temp, dst);
+        subtract(src, temp, dst, stream);
         break;
     case CV_MOP_BLACKHAT:
-        dilate( src, dst, kernel, anchor, iterations);
+        dilate( src, dst, kernel, anchor, iterations, stream);
-        erode( dst, temp, kernel, anchor, iterations);
+        erode( dst, temp, kernel, anchor, iterations, stream);
-        subtract(temp, src, dst);
+        subtract(temp, src, dst, stream);
         break;
     default:
         CV_Error( CV_StsBadArg, "unknown morphological operation" );
@@ -531,7 +567,7 @@ namespace
         NPPLinearFilter(const Size& ksize_, const Point& anchor_, const GpuMat& kernel_, Npp32s nDivisor_, nppFilter2D_t func_) : 
             BaseFilter_GPU(ksize_, anchor_), kernel(kernel_), nDivisor(nDivisor_), func(func_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
@@ -543,10 +579,15 @@ namespace
             oAnchor.x = anchor.x;
             oAnchor.y = anchor.y;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+                                  
             nppSafeCall( func(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, 
                 kernel.ptr<Npp32s>(), oKernelSize, oAnchor, nDivisor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
 
         GpuMat kernel;
@@ -578,7 +619,7 @@ Ptr<FilterEngine_GPU> cv::gpu::createLinearFilter_GPU(int srcType, int dstType,
     return createFilter2D_GPU(linearFilter, srcType, dstType);
 }
 
-void cv::gpu::filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor)
+void cv::gpu::filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor, Stream& stream)
 {
     if( ddepth < 0 )
         ddepth = src.depth();
@@ -586,7 +627,7 @@ void cv::gpu::filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& ke
     dst.create(src.size(), CV_MAKETYPE(ddepth, src.channels()));
 
     Ptr<FilterEngine_GPU> f = createLinearFilter_GPU(src.type(), dst.type(), kernel, anchor);
-    f->apply(src, dst);
+    f->apply(src, dst, Rect(0, 0, -1, -1), stream);
 }
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -595,10 +636,10 @@ void cv::gpu::filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& ke
 namespace cv { namespace gpu { namespace filters
 {
     template <typename T, typename D>
-    void linearRowFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    void linearRowFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
 
     template <typename T, typename D>
-    void linearColumnFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    void linearColumnFilter_gpu(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
 }}}
 
 namespace
@@ -606,7 +647,7 @@ namespace
     typedef NppStatus (*nppFilter1D_t)(const Npp8u * pSrc, Npp32s nSrcStep, Npp8u * pDst, Npp32s nDstStep, NppiSize oROI, 
         const Npp32s * pKernel, Npp32s nMaskSize, Npp32s nAnchor, Npp32s nDivisor);
 
-    typedef void (*gpuFilter1D_t)(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type);
+    typedef void (*gpuFilter1D_t)(const DevMem2D& src, const DevMem2D& dst, const float kernel[], int ksize, int anchor, int brd_type, cudaStream_t stream);
 
     class NppLinearRowFilter : public BaseRowFilter_GPU
     {
@@ -614,15 +655,20 @@ namespace
         NppLinearRowFilter(int ksize_, int anchor_, const GpuMat& kernel_, Npp32s nDivisor_, nppFilter1D_t func_) : 
             BaseRowFilter_GPU(ksize_, anchor_), kernel(kernel_), nDivisor(nDivisor_), func(func_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
             sz.height = src.rows;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, kernel.ptr<Npp32s>(), ksize, anchor, nDivisor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
 
         GpuMat kernel;
@@ -636,9 +682,9 @@ namespace
         GpuLinearRowFilter(int ksize_, int anchor_, const Mat& kernel_, gpuFilter1D_t func_, int brd_type_) : 
             BaseRowFilter_GPU(ksize_, anchor_), kernel(kernel_), func(func_), brd_type(brd_type_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
-            func(src, dst, kernel.ptr<float>(), ksize, anchor, brd_type);
+            func(src, dst, kernel.ptr<float>(), ksize, anchor, brd_type, StreamAccessor::getStream(s));
         }
 
         Mat kernel;
@@ -720,15 +766,20 @@ namespace
         NppLinearColumnFilter(int ksize_, int anchor_, const GpuMat& kernel_, Npp32s nDivisor_, nppFilter1D_t func_) : 
             BaseColumnFilter_GPU(ksize_, anchor_), kernel(kernel_), nDivisor(nDivisor_), func(func_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
             sz.height = src.rows;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, kernel.ptr<Npp32s>(), ksize, anchor, nDivisor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
 
         GpuMat kernel;
@@ -742,9 +793,9 @@ namespace
         GpuLinearColumnFilter(int ksize_, int anchor_, const Mat& kernel_, gpuFilter1D_t func_, int brd_type_) : 
             BaseColumnFilter_GPU(ksize_, anchor_), kernel(kernel_), func(func_), brd_type(brd_type_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
-            func(src, dst, kernel.ptr<float>(), ksize, anchor, brd_type);
+            func(src, dst, kernel.ptr<float>(), ksize, anchor, brd_type, StreamAccessor::getStream(s));
         }
 
         Mat kernel;
@@ -834,7 +885,8 @@ Ptr<FilterEngine_GPU> cv::gpu::createSeparableLinearFilter_GPU(int srcType, int
     return createSeparableFilter_GPU(rowFilter, columnFilter, srcType, bufType, dstType);
 }
 
-void cv::gpu::sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernelX, const Mat& kernelY, Point anchor, int rowBorderType, int columnBorderType)
+void cv::gpu::sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernelX, const Mat& kernelY, Point anchor, int rowBorderType, int columnBorderType,
+                          Stream& stream)
 {
     if( ddepth < 0 )
         ddepth = src.depth();
@@ -842,7 +894,7 @@ void cv::gpu::sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat&
     dst.create(src.size(), CV_MAKETYPE(ddepth, src.channels()));
 
     Ptr<FilterEngine_GPU> f = createSeparableLinearFilter_GPU(src.type(), dst.type(), kernelX, kernelY, anchor, rowBorderType, columnBorderType);
-    f->apply(src, dst, Rect(0, 0, src.cols, src.rows));
+    f->apply(src, dst, Rect(0, 0, src.cols, src.rows), stream);
 }
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -855,7 +907,7 @@ Ptr<FilterEngine_GPU> cv::gpu::createDerivFilter_GPU(int srcType, int dstType, i
     return createSeparableLinearFilter_GPU(srcType, dstType, kx, ky, Point(-1,-1), rowBorderType, columnBorderType);
 }
 
-void cv::gpu::Sobel(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, int ksize, double scale, int rowBorderType, int columnBorderType)
+void cv::gpu::Sobel(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, int ksize, double scale, int rowBorderType, int columnBorderType, Stream& stream)
 {
     Mat kx, ky;
     getDerivKernels(kx, ky, dx, dy, ksize, false, CV_32F);
@@ -870,10 +922,10 @@ void cv::gpu::Sobel(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy,
             ky *= scale;
     }
     
-    sepFilter2D(src, dst, ddepth, kx, ky, Point(-1,-1), rowBorderType, columnBorderType);
+    sepFilter2D(src, dst, ddepth, kx, ky, Point(-1,-1), rowBorderType, columnBorderType, stream);
 }
 
-void cv::gpu::Scharr(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, double scale, int rowBorderType, int columnBorderType)
+void cv::gpu::Scharr(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, double scale, int rowBorderType, int columnBorderType, Stream& stream)
 {
     Mat kx, ky;
     getDerivKernels(kx, ky, dx, dy, -1, false, CV_32F);
@@ -888,10 +940,10 @@ void cv::gpu::Scharr(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy,
             ky *= scale;
     }
 
-    sepFilter2D(src, dst, ddepth, kx, ky, Point(-1,-1), rowBorderType, columnBorderType);
+    sepFilter2D(src, dst, ddepth, kx, ky, Point(-1,-1), rowBorderType, columnBorderType, stream);
 }
 
-void cv::gpu::Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize, double scale)
+void cv::gpu::Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize, double scale, Stream& stream)
 {
     CV_Assert(ksize == 1 || ksize == 3);
 
@@ -904,7 +956,7 @@ void cv::gpu::Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize, d
     if (scale != 1)
         kernel *= scale;
     
-    filter2D(src, dst, ddepth, kernel, Point(-1,-1));
+    filter2D(src, dst, ddepth, kernel, Point(-1,-1), stream);
 }
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -938,7 +990,7 @@ Ptr<FilterEngine_GPU> cv::gpu::createGaussianFilter_GPU(int type, Size ksize, do
     return createSeparableLinearFilter_GPU(type, type, kx, ky, Point(-1,-1), rowBorderType, columnBorderType);
 }
 
-void cv::gpu::GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double sigma1, double sigma2, int rowBorderType, int columnBorderType)
+void cv::gpu::GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double sigma1, double sigma2, int rowBorderType, int columnBorderType, Stream& stream)
 {
     if (ksize.width == 1 && ksize.height == 1)
     {
@@ -949,7 +1001,7 @@ void cv::gpu::GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double si
     dst.create(src.size(), src.type());
     
     Ptr<FilterEngine_GPU> f = createGaussianFilter_GPU(src.type(), ksize, sigma1, sigma2, rowBorderType, columnBorderType);
-    f->apply(src, dst, Rect(0, 0, src.cols, src.rows));
+    f->apply(src, dst, Rect(0, 0, src.cols, src.rows), stream);
 }
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -965,7 +1017,7 @@ namespace
     public:
         NPPRankFilter(const Size& ksize_, const Point& anchor_, nppFilterRank_t func_) : BaseFilter_GPU(ksize_, anchor_), func(func_) {}
 
-        virtual void operator()(const GpuMat& src, GpuMat& dst)
+        virtual void operator()(const GpuMat& src, GpuMat& dst, Stream& s = Stream::Null())
         {
             NppiSize sz;
             sz.width = src.cols;
@@ -977,9 +1029,14 @@ namespace
             oAnchor.x = anchor.x;
             oAnchor.y = anchor.y;
 
+            cudaStream_t stream = StreamAccessor::getStream(s);
+
+            NppStreamHandler h(stream);
+            
             nppSafeCall( func(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz, oKernelSize, oAnchor) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
 
         nppFilterRank_t func;

modules/gpu/src/graphcuts.cpp

@@ -44,11 +44,11 @@
 
 #if !defined (HAVE_CUDA)
 
-void cv::gpu::graphcut(GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::graphcut(GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
 
-void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf)
+void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf, Stream& s)
 {
     Size src_size = terminals.size();
     CV_Assert(terminals.type() == CV_32S);
@@ -73,17 +73,17 @@ void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTrans
     if ((size_t)bufsz > buf.cols * buf.rows * buf.elemSize())
         buf.create(1, bufsz, CV_8U);
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     nppSafeCall( nppiGraphcut_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(), top.ptr<Npp32s>(), bottom.ptr<Npp32s>(),
         terminals.step, leftTransp.step, sznpp, labels.ptr<Npp8u>(), labels.step, buf.ptr<Npp8u>()) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 
 #endif /* !defined (HAVE_CUDA) */
 
-
-
-
-
-

modules/gpu/src/imgproc_gpu.cpp

@@ -50,30 +50,24 @@ using namespace cv::gpu;
 void cv::gpu::remap(const GpuMat&, GpuMat&, const GpuMat&, const GpuMat&){ throw_nogpu(); }
 void cv::gpu::meanShiftFiltering(const GpuMat&, GpuMat&, int, int, TermCriteria) { throw_nogpu(); }
 void cv::gpu::meanShiftProc(const GpuMat&, GpuMat&, GpuMat&, int, int, TermCriteria) { throw_nogpu(); }
-void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int) { throw_nogpu(); }
+void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
-void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int, const Stream&) { throw_nogpu(); }
+void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, Stream&) { throw_nogpu(); }
-void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&) { throw_nogpu(); }
+void cv::gpu::resize(const GpuMat&, GpuMat&, Size, double, double, int, Stream&) { throw_nogpu(); }
-void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, const Stream&) { throw_nogpu(); }
+void cv::gpu::copyMakeBorder(const GpuMat&, GpuMat&, int, int, int, int, const Scalar&, Stream&) { throw_nogpu(); }
-void cv::gpu::resize(const GpuMat&, GpuMat&, Size, double, double, int) { throw_nogpu(); }
+void cv::gpu::warpAffine(const GpuMat&, GpuMat&, const Mat&, Size, int, Stream&) { throw_nogpu(); }
-void cv::gpu::copyMakeBorder(const GpuMat&, GpuMat&, int, int, int, int, const Scalar&) { throw_nogpu(); }
+void cv::gpu::warpPerspective(const GpuMat&, GpuMat&, const Mat&, Size, int, Stream&) { throw_nogpu(); }
-void cv::gpu::warpAffine(const GpuMat&, GpuMat&, const Mat&, Size, int) { throw_nogpu(); }
+void cv::gpu::rotate(const GpuMat&, GpuMat&, Size, double, double, double, int, Stream&) { throw_nogpu(); }
-void cv::gpu::warpPerspective(const GpuMat&, GpuMat&, const Mat&, Size, int) { throw_nogpu(); }
+void cv::gpu::integral(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::rotate(const GpuMat&, GpuMat&, Size, double, double, double, int) { throw_nogpu(); }
+void cv::gpu::integralBuffered(const GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::integral(const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::integral(const GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::integralBuffered(const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::sqrIntegral(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::integral(const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
-void cv::gpu::sqrIntegral(const GpuMat&, GpuMat&) { throw_nogpu(); }
 void cv::gpu::columnSum(const GpuMat&, GpuMat&) { throw_nogpu(); }
-void cv::gpu::rectStdDev(const GpuMat&, const GpuMat&, GpuMat&, const Rect&) { throw_nogpu(); }
+void cv::gpu::rectStdDev(const GpuMat&, const GpuMat&, GpuMat&, const Rect&, Stream&) { throw_nogpu(); }
-//void cv::gpu::Canny(const GpuMat&, GpuMat&, double, double, int) { throw_nogpu(); }
-//void cv::gpu::Canny(const GpuMat&, GpuMat&, GpuMat&, double, double, int) { throw_nogpu(); }
-//void cv::gpu::Canny(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, double, double, int) { throw_nogpu(); }
-//void cv::gpu::Canny(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, double, double, int) { throw_nogpu(); }
 void cv::gpu::evenLevels(GpuMat&, int, int, int) { throw_nogpu(); }
-void cv::gpu::histEven(const GpuMat&, GpuMat&, int, int, int) { throw_nogpu(); }
+void cv::gpu::histEven(const GpuMat&, GpuMat&, int, int, int, Stream&) { throw_nogpu(); }
-void cv::gpu::histEven(const GpuMat&, GpuMat*, int*, int*, int*) { throw_nogpu(); }
+void cv::gpu::histEven(const GpuMat&, GpuMat*, int*, int*, int*, Stream&) { throw_nogpu(); }
-void cv::gpu::histRange(const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
+void cv::gpu::histRange(const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::histRange(const GpuMat&, GpuMat*, const GpuMat*) { throw_nogpu(); }
+void cv::gpu::histRange(const GpuMat&, GpuMat*, const GpuMat*, Stream&) { throw_nogpu(); }
 void cv::gpu::cornerHarris(const GpuMat&, GpuMat&, int, int, double, int) { throw_nogpu(); }
 void cv::gpu::cornerMinEigenVal(const GpuMat&, GpuMat&, int, int, int) { throw_nogpu(); }
 void cv::gpu::mulSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, bool) { throw_nogpu(); }
@@ -203,14 +197,7 @@ namespace
     const drawColorDisp_caller_t drawColorDisp_callers[] = {drawColorDisp_caller<unsigned char>, 0, 0, drawColorDisp_caller<short>, 0, 0, 0, 0};
 }
 
-void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp)
+void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp, Stream& stream)
-{
-    CV_Assert(src.type() == CV_8U || src.type() == CV_16S);
-
-    drawColorDisp_callers[src.type()](src, dst, ndisp, 0);
-}
-
-void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp, const Stream& stream)
 {
     CV_Assert(src.type() == CV_8U || src.type() == CV_16S);
 
@@ -234,14 +221,7 @@ namespace
     const reprojectImageTo3D_caller_t reprojectImageTo3D_callers[] = {reprojectImageTo3D_caller<unsigned char>, 0, 0, reprojectImageTo3D_caller<short>, 0, 0, 0, 0};
 }
 
-void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q)
+void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, Stream& stream)
-{
-    CV_Assert((disp.type() == CV_8U || disp.type() == CV_16S) && Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4);
-
-    reprojectImageTo3D_callers[disp.type()](disp, xyzw, Q, 0);
-}
-
-void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const Stream& stream)
 {
     CV_Assert((disp.type() == CV_8U || disp.type() == CV_16S) && Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4);
 
@@ -251,7 +231,7 @@ void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q,
 ////////////////////////////////////////////////////////////////////////
 // resize
 
-void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation)
+void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
 {
     static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR/*, NPPI_INTER_CUBIC, 0, NPPI_INTER_LANCZOS*/};
 
@@ -284,6 +264,10 @@ void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, doub
     dstsz.width  = dst.cols;
     dstsz.height = dst.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     if (src.type() == CV_8UC1)
     {
         nppSafeCall( nppiResize_8u_C1R(src.ptr<Npp8u>(), srcsz, src.step, srcrect,
@@ -295,13 +279,14 @@ void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, doub
             dst.ptr<Npp8u>(), dst.step, dstsz, fx, fy, npp_inter[interpolation]) );
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
 // copyMakeBorder
 
-void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, const Scalar& value)
+void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, const Scalar& value, Stream& s)
 {
     CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4 || src.type() == CV_32SC1 || src.type() == CV_32FC1);
 
@@ -314,6 +299,10 @@ void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom
     dstsz.width  = dst.cols;
     dstsz.height = dst.rows;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     switch (src.type())
     {
     case CV_8UC1:
@@ -349,7 +338,8 @@ void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom
         CV_Assert(!"Unsupported source type");
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
@@ -372,7 +362,7 @@ namespace
 
     void nppWarpCaller(const GpuMat& src, GpuMat& dst, double coeffs[][3], const Size& dsize, int flags,
                        npp_warp_8u_t npp_warp_8u[][2], npp_warp_16u_t npp_warp_16u[][2],
-                       npp_warp_32s_t npp_warp_32s[][2], npp_warp_32f_t npp_warp_32f[][2])
+                       npp_warp_32s_t npp_warp_32s[][2], npp_warp_32f_t npp_warp_32f[][2], cudaStream_t stream)
     {
         static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};
 
@@ -397,6 +387,8 @@ namespace
 
         int warpInd = (flags & WARP_INVERSE_MAP) >> 4;
 
+        NppStreamHandler h(stream);
+
         switch (src.depth())
         {
         case CV_8U:
@@ -419,11 +411,12 @@ namespace
             CV_Assert(!"Unsupported source type");
         }
 
-        cudaSafeCall( cudaThreadSynchronize() );
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
     }
 }
 
-void cv::gpu::warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags)
+void cv::gpu::warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags, Stream& s)
 {
     static npp_warp_8u_t npp_warpAffine_8u[][2] =
         {
@@ -464,10 +457,10 @@ void cv::gpu::warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsiz
     Mat coeffsMat(2, 3, CV_64F, (void*)coeffs);
     M.convertTo(coeffsMat, coeffsMat.type());
 
-    nppWarpCaller(src, dst, coeffs, dsize, flags, npp_warpAffine_8u, npp_warpAffine_16u, npp_warpAffine_32s, npp_warpAffine_32f);
+    nppWarpCaller(src, dst, coeffs, dsize, flags, npp_warpAffine_8u, npp_warpAffine_16u, npp_warpAffine_32s, npp_warpAffine_32f, StreamAccessor::getStream(s));
 }
 
-void cv::gpu::warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags)
+void cv::gpu::warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags, Stream& s)
 {
     static npp_warp_8u_t npp_warpPerspective_8u[][2] =
         {
@@ -508,13 +501,13 @@ void cv::gpu::warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size
     Mat coeffsMat(3, 3, CV_64F, (void*)coeffs);
     M.convertTo(coeffsMat, coeffsMat.type());
 
-    nppWarpCaller(src, dst, coeffs, dsize, flags, npp_warpPerspective_8u, npp_warpPerspective_16u, npp_warpPerspective_32s, npp_warpPerspective_32f);
+    nppWarpCaller(src, dst, coeffs, dsize, flags, npp_warpPerspective_8u, npp_warpPerspective_16u, npp_warpPerspective_32s, npp_warpPerspective_32f, StreamAccessor::getStream(s));
 }
 
 ////////////////////////////////////////////////////////////////////////
 // rotate
 
-void cv::gpu::rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift, double yShift, int interpolation)
+void cv::gpu::rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift, double yShift, int interpolation, Stream& s)
 {
     static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};
 
@@ -535,6 +528,10 @@ void cv::gpu::rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, d
     dstroi.height = dst.rows;
     dstroi.width = dst.cols;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     if (src.type() == CV_8UC1)
     {
         nppSafeCall( nppiRotate_8u_C1R(src.ptr<Npp8u>(), srcsz, src.step, srcroi,
@@ -546,19 +543,20 @@ void cv::gpu::rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, d
             dst.ptr<Npp8u>(), dst.step, dstroi, angle, xShift, yShift, npp_inter[interpolation]) );
     }
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 ////////////////////////////////////////////////////////////////////////
 // integral
 
-void cv::gpu::integral(const GpuMat& src, GpuMat& sum)
+void cv::gpu::integral(const GpuMat& src, GpuMat& sum, Stream& s)
 {
     GpuMat buffer;
-    integralBuffered(src, sum, buffer);
+    integralBuffered(src, sum, buffer, s);
 }
 
-void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer)
+void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, Stream& s)
 {
     CV_Assert(src.type() == CV_8UC1);
 
@@ -575,35 +573,45 @@ void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer)
     nppSafeCall( nppiStIntegralGetSize_8u32u(roiSize, &bufSize, prop) );
     ensureSizeIsEnough(1, bufSize, CV_8UC1, buffer);
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStStreamHandler h(stream);
+
     nppSafeCall( nppiStIntegral_8u32u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>()), src.step, 
         sum.ptr<Ncv32u>(), sum.step, roiSize, buffer.ptr<Ncv8u>(), bufSize, prop) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
-void cv::gpu::integral(const GpuMat& src, GpuMat& sum, GpuMat& sqsum)
+void cv::gpu::integral(const GpuMat& src, GpuMat& sum, GpuMat& sqsum, Stream& s)
 {
     CV_Assert(src.type() == CV_8UC1);
 
-    int w = src.cols + 1, h = src.rows + 1;
+    int width = src.cols + 1, height = src.rows + 1;
 
-    sum.create(h, w, CV_32S);
+    sum.create(height, width, CV_32S);
-    sqsum.create(h, w, CV_32F);
+    sqsum.create(height, width, CV_32F);
 
     NppiSize sz;
     sz.width = src.cols;
     sz.height = src.rows;
 
-    nppSafeCall( nppiSqrIntegral_8u32s32f_C1R(const_cast<Npp8u*>(src.ptr<Npp8u>()), src.step, sum.ptr<Npp32s>(),
+    cudaStream_t stream = StreamAccessor::getStream(s);
-        sum.step, sqsum.ptr<Npp32f>(), sqsum.step, sz, 0, 0.0f, h) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    NppStreamHandler h(stream);
+
+    nppSafeCall( nppiSqrIntegral_8u32s32f_C1R(const_cast<Npp8u*>(src.ptr<Npp8u>()), src.step, sum.ptr<Npp32s>(),
+        sum.step, sqsum.ptr<Npp32f>(), sqsum.step, sz, 0, 0.0f, height) );
+
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 //////////////////////////////////////////////////////////////////////////////
 // sqrIntegral
 
-void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum)
+void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& s)
 {
     CV_Assert(src.type() == CV_8U);
 
@@ -618,11 +626,16 @@ void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum)
     nppSafeCall(nppiStSqrIntegralGetSize_8u64u(roiSize, &bufSize, prop));	
     GpuMat buf(1, bufSize, CV_8U);
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStStreamHandler h(stream);
+
     sqsum.create(src.rows + 1, src.cols + 1, CV_64F);
     nppSafeCall(nppiStSqrIntegral_8u64u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>(0)), src.step, 
             sqsum.ptr<Ncv64u>(0), sqsum.step, roiSize, buf.ptr<Ncv8u>(0), bufSize, prop));
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 //////////////////////////////////////////////////////////////////////////////
@@ -641,7 +654,7 @@ void cv::gpu::columnSum(const GpuMat& src, GpuMat& dst)
     imgproc::columnSum_32F(src, dst);
 }
 
-void cv::gpu::rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, const Rect& rect)
+void cv::gpu::rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, const Rect& rect, Stream& s)
 {
     CV_Assert(src.type() == CV_32SC1 && sqr.type() == CV_32FC1);
 
@@ -657,69 +670,17 @@ void cv::gpu::rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, cons
     nppRect.x = rect.x;
     nppRect.y = rect.y;
 
+    cudaStream_t stream = StreamAccessor::getStream(s);
+
+    NppStreamHandler h(stream);
+
     nppSafeCall( nppiRectStdDev_32s32f_C1R(src.ptr<Npp32s>(), src.step, sqr.ptr<Npp32f>(), sqr.step,
                 dst.ptr<Npp32f>(), dst.step, sz, nppRect) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    if (stream == 0)
+        cudaSafeCall( cudaDeviceSynchronize() );
 }
 
-////////////////////////////////////////////////////////////////////////
-// Canny
-
-//void cv::gpu::Canny(const GpuMat& image, GpuMat& edges, double threshold1, double threshold2, int apertureSize)
-//{
-//    CV_Assert(!"disabled until fix crash");
-//
-//    GpuMat srcDx, srcDy;
-//
-//    Sobel(image, srcDx, CV_32F, 1, 0, apertureSize);
-//    Sobel(image, srcDy, CV_32F, 0, 1, apertureSize);
-//
-//    GpuMat buf;
-//
-//    Canny(srcDx, srcDy, edges, buf, threshold1, threshold2, apertureSize);
-//}
-//
-//void cv::gpu::Canny(const GpuMat& image, GpuMat& edges, GpuMat& buf, double threshold1, double threshold2, int apertureSize)
-//{
-//    CV_Assert(!"disabled until fix crash");
-//
-//    GpuMat srcDx, srcDy;
-//
-//    Sobel(image, srcDx, CV_32F, 1, 0, apertureSize);
-//    Sobel(image, srcDy, CV_32F, 0, 1, apertureSize);
-//
-//    Canny(srcDx, srcDy, edges, buf, threshold1, threshold2, apertureSize);
-//}
-//
-//void cv::gpu::Canny(const GpuMat& srcDx, const GpuMat& srcDy, GpuMat& edges, double threshold1, double threshold2, int apertureSize)
-//{
-//    CV_Assert(!"disabled until fix crash");
-//
-//    GpuMat buf;
-//    Canny(srcDx, srcDy, edges, buf, threshold1, threshold2, apertureSize);
-//}
-//
-//void cv::gpu::Canny(const GpuMat& srcDx, const GpuMat& srcDy, GpuMat& edges, GpuMat& buf, double threshold1, double threshold2, int apertureSize)
-//{
-//    CV_Assert(!"disabled until fix crash");
-//    CV_Assert(srcDx.type() == CV_32FC1 && srcDy.type() == CV_32FC1 && srcDx.size() == srcDy.size());
-//
-//    edges.create(srcDx.size(), CV_8UC1);
-//
-//    NppiSize sz;
-//    sz.height = srcDx.rows;
-//    sz.width = srcDx.cols;
-//
-//    int bufsz;
-//    nppSafeCall( nppiCannyGetBufferSize(sz, &bufsz) );
-//    ensureSizeIsEnough(1, bufsz, CV_8UC1, buf);
-//
-//    nppSafeCall( nppiCanny_32f8u_C1R(srcDx.ptr<Npp32f>(), srcDx.step, srcDy.ptr<Npp32f>(), srcDy.step,
-//        edges.ptr<Npp8u>(), edges.step, sz, (Npp32f)threshold1, (Npp32f)threshold2, buf.ptr<Npp8u>()) );
-//
-//    cudaSafeCall( cudaThreadSynchronize() );
-//}
 
 ////////////////////////////////////////////////////////////////////////
 // Histogram
@@ -755,7 +716,7 @@ namespace
     {
         typedef typename NppHistogramEvenFuncC1<SDEPTH>::src_t src_t;
 
-        static void hist(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel)
+        static void hist(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, cudaStream_t stream)
         {
             int levels = histSize + 1;
             hist.create(1, histSize, CV_32S);
@@ -769,10 +730,14 @@ namespace
 
             get_buf_size(sz, levels, &buf_size);
             buffer.create(1, buf_size, CV_8U);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<src_t>(), src.step, sz, hist.ptr<Npp32s>(), levels,
                 lowerLevel, upperLevel, buffer.ptr<Npp8u>()) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     template<int SDEPTH, typename NppHistogramEvenFuncC4<SDEPTH>::func_ptr func, get_buf_size_c4_t get_buf_size>
@@ -780,7 +745,7 @@ namespace
     {
         typedef typename NppHistogramEvenFuncC4<SDEPTH>::src_t src_t;
 
-        static void hist(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4])
+        static void hist(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], cudaStream_t stream)
         {
             int levels[] = {histSize[0] + 1, histSize[1] + 1, histSize[2] + 1, histSize[3] + 1};
             hist[0].create(1, histSize[0], CV_32S);
@@ -799,9 +764,13 @@ namespace
 
             get_buf_size(sz, levels, &buf_size);
             buffer.create(1, buf_size, CV_8U);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<src_t>(), src.step, sz, pHist, levels, lowerLevel, upperLevel, buffer.ptr<Npp8u>()) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 
@@ -849,7 +818,7 @@ namespace
         typedef typename NppHistogramRangeFuncC1<SDEPTH>::level_t level_t;
         enum {LEVEL_TYPE_CODE=NppHistogramRangeFuncC1<SDEPTH>::LEVEL_TYPE_CODE};
 
-        static void hist(const GpuMat& src, GpuMat& hist, const GpuMat& levels)
+        static void hist(const GpuMat& src, GpuMat& hist, const GpuMat& levels, cudaStream_t stream)
         {
             CV_Assert(levels.type() == LEVEL_TYPE_CODE && levels.rows == 1);
 
@@ -864,9 +833,13 @@ namespace
 
             get_buf_size(sz, levels.cols, &buf_size);
             buffer.create(1, buf_size, CV_8U);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<src_t>(), src.step, sz, hist.ptr<Npp32s>(), levels.ptr<level_t>(), levels.cols, buffer.ptr<Npp8u>()) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     template<int SDEPTH, typename NppHistogramRangeFuncC4<SDEPTH>::func_ptr func, get_buf_size_c4_t get_buf_size>
@@ -876,7 +849,7 @@ namespace
         typedef typename NppHistogramRangeFuncC1<SDEPTH>::level_t level_t;
         enum {LEVEL_TYPE_CODE=NppHistogramRangeFuncC1<SDEPTH>::LEVEL_TYPE_CODE};
 
-        static void hist(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4])
+        static void hist(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], cudaStream_t stream)
         {
             CV_Assert(levels[0].type() == LEVEL_TYPE_CODE && levels[0].rows == 1);
             CV_Assert(levels[1].type() == LEVEL_TYPE_CODE && levels[1].rows == 1);
@@ -901,9 +874,13 @@ namespace
 
             get_buf_size(sz, nLevels, &buf_size);
             buffer.create(1, buf_size, CV_8U);
+
+            NppStreamHandler h(stream);
+
             nppSafeCall( func(src.ptr<src_t>(), src.step, sz, pHist, pLevels, nLevels, buffer.ptr<Npp8u>()) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            if (stream == 0)
+                cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 }
@@ -915,11 +892,11 @@ void cv::gpu::evenLevels(GpuMat& levels, int nLevels, int lowerLevel, int upperL
     levels.upload(host_levels);
 }
 
-void cv::gpu::histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel)
+void cv::gpu::histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, Stream& stream)
 {
     CV_Assert(src.type() == CV_8UC1 || src.type() == CV_16UC1 || src.type() == CV_16SC1 );
 
-    typedef void (*hist_t)(const GpuMat& src, GpuMat& hist, int levels, int lowerLevel, int upperLevel);
+    typedef void (*hist_t)(const GpuMat& src, GpuMat& hist, int levels, int lowerLevel, int upperLevel, cudaStream_t stream);
     static const hist_t hist_callers[] =
     {
         NppHistogramEvenC1<CV_8U , nppiHistogramEven_8u_C1R , nppiHistogramEvenGetBufferSize_8u_C1R >::hist,
@@ -928,14 +905,14 @@ void cv::gpu::histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerL
         NppHistogramEvenC1<CV_16S, nppiHistogramEven_16s_C1R, nppiHistogramEvenGetBufferSize_16s_C1R>::hist
     };
 
-    hist_callers[src.depth()](src, hist, histSize, lowerLevel, upperLevel);
+    hist_callers[src.depth()](src, hist, histSize, lowerLevel, upperLevel, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4])
+void cv::gpu::histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream)
 {
     CV_Assert(src.type() == CV_8UC4 || src.type() == CV_16UC4 || src.type() == CV_16SC4 );
 
-    typedef void (*hist_t)(const GpuMat& src, GpuMat hist[4], int levels[4], int lowerLevel[4], int upperLevel[4]);
+    typedef void (*hist_t)(const GpuMat& src, GpuMat hist[4], int levels[4], int lowerLevel[4], int upperLevel[4], cudaStream_t stream);
     static const hist_t hist_callers[] =
     {
         NppHistogramEvenC4<CV_8U , nppiHistogramEven_8u_C4R , nppiHistogramEvenGetBufferSize_8u_C4R >::hist,
@@ -944,14 +921,14 @@ void cv::gpu::histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int l
         NppHistogramEvenC4<CV_16S, nppiHistogramEven_16s_C4R, nppiHistogramEvenGetBufferSize_16s_C4R>::hist
     };
 
-    hist_callers[src.depth()](src, hist, histSize, lowerLevel, upperLevel);
+    hist_callers[src.depth()](src, hist, histSize, lowerLevel, upperLevel, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels)
+void cv::gpu::histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, Stream& stream)
 {
     CV_Assert(src.type() == CV_8UC1 || src.type() == CV_16UC1 || src.type() == CV_16SC1 || src.type() == CV_32FC1);
 
-    typedef void (*hist_t)(const GpuMat& src, GpuMat& hist, const GpuMat& levels);
+    typedef void (*hist_t)(const GpuMat& src, GpuMat& hist, const GpuMat& levels, cudaStream_t stream);
     static const hist_t hist_callers[] =
     {
         NppHistogramRangeC1<CV_8U , nppiHistogramRange_8u_C1R , nppiHistogramRangeGetBufferSize_8u_C1R >::hist,
@@ -962,14 +939,14 @@ void cv::gpu::histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels)
         NppHistogramRangeC1<CV_32F, nppiHistogramRange_32f_C1R, nppiHistogramRangeGetBufferSize_32f_C1R>::hist
     };
 
-    hist_callers[src.depth()](src, hist, levels);
+    hist_callers[src.depth()](src, hist, levels, StreamAccessor::getStream(stream));
 }
 
-void cv::gpu::histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4])
+void cv::gpu::histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], Stream& stream)
 {
     CV_Assert(src.type() == CV_8UC4 || src.type() == CV_16UC4 || src.type() == CV_16SC4 || src.type() == CV_32FC4);
 
-    typedef void (*hist_t)(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4]);
+    typedef void (*hist_t)(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], cudaStream_t stream);
     static const hist_t hist_callers[] =
     {
         NppHistogramRangeC4<CV_8U , nppiHistogramRange_8u_C4R , nppiHistogramRangeGetBufferSize_8u_C4R >::hist,
@@ -980,7 +957,7 @@ void cv::gpu::histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4
         NppHistogramRangeC4<CV_32F, nppiHistogramRange_32f_C4R, nppiHistogramRangeGetBufferSize_32f_C4R>::hist
     };
 
-    hist_callers[src.depth()](src, hist, levels);
+    hist_callers[src.depth()](src, hist, levels, StreamAccessor::getStream(stream));
 }
 
 ////////////////////////////////////////////////////////////////////////

modules/gpu/src/matrix_operations.cpp

@@ -128,7 +128,7 @@ void cv::gpu::GpuMat::copyTo( GpuMat& m ) const
     CV_DbgAssert(!this->empty());
     m.create(size(), type());
     cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToDevice) );
-    cudaSafeCall( cudaThreadSynchronize() );
+    cudaSafeCall( cudaDeviceSynchronize() );
 }
 
 void cv::gpu::GpuMat::copyTo( GpuMat& mat, const GpuMat& mask ) const
@@ -179,7 +179,7 @@ namespace
             sz.height = src.rows;
             nppSafeCall( func(src.ptr<src_t>(), src.step, dst.ptr<dst_t>(), dst.step, sz) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
@@ -193,7 +193,7 @@ namespace
             sz.height = src.rows;
             nppSafeCall( func(src.ptr<Npp32f>(), src.step, dst.ptr<dst_t>(), dst.step, sz, NPP_RND_NEAR) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 
@@ -349,7 +349,7 @@ namespace
             Scalar_<src_t> nppS = s;
             nppSafeCall( func(nppS.val, src.ptr<src_t>(), src.step, sz) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
@@ -364,7 +364,7 @@ namespace
             Scalar_<src_t> nppS = s;
             nppSafeCall( func(nppS[0], src.ptr<src_t>(), src.step, sz) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 
@@ -400,7 +400,7 @@ namespace
             Scalar_<src_t> nppS = s;
             nppSafeCall( func(nppS.val, src.ptr<src_t>(), src.step, sz, mask.ptr<Npp8u>(), mask.step) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
     template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
@@ -415,7 +415,7 @@ namespace
             Scalar_<src_t> nppS = s;
             nppSafeCall( func(nppS[0], src.ptr<src_t>(), src.step, sz, mask.ptr<Npp8u>(), mask.step) );
 
-            cudaSafeCall( cudaThreadSynchronize() );
+            cudaSafeCall( cudaDeviceSynchronize() );
         }
     };
 
@@ -463,8 +463,8 @@ GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
         {
             {NppSet<CV_8U, 1, nppiSet_8u_C1R>::set,kernelSet<uchar>,kernelSet<uchar>,NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
             {kernelSet<schar>,kernelSet<schar>,kernelSet<schar>,kernelSet<schar>},
-            {NppSet<CV_16U, 1, nppiSet_16u_C1R>::set,kernelSet<ushort>,kernelSet<ushort>,NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
+            {NppSet<CV_16U, 1, nppiSet_16u_C1R>::set,NppSet<CV_16U, 2, nppiSet_16u_C2R>::set,kernelSet<ushort>,NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
-            {NppSet<CV_16S, 1, nppiSet_16s_C1R>::set,kernelSet<short>,kernelSet<short>,NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
+            {NppSet<CV_16S, 1, nppiSet_16s_C1R>::set,NppSet<CV_16S, 2, nppiSet_16s_C2R>::set,kernelSet<short>,NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
             {NppSet<CV_32S, 1, nppiSet_32s_C1R>::set,kernelSet<int>,kernelSet<int>,NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
             {NppSet<CV_32F, 1, nppiSet_32f_C1R>::set,kernelSet<float>,kernelSet<float>,NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
             {kernelSet<double>,kernelSet<double>,kernelSet<double>,kernelSet<double>},

modules/gpu/src/matrix_reductions.cpp

@@ -114,24 +114,14 @@ void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
     sz.width  = src.cols;
     sz.height = src.rows;
 
-#if NPP_VERSION_MAJOR >= 4
-
     DeviceBuffer dbuf(2);
 
     nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), src.step, sz, dbuf, (double*)dbuf + 1) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    cudaSafeCall( cudaDeviceSynchronize() );
     
     double* ptrs[2] = {mean.val, stddev.val};
     dbuf.download(ptrs);
-
-#else
-    
-    nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), src.step, sz, mean.val, stddev.val) );
-
-    cudaSafeCall( cudaThreadSynchronize() );
-
-#endif
 }
 
 
@@ -185,24 +175,14 @@ double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
     
     double retVal;
 
-#if NPP_VERSION_MAJOR >= 4
-
     DeviceBuffer dbuf;
 
     nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step, src2.ptr<Npp8u>(), src2.step, sz, dbuf) );
 
-    cudaSafeCall( cudaThreadSynchronize() );
+    cudaSafeCall( cudaDeviceSynchronize() );
     
     dbuf.download(&retVal);
 
-#else
-
-    nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step, src2.ptr<Npp8u>(), src2.step, sz, &retVal) );
-
-    cudaSafeCall( cudaThreadSynchronize() );
-
-#endif   
-
     return retVal;
 }
 

modules/gpu/src/opencv2/gpu/device/transform.hpp

@@ -332,7 +332,7 @@ namespace cv
                 cudaSafeCall( cudaGetLastError() );
 
                 if (stream == 0)
-                    cudaSafeCall( cudaThreadSynchronize() ); 
+                    cudaSafeCall( cudaDeviceSynchronize() ); 
             }
 
             template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
@@ -349,7 +349,7 @@ namespace cv
                 cudaSafeCall( cudaGetLastError() );
 
                 if (stream == 0)
-                    cudaSafeCall( cudaThreadSynchronize() );            
+                    cudaSafeCall( cudaDeviceSynchronize() );            
             }
         };
         template<> struct TransformDispatcher<true>
@@ -370,7 +370,7 @@ namespace cv
                 cudaSafeCall( cudaGetLastError() );
 
                 if (stream == 0)
-                    cudaSafeCall( cudaThreadSynchronize() );
+                    cudaSafeCall( cudaDeviceSynchronize() );
             }
 
             template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
@@ -389,7 +389,7 @@ namespace cv
                 cudaSafeCall( cudaGetLastError() );
 
                 if (stream == 0)
-                    cudaSafeCall( cudaThreadSynchronize() );            
+                    cudaSafeCall( cudaDeviceSynchronize() );            
             }
         };
 

modules/gpu/src/precomp.hpp

@@ -77,8 +77,8 @@
     #include "nvidia/NPP_staging/NPP_staging.hpp"
     #include "nvidia/NCVHaarObjectDetection.hpp"
 
-#define CUDART_MINIMUM_REQUIRED_VERSION 3020
+#define CUDART_MINIMUM_REQUIRED_VERSION 4000
-#define NPP_MINIMUM_REQUIRED_VERSION 3216
+#define NPP_MINIMUM_REQUIRED_VERSION 4000
 
 #if (CUDART_VERSION < CUDART_MINIMUM_REQUIRED_VERSION)
     #error "Insufficient Cuda Runtime library version, please update it."

modules/gpu/src/split_merge.cpp

@@ -46,14 +46,10 @@ using namespace std;
 
 #if !defined (HAVE_CUDA)
 
-void cv::gpu::merge(const GpuMat* /*src*/, size_t /*count*/, GpuMat& /*dst*/) { throw_nogpu(); }
+void cv::gpu::merge(const GpuMat* /*src*/, size_t /*count*/, GpuMat& /*dst*/, Stream& /*stream*/) { throw_nogpu(); }
-void cv::gpu::merge(const vector<GpuMat>& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
+void cv::gpu::merge(const vector<GpuMat>& /*src*/, GpuMat& /*dst*/, Stream& /*stream*/) { throw_nogpu(); }
-void cv::gpu::merge(const GpuMat* /*src*/, size_t /*count*/, GpuMat& /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
+void cv::gpu::split(const GpuMat& /*src*/, GpuMat* /*dst*/, Stream& /*stream*/) { throw_nogpu(); }
-void cv::gpu::merge(const vector<GpuMat>& /*src*/, GpuMat& /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
+void cv::gpu::split(const GpuMat& /*src*/, vector<GpuMat>& /*dst*/, Stream& /*stream*/) { throw_nogpu(); }
-void cv::gpu::split(const GpuMat& /*src*/, GpuMat* /*dst*/) { throw_nogpu(); }
-void cv::gpu::split(const GpuMat& /*src*/, vector<GpuMat>& /*dst*/) { throw_nogpu(); }
-void cv::gpu::split(const GpuMat& /*src*/, GpuMat* /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
-void cv::gpu::split(const GpuMat& /*src*/, vector<GpuMat>& /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
 
@@ -148,51 +144,25 @@ namespace cv { namespace gpu { namespace split_merge
 }}}
 
 
-void cv::gpu::merge(const GpuMat* src, size_t n, GpuMat& dst) 
+void cv::gpu::merge(const GpuMat* src, size_t n, GpuMat& dst, Stream& stream) 
-{ 
-    split_merge::merge(src, n, dst, 0);
-}
-
-
-void cv::gpu::merge(const vector<GpuMat>& src, GpuMat& dst) 
-{
-    split_merge::merge(&src[0], src.size(), dst, 0);
-}
-
-
-void cv::gpu::merge(const GpuMat* src, size_t n, GpuMat& dst, const Stream& stream) 
 { 
     split_merge::merge(src, n, dst, StreamAccessor::getStream(stream));
 }
 
 
-void cv::gpu::merge(const vector<GpuMat>& src, GpuMat& dst, const Stream& stream) 
+void cv::gpu::merge(const vector<GpuMat>& src, GpuMat& dst, Stream& stream) 
 {
     split_merge::merge(&src[0], src.size(), dst, StreamAccessor::getStream(stream));
 }
 
 
-void cv::gpu::split(const GpuMat& src, GpuMat* dst) 
+void cv::gpu::split(const GpuMat& src, GpuMat* dst, Stream& stream) 
-{
-    split_merge::split(src, dst, 0);
-}
-
-
-void cv::gpu::split(const GpuMat& src, vector<GpuMat>& dst) 
-{
-    dst.resize(src.channels());
-    if(src.channels() > 0)
-        split_merge::split(src, &dst[0], 0);
-}
-
-
-void cv::gpu::split(const GpuMat& src, GpuMat* dst, const Stream& stream) 
 {
     split_merge::split(src, dst, StreamAccessor::getStream(stream));
 }
 
 
-void cv::gpu::split(const GpuMat& src, vector<GpuMat>& dst, const Stream& stream) 
+void cv::gpu::split(const GpuMat& src, vector<GpuMat>& dst, Stream& stream) 
 {
     dst.resize(src.channels());
     if(src.channels() > 0)

modules/gpu/src/stereobm.cpp

@@ -51,8 +51,7 @@ cv::gpu::StereoBM_GPU::StereoBM_GPU() { throw_nogpu(); }
 cv::gpu::StereoBM_GPU::StereoBM_GPU(int, int, int) { throw_nogpu(); }
 
 bool cv::gpu::StereoBM_GPU::checkIfGpuCallReasonable() { throw_nogpu(); return false; }
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
 
@@ -124,13 +123,7 @@ static void stereo_bm_gpu_operator ( GpuMat& minSSD,  GpuMat& leBuf, GpuMat&  ri
         bm::postfilter_textureness(le_for_bm, winSize, avergeTexThreshold, disparity, stream);
 }
 
-
+void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream)
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity)
-{
-    ::stereo_bm_gpu_operator(minSSD, leBuf, riBuf, preset, ndisp, winSize, avergeTexThreshold, left, right, disparity, 0);
-}
-
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream& stream)
 {
     ::stereo_bm_gpu_operator(minSSD, leBuf, riBuf, preset, ndisp, winSize, avergeTexThreshold, left, right, disparity, StreamAccessor::getStream(stream));
 }

modules/gpu/src/stereobp.cpp

@@ -53,10 +53,8 @@ void cv::gpu::StereoBeliefPropagation::estimateRecommendedParams(int, int, int&,
 cv::gpu::StereoBeliefPropagation::StereoBeliefPropagation(int, int, int, int) { throw_nogpu(); }
 cv::gpu::StereoBeliefPropagation::StereoBeliefPropagation(int, int, int, float, float, float, float, int) { throw_nogpu(); }
 
-void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
 void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
 
-void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, GpuMat&) { throw_nogpu(); }
 void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
@@ -133,7 +131,7 @@ namespace
             CV_Assert(rthis.msg_type == CV_32F || (1 << (rthis.levels - 1)) * scale * rthis.max_data_term < numeric_limits<short>::max());
         }
 
-        void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, cudaStream_t stream)
+        void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
         {
             typedef void (*comp_data_t)(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream);
             static const comp_data_t comp_data_callers[2][5] = 
@@ -154,16 +152,16 @@ namespace
             const int min_image_dim_size = 2;
             CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
 
-            init();
+            init(stream);
 
             datas[0].create(rows * rthis.ndisp, cols, rthis.msg_type);
 
-            comp_data_callers[rthis.msg_type == CV_32F][left.channels()](left, right, datas[0], stream);
+            comp_data_callers[rthis.msg_type == CV_32F][left.channels()](left, right, datas[0], StreamAccessor::getStream(stream));
 
             calcBP(disp, stream);
         }
 
-        void operator()(const GpuMat& data, GpuMat& disp, cudaStream_t stream)
+        void operator()(const GpuMat& data, GpuMat& disp, Stream& stream)
         {
             CV_Assert((data.type() == rthis.msg_type) && (data.rows % rthis.ndisp == 0));
 
@@ -176,14 +174,14 @@ namespace
             const int min_image_dim_size = 2;
             CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
 
-            init();
+            init(stream);
 
             datas[0] = data;
 
             calcBP(disp, stream);
         }
     private:
-        void init()
+        void init(Stream& stream)
         {
             u.create(rows * rthis.ndisp, cols, rthis.msg_type);
             d.create(rows * rthis.ndisp, cols, rthis.msg_type);
@@ -193,10 +191,20 @@ namespace
             if (rthis.levels & 1)
             {
                 //can clear less area
-                u = zero;
+                if (stream)
-                d = zero;
+                {
-                l = zero;
+                    stream.enqueueMemSet(u, zero);
-                r = zero;
+                    stream.enqueueMemSet(d, zero);
+                    stream.enqueueMemSet(l, zero);
+                    stream.enqueueMemSet(r, zero);
+                }
+                else
+                {
+                    u.setTo(zero);
+                    d.setTo(zero);
+                    l.setTo(zero);
+                    r.setTo(zero);
+                }
             }
 
             if (rthis.levels > 1)
@@ -211,10 +219,20 @@ namespace
 
                 if ((rthis.levels & 1) == 0)
                 {
-                    u2 = zero;
+                    if (stream)
-                    d2 = zero;
+                    {
-                    l2 = zero;
+                        stream.enqueueMemSet(u2, zero);
-                    r2 = zero;
+                        stream.enqueueMemSet(d2, zero);
+                        stream.enqueueMemSet(l2, zero);
+                        stream.enqueueMemSet(r2, zero);
+                    }
+                    else
+                    {
+                        u2.setTo(zero);
+                        d2.setTo(zero);
+                        l2.setTo(zero);
+                        r2.setTo(zero);
+                    }
                 }
             }
 
@@ -229,7 +247,7 @@ namespace
             rows_all[0] = rows;
         }
 
-        void calcBP(GpuMat& disp, cudaStream_t stream)
+        void calcBP(GpuMat& disp, Stream& stream)
         {
             using namespace cv::gpu::bp;
 
@@ -259,6 +277,8 @@ namespace
 
             const int funcIdx = rthis.msg_type == CV_32F;
 
+            cudaStream_t cudaStream = StreamAccessor::getStream(stream);
+
             for (int i = 1; i < rthis.levels; ++i)
             {
                 cols_all[i] = (cols_all[i-1] + 1) / 2;
@@ -266,7 +286,7 @@ namespace
 
                 datas[i].create(rows_all[i] * rthis.ndisp, cols_all[i], rthis.msg_type);
 
-                data_step_down_callers[funcIdx](cols_all[i], rows_all[i], rows_all[i-1], datas[i-1], datas[i], stream);
+                data_step_down_callers[funcIdx](cols_all[i], rows_all[i], rows_all[i-1], datas[i-1], datas[i], cudaStream);
             }
 
             DevMem2D mus[] = {u, u2};
@@ -280,9 +300,9 @@ namespace
             {
                 // for lower level we have already computed messages by setting to zero
                 if (i != rthis.levels - 1)
-                    level_up_messages_callers[funcIdx](mem_idx, cols_all[i], rows_all[i], rows_all[i+1], mus, mds, mls, mrs, stream);
+                    level_up_messages_callers[funcIdx](mem_idx, cols_all[i], rows_all[i], rows_all[i+1], mus, mds, mls, mrs, cudaStream);
 
-                calc_all_iterations_callers[funcIdx](cols_all[i], rows_all[i], rthis.iters, mus[mem_idx], mds[mem_idx], mls[mem_idx], mrs[mem_idx], datas[i], stream);
+                calc_all_iterations_callers[funcIdx](cols_all[i], rows_all[i], rthis.iters, mus[mem_idx], mds[mem_idx], mls[mem_idx], mrs[mem_idx], datas[i], cudaStream);
 
                 mem_idx = (mem_idx + 1) & 1;
             }
@@ -291,13 +311,22 @@ namespace
                 disp.create(rows, cols, CV_16S);
 
             out = ((disp.type() == CV_16S) ? disp : (out.create(rows, cols, CV_16S), out));
-            out = zero;
 
-            output_callers[funcIdx](u, d, l, r, datas.front(), out, stream);
+            if (stream)
+                stream.enqueueMemSet(out, zero);
+            else
+                out.setTo(zero);
+
+            output_callers[funcIdx](u, d, l, r, datas.front(), out, cudaStream);
 
             if (disp.type() != CV_16S)
+            {
+                if (stream)
+                    stream.enqueueConvert(out, disp, disp.type());
+                else
                     out.convertTo(disp, disp.type());
             }                
+        }
 
         StereoBeliefPropagation& rthis;
 
@@ -323,28 +352,16 @@ namespace
     };
 }
 
-void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
-{
-    ::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
-    impl(left, right, disp, 0);
-}
-
 void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
 {
     ::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
-    impl(left, right, disp, StreamAccessor::getStream(stream));
+    impl(left, right, disp, stream);
-}
-
-void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& data, GpuMat& disp)
-{
-    ::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
-    impl(data, disp, 0);
 }
 
 void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& data, GpuMat& disp, Stream& stream)
 {
     ::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
-    impl(data, disp, StreamAccessor::getStream(stream));
+    impl(data, disp, stream);
 }
 
 #endif /* !defined (HAVE_CUDA) */

modules/gpu/src/stereocsbp.cpp

@@ -53,7 +53,6 @@ void cv::gpu::StereoConstantSpaceBP::estimateRecommendedParams(int, int, int&, i
 cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int, int, int, int, int) { throw_nogpu(); }
 cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int, int, int, int, float, float, float, float, int, int) { throw_nogpu(); }
 
-void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
 void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
 
 #else /* !defined (HAVE_CUDA) */
@@ -136,7 +135,7 @@ cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp_, int iters_, in
 template<class T>
 static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
                           GpuMat disp_selected_pyr[2], GpuMat& data_cost, GpuMat& data_cost_selected,
-                          GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, cudaStream_t stream)
+                          GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
 {
     CV_DbgAssert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels && 0 < rthis.nr_plane
         && left.rows == right.rows && left.cols == right.cols && left.type() == right.type());
@@ -145,6 +144,8 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
 
     const Scalar zero = Scalar::all(0);
 
+    cudaStream_t cudaStream = StreamAccessor::getStream(stream);
+
     ////////////////////////////////////////////////////////////////////////////////////////////
     // Init
 
@@ -210,18 +211,36 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
     csbp::load_constants(rthis.ndisp, rthis.max_data_term, rthis.data_weight,
         rthis.max_disc_term, rthis.disc_single_jump, rthis.min_disp_th, left, right, temp);
 
-    l[0] = zero;
+    if (stream)
-    d[0] = zero;
+    {
-    r[0] = zero;
+        stream.enqueueMemSet(l[0], zero);
-    u[0] = zero;
+        stream.enqueueMemSet(d[0], zero);
+        stream.enqueueMemSet(r[0], zero);
+        stream.enqueueMemSet(u[0], zero);
         
-    l[1] = zero;
+        stream.enqueueMemSet(l[1], zero);
-    d[1] = zero;
+        stream.enqueueMemSet(d[1], zero);
-    r[1] = zero;
+        stream.enqueueMemSet(r[1], zero);
-    u[1] = zero;
+        stream.enqueueMemSet(u[1], zero);
 
-    data_cost = zero;
+        stream.enqueueMemSet(data_cost, zero);
-    data_cost_selected = zero;
+        stream.enqueueMemSet(data_cost_selected, zero);
+    }
+    else
+    {
+        l[0].setTo(zero);
+        d[0].setTo(zero);
+        r[0].setTo(zero);
+        u[0].setTo(zero);
+
+        l[1].setTo(zero);
+        d[1].setTo(zero);
+        r[1].setTo(zero);
+        u[1].setTo(zero);
+
+        data_cost.setTo(zero);
+        data_cost_selected.setTo(zero);
+    }
 
     int cur_idx = 0;
 
@@ -230,12 +249,12 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
         if (i == levels - 1)
         {
             csbp::init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<T>(), data_cost_selected.ptr<T>(),
-                step_pyr[i], rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], rthis.ndisp, left.channels(), rthis.use_local_init_data_cost, stream);
+                step_pyr[i], rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], rthis.ndisp, left.channels(), rthis.use_local_init_data_cost, cudaStream);
         }
         else
         {
             csbp::compute_data_cost(disp_selected_pyr[cur_idx].ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1],
-                left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), stream);
+                left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), cudaStream);
 
             int new_idx = (cur_idx + 1) & 1;
 
@@ -243,46 +262,49 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
                                u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
                                disp_selected_pyr[new_idx].ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(),
                                data_cost_selected.ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1], rows_pyr[i],
-                               cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], stream);
+                               cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], cudaStream);
 
             cur_idx = new_idx;
         }
 
         csbp::calc_all_iterations(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
                                   data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[i],
-                                  rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rthis.iters, stream);
+                                  rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rthis.iters, cudaStream);
     }
 
     if (disp.empty())
         disp.create(rows, cols, CV_16S);
 
     out = ((disp.type() == CV_16S) ? disp : (out.create(rows, cols, CV_16S), out));
-    out = zero;
+
+    if (stream)
+        stream.enqueueMemSet(out, zero);
+    else
+        out.setTo(zero);
 
     csbp::compute_disp(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
-                       data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[0], out, nr_plane_pyr[0], stream);
+                       data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[0], out, nr_plane_pyr[0], cudaStream);
 
     if (disp.type() != CV_16S)
+    {
+        if (stream)
+            stream.enqueueConvert(out, disp, disp.type());
+        else
             out.convertTo(disp, disp.type());
     }
+}
 
 
 typedef void (*csbp_operator_t)(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
                                      GpuMat disp_selected_pyr[2], GpuMat& data_cost, GpuMat& data_cost_selected,
-                                     GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, cudaStream_t stream);
+                                     GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream);
 
 const static csbp_operator_t operators[] = {0, 0, 0, csbp_operator<short>, 0, csbp_operator<float>, 0, 0};
 
-void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
-{
-    CV_Assert(msg_type == CV_32F || msg_type == CV_16S);
-    operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, 0);
-}
-
 void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
 {
     CV_Assert(msg_type == CV_32F || msg_type == CV_16S);
-    operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, StreamAccessor::getStream(stream));
+    operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, stream);
 }
 
 #endif /* !defined (HAVE_CUDA) */