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Master commit of OpenFace.

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unknown 2016-04-28 15:40:36 -04:00
parent 5346d303ab
commit 57e58a6949
4406 changed files with 1441342 additions and 0 deletions

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CMakeLists.txt Normal file
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cmake_minimum_required (VERSION 2.8)
project (OpenFace)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin/)
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_SOURCE_DIR}/cmake/modules/")
find_package( OpenCV REQUIRED )
MESSAGE("OpenCV information:")
MESSAGE(" OpenCV_INCLUDE_DIRS: ${OpenCV_INCLUDE_DIRS}")
MESSAGE(" OpenCV_LIBRARIES: ${OpenCV_LIBRARIES}")
MESSAGE(" OpenCV_LIBRARY_DIRS: ${OpenCV_LIBRARY_DIRS}")
include_directories( ${OpenCV_INCLUDE_DIRS} )
find_package( Boost 1.5.9 REQUIRED COMPONENTS filesystem system)
MESSAGE("Boost information:")
MESSAGE(" Boost_INCLUDE_DIRS: ${Boost_INCLUDE_DIRS}")
MESSAGE(" Boost_LIBRARIES: ${Boost_LIBRARIES}")
MESSAGE(" Boost_LIBRARY_DIRS: ${Boost_LIBRARY_DIRS}")
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS})
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS}/boost)
LINK_DIRECTORIES(${Boost_LIBRARY_DIRS})
find_package(TBB REQUIRED)
# Move LandmarkDetector model
file(GLOB files "lib/local/LandmarkDetector/model/*.txt")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/model)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/model)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/model)
endif(MSVC)
endforeach()
# Move the hierarchical LandmarkDetector models
file(GLOB files "lib/local/LandmarkDetector/model/model*")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/model)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/model)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/model)
endif(MSVC)
endforeach()
file(GLOB files "lib/local/LandmarkDetector/model/detection_validation/*.txt")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/model/detection_validation)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/model/detection_validation)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/model/detection_validation)
endif(MSVC)
endforeach()
file(GLOB files "lib/local/LandmarkDetector/model/patch_experts/*.txt")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/model/patch_experts)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/model/patch_experts)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/model/patch_experts)
endif(MSVC)
endforeach()
file(GLOB files "lib/local/LandmarkDetector/model/pdms/*.txt")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/model/pdms)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/model/pdms)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/model/pdms)
endif(MSVC)
endforeach()
# Move OpenCV classifiers
file(GLOB files "lib/3rdParty/OpenCV3.1/classifiers/*.xml")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/classifiers)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/classifiers)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/classifiers)
endif(MSVC)
endforeach()
# Move AU prediction modules
file(GLOB files "lib/local/FaceAnalyser/AU_predictors/*.txt")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/AU_predictors)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/AU_predictors)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/AU_predictors)
endif(MSVC)
endforeach()
# Move AU prediction modules
file(GLOB files "lib/local/FaceAnalyser/AU_predictors/svr*")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/AU_predictors)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/AU_predictors)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/AU_predictors)
endif(MSVC)
endforeach()
# Move AU prediction modules
file(GLOB files "lib/local/FaceAnalyser/AU_predictors/svm*")
foreach(file ${files})
if (MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Debug/AU_predictors)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/Release/AU_predictors)
else(MSVC)
file(COPY ${file} DESTINATION ${CMAKE_BINARY_DIR}/bin/AU_predictors)
endif(MSVC)
endforeach()
if (${CMAKE_CXX_COMPILER_ID} STREQUAL "GNU")
execute_process(COMMAND ${CMAKE_CXX_COMPILER} -dumpversion OUTPUT_VARIABLE GCC_VERSION)
if (GCC_VERSION VERSION_LESS 4.7)
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x -msse -msse2 -msse3")
else ()
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -msse -msse2 -msse3")
endif ()
else ()
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -msse -msse2 -msse3")
endif ()
# Boost
if(WIN32)
include_directories(lib/3rdParty/boost)
include_directories(lib/3rdParty/boost/boost)
link_directories( ${PROJECT_SOURCE_DIR}/lib/3rdParty/boost/lib )
else()
INCLUDE_DIRECTORIES(${BOOST_INCLUDE_DIR})
endif()
# dlib
include_directories(lib/3rdParty/dlib/include)
# dlib library
add_subdirectory(lib/3rdParty/dlib)
# LandmarkDetector library
add_subdirectory(lib/local/LandmarkDetector)
# Facial Expression analysis library
add_subdirectory(lib/local/FaceAnalyser)
# executables
add_subdirectory(exe/FaceLandmarkImg)
add_subdirectory(exe/FaceLandmarkVid)
add_subdirectory(exe/FaceLandmarkVidMulti)
add_subdirectory(exe/FeatureExtraction)

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Copyright.txt Normal file
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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
// License Agreement with respect to such Open Source Component, such restrictions will not
// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
// delivery of the Software.
// * Any publications arising from the use of this software, including but
// not limited to academic journal and conference publications, technical
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////

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# OpenFace: an open source facial behavior analysis toolkit
Over the past few years, there has been an increased interest in automatic facial behavior analysis and understanding. We present OpenFace – an open source tool intended for computer vision and machine learning researchers, affective computing community and people interested in building interactive applications based on facial behavior analysis. OpenFace is the first open source tool capable of facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation. The computer vision algorithms which represent the core of OpenFace demonstrate state-of-the-art results in all of the above mentioned tasks. Furthermore, our tool is capable of real-time performance and is able to run from a simple webcam without any specialist hardware.
The code was written mainly by Tadas Baltrusaitis during his time at the Language Technologies Institute at the Carnegie Mellon University; Computer Laboratory, University of Cambridge; and Institute for Creative Technologies, University of Southern California.
Special thanks goes to Louis-Philippe Morency and his MultiComp Lab at Institute for Creative Technologies for help in writing and testing the code, and Erroll Wood for the gaze estimation work.
More details about the project - http://www.cl.cam.ac.uk/research/rainbow/projects/openface/
## Table of contents
## Windows Instalation
For Windows this software comes prepackaged with all the necessary binaries and dll's for compilation of the project, you still need to compile it in order to run it. You don't need to download anything additional, just open "OpenFace.sln" using Visual Studio 2015 and compile the code. The project was built and tested on Visual Studio 2015 (can't guarantee compatibility with other versions, and you would need to find/build the appropriate dll and lib files for them yourself). Code was tested on Windows 7/8/10 and Windows Server 2008 can't guarantee compatibility with other Windows versions (but in theory it should work).
NOTE be sure to run the project without debugger attached and in Release mode for speed (if running from Visual Studio). To run without debugger attach use CTRL + F5 instead of F5. To change from Debug mode to Release mode select Release from drop down menu in the toolbar. This can mean the difference between running at 5fps and 60fps on 320x240px videos. I also found that the x64 version seems to run faster on most machines.
## Unix Instalation
For Unix based systems and different compilers, I included Cmake files for cross-platform and cross-IDE support. For running the code on Ubuntu please see readme-ubuntu.txt for detailed instructions of how to get required libraries and build the project.
## Copyright
Copyright can be found in the Copyright.txt
You have to respect boost, TBB, dlib, and OpenCV licenses.
## Use
Explanation of the code layout and the command line arguments can be found in Readme.txt
## Windows Binaries
Coming Soon
## Citation
If you use any of the resources provided on this page in any of your publications we ask you to cite the following work and the work for a relevant submodule you used.
####Overall system
**OpenFace: an open source facial behavior analysis toolkit**
Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency,
in *IEEE Winter Conference on Applications of Computer Vision*, 2016
#### Facial landmark detection and tracking
**Constrained Local Neural Fields for robust facial landmark detection in the wild**
Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
in IEEE Int. *Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge*, 2013.
#### Eye gaze tracking
**Rendering of Eyes for Eye-Shape Registration and Gaze Estimation**
Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
in *IEEE International. Conference on Computer Vision (ICCV)*, 2015
#### Facial Action Unit detection
**Cross-dataset learning and person-specific normalisation for automatic Action Unit detection**
Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
in *Facial Expression Recognition and Analysis Challenge*,
*IEEE International Conference on Automatic Face and Gesture Recognition*, 2015

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@ -0,0 +1,293 @@
# Module for locating Intel's Threading Building Blocks (TBB).
#
# Customizable variables:
# TBB_ROOT_DIR
# Specifies TBB's root directory.
#
# Read-only variables:
# TBB_FOUND
# Indicates whether the library has been found.
#
# TBB_INCLUDE_DIRS
# Specifies TBB's include directory.
#
# TBB_LIBRARIES
# Specifies TBB libraries that should be passed to target_link_libararies.
#
# TBB_<COMPONENT>_LIBRARIES
# Specifies the libraries of a specific <COMPONENT>.
#
# TBB_<COMPONENT>_FOUND
# Indicates whether the specified <COMPONENT> was found.
#
#
# Copyright (c) 2013, 2014 Sergiu Dotenco
#
# 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 PARTTBBLAR 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.
INCLUDE (FindPackageHandleStandardArgs)
IF (CMAKE_VERSION VERSION_GREATER 2.8.7)
SET (_TBB_CHECK_COMPONENTS FALSE)
ELSE (CMAKE_VERSION VERSION_GREATER 2.8.7)
SET (_TBB_CHECK_COMPONENTS TRUE)
ENDIF (CMAKE_VERSION VERSION_GREATER 2.8.7)
FIND_PATH (TBB_ROOT_DIR
NAMES include/tbb/tbb.h
PATHS ENV TBBROOT
ENV TBB40_INSTALL_DIR
ENV TBB30_INSTALL_DIR
ENV TBB22_INSTALL_DIR
ENV TBB21_INSTALL_DIR
ENV ICPP_COMPILER13
ENV ICPP_COMPILER14
PATH_SUFFIXES tbb
DOC "TBB root directory")
FIND_PATH (TBB_INCLUDE_DIR
NAMES tbb/tbb.h
HINTS ${TBB_ROOT_DIR}
PATH_SUFFIXES include
DOC "TBB include directory")
IF (DEFINED TBB_COMPILER)
SET (_TBB_COMPILER ${TBB_COMPILER})
ELSEIF (MSVC12)
SET (_TBB_COMPILER vc12)
ELSEIF (MSVC11)
SET (_TBB_COMPILER vc11)
ELSEIF (MSVC10)
SET (_TBB_COMPILER vc10)
ELSEIF (MSVC90)
SET (_TBB_COMPILER vc9)
ELSEIF (MSVC80)
SET (_TBB_COMPILER vc8)
ELSEIF (MINGW)
SET (_TBB_COMPILER mingw)
ELSEIF (WIN32)
SET (_TBB_COMPILER vc_mt)
ENDIF (DEFINED TBB_COMPILER)
IF (CMAKE_SIZEOF_VOID_P EQUAL 8)
SET (_TBB_POSSIBLE_LIB_SUFFIXES lib/intel64/${_TBB_COMPILER})
SET (_TBB_POSSIBLE_BIN_SUFFIXES bin/intel64/${_TBB_COMPILER})
ELSE (CMAKE_SIZEOF_VOID_P EQUAL 8)
SET (_TBB_POSSIBLE_LIB_SUFFIXES lib/ia32/${_TBB_COMPILER})
SET (_TBB_POSSIBLE_BIN_SUFFIXES bin/ia32/${_TBB_COMPILER})
ENDIF (CMAKE_SIZEOF_VOID_P EQUAL 8)
LIST (APPEND _TBB_POSSIBLE_LIB_SUFFIXES lib/$ENV{TBB_ARCH_PLATFORM})
FIND_LIBRARY (TBB_LIBRARY_RELEASE
NAMES tbb
HINTS ${TBB_ROOT_DIR}
PATH_SUFFIXES ${_TBB_POSSIBLE_LIB_SUFFIXES}
DOC "TBB release library")
FIND_LIBRARY (TBB_LIBRARY_DEBUG
NAMES tbb_debug
HINTS ${TBB_ROOT_DIR}
PATH_SUFFIXES ${_TBB_POSSIBLE_LIB_SUFFIXES}
DOC "TBB debug library")
IF (TBB_LIBRARY_RELEASE AND TBB_LIBRARY_DEBUG)
SET (TBB_LIBRARY optimized ${TBB_LIBRARY_RELEASE} debug ${TBB_LIBRARY_DEBUG}
CACHE DOC "TBB library")
ELSEIF (TBB_LIBRARY_RELEASE)
SET (TBB_LIBRARY ${TBB_LIBRARY_RELEASE} CACHE DOC "TBB library")
ENDIF (TBB_LIBRARY_RELEASE AND TBB_LIBRARY_DEBUG)
IF (TBB_LIBRARY_DEBUG)
LIST (APPEND _TBB_ALL_LIBS ${TBB_LIBRARY_DEBUG})
ENDIF (TBB_LIBRARY_DEBUG)
IF (TBB_LIBRARY_RELEASE)
LIST (APPEND _TBB_ALL_LIBS ${TBB_LIBRARY_RELEASE})
ENDIF (TBB_LIBRARY_RELEASE)
FOREACH (_TBB_COMPONENT ${TBB_FIND_COMPONENTS})
STRING (TOUPPER ${_TBB_COMPONENT} _TBB_COMPONENT_UPPER)
SET (_TBB_LIBRARY_BASE TBB_${_TBB_COMPONENT_UPPER}_LIBRARY)
IF (${_TBB_COMPONENT} STREQUAL preview)
SET (_TBB_LIBRARY_NAME tbb_${_TBB_COMPONENT})
ELSE (${_TBB_COMPONENT} STREQUAL preview)
SET (_TBB_LIBRARY_NAME tbb${_TBB_COMPONENT})
ENDIF (${_TBB_COMPONENT} STREQUAL preview)
FIND_LIBRARY (${_TBB_LIBRARY_BASE}_RELEASE
NAMES ${_TBB_LIBRARY_NAME}
HINTS ${TBB_ROOT_DIR}
PATH_SUFFIXES ${_TBB_POSSIBLE_LIB_SUFFIXES}
DOC "TBB ${_TBB_COMPONENT} release library")
FIND_LIBRARY (${_TBB_LIBRARY_BASE}_DEBUG
NAMES ${_TBB_LIBRARY_NAME}_debug
HINTS ${TBB_ROOT_DIR}
PATH_SUFFIXES ${_TBB_POSSIBLE_LIB_SUFFIXES}
DOC "TBB ${_TBB_COMPONENT} debug library")
MARK_AS_ADVANCED (${_TBB_LIBRARY_BASE} ${_TBB_LIBRARY_BASE}_DEBUG)
SET (TBB_${_TBB_COMPONENT_UPPER}_FOUND TRUE)
IF (${_TBB_LIBRARY_BASE}_DEBUG AND ${_TBB_LIBRARY_BASE}_RELEASE)
SET (${_TBB_LIBRARY_BASE}
debug ${${_TBB_LIBRARY_BASE}_DEBUG}
optimized ${${_TBB_LIBRARY_BASE}_RELEASE} CACHE DOC
"TBB ${_TBB_COMPONENT} library")
ELSEIF (${_TBB_LIBRARY_BASE}_DEBUG)
SET (${_TBB_LIBRARY_BASE} ${${_TBB_LIBRARY_BASE}_DEBUG})
ELSEIF (${_TBB_LIBRARY_BASE}_RELEASE)
SET (${_TBB_LIBRARY_BASE} ${${_TBB_LIBRARY_BASE}_RELEASE}
CACHE DOC "TBB ${_TBB_COMPONENT} library")
ELSE (${_TBB_LIBRARY_BASE}_DEBUG AND ${_TBB_LIBRARY_BASE}_RELEASE)
# Component missing: record it for a later report
LIST (APPEND _TBB_MISSING_COMPONENTS ${_TBB_COMPONENT})
SET (TBB_${_TBB_COMPONENT_UPPER}_FOUND FALSE)
ENDIF (${_TBB_LIBRARY_BASE}_DEBUG AND ${_TBB_LIBRARY_BASE}_RELEASE)
IF (${_TBB_LIBRARY_BASE}_DEBUG)
LIST (APPEND _TBB_ALL_LIBS ${${_TBB_LIBRARY_BASE}_DEBUG})
ENDIF (${_TBB_LIBRARY_BASE}_DEBUG)
IF (${_TBB_LIBRARY_BASE}_RELEASE)
LIST (APPEND _TBB_ALL_LIBS ${${_TBB_LIBRARY_BASE}_RELEASE})
ENDIF (${_TBB_LIBRARY_BASE}_RELEASE)
SET (TBB_${_TBB_COMPONENT}_FOUND ${TBB_${_TBB_COMPONENT_UPPER}_FOUND})
IF (${_TBB_LIBRARY_BASE})
# setup the TBB_<COMPONENT>_LIBRARIES variable
SET (TBB_${_TBB_COMPONENT_UPPER}_LIBRARIES ${${_TBB_LIBRARY_BASE}})
LIST (APPEND TBB_LIBRARIES ${${_TBB_LIBRARY_BASE}})
ELSE (${_TBB_LIBRARY_BASE})
LIST (APPEND _TBB_MISSING_LIBRARIES ${_TBB_LIBRARY_BASE})
ENDIF (${_TBB_LIBRARY_BASE})
ENDFOREACH (_TBB_COMPONENT ${TBB_FIND_COMPONENTS})
LIST (APPEND TBB_LIBRARIES ${TBB_LIBRARY})
SET (TBB_INCLUDE_DIRS ${TBB_INCLUDE_DIR})
IF (DEFINED _TBB_MISSING_COMPONENTS AND _TBB_CHECK_COMPONENTS)
IF (NOT TBB_FIND_QUIETLY)
MESSAGE (STATUS "One or more TBB components were not found:")
# Display missing components indented, each on a separate line
FOREACH (_TBB_MISSING_COMPONENT ${_TBB_MISSING_COMPONENTS})
MESSAGE (STATUS " " ${_TBB_MISSING_COMPONENT})
ENDFOREACH (_TBB_MISSING_COMPONENT ${_TBB_MISSING_COMPONENTS})
ENDIF (NOT TBB_FIND_QUIETLY)
ENDIF (DEFINED _TBB_MISSING_COMPONENTS AND _TBB_CHECK_COMPONENTS)
# Determine library's version
SET (_TBB_VERSION_HEADER ${TBB_INCLUDE_DIR}/tbb/tbb_stddef.h)
IF (EXISTS ${_TBB_VERSION_HEADER})
FILE (READ ${_TBB_VERSION_HEADER} _TBB_VERSION_CONTENTS)
STRING (REGEX REPLACE ".*#define TBB_VERSION_MAJOR[ \t]+([0-9]+).*" "\\1"
TBB_VERSION_MAJOR "${_TBB_VERSION_CONTENTS}")
STRING (REGEX REPLACE ".*#define TBB_VERSION_MINOR[ \t]+([0-9]+).*" "\\1"
TBB_VERSION_MINOR "${_TBB_VERSION_CONTENTS}")
SET (TBB_VERSION ${TBB_VERSION_MAJOR}.${TBB_VERSION_MINOR})
SET (TBB_VERSION_COMPONENTS 2)
ENDIF (EXISTS ${_TBB_VERSION_HEADER})
IF (WIN32)
FIND_PROGRAM (LIB_EXECUTABLE NAMES lib
HINTS "$ENV{VS120COMNTOOLS}/../../VC/bin"
"$ENV{VS110COMNTOOLS}/../../VC/bin"
"$ENV{VS100COMNTOOLS}/../../VC/bin"
"$ENV{VS90COMNTOOLS}/../../VC/bin"
"$ENV{VS71COMNTOOLS}/../../VC/bin"
"$ENV{VS80COMNTOOLS}/../../VC/bin"
DOC "Library manager")
MARK_AS_ADVANCED (LIB_EXECUTABLE)
ENDIF (WIN32)
MACRO (GET_LIB_REQUISITES LIB REQUISITES)
IF (LIB_EXECUTABLE)
GET_FILENAME_COMPONENT (_LIB_PATH ${LIB_EXECUTABLE} PATH)
IF (MSVC)
# Do not redirect the output
UNSET (ENV{VS_UNICODE_OUTPUT})
ENDIF (MSVC)
EXECUTE_PROCESS (COMMAND ${LIB_EXECUTABLE} /nologo /list ${LIB}
WORKING_DIRECTORY ${_LIB_PATH}/../../Common7/IDE
OUTPUT_VARIABLE _LIB_OUTPUT ERROR_QUIET)
STRING (REPLACE "\n" ";" "${REQUISITES}" "${_LIB_OUTPUT}")
LIST (REMOVE_DUPLICATES ${REQUISITES})
ENDIF (LIB_EXECUTABLE)
ENDMACRO (GET_LIB_REQUISITES)
IF (_TBB_ALL_LIBS)
# collect lib requisites using the lib tool
FOREACH (_TBB_COMPONENT ${_TBB_ALL_LIBS})
GET_LIB_REQUISITES (${_TBB_COMPONENT} _TBB_REQUISITES)
ENDFOREACH (_TBB_COMPONENT)
ENDIF (_TBB_ALL_LIBS)
IF (NOT TBB_BINARY_DIR)
SET (_TBB_UPDATE_BINARY_DIR TRUE)
ELSE (NOT TBB_BINARY_DIR)
SET (_TBB_UPDATE_BINARY_DIR FALSE)
ENDIF (NOT TBB_BINARY_DIR)
SET (_TBB_BINARY_DIR_HINTS ${_TBB_POSSIBLE_BIN_SUFFIXES})
IF (_TBB_REQUISITES)
FIND_FILE (TBB_BINARY_DIR NAMES ${_TBB_REQUISITES}
HINTS ${TBB_ROOT_DIR}
PATH_SUFFIXES ${_TBB_BINARY_DIR_HINTS} NO_DEFAULT_PATH)
ENDIF (_TBB_REQUISITES)
IF (TBB_BINARY_DIR AND _TBB_UPDATE_BINARY_DIR)
SET (_TBB_BINARY_DIR ${TBB_BINARY_DIR})
UNSET (TBB_BINARY_DIR CACHE)
IF (_TBB_BINARY_DIR)
GET_FILENAME_COMPONENT (TBB_BINARY_DIR ${_TBB_BINARY_DIR} PATH)
IF (TBB_BINARY_DIR)
SET (TBB_BINARY_DIR ${TBB_BINARY_DIR} CACHE PATH "TBB binary directory")
ENDIF (TBB_BINARY_DIR)
ENDIF (_TBB_BINARY_DIR)
ENDIF (TBB_BINARY_DIR AND _TBB_UPDATE_BINARY_DIR)
MARK_AS_ADVANCED (TBB_INCLUDE_DIR TBB_LIBRARY TBB_LIBRARY_RELEASE
TBB_LIBRARY_DEBUG)
IF (NOT _TBB_CHECK_COMPONENTS)
SET (_TBB_FPHSA_ADDITIONAL_ARGS HANDLE_COMPONENTS)
ENDIF (NOT _TBB_CHECK_COMPONENTS)
IF (CMAKE_VERSION VERSION_GREATER 2.8.2)
LIST (APPEND _TBB_FPHSA_ADDITIONAL_ARGS VERSION_VAR TBB_VERSION)
ENDIF (CMAKE_VERSION VERSION_GREATER 2.8.2)
FIND_PACKAGE_HANDLE_STANDARD_ARGS (TBB REQUIRED_VARS TBB_ROOT_DIR
TBB_INCLUDE_DIR TBB_LIBRARY ${_TBB_MISSING_LIBRARIES}
${_TBB_FPHSA_ADDITIONAL_ARGS})

14
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# Local libraries
include_directories(${LandmarkDetector_SOURCE_DIR}/include)
include_directories(../../lib/local/LandmarkDetector/include)
include_directories(../../lib/local/FaceAnalyser/include)
add_executable(FaceLandmarkImg FaceLandmarkImg.cpp)
target_link_libraries(FaceLandmarkImg LandmarkDetector)
target_link_libraries(FaceLandmarkImg FaceAnalyser)
target_link_libraries(FaceLandmarkImg dlib)
target_link_libraries(FaceLandmarkImg ${OpenCV_LIBS} ${Boost_LIBRARIES} ${TBB_LIBRARIES})
install (TARGETS FaceLandmarkImg DESTINATION ${CMAKE_BINARY_DIR}/bin)

555
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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
// License Agreement with respect to such Open Source Component, such restrictions will not
// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
// delivery of the Software.
// * Any publications arising from the use of this software, including but
// not limited to academic journal and conference publications, technical
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
// FaceLandmarkImg.cpp : Defines the entry point for the console application for detecting landmarks in images.
#include "LandmarkCoreIncludes.h"
// System includes
#include <fstream>
// OpenCV includes
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc.hpp>
// Boost includes
#include <filesystem.hpp>
#include <filesystem/fstream.hpp>
#include <dlib/image_processing/frontal_face_detector.h>
#include <tbb/tbb.h>
#include <FaceAnalyser.h>
#include <GazeEstimation.h>
using namespace std;
vector<string> get_arguments(int argc, char **argv)
{
vector<string> arguments;
for(int i = 0; i < argc; ++i)
{
arguments.push_back(string(argv[i]));
}
return arguments;
}
void convert_to_grayscale(const cv::Mat& in, cv::Mat& out)
{
if(in.channels() == 3)
{
// Make sure it's in a correct format
if(in.depth() != CV_8U)
{
if(in.depth() == CV_16U)
{
cv::Mat tmp = in / 256;
tmp.convertTo(tmp, CV_8U);
cv::cvtColor(tmp, out, CV_BGR2GRAY);
}
}
else
{
cv::cvtColor(in, out, CV_BGR2GRAY);
}
}
else if(in.channels() == 4)
{
cv::cvtColor(in, out, CV_BGRA2GRAY);
}
else
{
if(in.depth() == CV_16U)
{
cv::Mat tmp = in / 256;
out = tmp.clone();
}
else if(in.depth() != CV_8U)
{
in.convertTo(out, CV_8U);
}
else
{
out = in.clone();
}
}
}
// Useful utility for creating directories for storing the output files
void create_directory_from_file(string output_path)
{
// Creating the right directory structure
// First get rid of the file
auto p = boost::filesystem::path(boost::filesystem::path(output_path).parent_path());
if (!p.empty() && !boost::filesystem::exists(p))
{
bool success = boost::filesystem::create_directories(p);
if (!success)
{
cout << "Failed to create a directory... " << p.string() << endl;
}
}
}
// This will only be accurate when camera parameters are accurate, useful for work on 3D data
void write_out_pose_landmarks(const string& outfeatures, const cv::Mat_<double>& shape3D, const cv::Vec6d& pose, const cv::Point3f& gaze0, const cv::Point3f& gaze1)
{
create_directory_from_file(outfeatures);
std::ofstream featuresFile;
featuresFile.open(outfeatures);
if (featuresFile.is_open())
{
int n = shape3D.cols;
featuresFile << "version: 1" << endl;
featuresFile << "npoints: " << n << endl;
featuresFile << "{" << endl;
for (int i = 0; i < n; ++i)
{
// Use matlab format, so + 1
featuresFile << shape3D.at<double>(i) << " " << shape3D.at<double>(i + n) << " " << shape3D.at<double>(i + 2*n) << endl;
}
featuresFile << "}" << endl;
// Do the pose and eye gaze if present as well
featuresFile << "pose: eul_x, eul_y, eul_z: " << endl;
featuresFile << "{" << endl;
featuresFile << pose[3] << " " << pose[4] << " " << pose[5] << endl;
featuresFile << "}" << endl;
// Do the pose and eye gaze if present as well
featuresFile << "gaze: dir_x_1, dir_y_1, dir_z_1, dir_x_2, dir_y_2, dir_z_2: " << endl;
featuresFile << "{" << endl;
featuresFile << gaze0.x << " " << gaze0.y << " " << gaze0.z << " " << gaze1.x << " " << gaze1.y << " " << gaze1.z << endl;
featuresFile << "}" << endl;
featuresFile.close();
}
}
void write_out_landmarks(const string& outfeatures, const LandmarkDetector::CLNF& clnf_model)
{
create_directory_from_file(outfeatures);
std::ofstream featuresFile;
featuresFile.open(outfeatures);
if(featuresFile.is_open())
{
int n = clnf_model.patch_experts.visibilities[0][0].rows;
featuresFile << "version: 1" << endl;
featuresFile << "npoints: " << n << endl;
featuresFile << "{" << endl;
for (int i = 0; i < n; ++ i)
{
// Use matlab format, so + 1
featuresFile << clnf_model.detected_landmarks.at<double>(i) + 1 << " " << clnf_model.detected_landmarks.at<double>(i+n) + 1 << endl;
}
featuresFile << "}" << endl;
}
}
void create_display_image(const cv::Mat& orig, cv::Mat& display_image, LandmarkDetector::CLNF& clnf_model)
{
// Draw head pose if present and draw eye gaze as well
// preparing the visualisation image
display_image = orig.clone();
// Creating a display image
cv::Mat xs = clnf_model.detected_landmarks(cv::Rect(0, 0, 1, clnf_model.detected_landmarks.rows/2));
cv::Mat ys = clnf_model.detected_landmarks(cv::Rect(0, clnf_model.detected_landmarks.rows/2, 1, clnf_model.detected_landmarks.rows/2));
double min_x, max_x, min_y, max_y;
cv::minMaxLoc(xs, &min_x, &max_x);
cv::minMaxLoc(ys, &min_y, &max_y);
double width = max_x - min_x;
double height = max_y - min_y;
int minCropX = max((int)(min_x-width/3.0),0);
int minCropY = max((int)(min_y-height/3.0),0);
int widthCrop = min((int)(width*5.0/3.0), display_image.cols - minCropX - 1);
int heightCrop = min((int)(height*5.0/3.0), display_image.rows - minCropY - 1);
double scaling = 350.0/widthCrop;
// first crop the image
display_image = display_image(cv::Rect((int)(minCropX), (int)(minCropY), (int)(widthCrop), (int)(heightCrop)));
// now scale it
cv::resize(display_image.clone(), display_image, cv::Size(), scaling, scaling);
// Make the adjustments to points
xs = (xs - minCropX)*scaling;
ys = (ys - minCropY)*scaling;
cv::Mat shape = clnf_model.detected_landmarks.clone();
xs.copyTo(shape(cv::Rect(0, 0, 1, clnf_model.detected_landmarks.rows/2)));
ys.copyTo(shape(cv::Rect(0, clnf_model.detected_landmarks.rows/2, 1, clnf_model.detected_landmarks.rows/2)));
// Do the shifting for the hierarchical models as well
for (size_t part = 0; part < clnf_model.hierarchical_models.size(); ++part)
{
cv::Mat xs = clnf_model.hierarchical_models[part].detected_landmarks(cv::Rect(0, 0, 1, clnf_model.hierarchical_models[part].detected_landmarks.rows / 2));
cv::Mat ys = clnf_model.hierarchical_models[part].detected_landmarks(cv::Rect(0, clnf_model.hierarchical_models[part].detected_landmarks.rows / 2, 1, clnf_model.hierarchical_models[part].detected_landmarks.rows / 2));
xs = (xs - minCropX)*scaling;
ys = (ys - minCropY)*scaling;
cv::Mat shape = clnf_model.hierarchical_models[part].detected_landmarks.clone();
xs.copyTo(shape(cv::Rect(0, 0, 1, clnf_model.hierarchical_models[part].detected_landmarks.rows / 2)));
ys.copyTo(shape(cv::Rect(0, clnf_model.hierarchical_models[part].detected_landmarks.rows / 2, 1, clnf_model.hierarchical_models[part].detected_landmarks.rows / 2)));
}
LandmarkDetector::Draw(display_image, clnf_model);
}
int main (int argc, char **argv)
{
//Convert arguments to more convenient vector form
vector<string> arguments = get_arguments(argc, argv);
// Some initial parameters that can be overriden from command line
vector<string> files, depth_files, output_images, output_landmark_locations, output_pose_locations;
// Bounding boxes for a face in each image (optional)
vector<cv::Rect_<double> > bounding_boxes;
LandmarkDetector::get_image_input_output_params(files, depth_files, output_landmark_locations, output_pose_locations, output_images, bounding_boxes, arguments);
LandmarkDetector::FaceModelParameters det_parameters(arguments);
// No need to validate detections, as we're not doing tracking
det_parameters.validate_detections = false;
// Grab camera parameters if provided (only used for pose and eye gaze and are quite important for accurate estimates)
float fx = 0, fy = 0, cx = 0, cy = 0;
int device = -1;
LandmarkDetector::get_camera_params(device, fx, fy, cx, cy, arguments);
// If cx (optical axis centre) is undefined will use the image size/2 as an estimate
bool cx_undefined = false;
bool fx_undefined = false;
if (cx == 0 || cy == 0)
{
cx_undefined = true;
}
if (fx == 0 || fy == 0)
{
fx_undefined = true;
}
// The modules that are being used for tracking
cout << "Loading the model" << endl;
LandmarkDetector::CLNF clnf_model(det_parameters.model_location);
cout << "Model loaded" << endl;
cv::CascadeClassifier classifier(det_parameters.face_detector_location);
dlib::frontal_face_detector face_detector_hog = dlib::get_frontal_face_detector();
bool visualise = !det_parameters.quiet_mode;
// Do some image loading
for(size_t i = 0; i < files.size(); i++)
{
string file = files.at(i);
// Loading image
cv::Mat read_image = cv::imread(file, -1);
// Loading depth file if exists (optional)
cv::Mat_<float> depth_image;
if(depth_files.size() > 0)
{
string dFile = depth_files.at(i);
cv::Mat dTemp = cv::imread(dFile, -1);
dTemp.convertTo(depth_image, CV_32F);
}
// Making sure the image is in uchar grayscale
cv::Mat_<uchar> grayscale_image;
convert_to_grayscale(read_image, grayscale_image);
// If optical centers are not defined just use center of image
if (cx_undefined)
{
cx = grayscale_image.cols / 2.0f;
cy = grayscale_image.rows / 2.0f;
}
// Use a rough guess-timate of focal length
if (fx_undefined)
{
fx = 500 * (grayscale_image.cols / 640.0);
fy = 500 * (grayscale_image.rows / 480.0);
fx = (fx + fy) / 2.0;
fy = fx;
}
// if no pose defined we just use a face detector
if(bounding_boxes.empty())
{
// Detect faces in an image
vector<cv::Rect_<double> > face_detections;
if(det_parameters.curr_face_detector == LandmarkDetector::FaceModelParameters::HOG_SVM_DETECTOR)
{
vector<double> confidences;
LandmarkDetector::DetectFacesHOG(face_detections, grayscale_image, face_detector_hog, confidences);
}
else
{
LandmarkDetector::DetectFaces(face_detections, grayscale_image, classifier);
}
// Detect landmarks around detected faces
int face_det = 0;
// perform landmark detection for every face detected
for(size_t face=0; face < face_detections.size(); ++face)
{
// if there are multiple detections go through them
bool success = LandmarkDetector::DetectLandmarksInImage(grayscale_image, depth_image, face_detections[face], clnf_model, det_parameters);
// Estimate head pose and eye gaze
cv::Vec6d headPose = LandmarkDetector::GetCorrectedPoseWorld(clnf_model, fx, fy, cx, cy);
// Gaze tracking, absolute gaze direction
cv::Point3f gazeDirection0(0, 0, -1);
cv::Point3f gazeDirection1(0, 0, -1);
if (success && det_parameters.track_gaze)
{
FaceAnalysis::EstimateGaze(clnf_model, gazeDirection0, fx, fy, cx, cy, true);
FaceAnalysis::EstimateGaze(clnf_model, gazeDirection1, fx, fy, cx, cy, false);
}
// Writing out the detected landmarks (in an OS independent manner)
if(!output_landmark_locations.empty())
{
char name[100];
// append detection number (in case multiple faces are detected)
sprintf(name, "_det_%d", face_det);
// Construct the output filename
boost::filesystem::path slash("/");
std::string preferredSlash = slash.make_preferred().string();
boost::filesystem::path out_feat_path(output_landmark_locations.at(i));
boost::filesystem::path dir = out_feat_path.parent_path();
boost::filesystem::path fname = out_feat_path.filename().replace_extension("");
boost::filesystem::path ext = out_feat_path.extension();
string outfeatures = dir.string() + preferredSlash + fname.string() + string(name) + ext.string();
write_out_landmarks(outfeatures, clnf_model);
}
if (!output_pose_locations.empty())
{
char name[100];
// append detection number (in case multiple faces are detected)
sprintf(name, "_det_%d", face_det);
// Construct the output filename
boost::filesystem::path slash("/");
std::string preferredSlash = slash.make_preferred().string();
boost::filesystem::path out_pose_path(output_pose_locations.at(i));
boost::filesystem::path dir = out_pose_path.parent_path();
boost::filesystem::path fname = out_pose_path.filename().replace_extension("");
boost::filesystem::path ext = out_pose_path.extension();
string outfeatures = dir.string() + preferredSlash + fname.string() + string(name) + ext.string();
write_out_pose_landmarks(outfeatures, clnf_model.GetShape(fx, fy, cx, cy), headPose, gazeDirection0, gazeDirection1);
}
if (det_parameters.track_gaze)
{
cv::Vec6d pose_estimate_to_draw = LandmarkDetector::GetCorrectedPoseWorld(clnf_model, fx, fy, cx, cy);
// Draw it in reddish if uncertain, blueish if certain
LandmarkDetector::DrawBox(read_image, pose_estimate_to_draw, cv::Scalar(255.0, 0, 0), 3, fx, fy, cx, cy);
FaceAnalysis::DrawGaze(read_image, clnf_model, gazeDirection0, gazeDirection1, fx, fy, cx, cy);
}
// displaying detected landmarks
cv::Mat display_image;
create_display_image(read_image, display_image, clnf_model);
if(visualise && success)
{
imshow("colour", display_image);
cv::waitKey(1);
}
// Saving the display images (in an OS independent manner)
if(!output_images.empty() && success)
{
string outimage = output_images.at(i);
if(!outimage.empty())
{
char name[100];
sprintf(name, "_det_%d", face_det);
boost::filesystem::path slash("/");
std::string preferredSlash = slash.make_preferred().string();
// append detection number
boost::filesystem::path out_feat_path(outimage);
boost::filesystem::path dir = out_feat_path.parent_path();
boost::filesystem::path fname = out_feat_path.filename().replace_extension("");
boost::filesystem::path ext = out_feat_path.extension();
outimage = dir.string() + preferredSlash + fname.string() + string(name) + ext.string();
create_directory_from_file(outimage);
imwrite(outimage, display_image);
}
}
if(success)
{
face_det++;
}
}
}
else
{
// Have provided bounding boxes
LandmarkDetector::DetectLandmarksInImage(grayscale_image, bounding_boxes[i], clnf_model, det_parameters);
// Estimate head pose and eye gaze
cv::Vec6d headPose = LandmarkDetector::GetCorrectedPoseWorld(clnf_model, fx, fy, cx, cy);
// Gaze tracking, absolute gaze direction
cv::Point3f gazeDirection0(0, 0, -1);
cv::Point3f gazeDirection1(0, 0, -1);
if (det_parameters.track_gaze)
{
FaceAnalysis::EstimateGaze(clnf_model, gazeDirection0, fx, fy, cx, cy, true);
FaceAnalysis::EstimateGaze(clnf_model, gazeDirection1, fx, fy, cx, cy, false);
}
// Writing out the detected landmarks
if(!output_landmark_locations.empty())
{
string outfeatures = output_landmark_locations.at(i);
write_out_landmarks(outfeatures, clnf_model);
}
// Writing out the detected landmarks
if (!output_pose_locations.empty())
{
string outfeatures = output_pose_locations.at(i);
write_out_pose_landmarks(outfeatures, clnf_model.GetShape(fx, fy, cx, cy), headPose, gazeDirection0, gazeDirection1);
}
// displaying detected stuff
cv::Mat display_image;
if (det_parameters.track_gaze)
{
cv::Vec6d pose_estimate_to_draw = LandmarkDetector::GetCorrectedPoseWorld(clnf_model, fx, fy, cx, cy);
// Draw it in reddish if uncertain, blueish if certain
LandmarkDetector::DrawBox(read_image, pose_estimate_to_draw, cv::Scalar(255.0, 0, 0), 3, fx, fy, cx, cy);
FaceAnalysis::DrawGaze(read_image, clnf_model, gazeDirection0, gazeDirection1, fx, fy, cx, cy);
}
create_display_image(read_image, display_image, clnf_model);
if(visualise)
{
imshow("colour", display_image);
cv::waitKey(1);
}
if(!output_images.empty())
{
string outimage = output_images.at(i);
if(!outimage.empty())
{
create_directory_from_file(outimage);
imwrite(outimage, display_image);
}
}
}
}
return 0;
}

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add_executable(FaceLandmarkVid FaceLandmarkVid.cpp)
# Local libraries
include_directories(${LandmarkDetector_SOURCE_DIR}/include)
include_directories(../../lib/local/LandmarkDetector/include)
include_directories(../../lib/local/FaceAnalyser/include)
target_link_libraries(FaceLandmarkVid LandmarkDetector)
target_link_libraries(FaceLandmarkVid FaceAnalyser)
target_link_libraries(FaceLandmarkVid dlib)
target_link_libraries(FaceLandmarkVid ${OpenCV_LIBS} ${Boost_LIBRARIES} ${TBB_LIBRARIES})
install (TARGETS FaceLandmarkVid DESTINATION ${CMAKE_BINARY_DIR}/bin)

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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
// License Agreement with respect to such Open Source Component, such restrictions will not
// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
// delivery of the Software.
// * Any publications arising from the use of this software, including but
// not limited to academic journal and conference publications, technical
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
// FaceTrackingVid.cpp : Defines the entry point for the console application for tracking faces in videos.
// Libraries for landmark detection (includes CLNF and CLM modules)
#include "LandmarkCoreIncludes.h"
#include "GazeEstimation.h"
#include <fstream>
#include <sstream>
// OpenCV includes
#include <opencv2/videoio/videoio.hpp> // Video write
#include <opencv2/videoio/videoio_c.h> // Video write
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
// Boost includes
#include <filesystem.hpp>
#include <filesystem/fstream.hpp>
#define INFO_STREAM( stream ) \
std::cout << stream << std::endl
#define WARN_STREAM( stream ) \
std::cout << "Warning: " << stream << std::endl
#define ERROR_STREAM( stream ) \
std::cout << "Error: " << stream << std::endl
static void printErrorAndAbort( const std::string & error )
{
std::cout << error << std::endl;
abort();
}
#define FATAL_STREAM( stream ) \
printErrorAndAbort( std::string( "Fatal error: " ) + stream )
using namespace std;
vector<string> get_arguments(int argc, char **argv)
{
vector<string> arguments;
for(int i = 0; i < argc; ++i)
{
arguments.push_back(string(argv[i]));
}
return arguments;
}
// Some globals for tracking timing information for visualisation
double fps_tracker = -1.0;
int64 t0 = 0;
// Visualising the results
void visualise_tracking(cv::Mat& captured_image, cv::Mat_<float>& depth_image, const LandmarkDetector::CLNF& face_model, const LandmarkDetector::FaceModelParameters& det_parameters, cv::Point3f gazeDirection0, cv::Point3f gazeDirection1, int frame_count, double fx, double fy, double cx, double cy)
{
// Drawing the facial landmarks on the face and the bounding box around it if tracking is successful and initialised
double detection_certainty = face_model.detection_certainty;
bool detection_success = face_model.detection_success;
double visualisation_boundary = 0.2;
// Only draw if the reliability is reasonable, the value is slightly ad-hoc
if (detection_certainty < visualisation_boundary)
{
LandmarkDetector::Draw(captured_image, face_model);
double vis_certainty = detection_certainty;
if (vis_certainty > 1)
vis_certainty = 1;
if (vis_certainty < -1)
vis_certainty = -1;
vis_certainty = (vis_certainty + 1) / (visualisation_boundary + 1);
// A rough heuristic for box around the face width
int thickness = (int)std::ceil(2.0* ((double)captured_image.cols) / 640.0);
cv::Vec6d pose_estimate_to_draw = LandmarkDetector::GetCorrectedPoseWorld(face_model, fx, fy, cx, cy);
// Draw it in reddish if uncertain, blueish if certain
LandmarkDetector::DrawBox(captured_image, pose_estimate_to_draw, cv::Scalar((1 - vis_certainty)*255.0, 0, vis_certainty * 255), thickness, fx, fy, cx, cy);
if (det_parameters.track_gaze && detection_success && face_model.eye_model)
{
FaceAnalysis::DrawGaze(captured_image, face_model, gazeDirection0, gazeDirection1, fx, fy, cx, cy);
}
}
// Work out the framerate
if (frame_count % 10 == 0)
{
double t1 = cv::getTickCount();
fps_tracker = 10.0 / (double(t1 - t0) / cv::getTickFrequency());
t0 = t1;
}
// Write out the framerate on the image before displaying it
char fpsC[255];
std::sprintf(fpsC, "%d", (int)fps_tracker);
string fpsSt("FPS:");
fpsSt += fpsC;
cv::putText(captured_image, fpsSt, cv::Point(10, 20), CV_FONT_HERSHEY_SIMPLEX, 0.5, CV_RGB(255, 0, 0));
if (!det_parameters.quiet_mode)
{
cv::namedWindow("tracking_result", 1);
cv::imshow("tracking_result", captured_image);
if (!depth_image.empty())
{
// Division needed for visualisation purposes
imshow("depth", depth_image / 2000.0);
}
}
}
int main (int argc, char **argv)
{
vector<string> arguments = get_arguments(argc, argv);
// Some initial parameters that can be overriden from command line
vector<string> files, depth_directories, output_video_files, out_dummy;
// By default try webcam 0
int device = 0;
LandmarkDetector::FaceModelParameters det_parameters(arguments);
// Get the input output file parameters
// Indicates that rotation should be with respect to world or camera coordinates
bool u;
LandmarkDetector::get_video_input_output_params(files, depth_directories, out_dummy, output_video_files, u, arguments);
// The modules that are being used for tracking
LandmarkDetector::CLNF clnf_model(det_parameters.model_location);
// Grab camera parameters, if they are not defined (approximate values will be used)
float fx = 0, fy = 0, cx = 0, cy = 0;
// Get camera parameters
LandmarkDetector::get_camera_params(device, fx, fy, cx, cy, arguments);
// If cx (optical axis centre) is undefined will use the image size/2 as an estimate
bool cx_undefined = false;
bool fx_undefined = false;
if (cx == 0 || cy == 0)
{
cx_undefined = true;
}
if (fx == 0 || fy == 0)
{
fx_undefined = true;
}
// If multiple video files are tracked, use this to indicate if we are done
bool done = false;
int f_n = -1;
det_parameters.track_gaze = true;
while(!done) // this is not a for loop as we might also be reading from a webcam
{
string current_file;
// We might specify multiple video files as arguments
if(files.size() > 0)
{
f_n++;
current_file = files[f_n];
}
else
{
// If we want to write out from webcam
f_n = 0;
}
bool use_depth = !depth_directories.empty();
// Do some grabbing
cv::VideoCapture video_capture;
if( current_file.size() > 0 )
{
if (!boost::filesystem::exists(current_file))
{
FATAL_STREAM("File does not exist");
}
current_file = boost::filesystem::path(current_file).generic_string();
INFO_STREAM( "Attempting to read from file: " << current_file );
video_capture = cv::VideoCapture( current_file );
}
else
{
INFO_STREAM( "Attempting to capture from device: " << device );
video_capture = cv::VideoCapture( device );
// Read a first frame often empty in camera
cv::Mat captured_image;
video_capture >> captured_image;
}
if( !video_capture.isOpened() ) FATAL_STREAM( "Failed to open video source" );
else INFO_STREAM( "Device or file opened");
cv::Mat captured_image;
video_capture >> captured_image;
// If optical centers are not defined just use center of image
if (cx_undefined)
{
cx = captured_image.cols / 2.0f;
cy = captured_image.rows / 2.0f;
}
// Use a rough guess-timate of focal length
if (fx_undefined)
{
fx = 500 * (captured_image.cols / 640.0);
fy = 500 * (captured_image.rows / 480.0);
fx = (fx + fy) / 2.0;
fy = fx;
}
int frame_count = 0;
// saving the videos
cv::VideoWriter writerFace;
if (!output_video_files.empty())
{
writerFace = cv::VideoWriter(output_video_files[f_n], CV_FOURCC('D', 'I', 'V', 'X'), 30, captured_image.size(), true);
}
// Use for timestamping if using a webcam
int64 t_initial = cv::getTickCount();
INFO_STREAM( "Starting tracking");
while(!captured_image.empty())
{
// Reading the images
cv::Mat_<float> depth_image;
cv::Mat_<uchar> grayscale_image;
if(captured_image.channels() == 3)
{
cv::cvtColor(captured_image, grayscale_image, CV_BGR2GRAY);
}
else
{
grayscale_image = captured_image.clone();
}
// Get depth image
if(use_depth)
{
char* dst = new char[100];
std::stringstream sstream;
sstream << depth_directories[f_n] << "\\depth%05d.png";
sprintf(dst, sstream.str().c_str(), frame_count + 1);
// Reading in 16-bit png image representing depth
cv::Mat_<short> depth_image_16_bit = cv::imread(string(dst), -1);
// Convert to a floating point depth image
if(!depth_image_16_bit.empty())
{
depth_image_16_bit.convertTo(depth_image, CV_32F);
}
else
{
WARN_STREAM( "Can't find depth image" );
}
}
// The actual facial landmark detection / tracking
bool detection_success = LandmarkDetector::DetectLandmarksInVideo(grayscale_image, depth_image, clnf_model, det_parameters);
// Visualising the results
// Drawing the facial landmarks on the face and the bounding box around it if tracking is successful and initialised
double detection_certainty = clnf_model.detection_certainty;
// Gaze tracking, absolute gaze direction
cv::Point3f gazeDirection0(0, 0, -1);
cv::Point3f gazeDirection1(0, 0, -1);
if (det_parameters.track_gaze && detection_success && clnf_model.eye_model)
{
FaceAnalysis::EstimateGaze(clnf_model, gazeDirection0, fx, fy, cx, cy, true);
FaceAnalysis::EstimateGaze(clnf_model, gazeDirection1, fx, fy, cx, cy, false);
}
visualise_tracking(captured_image, depth_image, clnf_model, det_parameters, gazeDirection0, gazeDirection1, frame_count, fx, fy, cx, cy);
// output the tracked video
if (!output_video_files.empty())
{
writerFace << captured_image;
}
video_capture >> captured_image;
// detect key presses
char character_press = cv::waitKey(1);
// restart the tracker
if(character_press == 'r')
{
clnf_model.Reset();
}
// quit the application
else if(character_press=='q')
{
return(0);
}
// Update the frame count
frame_count++;
}
frame_count = 0;
// Reset the model, for the next video
clnf_model.Reset();
// break out of the loop if done with all the files (or using a webcam)
if(f_n == files.size() -1 || files.empty())
{
done = true;
}
}
return 0;
}

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# Local libraries
include_directories(${LandmarkDetector_SOURCE_DIR}/include)
include_directories(../../lib/local/LandmarkDetector/include)
add_executable(FaceLandmarkVidMulti FaceLandmarkVidMulti.cpp)
target_link_libraries(FaceLandmarkVidMulti LandmarkDetector)
target_link_libraries(FaceLandmarkVidMulti dlib)
target_link_libraries(FaceLandmarkVidMulti ${OpenCV_LIBS} ${Boost_LIBRARIES} ${TBB_LIBRARIES})
install (TARGETS FaceLandmarkVidMulti DESTINATION ${CMAKE_BINARY_DIR}/bin)

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exe/FaceLandmarkVidMulti/FaceLandmarkVidMulti.cpp Normal file
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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
// License Agreement with respect to such Open Source Component, such restrictions will not
// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
// delivery of the Software.
// * Any publications arising from the use of this software, including but
// not limited to academic journal and conference publications, technical
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
// FaceTrackingVidMulti.cpp : Defines the entry point for the multiple face tracking console application.
#include "LandmarkCoreIncludes.h"
#include <fstream>
#include <sstream>
// OpenCV includes
#include <opencv2/videoio/videoio.hpp> // Video write
#include <opencv2/videoio/videoio_c.h> // Video write
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#define INFO_STREAM( stream ) \
std::cout << stream << std::endl
#define WARN_STREAM( stream ) \
std::cout << "Warning: " << stream << std::endl
#define ERROR_STREAM( stream ) \
std::cout << "Error: " << stream << std::endl
static void printErrorAndAbort( const std::string & error )
{
std::cout << error << std::endl;
abort();
}
#define FATAL_STREAM( stream ) \
printErrorAndAbort( std::string( "Fatal error: " ) + stream )
using namespace std;
vector<string> get_arguments(int argc, char **argv)
{
vector<string> arguments;
for(int i = 0; i < argc; ++i)
{
arguments.push_back(string(argv[i]));
}
return arguments;
}
void NonOverlapingDetections(const vector<LandmarkDetector::CLNF>& clnf_models, vector<cv::Rect_<double> >& face_detections)
{
// Go over the model and eliminate detections that are not informative (there already is a tracker there)
for(size_t model = 0; model < clnf_models.size(); ++model)
{
// See if the detections intersect
cv::Rect_<double> model_rect = clnf_models[model].GetBoundingBox();
for(int detection = face_detections.size()-1; detection >=0; --detection)
{
double intersection_area = (model_rect & face_detections[detection]).area();
double union_area = model_rect.area() + face_detections[detection].area() - 2 * intersection_area;
// If the model is already tracking what we're detecting ignore the detection, this is determined by amount of overlap
if( intersection_area/union_area > 0.5)
{
face_detections.erase(face_detections.begin() + detection);
}
}
}
}
int main (int argc, char **argv)
{
vector<string> arguments = get_arguments(argc, argv);
// Some initial parameters that can be overriden from command line
vector<string> files, depth_directories, tracked_videos_output, dummy_out;
// By default try webcam 0
int device = 0;
// cx and cy aren't necessarilly in the image center, so need to be able to override it (start with unit vals and init them if none specified)
float fx = 600, fy = 600, cx = 0, cy = 0;
LandmarkDetector::FaceModelParameters det_params(arguments);
det_params.use_face_template = true;
// This is so that the model would not try re-initialising itself
det_params.reinit_video_every = -1;
det_params.curr_face_detector = LandmarkDetector::FaceModelParameters::HOG_SVM_DETECTOR;
vector<LandmarkDetector::FaceModelParameters> det_parameters;
det_parameters.push_back(det_params);
// Get the input output file parameters
bool u;
LandmarkDetector::get_video_input_output_params(files, depth_directories, dummy_out, tracked_videos_output, u, arguments);
// Get camera parameters
LandmarkDetector::get_camera_params(device, fx, fy, cx, cy, arguments);
// The modules that are being used for tracking
vector<LandmarkDetector::CLNF> clnf_models;
vector<bool> active_models;
int num_faces_max = 4;
LandmarkDetector::CLNF clnf_model(det_parameters[0].model_location);
clnf_model.face_detector_HAAR.load(det_parameters[0].face_detector_location);
clnf_model.face_detector_location = det_parameters[0].face_detector_location;
clnf_models.reserve(num_faces_max);
clnf_models.push_back(clnf_model);
active_models.push_back(false);
for (int i = 1; i < num_faces_max; ++i)
{
clnf_models.push_back(clnf_model);
active_models.push_back(false);
det_parameters.push_back(det_params);
}
// If multiple video files are tracked, use this to indicate if we are done
bool done = false;
int f_n = -1;
// If cx (optical axis centre) is undefined will use the image size/2 as an estimate
bool cx_undefined = false;
if(cx == 0 || cy == 0)
{
cx_undefined = true;
}
while(!done) // this is not a for loop as we might also be reading from a webcam
{
string current_file;
// We might specify multiple video files as arguments
if(files.size() > 0)
{
f_n++;
current_file = files[f_n];
}
bool use_depth = !depth_directories.empty();
// Do some grabbing
cv::VideoCapture video_capture;
if( current_file.size() > 0 )
{
INFO_STREAM( "Attempting to read from file: " << current_file );
video_capture = cv::VideoCapture( current_file );
}
else
{
INFO_STREAM( "Attempting to capture from device: " << device );
video_capture = cv::VideoCapture( device );
// Read a first frame often empty in camera
cv::Mat captured_image;
video_capture >> captured_image;
}
if( !video_capture.isOpened() ) FATAL_STREAM( "Failed to open video source" );
else INFO_STREAM( "Device or file opened");
cv::Mat captured_image;
video_capture >> captured_image;
// If optical centers are not defined just use center of image
if(cx_undefined)
{
cx = captured_image.cols / 2.0f;
cy = captured_image.rows / 2.0f;
}
int frame_count = 0;
// saving the videos
cv::VideoWriter writerFace;
if(!tracked_videos_output.empty())
{
writerFace = cv::VideoWriter(tracked_videos_output[f_n], CV_FOURCC('D','I','V','X'), 30, captured_image.size(), true);
}
// For measuring the timings
int64 t1,t0 = cv::getTickCount();
double fps = 10;
INFO_STREAM( "Starting tracking");
while(!captured_image.empty())
{
// Reading the images
cv::Mat_<float> depth_image;
cv::Mat_<uchar> grayscale_image;
cv::Mat disp_image = captured_image.clone();
if(captured_image.channels() == 3)
{
cv::cvtColor(captured_image, grayscale_image, CV_BGR2GRAY);
}
else
{
grayscale_image = captured_image.clone();
}
// Get depth image
if(use_depth)
{
char* dst = new char[100];
std::stringstream sstream;
sstream << depth_directories[f_n] << "\\depth%05d.png";
sprintf(dst, sstream.str().c_str(), frame_count + 1);
// Reading in 16-bit png image representing depth
cv::Mat_<short> depth_image_16_bit = cv::imread(string(dst), -1);
// Convert to a floating point depth image
if(!depth_image_16_bit.empty())
{
depth_image_16_bit.convertTo(depth_image, CV_32F);
}
else
{
WARN_STREAM( "Can't find depth image" );
}
}
vector<cv::Rect_<double> > face_detections;
bool all_models_active = true;
for(unsigned int model = 0; model < clnf_models.size(); ++model)
{
if(!active_models[model])
{
all_models_active = false;
}
}
// Get the detections (every 8th frame and when there are free models available for tracking)
if(frame_count % 8 == 0 && !all_models_active)
{
if(det_parameters[0].curr_face_detector == LandmarkDetector::FaceModelParameters::HOG_SVM_DETECTOR)
{
vector<double> confidences;
LandmarkDetector::DetectFacesHOG(face_detections, grayscale_image, clnf_models[0].face_detector_HOG, confidences);
}
else
{
LandmarkDetector::DetectFaces(face_detections, grayscale_image, clnf_models[0].face_detector_HAAR);
}
}
// Keep only non overlapping detections (also convert to a concurrent vector
NonOverlapingDetections(clnf_models, face_detections);
vector<tbb::atomic<bool> > face_detections_used(face_detections.size());
// Go through every model and update the tracking
tbb::parallel_for(0, (int)clnf_models.size(), [&](int model){
//for(unsigned int model = 0; model < clnf_models.size(); ++model)
//{
bool detection_success = false;
// If the current model has failed more than 4 times in a row, remove it
if(clnf_models[model].failures_in_a_row > 4)
{
active_models[model] = false;
clnf_models[model].Reset();
}
// If the model is inactive reactivate it with new detections
if(!active_models[model])
{
for(size_t detection_ind = 0; detection_ind < face_detections.size(); ++detection_ind)
{
// if it was not taken by another tracker take it (if it is false swap it to true and enter detection, this makes it parallel safe)
if(face_detections_used[detection_ind].compare_and_swap(true, false) == false)
{
// Reinitialise the model
clnf_models[model].Reset();
// This ensures that a wider window is used for the initial landmark localisation
clnf_models[model].detection_success = false;
detection_success = LandmarkDetector::DetectLandmarksInVideo(grayscale_image, depth_image, face_detections[detection_ind], clnf_models[model], det_parameters[model]);
// This activates the model
active_models[model] = true;
// break out of the loop as the tracker has been reinitialised
break;
}
}
}
else
{
// The actual facial landmark detection / tracking
detection_success = LandmarkDetector::DetectLandmarksInVideo(grayscale_image, depth_image, clnf_models[model], det_parameters[model]);
}
});
// Go through every model and visualise the results
for(size_t model = 0; model < clnf_models.size(); ++model)
{
// Visualising the results
// Drawing the facial landmarks on the face and the bounding box around it if tracking is successful and initialised
double detection_certainty = clnf_models[model].detection_certainty;
double visualisation_boundary = -0.1;
// Only draw if the reliability is reasonable, the value is slightly ad-hoc
if(detection_certainty < visualisation_boundary)
{
LandmarkDetector::Draw(disp_image, clnf_models[model]);
if(detection_certainty > 1)
detection_certainty = 1;
if(detection_certainty < -1)
detection_certainty = -1;
detection_certainty = (detection_certainty + 1)/(visualisation_boundary +1);
// A rough heuristic for box around the face width
int thickness = (int)std::ceil(2.0* ((double)captured_image.cols) / 640.0);
// Work out the pose of the head from the tracked model
cv::Vec6d pose_estimate = LandmarkDetector::GetCorrectedPoseWorld(clnf_models[model], fx, fy, cx, cy);
// Draw it in reddish if uncertain, blueish if certain
LandmarkDetector::DrawBox(disp_image, pose_estimate, cv::Scalar((1-detection_certainty)*255.0,0, detection_certainty*255), thickness, fx, fy, cx, cy);
}
}
// Work out the framerate
if(frame_count % 10 == 0)
{
t1 = cv::getTickCount();
fps = 10.0 / (double(t1-t0)/cv::getTickFrequency());
t0 = t1;
}
// Write out the framerate on the image before displaying it
char fpsC[255];
sprintf(fpsC, "%d", (int)fps);
string fpsSt("FPS:");
fpsSt += fpsC;
cv::putText(disp_image, fpsSt, cv::Point(10,20), CV_FONT_HERSHEY_SIMPLEX, 0.5, CV_RGB(255,0,0));
int num_active_models = 0;
for( size_t active_model = 0; active_model < active_models.size(); active_model++)
{
if(active_models[active_model])
{
num_active_models++;
}
}
char active_m_C[255];
sprintf(active_m_C, "%d", num_active_models);
string active_models_st("Active models:");
active_models_st += active_m_C;
cv::putText(disp_image, active_models_st, cv::Point(10,60), CV_FONT_HERSHEY_SIMPLEX, 0.5, CV_RGB(255,0,0));
if(!det_parameters[0].quiet_mode)
{
cv::namedWindow("tracking_result",1);
cv::imshow("tracking_result", disp_image);
if(!depth_image.empty())
{
// Division needed for visualisation purposes
imshow("depth", depth_image/2000.0);
}
}
// output the tracked video
if(!tracked_videos_output.empty())
{
writerFace << disp_image;
}
video_capture >> captured_image;
// detect key presses
char character_press = cv::waitKey(1);
// restart the trackers
if(character_press == 'r')
{
for(size_t i=0; i < clnf_models.size(); ++i)
{
clnf_models[i].Reset();
active_models[i] = false;
}
}
// quit the application
else if(character_press=='q')
{
return(0);
}
// Update the frame count
frame_count++;
}
frame_count = 0;
// Reset the model, for the next video
for(size_t model=0; model < clnf_models.size(); ++model)
{
clnf_models[model].Reset();
active_models[model] = false;
}
// break out of the loop if done with all the files
if(f_n == files.size() -1)
{
done = true;
}
}
return 0;
}

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add_executable(FeatureExtraction FeatureExtraction.cpp)
# Local libraries
include_directories(${LandmarkDetector_SOURCE_DIR}/include)
include_directories(../../lib/local/LandmarkDetector/include)
include_directories(../../lib/local/FaceAnalyser/include)
target_link_libraries(FeatureExtraction LandmarkDetector)
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target_link_libraries(FeatureExtraction dlib)
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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
// License Agreement with respect to such Open Source Component, such restrictions will not
// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
// delivery of the Software.
// * Any publications arising from the use of this software, including but
// not limited to academic journal and conference publications, technical
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
// Record.cpp : A useful function for quick recording from a webcam for test purposes
#include <fstream>
#include <sstream>
#include <iostream>
#include <windows.h>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/videoio/videoio.hpp> // Video write
#include <opencv2/videoio/videoio_c.h> // Video write
#include <stdio.h>
#include <time.h>
#include <filesystem.hpp>
#include <filesystem/fstream.hpp>
#define INFO_STREAM( stream ) \
std::cout << stream << std::endl
#define WARN_STREAM( stream ) \
std::cout << "Warning: " << stream << std::endl
#define ERROR_STREAM( stream ) \
std::cout << "Error: " << stream << std::endl
static void printErrorAndAbort( const std::string & error )
{
std::cout << error << std::endl;
abort();
}
#define FATAL_STREAM( stream ) \
printErrorAndAbort( std::string( "Fatal error: " ) + stream )
using namespace std;
// Get current date/time, format is YYYY-MM-DD.HH:mm:ss
const std::string currentDateTime() {
time_t now = time(0);
struct tm tstruct;
char buf[80];
localtime_s(&tstruct, &now);
// Visit http://www.cplusplus.com/reference/clibrary/ctime/strftime/
// for more information about date/time format
strftime(buf, sizeof(buf), "%Y-%m-%d-%H-%M", &tstruct);
return buf;
}
vector<string> get_arguments(int argc, char **argv)
{
vector<string> arguments;
for(int i = 1; i < argc; ++i)
{
arguments.push_back(string(argv[i]));
}
return arguments;
}
int main (int argc, char **argv)
{
vector<string> arguments = get_arguments(argc, argv);
// Some initial parameters that can be overriden from command line
string outroot, outfile;
TCHAR NPath[200];
GetCurrentDirectory(200, NPath);
// By default write to same directory
outroot = NPath;
outroot = outroot + "/recording/";
outfile = currentDateTime() + ".avi";
// By default try webcam
int device = 0;
for (size_t i = 0; i < arguments.size(); i++)
{
if( strcmp( arguments[i].c_str(), "-dev") == 0 )
{
std::stringstream ss;
ss << arguments[i+1].c_str();
ss >> device;
}
else if (strcmp(arguments[i].c_str(), "-r") == 0)
{
outroot = arguments[i+1];
}
else if (strcmp(arguments[i].c_str(), "-of") == 0)
{
outroot = arguments[i+1];
}
else
{
WARN_STREAM( "invalid argument" );
}
i++;
}
// Do some grabbing
cv::VideoCapture vCap;
INFO_STREAM( "Attempting to capture from device: " << device );
vCap = cv::VideoCapture( device );
if( !vCap.isOpened() ) FATAL_STREAM( "Failed to open video source" );
cv::Mat img;
vCap >> img;
boost::filesystem::path dir(outroot);
boost::filesystem::create_directory(dir);
string out_file = outroot + outfile;
// saving the videos
cv::VideoWriter video_writer(out_file, CV_FOURCC('D','I','V','X'), 30, img.size(), true);
ofstream outlog;
outlog.open((outroot + outfile + ".log").c_str(), ios_base::out);
outlog << "frame, time(ms)" << endl;
double freq = cv::getTickFrequency();
double init_time = (double)cv::getTickCount();
int frameProc = 0;
while(!img.empty())
{
cv::namedWindow("rec",1);
vCap >> img;
double curr_time = (cv::getTickCount() - init_time) / freq;
curr_time *= 1000;
video_writer << img;
outlog << frameProc + 1 << " " << curr_time;
outlog << endl;
cv::imshow("rec", img);
frameProc++;
// detect key presses
char c = cv::waitKey(1);
// quit the application
if(c=='q')
{
outlog.close();
return(0);
}
}
return 0;
}

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<CallingConvention>Cdecl</CallingConvention>
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<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<EnableCOMDATFolding>true</EnableCOMDATFolding>
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_CV_H__
#define __OPENCV_OLD_CV_H__
#if defined(_MSC_VER)
#define CV_DO_PRAGMA(x) __pragma(x)
#define __CVSTR2__(x) #x
#define __CVSTR1__(x) __CVSTR2__(x)
#define __CVMSVCLOC__ __FILE__ "("__CVSTR1__(__LINE__)") : "
#define CV_MSG_PRAGMA(_msg) CV_DO_PRAGMA(message (__CVMSVCLOC__ _msg))
#elif defined(__GNUC__)
#define CV_DO_PRAGMA(x) _Pragma (#x)
#define CV_MSG_PRAGMA(_msg) CV_DO_PRAGMA(message (_msg))
#else
#define CV_DO_PRAGMA(x)
#define CV_MSG_PRAGMA(_msg)
#endif
#define CV_WARNING(x) CV_MSG_PRAGMA("Warning: " #x)
//CV_WARNING("This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module")
#include "opencv2/core/core_c.h"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/photo/photo_c.h"
#include "opencv2/video/tracking_c.h"
#include "opencv2/objdetect/objdetect_c.h"
#if !defined(CV_IMPL)
#define CV_IMPL extern "C"
#endif //CV_IMPL
#endif // __OPENCV_OLD_CV_H_

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_CV_HPP__
#define __OPENCV_OLD_CV_HPP__
//#if defined(__GNUC__)
//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module"
//#endif
#include "cv.h"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/photo.hpp"
#include "opencv2/video.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/objdetect.hpp"
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_AUX_H__
#define __OPENCV_OLD_AUX_H__
//#if defined(__GNUC__)
//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module"
//#endif
#include "opencv2/core/core_c.h"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/photo/photo_c.h"
#include "opencv2/video/tracking_c.h"
#include "opencv2/objdetect/objdetect_c.h"
#endif
/* End of file. */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_AUX_HPP__
#define __OPENCV_OLD_AUX_HPP__
//#if defined(__GNUC__)
//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module"
//#endif
#include "cvaux.h"
#include "opencv2/core/utility.hpp"
#endif

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///////////////////////////////////////////////////////////////////////////////
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to
// this license. If you do not agree to this license, do not download,
// install, copy or use the software.
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2008, Google, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation or contributors may not be used to endorse
// or promote products derived from this software without specific
// prior written permission.
//
// This software is provided by the copyright holders and contributors "as is"
// and any express or implied warranties, including, but not limited to, the
// implied warranties of merchantability and fitness for a particular purpose
// are disclaimed. In no event shall the Intel Corporation or contributors be
// liable for any direct, indirect, incidental, special, exemplary, or
// consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
#ifndef __OPENCV_OLD_WIMAGE_HPP__
#define __OPENCV_OLD_WIMAGE_HPP__
#include "opencv2/core/wimage.hpp"
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_CXCORE_H__
#define __OPENCV_OLD_CXCORE_H__
//#if defined(__GNUC__)
//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module"
//#endif
#include "opencv2/core/core_c.h"
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_CXCORE_HPP__
#define __OPENCV_OLD_CXCORE_HPP__
//#if defined(__GNUC__)
//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module"
//#endif
#include "cxcore.h"
#include "opencv2/core.hpp"
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_EIGEN_HPP__
#define __OPENCV_OLD_EIGEN_HPP__
#include "opencv2/core/eigen.hpp"
#endif

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#ifndef __OPENCV_OLD_CXMISC_H__
#define __OPENCV_OLD_CXMISC_H__
#ifdef __cplusplus
# include "opencv2/core/utility.hpp"
#endif
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_HIGHGUI_H__
#define __OPENCV_OLD_HIGHGUI_H__
#include "opencv2/core/core_c.h"
#include "opencv2/highgui/highgui_c.h"
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OLD_ML_H__
#define __OPENCV_OLD_ML_H__
#include "opencv2/core/core_c.h"
#include "opencv2/ml.hpp"
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifdef __OPENCV_BUILD
#error this is a compatibility header which should not be used inside the OpenCV library
#endif
#include "opencv2/calib3d.hpp"

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CALIB3D_C_H__
#define __OPENCV_CALIB3D_C_H__
#include "opencv2/core/core_c.h"
#ifdef __cplusplus
extern "C" {
#endif
/** @addtogroup calib3d_c
@{
*/
/****************************************************************************************\
* Camera Calibration, Pose Estimation and Stereo *
\****************************************************************************************/
typedef struct CvPOSITObject CvPOSITObject;
/* Allocates and initializes CvPOSITObject structure before doing cvPOSIT */
CVAPI(CvPOSITObject*) cvCreatePOSITObject( CvPoint3D32f* points, int point_count );
/* Runs POSIT (POSe from ITeration) algorithm for determining 3d position of
an object given its model and projection in a weak-perspective case */
CVAPI(void) cvPOSIT( CvPOSITObject* posit_object, CvPoint2D32f* image_points,
double focal_length, CvTermCriteria criteria,
float* rotation_matrix, float* translation_vector);
/* Releases CvPOSITObject structure */
CVAPI(void) cvReleasePOSITObject( CvPOSITObject** posit_object );
/* updates the number of RANSAC iterations */
CVAPI(int) cvRANSACUpdateNumIters( double p, double err_prob,
int model_points, int max_iters );
CVAPI(void) cvConvertPointsHomogeneous( const CvMat* src, CvMat* dst );
/* Calculates fundamental matrix given a set of corresponding points */
#define CV_FM_7POINT 1
#define CV_FM_8POINT 2
#define CV_LMEDS 4
#define CV_RANSAC 8
#define CV_FM_LMEDS_ONLY CV_LMEDS
#define CV_FM_RANSAC_ONLY CV_RANSAC
#define CV_FM_LMEDS CV_LMEDS
#define CV_FM_RANSAC CV_RANSAC
enum
{
CV_ITERATIVE = 0,
CV_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation"
CV_P3P = 2, // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem"
CV_DLS = 3 // Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP"
};
CVAPI(int) cvFindFundamentalMat( const CvMat* points1, const CvMat* points2,
CvMat* fundamental_matrix,
int method CV_DEFAULT(CV_FM_RANSAC),
double param1 CV_DEFAULT(3.), double param2 CV_DEFAULT(0.99),
CvMat* status CV_DEFAULT(NULL) );
/* For each input point on one of images
computes parameters of the corresponding
epipolar line on the other image */
CVAPI(void) cvComputeCorrespondEpilines( const CvMat* points,
int which_image,
const CvMat* fundamental_matrix,
CvMat* correspondent_lines );
/* Triangulation functions */
CVAPI(void) cvTriangulatePoints(CvMat* projMatr1, CvMat* projMatr2,
CvMat* projPoints1, CvMat* projPoints2,
CvMat* points4D);
CVAPI(void) cvCorrectMatches(CvMat* F, CvMat* points1, CvMat* points2,
CvMat* new_points1, CvMat* new_points2);
/* Computes the optimal new camera matrix according to the free scaling parameter alpha:
alpha=0 - only valid pixels will be retained in the undistorted image
alpha=1 - all the source image pixels will be retained in the undistorted image
*/
CVAPI(void) cvGetOptimalNewCameraMatrix( const CvMat* camera_matrix,
const CvMat* dist_coeffs,
CvSize image_size, double alpha,
CvMat* new_camera_matrix,
CvSize new_imag_size CV_DEFAULT(cvSize(0,0)),
CvRect* valid_pixel_ROI CV_DEFAULT(0),
int center_principal_point CV_DEFAULT(0));
/* Converts rotation vector to rotation matrix or vice versa */
CVAPI(int) cvRodrigues2( const CvMat* src, CvMat* dst,
CvMat* jacobian CV_DEFAULT(0) );
/* Finds perspective transformation between the object plane and image (view) plane */
CVAPI(int) cvFindHomography( const CvMat* src_points,
const CvMat* dst_points,
CvMat* homography,
int method CV_DEFAULT(0),
double ransacReprojThreshold CV_DEFAULT(3),
CvMat* mask CV_DEFAULT(0),
int maxIters CV_DEFAULT(2000),
double confidence CV_DEFAULT(0.995));
/* Computes RQ decomposition for 3x3 matrices */
CVAPI(void) cvRQDecomp3x3( const CvMat *matrixM, CvMat *matrixR, CvMat *matrixQ,
CvMat *matrixQx CV_DEFAULT(NULL),
CvMat *matrixQy CV_DEFAULT(NULL),
CvMat *matrixQz CV_DEFAULT(NULL),
CvPoint3D64f *eulerAngles CV_DEFAULT(NULL));
/* Computes projection matrix decomposition */
CVAPI(void) cvDecomposeProjectionMatrix( const CvMat *projMatr, CvMat *calibMatr,
CvMat *rotMatr, CvMat *posVect,
CvMat *rotMatrX CV_DEFAULT(NULL),
CvMat *rotMatrY CV_DEFAULT(NULL),
CvMat *rotMatrZ CV_DEFAULT(NULL),
CvPoint3D64f *eulerAngles CV_DEFAULT(NULL));
/* Computes d(AB)/dA and d(AB)/dB */
CVAPI(void) cvCalcMatMulDeriv( const CvMat* A, const CvMat* B, CvMat* dABdA, CvMat* dABdB );
/* Computes r3 = rodrigues(rodrigues(r2)*rodrigues(r1)),
t3 = rodrigues(r2)*t1 + t2 and the respective derivatives */
CVAPI(void) cvComposeRT( const CvMat* _rvec1, const CvMat* _tvec1,
const CvMat* _rvec2, const CvMat* _tvec2,
CvMat* _rvec3, CvMat* _tvec3,
CvMat* dr3dr1 CV_DEFAULT(0), CvMat* dr3dt1 CV_DEFAULT(0),
CvMat* dr3dr2 CV_DEFAULT(0), CvMat* dr3dt2 CV_DEFAULT(0),
CvMat* dt3dr1 CV_DEFAULT(0), CvMat* dt3dt1 CV_DEFAULT(0),
CvMat* dt3dr2 CV_DEFAULT(0), CvMat* dt3dt2 CV_DEFAULT(0) );
/* Projects object points to the view plane using
the specified extrinsic and intrinsic camera parameters */
CVAPI(void) cvProjectPoints2( const CvMat* object_points, const CvMat* rotation_vector,
const CvMat* translation_vector, const CvMat* camera_matrix,
const CvMat* distortion_coeffs, CvMat* image_points,
CvMat* dpdrot CV_DEFAULT(NULL), CvMat* dpdt CV_DEFAULT(NULL),
CvMat* dpdf CV_DEFAULT(NULL), CvMat* dpdc CV_DEFAULT(NULL),
CvMat* dpddist CV_DEFAULT(NULL),
double aspect_ratio CV_DEFAULT(0));
/* Finds extrinsic camera parameters from
a few known corresponding point pairs and intrinsic parameters */
CVAPI(void) cvFindExtrinsicCameraParams2( const CvMat* object_points,
const CvMat* image_points,
const CvMat* camera_matrix,
const CvMat* distortion_coeffs,
CvMat* rotation_vector,
CvMat* translation_vector,
int use_extrinsic_guess CV_DEFAULT(0) );
/* Computes initial estimate of the intrinsic camera parameters
in case of planar calibration target (e.g. chessboard) */
CVAPI(void) cvInitIntrinsicParams2D( const CvMat* object_points,
const CvMat* image_points,
const CvMat* npoints, CvSize image_size,
CvMat* camera_matrix,
double aspect_ratio CV_DEFAULT(1.) );
#define CV_CALIB_CB_ADAPTIVE_THRESH 1
#define CV_CALIB_CB_NORMALIZE_IMAGE 2
#define CV_CALIB_CB_FILTER_QUADS 4
#define CV_CALIB_CB_FAST_CHECK 8
// Performs a fast check if a chessboard is in the input image. This is a workaround to
// a problem of cvFindChessboardCorners being slow on images with no chessboard
// - src: input image
// - size: chessboard size
// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
// 0 if there is no chessboard, -1 in case of error
CVAPI(int) cvCheckChessboard(IplImage* src, CvSize size);
/* Detects corners on a chessboard calibration pattern */
CVAPI(int) cvFindChessboardCorners( const void* image, CvSize pattern_size,
CvPoint2D32f* corners,
int* corner_count CV_DEFAULT(NULL),
int flags CV_DEFAULT(CV_CALIB_CB_ADAPTIVE_THRESH+CV_CALIB_CB_NORMALIZE_IMAGE) );
/* Draws individual chessboard corners or the whole chessboard detected */
CVAPI(void) cvDrawChessboardCorners( CvArr* image, CvSize pattern_size,
CvPoint2D32f* corners,
int count, int pattern_was_found );
#define CV_CALIB_USE_INTRINSIC_GUESS 1
#define CV_CALIB_FIX_ASPECT_RATIO 2
#define CV_CALIB_FIX_PRINCIPAL_POINT 4
#define CV_CALIB_ZERO_TANGENT_DIST 8
#define CV_CALIB_FIX_FOCAL_LENGTH 16
#define CV_CALIB_FIX_K1 32
#define CV_CALIB_FIX_K2 64
#define CV_CALIB_FIX_K3 128
#define CV_CALIB_FIX_K4 2048
#define CV_CALIB_FIX_K5 4096
#define CV_CALIB_FIX_K6 8192
#define CV_CALIB_RATIONAL_MODEL 16384
#define CV_CALIB_THIN_PRISM_MODEL 32768
#define CV_CALIB_FIX_S1_S2_S3_S4 65536
#define CV_CALIB_TILTED_MODEL 262144
#define CV_CALIB_FIX_TAUX_TAUY 524288
/* Finds intrinsic and extrinsic camera parameters
from a few views of known calibration pattern */
CVAPI(double) cvCalibrateCamera2( const CvMat* object_points,
const CvMat* image_points,
const CvMat* point_counts,
CvSize image_size,
CvMat* camera_matrix,
CvMat* distortion_coeffs,
CvMat* rotation_vectors CV_DEFAULT(NULL),
CvMat* translation_vectors CV_DEFAULT(NULL),
int flags CV_DEFAULT(0),
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON)) );
/* Computes various useful characteristics of the camera from the data computed by
cvCalibrateCamera2 */
CVAPI(void) cvCalibrationMatrixValues( const CvMat *camera_matrix,
CvSize image_size,
double aperture_width CV_DEFAULT(0),
double aperture_height CV_DEFAULT(0),
double *fovx CV_DEFAULT(NULL),
double *fovy CV_DEFAULT(NULL),
double *focal_length CV_DEFAULT(NULL),
CvPoint2D64f *principal_point CV_DEFAULT(NULL),
double *pixel_aspect_ratio CV_DEFAULT(NULL));
#define CV_CALIB_FIX_INTRINSIC 256
#define CV_CALIB_SAME_FOCAL_LENGTH 512
/* Computes the transformation from one camera coordinate system to another one
from a few correspondent views of the same calibration target. Optionally, calibrates
both cameras */
CVAPI(double) cvStereoCalibrate( const CvMat* object_points, const CvMat* image_points1,
const CvMat* image_points2, const CvMat* npoints,
CvMat* camera_matrix1, CvMat* dist_coeffs1,
CvMat* camera_matrix2, CvMat* dist_coeffs2,
CvSize image_size, CvMat* R, CvMat* T,
CvMat* E CV_DEFAULT(0), CvMat* F CV_DEFAULT(0),
int flags CV_DEFAULT(CV_CALIB_FIX_INTRINSIC),
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,1e-6)) );
#define CV_CALIB_ZERO_DISPARITY 1024
/* Computes 3D rotations (+ optional shift) for each camera coordinate system to make both
views parallel (=> to make all the epipolar lines horizontal or vertical) */
CVAPI(void) cvStereoRectify( const CvMat* camera_matrix1, const CvMat* camera_matrix2,
const CvMat* dist_coeffs1, const CvMat* dist_coeffs2,
CvSize image_size, const CvMat* R, const CvMat* T,
CvMat* R1, CvMat* R2, CvMat* P1, CvMat* P2,
CvMat* Q CV_DEFAULT(0),
int flags CV_DEFAULT(CV_CALIB_ZERO_DISPARITY),
double alpha CV_DEFAULT(-1),
CvSize new_image_size CV_DEFAULT(cvSize(0,0)),
CvRect* valid_pix_ROI1 CV_DEFAULT(0),
CvRect* valid_pix_ROI2 CV_DEFAULT(0));
/* Computes rectification transformations for uncalibrated pair of images using a set
of point correspondences */
CVAPI(int) cvStereoRectifyUncalibrated( const CvMat* points1, const CvMat* points2,
const CvMat* F, CvSize img_size,
CvMat* H1, CvMat* H2,
double threshold CV_DEFAULT(5));
/* stereo correspondence parameters and functions */
#define CV_STEREO_BM_NORMALIZED_RESPONSE 0
#define CV_STEREO_BM_XSOBEL 1
/* Block matching algorithm structure */
typedef struct CvStereoBMState
{
// pre-filtering (normalization of input images)
int preFilterType; // =CV_STEREO_BM_NORMALIZED_RESPONSE now
int preFilterSize; // averaging window size: ~5x5..21x21
int preFilterCap; // the output of pre-filtering is clipped by [-preFilterCap,preFilterCap]
// correspondence using Sum of Absolute Difference (SAD)
int SADWindowSize; // ~5x5..21x21
int minDisparity; // minimum disparity (can be negative)
int numberOfDisparities; // maximum disparity - minimum disparity (> 0)
// post-filtering
int textureThreshold; // the disparity is only computed for pixels
// with textured enough neighborhood
int uniquenessRatio; // accept the computed disparity d* only if
// SAD(d) >= SAD(d*)*(1 + uniquenessRatio/100.)
// for any d != d*+/-1 within the search range.
int speckleWindowSize; // disparity variation window
int speckleRange; // acceptable range of variation in window
int trySmallerWindows; // if 1, the results may be more accurate,
// at the expense of slower processing
CvRect roi1, roi2;
int disp12MaxDiff;
// temporary buffers
CvMat* preFilteredImg0;
CvMat* preFilteredImg1;
CvMat* slidingSumBuf;
CvMat* cost;
CvMat* disp;
} CvStereoBMState;
#define CV_STEREO_BM_BASIC 0
#define CV_STEREO_BM_FISH_EYE 1
#define CV_STEREO_BM_NARROW 2
CVAPI(CvStereoBMState*) cvCreateStereoBMState(int preset CV_DEFAULT(CV_STEREO_BM_BASIC),
int numberOfDisparities CV_DEFAULT(0));
CVAPI(void) cvReleaseStereoBMState( CvStereoBMState** state );
CVAPI(void) cvFindStereoCorrespondenceBM( const CvArr* left, const CvArr* right,
CvArr* disparity, CvStereoBMState* state );
CVAPI(CvRect) cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity,
int numberOfDisparities, int SADWindowSize );
CVAPI(void) cvValidateDisparity( CvArr* disparity, const CvArr* cost,
int minDisparity, int numberOfDisparities,
int disp12MaxDiff CV_DEFAULT(1) );
/* Reprojects the computed disparity image to the 3D space using the specified 4x4 matrix */
CVAPI(void) cvReprojectImageTo3D( const CvArr* disparityImage,
CvArr* _3dImage, const CvMat* Q,
int handleMissingValues CV_DEFAULT(0) );
/** @} calib3d_c */
#ifdef __cplusplus
} // extern "C"
//////////////////////////////////////////////////////////////////////////////////////////
class CV_EXPORTS CvLevMarq
{
public:
CvLevMarq();
CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria=
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
bool completeSymmFlag=false );
~CvLevMarq();
void init( int nparams, int nerrs, CvTermCriteria criteria=
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
bool completeSymmFlag=false );
bool update( const CvMat*& param, CvMat*& J, CvMat*& err );
bool updateAlt( const CvMat*& param, CvMat*& JtJ, CvMat*& JtErr, double*& errNorm );
void clear();
void step();
enum { DONE=0, STARTED=1, CALC_J=2, CHECK_ERR=3 };
cv::Ptr<CvMat> mask;
cv::Ptr<CvMat> prevParam;
cv::Ptr<CvMat> param;
cv::Ptr<CvMat> J;
cv::Ptr<CvMat> err;
cv::Ptr<CvMat> JtJ;
cv::Ptr<CvMat> JtJN;
cv::Ptr<CvMat> JtErr;
cv::Ptr<CvMat> JtJV;
cv::Ptr<CvMat> JtJW;
double prevErrNorm, errNorm;
int lambdaLg10;
CvTermCriteria criteria;
int state;
int iters;
bool completeSymmFlag;
int solveMethod;
};
#endif
#endif /* __OPENCV_CALIB3D_C_H__ */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_AFFINE3_HPP__
#define __OPENCV_CORE_AFFINE3_HPP__
#ifdef __cplusplus
#include <opencv2/core.hpp>
namespace cv
{
//! @addtogroup core
//! @{
/** @brief Affine transform
@todo document
*/
template<typename T>
class Affine3
{
public:
typedef T float_type;
typedef Matx<float_type, 3, 3> Mat3;
typedef Matx<float_type, 4, 4> Mat4;
typedef Vec<float_type, 3> Vec3;
Affine3();
//! Augmented affine matrix
Affine3(const Mat4& affine);
//! Rotation matrix
Affine3(const Mat3& R, const Vec3& t = Vec3::all(0));
//! Rodrigues vector
Affine3(const Vec3& rvec, const Vec3& t = Vec3::all(0));
//! Combines all contructors above. Supports 4x4, 4x3, 3x3, 1x3, 3x1 sizes of data matrix
explicit Affine3(const Mat& data, const Vec3& t = Vec3::all(0));
//! From 16th element array
explicit Affine3(const float_type* vals);
//! Create identity transform
static Affine3 Identity();
//! Rotation matrix
void rotation(const Mat3& R);
//! Rodrigues vector
void rotation(const Vec3& rvec);
//! Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix;
void rotation(const Mat& data);
void linear(const Mat3& L);
void translation(const Vec3& t);
Mat3 rotation() const;
Mat3 linear() const;
Vec3 translation() const;
//! Rodrigues vector
Vec3 rvec() const;
Affine3 inv(int method = cv::DECOMP_SVD) const;
//! a.rotate(R) is equivalent to Affine(R, 0) * a;
Affine3 rotate(const Mat3& R) const;
//! a.rotate(rvec) is equivalent to Affine(rvec, 0) * a;
Affine3 rotate(const Vec3& rvec) const;
//! a.translate(t) is equivalent to Affine(E, t) * a;
Affine3 translate(const Vec3& t) const;
//! a.concatenate(affine) is equivalent to affine * a;
Affine3 concatenate(const Affine3& affine) const;
template <typename Y> operator Affine3<Y>() const;
template <typename Y> Affine3<Y> cast() const;
Mat4 matrix;
#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H
Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine);
Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine);
operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const;
operator Eigen::Transform<T, 3, Eigen::Affine>() const;
#endif
};
template<typename T> static
Affine3<T> operator*(const Affine3<T>& affine1, const Affine3<T>& affine2);
template<typename T, typename V> static
V operator*(const Affine3<T>& affine, const V& vector);
typedef Affine3<float> Affine3f;
typedef Affine3<double> Affine3d;
static Vec3f operator*(const Affine3f& affine, const Vec3f& vector);
static Vec3d operator*(const Affine3d& affine, const Vec3d& vector);
template<typename _Tp> class DataType< Affine3<_Tp> >
{
public:
typedef Affine3<_Tp> value_type;
typedef Affine3<typename DataType<_Tp>::work_type> work_type;
typedef _Tp channel_type;
enum { generic_type = 0,
depth = DataType<channel_type>::depth,
channels = 16,
fmt = DataType<channel_type>::fmt + ((channels - 1) << 8),
type = CV_MAKETYPE(depth, channels)
};
typedef Vec<channel_type, channels> vec_type;
};
//! @} core
}
//! @cond IGNORED
///////////////////////////////////////////////////////////////////////////////////
// Implementaiton
template<typename T> inline
cv::Affine3<T>::Affine3()
: matrix(Mat4::eye())
{}
template<typename T> inline
cv::Affine3<T>::Affine3(const Mat4& affine)
: matrix(affine)
{}
template<typename T> inline
cv::Affine3<T>::Affine3(const Mat3& R, const Vec3& t)
{
rotation(R);
translation(t);
matrix.val[12] = matrix.val[13] = matrix.val[14] = 0;
matrix.val[15] = 1;
}
template<typename T> inline
cv::Affine3<T>::Affine3(const Vec3& _rvec, const Vec3& t)
{
rotation(_rvec);
translation(t);
matrix.val[12] = matrix.val[13] = matrix.val[14] = 0;
matrix.val[15] = 1;
}
template<typename T> inline
cv::Affine3<T>::Affine3(const cv::Mat& data, const Vec3& t)
{
CV_Assert(data.type() == cv::DataType<T>::type);
if (data.cols == 4 && data.rows == 4)
{
data.copyTo(matrix);
return;
}
else if (data.cols == 4 && data.rows == 3)
{
rotation(data(Rect(0, 0, 3, 3)));
translation(data(Rect(3, 0, 1, 3)));
return;
}
rotation(data);
translation(t);
matrix.val[12] = matrix.val[13] = matrix.val[14] = 0;
matrix.val[15] = 1;
}
template<typename T> inline
cv::Affine3<T>::Affine3(const float_type* vals) : matrix(vals)
{}
template<typename T> inline
cv::Affine3<T> cv::Affine3<T>::Identity()
{
return Affine3<T>(cv::Affine3<T>::Mat4::eye());
}
template<typename T> inline
void cv::Affine3<T>::rotation(const Mat3& R)
{
linear(R);
}
template<typename T> inline
void cv::Affine3<T>::rotation(const Vec3& _rvec)
{
double rx = _rvec[0], ry = _rvec[1], rz = _rvec[2];
double theta = std::sqrt(rx*rx + ry*ry + rz*rz);
if (theta < DBL_EPSILON)
rotation(Mat3::eye());
else
{
const double I[] = { 1, 0, 0, 0, 1, 0, 0, 0, 1 };
double c = std::cos(theta);
double s = std::sin(theta);
double c1 = 1. - c;
double itheta = (theta != 0) ? 1./theta : 0.;
rx *= itheta; ry *= itheta; rz *= itheta;
double rrt[] = { rx*rx, rx*ry, rx*rz, rx*ry, ry*ry, ry*rz, rx*rz, ry*rz, rz*rz };
double _r_x_[] = { 0, -rz, ry, rz, 0, -rx, -ry, rx, 0 };
Mat3 R;
// R = cos(theta)*I + (1 - cos(theta))*r*rT + sin(theta)*[r_x]
// where [r_x] is [0 -rz ry; rz 0 -rx; -ry rx 0]
for(int k = 0; k < 9; ++k)
R.val[k] = static_cast<float_type>(c*I[k] + c1*rrt[k] + s*_r_x_[k]);
rotation(R);
}
}
//Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix;
template<typename T> inline
void cv::Affine3<T>::rotation(const cv::Mat& data)
{
CV_Assert(data.type() == cv::DataType<T>::type);
if (data.cols == 3 && data.rows == 3)
{
Mat3 R;
data.copyTo(R);
rotation(R);
}
else if ((data.cols == 3 && data.rows == 1) || (data.cols == 1 && data.rows == 3))
{
Vec3 _rvec;
data.reshape(1, 3).copyTo(_rvec);
rotation(_rvec);
}
else
CV_Assert(!"Input marix can be 3x3, 1x3 or 3x1");
}
template<typename T> inline
void cv::Affine3<T>::linear(const Mat3& L)
{
matrix.val[0] = L.val[0]; matrix.val[1] = L.val[1]; matrix.val[ 2] = L.val[2];
matrix.val[4] = L.val[3]; matrix.val[5] = L.val[4]; matrix.val[ 6] = L.val[5];
matrix.val[8] = L.val[6]; matrix.val[9] = L.val[7]; matrix.val[10] = L.val[8];
}
template<typename T> inline
void cv::Affine3<T>::translation(const Vec3& t)
{
matrix.val[3] = t[0]; matrix.val[7] = t[1]; matrix.val[11] = t[2];
}
template<typename T> inline
typename cv::Affine3<T>::Mat3 cv::Affine3<T>::rotation() const
{
return linear();
}
template<typename T> inline
typename cv::Affine3<T>::Mat3 cv::Affine3<T>::linear() const
{
typename cv::Affine3<T>::Mat3 R;
R.val[0] = matrix.val[0]; R.val[1] = matrix.val[1]; R.val[2] = matrix.val[ 2];
R.val[3] = matrix.val[4]; R.val[4] = matrix.val[5]; R.val[5] = matrix.val[ 6];
R.val[6] = matrix.val[8]; R.val[7] = matrix.val[9]; R.val[8] = matrix.val[10];
return R;
}
template<typename T> inline
typename cv::Affine3<T>::Vec3 cv::Affine3<T>::translation() const
{
return Vec3(matrix.val[3], matrix.val[7], matrix.val[11]);
}
template<typename T> inline
typename cv::Affine3<T>::Vec3 cv::Affine3<T>::rvec() const
{
cv::Vec3d w;
cv::Matx33d u, vt, R = rotation();
cv::SVD::compute(R, w, u, vt, cv::SVD::FULL_UV + cv::SVD::MODIFY_A);
R = u * vt;
double rx = R.val[7] - R.val[5];
double ry = R.val[2] - R.val[6];
double rz = R.val[3] - R.val[1];
double s = std::sqrt((rx*rx + ry*ry + rz*rz)*0.25);
double c = (R.val[0] + R.val[4] + R.val[8] - 1) * 0.5;
c = c > 1.0 ? 1.0 : c < -1.0 ? -1.0 : c;
double theta = acos(c);
if( s < 1e-5 )
{
if( c > 0 )
rx = ry = rz = 0;
else
{
double t;
t = (R.val[0] + 1) * 0.5;
rx = std::sqrt(std::max(t, 0.0));
t = (R.val[4] + 1) * 0.5;
ry = std::sqrt(std::max(t, 0.0)) * (R.val[1] < 0 ? -1.0 : 1.0);
t = (R.val[8] + 1) * 0.5;
rz = std::sqrt(std::max(t, 0.0)) * (R.val[2] < 0 ? -1.0 : 1.0);
if( fabs(rx) < fabs(ry) && fabs(rx) < fabs(rz) && (R.val[5] > 0) != (ry*rz > 0) )
rz = -rz;
theta /= std::sqrt(rx*rx + ry*ry + rz*rz);
rx *= theta;
ry *= theta;
rz *= theta;
}
}
else
{
double vth = 1/(2*s);
vth *= theta;
rx *= vth; ry *= vth; rz *= vth;
}
return cv::Vec3d(rx, ry, rz);
}
template<typename T> inline
cv::Affine3<T> cv::Affine3<T>::inv(int method) const
{
return matrix.inv(method);
}
template<typename T> inline
cv::Affine3<T> cv::Affine3<T>::rotate(const Mat3& R) const
{
Mat3 Lc = linear();
Vec3 tc = translation();
Mat4 result;
result.val[12] = result.val[13] = result.val[14] = 0;
result.val[15] = 1;
for(int j = 0; j < 3; ++j)
{
for(int i = 0; i < 3; ++i)
{
float_type value = 0;
for(int k = 0; k < 3; ++k)
value += R(j, k) * Lc(k, i);
result(j, i) = value;
}
result(j, 3) = R.row(j).dot(tc.t());
}
return result;
}
template<typename T> inline
cv::Affine3<T> cv::Affine3<T>::rotate(const Vec3& _rvec) const
{
return rotate(Affine3f(_rvec).rotation());
}
template<typename T> inline
cv::Affine3<T> cv::Affine3<T>::translate(const Vec3& t) const
{
Mat4 m = matrix;
m.val[ 3] += t[0];
m.val[ 7] += t[1];
m.val[11] += t[2];
return m;
}
template<typename T> inline
cv::Affine3<T> cv::Affine3<T>::concatenate(const Affine3<T>& affine) const
{
return (*this).rotate(affine.rotation()).translate(affine.translation());
}
template<typename T> template <typename Y> inline
cv::Affine3<T>::operator Affine3<Y>() const
{
return Affine3<Y>(matrix);
}
template<typename T> template <typename Y> inline
cv::Affine3<Y> cv::Affine3<T>::cast() const
{
return Affine3<Y>(matrix);
}
template<typename T> inline
cv::Affine3<T> cv::operator*(const cv::Affine3<T>& affine1, const cv::Affine3<T>& affine2)
{
return affine2.concatenate(affine1);
}
template<typename T, typename V> inline
V cv::operator*(const cv::Affine3<T>& affine, const V& v)
{
const typename Affine3<T>::Mat4& m = affine.matrix;
V r;
r.x = m.val[0] * v.x + m.val[1] * v.y + m.val[ 2] * v.z + m.val[ 3];
r.y = m.val[4] * v.x + m.val[5] * v.y + m.val[ 6] * v.z + m.val[ 7];
r.z = m.val[8] * v.x + m.val[9] * v.y + m.val[10] * v.z + m.val[11];
return r;
}
static inline
cv::Vec3f cv::operator*(const cv::Affine3f& affine, const cv::Vec3f& v)
{
const cv::Matx44f& m = affine.matrix;
cv::Vec3f r;
r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3];
r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7];
r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11];
return r;
}
static inline
cv::Vec3d cv::operator*(const cv::Affine3d& affine, const cv::Vec3d& v)
{
const cv::Matx44d& m = affine.matrix;
cv::Vec3d r;
r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3];
r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7];
r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11];
return r;
}
#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H
template<typename T> inline
cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine)
{
cv::Mat(4, 4, cv::DataType<T>::type, affine.matrix().data()).copyTo(matrix);
}
template<typename T> inline
cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine)
{
Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> a = affine;
cv::Mat(4, 4, cv::DataType<T>::type, a.matrix().data()).copyTo(matrix);
}
template<typename T> inline
cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const
{
Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> r;
cv::Mat hdr(4, 4, cv::DataType<T>::type, r.matrix().data());
cv::Mat(matrix, false).copyTo(hdr);
return r;
}
template<typename T> inline
cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine>() const
{
return this->operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>();
}
#endif /* defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H */
//! @endcond
#endif /* __cplusplus */
#endif /* __OPENCV_CORE_AFFINE3_HPP__ */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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#ifndef __OPENCV_CORE_BASE_HPP__
#define __OPENCV_CORE_BASE_HPP__
#ifndef __cplusplus
# error base.hpp header must be compiled as C++
#endif
#include <climits>
#include <algorithm>
#include "opencv2/core/cvdef.h"
#include "opencv2/core/cvstd.hpp"
namespace cv
{
//! @addtogroup core_utils
//! @{
namespace Error {
//! error codes
enum Code {
StsOk= 0, //!< everithing is ok
StsBackTrace= -1, //!< pseudo error for back trace
StsError= -2, //!< unknown /unspecified error
StsInternal= -3, //!< internal error (bad state)
StsNoMem= -4, //!< insufficient memory
StsBadArg= -5, //!< function arg/param is bad
StsBadFunc= -6, //!< unsupported function
StsNoConv= -7, //!< iter. didn't converge
StsAutoTrace= -8, //!< tracing
HeaderIsNull= -9, //!< image header is NULL
BadImageSize= -10, //!< image size is invalid
BadOffset= -11, //!< offset is invalid
BadDataPtr= -12, //!<
BadStep= -13, //!<
BadModelOrChSeq= -14, //!<
BadNumChannels= -15, //!<
BadNumChannel1U= -16, //!<
BadDepth= -17, //!<
BadAlphaChannel= -18, //!<
BadOrder= -19, //!<
BadOrigin= -20, //!<
BadAlign= -21, //!<
BadCallBack= -22, //!<
BadTileSize= -23, //!<
BadCOI= -24, //!<
BadROISize= -25, //!<
MaskIsTiled= -26, //!<
StsNullPtr= -27, //!< null pointer
StsVecLengthErr= -28, //!< incorrect vector length
StsFilterStructContentErr= -29, //!< incorr. filter structure content
StsKernelStructContentErr= -30, //!< incorr. transform kernel content
StsFilterOffsetErr= -31, //!< incorrect filter ofset value
StsBadSize= -201, //!< the input/output structure size is incorrect
StsDivByZero= -202, //!< division by zero
StsInplaceNotSupported= -203, //!< in-place operation is not supported
StsObjectNotFound= -204, //!< request can't be completed
StsUnmatchedFormats= -205, //!< formats of input/output arrays differ
StsBadFlag= -206, //!< flag is wrong or not supported
StsBadPoint= -207, //!< bad CvPoint
StsBadMask= -208, //!< bad format of mask (neither 8uC1 nor 8sC1)
StsUnmatchedSizes= -209, //!< sizes of input/output structures do not match
StsUnsupportedFormat= -210, //!< the data format/type is not supported by the function
StsOutOfRange= -211, //!< some of parameters are out of range
StsParseError= -212, //!< invalid syntax/structure of the parsed file
StsNotImplemented= -213, //!< the requested function/feature is not implemented
StsBadMemBlock= -214, //!< an allocated block has been corrupted
StsAssert= -215, //!< assertion failed
GpuNotSupported= -216,
GpuApiCallError= -217,
OpenGlNotSupported= -218,
OpenGlApiCallError= -219,
OpenCLApiCallError= -220,
OpenCLDoubleNotSupported= -221,
OpenCLInitError= -222,
OpenCLNoAMDBlasFft= -223
};
} //Error
//! @} core_utils
//! @addtogroup core_array
//! @{
//! matrix decomposition types
enum DecompTypes {
/** Gaussian elimination with the optimal pivot element chosen. */
DECOMP_LU = 0,
/** singular value decomposition (SVD) method; the system can be over-defined and/or the matrix
src1 can be singular */
DECOMP_SVD = 1,
/** eigenvalue decomposition; the matrix src1 must be symmetrical */
DECOMP_EIG = 2,
/** Cholesky \f$LL^T\f$ factorization; the matrix src1 must be symmetrical and positively
defined */
DECOMP_CHOLESKY = 3,
/** QR factorization; the system can be over-defined and/or the matrix src1 can be singular */
DECOMP_QR = 4,
/** while all the previous flags are mutually exclusive, this flag can be used together with
any of the previous; it means that the normal equations
\f$\texttt{src1}^T\cdot\texttt{src1}\cdot\texttt{dst}=\texttt{src1}^T\texttt{src2}\f$ are
solved instead of the original system
\f$\texttt{src1}\cdot\texttt{dst}=\texttt{src2}\f$ */
DECOMP_NORMAL = 16
};
/** norm types
- For one array:
\f[norm = \forkthree{\|\texttt{src1}\|_{L_{\infty}} = \max _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) }
{ \| \texttt{src1} \| _{L_1} = \sum _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) }
{ \| \texttt{src1} \| _{L_2} = \sqrt{\sum_I \texttt{src1}(I)^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) }\f]
- Absolute norm for two arrays
\f[norm = \forkthree{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} = \max _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) }
{ \| \texttt{src1} - \texttt{src2} \| _{L_1} = \sum _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) }
{ \| \texttt{src1} - \texttt{src2} \| _{L_2} = \sqrt{\sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) }\f]
- Relative norm for two arrays
\f[norm = \forkthree{\frac{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} }{\|\texttt{src2}\|_{L_{\infty}} }}{if \(\texttt{normType} = \texttt{NORM_RELATIVE_INF}\) }
{ \frac{\|\texttt{src1}-\texttt{src2}\|_{L_1} }{\|\texttt{src2}\|_{L_1}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE_L1}\) }
{ \frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE_L2}\) }\f]
As example for one array consider the function \f$r(x)= \begin{pmatrix} x \\ 1-x \end{pmatrix}, x \in [-1;1]\f$.
The \f$ L_{1}, L_{2} \f$ and \f$ L_{\infty} \f$ norm for the sample value \f$r(-1) = \begin{pmatrix} -1 \\ 2 \end{pmatrix}\f$
is calculated as follows
\f{align*}
\| r(-1) \|_{L_1} &= |-1| + |2| = 3 \\
\| r(-1) \|_{L_2} &= \sqrt{(-1)^{2} + (2)^{2}} = \sqrt{5} \\
\| r(-1) \|_{L_\infty} &= \max(|-1|,|2|) = 2
\f}
and for \f$r(0.5) = \begin{pmatrix} 0.5 \\ 0.5 \end{pmatrix}\f$ the calculation is
\f{align*}
\| r(0.5) \|_{L_1} &= |0.5| + |0.5| = 1 \\
\| r(0.5) \|_{L_2} &= \sqrt{(0.5)^{2} + (0.5)^{2}} = \sqrt{0.5} \\
\| r(0.5) \|_{L_\infty} &= \max(|0.5|,|0.5|) = 0.5.
\f}
The following graphic shows all values for the three norm functions \f$\| r(x) \|_{L_1}, \| r(x) \|_{L_2}\f$ and \f$\| r(x) \|_{L_\infty}\f$.
It is notable that the \f$ L_{1} \f$ norm forms the upper and the \f$ L_{\infty} \f$ norm forms the lower border for the example function \f$ r(x) \f$.
![Graphs for the different norm functions from the above example](pics/NormTypes_OneArray_1-2-INF.png)
*/
enum NormTypes { NORM_INF = 1,
NORM_L1 = 2,
NORM_L2 = 4,
NORM_L2SQR = 5,
NORM_HAMMING = 6,
NORM_HAMMING2 = 7,
NORM_TYPE_MASK = 7,
NORM_RELATIVE = 8, //!< flag
NORM_MINMAX = 32 //!< flag
};
//! comparison types
enum CmpTypes { CMP_EQ = 0, //!< src1 is equal to src2.
CMP_GT = 1, //!< src1 is greater than src2.
CMP_GE = 2, //!< src1 is greater than or equal to src2.
CMP_LT = 3, //!< src1 is less than src2.
CMP_LE = 4, //!< src1 is less than or equal to src2.
CMP_NE = 5 //!< src1 is unequal to src2.
};
//! generalized matrix multiplication flags
enum GemmFlags { GEMM_1_T = 1, //!< transposes src1
GEMM_2_T = 2, //!< transposes src2
GEMM_3_T = 4 //!< transposes src3
};
enum DftFlags {
/** performs an inverse 1D or 2D transform instead of the default forward
transform. */
DFT_INVERSE = 1,
/** scales the result: divide it by the number of array elements. Normally, it is
combined with DFT_INVERSE. */
DFT_SCALE = 2,
/** performs a forward or inverse transform of every individual row of the input
matrix; this flag enables you to transform multiple vectors simultaneously and can be used to
decrease the overhead (which is sometimes several times larger than the processing itself) to
perform 3D and higher-dimensional transformations and so forth.*/
DFT_ROWS = 4,
/** performs a forward transformation of 1D or 2D real array; the result,
though being a complex array, has complex-conjugate symmetry (*CCS*, see the function
description below for details), and such an array can be packed into a real array of the same
size as input, which is the fastest option and which is what the function does by default;
however, you may wish to get a full complex array (for simpler spectrum analysis, and so on) -
pass the flag to enable the function to produce a full-size complex output array. */
DFT_COMPLEX_OUTPUT = 16,
/** performs an inverse transformation of a 1D or 2D complex array; the
result is normally a complex array of the same size, however, if the input array has
conjugate-complex symmetry (for example, it is a result of forward transformation with
DFT_COMPLEX_OUTPUT flag), the output is a real array; while the function itself does not
check whether the input is symmetrical or not, you can pass the flag and then the function
will assume the symmetry and produce the real output array (note that when the input is packed
into a real array and inverse transformation is executed, the function treats the input as a
packed complex-conjugate symmetrical array, and the output will also be a real array). */
DFT_REAL_OUTPUT = 32,
/** performs an inverse 1D or 2D transform instead of the default forward transform. */
DCT_INVERSE = DFT_INVERSE,
/** performs a forward or inverse transform of every individual row of the input
matrix. This flag enables you to transform multiple vectors simultaneously and can be used to
decrease the overhead (which is sometimes several times larger than the processing itself) to
perform 3D and higher-dimensional transforms and so forth.*/
DCT_ROWS = DFT_ROWS
};
//! Various border types, image boundaries are denoted with `|`
//! @see borderInterpolate, copyMakeBorder
enum BorderTypes {
BORDER_CONSTANT = 0, //!< `iiiiii|abcdefgh|iiiiiii` with some specified `i`
BORDER_REPLICATE = 1, //!< `aaaaaa|abcdefgh|hhhhhhh`
BORDER_REFLECT = 2, //!< `fedcba|abcdefgh|hgfedcb`
BORDER_WRAP = 3, //!< `cdefgh|abcdefgh|abcdefg`
BORDER_REFLECT_101 = 4, //!< `gfedcb|abcdefgh|gfedcba`
BORDER_TRANSPARENT = 5, //!< `uvwxyz|absdefgh|ijklmno`
BORDER_REFLECT101 = BORDER_REFLECT_101, //!< same as BORDER_REFLECT_101
BORDER_DEFAULT = BORDER_REFLECT_101, //!< same as BORDER_REFLECT_101
BORDER_ISOLATED = 16 //!< do not look outside of ROI
};
//! @} core_array
//! @addtogroup core_utils
//! @{
//! @cond IGNORED
//////////////// static assert /////////////////
#define CVAUX_CONCAT_EXP(a, b) a##b
#define CVAUX_CONCAT(a, b) CVAUX_CONCAT_EXP(a,b)
#if defined(__clang__)
# ifndef __has_extension
# define __has_extension __has_feature /* compatibility, for older versions of clang */
# endif
# if __has_extension(cxx_static_assert)
# define CV_StaticAssert(condition, reason) static_assert((condition), reason " " #condition)
# elif __has_extension(c_static_assert)
# define CV_StaticAssert(condition, reason) _Static_assert((condition), reason " " #condition)
# endif
#elif defined(__GNUC__)
# if (defined(__GXX_EXPERIMENTAL_CXX0X__) || __cplusplus >= 201103L)
# define CV_StaticAssert(condition, reason) static_assert((condition), reason " " #condition)
# endif
#elif defined(_MSC_VER)
# if _MSC_VER >= 1600 /* MSVC 10 */
# define CV_StaticAssert(condition, reason) static_assert((condition), reason " " #condition)
# endif
#endif
#ifndef CV_StaticAssert
# if !defined(__clang__) && defined(__GNUC__) && (__GNUC__*100 + __GNUC_MINOR__ > 302)
# define CV_StaticAssert(condition, reason) ({ extern int __attribute__((error("CV_StaticAssert: " reason " " #condition))) CV_StaticAssert(); ((condition) ? 0 : CV_StaticAssert()); })
# else
template <bool x> struct CV_StaticAssert_failed;
template <> struct CV_StaticAssert_failed<true> { enum { val = 1 }; };
template<int x> struct CV_StaticAssert_test {};
# define CV_StaticAssert(condition, reason)\
typedef cv::CV_StaticAssert_test< sizeof(cv::CV_StaticAssert_failed< static_cast<bool>(condition) >) > CVAUX_CONCAT(CV_StaticAssert_failed_at_, __LINE__)
# endif
#endif
// Suppress warning "-Wdeprecated-declarations" / C4996
#if defined(_MSC_VER)
#define CV_DO_PRAGMA(x) __pragma(x)
#elif defined(__GNUC__)
#define CV_DO_PRAGMA(x) _Pragma (#x)
#else
#define CV_DO_PRAGMA(x)
#endif
#ifdef _MSC_VER
#define CV_SUPPRESS_DEPRECATED_START \
CV_DO_PRAGMA(warning(push)) \
CV_DO_PRAGMA(warning(disable: 4996))
#define CV_SUPPRESS_DEPRECATED_END CV_DO_PRAGMA(warning(pop))
#elif defined (__clang__) || ((__GNUC__) && (__GNUC__*100 + __GNUC_MINOR__ > 405))
#define CV_SUPPRESS_DEPRECATED_START \
CV_DO_PRAGMA(GCC diagnostic push) \
CV_DO_PRAGMA(GCC diagnostic ignored "-Wdeprecated-declarations")
#define CV_SUPPRESS_DEPRECATED_END CV_DO_PRAGMA(GCC diagnostic pop)
#else
#define CV_SUPPRESS_DEPRECATED_START
#define CV_SUPPRESS_DEPRECATED_END
#endif
#define CV_UNUSED(name) (void)name
//! @endcond
/*! @brief Signals an error and raises the exception.
By default the function prints information about the error to stderr,
then it either stops if setBreakOnError() had been called before or raises the exception.
It is possible to alternate error processing by using redirectError().
@param _code - error code (Error::Code)
@param _err - error description
@param _func - function name. Available only when the compiler supports getting it
@param _file - source file name where the error has occured
@param _line - line number in the source file where the error has occured
@see CV_Error, CV_Error_, CV_ErrorNoReturn, CV_ErrorNoReturn_, CV_Assert, CV_DbgAssert
*/
CV_EXPORTS void error(int _code, const String& _err, const char* _func, const char* _file, int _line);
#ifdef __GNUC__
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Winvalid-noreturn"
# endif
#endif
/** same as cv::error, but does not return */
CV_INLINE CV_NORETURN void errorNoReturn(int _code, const String& _err, const char* _func, const char* _file, int _line)
{
error(_code, _err, _func, _file, _line);
#ifdef __GNUC__
# if !defined __clang__ && !defined __APPLE__
// this suppresses this warning: "noreturn" function does return [enabled by default]
__builtin_trap();
// or use infinite loop: for (;;) {}
# endif
#endif
}
#ifdef __GNUC__
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic pop
# endif
#endif
#if defined __GNUC__
#define CV_Func __func__
#elif defined _MSC_VER
#define CV_Func __FUNCTION__
#else
#define CV_Func ""
#endif
/** @brief Call the error handler.
Currently, the error handler prints the error code and the error message to the standard
error stream `stderr`. In the Debug configuration, it then provokes memory access violation, so that
the execution stack and all the parameters can be analyzed by the debugger. In the Release
configuration, the exception is thrown.
@param code one of Error::Code
@param msg error message
*/
#define CV_Error( code, msg ) cv::error( code, msg, CV_Func, __FILE__, __LINE__ )
/** @brief Call the error handler.
This macro can be used to construct an error message on-fly to include some dynamic information,
for example:
@code
// note the extra parentheses around the formatted text message
CV_Error_( CV_StsOutOfRange,
("the value at (%d, %d)=%g is out of range", badPt.x, badPt.y, badValue));
@endcode
@param code one of Error::Code
@param args printf-like formatted error message in parentheses
*/
#define CV_Error_( code, args ) cv::error( code, cv::format args, CV_Func, __FILE__, __LINE__ )
/** @brief Checks a condition at runtime and throws exception if it fails
The macros CV_Assert (and CV_DbgAssert(expr)) evaluate the specified expression. If it is 0, the macros
raise an error (see cv::error). The macro CV_Assert checks the condition in both Debug and Release
configurations while CV_DbgAssert is only retained in the Debug configuration.
*/
#define CV_Assert( expr ) if(!!(expr)) ; else cv::error( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ )
/** same as CV_Error(code,msg), but does not return */
#define CV_ErrorNoReturn( code, msg ) cv::errorNoReturn( code, msg, CV_Func, __FILE__, __LINE__ )
/** same as CV_Error_(code,args), but does not return */
#define CV_ErrorNoReturn_( code, args ) cv::errorNoReturn( code, cv::format args, CV_Func, __FILE__, __LINE__ )
/** replaced with CV_Assert(expr) in Debug configuration */
#ifdef _DEBUG
# define CV_DbgAssert(expr) CV_Assert(expr)
#else
# define CV_DbgAssert(expr)
#endif
/*
* Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor
* bit count of A exclusive XOR'ed with B
*/
struct CV_EXPORTS Hamming
{
enum { normType = NORM_HAMMING };
typedef unsigned char ValueType;
typedef int ResultType;
/** this will count the bits in a ^ b
*/
ResultType operator()( const unsigned char* a, const unsigned char* b, int size ) const;
};
typedef Hamming HammingLUT;
/////////////////////////////////// inline norms ////////////////////////////////////
template<typename _Tp> inline _Tp cv_abs(_Tp x) { return std::abs(x); }
inline int cv_abs(uchar x) { return x; }
inline int cv_abs(schar x) { return std::abs(x); }
inline int cv_abs(ushort x) { return x; }
inline int cv_abs(short x) { return std::abs(x); }
template<typename _Tp, typename _AccTp> static inline
_AccTp normL2Sqr(const _Tp* a, int n)
{
_AccTp s = 0;
int i=0;
#if CV_ENABLE_UNROLLED
for( ; i <= n - 4; i += 4 )
{
_AccTp v0 = a[i], v1 = a[i+1], v2 = a[i+2], v3 = a[i+3];
s += v0*v0 + v1*v1 + v2*v2 + v3*v3;
}
#endif
for( ; i < n; i++ )
{
_AccTp v = a[i];
s += v*v;
}
return s;
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normL1(const _Tp* a, int n)
{
_AccTp s = 0;
int i = 0;
#if CV_ENABLE_UNROLLED
for(; i <= n - 4; i += 4 )
{
s += (_AccTp)cv_abs(a[i]) + (_AccTp)cv_abs(a[i+1]) +
(_AccTp)cv_abs(a[i+2]) + (_AccTp)cv_abs(a[i+3]);
}
#endif
for( ; i < n; i++ )
s += cv_abs(a[i]);
return s;
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normInf(const _Tp* a, int n)
{
_AccTp s = 0;
for( int i = 0; i < n; i++ )
s = std::max(s, (_AccTp)cv_abs(a[i]));
return s;
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normL2Sqr(const _Tp* a, const _Tp* b, int n)
{
_AccTp s = 0;
int i= 0;
#if CV_ENABLE_UNROLLED
for(; i <= n - 4; i += 4 )
{
_AccTp v0 = _AccTp(a[i] - b[i]), v1 = _AccTp(a[i+1] - b[i+1]), v2 = _AccTp(a[i+2] - b[i+2]), v3 = _AccTp(a[i+3] - b[i+3]);
s += v0*v0 + v1*v1 + v2*v2 + v3*v3;
}
#endif
for( ; i < n; i++ )
{
_AccTp v = _AccTp(a[i] - b[i]);
s += v*v;
}
return s;
}
static inline float normL2Sqr(const float* a, const float* b, int n)
{
float s = 0.f;
for( int i = 0; i < n; i++ )
{
float v = a[i] - b[i];
s += v*v;
}
return s;
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normL1(const _Tp* a, const _Tp* b, int n)
{
_AccTp s = 0;
int i= 0;
#if CV_ENABLE_UNROLLED
for(; i <= n - 4; i += 4 )
{
_AccTp v0 = _AccTp(a[i] - b[i]), v1 = _AccTp(a[i+1] - b[i+1]), v2 = _AccTp(a[i+2] - b[i+2]), v3 = _AccTp(a[i+3] - b[i+3]);
s += std::abs(v0) + std::abs(v1) + std::abs(v2) + std::abs(v3);
}
#endif
for( ; i < n; i++ )
{
_AccTp v = _AccTp(a[i] - b[i]);
s += std::abs(v);
}
return s;
}
inline float normL1(const float* a, const float* b, int n)
{
float s = 0.f;
for( int i = 0; i < n; i++ )
{
s += std::abs(a[i] - b[i]);
}
return s;
}
inline int normL1(const uchar* a, const uchar* b, int n)
{
int s = 0;
for( int i = 0; i < n; i++ )
{
s += std::abs(a[i] - b[i]);
}
return s;
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normInf(const _Tp* a, const _Tp* b, int n)
{
_AccTp s = 0;
for( int i = 0; i < n; i++ )
{
_AccTp v0 = a[i] - b[i];
s = std::max(s, std::abs(v0));
}
return s;
}
/** @brief Computes the cube root of an argument.
The function cubeRoot computes \f$\sqrt[3]{\texttt{val}}\f$. Negative arguments are handled correctly.
NaN and Inf are not handled. The accuracy approaches the maximum possible accuracy for
single-precision data.
@param val A function argument.
*/
CV_EXPORTS_W float cubeRoot(float val);
/** @brief Calculates the angle of a 2D vector in degrees.
The function fastAtan2 calculates the full-range angle of an input 2D vector. The angle is measured
in degrees and varies from 0 to 360 degrees. The accuracy is about 0.3 degrees.
@param x x-coordinate of the vector.
@param y y-coordinate of the vector.
*/
CV_EXPORTS_W float fastAtan2(float y, float x);
/** proxy for hal::LU */
CV_EXPORTS int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n);
/** proxy for hal::LU */
CV_EXPORTS int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n);
/** proxy for hal::Cholesky */
CV_EXPORTS bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n);
/** proxy for hal::Cholesky */
CV_EXPORTS bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n);
////////////////// forward declarations for important OpenCV types //////////////////
//! @cond IGNORED
template<typename _Tp, int cn> class Vec;
template<typename _Tp, int m, int n> class Matx;
template<typename _Tp> class Complex;
template<typename _Tp> class Point_;
template<typename _Tp> class Point3_;
template<typename _Tp> class Size_;
template<typename _Tp> class Rect_;
template<typename _Tp> class Scalar_;
class CV_EXPORTS RotatedRect;
class CV_EXPORTS Range;
class CV_EXPORTS TermCriteria;
class CV_EXPORTS KeyPoint;
class CV_EXPORTS DMatch;
class CV_EXPORTS RNG;
class CV_EXPORTS Mat;
class CV_EXPORTS MatExpr;
class CV_EXPORTS UMat;
class CV_EXPORTS SparseMat;
typedef Mat MatND;
template<typename _Tp> class Mat_;
template<typename _Tp> class SparseMat_;
class CV_EXPORTS MatConstIterator;
class CV_EXPORTS SparseMatIterator;
class CV_EXPORTS SparseMatConstIterator;
template<typename _Tp> class MatIterator_;
template<typename _Tp> class MatConstIterator_;
template<typename _Tp> class SparseMatIterator_;
template<typename _Tp> class SparseMatConstIterator_;
namespace ogl
{
class CV_EXPORTS Buffer;
class CV_EXPORTS Texture2D;
class CV_EXPORTS Arrays;
}
namespace cuda
{
class CV_EXPORTS GpuMat;
class CV_EXPORTS HostMem;
class CV_EXPORTS Stream;
class CV_EXPORTS Event;
}
namespace cudev
{
template <typename _Tp> class GpuMat_;
}
namespace ipp
{
CV_EXPORTS int getIppFeatures();
CV_EXPORTS void setIppStatus(int status, const char * const funcname = NULL, const char * const filename = NULL,
int line = 0);
CV_EXPORTS int getIppStatus();
CV_EXPORTS String getIppErrorLocation();
CV_EXPORTS bool useIPP();
CV_EXPORTS void setUseIPP(bool flag);
} // ipp
//! @endcond
//! @} core_utils
} // cv
#include "opencv2/core/neon_utils.hpp"
#endif //__OPENCV_CORE_BASE_HPP__

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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
#ifndef __OPENCV_CORE_BUFFER_POOL_HPP__
#define __OPENCV_CORE_BUFFER_POOL_HPP__
namespace cv
{
//! @addtogroup core
//! @{
class BufferPoolController
{
protected:
~BufferPoolController() { }
public:
virtual size_t getReservedSize() const = 0;
virtual size_t getMaxReservedSize() const = 0;
virtual void setMaxReservedSize(size_t size) = 0;
virtual void freeAllReservedBuffers() = 0;
};
//! @}
}
#endif // __OPENCV_CORE_BUFFER_POOL_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifdef __OPENCV_BUILD
#error this is a compatibility header which should not be used inside the OpenCV library
#endif
#include "opencv2/core.hpp"

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_CUDA_HPP__
#define __OPENCV_CORE_CUDA_HPP__
#ifndef __cplusplus
# error cuda.hpp header must be compiled as C++
#endif
#include "opencv2/core.hpp"
#include "opencv2/core/cuda_types.hpp"
/**
@defgroup cuda CUDA-accelerated Computer Vision
@{
@defgroup cudacore Core part
@{
@defgroup cudacore_init Initalization and Information
@defgroup cudacore_struct Data Structures
@}
@}
*/
namespace cv { namespace cuda {
//! @addtogroup cudacore_struct
//! @{
//===================================================================================
// GpuMat
//===================================================================================
/** @brief Base storage class for GPU memory with reference counting.
Its interface matches the Mat interface with the following limitations:
- no arbitrary dimensions support (only 2D)
- no functions that return references to their data (because references on GPU are not valid for
CPU)
- no expression templates technique support
Beware that the latter limitation may lead to overloaded matrix operators that cause memory
allocations. The GpuMat class is convertible to cuda::PtrStepSz and cuda::PtrStep so it can be
passed directly to the kernel.
@note In contrast with Mat, in most cases GpuMat::isContinuous() == false . This means that rows are
aligned to a size depending on the hardware. Single-row GpuMat is always a continuous matrix.
@note You are not recommended to leave static or global GpuMat variables allocated, that is, to rely
on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory
release function returns error if the CUDA context has been destroyed before.
@sa Mat
*/
class CV_EXPORTS GpuMat
{
public:
class CV_EXPORTS Allocator
{
public:
virtual ~Allocator() {}
// allocator must fill data, step and refcount fields
virtual bool allocate(GpuMat* mat, int rows, int cols, size_t elemSize) = 0;
virtual void free(GpuMat* mat) = 0;
};
//! default allocator
static Allocator* defaultAllocator();
static void setDefaultAllocator(Allocator* allocator);
//! default constructor
explicit GpuMat(Allocator* allocator = defaultAllocator());
//! constructs GpuMat of the specified size and type
GpuMat(int rows, int cols, int type, Allocator* allocator = defaultAllocator());
GpuMat(Size size, int type, Allocator* allocator = defaultAllocator());
//! constucts GpuMat and fills it with the specified value _s
GpuMat(int rows, int cols, int type, Scalar s, Allocator* allocator = defaultAllocator());
GpuMat(Size size, int type, Scalar s, Allocator* allocator = defaultAllocator());
//! copy constructor
GpuMat(const GpuMat& m);
//! constructor for GpuMat headers pointing to user-allocated data
GpuMat(int rows, int cols, int type, void* data, size_t step = Mat::AUTO_STEP);
GpuMat(Size size, int type, void* data, size_t step = Mat::AUTO_STEP);
//! creates a GpuMat header for a part of the bigger matrix
GpuMat(const GpuMat& m, Range rowRange, Range colRange);
GpuMat(const GpuMat& m, Rect roi);
//! builds GpuMat from host memory (Blocking call)
explicit GpuMat(InputArray arr, Allocator* allocator = defaultAllocator());
//! destructor - calls release()
~GpuMat();
//! assignment operators
GpuMat& operator =(const GpuMat& m);
//! allocates new GpuMat data unless the GpuMat already has specified size and type
void create(int rows, int cols, int type);
void create(Size size, int type);
//! decreases reference counter, deallocate the data when reference counter reaches 0
void release();
//! swaps with other smart pointer
void swap(GpuMat& mat);
//! pefroms upload data to GpuMat (Blocking call)
void upload(InputArray arr);
//! pefroms upload data to GpuMat (Non-Blocking call)
void upload(InputArray arr, Stream& stream);
//! pefroms download data from device to host memory (Blocking call)
void download(OutputArray dst) const;
//! pefroms download data from device to host memory (Non-Blocking call)
void download(OutputArray dst, Stream& stream) const;
//! returns deep copy of the GpuMat, i.e. the data is copied
GpuMat clone() const;
//! copies the GpuMat content to device memory (Blocking call)
void copyTo(OutputArray dst) const;
//! copies the GpuMat content to device memory (Non-Blocking call)
void copyTo(OutputArray dst, Stream& stream) const;
//! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call)
void copyTo(OutputArray dst, InputArray mask) const;
//! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call)
void copyTo(OutputArray dst, InputArray mask, Stream& stream) const;
//! sets some of the GpuMat elements to s (Blocking call)
GpuMat& setTo(Scalar s);
//! sets some of the GpuMat elements to s (Non-Blocking call)
GpuMat& setTo(Scalar s, Stream& stream);
//! sets some of the GpuMat elements to s, according to the mask (Blocking call)
GpuMat& setTo(Scalar s, InputArray mask);
//! sets some of the GpuMat elements to s, according to the mask (Non-Blocking call)
GpuMat& setTo(Scalar s, InputArray mask, Stream& stream);
//! converts GpuMat to another datatype (Blocking call)
void convertTo(OutputArray dst, int rtype) const;
//! converts GpuMat to another datatype (Non-Blocking call)
void convertTo(OutputArray dst, int rtype, Stream& stream) const;
//! converts GpuMat to another datatype with scaling (Blocking call)
void convertTo(OutputArray dst, int rtype, double alpha, double beta = 0.0) const;
//! converts GpuMat to another datatype with scaling (Non-Blocking call)
void convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const;
//! converts GpuMat to another datatype with scaling (Non-Blocking call)
void convertTo(OutputArray dst, int rtype, double alpha, double beta, Stream& stream) const;
void assignTo(GpuMat& m, int type=-1) const;
//! returns pointer to y-th row
uchar* ptr(int y = 0);
const uchar* ptr(int y = 0) const;
//! template version of the above method
template<typename _Tp> _Tp* ptr(int y = 0);
template<typename _Tp> const _Tp* ptr(int y = 0) const;
template <typename _Tp> operator PtrStepSz<_Tp>() const;
template <typename _Tp> operator PtrStep<_Tp>() const;
//! returns a new GpuMat header for the specified row
GpuMat row(int y) const;
//! returns a new GpuMat header for the specified column
GpuMat col(int x) const;
//! ... for the specified row span
GpuMat rowRange(int startrow, int endrow) const;
GpuMat rowRange(Range r) const;
//! ... for the specified column span
GpuMat colRange(int startcol, int endcol) const;
GpuMat colRange(Range r) const;
//! extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.)
GpuMat operator ()(Range rowRange, Range colRange) const;
GpuMat operator ()(Rect roi) const;
//! creates alternative GpuMat header for the same data, with different
//! number of channels and/or different number of rows
GpuMat reshape(int cn, int rows = 0) const;
//! locates GpuMat header within a parent GpuMat
void locateROI(Size& wholeSize, Point& ofs) const;
//! moves/resizes the current GpuMat ROI inside the parent GpuMat
GpuMat& adjustROI(int dtop, int dbottom, int dleft, int dright);
//! returns true iff the GpuMat data is continuous
//! (i.e. when there are no gaps between successive rows)
bool isContinuous() const;
//! returns element size in bytes
size_t elemSize() const;
//! returns the size of element channel in bytes
size_t elemSize1() const;
//! returns element type
int type() const;
//! returns element type
int depth() const;
//! returns number of channels
int channels() const;
//! returns step/elemSize1()
size_t step1() const;
//! returns GpuMat size : width == number of columns, height == number of rows
Size size() const;
//! returns true if GpuMat data is NULL
bool empty() const;
/*! includes several bit-fields:
- the magic signature
- continuity flag
- depth
- number of channels
*/
int flags;
//! the number of rows and columns
int rows, cols;
//! a distance between successive rows in bytes; includes the gap if any
size_t step;
//! pointer to the data
uchar* data;
//! pointer to the reference counter;
//! when GpuMat points to user-allocated data, the pointer is NULL
int* refcount;
//! helper fields used in locateROI and adjustROI
uchar* datastart;
const uchar* dataend;
//! allocator
Allocator* allocator;
};
/** @brief Creates a continuous matrix.
@param rows Row count.
@param cols Column count.
@param type Type of the matrix.
@param arr Destination matrix. This parameter changes only if it has a proper type and area (
\f$\texttt{rows} \times \texttt{cols}\f$ ).
Matrix is called continuous if its elements are stored continuously, that is, without gaps at the
end of each row.
*/
CV_EXPORTS void createContinuous(int rows, int cols, int type, OutputArray arr);
/** @brief Ensures that the size of a matrix is big enough and the matrix has a proper type.
@param rows Minimum desired number of rows.
@param cols Minimum desired number of columns.
@param type Desired matrix type.
@param arr Destination matrix.
The function does not reallocate memory if the matrix has proper attributes already.
*/
CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, OutputArray arr);
//! BufferPool management (must be called before Stream creation)
CV_EXPORTS void setBufferPoolUsage(bool on);
CV_EXPORTS void setBufferPoolConfig(int deviceId, size_t stackSize, int stackCount);
//===================================================================================
// HostMem
//===================================================================================
/** @brief Class with reference counting wrapping special memory type allocation functions from CUDA.
Its interface is also Mat-like but with additional memory type parameters.
- **PAGE_LOCKED** sets a page locked memory type used commonly for fast and asynchronous
uploading/downloading data from/to GPU.
- **SHARED** specifies a zero copy memory allocation that enables mapping the host memory to GPU
address space, if supported.
- **WRITE_COMBINED** sets the write combined buffer that is not cached by CPU. Such buffers are
used to supply GPU with data when GPU only reads it. The advantage is a better CPU cache
utilization.
@note Allocation size of such memory types is usually limited. For more details, see *CUDA 2.2
Pinned Memory APIs* document or *CUDA C Programming Guide*.
*/
class CV_EXPORTS HostMem
{
public:
enum AllocType { PAGE_LOCKED = 1, SHARED = 2, WRITE_COMBINED = 4 };
static MatAllocator* getAllocator(AllocType alloc_type = PAGE_LOCKED);
explicit HostMem(AllocType alloc_type = PAGE_LOCKED);
HostMem(const HostMem& m);
HostMem(int rows, int cols, int type, AllocType alloc_type = PAGE_LOCKED);
HostMem(Size size, int type, AllocType alloc_type = PAGE_LOCKED);
//! creates from host memory with coping data
explicit HostMem(InputArray arr, AllocType alloc_type = PAGE_LOCKED);
~HostMem();
HostMem& operator =(const HostMem& m);
//! swaps with other smart pointer
void swap(HostMem& b);
//! returns deep copy of the matrix, i.e. the data is copied
HostMem clone() const;
//! allocates new matrix data unless the matrix already has specified size and type.
void create(int rows, int cols, int type);
void create(Size size, int type);
//! creates alternative HostMem header for the same data, with different
//! number of channels and/or different number of rows
HostMem reshape(int cn, int rows = 0) const;
//! decrements reference counter and released memory if needed.
void release();
//! returns matrix header with disabled reference counting for HostMem data.
Mat createMatHeader() const;
/** @brief Maps CPU memory to GPU address space and creates the cuda::GpuMat header without reference counting
for it.
This can be done only if memory was allocated with the SHARED flag and if it is supported by the
hardware. Laptops often share video and CPU memory, so address spaces can be mapped, which
eliminates an extra copy.
*/
GpuMat createGpuMatHeader() const;
// Please see cv::Mat for descriptions
bool isContinuous() const;
size_t elemSize() const;
size_t elemSize1() const;
int type() const;
int depth() const;
int channels() const;
size_t step1() const;
Size size() const;
bool empty() const;
// Please see cv::Mat for descriptions
int flags;
int rows, cols;
size_t step;
uchar* data;
int* refcount;
uchar* datastart;
const uchar* dataend;
AllocType alloc_type;
};
/** @brief Page-locks the memory of matrix and maps it for the device(s).
@param m Input matrix.
*/
CV_EXPORTS void registerPageLocked(Mat& m);
/** @brief Unmaps the memory of matrix and makes it pageable again.
@param m Input matrix.
*/
CV_EXPORTS void unregisterPageLocked(Mat& m);
//===================================================================================
// Stream
//===================================================================================
/** @brief This class encapsulates a queue of asynchronous calls.
@note Currently, you may face problems if an operation is enqueued twice with different data. Some
functions use the constant GPU memory, and next call may update the memory before the previous one
has been finished. But calling different operations asynchronously is safe because each operation
has its own constant buffer. Memory copy/upload/download/set operations to the buffers you hold are
also safe. :
*/
class CV_EXPORTS Stream
{
typedef void (Stream::*bool_type)() const;
void this_type_does_not_support_comparisons() const {}
public:
typedef void (*StreamCallback)(int status, void* userData);
//! creates a new asynchronous stream
Stream();
/** @brief Returns true if the current stream queue is finished. Otherwise, it returns false.
*/
bool queryIfComplete() const;
/** @brief Blocks the current CPU thread until all operations in the stream are complete.
*/
void waitForCompletion();
/** @brief Makes a compute stream wait on an event.
*/
void waitEvent(const Event& event);
/** @brief Adds a callback to be called on the host after all currently enqueued items in the stream have
completed.
@note Callbacks must not make any CUDA API calls. Callbacks must not perform any synchronization
that may depend on outstanding device work or other callbacks that are not mandated to run earlier.
Callbacks without a mandated order (in independent streams) execute in undefined order and may be
serialized.
*/
void enqueueHostCallback(StreamCallback callback, void* userData);
//! return Stream object for default CUDA stream
static Stream& Null();
//! returns true if stream object is not default (!= 0)
operator bool_type() const;
class Impl;
private:
Ptr<Impl> impl_;
Stream(const Ptr<Impl>& impl);
friend struct StreamAccessor;
friend class BufferPool;
friend class DefaultDeviceInitializer;
};
class CV_EXPORTS Event
{
public:
enum CreateFlags
{
DEFAULT = 0x00, /**< Default event flag */
BLOCKING_SYNC = 0x01, /**< Event uses blocking synchronization */
DISABLE_TIMING = 0x02, /**< Event will not record timing data */
INTERPROCESS = 0x04 /**< Event is suitable for interprocess use. DisableTiming must be set */
};
explicit Event(CreateFlags flags = DEFAULT);
//! records an event
void record(Stream& stream = Stream::Null());
//! queries an event's status
bool queryIfComplete() const;
//! waits for an event to complete
void waitForCompletion();
//! computes the elapsed time between events
static float elapsedTime(const Event& start, const Event& end);
class Impl;
private:
Ptr<Impl> impl_;
Event(const Ptr<Impl>& impl);
friend struct EventAccessor;
};
//! @} cudacore_struct
//===================================================================================
// Initialization & Info
//===================================================================================
//! @addtogroup cudacore_init
//! @{
/** @brief Returns the number of installed CUDA-enabled devices.
Use this function before any other CUDA functions calls. If OpenCV is compiled without CUDA support,
this function returns 0.
*/
CV_EXPORTS int getCudaEnabledDeviceCount();
/** @brief Sets a device and initializes it for the current thread.
@param device System index of a CUDA device starting with 0.
If the call of this function is omitted, a default device is initialized at the fist CUDA usage.
*/
CV_EXPORTS void setDevice(int device);
/** @brief Returns the current device index set by cuda::setDevice or initialized by default.
*/
CV_EXPORTS int getDevice();
/** @brief Explicitly destroys and cleans up all resources associated with the current device in the current
process.
Any subsequent API call to this device will reinitialize the device.
*/
CV_EXPORTS void resetDevice();
/** @brief Enumeration providing CUDA computing features.
*/
enum FeatureSet
{
FEATURE_SET_COMPUTE_10 = 10,
FEATURE_SET_COMPUTE_11 = 11,
FEATURE_SET_COMPUTE_12 = 12,
FEATURE_SET_COMPUTE_13 = 13,
FEATURE_SET_COMPUTE_20 = 20,
FEATURE_SET_COMPUTE_21 = 21,
FEATURE_SET_COMPUTE_30 = 30,
FEATURE_SET_COMPUTE_32 = 32,
FEATURE_SET_COMPUTE_35 = 35,
FEATURE_SET_COMPUTE_50 = 50,
GLOBAL_ATOMICS = FEATURE_SET_COMPUTE_11,
SHARED_ATOMICS = FEATURE_SET_COMPUTE_12,
NATIVE_DOUBLE = FEATURE_SET_COMPUTE_13,
WARP_SHUFFLE_FUNCTIONS = FEATURE_SET_COMPUTE_30,
DYNAMIC_PARALLELISM = FEATURE_SET_COMPUTE_35
};
//! checks whether current device supports the given feature
CV_EXPORTS bool deviceSupports(FeatureSet feature_set);
/** @brief Class providing a set of static methods to check what NVIDIA\* card architecture the CUDA module was
built for.
According to the CUDA C Programming Guide Version 3.2: "PTX code produced for some specific compute
capability can always be compiled to binary code of greater or equal compute capability".
*/
class CV_EXPORTS TargetArchs
{
public:
/** @brief The following method checks whether the module was built with the support of the given feature:
@param feature_set Features to be checked. See :ocvcuda::FeatureSet.
*/
static bool builtWith(FeatureSet feature_set);
/** @brief There is a set of methods to check whether the module contains intermediate (PTX) or binary CUDA
code for the given architecture(s):
@param major Major compute capability version.
@param minor Minor compute capability version.
*/
static bool has(int major, int minor);
static bool hasPtx(int major, int minor);
static bool hasBin(int major, int minor);
static bool hasEqualOrLessPtx(int major, int minor);
static bool hasEqualOrGreater(int major, int minor);
static bool hasEqualOrGreaterPtx(int major, int minor);
static bool hasEqualOrGreaterBin(int major, int minor);
};
/** @brief Class providing functionality for querying the specified GPU properties.
*/
class CV_EXPORTS DeviceInfo
{
public:
//! creates DeviceInfo object for the current GPU
DeviceInfo();
/** @brief The constructors.
@param device_id System index of the CUDA device starting with 0.
Constructs the DeviceInfo object for the specified device. If device_id parameter is missed, it
constructs an object for the current device.
*/
DeviceInfo(int device_id);
/** @brief Returns system index of the CUDA device starting with 0.
*/
int deviceID() const;
//! ASCII string identifying device
const char* name() const;
//! global memory available on device in bytes
size_t totalGlobalMem() const;
//! shared memory available per block in bytes
size_t sharedMemPerBlock() const;
//! 32-bit registers available per block
int regsPerBlock() const;
//! warp size in threads
int warpSize() const;
//! maximum pitch in bytes allowed by memory copies
size_t memPitch() const;
//! maximum number of threads per block
int maxThreadsPerBlock() const;
//! maximum size of each dimension of a block
Vec3i maxThreadsDim() const;
//! maximum size of each dimension of a grid
Vec3i maxGridSize() const;
//! clock frequency in kilohertz
int clockRate() const;
//! constant memory available on device in bytes
size_t totalConstMem() const;
//! major compute capability
int majorVersion() const;
//! minor compute capability
int minorVersion() const;
//! alignment requirement for textures
size_t textureAlignment() const;
//! pitch alignment requirement for texture references bound to pitched memory
size_t texturePitchAlignment() const;
//! number of multiprocessors on device
int multiProcessorCount() const;
//! specified whether there is a run time limit on kernels
bool kernelExecTimeoutEnabled() const;
//! device is integrated as opposed to discrete
bool integrated() const;
//! device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer
bool canMapHostMemory() const;
enum ComputeMode
{
ComputeModeDefault, /**< default compute mode (Multiple threads can use cudaSetDevice with this device) */
ComputeModeExclusive, /**< compute-exclusive-thread mode (Only one thread in one process will be able to use cudaSetDevice with this device) */
ComputeModeProhibited, /**< compute-prohibited mode (No threads can use cudaSetDevice with this device) */
ComputeModeExclusiveProcess /**< compute-exclusive-process mode (Many threads in one process will be able to use cudaSetDevice with this device) */
};
//! compute mode
ComputeMode computeMode() const;
//! maximum 1D texture size
int maxTexture1D() const;
//! maximum 1D mipmapped texture size
int maxTexture1DMipmap() const;
//! maximum size for 1D textures bound to linear memory
int maxTexture1DLinear() const;
//! maximum 2D texture dimensions
Vec2i maxTexture2D() const;
//! maximum 2D mipmapped texture dimensions
Vec2i maxTexture2DMipmap() const;
//! maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory
Vec3i maxTexture2DLinear() const;
//! maximum 2D texture dimensions if texture gather operations have to be performed
Vec2i maxTexture2DGather() const;
//! maximum 3D texture dimensions
Vec3i maxTexture3D() const;
//! maximum Cubemap texture dimensions
int maxTextureCubemap() const;
//! maximum 1D layered texture dimensions
Vec2i maxTexture1DLayered() const;
//! maximum 2D layered texture dimensions
Vec3i maxTexture2DLayered() const;
//! maximum Cubemap layered texture dimensions
Vec2i maxTextureCubemapLayered() const;
//! maximum 1D surface size
int maxSurface1D() const;
//! maximum 2D surface dimensions
Vec2i maxSurface2D() const;
//! maximum 3D surface dimensions
Vec3i maxSurface3D() const;
//! maximum 1D layered surface dimensions
Vec2i maxSurface1DLayered() const;
//! maximum 2D layered surface dimensions
Vec3i maxSurface2DLayered() const;
//! maximum Cubemap surface dimensions
int maxSurfaceCubemap() const;
//! maximum Cubemap layered surface dimensions
Vec2i maxSurfaceCubemapLayered() const;
//! alignment requirements for surfaces
size_t surfaceAlignment() const;
//! device can possibly execute multiple kernels concurrently
bool concurrentKernels() const;
//! device has ECC support enabled
bool ECCEnabled() const;
//! PCI bus ID of the device
int pciBusID() const;
//! PCI device ID of the device
int pciDeviceID() const;
//! PCI domain ID of the device
int pciDomainID() const;
//! true if device is a Tesla device using TCC driver, false otherwise
bool tccDriver() const;
//! number of asynchronous engines
int asyncEngineCount() const;
//! device shares a unified address space with the host
bool unifiedAddressing() const;
//! peak memory clock frequency in kilohertz
int memoryClockRate() const;
//! global memory bus width in bits
int memoryBusWidth() const;
//! size of L2 cache in bytes
int l2CacheSize() const;
//! maximum resident threads per multiprocessor
int maxThreadsPerMultiProcessor() const;
//! gets free and total device memory
void queryMemory(size_t& totalMemory, size_t& freeMemory) const;
size_t freeMemory() const;
size_t totalMemory() const;
/** @brief Provides information on CUDA feature support.
@param feature_set Features to be checked. See cuda::FeatureSet.
This function returns true if the device has the specified CUDA feature. Otherwise, it returns false
*/
bool supports(FeatureSet feature_set) const;
/** @brief Checks the CUDA module and device compatibility.
This function returns true if the CUDA module can be run on the specified device. Otherwise, it
returns false .
*/
bool isCompatible() const;
private:
int device_id_;
};
CV_EXPORTS void printCudaDeviceInfo(int device);
CV_EXPORTS void printShortCudaDeviceInfo(int device);
//! @} cudacore_init
}} // namespace cv { namespace cuda {
#include "opencv2/core/cuda.inl.hpp"
#endif /* __OPENCV_CORE_CUDA_HPP__ */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_CUDAINL_HPP__
#define __OPENCV_CORE_CUDAINL_HPP__
#include "opencv2/core/cuda.hpp"
//! @cond IGNORED
namespace cv { namespace cuda {
//===================================================================================
// GpuMat
//===================================================================================
inline
GpuMat::GpuMat(Allocator* allocator_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
{}
inline
GpuMat::GpuMat(int rows_, int cols_, int type_, Allocator* allocator_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
{
if (rows_ > 0 && cols_ > 0)
create(rows_, cols_, type_);
}
inline
GpuMat::GpuMat(Size size_, int type_, Allocator* allocator_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
{
if (size_.height > 0 && size_.width > 0)
create(size_.height, size_.width, type_);
}
inline
GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_, Allocator* allocator_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
{
if (rows_ > 0 && cols_ > 0)
{
create(rows_, cols_, type_);
setTo(s_);
}
}
inline
GpuMat::GpuMat(Size size_, int type_, Scalar s_, Allocator* allocator_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
{
if (size_.height > 0 && size_.width > 0)
{
create(size_.height, size_.width, type_);
setTo(s_);
}
}
inline
GpuMat::GpuMat(const GpuMat& m)
: flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), allocator(m.allocator)
{
if (refcount)
CV_XADD(refcount, 1);
}
inline
GpuMat::GpuMat(InputArray arr, Allocator* allocator_) :
flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
{
upload(arr);
}
inline
GpuMat::~GpuMat()
{
release();
}
inline
GpuMat& GpuMat::operator =(const GpuMat& m)
{
if (this != &m)
{
GpuMat temp(m);
swap(temp);
}
return *this;
}
inline
void GpuMat::create(Size size_, int type_)
{
create(size_.height, size_.width, type_);
}
inline
void GpuMat::swap(GpuMat& b)
{
std::swap(flags, b.flags);
std::swap(rows, b.rows);
std::swap(cols, b.cols);
std::swap(step, b.step);
std::swap(data, b.data);
std::swap(datastart, b.datastart);
std::swap(dataend, b.dataend);
std::swap(refcount, b.refcount);
std::swap(allocator, b.allocator);
}
inline
GpuMat GpuMat::clone() const
{
GpuMat m;
copyTo(m);
return m;
}
inline
void GpuMat::copyTo(OutputArray dst, InputArray mask) const
{
copyTo(dst, mask, Stream::Null());
}
inline
GpuMat& GpuMat::setTo(Scalar s)
{
return setTo(s, Stream::Null());
}
inline
GpuMat& GpuMat::setTo(Scalar s, InputArray mask)
{
return setTo(s, mask, Stream::Null());
}
inline
void GpuMat::convertTo(OutputArray dst, int rtype) const
{
convertTo(dst, rtype, Stream::Null());
}
inline
void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, double beta) const
{
convertTo(dst, rtype, alpha, beta, Stream::Null());
}
inline
void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const
{
convertTo(dst, rtype, alpha, 0.0, stream);
}
inline
void GpuMat::assignTo(GpuMat& m, int _type) const
{
if (_type < 0)
m = *this;
else
convertTo(m, _type);
}
inline
uchar* GpuMat::ptr(int y)
{
CV_DbgAssert( (unsigned)y < (unsigned)rows );
return data + step * y;
}
inline
const uchar* GpuMat::ptr(int y) const
{
CV_DbgAssert( (unsigned)y < (unsigned)rows );
return data + step * y;
}
template<typename _Tp> inline
_Tp* GpuMat::ptr(int y)
{
return (_Tp*)ptr(y);
}
template<typename _Tp> inline
const _Tp* GpuMat::ptr(int y) const
{
return (const _Tp*)ptr(y);
}
template <class T> inline
GpuMat::operator PtrStepSz<T>() const
{
return PtrStepSz<T>(rows, cols, (T*)data, step);
}
template <class T> inline
GpuMat::operator PtrStep<T>() const
{
return PtrStep<T>((T*)data, step);
}
inline
GpuMat GpuMat::row(int y) const
{
return GpuMat(*this, Range(y, y+1), Range::all());
}
inline
GpuMat GpuMat::col(int x) const
{
return GpuMat(*this, Range::all(), Range(x, x+1));
}
inline
GpuMat GpuMat::rowRange(int startrow, int endrow) const
{
return GpuMat(*this, Range(startrow, endrow), Range::all());
}
inline
GpuMat GpuMat::rowRange(Range r) const
{
return GpuMat(*this, r, Range::all());
}
inline
GpuMat GpuMat::colRange(int startcol, int endcol) const
{
return GpuMat(*this, Range::all(), Range(startcol, endcol));
}
inline
GpuMat GpuMat::colRange(Range r) const
{
return GpuMat(*this, Range::all(), r);
}
inline
GpuMat GpuMat::operator ()(Range rowRange_, Range colRange_) const
{
return GpuMat(*this, rowRange_, colRange_);
}
inline
GpuMat GpuMat::operator ()(Rect roi) const
{
return GpuMat(*this, roi);
}
inline
bool GpuMat::isContinuous() const
{
return (flags & Mat::CONTINUOUS_FLAG) != 0;
}
inline
size_t GpuMat::elemSize() const
{
return CV_ELEM_SIZE(flags);
}
inline
size_t GpuMat::elemSize1() const
{
return CV_ELEM_SIZE1(flags);
}
inline
int GpuMat::type() const
{
return CV_MAT_TYPE(flags);
}
inline
int GpuMat::depth() const
{
return CV_MAT_DEPTH(flags);
}
inline
int GpuMat::channels() const
{
return CV_MAT_CN(flags);
}
inline
size_t GpuMat::step1() const
{
return step / elemSize1();
}
inline
Size GpuMat::size() const
{
return Size(cols, rows);
}
inline
bool GpuMat::empty() const
{
return data == 0;
}
static inline
GpuMat createContinuous(int rows, int cols, int type)
{
GpuMat m;
createContinuous(rows, cols, type, m);
return m;
}
static inline
void createContinuous(Size size, int type, OutputArray arr)
{
createContinuous(size.height, size.width, type, arr);
}
static inline
GpuMat createContinuous(Size size, int type)
{
GpuMat m;
createContinuous(size, type, m);
return m;
}
static inline
void ensureSizeIsEnough(Size size, int type, OutputArray arr)
{
ensureSizeIsEnough(size.height, size.width, type, arr);
}
static inline
void swap(GpuMat& a, GpuMat& b)
{
a.swap(b);
}
//===================================================================================
// HostMem
//===================================================================================
inline
HostMem::HostMem(AllocType alloc_type_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
{
}
inline
HostMem::HostMem(const HostMem& m)
: flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), alloc_type(m.alloc_type)
{
if( refcount )
CV_XADD(refcount, 1);
}
inline
HostMem::HostMem(int rows_, int cols_, int type_, AllocType alloc_type_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
{
if (rows_ > 0 && cols_ > 0)
create(rows_, cols_, type_);
}
inline
HostMem::HostMem(Size size_, int type_, AllocType alloc_type_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
{
if (size_.height > 0 && size_.width > 0)
create(size_.height, size_.width, type_);
}
inline
HostMem::HostMem(InputArray arr, AllocType alloc_type_)
: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
{
arr.getMat().copyTo(*this);
}
inline
HostMem::~HostMem()
{
release();
}
inline
HostMem& HostMem::operator =(const HostMem& m)
{
if (this != &m)
{
HostMem temp(m);
swap(temp);
}
return *this;
}
inline
void HostMem::swap(HostMem& b)
{
std::swap(flags, b.flags);
std::swap(rows, b.rows);
std::swap(cols, b.cols);
std::swap(step, b.step);
std::swap(data, b.data);
std::swap(datastart, b.datastart);
std::swap(dataend, b.dataend);
std::swap(refcount, b.refcount);
std::swap(alloc_type, b.alloc_type);
}
inline
HostMem HostMem::clone() const
{
HostMem m(size(), type(), alloc_type);
createMatHeader().copyTo(m);
return m;
}
inline
void HostMem::create(Size size_, int type_)
{
create(size_.height, size_.width, type_);
}
inline
Mat HostMem::createMatHeader() const
{
return Mat(size(), type(), data, step);
}
inline
bool HostMem::isContinuous() const
{
return (flags & Mat::CONTINUOUS_FLAG) != 0;
}
inline
size_t HostMem::elemSize() const
{
return CV_ELEM_SIZE(flags);
}
inline
size_t HostMem::elemSize1() const
{
return CV_ELEM_SIZE1(flags);
}
inline
int HostMem::type() const
{
return CV_MAT_TYPE(flags);
}
inline
int HostMem::depth() const
{
return CV_MAT_DEPTH(flags);
}
inline
int HostMem::channels() const
{
return CV_MAT_CN(flags);
}
inline
size_t HostMem::step1() const
{
return step / elemSize1();
}
inline
Size HostMem::size() const
{
return Size(cols, rows);
}
inline
bool HostMem::empty() const
{
return data == 0;
}
static inline
void swap(HostMem& a, HostMem& b)
{
a.swap(b);
}
//===================================================================================
// Stream
//===================================================================================
inline
Stream::Stream(const Ptr<Impl>& impl)
: impl_(impl)
{
}
//===================================================================================
// Event
//===================================================================================
inline
Event::Event(const Ptr<Impl>& impl)
: impl_(impl)
{
}
//===================================================================================
// Initialization & Info
//===================================================================================
inline
bool TargetArchs::has(int major, int minor)
{
return hasPtx(major, minor) || hasBin(major, minor);
}
inline
bool TargetArchs::hasEqualOrGreater(int major, int minor)
{
return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
}
inline
DeviceInfo::DeviceInfo()
{
device_id_ = getDevice();
}
inline
DeviceInfo::DeviceInfo(int device_id)
{
CV_Assert( device_id >= 0 && device_id < getCudaEnabledDeviceCount() );
device_id_ = device_id;
}
inline
int DeviceInfo::deviceID() const
{
return device_id_;
}
inline
size_t DeviceInfo::freeMemory() const
{
size_t _totalMemory = 0, _freeMemory = 0;
queryMemory(_totalMemory, _freeMemory);
return _freeMemory;
}
inline
size_t DeviceInfo::totalMemory() const
{
size_t _totalMemory = 0, _freeMemory = 0;
queryMemory(_totalMemory, _freeMemory);
return _totalMemory;
}
inline
bool DeviceInfo::supports(FeatureSet feature_set) const
{
int version = majorVersion() * 10 + minorVersion();
return version >= feature_set;
}
}} // namespace cv { namespace cuda {
//===================================================================================
// Mat
//===================================================================================
namespace cv {
inline
Mat::Mat(const cuda::GpuMat& m)
: flags(0), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows)
{
m.download(*this);
}
}
//! @endcond
#endif // __OPENCV_CORE_CUDAINL_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP__
#define __OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP__
#ifndef __cplusplus
# error cuda_stream_accessor.hpp header must be compiled as C++
#endif
/** @file cuda_stream_accessor.hpp
* This is only header file that depends on CUDA Runtime API. All other headers are independent.
*/
#include <cuda_runtime.h>
#include "opencv2/core/cuda.hpp"
namespace cv
{
namespace cuda
{
//! @addtogroup cudacore_struct
//! @{
/** @brief Class that enables getting cudaStream_t from cuda::Stream
*/
struct StreamAccessor
{
CV_EXPORTS static cudaStream_t getStream(const Stream& stream);
CV_EXPORTS static Stream wrapStream(cudaStream_t stream);
};
/** @brief Class that enables getting cudaEvent_t from cuda::Event
*/
struct EventAccessor
{
CV_EXPORTS static cudaEvent_t getEvent(const Event& event);
CV_EXPORTS static Event wrapEvent(cudaEvent_t event);
};
//! @}
}
}
#endif /* __OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP__ */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_CUDA_TYPES_HPP__
#define __OPENCV_CORE_CUDA_TYPES_HPP__
#ifndef __cplusplus
# error cuda_types.hpp header must be compiled as C++
#endif
/** @file
* @deprecated Use @ref cudev instead.
*/
//! @cond IGNORED
#ifdef __CUDACC__
#define __CV_CUDA_HOST_DEVICE__ __host__ __device__ __forceinline__
#else
#define __CV_CUDA_HOST_DEVICE__
#endif
namespace cv
{
namespace cuda
{
// Simple lightweight structures that encapsulates information about an image on device.
// It is intended to pass to nvcc-compiled code. GpuMat depends on headers that nvcc can't compile
template <typename T> struct DevPtr
{
typedef T elem_type;
typedef int index_type;
enum { elem_size = sizeof(elem_type) };
T* data;
__CV_CUDA_HOST_DEVICE__ DevPtr() : data(0) {}
__CV_CUDA_HOST_DEVICE__ DevPtr(T* data_) : data(data_) {}
__CV_CUDA_HOST_DEVICE__ size_t elemSize() const { return elem_size; }
__CV_CUDA_HOST_DEVICE__ operator T*() { return data; }
__CV_CUDA_HOST_DEVICE__ operator const T*() const { return data; }
};
template <typename T> struct PtrSz : public DevPtr<T>
{
__CV_CUDA_HOST_DEVICE__ PtrSz() : size(0) {}
__CV_CUDA_HOST_DEVICE__ PtrSz(T* data_, size_t size_) : DevPtr<T>(data_), size(size_) {}
size_t size;
};
template <typename T> struct PtrStep : public DevPtr<T>
{
__CV_CUDA_HOST_DEVICE__ PtrStep() : step(0) {}
__CV_CUDA_HOST_DEVICE__ PtrStep(T* data_, size_t step_) : DevPtr<T>(data_), step(step_) {}
size_t step;
__CV_CUDA_HOST_DEVICE__ T* ptr(int y = 0) { return ( T*)( ( char*)DevPtr<T>::data + y * step); }
__CV_CUDA_HOST_DEVICE__ const T* ptr(int y = 0) const { return (const T*)( (const char*)DevPtr<T>::data + y * step); }
__CV_CUDA_HOST_DEVICE__ T& operator ()(int y, int x) { return ptr(y)[x]; }
__CV_CUDA_HOST_DEVICE__ const T& operator ()(int y, int x) const { return ptr(y)[x]; }
};
template <typename T> struct PtrStepSz : public PtrStep<T>
{
__CV_CUDA_HOST_DEVICE__ PtrStepSz() : cols(0), rows(0) {}
__CV_CUDA_HOST_DEVICE__ PtrStepSz(int rows_, int cols_, T* data_, size_t step_)
: PtrStep<T>(data_, step_), cols(cols_), rows(rows_) {}
template <typename U>
explicit PtrStepSz(const PtrStepSz<U>& d) : PtrStep<T>((T*)d.data, d.step), cols(d.cols), rows(d.rows){}
int cols;
int rows;
};
typedef PtrStepSz<unsigned char> PtrStepSzb;
typedef PtrStepSz<float> PtrStepSzf;
typedef PtrStepSz<int> PtrStepSzi;
typedef PtrStep<unsigned char> PtrStepb;
typedef PtrStep<float> PtrStepf;
typedef PtrStep<int> PtrStepi;
}
}
//! @endcond
#endif /* __OPENCV_CORE_CUDA_TYPES_HPP__ */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_CVDEF_H__
#define __OPENCV_CORE_CVDEF_H__
//! @addtogroup core_utils
//! @{
#if !defined _CRT_SECURE_NO_DEPRECATE && defined _MSC_VER && _MSC_VER > 1300
# define _CRT_SECURE_NO_DEPRECATE /* to avoid multiple Visual Studio warnings */
#endif
// undef problematic defines sometimes defined by system headers (windows.h in particular)
#undef small
#undef min
#undef max
#undef abs
#undef Complex
#if !defined _CRT_SECURE_NO_DEPRECATE && defined _MSC_VER && _MSC_VER > 1300
# define _CRT_SECURE_NO_DEPRECATE /* to avoid multiple Visual Studio warnings */
#endif
#include <limits.h>
#include "opencv2/core/hal/interface.h"
#if defined __ICL
# define CV_ICC __ICL
#elif defined __ICC
# define CV_ICC __ICC
#elif defined __ECL
# define CV_ICC __ECL
#elif defined __ECC
# define CV_ICC __ECC
#elif defined __INTEL_COMPILER
# define CV_ICC __INTEL_COMPILER
#endif
#ifndef CV_INLINE
# if defined __cplusplus
# define CV_INLINE static inline
# elif defined _MSC_VER
# define CV_INLINE __inline
# else
# define CV_INLINE static
# endif
#endif
#if defined CV_ICC && !defined CV_ENABLE_UNROLLED
# define CV_ENABLE_UNROLLED 0
#else
# define CV_ENABLE_UNROLLED 1
#endif
#ifdef __GNUC__
# define CV_DECL_ALIGNED(x) __attribute__ ((aligned (x)))
#elif defined _MSC_VER
# define CV_DECL_ALIGNED(x) __declspec(align(x))
#else
# define CV_DECL_ALIGNED(x)
#endif
/* CPU features and intrinsics support */
#define CV_CPU_NONE 0
#define CV_CPU_MMX 1
#define CV_CPU_SSE 2
#define CV_CPU_SSE2 3
#define CV_CPU_SSE3 4
#define CV_CPU_SSSE3 5
#define CV_CPU_SSE4_1 6
#define CV_CPU_SSE4_2 7
#define CV_CPU_POPCNT 8
#define CV_CPU_AVX 10
#define CV_CPU_AVX2 11
#define CV_CPU_FMA3 12
#define CV_CPU_AVX_512F 13
#define CV_CPU_AVX_512BW 14
#define CV_CPU_AVX_512CD 15
#define CV_CPU_AVX_512DQ 16
#define CV_CPU_AVX_512ER 17
#define CV_CPU_AVX_512IFMA512 18
#define CV_CPU_AVX_512PF 19
#define CV_CPU_AVX_512VBMI 20
#define CV_CPU_AVX_512VL 21
#define CV_CPU_NEON 100
// when adding to this list remember to update the following enum
#define CV_HARDWARE_MAX_FEATURE 255
/** @brief Available CPU features.
*/
enum CpuFeatures {
CPU_MMX = 1,
CPU_SSE = 2,
CPU_SSE2 = 3,
CPU_SSE3 = 4,
CPU_SSSE3 = 5,
CPU_SSE4_1 = 6,
CPU_SSE4_2 = 7,
CPU_POPCNT = 8,
CPU_AVX = 10,
CPU_AVX2 = 11,
CPU_FMA3 = 12,
CPU_AVX_512F = 13,
CPU_AVX_512BW = 14,
CPU_AVX_512CD = 15,
CPU_AVX_512DQ = 16,
CPU_AVX_512ER = 17,
CPU_AVX_512IFMA512 = 18,
CPU_AVX_512PF = 19,
CPU_AVX_512VBMI = 20,
CPU_AVX_512VL = 21,
CPU_NEON = 100
};
// do not include SSE/AVX/NEON headers for NVCC compiler
#ifndef __CUDACC__
#if defined __SSE2__ || defined _M_X64 || (defined _M_IX86_FP && _M_IX86_FP >= 2)
# include <emmintrin.h>
# define CV_MMX 1
# define CV_SSE 1
# define CV_SSE2 1
# if defined __SSE3__ || (defined _MSC_VER && _MSC_VER >= 1500)
# include <pmmintrin.h>
# define CV_SSE3 1
# endif
# if defined __SSSE3__ || (defined _MSC_VER && _MSC_VER >= 1500)
# include <tmmintrin.h>
# define CV_SSSE3 1
# endif
# if defined __SSE4_1__ || (defined _MSC_VER && _MSC_VER >= 1500)
# include <smmintrin.h>
# define CV_SSE4_1 1
# endif
# if defined __SSE4_2__ || (defined _MSC_VER && _MSC_VER >= 1500)
# include <nmmintrin.h>
# define CV_SSE4_2 1
# endif
# if defined __POPCNT__ || (defined _MSC_VER && _MSC_VER >= 1500)
# ifdef _MSC_VER
# include <nmmintrin.h>
# else
# include <popcntintrin.h>
# endif
# define CV_POPCNT 1
# endif
# if defined __AVX__ || (defined _MSC_VER && _MSC_VER >= 1600 && 0)
// MS Visual Studio 2010 (2012?) has no macro pre-defined to identify the use of /arch:AVX
// See: http://connect.microsoft.com/VisualStudio/feedback/details/605858/arch-avx-should-define-a-predefined-macro-in-x64-and-set-a-unique-value-for-m-ix86-fp-in-win32
# include <immintrin.h>
# define CV_AVX 1
# if defined(_XCR_XFEATURE_ENABLED_MASK)
# define __xgetbv() _xgetbv(_XCR_XFEATURE_ENABLED_MASK)
# else
# define __xgetbv() 0
# endif
# endif
# if defined __AVX2__ || (defined _MSC_VER && _MSC_VER >= 1800 && 0)
# include <immintrin.h>
# define CV_AVX2 1
# if defined __FMA__
# define CV_FMA3 1
# endif
# endif
#endif
#if (defined WIN32 || defined _WIN32) && defined(_M_ARM)
# include <Intrin.h>
# include "arm_neon.h"
# define CV_NEON 1
# define CPU_HAS_NEON_FEATURE (true)
#elif defined(__ARM_NEON__) || (defined (__ARM_NEON) && defined(__aarch64__))
# include <arm_neon.h>
# define CV_NEON 1
#endif
#if defined __GNUC__ && defined __arm__ && (defined __ARM_PCS_VFP || defined __ARM_VFPV3__ || defined __ARM_NEON__) && !defined __SOFTFP__
# define CV_VFP 1
#endif
#endif // __CUDACC__
#ifndef CV_POPCNT
#define CV_POPCNT 0
#endif
#ifndef CV_MMX
# define CV_MMX 0
#endif
#ifndef CV_SSE
# define CV_SSE 0
#endif
#ifndef CV_SSE2
# define CV_SSE2 0
#endif
#ifndef CV_SSE3
# define CV_SSE3 0
#endif
#ifndef CV_SSSE3
# define CV_SSSE3 0
#endif
#ifndef CV_SSE4_1
# define CV_SSE4_1 0
#endif
#ifndef CV_SSE4_2
# define CV_SSE4_2 0
#endif
#ifndef CV_AVX
# define CV_AVX 0
#endif
#ifndef CV_AVX2
# define CV_AVX2 0
#endif
#ifndef CV_FMA3
# define CV_FMA3 0
#endif
#ifndef CV_AVX_512F
# define CV_AVX_512F 0
#endif
#ifndef CV_AVX_512BW
# define CV_AVX_512BW 0
#endif
#ifndef CV_AVX_512CD
# define CV_AVX_512CD 0
#endif
#ifndef CV_AVX_512DQ
# define CV_AVX_512DQ 0
#endif
#ifndef CV_AVX_512ER
# define CV_AVX_512ER 0
#endif
#ifndef CV_AVX_512IFMA512
# define CV_AVX_512IFMA512 0
#endif
#ifndef CV_AVX_512PF
# define CV_AVX_512PF 0
#endif
#ifndef CV_AVX_512VBMI
# define CV_AVX_512VBMI 0
#endif
#ifndef CV_AVX_512VL
# define CV_AVX_512VL 0
#endif
#ifndef CV_NEON
# define CV_NEON 0
#endif
#ifndef CV_VFP
# define CV_VFP 0
#endif
/* fundamental constants */
#define CV_PI 3.1415926535897932384626433832795
#define CV_2PI 6.283185307179586476925286766559
#define CV_LOG2 0.69314718055994530941723212145818
typedef union Cv32suf
{
int i;
unsigned u;
float f;
}
Cv32suf;
typedef union Cv64suf
{
int64 i;
uint64 u;
double f;
}
Cv64suf;
#define OPENCV_ABI_COMPATIBILITY 300
#ifdef __OPENCV_BUILD
# define DISABLE_OPENCV_24_COMPATIBILITY
#endif
#if (defined WIN32 || defined _WIN32 || defined WINCE || defined __CYGWIN__) && defined CVAPI_EXPORTS
# define CV_EXPORTS __declspec(dllexport)
#elif defined __GNUC__ && __GNUC__ >= 4
# define CV_EXPORTS __attribute__ ((visibility ("default")))
#else
# define CV_EXPORTS
#endif
#ifndef CV_EXTERN_C
# ifdef __cplusplus
# define CV_EXTERN_C extern "C"
# else
# define CV_EXTERN_C
# endif
#endif
/* special informative macros for wrapper generators */
#define CV_EXPORTS_W CV_EXPORTS
#define CV_EXPORTS_W_SIMPLE CV_EXPORTS
#define CV_EXPORTS_AS(synonym) CV_EXPORTS
#define CV_EXPORTS_W_MAP CV_EXPORTS
#define CV_IN_OUT
#define CV_OUT
#define CV_PROP
#define CV_PROP_RW
#define CV_WRAP
#define CV_WRAP_AS(synonym)
/****************************************************************************************\
* Matrix type (Mat) *
\****************************************************************************************/
#define CV_CN_MAX 512
#define CV_CN_SHIFT 3
#define CV_DEPTH_MAX (1 << CV_CN_SHIFT)
#define CV_8U 0
#define CV_8S 1
#define CV_16U 2
#define CV_16S 3
#define CV_32S 4
#define CV_32F 5
#define CV_64F 6
#define CV_USRTYPE1 7
#define CV_MAT_DEPTH_MASK (CV_DEPTH_MAX - 1)
#define CV_MAT_DEPTH(flags) ((flags) & CV_MAT_DEPTH_MASK)
#define CV_MAKETYPE(depth,cn) (CV_MAT_DEPTH(depth) + (((cn)-1) << CV_CN_SHIFT))
#define CV_MAKE_TYPE CV_MAKETYPE
#define CV_8UC1 CV_MAKETYPE(CV_8U,1)
#define CV_8UC2 CV_MAKETYPE(CV_8U,2)
#define CV_8UC3 CV_MAKETYPE(CV_8U,3)
#define CV_8UC4 CV_MAKETYPE(CV_8U,4)
#define CV_8UC(n) CV_MAKETYPE(CV_8U,(n))
#define CV_8SC1 CV_MAKETYPE(CV_8S,1)
#define CV_8SC2 CV_MAKETYPE(CV_8S,2)
#define CV_8SC3 CV_MAKETYPE(CV_8S,3)
#define CV_8SC4 CV_MAKETYPE(CV_8S,4)
#define CV_8SC(n) CV_MAKETYPE(CV_8S,(n))
#define CV_16UC1 CV_MAKETYPE(CV_16U,1)
#define CV_16UC2 CV_MAKETYPE(CV_16U,2)
#define CV_16UC3 CV_MAKETYPE(CV_16U,3)
#define CV_16UC4 CV_MAKETYPE(CV_16U,4)
#define CV_16UC(n) CV_MAKETYPE(CV_16U,(n))
#define CV_16SC1 CV_MAKETYPE(CV_16S,1)
#define CV_16SC2 CV_MAKETYPE(CV_16S,2)
#define CV_16SC3 CV_MAKETYPE(CV_16S,3)
#define CV_16SC4 CV_MAKETYPE(CV_16S,4)
#define CV_16SC(n) CV_MAKETYPE(CV_16S,(n))
#define CV_32SC1 CV_MAKETYPE(CV_32S,1)
#define CV_32SC2 CV_MAKETYPE(CV_32S,2)
#define CV_32SC3 CV_MAKETYPE(CV_32S,3)
#define CV_32SC4 CV_MAKETYPE(CV_32S,4)
#define CV_32SC(n) CV_MAKETYPE(CV_32S,(n))
#define CV_32FC1 CV_MAKETYPE(CV_32F,1)
#define CV_32FC2 CV_MAKETYPE(CV_32F,2)
#define CV_32FC3 CV_MAKETYPE(CV_32F,3)
#define CV_32FC4 CV_MAKETYPE(CV_32F,4)
#define CV_32FC(n) CV_MAKETYPE(CV_32F,(n))
#define CV_64FC1 CV_MAKETYPE(CV_64F,1)
#define CV_64FC2 CV_MAKETYPE(CV_64F,2)
#define CV_64FC3 CV_MAKETYPE(CV_64F,3)
#define CV_64FC4 CV_MAKETYPE(CV_64F,4)
#define CV_64FC(n) CV_MAKETYPE(CV_64F,(n))
#define CV_MAT_CN_MASK ((CV_CN_MAX - 1) << CV_CN_SHIFT)
#define CV_MAT_CN(flags) ((((flags) & CV_MAT_CN_MASK) >> CV_CN_SHIFT) + 1)
#define CV_MAT_TYPE_MASK (CV_DEPTH_MAX*CV_CN_MAX - 1)
#define CV_MAT_TYPE(flags) ((flags) & CV_MAT_TYPE_MASK)
#define CV_MAT_CONT_FLAG_SHIFT 14
#define CV_MAT_CONT_FLAG (1 << CV_MAT_CONT_FLAG_SHIFT)
#define CV_IS_MAT_CONT(flags) ((flags) & CV_MAT_CONT_FLAG)
#define CV_IS_CONT_MAT CV_IS_MAT_CONT
#define CV_SUBMAT_FLAG_SHIFT 15
#define CV_SUBMAT_FLAG (1 << CV_SUBMAT_FLAG_SHIFT)
#define CV_IS_SUBMAT(flags) ((flags) & CV_MAT_SUBMAT_FLAG)
/** Size of each channel item,
0x124489 = 1000 0100 0100 0010 0010 0001 0001 ~ array of sizeof(arr_type_elem) */
#define CV_ELEM_SIZE1(type) \
((((sizeof(size_t)<<28)|0x8442211) >> CV_MAT_DEPTH(type)*4) & 15)
/** 0x3a50 = 11 10 10 01 01 00 00 ~ array of log2(sizeof(arr_type_elem)) */
#define CV_ELEM_SIZE(type) \
(CV_MAT_CN(type) << ((((sizeof(size_t)/4+1)*16384|0x3a50) >> CV_MAT_DEPTH(type)*2) & 3))
#ifndef MIN
# define MIN(a,b) ((a) > (b) ? (b) : (a))
#endif
#ifndef MAX
# define MAX(a,b) ((a) < (b) ? (b) : (a))
#endif
/****************************************************************************************\
* exchange-add operation for atomic operations on reference counters *
\****************************************************************************************/
#if defined __INTEL_COMPILER && !(defined WIN32 || defined _WIN32)
// atomic increment on the linux version of the Intel(tm) compiler
# define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd(const_cast<void*>(reinterpret_cast<volatile void*>(addr)), delta)
#elif defined __GNUC__
# if defined __clang__ && __clang_major__ >= 3 && !defined __ANDROID__ && !defined __EMSCRIPTEN__ && !defined(__CUDACC__)
# ifdef __ATOMIC_ACQ_REL
# define CV_XADD(addr, delta) __c11_atomic_fetch_add((_Atomic(int)*)(addr), delta, __ATOMIC_ACQ_REL)
# else
# define CV_XADD(addr, delta) __atomic_fetch_add((_Atomic(int)*)(addr), delta, 4)
# endif
# else
# if defined __ATOMIC_ACQ_REL && !defined __clang__
// version for gcc >= 4.7
# define CV_XADD(addr, delta) (int)__atomic_fetch_add((unsigned*)(addr), (unsigned)(delta), __ATOMIC_ACQ_REL)
# else
# define CV_XADD(addr, delta) (int)__sync_fetch_and_add((unsigned*)(addr), (unsigned)(delta))
# endif
# endif
#elif defined _MSC_VER && !defined RC_INVOKED
# include <intrin.h>
# define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd((long volatile*)addr, delta)
#else
CV_INLINE CV_XADD(int* addr, int delta) { int tmp = *addr; *addr += delta; return tmp; }
#endif
/****************************************************************************************\
* CV_NORETURN attribute *
\****************************************************************************************/
#ifndef CV_NORETURN
# if defined(__GNUC__)
# define CV_NORETURN __attribute__((__noreturn__))
# elif defined(_MSC_VER) && (_MSC_VER >= 1300)
# define CV_NORETURN __declspec(noreturn)
# else
# define CV_NORETURN /* nothing by default */
# endif
#endif
/****************************************************************************************\
* C++ Move semantics *
\****************************************************************************************/
#ifndef CV_CXX_MOVE_SEMANTICS
# if __cplusplus >= 201103L || defined(__GXX_EXPERIMENTAL_CXX0X__) || defined(_MSC_VER) && _MSC_VER >= 1600
# define CV_CXX_MOVE_SEMANTICS 1
# elif defined(__clang)
# if __has_feature(cxx_rvalue_references)
# define CV_CXX_MOVE_SEMANTICS 1
# endif
# endif
#else
# if CV_CXX_MOVE_SEMANTICS == 0
# undef CV_CXX_MOVE_SEMANTICS
# endif
#endif
//! @}
#endif // __OPENCV_CORE_CVDEF_H__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_CVSTDINL_HPP__
#define __OPENCV_CORE_CVSTDINL_HPP__
#ifndef OPENCV_NOSTL
# include <complex>
# include <ostream>
#endif
//! @cond IGNORED
namespace cv
{
#ifndef OPENCV_NOSTL
template<typename _Tp> class DataType< std::complex<_Tp> >
{
public:
typedef std::complex<_Tp> value_type;
typedef value_type work_type;
typedef _Tp channel_type;
enum { generic_type = 0,
depth = DataType<channel_type>::depth,
channels = 2,
fmt = DataType<channel_type>::fmt + ((channels - 1) << 8),
type = CV_MAKETYPE(depth, channels) };
typedef Vec<channel_type, channels> vec_type;
};
inline
String::String(const std::string& str)
: cstr_(0), len_(0)
{
if (!str.empty())
{
size_t len = str.size();
memcpy(allocate(len), str.c_str(), len);
}
}
inline
String::String(const std::string& str, size_t pos, size_t len)
: cstr_(0), len_(0)
{
size_t strlen = str.size();
pos = min(pos, strlen);
len = min(strlen - pos, len);
if (!len) return;
memcpy(allocate(len), str.c_str() + pos, len);
}
inline
String& String::operator = (const std::string& str)
{
deallocate();
if (!str.empty())
{
size_t len = str.size();
memcpy(allocate(len), str.c_str(), len);
}
return *this;
}
inline
String& String::operator += (const std::string& str)
{
*this = *this + str;
return *this;
}
inline
String::operator std::string() const
{
return std::string(cstr_, len_);
}
inline
String operator + (const String& lhs, const std::string& rhs)
{
String s;
size_t rhslen = rhs.size();
s.allocate(lhs.len_ + rhslen);
memcpy(s.cstr_, lhs.cstr_, lhs.len_);
memcpy(s.cstr_ + lhs.len_, rhs.c_str(), rhslen);
return s;
}
inline
String operator + (const std::string& lhs, const String& rhs)
{
String s;
size_t lhslen = lhs.size();
s.allocate(lhslen + rhs.len_);
memcpy(s.cstr_, lhs.c_str(), lhslen);
memcpy(s.cstr_ + lhslen, rhs.cstr_, rhs.len_);
return s;
}
inline
FileNode::operator std::string() const
{
String value;
read(*this, value, value);
return value;
}
template<> inline
void operator >> (const FileNode& n, std::string& value)
{
String val;
read(n, val, val);
value = val;
}
template<> inline
FileStorage& operator << (FileStorage& fs, const std::string& value)
{
return fs << cv::String(value);
}
static inline
std::ostream& operator << (std::ostream& os, const String& str)
{
return os << str.c_str();
}
static inline
std::ostream& operator << (std::ostream& out, Ptr<Formatted> fmtd)
{
fmtd->reset();
for(const char* str = fmtd->next(); str; str = fmtd->next())
out << str;
return out;
}
static inline
std::ostream& operator << (std::ostream& out, const Mat& mtx)
{
return out << Formatter::get()->format(mtx);
}
template<typename _Tp> static inline
std::ostream& operator << (std::ostream& out, const std::vector<Point_<_Tp> >& vec)
{
return out << Formatter::get()->format(Mat(vec));
}
template<typename _Tp> static inline
std::ostream& operator << (std::ostream& out, const std::vector<Point3_<_Tp> >& vec)
{
return out << Formatter::get()->format(Mat(vec));
}
template<typename _Tp, int m, int n> static inline
std::ostream& operator << (std::ostream& out, const Matx<_Tp, m, n>& matx)
{
return out << Formatter::get()->format(Mat(matx));
}
template<typename _Tp> static inline
std::ostream& operator << (std::ostream& out, const Point_<_Tp>& p)
{
out << "[" << p.x << ", " << p.y << "]";
return out;
}
template<typename _Tp> static inline
std::ostream& operator << (std::ostream& out, const Point3_<_Tp>& p)
{
out << "[" << p.x << ", " << p.y << ", " << p.z << "]";
return out;
}
template<typename _Tp, int n> static inline
std::ostream& operator << (std::ostream& out, const Vec<_Tp, n>& vec)
{
out << "[";
#ifdef _MSC_VER
#pragma warning( push )
#pragma warning( disable: 4127 )
#endif
if(Vec<_Tp, n>::depth < CV_32F)
#ifdef _MSC_VER
#pragma warning( pop )
#endif
{
for (int i = 0; i < n - 1; ++i) {
out << (int)vec[i] << ", ";
}
out << (int)vec[n-1] << "]";
}
else
{
for (int i = 0; i < n - 1; ++i) {
out << vec[i] << ", ";
}
out << vec[n-1] << "]";
}
return out;
}
template<typename _Tp> static inline
std::ostream& operator << (std::ostream& out, const Size_<_Tp>& size)
{
return out << "[" << size.width << " x " << size.height << "]";
}
template<typename _Tp> static inline
std::ostream& operator << (std::ostream& out, const Rect_<_Tp>& rect)
{
return out << "[" << rect.width << " x " << rect.height << " from (" << rect.x << ", " << rect.y << ")]";
}
#endif // OPENCV_NOSTL
} // cv
//! @endcond
#endif // __OPENCV_CORE_CVSTDINL_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors as is and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the copyright holders or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_DIRECTX_HPP__
#define __OPENCV_CORE_DIRECTX_HPP__
#include "mat.hpp"
#include "ocl.hpp"
#if !defined(__d3d11_h__)
struct ID3D11Device;
struct ID3D11Texture2D;
#endif
#if !defined(__d3d10_h__)
struct ID3D10Device;
struct ID3D10Texture2D;
#endif
#if !defined(_D3D9_H_)
struct IDirect3DDevice9;
struct IDirect3DDevice9Ex;
struct IDirect3DSurface9;
#endif
namespace cv { namespace directx {
namespace ocl {
using namespace cv::ocl;
//! @addtogroup core_directx
// This section describes OpenCL and DirectX interoperability.
//
// To enable DirectX support, configure OpenCV using CMake with WITH_DIRECTX=ON . Note, DirectX is
// supported only on Windows.
//
// To use OpenCL functionality you should first initialize OpenCL context from DirectX resource.
//
//! @{
// TODO static functions in the Context class
//! @brief Creates OpenCL context from D3D11 device
//
//! @param pD3D11Device - pointer to D3D11 device
//! @return Returns reference to OpenCL Context
CV_EXPORTS Context& initializeContextFromD3D11Device(ID3D11Device* pD3D11Device);
//! @brief Creates OpenCL context from D3D10 device
//
//! @param pD3D10Device - pointer to D3D10 device
//! @return Returns reference to OpenCL Context
CV_EXPORTS Context& initializeContextFromD3D10Device(ID3D10Device* pD3D10Device);
//! @brief Creates OpenCL context from Direct3DDevice9Ex device
//
//! @param pDirect3DDevice9Ex - pointer to Direct3DDevice9Ex device
//! @return Returns reference to OpenCL Context
CV_EXPORTS Context& initializeContextFromDirect3DDevice9Ex(IDirect3DDevice9Ex* pDirect3DDevice9Ex);
//! @brief Creates OpenCL context from Direct3DDevice9 device
//
//! @param pDirect3DDevice9 - pointer to Direct3Device9 device
//! @return Returns reference to OpenCL Context
CV_EXPORTS Context& initializeContextFromDirect3DDevice9(IDirect3DDevice9* pDirect3DDevice9);
//! @}
} // namespace cv::directx::ocl
//! @addtogroup core_directx
//! @{
//! @brief Converts InputArray to ID3D11Texture2D. If destination texture format is DXGI_FORMAT_NV12 then
//! input UMat expected to be in BGR format and data will be downsampled and color-converted to NV12.
//
//! @note Note: Destination texture must be allocated by application. Function does memory copy from src to
//! pD3D11Texture2D
//
//! @param src - source InputArray
//! @param pD3D11Texture2D - destination D3D11 texture
CV_EXPORTS void convertToD3D11Texture2D(InputArray src, ID3D11Texture2D* pD3D11Texture2D);
//! @brief Converts ID3D11Texture2D to OutputArray. If input texture format is DXGI_FORMAT_NV12 then
//! data will be upsampled and color-converted to BGR format.
//
//! @note Note: Destination matrix will be re-allocated if it has not enough memory to match texture size.
//! function does memory copy from pD3D11Texture2D to dst
//
//! @param pD3D11Texture2D - source D3D11 texture
//! @param dst - destination OutputArray
CV_EXPORTS void convertFromD3D11Texture2D(ID3D11Texture2D* pD3D11Texture2D, OutputArray dst);
//! @brief Converts InputArray to ID3D10Texture2D
//
//! @note Note: function does memory copy from src to
//! pD3D10Texture2D
//
//! @param src - source InputArray
//! @param pD3D10Texture2D - destination D3D10 texture
CV_EXPORTS void convertToD3D10Texture2D(InputArray src, ID3D10Texture2D* pD3D10Texture2D);
//! @brief Converts ID3D10Texture2D to OutputArray
//
//! @note Note: function does memory copy from pD3D10Texture2D
//! to dst
//
//! @param pD3D10Texture2D - source D3D10 texture
//! @param dst - destination OutputArray
CV_EXPORTS void convertFromD3D10Texture2D(ID3D10Texture2D* pD3D10Texture2D, OutputArray dst);
//! @brief Converts InputArray to IDirect3DSurface9
//
//! @note Note: function does memory copy from src to
//! pDirect3DSurface9
//
//! @param src - source InputArray
//! @param pDirect3DSurface9 - destination D3D10 texture
//! @param surfaceSharedHandle - shared handle
CV_EXPORTS void convertToDirect3DSurface9(InputArray src, IDirect3DSurface9* pDirect3DSurface9, void* surfaceSharedHandle = NULL);
//! @brief Converts IDirect3DSurface9 to OutputArray
//
//! @note Note: function does memory copy from pDirect3DSurface9
//! to dst
//
//! @param pDirect3DSurface9 - source D3D10 texture
//! @param dst - destination OutputArray
//! @param surfaceSharedHandle - shared handle
CV_EXPORTS void convertFromDirect3DSurface9(IDirect3DSurface9* pDirect3DSurface9, OutputArray dst, void* surfaceSharedHandle = NULL);
//! @brief Get OpenCV type from DirectX type
//! @param iDXGI_FORMAT - enum DXGI_FORMAT for D3D10/D3D11
//! @return OpenCV type or -1 if there is no equivalent
CV_EXPORTS int getTypeFromDXGI_FORMAT(const int iDXGI_FORMAT); // enum DXGI_FORMAT for D3D10/D3D11
//! @brief Get OpenCV type from DirectX type
//! @param iD3DFORMAT - enum D3DTYPE for D3D9
//! @return OpenCV type or -1 if there is no equivalent
CV_EXPORTS int getTypeFromD3DFORMAT(const int iD3DFORMAT); // enum D3DTYPE for D3D9
//! @}
} } // namespace cv::directx
#endif // __OPENCV_CORE_DIRECTX_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_EIGEN_HPP__
#define __OPENCV_CORE_EIGEN_HPP__
#include "opencv2/core.hpp"
#if defined _MSC_VER && _MSC_VER >= 1200
#pragma warning( disable: 4714 ) //__forceinline is not inlined
#pragma warning( disable: 4127 ) //conditional expression is constant
#pragma warning( disable: 4244 ) //conversion from '__int64' to 'int', possible loss of data
#endif
namespace cv
{
//! @addtogroup core_eigen
//! @{
template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
void eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src, Mat& dst )
{
if( !(src.Flags & Eigen::RowMajorBit) )
{
Mat _src(src.cols(), src.rows(), DataType<_Tp>::type,
(void*)src.data(), src.stride()*sizeof(_Tp));
transpose(_src, dst);
}
else
{
Mat _src(src.rows(), src.cols(), DataType<_Tp>::type,
(void*)src.data(), src.stride()*sizeof(_Tp));
_src.copyTo(dst);
}
}
// Matx case
template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
void eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src,
Matx<_Tp, _rows, _cols>& dst )
{
if( !(src.Flags & Eigen::RowMajorBit) )
{
dst = Matx<_Tp, _cols, _rows>(static_cast<const _Tp*>(src.data())).t();
}
else
{
dst = Matx<_Tp, _rows, _cols>(static_cast<const _Tp*>(src.data()));
}
}
template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
void cv2eigen( const Mat& src,
Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst )
{
CV_DbgAssert(src.rows == _rows && src.cols == _cols);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(src.cols, src.rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
if( src.type() == _dst.type() )
transpose(src, _dst);
else if( src.cols == src.rows )
{
src.convertTo(_dst, _dst.type());
transpose(_dst, _dst);
}
else
Mat(src.t()).convertTo(_dst, _dst.type());
}
else
{
const Mat _dst(src.rows, src.cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
src.convertTo(_dst, _dst.type());
}
}
// Matx case
template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
void cv2eigen( const Matx<_Tp, _rows, _cols>& src,
Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst )
{
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(_cols, _rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
transpose(src, _dst);
}
else
{
const Mat _dst(_rows, _cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
Mat(src).copyTo(_dst);
}
}
template<typename _Tp> static inline
void cv2eigen( const Mat& src,
Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst )
{
dst.resize(src.rows, src.cols);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(src.cols, src.rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
if( src.type() == _dst.type() )
transpose(src, _dst);
else if( src.cols == src.rows )
{
src.convertTo(_dst, _dst.type());
transpose(_dst, _dst);
}
else
Mat(src.t()).convertTo(_dst, _dst.type());
}
else
{
const Mat _dst(src.rows, src.cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
src.convertTo(_dst, _dst.type());
}
}
// Matx case
template<typename _Tp, int _rows, int _cols> static inline
void cv2eigen( const Matx<_Tp, _rows, _cols>& src,
Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst )
{
dst.resize(_rows, _cols);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(_cols, _rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
transpose(src, _dst);
}
else
{
const Mat _dst(_rows, _cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
Mat(src).copyTo(_dst);
}
}
template<typename _Tp> static inline
void cv2eigen( const Mat& src,
Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst )
{
CV_Assert(src.cols == 1);
dst.resize(src.rows);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(src.cols, src.rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
if( src.type() == _dst.type() )
transpose(src, _dst);
else
Mat(src.t()).convertTo(_dst, _dst.type());
}
else
{
const Mat _dst(src.rows, src.cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
src.convertTo(_dst, _dst.type());
}
}
// Matx case
template<typename _Tp, int _rows> static inline
void cv2eigen( const Matx<_Tp, _rows, 1>& src,
Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst )
{
dst.resize(_rows);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(1, _rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
transpose(src, _dst);
}
else
{
const Mat _dst(_rows, 1, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
src.copyTo(_dst);
}
}
template<typename _Tp> static inline
void cv2eigen( const Mat& src,
Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst )
{
CV_Assert(src.rows == 1);
dst.resize(src.cols);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(src.cols, src.rows, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
if( src.type() == _dst.type() )
transpose(src, _dst);
else
Mat(src.t()).convertTo(_dst, _dst.type());
}
else
{
const Mat _dst(src.rows, src.cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
src.convertTo(_dst, _dst.type());
}
}
//Matx
template<typename _Tp, int _cols> static inline
void cv2eigen( const Matx<_Tp, 1, _cols>& src,
Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst )
{
dst.resize(_cols);
if( !(dst.Flags & Eigen::RowMajorBit) )
{
const Mat _dst(_cols, 1, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
transpose(src, _dst);
}
else
{
const Mat _dst(1, _cols, DataType<_Tp>::type,
dst.data(), (size_t)(dst.stride()*sizeof(_Tp)));
Mat(src).copyTo(_dst);
}
}
//! @}
} // cv
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_FAST_MATH_HPP__
#define __OPENCV_CORE_FAST_MATH_HPP__
#include "opencv2/core/cvdef.h"
//! @addtogroup core_utils
//! @{
/****************************************************************************************\
* fast math *
\****************************************************************************************/
#if defined __BORLANDC__
# include <fastmath.h>
#elif defined __cplusplus
# include <cmath>
#else
# include <math.h>
#endif
#ifdef HAVE_TEGRA_OPTIMIZATION
# include "tegra_round.hpp"
#endif
#if CV_VFP
// 1. general scheme
#define ARM_ROUND(_value, _asm_string) \
int res; \
float temp; \
asm(_asm_string : [res] "=r" (res), [temp] "=w" (temp) : [value] "w" (_value)); \
return res
// 2. version for double
#ifdef __clang__
#define ARM_ROUND_DBL(value) ARM_ROUND(value, "vcvtr.s32.f64 %[temp], %[value] \n vmov %[res], %[temp]")
#else
#define ARM_ROUND_DBL(value) ARM_ROUND(value, "vcvtr.s32.f64 %[temp], %P[value] \n vmov %[res], %[temp]")
#endif
// 3. version for float
#define ARM_ROUND_FLT(value) ARM_ROUND(value, "vcvtr.s32.f32 %[temp], %[value]\n vmov %[res], %[temp]")
#endif // CV_VFP
/** @brief Rounds floating-point number to the nearest integer
@param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the
result is not defined.
*/
CV_INLINE int
cvRound( double value )
{
#if ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __x86_64__ \
&& defined __SSE2__ && !defined __APPLE__)) && !defined(__CUDACC__)
__m128d t = _mm_set_sd( value );
return _mm_cvtsd_si32(t);
#elif defined _MSC_VER && defined _M_IX86
int t;
__asm
{
fld value;
fistp t;
}
return t;
#elif ((defined _MSC_VER && defined _M_ARM) || defined CV_ICC || \
defined __GNUC__) && defined HAVE_TEGRA_OPTIMIZATION
TEGRA_ROUND_DBL(value);
#elif defined CV_ICC || defined __GNUC__
# if CV_VFP
ARM_ROUND_DBL(value);
# else
return (int)lrint(value);
# endif
#else
/* it's ok if round does not comply with IEEE754 standard;
the tests should allow +/-1 difference when the tested functions use round */
return (int)(value + (value >= 0 ? 0.5 : -0.5));
#endif
}
/** @brief Rounds floating-point number to the nearest integer not larger than the original.
The function computes an integer i such that:
\f[i \le \texttt{value} < i+1\f]
@param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the
result is not defined.
*/
CV_INLINE int cvFloor( double value )
{
#if (defined _MSC_VER && defined _M_X64 || (defined __GNUC__ && defined __SSE2__ && !defined __APPLE__)) && !defined(__CUDACC__)
__m128d t = _mm_set_sd( value );
int i = _mm_cvtsd_si32(t);
return i - _mm_movemask_pd(_mm_cmplt_sd(t, _mm_cvtsi32_sd(t,i)));
#elif defined __GNUC__
int i = (int)value;
return i - (i > value);
#else
int i = cvRound(value);
float diff = (float)(value - i);
return i - (diff < 0);
#endif
}
/** @brief Rounds floating-point number to the nearest integer not smaller than the original.
The function computes an integer i such that:
\f[i \le \texttt{value} < i+1\f]
@param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the
result is not defined.
*/
CV_INLINE int cvCeil( double value )
{
#if (defined _MSC_VER && defined _M_X64 || (defined __GNUC__ && defined __SSE2__&& !defined __APPLE__)) && !defined(__CUDACC__)
__m128d t = _mm_set_sd( value );
int i = _mm_cvtsd_si32(t);
return i + _mm_movemask_pd(_mm_cmplt_sd(_mm_cvtsi32_sd(t,i), t));
#elif defined __GNUC__
int i = (int)value;
return i + (i < value);
#else
int i = cvRound(value);
float diff = (float)(i - value);
return i + (diff < 0);
#endif
}
/** @brief Determines if the argument is Not A Number.
@param value The input floating-point value
The function returns 1 if the argument is Not A Number (as defined by IEEE754 standard), 0
otherwise. */
CV_INLINE int cvIsNaN( double value )
{
Cv64suf ieee754;
ieee754.f = value;
return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) +
((unsigned)ieee754.u != 0) > 0x7ff00000;
}
/** @brief Determines if the argument is Infinity.
@param value The input floating-point value
The function returns 1 if the argument is a plus or minus infinity (as defined by IEEE754 standard)
and 0 otherwise. */
CV_INLINE int cvIsInf( double value )
{
Cv64suf ieee754;
ieee754.f = value;
return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) == 0x7ff00000 &&
(unsigned)ieee754.u == 0;
}
#ifdef __cplusplus
/** @overload */
CV_INLINE int cvRound(float value)
{
#if ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __x86_64__ && \
defined __SSE2__ && !defined __APPLE__)) && !defined(__CUDACC__)
__m128 t = _mm_set_ss( value );
return _mm_cvtss_si32(t);
#elif defined _MSC_VER && defined _M_IX86
int t;
__asm
{
fld value;
fistp t;
}
return t;
#elif ((defined _MSC_VER && defined _M_ARM) || defined CV_ICC || \
defined __GNUC__) && defined HAVE_TEGRA_OPTIMIZATION
TEGRA_ROUND_FLT(value);
#elif defined CV_ICC || defined __GNUC__
# if CV_VFP
ARM_ROUND_FLT(value);
# else
return (int)lrintf(value);
# endif
#else
/* it's ok if round does not comply with IEEE754 standard;
the tests should allow +/-1 difference when the tested functions use round */
return (int)(value + (value >= 0 ? 0.5f : -0.5f));
#endif
}
/** @overload */
CV_INLINE int cvRound( int value )
{
return value;
}
/** @overload */
CV_INLINE int cvFloor( float value )
{
#if (defined _MSC_VER && defined _M_X64 || (defined __GNUC__ && defined __SSE2__ && !defined __APPLE__)) && !defined(__CUDACC__)
__m128 t = _mm_set_ss( value );
int i = _mm_cvtss_si32(t);
return i - _mm_movemask_ps(_mm_cmplt_ss(t, _mm_cvtsi32_ss(t,i)));
#elif defined __GNUC__
int i = (int)value;
return i - (i > value);
#else
int i = cvRound(value);
float diff = (float)(value - i);
return i - (diff < 0);
#endif
}
/** @overload */
CV_INLINE int cvFloor( int value )
{
return value;
}
/** @overload */
CV_INLINE int cvCeil( float value )
{
#if (defined _MSC_VER && defined _M_X64 || (defined __GNUC__ && defined __SSE2__&& !defined __APPLE__)) && !defined(__CUDACC__)
__m128 t = _mm_set_ss( value );
int i = _mm_cvtss_si32(t);
return i + _mm_movemask_ps(_mm_cmplt_ss(_mm_cvtsi32_ss(t,i), t));
#elif defined __GNUC__
int i = (int)value;
return i + (i < value);
#else
int i = cvRound(value);
float diff = (float)(i - value);
return i + (diff < 0);
#endif
}
/** @overload */
CV_INLINE int cvCeil( int value )
{
return value;
}
/** @overload */
CV_INLINE int cvIsNaN( float value )
{
Cv32suf ieee754;
ieee754.f = value;
return (ieee754.u & 0x7fffffff) > 0x7f800000;
}
/** @overload */
CV_INLINE int cvIsInf( float value )
{
Cv32suf ieee754;
ieee754.f = value;
return (ieee754.u & 0x7fffffff) == 0x7f800000;
}
#endif // __cplusplus
//! @} core_utils
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_HAL_HPP__
#define __OPENCV_HAL_HPP__
#include "opencv2/core/cvdef.h"
#include "opencv2/core/hal/interface.h"
//! @cond IGNORED
#define CALL_HAL(name, fun, ...) \
int res = fun(__VA_ARGS__); \
if (res == CV_HAL_ERROR_OK) \
return; \
else if (res != CV_HAL_ERROR_NOT_IMPLEMENTED) \
CV_Error_(cv::Error::StsInternal, \
("HAL implementation " CVAUX_STR(name) " ==> " CVAUX_STR(fun) " returned %d (0x%08x)", res, res));
//! @endcond
namespace cv { namespace hal {
//! @addtogroup core_hal_functions
//! @{
CV_EXPORTS int normHamming(const uchar* a, int n);
CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n);
CV_EXPORTS int normHamming(const uchar* a, int n, int cellSize);
CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n, int cellSize);
CV_EXPORTS int LU32f(float* A, size_t astep, int m, float* b, size_t bstep, int n);
CV_EXPORTS int LU64f(double* A, size_t astep, int m, double* b, size_t bstep, int n);
CV_EXPORTS bool Cholesky32f(float* A, size_t astep, int m, float* b, size_t bstep, int n);
CV_EXPORTS bool Cholesky64f(double* A, size_t astep, int m, double* b, size_t bstep, int n);
CV_EXPORTS int normL1_(const uchar* a, const uchar* b, int n);
CV_EXPORTS float normL1_(const float* a, const float* b, int n);
CV_EXPORTS float normL2Sqr_(const float* a, const float* b, int n);
CV_EXPORTS void exp32f(const float* src, float* dst, int n);
CV_EXPORTS void exp64f(const double* src, double* dst, int n);
CV_EXPORTS void log32f(const float* src, float* dst, int n);
CV_EXPORTS void log64f(const double* src, double* dst, int n);
CV_EXPORTS void fastAtan2(const float* y, const float* x, float* dst, int n, bool angleInDegrees);
CV_EXPORTS void magnitude32f(const float* x, const float* y, float* dst, int n);
CV_EXPORTS void magnitude64f(const double* x, const double* y, double* dst, int n);
CV_EXPORTS void sqrt32f(const float* src, float* dst, int len);
CV_EXPORTS void sqrt64f(const double* src, double* dst, int len);
CV_EXPORTS void invSqrt32f(const float* src, float* dst, int len);
CV_EXPORTS void invSqrt64f(const double* src, double* dst, int len);
CV_EXPORTS void split8u(const uchar* src, uchar** dst, int len, int cn );
CV_EXPORTS void split16u(const ushort* src, ushort** dst, int len, int cn );
CV_EXPORTS void split32s(const int* src, int** dst, int len, int cn );
CV_EXPORTS void split64s(const int64* src, int64** dst, int len, int cn );
CV_EXPORTS void merge8u(const uchar** src, uchar* dst, int len, int cn );
CV_EXPORTS void merge16u(const ushort** src, ushort* dst, int len, int cn );
CV_EXPORTS void merge32s(const int** src, int* dst, int len, int cn );
CV_EXPORTS void merge64s(const int64** src, int64* dst, int len, int cn );
CV_EXPORTS void add8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void add8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void add16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
CV_EXPORTS void add16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
CV_EXPORTS void add32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
CV_EXPORTS void add32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
CV_EXPORTS void add64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
CV_EXPORTS void sub64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
CV_EXPORTS void max64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
CV_EXPORTS void min64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
CV_EXPORTS void absdiff64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
CV_EXPORTS void and8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void or8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void xor8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void not8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
CV_EXPORTS void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void cmp32s(const int* src1, size_t step1, const int* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
CV_EXPORTS void mul8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void mul8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void mul16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void mul16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void mul32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void mul32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void mul64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void div64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void recip64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale);
CV_EXPORTS void addWeighted8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _scalars );
CV_EXPORTS void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scalars );
CV_EXPORTS void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scalars );
CV_EXPORTS void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scalars );
CV_EXPORTS void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scalars );
CV_EXPORTS void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scalars );
CV_EXPORTS void addWeighted64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scalars );
//! @} core_hal
//=============================================================================
// for binary compatibility with 3.0
//! @cond IGNORED
CV_EXPORTS int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n);
CV_EXPORTS int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n);
CV_EXPORTS bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n);
CV_EXPORTS bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n);
CV_EXPORTS void exp(const float* src, float* dst, int n);
CV_EXPORTS void exp(const double* src, double* dst, int n);
CV_EXPORTS void log(const float* src, float* dst, int n);
CV_EXPORTS void log(const double* src, double* dst, int n);
CV_EXPORTS void magnitude(const float* x, const float* y, float* dst, int n);
CV_EXPORTS void magnitude(const double* x, const double* y, double* dst, int n);
CV_EXPORTS void sqrt(const float* src, float* dst, int len);
CV_EXPORTS void sqrt(const double* src, double* dst, int len);
CV_EXPORTS void invSqrt(const float* src, float* dst, int len);
CV_EXPORTS void invSqrt(const double* src, double* dst, int len);
//! @endcond
}} //cv::hal
#endif //__OPENCV_HAL_HPP__

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#ifndef _HAL_INTERFACE_HPP_INCLUDED_
#define _HAL_INTERFACE_HPP_INCLUDED_
//! @addtogroup core_hal_interface
//! @{
#define CV_HAL_ERROR_OK 0
#define CV_HAL_ERROR_NOT_IMPLEMENTED 1
#define CV_HAL_ERROR_UNKNOWN -1
#define CV_HAL_CMP_EQ 0
#define CV_HAL_CMP_GT 1
#define CV_HAL_CMP_GE 2
#define CV_HAL_CMP_LT 3
#define CV_HAL_CMP_LE 4
#define CV_HAL_CMP_NE 5
#ifdef __cplusplus
#include <cstddef>
#else
#include <stddef.h>
#endif
/* primitive types */
/*
schar - signed 1 byte integer
uchar - unsigned 1 byte integer
short - signed 2 byte integer
ushort - unsigned 2 byte integer
int - signed 4 byte integer
uint - unsigned 4 byte integer
int64 - signed 8 byte integer
uint64 - unsigned 8 byte integer
*/
#if !defined _MSC_VER && !defined __BORLANDC__
# if defined __cplusplus && __cplusplus >= 201103L && !defined __APPLE__
# include <cstdint>
typedef std::uint32_t uint;
# else
# include <stdint.h>
typedef uint32_t uint;
# endif
#else
typedef unsigned uint;
#endif
typedef signed char schar;
#ifndef __IPL_H__
typedef unsigned char uchar;
typedef unsigned short ushort;
#endif
#if defined _MSC_VER || defined __BORLANDC__
typedef __int64 int64;
typedef unsigned __int64 uint64;
# define CV_BIG_INT(n) n##I64
# define CV_BIG_UINT(n) n##UI64
#else
typedef int64_t int64;
typedef uint64_t uint64;
# define CV_BIG_INT(n) n##LL
# define CV_BIG_UINT(n) n##ULL
#endif
//! @}
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_HAL_INTRIN_HPP__
#define __OPENCV_HAL_INTRIN_HPP__
#include <cmath>
#include <float.h>
#include <stdlib.h>
#include "opencv2/core/cvdef.h"
#define OPENCV_HAL_ADD(a, b) ((a) + (b))
#define OPENCV_HAL_AND(a, b) ((a) & (b))
#define OPENCV_HAL_NOP(a) (a)
#define OPENCV_HAL_1ST(a, b) (a)
// unlike HAL API, which is in cv::hal,
// we put intrinsics into cv namespace to make its
// access from within opencv code more accessible
namespace cv {
//! @addtogroup core_hal_intrin
//! @{
//! @cond IGNORED
template<typename _Tp> struct V_TypeTraits
{
typedef _Tp int_type;
typedef _Tp uint_type;
typedef _Tp abs_type;
typedef _Tp sum_type;
enum { delta = 0, shift = 0 };
static int_type reinterpret_int(_Tp x) { return x; }
static uint_type reinterpet_uint(_Tp x) { return x; }
static _Tp reinterpret_from_int(int_type x) { return (_Tp)x; }
};
template<> struct V_TypeTraits<uchar>
{
typedef uchar value_type;
typedef schar int_type;
typedef uchar uint_type;
typedef uchar abs_type;
typedef int sum_type;
typedef ushort w_type;
typedef unsigned q_type;
enum { delta = 128, shift = 8 };
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<schar>
{
typedef schar value_type;
typedef schar int_type;
typedef uchar uint_type;
typedef uchar abs_type;
typedef int sum_type;
typedef short w_type;
typedef int q_type;
enum { delta = 128, shift = 8 };
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<ushort>
{
typedef ushort value_type;
typedef short int_type;
typedef ushort uint_type;
typedef ushort abs_type;
typedef int sum_type;
typedef unsigned w_type;
typedef uchar nu_type;
enum { delta = 32768, shift = 16 };
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<short>
{
typedef short value_type;
typedef short int_type;
typedef ushort uint_type;
typedef ushort abs_type;
typedef int sum_type;
typedef int w_type;
typedef uchar nu_type;
typedef schar n_type;
enum { delta = 128, shift = 8 };
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<unsigned>
{
typedef unsigned value_type;
typedef int int_type;
typedef unsigned uint_type;
typedef unsigned abs_type;
typedef unsigned sum_type;
typedef uint64 w_type;
typedef ushort nu_type;
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<int>
{
typedef int value_type;
typedef int int_type;
typedef unsigned uint_type;
typedef unsigned abs_type;
typedef int sum_type;
typedef int64 w_type;
typedef short n_type;
typedef ushort nu_type;
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<uint64>
{
typedef uint64 value_type;
typedef int64 int_type;
typedef uint64 uint_type;
typedef uint64 abs_type;
typedef uint64 sum_type;
typedef unsigned nu_type;
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<int64>
{
typedef int64 value_type;
typedef int64 int_type;
typedef uint64 uint_type;
typedef uint64 abs_type;
typedef int64 sum_type;
typedef int nu_type;
static int_type reinterpret_int(value_type x) { return (int_type)x; }
static uint_type reinterpret_uint(value_type x) { return (uint_type)x; }
static value_type reinterpret_from_int(int_type x) { return (value_type)x; }
};
template<> struct V_TypeTraits<float>
{
typedef float value_type;
typedef int int_type;
typedef unsigned uint_type;
typedef float abs_type;
typedef float sum_type;
typedef double w_type;
static int_type reinterpret_int(value_type x)
{
Cv32suf u;
u.f = x;
return u.i;
}
static uint_type reinterpet_uint(value_type x)
{
Cv32suf u;
u.f = x;
return u.u;
}
static value_type reinterpret_from_int(int_type x)
{
Cv32suf u;
u.i = x;
return u.f;
}
};
template<> struct V_TypeTraits<double>
{
typedef double value_type;
typedef int64 int_type;
typedef uint64 uint_type;
typedef double abs_type;
typedef double sum_type;
static int_type reinterpret_int(value_type x)
{
Cv64suf u;
u.f = x;
return u.i;
}
static uint_type reinterpet_uint(value_type x)
{
Cv64suf u;
u.f = x;
return u.u;
}
static value_type reinterpret_from_int(int_type x)
{
Cv64suf u;
u.i = x;
return u.f;
}
};
template <typename T> struct V_SIMD128Traits
{
enum { nlanes = 16 / sizeof(T) };
};
//! @endcond
//! @}
}
#ifdef CV_DOXYGEN
# undef CV_SSE2
# undef CV_NEON
#endif
#if CV_SSE2
#include "opencv2/core/hal/intrin_sse.hpp"
#elif CV_NEON
#include "opencv2/core/hal/intrin_neon.hpp"
#else
#include "opencv2/core/hal/intrin_cpp.hpp"
#endif
//! @addtogroup core_hal_intrin
//! @{
#ifndef CV_SIMD128
//! Set to 1 if current compiler supports vector extensions (NEON or SSE is enabled)
#define CV_SIMD128 0
#endif
#ifndef CV_SIMD128_64F
//! Set to 1 if current intrinsics implementation supports 64-bit float vectors
#define CV_SIMD128_64F 0
#endif
//! @}
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_HAL_INTRIN_NEON_HPP__
#define __OPENCV_HAL_INTRIN_NEON_HPP__
#include <algorithm>
namespace cv
{
//! @cond IGNORED
#define CV_SIMD128 1
struct v_uint8x16
{
typedef uchar lane_type;
enum { nlanes = 16 };
v_uint8x16() {}
explicit v_uint8x16(uint8x16_t v) : val(v) {}
v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
{
uchar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
val = vld1q_u8(v);
}
uchar get0() const
{
return vgetq_lane_u8(val, 0);
}
uint8x16_t val;
};
struct v_int8x16
{
typedef schar lane_type;
enum { nlanes = 16 };
v_int8x16() {}
explicit v_int8x16(int8x16_t v) : val(v) {}
v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
{
schar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
val = vld1q_s8(v);
}
schar get0() const
{
return vgetq_lane_s8(val, 0);
}
int8x16_t val;
};
struct v_uint16x8
{
typedef ushort lane_type;
enum { nlanes = 8 };
v_uint16x8() {}
explicit v_uint16x8(uint16x8_t v) : val(v) {}
v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
{
ushort v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
val = vld1q_u16(v);
}
ushort get0() const
{
return vgetq_lane_u16(val, 0);
}
uint16x8_t val;
};
struct v_int16x8
{
typedef short lane_type;
enum { nlanes = 8 };
v_int16x8() {}
explicit v_int16x8(int16x8_t v) : val(v) {}
v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
{
short v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
val = vld1q_s16(v);
}
short get0() const
{
return vgetq_lane_s16(val, 0);
}
int16x8_t val;
};
struct v_uint32x4
{
typedef unsigned lane_type;
enum { nlanes = 4 };
v_uint32x4() {}
explicit v_uint32x4(uint32x4_t v) : val(v) {}
v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3)
{
unsigned v[] = {v0, v1, v2, v3};
val = vld1q_u32(v);
}
unsigned get0() const
{
return vgetq_lane_u32(val, 0);
}
uint32x4_t val;
};
struct v_int32x4
{
typedef int lane_type;
enum { nlanes = 4 };
v_int32x4() {}
explicit v_int32x4(int32x4_t v) : val(v) {}
v_int32x4(int v0, int v1, int v2, int v3)
{
int v[] = {v0, v1, v2, v3};
val = vld1q_s32(v);
}
int get0() const
{
return vgetq_lane_s32(val, 0);
}
int32x4_t val;
};
struct v_float32x4
{
typedef float lane_type;
enum { nlanes = 4 };
v_float32x4() {}
explicit v_float32x4(float32x4_t v) : val(v) {}
v_float32x4(float v0, float v1, float v2, float v3)
{
float v[] = {v0, v1, v2, v3};
val = vld1q_f32(v);
}
float get0() const
{
return vgetq_lane_f32(val, 0);
}
float32x4_t val;
};
struct v_uint64x2
{
typedef uint64 lane_type;
enum { nlanes = 2 };
v_uint64x2() {}
explicit v_uint64x2(uint64x2_t v) : val(v) {}
v_uint64x2(unsigned v0, unsigned v1)
{
uint64 v[] = {v0, v1};
val = vld1q_u64(v);
}
uint64 get0() const
{
return vgetq_lane_u64(val, 0);
}
uint64x2_t val;
};
struct v_int64x2
{
typedef int64 lane_type;
enum { nlanes = 2 };
v_int64x2() {}
explicit v_int64x2(int64x2_t v) : val(v) {}
v_int64x2(int v0, int v1)
{
int64 v[] = {v0, v1};
val = vld1q_s64(v);
}
int64 get0() const
{
return vgetq_lane_s64(val, 0);
}
int64x2_t val;
};
#define OPENCV_HAL_IMPL_NEON_INIT(_Tpv, _Tp, suffix) \
inline v_##_Tpv v_setzero_##suffix() { return v_##_Tpv(vdupq_n_##suffix((_Tp)0)); } \
inline v_##_Tpv v_setall_##suffix(_Tp v) { return v_##_Tpv(vdupq_n_##suffix(v)); } \
inline _Tpv##_t vreinterpretq_##suffix##_##suffix(_Tpv##_t v) { return v; } \
inline v_uint8x16 v_reinterpret_as_u8(const v_##_Tpv& v) { return v_uint8x16(vreinterpretq_u8_##suffix(v.val)); } \
inline v_int8x16 v_reinterpret_as_s8(const v_##_Tpv& v) { return v_int8x16(vreinterpretq_s8_##suffix(v.val)); } \
inline v_uint16x8 v_reinterpret_as_u16(const v_##_Tpv& v) { return v_uint16x8(vreinterpretq_u16_##suffix(v.val)); } \
inline v_int16x8 v_reinterpret_as_s16(const v_##_Tpv& v) { return v_int16x8(vreinterpretq_s16_##suffix(v.val)); } \
inline v_uint32x4 v_reinterpret_as_u32(const v_##_Tpv& v) { return v_uint32x4(vreinterpretq_u32_##suffix(v.val)); } \
inline v_int32x4 v_reinterpret_as_s32(const v_##_Tpv& v) { return v_int32x4(vreinterpretq_s32_##suffix(v.val)); } \
inline v_uint64x2 v_reinterpret_as_u64(const v_##_Tpv& v) { return v_uint64x2(vreinterpretq_u64_##suffix(v.val)); } \
inline v_int64x2 v_reinterpret_as_s64(const v_##_Tpv& v) { return v_int64x2(vreinterpretq_s64_##suffix(v.val)); } \
inline v_float32x4 v_reinterpret_as_f32(const v_##_Tpv& v) { return v_float32x4(vreinterpretq_f32_##suffix(v.val)); }
OPENCV_HAL_IMPL_NEON_INIT(uint8x16, uchar, u8)
OPENCV_HAL_IMPL_NEON_INIT(int8x16, schar, s8)
OPENCV_HAL_IMPL_NEON_INIT(uint16x8, ushort, u16)
OPENCV_HAL_IMPL_NEON_INIT(int16x8, short, s16)
OPENCV_HAL_IMPL_NEON_INIT(uint32x4, unsigned, u32)
OPENCV_HAL_IMPL_NEON_INIT(int32x4, int, s32)
OPENCV_HAL_IMPL_NEON_INIT(uint64x2, uint64, u64)
OPENCV_HAL_IMPL_NEON_INIT(int64x2, int64, s64)
OPENCV_HAL_IMPL_NEON_INIT(float32x4, float, f32)
#define OPENCV_HAL_IMPL_NEON_PACK(_Tpvec, _Tp, hreg, suffix, _Tpwvec, wsuffix, pack, op) \
inline _Tpvec v_##pack(const _Tpwvec& a, const _Tpwvec& b) \
{ \
hreg a1 = vqmov##op##_##wsuffix(a.val), b1 = vqmov##op##_##wsuffix(b.val); \
return _Tpvec(vcombine_##suffix(a1, b1)); \
} \
inline void v_##pack##_store(_Tp* ptr, const _Tpwvec& a) \
{ \
hreg a1 = vqmov##op##_##wsuffix(a.val); \
vst1_##suffix(ptr, a1); \
} \
template<int n> inline \
_Tpvec v_rshr_##pack(const _Tpwvec& a, const _Tpwvec& b) \
{ \
hreg a1 = vqrshr##op##_n_##wsuffix(a.val, n); \
hreg b1 = vqrshr##op##_n_##wsuffix(b.val, n); \
return _Tpvec(vcombine_##suffix(a1, b1)); \
} \
template<int n> inline \
void v_rshr_##pack##_store(_Tp* ptr, const _Tpwvec& a) \
{ \
hreg a1 = vqrshr##op##_n_##wsuffix(a.val, n); \
vst1_##suffix(ptr, a1); \
}
OPENCV_HAL_IMPL_NEON_PACK(v_uint8x16, uchar, uint8x8_t, u8, v_uint16x8, u16, pack, n)
OPENCV_HAL_IMPL_NEON_PACK(v_int8x16, schar, int8x8_t, s8, v_int16x8, s16, pack, n)
OPENCV_HAL_IMPL_NEON_PACK(v_uint16x8, ushort, uint16x4_t, u16, v_uint32x4, u32, pack, n)
OPENCV_HAL_IMPL_NEON_PACK(v_int16x8, short, int16x4_t, s16, v_int32x4, s32, pack, n)
OPENCV_HAL_IMPL_NEON_PACK(v_uint32x4, unsigned, uint32x2_t, u32, v_uint64x2, u64, pack, n)
OPENCV_HAL_IMPL_NEON_PACK(v_int32x4, int, int32x2_t, s32, v_int64x2, s64, pack, n)
OPENCV_HAL_IMPL_NEON_PACK(v_uint8x16, uchar, uint8x8_t, u8, v_int16x8, s16, pack_u, un)
OPENCV_HAL_IMPL_NEON_PACK(v_uint16x8, ushort, uint16x4_t, u16, v_int32x4, s32, pack_u, un)
inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
const v_float32x4& m1, const v_float32x4& m2,
const v_float32x4& m3)
{
float32x2_t vl = vget_low_f32(v.val), vh = vget_high_f32(v.val);
float32x4_t res = vmulq_lane_f32(m0.val, vl, 0);
res = vmlaq_lane_f32(res, m1.val, vl, 1);
res = vmlaq_lane_f32(res, m2.val, vh, 0);
res = vmlaq_lane_f32(res, m3.val, vh, 1);
return v_float32x4(res);
}
#define OPENCV_HAL_IMPL_NEON_BIN_OP(bin_op, _Tpvec, intrin) \
inline _Tpvec operator bin_op (const _Tpvec& a, const _Tpvec& b) \
{ \
return _Tpvec(intrin(a.val, b.val)); \
} \
inline _Tpvec& operator bin_op##= (_Tpvec& a, const _Tpvec& b) \
{ \
a.val = intrin(a.val, b.val); \
return a; \
}
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint8x16, vqaddq_u8)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint8x16, vqsubq_u8)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int8x16, vqaddq_s8)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int8x16, vqsubq_s8)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint16x8, vqaddq_u16)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint16x8, vqsubq_u16)
OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_uint16x8, vmulq_u16)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int16x8, vqaddq_s16)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int16x8, vqsubq_s16)
OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_int16x8, vmulq_s16)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int32x4, vaddq_s32)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int32x4, vsubq_s32)
OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_int32x4, vmulq_s32)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint32x4, vaddq_u32)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint32x4, vsubq_u32)
OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_uint32x4, vmulq_u32)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_float32x4, vaddq_f32)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_float32x4, vsubq_f32)
OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_float32x4, vmulq_f32)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int64x2, vaddq_s64)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int64x2, vsubq_s64)
OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint64x2, vaddq_u64)
OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint64x2, vsubq_u64)
inline v_float32x4 operator / (const v_float32x4& a, const v_float32x4& b)
{
float32x4_t reciprocal = vrecpeq_f32(b.val);
reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal);
reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal);
return v_float32x4(vmulq_f32(a.val, reciprocal));
}
inline v_float32x4& operator /= (v_float32x4& a, const v_float32x4& b)
{
float32x4_t reciprocal = vrecpeq_f32(b.val);
reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal);
reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal);
a.val = vmulq_f32(a.val, reciprocal);
return a;
}
inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
v_int32x4& c, v_int32x4& d)
{
c.val = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val));
d.val = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val));
}
inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
v_uint32x4& c, v_uint32x4& d)
{
c.val = vmull_u16(vget_low_u16(a.val), vget_low_u16(b.val));
d.val = vmull_u16(vget_high_u16(a.val), vget_high_u16(b.val));
}
inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
v_uint64x2& c, v_uint64x2& d)
{
c.val = vmull_u32(vget_low_u32(a.val), vget_low_u32(b.val));
d.val = vmull_u32(vget_high_u32(a.val), vget_high_u32(b.val));
}
inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
{
int32x4_t c = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val));
int32x4_t d = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val));
int32x4x2_t cd = vuzpq_s32(c, d);
return v_int32x4(vaddq_s32(cd.val[0], cd.val[1]));
}
#define OPENCV_HAL_IMPL_NEON_LOGIC_OP(_Tpvec, suffix) \
OPENCV_HAL_IMPL_NEON_BIN_OP(&, _Tpvec, vandq_##suffix) \
OPENCV_HAL_IMPL_NEON_BIN_OP(|, _Tpvec, vorrq_##suffix) \
OPENCV_HAL_IMPL_NEON_BIN_OP(^, _Tpvec, veorq_##suffix) \
inline _Tpvec operator ~ (const _Tpvec& a) \
{ \
return _Tpvec(vreinterpretq_##suffix##_u8(vmvnq_u8(vreinterpretq_u8_##suffix(a.val)))); \
}
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint8x16, u8)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int8x16, s8)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint16x8, u16)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int16x8, s16)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint32x4, u32)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int32x4, s32)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint64x2, u64)
OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int64x2, s64)
#define OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(bin_op, intrin) \
inline v_float32x4 operator bin_op (const v_float32x4& a, const v_float32x4& b) \
{ \
return v_float32x4(vreinterpretq_f32_s32(intrin(vreinterpretq_s32_f32(a.val), vreinterpretq_s32_f32(b.val)))); \
} \
inline v_float32x4& operator bin_op##= (v_float32x4& a, const v_float32x4& b) \
{ \
a.val = vreinterpretq_f32_s32(intrin(vreinterpretq_s32_f32(a.val), vreinterpretq_s32_f32(b.val))); \
return a; \
}
OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(&, vandq_s32)
OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(|, vorrq_s32)
OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(^, veorq_s32)
inline v_float32x4 operator ~ (const v_float32x4& a)
{
return v_float32x4(vreinterpretq_f32_s32(vmvnq_s32(vreinterpretq_s32_f32(a.val))));
}
inline v_float32x4 v_sqrt(const v_float32x4& x)
{
float32x4_t x1 = vmaxq_f32(x.val, vdupq_n_f32(FLT_MIN));
float32x4_t e = vrsqrteq_f32(x1);
e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x1, e), e), e);
e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x1, e), e), e);
return v_float32x4(vmulq_f32(x.val, e));
}
inline v_float32x4 v_invsqrt(const v_float32x4& x)
{
float32x4_t e = vrsqrteq_f32(x.val);
e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x.val, e), e), e);
e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x.val, e), e), e);
return v_float32x4(e);
}
inline v_float32x4 v_abs(v_float32x4 x)
{ return v_float32x4(vabsq_f32(x.val)); }
// TODO: exp, log, sin, cos
#define OPENCV_HAL_IMPL_NEON_BIN_FUNC(_Tpvec, func, intrin) \
inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
{ \
return _Tpvec(intrin(a.val, b.val)); \
}
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_min, vminq_u8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_max, vmaxq_u8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_min, vminq_s8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_max, vmaxq_s8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_min, vminq_u16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_max, vmaxq_u16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_min, vminq_s16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_max, vmaxq_s16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_min, vminq_u32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_max, vmaxq_u32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int32x4, v_min, vminq_s32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int32x4, v_max, vmaxq_s32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_min, vminq_f32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_max, vmaxq_f32)
#define OPENCV_HAL_IMPL_NEON_INT_CMP_OP(_Tpvec, cast, suffix, not_suffix) \
inline _Tpvec operator == (const _Tpvec& a, const _Tpvec& b) \
{ return _Tpvec(cast(vceqq_##suffix(a.val, b.val))); } \
inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \
{ return _Tpvec(cast(vmvnq_##not_suffix(vceqq_##suffix(a.val, b.val)))); } \
inline _Tpvec operator < (const _Tpvec& a, const _Tpvec& b) \
{ return _Tpvec(cast(vcltq_##suffix(a.val, b.val))); } \
inline _Tpvec operator > (const _Tpvec& a, const _Tpvec& b) \
{ return _Tpvec(cast(vcgtq_##suffix(a.val, b.val))); } \
inline _Tpvec operator <= (const _Tpvec& a, const _Tpvec& b) \
{ return _Tpvec(cast(vcleq_##suffix(a.val, b.val))); } \
inline _Tpvec operator >= (const _Tpvec& a, const _Tpvec& b) \
{ return _Tpvec(cast(vcgeq_##suffix(a.val, b.val))); }
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint8x16, OPENCV_HAL_NOP, u8, u8)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int8x16, vreinterpretq_s8_u8, s8, u8)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint16x8, OPENCV_HAL_NOP, u16, u16)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int16x8, vreinterpretq_s16_u16, s16, u16)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint32x4, OPENCV_HAL_NOP, u32, u32)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int32x4, vreinterpretq_s32_u32, s32, u32)
OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float32x4, vreinterpretq_f32_u32, f32, u32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_add_wrap, vaddq_u8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_add_wrap, vaddq_s8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_add_wrap, vaddq_u16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_add_wrap, vaddq_s16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_sub_wrap, vsubq_u8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_sub_wrap, vsubq_s8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_sub_wrap, vsubq_u16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_sub_wrap, vsubq_s16)
// TODO: absdiff for signed integers
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_absdiff, vabdq_u8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_absdiff, vabdq_u16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_absdiff, vabdq_u32)
OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_absdiff, vabdq_f32)
#define OPENCV_HAL_IMPL_NEON_BIN_FUNC2(_Tpvec, _Tpvec2, cast, func, intrin) \
inline _Tpvec2 func(const _Tpvec& a, const _Tpvec& b) \
{ \
return _Tpvec2(cast(intrin(a.val, b.val))); \
}
OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int8x16, v_uint8x16, vreinterpretq_u8_s8, v_absdiff, vabdq_s8)
OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int16x8, v_uint16x8, vreinterpretq_u16_s16, v_absdiff, vabdq_s16)
OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int32x4, v_uint32x4, vreinterpretq_u32_s32, v_absdiff, vabdq_s32)
inline v_float32x4 v_magnitude(const v_float32x4& a, const v_float32x4& b)
{
v_float32x4 x(vmlaq_f32(vmulq_f32(a.val, a.val), b.val, b.val));
return v_sqrt(x);
}
inline v_float32x4 v_sqr_magnitude(const v_float32x4& a, const v_float32x4& b)
{
return v_float32x4(vmlaq_f32(vmulq_f32(a.val, a.val), b.val, b.val));
}
inline v_float32x4 v_muladd(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
{
return v_float32x4(vmlaq_f32(c.val, a.val, b.val));
}
// trade efficiency for convenience
#define OPENCV_HAL_IMPL_NEON_SHIFT_OP(_Tpvec, suffix, _Tps, ssuffix) \
inline _Tpvec operator << (const _Tpvec& a, int n) \
{ return _Tpvec(vshlq_##suffix(a.val, vdupq_n_##ssuffix((_Tps)n))); } \
inline _Tpvec operator >> (const _Tpvec& a, int n) \
{ return _Tpvec(vshlq_##suffix(a.val, vdupq_n_##ssuffix((_Tps)-n))); } \
template<int n> inline _Tpvec v_shl(const _Tpvec& a) \
{ return _Tpvec(vshlq_n_##suffix(a.val, n)); } \
template<int n> inline _Tpvec v_shr(const _Tpvec& a) \
{ return _Tpvec(vshrq_n_##suffix(a.val, n)); } \
template<int n> inline _Tpvec v_rshr(const _Tpvec& a) \
{ return _Tpvec(vrshrq_n_##suffix(a.val, n)); }
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint8x16, u8, schar, s8)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int8x16, s8, schar, s8)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint16x8, u16, short, s16)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int16x8, s16, short, s16)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint32x4, u32, int, s32)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int32x4, s32, int, s32)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint64x2, u64, int64, s64)
OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int64x2, s64, int64, s64)
#define OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(_Tpvec, _Tp, suffix) \
inline _Tpvec v_load(const _Tp* ptr) \
{ return _Tpvec(vld1q_##suffix(ptr)); } \
inline _Tpvec v_load_aligned(const _Tp* ptr) \
{ return _Tpvec(vld1q_##suffix(ptr)); } \
inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
{ return _Tpvec(vcombine_##suffix(vld1_##suffix(ptr0), vld1_##suffix(ptr1))); } \
inline void v_store(_Tp* ptr, const _Tpvec& a) \
{ vst1q_##suffix(ptr, a.val); } \
inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
{ vst1q_##suffix(ptr, a.val); } \
inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
{ vst1_##suffix(ptr, vget_low_##suffix(a.val)); } \
inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
{ vst1_##suffix(ptr, vget_high_##suffix(a.val)); }
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint8x16, uchar, u8)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int8x16, schar, s8)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint16x8, ushort, u16)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int16x8, short, s16)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint32x4, unsigned, u32)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int32x4, int, s32)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint64x2, uint64, u64)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int64x2, int64, s64)
OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_float32x4, float, f32)
#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(_Tpvec, scalartype, func, scalar_func) \
inline scalartype v_reduce_##func(const _Tpvec& a) \
{ \
scalartype CV_DECL_ALIGNED(16) buf[4]; \
v_store_aligned(buf, a); \
scalartype s0 = scalar_func(buf[0], buf[1]); \
scalartype s1 = scalar_func(buf[2], buf[3]); \
return scalar_func(s0, s1); \
}
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, unsigned, sum, OPENCV_HAL_ADD)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, unsigned, max, std::max)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, unsigned, min, std::min)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int, sum, OPENCV_HAL_ADD)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int, max, std::max)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int, min, std::min)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float, sum, OPENCV_HAL_ADD)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float, max, std::max)
OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float, min, std::min)
inline int v_signmask(const v_uint8x16& a)
{
int8x8_t m0 = vcreate_s8(CV_BIG_UINT(0x0706050403020100));
uint8x16_t v0 = vshlq_u8(vshrq_n_u8(a.val, 7), vcombine_s8(m0, m0));
uint64x2_t v1 = vpaddlq_u32(vpaddlq_u16(vpaddlq_u8(v0)));
return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 8);
}
inline int v_signmask(const v_int8x16& a)
{ return v_signmask(v_reinterpret_as_u8(a)); }
inline int v_signmask(const v_uint16x8& a)
{
int16x4_t m0 = vcreate_s16(CV_BIG_UINT(0x0003000200010000));
uint16x8_t v0 = vshlq_u16(vshrq_n_u16(a.val, 15), vcombine_s16(m0, m0));
uint64x2_t v1 = vpaddlq_u32(vpaddlq_u16(v0));
return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 4);
}
inline int v_signmask(const v_int16x8& a)
{ return v_signmask(v_reinterpret_as_u16(a)); }
inline int v_signmask(const v_uint32x4& a)
{
int32x2_t m0 = vcreate_s32(CV_BIG_UINT(0x0000000100000000));
uint32x4_t v0 = vshlq_u32(vshrq_n_u32(a.val, 31), vcombine_s32(m0, m0));
uint64x2_t v1 = vpaddlq_u32(v0);
return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 2);
}
inline int v_signmask(const v_int32x4& a)
{ return v_signmask(v_reinterpret_as_u32(a)); }
inline int v_signmask(const v_float32x4& a)
{ return v_signmask(v_reinterpret_as_u32(a)); }
#define OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(_Tpvec, suffix, shift) \
inline bool v_check_all(const v_##_Tpvec& a) \
{ \
_Tpvec##_t v0 = vshrq_n_##suffix(vmvnq_##suffix(a.val), shift); \
uint64x2_t v1 = vreinterpretq_u64_##suffix(v0); \
return (vgetq_lane_u64(v1, 0) | vgetq_lane_u64(v1, 1)) == 0; \
} \
inline bool v_check_any(const v_##_Tpvec& a) \
{ \
_Tpvec##_t v0 = vshrq_n_##suffix(a.val, shift); \
uint64x2_t v1 = vreinterpretq_u64_##suffix(v0); \
return (vgetq_lane_u64(v1, 0) | vgetq_lane_u64(v1, 1)) != 0; \
}
OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint8x16, u8, 7)
OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint16x8, u16, 15)
OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint32x4, u32, 31)
inline bool v_check_all(const v_int8x16& a)
{ return v_check_all(v_reinterpret_as_u8(a)); }
inline bool v_check_all(const v_int16x8& a)
{ return v_check_all(v_reinterpret_as_u16(a)); }
inline bool v_check_all(const v_int32x4& a)
{ return v_check_all(v_reinterpret_as_u32(a)); }
inline bool v_check_all(const v_float32x4& a)
{ return v_check_all(v_reinterpret_as_u32(a)); }
inline bool v_check_any(const v_int8x16& a)
{ return v_check_any(v_reinterpret_as_u8(a)); }
inline bool v_check_any(const v_int16x8& a)
{ return v_check_any(v_reinterpret_as_u16(a)); }
inline bool v_check_any(const v_int32x4& a)
{ return v_check_any(v_reinterpret_as_u32(a)); }
inline bool v_check_any(const v_float32x4& a)
{ return v_check_any(v_reinterpret_as_u32(a)); }
#define OPENCV_HAL_IMPL_NEON_SELECT(_Tpvec, suffix, usuffix) \
inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
{ \
return _Tpvec(vbslq_##suffix(vreinterpretq_##usuffix##_##suffix(mask.val), a.val, b.val)); \
}
OPENCV_HAL_IMPL_NEON_SELECT(v_uint8x16, u8, u8)
OPENCV_HAL_IMPL_NEON_SELECT(v_int8x16, s8, u8)
OPENCV_HAL_IMPL_NEON_SELECT(v_uint16x8, u16, u16)
OPENCV_HAL_IMPL_NEON_SELECT(v_int16x8, s16, u16)
OPENCV_HAL_IMPL_NEON_SELECT(v_uint32x4, u32, u32)
OPENCV_HAL_IMPL_NEON_SELECT(v_int32x4, s32, u32)
OPENCV_HAL_IMPL_NEON_SELECT(v_float32x4, f32, u32)
#define OPENCV_HAL_IMPL_NEON_EXPAND(_Tpvec, _Tpwvec, _Tp, suffix) \
inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
{ \
b0.val = vmovl_##suffix(vget_low_##suffix(a.val)); \
b1.val = vmovl_##suffix(vget_high_##suffix(a.val)); \
} \
inline _Tpwvec v_load_expand(const _Tp* ptr) \
{ \
return _Tpwvec(vmovl_##suffix(vld1_##suffix(ptr))); \
}
OPENCV_HAL_IMPL_NEON_EXPAND(v_uint8x16, v_uint16x8, uchar, u8)
OPENCV_HAL_IMPL_NEON_EXPAND(v_int8x16, v_int16x8, schar, s8)
OPENCV_HAL_IMPL_NEON_EXPAND(v_uint16x8, v_uint32x4, ushort, u16)
OPENCV_HAL_IMPL_NEON_EXPAND(v_int16x8, v_int32x4, short, s16)
OPENCV_HAL_IMPL_NEON_EXPAND(v_uint32x4, v_uint64x2, uint, u32)
OPENCV_HAL_IMPL_NEON_EXPAND(v_int32x4, v_int64x2, int, s32)
inline v_uint32x4 v_load_expand_q(const uchar* ptr)
{
uint8x8_t v0 = vcreate_u8(*(unsigned*)ptr);
uint16x4_t v1 = vget_low_u16(vmovl_u8(v0));
return v_uint32x4(vmovl_u16(v1));
}
inline v_int32x4 v_load_expand_q(const schar* ptr)
{
int8x8_t v0 = vcreate_s8(*(unsigned*)ptr);
int16x4_t v1 = vget_low_s16(vmovl_s8(v0));
return v_int32x4(vmovl_s16(v1));
}
#define OPENCV_HAL_IMPL_NEON_UNPACKS(_Tpvec, suffix) \
inline void v_zip(const v_##_Tpvec& a0, const v_##_Tpvec& a1, v_##_Tpvec& b0, v_##_Tpvec& b1) \
{ \
_Tpvec##x2_t p = vzipq_##suffix(a0.val, a1.val); \
b0.val = p.val[0]; \
b1.val = p.val[1]; \
} \
inline v_##_Tpvec v_combine_low(const v_##_Tpvec& a, const v_##_Tpvec& b) \
{ \
return v_##_Tpvec(vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val))); \
} \
inline v_##_Tpvec v_combine_high(const v_##_Tpvec& a, const v_##_Tpvec& b) \
{ \
return v_##_Tpvec(vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val))); \
} \
inline void v_recombine(const v_##_Tpvec& a, const v_##_Tpvec& b, v_##_Tpvec& c, v_##_Tpvec& d) \
{ \
c.val = vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val)); \
d.val = vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val)); \
}
OPENCV_HAL_IMPL_NEON_UNPACKS(uint8x16, u8)
OPENCV_HAL_IMPL_NEON_UNPACKS(int8x16, s8)
OPENCV_HAL_IMPL_NEON_UNPACKS(uint16x8, u16)
OPENCV_HAL_IMPL_NEON_UNPACKS(int16x8, s16)
OPENCV_HAL_IMPL_NEON_UNPACKS(uint32x4, u32)
OPENCV_HAL_IMPL_NEON_UNPACKS(int32x4, s32)
OPENCV_HAL_IMPL_NEON_UNPACKS(float32x4, f32)
#define OPENCV_HAL_IMPL_NEON_EXTRACT(_Tpvec, suffix) \
template <int s> \
inline v_##_Tpvec v_extract(const v_##_Tpvec& a, const v_##_Tpvec& b) \
{ \
return v_##_Tpvec(vextq_##suffix(a.val, b.val, s)); \
}
OPENCV_HAL_IMPL_NEON_EXTRACT(uint8x16, u8)
OPENCV_HAL_IMPL_NEON_EXTRACT(int8x16, s8)
OPENCV_HAL_IMPL_NEON_EXTRACT(uint16x8, u16)
OPENCV_HAL_IMPL_NEON_EXTRACT(int16x8, s16)
OPENCV_HAL_IMPL_NEON_EXTRACT(uint32x4, u32)
OPENCV_HAL_IMPL_NEON_EXTRACT(int32x4, s32)
OPENCV_HAL_IMPL_NEON_EXTRACT(uint64x2, u64)
OPENCV_HAL_IMPL_NEON_EXTRACT(int64x2, s64)
OPENCV_HAL_IMPL_NEON_EXTRACT(float32x4, f32)
inline v_int32x4 v_round(const v_float32x4& a)
{
static const int32x4_t v_sign = vdupq_n_s32(1 << 31),
v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f));
int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(a.val)));
return v_int32x4(vcvtq_s32_f32(vaddq_f32(a.val, vreinterpretq_f32_s32(v_addition))));
}
inline v_int32x4 v_floor(const v_float32x4& a)
{
int32x4_t a1 = vcvtq_s32_f32(a.val);
uint32x4_t mask = vcgtq_f32(vcvtq_f32_s32(a1), a.val);
return v_int32x4(vaddq_s32(a1, vreinterpretq_s32_u32(mask)));
}
inline v_int32x4 v_ceil(const v_float32x4& a)
{
int32x4_t a1 = vcvtq_s32_f32(a.val);
uint32x4_t mask = vcgtq_f32(a.val, vcvtq_f32_s32(a1));
return v_int32x4(vsubq_s32(a1, vreinterpretq_s32_u32(mask)));
}
inline v_int32x4 v_trunc(const v_float32x4& a)
{ return v_int32x4(vcvtq_s32_f32(a.val)); }
#define OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(_Tpvec, suffix) \
inline void v_transpose4x4(const v_##_Tpvec& a0, const v_##_Tpvec& a1, \
const v_##_Tpvec& a2, const v_##_Tpvec& a3, \
v_##_Tpvec& b0, v_##_Tpvec& b1, \
v_##_Tpvec& b2, v_##_Tpvec& b3) \
{ \
/* m00 m01 m02 m03 */ \
/* m10 m11 m12 m13 */ \
/* m20 m21 m22 m23 */ \
/* m30 m31 m32 m33 */ \
_Tpvec##x2_t t0 = vtrnq_##suffix(a0.val, a1.val); \
_Tpvec##x2_t t1 = vtrnq_##suffix(a2.val, a3.val); \
/* m00 m10 m02 m12 */ \
/* m01 m11 m03 m13 */ \
/* m20 m30 m22 m32 */ \
/* m21 m31 m23 m33 */ \
b0.val = vcombine_##suffix(vget_low_##suffix(t0.val[0]), vget_low_##suffix(t1.val[0])); \
b1.val = vcombine_##suffix(vget_low_##suffix(t0.val[1]), vget_low_##suffix(t1.val[1])); \
b2.val = vcombine_##suffix(vget_high_##suffix(t0.val[0]), vget_high_##suffix(t1.val[0])); \
b3.val = vcombine_##suffix(vget_high_##suffix(t0.val[1]), vget_high_##suffix(t1.val[1])); \
}
OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(uint32x4, u32)
OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(int32x4, s32)
OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(float32x4, f32)
#define OPENCV_HAL_IMPL_NEON_INTERLEAVED(_Tpvec, _Tp, suffix) \
inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, v_##_Tpvec& c) \
{ \
_Tpvec##x3_t v = vld3q_##suffix(ptr); \
a.val = v.val[0]; \
b.val = v.val[1]; \
c.val = v.val[2]; \
} \
inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, \
v_##_Tpvec& c, v_##_Tpvec& d) \
{ \
_Tpvec##x4_t v = vld4q_##suffix(ptr); \
a.val = v.val[0]; \
b.val = v.val[1]; \
c.val = v.val[2]; \
d.val = v.val[3]; \
} \
inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, const v_##_Tpvec& c) \
{ \
_Tpvec##x3_t v; \
v.val[0] = a.val; \
v.val[1] = b.val; \
v.val[2] = c.val; \
vst3q_##suffix(ptr, v); \
} \
inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
const v_##_Tpvec& c, const v_##_Tpvec& d) \
{ \
_Tpvec##x4_t v; \
v.val[0] = a.val; \
v.val[1] = b.val; \
v.val[2] = c.val; \
v.val[3] = d.val; \
vst4q_##suffix(ptr, v); \
}
OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint8x16, uchar, u8)
OPENCV_HAL_IMPL_NEON_INTERLEAVED(int8x16, schar, s8)
OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint16x8, ushort, u16)
OPENCV_HAL_IMPL_NEON_INTERLEAVED(int16x8, short, s16)
OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint32x4, unsigned, u32)
OPENCV_HAL_IMPL_NEON_INTERLEAVED(int32x4, int, s32)
OPENCV_HAL_IMPL_NEON_INTERLEAVED(float32x4, float, f32)
inline v_float32x4 v_cvt_f32(const v_int32x4& a)
{
return v_float32x4(vcvtq_f32_s32(a.val));
}
//! @endcond
}
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_IPPASYNC_HPP__
#define __OPENCV_CORE_IPPASYNC_HPP__
#ifdef HAVE_IPP_A
#include "opencv2/core.hpp"
#include <ipp_async_op.h>
#include <ipp_async_accel.h>
namespace cv
{
namespace hpp
{
/** @addtogroup core_ipp
This section describes conversion between OpenCV and [Intel&reg; IPP Asynchronous
C/C++](http://software.intel.com/en-us/intel-ipp-preview) library. [Getting Started
Guide](http://registrationcenter.intel.com/irc_nas/3727/ipp_async_get_started.htm) help you to
install the library, configure header and library build paths.
*/
//! @{
//! convert OpenCV data type to hppDataType
inline int toHppType(const int cvType)
{
int depth = CV_MAT_DEPTH(cvType);
int hppType = depth == CV_8U ? HPP_DATA_TYPE_8U :
depth == CV_16U ? HPP_DATA_TYPE_16U :
depth == CV_16S ? HPP_DATA_TYPE_16S :
depth == CV_32S ? HPP_DATA_TYPE_32S :
depth == CV_32F ? HPP_DATA_TYPE_32F :
depth == CV_64F ? HPP_DATA_TYPE_64F : -1;
CV_Assert( hppType >= 0 );
return hppType;
}
//! convert hppDataType to OpenCV data type
inline int toCvType(const int hppType)
{
int cvType = hppType == HPP_DATA_TYPE_8U ? CV_8U :
hppType == HPP_DATA_TYPE_16U ? CV_16U :
hppType == HPP_DATA_TYPE_16S ? CV_16S :
hppType == HPP_DATA_TYPE_32S ? CV_32S :
hppType == HPP_DATA_TYPE_32F ? CV_32F :
hppType == HPP_DATA_TYPE_64F ? CV_64F : -1;
CV_Assert( cvType >= 0 );
return cvType;
}
/** @brief Convert hppiMatrix to Mat.
This function allocates and initializes new matrix (if needed) that has the same size and type as
input matrix. Supports CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F.
@param src input hppiMatrix.
@param dst output matrix.
@param accel accelerator instance (see hpp::getHpp for the list of acceleration framework types).
@param cn number of channels.
*/
inline void copyHppToMat(hppiMatrix* src, Mat& dst, hppAccel accel, int cn)
{
hppDataType type;
hpp32u width, height;
hppStatus sts;
if (src == NULL)
return dst.release();
sts = hppiInquireMatrix(src, &type, &width, &height);
CV_Assert( sts == HPP_STATUS_NO_ERROR);
int matType = CV_MAKETYPE(toCvType(type), cn);
CV_Assert(width%cn == 0);
width /= cn;
dst.create((int)height, (int)width, (int)matType);
size_t newSize = (size_t)(height*(hpp32u)(dst.step));
sts = hppiGetMatrixData(accel,src,(hpp32u)(dst.step),dst.data,&newSize);
CV_Assert( sts == HPP_STATUS_NO_ERROR);
}
/** @brief Create Mat from hppiMatrix.
This function allocates and initializes the Mat that has the same size and type as input matrix.
Supports CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F.
@param src input hppiMatrix.
@param accel accelerator instance (see hpp::getHpp for the list of acceleration framework types).
@param cn number of channels.
@sa howToUseIPPAconversion, hpp::copyHppToMat, hpp::getHpp.
*/
inline Mat getMat(hppiMatrix* src, hppAccel accel, int cn)
{
Mat dst;
copyHppToMat(src, dst, accel, cn);
return dst;
}
/** @brief Create hppiMatrix from Mat.
This function allocates and initializes the hppiMatrix that has the same size and type as input
matrix, returns the hppiMatrix*.
If you want to use zero-copy for GPU you should to have 4KB aligned matrix data. See details
[hppiCreateSharedMatrix](http://software.intel.com/ru-ru/node/501697).
Supports CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F.
@note The hppiMatrix pointer to the image buffer in system memory refers to the src.data. Control
the lifetime of the matrix and don't change its data, if there is no special need.
@param src input matrix.
@param accel accelerator instance. Supports type:
- **HPP_ACCEL_TYPE_CPU** - accelerated by optimized CPU instructions.
- **HPP_ACCEL_TYPE_GPU** - accelerated by GPU programmable units or fixed-function
accelerators.
- **HPP_ACCEL_TYPE_ANY** - any acceleration or no acceleration available.
@sa howToUseIPPAconversion, hpp::getMat
*/
inline hppiMatrix* getHpp(const Mat& src, hppAccel accel)
{
int htype = toHppType(src.type());
int cn = src.channels();
CV_Assert(src.data);
hppAccelType accelType = hppQueryAccelType(accel);
if (accelType!=HPP_ACCEL_TYPE_CPU)
{
hpp32u pitch, size;
hppQueryMatrixAllocParams(accel, src.cols*cn, src.rows, htype, &pitch, &size);
if (pitch!=0 && size!=0)
if ((int)(src.data)%4096==0 && pitch==(hpp32u)(src.step))
{
return hppiCreateSharedMatrix(htype, src.cols*cn, src.rows, src.data, pitch, size);
}
}
return hppiCreateMatrix(htype, src.cols*cn, src.rows, src.data, (hpp32s)(src.step));;
}
//! @}
}}
#endif
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_HAL_NEON_UTILS_HPP__
#define __OPENCV_HAL_NEON_UTILS_HPP__
#include "opencv2/core/cvdef.h"
//! @addtogroup core_utils_neon
//! @{
#if CV_NEON
inline int32x2_t cv_vrnd_s32_f32(float32x2_t v)
{
static int32x2_t v_sign = vdup_n_s32(1 << 31),
v_05 = vreinterpret_s32_f32(vdup_n_f32(0.5f));
int32x2_t v_addition = vorr_s32(v_05, vand_s32(v_sign, vreinterpret_s32_f32(v)));
return vcvt_s32_f32(vadd_f32(v, vreinterpret_f32_s32(v_addition)));
}
inline int32x4_t cv_vrndq_s32_f32(float32x4_t v)
{
static int32x4_t v_sign = vdupq_n_s32(1 << 31),
v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f));
int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(v)));
return vcvtq_s32_f32(vaddq_f32(v, vreinterpretq_f32_s32(v_addition)));
}
inline uint32x2_t cv_vrnd_u32_f32(float32x2_t v)
{
static float32x2_t v_05 = vdup_n_f32(0.5f);
return vcvt_u32_f32(vadd_f32(v, v_05));
}
inline uint32x4_t cv_vrndq_u32_f32(float32x4_t v)
{
static float32x4_t v_05 = vdupq_n_f32(0.5f);
return vcvtq_u32_f32(vaddq_f32(v, v_05));
}
inline float32x4_t cv_vrecpq_f32(float32x4_t val)
{
float32x4_t reciprocal = vrecpeq_f32(val);
reciprocal = vmulq_f32(vrecpsq_f32(val, reciprocal), reciprocal);
reciprocal = vmulq_f32(vrecpsq_f32(val, reciprocal), reciprocal);
return reciprocal;
}
inline float32x2_t cv_vrecp_f32(float32x2_t val)
{
float32x2_t reciprocal = vrecpe_f32(val);
reciprocal = vmul_f32(vrecps_f32(val, reciprocal), reciprocal);
reciprocal = vmul_f32(vrecps_f32(val, reciprocal), reciprocal);
return reciprocal;
}
inline float32x4_t cv_vrsqrtq_f32(float32x4_t val)
{
float32x4_t e = vrsqrteq_f32(val);
e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(e, e), val), e);
e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(e, e), val), e);
return e;
}
inline float32x2_t cv_vrsqrt_f32(float32x2_t val)
{
float32x2_t e = vrsqrte_f32(val);
e = vmul_f32(vrsqrts_f32(vmul_f32(e, e), val), e);
e = vmul_f32(vrsqrts_f32(vmul_f32(e, e), val), e);
return e;
}
inline float32x4_t cv_vsqrtq_f32(float32x4_t val)
{
return cv_vrecpq_f32(cv_vrsqrtq_f32(val));
}
inline float32x2_t cv_vsqrt_f32(float32x2_t val)
{
return cv_vrecp_f32(cv_vrsqrt_f32(val));
}
#endif
//! @}
#endif // __OPENCV_HAL_NEON_UTILS_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the OpenCV Foundation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OPENCL_HPP__
#define __OPENCV_OPENCL_HPP__
#include "opencv2/core.hpp"
namespace cv { namespace ocl {
//! @addtogroup core_opencl
//! @{
CV_EXPORTS_W bool haveOpenCL();
CV_EXPORTS_W bool useOpenCL();
CV_EXPORTS_W bool haveAmdBlas();
CV_EXPORTS_W bool haveAmdFft();
CV_EXPORTS_W void setUseOpenCL(bool flag);
CV_EXPORTS_W void finish();
CV_EXPORTS bool haveSVM();
class CV_EXPORTS Context;
class CV_EXPORTS Device;
class CV_EXPORTS Kernel;
class CV_EXPORTS Program;
class CV_EXPORTS ProgramSource;
class CV_EXPORTS Queue;
class CV_EXPORTS PlatformInfo;
class CV_EXPORTS Image2D;
class CV_EXPORTS Device
{
public:
Device();
explicit Device(void* d);
Device(const Device& d);
Device& operator = (const Device& d);
~Device();
void set(void* d);
enum
{
TYPE_DEFAULT = (1 << 0),
TYPE_CPU = (1 << 1),
TYPE_GPU = (1 << 2),
TYPE_ACCELERATOR = (1 << 3),
TYPE_DGPU = TYPE_GPU + (1 << 16),
TYPE_IGPU = TYPE_GPU + (1 << 17),
TYPE_ALL = 0xFFFFFFFF
};
String name() const;
String extensions() const;
String version() const;
String vendorName() const;
String OpenCL_C_Version() const;
String OpenCLVersion() const;
int deviceVersionMajor() const;
int deviceVersionMinor() const;
String driverVersion() const;
void* ptr() const;
int type() const;
int addressBits() const;
bool available() const;
bool compilerAvailable() const;
bool linkerAvailable() const;
enum
{
FP_DENORM=(1 << 0),
FP_INF_NAN=(1 << 1),
FP_ROUND_TO_NEAREST=(1 << 2),
FP_ROUND_TO_ZERO=(1 << 3),
FP_ROUND_TO_INF=(1 << 4),
FP_FMA=(1 << 5),
FP_SOFT_FLOAT=(1 << 6),
FP_CORRECTLY_ROUNDED_DIVIDE_SQRT=(1 << 7)
};
int doubleFPConfig() const;
int singleFPConfig() const;
int halfFPConfig() const;
bool endianLittle() const;
bool errorCorrectionSupport() const;
enum
{
EXEC_KERNEL=(1 << 0),
EXEC_NATIVE_KERNEL=(1 << 1)
};
int executionCapabilities() const;
size_t globalMemCacheSize() const;
enum
{
NO_CACHE=0,
READ_ONLY_CACHE=1,
READ_WRITE_CACHE=2
};
int globalMemCacheType() const;
int globalMemCacheLineSize() const;
size_t globalMemSize() const;
size_t localMemSize() const;
enum
{
NO_LOCAL_MEM=0,
LOCAL_IS_LOCAL=1,
LOCAL_IS_GLOBAL=2
};
int localMemType() const;
bool hostUnifiedMemory() const;
bool imageSupport() const;
bool imageFromBufferSupport() const;
uint imagePitchAlignment() const;
uint imageBaseAddressAlignment() const;
size_t image2DMaxWidth() const;
size_t image2DMaxHeight() const;
size_t image3DMaxWidth() const;
size_t image3DMaxHeight() const;
size_t image3DMaxDepth() const;
size_t imageMaxBufferSize() const;
size_t imageMaxArraySize() const;
enum
{
UNKNOWN_VENDOR=0,
VENDOR_AMD=1,
VENDOR_INTEL=2,
VENDOR_NVIDIA=3
};
int vendorID() const;
// FIXIT
// dev.isAMD() doesn't work for OpenCL CPU devices from AMD OpenCL platform.
// This method should use platform name instead of vendor name.
// After fix restore code in arithm.cpp: ocl_compare()
inline bool isAMD() const { return vendorID() == VENDOR_AMD; }
inline bool isIntel() const { return vendorID() == VENDOR_INTEL; }
inline bool isNVidia() const { return vendorID() == VENDOR_NVIDIA; }
int maxClockFrequency() const;
int maxComputeUnits() const;
int maxConstantArgs() const;
size_t maxConstantBufferSize() const;
size_t maxMemAllocSize() const;
size_t maxParameterSize() const;
int maxReadImageArgs() const;
int maxWriteImageArgs() const;
int maxSamplers() const;
size_t maxWorkGroupSize() const;
int maxWorkItemDims() const;
void maxWorkItemSizes(size_t*) const;
int memBaseAddrAlign() const;
int nativeVectorWidthChar() const;
int nativeVectorWidthShort() const;
int nativeVectorWidthInt() const;
int nativeVectorWidthLong() const;
int nativeVectorWidthFloat() const;
int nativeVectorWidthDouble() const;
int nativeVectorWidthHalf() const;
int preferredVectorWidthChar() const;
int preferredVectorWidthShort() const;
int preferredVectorWidthInt() const;
int preferredVectorWidthLong() const;
int preferredVectorWidthFloat() const;
int preferredVectorWidthDouble() const;
int preferredVectorWidthHalf() const;
size_t printfBufferSize() const;
size_t profilingTimerResolution() const;
static const Device& getDefault();
protected:
struct Impl;
Impl* p;
};
class CV_EXPORTS Context
{
public:
Context();
explicit Context(int dtype);
~Context();
Context(const Context& c);
Context& operator = (const Context& c);
bool create();
bool create(int dtype);
size_t ndevices() const;
const Device& device(size_t idx) const;
Program getProg(const ProgramSource& prog,
const String& buildopt, String& errmsg);
static Context& getDefault(bool initialize = true);
void* ptr() const;
friend void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);
bool useSVM() const;
void setUseSVM(bool enabled);
struct Impl;
Impl* p;
};
class CV_EXPORTS Platform
{
public:
Platform();
~Platform();
Platform(const Platform& p);
Platform& operator = (const Platform& p);
void* ptr() const;
static Platform& getDefault();
friend void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);
protected:
struct Impl;
Impl* p;
};
/*
//! @brief Attaches OpenCL context to OpenCV
//
//! @note Note:
// OpenCV will check if available OpenCL platform has platformName name,
// then assign context to OpenCV and call clRetainContext function.
// The deviceID device will be used as target device and new command queue
// will be created.
//
// Params:
//! @param platformName - name of OpenCL platform to attach,
//! this string is used to check if platform is available
//! to OpenCV at runtime
//! @param platfromID - ID of platform attached context was created for
//! @param context - OpenCL context to be attached to OpenCV
//! @param deviceID - ID of device, must be created from attached context
*/
CV_EXPORTS void attachContext(const String& platformName, void* platformID, void* context, void* deviceID);
/*
//! @brief Convert OpenCL buffer to UMat
//
//! @note Note:
// OpenCL buffer (cl_mem_buffer) should contain 2D image data, compatible with OpenCV.
// Memory content is not copied from clBuffer to UMat. Instead, buffer handle assigned
// to UMat and clRetainMemObject is called.
//
// Params:
//! @param cl_mem_buffer - source clBuffer handle
//! @param step - num of bytes in single row
//! @param rows - number of rows
//! @param cols - number of cols
//! @param type - OpenCV type of image
//! @param dst - destination UMat
*/
CV_EXPORTS void convertFromBuffer(void* cl_mem_buffer, size_t step, int rows, int cols, int type, UMat& dst);
/*
//! @brief Convert OpenCL image2d_t to UMat
//
//! @note Note:
// OpenCL image2d_t (cl_mem_image), should be compatible with OpenCV
// UMat formats.
// Memory content is copied from image to UMat with
// clEnqueueCopyImageToBuffer function.
//
// Params:
//! @param cl_mem_image - source image2d_t handle
//! @param dst - destination UMat
*/
CV_EXPORTS void convertFromImage(void* cl_mem_image, UMat& dst);
// TODO Move to internal header
void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);
class CV_EXPORTS Queue
{
public:
Queue();
explicit Queue(const Context& c, const Device& d=Device());
~Queue();
Queue(const Queue& q);
Queue& operator = (const Queue& q);
bool create(const Context& c=Context(), const Device& d=Device());
void finish();
void* ptr() const;
static Queue& getDefault();
protected:
struct Impl;
Impl* p;
};
class CV_EXPORTS KernelArg
{
public:
enum { LOCAL=1, READ_ONLY=2, WRITE_ONLY=4, READ_WRITE=6, CONSTANT=8, PTR_ONLY = 16, NO_SIZE=256 };
KernelArg(int _flags, UMat* _m, int wscale=1, int iwscale=1, const void* _obj=0, size_t _sz=0);
KernelArg();
static KernelArg Local() { return KernelArg(LOCAL, 0); }
static KernelArg PtrWriteOnly(const UMat& m)
{ return KernelArg(PTR_ONLY+WRITE_ONLY, (UMat*)&m); }
static KernelArg PtrReadOnly(const UMat& m)
{ return KernelArg(PTR_ONLY+READ_ONLY, (UMat*)&m); }
static KernelArg PtrReadWrite(const UMat& m)
{ return KernelArg(PTR_ONLY+READ_WRITE, (UMat*)&m); }
static KernelArg ReadWrite(const UMat& m, int wscale=1, int iwscale=1)
{ return KernelArg(READ_WRITE, (UMat*)&m, wscale, iwscale); }
static KernelArg ReadWriteNoSize(const UMat& m, int wscale=1, int iwscale=1)
{ return KernelArg(READ_WRITE+NO_SIZE, (UMat*)&m, wscale, iwscale); }
static KernelArg ReadOnly(const UMat& m, int wscale=1, int iwscale=1)
{ return KernelArg(READ_ONLY, (UMat*)&m, wscale, iwscale); }
static KernelArg WriteOnly(const UMat& m, int wscale=1, int iwscale=1)
{ return KernelArg(WRITE_ONLY, (UMat*)&m, wscale, iwscale); }
static KernelArg ReadOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1)
{ return KernelArg(READ_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); }
static KernelArg WriteOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1)
{ return KernelArg(WRITE_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); }
static KernelArg Constant(const Mat& m);
template<typename _Tp> static KernelArg Constant(const _Tp* arr, size_t n)
{ return KernelArg(CONSTANT, 0, 1, 1, (void*)arr, n); }
int flags;
UMat* m;
const void* obj;
size_t sz;
int wscale, iwscale;
};
class CV_EXPORTS Kernel
{
public:
Kernel();
Kernel(const char* kname, const Program& prog);
Kernel(const char* kname, const ProgramSource& prog,
const String& buildopts = String(), String* errmsg=0);
~Kernel();
Kernel(const Kernel& k);
Kernel& operator = (const Kernel& k);
bool empty() const;
bool create(const char* kname, const Program& prog);
bool create(const char* kname, const ProgramSource& prog,
const String& buildopts, String* errmsg=0);
int set(int i, const void* value, size_t sz);
int set(int i, const Image2D& image2D);
int set(int i, const UMat& m);
int set(int i, const KernelArg& arg);
template<typename _Tp> int set(int i, const _Tp& value)
{ return set(i, &value, sizeof(value)); }
template<typename _Tp0>
Kernel& args(const _Tp0& a0)
{
set(0, a0); return *this;
}
template<typename _Tp0, typename _Tp1>
Kernel& args(const _Tp0& a0, const _Tp1& a1)
{
int i = set(0, a0); set(i, a1); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2)
{
int i = set(0, a0); i = set(i, a1); set(i, a2); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3, typename _Tp4>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2,
const _Tp3& a3, const _Tp4& a4)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2);
i = set(i, a3); set(i, a4); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2,
typename _Tp3, typename _Tp4, typename _Tp5>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2,
const _Tp3& a3, const _Tp4& a4, const _Tp5& a5)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2);
i = set(i, a3); i = set(i, a4); set(i, a5); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3);
i = set(i, a4); i = set(i, a5); set(i, a6); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3);
i = set(i, a4); i = set(i, a5); i = set(i, a6); set(i, a7); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3, typename _Tp4,
typename _Tp5, typename _Tp6, typename _Tp7, typename _Tp8>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4);
i = set(i, a5); i = set(i, a6); i = set(i, a7); set(i, a8); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3, typename _Tp4,
typename _Tp5, typename _Tp6, typename _Tp7, typename _Tp8, typename _Tp9>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); set(i, a9); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
typename _Tp8, typename _Tp9, typename _Tp10>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9, const _Tp10& a10)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); set(i, a10); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); set(i, a11); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
const _Tp12& a12)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
set(i, a12); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12,
typename _Tp13>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
const _Tp12& a12, const _Tp13& a13)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
i = set(i, a12); set(i, a13); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12,
typename _Tp13, typename _Tp14>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
const _Tp12& a12, const _Tp13& a13, const _Tp14& a14)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
i = set(i, a12); i = set(i, a13); set(i, a14); return *this;
}
template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12,
typename _Tp13, typename _Tp14, typename _Tp15>
Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
const _Tp12& a12, const _Tp13& a13, const _Tp14& a14, const _Tp15& a15)
{
int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
i = set(i, a12); i = set(i, a13); i = set(i, a14); set(i, a15); return *this;
}
bool run(int dims, size_t globalsize[],
size_t localsize[], bool sync, const Queue& q=Queue());
bool runTask(bool sync, const Queue& q=Queue());
size_t workGroupSize() const;
size_t preferedWorkGroupSizeMultiple() const;
bool compileWorkGroupSize(size_t wsz[]) const;
size_t localMemSize() const;
void* ptr() const;
struct Impl;
protected:
Impl* p;
};
class CV_EXPORTS Program
{
public:
Program();
Program(const ProgramSource& src,
const String& buildflags, String& errmsg);
explicit Program(const String& buf);
Program(const Program& prog);
Program& operator = (const Program& prog);
~Program();
bool create(const ProgramSource& src,
const String& buildflags, String& errmsg);
bool read(const String& buf, const String& buildflags);
bool write(String& buf) const;
const ProgramSource& source() const;
void* ptr() const;
String getPrefix() const;
static String getPrefix(const String& buildflags);
protected:
struct Impl;
Impl* p;
};
class CV_EXPORTS ProgramSource
{
public:
typedef uint64 hash_t;
ProgramSource();
explicit ProgramSource(const String& prog);
explicit ProgramSource(const char* prog);
~ProgramSource();
ProgramSource(const ProgramSource& prog);
ProgramSource& operator = (const ProgramSource& prog);
const String& source() const;
hash_t hash() const;
protected:
struct Impl;
Impl* p;
};
class CV_EXPORTS PlatformInfo
{
public:
PlatformInfo();
explicit PlatformInfo(void* id);
~PlatformInfo();
PlatformInfo(const PlatformInfo& i);
PlatformInfo& operator =(const PlatformInfo& i);
String name() const;
String vendor() const;
String version() const;
int deviceNumber() const;
void getDevice(Device& device, int d) const;
protected:
struct Impl;
Impl* p;
};
CV_EXPORTS const char* convertTypeStr(int sdepth, int ddepth, int cn, char* buf);
CV_EXPORTS const char* typeToStr(int t);
CV_EXPORTS const char* memopTypeToStr(int t);
CV_EXPORTS const char* vecopTypeToStr(int t);
CV_EXPORTS String kernelToStr(InputArray _kernel, int ddepth = -1, const char * name = NULL);
CV_EXPORTS void getPlatfomsInfo(std::vector<PlatformInfo>& platform_info);
enum OclVectorStrategy
{
// all matrices have its own vector width
OCL_VECTOR_OWN = 0,
// all matrices have maximal vector width among all matrices
// (useful for cases when matrices have different data types)
OCL_VECTOR_MAX = 1,
// default strategy
OCL_VECTOR_DEFAULT = OCL_VECTOR_OWN
};
CV_EXPORTS int predictOptimalVectorWidth(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
OclVectorStrategy strat = OCL_VECTOR_DEFAULT);
CV_EXPORTS int checkOptimalVectorWidth(const int *vectorWidths,
InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
OclVectorStrategy strat = OCL_VECTOR_DEFAULT);
// with OCL_VECTOR_MAX strategy
CV_EXPORTS int predictOptimalVectorWidthMax(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray());
CV_EXPORTS void buildOptionsAddMatrixDescription(String& buildOptions, const String& name, InputArray _m);
class CV_EXPORTS Image2D
{
public:
Image2D();
// src: The UMat from which to get image properties and data
// norm: Flag to enable the use of normalized channel data types
// alias: Flag indicating that the image should alias the src UMat.
// If true, changes to the image or src will be reflected in
// both objects.
explicit Image2D(const UMat &src, bool norm = false, bool alias = false);
Image2D(const Image2D & i);
~Image2D();
Image2D & operator = (const Image2D & i);
// Indicates if creating an aliased image should succeed. Depends on the
// underlying platform and the dimensions of the UMat.
static bool canCreateAlias(const UMat &u);
// Indicates if the image format is supported.
static bool isFormatSupported(int depth, int cn, bool norm);
void* ptr() const;
protected:
struct Impl;
Impl* p;
};
CV_EXPORTS MatAllocator* getOpenCLAllocator();
#ifdef __OPENCV_BUILD
namespace internal {
CV_EXPORTS bool isPerformanceCheckBypassed();
#define OCL_PERFORMANCE_CHECK(condition) (cv::ocl::internal::isPerformanceCheckBypassed() || (condition))
CV_EXPORTS bool isCLBuffer(UMat& u);
} // namespace internal
#endif
//! @}
}}
#endif

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lib/3rdParty/OpenCV3.1/include/opencv2/core/ocl_genbase.hpp vendored Normal file
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the OpenCV Foundation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_OPENCL_GENBASE_HPP__
#define __OPENCV_OPENCL_GENBASE_HPP__
namespace cv
{
namespace ocl
{
//! @cond IGNORED
struct ProgramEntry
{
const char* name;
const char* programStr;
const char* programHash;
};
//! @endcond
}
}
#endif

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CORE_OPENGL_HPP__
#define __OPENCV_CORE_OPENGL_HPP__
#ifndef __cplusplus
# error opengl.hpp header must be compiled as C++
#endif
#include "opencv2/core.hpp"
#include "ocl.hpp"
namespace cv { namespace ogl {
/** @addtogroup core_opengl
This section describes OpenGL interoperability.
To enable OpenGL support, configure OpenCV using CMake with WITH_OPENGL=ON . Currently OpenGL is
supported only with WIN32, GTK and Qt backends on Windows and Linux (MacOS and Android are not
supported). For GTK backend gtkglext-1.0 library is required.
To use OpenGL functionality you should first create OpenGL context (window or frame buffer). You can
do this with namedWindow function or with other OpenGL toolkit (GLUT, for example).
*/
//! @{
/////////////////// OpenGL Objects ///////////////////
/** @brief Smart pointer for OpenGL buffer object with reference counting.
Buffer Objects are OpenGL objects that store an array of unformatted memory allocated by the OpenGL
context. These can be used to store vertex data, pixel data retrieved from images or the
framebuffer, and a variety of other things.
ogl::Buffer has interface similar with Mat interface and represents 2D array memory.
ogl::Buffer supports memory transfers between host and device and also can be mapped to CUDA memory.
*/
class CV_EXPORTS Buffer
{
public:
/** @brief The target defines how you intend to use the buffer object.
*/
enum Target
{
ARRAY_BUFFER = 0x8892, //!< The buffer will be used as a source for vertex data
ELEMENT_ARRAY_BUFFER = 0x8893, //!< The buffer will be used for indices (in glDrawElements, for example)
PIXEL_PACK_BUFFER = 0x88EB, //!< The buffer will be used for reading from OpenGL textures
PIXEL_UNPACK_BUFFER = 0x88EC //!< The buffer will be used for writing to OpenGL textures
};
enum Access
{
READ_ONLY = 0x88B8,
WRITE_ONLY = 0x88B9,
READ_WRITE = 0x88BA
};
/** @brief The constructors.
Creates empty ogl::Buffer object, creates ogl::Buffer object from existed buffer ( abufId
parameter), allocates memory for ogl::Buffer object or copies from host/device memory.
*/
Buffer();
/** @overload
@param arows Number of rows in a 2D array.
@param acols Number of columns in a 2D array.
@param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details.
@param abufId Buffer object name.
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
Buffer(int arows, int acols, int atype, unsigned int abufId, bool autoRelease = false);
/** @overload
@param asize 2D array size.
@param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details.
@param abufId Buffer object name.
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
Buffer(Size asize, int atype, unsigned int abufId, bool autoRelease = false);
/** @overload
@param arows Number of rows in a 2D array.
@param acols Number of columns in a 2D array.
@param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details.
@param target Buffer usage. See cv::ogl::Buffer::Target .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
Buffer(int arows, int acols, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @overload
@param asize 2D array size.
@param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details.
@param target Buffer usage. See cv::ogl::Buffer::Target .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
Buffer(Size asize, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @overload
@param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or std::vector ).
@param target Buffer usage. See cv::ogl::Buffer::Target .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
explicit Buffer(InputArray arr, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @brief Allocates memory for ogl::Buffer object.
@param arows Number of rows in a 2D array.
@param acols Number of columns in a 2D array.
@param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details.
@param target Buffer usage. See cv::ogl::Buffer::Target .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
void create(int arows, int acols, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @overload
@param asize 2D array size.
@param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details.
@param target Buffer usage. See cv::ogl::Buffer::Target .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
void create(Size asize, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @brief Decrements the reference counter and destroys the buffer object if needed.
The function will call setAutoRelease(true) .
*/
void release();
/** @brief Sets auto release mode.
The lifetime of the OpenGL object is tied to the lifetime of the context. If OpenGL context was
bound to a window it could be released at any time (user can close a window). If object's destructor
is called after destruction of the context it will cause an error. Thus ogl::Buffer doesn't destroy
OpenGL object in destructor by default (all OpenGL resources will be released with OpenGL context).
This function can force ogl::Buffer destructor to destroy OpenGL object.
@param flag Auto release mode (if true, release will be called in object's destructor).
*/
void setAutoRelease(bool flag);
/** @brief Copies from host/device memory to OpenGL buffer.
@param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or std::vector ).
@param target Buffer usage. See cv::ogl::Buffer::Target .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
void copyFrom(InputArray arr, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @overload */
void copyFrom(InputArray arr, cuda::Stream& stream, Target target = ARRAY_BUFFER, bool autoRelease = false);
/** @brief Copies from OpenGL buffer to host/device memory or another OpenGL buffer object.
@param arr Destination array (host or device memory, can be Mat , cuda::GpuMat , std::vector or
ogl::Buffer ).
*/
void copyTo(OutputArray arr) const;
/** @overload */
void copyTo(OutputArray arr, cuda::Stream& stream) const;
/** @brief Creates a full copy of the buffer object and the underlying data.
@param target Buffer usage for destination buffer.
@param autoRelease Auto release mode for destination buffer.
*/
Buffer clone(Target target = ARRAY_BUFFER, bool autoRelease = false) const;
/** @brief Binds OpenGL buffer to the specified buffer binding point.
@param target Binding point. See cv::ogl::Buffer::Target .
*/
void bind(Target target) const;
/** @brief Unbind any buffers from the specified binding point.
@param target Binding point. See cv::ogl::Buffer::Target .
*/
static void unbind(Target target);
/** @brief Maps OpenGL buffer to host memory.
mapHost maps to the client's address space the entire data store of the buffer object. The data can
then be directly read and/or written relative to the returned pointer, depending on the specified
access policy.
A mapped data store must be unmapped with ogl::Buffer::unmapHost before its buffer object is used.
This operation can lead to memory transfers between host and device.
Only one buffer object can be mapped at a time.
@param access Access policy, indicating whether it will be possible to read from, write to, or both
read from and write to the buffer object's mapped data store. The symbolic constant must be
ogl::Buffer::READ_ONLY , ogl::Buffer::WRITE_ONLY or ogl::Buffer::READ_WRITE .
*/
Mat mapHost(Access access);
/** @brief Unmaps OpenGL buffer.
*/
void unmapHost();
//! map to device memory (blocking)
cuda::GpuMat mapDevice();
void unmapDevice();
/** @brief Maps OpenGL buffer to CUDA device memory.
This operatation doesn't copy data. Several buffer objects can be mapped to CUDA memory at a time.
A mapped data store must be unmapped with ogl::Buffer::unmapDevice before its buffer object is used.
*/
cuda::GpuMat mapDevice(cuda::Stream& stream);
/** @brief Unmaps OpenGL buffer.
*/
void unmapDevice(cuda::Stream& stream);
int rows() const;
int cols() const;
Size size() const;
bool empty() const;
int type() const;
int depth() const;
int channels() const;
int elemSize() const;
int elemSize1() const;
//! get OpenGL opject id
unsigned int bufId() const;
class Impl;
private:
Ptr<Impl> impl_;
int rows_;
int cols_;
int type_;
};
/** @brief Smart pointer for OpenGL 2D texture memory with reference counting.
*/
class CV_EXPORTS Texture2D
{
public:
/** @brief An Image Format describes the way that the images in Textures store their data.
*/
enum Format
{
NONE = 0,
DEPTH_COMPONENT = 0x1902, //!< Depth
RGB = 0x1907, //!< Red, Green, Blue
RGBA = 0x1908 //!< Red, Green, Blue, Alpha
};
/** @brief The constructors.
Creates empty ogl::Texture2D object, allocates memory for ogl::Texture2D object or copies from
host/device memory.
*/
Texture2D();
/** @overload */
Texture2D(int arows, int acols, Format aformat, unsigned int atexId, bool autoRelease = false);
/** @overload */
Texture2D(Size asize, Format aformat, unsigned int atexId, bool autoRelease = false);
/** @overload
@param arows Number of rows.
@param acols Number of columns.
@param aformat Image format. See cv::ogl::Texture2D::Format .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
Texture2D(int arows, int acols, Format aformat, bool autoRelease = false);
/** @overload
@param asize 2D array size.
@param aformat Image format. See cv::ogl::Texture2D::Format .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
Texture2D(Size asize, Format aformat, bool autoRelease = false);
/** @overload
@param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or ogl::Buffer ).
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
explicit Texture2D(InputArray arr, bool autoRelease = false);
/** @brief Allocates memory for ogl::Texture2D object.
@param arows Number of rows.
@param acols Number of columns.
@param aformat Image format. See cv::ogl::Texture2D::Format .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
void create(int arows, int acols, Format aformat, bool autoRelease = false);
/** @overload
@param asize 2D array size.
@param aformat Image format. See cv::ogl::Texture2D::Format .
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
void create(Size asize, Format aformat, bool autoRelease = false);
/** @brief Decrements the reference counter and destroys the texture object if needed.
The function will call setAutoRelease(true) .
*/
void release();
/** @brief Sets auto release mode.
@param flag Auto release mode (if true, release will be called in object's destructor).
The lifetime of the OpenGL object is tied to the lifetime of the context. If OpenGL context was
bound to a window it could be released at any time (user can close a window). If object's destructor
is called after destruction of the context it will cause an error. Thus ogl::Texture2D doesn't
destroy OpenGL object in destructor by default (all OpenGL resources will be released with OpenGL
context). This function can force ogl::Texture2D destructor to destroy OpenGL object.
*/
void setAutoRelease(bool flag);
/** @brief Copies from host/device memory to OpenGL texture.
@param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or ogl::Buffer ).
@param autoRelease Auto release mode (if true, release will be called in object's destructor).
*/
void copyFrom(InputArray arr, bool autoRelease = false);
/** @brief Copies from OpenGL texture to host/device memory or another OpenGL texture object.
@param arr Destination array (host or device memory, can be Mat , cuda::GpuMat , ogl::Buffer or
ogl::Texture2D ).
@param ddepth Destination depth.
@param autoRelease Auto release mode for destination buffer (if arr is OpenGL buffer or texture).
*/
void copyTo(OutputArray arr, int ddepth = CV_32F, bool autoRelease = false) const;
/** @brief Binds texture to current active texture unit for GL_TEXTURE_2D target.
*/
void bind() const;
int rows() const;
int cols() const;
Size size() const;
bool empty() const;
Format format() const;
//! get OpenGL opject id
unsigned int texId() const;
class Impl;
private:
Ptr<Impl> impl_;
int rows_;
int cols_;
Format format_;
};
/** @brief Wrapper for OpenGL Client-Side Vertex arrays.
ogl::Arrays stores vertex data in ogl::Buffer objects.
*/
class CV_EXPORTS Arrays
{
public:
/** @brief Default constructor
*/
Arrays();
/** @brief Sets an array of vertex coordinates.
@param vertex array with vertex coordinates, can be both host and device memory.
*/
void setVertexArray(InputArray vertex);
/** @brief Resets vertex coordinates.
*/
void resetVertexArray();
/** @brief Sets an array of vertex colors.
@param color array with vertex colors, can be both host and device memory.
*/
void setColorArray(InputArray color);
/** @brief Resets vertex colors.
*/
void resetColorArray();
/** @brief Sets an array of vertex normals.
@param normal array with vertex normals, can be both host and device memory.
*/
void setNormalArray(InputArray normal);
/** @brief Resets vertex normals.
*/
void resetNormalArray();
/** @brief Sets an array of vertex texture coordinates.
@param texCoord array with vertex texture coordinates, can be both host and device memory.
*/
void setTexCoordArray(InputArray texCoord);
/** @brief Resets vertex texture coordinates.
*/
void resetTexCoordArray();
/** @brief Releases all inner buffers.
*/
void release();
/** @brief Sets auto release mode all inner buffers.
@param flag Auto release mode.
*/
void setAutoRelease(bool flag);
/** @brief Binds all vertex arrays.
*/
void bind() const;
/** @brief Returns the vertex count.
*/
int size() const;
bool empty() const;
private:
int size_;
Buffer vertex_;
Buffer color_;
Buffer normal_;
Buffer texCoord_;
};
/////////////////// Render Functions ///////////////////
//! render mode
enum RenderModes {
POINTS = 0x0000,
LINES = 0x0001,
LINE_LOOP = 0x0002,
LINE_STRIP = 0x0003,
TRIANGLES = 0x0004,
TRIANGLE_STRIP = 0x0005,
TRIANGLE_FAN = 0x0006,
QUADS = 0x0007,
QUAD_STRIP = 0x0008,
POLYGON = 0x0009
};
/** @brief Render OpenGL texture or primitives.
@param tex Texture to draw.
@param wndRect Region of window, where to draw a texture (normalized coordinates).
@param texRect Region of texture to draw (normalized coordinates).
*/
CV_EXPORTS void render(const Texture2D& tex,
Rect_<double> wndRect = Rect_<double>(0.0, 0.0, 1.0, 1.0),
Rect_<double> texRect = Rect_<double>(0.0, 0.0, 1.0, 1.0));
/** @overload
@param arr Array of privitives vertices.
@param mode Render mode. One of cv::ogl::RenderModes
@param color Color for all vertices. Will be used if arr doesn't contain color array.
*/
CV_EXPORTS void render(const Arrays& arr, int mode = POINTS, Scalar color = Scalar::all(255));
/** @overload
@param arr Array of privitives vertices.
@param indices Array of vertices indices (host or device memory).
@param mode Render mode. One of cv::ogl::RenderModes
@param color Color for all vertices. Will be used if arr doesn't contain color array.
*/
CV_EXPORTS void render(const Arrays& arr, InputArray indices, int mode = POINTS, Scalar color = Scalar::all(255));
/////////////////// CL-GL Interoperability Functions ///////////////////
namespace ocl {
using namespace cv::ocl;
// TODO static functions in the Context class
/** @brief Creates OpenCL context from GL.
@return Returns reference to OpenCL Context
*/
CV_EXPORTS Context& initializeContextFromGL();
} // namespace cv::ogl::ocl
/** @brief Converts InputArray to Texture2D object.
@param src - source InputArray.
@param texture - destination Texture2D object.
*/
CV_EXPORTS void convertToGLTexture2D(InputArray src, Texture2D& texture);
/** @brief Converts Texture2D object to OutputArray.
@param texture - source Texture2D object.
@param dst - destination OutputArray.
*/
CV_EXPORTS void convertFromGLTexture2D(const Texture2D& texture, OutputArray dst);
/** @brief Maps Buffer object to process on CL side (convert to UMat).
Function creates CL buffer from GL one, and then constructs UMat that can be used
to process buffer data with OpenCV functions. Note that in current implementation
UMat constructed this way doesn't own corresponding GL buffer object, so it is
the user responsibility to close down CL/GL buffers relationships by explicitly
calling unmapGLBuffer() function.
@param buffer - source Buffer object.
@param accessFlags - data access flags (ACCESS_READ|ACCESS_WRITE).
@return Returns UMat object
*/
CV_EXPORTS UMat mapGLBuffer(const Buffer& buffer, int accessFlags = ACCESS_READ|ACCESS_WRITE);
/** @brief Unmaps Buffer object (releases UMat, previously mapped from Buffer).
Function must be called explicitly by the user for each UMat previously constructed
by the call to mapGLBuffer() function.
@param u - source UMat, created by mapGLBuffer().
*/
CV_EXPORTS void unmapGLBuffer(UMat& u);
}} // namespace cv::ogl
namespace cv { namespace cuda {
//! @addtogroup cuda
//! @{
/** @brief Sets a CUDA device and initializes it for the current thread with OpenGL interoperability.
This function should be explicitly called after OpenGL context creation and before any CUDA calls.
@param device System index of a CUDA device starting with 0.
@ingroup core_opengl
*/
CV_EXPORTS void setGlDevice(int device = 0);
//! @}
}}
//! @cond IGNORED
////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////
inline
cv::ogl::Buffer::Buffer(int arows, int acols, int atype, Target target, bool autoRelease) : rows_(0), cols_(0), type_(0)
{
create(arows, acols, atype, target, autoRelease);
}
inline
cv::ogl::Buffer::Buffer(Size asize, int atype, Target target, bool autoRelease) : rows_(0), cols_(0), type_(0)
{
create(asize, atype, target, autoRelease);
}
inline
void cv::ogl::Buffer::create(Size asize, int atype, Target target, bool autoRelease)
{
create(asize.height, asize.width, atype, target, autoRelease);
}
inline
int cv::ogl::Buffer::rows() const
{
return rows_;
}
inline
int cv::ogl::Buffer::cols() const
{
return cols_;
}
inline
cv::Size cv::ogl::Buffer::size() const
{
return Size(cols_, rows_);
}
inline
bool cv::ogl::Buffer::empty() const
{
return rows_ == 0 || cols_ == 0;
}
inline
int cv::ogl::Buffer::type() const
{
return type_;
}
inline
int cv::ogl::Buffer::depth() const
{
return CV_MAT_DEPTH(type_);
}
inline
int cv::ogl::Buffer::channels() const
{
return CV_MAT_CN(type_);
}
inline
int cv::ogl::Buffer::elemSize() const
{
return CV_ELEM_SIZE(type_);
}
inline
int cv::ogl::Buffer::elemSize1() const
{
return CV_ELEM_SIZE1(type_);
}
///////
inline
cv::ogl::Texture2D::Texture2D(int arows, int acols, Format aformat, bool autoRelease) : rows_(0), cols_(0), format_(NONE)
{
create(arows, acols, aformat, autoRelease);
}
inline
cv::ogl::Texture2D::Texture2D(Size asize, Format aformat, bool autoRelease) : rows_(0), cols_(0), format_(NONE)
{
create(asize, aformat, autoRelease);
}
inline
void cv::ogl::Texture2D::create(Size asize, Format aformat, bool autoRelease)
{
create(asize.height, asize.width, aformat, autoRelease);
}
inline
int cv::ogl::Texture2D::rows() const
{
return rows_;
}
inline
int cv::ogl::Texture2D::cols() const
{
return cols_;
}
inline
cv::Size cv::ogl::Texture2D::size() const
{
return Size(cols_, rows_);
}
inline
bool cv::ogl::Texture2D::empty() const
{
return rows_ == 0 || cols_ == 0;
}
inline
cv::ogl::Texture2D::Format cv::ogl::Texture2D::format() const
{
return format_;
}
///////
inline
cv::ogl::Arrays::Arrays() : size_(0)
{
}
inline
int cv::ogl::Arrays::size() const
{
return size_;
}
inline
bool cv::ogl::Arrays::empty() const
{
return size_ == 0;
}
//! @endcond
#endif /* __OPENCV_CORE_OPENGL_HPP__ */

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