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Merged the trunk r8589:8653 - all changes related to build warnings

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This commit is contained in:
Andrey Kamaev 2012-06-15 13:04:17 +00:00
parent 73c152abc4
commit bd0e0b5800
438 changed files with 20374 additions and 19674 deletions
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27
3rdparty/libjasper/CMakeLists.txt vendored
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@ -7,31 +7,24 @@ project(${JASPER_LIBRARY})
add_definitions(-DEXCLUDE_MIF_SUPPORT -DEXCLUDE_PNM_SUPPORT -DEXCLUDE_BMP_SUPPORT -DEXCLUDE_RAS_SUPPORT -DEXCLUDE_JPG_SUPPORT -DEXCLUDE_PGX_SUPPORT)
# List of C++ files:
ocv_include_directories(${CMAKE_CURRENT_SOURCE_DIR})
# The .cpp files:
file(GLOB lib_srcs *.c)
file(GLOB lib_hdrs *.h)
file(GLOB lib_ext_hdrs jasper/*.h)
# ----------------------------------------------------------------------------------
# Define the library target:
# Define the library target:
# ----------------------------------------------------------------------------------
add_library(${JASPER_LIBRARY} STATIC ${lib_srcs} ${lib_hdrs} ${lib_ext_hdrs})
if(MSVC)
if(NOT ENABLE_NOISY_WARNINGS)
string(REPLACE "/W3" "/W0" CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
string(REPLACE "/W4" "/W0" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
endif()
add_definitions(-DJAS_WIN_MSVC_BUILD)
endif()
if(CMAKE_COMPILER_IS_GNUCXX)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wno-uninitialized")
endif()
ocv_warnings_disable(CMAKE_C_FLAGS -Wno-implicit-function-declaration -Wno-uninitialized -Wmissing-prototypes -Wmissing-declarations -Wunused -Wshadow
/wd4013 /wd4018 /wd4715 /wd4244 /wd4101 /wd4267)
if(UNIX)
if(CMAKE_COMPILER_IS_GNUCXX OR CV_ICC)
@ -39,16 +32,12 @@ if(UNIX)
endif()
endif()
if(CMAKE_COMPILER_IS_GNUCXX AND NOT ENABLE_NOISY_WARNINGS)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wno-implicit-function-declaration -Wno-unused")
endif()
set_target_properties(${JASPER_LIBRARY}
PROPERTIES
OUTPUT_NAME ${JASPER_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
PROPERTIES
OUTPUT_NAME ${JASPER_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${JASPER_LIBRARY} PROPERTIES FOLDER "3rdparty")

19
3rdparty/libjpeg/CMakeLists.txt vendored
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@ -4,24 +4,17 @@
# ----------------------------------------------------------------------------
project(${JPEG_LIBRARY})
# List of C++ files:
ocv_include_directories(${CMAKE_CURRENT_SOURCE_DIR})
# The .cpp files:
file(GLOB lib_srcs *.c)
file(GLOB lib_hdrs *.h)
# ----------------------------------------------------------------------------------
# Define the library target:
# Define the library target:
# ----------------------------------------------------------------------------------
add_library(${JPEG_LIBRARY} STATIC ${lib_srcs} ${lib_hdrs})
if(MSVC)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /W3")
endif()
if(UNIX)
if(CMAKE_COMPILER_IS_GNUCXX OR CV_ICC)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
@ -32,11 +25,13 @@ if(CMAKE_COMPILER_IS_GNUCXX)
set_source_files_properties(jcdctmgr.c PROPERTIES COMPILE_FLAGS "-O1")
endif()
ocv_warnings_disable(CMAKE_C_FLAGS -Wcast-align -Wshadow)
set_target_properties(${JPEG_LIBRARY}
PROPERTIES OUTPUT_NAME ${JPEG_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}
)
PROPERTIES OUTPUT_NAME ${JPEG_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}
)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${JPEG_LIBRARY} PROPERTIES FOLDER "3rdparty")

18
3rdparty/libpng/CMakeLists.txt vendored
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@ -4,34 +4,30 @@
# ----------------------------------------------------------------------------
project(${PNG_LIBRARY})
# List of C++ files:
ocv_include_directories("${CMAKE_CURRENT_SOURCE_DIR}" ${ZLIB_INCLUDE_DIR})
file(GLOB lib_srcs *.c)
file(GLOB lib_hdrs *.h)
# ----------------------------------------------------------------------------------
# Define the library target:
# Define the library target:
# ----------------------------------------------------------------------------------
add_library(${PNG_LIBRARY} STATIC ${lib_srcs} ${lib_hdrs})
if(MSVC)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /W3")
endif()
if(UNIX)
if(CMAKE_COMPILER_IS_GNUCXX OR CV_ICC)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
endif()
endif()
ocv_warnings_disable(CMAKE_C_FLAGS -Wcast-align)
set_target_properties(${PNG_LIBRARY}
PROPERTIES OUTPUT_NAME ${PNG_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
PROPERTIES OUTPUT_NAME ${PNG_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${PNG_LIBRARY} PROPERTIES FOLDER "3rdparty")

18
3rdparty/libtiff/CMakeLists.txt vendored
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@ -26,7 +26,6 @@ configure_file("${CMAKE_CURRENT_SOURCE_DIR}/tif_config.h.cmakein"
ocv_include_directories("${CMAKE_CURRENT_SOURCE_DIR}" "${CMAKE_CURRENT_BINARY_DIR}" ${ZLIB_INCLUDE_DIR})
# List of C++ files:
set(lib_srcs
tif_aux.c
tif_close.c
@ -91,10 +90,9 @@ if(WIN32)
list(APPEND lib_srcs tif_win32.c)
endif(WIN32)
if(MSVC AND NOT ENABLE_NOISY_WARNINGS)
string(REPLACE "/W4" "/W0" CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
string(REPLACE "/W4" "/W0" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
endif()
ocv_warnings_disable(CMAKE_C_FLAGS -Wno-unused-but-set-variable -Wmissing-prototypes -Wmissing-declarations -Wundef
-Wcast-align -Wshadow -Wno-maybe-uninitialized -Wno-pointer-to-int-cast -Wno-int-to-pointer-cast)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wmissing-declarations /wd4100 /wd4244 /wd4706 /wd4127 /wd4701 /wd4018 /wd4267 /wd4306 /wd4305 /wd4312 /wd4311)
if(UNIX AND (CMAKE_COMPILER_IS_GNUCXX OR CV_ICC))
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
@ -104,11 +102,11 @@ add_library(${TIFF_LIBRARY} STATIC ${lib_srcs})
target_link_libraries(${TIFF_LIBRARY} ${ZLIB_LIBRARIES})
set_target_properties(${TIFF_LIBRARY}
PROPERTIES
OUTPUT_NAME "${TIFF_LIBRARY}"
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
PROPERTIES
OUTPUT_NAME "${TIFF_LIBRARY}"
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${TIFF_LIBRARY} PROPERTIES FOLDER "3rdparty")

2
3rdparty/libtiff/tif_config.h.cmakein vendored
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@ -143,7 +143,7 @@
/* Signed 64-bit type formatter */
/* Unsigned 64-bit type formatter */
#ifdef _MSC_VER
#if defined _MSC_VER || defined __MINGW__ || defined __MINGW32__
# define TIFF_UINT64_FORMAT "%I64u"
# define TIFF_SSIZE_FORMAT "%Iu"
#else

13
3rdparty/tbb/CMakeLists.txt vendored
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@ -119,13 +119,16 @@ endif()
add_library(tbb STATIC ${lib_srcs} ${lib_hdrs} "${CMAKE_CURRENT_SOURCE_DIR}/android_additional.h" "${CMAKE_CURRENT_SOURCE_DIR}/${tbb_version_file}")
target_link_libraries(tbb c m dl)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -w -include \"${CMAKE_CURRENT_SOURCE_DIR}/android_additional.h\"")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wmissing-declarations)
string(REPLACE "-Werror=non-virtual-dtor" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -include \"${CMAKE_CURRENT_SOURCE_DIR}/android_additional.h\"")
set_target_properties(tbb
PROPERTIES OUTPUT_NAME tbb
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
PROPERTIES OUTPUT_NAME tbb
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/3rdparty/${OPENCV_LIB_INSTALL_PATH}"
)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(tbb PROPERTIES FOLDER "3rdparty")

2
3rdparty/tbb/version_string.tmp vendored
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@ -6,4 +6,4 @@
"TBB: BUILD_GLIBC Unknown" ENDL \
"TBB: BUILD_LD Unknown" ENDL \
"TBB: BUILD_TARGET Unknown" ENDL \
"TBB: BUILD_COMMAND use cv::getBuildInformation() for details" ENDL \
"TBB: BUILD_COMMAND use cv::getBuildInformation() for details" ENDL

2
3rdparty/tbb/version_string.ver vendored
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@ -6,4 +6,4 @@
#N": BUILD_GLIBC Unknown" ENDL \
#N": BUILD_LD Unknown" ENDL \
#N": BUILD_TARGET Unknown" ENDL \
#N": BUILD_COMMAND use cv::getBuildInformation() for details" ENDL \
#N": BUILD_COMMAND use cv::getBuildInformation() for details" ENDL

13
3rdparty/zlib/CMakeLists.txt vendored
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@ -5,19 +5,10 @@
project(${ZLIB_LIBRARY} C)
include(CheckTypeSize)
include(CheckFunctionExists)
include(CheckIncludeFile)
include(CheckCSourceCompiles)
#
# Check to see if we have large file support
#
check_type_size(off64_t OFF64_T)
if(HAVE_OFF64_T)
add_definitions(-D_LARGEFILE64_SOURCE=1)
endif()
#
# Check for fseeko
#
@ -82,9 +73,7 @@ if(UNIX)
endif()
endif()
if(MSVC AND NOT ENABLE_NOISY_WARNINGS)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /wd4013")
endif()
ocv_warnings_disable(CMAKE_C_FLAGS /wd4013 -Wattributes -Wstrict-prototypes -Wmissing-prototypes -Wmissing-declarations)
set_target_properties(${ZLIB_LIBRARY} PROPERTIES
OUTPUT_NAME ${ZLIB_LIBRARY}

10
3rdparty/zlib/zconf.h.cmakein vendored
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@ -410,10 +410,18 @@ typedef uLong FAR uLongf;
* both "#undef _LARGEFILE64_SOURCE" and "#define _LARGEFILE64_SOURCE 0" as
* equivalently requesting no 64-bit operations
*/
#if -_LARGEFILE64_SOURCE - -1 == 1
#if defined _LARGEFILE64_SOURCE && -_LARGEFILE64_SOURCE - -1 == 1
# undef _LARGEFILE64_SOURCE
#endif
#ifndef _LFS64_LARGEFILE
# define _LFS64_LARGEFILE 0
#endif
#ifndef _FILE_OFFSET_BITS
# define _FILE_OFFSET_BITS 0
#endif
#if defined(_LARGEFILE64_SOURCE) && _LFS64_LARGEFILE-0
# define Z_LARGE
#endif

18
CMakeLists.txt
View File

@ -188,6 +188,8 @@ OCV_OPTION(ENABLE_SSE42 "Enable SSE4.2 instructions"
OCV_OPTION(ENABLE_NOISY_WARNINGS "Show all warnings even if they are too noisy" OFF )
OCV_OPTION(OPENCV_WARNINGS_ARE_ERRORS "Treat warnings as errors" OFF )
OCV_OPTION(OPENCV_CAN_BREAK_BINARY_COMPATIBILITY "Allow changes breaking binary compatibility with OpenCV 2.4.0" OFF )
# uncategorized options
# ===================================================
OCV_OPTION(CMAKE_VERBOSE "Verbose mode" OFF )
@ -286,13 +288,13 @@ endif()
# ----------------------------------------------------------------------------
# OpenCV compiler and linker options
# ----------------------------------------------------------------------------
include(cmake/OpenCVCompilerOptions.cmake REQUIRED)
# In case of Makefiles if the user does not setup CMAKE_BUILD_TYPE, assume it's Release:
if(CMAKE_GENERATOR MATCHES "Makefiles|Ninja" AND "${CMAKE_BUILD_TYPE}" STREQUAL "")
set(CMAKE_BUILD_TYPE Release)
endif()
include(cmake/OpenCVCompilerOptions.cmake REQUIRED)
# ----------------------------------------------------------------------------
# Use statically or dynamically linked CRT?
@ -328,6 +330,15 @@ if(UNIX)
endif()
endif()
#
# Check to see if we have large file support (needed by zlib)
#
include(CheckTypeSize)
check_type_size(off64_t OFF64_T)
if(HAVE_OFF64_T)
add_definitions(-D_LARGEFILE64_SOURCE=1)
endif()
include(cmake/OpenCVPCHSupport.cmake REQUIRED)
include(cmake/OpenCVModule.cmake REQUIRED)
@ -471,6 +482,7 @@ else()
status(" Linker flags (Release):" ${CMAKE_SHARED_LINKER_FLAGS} ${CMAKE_SHARED_LINKER_FLAGS_RELEASE})
status(" Linker flags (Debug):" ${CMAKE_SHARED_LINKER_FLAGS} ${CMAKE_SHARED_LINKER_FLAGS_DEBUG})
endif()
status(" Precompiled headers:" PCHSupport_FOUND AND ENABLE_PRECOMPILED_HEADERS THEN YES ELSE NO)
# ========================== OpenCV modules ==========================
status("")
@ -560,7 +572,7 @@ if(WITH_TIFF)
if(TIFF_VERSION_STRING AND TIFF_FOUND)
status(" TIFF:" "${TIFF_LIBRARY} (ver ${TIFF_VERSION} - ${TIFF_VERSION_STRING})")
else()
status(" TIFF:" TIFF_FOUND THEN "${TIFF_LIBRARY} (ver ${TIFF_VERSION})" ELSE "build (ver ${TIFF_VERSION})")
status(" TIFF:" TIFF_FOUND THEN "${TIFF_LIBRARY} (ver ${TIFF_VERSION})" ELSE "build (ver ${TIFF_VERSION} - ${TIFF_VERSION_STRING})")
endif()
else()
status(" TIFF:" "NO")

3
apps/haartraining/_cvcommon.h
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@ -42,6 +42,9 @@
#ifndef __CVCOMMON_H_
#define __CVCOMMON_H_
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "cxcore.h"
#include "cv.h"
#include "cxmisc.h"

103
apps/haartraining/cvboost.cpp
View File

@ -80,11 +80,11 @@ typedef struct CvValArray
( *( (float*) (aux->data + ((int) (idx1)) * aux->step ) ) < \
*( (float*) (aux->data + ((int) (idx2)) * aux->step ) ) )
CV_IMPLEMENT_QSORT_EX( icvSortIndexedValArray_16s, short, CMP_VALUES, CvValArray* )
static CV_IMPLEMENT_QSORT_EX( icvSortIndexedValArray_16s, short, CMP_VALUES, CvValArray* )
CV_IMPLEMENT_QSORT_EX( icvSortIndexedValArray_32s, int, CMP_VALUES, CvValArray* )
static CV_IMPLEMENT_QSORT_EX( icvSortIndexedValArray_32s, int, CMP_VALUES, CvValArray* )
CV_IMPLEMENT_QSORT_EX( icvSortIndexedValArray_32f, float, CMP_VALUES, CvValArray* )
static CV_IMPLEMENT_QSORT_EX( icvSortIndexedValArray_32f, float, CMP_VALUES, CvValArray* )
CV_BOOST_IMPL
void cvGetSortedIndices( CvMat* val, CvMat* idx, int sortcols )
@ -190,7 +190,7 @@ float cvEvalStumpClassifier( CvClassifier* classifier, CvMat* sample )
}
#define ICV_DEF_FIND_STUMP_THRESHOLD( suffix, type, error ) \
CV_BOOST_IMPL int icvFindStumpThreshold_##suffix( \
static int icvFindStumpThreshold_##suffix( \
uchar* data, size_t datastep, \
uchar* wdata, size_t wstep, \
uchar* ydata, size_t ystep, \
@ -213,13 +213,10 @@ CV_BOOST_IMPL int icvFindStumpThreshold_##suffix(
float* curval = NULL; \
float curlerror = 0.0F; \
float currerror = 0.0F; \
float wposl; \
float wposr; \
\
int i = 0; \
int idx = 0; \
\
wposl = wposr = 0.0F; \
if( *sumw == FLT_MAX ) \
{ \
/* calculate sums */ \
@ -298,8 +295,8 @@ CV_BOOST_IMPL int icvFindStumpThreshold_##suffix(
*/
#define ICV_DEF_FIND_STUMP_THRESHOLD_MISC( suffix, type ) \
ICV_DEF_FIND_STUMP_THRESHOLD( misc_##suffix, type, \
wposl = 0.5F * ( wl + wyl ); \
wposr = 0.5F * ( wr + wyr ); \
float wposl = 0.5F * ( wl + wyl ); \
float wposr = 0.5F * ( wr + wyr ); \
curleft = 0.5F * ( 1.0F + curleft ); \
curright = 0.5F * ( 1.0F + curright ); \
curlerror = MIN( wposl, wl - wposl ); \
@ -311,8 +308,8 @@ CV_BOOST_IMPL int icvFindStumpThreshold_##suffix(
*/
#define ICV_DEF_FIND_STUMP_THRESHOLD_GINI( suffix, type ) \
ICV_DEF_FIND_STUMP_THRESHOLD( gini_##suffix, type, \
wposl = 0.5F * ( wl + wyl ); \
wposr = 0.5F * ( wr + wyr ); \
float wposl = 0.5F * ( wl + wyl ); \
float wposr = 0.5F * ( wr + wyr ); \
curleft = 0.5F * ( 1.0F + curleft ); \
curright = 0.5F * ( 1.0F + curright ); \
curlerror = 2.0F * wposl * ( 1.0F - curleft ); \
@ -326,8 +323,8 @@ CV_BOOST_IMPL int icvFindStumpThreshold_##suffix(
*/
#define ICV_DEF_FIND_STUMP_THRESHOLD_ENTROPY( suffix, type ) \
ICV_DEF_FIND_STUMP_THRESHOLD( entropy_##suffix, type, \
wposl = 0.5F * ( wl + wyl ); \
wposr = 0.5F * ( wr + wyr ); \
float wposl = 0.5F * ( wl + wyl ); \
float wposr = 0.5F * ( wr + wyr ); \
curleft = 0.5F * ( 1.0F + curleft ); \
curright = 0.5F * ( 1.0F + curright ); \
curlerror = currerror = 0.0F; \
@ -1149,7 +1146,7 @@ float cvEvalCARTClassifier( CvClassifier* classifier, CvMat* sample )
return ((CvCARTClassifier*) classifier)->val[-idx];
}
CV_BOOST_IMPL
static
float cvEvalCARTClassifierIdx( CvClassifier* classifier, CvMat* sample )
{
CV_FUNCNAME( "cvEvalCARTClassifierIdx" );
@ -1209,7 +1206,7 @@ void cvReleaseCARTClassifier( CvClassifier** classifier )
*classifier = NULL;
}
void CV_CDECL icvDefaultSplitIdx_R( int compidx, float threshold,
static void CV_CDECL icvDefaultSplitIdx_R( int compidx, float threshold,
CvMat* idx, CvMat** left, CvMat** right,
void* userdata )
{
@ -1258,7 +1255,7 @@ void CV_CDECL icvDefaultSplitIdx_R( int compidx, float threshold,
}
}
void CV_CDECL icvDefaultSplitIdx_C( int compidx, float threshold,
static void CV_CDECL icvDefaultSplitIdx_C( int compidx, float threshold,
CvMat* idx, CvMat** left, CvMat** right,
void* userdata )
{
@ -1529,7 +1526,7 @@ typedef struct CvBoostTrainer
* using ANY appropriate weak classifier
*/
CV_BOOST_IMPL
static
CvBoostTrainer* icvBoostStartTraining( CvMat* trainClasses,
CvMat* weakTrainVals,
CvMat* /*weights*/,
@ -1560,7 +1557,7 @@ CvBoostTrainer* icvBoostStartTraining( CvMat* trainClasses,
CV_MAT2VEC( *trainClasses, ydata, ystep, m );
CV_MAT2VEC( *weakTrainVals, traindata, trainstep, trainnum );
assert( m == trainnum );
CV_Assert( m == trainnum );
idxnum = 0;
idxstep = 0;
@ -1607,7 +1604,7 @@ CvBoostTrainer* icvBoostStartTraining( CvMat* trainClasses,
* Discrete AdaBoost functions
*
*/
CV_BOOST_IMPL
static
float icvBoostNextWeakClassifierDAB( CvMat* weakEvalVals,
CvMat* trainClasses,
CvMat* /*weakTrainVals*/,
@ -1640,8 +1637,8 @@ float icvBoostNextWeakClassifierDAB( CvMat* weakEvalVals,
CV_MAT2VEC( *trainClasses, ydata, ystep, ynum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == ynum );
assert( m == wnum );
CV_Assert( m == ynum );
CV_Assert( m == wnum );
sumw = 0.0F;
err = 0.0F;
@ -1681,7 +1678,7 @@ float icvBoostNextWeakClassifierDAB( CvMat* weakEvalVals,
* Real AdaBoost functions
*
*/
CV_BOOST_IMPL
static
float icvBoostNextWeakClassifierRAB( CvMat* weakEvalVals,
CvMat* trainClasses,
CvMat* /*weakTrainVals*/,
@ -1743,7 +1740,7 @@ float icvBoostNextWeakClassifierRAB( CvMat* weakEvalVals,
#define CV_LB_PROB_THRESH 0.01F
#define CV_LB_WEIGHT_THRESHOLD 0.0001F
CV_BOOST_IMPL
static
void icvResponsesAndWeightsLB( int num, uchar* wdata, int wstep,
uchar* ydata, int ystep,
uchar* fdata, int fstep,
@ -1772,7 +1769,7 @@ void icvResponsesAndWeightsLB( int num, uchar* wdata, int wstep,
}
}
CV_BOOST_IMPL
static
CvBoostTrainer* icvBoostStartTrainingLB( CvMat* trainClasses,
CvMat* weakTrainVals,
CvMat* weights,
@ -1808,8 +1805,8 @@ CvBoostTrainer* icvBoostStartTrainingLB( CvMat* trainClasses,
CV_MAT2VEC( *weakTrainVals, traindata, trainstep, trainnum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == trainnum );
assert( m == wnum );
CV_Assert( m == trainnum );
CV_Assert( m == wnum );
idxnum = 0;
@ -1854,7 +1851,7 @@ CvBoostTrainer* icvBoostStartTrainingLB( CvMat* trainClasses,
return ptr;
}
CV_BOOST_IMPL
static
float icvBoostNextWeakClassifierLB( CvMat* weakEvalVals,
CvMat* trainClasses,
CvMat* weakTrainVals,
@ -1889,9 +1886,9 @@ float icvBoostNextWeakClassifierLB( CvMat* weakEvalVals,
CV_MAT2VEC( *weakTrainVals, traindata, trainstep, trainnum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == ynum );
assert( m == wnum );
assert( m == trainnum );
CV_Assert( m == ynum );
CV_Assert( m == wnum );
CV_Assert( m == trainnum );
//assert( m == trainer->count );
for( i = 0; i < trainer->count; i++ )
@ -1913,7 +1910,7 @@ float icvBoostNextWeakClassifierLB( CvMat* weakEvalVals,
* Gentle AdaBoost
*
*/
CV_BOOST_IMPL
static
float icvBoostNextWeakClassifierGAB( CvMat* weakEvalVals,
CvMat* trainClasses,
CvMat* /*weakTrainVals*/,
@ -1944,8 +1941,8 @@ float icvBoostNextWeakClassifierGAB( CvMat* weakEvalVals,
CV_MAT2VEC( *trainClasses, ydata, ystep, ynum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == ynum );
assert( m == wnum );
CV_Assert( m == ynum );
CV_Assert( m == wnum );
sumw = 0.0F;
for( i = 0; i < trainer->count; i++ )
@ -2071,7 +2068,7 @@ typedef struct CvBtTrainer
typedef void (*CvZeroApproxFunc)( float* approx, CvBtTrainer* trainer );
/* Mean zero approximation */
void icvZeroApproxMean( float* approx, CvBtTrainer* trainer )
static void icvZeroApproxMean( float* approx, CvBtTrainer* trainer )
{
int i;
int idx;
@ -2088,7 +2085,7 @@ void icvZeroApproxMean( float* approx, CvBtTrainer* trainer )
/*
* Median zero approximation
*/
void icvZeroApproxMed( float* approx, CvBtTrainer* trainer )
static void icvZeroApproxMed( float* approx, CvBtTrainer* trainer )
{
int i;
int idx;
@ -2106,7 +2103,7 @@ void icvZeroApproxMed( float* approx, CvBtTrainer* trainer )
/*
* 0.5 * log( mean(y) / (1 - mean(y)) ) where y in {0, 1}
*/
void icvZeroApproxLog( float* approx, CvBtTrainer* trainer )
static void icvZeroApproxLog( float* approx, CvBtTrainer* trainer )
{
float y_mean;
@ -2117,7 +2114,7 @@ void icvZeroApproxLog( float* approx, CvBtTrainer* trainer )
/*
* 0 zero approximation
*/
void icvZeroApprox0( float* approx, CvBtTrainer* trainer )
static void icvZeroApprox0( float* approx, CvBtTrainer* trainer )
{
int i;
@ -2143,7 +2140,7 @@ static CvZeroApproxFunc icvZeroApproxFunc[] =
CV_BOOST_IMPL
void cvBtNext( CvCARTClassifier** trees, CvBtTrainer* trainer );
CV_BOOST_IMPL
static
CvBtTrainer* cvBtStart( CvCARTClassifier** trees,
CvMat* trainData,
int flags,
@ -2270,7 +2267,7 @@ CvBtTrainer* cvBtStart( CvCARTClassifier** trees,
return ptr;
}
void icvBtNext_LSREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
static void icvBtNext_LSREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
{
int i;
@ -2288,7 +2285,7 @@ void icvBtNext_LSREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
}
void icvBtNext_LADREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
static void icvBtNext_LADREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
{
CvCARTClassifier* ptr;
int i, j;
@ -2361,7 +2358,7 @@ void icvBtNext_LADREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
}
void icvBtNext_MREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
static void icvBtNext_MREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
{
CvCARTClassifier* ptr;
int i, j;
@ -2476,7 +2473,7 @@ void icvBtNext_MREG( CvCARTClassifier** trees, CvBtTrainer* trainer )
#define CV_LOG_VAL_MAX 18.0
void icvBtNext_L2CLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
static void icvBtNext_L2CLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
{
CvCARTClassifier* ptr;
int i, j;
@ -2617,7 +2614,7 @@ void icvBtNext_L2CLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
trees[0] = ptr;
}
void icvBtNext_LKCLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
static void icvBtNext_LKCLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
{
int i, j, k, kk, num;
CvMat sample;
@ -2781,7 +2778,7 @@ void icvBtNext_LKCLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
}
void icvBtNext_XXBCLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
static void icvBtNext_XXBCLASS( CvCARTClassifier** trees, CvBtTrainer* trainer )
{
float alpha;
int i;
@ -2898,7 +2895,7 @@ void cvBtNext( CvCARTClassifier** trees, CvBtTrainer* trainer )
}
}
CV_BOOST_IMPL
static
void cvBtEnd( CvBtTrainer** trainer )
{
CV_FUNCNAME( "cvBtEnd" );
@ -2931,7 +2928,7 @@ void cvBtEnd( CvBtTrainer** trainer )
* Boosted tree model as a classifier *
\****************************************************************************************/
CV_BOOST_IMPL
static
float cvEvalBtClassifier( CvClassifier* classifier, CvMat* sample )
{
float val;
@ -2972,7 +2969,7 @@ float cvEvalBtClassifier( CvClassifier* classifier, CvMat* sample )
return val;
}
CV_BOOST_IMPL
static
float cvEvalBtClassifier2( CvClassifier* classifier, CvMat* sample )
{
float val;
@ -2988,7 +2985,7 @@ float cvEvalBtClassifier2( CvClassifier* classifier, CvMat* sample )
return (float) (val >= 0.0F);
}
CV_BOOST_IMPL
static
float cvEvalBtClassifierK( CvClassifier* classifier, CvMat* sample )
{
int cls = 0;
@ -3072,7 +3069,7 @@ static CvEvalBtClassifier icvEvalBtClassifier[] =
cvEvalBtClassifier
};
CV_BOOST_IMPL
static
int cvSaveBtClassifier( CvClassifier* classifier, const char* filename )
{
CV_FUNCNAME( "cvSaveBtClassifier" );
@ -3137,7 +3134,7 @@ int cvSaveBtClassifier( CvClassifier* classifier, const char* filename )
}
CV_BOOST_IMPL
static
void cvReleaseBtClassifier( CvClassifier** ptr )
{
CV_FUNCNAME( "cvReleaseBtClassifier" );
@ -3183,7 +3180,7 @@ void cvReleaseBtClassifier( CvClassifier** ptr )
__END__;
}
void cvTuneBtClassifier( CvClassifier* classifier, CvMat*, int flags,
static void cvTuneBtClassifier( CvClassifier* classifier, CvMat*, int flags,
CvMat*, CvMat* , CvMat*, CvMat*, CvMat* )
{
CV_FUNCNAME( "cvTuneBtClassifier" );
@ -3244,7 +3241,7 @@ void cvTuneBtClassifier( CvClassifier* classifier, CvMat*, int flags,
__END__;
}
CvBtClassifier* icvAllocBtClassifier( CvBoostType type, int flags, int numclasses,
static CvBtClassifier* icvAllocBtClassifier( CvBoostType type, int flags, int numclasses,
int numiter )
{
CvBtClassifier* ptr;
@ -3720,7 +3717,7 @@ void cvWriteTrainData( const char* filename, int flags,
#define ICV_RAND_SHUFFLE( suffix, type ) \
void icvRandShuffle_##suffix( uchar* data, size_t step, int num ) \
static void icvRandShuffle_##suffix( uchar* data, size_t step, int num ) \
{ \
time_t seed; \
type tmp; \

6
apps/haartraining/cvhaarclassifier.cpp
View File

@ -394,7 +394,7 @@ void icvSaveStageHaarClassifier( CvIntHaarClassifier* classifier, FILE* file )
CvIntHaarClassifier* icvLoadCARTStageHaarClassifierF( FILE* file, int step )
static CvIntHaarClassifier* icvLoadCARTStageHaarClassifierF( FILE* file, int step )
{
CvStageHaarClassifier* ptr = NULL;
@ -525,9 +525,9 @@ float icvEvalTreeCascadeClassifierFilter( CvIntHaarClassifier* classifier, sum_t
sum_type* tilted, float normfactor )
{
CvTreeCascadeNode* ptr;
CvTreeCascadeClassifier* tree;
//CvTreeCascadeClassifier* tree;
tree = (CvTreeCascadeClassifier*) classifier;
//tree = (CvTreeCascadeClassifier*) classifier;

51
apps/haartraining/cvhaartraining.cpp
View File

@ -169,10 +169,11 @@ CvIntHaarFeatures* icvCreateIntHaarFeatures( CvSize winsize,
int dx = 0;
int dy = 0;
#if 0
float factor = 1.0F;
factor = ((float) winsize.width) * winsize.height / (24 * 24);
#if 0
s0 = (int) (s0 * factor);
s1 = (int) (s1 * factor);
s2 = (int) (s2 * factor);
@ -1257,11 +1258,11 @@ CvBackgroundData* icvCreateBackgroundData( const char* filename, CvSize winsize
while( !feof( input ) )
{
*imgfilename = '\0';
if( !fgets( imgfilename, PATH_MAX - (int)(imgfilename - full) - 1, input ))
if( !fgets( imgfilename, PATH_MAX - (int)(imgfilename - full) - 1, input ))
break;
len = (int)strlen( imgfilename );
if( len > 0 && imgfilename[len-1] == '\n' )
imgfilename[len-1] = 0, len--;
if( len > 0 && imgfilename[len-1] == '\n' )
imgfilename[len-1] = 0, len--;
if( len > 0 )
{
if( (*imgfilename) == '#' ) continue; /* comment */
@ -1878,7 +1879,7 @@ int icvGetHaarTraininDataFromVecCallback( CvMat* img, void* userdata )
return 1;
}
int icvGetHaarTrainingDataFromBGCallback ( CvMat* img, void* /*userdata*/ )
static int icvGetHaarTrainingDataFromBGCallback ( CvMat* img, void* /*userdata*/ )
{
if (! cvbgdata)
return 0;
@ -2190,15 +2191,15 @@ void cvCreateCascadeClassifier( const char* dirname,
{
char xml_path[1024];
int len = (int)strlen(dirname);
CvHaarClassifierCascade* cascade = 0;
CvHaarClassifierCascade* cascade1 = 0;
strcpy( xml_path, dirname );
if( xml_path[len-1] == '\\' || xml_path[len-1] == '/' )
len--;
strcpy( xml_path + len, ".xml" );
cascade = cvLoadHaarClassifierCascade( dirname, cvSize(winwidth,winheight) );
if( cascade )
cvSave( xml_path, cascade );
cvReleaseHaarClassifierCascade( &cascade );
cascade1 = cvLoadHaarClassifierCascade( dirname, cvSize(winwidth,winheight) );
if( cascade1 )
cvSave( xml_path, cascade1 );
cvReleaseHaarClassifierCascade( &cascade1 );
}
}
else
@ -2215,7 +2216,7 @@ void cvCreateCascadeClassifier( const char* dirname,
/* tree cascade classifier */
int icvNumSplits( CvStageHaarClassifier* stage )
static int icvNumSplits( CvStageHaarClassifier* stage )
{
int i;
int num;
@ -2229,7 +2230,7 @@ int icvNumSplits( CvStageHaarClassifier* stage )
return num;
}
void icvSetNumSamples( CvHaarTrainingData* training_data, int num )
static void icvSetNumSamples( CvHaarTrainingData* training_data, int num )
{
assert( num <= training_data->maxnum );
@ -2238,7 +2239,7 @@ void icvSetNumSamples( CvHaarTrainingData* training_data, int num )
training_data->cls.cols = training_data->weights.cols = num;
}
void icvSetWeightsAndClasses( CvHaarTrainingData* training_data,
static void icvSetWeightsAndClasses( CvHaarTrainingData* training_data,
int num1, float weight1, float cls1,
int num2, float weight2, float cls2 )
{
@ -2258,7 +2259,7 @@ void icvSetWeightsAndClasses( CvHaarTrainingData* training_data,
}
}
CvMat* icvGetUsedValues( CvHaarTrainingData* training_data,
static CvMat* icvGetUsedValues( CvHaarTrainingData* training_data,
int start, int num,
CvIntHaarFeatures* haar_features,
CvStageHaarClassifier* stage )
@ -2501,7 +2502,6 @@ void cvCreateTreeCascadeClassifier( const char* dirname,
{
CvTreeCascadeNode* single_cluster;
CvTreeCascadeNode* multiple_clusters;
CvSplit* cur_split;
int single_num;
icvSetNumSamples( training_data, poscount + negcount );
@ -2674,18 +2674,19 @@ void cvCreateTreeCascadeClassifier( const char* dirname,
} /* try different number of clusters */
cvReleaseMat( &vals );
CV_CALL( cur_split = (CvSplit*) cvAlloc( sizeof( *cur_split ) ) );
CV_ZERO_OBJ( cur_split );
CvSplit* curSplit;
CV_CALL( curSplit = (CvSplit*) cvAlloc( sizeof( *curSplit ) ) );
CV_ZERO_OBJ( curSplit );
if( last_split ) last_split->next = cur_split;
else first_split = cur_split;
last_split = cur_split;
if( last_split ) last_split->next = curSplit;
else first_split = curSplit;
last_split = curSplit;
cur_split->single_cluster = single_cluster;
cur_split->multiple_clusters = multiple_clusters;
cur_split->num_clusters = best_clusters;
cur_split->parent = parent;
cur_split->single_multiple_ratio = (float) single_num / best_num;
curSplit->single_cluster = single_cluster;
curSplit->multiple_clusters = multiple_clusters;
curSplit->num_clusters = best_clusters;
curSplit->parent = parent;
curSplit->single_multiple_ratio = (float) single_num / best_num;
}
if( parent ) parent = parent->next_same_level;

9
apps/haartraining/cvsamples.cpp
View File

@ -83,7 +83,7 @@
* cij - coeffs[i][j], coeffs[2][2] = 1
* (ui, vi) - rectangle vertices
*/
void cvGetPerspectiveTransform( CvSize src_size, double quad[4][2],
static void cvGetPerspectiveTransform( CvSize src_size, double quad[4][2],
double coeffs[3][3] )
{
//CV_FUNCNAME( "cvWarpPerspective" );
@ -130,7 +130,7 @@ void cvGetPerspectiveTransform( CvSize src_size, double quad[4][2],
}
/* Warps source into destination by a perspective transform */
void cvWarpPerspective( CvArr* src, CvArr* dst, double quad[4][2] )
static void cvWarpPerspective( CvArr* src, CvArr* dst, double quad[4][2] )
{
CV_FUNCNAME( "cvWarpPerspective" );
@ -323,8 +323,6 @@ void cvWarpPerspective( CvArr* src, CvArr* dst, double quad[4][2] )
int i00, i10, i01, i11;
i00 = i10 = i01 = i11 = (int) fill_value;
double i = fill_value;
/* linear interpolation using 2x2 neighborhood */
if( isrc_x >= 0 && isrc_x <= src_size.width &&
isrc_y >= 0 && isrc_y <= src_size.height )
@ -349,9 +347,8 @@ void cvWarpPerspective( CvArr* src, CvArr* dst, double quad[4][2] )
double i0 = i00 + (i10 - i00)*delta_x;
double i1 = i01 + (i11 - i01)*delta_x;
i = i0 + (i1 - i0)*delta_y;
((uchar*)(dst_data + y * dst_step))[x] = (uchar) i;
((uchar*)(dst_data + y * dst_step))[x] = (uchar) (i0 + (i1 - i0)*delta_y);
}
x_min += k_left;
x_max += k_right;

14
apps/haartraining/performance.cpp
View File

@ -44,6 +44,9 @@
*
* Measure performance of classifier
*/
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "cv.h"
#include "highgui.h"
@ -211,7 +214,7 @@ int main( int argc, char* argv[] )
totaltime = 0.0;
if( info != NULL )
{
int x, y, width, height;
int x, y;
IplImage* img;
int hits, missed, falseAlarms;
int totalHits, totalMissed, totalFalseAlarms;
@ -246,11 +249,12 @@ int main( int argc, char* argv[] )
ref = (ObjectPos*) cvAlloc( refcount * sizeof( *ref ) );
for( i = 0; i < refcount; i++ )
{
error = (fscanf( info, "%d %d %d %d", &x, &y, &width, &height ) != 4);
int w, h;
error = (fscanf( info, "%d %d %d %d", &x, &y, &w, &h ) != 4);
if( error ) break;
ref[i].x = 0.5F * width + x;
ref[i].y = 0.5F * height + y;
ref[i].width = sqrtf( 0.5F * (width * width + height * height) );
ref[i].x = 0.5F * w + x;
ref[i].y = 0.5F * h + y;
ref[i].width = sqrtf( 0.5F * (w * w + h * h) );
ref[i].found = 0;
ref[i].neghbors = 0;
}

3
apps/traincascade/HOGfeatures.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "HOGfeatures.h"
#include "cascadeclassifier.h"

17
apps/traincascade/boost.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "boost.h"
#include "cascadeclassifier.h"
#include <queue>
@ -481,7 +484,7 @@ CvCascadeBoostTrainData::CvCascadeBoostTrainData( const CvFeatureEvaluator* _fea
void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluator,
int _numSamples,
int _precalcValBufSize, int _precalcIdxBufSize,
const CvDTreeParams& _params )
const CvDTreeParams& _params )
{
int* idst = 0;
unsigned short* udst = 0;
@ -504,10 +507,10 @@ void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluat
responses = &_resp;
// TODO: check responses: elements must be 0 or 1
if( _precalcValBufSize < 0 || _precalcIdxBufSize < 0)
if( _precalcValBufSize < 0 || _precalcIdxBufSize < 0)
CV_Error( CV_StsOutOfRange, "_numPrecalcVal and _numPrecalcIdx must be positive or 0" );
var_count = var_all = featureEvaluator->getNumFeatures() * featureEvaluator->getFeatureSize();
var_count = var_all = featureEvaluator->getNumFeatures() * featureEvaluator->getFeatureSize();
sample_count = _numSamples;
is_buf_16u = false;
@ -556,7 +559,7 @@ void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluat
cat_count = cvCreateMat( 1, cat_var_count + 1, CV_32SC1 );
// precalculate valCache and set indices in buf
precalculate();
precalculate();
// now calculate the maximum size of split,
// create memory storage that will keep nodes and splits of the decision tree
@ -739,8 +742,8 @@ const int* CvCascadeBoostTrainData::get_cat_var_data( CvDTreeNode* n, int vi, in
float CvCascadeBoostTrainData::getVarValue( int vi, int si )
{
if ( vi < numPrecalcVal && !valCache.empty() )
return valCache.at<float>( vi, si );
return (*featureEvaluator)( vi, si );
return valCache.at<float>( vi, si );
return (*featureEvaluator)( vi, si );
}
@ -1232,7 +1235,7 @@ void CvCascadeBoostTree::split_node_data( CvDTreeNode* node )
data->free_node_data(node);
}
void auxMarkFeaturesInMap( const CvDTreeNode* node, Mat& featureMap)
static void auxMarkFeaturesInMap( const CvDTreeNode* node, Mat& featureMap)
{
if ( node && node->split )
{

3
apps/traincascade/cascadeclassifier.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "cascadeclassifier.h"
#include <queue>

3
apps/traincascade/features.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "traincascade_features.h"
#include "cascadeclassifier.h"

3
apps/traincascade/haarfeatures.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "haarfeatures.h"
#include "cascadeclassifier.h"

3
apps/traincascade/imagestorage.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "cv.h"
#include "imagestorage.h"
#include <stdio.h>

3
apps/traincascade/lbpfeatures.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "lbpfeatures.h"
#include "cascadeclassifier.h"

3
apps/traincascade/traincascade.cpp
View File

@ -1,3 +1,6 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
#include "cv.h"
#include "cascadeclassifier.h"

164
cmake/OpenCVCompilerOptions.cmake
View File

@ -14,6 +14,8 @@ if(MINGW)
endif()
if(MSVC)
string(REGEX REPLACE "^ *| * $" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
string(REGEX REPLACE "^ *| * $" "" CMAKE_CXX_FLAGS_INIT "${CMAKE_CXX_FLAGS_INIT}")
if(CMAKE_CXX_FLAGS STREQUAL CMAKE_CXX_FLAGS_INIT)
# override cmake default exception handling option
string(REPLACE "/EHsc" "/EHa" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
@ -21,73 +23,112 @@ if(MSVC)
endif()
endif()
set(OPENCV_EXTRA_FLAGS "")
set(OPENCV_EXTRA_C_FLAGS "")
set(OPENCV_EXTRA_C_FLAGS_RELEASE "")
set(OPENCV_EXTRA_C_FLAGS_DEBUG "")
set(OPENCV_EXTRA_CXX_FLAGS "")
set(OPENCV_EXTRA_FLAGS_RELEASE "")
set(OPENCV_EXTRA_FLAGS_DEBUG "")
set(OPENCV_EXTRA_EXE_LINKER_FLAGS "")
set(OPENCV_EXTRA_EXE_LINKER_FLAGS_RELEASE "")
set(OPENCV_EXTRA_EXE_LINKER_FLAGS_DEBUG "")
macro(add_extra_compiler_option option)
if(CMAKE_BUILD_TYPE)
set(CMAKE_TRY_COMPILE_CONFIGURATION ${CMAKE_BUILD_TYPE})
endif()
ocv_check_flag_support(CXX "${option}" _varname "${OPENCV_EXTRA_CXX_FLAGS} ${ARGN}")
if(${_varname})
set(OPENCV_EXTRA_CXX_FLAGS "${OPENCV_EXTRA_CXX_FLAGS} ${option}")
endif()
ocv_check_flag_support(C "${option}" _varname "${OPENCV_EXTRA_C_FLAGS} ${ARGN}")
if(${_varname})
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} ${option}")
endif()
endmacro()
if(MINGW)
# http://gcc.gnu.org/bugzilla/show_bug.cgi?id=40838
# here we are trying to workaround the problem
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG(-mstackrealign HAVE_STACKREALIGN_FLAG)
if(HAVE_STACKREALIGN_FLAG)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mstackrealign")
else()
CHECK_CXX_COMPILER_FLAG(-mpreferred-stack-boundary=2 HAVE_PREFERRED_STACKBOUNDARY_FLAG)
if(HAVE_PREFERRED_STACKBOUNDARY_FLAG)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mstackrealign")
endif()
add_extra_compiler_option(-mstackrealign)
if(NOT HAVE_CXX_MSTACKREALIGN)
add_extra_compiler_option(-mpreferred-stack-boundary=2)
endif()
endif()
if(OPENCV_CAN_BREAK_BINARY_COMPATIBILITY)
add_definitions(-DOPENCV_CAN_BREAK_BINARY_COMPATIBILITY)
endif()
if(CMAKE_COMPILER_IS_GNUCXX)
# High level of warnings.
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -Wall")
add_extra_compiler_option(-Wall)
add_extra_compiler_option(-Werror=return-type)
if(OPENCV_CAN_BREAK_BINARY_COMPATIBILITY)
add_extra_compiler_option(-Werror=non-virtual-dtor)
endif()
add_extra_compiler_option(-Werror=address)
add_extra_compiler_option(-Werror=sequence-point)
add_extra_compiler_option(-Wformat)
add_extra_compiler_option(-Werror=format-security -Wformat)
add_extra_compiler_option(-Wmissing-declarations)
add_extra_compiler_option(-Wmissing-prototypes)
add_extra_compiler_option(-Wstrict-prototypes)
add_extra_compiler_option(-Wundef)
add_extra_compiler_option(-Winit-self)
add_extra_compiler_option(-Wpointer-arith)
add_extra_compiler_option(-Wshadow)
if(ENABLE_NOISY_WARNINGS)
add_extra_compiler_option(-Wcast-align)
add_extra_compiler_option(-Wstrict-aliasing=2)
else()
add_extra_compiler_option(-Wno-narrowing)
add_extra_compiler_option(-Wno-delete-non-virtual-dtor)
add_extra_compiler_option(-Wno-unnamed-type-template-args)
endif()
# The -Wno-long-long is required in 64bit systems when including sytem headers.
if(X86_64)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -Wno-long-long")
add_extra_compiler_option(-Wno-long-long)
endif()
# We need pthread's
if(UNIX AND NOT ANDROID)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -pthread")
add_extra_compiler_option(-pthread)
endif()
if(OPENCV_WARNINGS_ARE_ERRORS)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -Werror")
add_extra_compiler_option(-Werror)
endif()
if(X86 AND NOT MINGW64 AND NOT X86_64 AND NOT APPLE)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -march=i686")
add_extra_compiler_option(-march=i686)
endif()
# Other optimizations
if(ENABLE_OMIT_FRAME_POINTER)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -fomit-frame-pointer")
add_extra_compiler_option(-fomit-frame-pointer)
else()
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -fno-omit-frame-pointer")
add_extra_compiler_option(-fno-omit-frame-pointer)
endif()
if(ENABLE_FAST_MATH)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -ffast-math")
add_extra_compiler_option(-ffast-math)
endif()
if(ENABLE_POWERPC)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mcpu=G3 -mtune=G5")
add_extra_compiler_option("-mcpu=G3 -mtune=G5")
endif()
if(ENABLE_SSE)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -msse")
add_extra_compiler_option(-msse)
endif()
if(ENABLE_SSE2)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -msse2")
add_extra_compiler_option(-msse2)
endif()
# SSE3 and further should be disabled under MingW because it generates compiler errors
if(NOT MINGW)
if(ENABLE_SSE3)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -msse3")
add_extra_compiler_option(-msse3)
endif()
if(${CMAKE_OPENCV_GCC_VERSION_NUM} GREATER 402)
@ -99,14 +140,14 @@ if(CMAKE_COMPILER_IS_GNUCXX)
if(HAVE_GCC42_OR_NEWER OR APPLE)
if(ENABLE_SSSE3)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mssse3")
add_extra_compiler_option(-mssse3)
endif()
if(HAVE_GCC43_OR_NEWER)
if(ENABLE_SSE41)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -msse4.1")
add_extra_compiler_option(-msse4.1)
endif()
if(ENABLE_SSE42)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -msse4.2")
add_extra_compiler_option(-msse4.2)
endif()
endif()
endif()
@ -114,39 +155,40 @@ if(CMAKE_COMPILER_IS_GNUCXX)
if(X86 OR X86_64)
if(NOT APPLE AND CMAKE_SIZEOF_VOID_P EQUAL 4)
if(ENABLE_SSE2)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mfpmath=sse")# !! important - be on the same wave with x64 compilers
else()
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mfpmath=387")
endif()
if(ENABLE_SSE2)
add_extra_compiler_option(-mfpmath=sse)# !! important - be on the same wave with x64 compilers
else()
add_extra_compiler_option(-mfpmath=387)
endif()
endif()
endif()
# Profiling?
if(ENABLE_PROFILING)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -pg -g")
add_extra_compiler_option("-pg -g")
# turn off incompatible options
foreach(flags CMAKE_CXX_FLAGS CMAKE_C_FLAGS CMAKE_CXX_FLAGS_RELEASE CMAKE_C_FLAGS_RELEASE CMAKE_CXX_FLAGS_DEBUG CMAKE_C_FLAGS_DEBUG OPENCV_EXTRA_C_FLAGS_RELEASE)
foreach(flags CMAKE_CXX_FLAGS CMAKE_C_FLAGS CMAKE_CXX_FLAGS_RELEASE CMAKE_C_FLAGS_RELEASE CMAKE_CXX_FLAGS_DEBUG CMAKE_C_FLAGS_DEBUG
OPENCV_EXTRA_FLAGS_RELEASE OPENCV_EXTRA_FLAGS_DEBUG OPENCV_EXTRA_C_FLAGS OPENCV_EXTRA_CXX_FLAGS)
string(REPLACE "-fomit-frame-pointer" "" ${flags} "${${flags}}")
string(REPLACE "-ffunction-sections" "" ${flags} "${${flags}}")
endforeach()
elseif(NOT APPLE AND NOT ANDROID)
# Remove unreferenced functions: function level linking
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -ffunction-sections")
add_extra_compiler_option(-ffunction-sections)
endif()
set(OPENCV_EXTRA_C_FLAGS_RELEASE "${OPENCV_EXTRA_C_FLAGS_RELEASE} -DNDEBUG")
set(OPENCV_EXTRA_C_FLAGS_DEBUG "${OPENCV_EXTRA_C_FLAGS_DEBUG} -O0 -DDEBUG -D_DEBUG")
set(OPENCV_EXTRA_FLAGS_RELEASE "${OPENCV_EXTRA_FLAGS_RELEASE} -DNDEBUG")
set(OPENCV_EXTRA_FLAGS_DEBUG "${OPENCV_EXTRA_FLAGS_DEBUG} -O0 -DDEBUG -D_DEBUG")
if(BUILD_WITH_DEBUG_INFO)
set(OPENCV_EXTRA_C_FLAGS_DEBUG "${OPENCV_EXTRA_C_FLAGS_DEBUG} -ggdb3")
set(OPENCV_EXTRA_FLAGS_DEBUG "${OPENCV_EXTRA_FLAGS_DEBUG} -ggdb3")
endif()
endif()
if(MSVC)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS")
# 64-bit portability warnings, in MSVC80
if(MSVC80)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /Wp64")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /Wp64")
endif()
if(BUILD_WITH_DEBUG_INFO)
@ -154,38 +196,38 @@ if(MSVC)
endif()
# Remove unreferenced functions: function level linking
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /Gy")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /Gy")
if(NOT MSVC_VERSION LESS 1400)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /bigobj")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /bigobj")
endif()
if(BUILD_WITH_DEBUG_INFO)
set(OPENCV_EXTRA_C_FLAGS_RELEASE "${OPENCV_EXTRA_C_FLAGS_RELEASE} /Zi")
set(OPENCV_EXTRA_FLAGS_RELEASE "${OPENCV_EXTRA_FLAGS_RELEASE} /Zi")
endif()
if(NOT MSVC64)
# 64-bit MSVC compiler uses SSE/SSE2 by default
if(ENABLE_SSE)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /arch:SSE")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /arch:SSE")
endif()
if(ENABLE_SSE2)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /arch:SSE2")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /arch:SSE2")
endif()
endif()
if(ENABLE_SSE3)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /arch:SSE3")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /arch:SSE3")
endif()
if(ENABLE_SSE4_1)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /arch:SSE4.1")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /arch:SSE4.1")
endif()
if(ENABLE_SSE OR ENABLE_SSE2 OR ENABLE_SSE3 OR ENABLE_SSE4_1)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /Oi")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /Oi")
endif()
if(X86 OR X86_64)
if(CMAKE_SIZEOF_VOID_P EQUAL 4 AND ENABLE_SSE2)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} /fp:fast")# !! important - be on the same wave with x64 compilers
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS} /fp:fast")# !! important - be on the same wave with x64 compilers
endif()
endif()
endif()
@ -194,25 +236,27 @@ endif()
if(NOT BUILD_SHARED_LIBS AND CMAKE_COMPILER_IS_GNUCXX AND NOT ANDROID)
# Android does not need these settings because they are already set by toolchain file
set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} stdc++)
set(OPENCV_EXTRA_C_FLAGS "-fPIC ${OPENCV_EXTRA_C_FLAGS}")
set(OPENCV_EXTRA_FLAGS "-fPIC ${OPENCV_EXTRA_FLAGS}")
endif()
# Add user supplied extra options (optimization, etc...)
# ==========================================================
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS}" CACHE INTERNAL "Extra compiler options")
set(OPENCV_EXTRA_C_FLAGS_RELEASE "${OPENCV_EXTRA_C_FLAGS_RELEASE}" CACHE INTERNAL "Extra compiler options for Release build")
set(OPENCV_EXTRA_C_FLAGS_DEBUG "${OPENCV_EXTRA_C_FLAGS_DEBUG}" CACHE INTERNAL "Extra compiler options for Debug build")
set(OPENCV_EXTRA_FLAGS "${OPENCV_EXTRA_FLAGS}" CACHE INTERNAL "Extra compiler options")
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS}" CACHE INTERNAL "Extra compiler options for C sources")
set(OPENCV_EXTRA_CXX_FLAGS "${OPENCV_EXTRA_CXX_FLAGS}" CACHE INTERNAL "Extra compiler options for C++ sources")
set(OPENCV_EXTRA_FLAGS_RELEASE "${OPENCV_EXTRA_FLAGS_RELEASE}" CACHE INTERNAL "Extra compiler options for Release build")
set(OPENCV_EXTRA_FLAGS_DEBUG "${OPENCV_EXTRA_FLAGS_DEBUG}" CACHE INTERNAL "Extra compiler options for Debug build")
set(OPENCV_EXTRA_EXE_LINKER_FLAGS "${OPENCV_EXTRA_EXE_LINKER_FLAGS}" CACHE INTERNAL "Extra linker flags")
set(OPENCV_EXTRA_EXE_LINKER_FLAGS_RELEASE "${OPENCV_EXTRA_EXE_LINKER_FLAGS_RELEASE}" CACHE INTERNAL "Extra linker flags for Release build")
set(OPENCV_EXTRA_EXE_LINKER_FLAGS_DEBUG "${OPENCV_EXTRA_EXE_LINKER_FLAGS_DEBUG}" CACHE INTERNAL "Extra linker flags for Debug build")
#combine all "extra" options
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OPENCV_EXTRA_C_FLAGS}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OPENCV_EXTRA_C_FLAGS}")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} ${OPENCV_EXTRA_C_FLAGS_RELEASE}")
set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} ${OPENCV_EXTRA_C_FLAGS_RELEASE}")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ${OPENCV_EXTRA_C_FLAGS_DEBUG}")
set(CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} ${OPENCV_EXTRA_C_FLAGS_DEBUG}")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OPENCV_EXTRA_FLAGS} ${OPENCV_EXTRA_C_FLAGS}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OPENCV_EXTRA_FLAGS} ${OPENCV_EXTRA_CXX_FLAGS}")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} ${OPENCV_EXTRA_FLAGS_RELEASE}")
set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} ${OPENCV_EXTRA_FLAGS_RELEASE}")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ${OPENCV_EXTRA_FLAGS_DEBUG}")
set(CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} ${OPENCV_EXTRA_FLAGS_DEBUG}")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} ${OPENCV_EXTRA_EXE_LINKER_FLAGS}")
set(CMAKE_EXE_LINKER_FLAGS_RELEASE "${CMAKE_EXE_LINKER_FLAGS_RELEASE} ${OPENCV_EXTRA_EXE_LINKER_FLAGS_RELEASE}")
set(CMAKE_EXE_LINKER_FLAGS_DEBUG "${CMAKE_EXE_LINKER_FLAGS_DEBUG} ${OPENCV_EXTRA_EXE_LINKER_FLAGS_DEBUG}")
@ -226,6 +270,10 @@ if(MSVC)
string(REPLACE "/W3" "/W4" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
string(REPLACE "/W3" "/W4" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
if(NOT ENABLE_NOISY_WARNINGS AND MSVC_VERSION EQUAL 1400)
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4510 /wd4610 /wd4312 /wd4201 /wd4244 /wd4328 /wd4267)
endif()
# allow extern "C" functions throw exceptions
foreach(flags CMAKE_C_FLAGS CMAKE_C_FLAGS_RELEASE CMAKE_C_FLAGS_RELEASE CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_RELEASE CMAKE_CXX_FLAGS_DEBUG)
string(REPLACE "/EHsc-" "/EHs" ${flags} "${${flags}}")

6
cmake/OpenCVDetectCXXCompiler.cmake
View File

@ -44,6 +44,12 @@ if(MSVC AND CMAKE_C_COMPILER MATCHES "icc")
set(CV_ICC __INTEL_COMPILER_FOR_WINDOWS)
endif()
if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID STREQUAL "Clang" OR (UNIX AND CV_ICC))
set(CV_COMPILER_IS_GNU TRUE)
else()
set(CV_COMPILER_IS_GNU FALSE)
endif()
# ----------------------------------------------------------------------------
# Detect GNU version:
# ----------------------------------------------------------------------------

2
cmake/OpenCVDetectTBB.cmake
View File

@ -1,6 +1,6 @@
if(ANDROID)
add_subdirectory("${OpenCV_SOURCE_DIR}/3rdparty/tbb")
ocv_include_directories(${TBB_INCLUDE_DIRS})
include_directories(SYSTEM ${TBB_INCLUDE_DIRS})
set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} tbb)
add_definitions(-DTBB_USE_GCC_BUILTINS=1 -D__TBB_GCC_BUILTIN_ATOMICS_PRESENT=1 -D__TBB_USE_GENERIC_DWORD_LOAD_STORE=1)
set(HAVE_TBB 1)

10
cmake/OpenCVFindLibsGrfmt.cmake
View File

@ -61,6 +61,16 @@ if(TIFF_BIGTIFF_VERSION AND NOT TIFF_VERSION_BIG)
set(TIFF_VERSION_BIG ${TIFF_BIGTIFF_VERSION})
endif()
if(NOT TIFF_VERSION_STRING AND TIFF_INCLUDE_DIR)
list(GET TIFF_INCLUDE_DIR 0 _TIFF_INCLUDE_DIR)
if(EXISTS "${_TIFF_INCLUDE_DIR}/tiffvers.h")
file(STRINGS "${_TIFF_INCLUDE_DIR}/tiffvers.h" tiff_version_str REGEX "^#define[\t ]+TIFFLIB_VERSION_STR[\t ]+\"LIBTIFF, Version .*")
string(REGEX REPLACE "^#define[\t ]+TIFFLIB_VERSION_STR[\t ]+\"LIBTIFF, Version +([^ \\n]*).*" "\\1" TIFF_VERSION_STRING "${tiff_version_str}")
unset(tiff_version_str)
endif()
unset(_TIFF_INCLUDE_DIR)
endif()
# --- libjpeg (optional) ---
if(WITH_JPEG)
if(BUILD_JPEG)

2
cmake/OpenCVFindXimea.cmake
View File

@ -18,7 +18,7 @@ if(WIN32)
# Try to find the XIMEA API path in registry.
GET_FILENAME_COMPONENT(XIMEA_PATH "[HKEY_CURRENT_USER\\Software\\XIMEA\\CamSupport\\API;Path]" ABSOLUTE)
if(XIMEA_PATH)
if(EXISTS XIMEA_PATH)
set(XIMEA_FOUND 1)
# set LIB folders

14
cmake/OpenCVGenHeaders.cmake
View File

@ -20,17 +20,17 @@ set(OPENCV_MOD_LIST ${OPENCV_MODULES_PUBLIC})
ocv_list_sort(OPENCV_MOD_LIST)
foreach(m ${OPENCV_MOD_LIST})
string(TOUPPER "${m}" m)
set(OPENCV_MODULE_DEFINITIONS_CONFIGMAKE "${OPENCV_MODULE_DEFINITIONS_CONFIGMAKE}#define HAVE_${m} 1\n")
set(OPENCV_MODULE_DEFINITIONS_CONFIGMAKE "${OPENCV_MODULE_DEFINITIONS_CONFIGMAKE}#define HAVE_${m}\n")
endforeach()
set(OPENCV_MODULE_DEFINITIONS_CONFIGMAKE "${OPENCV_MODULE_DEFINITIONS_CONFIGMAKE}\n")
set(OPENCV_MOD_LIST ${OPENCV_MODULES_DISABLED_USER} ${OPENCV_MODULES_DISABLED_AUTO})
ocv_list_sort(OPENCV_MOD_LIST)
foreach(m ${OPENCV_MOD_LIST})
string(TOUPPER "${m}" m)
set(OPENCV_MODULE_DEFINITIONS_CONFIGMAKE "${OPENCV_MODULE_DEFINITIONS_CONFIGMAKE}#undef HAVE_${m}\n")
endforeach()
#set(OPENCV_MOD_LIST ${OPENCV_MODULES_DISABLED_USER} ${OPENCV_MODULES_DISABLED_AUTO} ${OPENCV_MODULES_DISABLED_FORCE})
#ocv_list_sort(OPENCV_MOD_LIST)
#foreach(m ${OPENCV_MOD_LIST})
# string(TOUPPER "${m}" m)
# set(OPENCV_MODULE_DEFINITIONS_CONFIGMAKE "${OPENCV_MODULE_DEFINITIONS_CONFIGMAKE}#undef HAVE_${m}\n")
#endforeach()
configure_file("${OpenCV_SOURCE_DIR}/cmake/templates/opencv_modules.hpp.in" "${OPENCV_CONFIG_FILE_INCLUDE_DIR}/opencv2/opencv_modules.hpp")
install(FILES "${OPENCV_CONFIG_FILE_INCLUDE_DIR}/opencv2/opencv_modules.hpp" DESTINATION ${OPENCV_INCLUDE_PREFIX}/opencv2 COMPONENT main)

2
cmake/OpenCVModule.cmake
View File

@ -512,6 +512,8 @@ endmacro()
macro(ocv_add_precompiled_headers the_target)
if("${the_target}" MATCHES "^opencv_test_.*$")
SET(pch_path "test/test_")
elseif("${the_target}" MATCHES "opencv_perf_gpu_cpu")
SET(pch_path "perf_cpu/perf_cpu_")
elseif("${the_target}" MATCHES "^opencv_perf_.*$")
SET(pch_path "perf/perf_")
else()

10
cmake/OpenCVPCHSupport.cmake
View File

@ -24,10 +24,12 @@ IF(CMAKE_COMPILER_IS_GNUCXX)
ENDIF()
SET(_PCH_include_prefix "-I")
SET(_PCH_isystem_prefix "-isystem")
ELSEIF(WIN32)
SET(PCHSupport_FOUND TRUE) # for experimental msvc support
SET(_PCH_include_prefix "/I")
SET(_PCH_isystem_prefix "/I")
ELSE()
SET(PCHSupport_FOUND FALSE)
ENDIF()
@ -50,7 +52,11 @@ MACRO(_PCH_GET_COMPILE_FLAGS _out_compile_flags)
GET_DIRECTORY_PROPERTY(DIRINC INCLUDE_DIRECTORIES )
FOREACH(item ${DIRINC})
LIST(APPEND ${_out_compile_flags} "${_PCH_include_prefix}\"${item}\"")
if(item MATCHES "^${OpenCV_SOURCE_DIR}/modules/")
LIST(APPEND ${_out_compile_flags} "${_PCH_include_prefix}\"${item}\"")
else()
LIST(APPEND ${_out_compile_flags} "${_PCH_isystem_prefix}\"${item}\"")
endif()
ENDFOREACH(item)
GET_DIRECTORY_PROPERTY(_directory_flags DEFINITIONS)
@ -72,6 +78,7 @@ MACRO(_PCH_WRITE_PCHDEP_CXX _targetName _include_file _dephelp)
ADD_CUSTOM_COMMAND(
OUTPUT "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "#include \\\"${_include_file}\\\"" > "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "int testfunction();" >> "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "int testfunction()" >> "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "{" >> "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo " return 0;" >> "${${_dephelp}}"
@ -82,6 +89,7 @@ MACRO(_PCH_WRITE_PCHDEP_CXX _targetName _include_file _dephelp)
ADD_CUSTOM_COMMAND(
OUTPUT "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "\\#include \\\"${_include_file}\\\"" > "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "int testfunction\\(\\)\\;" >> "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "int testfunction\\(\\)" >> "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo "{" >> "${${_dephelp}}"
COMMAND ${CMAKE_COMMAND} -E echo " \\return 0\\;" >> "${${_dephelp}}"

121
cmake/OpenCVUtils.cmake
View File

@ -19,7 +19,7 @@ function(ocv_include_directories)
if("${__abs_dir}" MATCHES "^${OpenCV_SOURCE_DIR}" OR "${__abs_dir}" MATCHES "^${OpenCV_BINARY_DIR}")
list(APPEND __add_before "${dir}")
else()
include_directories(AFTER "${dir}")
include_directories(AFTER SYSTEM "${dir}")
endif()
endforeach()
include_directories(BEFORE ${__add_before})
@ -32,6 +32,125 @@ macro(ocv_clear_vars)
endforeach()
endmacro()
set(OCV_COMPILER_FAIL_REGEX
"command line option .* is valid for .* but not for C\\+\\+" # GNU
"unrecognized .*option" # GNU
"unknown .*option" # Clang
"ignoring unknown option" # MSVC
"warning D9002" # MSVC, any lang
"option .*not supported" # Intel
"[Uu]nknown option" # HP
"[Ww]arning: [Oo]ption" # SunPro
"command option .* is not recognized" # XL
"not supported in this configuration; ignored" # AIX
"File with unknown suffix passed to linker" # PGI
"WARNING: unknown flag:" # Open64
)
MACRO(ocv_check_compiler_flag LANG FLAG RESULT)
if(NOT DEFINED ${RESULT})
if("_${LANG}_" MATCHES "_CXX_")
set(_fname "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/src.cxx")
if("${CMAKE_CXX_FLAGS} ${FLAG} " MATCHES "-Werror " OR "${CMAKE_CXX_FLAGS} ${FLAG} " MATCHES "-Werror=unknown-pragmas ")
FILE(WRITE "${_fname}" "int main() { return 0; }\n")
else()
FILE(WRITE "${_fname}" "#pragma\nint main() { return 0; }\n")
endif()
elseif("_${LANG}_" MATCHES "_C_")
set(_fname "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/src.c")
if("${CMAKE_C_FLAGS} ${FLAG} " MATCHES "-Werror " OR "${CMAKE_C_FLAGS} ${FLAG} " MATCHES "-Werror=unknown-pragmas ")
FILE(WRITE "${_fname}" "int main(void) { return 0; }\n")
else()
FILE(WRITE "${_fname}" "#pragma\nint main(void) { return 0; }\n")
endif()
else()
unset(_fname)
endif()
if(_fname)
MESSAGE(STATUS "Performing Test ${RESULT}")
TRY_COMPILE(${RESULT}
${CMAKE_BINARY_DIR}
"${_fname}"
COMPILE_DEFINITIONS "${FLAG}"
OUTPUT_VARIABLE OUTPUT)
FOREACH(_regex ${OCV_COMPILER_FAIL_REGEX})
IF("${OUTPUT}" MATCHES "${_regex}")
SET(${RESULT} 0)
break()
ENDIF()
ENDFOREACH()
IF(${RESULT})
SET(${RESULT} 1 CACHE INTERNAL "Test ${RESULT}")
MESSAGE(STATUS "Performing Test ${RESULT} - Success")
ELSE(${RESULT})
MESSAGE(STATUS "Performing Test ${RESULT} - Failed")
SET(${RESULT} "" CACHE INTERNAL "Test ${RESULT}")
ENDIF(${RESULT})
else()
SET(${RESULT} 0)
endif()
endif()
ENDMACRO()
macro(ocv_check_flag_support lang flag varname)
if("_${lang}_" MATCHES "_CXX_")
set(_lang CXX)
elseif("_${lang}_" MATCHES "_C_")
set(_lang C)
else()
set(_lang ${lang})
endif()
string(TOUPPER "${flag}" ${varname})
string(REGEX REPLACE "^(/|-)" "HAVE_${_lang}_" ${varname} "${${varname}}")
string(REGEX REPLACE " -|-|=| |\\." "_" ${varname} "${${varname}}")
ocv_check_compiler_flag("${_lang}" "${ARGN} ${flag}" ${${varname}})
endmacro()
# turns off warnings
macro(ocv_warnings_disable)
if(NOT ENABLE_NOISY_WARNINGS)
set(_flag_vars "")
set(_msvc_warnings "")
set(_gxx_warnings "")
foreach(arg ${ARGN})
if(arg MATCHES "^CMAKE_")
list(APPEND _flag_vars ${arg})
elseif(arg MATCHES "^/wd")
list(APPEND _msvc_warnings ${arg})
elseif(arg MATCHES "^-W")
list(APPEND _gxx_warnings ${arg})
endif()
endforeach()
if(MSVC AND _msvc_warnings AND _flag_vars)
foreach(var ${_flag_vars})
foreach(warning ${_msvc_warnings})
set(${var} "${${var}} ${warning}")
endforeach()
endforeach()
elseif(CV_COMPILER_IS_GNU AND _gxx_warnings AND _flag_vars)
foreach(var ${_flag_vars})
foreach(warning ${_gxx_warnings})
if(NOT warning MATCHES "^-Wno-")
string(REPLACE "${warning}" "" ${var} "${${var}}")
string(REPLACE "-W" "-Wno-" warning "${warning}")
endif()
ocv_check_flag_support(${var} "${warning}" _varname)
if(${_varname})
set(${var} "${${var}} ${warning}")
endif()
endforeach()
endforeach()
endif()
unset(_flag_vars)
unset(_msvc_warnings)
unset(_gxx_warnings)
endif(NOT ENABLE_NOISY_WARNINGS)
endmacro()
# Provides an option that the user can optionally select.
# Can accept condition to control when option is available for user.
# Usage:

6
modules/calib3d/perf/perf_precomp.hpp
View File

@ -1,3 +1,7 @@
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
#endif
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
@ -6,7 +10,7 @@
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#if GTEST_CREATE_SHARED_LIBRARY
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined
#endif

67
modules/calib3d/src/calibinit.cpp
View File

@ -255,7 +255,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
IplImage _img;
int check_chessboard_result;
int quad_count = 0, group_idx = 0, i = 0, dilations = 0;
int quad_count = 0, group_idx = 0, dilations = 0;
img = cvGetMat( img, &stub );
//debug_img = img;
@ -316,7 +316,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
for( dilations = min_dilations; dilations <= max_dilations; dilations++ )
{
if (found)
break; // already found it
break; // already found it
cvFree(&quads);
cvFree(&corners);
@ -378,7 +378,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
cvCopy(dbg_img, dbg1_img);
cvNamedWindow("all_quads", 1);
// copy corners to temp array
for( i = 0; i < quad_count; i++ )
for(int i = 0; i < quad_count; i++ )
{
for (int k=0; k<4; k++)
{
@ -432,7 +432,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
cvCopy(dbg_img,dbg2_img);
cvNamedWindow("connected_group", 1);
// copy corners to temp array
for( i = 0; i < quad_count; i++ )
for(int i = 0; i < quad_count; i++ )
{
if (quads[i].group_idx == group_idx)
for (int k=0; k<4; k++)
@ -455,7 +455,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
#endif
if (count == 0)
continue; // haven't found inner quads
continue; // haven't found inner quads
// If count is more than it should be, this will remove those quads
@ -472,7 +472,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
float sum_dist = 0;
int total = 0;
for( i = 0; i < n; i++ )
for(int i = 0; i < n; i++ )
{
int ni = 0;
float avgi = corner_group[i]->meanDist(&ni);
@ -484,7 +484,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
if( count > 0 || (out_corner_count && -count > *out_corner_count) )
{
// copy corners to output array
for( i = 0; i < n; i++ )
for(int i = 0; i < n; i++ )
out_corners[i] = corner_group[i]->pt;
if( out_corner_count )
@ -505,19 +505,19 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
if( found )
found = icvCheckBoardMonotony( out_corners, pattern_size );
// check that none of the found corners is too close to the image boundary
// check that none of the found corners is too close to the image boundary
if( found )
{
const int BORDER = 8;
for( k = 0; k < pattern_size.width*pattern_size.height; k++ )
{
if( out_corners[k].x <= BORDER || out_corners[k].x > img->cols - BORDER ||
out_corners[k].y <= BORDER || out_corners[k].y > img->rows - BORDER )
break;
}
{
const int BORDER = 8;
for( k = 0; k < pattern_size.width*pattern_size.height; k++ )
{
if( out_corners[k].x <= BORDER || out_corners[k].x > img->cols - BORDER ||
out_corners[k].y <= BORDER || out_corners[k].y > img->rows - BORDER )
break;
}
found = k == pattern_size.width*pattern_size.height;
}
found = k == pattern_size.width*pattern_size.height;
}
if( found && pattern_size.height % 2 == 0 && pattern_size.width % 2 == 0 )
{
@ -525,8 +525,8 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
double dy0 = out_corners[last_row].y - out_corners[0].y;
if( dy0 < 0 )
{
int i, n = pattern_size.width*pattern_size.height;
for( i = 0; i < n/2; i++ )
int n = pattern_size.width*pattern_size.height;
for(int i = 0; i < n/2; i++ )
{
CvPoint2D32f temp;
CV_SWAP(out_corners[i], out_corners[n-i-1], temp);
@ -627,11 +627,10 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
{
cv::Ptr<CvMemStorage> temp_storage = cvCreateChildMemStorage( storage );
CvSeq* stack = cvCreateSeq( 0, sizeof(*stack), sizeof(void*), temp_storage );
int i;
// first find an interior quad
CvCBQuad *start = NULL;
for (i=0; i<quad_count; i++)
for (int i=0; i<quad_count; i++)
{
if (quads[i]->count == 4)
{
@ -682,7 +681,7 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
case 1:
col += 2; break;
case 2:
row += 2; break;
row += 2; break;
case 3:
col -= 2; break;
}
@ -700,7 +699,7 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
}
}
for (i=col_min; i<=col_max; i++)
for (int i=col_min; i<=col_max; i++)
PRINTF("HIST[%d] = %d\n", i, col_hist[i]);
// analyze inner quad structure
@ -763,7 +762,7 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
// if there is an outer quad missing, fill it in
// first order all inner quads
int found = 0;
for (i=0; i<quad_count; i++)
for (int i=0; i<quad_count; i++)
{
if (quads[i]->count == 4)
{ // ok, look at neighbors
@ -778,7 +777,7 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
case 1:
col += 2; break;
case 2:
row += 2; break;
row += 2; break;
case 3:
col -= 2; break;
}
@ -817,7 +816,7 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
// final trimming of outer quads
if (dcol == w && drow == h) // found correct inner quads
if (dcol == w && drow == h) // found correct inner quads
{
PRINTF("Inner bounds ok, check outer quads\n");
int rcount = quad_count;
@ -832,7 +831,7 @@ icvOrderFoundConnectedQuads( int quad_count, CvCBQuad **quads,
if (quads[i]->neighbors[j] && quads[i]->neighbors[j]->ordered)
outer = true;
}
if (!outer) // not an outer quad, eliminate
if (!outer) // not an outer quad, eliminate
{
PRINTF("Removing quad %d\n", i);
icvRemoveQuadFromGroup(quads,rcount,quads[i]);
@ -876,7 +875,7 @@ icvAddOuterQuad( CvCBQuad *quad, CvCBQuad **quads, int quad_count,
quad->count += 1;
q->neighbors[j] = quad;
q->group_idx = quad->group_idx;
q->count = 1; // number of neighbors
q->count = 1; // number of neighbors
q->ordered = false;
q->edge_len = quad->edge_len;
@ -2006,17 +2005,17 @@ bool cv::findCirclesGrid( InputArray _image, Size patternSize,
#endif
if (isFound)
{
switch(parameters.gridType)
{
switch(parameters.gridType)
{
case CirclesGridFinderParameters::SYMMETRIC_GRID:
boxFinder.getHoles(centers);
break;
case CirclesGridFinderParameters::ASYMMETRIC_GRID:
boxFinder.getAsymmetricHoles(centers);
break;
boxFinder.getAsymmetricHoles(centers);
break;
default:
CV_Error(CV_StsBadArg, "Unkown pattern type");
}
}
if (i != 0)
{

2
modules/calib3d/src/calibration.cpp
View File

@ -1153,7 +1153,7 @@ CV_IMPL void cvFindExtrinsicCameraParams2( const CvMat* objectPoints,
int useExtrinsicGuess )
{
const int max_iter = 20;
Ptr<CvMat> matM, _Mxy, _m, _mn, matL, matJ;
Ptr<CvMat> matM, _Mxy, _m, _mn, matL;
int i, count;
double a[9], ar[9]={1,0,0,0,1,0,0,0,1}, R[9];

6
modules/calib3d/src/checkchessboard.cpp
View File

@ -55,7 +55,7 @@
# endif
#endif
void icvGetQuadrangleHypotheses(CvSeq* contours, std::vector<std::pair<float, int> >& quads, int class_id)
static void icvGetQuadrangleHypotheses(CvSeq* contours, std::vector<std::pair<float, int> >& quads, int class_id)
{
const float min_aspect_ratio = 0.3f;
const float max_aspect_ratio = 3.0f;
@ -80,7 +80,7 @@ void icvGetQuadrangleHypotheses(CvSeq* contours, std::vector<std::pair<float, in
}
}
void countClasses(const std::vector<std::pair<float, int> >& pairs, size_t idx1, size_t idx2, std::vector<int>& counts)
static void countClasses(const std::vector<std::pair<float, int> >& pairs, size_t idx1, size_t idx2, std::vector<int>& counts)
{
counts.assign(2, 0);
for(size_t i = idx1; i != idx2; i++)
@ -89,7 +89,7 @@ void countClasses(const std::vector<std::pair<float, int> >& pairs, size_t idx1,
}
}
bool less_pred(const std::pair<float, int>& p1, const std::pair<float, int>& p2)
inline bool less_pred(const std::pair<float, int>& p1, const std::pair<float, int>& p2)
{
return p1.first < p2.first;
}

20
modules/calib3d/src/circlesgrid.cpp
View File

@ -65,14 +65,14 @@ void drawPoints(const vector<Point2f> &points, Mat &outImage, int radius = 2, S
}
#endif
void CirclesGridClusterFinder::hierarchicalClustering(const vector<Point2f> points, const Size &patternSize, vector<Point2f> &patternPoints)
void CirclesGridClusterFinder::hierarchicalClustering(const vector<Point2f> points, const Size &patternSz, vector<Point2f> &patternPoints)
{
#ifdef HAVE_TEGRA_OPTIMIZATION
if(tegra::hierarchicalClustering(points, patternSize, patternPoints))
if(tegra::hierarchicalClustering(points, patternSz, patternPoints))
return;
#endif
int i, j, n = (int)points.size();
size_t pn = static_cast<size_t>(patternSize.area());
int j, n = (int)points.size();
size_t pn = static_cast<size_t>(patternSz.area());
patternPoints.clear();
if (pn >= points.size())
@ -84,7 +84,7 @@ void CirclesGridClusterFinder::hierarchicalClustering(const vector<Point2f> poin
Mat dists(n, n, CV_32FC1, Scalar(0));
Mat distsMask(dists.size(), CV_8UC1, Scalar(0));
for(i = 0; i < n; i++)
for(int i = 0; i < n; i++)
{
for(j = i+1; j < n; j++)
{
@ -122,7 +122,7 @@ void CirclesGridClusterFinder::hierarchicalClustering(const vector<Point2f> poin
}
//the largest cluster can have more than pn points -- we need to filter out such situations
if(clusters[patternClusterIdx].size() != static_cast<size_t>(patternSize.area()))
if(clusters[patternClusterIdx].size() != static_cast<size_t>(patternSz.area()))
{
return;
}
@ -505,11 +505,11 @@ void Graph::floydWarshall(cv::Mat &distanceMatrix, int infinity) const
{
for (Vertices::const_iterator it3 = vertices.begin(); it3 != vertices.end(); it3++)
{
int i1 = (int)it1->first, i2 = (int)it2->first, i3 = (int)it3->first;
int i1 = (int)it1->first, i2 = (int)it2->first, i3 = (int)it3->first;
int val1 = distanceMatrix.at<int> (i2, i3);
int val2;
if (distanceMatrix.at<int> (i2, i1) == infinity ||
distanceMatrix.at<int> (i1, i3) == infinity)
distanceMatrix.at<int> (i1, i3) == infinity)
val2 = val1;
else
{
@ -1223,7 +1223,7 @@ void computePredecessorMatrix(const Mat &dm, int verticesCount, Mat &predecessor
}
}
void computeShortestPath(Mat &predecessorMatrix, size_t v1, size_t v2, vector<size_t> &path)
static void computeShortestPath(Mat &predecessorMatrix, size_t v1, size_t v2, vector<size_t> &path)
{
if (predecessorMatrix.at<int> ((int)v1, (int)v2) < 0)
{
@ -1403,7 +1403,7 @@ void CirclesGridFinder::getHoles(vector<Point2f> &outHoles) const
}
}
bool areIndicesCorrect(Point pos, vector<vector<size_t> > *points)
static bool areIndicesCorrect(Point pos, vector<vector<size_t> > *points)
{
if (pos.y < 0 || pos.x < 0)
return false;

158
modules/calib3d/src/epnp.cpp
View File

@ -8,7 +8,7 @@ epnp::epnp(const cv::Mat& cameraMatrix, const cv::Mat& opoints, const cv::Mat& i
if (cameraMatrix.depth() == CV_32F)
init_camera_parameters<float>(cameraMatrix);
else
init_camera_parameters<double>(cameraMatrix);
init_camera_parameters<double>(cameraMatrix);
number_of_correspondences = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
@ -17,15 +17,15 @@ epnp::epnp(const cv::Mat& cameraMatrix, const cv::Mat& opoints, const cv::Mat& i
if (opoints.depth() == ipoints.depth())
{
if (opoints.depth() == CV_32F)
init_points<cv::Point3f,cv::Point2f>(opoints, ipoints);
else
init_points<cv::Point3d,cv::Point2d>(opoints, ipoints);
if (opoints.depth() == CV_32F)
init_points<cv::Point3f,cv::Point2f>(opoints, ipoints);
else
init_points<cv::Point3d,cv::Point2d>(opoints, ipoints);
}
else if (opoints.depth() == CV_32F)
init_points<cv::Point3f,cv::Point2d>(opoints, ipoints);
init_points<cv::Point3f,cv::Point2d>(opoints, ipoints);
else
init_points<cv::Point3d,cv::Point2f>(opoints, ipoints);
init_points<cv::Point3d,cv::Point2f>(opoints, ipoints);
alphas.resize(4 * number_of_correspondences);
pcs.resize(3 * number_of_correspondences);
@ -97,15 +97,15 @@ void epnp::compute_barycentric_coordinates(void)
for(int j = 0; j < 3; j++)
a[1 + j] =
ci[3 * j ] * (pi[0] - cws[0][0]) +
ci[3 * j + 1] * (pi[1] - cws[0][1]) +
ci[3 * j + 2] * (pi[2] - cws[0][2]);
ci[3 * j ] * (pi[0] - cws[0][0]) +
ci[3 * j + 1] * (pi[1] - cws[0][1]) +
ci[3 * j + 2] * (pi[2] - cws[0][2]);
a[0] = 1.0f - a[1] - a[2] - a[3];
}
}
void epnp::fill_M(CvMat * M,
const int row, const double * as, const double u, const double v)
const int row, const double * as, const double u, const double v)
{
double * M1 = M->data.db + row * 12;
double * M2 = M1 + 12;
@ -130,7 +130,7 @@ void epnp::compute_ccs(const double * betas, const double * ut)
const double * v = ut + 12 * (11 - i);
for(int j = 0; j < 4; j++)
for(int k = 0; k < 3; k++)
ccs[j][k] += betas[i] * v[3 * j + k];
ccs[j][k] += betas[i] * v[3 * j + k];
}
}
@ -195,7 +195,7 @@ void epnp::compute_pose(cv::Mat& R, cv::Mat& t)
}
void epnp::copy_R_and_t(const double R_src[3][3], const double t_src[3],
double R_dst[3][3], double t_dst[3])
double R_dst[3][3], double t_dst[3])
{
for(int i = 0; i < 3; i++) {
for(int j = 0; j < 3; j++)
@ -282,7 +282,7 @@ void epnp::solve_for_sign(void)
if (pcs[2] < 0.0) {
for(int i = 0; i < 4; i++)
for(int j = 0; j < 3; j++)
ccs[i][j] = -ccs[i][j];
ccs[i][j] = -ccs[i][j];
for(int i = 0; i < number_of_correspondences; i++) {
pcs[3 * i ] = -pcs[3 * i];
@ -293,7 +293,7 @@ void epnp::solve_for_sign(void)
}
double epnp::compute_R_and_t(const double * ut, const double * betas,
double R[3][3], double t[3])
double R[3][3], double t[3])
{
compute_ccs(betas, ut);
compute_pcs();
@ -328,7 +328,7 @@ double epnp::reprojection_error(const double R[3][3], const double t[3])
// betas_approx_1 = [B11 B12 B13 B14]
void epnp::find_betas_approx_1(const CvMat * L_6x10, const CvMat * Rho,
double * betas)
double * betas)
{
double l_6x4[6 * 4], b4[4];
CvMat L_6x4 = cvMat(6, 4, CV_64F, l_6x4);
@ -360,7 +360,7 @@ void epnp::find_betas_approx_1(const CvMat * L_6x10, const CvMat * Rho,
// betas_approx_2 = [B11 B12 B22 ]
void epnp::find_betas_approx_2(const CvMat * L_6x10, const CvMat * Rho,
double * betas)
double * betas)
{
double l_6x3[6 * 3], b3[3];
CvMat L_6x3 = cvMat(6, 3, CV_64F, l_6x3);
@ -392,7 +392,7 @@ void epnp::find_betas_approx_2(const CvMat * L_6x10, const CvMat * Rho,
// betas_approx_3 = [B11 B12 B22 B13 B23 ]
void epnp::find_betas_approx_3(const CvMat * L_6x10, const CvMat * Rho,
double * betas)
double * betas)
{
double l_6x5[6 * 5], b5[5];
CvMat L_6x5 = cvMat(6, 5, CV_64F, l_6x5);
@ -440,8 +440,8 @@ void epnp::compute_L_6x10(const double * ut, double * l_6x10)
b++;
if (b > 3) {
a++;
b = a + 1;
a++;
b = a + 1;
}
}
}
@ -473,7 +473,7 @@ void epnp::compute_rho(double * rho)
}
void epnp::compute_A_and_b_gauss_newton(const double * l_6x10, const double * rho,
const double betas[4], CvMat * A, CvMat * b)
const double betas[4], CvMat * A, CvMat * b)
{
for(int i = 0; i < 6; i++) {
const double * rowL = l_6x10 + i * 10;
@ -485,23 +485,22 @@ void epnp::compute_A_and_b_gauss_newton(const double * l_6x10, const double * rh
rowA[3] = rowL[6] * betas[0] + rowL[7] * betas[1] + rowL[8] * betas[2] + 2 * rowL[9] * betas[3];
cvmSet(b, i, 0, rho[i] -
(
rowL[0] * betas[0] * betas[0] +
rowL[1] * betas[0] * betas[1] +
rowL[2] * betas[1] * betas[1] +
rowL[3] * betas[0] * betas[2] +
rowL[4] * betas[1] * betas[2] +
rowL[5] * betas[2] * betas[2] +
rowL[6] * betas[0] * betas[3] +
rowL[7] * betas[1] * betas[3] +
rowL[8] * betas[2] * betas[3] +
rowL[9] * betas[3] * betas[3]
));
(
rowL[0] * betas[0] * betas[0] +
rowL[1] * betas[0] * betas[1] +
rowL[2] * betas[1] * betas[1] +
rowL[3] * betas[0] * betas[2] +
rowL[4] * betas[1] * betas[2] +
rowL[5] * betas[2] * betas[2] +
rowL[6] * betas[0] * betas[3] +
rowL[7] * betas[1] * betas[3] +
rowL[8] * betas[2] * betas[3] +
rowL[9] * betas[3] * betas[3]
));
}
}
void epnp::gauss_newton(const CvMat * L_6x10, const CvMat * Rho,
double betas[4])
void epnp::gauss_newton(const CvMat * L_6x10, const CvMat * Rho, double betas[4])
{
const int iterations_number = 5;
@ -510,12 +509,13 @@ void epnp::gauss_newton(const CvMat * L_6x10, const CvMat * Rho,
CvMat B = cvMat(6, 1, CV_64F, b);
CvMat X = cvMat(4, 1, CV_64F, x);
for(int k = 0; k < iterations_number; k++) {
for(int k = 0; k < iterations_number; k++)
{
compute_A_and_b_gauss_newton(L_6x10->data.db, Rho->data.db,
betas, &A, &B);
betas, &A, &B);
qr_solve(&A, &B, &X);
for(int i = 0; i < 4; i++)
betas[i] += x[i];
betas[i] += x[i];
}
}
@ -524,53 +524,64 @@ void epnp::qr_solve(CvMat * A, CvMat * b, CvMat * X)
const int nr = A->rows;
const int nc = A->cols;
if (max_nr != 0 && max_nr < nr) {
if (max_nr != 0 && max_nr < nr)
{
delete [] A1;
delete [] A2;
}
if (max_nr < nr) {
if (max_nr < nr)
{
max_nr = nr;
A1 = new double[nr];
A2 = new double[nr];
}
double * pA = A->data.db, * ppAkk = pA;
for(int k = 0; k < nc; k++) {
double * ppAik = ppAkk, eta = fabs(*ppAik);
for(int i = k + 1; i < nr; i++) {
double elt = fabs(*ppAik);
for(int k = 0; k < nc; k++)
{
double * ppAik1 = ppAkk, eta = fabs(*ppAik1);
for(int i = k + 1; i < nr; i++)
{
double elt = fabs(*ppAik1);
if (eta < elt) eta = elt;
ppAik += nc;
ppAik1 += nc;
}
if (eta == 0) {
if (eta == 0)
{
A1[k] = A2[k] = 0.0;
//cerr << "God damnit, A is singular, this shouldn't happen." << endl;
return;
} else {
double * ppAik = ppAkk, sum = 0.0, inv_eta = 1. / eta;
for(int i = k; i < nr; i++) {
*ppAik *= inv_eta;
sum += *ppAik * *ppAik;
ppAik += nc;
}
else
{
double * ppAik2 = ppAkk, sum2 = 0.0, inv_eta = 1. / eta;
for(int i = k; i < nr; i++)
{
*ppAik2 *= inv_eta;
sum2 += *ppAik2 * *ppAik2;
ppAik2 += nc;
}
double sigma = sqrt(sum);
double sigma = sqrt(sum2);
if (*ppAkk < 0)
sigma = -sigma;
sigma = -sigma;
*ppAkk += sigma;
A1[k] = sigma * *ppAkk;
A2[k] = -eta * sigma;
for(int j = k + 1; j < nc; j++) {
double * ppAik = ppAkk, sum = 0;
for(int i = k; i < nr; i++) {
sum += *ppAik * ppAik[j - k];
ppAik += nc;
}
double tau = sum / A1[k];
ppAik = ppAkk;
for(int i = k; i < nr; i++) {
ppAik[j - k] -= tau * *ppAik;
ppAik += nc;
}
for(int j = k + 1; j < nc; j++)
{
double * ppAik = ppAkk, sum = 0;
for(int i = k; i < nr; i++)
{
sum += *ppAik * ppAik[j - k];
ppAik += nc;
}
double tau = sum / A1[k];
ppAik = ppAkk;
for(int i = k; i < nr; i++)
{
ppAik[j - k] -= tau * *ppAik;
ppAik += nc;
}
}
}
ppAkk += nc + 1;
@ -578,15 +589,18 @@ void epnp::qr_solve(CvMat * A, CvMat * b, CvMat * X)
// b <- Qt b
double * ppAjj = pA, * pb = b->data.db;
for(int j = 0; j < nc; j++) {
for(int j = 0; j < nc; j++)
{
double * ppAij = ppAjj, tau = 0;
for(int i = j; i < nr; i++) {
for(int i = j; i < nr; i++)
{
tau += *ppAij * pb[i];
ppAij += nc;
}
tau /= A1[j];
ppAij = ppAjj;
for(int i = j; i < nr; i++) {
for(int i = j; i < nr; i++)
{
pb[i] -= tau * *ppAij;
ppAij += nc;
}
@ -596,10 +610,12 @@ void epnp::qr_solve(CvMat * A, CvMat * b, CvMat * X)
// X = R-1 b
double * pX = X->data.db;
pX[nc - 1] = pb[nc - 1] / A2[nc - 1];
for(int i = nc - 2; i >= 0; i--) {
for(int i = nc - 2; i >= 0; i--)
{
double * ppAij = pA + i * nc + (i + 1), sum = 0;
for(int j = i + 1; j < nc; j++) {
for(int j = i + 1; j < nc; j++)
{
sum += *ppAij * pX[j];
ppAij++;
}

580
modules/calib3d/src/p3p.cpp
View File

@ -9,151 +9,151 @@ using namespace std;
void p3p::init_inverse_parameters()
{
inv_fx = 1. / fx;
inv_fy = 1. / fy;
cx_fx = cx / fx;
cy_fy = cy / fy;
inv_fx = 1. / fx;
inv_fy = 1. / fy;
cx_fx = cx / fx;
cy_fy = cy / fy;
}
p3p::p3p(cv::Mat cameraMatrix)
{
if (cameraMatrix.depth() == CV_32F)
init_camera_parameters<float>(cameraMatrix);
else
init_camera_parameters<double>(cameraMatrix);
init_inverse_parameters();
if (cameraMatrix.depth() == CV_32F)
init_camera_parameters<float>(cameraMatrix);
else
init_camera_parameters<double>(cameraMatrix);
init_inverse_parameters();
}
p3p::p3p(double _fx, double _fy, double _cx, double _cy)
{
fx = _fx;
fy = _fy;
cx = _cx;
cy = _cy;
init_inverse_parameters();
fx = _fx;
fy = _fy;
cx = _cx;
cy = _cy;
init_inverse_parameters();
}
bool p3p::solve(cv::Mat& R, cv::Mat& tvec, const cv::Mat& opoints, const cv::Mat& ipoints)
{
double rotation_matrix[3][3], translation[3];
std::vector<double> points;
if (opoints.depth() == ipoints.depth())
{
if (opoints.depth() == CV_32F)
extract_points<cv::Point3f,cv::Point2f>(opoints, ipoints, points);
else
extract_points<cv::Point3d,cv::Point2d>(opoints, ipoints, points);
}
else if (opoints.depth() == CV_32F)
extract_points<cv::Point3f,cv::Point2d>(opoints, ipoints, points);
else
extract_points<cv::Point3d,cv::Point2f>(opoints, ipoints, points);
double rotation_matrix[3][3], translation[3];
std::vector<double> points;
if (opoints.depth() == ipoints.depth())
{
if (opoints.depth() == CV_32F)
extract_points<cv::Point3f,cv::Point2f>(opoints, ipoints, points);
else
extract_points<cv::Point3d,cv::Point2d>(opoints, ipoints, points);
}
else if (opoints.depth() == CV_32F)
extract_points<cv::Point3f,cv::Point2d>(opoints, ipoints, points);
else
extract_points<cv::Point3d,cv::Point2f>(opoints, ipoints, points);
bool result = solve(rotation_matrix, translation, points[0], points[1], points[2], points[3], points[4], points[5],
points[6], points[7], points[8], points[9], points[10], points[11], points[12], points[13], points[14],
points[15], points[16], points[17], points[18], points[19]);
cv::Mat(3, 1, CV_64F, translation).copyTo(tvec);
bool result = solve(rotation_matrix, translation, points[0], points[1], points[2], points[3], points[4], points[5],
points[6], points[7], points[8], points[9], points[10], points[11], points[12], points[13], points[14],
points[15], points[16], points[17], points[18], points[19]);
cv::Mat(3, 1, CV_64F, translation).copyTo(tvec);
cv::Mat(3, 3, CV_64F, rotation_matrix).copyTo(R);
return result;
return result;
}
bool p3p::solve(double R[3][3], double t[3],
double mu0, double mv0, double X0, double Y0, double Z0,
double mu1, double mv1, double X1, double Y1, double Z1,
double mu2, double mv2, double X2, double Y2, double Z2,
double mu3, double mv3, double X3, double Y3, double Z3)
double mu0, double mv0, double X0, double Y0, double Z0,
double mu1, double mv1, double X1, double Y1, double Z1,
double mu2, double mv2, double X2, double Y2, double Z2,
double mu3, double mv3, double X3, double Y3, double Z3)
{
double Rs[4][3][3], ts[4][3];
double Rs[4][3][3], ts[4][3];
int n = solve(Rs, ts, mu0, mv0, X0, Y0, Z0, mu1, mv1, X1, Y1, Z1, mu2, mv2, X2, Y2, Z2);
int n = solve(Rs, ts, mu0, mv0, X0, Y0, Z0, mu1, mv1, X1, Y1, Z1, mu2, mv2, X2, Y2, Z2);
if (n == 0)
return false;
if (n == 0)
return false;
int ns = 0;
double min_reproj = 0;
for(int i = 0; i < n; i++) {
double X3p = Rs[i][0][0] * X3 + Rs[i][0][1] * Y3 + Rs[i][0][2] * Z3 + ts[i][0];
double Y3p = Rs[i][1][0] * X3 + Rs[i][1][1] * Y3 + Rs[i][1][2] * Z3 + ts[i][1];
double Z3p = Rs[i][2][0] * X3 + Rs[i][2][1] * Y3 + Rs[i][2][2] * Z3 + ts[i][2];
double mu3p = cx + fx * X3p / Z3p;
double mv3p = cy + fy * Y3p / Z3p;
double reproj = (mu3p - mu3) * (mu3p - mu3) + (mv3p - mv3) * (mv3p - mv3);
if (i == 0 || min_reproj > reproj) {
ns = i;
min_reproj = reproj;
}
}
int ns = 0;
double min_reproj = 0;
for(int i = 0; i < n; i++) {
double X3p = Rs[i][0][0] * X3 + Rs[i][0][1] * Y3 + Rs[i][0][2] * Z3 + ts[i][0];
double Y3p = Rs[i][1][0] * X3 + Rs[i][1][1] * Y3 + Rs[i][1][2] * Z3 + ts[i][1];
double Z3p = Rs[i][2][0] * X3 + Rs[i][2][1] * Y3 + Rs[i][2][2] * Z3 + ts[i][2];
double mu3p = cx + fx * X3p / Z3p;
double mv3p = cy + fy * Y3p / Z3p;
double reproj = (mu3p - mu3) * (mu3p - mu3) + (mv3p - mv3) * (mv3p - mv3);
if (i == 0 || min_reproj > reproj) {
ns = i;
min_reproj = reproj;
}
}
for(int i = 0; i < 3; i++) {
for(int j = 0; j < 3; j++)
R[i][j] = Rs[ns][i][j];
t[i] = ts[ns][i];
}
for(int i = 0; i < 3; i++) {
for(int j = 0; j < 3; j++)
R[i][j] = Rs[ns][i][j];
t[i] = ts[ns][i];
}
return true;
return true;
}
int p3p::solve(double R[4][3][3], double t[4][3],
double mu0, double mv0, double X0, double Y0, double Z0,
double mu1, double mv1, double X1, double Y1, double Z1,
double mu2, double mv2, double X2, double Y2, double Z2)
double mu0, double mv0, double X0, double Y0, double Z0,
double mu1, double mv1, double X1, double Y1, double Z1,
double mu2, double mv2, double X2, double Y2, double Z2)
{
double mk0, mk1, mk2;
double norm;
double mk0, mk1, mk2;
double norm;
mu0 = inv_fx * mu0 - cx_fx;
mv0 = inv_fy * mv0 - cy_fy;
norm = sqrt(mu0 * mu0 + mv0 * mv0 + 1);
mk0 = 1. / norm; mu0 *= mk0; mv0 *= mk0;
mu0 = inv_fx * mu0 - cx_fx;
mv0 = inv_fy * mv0 - cy_fy;
norm = sqrt(mu0 * mu0 + mv0 * mv0 + 1);
mk0 = 1. / norm; mu0 *= mk0; mv0 *= mk0;
mu1 = inv_fx * mu1 - cx_fx;
mv1 = inv_fy * mv1 - cy_fy;
norm = sqrt(mu1 * mu1 + mv1 * mv1 + 1);
mk1 = 1. / norm; mu1 *= mk1; mv1 *= mk1;
mu1 = inv_fx * mu1 - cx_fx;
mv1 = inv_fy * mv1 - cy_fy;
norm = sqrt(mu1 * mu1 + mv1 * mv1 + 1);
mk1 = 1. / norm; mu1 *= mk1; mv1 *= mk1;
mu2 = inv_fx * mu2 - cx_fx;
mv2 = inv_fy * mv2 - cy_fy;
norm = sqrt(mu2 * mu2 + mv2 * mv2 + 1);
mk2 = 1. / norm; mu2 *= mk2; mv2 *= mk2;
mu2 = inv_fx * mu2 - cx_fx;
mv2 = inv_fy * mv2 - cy_fy;
norm = sqrt(mu2 * mu2 + mv2 * mv2 + 1);
mk2 = 1. / norm; mu2 *= mk2; mv2 *= mk2;
double distances[3];
distances[0] = sqrt( (X1 - X2) * (X1 - X2) + (Y1 - Y2) * (Y1 - Y2) + (Z1 - Z2) * (Z1 - Z2) );
distances[1] = sqrt( (X0 - X2) * (X0 - X2) + (Y0 - Y2) * (Y0 - Y2) + (Z0 - Z2) * (Z0 - Z2) );
distances[2] = sqrt( (X0 - X1) * (X0 - X1) + (Y0 - Y1) * (Y0 - Y1) + (Z0 - Z1) * (Z0 - Z1) );
double distances[3];
distances[0] = sqrt( (X1 - X2) * (X1 - X2) + (Y1 - Y2) * (Y1 - Y2) + (Z1 - Z2) * (Z1 - Z2) );
distances[1] = sqrt( (X0 - X2) * (X0 - X2) + (Y0 - Y2) * (Y0 - Y2) + (Z0 - Z2) * (Z0 - Z2) );
distances[2] = sqrt( (X0 - X1) * (X0 - X1) + (Y0 - Y1) * (Y0 - Y1) + (Z0 - Z1) * (Z0 - Z1) );
// Calculate angles
double cosines[3];
cosines[0] = mu1 * mu2 + mv1 * mv2 + mk1 * mk2;
cosines[1] = mu0 * mu2 + mv0 * mv2 + mk0 * mk2;
cosines[2] = mu0 * mu1 + mv0 * mv1 + mk0 * mk1;
// Calculate angles
double cosines[3];
cosines[0] = mu1 * mu2 + mv1 * mv2 + mk1 * mk2;
cosines[1] = mu0 * mu2 + mv0 * mv2 + mk0 * mk2;
cosines[2] = mu0 * mu1 + mv0 * mv1 + mk0 * mk1;
double lengths[4][3];
int n = solve_for_lengths(lengths, distances, cosines);
double lengths[4][3];
int n = solve_for_lengths(lengths, distances, cosines);
int nb_solutions = 0;
for(int i = 0; i < n; i++) {
double M_orig[3][3];
int nb_solutions = 0;
for(int i = 0; i < n; i++) {
double M_orig[3][3];
M_orig[0][0] = lengths[i][0] * mu0;
M_orig[0][1] = lengths[i][0] * mv0;
M_orig[0][2] = lengths[i][0] * mk0;
M_orig[0][0] = lengths[i][0] * mu0;
M_orig[0][1] = lengths[i][0] * mv0;
M_orig[0][2] = lengths[i][0] * mk0;
M_orig[1][0] = lengths[i][1] * mu1;
M_orig[1][1] = lengths[i][1] * mv1;
M_orig[1][2] = lengths[i][1] * mk1;
M_orig[1][0] = lengths[i][1] * mu1;
M_orig[1][1] = lengths[i][1] * mv1;
M_orig[1][2] = lengths[i][1] * mk1;
M_orig[2][0] = lengths[i][2] * mu2;
M_orig[2][1] = lengths[i][2] * mv2;
M_orig[2][2] = lengths[i][2] * mk2;
M_orig[2][0] = lengths[i][2] * mu2;
M_orig[2][1] = lengths[i][2] * mv2;
M_orig[2][2] = lengths[i][2] * mk2;
if (!align(M_orig, X0, Y0, Z0, X1, Y1, Z1, X2, Y2, Z2, R[nb_solutions], t[nb_solutions]))
continue;
if (!align(M_orig, X0, Y0, Z0, X1, Y1, Z1, X2, Y2, Z2, R[nb_solutions], t[nb_solutions]))
continue;
nb_solutions++;
}
nb_solutions++;
}
return nb_solutions;
return nb_solutions;
}
/// Given 3D distances between three points and cosines of 3 angles at the apex, calculates
@ -170,247 +170,247 @@ int p3p::solve(double R[4][3][3], double t[4][3],
int p3p::solve_for_lengths(double lengths[4][3], double distances[3], double cosines[3])
{
double p = cosines[0] * 2;
double q = cosines[1] * 2;
double r = cosines[2] * 2;
double p = cosines[0] * 2;
double q = cosines[1] * 2;
double r = cosines[2] * 2;
double inv_d22 = 1. / (distances[2] * distances[2]);
double a = inv_d22 * (distances[0] * distances[0]);
double b = inv_d22 * (distances[1] * distances[1]);
double inv_d22 = 1. / (distances[2] * distances[2]);
double a = inv_d22 * (distances[0] * distances[0]);
double b = inv_d22 * (distances[1] * distances[1]);
double a2 = a * a, b2 = b * b, p2 = p * p, q2 = q * q, r2 = r * r;
double pr = p * r, pqr = q * pr;
double a2 = a * a, b2 = b * b, p2 = p * p, q2 = q * q, r2 = r * r;
double pr = p * r, pqr = q * pr;
// Check reality condition (the four points should not be coplanar)
if (p2 + q2 + r2 - pqr - 1 == 0)
return 0;
// Check reality condition (the four points should not be coplanar)
if (p2 + q2 + r2 - pqr - 1 == 0)
return 0;
double ab = a * b, a_2 = 2*a;
double ab = a * b, a_2 = 2*a;
double A = -2 * b + b2 + a2 + 1 + ab*(2 - r2) - a_2;
double A = -2 * b + b2 + a2 + 1 + ab*(2 - r2) - a_2;
// Check reality condition
if (A == 0) return 0;
// Check reality condition
if (A == 0) return 0;
double a_4 = 4*a;
double a_4 = 4*a;
double B = q*(-2*(ab + a2 + 1 - b) + r2*ab + a_4) + pr*(b - b2 + ab);
double C = q2 + b2*(r2 + p2 - 2) - b*(p2 + pqr) - ab*(r2 + pqr) + (a2 - a_2)*(2 + q2) + 2;
double D = pr*(ab-b2+b) + q*((p2-2)*b + 2 * (ab - a2) + a_4 - 2);
double E = 1 + 2*(b - a - ab) + b2 - b*p2 + a2;
double B = q*(-2*(ab + a2 + 1 - b) + r2*ab + a_4) + pr*(b - b2 + ab);
double C = q2 + b2*(r2 + p2 - 2) - b*(p2 + pqr) - ab*(r2 + pqr) + (a2 - a_2)*(2 + q2) + 2;
double D = pr*(ab-b2+b) + q*((p2-2)*b + 2 * (ab - a2) + a_4 - 2);
double E = 1 + 2*(b - a - ab) + b2 - b*p2 + a2;
double temp = (p2*(a-1+b) + r2*(a-1-b) + pqr - a*pqr);
double b0 = b * temp * temp;
// Check reality condition
if (b0 == 0)
return 0;
double temp = (p2*(a-1+b) + r2*(a-1-b) + pqr - a*pqr);
double b0 = b * temp * temp;
// Check reality condition
if (b0 == 0)
return 0;
double real_roots[4];
int n = solve_deg4(A, B, C, D, E, real_roots[0], real_roots[1], real_roots[2], real_roots[3]);
double real_roots[4];
int n = solve_deg4(A, B, C, D, E, real_roots[0], real_roots[1], real_roots[2], real_roots[3]);
if (n == 0)
return 0;
if (n == 0)
return 0;
int nb_solutions = 0;
double r3 = r2*r, pr2 = p*r2, r3q = r3 * q;
double inv_b0 = 1. / b0;
int nb_solutions = 0;
double r3 = r2*r, pr2 = p*r2, r3q = r3 * q;
double inv_b0 = 1. / b0;
// For each solution of x
for(int i = 0; i < n; i++) {
double x = real_roots[i];
// For each solution of x
for(int i = 0; i < n; i++) {
double x = real_roots[i];
// Check reality condition
if (x <= 0)
continue;
// Check reality condition
if (x <= 0)
continue;
double x2 = x*x;
double x2 = x*x;
double b1 =
((1-a-b)*x2 + (q*a-q)*x + 1 - a + b) *
(((r3*(a2 + ab*(2 - r2) - a_2 + b2 - 2*b + 1)) * x +
double b1 =
((1-a-b)*x2 + (q*a-q)*x + 1 - a + b) *
(((r3*(a2 + ab*(2 - r2) - a_2 + b2 - 2*b + 1)) * x +
(r3q*(2*(b-a2) + a_4 + ab*(r2 - 2) - 2) + pr2*(1 + a2 + 2*(ab-a-b) + r2*(b - b2) + b2))) * x2 +
(r3q*(2*(b-a2) + a_4 + ab*(r2 - 2) - 2) + pr2*(1 + a2 + 2*(ab-a-b) + r2*(b - b2) + b2))) * x2 +
(r3*(q2*(1-2*a+a2) + r2*(b2-ab) - a_4 + 2*(a2 - b2) + 2) + r*p2*(b2 + 2*(ab - b - a) + 1 + a2) + pr2*q*(a_4 + 2*(b - ab - a2) - 2 - r2*b)) * x +
(r3*(q2*(1-2*a+a2) + r2*(b2-ab) - a_4 + 2*(a2 - b2) + 2) + r*p2*(b2 + 2*(ab - b - a) + 1 + a2) + pr2*q*(a_4 + 2*(b - ab - a2) - 2 - r2*b)) * x +
2*r3q*(a_2 - b - a2 + ab - 1) + pr2*(q2 - a_4 + 2*(a2 - b2) + r2*b + q2*(a2 - a_2) + 2) +
p2*(p*(2*(ab - a - b) + a2 + b2 + 1) + 2*q*r*(b + a_2 - a2 - ab - 1)));
2*r3q*(a_2 - b - a2 + ab - 1) + pr2*(q2 - a_4 + 2*(a2 - b2) + r2*b + q2*(a2 - a_2) + 2) +
p2*(p*(2*(ab - a - b) + a2 + b2 + 1) + 2*q*r*(b + a_2 - a2 - ab - 1)));
// Check reality condition
if (b1 <= 0)
continue;
// Check reality condition
if (b1 <= 0)
continue;
double y = inv_b0 * b1;
double v = x2 + y*y - x*y*r;
double y = inv_b0 * b1;
double v = x2 + y*y - x*y*r;
if (v <= 0)
continue;
if (v <= 0)
continue;
double Z = distances[2] / sqrt(v);
double X = x * Z;
double Y = y * Z;
double Z = distances[2] / sqrt(v);
double X = x * Z;
double Y = y * Z;
lengths[nb_solutions][0] = X;
lengths[nb_solutions][1] = Y;
lengths[nb_solutions][2] = Z;
lengths[nb_solutions][0] = X;
lengths[nb_solutions][1] = Y;
lengths[nb_solutions][2] = Z;
nb_solutions++;
}
nb_solutions++;
}
return nb_solutions;
return nb_solutions;
}
bool p3p::align(double M_end[3][3],
double X0, double Y0, double Z0,
double X1, double Y1, double Z1,
double X2, double Y2, double Z2,
double R[3][3], double T[3])
double X0, double Y0, double Z0,
double X1, double Y1, double Z1,
double X2, double Y2, double Z2,
double R[3][3], double T[3])
{
// Centroids:
double C_start[3], C_end[3];
for(int i = 0; i < 3; i++) C_end[i] = (M_end[0][i] + M_end[1][i] + M_end[2][i]) / 3;
C_start[0] = (X0 + X1 + X2) / 3;
C_start[1] = (Y0 + Y1 + Y2) / 3;
C_start[2] = (Z0 + Z1 + Z2) / 3;
// Centroids:
double C_start[3], C_end[3];
for(int i = 0; i < 3; i++) C_end[i] = (M_end[0][i] + M_end[1][i] + M_end[2][i]) / 3;
C_start[0] = (X0 + X1 + X2) / 3;
C_start[1] = (Y0 + Y1 + Y2) / 3;
C_start[2] = (Z0 + Z1 + Z2) / 3;
// Covariance matrix s:
double s[3 * 3];
for(int j = 0; j < 3; j++) {
s[0 * 3 + j] = (X0 * M_end[0][j] + X1 * M_end[1][j] + X2 * M_end[2][j]) / 3 - C_end[j] * C_start[0];
s[1 * 3 + j] = (Y0 * M_end[0][j] + Y1 * M_end[1][j] + Y2 * M_end[2][j]) / 3 - C_end[j] * C_start[1];
s[2 * 3 + j] = (Z0 * M_end[0][j] + Z1 * M_end[1][j] + Z2 * M_end[2][j]) / 3 - C_end[j] * C_start[2];
}
// Covariance matrix s:
double s[3 * 3];
for(int j = 0; j < 3; j++) {
s[0 * 3 + j] = (X0 * M_end[0][j] + X1 * M_end[1][j] + X2 * M_end[2][j]) / 3 - C_end[j] * C_start[0];
s[1 * 3 + j] = (Y0 * M_end[0][j] + Y1 * M_end[1][j] + Y2 * M_end[2][j]) / 3 - C_end[j] * C_start[1];
s[2 * 3 + j] = (Z0 * M_end[0][j] + Z1 * M_end[1][j] + Z2 * M_end[2][j]) / 3 - C_end[j] * C_start[2];
}
double Qs[16], evs[4], U[16];
double Qs[16], evs[4], U[16];
Qs[0 * 4 + 0] = s[0 * 3 + 0] + s[1 * 3 + 1] + s[2 * 3 + 2];
Qs[1 * 4 + 1] = s[0 * 3 + 0] - s[1 * 3 + 1] - s[2 * 3 + 2];
Qs[2 * 4 + 2] = s[1 * 3 + 1] - s[2 * 3 + 2] - s[0 * 3 + 0];
Qs[3 * 4 + 3] = s[2 * 3 + 2] - s[0 * 3 + 0] - s[1 * 3 + 1];
Qs[0 * 4 + 0] = s[0 * 3 + 0] + s[1 * 3 + 1] + s[2 * 3 + 2];
Qs[1 * 4 + 1] = s[0 * 3 + 0] - s[1 * 3 + 1] - s[2 * 3 + 2];
Qs[2 * 4 + 2] = s[1 * 3 + 1] - s[2 * 3 + 2] - s[0 * 3 + 0];
Qs[3 * 4 + 3] = s[2 * 3 + 2] - s[0 * 3 + 0] - s[1 * 3 + 1];
Qs[1 * 4 + 0] = Qs[0 * 4 + 1] = s[1 * 3 + 2] - s[2 * 3 + 1];
Qs[2 * 4 + 0] = Qs[0 * 4 + 2] = s[2 * 3 + 0] - s[0 * 3 + 2];
Qs[3 * 4 + 0] = Qs[0 * 4 + 3] = s[0 * 3 + 1] - s[1 * 3 + 0];
Qs[2 * 4 + 1] = Qs[1 * 4 + 2] = s[1 * 3 + 0] + s[0 * 3 + 1];
Qs[3 * 4 + 1] = Qs[1 * 4 + 3] = s[2 * 3 + 0] + s[0 * 3 + 2];
Qs[3 * 4 + 2] = Qs[2 * 4 + 3] = s[2 * 3 + 1] + s[1 * 3 + 2];
Qs[1 * 4 + 0] = Qs[0 * 4 + 1] = s[1 * 3 + 2] - s[2 * 3 + 1];
Qs[2 * 4 + 0] = Qs[0 * 4 + 2] = s[2 * 3 + 0] - s[0 * 3 + 2];
Qs[3 * 4 + 0] = Qs[0 * 4 + 3] = s[0 * 3 + 1] - s[1 * 3 + 0];
Qs[2 * 4 + 1] = Qs[1 * 4 + 2] = s[1 * 3 + 0] + s[0 * 3 + 1];
Qs[3 * 4 + 1] = Qs[1 * 4 + 3] = s[2 * 3 + 0] + s[0 * 3 + 2];
Qs[3 * 4 + 2] = Qs[2 * 4 + 3] = s[2 * 3 + 1] + s[1 * 3 + 2];
jacobi_4x4(Qs, evs, U);
jacobi_4x4(Qs, evs, U);
// Looking for the largest eigen value:
int i_ev = 0;
double ev_max = evs[i_ev];
for(int i = 1; i < 4; i++)
if (evs[i] > ev_max)
ev_max = evs[i_ev = i];
// Looking for the largest eigen value:
int i_ev = 0;
double ev_max = evs[i_ev];
for(int i = 1; i < 4; i++)
if (evs[i] > ev_max)
ev_max = evs[i_ev = i];
// Quaternion:
double q[4];
for(int i = 0; i < 4; i++)
q[i] = U[i * 4 + i_ev];
// Quaternion:
double q[4];
for(int i = 0; i < 4; i++)
q[i] = U[i * 4 + i_ev];
double q02 = q[0] * q[0], q12 = q[1] * q[1], q22 = q[2] * q[2], q32 = q[3] * q[3];
double q0_1 = q[0] * q[1], q0_2 = q[0] * q[2], q0_3 = q[0] * q[3];
double q1_2 = q[1] * q[2], q1_3 = q[1] * q[3];
double q2_3 = q[2] * q[3];
double q02 = q[0] * q[0], q12 = q[1] * q[1], q22 = q[2] * q[2], q32 = q[3] * q[3];
double q0_1 = q[0] * q[1], q0_2 = q[0] * q[2], q0_3 = q[0] * q[3];
double q1_2 = q[1] * q[2], q1_3 = q[1] * q[3];
double q2_3 = q[2] * q[3];
R[0][0] = q02 + q12 - q22 - q32;
R[0][1] = 2. * (q1_2 - q0_3);
R[0][2] = 2. * (q1_3 + q0_2);
R[0][0] = q02 + q12 - q22 - q32;
R[0][1] = 2. * (q1_2 - q0_3);
R[0][2] = 2. * (q1_3 + q0_2);
R[1][0] = 2. * (q1_2 + q0_3);
R[1][1] = q02 + q22 - q12 - q32;
R[1][2] = 2. * (q2_3 - q0_1);
R[1][0] = 2. * (q1_2 + q0_3);
R[1][1] = q02 + q22 - q12 - q32;
R[1][2] = 2. * (q2_3 - q0_1);
R[2][0] = 2. * (q1_3 - q0_2);
R[2][1] = 2. * (q2_3 + q0_1);
R[2][2] = q02 + q32 - q12 - q22;
R[2][0] = 2. * (q1_3 - q0_2);
R[2][1] = 2. * (q2_3 + q0_1);
R[2][2] = q02 + q32 - q12 - q22;
for(int i = 0; i < 3; i++)
T[i] = C_end[i] - (R[i][0] * C_start[0] + R[i][1] * C_start[1] + R[i][2] * C_start[2]);
for(int i = 0; i < 3; i++)
T[i] = C_end[i] - (R[i][0] * C_start[0] + R[i][1] * C_start[1] + R[i][2] * C_start[2]);
return true;
return true;
}
bool p3p::jacobi_4x4(double * A, double * D, double * U)
{
double B[4], Z[4];
double Id[16] = {1., 0., 0., 0.,
0., 1., 0., 0.,
0., 0., 1., 0.,
0., 0., 0., 1.};
double B[4], Z[4];
double Id[16] = {1., 0., 0., 0.,
0., 1., 0., 0.,
0., 0., 1., 0.,
0., 0., 0., 1.};
memcpy(U, Id, 16 * sizeof(double));
memcpy(U, Id, 16 * sizeof(double));
B[0] = A[0]; B[1] = A[5]; B[2] = A[10]; B[3] = A[15];
memcpy(D, B, 4 * sizeof(double));
memset(Z, 0, 4 * sizeof(double));
B[0] = A[0]; B[1] = A[5]; B[2] = A[10]; B[3] = A[15];
memcpy(D, B, 4 * sizeof(double));
memset(Z, 0, 4 * sizeof(double));
for(int iter = 0; iter < 50; iter++) {
double sum = fabs(A[1]) + fabs(A[2]) + fabs(A[3]) + fabs(A[6]) + fabs(A[7]) + fabs(A[11]);
for(int iter = 0; iter < 50; iter++) {
double sum = fabs(A[1]) + fabs(A[2]) + fabs(A[3]) + fabs(A[6]) + fabs(A[7]) + fabs(A[11]);
if (sum == 0.0)
return true;
if (sum == 0.0)
return true;
double tresh = (iter < 3) ? 0.2 * sum / 16. : 0.0;
for(int i = 0; i < 3; i++) {
double * pAij = A + 5 * i + 1;
for(int j = i + 1 ; j < 4; j++) {
double Aij = *pAij;
double eps_machine = 100.0 * fabs(Aij);
double tresh = (iter < 3) ? 0.2 * sum / 16. : 0.0;
for(int i = 0; i < 3; i++) {
double * pAij = A + 5 * i + 1;
for(int j = i + 1 ; j < 4; j++) {
double Aij = *pAij;
double eps_machine = 100.0 * fabs(Aij);
if ( iter > 3 && fabs(D[i]) + eps_machine == fabs(D[i]) && fabs(D[j]) + eps_machine == fabs(D[j]) )
*pAij = 0.0;
else if (fabs(Aij) > tresh) {
double h = D[j] - D[i], t;
if (fabs(h) + eps_machine == fabs(h))
t = Aij / h;
else {
double theta = 0.5 * h / Aij;
t = 1.0 / (fabs(theta) + sqrt(1.0 + theta * theta));
if (theta < 0.0) t = -t;
}
if ( iter > 3 && fabs(D[i]) + eps_machine == fabs(D[i]) && fabs(D[j]) + eps_machine == fabs(D[j]) )
*pAij = 0.0;
else if (fabs(Aij) > tresh) {
double hh = D[j] - D[i], t;
if (fabs(hh) + eps_machine == fabs(hh))
t = Aij / hh;
else {
double theta = 0.5 * hh / Aij;
t = 1.0 / (fabs(theta) + sqrt(1.0 + theta * theta));
if (theta < 0.0) t = -t;
}
h = t * Aij;
Z[i] -= h;
Z[j] += h;
D[i] -= h;
D[j] += h;
*pAij = 0.0;
hh = t * Aij;
Z[i] -= hh;
Z[j] += hh;
D[i] -= hh;
D[j] += hh;
*pAij = 0.0;
double c = 1.0 / sqrt(1 + t * t);
double s = t * c;
double tau = s / (1.0 + c);
for(int k = 0; k <= i - 1; k++) {
double g = A[k * 4 + i], h = A[k * 4 + j];
A[k * 4 + i] = g - s * (h + g * tau);
A[k * 4 + j] = h + s * (g - h * tau);
}
for(int k = i + 1; k <= j - 1; k++) {
double g = A[i * 4 + k], h = A[k * 4 + j];
A[i * 4 + k] = g - s * (h + g * tau);
A[k * 4 + j] = h + s * (g - h * tau);
}
for(int k = j + 1; k < 4; k++) {
double g = A[i * 4 + k], h = A[j * 4 + k];
A[i * 4 + k] = g - s * (h + g * tau);
A[j * 4 + k] = h + s * (g - h * tau);
}
for(int k = 0; k < 4; k++) {
double g = U[k * 4 + i], h = U[k * 4 + j];
U[k * 4 + i] = g - s * (h + g * tau);
U[k * 4 + j] = h + s * (g - h * tau);
}
}
pAij++;
}
}
double c = 1.0 / sqrt(1 + t * t);
double s = t * c;
double tau = s / (1.0 + c);
for(int k = 0; k <= i - 1; k++) {
double g = A[k * 4 + i], h = A[k * 4 + j];
A[k * 4 + i] = g - s * (h + g * tau);
A[k * 4 + j] = h + s * (g - h * tau);
}
for(int k = i + 1; k <= j - 1; k++) {
double g = A[i * 4 + k], h = A[k * 4 + j];
A[i * 4 + k] = g - s * (h + g * tau);
A[k * 4 + j] = h + s * (g - h * tau);
}
for(int k = j + 1; k < 4; k++) {
double g = A[i * 4 + k], h = A[j * 4 + k];
A[i * 4 + k] = g - s * (h + g * tau);
A[j * 4 + k] = h + s * (g - h * tau);
}
for(int k = 0; k < 4; k++) {
double g = U[k * 4 + i], h = U[k * 4 + j];
U[k * 4 + i] = g - s * (h + g * tau);
U[k * 4 + j] = h + s * (g - h * tau);
}
}
pAij++;
}
}
for(int i = 0; i < 4; i++) B[i] += Z[i];
memcpy(D, B, 4 * sizeof(double));
memset(Z, 0, 4 * sizeof(double));
}
for(int i = 0; i < 4; i++) B[i] += Z[i];
memcpy(D, B, 4 * sizeof(double));
memset(Z, 0, 4 * sizeof(double));
}
return false;
return false;
}

4
modules/calib3d/src/precomp.hpp
View File

@ -42,10 +42,6 @@
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#if _MSC_VER >= 1200
#pragma warning( disable: 4251 4710 4711 4514 4996 )
#endif
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif

102
modules/calib3d/src/quadsubpix.cpp
View File

@ -54,39 +54,39 @@
namespace cv {
void drawCircles(Mat& img, const vector<Point2f>& corners, const vector<float>& radius)
{
for(size_t i = 0; i < corners.size(); i++)
{
circle(img, corners[i], cvRound(radius[i]), CV_RGB(255, 0, 0));
}
}
// static void drawCircles(Mat& img, const vector<Point2f>& corners, const vector<float>& radius)
// {
// for(size_t i = 0; i < corners.size(); i++)
// {
// circle(img, corners[i], cvRound(radius[i]), CV_RGB(255, 0, 0));
// }
// }
int histQuantile(const Mat& hist, float quantile)
{
if(hist.dims > 1) return -1; // works for 1D histograms only
// static int histQuantile(const Mat& hist, float quantile)
// {
// if(hist.dims > 1) return -1; // works for 1D histograms only
float cur_sum = 0;
float total_sum = (float)sum(hist).val[0];
float quantile_sum = total_sum*quantile;
for(int j = 0; j < hist.size[0]; j++)
{
cur_sum += (float)hist.at<float>(j);
if(cur_sum > quantile_sum)
{
return j;
}
}
// float cur_sum = 0;
// float total_sum = (float)sum(hist).val[0];
// float quantile_sum = total_sum*quantile;
// for(int j = 0; j < hist.size[0]; j++)
// {
// cur_sum += (float)hist.at<float>(j);
// if(cur_sum > quantile_sum)
// {
// return j;
// }
// }
return hist.size[0] - 1;
}
// return hist.size[0] - 1;
// }
bool is_smaller(const std::pair<int, float>& p1, const std::pair<int, float>& p2)
inline bool is_smaller(const std::pair<int, float>& p1, const std::pair<int, float>& p2)
{
return p1.second < p2.second;
}
void orderContours(const vector<vector<Point> >& contours, Point2f point, vector<std::pair<int, float> >& order)
static void orderContours(const vector<vector<Point> >& contours, Point2f point, vector<std::pair<int, float> >& order)
{
order.clear();
size_t i, j, n = contours.size();
@ -106,16 +106,16 @@ void orderContours(const vector<vector<Point> >& contours, Point2f point, vector
}
// fit second order curve to a set of 2D points
void fitCurve2Order(const vector<Point2f>& /*points*/, vector<float>& /*curve*/)
inline void fitCurve2Order(const vector<Point2f>& /*points*/, vector<float>& /*curve*/)
{
// TBD
}
void findCurvesCross(const vector<float>& /*curve1*/, const vector<float>& /*curve2*/, Point2f& /*cross_point*/)
inline void findCurvesCross(const vector<float>& /*curve1*/, const vector<float>& /*curve2*/, Point2f& /*cross_point*/)
{
}
void findLinesCrossPoint(Point2f origin1, Point2f dir1, Point2f origin2, Point2f dir2, Point2f& cross_point)
static void findLinesCrossPoint(Point2f origin1, Point2f dir1, Point2f origin2, Point2f dir2, Point2f& cross_point)
{
float det = dir2.x*dir1.y - dir2.y*dir1.x;
Point2f offset = origin2 - origin1;
@ -124,30 +124,30 @@ void findLinesCrossPoint(Point2f origin1, Point2f dir1, Point2f origin2, Point2f
cross_point = origin1 + dir1*alpha;
}
void findCorner(const vector<Point>& contour, Point2f point, Point2f& corner)
{
// find the nearest point
double min_dist = std::numeric_limits<double>::max();
int min_idx = -1;
// static void findCorner(const vector<Point>& contour, Point2f point, Point2f& corner)
// {
// // find the nearest point
// double min_dist = std::numeric_limits<double>::max();
// int min_idx = -1;
// find corner idx
for(size_t i = 0; i < contour.size(); i++)
{
double dist = norm(Point2f((float)contour[i].x, (float)contour[i].y) - point);
if(dist < min_dist)
{
min_dist = dist;
min_idx = (int)i;
}
}
assert(min_idx >= 0);
// // find corner idx
// for(size_t i = 0; i < contour.size(); i++)
// {
// double dist = norm(Point2f((float)contour[i].x, (float)contour[i].y) - point);
// if(dist < min_dist)
// {
// min_dist = dist;
// min_idx = (int)i;
// }
// }
// assert(min_idx >= 0);
// temporary solution, have to make something more precise
corner = contour[min_idx];
return;
}
// // temporary solution, have to make something more precise
// corner = contour[min_idx];
// return;
// }
void findCorner(const vector<Point2f>& contour, Point2f point, Point2f& corner)
static void findCorner(const vector<Point2f>& contour, Point2f point, Point2f& corner)
{
// find the nearest point
double min_dist = std::numeric_limits<double>::max();
@ -170,7 +170,7 @@ void findCorner(const vector<Point2f>& contour, Point2f point, Point2f& corner)
return;
}
int segment_hist_max(const Mat& hist, int& low_thresh, int& high_thresh)
static int segment_hist_max(const Mat& hist, int& low_thresh, int& high_thresh)
{
Mat bw;
//const double max_bell_width = 20; // we expect two bells with width bounded above
@ -252,7 +252,7 @@ bool cv::find4QuadCornerSubpix(InputArray _img, InputOutputArray _corners, Size
int black_thresh = histQuantile(hist, 0.45f);
int white_thresh = histQuantile(hist, 0.55f);
#else
int black_thresh, white_thresh;
int black_thresh = 0, white_thresh = 0;
segment_hist_max(hist, black_thresh, white_thresh);
#endif

108
modules/calib3d/src/solvepnp.cpp
View File

@ -59,41 +59,41 @@ bool cv::solvePnP( InputArray _opoints, InputArray _ipoints,
if (flags == CV_EPNP)
{
cv::Mat undistortedPoints;
cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
epnp PnP(cameraMatrix, opoints, undistortedPoints);
cv::Mat undistortedPoints;
cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
epnp PnP(cameraMatrix, opoints, undistortedPoints);
cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
PnP.compute_pose(R, tvec);
cv::Rodrigues(R, rvec);
return true;
}
else if (flags == CV_P3P)
{
CV_Assert( npoints == 4);
cv::Mat undistortedPoints;
cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
p3p P3Psolver(cameraMatrix);
return true;
}
else if (flags == CV_P3P)
{
CV_Assert( npoints == 4);
cv::Mat undistortedPoints;
cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
p3p P3Psolver(cameraMatrix);
cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
bool result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
if (result)
cv::Rodrigues(R, rvec);
return result;
}
else if (flags == CV_ITERATIVE)
{
CvMat c_objectPoints = opoints, c_imagePoints = ipoints;
CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
CvMat c_rvec = _rvec.getMat(), c_tvec = _tvec.getMat();
cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
c_distCoeffs.rows*c_distCoeffs.cols ? &c_distCoeffs : 0,
&c_rvec, &c_tvec, useExtrinsicGuess );
return true;
}
else
cv::Rodrigues(R, rvec);
return result;
}
else if (flags == CV_ITERATIVE)
{
CvMat c_objectPoints = opoints, c_imagePoints = ipoints;
CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
CvMat c_rvec = _rvec.getMat(), c_tvec = _tvec.getMat();
cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
c_distCoeffs.rows*c_distCoeffs.cols ? &c_distCoeffs : 0,
&c_rvec, &c_tvec, useExtrinsicGuess );
return true;
}
else
CV_Error(CV_StsBadArg, "The flags argument must be one of CV_ITERATIVE or CV_EPNP");
return false;
return false;
}
namespace cv
@ -102,7 +102,7 @@ namespace cv
{
const int MIN_POINTS_COUNT = 4;
void project3dPoints(const Mat& points, const Mat& rvec, const Mat& tvec, Mat& modif_points)
static void project3dPoints(const Mat& points, const Mat& rvec, const Mat& tvec, Mat& modif_points)
{
modif_points.create(1, points.cols, CV_32FC3);
Mat R(3, 3, CV_64FC1);
@ -119,11 +119,11 @@ namespace cv
{
public:
Mutex() {
}
}
void lock()
{
#ifdef HAVE_TBB
resultsMutex.lock();
resultsMutex.lock();
#endif
}
@ -158,11 +158,11 @@ namespace cv
float reprojectionError;
int minInliersCount;
bool useExtrinsicGuess;
int flags;
int flags;
CameraParameters camera;
};
void pnpTask(const vector<char>& pointsMask, const Mat& objectPoints, const Mat& imagePoints,
static void pnpTask(const vector<char>& pointsMask, const Mat& objectPoints, const Mat& imagePoints,
const Parameters& params, vector<int>& inliers, Mat& rvec, Mat& tvec,
const Mat& rvecInit, const Mat& tvecInit, Mutex& resultsMutex)
{
@ -195,8 +195,8 @@ namespace cv
rvecInit.copyTo(localRvec);
tvecInit.copyTo(localTvec);
solvePnP(modelObjectPoints, modelImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec,
params.useExtrinsicGuess, params.flags);
solvePnP(modelObjectPoints, modelImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec,
params.useExtrinsicGuess, params.flags);
vector<Point2f> projected_points;
@ -253,16 +253,16 @@ namespace cv
}
}
}
PnPSolver(const Mat& objectPoints, const Mat& imagePoints, const Parameters& parameters,
Mat& rvec, Mat& tvec, vector<int>& inliers):
objectPoints(objectPoints), imagePoints(imagePoints), parameters(parameters),
rvec(rvec), tvec(tvec), inliers(inliers)
PnPSolver(const Mat& _objectPoints, const Mat& _imagePoints, const Parameters& _parameters,
Mat& _rvec, Mat& _tvec, vector<int>& _inliers):
objectPoints(_objectPoints), imagePoints(_imagePoints), parameters(_parameters),
rvec(_rvec), tvec(_tvec), inliers(_inliers)
{
rvec.copyTo(initRvec);
tvec.copyTo(initTvec);
}
private:
PnPSolver& operator=(const PnPSolver&);
PnPSolver& operator=(const PnPSolver&);
const Mat& objectPoints;
const Mat& imagePoints;
@ -325,7 +325,7 @@ void cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
params.reprojectionError = reprojectionError;
params.useExtrinsicGuess = useExtrinsicGuess;
params.camera.init(cameraMatrix, distCoeffs);
params.flags = flags;
params.flags = flags;
vector<int> localInliers;
Mat localRvec, localTvec;
@ -340,21 +340,21 @@ void cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
if (localInliers.size() >= (size_t)pnpransac::MIN_POINTS_COUNT)
{
if (flags != CV_P3P)
{
int i, pointsCount = (int)localInliers.size();
Mat inlierObjectPoints(1, pointsCount, CV_32FC3), inlierImagePoints(1, pointsCount, CV_32FC2);
for (i = 0; i < pointsCount; i++)
{
int index = localInliers[i];
Mat colInlierImagePoints = inlierImagePoints(Rect(i, 0, 1, 1));
imagePoints.col(index).copyTo(colInlierImagePoints);
Mat colInlierObjectPoints = inlierObjectPoints(Rect(i, 0, 1, 1));
objectPoints.col(index).copyTo(colInlierObjectPoints);
}
solvePnP(inlierObjectPoints, inlierImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec, true, flags);
}
localRvec.copyTo(rvec);
if (flags != CV_P3P)
{
int i, pointsCount = (int)localInliers.size();
Mat inlierObjectPoints(1, pointsCount, CV_32FC3), inlierImagePoints(1, pointsCount, CV_32FC2);
for (i = 0; i < pointsCount; i++)
{
int index = localInliers[i];
Mat colInlierImagePoints = inlierImagePoints(Rect(i, 0, 1, 1));
imagePoints.col(index).copyTo(colInlierImagePoints);
Mat colInlierObjectPoints = inlierObjectPoints(Rect(i, 0, 1, 1));
objectPoints.col(index).copyTo(colInlierObjectPoints);
}
solvePnP(inlierObjectPoints, inlierImagePoints, params.camera.intrinsics, params.camera.distortion, localRvec, localTvec, true, flags);
}
localRvec.copyTo(rvec);
localTvec.copyTo(tvec);
if (_inliers.needed())
Mat(localInliers).copyTo(_inliers);

13
modules/calib3d/src/stereobm.cpp
View File

@ -336,7 +336,7 @@ static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
short* costptr = cost.data ? (short*)cost.data + lofs + x : &costbuf;
int x0 = x - wsz2 - 1, x1 = x + wsz2;
const uchar* cbuf_sub = cbuf0 + ((x0 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
uchar* cbuf = cbuf0 + ((x1 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
cbuf = cbuf0 + ((x1 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
hsad = hsad0 - dy0*ndisp;
lptr_sub = lptr0 + MIN(MAX(x0, -lofs), width-1-lofs) - dy0*sstep;
lptr = lptr0 + MIN(MAX(x1, -lofs), width-1-lofs) - dy0*sstep;
@ -463,7 +463,8 @@ static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
int thresh = minsad + ((minsad * uniquenessRatio) >> 8);
__m128i thresh8 = _mm_set1_epi16((short)(thresh + 1));
__m128i d1 = _mm_set1_epi16((short)(mind-1)), d2 = _mm_set1_epi16((short)(mind+1));
__m128i dd_16 = _mm_add_epi16(dd_8, dd_8), d8 = _mm_sub_epi16(d0_8, dd_16);
__m128i dd_16 = _mm_add_epi16(dd_8, dd_8);
d8 = _mm_sub_epi16(d0_8, dd_16);
for( d = 0; d < ndisp; d += 16 )
{
@ -492,7 +493,8 @@ static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
if( 0 < mind && mind < ndisp - 1 )
{
int p = sad[mind+1], n = sad[mind-1], d = p + n - 2*sad[mind] + std::abs(p - n);
int p = sad[mind+1], n = sad[mind-1];
d = p + n - 2*sad[mind] + std::abs(p - n);
dptr[y*dstep] = (short)(((ndisp - mind - 1 + mindisp)*256 + (d != 0 ? (p-n)*256/d : 0) + 15) >> 4);
}
else
@ -583,7 +585,7 @@ findStereoCorrespondenceBM( const Mat& left, const Mat& right,
int* costptr = cost.data ? (int*)cost.data + lofs + x : &costbuf;
int x0 = x - wsz2 - 1, x1 = x + wsz2;
const uchar* cbuf_sub = cbuf0 + ((x0 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
uchar* cbuf = cbuf0 + ((x1 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
cbuf = cbuf0 + ((x1 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
hsad = hsad0 - dy0*ndisp;
lptr_sub = lptr0 + MIN(MAX(x0, -lofs), width-1-lofs) - dy0*sstep;
lptr = lptr0 + MIN(MAX(x1, -lofs), width-1-lofs) - dy0*sstep;
@ -662,7 +664,8 @@ findStereoCorrespondenceBM( const Mat& left, const Mat& right,
{
sad[-1] = sad[1];
sad[ndisp] = sad[ndisp-2];
int p = sad[mind+1], n = sad[mind-1], d = p + n - 2*sad[mind] + std::abs(p - n);
int p = sad[mind+1], n = sad[mind-1];
d = p + n - 2*sad[mind] + std::abs(p - n);
dptr[y*dstep] = (short)(((ndisp - mind - 1 + mindisp)*256 + (d != 0 ? (p-n)*256/d : 0) + 15) >> 4);
costptr[y*coststep] = sad[mind];
}

34
modules/calib3d/src/stereosgbm.cpp
View File

@ -773,11 +773,11 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
if( d < D )
continue;
d = bestDisp;
int x2 = x + minX1 - d - minD;
if( disp2cost[x2] > minS )
int _x2 = x + minX1 - d - minD;
if( disp2cost[_x2] > minS )
{
disp2cost[x2] = (CostType)minS;
disp2ptr[x2] = (DispType)(d + minD);
disp2cost[_x2] = (CostType)minS;
disp2ptr[_x2] = (DispType)(d + minD);
}
if( 0 < d && d < D-1 )
@ -798,11 +798,11 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
// we round the computed disparity both towards -inf and +inf and check
// if either of the corresponding disparities in disp2 is consistent.
// This is to give the computed disparity a chance to look valid if it is.
int d = disp1ptr[x];
if( d == INVALID_DISP_SCALED )
int d1 = disp1ptr[x];
if( d1 == INVALID_DISP_SCALED )
continue;
int _d = d >> DISP_SHIFT;
int d_ = (d + DISP_SCALE-1) >> DISP_SHIFT;
int _d = d1 >> DISP_SHIFT;
int d_ = (d1 + DISP_SCALE-1) >> DISP_SHIFT;
int _x = x - _d, x_ = x - d_;
if( 0 <= _x && _x < width && disp2ptr[_x] >= minD && std::abs(disp2ptr[_x] - _d) > disp12MaxDiff &&
0 <= x_ && x_ < width && disp2ptr[x_] >= minD && std::abs(disp2ptr[x_] - d_) > disp12MaxDiff )
@ -890,9 +890,9 @@ void cv::filterSpeckles( InputOutputArray _img, double _newval, int maxSpeckleSi
for( j = 0; j < width; j++ )
{
if( ds[j] != newVal ) // not a bad disparity
if( ds[j] != newVal ) // not a bad disparity
{
if( ls[j] ) // has a label, check for bad label
if( ls[j] ) // has a label, check for bad label
{
if( rtype[ls[j]] ) // small region, zero out disparity
ds[j] = (short)newVal;
@ -900,10 +900,10 @@ void cv::filterSpeckles( InputOutputArray _img, double _newval, int maxSpeckleSi
// no label, assign and propagate
else
{
Point2s* ws = wbuf; // initialize wavefront
Point2s p((short)j, (short)i); // current pixel
curlabel++; // next label
int count = 0; // current region size
Point2s* ws = wbuf; // initialize wavefront
Point2s p((short)j, (short)i); // current pixel
curlabel++; // next label
int count = 0; // current region size
ls[j] = curlabel;
// wavefront propagation
@ -945,13 +945,13 @@ void cv::filterSpeckles( InputOutputArray _img, double _newval, int maxSpeckleSi
}
// assign label type
if( count <= maxSpeckleSize ) // speckle region
if( count <= maxSpeckleSize ) // speckle region
{
rtype[ls[j]] = 1; // small region label
rtype[ls[j]] = 1; // small region label
ds[j] = (short)newVal;
}
else
rtype[ls[j]] = 0; // large region label
rtype[ls[j]] = 0; // large region label
}
}
}

1364
modules/calib3d/test/test_cameracalibration.cpp
View File

File diff suppressed because it is too large Load Diff

8
modules/calib3d/test/test_cameracalibration_artificial.cpp
View File

@ -221,19 +221,19 @@ protected:
}
}
double reprojectErrorWithoutIntrinsics(const vector<Point3f>& cb3d, const vector<Mat>& rvecs_exp, const vector<Mat>& tvecs_exp,
double reprojectErrorWithoutIntrinsics(const vector<Point3f>& cb3d, const vector<Mat>& _rvecs_exp, const vector<Mat>& _tvecs_exp,
const vector<Mat>& rvecs_est, const vector<Mat>& tvecs_est)
{
const static Mat eye33 = Mat::eye(3, 3, CV_64F);
const static Mat zero15 = Mat::zeros(1, 5, CV_64F);
Mat chessboard3D(cb3d);
Mat _chessboard3D(cb3d);
vector<Point2f> uv_exp, uv_est;
double res = 0;
for(size_t i = 0; i < rvecs_exp.size(); ++i)
{
projectPoints(chessboard3D, rvecs_exp[i], tvecs_exp[i], eye33, zero15, uv_exp);
projectPoints(chessboard3D, rvecs_est[i], tvecs_est[i], eye33, zero15, uv_est);
projectPoints(_chessboard3D, _rvecs_exp[i], _tvecs_exp[i], eye33, zero15, uv_exp);
projectPoints(_chessboard3D, rvecs_est[i], tvecs_est[i], eye33, zero15, uv_est);
for(size_t j = 0; j < cb3d.size(); ++j)
res += norm(uv_exp[i] - uv_est[i]);
}

55
modules/calib3d/test/test_chesscorners.cpp
View File

@ -137,8 +137,7 @@ const double precise_success_error_level = 2;
/* ///////////////////// chess_corner_test ///////////////////////// */
void CV_ChessboardDetectorTest::run( int /*start_from */)
{
cvtest::TS& ts = *this->ts;
ts.set_failed_test_info( cvtest::TS::OK );
ts->set_failed_test_info( cvtest::TS::OK );
/*if (!checkByGenerator())
return;*/
@ -146,19 +145,19 @@ void CV_ChessboardDetectorTest::run( int /*start_from */)
{
case CHESSBOARD:
checkByGenerator();
if (ts.get_err_code() != cvtest::TS::OK)
if (ts->get_err_code() != cvtest::TS::OK)
{
break;
}
run_batch("negative_list.dat");
if (ts.get_err_code() != cvtest::TS::OK)
if (ts->get_err_code() != cvtest::TS::OK)
{
break;
}
run_batch("chessboard_list.dat");
if (ts.get_err_code() != cvtest::TS::OK)
if (ts->get_err_code() != cvtest::TS::OK)
{
break;
}
@ -176,9 +175,7 @@ void CV_ChessboardDetectorTest::run( int /*start_from */)
void CV_ChessboardDetectorTest::run_batch( const string& filename )
{
cvtest::TS& ts = *this->ts;
ts.printf(cvtest::TS::LOG, "\nRunning batch %s\n", filename.c_str());
ts->printf(cvtest::TS::LOG, "\nRunning batch %s\n", filename.c_str());
//#define WRITE_POINTS 1
#ifndef WRITE_POINTS
double max_rough_error = 0, max_precise_error = 0;
@ -187,13 +184,13 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
switch( pattern )
{
case CHESSBOARD:
folder = string(ts.get_data_path()) + "cameracalibration/";
folder = string(ts->get_data_path()) + "cameracalibration/";
break;
case CIRCLES_GRID:
folder = string(ts.get_data_path()) + "cameracalibration/circles/";
folder = string(ts->get_data_path()) + "cameracalibration/circles/";
break;
case ASYMMETRIC_CIRCLES_GRID:
folder = string(ts.get_data_path()) + "cameracalibration/asymmetric_circles/";
folder = string(ts->get_data_path()) + "cameracalibration/asymmetric_circles/";
break;
}
@ -202,10 +199,10 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
if( !fs.isOpened() || board_list.empty() || !board_list.isSeq() || board_list.size() % 2 != 0 )
{
ts.printf( cvtest::TS::LOG, "%s can not be readed or is not valid\n", (folder + filename).c_str() );
ts.printf( cvtest::TS::LOG, "fs.isOpened=%d, board_list.empty=%d, board_list.isSeq=%d,board_list.size()%2=%d\n",
ts->printf( cvtest::TS::LOG, "%s can not be readed or is not valid\n", (folder + filename).c_str() );
ts->printf( cvtest::TS::LOG, "fs.isOpened=%d, board_list.empty=%d, board_list.isSeq=%d,board_list.size()%2=%d\n",
fs.isOpened(), (int)board_list.empty(), board_list.isSeq(), board_list.size()%2);
ts.set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA );
ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA );
return;
}
@ -216,7 +213,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
for(int idx = 0; idx < max_idx; ++idx )
{
ts.update_context( this, idx, true );
ts->update_context( this, idx, true );
/* read the image */
string img_file = board_list[idx * 2];
@ -224,19 +221,19 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
if( gray.empty() )
{
ts.printf( cvtest::TS::LOG, "one of chessboard images can't be read: %s\n", img_file.c_str() );
ts.set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA );
ts->printf( cvtest::TS::LOG, "one of chessboard images can't be read: %s\n", img_file.c_str() );
ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA );
return;
}
string filename = folder + (string)board_list[idx * 2 + 1];
string _filename = folder + (string)board_list[idx * 2 + 1];
bool doesContatinChessboard;
Mat expected;
{
FileStorage fs(filename, FileStorage::READ);
fs["corners"] >> expected;
fs["isFound"] >> doesContatinChessboard;
fs.release();
FileStorage fs1(_filename, FileStorage::READ);
fs1["corners"] >> expected;
fs1["isFound"] >> doesContatinChessboard;
fs1.release();
}
size_t count_exp = static_cast<size_t>(expected.cols * expected.rows);
Size pattern_size = expected.size();
@ -259,8 +256,8 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
if( result ^ doesContatinChessboard || v.size() != count_exp )
{
ts.printf( cvtest::TS::LOG, "chessboard is detected incorrectly in %s\n", img_file.c_str() );
ts.set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
ts->printf( cvtest::TS::LOG, "chessboard is detected incorrectly in %s\n", img_file.c_str() );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
@ -291,19 +288,19 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
#if 1
if( err > precise_success_error_level )
{
ts.printf( cvtest::TS::LOG, "Image %s: bad accuracy of adjusted corners %f\n", img_file.c_str(), err );
ts.set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
ts->printf( cvtest::TS::LOG, "Image %s: bad accuracy of adjusted corners %f\n", img_file.c_str(), err );
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
return;
}
#endif
ts.printf(cvtest::TS::LOG, "Error on %s is %f\n", img_file.c_str(), err);
ts->printf(cvtest::TS::LOG, "Error on %s is %f\n", img_file.c_str(), err);
max_precise_error = MAX( max_precise_error, err );
#endif
}
#ifdef WRITE_POINTS
Mat mat_v(pattern_size, CV_32FC2, (void*)&v[0]);
FileStorage fs(filename, FileStorage::WRITE);
FileStorage fs(_filename, FileStorage::WRITE);
fs << "isFound" << result;
fs << "corners" << mat_v;
fs.release();
@ -312,7 +309,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
}
sum_error /= count;
ts.printf(cvtest::TS::LOG, "Average error is %f\n", sum_error);
ts->printf(cvtest::TS::LOG, "Average error is %f\n", sum_error);
}
double calcErrorMinError(const Size& cornSz, const vector<Point2f>& corners_found, const vector<Point2f>& corners_generated)

21
modules/calib3d/test/test_compose_rt.cpp
View File

@ -139,8 +139,7 @@ protected:
void run(int)
{
cvtest::TS& ts = *this->ts;
ts.set_failed_test_info(cvtest::TS::OK);
ts->set_failed_test_info(cvtest::TS::OK);
Mat_<double> rvec1(3, 1), tvec1(3, 1), rvec2(3, 1), tvec2(3, 1);
@ -164,7 +163,7 @@ protected:
const double thres = 1e-5;
if (norm(rvec3_exp, rvec3) > thres || norm(tvec3_exp, tvec3) > thres)
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
const double eps = 1e-3;
Differential diff(eps, rvec1, tvec1, rvec2, tvec2);
@ -179,8 +178,8 @@ protected:
if (norm(dr3_dr1, dr3dr1) > thres || norm(dt3_dr1, dt3dr1) > thres)
{
ts.printf( cvtest::TS::LOG, "Invalid derivates by r1\n" );
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( cvtest::TS::LOG, "Invalid derivates by r1\n" );
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
}
Mat_<double> dr3_dr2, dt3_dr2;
@ -188,8 +187,8 @@ protected:
if (norm(dr3_dr2, dr3dr2) > thres || norm(dt3_dr2, dt3dr2) > thres)
{
ts.printf( cvtest::TS::LOG, "Invalid derivates by r2\n" );
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( cvtest::TS::LOG, "Invalid derivates by r2\n" );
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
}
Mat_<double> dr3_dt1, dt3_dt1;
@ -197,8 +196,8 @@ protected:
if (norm(dr3_dt1, dr3dt1) > thres || norm(dt3_dt1, dt3dt1) > thres)
{
ts.printf( cvtest::TS::LOG, "Invalid derivates by t1\n" );
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( cvtest::TS::LOG, "Invalid derivates by t1\n" );
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
}
Mat_<double> dr3_dt2, dt3_dt2;
@ -206,8 +205,8 @@ protected:
if (norm(dr3_dt2, dr3dt2) > thres || norm(dt3_dt2, dt3dt2) > thres)
{
ts.printf( cvtest::TS::LOG, "Invalid derivates by t2\n" );
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( cvtest::TS::LOG, "Invalid derivates by t2\n" );
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
}
}
};

44
modules/calib3d/test/test_homography.cpp
View File

@ -86,20 +86,20 @@ protected:
double sigma;
private:
float max_diff, max_2diff;
bool check_matrix_size(const cv::Mat& H);
bool check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff);
float max_diff, max_2diff;
bool check_matrix_size(const cv::Mat& H);
bool check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type, double &diff);
int check_ransac_mask_1(const Mat& src, const Mat& mask);
int check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask);
int check_ransac_mask_2(const Mat& original_mask, const Mat& found_mask);
void print_information_1(int j, int N, int method, const Mat& H);
void print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff);
void print_information_3(int j, int N, const Mat& mask);
void print_information_4(int method, int j, int N, int k, int l, double diff);
void print_information_5(int method, int j, int N, int l, double diff);
void print_information_6(int j, int N, int k, double diff, bool value);
void print_information_7(int j, int N, int k, double diff, bool original_value, bool found_value);
void print_information_8(int j, int N, int k, int l, double diff);
void print_information_1(int j, int N, int method, const Mat& H);
void print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff);
void print_information_3(int j, int N, const Mat& mask);
void print_information_4(int method, int j, int N, int k, int l, double diff);
void print_information_5(int method, int j, int N, int l, double diff);
void print_information_6(int j, int N, int k, double diff, bool value);
void print_information_7(int j, int N, int k, double diff, bool original_value, bool found_value);
void print_information_8(int j, int N, int k, int l, double diff);
};
CV_HomographyTest::CV_HomographyTest() : max_diff(1e-2f), max_2diff(2e-2f)
@ -138,25 +138,25 @@ int CV_HomographyTest::check_ransac_mask_2(const Mat& original_mask, const Mat&
return 0;
}
void CV_HomographyTest::print_information_1(int j, int N, int method, const Mat& H)
void CV_HomographyTest::print_information_1(int j, int N, int _method, const Mat& H)
{
cout << endl; cout << "Checking for homography matrix sizes..." << endl; cout << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl;
cout << "Count of points: " << N << endl; cout << endl;
cout << "Method: "; if (method == 0) cout << 0; else if (method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl;
cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl;
cout << "Homography matrix:" << endl; cout << endl;
cout << H << endl; cout << endl;
cout << "Number of rows: " << H.rows << " Number of cols: " << H.cols << endl; cout << endl;
}
void CV_HomographyTest::print_information_2(int j, int N, int method, const Mat& H, const Mat& H_res, int k, double diff)
void CV_HomographyTest::print_information_2(int j, int N, int _method, const Mat& H, const Mat& H_res, int k, double diff)
{
cout << endl; cout << "Checking for accuracy of homography matrix computing..." << endl; cout << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl;
cout << "Count of points: " << N << endl; cout << endl;
cout << "Method: "; if (method == 0) cout << 0; else if (method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl;
cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl;
cout << "Original matrix:" << endl; cout << endl;
cout << H << endl; cout << endl;
cout << "Found matrix:" << endl; cout << endl;
@ -178,10 +178,10 @@ void CV_HomographyTest::print_information_3(int j, int N, const Mat& mask)
cout << "Number of rows: " << mask.rows << " Number of cols: " << mask.cols << endl; cout << endl;
}
void CV_HomographyTest::print_information_4(int method, int j, int N, int k, int l, double diff)
void CV_HomographyTest::print_information_4(int _method, int j, int N, int k, int l, double diff)
{
cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl;
cout << "Method: "; if (method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl;
cout << "Method: "; if (_method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl;
cout << "Sigma of normal noise: " << sigma << endl;
@ -192,10 +192,10 @@ void CV_HomographyTest::print_information_4(int method, int j, int N, int k, int
cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl;
}
void CV_HomographyTest::print_information_5(int method, int j, int N, int l, double diff)
void CV_HomographyTest::print_information_5(int _method, int j, int N, int l, double diff)
{
cout << endl; cout << "Checking for accuracy of reprojection error computing..." << endl; cout << endl;
cout << "Method: "; if (method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl;
cout << "Method: "; if (_method == 0) cout << 0 << endl; else cout << "CV_LMEDS" << endl;
cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>";
cout << " Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl;
cout << "Sigma of normal noise: " << sigma << endl;
@ -412,7 +412,7 @@ void CV_HomographyTest::run(int)
{
case 0:
case CV_LMEDS:
{
{
Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f),
cv::findHomography(src_mat_2f, dst_vec),
cv::findHomography(src_vec, dst_mat_2f),
@ -465,7 +465,7 @@ void CV_HomographyTest::run(int)
}
continue;
}
}
case CV_RANSAC:
{
cv::Mat mask_res [4];

4
modules/calib3d/test/test_precomp.hpp
View File

@ -1,3 +1,7 @@
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
#endif
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__

17
modules/calib3d/test/test_solvepnp_ransac.cpp
View File

@ -106,7 +106,7 @@ protected:
}
}
virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* eps, double& maxError)
virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* epsilon, double& maxError)
{
Mat rvec, tvec;
vector<int> inliers;
@ -136,7 +136,7 @@ protected:
bool isTestSuccess = inliers.size() >= points.size()*0.95;
double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec);
isTestSuccess = isTestSuccess && rvecDiff < eps[method] && tvecDiff < eps[method];
isTestSuccess = isTestSuccess && rvecDiff < epsilon[method] && tvecDiff < epsilon[method];
double error = rvecDiff > tvecDiff ? rvecDiff : tvecDiff;
//cout << error << " " << inliers.size() << " " << eps[method] << endl;
if (error > maxError)
@ -147,8 +147,7 @@ protected:
void run(int)
{
cvtest::TS& ts = *this->ts;
ts.set_failed_test_info(cvtest::TS::OK);
ts->set_failed_test_info(cvtest::TS::OK);
vector<Point3f> points;
const int pointsCount = 500;
@ -157,7 +156,7 @@ protected:
const int methodsCount = 3;
RNG rng = ts.get_rng();
RNG rng = ts->get_rng();
for (int mode = 0; mode < 2; mode++)
@ -174,9 +173,9 @@ protected:
//cout << maxError << " " << successfulTestsCount << endl;
if (successfulTestsCount < 0.7*totalTestsCount)
{
ts.printf( cvtest::TS::LOG, "Invalid accuracy for method %d, failed %d tests from %d, maximum error equals %f, distortion mode equals %d\n",
ts->printf( cvtest::TS::LOG, "Invalid accuracy for method %d, failed %d tests from %d, maximum error equals %f, distortion mode equals %d\n",
method, totalTestsCount - successfulTestsCount, totalTestsCount, maxError, mode);
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
}
}
}
@ -198,7 +197,7 @@ public:
~CV_solvePnP_Test() {}
protected:
virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* eps, double& maxError)
virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* epsilon, double& maxError)
{
Mat rvec, tvec;
Mat trueRvec, trueTvec;
@ -226,7 +225,7 @@ protected:
false, method);
double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec);
bool isTestSuccess = rvecDiff < eps[method] && tvecDiff < eps[method];
bool isTestSuccess = rvecDiff < epsilon[method] && tvecDiff < epsilon[method];
double error = rvecDiff > tvecDiff ? rvecDiff : tvecDiff;
if (error > maxError)

4
modules/calib3d/test/test_stereomatching.cpp
View File

@ -593,11 +593,11 @@ int CV_StereoMatchingTest::readDatasetsParams( FileStorage& fs )
assert(fn.isSeq());
for( int i = 0; i < (int)fn.size(); i+=3 )
{
string name = fn[i];
string _name = fn[i];
DatasetParams params;
string sf = fn[i+1]; params.dispScaleFactor = atoi(sf.c_str());
string uv = fn[i+2]; params.dispUnknVal = atoi(uv.c_str());
datasetsParams[name] = params;
datasetsParams[_name] = params;
}
return cvtest::TS::OK;
}

36
modules/contrib/include/opencv2/contrib/contrib.hpp
View File

@ -585,34 +585,34 @@ namespace cv
//! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
CV_WRAP_AS(compute) virtual void operator()(const Mat& left, const Mat& right, Mat& disp);
CV_PROP_RW int levels;
CV_PROP_RW double pyrScale;
CV_PROP_RW int nIt;
CV_PROP_RW int minDisp;
CV_PROP_RW int maxDisp;
CV_PROP_RW int poly_n;
CV_PROP_RW double poly_sigma;
CV_PROP_RW float fi;
CV_PROP_RW float lambda;
CV_PROP_RW int penalization;
CV_PROP_RW int cycle;
CV_PROP_RW int flags;
CV_PROP_RW int levels;
CV_PROP_RW double pyrScale;
CV_PROP_RW int nIt;
CV_PROP_RW int minDisp;
CV_PROP_RW int maxDisp;
CV_PROP_RW int poly_n;
CV_PROP_RW double poly_sigma;
CV_PROP_RW float fi;
CV_PROP_RW float lambda;
CV_PROP_RW int penalization;
CV_PROP_RW int cycle;
CV_PROP_RW int flags;
private:
void autoParams();
void FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level);
void FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level);
void VCycle_MyFAS(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
void VariationalSolver(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
};
CV_EXPORTS void polyfit(const Mat& srcx, const Mat& srcy, Mat& dst, int order);
class CV_EXPORTS Directory
class CV_EXPORTS Directory
{
public:
static std::vector<std::string> GetListFiles ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFilesR ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFolders( const std::string& path, const std::string & exten = "*", bool addPath = true );
public:
static std::vector<std::string> GetListFiles ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFilesR ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFolders( const std::string& path, const std::string & exten = "*", bool addPath = true );
};
/*

6
modules/contrib/include/opencv2/contrib/hybridtracker.hpp
View File

@ -86,10 +86,10 @@ struct CV_EXPORTS CvMeanShiftTrackerParams
struct CV_EXPORTS CvFeatureTrackerParams
{
enum { SIFT = 0, SURF = 1, OPTICAL_FLOW = 2 };
CvFeatureTrackerParams(int feature_type = 0, int window_size = 0)
CvFeatureTrackerParams(int featureType = 0, int windowSize = 0)
{
feature_type = 0;
window_size = 0;
featureType = 0;
windowSize = 0;
}
int feature_type; // Feature type to use

574
modules/contrib/src/ba.cpp
View File

@ -58,26 +58,26 @@ LevMarqSparse::~LevMarqSparse() {
}
LevMarqSparse::LevMarqSparse(int npoints, // number of points
int ncameras, // number of cameras
int nPointParams, // number of params per one point (3 in case of 3D points)
int nCameraParams, // number of parameters per one camera
int nErrParams, // number of parameters in measurement vector
// for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
// 1 - point is visible for the camera, 0 - invisible
Mat& P0, // starting vector of parameters, first cameras then points
Mat& X_, // measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria, // termination criteria
int ncameras, // number of cameras
int nPointParams, // number of params per one point (3 in case of 3D points)
int nCameraParams, // number of parameters per one camera
int nErrParams, // number of parameters in measurement vector
// for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
// 1 - point is visible for the camera, 0 - invisible
Mat& P0, // starting vector of parameters, first cameras then points
Mat& X_, // measurements, in order of visibility. non visible cases are skipped
TermCriteria _criteria, // termination criteria
// callback for estimation of Jacobian matrices
void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& A, Mat& B, void* data),
// callback for estimation of backprojection errors
void (CV_CDECL * func)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& estim, void* data),
void* data, // user-specific data passed to the callbacks
BundleAdjustCallback _cb, void* _user_data
) {
// callback for estimation of Jacobian matrices
void (CV_CDECL * _fjac)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& A, Mat& B, void* data),
// callback for estimation of backprojection errors
void (CV_CDECL * _func)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& estim, void* data),
void* _data, // user-specific data passed to the callbacks
BundleAdjustCallback _cb, void* _user_data
) {
Vis_index = X = prevP = P = deltaP = err = JtJ_diag = S = hX = NULL;
U = ea = V = inv_V_star = eb = Yj = NULL;
A = B = W = NULL;
@ -86,7 +86,7 @@ LevMarqSparse::LevMarqSparse(int npoints, // number of points
user_data = _user_data;
run(npoints, ncameras, nPointParams, nCameraParams, nErrParams, visibility,
P0, X_, criteria, fjac, func, data);
P0, X_, _criteria, _fjac, _func, _data);
}
void LevMarqSparse::clear() {
@ -95,17 +95,17 @@ void LevMarqSparse::clear() {
//CvMat* tmp = ((CvMat**)(A->data.ptr + i * A->step))[j];
CvMat* tmp = A[j+i*num_cams];
if (tmp)
cvReleaseMat( &tmp );
cvReleaseMat( &tmp );
//tmp = ((CvMat**)(B->data.ptr + i * B->step))[j];
tmp = B[j+i*num_cams];
if (tmp)
cvReleaseMat( &tmp );
cvReleaseMat( &tmp );
//tmp = ((CvMat**)(W->data.ptr + j * W->step))[i];
tmp = W[j+i*num_cams];
if (tmp)
cvReleaseMat( &tmp );
cvReleaseMat( &tmp );
}
}
delete A; //cvReleaseMat(&A);
@ -165,19 +165,19 @@ void LevMarqSparse::clear() {
//num_errors - number of measurements.
void LevMarqSparse::run( int num_points_, //number of points
int num_cams_, //number of cameras
int num_point_param_, //number of params per one point (3 in case of 3D points)
int num_cam_param_, //number of parameters per one camera
int num_err_param_, //number of parameters in measurement vector for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, //visibility matrix . rows correspond to points, columns correspond to cameras
// 0 - point is visible for the camera, 0 - invisible
Mat& P0, //starting vector of parameters, first cameras then points
Mat& X_init, //measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria_init,
void (*fjac_)(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data),
void (*func_)(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data),
void* data_
) { //termination criteria
int num_cams_, //number of cameras
int num_point_param_, //number of params per one point (3 in case of 3D points)
int num_cam_param_, //number of parameters per one camera
int num_err_param_, //number of parameters in measurement vector for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, //visibility matrix . rows correspond to points, columns correspond to cameras
// 0 - point is visible for the camera, 0 - invisible
Mat& P0, //starting vector of parameters, first cameras then points
Mat& X_init, //measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria_init,
void (*fjac_)(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data),
void (*func_)(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data),
void* data_
) { //termination criteria
//clear();
func = func_; //assign evaluation function
@ -228,28 +228,28 @@ void LevMarqSparse::run( int num_points_, //number of points
for (int i = 0; i < num_points; i++ ) {
for (int j = 0; j < num_cams; j++ ) {
if (((int*)(_vis.data.ptr+ i * _vis.step))[j] ) {
((int*)(Vis_index->data.ptr + i * Vis_index->step))[j] = index;
index += num_err_param;
((int*)(Vis_index->data.ptr + i * Vis_index->step))[j] = index;
index += num_err_param;
//create matrices Aij, Bij
CvMat* tmp = cvCreateMat(Aij_height, Aij_width, CV_64F );
//((CvMat**)(A->data.ptr + i * A->step))[j] = tmp;
cvSet(tmp,cvScalar(1.0,1.0,1.0,1.0));
A[j+i*num_cams] = tmp;
//create matrices Aij, Bij
CvMat* tmp = cvCreateMat(Aij_height, Aij_width, CV_64F );
//((CvMat**)(A->data.ptr + i * A->step))[j] = tmp;
cvSet(tmp,cvScalar(1.0,1.0,1.0,1.0));
A[j+i*num_cams] = tmp;
tmp = cvCreateMat( Bij_height, Bij_width, CV_64F );
//((CvMat**)(B->data.ptr + i * B->step))[j] = tmp;
cvSet(tmp,cvScalar(1.0,1.0,1.0,1.0));
B[j+i*num_cams] = tmp;
tmp = cvCreateMat( Bij_height, Bij_width, CV_64F );
//((CvMat**)(B->data.ptr + i * B->step))[j] = tmp;
cvSet(tmp,cvScalar(1.0,1.0,1.0,1.0));
B[j+i*num_cams] = tmp;
tmp = cvCreateMat( Wij_height, Wij_width, CV_64F );
//((CvMat**)(W->data.ptr + j * W->step))[i] = tmp; //note indices i and j swapped
cvSet(tmp,cvScalar(1.0,1.0,1.0,1.0));
W[j+i*num_cams] = tmp;
tmp = cvCreateMat( Wij_height, Wij_width, CV_64F );
//((CvMat**)(W->data.ptr + j * W->step))[i] = tmp; //note indices i and j swapped
cvSet(tmp,cvScalar(1.0,1.0,1.0,1.0));
W[j+i*num_cams] = tmp;
} else{
A[j+i*num_cams] = NULL;
B[j+i*num_cams] = NULL;
W[j+i*num_cams] = NULL;
A[j+i*num_cams] = NULL;
B[j+i*num_cams] = NULL;
W[j+i*num_cams] = NULL;
}
}
}
@ -423,29 +423,31 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
cvSetZero(ea[j]);
//summ by i (number of points)
for (int i = 0; i < num_points; i++ ) {
//get Aij
//CvMat* Aij = ((CvMat**)(A->data.ptr + A->step * i))[j];
CvMat* Aij = A[j+i*num_cams];
if (Aij ) {
//Uj+= AijT*Aij
cvGEMM( Aij, Aij, 1, U[j], 1, U[j], CV_GEMM_A_T );
//ea_j += AijT * e_ij
CvMat eij;
//get Aij
//CvMat* Aij = ((CvMat**)(A->data.ptr + A->step * i))[j];
CvMat* Aij = A[j+i*num_cams];
if (Aij ) {
//Uj+= AijT*Aij
cvGEMM( Aij, Aij, 1, U[j], 1, U[j], CV_GEMM_A_T );
//ea_j += AijT * e_ij
CvMat eij;
int index = ((int*)(Vis_index->data.ptr + i * Vis_index->step))[j];
int index = ((int*)(Vis_index->data.ptr + i * Vis_index->step))[j];
cvGetSubRect( err, &eij, cvRect( 0, index, 1, Aij->height ) ); //width of transposed Aij
cvGEMM( Aij, &eij, 1, ea[j], 1, ea[j], CV_GEMM_A_T );
}
else
invisible_count++;
cvGetSubRect( err, &eij, cvRect( 0, index, 1, Aij->height ) ); //width of transposed Aij
cvGEMM( Aij, &eij, 1, ea[j], 1, ea[j], CV_GEMM_A_T );
}
else
invisible_count++;
}
} //U_j and ea_j computed for all j
// if (!(iters%100))
int nviz = X->rows / num_err_param;
double e2 = prevErrNorm*prevErrNorm, e2n = e2 / nviz;
std::cerr<<"Iteration: "<<iters<<", normError: "<<e2<<" ("<<e2n<<")"<<std::endl;
{
int nviz = X->rows / num_err_param;
double e2 = prevErrNorm*prevErrNorm, e2n = e2 / nviz;
std::cerr<<"Iteration: "<<iters<<", normError: "<<e2<<" ("<<e2n<<")"<<std::endl;
}
if (cb)
cb(iters, prevErrNorm, user_data);
//compute V_i and eb_i
@ -455,37 +457,37 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
//summ by i (number of points)
for( int j = 0; j < num_cams; j++ ) {
//get Bij
//CvMat* Bij = ((CvMat**)(B->data.ptr + B->step * i))[j];
CvMat* Bij = B[j+i*num_cams];
if (Bij ) {
//Vi+= BijT*Bij
cvGEMM( Bij, Bij, 1, V[i], 1, V[i], CV_GEMM_A_T );
//get Bij
//CvMat* Bij = ((CvMat**)(B->data.ptr + B->step * i))[j];
CvMat* Bij = B[j+i*num_cams];
if (Bij ) {
//Vi+= BijT*Bij
cvGEMM( Bij, Bij, 1, V[i], 1, V[i], CV_GEMM_A_T );
//eb_i += BijT * e_ij
int index = ((int*)(Vis_index->data.ptr + i * Vis_index->step))[j];
//eb_i += BijT * e_ij
int index = ((int*)(Vis_index->data.ptr + i * Vis_index->step))[j];
CvMat eij;
cvGetSubRect( err, &eij, cvRect( 0, index, 1, Bij->height ) ); //width of transposed Bij
cvGEMM( Bij, &eij, 1, eb[i], 1, eb[i], CV_GEMM_A_T );
}
CvMat eij;
cvGetSubRect( err, &eij, cvRect( 0, index, 1, Bij->height ) ); //width of transposed Bij
cvGEMM( Bij, &eij, 1, eb[i], 1, eb[i], CV_GEMM_A_T );
}
}
} //V_i and eb_i computed for all i
//compute W_ij
for( int i = 0; i < num_points; i++ ) {
for( int j = 0; j < num_cams; j++ ) {
//CvMat* Aij = ((CvMat**)(A->data.ptr + A->step * i))[j];
CvMat* Aij = A[j+i*num_cams];
if( Aij ) { //visible
//CvMat* Bij = ((CvMat**)(B->data.ptr + B->step * i))[j];
CvMat* Bij = B[j+i*num_cams];
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
//CvMat* Aij = ((CvMat**)(A->data.ptr + A->step * i))[j];
CvMat* Aij = A[j+i*num_cams];
if( Aij ) { //visible
//CvMat* Bij = ((CvMat**)(B->data.ptr + B->step * i))[j];
CvMat* Bij = B[j+i*num_cams];
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
//multiply
cvGEMM( Aij, Bij, 1, NULL, 0, Wij, CV_GEMM_A_T );
}
//multiply
cvGEMM( Aij, Bij, 1, NULL, 0, Wij, CV_GEMM_A_T );
}
}
} //Wij computed
@ -494,16 +496,16 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
CvMat dia;
CvMat subr;
for( int j = 0; j < num_cams; j++ ) {
cvGetDiag(U[j], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, j*num_cam_param, 1, num_cam_param ));
cvCopy( &dia, &subr );
cvGetDiag(U[j], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, j*num_cam_param, 1, num_cam_param ));
cvCopy( &dia, &subr );
}
for( int i = 0; i < num_points; i++ ) {
cvGetDiag(V[i], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, num_cams*num_cam_param + i * num_point_param, 1, num_point_param ));
cvCopy( &dia, &subr );
cvGetDiag(V[i], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, num_cams*num_cam_param + i * num_point_param, 1, num_point_param ));
cvCopy( &dia, &subr );
}
}
@ -511,10 +513,10 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
//initialize lambda. It is set to 1e-3 * average diagonal element in JtJ
double average_diag = 0;
for( int j = 0; j < num_cams; j++ ) {
average_diag += cvTrace( U[j] ).val[0];
average_diag += cvTrace( U[j] ).val[0];
}
for( int i = 0; i < num_points; i++ ) {
average_diag += cvTrace( V[i] ).val[0];
average_diag += cvTrace( V[i] ).val[0];
}
average_diag /= (num_cams*num_cam_param + num_points * num_point_param );
@ -527,187 +529,189 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
for(;;) {
//augmentation of diagonal
for(int j = 0; j < num_cams; j++ ) {
CvMat diag;
cvGetDiag( U[j], &diag );
CvMat diag;
cvGetDiag( U[j], &diag );
#if 1
cvAddS( &diag, cvScalar( lambda ), &diag );
cvAddS( &diag, cvScalar( lambda ), &diag );
#else
cvScale( &diag, &diag, 1 + lambda );
cvScale( &diag, &diag, 1 + lambda );
#endif
}
for(int i = 0; i < num_points; i++ ) {
CvMat diag;
cvGetDiag( V[i], &diag );
CvMat diag;
cvGetDiag( V[i], &diag );
#if 1
cvAddS( &diag, cvScalar( lambda ), &diag );
cvAddS( &diag, cvScalar( lambda ), &diag );
#else
cvScale( &diag, &diag, 1 + lambda );
cvScale( &diag, &diag, 1 + lambda );
#endif
}
bool error = false;
//compute inv(V*)
bool inverted_ok = true;
for(int i = 0; i < num_points; i++ ) {
double det = cvInvert( V[i], inv_V_star[i] );
double det = cvInvert( V[i], inv_V_star[i] );
if( fabs(det) <= FLT_EPSILON ) {
inverted_ok = false;
std::cerr<<"V["<<i<<"] failed"<<std::endl;
break;
} //means we did wrong augmentation, try to choose different lambda
if( fabs(det) <= FLT_EPSILON ) {
inverted_ok = false;
std::cerr<<"V["<<i<<"] failed"<<std::endl;
break;
} //means we did wrong augmentation, try to choose different lambda
}
if( inverted_ok ) {
cvSetZero( E );
//loop through cameras, compute upper diagonal blocks of matrix S
for( int j = 0; j < num_cams; j++ ) {
//compute Yij = Wij (V*_i)^-1 for all i (if Wij exists/nonzero)
for( int i = 0; i < num_points; i++ ) {
//
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
if( Wij ) {
cvMatMul( Wij, inv_V_star[i], Yj[i] );
}
}
cvSetZero( E );
//loop through cameras, compute upper diagonal blocks of matrix S
for( int j = 0; j < num_cams; j++ ) {
//compute Yij = Wij (V*_i)^-1 for all i (if Wij exists/nonzero)
for( int i = 0; i < num_points; i++ ) {
//
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
if( Wij ) {
cvMatMul( Wij, inv_V_star[i], Yj[i] );
}
}
//compute Sjk for k>=j (because Sjk = Skj)
for( int k = j; k < num_cams; k++ ) {
cvSetZero( YWt );
for( int i = 0; i < num_points; i++ ) {
//check that both Wij and Wik exist
// CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
//CvMat* Wik = ((CvMat**)(W->data.ptr + W->step * k))[i];
CvMat* Wik = W[k+i*num_cams];
//compute Sjk for k>=j (because Sjk = Skj)
for( int k = j; k < num_cams; k++ ) {
cvSetZero( YWt );
for( int i = 0; i < num_points; i++ ) {
//check that both Wij and Wik exist
// CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
//CvMat* Wik = ((CvMat**)(W->data.ptr + W->step * k))[i];
CvMat* Wik = W[k+i*num_cams];
if( Wij && Wik ) {
//multiply YWt += Yj[i]*Wik'
cvGEMM( Yj[i], Wik, 1, YWt, 1, YWt, CV_GEMM_B_T ); ///*transpose Wik
}
}
if( Wij && Wik ) {
//multiply YWt += Yj[i]*Wik'
cvGEMM( Yj[i], Wik, 1, YWt, 1, YWt, CV_GEMM_B_T ); ///*transpose Wik
}
}
//copy result to matrix S
//copy result to matrix S
CvMat Sjk;
//extract submat
cvGetSubRect( S, &Sjk, cvRect( k * num_cam_param, j * num_cam_param, num_cam_param, num_cam_param ));
CvMat Sjk;
//extract submat
cvGetSubRect( S, &Sjk, cvRect( k * num_cam_param, j * num_cam_param, num_cam_param, num_cam_param ));
//if j==k, add diagonal
if( j != k ) {
//just copy with minus
cvScale( YWt, &Sjk, -1 ); //if we set initial S to zero then we can use cvSub( Sjk, YWt, Sjk);
} else {
//add diagonal value
//subtract YWt from augmented Uj
cvSub( U[j], YWt, &Sjk );
}
}
//compute right part of equation involving matrix S
// e_j=ea_j - \sum_i Y_ij eb_i
{
CvMat e_j;
//select submat
cvGetSubRect( E, &e_j, cvRect( 0, j * num_cam_param, 1, num_cam_param ) );
for( int i = 0; i < num_points; i++ ) {
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
if( Wij )
cvMatMulAdd( Yj[i], eb[i], &e_j, &e_j );
}
cvSub( ea[j], &e_j, &e_j );
}
}
//fill below diagonal elements of matrix S
cvCompleteSymm( S, 0 ); ///*from upper to low //operation may be done by nonzero blocks or during upper diagonal computation
//Solve linear system S * deltaP_a = E
CvMat dpa;
cvGetSubRect( deltaP, &dpa, cvRect(0, 0, 1, S->width ) );
int res = cvSolve( S, E, &dpa, CV_CHOLESKY );
if( res ) { //system solved ok
//compute db_i
for( int i = 0; i < num_points; i++ ) {
CvMat dbi;
cvGetSubRect( deltaP, &dbi, cvRect( 0, dpa.height + i * num_point_param, 1, num_point_param ) );
// compute \sum_j W_ij^T da_j
for( int j = 0; j < num_cams; j++ ) {
//get Wij
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
if( Wij ) {
//get da_j
CvMat daj;
cvGetSubRect( &dpa, &daj, cvRect( 0, j * num_cam_param, 1, num_cam_param ));
cvGEMM( Wij, &daj, 1, &dbi, 1, &dbi, CV_GEMM_A_T ); ///* transpose Wij
}
}
//finalize dbi
cvSub( eb[i], &dbi, &dbi );
cvMatMul(inv_V_star[i], &dbi, &dbi ); //here we get final dbi
} //now we computed whole deltaP
//add deltaP to delta
cvAdd( prevP, deltaP, P );
//evaluate function with new parameters
ask_for_proj(_vis); // func( P, hX );
//compute error
errNorm = cvNorm( X, hX, CV_L2 );
} else {
error = true;
}
//if j==k, add diagonal
if( j != k ) {
//just copy with minus
cvScale( YWt, &Sjk, -1 ); //if we set initial S to zero then we can use cvSub( Sjk, YWt, Sjk);
} else {
error = true;
//add diagonal value
//subtract YWt from augmented Uj
cvSub( U[j], YWt, &Sjk );
}
}
//compute right part of equation involving matrix S
// e_j=ea_j - \sum_i Y_ij eb_i
{
CvMat e_j;
//select submat
cvGetSubRect( E, &e_j, cvRect( 0, j * num_cam_param, 1, num_cam_param ) );
for( int i = 0; i < num_points; i++ ) {
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
if( Wij )
cvMatMulAdd( Yj[i], eb[i], &e_j, &e_j );
}
cvSub( ea[j], &e_j, &e_j );
}
}
//fill below diagonal elements of matrix S
cvCompleteSymm( S, 0 ); ///*from upper to low //operation may be done by nonzero blocks or during upper diagonal computation
//Solve linear system S * deltaP_a = E
CvMat dpa;
cvGetSubRect( deltaP, &dpa, cvRect(0, 0, 1, S->width ) );
int res = cvSolve( S, E, &dpa, CV_CHOLESKY );
if( res ) { //system solved ok
//compute db_i
for( int i = 0; i < num_points; i++ ) {
CvMat dbi;
cvGetSubRect( deltaP, &dbi, cvRect( 0, dpa.height + i * num_point_param, 1, num_point_param ) );
// compute \sum_j W_ij^T da_j
for( int j = 0; j < num_cams; j++ ) {
//get Wij
//CvMat* Wij = ((CvMat**)(W->data.ptr + W->step * j))[i];
CvMat* Wij = W[j+i*num_cams];
if( Wij ) {
//get da_j
CvMat daj;
cvGetSubRect( &dpa, &daj, cvRect( 0, j * num_cam_param, 1, num_cam_param ));
cvGEMM( Wij, &daj, 1, &dbi, 1, &dbi, CV_GEMM_A_T ); ///* transpose Wij
}
}
//finalize dbi
cvSub( eb[i], &dbi, &dbi );
cvMatMul(inv_V_star[i], &dbi, &dbi ); //here we get final dbi
} //now we computed whole deltaP
//add deltaP to delta
cvAdd( prevP, deltaP, P );
//evaluate function with new parameters
ask_for_proj(_vis); // func( P, hX );
//compute error
errNorm = cvNorm( X, hX, CV_L2 );
} else {
error = true;
}
} else {
error = true;
}
//check solution
if( error || ///* singularities somewhere
errNorm > prevErrNorm ) { //step was not accepted
//increase lambda and reject change
lambda *= 10;
int nviz = X->rows / num_err_param;
double e2 = errNorm*errNorm, e2_prev = prevErrNorm*prevErrNorm;
double e2n = e2/nviz, e2n_prev = e2_prev/nviz;
std::cerr<<"move failed: lambda = "<<lambda<<", e2 = "<<e2<<" ("<<e2n<<") > "<<e2_prev<<" ("<<e2n_prev<<")"<<std::endl;
errNorm > prevErrNorm ) { //step was not accepted
//increase lambda and reject change
lambda *= 10;
{
int nviz = X->rows / num_err_param;
double e2 = errNorm*errNorm, e2_prev = prevErrNorm*prevErrNorm;
double e2n = e2/nviz, e2n_prev = e2_prev/nviz;
std::cerr<<"move failed: lambda = "<<lambda<<", e2 = "<<e2<<" ("<<e2n<<") > "<<e2_prev<<" ("<<e2n_prev<<")"<<std::endl;
}
//restore diagonal from backup
{
CvMat dia;
CvMat subr;
for( int j = 0; j < num_cams; j++ ) {
cvGetDiag(U[j], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, j*num_cam_param, 1, num_cam_param ));
cvCopy( &subr, &dia );
}
for( int i = 0; i < num_points; i++ ) {
cvGetDiag(V[i], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, num_cams*num_cam_param + i * num_point_param, 1, num_point_param ));
cvCopy( &subr, &dia );
}
}
//restore diagonal from backup
{
CvMat dia;
CvMat subr;
for( int j = 0; j < num_cams; j++ ) {
cvGetDiag(U[j], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, j*num_cam_param, 1, num_cam_param ));
cvCopy( &subr, &dia );
}
for( int i = 0; i < num_points; i++ ) {
cvGetDiag(V[i], &dia);
cvGetSubRect(JtJ_diag, &subr,
cvRect(0, num_cams*num_cam_param + i * num_point_param, 1, num_point_param ));
cvCopy( &subr, &dia );
}
}
} else { //all is ok
//accept change and decrease lambda
lambda /= 10;
lambda = MAX(lambda, 1e-16);
std::cerr<<"decreasing lambda to "<<lambda<<std::endl;
prevErrNorm = errNorm;
//accept change and decrease lambda
lambda /= 10;
lambda = MAX(lambda, 1e-16);
std::cerr<<"decreasing lambda to "<<lambda<<std::endl;
prevErrNorm = errNorm;
//compute new projection error vector
cvSub( X, hX, err );
break;
//compute new projection error vector
cvSub( X, hX, err );
break;
}
}
iters++;
@ -715,7 +719,7 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
double param_change_norm = cvNorm(P, prevP, CV_RELATIVE_L2);
//check termination criteria
if( (criteria.type&CV_TERMCRIT_ITER && iters > criteria.max_iter ) ||
(criteria.type&CV_TERMCRIT_EPS && param_change_norm < criteria.epsilon) ) {
(criteria.type&CV_TERMCRIT_EPS && param_change_norm < criteria.epsilon) ) {
// std::cerr<<"relative norm change "<<param_change_norm<<" lower than eps "<<criteria.epsilon<<", stopping"<<std::endl;
done = true;
break;
@ -730,7 +734,7 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
//Utilities
void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A, CvMat* B, void* /*data*/) {
static void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A, CvMat* B, void* /*data*/) {
//compute jacobian per camera parameters (i.e. Aij)
//take i-th point 3D current coordinates
@ -766,7 +770,7 @@ void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A
cvGetCols( A, &_dpdk, 10, A->width );
}
cvProjectPoints2(&_Mi, &_ri, &_ti, &_A, have_dk ? &_k : NULL, _mp, &_dpdr, &_dpdt,
&_dpdf, &_dpdc, have_dk ? &_dpdk : NULL, 0);
&_dpdf, &_dpdc, have_dk ? &_dpdk : NULL, 0);
cvReleaseMat( &_mp );
@ -843,7 +847,7 @@ void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A
// dy'/dX dy'/dY dy'/dZ
double coeff[6] = { z, 0, -x,
0, z, -y };
0, z, -y };
CvMat coeffmat = cvMat( 2, 3, CV_64F, coeff );
CvMat* dstrike_dbig = cvCreateMat(2,3,CV_64F);
@ -884,11 +888,11 @@ void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A
CvMat* dstrike2_dbig = cvCreateMat( 2, 3, CV_64F );
double c[4] = { g+2*p1*y_strike+4*p2*x_strike, 2*p1*x_strike,
2*p2*y_strike, g+2*p2*x_strike + 4*p1*y_strike };
2*p2*y_strike, g+2*p2*x_strike + 4*p1*y_strike };
CvMat coeffmat = cvMat(2,2,CV_64F, c );
CvMat coeffmat2 = cvMat(2,2,CV_64F, c );
cvMatMul(&coeffmat, dstrike_dbig, dstrike2_dbig );
cvMatMul(&coeffmat2, dstrike_dbig, dstrike2_dbig );
cvGEMM( &strike, dg_dbig, 1, NULL, 0, tmp, CV_GEMM_A_T );
cvAdd( dstrike2_dbig, tmp, dstrike2_dbig );
@ -935,7 +939,7 @@ void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A
#endif
};
void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* estim, void* /*data*/) {
static void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* estim, void* /*data*/) {
//just do projections
CvMat _Mi;
cvReshape( point_params, &_Mi, 3, 1 );
@ -965,7 +969,7 @@ void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* e
cvGetRows( cam_params, &_k, 10, cam_params->height );
}
cvProjectPoints2( &_Mi, &_ri, &_ti, &_A, have_dk ? &_k : NULL, _mp, NULL, NULL,
NULL, NULL, NULL, 0);
NULL, NULL, NULL, 0);
// std::cerr<<"_mp = "<<_mp->data.db[0]<<","<<_mp->data.db[1]<<std::endl;
//
_mp2->data.db[0] = _mp->data.db[0];
@ -975,34 +979,34 @@ void func(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* e
cvReleaseMat( &_mp2 );
};
void fjac_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data) {
static void fjac_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data) {
CvMat _point_params = point_params, _cam_params = cam_params, _Al = A, _Bl = B;
fjac(i,j, &_point_params, &_cam_params, &_Al, &_Bl, data);
};
void func_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data) {
static void func_new(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data) {
CvMat _point_params = point_params, _cam_params = cam_params, _estim = estim;
func(i,j,&_point_params,&_cam_params,&_estim,data);
};
void LevMarqSparse::bundleAdjust( vector<Point3d>& points, //positions of points in global coordinate system (input and output)
const vector<vector<Point2d> >& imagePoints, //projections of 3d points for every camera
const vector<vector<int> >& visibility, //visibility of 3d points for every camera
vector<Mat>& cameraMatrix, //intrinsic matrices of all cameras (input and output)
vector<Mat>& R, //rotation matrices of all cameras (input and output)
vector<Mat>& T, //translation vector of all cameras (input and output)
vector<Mat>& distCoeffs, //distortion coefficients of all cameras (input and output)
const TermCriteria& criteria,
BundleAdjustCallback cb, void* user_data) {
const vector<vector<Point2d> >& imagePoints, //projections of 3d points for every camera
const vector<vector<int> >& visibility, //visibility of 3d points for every camera
vector<Mat>& cameraMatrix, //intrinsic matrices of all cameras (input and output)
vector<Mat>& R, //rotation matrices of all cameras (input and output)
vector<Mat>& T, //translation vector of all cameras (input and output)
vector<Mat>& distCoeffs, //distortion coefficients of all cameras (input and output)
const TermCriteria& criteria,
BundleAdjustCallback cb, void* user_data) {
//,enum{MOTION_AND_STRUCTURE,MOTION,STRUCTURE})
int num_points = (int)points.size();
int num_cameras = (int)cameraMatrix.size();
CV_Assert( imagePoints.size() == (size_t)num_cameras &&
visibility.size() == (size_t)num_cameras &&
R.size() == (size_t)num_cameras &&
T.size() == (size_t)num_cameras &&
(distCoeffs.size() == (size_t)num_cameras || distCoeffs.size() == 0) );
visibility.size() == (size_t)num_cameras &&
R.size() == (size_t)num_cameras &&
T.size() == (size_t)num_cameras &&
(distCoeffs.size() == (size_t)num_cameras || distCoeffs.size() == 0) );
int numdist = distCoeffs.size() ? (distCoeffs[0].rows * distCoeffs[0].cols) : 0;
@ -1066,19 +1070,19 @@ void LevMarqSparse::bundleAdjust( vector<Point3d>& points, //positions of points
for(int j = 0; j < num_cameras; j++ ) {
//check visibility
if( visibility[j][i] ) {
//extract point and put tu vector
Point2d p = imagePoints[j][i];
((double*)(X.data))[counter] = p.x;
((double*)(X.data))[counter+1] = p.y;
assert(p.x != -1 || p.y != -1);
counter+=2;
//extract point and put tu vector
Point2d p = imagePoints[j][i];
((double*)(X.data))[counter] = p.x;
((double*)(X.data))[counter+1] = p.y;
assert(p.x != -1 || p.y != -1);
counter+=2;
}
}
}
LevMarqSparse levmar( num_points, num_cameras, num_point_param, num_cam_param, 2, vismat, params, X,
TermCriteria(criteria), fjac_new, func_new, NULL,
cb, user_data);
TermCriteria(criteria), fjac_new, func_new, NULL,
cb, user_data);
//extract results
//fill point params
/*Mat final_points(num_points, 1, CV_64FC3,

18
modules/contrib/src/basicretinafilter.cpp
View File

@ -180,13 +180,13 @@ void BasicRetinaFilter::setLPfilterParameters(const float beta, const float tau,
}
float _temp = (1.0f+_beta)/(2.0f*_mu*_alpha);
float _a = _filteringCoeficientsTable[tableOffset] = 1.0f + _temp - (float)sqrt( (1.0f+_temp)*(1.0f+_temp) - 1.0f);
_filteringCoeficientsTable[1+tableOffset]=(1.0f-_a)*(1.0f-_a)*(1.0f-_a)*(1.0f-_a)/(1.0f+_beta);
float a = _filteringCoeficientsTable[tableOffset] = 1.0f + _temp - (float)sqrt( (1.0f+_temp)*(1.0f+_temp) - 1.0f);
_filteringCoeficientsTable[1+tableOffset]=(1.0f-a)*(1.0f-a)*(1.0f-a)*(1.0f-a)/(1.0f+_beta);
_filteringCoeficientsTable[2+tableOffset] =tau;
//std::cout<<"BasicRetinaFilter::normal:"<<(1.0-_a)*(1.0-_a)*(1.0-_a)*(1.0-_a)/(1.0+_beta)<<" -> old:"<<(1-_a)*(1-_a)*(1-_a)*(1-_a)/(1+_beta)<<std::endl;
//std::cout<<"BasicRetinaFilter::normal:"<<(1.0-a)*(1.0-a)*(1.0-a)*(1.0-a)/(1.0+_beta)<<" -> old:"<<(1-a)*(1-a)*(1-a)*(1-a)/(1+_beta)<<std::endl;
//std::cout<<"BasicRetinaFilter::_a="<<_a<<", gain="<<_filteringCoeficientsTable[1+tableOffset]<<", tau="<<tau<<std::endl;
//std::cout<<"BasicRetinaFilter::a="<<a<<", gain="<<_filteringCoeficientsTable[1+tableOffset]<<", tau="<<tau<<std::endl;
}
void BasicRetinaFilter::setProgressiveFilterConstants_CentredAccuracy(const float beta, const float tau, const float alpha0, const unsigned int filterIndex)
@ -210,8 +210,8 @@ void BasicRetinaFilter::setProgressiveFilterConstants_CentredAccuracy(const floa
float _alpha=0.8f;
float _temp = (1.0f+_beta)/(2.0f*_mu*_alpha);
float _a=_filteringCoeficientsTable[tableOffset] = 1.0f + _temp - (float)sqrt( (1.0f+_temp)*(1.0f+_temp) - 1.0f);
_filteringCoeficientsTable[tableOffset+1]=(1.0f-_a)*(1.0f-_a)*(1.0f-_a)*(1.0f-_a)/(1.0f+_beta);
float a=_filteringCoeficientsTable[tableOffset] = 1.0f + _temp - (float)sqrt( (1.0f+_temp)*(1.0f+_temp) - 1.0f);
_filteringCoeficientsTable[tableOffset+1]=(1.0f-a)*(1.0f-a)*(1.0f-a)*(1.0f-a)/(1.0f+_beta);
_filteringCoeficientsTable[tableOffset+2] =tau;
float commonFactor=alpha0/(float)sqrt(_halfNBcolumns*_halfNBcolumns+_halfNBrows*_halfNBrows+1.0f);
@ -266,8 +266,8 @@ void BasicRetinaFilter::setProgressiveFilterConstants_CustomAccuracy(const float
}
unsigned int tableOffset=filterIndex*3;
float _temp = (1.0f+_beta)/(2.0f*_mu*_alpha);
float _a=_filteringCoeficientsTable[tableOffset] = 1.0f + _temp - (float)sqrt( (1.0f+_temp)*(1.0f+_temp) - 1.0f);
_filteringCoeficientsTable[tableOffset+1]=(1.0f-_a)*(1.0f-_a)*(1.0f-_a)*(1.0f-_a)/(1.0f+_beta);
float a=_filteringCoeficientsTable[tableOffset] = 1.0f + _temp - (float)sqrt( (1.0f+_temp)*(1.0f+_temp) - 1.0f);
_filteringCoeficientsTable[tableOffset+1]=(1.0f-a)*(1.0f-a)*(1.0f-a)*(1.0f-a)/(1.0f+_beta);
_filteringCoeficientsTable[tableOffset+2] =tau;
//memset(_progressiveSpatialConstant, 255, _filterOutput.getNBpixels());
@ -335,7 +335,7 @@ void BasicRetinaFilter::_localLuminanceAdaptation(const float *inputFrame, const
{
float X0=*(localLuminancePTR++)*_localLuminanceFactor+_localLuminanceAddon;
// TODO : the following line can lead to a divide by zero ! A small offset is added, take care if the offset is too large in case of High Dynamic Range images which can use very small values...
*(outputFramePTR++) = (_maxInputValue+X0)**inputFramePTR/(*inputFramePTR +X0+0.00000000001);
*(outputFramePTR++) = (_maxInputValue+X0)**inputFramePTR/(*inputFramePTR +X0+0.00000000001f);
//std::cout<<"BasicRetinaFilter::inputFrame[IDpixel]=%f, X0=%f, outputFrame[IDpixel]=%f\n", inputFrame[IDpixel], X0, outputFrame[IDpixel]);
}
}

1
modules/contrib/src/chamfermatching.cpp
View File

@ -81,6 +81,7 @@ private:
{
public:
virtual ImageIterator* iterator() const = 0;
virtual ~ImageRange() {}
};
// Sliding window

4
modules/contrib/src/colormap.cpp
View File

@ -18,7 +18,7 @@
#include "precomp.hpp"
#include <iostream>
#if defined _MSC_VER && _MSC_VER >= 1400
#ifdef _MSC_VER
#pragma warning( disable: 4305 )
#endif
@ -60,7 +60,7 @@ static Mat sortMatrixRowsByIndices(InputArray src, InputArray indices)
}
Mat argsort(InputArray _src, bool ascending=true)
static Mat argsort(InputArray _src, bool ascending=true)
{
Mat src = _src.getMat();
if (src.rows != 1 && src.cols != 1)

4
modules/contrib/src/colortracker.cpp
View File

@ -68,10 +68,10 @@ void CvMeanShiftTracker::newTrackingWindow(Mat image, Rect selection)
mixChannels(&hsv, 1, &hue, 1, channels, 2);
Mat roi(hue, selection);
Mat maskroi(mask, selection);
Mat mskroi(mask, selection);
int ch[] = {0, 1};
int chsize[] = {32, 32};
calcHist(&roi, 1, ch, maskroi, hist, 1, chsize, ranges);
calcHist(&roi, 1, ch, mskroi, hist, 1, chsize, ranges);
normalize(hist, hist, 0, 255, CV_MINMAX);
prev_trackwindow = selection;

2
modules/contrib/src/detection_based_tracker.cpp
View File

@ -3,7 +3,7 @@
#define DEBUGLOGS 1
#if ANDROID
#ifdef ANDROID
#include <android/log.h>
#define LOG_TAG "OBJECT_DETECTOR"
#define LOGD0(...) ((void)__android_log_print(ANDROID_LOG_DEBUG, LOG_TAG, __VA_ARGS__))

38
modules/contrib/src/facerec.cpp
View File

@ -100,15 +100,15 @@ public:
using FaceRecognizer::load;
// Initializes an empty Eigenfaces model.
Eigenfaces(int num_components = 0) :
_num_components(num_components) { }
Eigenfaces(int numComponents = 0) :
_num_components(numComponents) { }
// Initializes and computes an Eigenfaces model with images in src and
// corresponding labels in labels. num_components will be kept for
// classification.
Eigenfaces(InputArray src, InputArray labels,
int num_components = 0) :
_num_components(num_components) {
int numComponents = 0) :
_num_components(numComponents) {
train(src, labels);
}
@ -157,16 +157,16 @@ public:
using FaceRecognizer::load;
// Initializes an empty Fisherfaces model.
Fisherfaces(int num_components = 0) :
_num_components(num_components) {}
Fisherfaces(int numComponents = 0) :
_num_components(numComponents) {}
// Initializes and computes a Fisherfaces model with images in src and
// corresponding labels in labels. num_components will be kept for
// classification.
Fisherfaces(InputArray src,
InputArray labels,
int num_components = 0) :
_num_components(num_components) {
int numComponents = 0) :
_num_components(numComponents) {
train(src, labels);
}
@ -228,11 +228,11 @@ public:
//
// radius, neighbors are used in the local binary patterns creation.
// grid_x, grid_y control the grid size of the spatial histograms.
LBPH(int radius=1, int neighbors=8, int grid_x=8, int grid_y=8) :
_grid_x(grid_x),
_grid_y(grid_y),
_radius(radius),
_neighbors(neighbors) {}
LBPH(int radius_=1, int neighbors_=8, int grid_x_=8, int grid_y_=8) :
_grid_x(grid_x_),
_grid_y(grid_y_),
_radius(radius_),
_neighbors(neighbors_) {}
// Initializes and computes this LBPH Model. The current implementation is
// rather fixed as it uses the Extended Local Binary Patterns per default.
@ -241,12 +241,12 @@ public:
// (grid_x=8), (grid_y=8) controls the grid size of the spatial histograms.
LBPH(InputArray src,
InputArray labels,
int radius=1, int neighbors=8,
int grid_x=8, int grid_y=8) :
_grid_x(grid_x),
_grid_y(grid_y),
_radius(radius),
_neighbors(neighbors) {
int radius_=1, int neighbors_=8,
int grid_x_=8, int grid_y_=8) :
_grid_x(grid_x_),
_grid_y(grid_y_),
_radius(radius_),
_neighbors(neighbors_) {
train(src, labels);
}

2
modules/contrib/src/gencolors.cpp
View File

@ -46,7 +46,7 @@
using namespace cv;
void downsamplePoints( const Mat& src, Mat& dst, size_t count )
static void downsamplePoints( const Mat& src, Mat& dst, size_t count )
{
CV_Assert( count >= 2 );
CV_Assert( src.cols == 1 || src.rows == 1 );

359
modules/contrib/src/lda.cpp
View File

@ -46,36 +46,54 @@ inline vector<_Tp> remove_dups(const vector<_Tp>& src) {
static Mat argsort(InputArray _src, bool ascending=true)
{
Mat src = _src.getMat();
if (src.rows != 1 && src.cols != 1)
CV_Error(CV_StsBadArg, "cv::argsort only sorts 1D matrices.");
if (src.rows != 1 && src.cols != 1) {
string error_message = "Wrong shape of input matrix! Expected a matrix with one row or column.";
CV_Error(CV_StsBadArg, error_message);
}
int flags = CV_SORT_EVERY_ROW+(ascending ? CV_SORT_ASCENDING : CV_SORT_DESCENDING);
Mat sorted_indices;
sortIdx(src.reshape(1,1),sorted_indices,flags);
return sorted_indices;
}
static Mat asRowMatrix(InputArrayOfArrays src, int rtype, double alpha=1, double beta=0)
{
static Mat asRowMatrix(InputArrayOfArrays src, int rtype, double alpha=1, double beta=0) {
// make sure the input data is a vector of matrices or vector of vector
if(src.kind() != _InputArray::STD_VECTOR_MAT && src.kind() != _InputArray::STD_VECTOR_VECTOR) {
string error_message = "The data is expected as InputArray::STD_VECTOR_MAT (a std::vector<Mat>) or _InputArray::STD_VECTOR_VECTOR (a std::vector< vector<...> >).";
CV_Error(CV_StsBadArg, error_message);
}
// number of samples
int n = (int) src.total();
// return empty matrix if no data given
size_t n = src.total();
// return empty matrix if no matrices given
if(n == 0)
return Mat();
// dimensionality of samples
int d = (int)src.getMat(0).total();
// dimensionality of (reshaped) samples
size_t d = src.getMat(0).total();
// create data matrix
Mat data(n, d, rtype);
// copy data
for(int i = 0; i < n; i++) {
Mat data((int)n, (int)d, rtype);
// now copy data
for(int i = 0; i < (int)n; i++) {
// make sure data can be reshaped, throw exception if not!
if(src.getMat(i).total() != d) {
string error_message = format("Wrong number of elements in matrix #%d! Expected %d was %d.", i, (int)d, (int)src.getMat(i).total());
CV_Error(CV_StsBadArg, error_message);
}
// get a hold of the current row
Mat xi = data.row(i);
src.getMat(i).reshape(1, 1).convertTo(xi, rtype, alpha, beta);
// make reshape happy by cloning for non-continuous matrices
if(src.getMat(i).isContinuous()) {
src.getMat(i).reshape(1, 1).convertTo(xi, rtype, alpha, beta);
} else {
src.getMat(i).clone().reshape(1, 1).convertTo(xi, rtype, alpha, beta);
}
}
return data;
}
void sortMatrixColumnsByIndices(InputArray _src, InputArray _indices, OutputArray _dst) {
if(_indices.getMat().type() != CV_32SC1)
static void sortMatrixColumnsByIndices(InputArray _src, InputArray _indices, OutputArray _dst) {
if(_indices.getMat().type() != CV_32SC1) {
CV_Error(CV_StsUnsupportedFormat, "cv::sortColumnsByIndices only works on integer indices!");
}
Mat src = _src.getMat();
vector<int> indices = _indices.getMat();
_dst.create(src.rows, src.cols, src.type());
@ -87,7 +105,7 @@ void sortMatrixColumnsByIndices(InputArray _src, InputArray _indices, OutputArra
}
}
Mat sortMatrixColumnsByIndices(InputArray src, InputArray indices) {
static Mat sortMatrixColumnsByIndices(InputArray src, InputArray indices) {
Mat dst;
sortMatrixColumnsByIndices(src, indices, dst);
return dst;
@ -153,31 +171,44 @@ static bool isSymmetric(InputArray src, double eps=1e-16)
//------------------------------------------------------------------------------
// subspace::project
// cv::subspaceProject
//------------------------------------------------------------------------------
Mat subspaceProject(InputArray _W, InputArray _mean, InputArray _src)
{
Mat subspaceProject(InputArray _W, InputArray _mean, InputArray _src) {
// get data matrices
Mat W = _W.getMat();
Mat mean = _mean.getMat();
Mat src = _src.getMat();
// get number of samples and dimension
int n = src.rows;
int d = src.cols;
// make sure the data has the correct shape
if(W.rows != d) {
string error_message = format("Wrong shapes for given matrices. Was size(src) = (%d,%d), size(W) = (%d,%d).", src.rows, src.cols, W.rows, W.cols);
CV_Error(CV_StsBadArg, error_message);
}
// make sure mean is correct if not empty
if(!mean.empty() && (mean.total() != (size_t) d)) {
string error_message = format("Wrong mean shape for the given data matrix. Expected %d, but was %d.", d, mean.total());
CV_Error(CV_StsBadArg, error_message);
}
// create temporary matrices
Mat X, Y;
// copy data & make sure we are using the correct type
// make sure you operate on correct type
src.convertTo(X, W.type());
// get number of samples and dimension
int n = X.rows;
int d = X.cols;
// center the data if correct aligned sample mean is given
if(mean.total() == (size_t)d)
subtract(X, repeat(mean.reshape(1,1), n, 1), X);
// safe to do, because of above assertion
if(!mean.empty()) {
for(int i=0; i<n; i++) {
Mat r_i = X.row(i);
subtract(r_i, mean.reshape(1,1), r_i);
}
}
// finally calculate projection as Y = (X-mean)*W
gemm(X, W, 1.0, Mat(), 0.0, Y);
return Y;
}
//------------------------------------------------------------------------------
// subspace::reconstruct
// cv::subspaceReconstruct
//------------------------------------------------------------------------------
Mat subspaceReconstruct(InputArray _W, InputArray _mean, InputArray _src)
{
@ -185,16 +216,32 @@ Mat subspaceReconstruct(InputArray _W, InputArray _mean, InputArray _src)
Mat W = _W.getMat();
Mat mean = _mean.getMat();
Mat src = _src.getMat();
// get number of samples
// get number of samples and dimension
int n = src.rows;
int d = src.cols;
// make sure the data has the correct shape
if(W.cols != d) {
string error_message = format("Wrong shapes for given matrices. Was size(src) = (%d,%d), size(W) = (%d,%d).", src.rows, src.cols, W.rows, W.cols);
CV_Error(CV_StsBadArg, error_message);
}
// make sure mean is correct if not empty
if(!mean.empty() && (mean.total() != (size_t) W.rows)) {
string error_message = format("Wrong mean shape for the given eigenvector matrix. Expected %d, but was %d.", W.cols, mean.total());
CV_Error(CV_StsBadArg, error_message);
}
// initalize temporary matrices
Mat X, Y;
// copy data & make sure we are using the correct type
src.convertTo(Y, W.type());
// calculate the reconstruction
gemm(Y, W, 1.0, Mat(), 0.0, X, GEMM_2_T);
if(mean.total() == (size_t) X.cols)
add(X, repeat(mean.reshape(1,1), n, 1), X);
// safe to do because of above assertion
if(!mean.empty()) {
for(int i=0; i<n; i++) {
Mat r_i = X.row(i);
add(r_i, mean.reshape(1,1), r_i);
}
}
return X;
}
@ -235,19 +282,19 @@ private:
// Allocates memory.
template<typename _Tp>
_Tp **alloc_2d(int m, int n) {
_Tp **alloc_2d(int m, int _n) {
_Tp **arr = new _Tp*[m];
for (int i = 0; i < m; i++)
arr[i] = new _Tp[n];
arr[i] = new _Tp[_n];
return arr;
}
// Allocates memory.
template<typename _Tp>
_Tp **alloc_2d(int m, int n, _Tp val) {
_Tp **arr = alloc_2d<_Tp> (m, n);
_Tp **alloc_2d(int m, int _n, _Tp val) {
_Tp **arr = alloc_2d<_Tp> (m, _n);
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
for (int j = 0; j < _n; j++) {
arr[i][j] = val;
}
}
@ -255,17 +302,17 @@ private:
}
void cdiv(double xr, double xi, double yr, double yi) {
double r, d;
double r, dv;
if (std::abs(yr) > std::abs(yi)) {
r = yi / yr;
d = yr + r * yi;
cdivr = (xr + r * xi) / d;
cdivi = (xi - r * xr) / d;
dv = yr + r * yi;
cdivr = (xr + r * xi) / dv;
cdivi = (xi - r * xr) / dv;
} else {
r = yr / yi;
d = yi + r * yr;
cdivr = (r * xr + xi) / d;
cdivi = (r * xi - xr) / d;
dv = yi + r * yr;
cdivr = (r * xr + xi) / dv;
cdivi = (r * xi - xr) / dv;
}
}
@ -280,7 +327,7 @@ private:
// Initialize
int nn = this->n;
int n = nn - 1;
int n1 = nn - 1;
int low = 0;
int high = nn - 1;
double eps = pow(2.0, -52.0);
@ -302,10 +349,10 @@ private:
// Outer loop over eigenvalue index
int iter = 0;
while (n >= low) {
while (n1 >= low) {
// Look for single small sub-diagonal element
int l = n;
int l = n1;
while (l > low) {
s = std::abs(H[l - 1][l - 1]) + std::abs(H[l][l]);
if (s == 0.0) {
@ -320,23 +367,23 @@ private:
// Check for convergence
// One root found
if (l == n) {
H[n][n] = H[n][n] + exshift;
d[n] = H[n][n];
e[n] = 0.0;
n--;
if (l == n1) {
H[n1][n1] = H[n1][n1] + exshift;
d[n1] = H[n1][n1];
e[n1] = 0.0;
n1--;
iter = 0;
// Two roots found
} else if (l == n - 1) {
w = H[n][n - 1] * H[n - 1][n];
p = (H[n - 1][n - 1] - H[n][n]) / 2.0;
} else if (l == n1 - 1) {
w = H[n1][n1 - 1] * H[n1 - 1][n1];
p = (H[n1 - 1][n1 - 1] - H[n1][n1]) / 2.0;
q = p * p + w;
z = sqrt(std::abs(q));
H[n][n] = H[n][n] + exshift;
H[n - 1][n - 1] = H[n - 1][n - 1] + exshift;
x = H[n][n];
H[n1][n1] = H[n1][n1] + exshift;
H[n1 - 1][n1 - 1] = H[n1 - 1][n1 - 1] + exshift;
x = H[n1][n1];
// Real pair
@ -346,14 +393,14 @@ private:
} else {
z = p - z;
}
d[n - 1] = x + z;
d[n] = d[n - 1];
d[n1 - 1] = x + z;
d[n1] = d[n1 - 1];
if (z != 0.0) {
d[n] = x - w / z;
d[n1] = x - w / z;
}
e[n - 1] = 0.0;
e[n] = 0.0;
x = H[n][n - 1];
e[n1 - 1] = 0.0;
e[n1] = 0.0;
x = H[n1][n1 - 1];
s = std::abs(x) + std::abs(z);
p = x / s;
q = z / s;
@ -363,37 +410,37 @@ private:
// Row modification
for (int j = n - 1; j < nn; j++) {
z = H[n - 1][j];
H[n - 1][j] = q * z + p * H[n][j];
H[n][j] = q * H[n][j] - p * z;
for (int j = n1 - 1; j < nn; j++) {
z = H[n1 - 1][j];
H[n1 - 1][j] = q * z + p * H[n1][j];
H[n1][j] = q * H[n1][j] - p * z;
}
// Column modification
for (int i = 0; i <= n; i++) {
z = H[i][n - 1];
H[i][n - 1] = q * z + p * H[i][n];
H[i][n] = q * H[i][n] - p * z;
for (int i = 0; i <= n1; i++) {
z = H[i][n1 - 1];
H[i][n1 - 1] = q * z + p * H[i][n1];
H[i][n1] = q * H[i][n1] - p * z;
}
// Accumulate transformations
for (int i = low; i <= high; i++) {
z = V[i][n - 1];
V[i][n - 1] = q * z + p * V[i][n];
V[i][n] = q * V[i][n] - p * z;
z = V[i][n1 - 1];
V[i][n1 - 1] = q * z + p * V[i][n1];
V[i][n1] = q * V[i][n1] - p * z;
}
// Complex pair
} else {
d[n - 1] = x + p;
d[n] = x + p;
e[n - 1] = z;
e[n] = -z;
d[n1 - 1] = x + p;
d[n1] = x + p;
e[n1 - 1] = z;
e[n1] = -z;
}
n = n - 2;
n1 = n1 - 2;
iter = 0;
// No convergence yet
@ -402,22 +449,22 @@ private:
// Form shift
x = H[n][n];
x = H[n1][n1];
y = 0.0;
w = 0.0;
if (l < n) {
y = H[n - 1][n - 1];
w = H[n][n - 1] * H[n - 1][n];
if (l < n1) {
y = H[n1 - 1][n1 - 1];
w = H[n1][n1 - 1] * H[n1 - 1][n1];
}
// Wilkinson's original ad hoc shift
if (iter == 10) {
exshift += x;
for (int i = low; i <= n; i++) {
for (int i = low; i <= n1; i++) {
H[i][i] -= x;
}
s = std::abs(H[n][n - 1]) + std::abs(H[n - 1][n - 2]);
s = std::abs(H[n1][n1 - 1]) + std::abs(H[n1 - 1][n1 - 2]);
x = y = 0.75 * s;
w = -0.4375 * s * s;
}
@ -433,7 +480,7 @@ private:
s = -s;
}
s = x - w / ((y - x) / 2.0 + s);
for (int i = low; i <= n; i++) {
for (int i = low; i <= n1; i++) {
H[i][i] -= s;
}
exshift += s;
@ -444,7 +491,7 @@ private:
iter = iter + 1; // (Could check iteration count here.)
// Look for two consecutive small sub-diagonal elements
int m = n - 2;
int m = n1 - 2;
while (m >= l) {
z = H[m][m];
r = x - z;
@ -467,7 +514,7 @@ private:
m--;
}
for (int i = m + 2; i <= n; i++) {
for (int i = m + 2; i <= n1; i++) {
H[i][i - 2] = 0.0;
if (i > m + 2) {
H[i][i - 3] = 0.0;
@ -476,8 +523,8 @@ private:
// Double QR step involving rows l:n and columns m:n
for (int k = m; k <= n - 1; k++) {
bool notlast = (k != n - 1);
for (int k = m; k <= n1 - 1; k++) {
bool notlast = (k != n1 - 1);
if (k != m) {
p = H[k][k - 1];
q = H[k + 1][k - 1];
@ -523,7 +570,7 @@ private:
// Column modification
for (int i = 0; i <= min(n, k + 3); i++) {
for (int i = 0; i <= min(n1, k + 3); i++) {
p = x * H[i][k] + y * H[i][k + 1];
if (notlast) {
p = p + z * H[i][k + 2];
@ -547,7 +594,7 @@ private:
} // (s != 0)
} // k loop
} // check convergence
} // while (n >= low)
} // while (n1 >= low)
// Backsubstitute to find vectors of upper triangular form
@ -555,20 +602,20 @@ private:
return;
}
for (n = nn - 1; n >= 0; n--) {
p = d[n];
q = e[n];
for (n1 = nn - 1; n1 >= 0; n1--) {
p = d[n1];
q = e[n1];
// Real vector
if (q == 0) {
int l = n;
H[n][n] = 1.0;
for (int i = n - 1; i >= 0; i--) {
int l = n1;
H[n1][n1] = 1.0;
for (int i = n1 - 1; i >= 0; i--) {
w = H[i][i] - p;
r = 0.0;
for (int j = l; j <= n; j++) {
r = r + H[i][j] * H[j][n];
for (int j = l; j <= n1; j++) {
r = r + H[i][j] * H[j][n1];
}
if (e[i] < 0.0) {
z = w;
@ -577,9 +624,9 @@ private:
l = i;
if (e[i] == 0.0) {
if (w != 0.0) {
H[i][n] = -r / w;
H[i][n1] = -r / w;
} else {
H[i][n] = -r / (eps * norm);
H[i][n1] = -r / (eps * norm);
}
// Solve real equations
@ -589,49 +636,47 @@ private:
y = H[i + 1][i];
q = (d[i] - p) * (d[i] - p) + e[i] * e[i];
t = (x * s - z * r) / q;
H[i][n] = t;
H[i][n1] = t;
if (std::abs(x) > std::abs(z)) {
H[i + 1][n] = (-r - w * t) / x;
H[i + 1][n1] = (-r - w * t) / x;
} else {
H[i + 1][n] = (-s - y * t) / z;
H[i + 1][n1] = (-s - y * t) / z;
}
}
// Overflow control
t = std::abs(H[i][n]);
t = std::abs(H[i][n1]);
if ((eps * t) * t > 1) {
for (int j = i; j <= n; j++) {
H[j][n] = H[j][n] / t;
for (int j = i; j <= n1; j++) {
H[j][n1] = H[j][n1] / t;
}
}
}
}
// Complex vector
} else if (q < 0) {
int l = n - 1;
int l = n1 - 1;
// Last vector component imaginary so matrix is triangular
if (std::abs(H[n][n - 1]) > std::abs(H[n - 1][n])) {
H[n - 1][n - 1] = q / H[n][n - 1];
H[n - 1][n] = -(H[n][n] - p) / H[n][n - 1];
if (std::abs(H[n1][n1 - 1]) > std::abs(H[n1 - 1][n1])) {
H[n1 - 1][n1 - 1] = q / H[n1][n1 - 1];
H[n1 - 1][n1] = -(H[n1][n1] - p) / H[n1][n1 - 1];
} else {
cdiv(0.0, -H[n - 1][n], H[n - 1][n - 1] - p, q);
H[n - 1][n - 1] = cdivr;
H[n - 1][n] = cdivi;
cdiv(0.0, -H[n1 - 1][n1], H[n1 - 1][n1 - 1] - p, q);
H[n1 - 1][n1 - 1] = cdivr;
H[n1 - 1][n1] = cdivi;
}
H[n][n - 1] = 0.0;
H[n][n] = 1.0;
for (int i = n - 2; i >= 0; i--) {
H[n1][n1 - 1] = 0.0;
H[n1][n1] = 1.0;
for (int i = n1 - 2; i >= 0; i--) {
double ra, sa, vr, vi;
ra = 0.0;
sa = 0.0;
for (int j = l; j <= n; j++) {
ra = ra + H[i][j] * H[j][n - 1];
sa = sa + H[i][j] * H[j][n];
for (int j = l; j <= n1; j++) {
ra = ra + H[i][j] * H[j][n1 - 1];
sa = sa + H[i][j] * H[j][n1];
}
w = H[i][i] - p;
@ -643,8 +688,8 @@ private:
l = i;
if (e[i] == 0) {
cdiv(-ra, -sa, w, q);
H[i][n - 1] = cdivr;
H[i][n] = cdivi;
H[i][n1 - 1] = cdivr;
H[i][n1] = cdivi;
} else {
// Solve complex equations
@ -659,28 +704,28 @@ private:
}
cdiv(x * r - z * ra + q * sa,
x * s - z * sa - q * ra, vr, vi);
H[i][n - 1] = cdivr;
H[i][n] = cdivi;
H[i][n1 - 1] = cdivr;
H[i][n1] = cdivi;
if (std::abs(x) > (std::abs(z) + std::abs(q))) {
H[i + 1][n - 1] = (-ra - w * H[i][n - 1] + q
* H[i][n]) / x;
H[i + 1][n] = (-sa - w * H[i][n] - q * H[i][n
H[i + 1][n1 - 1] = (-ra - w * H[i][n1 - 1] + q
* H[i][n1]) / x;
H[i + 1][n1] = (-sa - w * H[i][n1] - q * H[i][n1
- 1]) / x;
} else {
cdiv(-r - y * H[i][n - 1], -s - y * H[i][n], z,
cdiv(-r - y * H[i][n1 - 1], -s - y * H[i][n1], z,
q);
H[i + 1][n - 1] = cdivr;
H[i + 1][n] = cdivi;
H[i + 1][n1 - 1] = cdivr;
H[i + 1][n1] = cdivi;
}
}
// Overflow control
t = max(std::abs(H[i][n - 1]), std::abs(H[i][n]));
t = max(std::abs(H[i][n1 - 1]), std::abs(H[i][n1]));
if ((eps * t) * t > 1) {
for (int j = i; j <= n; j++) {
H[j][n - 1] = H[j][n - 1] / t;
H[j][n] = H[j][n] / t;
for (int j = i; j <= n1; j++) {
H[j][n1 - 1] = H[j][n1 - 1] / t;
H[j][n1] = H[j][n1] / t;
}
}
}
@ -898,8 +943,9 @@ public:
//------------------------------------------------------------------------------
void LDA::save(const string& filename) const {
FileStorage fs(filename, FileStorage::WRITE);
if (!fs.isOpened())
if (!fs.isOpened()) {
CV_Error(CV_StsError, "File can't be opened for writing!");
}
this->save(fs);
fs.release();
}
@ -941,8 +987,8 @@ void LDA::lda(InputArray _src, InputArray _lbls) {
vector<int> mapped_labels(labels.size());
vector<int> num2label = remove_dups(labels);
map<int, int> label2num;
for (size_t i = 0; i < num2label.size(); i++)
label2num[num2label[i]] = (int)i;
for (int i = 0; i < (int)num2label.size(); i++)
label2num[num2label[i]] = i;
for (size_t i = 0; i < labels.size(); i++)
mapped_labels[i] = label2num[labels[i]];
// get sample size, dimension
@ -950,17 +996,27 @@ void LDA::lda(InputArray _src, InputArray _lbls) {
int D = data.cols;
// number of unique labels
int C = (int)num2label.size();
// we can't do a LDA on one class, what do you
// want to separate from each other then?
if(C == 1) {
string error_message = "At least two classes are needed to perform a LDA. Reason: Only one class was given!";
CV_Error(CV_StsBadArg, error_message);
}
// throw error if less labels, than samples
if (labels.size() != (size_t)N)
CV_Error(CV_StsBadArg, "Error: The number of samples must equal the number of labels.");
if (labels.size() != static_cast<size_t>(N)) {
string error_message = format("The number of samples must equal the number of labels. Given %d labels, %d samples. ", labels.size(), N);
CV_Error(CV_StsBadArg, error_message);
}
// warn if within-classes scatter matrix becomes singular
if (N < D)
if (N < D) {
cout << "Warning: Less observations than feature dimension given!"
<< "Computation will probably fail."
<< endl;
<< "Computation will probably fail."
<< endl;
}
// clip number of components to be a valid number
if ((_num_components <= 0) || (_num_components > (C - 1)))
if ((_num_components <= 0) || (_num_components > (C - 1))) {
_num_components = (C - 1);
}
// holds the mean over all classes
Mat meanTotal = Mat::zeros(1, D, data.type());
// holds the mean for each class
@ -979,12 +1035,12 @@ void LDA::lda(InputArray _src, InputArray _lbls) {
add(meanClass[classIdx], instance, meanClass[classIdx]);
numClass[classIdx]++;
}
// calculate means
meanTotal.convertTo(meanTotal, meanTotal.type(),
1.0 / static_cast<double> (N));
for (int i = 0; i < C; i++)
meanClass[i].convertTo(meanClass[i], meanClass[i].type(),
1.0 / static_cast<double> (numClass[i]));
// calculate total mean
meanTotal.convertTo(meanTotal, meanTotal.type(), 1.0 / static_cast<double> (N));
// calculate class means
for (int i = 0; i < C; i++) {
meanClass[i].convertTo(meanClass[i], meanClass[i].type(), 1.0 / static_cast<double> (numClass[i]));
}
// subtract class means
for (int i = 0; i < N; i++) {
int classIdx = mapped_labels[i];
@ -1031,7 +1087,8 @@ void LDA::compute(InputArray _src, InputArray _lbls) {
lda(_src.getMat(), _lbls);
break;
default:
CV_Error(CV_StsNotImplemented, "This data type is not supported by subspace::LDA::compute.");
string error_message= format("InputArray Datatype %d is not supported.", _src.kind());
CV_Error(CV_StsBadArg, error_message);
break;
}
}

68
modules/contrib/src/logpolar_bsm.cpp
View File

@ -62,7 +62,7 @@ namespace cv
{
//------------------------------------interp-------------------------------------------
LogPolar_Interp::LogPolar_Interp(int w, int h, Point2i center, int R, double ro0, int interp, int full, int S, int sp)
LogPolar_Interp::LogPolar_Interp(int w, int h, Point2i center, int _R, double _ro0, int _interp, int full, int _s, int sp)
{
if ( (center.x!=w/2 || center.y!=h/2) && full==0) full=1;
@ -97,23 +97,23 @@ LogPolar_Interp::LogPolar_Interp(int w, int h, Point2i center, int R, double ro0
if (sp){
int jc=M/2-1, ic=N/2-1;
int romax=min(ic, jc);
double a=exp(log((double)(romax/2-1)/(double)ro0)/(double)R);
S=(int) floor(2*CV_PI/(a-1)+0.5);
int _romax=min(ic, jc);
double _a=exp(log((double)(_romax/2-1)/(double)ro0)/(double)R);
S=(int) floor(2*CV_PI/(_a-1)+0.5);
}
this->interp=interp;
interp=_interp;
create_map(M, N, R, S, ro0);
create_map(M, N, _R, _s, _ro0);
}
void LogPolar_Interp::create_map(int M, int N, int R, int S, double ro0)
void LogPolar_Interp::create_map(int _M, int _n, int _R, int _s, double _ro0)
{
this->M=M;
this->N=N;
this->R=R;
this->S=S;
this->ro0=ro0;
M=_M;
N=_n;
R=_R;
S=_s;
ro0=_ro0;
int jc=N/2-1, ic=M/2-1;
romax=min(ic, jc);
@ -208,7 +208,7 @@ LogPolar_Interp::~LogPolar_Interp()
//------------------------------------overlapping----------------------------------
LogPolar_Overlapping::LogPolar_Overlapping(int w, int h, Point2i center, int R, double ro0, int full, int S, int sp)
LogPolar_Overlapping::LogPolar_Overlapping(int w, int h, Point2i center, int _R, double _ro0, int full, int _s, int sp)
{
if ( (center.x!=w/2 || center.y!=h/2) && full==0) full=1;
@ -244,21 +244,21 @@ LogPolar_Overlapping::LogPolar_Overlapping(int w, int h, Point2i center, int R,
if (sp){
int jc=M/2-1, ic=N/2-1;
int romax=min(ic, jc);
double a=exp(log((double)(romax/2-1)/(double)ro0)/(double)R);
S=(int) floor(2*CV_PI/(a-1)+0.5);
int _romax=min(ic, jc);
double _a=exp(log((double)(_romax/2-1)/(double)ro0)/(double)R);
S=(int) floor(2*CV_PI/(_a-1)+0.5);
}
create_map(M, N, R, S, ro0);
create_map(M, N, _R, _s, _ro0);
}
void LogPolar_Overlapping::create_map(int M, int N, int R, int S, double ro0)
void LogPolar_Overlapping::create_map(int _M, int _n, int _R, int _s, double _ro0)
{
this->M=M;
this->N=N;
this->R=R;
this->S=S;
this->ro0=ro0;
M=_M;
N=_n;
R=_R;
S=_s;
ro0=_ro0;
int jc=N/2-1, ic=M/2-1;
romax=min(ic, jc);
@ -433,7 +433,7 @@ LogPolar_Overlapping::~LogPolar_Overlapping()
//----------------------------------------adjacent---------------------------------------
LogPolar_Adjacent::LogPolar_Adjacent(int w, int h, Point2i center, int R, double ro0, double smin, int full, int S, int sp)
LogPolar_Adjacent::LogPolar_Adjacent(int w, int h, Point2i center, int _R, double _ro0, double smin, int full, int _s, int sp)
{
if ( (center.x!=w/2 || center.y!=h/2) && full==0) full=1;
@ -468,22 +468,22 @@ LogPolar_Adjacent::LogPolar_Adjacent(int w, int h, Point2i center, int R, double
if (sp){
int jc=M/2-1, ic=N/2-1;
int romax=min(ic, jc);
double a=exp(log((double)(romax/2-1)/(double)ro0)/(double)R);
S=(int) floor(2*CV_PI/(a-1)+0.5);
int _romax=min(ic, jc);
double _a=exp(log((double)(_romax/2-1)/(double)ro0)/(double)R);
S=(int) floor(2*CV_PI/(_a-1)+0.5);
}
create_map(M, N, R, S, ro0, smin);
create_map(M, N, _R, _s, _ro0, smin);
}
void LogPolar_Adjacent::create_map(int M, int N, int R, int S, double ro0, double smin)
void LogPolar_Adjacent::create_map(int _M, int _n, int _R, int _s, double _ro0, double smin)
{
LogPolar_Adjacent::M=M;
LogPolar_Adjacent::N=N;
LogPolar_Adjacent::R=R;
LogPolar_Adjacent::S=S;
LogPolar_Adjacent::ro0=ro0;
M=_M;
N=_n;
R=_R;
S=_s;
ro0=_ro0;
romax=min(M/2.0, N/2.0);
a=exp(log(romax/ro0)/(double)R);

18
modules/contrib/src/octree.cpp
View File

@ -43,8 +43,9 @@
#include "precomp.hpp"
#include <limits>
namespace cv
namespace
{
using namespace cv;
const size_t MAX_STACK_SIZE = 255;
const size_t MAX_LEAFS = 8;
@ -159,17 +160,20 @@ namespace cv
child.x_min = parent.x_min;
}
}//namespace
////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////// Octree //////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////
namespace cv
{
Octree::Octree()
{
}
Octree::Octree(const vector<Point3f>& points3d, int maxLevels, int minPoints)
Octree::Octree(const vector<Point3f>& points3d, int maxLevels, int _minPoints)
{
buildTree(points3d, maxLevels, minPoints);
buildTree(points3d, maxLevels, _minPoints);
}
Octree::~Octree()
@ -252,12 +256,12 @@ namespace cv
}
}
void Octree::buildTree(const vector<Point3f>& points3d, int maxLevels, int minPoints)
void Octree::buildTree(const vector<Point3f>& points3d, int maxLevels, int _minPoints)
{
assert((size_t)maxLevels * 8 < MAX_STACK_SIZE);
points.resize(points3d.size());
std::copy(points3d.begin(), points3d.end(), points.begin());
this->minPoints = minPoints;
minPoints = _minPoints;
nodes.clear();
nodes.push_back(Node());
@ -271,7 +275,7 @@ namespace cv
for (size_t i = 0; i < MAX_LEAFS; i++)
root.children[i] = 0;
if (maxLevels != 1 && (root.end - root.begin) > minPoints)
if (maxLevels != 1 && (root.end - root.begin) > _minPoints)
{
root.isLeaf = false;
buildNext(0);

4
modules/contrib/src/precomp.hpp
View File

@ -43,10 +43,6 @@
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#if _MSC_VER >= 1200
#pragma warning( disable: 4251 4710 4711 4514 4996 )
#endif
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif

456
modules/contrib/src/retina.cpp
View File

@ -75,16 +75,16 @@
namespace cv
{
Retina::Retina(const cv::Size inputSize)
Retina::Retina(const cv::Size inputSz)
{
_retinaFilter = 0;
_init(inputSize, true, RETINA_COLOR_BAYER, false);
_init(inputSz, true, RETINA_COLOR_BAYER, false);
}
Retina::Retina(const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
Retina::Retina(const cv::Size inputSz, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
{
_retinaFilter = 0;
_init(inputSize, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
_init(inputSz, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
};
Retina::~Retina()
@ -106,7 +106,7 @@ Size Retina::outputSize(){return cv::Size(_retinaFilter->getOutputNBcolumns(), _
void Retina::setColorSaturation(const bool saturateColors, const float colorSaturationValue)
{
_retinaFilter->setColorSaturation(saturateColors, colorSaturationValue);
_retinaFilter->setColorSaturation(saturateColors, colorSaturationValue);
}
struct Retina::RetinaParameters Retina::getParameters(){return _retinaParameters;}
@ -121,71 +121,71 @@ void Retina::setup(std::string retinaParameterFile, const bool applyDefaultSetup
setup(fs, applyDefaultSetupOnFailure);
}catch(Exception &e)
{
std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
if (applyDefaultSetupOnFailure)
{
std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
if (applyDefaultSetupOnFailure)
{
std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
setupOPLandIPLParvoChannel();
setupIPLMagnoChannel();
}
setupOPLandIPLParvoChannel();
setupIPLMagnoChannel();
}
else
{
std::cout<<"=> keeping current parameters"<<std::endl;
std::cout<<"=> keeping current parameters"<<std::endl;
}
}
}
void Retina::setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure)
{
try
{
// read parameters file if it exists or apply default setup if asked for
if (!fs.isOpened())
{
std::cout<<"Retina::setup: provided parameters file could not be open... skeeping configuration"<<std::endl;
return;
// implicit else case : retinaParameterFile could be open (it exists at least)
}
try
{
// read parameters file if it exists or apply default setup if asked for
if (!fs.isOpened())
{
std::cout<<"Retina::setup: provided parameters file could not be open... skeeping configuration"<<std::endl;
return;
// implicit else case : retinaParameterFile could be open (it exists at least)
}
// OPL and Parvo init first... update at the same time the parameters structure and the retina core
cv::FileNode rootFn = fs.root(), currFn=rootFn["OPLandIPLparvo"];
currFn["colorMode"]>>_retinaParameters.OPLandIplParvo.colorMode;
currFn["normaliseOutput"]>>_retinaParameters.OPLandIplParvo.normaliseOutput;
currFn["photoreceptorsLocalAdaptationSensitivity"]>>_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
currFn["photoreceptorsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
currFn["photoreceptorsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
currFn["horizontalCellsGain"]>>_retinaParameters.OPLandIplParvo.horizontalCellsGain;
currFn["hcellsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
currFn["hcellsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
currFn["ganglionCellsSensitivity"]>>_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
setupOPLandIPLParvoChannel(_retinaParameters.OPLandIplParvo.colorMode, _retinaParameters.OPLandIplParvo.normaliseOutput, _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity, _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant, _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant, _retinaParameters.OPLandIplParvo.horizontalCellsGain, _retinaParameters.OPLandIplParvo.hcellsTemporalConstant, _retinaParameters.OPLandIplParvo.hcellsSpatialConstant, _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity);
cv::FileNode rootFn = fs.root(), currFn=rootFn["OPLandIPLparvo"];
currFn["colorMode"]>>_retinaParameters.OPLandIplParvo.colorMode;
currFn["normaliseOutput"]>>_retinaParameters.OPLandIplParvo.normaliseOutput;
currFn["photoreceptorsLocalAdaptationSensitivity"]>>_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
currFn["photoreceptorsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
currFn["photoreceptorsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
currFn["horizontalCellsGain"]>>_retinaParameters.OPLandIplParvo.horizontalCellsGain;
currFn["hcellsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
currFn["hcellsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
currFn["ganglionCellsSensitivity"]>>_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
setupOPLandIPLParvoChannel(_retinaParameters.OPLandIplParvo.colorMode, _retinaParameters.OPLandIplParvo.normaliseOutput, _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity, _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant, _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant, _retinaParameters.OPLandIplParvo.horizontalCellsGain, _retinaParameters.OPLandIplParvo.hcellsTemporalConstant, _retinaParameters.OPLandIplParvo.hcellsSpatialConstant, _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity);
// init retina IPL magno setup... update at the same time the parameters structure and the retina core
currFn=rootFn["IPLmagno"];
currFn["normaliseOutput"]>>_retinaParameters.IplMagno.normaliseOutput;
currFn["parasolCells_beta"]>>_retinaParameters.IplMagno.parasolCells_beta;
currFn["parasolCells_tau"]>>_retinaParameters.IplMagno.parasolCells_tau;
currFn["parasolCells_k"]>>_retinaParameters.IplMagno.parasolCells_k;
currFn["amacrinCellsTemporalCutFrequency"]>>_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
currFn["V0CompressionParameter"]>>_retinaParameters.IplMagno.V0CompressionParameter;
currFn["localAdaptintegration_tau"]>>_retinaParameters.IplMagno.localAdaptintegration_tau;
currFn["localAdaptintegration_k"]>>_retinaParameters.IplMagno.localAdaptintegration_k;
// init retina IPL magno setup... update at the same time the parameters structure and the retina core
currFn=rootFn["IPLmagno"];
currFn["normaliseOutput"]>>_retinaParameters.IplMagno.normaliseOutput;
currFn["parasolCells_beta"]>>_retinaParameters.IplMagno.parasolCells_beta;
currFn["parasolCells_tau"]>>_retinaParameters.IplMagno.parasolCells_tau;
currFn["parasolCells_k"]>>_retinaParameters.IplMagno.parasolCells_k;
currFn["amacrinCellsTemporalCutFrequency"]>>_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
currFn["V0CompressionParameter"]>>_retinaParameters.IplMagno.V0CompressionParameter;
currFn["localAdaptintegration_tau"]>>_retinaParameters.IplMagno.localAdaptintegration_tau;
currFn["localAdaptintegration_k"]>>_retinaParameters.IplMagno.localAdaptintegration_k;
setupIPLMagnoChannel(_retinaParameters.IplMagno.normaliseOutput, _retinaParameters.IplMagno.parasolCells_beta, _retinaParameters.IplMagno.parasolCells_tau, _retinaParameters.IplMagno.parasolCells_k, _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency,_retinaParameters.IplMagno.V0CompressionParameter, _retinaParameters.IplMagno.localAdaptintegration_tau, _retinaParameters.IplMagno.localAdaptintegration_k);
setupIPLMagnoChannel(_retinaParameters.IplMagno.normaliseOutput, _retinaParameters.IplMagno.parasolCells_beta, _retinaParameters.IplMagno.parasolCells_tau, _retinaParameters.IplMagno.parasolCells_k, _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency,_retinaParameters.IplMagno.V0CompressionParameter, _retinaParameters.IplMagno.localAdaptintegration_tau, _retinaParameters.IplMagno.localAdaptintegration_k);
}catch(Exception &e)
{
std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
if (applyDefaultSetupOnFailure)
{
setupOPLandIPLParvoChannel();
setupIPLMagnoChannel();
}
std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
std::cout<<"=> keeping current parameters"<<std::endl;
}
}catch(Exception &e)
{
std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
if (applyDefaultSetupOnFailure)
{
setupOPLandIPLParvoChannel();
setupIPLMagnoChannel();
}
std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
std::cout<<"=> keeping current parameters"<<std::endl;
}
// report current configuration
std::cout<<printSetup()<<std::endl;
// report current configuration
std::cout<<printSetup()<<std::endl;
}
void Retina::setup(cv::Retina::RetinaParameters newConfiguration)
@ -201,35 +201,35 @@ void Retina::setup(cv::Retina::RetinaParameters newConfiguration)
const std::string Retina::printSetup()
{
std::stringstream outmessage;
std::stringstream outmessage;
// displaying OPL and IPL parvo setup
outmessage<<"Current Retina instance setup :"
<<"\nOPLandIPLparvo"<<"{"
<< "\n==> colorMode : " << _retinaParameters.OPLandIplParvo.colorMode
<< "\n==> normalizeParvoOutput :" << _retinaParameters.OPLandIplParvo.normaliseOutput
<< "\n==> photoreceptorsLocalAdaptationSensitivity : " << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity
<< "\n==> photoreceptorsTemporalConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant
<< "\n==> photoreceptorsSpatialConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant
<< "\n==> horizontalCellsGain : " << _retinaParameters.OPLandIplParvo.horizontalCellsGain
<< "\n==> hcellsTemporalConstant : " << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant
<< "\n==> hcellsSpatialConstant : " << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant
<< "\n==> parvoGanglionCellsSensitivity : " << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity
<<"}\n";
// displaying OPL and IPL parvo setup
outmessage<<"Current Retina instance setup :"
<<"\nOPLandIPLparvo"<<"{"
<< "\n==> colorMode : " << _retinaParameters.OPLandIplParvo.colorMode
<< "\n==> normalizeParvoOutput :" << _retinaParameters.OPLandIplParvo.normaliseOutput
<< "\n==> photoreceptorsLocalAdaptationSensitivity : " << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity
<< "\n==> photoreceptorsTemporalConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant
<< "\n==> photoreceptorsSpatialConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant
<< "\n==> horizontalCellsGain : " << _retinaParameters.OPLandIplParvo.horizontalCellsGain
<< "\n==> hcellsTemporalConstant : " << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant
<< "\n==> hcellsSpatialConstant : " << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant
<< "\n==> parvoGanglionCellsSensitivity : " << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity
<<"}\n";
// displaying IPL magno setup
outmessage<<"Current Retina instance setup :"
<<"\nIPLmagno"<<"{"
<< "\n==> normaliseOutput : " << _retinaParameters.IplMagno.normaliseOutput
<< "\n==> parasolCells_beta : " << _retinaParameters.IplMagno.parasolCells_beta
<< "\n==> parasolCells_tau : " << _retinaParameters.IplMagno.parasolCells_tau
<< "\n==> parasolCells_k : " << _retinaParameters.IplMagno.parasolCells_k
<< "\n==> amacrinCellsTemporalCutFrequency : " << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency
<< "\n==> V0CompressionParameter : " << _retinaParameters.IplMagno.V0CompressionParameter
<< "\n==> localAdaptintegration_tau : " << _retinaParameters.IplMagno.localAdaptintegration_tau
<< "\n==> localAdaptintegration_k : " << _retinaParameters.IplMagno.localAdaptintegration_k
<<"}";
return outmessage.str();
// displaying IPL magno setup
outmessage<<"Current Retina instance setup :"
<<"\nIPLmagno"<<"{"
<< "\n==> normaliseOutput : " << _retinaParameters.IplMagno.normaliseOutput
<< "\n==> parasolCells_beta : " << _retinaParameters.IplMagno.parasolCells_beta
<< "\n==> parasolCells_tau : " << _retinaParameters.IplMagno.parasolCells_tau
<< "\n==> parasolCells_k : " << _retinaParameters.IplMagno.parasolCells_k
<< "\n==> amacrinCellsTemporalCutFrequency : " << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency
<< "\n==> V0CompressionParameter : " << _retinaParameters.IplMagno.V0CompressionParameter
<< "\n==> localAdaptintegration_tau : " << _retinaParameters.IplMagno.localAdaptintegration_tau
<< "\n==> localAdaptintegration_k : " << _retinaParameters.IplMagno.localAdaptintegration_k
<<"}";
return outmessage.str();
}
void Retina::write( std::string fs ) const
@ -240,98 +240,98 @@ void Retina::write( std::string fs ) const
void Retina::write( FileStorage& fs ) const
{
if (!fs.isOpened())
return; // basic error case
fs<<"OPLandIPLparvo"<<"{";
fs << "colorMode" << _retinaParameters.OPLandIplParvo.colorMode;
fs << "normaliseOutput" << _retinaParameters.OPLandIplParvo.normaliseOutput;
fs << "photoreceptorsLocalAdaptationSensitivity" << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
fs << "photoreceptorsTemporalConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
fs << "photoreceptorsSpatialConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
fs << "horizontalCellsGain" << _retinaParameters.OPLandIplParvo.horizontalCellsGain;
fs << "hcellsTemporalConstant" << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
fs << "hcellsSpatialConstant" << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
fs << "ganglionCellsSensitivity" << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
fs << "}";
fs<<"IPLmagno"<<"{";
fs << "normaliseOutput" << _retinaParameters.IplMagno.normaliseOutput;
fs << "parasolCells_beta" << _retinaParameters.IplMagno.parasolCells_beta;
fs << "parasolCells_tau" << _retinaParameters.IplMagno.parasolCells_tau;
fs << "parasolCells_k" << _retinaParameters.IplMagno.parasolCells_k;
fs << "amacrinCellsTemporalCutFrequency" << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
fs << "V0CompressionParameter" << _retinaParameters.IplMagno.V0CompressionParameter;
fs << "localAdaptintegration_tau" << _retinaParameters.IplMagno.localAdaptintegration_tau;
fs << "localAdaptintegration_k" << _retinaParameters.IplMagno.localAdaptintegration_k;
fs<<"}";
if (!fs.isOpened())
return; // basic error case
fs<<"OPLandIPLparvo"<<"{";
fs << "colorMode" << _retinaParameters.OPLandIplParvo.colorMode;
fs << "normaliseOutput" << _retinaParameters.OPLandIplParvo.normaliseOutput;
fs << "photoreceptorsLocalAdaptationSensitivity" << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
fs << "photoreceptorsTemporalConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
fs << "photoreceptorsSpatialConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
fs << "horizontalCellsGain" << _retinaParameters.OPLandIplParvo.horizontalCellsGain;
fs << "hcellsTemporalConstant" << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
fs << "hcellsSpatialConstant" << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
fs << "ganglionCellsSensitivity" << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
fs << "}";
fs<<"IPLmagno"<<"{";
fs << "normaliseOutput" << _retinaParameters.IplMagno.normaliseOutput;
fs << "parasolCells_beta" << _retinaParameters.IplMagno.parasolCells_beta;
fs << "parasolCells_tau" << _retinaParameters.IplMagno.parasolCells_tau;
fs << "parasolCells_k" << _retinaParameters.IplMagno.parasolCells_k;
fs << "amacrinCellsTemporalCutFrequency" << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
fs << "V0CompressionParameter" << _retinaParameters.IplMagno.V0CompressionParameter;
fs << "localAdaptintegration_tau" << _retinaParameters.IplMagno.localAdaptintegration_tau;
fs << "localAdaptintegration_k" << _retinaParameters.IplMagno.localAdaptintegration_k;
fs<<"}";
}
void Retina::setupOPLandIPLParvoChannel(const bool colorMode, const bool normaliseOutput, const float photoreceptorsLocalAdaptationSensitivity, const float photoreceptorsTemporalConstant, const float photoreceptorsSpatialConstant, const float horizontalCellsGain, const float HcellsTemporalConstant, const float HcellsSpatialConstant, const float ganglionCellsSensitivity)
{
// retina core parameters setup
_retinaFilter->setColorMode(colorMode);
_retinaFilter->setPhotoreceptorsLocalAdaptationSensitivity(photoreceptorsLocalAdaptationSensitivity);
_retinaFilter->setOPLandParvoParameters(0, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, HcellsTemporalConstant, HcellsSpatialConstant, ganglionCellsSensitivity);
_retinaFilter->setParvoGanglionCellsLocalAdaptationSensitivity(ganglionCellsSensitivity);
_retinaFilter->activateNormalizeParvoOutput_0_maxOutputValue(normaliseOutput);
// retina core parameters setup
_retinaFilter->setColorMode(colorMode);
_retinaFilter->setPhotoreceptorsLocalAdaptationSensitivity(photoreceptorsLocalAdaptationSensitivity);
_retinaFilter->setOPLandParvoParameters(0, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, HcellsTemporalConstant, HcellsSpatialConstant, ganglionCellsSensitivity);
_retinaFilter->setParvoGanglionCellsLocalAdaptationSensitivity(ganglionCellsSensitivity);
_retinaFilter->activateNormalizeParvoOutput_0_maxOutputValue(normaliseOutput);
// update parameters struture
_retinaParameters.OPLandIplParvo.colorMode = colorMode;
_retinaParameters.OPLandIplParvo.normaliseOutput = normaliseOutput;
_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity = photoreceptorsLocalAdaptationSensitivity;
_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant = photoreceptorsTemporalConstant;
_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant = photoreceptorsSpatialConstant;
_retinaParameters.OPLandIplParvo.horizontalCellsGain = horizontalCellsGain;
_retinaParameters.OPLandIplParvo.hcellsTemporalConstant = HcellsTemporalConstant;
_retinaParameters.OPLandIplParvo.hcellsSpatialConstant = HcellsSpatialConstant;
_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity = ganglionCellsSensitivity;
_retinaParameters.OPLandIplParvo.colorMode = colorMode;
_retinaParameters.OPLandIplParvo.normaliseOutput = normaliseOutput;
_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity = photoreceptorsLocalAdaptationSensitivity;
_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant = photoreceptorsTemporalConstant;
_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant = photoreceptorsSpatialConstant;
_retinaParameters.OPLandIplParvo.horizontalCellsGain = horizontalCellsGain;
_retinaParameters.OPLandIplParvo.hcellsTemporalConstant = HcellsTemporalConstant;
_retinaParameters.OPLandIplParvo.hcellsSpatialConstant = HcellsSpatialConstant;
_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity = ganglionCellsSensitivity;
}
void Retina::setupIPLMagnoChannel(const bool normaliseOutput, const float parasolCells_beta, const float parasolCells_tau, const float parasolCells_k, const float amacrinCellsTemporalCutFrequency, const float V0CompressionParameter, const float localAdaptintegration_tau, const float localAdaptintegration_k)
{
_retinaFilter->setMagnoCoefficientsTable(parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k);
_retinaFilter->activateNormalizeMagnoOutput_0_maxOutputValue(normaliseOutput);
_retinaFilter->setMagnoCoefficientsTable(parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k);
_retinaFilter->activateNormalizeMagnoOutput_0_maxOutputValue(normaliseOutput);
// update parameters struture
_retinaParameters.IplMagno.normaliseOutput = normaliseOutput;
_retinaParameters.IplMagno.parasolCells_beta = parasolCells_beta;
_retinaParameters.IplMagno.parasolCells_tau = parasolCells_tau;
_retinaParameters.IplMagno.parasolCells_k = parasolCells_k;
_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency = amacrinCellsTemporalCutFrequency;
_retinaParameters.IplMagno.V0CompressionParameter = V0CompressionParameter;
_retinaParameters.IplMagno.localAdaptintegration_tau = localAdaptintegration_tau;
_retinaParameters.IplMagno.localAdaptintegration_k = localAdaptintegration_k;
_retinaParameters.IplMagno.normaliseOutput = normaliseOutput;
_retinaParameters.IplMagno.parasolCells_beta = parasolCells_beta;
_retinaParameters.IplMagno.parasolCells_tau = parasolCells_tau;
_retinaParameters.IplMagno.parasolCells_k = parasolCells_k;
_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency = amacrinCellsTemporalCutFrequency;
_retinaParameters.IplMagno.V0CompressionParameter = V0CompressionParameter;
_retinaParameters.IplMagno.localAdaptintegration_tau = localAdaptintegration_tau;
_retinaParameters.IplMagno.localAdaptintegration_k = localAdaptintegration_k;
}
void Retina::run(const cv::Mat &inputMatToConvert)
{
// first convert input image to the compatible format : std::valarray<float>
const bool colorMode = _convertCvMat2ValarrayBuffer(inputMatToConvert, _inputBuffer);
// process the retina
if (!_retinaFilter->runFilter(_inputBuffer, colorMode, false, _retinaParameters.OPLandIplParvo.colorMode && colorMode, false))
throw cv::Exception(-1, "Retina cannot be applied, wrong input buffer size", "Retina::run", "Retina.h", 0);
// first convert input image to the compatible format : std::valarray<float>
const bool colorMode = _convertCvMat2ValarrayBuffer(inputMatToConvert, _inputBuffer);
// process the retina
if (!_retinaFilter->runFilter(_inputBuffer, colorMode, false, _retinaParameters.OPLandIplParvo.colorMode && colorMode, false))
throw cv::Exception(-1, "Retina cannot be applied, wrong input buffer size", "Retina::run", "Retina.h", 0);
}
void Retina::getParvo(cv::Mat &retinaOutput_parvo)
{
if (_retinaFilter->getColorMode())
{
// reallocate output buffer (if necessary)
_convertValarrayBuffer2cvMat(_retinaFilter->getColorOutput(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), true, retinaOutput_parvo);
}else
{
// reallocate output buffer (if necessary)
_convertValarrayBuffer2cvMat(_retinaFilter->getContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_parvo);
}
//retinaOutput_parvo/=255.0;
if (_retinaFilter->getColorMode())
{
// reallocate output buffer (if necessary)
_convertValarrayBuffer2cvMat(_retinaFilter->getColorOutput(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), true, retinaOutput_parvo);
}else
{
// reallocate output buffer (if necessary)
_convertValarrayBuffer2cvMat(_retinaFilter->getContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_parvo);
}
//retinaOutput_parvo/=255.0;
}
void Retina::getMagno(cv::Mat &retinaOutput_magno)
{
// reallocate output buffer (if necessary)
_convertValarrayBuffer2cvMat(_retinaFilter->getMovingContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_magno);
//retinaOutput_magno/=255.0;
// reallocate output buffer (if necessary)
_convertValarrayBuffer2cvMat(_retinaFilter->getMovingContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_magno);
//retinaOutput_magno/=255.0;
}
// original API level data accessors : copy buffers if size matches
@ -342,109 +342,111 @@ const std::valarray<float> & Retina::getMagno() const {return _retinaFilter->get
const std::valarray<float> & Retina::getParvo() const {if (_retinaFilter->getColorMode())return _retinaFilter->getColorOutput(); /* implicite else */return _retinaFilter->getContours();}
// private method called by constructirs
void Retina::_init(const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
void Retina::_init(const cv::Size inputSz, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
{
// basic error check
if (inputSize.height*inputSize.width <= 0)
throw cv::Exception(-1, "Bad retina size setup : size height and with must be superior to zero", "Retina::setup", "Retina.h", 0);
// basic error check
if (inputSz.height*inputSz.width <= 0)
throw cv::Exception(-1, "Bad retina size setup : size height and with must be superior to zero", "Retina::setup", "Retina.h", 0);
unsigned int nbPixels=inputSize.height*inputSize.width;
// resize buffers if size does not match
_inputBuffer.resize(nbPixels*3); // buffer supports gray images but also 3 channels color buffers... (larger is better...)
unsigned int nbPixels=inputSz.height*inputSz.width;
// resize buffers if size does not match
_inputBuffer.resize(nbPixels*3); // buffer supports gray images but also 3 channels color buffers... (larger is better...)
// allocate the retina model
// allocate the retina model
if (_retinaFilter)
delete _retinaFilter;
_retinaFilter = new RetinaFilter(inputSize.height, inputSize.width, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
_retinaFilter = new RetinaFilter(inputSz.height, inputSz.width, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
// prepare the default parameter XML file with default setup
// prepare the default parameter XML file with default setup
setup(_retinaParameters);
// init retina
_retinaFilter->clearAllBuffers();
// init retina
_retinaFilter->clearAllBuffers();
// report current configuration
std::cout<<printSetup()<<std::endl;
// report current configuration
std::cout<<printSetup()<<std::endl;
}
void Retina::_convertValarrayBuffer2cvMat(const std::valarray<float> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, cv::Mat &outBuffer)
{
// fill output buffer with the valarray buffer
const float *valarrayPTR=get_data(grayMatrixToConvert);
if (!colorMode)
{
outBuffer.create(cv::Size(nbColumns, nbRows), CV_8U);
for (unsigned int i=0;i<nbRows;++i)
{
for (unsigned int j=0;j<nbColumns;++j)
{
cv::Point2d pixel(j,i);
outBuffer.at<unsigned char>(pixel)=(unsigned char)*(valarrayPTR++);
}
}
}else
{
const unsigned int doubleNBpixels=_retinaFilter->getOutputNBpixels()*2;
outBuffer.create(cv::Size(nbColumns, nbRows), CV_8UC3);
for (unsigned int i=0;i<nbRows;++i)
{
for (unsigned int j=0;j<nbColumns;++j,++valarrayPTR)
{
cv::Point2d pixel(j,i);
cv::Vec3b pixelValues;
pixelValues[2]=(unsigned char)*(valarrayPTR);
pixelValues[1]=(unsigned char)*(valarrayPTR+_retinaFilter->getOutputNBpixels());
pixelValues[0]=(unsigned char)*(valarrayPTR+doubleNBpixels);
// fill output buffer with the valarray buffer
const float *valarrayPTR=get_data(grayMatrixToConvert);
if (!colorMode)
{
outBuffer.create(cv::Size(nbColumns, nbRows), CV_8U);
for (unsigned int i=0;i<nbRows;++i)
{
for (unsigned int j=0;j<nbColumns;++j)
{
cv::Point2d pixel(j,i);
outBuffer.at<unsigned char>(pixel)=(unsigned char)*(valarrayPTR++);
}
}
}else
{
const unsigned int doubleNBpixels=_retinaFilter->getOutputNBpixels()*2;
outBuffer.create(cv::Size(nbColumns, nbRows), CV_8UC3);
for (unsigned int i=0;i<nbRows;++i)
{
for (unsigned int j=0;j<nbColumns;++j,++valarrayPTR)
{
cv::Point2d pixel(j,i);
cv::Vec3b pixelValues;
pixelValues[2]=(unsigned char)*(valarrayPTR);
pixelValues[1]=(unsigned char)*(valarrayPTR+_retinaFilter->getOutputNBpixels());
pixelValues[0]=(unsigned char)*(valarrayPTR+doubleNBpixels);
outBuffer.at<cv::Vec3b>(pixel)=pixelValues;
}
}
}
outBuffer.at<cv::Vec3b>(pixel)=pixelValues;
}
}
}
}
bool Retina::_convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::valarray<float> &outputValarrayMatrix)
{
// first check input consistency
if (inputMatToConvert.empty())
throw cv::Exception(-1, "Retina cannot be applied, input buffer is empty", "Retina::run", "Retina.h", 0);
// first check input consistency
if (inputMatToConvert.empty())
throw cv::Exception(-1, "Retina cannot be applied, input buffer is empty", "Retina::run", "Retina.h", 0);
// retreive color mode from image input
int imageNumberOfChannels = inputMatToConvert.channels();
// retreive color mode from image input
int imageNumberOfChannels = inputMatToConvert.channels();
// convert to float AND fill the valarray buffer
typedef float T; // define here the target pixel format, here, float
typedef float T; // define here the target pixel format, here, float
const int dsttype = DataType<T>::depth; // output buffer is float format
if(imageNumberOfChannels==4)
if(imageNumberOfChannels==4)
{
// create a cv::Mat table (for RGBA planes)
cv::Mat planes[4] =
{
// create a cv::Mat table (for RGBA planes)
cv::Mat planes[] =
{
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]),
cv::Mat(inputMatToConvert.size(), dsttype) // last channel (alpha) does not point on the valarray (not usefull in our case)
};
// split color cv::Mat in 4 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 4> >(inputMatToConvert), planes);
}else if (imageNumberOfChannels==3)
{
// create a cv::Mat table (for RGB planes)
cv::Mat planes[] =
{
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0])
};
// split color cv::Mat in 3 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 3> >(inputMatToConvert), planes);
}else if(imageNumberOfChannels==1)
{
// create a cv::Mat header for the valarray
cv::Mat dst(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]);
inputMatToConvert.convertTo(dst, dsttype);
}
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0])
};
planes[3] = cv::Mat(inputMatToConvert.size(), dsttype); // last channel (alpha) does not point on the valarray (not usefull in our case)
// split color cv::Mat in 4 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 4> >(inputMatToConvert), planes);
}
else if (imageNumberOfChannels==3)
{
// create a cv::Mat table (for RGB planes)
cv::Mat planes[] =
{
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0])
};
// split color cv::Mat in 3 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 3> >(inputMatToConvert), planes);
}
else if(imageNumberOfChannels==1)
{
// create a cv::Mat header for the valarray
cv::Mat dst(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]);
inputMatToConvert.convertTo(dst, dsttype);
}
else
CV_Error(CV_StsUnsupportedFormat, "input image must be single channel (gray levels), bgr format (color) or bgra (color with transparency which won't be considered");

6
modules/contrib/src/retinacolor.cpp
View File

@ -325,15 +325,15 @@ void RetinaColor::runColorDemultiplexing(const std::valarray<float> &multiplexed
}else
{
register const float *multiplexedColorFramePTR= get_data(multiplexedColorFrame);
for (unsigned int indexc=0; indexc<_filterOutput.getNBpixels() ; ++indexc, ++chrominancePTR, ++colorLocalDensityPTR, ++luminance, ++multiplexedColorFramePTR)
register const float *multiplexedColorFramePTR1= get_data(multiplexedColorFrame);
for (unsigned int indexc=0; indexc<_filterOutput.getNBpixels() ; ++indexc, ++chrominancePTR, ++colorLocalDensityPTR, ++luminance, ++multiplexedColorFramePTR1)
{
// normalize by photoreceptors density
float Cr=*(chrominancePTR)*_colorLocalDensity[indexc];
float Cg=*(chrominancePTR+_filterOutput.getNBpixels())*_colorLocalDensity[indexc+_filterOutput.getNBpixels()];
float Cb=*(chrominancePTR+_filterOutput.getDoubleNBpixels())*_colorLocalDensity[indexc+_filterOutput.getDoubleNBpixels()];
*luminance=(Cr+Cg+Cb)*_pG;
_demultiplexedTempBuffer[_colorSampling[indexc]] = *multiplexedColorFramePTR - *luminance;
_demultiplexedTempBuffer[_colorSampling[indexc]] = *multiplexedColorFramePTR1 - *luminance;
}

42
modules/contrib/src/spinimages.cpp
View File

@ -336,18 +336,18 @@ void computeSpinImages( const Octree& Octree, const vector<Point3f>& points, con
__m128 f1f2 = _mm_mul_ps(f1, f2); // f1 * f2
__m128 omf1omf2 = _mm_add_ps(_mm_sub_ps(_mm_sub_ps(one4f, f2), f1), f1f2); // (1-f1) * (1-f2)
__m128i mask = _mm_and_si128(
__m128i _mask = _mm_and_si128(
_mm_andnot_si128(_mm_cmpgt_epi32(zero4, n1), _mm_cmpgt_epi32(height4m1, n1)),
_mm_andnot_si128(_mm_cmpgt_epi32(zero4, n2), _mm_cmpgt_epi32(width4m1, n2)));
__m128 maskf = _mm_cmpneq_ps(_mm_cvtepi32_ps(mask), zero4f);
__m128 maskf = _mm_cmpneq_ps(_mm_cvtepi32_ps(_mask), zero4f);
__m128 v00 = _mm_and_ps( omf1omf2 , maskf); // a00 b00 c00 d00
__m128 v01 = _mm_and_ps( _mm_sub_ps( f2, f1f2 ), maskf); // a01 b01 c01 d01
__m128 v10 = _mm_and_ps( _mm_sub_ps( f1, f1f2 ), maskf); // a10 b10 c10 d10
__m128 v11 = _mm_and_ps( f1f2 , maskf); // a11 b11 c11 d11
__m128i ofs4 = _mm_and_si128(_mm_add_epi32(_mm_mullo_epi32_emul(n1, step4), n2), mask);
__m128i ofs4 = _mm_and_si128(_mm_add_epi32(_mm_mullo_epi32_emul(n1, step4), n2), _mask);
_mm_store_si128((__m128i*)o, ofs4);
__m128 t0 = _mm_unpacklo_ps(v00, v01); // a00 a01 b00 b01
@ -504,16 +504,16 @@ void cv::Mesh3D::writeAsVrml(const String& file, const vector<Scalar>& _colors)
ofstream ofs(file.c_str());
ofs << "#VRML V2.0 utf8" << endl;
ofs << "Shape" << std::endl << "{" << endl;
ofs << "geometry PointSet" << endl << "{" << endl;
ofs << "coord Coordinate" << endl << "{" << endl;
ofs << "point[" << endl;
ofs << "Shape" << std::endl << "{" << endl;
ofs << "geometry PointSet" << endl << "{" << endl;
ofs << "coord Coordinate" << endl << "{" << endl;
ofs << "point[" << endl;
for(size_t i = 0; i < vtx.size(); ++i)
ofs << vtx[i].x << " " << vtx[i].y << " " << vtx[i].z << endl;
ofs << "]" << endl; //point[
ofs << "}" << endl; //Coordinate{
ofs << "]" << endl; //point[
ofs << "}" << endl; //Coordinate{
if (vtx.size() == _colors.size())
{
@ -524,11 +524,11 @@ void cv::Mesh3D::writeAsVrml(const String& file, const vector<Scalar>& _colors)
ofs << (float)_colors[i][2] << " " << (float)_colors[i][1] << " " << (float)_colors[i][0] << endl;
ofs << "]" << endl; //color[
ofs << "}" << endl; //color Color{
ofs << "}" << endl; //color Color{
}
ofs << "}" << endl; //PointSet{
ofs << "}" << endl; //Shape{
ofs << "}" << endl; //PointSet{
ofs << "}" << endl; //Shape{
}
@ -808,7 +808,7 @@ void cv::SpinImageModel::selectRandomSubset(float ratio)
subset.resize(setSize);
for(size_t i = 0; i < setSize; ++i)
{
int pos = rnd.next() % left.size();
int pos = rnd.next() % (int)left.size();
subset[i] = (int)left[pos];
left[pos] = left.back();
@ -823,21 +823,21 @@ void cv::SpinImageModel::setSubset(const vector<int>& ss)
subset = ss;
}
void cv::SpinImageModel::repackSpinImages(const vector<uchar>& mask, Mat& spinImages, bool reAlloc) const
void cv::SpinImageModel::repackSpinImages(const vector<uchar>& mask, Mat& _spinImages, bool reAlloc) const
{
if (reAlloc)
{
size_t spinCount = mask.size() - count(mask.begin(), mask.end(), (uchar)0);
Mat newImgs((int)spinCount, spinImages.cols, spinImages.type());
Mat newImgs((int)spinCount, _spinImages.cols, _spinImages.type());
int pos = 0;
for(size_t t = 0; t < mask.size(); ++t)
if (mask[t])
{
Mat row = newImgs.row(pos++);
spinImages.row((int)t).copyTo(row);
_spinImages.row((int)t).copyTo(row);
}
spinImages = newImgs;
_spinImages = newImgs;
}
else
{
@ -849,13 +849,13 @@ void cv::SpinImageModel::repackSpinImages(const vector<uchar>& mask, Mat& spinIm
int first = dest + 1;
for (; first != last; ++first)
if (mask[first] != 0)
if (mask[first] != 0)
{
Mat row = spinImages.row(dest);
spinImages.row(first).copyTo(row);
Mat row = _spinImages.row(dest);
_spinImages.row(first).copyTo(row);
++dest;
}
spinImages = spinImages.rowRange(0, dest);
_spinImages = _spinImages.rowRange(0, dest);
}
}

504
modules/contrib/src/stereovar.cpp
View File

@ -67,9 +67,9 @@ StereoVar::~StereoVar()
static Mat diffX(Mat &src)
{
register int x, y, cols = src.cols - 1;
Mat dst(src.size(), src.type());
for(y = 0; y < src.rows; y++){
register int x, y, cols = src.cols - 1;
Mat dst(src.size(), src.type());
for(y = 0; y < src.rows; y++){
const float* pSrc = src.ptr<float>(y);
float* pDst = dst.ptr<float>(y);
#if CV_SSE2
@ -92,319 +92,319 @@ static Mat diffX(Mat &src)
static Mat getGradient(Mat &src)
{
register int x, y;
Mat dst(src.size(), src.type());
dst.setTo(0);
for (y = 0; y < src.rows - 1; y++) {
float *pSrc = src.ptr<float>(y);
float *pSrcF = src.ptr<float>(y + 1);
float *pDst = dst.ptr<float>(y);
for (x = 0; x < src.cols - 1; x++)
pDst[x] = fabs(pSrc[x + 1] - pSrc[x]) + fabs(pSrcF[x] - pSrc[x]);
}
return dst;
register int x, y;
Mat dst(src.size(), src.type());
dst.setTo(0);
for (y = 0; y < src.rows - 1; y++) {
float *pSrc = src.ptr<float>(y);
float *pSrcF = src.ptr<float>(y + 1);
float *pDst = dst.ptr<float>(y);
for (x = 0; x < src.cols - 1; x++)
pDst[x] = fabs(pSrc[x + 1] - pSrc[x]) + fabs(pSrcF[x] - pSrc[x]);
}
return dst;
}
static Mat getG_c(Mat &src, float l)
{
Mat dst(src.size(), src.type());
for (register int y = 0; y < src.rows; y++) {
float *pSrc = src.ptr<float>(y);
float *pDst = dst.ptr<float>(y);
for (register int x = 0; x < src.cols; x++)
pDst[x] = 0.5f*l / sqrtf(l*l + pSrc[x]*pSrc[x]);
}
return dst;
Mat dst(src.size(), src.type());
for (register int y = 0; y < src.rows; y++) {
float *pSrc = src.ptr<float>(y);
float *pDst = dst.ptr<float>(y);
for (register int x = 0; x < src.cols; x++)
pDst[x] = 0.5f*l / sqrtf(l*l + pSrc[x]*pSrc[x]);
}
return dst;
}
static Mat getG_p(Mat &src, float l)
{
Mat dst(src.size(), src.type());
for (register int y = 0; y < src.rows; y++) {
float *pSrc = src.ptr<float>(y);
float *pDst = dst.ptr<float>(y);
for (register int x = 0; x < src.cols; x++)
pDst[x] = 0.5f*l*l / (l*l + pSrc[x]*pSrc[x]);
}
return dst;
Mat dst(src.size(), src.type());
for (register int y = 0; y < src.rows; y++) {
float *pSrc = src.ptr<float>(y);
float *pDst = dst.ptr<float>(y);
for (register int x = 0; x < src.cols; x++)
pDst[x] = 0.5f*l*l / (l*l + pSrc[x]*pSrc[x]);
}
return dst;
}
void StereoVar::VariationalSolver(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level)
{
register int n, x, y;
float gl = 1, gr = 1, gu = 1, gd = 1, gc = 4;
Mat g_c, g_p;
Mat U;
u.copyTo(U);
register int n, x, y;
float gl = 1, gr = 1, gu = 1, gd = 1, gc = 4;
Mat g_c, g_p;
Mat U;
u.copyTo(U);
int N = nIt;
float l = lambda;
float Fi = fi;
int N = nIt;
float l = lambda;
float Fi = fi;
if (flags & USE_SMART_ID) {
double scale = pow(pyrScale, (double) level) * (1 + pyrScale);
N = (int) (N / scale);
}
if (flags & USE_SMART_ID) {
double scale = pow(pyrScale, (double) level) * (1 + pyrScale);
N = (int) (N / scale);
}
double scale = pow(pyrScale, (double) level);
Fi /= (float) scale;
l *= (float) scale;
double scale = pow(pyrScale, (double) level);
Fi /= (float) scale;
l *= (float) scale;
int width = u.cols - 1;
int height = u.rows - 1;
for (n = 0; n < N; n++) {
if (penalization != PENALIZATION_TICHONOV) {
Mat gradient = getGradient(U);
switch (penalization) {
case PENALIZATION_CHARBONNIER: g_c = getG_c(gradient, l); break;
case PENALIZATION_PERONA_MALIK: g_p = getG_p(gradient, l); break;
}
gradient.release();
}
for (y = 1 ; y < height; y++) {
float *pU = U.ptr<float>(y);
float *pUu = U.ptr<float>(y + 1);
float *pUd = U.ptr<float>(y - 1);
float *pu = u.ptr<float>(y);
float *pI1 = I1.ptr<float>(y);
float *pI2 = I2.ptr<float>(y);
float *pI2x = I2x.ptr<float>(y);
float *pG_c = NULL, *pG_cu = NULL, *pG_cd = NULL;
float *pG_p = NULL, *pG_pu = NULL, *pG_pd = NULL;
switch (penalization) {
case PENALIZATION_CHARBONNIER:
pG_c = g_c.ptr<float>(y);
pG_cu = g_c.ptr<float>(y + 1);
pG_cd = g_c.ptr<float>(y - 1);
break;
case PENALIZATION_PERONA_MALIK:
pG_p = g_p.ptr<float>(y);
pG_pu = g_p.ptr<float>(y + 1);
pG_pd = g_p.ptr<float>(y - 1);
break;
}
for (x = 1; x < width; x++) {
switch (penalization) {
case PENALIZATION_CHARBONNIER:
gc = pG_c[x];
gl = gc + pG_c[x - 1];
gr = gc + pG_c[x + 1];
gu = gc + pG_cu[x];
gd = gc + pG_cd[x];
gc = gl + gr + gu + gd;
break;
case PENALIZATION_PERONA_MALIK:
gc = pG_p[x];
gl = gc + pG_p[x - 1];
gr = gc + pG_p[x + 1];
gu = gc + pG_pu[x];
gd = gc + pG_pd[x];
gc = gl + gr + gu + gd;
break;
}
int width = u.cols - 1;
int height = u.rows - 1;
for (n = 0; n < N; n++) {
if (penalization != PENALIZATION_TICHONOV) {
Mat gradient = getGradient(U);
switch (penalization) {
case PENALIZATION_CHARBONNIER: g_c = getG_c(gradient, l); break;
case PENALIZATION_PERONA_MALIK: g_p = getG_p(gradient, l); break;
}
gradient.release();
}
for (y = 1 ; y < height; y++) {
float *pU = U.ptr<float>(y);
float *pUu = U.ptr<float>(y + 1);
float *pUd = U.ptr<float>(y - 1);
float *pu = u.ptr<float>(y);
float *pI1 = I1.ptr<float>(y);
float *pI2 = I2.ptr<float>(y);
float *pI2x = I2x.ptr<float>(y);
float *pG_c = NULL, *pG_cu = NULL, *pG_cd = NULL;
float *pG_p = NULL, *pG_pu = NULL, *pG_pd = NULL;
switch (penalization) {
case PENALIZATION_CHARBONNIER:
pG_c = g_c.ptr<float>(y);
pG_cu = g_c.ptr<float>(y + 1);
pG_cd = g_c.ptr<float>(y - 1);
break;
case PENALIZATION_PERONA_MALIK:
pG_p = g_p.ptr<float>(y);
pG_pu = g_p.ptr<float>(y + 1);
pG_pd = g_p.ptr<float>(y - 1);
break;
}
for (x = 1; x < width; x++) {
switch (penalization) {
case PENALIZATION_CHARBONNIER:
gc = pG_c[x];
gl = gc + pG_c[x - 1];
gr = gc + pG_c[x + 1];
gu = gc + pG_cu[x];
gd = gc + pG_cd[x];
gc = gl + gr + gu + gd;
break;
case PENALIZATION_PERONA_MALIK:
gc = pG_p[x];
gl = gc + pG_p[x - 1];
gr = gc + pG_p[x + 1];
gu = gc + pG_pu[x];
gd = gc + pG_pd[x];
gc = gl + gr + gu + gd;
break;
}
float fi = Fi;
if (maxDisp > minDisp) {
if (pU[x] > maxDisp * scale) {fi *= 1000; pU[x] = static_cast<float>(maxDisp * scale);}
if (pU[x] < minDisp * scale) {fi *= 1000; pU[x] = static_cast<float>(minDisp * scale);}
}
float _fi = Fi;
if (maxDisp > minDisp) {
if (pU[x] > maxDisp * scale) {_fi *= 1000; pU[x] = static_cast<float>(maxDisp * scale);}
if (pU[x] < minDisp * scale) {_fi *= 1000; pU[x] = static_cast<float>(minDisp * scale);}
}
int A = static_cast<int>(pU[x]);
int neg = 0; if (pU[x] <= 0) neg = -1;
int A = static_cast<int>(pU[x]);
int neg = 0; if (pU[x] <= 0) neg = -1;
if (x + A > width)
pu[x] = pU[width - A];
else if (x + A + neg < 0)
pu[x] = pU[- A + 2];
else {
pu[x] = A + (pI2x[x + A + neg] * (pI1[x] - pI2[x + A])
+ fi * (gr * pU[x + 1] + gl * pU[x - 1] + gu * pUu[x] + gd * pUd[x] - gc * A))
/ (pI2x[x + A + neg] * pI2x[x + A + neg] + gc * fi) ;
}
}// x
pu[0] = pu[1];
pu[width] = pu[width - 1];
}// y
for (x = 0; x <= width; x++) {
u.at<float>(0, x) = u.at<float>(1, x);
u.at<float>(height, x) = u.at<float>(height - 1, x);
}
u.copyTo(U);
if (!g_c.empty()) g_c.release();
if (!g_p.empty()) g_p.release();
}//n
if (x + A > width)
pu[x] = pU[width - A];
else if (x + A + neg < 0)
pu[x] = pU[- A + 2];
else {
pu[x] = A + (pI2x[x + A + neg] * (pI1[x] - pI2[x + A])
+ _fi * (gr * pU[x + 1] + gl * pU[x - 1] + gu * pUu[x] + gd * pUd[x] - gc * A))
/ (pI2x[x + A + neg] * pI2x[x + A + neg] + gc * _fi) ;
}
}// x
pu[0] = pu[1];
pu[width] = pu[width - 1];
}// y
for (x = 0; x <= width; x++) {
u.at<float>(0, x) = u.at<float>(1, x);
u.at<float>(height, x) = u.at<float>(height - 1, x);
}
u.copyTo(U);
if (!g_c.empty()) g_c.release();
if (!g_p.empty()) g_p.release();
}//n
}
void StereoVar::VCycle_MyFAS(Mat &I1, Mat &I2, Mat &I2x, Mat &_u, int level)
{
CvSize imgSize = _u.size();
CvSize frmSize = cvSize((int) (imgSize.width * pyrScale + 0.5), (int) (imgSize.height * pyrScale + 0.5));
Mat I1_h, I2_h, I2x_h, u_h, U, U_h;
CvSize imgSize = _u.size();
CvSize frmSize = cvSize((int) (imgSize.width * pyrScale + 0.5), (int) (imgSize.height * pyrScale + 0.5));
Mat I1_h, I2_h, I2x_h, u_h, U, U_h;
//PRE relaxation
VariationalSolver(I1, I2, I2x, _u, level);
//PRE relaxation
VariationalSolver(I1, I2, I2x, _u, level);
if (level >= levels - 1) return;
level ++;
if (level >= levels - 1) return;
level ++;
//scaling DOWN
resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
resize(_u, u_h, frmSize, 0, 0, INTER_AREA);
u_h.convertTo(u_h, u_h.type(), pyrScale);
I2x_h = diffX(I2_h);
//scaling DOWN
resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
resize(_u, u_h, frmSize, 0, 0, INTER_AREA);
u_h.convertTo(u_h, u_h.type(), pyrScale);
I2x_h = diffX(I2_h);
//Next level
U_h = u_h.clone();
VCycle_MyFAS(I1_h, I2_h, I2x_h, U_h, level);
//Next level
U_h = u_h.clone();
VCycle_MyFAS(I1_h, I2_h, I2x_h, U_h, level);
subtract(U_h, u_h, U_h);
U_h.convertTo(U_h, U_h.type(), 1.0 / pyrScale);
subtract(U_h, u_h, U_h);
U_h.convertTo(U_h, U_h.type(), 1.0 / pyrScale);
//scaling UP
resize(U_h, U, imgSize);
//scaling UP
resize(U_h, U, imgSize);
//correcting the solution
add(_u, U, _u);
//correcting the solution
add(_u, U, _u);
//POST relaxation
VariationalSolver(I1, I2, I2x, _u, level - 1);
//POST relaxation
VariationalSolver(I1, I2, I2x, _u, level - 1);
if (flags & USE_MEDIAN_FILTERING) medianBlur(_u, _u, 3);
if (flags & USE_MEDIAN_FILTERING) medianBlur(_u, _u, 3);
I1_h.release();
I2_h.release();
I2x_h.release();
u_h.release();
U.release();
U_h.release();
I1_h.release();
I2_h.release();
I2x_h.release();
u_h.release();
U.release();
U_h.release();
}
void StereoVar::FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level)
{
double scale = pow(pyrScale, (double) level);
CvSize frmSize = cvSize((int) (u.cols * scale + 0.5), (int) (u.rows * scale + 0.5));
Mat I1_h, I2_h, I2x_h, u_h;
double scale = pow(pyrScale, (double) level);
CvSize frmSize = cvSize((int) (u.cols * scale + 0.5), (int) (u.rows * scale + 0.5));
Mat I1_h, I2_h, I2x_h, u_h;
//scaling DOWN
resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
resize(u, u_h, frmSize, 0, 0, INTER_AREA);
u_h.convertTo(u_h, u_h.type(), scale);
I2x_h = diffX(I2_h);
//scaling DOWN
resize(I1, I1_h, frmSize, 0, 0, INTER_AREA);
resize(I2, I2_h, frmSize, 0, 0, INTER_AREA);
resize(u, u_h, frmSize, 0, 0, INTER_AREA);
u_h.convertTo(u_h, u_h.type(), scale);
I2x_h = diffX(I2_h);
switch (cycle) {
case CYCLE_O:
VariationalSolver(I1_h, I2_h, I2x_h, u_h, level);
break;
case CYCLE_V:
VCycle_MyFAS(I1_h, I2_h, I2x_h, u_h, level);
break;
}
switch (cycle) {
case CYCLE_O:
VariationalSolver(I1_h, I2_h, I2x_h, u_h, level);
break;
case CYCLE_V:
VCycle_MyFAS(I1_h, I2_h, I2x_h, u_h, level);
break;
}
u_h.convertTo(u_h, u_h.type(), 1.0 / scale);
u_h.convertTo(u_h, u_h.type(), 1.0 / scale);
//scaling UP
resize(u_h, u, u.size(), 0, 0, INTER_CUBIC);
//scaling UP
resize(u_h, u, u.size(), 0, 0, INTER_CUBIC);
I1_h.release();
I2_h.release();
I2x_h.release();
u_h.release();
I1_h.release();
I2_h.release();
I2x_h.release();
u_h.release();
level--;
if ((flags & USE_AUTO_PARAMS) && (level < levels / 3)) {
penalization = PENALIZATION_PERONA_MALIK;
fi *= 100;
flags -= USE_AUTO_PARAMS;
autoParams();
}
if (flags & USE_MEDIAN_FILTERING) medianBlur(u, u, 3);
if (level >= 0) FMG(I1, I2, I2x, u, level);
level--;
if ((flags & USE_AUTO_PARAMS) && (level < levels / 3)) {
penalization = PENALIZATION_PERONA_MALIK;
fi *= 100;
flags -= USE_AUTO_PARAMS;
autoParams();
}
if (flags & USE_MEDIAN_FILTERING) medianBlur(u, u, 3);
if (level >= 0) FMG(I1, I2, I2x, u, level);
}
void StereoVar::autoParams()
{
int maxD = MAX(labs(maxDisp), labs(minDisp));
int maxD = MAX(labs(maxDisp), labs(minDisp));
if (!maxD) pyrScale = 0.85;
else if (maxD < 8) pyrScale = 0.5;
else if (maxD < 64) pyrScale = 0.5 + static_cast<double>(maxD - 8) * 0.00625;
else pyrScale = 0.85;
if (!maxD) pyrScale = 0.85;
else if (maxD < 8) pyrScale = 0.5;
else if (maxD < 64) pyrScale = 0.5 + static_cast<double>(maxD - 8) * 0.00625;
else pyrScale = 0.85;
if (maxD) {
levels = 0;
while ( pow(pyrScale, levels) * maxD > 1.5) levels ++;
levels++;
}
if (maxD) {
levels = 0;
while ( pow(pyrScale, levels) * maxD > 1.5) levels ++;
levels++;
}
switch(penalization) {
case PENALIZATION_TICHONOV: cycle = CYCLE_V; break;
case PENALIZATION_CHARBONNIER: cycle = CYCLE_O; break;
case PENALIZATION_PERONA_MALIK: cycle = CYCLE_O; break;
}
switch(penalization) {
case PENALIZATION_TICHONOV: cycle = CYCLE_V; break;
case PENALIZATION_CHARBONNIER: cycle = CYCLE_O; break;
case PENALIZATION_PERONA_MALIK: cycle = CYCLE_O; break;
}
}
void StereoVar::operator ()( const Mat& left, const Mat& right, Mat& disp )
{
CV_Assert(left.size() == right.size() && left.type() == right.type());
CvSize imgSize = left.size();
int MaxD = MAX(labs(minDisp), labs(maxDisp));
int SignD = 1; if (MIN(minDisp, maxDisp) < 0) SignD = -1;
if (minDisp >= maxDisp) {MaxD = 256; SignD = 1;}
CV_Assert(left.size() == right.size() && left.type() == right.type());
CvSize imgSize = left.size();
int MaxD = MAX(labs(minDisp), labs(maxDisp));
int SignD = 1; if (MIN(minDisp, maxDisp) < 0) SignD = -1;
if (minDisp >= maxDisp) {MaxD = 256; SignD = 1;}
Mat u;
if ((flags & USE_INITIAL_DISPARITY) && (!disp.empty())) {
CV_Assert(disp.size() == left.size() && disp.type() == CV_8UC1);
disp.convertTo(u, CV_32FC1, static_cast<double>(SignD * MaxD) / 256);
} else {
u.create(imgSize, CV_32FC1);
u.setTo(0);
}
Mat u;
if ((flags & USE_INITIAL_DISPARITY) && (!disp.empty())) {
CV_Assert(disp.size() == left.size() && disp.type() == CV_8UC1);
disp.convertTo(u, CV_32FC1, static_cast<double>(SignD * MaxD) / 256);
} else {
u.create(imgSize, CV_32FC1);
u.setTo(0);
}
// Preprocessing
Mat leftgray, rightgray;
if (left.type() != CV_8UC1) {
cvtColor(left, leftgray, CV_BGR2GRAY);
cvtColor(right, rightgray, CV_BGR2GRAY);
} else {
left.copyTo(leftgray);
right.copyTo(rightgray);
}
if (flags & USE_EQUALIZE_HIST) {
equalizeHist(leftgray, leftgray);
equalizeHist(rightgray, rightgray);
}
if (poly_sigma > 0.0001) {
GaussianBlur(leftgray, leftgray, cvSize(poly_n, poly_n), poly_sigma);
GaussianBlur(rightgray, rightgray, cvSize(poly_n, poly_n), poly_sigma);
}
// Preprocessing
Mat leftgray, rightgray;
if (left.type() != CV_8UC1) {
cvtColor(left, leftgray, CV_BGR2GRAY);
cvtColor(right, rightgray, CV_BGR2GRAY);
} else {
left.copyTo(leftgray);
right.copyTo(rightgray);
}
if (flags & USE_EQUALIZE_HIST) {
equalizeHist(leftgray, leftgray);
equalizeHist(rightgray, rightgray);
}
if (poly_sigma > 0.0001) {
GaussianBlur(leftgray, leftgray, cvSize(poly_n, poly_n), poly_sigma);
GaussianBlur(rightgray, rightgray, cvSize(poly_n, poly_n), poly_sigma);
}
if (flags & USE_AUTO_PARAMS) {
penalization = PENALIZATION_TICHONOV;
autoParams();
}
if (flags & USE_AUTO_PARAMS) {
penalization = PENALIZATION_TICHONOV;
autoParams();
}
Mat I1, I2;
leftgray.convertTo(I1, CV_32FC1);
rightgray.convertTo(I2, CV_32FC1);
leftgray.release();
rightgray.release();
Mat I1, I2;
leftgray.convertTo(I1, CV_32FC1);
rightgray.convertTo(I2, CV_32FC1);
leftgray.release();
rightgray.release();
Mat I2x = diffX(I2);
Mat I2x = diffX(I2);
FMG(I1, I2, I2x, u, levels - 1);
FMG(I1, I2, I2x, u, levels - 1);
I1.release();
I2.release();
I2x.release();
I1.release();
I2.release();
I2x.release();
disp.create( left.size(), CV_8UC1 );
u = abs(u);
u.convertTo(disp, disp.type(), 256 / MaxD, 0);
disp.create( left.size(), CV_8UC1 );
u = abs(u);
u.convertTo(disp, disp.type(), 256 / MaxD, 0);
u.release();
u.release();
}
} // namespace

4
modules/contrib/test/test_precomp.hpp
View File

@ -1,3 +1,7 @@
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
#endif
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__

5
modules/core/CMakeLists.txt
View File

@ -6,8 +6,9 @@ if(HAVE_CUDA)
file(GLOB lib_cuda "src/cuda/*.cu")
source_group("Cuda" FILES "${lib_cuda}")
ocv_include_directories(${CUDA_INCLUDE_DIRS} "${OpenCV_SOURCE_DIR}/modules/gpu/src" "${OpenCV_SOURCE_DIR}/modules/gpu/src/cuda")
OCV_CUDA_COMPILE(cuda_objs ${lib_cuda})
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/src" "${OpenCV_SOURCE_DIR}/modules/gpu/src/cuda" ${CUDA_INCLUDE_DIRS})
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
ocv_cuda_compile(cuda_objs ${lib_cuda})
set(cuda_link_libs ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
else()

9
modules/core/include/opencv2/core/core.hpp
View File

@ -1299,6 +1299,7 @@ public:
GPU_MAT = 9 << KIND_SHIFT
};
_InputArray();
_InputArray(const Mat& m);
_InputArray(const MatExpr& expr);
template<typename _Tp> _InputArray(const _Tp* vec, int n);
@ -1328,6 +1329,10 @@ public:
virtual int channels(int i=-1) const;
virtual bool empty() const;
#ifdef OPENCV_CAN_BREAK_BINARY_COMPATIBILITY
virtual ~_InputArray();
#endif
int flags;
void* obj;
Size sz;
@ -1384,6 +1389,10 @@ public:
virtual void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
virtual void release() const;
virtual void clear() const;
#ifdef OPENCV_CAN_BREAK_BINARY_COMPATIBILITY
virtual ~_OutputArray();
#endif
};
typedef const _InputArray& InputArray;

22
modules/core/include/opencv2/core/core_c.h
View File

@ -666,7 +666,7 @@ CVAPI(int) cvSolveCubic( const CvMat* coeffs, CvMat* roots );
/* Finds all real and complex roots of a polynomial equation */
CVAPI(void) cvSolvePoly(const CvMat* coeffs, CvMat *roots2,
int maxiter CV_DEFAULT(20), int fig CV_DEFAULT(100));
int maxiter CV_DEFAULT(20), int fig CV_DEFAULT(100));
/****************************************************************************************\
* Matrix operations *
@ -1127,9 +1127,9 @@ CVAPI(void) cvSetRemove( CvSet* set_header, int index );
/* Returns a set element by index. If the element doesn't belong to the set,
NULL is returned */
CV_INLINE CvSetElem* cvGetSetElem( const CvSet* set_header, int index )
CV_INLINE CvSetElem* cvGetSetElem( const CvSet* set_header, int idx )
{
CvSetElem* elem = (CvSetElem*)cvGetSeqElem( (CvSeq*)set_header, index );
CvSetElem* elem = (CvSetElem*)cvGetSeqElem( (CvSeq*)set_header, idx );
return elem && CV_IS_SET_ELEM( elem ) ? elem : 0;
}
@ -1374,17 +1374,17 @@ CVAPI(int) cvInitLineIterator( const CvArr* image, CvPoint pt1, CvPoint pt2,
/* Font structure */
typedef struct CvFont
{
const char* nameFont; //Qt:nameFont
CvScalar color; //Qt:ColorFont -> cvScalar(blue_component, green_component, red\_component[, alpha_component])
int font_face; //Qt: bool italic /* =CV_FONT_* */
const int* ascii; /* font data and metrics */
const char* nameFont; //Qt:nameFont
CvScalar color; //Qt:ColorFont -> cvScalar(blue_component, green_component, red\_component[, alpha_component])
int font_face; //Qt: bool italic /* =CV_FONT_* */
const int* ascii; /* font data and metrics */
const int* greek;
const int* cyrillic;
float hscale, vscale;
float shear; /* slope coefficient: 0 - normal, >0 - italic */
int thickness; //Qt: weight /* letters thickness */
float dx; /* horizontal interval between letters */
int line_type; //Qt: PointSize
float shear; /* slope coefficient: 0 - normal, >0 - italic */
int thickness; //Qt: weight /* letters thickness */
float dx; /* horizontal interval between letters */
int line_type; //Qt: PointSize
}
CvFont;

5
modules/core/include/opencv2/core/eigen.hpp
View File

@ -48,6 +48,11 @@
#include "opencv2/core/core_c.h"
#include "opencv2/core/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
#endif
namespace cv
{

10
modules/core/include/opencv2/core/gpumat.hpp
View File

@ -366,12 +366,12 @@ namespace cv { namespace gpu
return m;
}
inline void GpuMat::assignTo(GpuMat& m, int type) const
inline void GpuMat::assignTo(GpuMat& m, int _type) const
{
if (type < 0)
if (_type < 0)
m = *this;
else
convertTo(m, type);
convertTo(m, _type);
}
inline size_t GpuMat::step1() const
@ -434,9 +434,9 @@ namespace cv { namespace gpu
create(size_.height, size_.width, type_);
}
inline GpuMat GpuMat::operator()(Range rowRange, Range colRange) const
inline GpuMat GpuMat::operator()(Range _rowRange, Range _colRange) const
{
return GpuMat(*this, rowRange, colRange);
return GpuMat(*this, _rowRange, _colRange);
}
inline GpuMat GpuMat::operator()(Rect roi) const

307
modules/core/include/opencv2/core/internal.hpp
View File

@ -60,34 +60,34 @@
#endif
#if defined WIN32 || defined WINCE
#ifndef _WIN32_WINNT // This is needed for the declaration of TryEnterCriticalSection in winbase.h with Visual Studio 2005 (and older?)
#define _WIN32_WINNT 0x0400 // http://msdn.microsoft.com/en-us/library/ms686857(VS.85).aspx
#endif
#include <windows.h>
#undef small
#undef min
#undef max
# ifndef _WIN32_WINNT // This is needed for the declaration of TryEnterCriticalSection in winbase.h with Visual Studio 2005 (and older?)
# define _WIN32_WINNT 0x0400 // http://msdn.microsoft.com/en-us/library/ms686857(VS.85).aspx
# endif
# include <windows.h>
# undef small
# undef min
# undef max
#else
#include <pthread.h>
# include <pthread.h>
#endif
#ifdef __BORLANDC__
#ifndef WIN32
#define WIN32
#endif
#ifndef _WIN32
#define _WIN32
#endif
#define CV_DLL
#undef _CV_ALWAYS_PROFILE_
#define _CV_ALWAYS_NO_PROFILE_
# ifndef WIN32
# define WIN32
# endif
# ifndef _WIN32
# define _WIN32
# endif
# define CV_DLL
# undef _CV_ALWAYS_PROFILE_
# define _CV_ALWAYS_NO_PROFILE_
#endif
#ifndef FALSE
#define FALSE 0
# define FALSE 0
#endif
#ifndef TRUE
#define TRUE 1
# define TRUE 1
#endif
#define __BEGIN__ __CV_BEGIN__
@ -95,7 +95,7 @@
#define EXIT __CV_EXIT__
#ifdef HAVE_IPP
#include "ipp.h"
# include "ipp.h"
CV_INLINE IppiSize ippiSize(int width, int height)
{
@ -104,137 +104,132 @@ CV_INLINE IppiSize ippiSize(int width, int height)
}
#endif
#if defined __SSE2__ || _MSC_VER >= 1300
#include "emmintrin.h"
#define CV_SSE 1
#define CV_SSE2 1
#if defined __SSE3__ || _MSC_VER >= 1500
#include "pmmintrin.h"
#define CV_SSE3 1
#endif
#if defined __SSSE3__
#include "tmmintrin.h"
#define CV_SSSE3 1
#endif
#if defined __SSE2__ || (defined _MSC_VER && _MSC_VER >= 1300)
# include "emmintrin.h"
# define CV_SSE 1
# define CV_SSE2 1
# if defined __SSE3__ || (defined _MSC_VER && _MSC_VER >= 1500)
# include "pmmintrin.h"
# define CV_SSE3 1
# else
# define CV_SSE3 0
# endif
# if defined __SSSE3__
# include "tmmintrin.h"
# define CV_SSSE3 1
# else
# define CV_SSSE3 0
# endif
#else
#define CV_SSE 0
#define CV_SSE2 0
#define CV_SSE3 0
#define CV_SSSE3 0
# define CV_SSE 0
# define CV_SSE2 0
# define CV_SSE3 0
# define CV_SSSE3 0
#endif
#if defined ANDROID && defined __ARM_NEON__ && defined __GNUC__
#include "arm_neon.h"
#define CV_NEON 1
#if defined ANDROID && defined __ARM_NEON__
# include "arm_neon.h"
# define CV_NEON 1
#define CPU_HAS_NEON_FEATURE (true)
# define CPU_HAS_NEON_FEATURE (true)
//TODO: make real check using stuff from "cpu-features.h"
//((bool)android_getCpuFeatures() & ANDROID_CPU_ARM_FEATURE_NEON)
#else
#define CV_NEON 0
#define CPU_HAS_NEON_FEATURE (false)
#endif
#ifdef CV_ICC
#define CV_ENABLE_UNROLLED 0
#else
#define CV_ENABLE_UNROLLED 1
# define CV_NEON 0
# define CPU_HAS_NEON_FEATURE (false)
#endif
#ifndef IPPI_CALL
#define IPPI_CALL(func) CV_Assert((func) >= 0)
# define IPPI_CALL(func) CV_Assert((func) >= 0)
#endif
#ifdef HAVE_TBB
#include "tbb/tbb_stddef.h"
#if TBB_VERSION_MAJOR*100 + TBB_VERSION_MINOR >= 202
#include "tbb/tbb.h"
#include "tbb/task.h"
#undef min
#undef max
#else
#undef HAVE_TBB
#endif
# include "tbb/tbb_stddef.h"
# if TBB_VERSION_MAJOR*100 + TBB_VERSION_MINOR >= 202
# include "tbb/tbb.h"
# include "tbb/task.h"
# undef min
# undef max
# else
# undef HAVE_TBB
# endif
#endif
#ifdef HAVE_EIGEN
#include <Eigen/Core>
#include "opencv2/core/eigen.hpp"
# include <Eigen/Core>
# include "opencv2/core/eigen.hpp"
#endif
#ifdef __cplusplus
namespace cv
{
#ifdef HAVE_TBB
namespace cv
typedef tbb::blocked_range<int> BlockedRange;
template<typename Body> static inline
void parallel_for( const BlockedRange& range, const Body& body )
{
typedef tbb::blocked_range<int> BlockedRange;
template<typename Body> static inline
void parallel_for( const BlockedRange& range, const Body& body )
{
tbb::parallel_for(range, body);
}
template<typename Iterator, typename Body> static inline
void parallel_do( Iterator first, Iterator last, const Body& body )
{
tbb::parallel_do(first, last, body);
}
typedef tbb::split Split;
template<typename Body> static inline
void parallel_reduce( const BlockedRange& range, Body& body )
{
tbb::parallel_reduce(range, body);
}
typedef tbb::concurrent_vector<Rect> ConcurrentRectVector;
typedef tbb::concurrent_vector<double> ConcurrentDoubleVector;
tbb::parallel_for(range, body);
}
#else
namespace cv
template<typename Iterator, typename Body> static inline
void parallel_do( Iterator first, Iterator last, const Body& body )
{
class BlockedRange
{
public:
BlockedRange() : _begin(0), _end(0), _grainsize(0) {}
BlockedRange(int b, int e, int g=1) : _begin(b), _end(e), _grainsize(g) {}
int begin() const { return _begin; }
int end() const { return _end; }
int grainsize() const { return _grainsize; }
tbb::parallel_do(first, last, body);
}
protected:
int _begin, _end, _grainsize;
};
typedef tbb::split Split;
template<typename Body> static inline
void parallel_for( const BlockedRange& range, const Body& body )
{
body(range);
}
typedef std::vector<Rect> ConcurrentRectVector;
typedef std::vector<double> ConcurrentDoubleVector;
template<typename Body> static inline
void parallel_reduce( const BlockedRange& range, Body& body )
{
tbb::parallel_reduce(range, body);
}
template<typename Iterator, typename Body> static inline
void parallel_do( Iterator first, Iterator last, const Body& body )
{
for( ; first != last; ++first )
body(*first);
}
typedef tbb::concurrent_vector<Rect> ConcurrentRectVector;
typedef tbb::concurrent_vector<double> ConcurrentDoubleVector;
#else
class BlockedRange
{
public:
BlockedRange() : _begin(0), _end(0), _grainsize(0) {}
BlockedRange(int b, int e, int g=1) : _begin(b), _end(e), _grainsize(g) {}
int begin() const { return _begin; }
int end() const { return _end; }
int grainsize() const { return _grainsize; }
class Split {};
protected:
int _begin, _end, _grainsize;
};
template<typename Body> static inline
void parallel_reduce( const BlockedRange& range, Body& body )
{
body(range);
}
template<typename Body> static inline
void parallel_for( const BlockedRange& range, const Body& body )
{
body(range);
}
typedef std::vector<Rect> ConcurrentRectVector;
typedef std::vector<double> ConcurrentDoubleVector;
template<typename Iterator, typename Body> static inline
void parallel_do( Iterator first, Iterator last, const Body& body )
{
for( ; first != last; ++first )
body(*first);
}
class Split {};
template<typename Body> static inline
void parallel_reduce( const BlockedRange& range, Body& body )
{
body(range);
}
#endif
} //namespace cv
#define CV_INIT_ALGORITHM(classname, algname, memberinit) \
#define CV_INIT_ALGORITHM(classname, algname, memberinit) \
static Algorithm* create##classname() \
{ \
return new classname; \
@ -261,7 +256,7 @@ CV_INLINE IppiSize ippiSize(int width, int height)
return &classname##_info(); \
}
#endif
#endif //__cplusplus
/* maximal size of vector to run matrix operations on it inline (i.e. w/o ipp calls) */
#define CV_MAX_INLINE_MAT_OP_SIZE 10
@ -305,9 +300,9 @@ CV_INLINE IppiSize ippiSize(int width, int height)
#define CV_MAX_STRLEN 1024
#if 0 /*def CV_CHECK_FOR_NANS*/
#define CV_CHECK_NANS( arr ) cvCheckArray((arr))
# define CV_CHECK_NANS( arr ) cvCheckArray((arr))
#else
#define CV_CHECK_NANS( arr )
# define CV_CHECK_NANS( arr )
#endif
/****************************************************************************************\
@ -316,38 +311,38 @@ CV_INLINE IppiSize ippiSize(int width, int height)
/* get alloca declaration */
#ifdef __GNUC__
#undef alloca
#define alloca __builtin_alloca
#define CV_HAVE_ALLOCA 1
# undef alloca
# define alloca __builtin_alloca
# define CV_HAVE_ALLOCA 1
#elif defined WIN32 || defined _WIN32 || \
defined WINCE || defined _MSC_VER || defined __BORLANDC__
#include <malloc.h>
#define CV_HAVE_ALLOCA 1
# include <malloc.h>
# define CV_HAVE_ALLOCA 1
#elif defined HAVE_ALLOCA_H
#include <alloca.h>
#define CV_HAVE_ALLOCA 1
# include <alloca.h>
# define CV_HAVE_ALLOCA 1
#elif defined HAVE_ALLOCA
#include <stdlib.h>
#define CV_HAVE_ALLOCA 1
# include <stdlib.h>
# define CV_HAVE_ALLOCA 1
#else
#undef CV_HAVE_ALLOCA
# undef CV_HAVE_ALLOCA
#endif
#ifdef __GNUC__
#define CV_DECL_ALIGNED(x) __attribute__ ((aligned (x)))
# define CV_DECL_ALIGNED(x) __attribute__ ((aligned (x)))
#elif defined _MSC_VER
#define CV_DECL_ALIGNED(x) __declspec(align(x))
# define CV_DECL_ALIGNED(x) __declspec(align(x))
#else
#define CV_DECL_ALIGNED(x)
# define CV_DECL_ALIGNED(x)
#endif
#if CV_HAVE_ALLOCA
/* ! DO NOT make it an inline function */
#define cvStackAlloc(size) cvAlignPtr( alloca((size) + CV_MALLOC_ALIGN), CV_MALLOC_ALIGN )
# define cvStackAlloc(size) cvAlignPtr( alloca((size) + CV_MALLOC_ALIGN), CV_MALLOC_ALIGN )
#endif
#ifndef CV_IMPL
#define CV_IMPL CV_EXTERN_C
# define CV_IMPL CV_EXTERN_C
#endif
#define CV_DBG_BREAK() { volatile int* crashMe = 0; *crashMe = 0; }
@ -687,25 +682,25 @@ typedef enum CvStatus
CV_UNSUPPORTED_DEPTH_ERR = -101,
CV_UNSUPPORTED_FORMAT_ERR = -100,
CV_BADARG_ERR = -49, //ipp comp
CV_NOTDEFINED_ERR = -48, //ipp comp
CV_BADARG_ERR = -49, //ipp comp
CV_NOTDEFINED_ERR = -48, //ipp comp
CV_BADCHANNELS_ERR = -47, //ipp comp
CV_BADRANGE_ERR = -44, //ipp comp
CV_BADSTEP_ERR = -29, //ipp comp
CV_BADCHANNELS_ERR = -47, //ipp comp
CV_BADRANGE_ERR = -44, //ipp comp
CV_BADSTEP_ERR = -29, //ipp comp
CV_BADFLAG_ERR = -12,
CV_DIV_BY_ZERO_ERR = -11, //ipp comp
CV_BADCOEF_ERR = -10,
CV_BADFLAG_ERR = -12,
CV_DIV_BY_ZERO_ERR = -11, //ipp comp
CV_BADCOEF_ERR = -10,
CV_BADFACTOR_ERR = -7,
CV_BADPOINT_ERR = -6,
CV_BADSCALE_ERR = -4,
CV_OUTOFMEM_ERR = -3,
CV_NULLPTR_ERR = -2,
CV_BADSIZE_ERR = -1,
CV_NO_ERR = 0,
CV_OK = CV_NO_ERR
CV_BADFACTOR_ERR = -7,
CV_BADPOINT_ERR = -6,
CV_BADSCALE_ERR = -4,
CV_OUTOFMEM_ERR = -3,
CV_NULLPTR_ERR = -2,
CV_BADSIZE_ERR = -1,
CV_NO_ERR = 0,
CV_OK = CV_NO_ERR
}
CvStatus;
@ -720,8 +715,7 @@ CvFuncTable;
typedef struct CvBigFuncTable
{
void* fn_2d[CV_DEPTH_MAX*4];
}
CvBigFuncTable;
} CvBigFuncTable;
#define CV_INIT_FUNC_TAB( tab, FUNCNAME, FLAG ) \
(tab).fn_2d[CV_8U] = (void*)FUNCNAME##_8u##FLAG; \
@ -732,6 +726,7 @@ CvBigFuncTable;
(tab).fn_2d[CV_32F] = (void*)FUNCNAME##_32f##FLAG; \
(tab).fn_2d[CV_64F] = (void*)FUNCNAME##_64f##FLAG
#ifdef __cplusplus
//! OpenGL extension table
class CV_EXPORTS CvOpenGlFuncTab
{
@ -764,4 +759,6 @@ CV_EXPORTS bool icvCheckGlError(const char* file, const int line, const char* fu
#define CV_CheckGlError() CV_DbgAssert( (::icvCheckGlError(__FILE__, __LINE__)) )
#endif
#endif
#endif //__cplusplus
#endif // __OPENCV_CORE_INTERNAL_HPP__

34
modules/core/include/opencv2/core/mat.hpp
View File

@ -336,12 +336,12 @@ inline Mat Mat::clone() const
return m;
}
inline void Mat::assignTo( Mat& m, int type ) const
inline void Mat::assignTo( Mat& m, int _type ) const
{
if( type < 0 )
if( _type < 0 )
m = *this;
else
convertTo(m, type);
convertTo(m, _type);
}
inline void Mat::create(int _rows, int _cols, int _type)
@ -370,9 +370,9 @@ inline void Mat::release()
refcount = 0;
}
inline Mat Mat::operator()( Range rowRange, Range colRange ) const
inline Mat Mat::operator()( Range _rowRange, Range _colRange ) const
{
return Mat(*this, rowRange, colRange);
return Mat(*this, _rowRange, _colRange);
}
inline Mat Mat::operator()( const Rect& roi ) const
@ -682,11 +682,11 @@ template<typename _Tp, int m, int n> inline Mat::operator Matx<_Tp, m, n>() cons
template<typename _Tp> inline void Mat::push_back(const _Tp& elem)
{
if( !data )
{
*this = Mat(1, 1, DataType<_Tp>::type, (void*)&elem).clone();
return;
}
CV_Assert(DataType<_Tp>::type == type() && cols == 1
{
*this = Mat(1, 1, DataType<_Tp>::type, (void*)&elem).clone();
return;
}
CV_Assert(DataType<_Tp>::type == type() && cols == 1
/* && dims == 2 (cols == 1 implies dims == 2) */);
uchar* tmp = dataend + step[0];
if( !isSubmatrix() && isContinuous() && tmp <= datalimit )
@ -829,8 +829,8 @@ template<typename _Tp> inline Mat_<_Tp>::Mat_(const Mat_& m)
template<typename _Tp> inline Mat_<_Tp>::Mat_(int _rows, int _cols, _Tp* _data, size_t steps)
: Mat(_rows, _cols, DataType<_Tp>::type, _data, steps) {}
template<typename _Tp> inline Mat_<_Tp>::Mat_(const Mat_& m, const Range& rowRange, const Range& colRange)
: Mat(m, rowRange, colRange) {}
template<typename _Tp> inline Mat_<_Tp>::Mat_(const Mat_& m, const Range& _rowRange, const Range& _colRange)
: Mat(m, _rowRange, _colRange) {}
template<typename _Tp> inline Mat_<_Tp>::Mat_(const Mat_& m, const Rect& roi)
: Mat(m, roi) {}
@ -967,8 +967,8 @@ template<typename _Tp> inline size_t Mat_<_Tp>::step1(int i) const { return step
template<typename _Tp> inline Mat_<_Tp>& Mat_<_Tp>::adjustROI( int dtop, int dbottom, int dleft, int dright )
{ return (Mat_<_Tp>&)(Mat::adjustROI(dtop, dbottom, dleft, dright)); }
template<typename _Tp> inline Mat_<_Tp> Mat_<_Tp>::operator()( const Range& rowRange, const Range& colRange ) const
{ return Mat_<_Tp>(*this, rowRange, colRange); }
template<typename _Tp> inline Mat_<_Tp> Mat_<_Tp>::operator()( const Range& _rowRange, const Range& _colRange ) const
{ return Mat_<_Tp>(*this, _rowRange, _colRange); }
template<typename _Tp> inline Mat_<_Tp> Mat_<_Tp>::operator()( const Rect& roi ) const
{ return Mat_<_Tp>(*this, roi); }
@ -2123,12 +2123,12 @@ inline SparseMat SparseMat::clone() const
}
inline void SparseMat::assignTo( SparseMat& m, int type ) const
inline void SparseMat::assignTo( SparseMat& m, int _type ) const
{
if( type < 0 )
if( _type < 0 )
m = *this;
else
convertTo(m, type);
convertTo(m, _type);
}
inline void SparseMat::addref()

527
modules/core/include/opencv2/core/opengl_interop.hpp
View File

@ -49,280 +49,285 @@
namespace cv
{
//! Smart pointer for OpenGL buffer memory with reference counting.
class CV_EXPORTS GlBuffer
//! Smart pointer for OpenGL buffer memory with reference counting.
class CV_EXPORTS GlBuffer
{
public:
enum Usage
{
public:
enum Usage
{
ARRAY_BUFFER = 0x8892, // buffer will use for OpenGL arrays (vertices, colors, normals, etc)
TEXTURE_BUFFER = 0x88EC // buffer will ise for OpenGL textures
};
//! create empty buffer
explicit GlBuffer(Usage usage);
//! create buffer
GlBuffer(int rows, int cols, int type, Usage usage);
GlBuffer(Size size, int type, Usage usage);
//! copy from host/device memory
GlBuffer(InputArray mat, Usage usage);
void create(int rows, int cols, int type, Usage usage);
inline void create(Size size, int type, Usage usage) { create(size.height, size.width, type, usage); }
inline void create(int rows, int cols, int type) { create(rows, cols, type, usage()); }
inline void create(Size size, int type) { create(size.height, size.width, type, usage()); }
void release();
//! copy from host/device memory
void copyFrom(InputArray mat);
void bind() const;
void unbind() const;
//! map to host memory
Mat mapHost();
void unmapHost();
//! map to device memory
gpu::GpuMat mapDevice();
void unmapDevice();
inline int rows() const { return rows_; }
inline int cols() const { return cols_; }
inline Size size() const { return Size(cols_, rows_); }
inline bool empty() const { return rows_ == 0 || cols_ == 0; }
inline int type() const { return type_; }
inline int depth() const { return CV_MAT_DEPTH(type_); }
inline int channels() const { return CV_MAT_CN(type_); }
inline int elemSize() const { return CV_ELEM_SIZE(type_); }
inline int elemSize1() const { return CV_ELEM_SIZE1(type_); }
inline Usage usage() const { return usage_; }
class Impl;
private:
int rows_;
int cols_;
int type_;
Usage usage_;
Ptr<Impl> impl_;
ARRAY_BUFFER = 0x8892, // buffer will use for OpenGL arrays (vertices, colors, normals, etc)
TEXTURE_BUFFER = 0x88EC // buffer will ise for OpenGL textures
};
template <> CV_EXPORTS void Ptr<GlBuffer::Impl>::delete_obj();
//! create empty buffer
explicit GlBuffer(Usage usage);
//! Smart pointer for OpenGL 2d texture memory with reference counting.
class CV_EXPORTS GlTexture
//! create buffer
GlBuffer(int rows, int cols, int type, Usage usage);
GlBuffer(Size size, int type, Usage usage);
//! copy from host/device memory
GlBuffer(InputArray mat, Usage usage);
void create(int rows, int cols, int type, Usage usage);
void create(Size size, int type, Usage usage);
void create(int rows, int cols, int type);
void create(Size size, int type);
void release();
//! copy from host/device memory
void copyFrom(InputArray mat);
void bind() const;
void unbind() const;
//! map to host memory
Mat mapHost();
void unmapHost();
//! map to device memory
gpu::GpuMat mapDevice();
void unmapDevice();
inline int rows() const { return rows_; }
inline int cols() const { return cols_; }
inline Size size() const { return Size(cols_, rows_); }
inline bool empty() const { return rows_ == 0 || cols_ == 0; }
inline int type() const { return type_; }
inline int depth() const { return CV_MAT_DEPTH(type_); }
inline int channels() const { return CV_MAT_CN(type_); }
inline int elemSize() const { return CV_ELEM_SIZE(type_); }
inline int elemSize1() const { return CV_ELEM_SIZE1(type_); }
inline Usage usage() const { return usage_; }
class Impl;
private:
int rows_;
int cols_;
int type_;
Usage usage_;
Ptr<Impl> impl_;
};
template <> CV_EXPORTS void Ptr<GlBuffer::Impl>::delete_obj();
//! Smart pointer for OpenGL 2d texture memory with reference counting.
class CV_EXPORTS GlTexture
{
public:
//! create empty texture
GlTexture();
//! create texture
GlTexture(int rows, int cols, int type);
GlTexture(Size size, int type);
//! copy from host/device memory
explicit GlTexture(InputArray mat, bool bgra = true);
void create(int rows, int cols, int type);
void create(Size size, int type);
void release();
//! copy from host/device memory
void copyFrom(InputArray mat, bool bgra = true);
void bind() const;
void unbind() const;
inline int rows() const { return rows_; }
inline int cols() const { return cols_; }
inline Size size() const { return Size(cols_, rows_); }
inline bool empty() const { return rows_ == 0 || cols_ == 0; }
inline int type() const { return type_; }
inline int depth() const { return CV_MAT_DEPTH(type_); }
inline int channels() const { return CV_MAT_CN(type_); }
inline int elemSize() const { return CV_ELEM_SIZE(type_); }
inline int elemSize1() const { return CV_ELEM_SIZE1(type_); }
class Impl;
private:
int rows_;
int cols_;
int type_;
Ptr<Impl> impl_;
GlBuffer buf_;
};
template <> CV_EXPORTS void Ptr<GlTexture::Impl>::delete_obj();
//! OpenGL Arrays
class CV_EXPORTS GlArrays
{
public:
inline GlArrays()
: vertex_(GlBuffer::ARRAY_BUFFER), color_(GlBuffer::ARRAY_BUFFER), bgra_(true), normal_(GlBuffer::ARRAY_BUFFER), texCoord_(GlBuffer::ARRAY_BUFFER)
{
public:
//! create empty texture
GlTexture();
//! create texture
GlTexture(int rows, int cols, int type);
GlTexture(Size size, int type);
//! copy from host/device memory
explicit GlTexture(InputArray mat, bool bgra = true);
void create(int rows, int cols, int type);
inline void create(Size size, int type) { create(size.height, size.width, type); }
void release();
//! copy from host/device memory
void copyFrom(InputArray mat, bool bgra = true);
void bind() const;
void unbind() const;
inline int rows() const { return rows_; }
inline int cols() const { return cols_; }
inline Size size() const { return Size(cols_, rows_); }
inline bool empty() const { return rows_ == 0 || cols_ == 0; }
inline int type() const { return type_; }
inline int depth() const { return CV_MAT_DEPTH(type_); }
inline int channels() const { return CV_MAT_CN(type_); }
inline int elemSize() const { return CV_ELEM_SIZE(type_); }
inline int elemSize1() const { return CV_ELEM_SIZE1(type_); }
class Impl;
private:
int rows_;
int cols_;
int type_;
Ptr<Impl> impl_;
GlBuffer buf_;
};
template <> CV_EXPORTS void Ptr<GlTexture::Impl>::delete_obj();
//! OpenGL Arrays
class CV_EXPORTS GlArrays
{
public:
inline GlArrays()
: vertex_(GlBuffer::ARRAY_BUFFER), color_(GlBuffer::ARRAY_BUFFER), bgra_(true), normal_(GlBuffer::ARRAY_BUFFER), texCoord_(GlBuffer::ARRAY_BUFFER)
{
}
void setVertexArray(InputArray vertex);
inline void resetVertexArray() { vertex_.release(); }
void setColorArray(InputArray color, bool bgra = true);
inline void resetColorArray() { color_.release(); }
void setNormalArray(InputArray normal);
inline void resetNormalArray() { normal_.release(); }
void setTexCoordArray(InputArray texCoord);
inline void resetTexCoordArray() { texCoord_.release(); }
void bind() const;
void unbind() const;
inline int rows() const { return vertex_.rows(); }
inline int cols() const { return vertex_.cols(); }
inline Size size() const { return vertex_.size(); }
inline bool empty() const { return vertex_.empty(); }
private:
GlBuffer vertex_;
GlBuffer color_;
bool bgra_;
GlBuffer normal_;
GlBuffer texCoord_;
};
//! OpenGL Font
class CV_EXPORTS GlFont
{
public:
enum Weight
{
WEIGHT_LIGHT = 300,
WEIGHT_NORMAL = 400,
WEIGHT_SEMIBOLD = 600,
WEIGHT_BOLD = 700,
WEIGHT_BLACK = 900
};
enum Style
{
STYLE_NORMAL = 0,
STYLE_ITALIC = 1,
STYLE_UNDERLINE = 2
};
static Ptr<GlFont> get(const std::string& family, int height = 12, Weight weight = WEIGHT_NORMAL, Style style = STYLE_NORMAL);
void draw(const char* str, int len) const;
inline const std::string& family() const { return family_; }
inline int height() const { return height_; }
inline Weight weight() const { return weight_; }
inline Style style() const { return style_; }
private:
GlFont(const std::string& family, int height, Weight weight, Style style);
std::string family_;
int height_;
Weight weight_;
Style style_;
unsigned int base_;
GlFont(const GlFont&);
GlFont& operator =(const GlFont&);
};
//! render functions
//! render texture rectangle in window
CV_EXPORTS void render(const GlTexture& 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));
//! render mode
namespace RenderMode {
enum {
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
};
}
//! render OpenGL arrays
CV_EXPORTS void render(const GlArrays& arr, int mode = RenderMode::POINTS, Scalar color = Scalar::all(255));
void setVertexArray(InputArray vertex);
inline void resetVertexArray() { vertex_.release(); }
CV_EXPORTS void render(const std::string& str, const Ptr<GlFont>& font, Scalar color, Point2d pos);
void setColorArray(InputArray color, bool bgra = true);
inline void resetColorArray() { color_.release(); }
//! OpenGL camera
class CV_EXPORTS GlCamera
void setNormalArray(InputArray normal);
inline void resetNormalArray() { normal_.release(); }
void setTexCoordArray(InputArray texCoord);
inline void resetTexCoordArray() { texCoord_.release(); }
void bind() const;
void unbind() const;
inline int rows() const { return vertex_.rows(); }
inline int cols() const { return vertex_.cols(); }
inline Size size() const { return vertex_.size(); }
inline bool empty() const { return vertex_.empty(); }
private:
GlBuffer vertex_;
GlBuffer color_;
bool bgra_;
GlBuffer normal_;
GlBuffer texCoord_;
};
//! OpenGL Font
class CV_EXPORTS GlFont
{
public:
enum Weight
{
public:
GlCamera();
void lookAt(Point3d eye, Point3d center, Point3d up);
void setCameraPos(Point3d pos, double yaw, double pitch, double roll);
void setScale(Point3d scale);
void setProjectionMatrix(const Mat& projectionMatrix, bool transpose = true);
void setPerspectiveProjection(double fov, double aspect, double zNear, double zFar);
void setOrthoProjection(double left, double right, double bottom, double top, double zNear, double zFar);
void setupProjectionMatrix() const;
void setupModelViewMatrix() const;
private:
Point3d eye_;
Point3d center_;
Point3d up_;
Point3d pos_;
double yaw_;
double pitch_;
double roll_;
bool useLookAtParams_;
Point3d scale_;
Mat projectionMatrix_;
double fov_;
double aspect_;
double left_;
double right_;
double bottom_;
double top_;
double zNear_;
double zFar_;
bool perspectiveProjection_;
WEIGHT_LIGHT = 300,
WEIGHT_NORMAL = 400,
WEIGHT_SEMIBOLD = 600,
WEIGHT_BOLD = 700,
WEIGHT_BLACK = 900
};
namespace gpu
enum Style
{
//! set a CUDA device to use OpenGL interoperability
CV_EXPORTS void setGlDevice(int device = 0);
}
STYLE_NORMAL = 0,
STYLE_ITALIC = 1,
STYLE_UNDERLINE = 2
};
static Ptr<GlFont> get(const std::string& family, int height = 12, Weight weight = WEIGHT_NORMAL, Style style = STYLE_NORMAL);
void draw(const char* str, int len) const;
inline const std::string& family() const { return family_; }
inline int height() const { return height_; }
inline Weight weight() const { return weight_; }
inline Style style() const { return style_; }
private:
GlFont(const std::string& family, int height, Weight weight, Style style);
std::string family_;
int height_;
Weight weight_;
Style style_;
unsigned int base_;
GlFont(const GlFont&);
GlFont& operator =(const GlFont&);
};
//! render functions
//! render texture rectangle in window
CV_EXPORTS void render(const GlTexture& 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));
//! render mode
namespace RenderMode {
enum {
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
};
}
//! render OpenGL arrays
CV_EXPORTS void render(const GlArrays& arr, int mode = RenderMode::POINTS, Scalar color = Scalar::all(255));
CV_EXPORTS void render(const std::string& str, const Ptr<GlFont>& font, Scalar color, Point2d pos);
//! OpenGL camera
class CV_EXPORTS GlCamera
{
public:
GlCamera();
void lookAt(Point3d eye, Point3d center, Point3d up);
void setCameraPos(Point3d pos, double yaw, double pitch, double roll);
void setScale(Point3d scale);
void setProjectionMatrix(const Mat& projectionMatrix, bool transpose = true);
void setPerspectiveProjection(double fov, double aspect, double zNear, double zFar);
void setOrthoProjection(double left, double right, double bottom, double top, double zNear, double zFar);
void setupProjectionMatrix() const;
void setupModelViewMatrix() const;
private:
Point3d eye_;
Point3d center_;
Point3d up_;
Point3d pos_;
double yaw_;
double pitch_;
double roll_;
bool useLookAtParams_;
Point3d scale_;
Mat projectionMatrix_;
double fov_;
double aspect_;
double left_;
double right_;
double bottom_;
double top_;
double zNear_;
double zFar_;
bool perspectiveProjection_;
};
inline void GlBuffer::create(Size _size, int _type, Usage _usage) { create(_size.height, _size.width, _type, _usage); }
inline void GlBuffer::create(int _rows, int _cols, int _type) { create(_rows, _cols, _type, usage()); }
inline void GlBuffer::create(Size _size, int _type) { create(_size.height, _size.width, _type, usage()); }
inline void GlTexture::create(Size _size, int _type) { create(_size.height, _size.width, _type); }
namespace gpu
{
//! set a CUDA device to use OpenGL interoperability
CV_EXPORTS void setGlDevice(int device = 0);
}
} // namespace cv
#endif // __cplusplus

34
modules/core/include/opencv2/core/operations.hpp
View File

@ -984,13 +984,13 @@ _AccTp normL2Sqr(const _Tp* a, const _Tp* b, int n)
#if CV_ENABLE_UNROLLED
for(; i <= n - 4; i += 4 )
{
_AccTp v0 = a[i] - b[i], v1 = a[i+1] - b[i+1], v2 = a[i+2] - b[i+2], v3 = a[i+3] - b[i+3];
_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]);
_AccTp v = _AccTp(a[i] - b[i]);
s += v*v;
}
return s;
@ -1024,13 +1024,13 @@ _AccTp normL1(const _Tp* a, const _Tp* b, int n)
#if CV_ENABLE_UNROLLED
for(; i <= n - 4; i += 4 )
{
_AccTp v0 = a[i] - b[i], v1 = a[i+1] - b[i+1], v2 = a[i+2] - b[i+2], v3 = a[i+3] - b[i+3];
_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]);
_AccTp v = _AccTp(a[i] - b[i]);
s += std::abs(v);
}
return s;
@ -2616,20 +2616,20 @@ template<typename _Tp> inline void Ptr<_Tp>::delete_obj()
template<typename _Tp> inline Ptr<_Tp>::~Ptr() { release(); }
template<typename _Tp> inline Ptr<_Tp>::Ptr(const Ptr<_Tp>& ptr)
template<typename _Tp> inline Ptr<_Tp>::Ptr(const Ptr<_Tp>& _ptr)
{
obj = ptr.obj;
refcount = ptr.refcount;
obj = _ptr.obj;
refcount = _ptr.refcount;
addref();
}
template<typename _Tp> inline Ptr<_Tp>& Ptr<_Tp>::operator = (const Ptr<_Tp>& ptr)
template<typename _Tp> inline Ptr<_Tp>& Ptr<_Tp>::operator = (const Ptr<_Tp>& _ptr)
{
int* _refcount = ptr.refcount;
int* _refcount = _ptr.refcount;
if( _refcount )
CV_XADD(_refcount, 1);
release();
obj = ptr.obj;
obj = _ptr.obj;
refcount = _refcount;
return *this;
}
@ -3593,10 +3593,10 @@ template<typename _Tp> inline Seq<_Tp>::operator vector<_Tp>() const
template<typename _Tp> inline SeqIterator<_Tp>::SeqIterator()
{ memset(this, 0, sizeof(*this)); }
template<typename _Tp> inline SeqIterator<_Tp>::SeqIterator(const Seq<_Tp>& seq, bool seekEnd)
template<typename _Tp> inline SeqIterator<_Tp>::SeqIterator(const Seq<_Tp>& _seq, bool seekEnd)
{
cvStartReadSeq(seq.seq, this);
index = seekEnd ? seq.seq->total : 0;
cvStartReadSeq(_seq.seq, this);
index = seekEnd ? _seq.seq->total : 0;
}
template<typename _Tp> inline void SeqIterator<_Tp>::seek(size_t pos)
@ -3842,17 +3842,17 @@ template<typename _Tp> inline Ptr<_Tp> Algorithm::create(const string& name)
return _create(name).ptr<_Tp>();
}
template<typename _Tp> inline typename ParamType<_Tp>::member_type Algorithm::get(const string& name) const
template<typename _Tp> inline typename ParamType<_Tp>::member_type Algorithm::get(const string& _name) const
{
typename ParamType<_Tp>::member_type value;
info()->get(this, name.c_str(), ParamType<_Tp>::type, &value);
info()->get(this, _name.c_str(), ParamType<_Tp>::type, &value);
return value;
}
template<typename _Tp> inline typename ParamType<_Tp>::member_type Algorithm::get(const char* name) const
template<typename _Tp> inline typename ParamType<_Tp>::member_type Algorithm::get(const char* _name) const
{
typename ParamType<_Tp>::member_type value;
info()->get(this, name, ParamType<_Tp>::type, &value);
info()->get(this, _name, ParamType<_Tp>::type, &value);
return value;
}

186
modules/core/include/opencv2/core/types_c.h
View File

@ -43,122 +43,132 @@
#ifndef __OPENCV_CORE_TYPES_H__
#define __OPENCV_CORE_TYPES_H__
#if !defined _CRT_SECURE_NO_DEPRECATE && _MSC_VER > 1300
#define _CRT_SECURE_NO_DEPRECATE /* to avoid multiple Visual Studio 2005 warnings */
#if !defined _CRT_SECURE_NO_DEPRECATE && defined _MSC_VER
# if _MSC_VER > 1300
# define _CRT_SECURE_NO_DEPRECATE /* to avoid multiple Visual Studio 2005 warnings */
# endif
#endif
#ifndef SKIP_INCLUDES
#include <assert.h>
#include <stdlib.h>
#include <string.h>
#include <float.h>
#include <assert.h>
#include <stdlib.h>
#include <string.h>
#include <float.h>
#if !defined _MSC_VER && !defined __BORLANDC__
#include <stdint.h>
# include <stdint.h>
#endif
#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
#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
#if (_MSC_VER >= 1400 && defined _M_X64) || (__GNUC__ >= 4 && defined __x86_64__)
#if defined WIN32
#include <intrin.h>
#endif
#if __SSE2__ || !defined __GNUC__
#include <emmintrin.h>
#endif
#endif
#if defined CV_ICC && !defined CV_ENABLE_UNROLLED
# define CV_ENABLE_UNROLLED 0
#else
# define CV_ENABLE_UNROLLED 1
#endif
#if defined __BORLANDC__
#include <fastmath.h>
#else
#include <math.h>
#endif
#if (defined _M_X64 && defined _MSC_VER && _MSC_VER >= 1400) || (__GNUC__ >= 4 && defined __x86_64__)
# if defined WIN32
# include <intrin.h>
# endif
# if __SSE2__ || !defined __GNUC__
# include <emmintrin.h>
# endif
#endif
#if defined __BORLANDC__
# include <fastmath.h>
#else
# include <math.h>
#endif
#ifdef HAVE_IPL
# ifndef __IPL_H__
# if defined WIN32 || defined _WIN32
# include <ipl.h>
# else
# include <ipl/ipl.h>
# endif
# endif
#elif defined __IPL_H__
# define HAVE_IPL
#endif
#ifdef HAVE_IPL
#ifndef __IPL_H__
#if defined WIN32 || defined _WIN32
#include <ipl.h>
#else
#include <ipl/ipl.h>
#endif
#endif
#elif defined __IPL_H__
#define HAVE_IPL
#endif
#endif // SKIP_INCLUDES
#if defined WIN32 || defined _WIN32
#define CV_CDECL __cdecl
#define CV_STDCALL __stdcall
# define CV_CDECL __cdecl
# define CV_STDCALL __stdcall
#else
#define CV_CDECL
#define CV_STDCALL
# define CV_CDECL
# define CV_STDCALL
#endif
#ifndef CV_EXTERN_C
#ifdef __cplusplus
#define CV_EXTERN_C extern "C"
#define CV_DEFAULT(val) = val
#else
#define CV_EXTERN_C
#define CV_DEFAULT(val)
#endif
# ifdef __cplusplus
# define CV_EXTERN_C extern "C"
# define CV_DEFAULT(val) = val
# else
# define CV_EXTERN_C
# define CV_DEFAULT(val)
# endif
#endif
#ifndef CV_EXTERN_C_FUNCPTR
#ifdef __cplusplus
#define CV_EXTERN_C_FUNCPTR(x) extern "C" { typedef x; }
#else
#define CV_EXTERN_C_FUNCPTR(x) typedef x
#endif
# ifdef __cplusplus
# define CV_EXTERN_C_FUNCPTR(x) extern "C" { typedef x; }
# else
# define CV_EXTERN_C_FUNCPTR(x) typedef x
# endif
#endif
#ifndef CV_INLINE
#if defined __cplusplus
#define CV_INLINE inline
#elif (defined WIN32 || defined _WIN32 || defined WINCE) && !defined __GNUC__
#define CV_INLINE __inline
#else
#define CV_INLINE static
#endif
# if defined __cplusplus
# define CV_INLINE inline
# elif (defined WIN32 || defined _WIN32 || defined WINCE) && !defined __GNUC__
# define CV_INLINE __inline
# else
# define CV_INLINE static
# endif
#endif /* CV_INLINE */
#if (defined WIN32 || defined _WIN32 || defined WINCE) && defined CVAPI_EXPORTS
#define CV_EXPORTS __declspec(dllexport)
# define CV_EXPORTS __declspec(dllexport)
#else
#define CV_EXPORTS
# define CV_EXPORTS
#endif
#ifndef CVAPI
#define CVAPI(rettype) CV_EXTERN_C CV_EXPORTS rettype CV_CDECL
# define CVAPI(rettype) CV_EXTERN_C CV_EXPORTS rettype CV_CDECL
#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
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
typedef int64_t int64;
typedef uint64_t uint64;
# define CV_BIG_INT(n) n##LL
# define CV_BIG_UINT(n) n##ULL
#endif
#ifndef HAVE_IPL
typedef unsigned char uchar;
typedef unsigned short ushort;
typedef unsigned char uchar;
typedef unsigned short ushort;
#endif
typedef signed char schar;
@ -262,7 +272,7 @@ enum {
\****************************************************************************************/
#ifdef HAVE_TEGRA_OPTIMIZATION
# include "tegra_round.hpp"
# include "tegra_round.hpp"
#endif
#define CV_PI 3.1415926535897932384626433832795
@ -271,11 +281,11 @@ enum {
#define CV_SWAP(a,b,t) ((t) = (a), (a) = (b), (b) = (t))
#ifndef MIN
#define MIN(a,b) ((a) > (b) ? (b) : (a))
# define MIN(a,b) ((a) > (b) ? (b) : (a))
#endif
#ifndef MAX
#define MAX(a,b) ((a) < (b) ? (b) : (a))
# define MAX(a,b) ((a) < (b) ? (b) : (a))
#endif
/* min & max without jumps */
@ -285,9 +295,9 @@ enum {
/* absolute value without jumps */
#ifndef __cplusplus
#define CV_IABS(a) (((a) ^ ((a) < 0 ? -1 : 0)) - ((a) < 0 ? -1 : 0))
# define CV_IABS(a) (((a) ^ ((a) < 0 ? -1 : 0)) - ((a) < 0 ? -1 : 0))
#else
#define CV_IABS(a) abs(a)
# define CV_IABS(a) abs(a)
#endif
#define CV_CMP(a,b) (((a) > (b)) - ((a) < (b)))
#define CV_SIGN(a) CV_CMP((a),0)
@ -306,11 +316,11 @@ CV_INLINE int cvRound( double value )
}
return t;
#elif defined HAVE_LRINT || defined CV_ICC || defined __GNUC__
# ifdef HAVE_TEGRA_OPTIMIZATION
# ifdef HAVE_TEGRA_OPTIMIZATION
TEGRA_ROUND(value);
# else
# else
return (int)lrint(value);
# endif
# endif
#else
// while this is not IEEE754-compliant rounding, it's usually a good enough approximation
return (int)(value + (value >= 0 ? 0.5 : -0.5));
@ -318,7 +328,7 @@ CV_INLINE int cvRound( double value )
}
#if defined __SSE2__ || (defined _M_IX86_FP && 2 == _M_IX86_FP)
#include "emmintrin.h"
# include "emmintrin.h"
#endif
CV_INLINE int cvFloor( double value )
@ -1886,6 +1896,6 @@ typedef struct CvModuleInfo
}
CvModuleInfo;
#endif /*_CXCORE_TYPES_H_*/
#endif /*__OPENCV_CORE_TYPES_H__*/
/* End of file. */

6
modules/core/perf/perf_precomp.hpp
View File

@ -1,9 +1,13 @@
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
#endif
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#if GTEST_CREATE_SHARED_LIBRARY
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined
#endif

154
modules/core/src/algorithm.cpp
View File

@ -181,124 +181,124 @@ string Algorithm::name() const
return info()->name();
}
void Algorithm::set(const string& name, int value)
void Algorithm::set(const string& parameter, int value)
{
info()->set(this, name.c_str(), ParamType<int>::type, &value);
info()->set(this, parameter.c_str(), ParamType<int>::type, &value);
}
void Algorithm::set(const string& name, double value)
void Algorithm::set(const string& parameter, double value)
{
info()->set(this, name.c_str(), ParamType<double>::type, &value);
info()->set(this, parameter.c_str(), ParamType<double>::type, &value);
}
void Algorithm::set(const string& name, bool value)
void Algorithm::set(const string& parameter, bool value)
{
info()->set(this, name.c_str(), ParamType<bool>::type, &value);
info()->set(this, parameter.c_str(), ParamType<bool>::type, &value);
}
void Algorithm::set(const string& name, const string& value)
void Algorithm::set(const string& parameter, const string& value)
{
info()->set(this, name.c_str(), ParamType<string>::type, &value);
info()->set(this, parameter.c_str(), ParamType<string>::type, &value);
}
void Algorithm::set(const string& name, const Mat& value)
void Algorithm::set(const string& parameter, const Mat& value)
{
info()->set(this, name.c_str(), ParamType<Mat>::type, &value);
info()->set(this, parameter.c_str(), ParamType<Mat>::type, &value);
}
void Algorithm::set(const string& name, const vector<Mat>& value)
void Algorithm::set(const string& parameter, const vector<Mat>& value)
{
info()->set(this, name.c_str(), ParamType<vector<Mat> >::type, &value);
info()->set(this, parameter.c_str(), ParamType<vector<Mat> >::type, &value);
}
void Algorithm::set(const string& name, const Ptr<Algorithm>& value)
void Algorithm::set(const string& parameter, const Ptr<Algorithm>& value)
{
info()->set(this, name.c_str(), ParamType<Algorithm>::type, &value);
info()->set(this, parameter.c_str(), ParamType<Algorithm>::type, &value);
}
void Algorithm::set(const char* name, int value)
void Algorithm::set(const char* parameter, int value)
{
info()->set(this, name, ParamType<int>::type, &value);
info()->set(this, parameter, ParamType<int>::type, &value);
}
void Algorithm::set(const char* name, double value)
void Algorithm::set(const char* parameter, double value)
{
info()->set(this, name, ParamType<double>::type, &value);
info()->set(this, parameter, ParamType<double>::type, &value);
}
void Algorithm::set(const char* name, bool value)
void Algorithm::set(const char* parameter, bool value)
{
info()->set(this, name, ParamType<bool>::type, &value);
info()->set(this, parameter, ParamType<bool>::type, &value);
}
void Algorithm::set(const char* name, const string& value)
void Algorithm::set(const char* parameter, const string& value)
{
info()->set(this, name, ParamType<string>::type, &value);
info()->set(this, parameter, ParamType<string>::type, &value);
}
void Algorithm::set(const char* name, const Mat& value)
void Algorithm::set(const char* parameter, const Mat& value)
{
info()->set(this, name, ParamType<Mat>::type, &value);
info()->set(this, parameter, ParamType<Mat>::type, &value);
}
void Algorithm::set(const char* name, const vector<Mat>& value)
void Algorithm::set(const char* parameter, const vector<Mat>& value)
{
info()->set(this, name, ParamType<vector<Mat> >::type, &value);
info()->set(this, parameter, ParamType<vector<Mat> >::type, &value);
}
void Algorithm::set(const char* name, const Ptr<Algorithm>& value)
void Algorithm::set(const char* parameter, const Ptr<Algorithm>& value)
{
info()->set(this, name, ParamType<Algorithm>::type, &value);
info()->set(this, parameter, ParamType<Algorithm>::type, &value);
}
int Algorithm::getInt(const string& name) const
int Algorithm::getInt(const string& parameter) const
{
return get<int>(name);
return get<int>(parameter);
}
double Algorithm::getDouble(const string& name) const
double Algorithm::getDouble(const string& parameter) const
{
return get<double>(name);
return get<double>(parameter);
}
bool Algorithm::getBool(const string& name) const
bool Algorithm::getBool(const string& parameter) const
{
return get<bool>(name);
return get<bool>(parameter);
}
string Algorithm::getString(const string& name) const
string Algorithm::getString(const string& parameter) const
{
return get<string>(name);
return get<string>(parameter);
}
Mat Algorithm::getMat(const string& name) const
Mat Algorithm::getMat(const string& parameter) const
{
return get<Mat>(name);
return get<Mat>(parameter);
}
vector<Mat> Algorithm::getMatVector(const string& name) const
vector<Mat> Algorithm::getMatVector(const string& parameter) const
{
return get<vector<Mat> >(name);
return get<vector<Mat> >(parameter);
}
Ptr<Algorithm> Algorithm::getAlgorithm(const string& name) const
Ptr<Algorithm> Algorithm::getAlgorithm(const string& parameter) const
{
return get<Algorithm>(name);
return get<Algorithm>(parameter);
}
string Algorithm::paramHelp(const string& name) const
string Algorithm::paramHelp(const string& parameter) const
{
return info()->paramHelp(name.c_str());
return info()->paramHelp(parameter.c_str());
}
int Algorithm::paramType(const string& name) const
int Algorithm::paramType(const string& parameter) const
{
return info()->paramType(name.c_str());
return info()->paramType(parameter.c_str());
}
int Algorithm::paramType(const char* name) const
int Algorithm::paramType(const char* parameter) const
{
return info()->paramType(name);
return info()->paramType(parameter);
}
void Algorithm::getParams(vector<string>& names) const
@ -440,15 +440,15 @@ union GetSetParam
void (Algorithm::*set_algo)(const Ptr<Algorithm>&);
};
void AlgorithmInfo::set(Algorithm* algo, const char* name, int argType, const void* value, bool force) const
void AlgorithmInfo::set(Algorithm* algo, const char* parameter, int argType, const void* value, bool force) const
{
const Param* p = findstr(data->params, name);
const Param* p = findstr(data->params, parameter);
if( !p )
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", name ? name : "<NULL>") );
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", parameter ? parameter : "<NULL>") );
if( !force && p->readonly )
CV_Error_( CV_StsError, ("Parameter '%s' is readonly", name));
CV_Error_( CV_StsError, ("Parameter '%s' is readonly", parameter));
GetSetParam f;
f.set_int = p->setter;
@ -532,11 +532,11 @@ void AlgorithmInfo::set(Algorithm* algo, const char* name, int argType, const vo
CV_Error(CV_StsBadArg, "Unknown/unsupported parameter type");
}
void AlgorithmInfo::get(const Algorithm* algo, const char* name, int argType, void* value) const
void AlgorithmInfo::get(const Algorithm* algo, const char* parameter, int argType, void* value) const
{
const Param* p = findstr(data->params, name);
const Param* p = findstr(data->params, parameter);
if( !p )
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", name ? name : "<NULL>") );
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", parameter ? parameter : "<NULL>") );
GetSetParam f;
f.get_int = p->getter;
@ -606,20 +606,20 @@ void AlgorithmInfo::get(const Algorithm* algo, const char* name, int argType, vo
}
int AlgorithmInfo::paramType(const char* name) const
int AlgorithmInfo::paramType(const char* parameter) const
{
const Param* p = findstr(data->params, name);
const Param* p = findstr(data->params, parameter);
if( !p )
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", name ? name : "<NULL>") );
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", parameter ? parameter : "<NULL>") );
return p->type;
}
string AlgorithmInfo::paramHelp(const char* name) const
string AlgorithmInfo::paramHelp(const char* parameter) const
{
const Param* p = findstr(data->params, name);
const Param* p = findstr(data->params, parameter);
if( !p )
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", name ? name : "<NULL>") );
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", parameter ? parameter : "<NULL>") );
return p->help;
}
@ -630,7 +630,7 @@ void AlgorithmInfo::getParams(vector<string>& names) const
}
void AlgorithmInfo::addParam_(Algorithm& algo, const char* name, int argType,
void AlgorithmInfo::addParam_(Algorithm& algo, const char* parameter, int argType,
void* value, bool readOnly,
Algorithm::Getter getter, Algorithm::Setter setter,
const string& help)
@ -639,79 +639,79 @@ void AlgorithmInfo::addParam_(Algorithm& algo, const char* name, int argType,
argType == Param::REAL || argType == Param::STRING ||
argType == Param::MAT || argType == Param::MAT_VECTOR ||
argType == Param::ALGORITHM );
data->params.add(string(name), Param(argType, readOnly,
data->params.add(string(parameter), Param(argType, readOnly,
(int)((size_t)value - (size_t)(void*)&algo),
getter, setter, help));
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
int& value, bool readOnly,
int (Algorithm::*getter)(),
void (Algorithm::*setter)(int),
const string& help)
{
addParam_(algo, name, ParamType<int>::type, &value, readOnly,
addParam_(algo, parameter, ParamType<int>::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
bool& value, bool readOnly,
int (Algorithm::*getter)(),
void (Algorithm::*setter)(int),
const string& help)
{
addParam_(algo, name, ParamType<bool>::type, &value, readOnly,
addParam_(algo, parameter, ParamType<bool>::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
double& value, bool readOnly,
double (Algorithm::*getter)(),
void (Algorithm::*setter)(double),
const string& help)
{
addParam_(algo, name, ParamType<double>::type, &value, readOnly,
addParam_(algo, parameter, ParamType<double>::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
string& value, bool readOnly,
string (Algorithm::*getter)(),
void (Algorithm::*setter)(const string&),
const string& help)
{
addParam_(algo, name, ParamType<string>::type, &value, readOnly,
addParam_(algo, parameter, ParamType<string>::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
Mat& value, bool readOnly,
Mat (Algorithm::*getter)(),
void (Algorithm::*setter)(const Mat&),
const string& help)
{
addParam_(algo, name, ParamType<Mat>::type, &value, readOnly,
addParam_(algo, parameter, ParamType<Mat>::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
vector<Mat>& value, bool readOnly,
vector<Mat> (Algorithm::*getter)(),
void (Algorithm::*setter)(const vector<Mat>&),
const string& help)
{
addParam_(algo, name, ParamType<vector<Mat> >::type, &value, readOnly,
addParam_(algo, parameter, ParamType<vector<Mat> >::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}
void AlgorithmInfo::addParam(Algorithm& algo, const char* name,
void AlgorithmInfo::addParam(Algorithm& algo, const char* parameter,
Ptr<Algorithm>& value, bool readOnly,
Ptr<Algorithm> (Algorithm::*getter)(),
void (Algorithm::*setter)(const Ptr<Algorithm>&),
const string& help)
{
addParam_(algo, name, ParamType<Algorithm>::type, &value, readOnly,
addParam_(algo, parameter, ParamType<Algorithm>::type, &value, readOnly,
(Algorithm::Getter)getter, (Algorithm::Setter)setter, help);
}

4
modules/core/src/alloc.cpp
View File

@ -55,7 +55,9 @@ static void* OutOfMemoryError(size_t size)
#if CV_USE_SYSTEM_MALLOC
#if defined WIN32 || defined _WIN32
void deleteThreadAllocData() {}
#endif
void* fastMalloc( size_t size )
{
@ -388,7 +390,7 @@ struct ThreadData
#ifdef WIN32
#ifdef WINCE
# define TLS_OUT_OF_INDEXES ((DWORD)0xFFFFFFFF)
# define TLS_OUT_OF_INDEXES ((DWORD)0xFFFFFFFF)
#endif //WINCE
static DWORD tlsKey;

4
modules/core/src/arithm.cpp
View File

@ -974,7 +974,7 @@ void convertAndUnrollScalar( const Mat& sc, int buftype, uchar* scbuf, size_t bl
scbuf[i] = scbuf[i - esz];
}
void binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
static void binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
InputArray _mask, const BinaryFunc* tab, bool bitwise)
{
int kind1 = _src1.kind(), kind2 = _src2.kind();
@ -1216,7 +1216,7 @@ void cv::min(const Mat& src1, double src2, Mat& dst)
namespace cv
{
void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
static void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
InputArray _mask, int dtype, BinaryFunc* tab, bool muldiv=false, void* usrdata=0)
{
int kind1 = _src1.kind(), kind2 = _src2.kind();

3
modules/core/src/cmdparser.cpp
View File

@ -6,6 +6,7 @@
using namespace std;
using namespace cv;
namespace {
void helpParser()
{
printf("\nThe CommandLineParser class is designed for command line arguments parsing\n"
@ -89,6 +90,8 @@ string del_space(string name)
return name;
}
}//namespace
CommandLineParser::CommandLineParser(int argc, const char* const argv[], const char* keys)
{
std::string keys_buffer;

10
modules/core/src/convert.cpp
View File

@ -328,8 +328,8 @@ void cv::merge(const Mat* mv, size_t n, OutputArray _dst)
if( j + blocksize < total )
{
ptrs[0] += bsz*esz;
for( int k = 0; k < cn; k++ )
ptrs[k+1] += bsz*esz1;
for( int t = 0; t < cn; t++ )
ptrs[t+1] += bsz*esz1;
}
}
}
@ -480,12 +480,12 @@ void cv::mixChannels( const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts, cons
dsts[k] = ptrs[tab[k*4+2]] + tab[k*4+3];
}
for( int j = 0; j < total; j += blocksize )
for( int t = 0; t < total; t += blocksize )
{
int bsz = std::min(total - j, blocksize);
int bsz = std::min(total - t, blocksize);
func( srcs, sdelta, dsts, ddelta, bsz, (int)npairs );
if( j + blocksize < total )
if( t + blocksize < total )
for( k = 0; k < npairs; k++ )
{
srcs[k] += blocksize*sdelta[k]*esz1;

28
modules/core/src/copy.cpp
View File

@ -59,7 +59,7 @@ copyMask_(const uchar* _src, size_t sstep, const uchar* mask, size_t mstep, ucha
const T* src = (const T*)_src;
T* dst = (T*)_dst;
int x = 0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; x <= size.width - 4; x += 4 )
{
if( mask[x] )
@ -193,10 +193,10 @@ void Mat::copyTo( OutputArray _dst ) const
const Mat* arrays[] = { this, &dst };
uchar* ptrs[2];
NAryMatIterator it(arrays, ptrs, 2);
size_t size = it.size*elemSize();
size_t sz = it.size*elemSize();
for( size_t i = 0; i < it.nplanes; i++, ++it )
memcpy(ptrs[1], ptrs[0], size);
memcpy(ptrs[1], ptrs[0], sz);
}
}
@ -242,14 +242,14 @@ void Mat::copyTo( OutputArray _dst, InputArray _mask ) const
Mat& Mat::operator = (const Scalar& s)
{
const Mat* arrays[] = { this };
uchar* ptr;
NAryMatIterator it(arrays, &ptr, 1);
size_t size = it.size*elemSize();
uchar* dptr;
NAryMatIterator it(arrays, &dptr, 1);
size_t elsize = it.size*elemSize();
if( s[0] == 0 && s[1] == 0 && s[2] == 0 && s[3] == 0 )
{
for( size_t i = 0; i < it.nplanes; i++, ++it )
memset( ptr, 0, size );
memset( dptr, 0, elsize );
}
else
{
@ -259,17 +259,17 @@ Mat& Mat::operator = (const Scalar& s)
scalarToRawData(s, scalar, type(), 12);
size_t blockSize = 12*elemSize1();
for( size_t j = 0; j < size; j += blockSize )
for( size_t j = 0; j < elsize; j += blockSize )
{
size_t sz = MIN(blockSize, size - j);
memcpy( ptr + j, scalar, sz );
size_t sz = MIN(blockSize, elsize - j);
memcpy( dptr + j, scalar, sz );
}
}
for( size_t i = 1; i < it.nplanes; i++ )
{
++it;
memcpy( ptr, data, size );
memcpy( dptr, data, elsize );
}
}
return *this;
@ -292,16 +292,16 @@ Mat& Mat::setTo(InputArray _value, InputArray _mask)
const Mat* arrays[] = { this, !mask.empty() ? &mask : 0, 0 };
uchar* ptrs[2]={0,0};
NAryMatIterator it(arrays, ptrs);
int total = (int)it.size, blockSize0 = std::min(total, (int)((BLOCK_SIZE + esz-1)/esz));
int totalsz = (int)it.size, blockSize0 = std::min(totalsz, (int)((BLOCK_SIZE + esz-1)/esz));
AutoBuffer<uchar> _scbuf(blockSize0*esz + 32);
uchar* scbuf = alignPtr((uchar*)_scbuf, (int)sizeof(double));
convertAndUnrollScalar( value, type(), scbuf, blockSize0 );
for( size_t i = 0; i < it.nplanes; i++, ++it )
{
for( int j = 0; j < total; j += blockSize0 )
for( int j = 0; j < totalsz; j += blockSize0 )
{
Size sz(std::min(blockSize0, total - j), 1);
Size sz(std::min(blockSize0, totalsz - j), 1);
size_t blockSize = sz.width*esz;
if( ptrs[1] )
{

32
modules/core/src/datastructs.cpp
View File

@ -3653,7 +3653,7 @@ void KDTree::build(InputArray __points, InputArray __labels, bool _copyData)
points.create(_points.size(), _points.type());
}
int i, j, n = _points.rows, dims = _points.cols, top = 0;
int i, j, n = _points.rows, ptdims = _points.cols, top = 0;
const float* data = _points.ptr<float>(0);
float* dstdata = points.ptr<float>(0);
size_t step = _points.step1();
@ -3669,7 +3669,7 @@ void KDTree::build(InputArray __points, InputArray __labels, bool _copyData)
_labels_data = (const int*)_labels.data;
}
Mat sumstack(MAX_TREE_DEPTH*2, dims*2, CV_64F);
Mat sumstack(MAX_TREE_DEPTH*2, ptdims*2, CV_64F);
SubTree stack[MAX_TREE_DEPTH*2];
vector<size_t> _ptofs(n);
@ -3700,7 +3700,7 @@ void KDTree::build(InputArray __points, InputArray __labels, bool _copyData)
{
const float* src = data + ptofs[first];
float* dst = dstdata + idx*dstep;
for( j = 0; j < dims; j++ )
for( j = 0; j < ptdims; j++ )
dst[j] = src[j];
}
labels[idx] = _labels_data ? _labels_data[idx0] : idx0;
@ -3709,7 +3709,7 @@ void KDTree::build(InputArray __points, InputArray __labels, bool _copyData)
}
// find the dimensionality with the biggest variance
for( j = 0; j < dims; j++ )
for( j = 0; j < ptdims; j++ )
{
double m = sums[j*2]*invCount;
double varj = sums[j*2+1]*invCount - m*m;
@ -3729,9 +3729,9 @@ void KDTree::build(InputArray __points, InputArray __labels, bool _copyData)
nodes[nidx].boundary = medianPartition(ptofs, first, last, data + dim);
int middle = (first + last)/2;
double *lsums = (double*)sums, *rsums = lsums + dims*2;
double *lsums = (double*)sums, *rsums = lsums + ptdims*2;
computeSums(points, ptofs, middle+1, last, rsums);
for( j = 0; j < dims*2; j++ )
for( j = 0; j < ptdims*2; j++ )
lsums[j] = sums[j] - rsums[j];
stack[top++] = SubTree(first, middle, left, depth+1);
stack[top++] = SubTree(middle+1, last, right, depth+1);
@ -3758,7 +3758,7 @@ int KDTree::findNearest(InputArray _vec, int K, int emax,
CV_Assert( vecmat.isContinuous() && vecmat.type() == CV_32F && vecmat.total() == (size_t)points.cols );
const float* vec = vecmat.ptr<float>();
K = std::min(K, points.rows);
int dims = points.cols;
int ptdims = points.cols;
CV_Assert(K > 0 && (normType == NORM_L2 || normType == NORM_L1));
@ -3819,13 +3819,13 @@ int KDTree::findNearest(InputArray _vec, int K, int emax,
i = ~n.idx;
const float* row = points.ptr<float>(i);
if( normType == NORM_L2 )
for( j = 0, d = 0.f; j < dims; j++ )
for( j = 0, d = 0.f; j < ptdims; j++ )
{
float t = vec[j] - row[j];
d += t*t;
}
else
for( j = 0, d = 0.f; j < dims; j++ )
for( j = 0, d = 0.f; j < ptdims; j++ )
d += std::abs(vec[j] - row[j]);
dist[ncount] = d;
@ -3898,14 +3898,14 @@ void KDTree::findOrthoRange(InputArray _lowerBound,
OutputArray _neighbors,
OutputArray _labels ) const
{
int dims = points.cols;
int ptdims = points.cols;
Mat lowerBound = _lowerBound.getMat(), upperBound = _upperBound.getMat();
CV_Assert( lowerBound.size == upperBound.size &&
lowerBound.isContinuous() &&
upperBound.isContinuous() &&
lowerBound.type() == upperBound.type() &&
lowerBound.type() == CV_32F &&
lowerBound.total() == (size_t)dims );
lowerBound.total() == (size_t)ptdims );
const float* L = lowerBound.ptr<float>();
const float* R = upperBound.ptr<float>();
@ -3926,10 +3926,10 @@ void KDTree::findOrthoRange(InputArray _lowerBound,
{
int j, i = ~n.idx;
const float* row = points.ptr<float>(i);
for( j = 0; j < dims; j++ )
for( j = 0; j < ptdims; j++ )
if( row[j] < L[j] || row[j] >= R[j] )
break;
if( j == dims )
if( j == ptdims )
idx.push_back(i);
continue;
}
@ -3957,7 +3957,7 @@ void KDTree::getPoints(InputArray _idx, OutputArray _pts, OutputArray _labels) c
const int* idx = idxmat.ptr<int>();
int* dstlabels = 0;
int dims = points.cols;
int ptdims = points.cols;
int i, nidx = (int)idxmat.total();
if( nidx == 0 )
{
@ -3968,7 +3968,7 @@ void KDTree::getPoints(InputArray _idx, OutputArray _pts, OutputArray _labels) c
if( _pts.needed() )
{
_pts.create( nidx, dims, points.type());
_pts.create( nidx, ptdims, points.type());
pts = _pts.getMat();
}
@ -3987,7 +3987,7 @@ void KDTree::getPoints(InputArray _idx, OutputArray _pts, OutputArray _labels) c
CV_Assert( (unsigned)k < (unsigned)points.rows );
const float* src = points.ptr<float>(k);
if( pts.data )
std::copy(src, src + dims, pts.ptr<float>(i));
std::copy(src, src + ptdims, pts.ptr<float>(i));
if( dstlabels )
dstlabels[i] = srclabels ? srclabels[k] : k;
}

16
modules/core/src/drawing.cpp
View File

@ -169,7 +169,7 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
}
int bt_pix0 = (int)img.elemSize(), bt_pix = bt_pix0;
size_t step = img.step;
size_t istep = img.step;
int dx = pt2.x - pt1.x;
int dy = pt2.y - pt1.y;
@ -188,11 +188,11 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
bt_pix = (bt_pix ^ s) - s;
}
ptr = (uchar*)(img.data + pt1.y * step + pt1.x * bt_pix0);
ptr = (uchar*)(img.data + pt1.y * istep + pt1.x * bt_pix0);
s = dy < 0 ? -1 : 0;
dy = (dy ^ s) - s;
step = (step ^ s) - s;
istep = (istep ^ s) - s;
s = dy > dx ? -1 : 0;
@ -201,9 +201,9 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
dy ^= dx & s;
dx ^= dy & s;
bt_pix ^= step & s;
step ^= bt_pix & s;
bt_pix ^= step & s;
bt_pix ^= istep & s;
istep ^= bt_pix & s;
bt_pix ^= istep & s;
if( connectivity == 8 )
{
@ -212,7 +212,7 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
err = dx - (dy + dy);
plusDelta = dx + dx;
minusDelta = -(dy + dy);
plusStep = (int)step;
plusStep = (int)istep;
minusStep = bt_pix;
count = dx + 1;
}
@ -223,7 +223,7 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
err = 0;
plusDelta = (dx + dx) + (dy + dy);
minusDelta = -(dy + dy);
plusStep = (int)step - bt_pix;
plusStep = (int)istep - bt_pix;
minusStep = bt_pix;
count = dx + dy + 1;
}

4
modules/core/src/dxt.cpp
View File

@ -46,8 +46,8 @@ namespace cv
// On Win64 optimized versions of DFT and DCT fail the tests (fixed in VS2010)
#if defined _MSC_VER && !defined CV_ICC && defined _M_X64 && _MSC_VER < 1600
#pragma optimize("", off)
#pragma warning( disable : 4748 )
# pragma optimize("", off)
# pragma warning(disable: 4748)
#endif
/****************************************************************************************\

18
modules/core/src/gpumat.cpp
View File

@ -524,30 +524,30 @@ cv::gpu::GpuMat::GpuMat(Size size_, int type_, void* data_, size_t step_) :
dataend += step * (rows - 1) + minstep;
}
cv::gpu::GpuMat::GpuMat(const GpuMat& m, Range rowRange, Range colRange)
cv::gpu::GpuMat::GpuMat(const GpuMat& m, Range _rowRange, Range _colRange)
{
flags = m.flags;
step = m.step; refcount = m.refcount;
data = m.data; datastart = m.datastart; dataend = m.dataend;
if (rowRange == Range::all())
if (_rowRange == Range::all())
rows = m.rows;
else
{
CV_Assert(0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows);
CV_Assert(0 <= _rowRange.start && _rowRange.start <= _rowRange.end && _rowRange.end <= m.rows);
rows = rowRange.size();
data += step*rowRange.start;
rows = _rowRange.size();
data += step*_rowRange.start;
}
if (colRange == Range::all())
if (_colRange == Range::all())
cols = m.cols;
else
{
CV_Assert(0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols);
CV_Assert(0 <= _colRange.start && _colRange.start <= _colRange.end && _colRange.end <= m.cols);
cols = colRange.size();
data += colRange.start*elemSize();
cols = _colRange.size();
data += _colRange.start*elemSize();
flags &= cols < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
}

14
modules/core/src/mathfuncs.cpp
View File

@ -1845,37 +1845,37 @@ iPow_( const T* src, T* dst, int len, int power )
}
void iPow8u(const uchar* src, uchar* dst, int len, int power)
static void iPow8u(const uchar* src, uchar* dst, int len, int power)
{
iPow_<uchar, int>(src, dst, len, power);
}
void iPow8s(const schar* src, schar* dst, int len, int power)
static void iPow8s(const schar* src, schar* dst, int len, int power)
{
iPow_<schar, int>(src, dst, len, power);
}
void iPow16u(const ushort* src, ushort* dst, int len, int power)
static void iPow16u(const ushort* src, ushort* dst, int len, int power)
{
iPow_<ushort, int>(src, dst, len, power);
}
void iPow16s(const short* src, short* dst, int len, int power)
static void iPow16s(const short* src, short* dst, int len, int power)
{
iPow_<short, int>(src, dst, len, power);
}
void iPow32s(const int* src, int* dst, int len, int power)
static void iPow32s(const int* src, int* dst, int len, int power)
{
iPow_<int, int>(src, dst, len, power);
}
void iPow32f(const float* src, float* dst, int len, int power)
static void iPow32f(const float* src, float* dst, int len, int power)
{
iPow_<float, float>(src, dst, len, power);
}
void iPow64f(const double* src, double* dst, int len, int power)
static void iPow64f(const double* src, double* dst, int len, int power)
{
iPow_<double, double>(src, dst, len, power);
}

46
modules/core/src/matmul.cpp
View File

@ -63,7 +63,7 @@ GEMM_CopyBlock( const uchar* src, size_t src_step,
for( ; size.height--; src += src_step, dst += dst_step )
{
j=0;
j=0;
#if CV_ENABLE_UNROLLED
for( ; j <= size.width - 4; j += 4 )
{
@ -345,7 +345,7 @@ GEMMSingleMul( const T* a_data, size_t a_step,
for( k = 0; k < n; k++, b_data += b_step )
{
WT al(a_data[k]);
j=0;
j=0;
#if CV_ENABLE_UNROLLED
for(; j <= m - 4; j += 4 )
{
@ -513,8 +513,8 @@ GEMMStore( const T* c_data, size_t c_step,
if( _c_data )
{
c_data = _c_data;
j=0;
#if CV_ENABLE_UNROLLED
j=0;
#if CV_ENABLE_UNROLLED
for(; j <= d_size.width - 4; j += 4, c_data += 4*c_step1 )
{
WT t0 = alpha*d_buf[j];
@ -539,8 +539,8 @@ GEMMStore( const T* c_data, size_t c_step,
}
else
{
j = 0;
#if CV_ENABLE_UNROLLED
j = 0;
#if CV_ENABLE_UNROLLED
for( ; j <= d_size.width - 4; j += 4 )
{
WT t0 = alpha*d_buf[j];
@ -552,7 +552,7 @@ GEMMStore( const T* c_data, size_t c_step,
d_data[j+2] = T(t0);
d_data[j+3] = T(t1);
}
#endif
#endif
for( ; j < d_size.width; j++ )
d_data[j] = T(alpha*d_buf[j]);
}
@ -696,7 +696,7 @@ static void GEMMStore_64fc( const Complexd* c_data, size_t c_step,
}
void cv::gemm( InputArray matA, InputArray matB, double alpha,
InputArray matC, double beta, OutputArray matD, int flags )
InputArray matC, double beta, OutputArray _matD, int flags )
{
const int block_lin_size = 128;
const int block_size = block_lin_size * block_lin_size;
@ -741,8 +741,8 @@ void cv::gemm( InputArray matA, InputArray matB, double alpha,
((flags&GEMM_3_T) != 0 && C.rows == d_size.width && C.cols == d_size.height)));
}
matD.create( d_size.height, d_size.width, type );
Mat D = matD.getMat();
_matD.create( d_size.height, d_size.width, type );
Mat D = _matD.getMat();
if( (flags & GEMM_3_T) != 0 && C.data == D.data )
{
transpose( C, C );
@ -2008,7 +2008,7 @@ static void scaleAdd_32f(const float* src1, const float* src2, float* dst,
t1 = src1[i+3]*alpha + src2[i+3];
dst[i+2] = t0; dst[i+3] = t1;
}
for(; i < len; i++ )
for(; i < len; i++ )
dst[i] = src1[i]*alpha + src2[i];
}
@ -2046,7 +2046,7 @@ static void scaleAdd_64f(const double* src1, const double* src2, double* dst,
t1 = src1[i+3]*alpha + src2[i+3];
dst[i+2] = t0; dst[i+3] = t1;
}
for(; i < len; i++ )
for(; i < len; i++ )
dst[i] = src1[i]*alpha + src2[i];
}
@ -2134,12 +2134,12 @@ void cv::calcCovarMatrix( const Mat* data, int nsamples, Mat& covar, Mat& _mean,
_mean = mean.reshape(1, size.height);
}
void cv::calcCovarMatrix( InputArray _data, OutputArray _covar, InputOutputArray _mean, int flags, int ctype )
void cv::calcCovarMatrix( InputArray _src, OutputArray _covar, InputOutputArray _mean, int flags, int ctype )
{
if(_data.kind() == _InputArray::STD_VECTOR_MAT)
if(_src.kind() == _InputArray::STD_VECTOR_MAT)
{
std::vector<cv::Mat> src;
_data.getMatVector(src);
_src.getMatVector(src);
CV_Assert( src.size() > 0 );
@ -2185,7 +2185,7 @@ void cv::calcCovarMatrix( InputArray _data, OutputArray _covar, InputOutputArray
return;
}
Mat data = _data.getMat(), mean;
Mat data = _src.getMat(), mean;
CV_Assert( ((flags & CV_COVAR_ROWS) != 0) ^ ((flags & CV_COVAR_COLS) != 0) );
bool takeRows = (flags & CV_COVAR_ROWS) != 0;
int type = data.type();
@ -2209,7 +2209,7 @@ void cv::calcCovarMatrix( InputArray _data, OutputArray _covar, InputOutputArray
else
{
ctype = std::max(CV_MAT_DEPTH(ctype >= 0 ? ctype : type), CV_32F);
reduce( _data, _mean, takeRows ? 0 : 1, CV_REDUCE_AVG, ctype );
reduce( _src, _mean, takeRows ? 0 : 1, CV_REDUCE_AVG, ctype );
mean = _mean.getMat();
}
@ -2261,7 +2261,7 @@ double cv::Mahalanobis( InputArray _v1, InputArray _v2, InputArray _icovar )
{
double row_sum = 0;
j = 0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for(; j <= len - 4; j += 4 )
row_sum += diff[j]*mat[j] + diff[j+1]*mat[j+1] +
diff[j+2]*mat[j+2] + diff[j+3]*mat[j+3];
@ -2292,7 +2292,7 @@ double cv::Mahalanobis( InputArray _v1, InputArray _v2, InputArray _icovar )
{
double row_sum = 0;
j = 0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for(; j <= len - 4; j += 4 )
row_sum += diff[j]*mat[j] + diff[j+1]*mat[j+1] +
diff[j+2]*mat[j+2] + diff[j+3]*mat[j+3];
@ -2642,7 +2642,7 @@ dotProd_(const T* src1, const T* src2, int len)
{
int i = 0;
double result = 0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
result += (double)src1[i]*src2[i] + (double)src1[i+1]*src2[i+1] +
(double)src1[i+2]*src2[i+2] + (double)src1[i+3]*src2[i+3];
@ -2674,7 +2674,7 @@ static double dotProd_8u(const uchar* src1, const uchar* src2, int len)
{
blockSize = std::min(len0 - i, blockSize0);
__m128i s = _mm_setzero_si128();
j = 0;
j = 0;
for( ; j <= blockSize - 16; j += 16 )
{
__m128i b0 = _mm_loadu_si128((const __m128i*)(src1 + j));
@ -2806,9 +2806,9 @@ double Mat::dot(InputArray _mat) const
PCA::PCA() {}
PCA::PCA(InputArray data, InputArray mean, int flags, int maxComponents)
PCA::PCA(InputArray data, InputArray _mean, int flags, int maxComponents)
{
operator()(data, mean, flags, maxComponents);
operator()(data, _mean, flags, maxComponents);
}
PCA& PCA::operator()(InputArray _data, InputArray __mean, int flags, int maxComponents)

58
modules/core/src/matop.cpp
View File

@ -1181,14 +1181,14 @@ int MatExpr::type() const
/////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Identity::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_Identity::assign(const MatExpr& e, Mat& m, int _type) const
{
if( type == -1 || type == e.a.type() )
if( _type == -1 || _type == e.a.type() )
m = e.a;
else
{
CV_Assert( CV_MAT_CN(type) == e.a.channels() );
e.a.convertTo(m, type);
CV_Assert( CV_MAT_CN(_type) == e.a.channels() );
e.a.convertTo(m, _type);
}
}
@ -1199,9 +1199,9 @@ inline void MatOp_Identity::makeExpr(MatExpr& res, const Mat& m)
/////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_AddEx::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_AddEx::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || e.a.type() == type ? m : temp;
Mat temp, &dst = _type == -1 || e.a.type() == _type ? m : temp;
if( e.b.data )
{
if( e.s == Scalar() || !e.s.isReal() )
@ -1233,7 +1233,7 @@ void MatOp_AddEx::assign(const MatExpr& e, Mat& m, int type) const
}
else if( e.s.isReal() && (dst.data != m.data || fabs(e.alpha) != 1))
{
e.a.convertTo(m, type, e.alpha, e.s[0]);
e.a.convertTo(m, _type, e.alpha, e.s[0]);
return;
}
else if( e.alpha == 1 )
@ -1308,9 +1308,9 @@ inline void MatOp_AddEx::makeExpr(MatExpr& res, const Mat& a, const Mat& b, doub
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Bin::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_Bin::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || e.a.type() == type ? m : temp;
Mat temp, &dst = _type == -1 || e.a.type() == _type ? m : temp;
if( e.flags == '*' )
cv::multiply(e.a, e.b, dst, e.alpha);
@ -1348,7 +1348,7 @@ void MatOp_Bin::assign(const MatExpr& e, Mat& m, int type) const
CV_Error(CV_StsError, "Unknown operation");
if( dst.data != m.data )
dst.convertTo(m, type);
dst.convertTo(m, _type);
}
void MatOp_Bin::multiply(const MatExpr& e, double s, MatExpr& res) const
@ -1382,9 +1382,9 @@ inline void MatOp_Bin::makeExpr(MatExpr& res, char op, const Mat& a, const Scala
///////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Cmp::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_Cmp::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || type == CV_8U ? m : temp;
Mat temp, &dst = _type == -1 || _type == CV_8U ? m : temp;
if( e.b.data )
cv::compare(e.a, e.b, dst, e.flags);
@ -1392,7 +1392,7 @@ void MatOp_Cmp::assign(const MatExpr& e, Mat& m, int type) const
cv::compare(e.a, e.alpha, dst, e.flags);
if( dst.data != m.data )
dst.convertTo(m, type);
dst.convertTo(m, _type);
}
inline void MatOp_Cmp::makeExpr(MatExpr& res, int cmpop, const Mat& a, const Mat& b)
@ -1407,14 +1407,14 @@ inline void MatOp_Cmp::makeExpr(MatExpr& res, int cmpop, const Mat& a, double al
/////////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_T::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_T::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || type == e.a.type() ? m : temp;
Mat temp, &dst = _type == -1 || _type == e.a.type() ? m : temp;
cv::transpose(e.a, dst);
if( dst.data != m.data || e.alpha != 1 )
dst.convertTo(m, type, e.alpha);
dst.convertTo(m, _type, e.alpha);
}
void MatOp_T::multiply(const MatExpr& e, double s, MatExpr& res) const
@ -1438,13 +1438,13 @@ inline void MatOp_T::makeExpr(MatExpr& res, const Mat& a, double alpha)
/////////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_GEMM::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_GEMM::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || type == e.a.type() ? m : temp;
Mat temp, &dst = _type == -1 || _type == e.a.type() ? m : temp;
cv::gemm(e.a, e.b, e.alpha, e.c, e.beta, dst, e.flags);
if( dst.data != m.data )
dst.convertTo(m, type);
dst.convertTo(m, _type);
}
void MatOp_GEMM::add(const MatExpr& e1, const MatExpr& e2, MatExpr& res) const
@ -1503,13 +1503,13 @@ inline void MatOp_GEMM::makeExpr(MatExpr& res, int flags, const Mat& a, const Ma
///////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Invert::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_Invert::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || type == e.a.type() ? m : temp;
Mat temp, &dst = _type == -1 || _type == e.a.type() ? m : temp;
cv::invert(e.a, dst, e.flags);
if( dst.data != m.data )
dst.convertTo(m, type);
dst.convertTo(m, _type);
}
void MatOp_Invert::matmul(const MatExpr& e1, const MatExpr& e2, MatExpr& res) const
@ -1529,13 +1529,13 @@ inline void MatOp_Invert::makeExpr(MatExpr& res, int method, const Mat& m)
/////////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Solve::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_Solve::assign(const MatExpr& e, Mat& m, int _type) const
{
Mat temp, &dst = type == -1 || type == e.a.type() ? m : temp;
Mat temp, &dst = _type == -1 || _type == e.a.type() ? m : temp;
cv::solve(e.a, e.b, dst, e.flags);
if( dst.data != m.data )
dst.convertTo(m, type);
dst.convertTo(m, _type);
}
inline void MatOp_Solve::makeExpr(MatExpr& res, int method, const Mat& a, const Mat& b)
@ -1545,11 +1545,11 @@ inline void MatOp_Solve::makeExpr(MatExpr& res, int method, const Mat& a, const
//////////////////////////////////////////////////////////////////////////////////////////////////////////
void MatOp_Initializer::assign(const MatExpr& e, Mat& m, int type) const
void MatOp_Initializer::assign(const MatExpr& e, Mat& m, int _type) const
{
if( type == -1 )
type = e.a.type();
m.create(e.a.size(), type);
if( _type == -1 )
_type = e.a.type();
m.create(e.a.size(), _type);
if( e.flags == 'I' )
setIdentity(m, Scalar(e.alpha));
else if( e.flags == '0' )

164
modules/core/src/matrix.cpp
View File

@ -210,9 +210,9 @@ void Mat::create(int d, const int* _sizes, int _type)
#endif
if( !allocator )
{
size_t total = alignSize(step.p[0]*size.p[0], (int)sizeof(*refcount));
data = datastart = (uchar*)fastMalloc(total + (int)sizeof(*refcount));
refcount = (int*)(data + total);
size_t totalsize = alignSize(step.p[0]*size.p[0], (int)sizeof(*refcount));
data = datastart = (uchar*)fastMalloc(totalsize + (int)sizeof(*refcount));
refcount = (int*)(data + totalsize);
*refcount = 1;
}
else
@ -225,9 +225,9 @@ void Mat::create(int d, const int* _sizes, int _type)
}catch(...)
{
allocator = 0;
size_t total = alignSize(step.p[0]*size.p[0], (int)sizeof(*refcount));
data = datastart = (uchar*)fastMalloc(total + (int)sizeof(*refcount));
refcount = (int*)(data + total);
size_t totalSize = alignSize(step.p[0]*size.p[0], (int)sizeof(*refcount));
data = datastart = (uchar*)fastMalloc(totalSize + (int)sizeof(*refcount));
refcount = (int*)(data + totalSize);
*refcount = 1;
}
#else
@ -262,15 +262,15 @@ void Mat::deallocate()
}
Mat::Mat(const Mat& m, const Range& rowRange, const Range& colRange) : size(&rows)
Mat::Mat(const Mat& m, const Range& _rowRange, const Range& _colRange) : size(&rows)
{
initEmpty();
CV_Assert( m.dims >= 2 );
if( m.dims > 2 )
{
AutoBuffer<Range> rs(m.dims);
rs[0] = rowRange;
rs[1] = colRange;
rs[0] = _rowRange;
rs[1] = _colRange;
for( int i = 2; i < m.dims; i++ )
rs[i] = Range::all();
*this = m(rs);
@ -278,19 +278,19 @@ Mat::Mat(const Mat& m, const Range& rowRange, const Range& colRange) : size(&row
}
*this = m;
if( rowRange != Range::all() && rowRange != Range(0,rows) )
if( _rowRange != Range::all() && _rowRange != Range(0,rows) )
{
CV_Assert( 0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows );
rows = rowRange.size();
data += step*rowRange.start;
CV_Assert( 0 <= _rowRange.start && _rowRange.start <= _rowRange.end && _rowRange.end <= m.rows );
rows = _rowRange.size();
data += step*_rowRange.start;
flags |= SUBMATRIX_FLAG;
}
if( colRange != Range::all() && colRange != Range(0,cols) )
if( _colRange != Range::all() && _colRange != Range(0,cols) )
{
CV_Assert( 0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols );
cols = colRange.size();
data += colRange.start*elemSize();
CV_Assert( 0 <= _colRange.start && _colRange.start <= _colRange.end && _colRange.end <= m.cols );
cols = _colRange.size();
data += _colRange.start*elemSize();
flags &= cols < m.cols ? ~CONTINUOUS_FLAG : -1;
flags |= SUBMATRIX_FLAG;
}
@ -473,14 +473,14 @@ Mat::Mat(const IplImage* img, bool copyData) : size(&rows)
dims = 2;
CV_DbgAssert(CV_IS_IMAGE(img) && img->imageData != 0);
int depth = IPL2CV_DEPTH(img->depth);
int imgdepth = IPL2CV_DEPTH(img->depth);
size_t esz;
step[0] = img->widthStep;
if(!img->roi)
{
CV_Assert(img->dataOrder == IPL_DATA_ORDER_PIXEL);
flags = MAGIC_VAL + CV_MAKETYPE(depth, img->nChannels);
flags = MAGIC_VAL + CV_MAKETYPE(imgdepth, img->nChannels);
rows = img->height; cols = img->width;
datastart = data = (uchar*)img->imageData;
esz = CV_ELEM_SIZE(flags);
@ -489,12 +489,12 @@ Mat::Mat(const IplImage* img, bool copyData) : size(&rows)
{
CV_Assert(img->dataOrder == IPL_DATA_ORDER_PIXEL || img->roi->coi != 0);
bool selectedPlane = img->roi->coi && img->dataOrder == IPL_DATA_ORDER_PLANE;
flags = MAGIC_VAL + CV_MAKETYPE(depth, selectedPlane ? 1 : img->nChannels);
flags = MAGIC_VAL + CV_MAKETYPE(imgdepth, selectedPlane ? 1 : img->nChannels);
rows = img->roi->height; cols = img->roi->width;
esz = CV_ELEM_SIZE(flags);
data = datastart = (uchar*)img->imageData +
(selectedPlane ? (img->roi->coi - 1)*step*img->height : 0) +
img->roi->yOffset*step[0] + img->roi->xOffset*esz;
(selectedPlane ? (img->roi->coi - 1)*step*img->height : 0) +
img->roi->yOffset*step[0] + img->roi->xOffset*esz;
}
datalimit = datastart + step.p[0]*rows;
dataend = datastart + step.p[0]*(rows-1) + esz*cols;
@ -636,11 +636,11 @@ void Mat::push_back(const Mat& elems)
push_back(tmp);
return;
}
if( !data )
{
*this = elems.clone();
return;
}
if( !data )
{
*this = elems.clone();
return;
}
size.p[0] = elems.size.p[0];
bool eq = size == elems.size;
@ -917,6 +917,9 @@ void scalarToRawData(const Scalar& s, void* _buf, int type, int unroll_to)
\*************************************************************************************************/
_InputArray::_InputArray() : flags(0), obj(0) {}
#ifdef OPENCV_CAN_BREAK_BINARY_COMPATIBILITY
_InputArray::~_InputArray() {}
#endif
_InputArray::_InputArray(const Mat& m) : flags(MAT), obj((void*)&m) {}
_InputArray::_InputArray(const vector<Mat>& vec) : flags(STD_VECTOR_MAT), obj((void*)&vec) {}
_InputArray::_InputArray(const double& val) : flags(FIXED_TYPE + FIXED_SIZE + MATX + CV_64F), obj((void*)&val), sz(Size(1,1)) {}
@ -1280,6 +1283,9 @@ bool _InputArray::empty() const
_OutputArray::_OutputArray() {}
#ifdef OPENCV_CAN_BREAK_BINARY_COMPATIBILITY
_OutputArray::~_OutputArray() {}
#endif
_OutputArray::_OutputArray(Mat& m) : _InputArray(m) {}
_OutputArray::_OutputArray(vector<Mat>& vec) : _InputArray(vec) {}
@ -1297,38 +1303,38 @@ bool _OutputArray::fixedType() const
return (flags & FIXED_TYPE) == FIXED_TYPE;
}
void _OutputArray::create(Size _sz, int type, int i, bool allowTransposed, int fixedDepthMask) const
void _OutputArray::create(Size _sz, int mtype, int i, bool allowTransposed, int fixedDepthMask) const
{
int k = kind();
if( k == MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((Mat*)obj)->size.operator()() == _sz);
CV_Assert(!fixedType() || ((Mat*)obj)->type() == type);
((Mat*)obj)->create(_sz, type);
CV_Assert(!fixedType() || ((Mat*)obj)->type() == mtype);
((Mat*)obj)->create(_sz, mtype);
return;
}
int sz[] = {_sz.height, _sz.width};
create(2, sz, type, i, allowTransposed, fixedDepthMask);
int sizes[] = {_sz.height, _sz.width};
create(2, sizes, mtype, i, allowTransposed, fixedDepthMask);
}
void _OutputArray::create(int rows, int cols, int type, int i, bool allowTransposed, int fixedDepthMask) const
void _OutputArray::create(int rows, int cols, int mtype, int i, bool allowTransposed, int fixedDepthMask) const
{
int k = kind();
if( k == MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((Mat*)obj)->size.operator()() == Size(cols, rows));
CV_Assert(!fixedType() || ((Mat*)obj)->type() == type);
((Mat*)obj)->create(rows, cols, type);
CV_Assert(!fixedType() || ((Mat*)obj)->type() == mtype);
((Mat*)obj)->create(rows, cols, mtype);
return;
}
int sz[] = {rows, cols};
create(2, sz, type, i, allowTransposed, fixedDepthMask);
int sizes[] = {rows, cols};
create(2, sizes, mtype, i, allowTransposed, fixedDepthMask);
}
void _OutputArray::create(int dims, const int* size, int type, int i, bool allowTransposed, int fixedDepthMask) const
void _OutputArray::create(int dims, const int* sizes, int mtype, int i, bool allowTransposed, int fixedDepthMask) const
{
int k = kind();
type = CV_MAT_TYPE(type);
mtype = CV_MAT_TYPE(mtype);
if( k == MAT )
{
@ -1343,24 +1349,24 @@ void _OutputArray::create(int dims, const int* size, int type, int i, bool allow
}
if( dims == 2 && m.dims == 2 && m.data &&
m.type() == type && m.rows == size[1] && m.cols == size[0] )
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
if(fixedType())
{
if(CV_MAT_CN(type) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
type = m.type();
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(CV_MAT_TYPE(type) == m.type());
CV_Assert(CV_MAT_TYPE(mtype) == m.type());
}
if(fixedSize())
{
CV_Assert(m.dims == dims);
for(int j = 0; j < dims; ++j)
CV_Assert(m.size[j] == size[j]);
CV_Assert(m.size[j] == sizes[j]);
}
m.create(dims, size, type);
m.create(dims, sizes, mtype);
return;
}
@ -1368,16 +1374,16 @@ void _OutputArray::create(int dims, const int* size, int type, int i, bool allow
{
CV_Assert( i < 0 );
int type0 = CV_MAT_TYPE(flags);
CV_Assert( type == type0 || (CV_MAT_CN(type) == 1 && ((1 << type0) & fixedDepthMask) != 0) );
CV_Assert( dims == 2 && ((size[0] == sz.height && size[1] == sz.width) ||
(allowTransposed && size[0] == sz.width && size[1] == sz.height)));
CV_Assert( mtype == type0 || (CV_MAT_CN(mtype) == 1 && ((1 << type0) & fixedDepthMask) != 0) );
CV_Assert( dims == 2 && ((sizes[0] == sz.height && sizes[1] == sz.width) ||
(allowTransposed && sizes[0] == sz.width && sizes[1] == sz.height)));
return;
}
if( k == STD_VECTOR || k == STD_VECTOR_VECTOR )
{
CV_Assert( dims == 2 && (size[0] == 1 || size[1] == 1 || size[0]*size[1] == 0) );
size_t len = size[0]*size[1] > 0 ? size[0] + size[1] - 1 : 0;
CV_Assert( dims == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) );
size_t len = sizes[0]*sizes[1] > 0 ? sizes[0] + sizes[1] - 1 : 0;
vector<uchar>* v = (vector<uchar>*)obj;
if( k == STD_VECTOR_VECTOR )
@ -1396,7 +1402,7 @@ void _OutputArray::create(int dims, const int* size, int type, int i, bool allow
CV_Assert( i < 0 );
int type0 = CV_MAT_TYPE(flags);
CV_Assert( type == type0 || (CV_MAT_CN(type) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0) );
CV_Assert( mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0) );
int esz = CV_ELEM_SIZE(type0);
CV_Assert(!fixedSize() || len == ((vector<uchar>*)v)->size() / esz);
@ -1469,20 +1475,20 @@ void _OutputArray::create(int dims, const int* size, int type, int i, bool allow
if( i < 0 )
{
CV_Assert( dims == 2 && (size[0] == 1 || size[1] == 1 || size[0]*size[1] == 0) );
size_t len = size[0]*size[1] > 0 ? size[0] + size[1] - 1 : 0, len0 = v.size();
CV_Assert( dims == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) );
size_t len = sizes[0]*sizes[1] > 0 ? sizes[0] + sizes[1] - 1 : 0, len0 = v.size();
CV_Assert(!fixedSize() || len == len0);
v.resize(len);
if( fixedType() )
{
int type = CV_MAT_TYPE(flags);
int _type = CV_MAT_TYPE(flags);
for( size_t j = len0; j < len; j++ )
{
if( v[i].type() == type )
if( v[i].type() == _type )
continue;
CV_Assert( v[i].empty() );
v[i].flags = (v[i].flags & ~CV_MAT_TYPE_MASK) | type;
v[i].flags = (v[i].flags & ~CV_MAT_TYPE_MASK) | _type;
}
}
return;
@ -1500,25 +1506,25 @@ void _OutputArray::create(int dims, const int* size, int type, int i, bool allow
}
if( dims == 2 && m.dims == 2 && m.data &&
m.type() == type && m.rows == size[1] && m.cols == size[0] )
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
if(fixedType())
{
if(CV_MAT_CN(type) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
type = m.type();
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(!fixedType() || (CV_MAT_CN(type) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0));
CV_Assert(!fixedType() || (CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0));
}
if(fixedSize())
{
CV_Assert(m.dims == dims);
for(int j = 0; j < dims; ++j)
CV_Assert(m.size[j] == size[j]);
CV_Assert(m.size[j] == sizes[j]);
}
m.create(dims, size, type);
m.create(dims, sizes, mtype);
}
}
@ -1763,7 +1769,7 @@ transpose_( const uchar* src, size_t sstep, uchar* dst, size_t dstep, Size sz )
{
int i=0, j, m = sz.width, n = sz.height;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for(; i <= m - 4; i += 4 )
{
T* d0 = (T*)(dst + dstep*i);
@ -1795,7 +1801,7 @@ transpose_( const uchar* src, size_t sstep, uchar* dst, size_t dstep, Size sz )
{
T* d0 = (T*)(dst + dstep*i);
j = 0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for(; j <= n - 4; j += 4 )
{
const T* s0 = (const T*)(src + i*sizeof(T) + sstep*j);
@ -1927,10 +1933,10 @@ void cv::completeSymm( InputOutputArray _m, bool LtoR )
cv::Mat cv::Mat::cross(InputArray _m) const
{
Mat m = _m.getMat();
int t = type(), d = CV_MAT_DEPTH(t);
CV_Assert( dims <= 2 && m.dims <= 2 && size() == m.size() && t == m.type() &&
int tp = type(), d = CV_MAT_DEPTH(tp);
CV_Assert( dims <= 2 && m.dims <= 2 && size() == m.size() && tp == m.type() &&
((rows == 3 && cols == 1) || (cols*channels() == 3 && rows == 1)));
Mat result(rows, cols, t);
Mat result(rows, cols, tp);
if( d == CV_32F )
{
@ -1985,7 +1991,7 @@ reduceR_( const Mat& srcmat, Mat& dstmat )
{
src += srcstep;
i = 0;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for(; i <= size.width - 4; i += 4 )
{
WT s0, s1;
@ -2044,7 +2050,7 @@ reduceC_( const Mat& srcmat, Mat& dstmat )
dst[k] = (ST)a0;
}
}
}
}
}
typedef void (*ReduceFunc)( const Mat& src, Mat& dst );
@ -2577,8 +2583,8 @@ double cv::kmeans( InputArray _data, int K,
sample = data.ptr<float>(i);
k = labels[i];
float* center = centers.ptr<float>(k);
j=0;
#if CV_ENABLE_UNROLLED
j=0;
#if CV_ENABLE_UNROLLED
for(; j <= dims - 4; j += 4 )
{
float t0 = center[j] + sample[j];
@ -2843,7 +2849,7 @@ cvRange( CvArr* arr, double start, double end )
CV_IMPL void
cvSort( const CvArr* _src, CvArr* _dst, CvArr* _idx, int flags )
{
cv::Mat src = cv::cvarrToMat(_src), dst, idx;
cv::Mat src = cv::cvarrToMat(_src);
if( _idx )
{
@ -3260,7 +3266,7 @@ convertScaleData_(const void* _from, void* _to, int cn, double alpha, double bet
to[i] = saturate_cast<T2>(from[i]*alpha + beta);
}
ConvertData getConvertData(int fromType, int toType)
static ConvertData getConvertData(int fromType, int toType)
{
static ConvertData tab[][8] =
{{ convertData_<uchar, uchar>, convertData_<uchar, schar>,
@ -3305,7 +3311,7 @@ ConvertData getConvertData(int fromType, int toType)
return func;
}
ConvertScaleData getConvertScaleData(int fromType, int toType)
static ConvertScaleData getConvertScaleData(int fromType, int toType)
{
static ConvertScaleData tab[][8] =
{{ convertScaleData_<uchar, uchar>, convertScaleData_<uchar, schar>,
@ -3408,22 +3414,22 @@ SparseMat::SparseMat(const Mat& m)
int i, idx[CV_MAX_DIM] = {0}, d = m.dims, lastSize = m.size[d - 1];
size_t esz = m.elemSize();
uchar* ptr = m.data;
uchar* dptr = m.data;
for(;;)
{
for( i = 0; i < lastSize; i++, ptr += esz )
for( i = 0; i < lastSize; i++, dptr += esz )
{
if( isZeroElem(ptr, esz) )
if( isZeroElem(dptr, esz) )
continue;
idx[d-1] = i;
uchar* to = newNode(idx, hash(idx));
copyElem( ptr, to, esz );
copyElem( dptr, to, esz );
}
for( i = d - 2; i >= 0; i-- )
{
ptr += m.step[i] - m.size[i+1]*m.step[i+1];
dptr += m.step[i] - m.size[i+1]*m.step[i+1];
if( ++idx[i] < m.size[i] )
break;
idx[i] = 0;

204
modules/core/src/opengl_interop.cpp
View File

@ -163,11 +163,11 @@ void icvSetOpenGlFuncTab(const CvOpenGlFuncTab* tab)
void cv::gpu::setGlDevice(int device)
{
#ifndef HAVE_CUDA
(void)device;
(void)device;
throw_nocuda;
#else
#ifndef HAVE_OPENGL
(void)device;
(void)device;
throw_nogl;
#else
if (!glFuncTab()->isGlContextInitialized())
@ -484,57 +484,57 @@ inline void cv::GlBuffer::Impl::unmapDevice(cudaStream_t stream)
#endif // HAVE_OPENGL
cv::GlBuffer::GlBuffer(Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage)
cv::GlBuffer::GlBuffer(Usage _usage) : rows_(0), cols_(0), type_(0), usage_(_usage)
{
#ifndef HAVE_OPENGL
(void)usage;
(void)_usage;
throw_nogl;
#else
impl_ = Impl::empty();
#endif
}
cv::GlBuffer::GlBuffer(int rows, int cols, int type, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage)
cv::GlBuffer::GlBuffer(int _rows, int _cols, int _type, Usage _usage) : rows_(0), cols_(0), type_(0), usage_(_usage)
{
#ifndef HAVE_OPENGL
(void)rows;
(void)cols;
(void)type;
(void)usage;
(void)_rows;
(void)_cols;
(void)_type;
(void)_usage;
throw_nogl;
#else
impl_ = new Impl(rows, cols, type, usage);
rows_ = rows;
cols_ = cols;
type_ = type;
impl_ = new Impl(_rows, _cols, _type, _usage);
rows_ = _rows;
cols_ = _cols;
type_ = _type;
#endif
}
cv::GlBuffer::GlBuffer(Size size, int type, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage)
cv::GlBuffer::GlBuffer(Size _size, int _type, Usage _usage) : rows_(0), cols_(0), type_(0), usage_(_usage)
{
#ifndef HAVE_OPENGL
(void)size;
(void)type;
(void)usage;
(void)_size;
(void)_type;
(void)_usage;
throw_nogl;
#else
impl_ = new Impl(size.height, size.width, type, usage);
rows_ = size.height;
cols_ = size.width;
type_ = type;
impl_ = new Impl(_size.height, _size.width, _type, _usage);
rows_ = _size.height;
cols_ = _size.width;
type_ = _type;
#endif
}
cv::GlBuffer::GlBuffer(InputArray mat_, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage)
cv::GlBuffer::GlBuffer(InputArray mat_, Usage _usage) : rows_(0), cols_(0), type_(0), usage_(_usage)
{
#ifndef HAVE_OPENGL
(void)mat_;
(void)usage;
(void)mat_;
(void)_usage;
throw_nogl;
#else
int kind = mat_.kind();
Size size = mat_.size();
int type = mat_.type();
Size _size = mat_.size();
int _type = mat_.type();
if (kind == _InputArray::GPU_MAT)
{
@ -542,38 +542,38 @@ cv::GlBuffer::GlBuffer(InputArray mat_, Usage usage) : rows_(0), cols_(0), type_
throw_nocuda;
#else
GpuMat d_mat = mat_.getGpuMat();
impl_ = new Impl(d_mat.rows, d_mat.cols, d_mat.type(), usage);
impl_ = new Impl(d_mat.rows, d_mat.cols, d_mat.type(), _usage);
impl_->copyFrom(d_mat);
#endif
}
else
{
Mat mat = mat_.getMat();
impl_ = new Impl(mat, usage);
impl_ = new Impl(mat, _usage);
}
rows_ = size.height;
cols_ = size.width;
type_ = type;
rows_ = _size.height;
cols_ = _size.width;
type_ = _type;
#endif
}
void cv::GlBuffer::create(int rows, int cols, int type, Usage usage)
void cv::GlBuffer::create(int _rows, int _cols, int _type, Usage _usage)
{
#ifndef HAVE_OPENGL
(void)rows;
(void)cols;
(void)type;
(void)usage;
(void)_rows;
(void)_cols;
(void)_type;
(void)_usage;
throw_nogl;
#else
if (rows_ != rows || cols_ != cols || type_ != type || usage_ != usage)
if (rows_ != _rows || cols_ != _cols || type_ != _type || usage_ != _usage)
{
impl_ = new Impl(rows, cols, type, usage);
rows_ = rows;
cols_ = cols;
type_ = type;
usage_ = usage;
impl_ = new Impl(_rows, _cols, _type, _usage);
rows_ = _rows;
cols_ = _cols;
type_ = _type;
usage_ = _usage;
}
#endif
}
@ -590,14 +590,14 @@ void cv::GlBuffer::release()
void cv::GlBuffer::copyFrom(InputArray mat_)
{
#ifndef HAVE_OPENGL
(void)mat_;
(void)mat_;
throw_nogl;
#else
int kind = mat_.kind();
Size size = mat_.size();
int type = mat_.type();
Size _size = mat_.size();
int _type = mat_.type();
create(size, type);
create(_size, _type);
switch (kind)
{
@ -926,45 +926,45 @@ cv::GlTexture::GlTexture() : rows_(0), cols_(0), type_(0), buf_(GlBuffer::TEXTUR
#endif
}
cv::GlTexture::GlTexture(int rows, int cols, int type) : rows_(0), cols_(0), type_(0), buf_(GlBuffer::TEXTURE_BUFFER)
cv::GlTexture::GlTexture(int _rows, int _cols, int _type) : rows_(0), cols_(0), type_(0), buf_(GlBuffer::TEXTURE_BUFFER)
{
#ifndef HAVE_OPENGL
(void)rows;
(void)cols;
(void)type;
(void)_rows;
(void)_cols;
(void)_type;
throw_nogl;
#else
impl_ = new Impl(rows, cols, type);
rows_ = rows;
cols_ = cols;
type_ = type;
impl_ = new Impl(_rows, _cols, _type);
rows_ = _rows;
cols_ = _cols;
type_ = _type;
#endif
}
cv::GlTexture::GlTexture(Size size, int type) : rows_(0), cols_(0), type_(0), buf_(GlBuffer::TEXTURE_BUFFER)
cv::GlTexture::GlTexture(Size _size, int _type) : rows_(0), cols_(0), type_(0), buf_(GlBuffer::TEXTURE_BUFFER)
{
#ifndef HAVE_OPENGL
(void)size;
(void)type;
(void)_size;
(void)_type;
throw_nogl;
#else
impl_ = new Impl(size.height, size.width, type);
rows_ = size.height;
cols_ = size.width;
type_ = type;
impl_ = new Impl(_size.height, _size.width, _type);
rows_ = _size.height;
cols_ = _size.width;
type_ = _type;
#endif
}
cv::GlTexture::GlTexture(InputArray mat_, bool bgra) : rows_(0), cols_(0), type_(0), buf_(GlBuffer::TEXTURE_BUFFER)
{
#ifndef HAVE_OPENGL
(void)mat_;
(void)bgra;
(void)mat_;
(void)bgra;
throw_nogl;
#else
int kind = mat_.kind();
Size size = mat_.size();
int type = mat_.type();
Size _size = mat_.size();
int _type = mat_.type();
switch (kind)
{
@ -994,26 +994,26 @@ cv::GlTexture::GlTexture(InputArray mat_, bool bgra) : rows_(0), cols_(0), type_
}
}
rows_ = size.height;
cols_ = size.width;
type_ = type;
rows_ = _size.height;
cols_ = _size.width;
type_ = _type;
#endif
}
void cv::GlTexture::create(int rows, int cols, int type)
void cv::GlTexture::create(int _rows, int _cols, int _type)
{
#ifndef HAVE_OPENGL
(void)rows;
(void)cols;
(void)type;
(void)_rows;
(void)_cols;
(void)_type;
throw_nogl;
#else
if (rows_ != rows || cols_ != cols || type_ != type)
if (rows_ != _rows || cols_ != _cols || type_ != _type)
{
impl_ = new Impl(rows, cols, type);
rows_ = rows;
cols_ = cols;
type_ = type;
impl_ = new Impl(_rows, _cols, _type);
rows_ = _rows;
cols_ = _cols;
type_ = _type;
}
#endif
}
@ -1030,15 +1030,15 @@ void cv::GlTexture::release()
void cv::GlTexture::copyFrom(InputArray mat_, bool bgra)
{
#ifndef HAVE_OPENGL
(void)mat_;
(void)bgra;
(void)mat_;
(void)bgra;
throw_nogl;
#else
int kind = mat_.kind();
Size size = mat_.size();
int type = mat_.type();
Size _size = mat_.size();
int _type = mat_.type();
create(size, type);
create(_size, _type);
switch(kind)
{
@ -1244,8 +1244,8 @@ void cv::GlArrays::unbind() const
////////////////////////////////////////////////////////////////////////
// GlFont
cv::GlFont::GlFont(const string& family, int height, Weight weight, Style style)
: family_(family), height_(height), weight_(weight), style_(style), base_(0)
cv::GlFont::GlFont(const string& _family, int _height, Weight _weight, Style _style)
: family_(_family), height_(_height), weight_(_weight), style_(_style), base_(0)
{
#ifndef HAVE_OPENGL
throw_nogl;
@ -1253,7 +1253,7 @@ cv::GlFont::GlFont(const string& family, int height, Weight weight, Style style)
base_ = glGenLists(256);
CV_CheckGlError();
glFuncTab()->generateBitmapFont(family, height, weight, (style & STYLE_ITALIC) != 0, (style & STYLE_UNDERLINE) != 0, 0, 256, base_);
glFuncTab()->generateBitmapFont(family_, height_, weight_, (style_ & STYLE_ITALIC) != 0, (style_ & STYLE_UNDERLINE) != 0, 0, 256, base_);
#endif
}
@ -1304,10 +1304,10 @@ namespace
Ptr<GlFont> cv::GlFont::get(const std::string& family, int height, Weight weight, Style style)
{
#ifndef HAVE_OPENGL
(void)family;
(void)height;
(void)weight;
(void)style;
(void)family;
(void)height;
(void)weight;
(void)style;
throw_nogl;
return Ptr<GlFont>();
#else
@ -1333,9 +1333,9 @@ Ptr<GlFont> cv::GlFont::get(const std::string& family, int height, Weight weight
void cv::render(const GlTexture& tex, Rect_<double> wndRect, Rect_<double> texRect)
{
#ifndef HAVE_OPENGL
(void)tex;
(void)wndRect;
(void)texRect;
(void)tex;
(void)wndRect;
(void)texRect;
throw_nogl;
#else
if (!tex.empty())
@ -1368,9 +1368,9 @@ void cv::render(const GlTexture& tex, Rect_<double> wndRect, Rect_<double> texRe
void cv::render(const GlArrays& arr, int mode, Scalar color)
{
#ifndef HAVE_OPENGL
(void)arr;
(void)mode;
(void)color;
(void)arr;
(void)mode;
(void)color;
throw_nogl;
#else
glColor3d(color[0] / 255.0, color[1] / 255.0, color[2] / 255.0);
@ -1386,10 +1386,10 @@ void cv::render(const GlArrays& arr, int mode, Scalar color)
void cv::render(const string& str, const Ptr<GlFont>& font, Scalar color, Point2d pos)
{
#ifndef HAVE_OPENGL
(void)str;
(void)font;
(void)color;
(void)pos;
(void)str;
(void)font;
(void)color;
(void)pos;
throw_nogl;
#else
glPushAttrib(GL_DEPTH_BUFFER_BIT);
@ -1544,9 +1544,9 @@ void cv::GlCamera::setupModelViewMatrix() const
bool icvCheckGlError(const char* file, const int line, const char* func)
{
#ifndef HAVE_OPENGL
(void)file;
(void)line;
(void)func;
(void)file;
(void)line;
(void)func;
return true;
#else
GLenum err = glGetError();

2
modules/core/src/out.cpp
View File

@ -243,7 +243,7 @@ static CFormatter cFormatter;
static const Formatter* g_defaultFormatter0 = &matlabFormatter;
static const Formatter* g_defaultFormatter = &matlabFormatter;
bool my_streq(const char* a, const char* b)
static bool my_streq(const char* a, const char* b)
{
size_t i, alen = strlen(a), blen = strlen(b);
if( alen != blen )

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