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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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15
3rdparty/libjasper/CMakeLists.txt vendored
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@ -7,10 +7,8 @@ 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)
@ -22,16 +20,11 @@ file(GLOB lib_ext_hdrs jasper/*.h)
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)
@ -39,10 +32,6 @@ 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}

9
3rdparty/libjpeg/CMakeLists.txt vendored
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@ -4,11 +4,8 @@
# ----------------------------------------------------------------------------
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)
@ -18,10 +15,6 @@ file(GLOB lib_hdrs *.h)
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 "${CMAKE_C_FLAGS} -fPIC")
@ -32,6 +25,8 @@ if(CMAKE_COMPILER_IS_GNUCXX)
set_source_files_properties(jcdctmgr.c PROPERTIES COMPILE_FLAGS "-O1")
endif()
ocv_warnings_disable(CMAKE_C_FLAGS -Wcast-align -Wshadow)
set_target_properties(${JPEG_LIBRARY}
PROPERTIES OUTPUT_NAME ${JPEG_LIBRARY}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"

8
3rdparty/libpng/CMakeLists.txt vendored
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@ -4,8 +4,6 @@
# ----------------------------------------------------------------------------
project(${PNG_LIBRARY})
# List of C++ files:
ocv_include_directories("${CMAKE_CURRENT_SOURCE_DIR}" ${ZLIB_INCLUDE_DIR})
file(GLOB lib_srcs *.c)
@ -17,16 +15,14 @@ file(GLOB lib_hdrs *.h)
add_library(${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}"

8
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")

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

5
3rdparty/tbb/CMakeLists.txt vendored
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@ -119,7 +119,10 @@ 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

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
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@ -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;

45
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);
@ -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"

5
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>
@ -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"

156
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 "${OPENCV_EXTRA_C_FLAGS} -mstackrealign")
add_extra_compiler_option(-mstackrealign)
if(NOT HAVE_CXX_MSTACKREALIGN)
add_extra_compiler_option(-mpreferred-stack-boundary=2)
endif()
endif()
if(OPENCV_CAN_BREAK_BINARY_COMPATIBILITY)
add_definitions(-DOPENCV_CAN_BREAK_BINARY_COMPATIBILITY)
endif()
if(CMAKE_COMPILER_IS_GNUCXX)
# High level of warnings.
set(OPENCV_EXTRA_C_FLAGS "${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 "${OPENCV_EXTRA_C_FLAGS} -msse4.2")
add_extra_compiler_option(-msse4.2)
endif()
endif()
endif()
@ -115,38 +156,39 @@ if(CMAKE_COMPILER_IS_GNUCXX)
if(X86 OR X86_64)
if(NOT APPLE AND CMAKE_SIZEOF_VOID_P EQUAL 4)
if(ENABLE_SSE2)
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mfpmath=sse")# !! important - be on the same wave with x64 compilers
add_extra_compiler_option(-mfpmath=sse)# !! important - be on the same wave with x64 compilers
else()
set(OPENCV_EXTRA_C_FLAGS "${OPENCV_EXTRA_C_FLAGS} -mfpmath=387")
add_extra_compiler_option(-mfpmath=387)
endif()
endif()
endif()
# Profiling?
if(ENABLE_PROFILING)
set(OPENCV_EXTRA_C_FLAGS "${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()

8
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 ${DIRINC})
if(item MATCHES "^${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

21
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;
@ -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++)
@ -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 )
@ -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)
{
@ -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

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;
}

16
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;
}
@ -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;

68
modules/calib3d/src/epnp.cpp
View File

@ -500,8 +500,7 @@ void epnp::compute_A_and_b_gauss_newton(const double * l_6x10, const double * rh
}
}
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;
@ -510,7 +509,8 @@ 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);
qr_solve(&A, &B, &X);
@ -524,50 +524,61 @@ 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;
}
double sigma = sqrt(sum);
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(sum2);
if (*ppAkk < 0)
sigma = -sigma;
*ppAkk += sigma;
A1[k] = sigma * *ppAkk;
A2[k] = -eta * sigma;
for(int j = k + 1; j < nc; j++) {
for(int j = k + 1; j < nc; j++)
{
double * ppAik = ppAkk, sum = 0;
for(int i = k; i < nr; i++) {
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++) {
for(int i = k; i < nr; i++)
{
ppAik[j - k] -= tau * *ppAik;
ppAik += nc;
}
@ -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++;
}

18
modules/calib3d/src/p3p.cpp
View File

@ -362,20 +362,20 @@ bool p3p::jacobi_4x4(double * A, double * D, double * U)
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;
double hh = D[j] - D[i], t;
if (fabs(hh) + eps_machine == fabs(hh))
t = Aij / hh;
else {
double theta = 0.5 * h / Aij;
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;
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);

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

12
modules/calib3d/src/solvepnp.cpp
View File

@ -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);
@ -162,7 +162,7 @@ namespace cv
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)
{
@ -253,10 +253,10 @@ 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);

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];
}

16
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 )

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

@ -529,14 +529,14 @@ void CV_CameraCalibrationTest::run( int start_from )
/* ---- Reproject points to the image ---- */
for( currImage = 0; currImage < numImages; currImage++ )
{
int numPoints = etalonSize.width * etalonSize.height;
project( numPoints,
objectPoints + currImage * numPoints,
int nPoints = etalonSize.width * etalonSize.height;
project( nPoints,
objectPoints + currImage * nPoints,
rotMatrs + currImage * 9,
transVects + currImage * 3,
cameraMatrix,
distortion,
reprojectPoints + currImage * numPoints);
reprojectPoints + currImage * nPoints);
}
/* ----- Compute reprojection error ----- */

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);
}
}
};

16
modules/calib3d/test/test_homography.cpp
View File

@ -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;

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;
}

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

26
modules/contrib/src/ba.cpp
View File

@ -67,15 +67,15 @@ LevMarqSparse::LevMarqSparse(int npoints, // number of points
// 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
TermCriteria _criteria, // termination criteria
// callback for estimation of Jacobian matrices
void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
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,
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
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;
@ -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() {
@ -443,9 +443,11 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
} //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;
}
if (cb)
cb(iters, prevErrNorm, user_data);
//compute V_i and eb_i
@ -676,10 +678,12 @@ void LevMarqSparse::optimize(CvMat &_vis) { //main function that runs minimizati
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
{
@ -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
@ -886,9 +890,9 @@ void fjac(int /*i*/, int /*j*/, CvMat *point_params, CvMat* cam_params, CvMat* A
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 };
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 );
@ -975,12 +979,12 @@ 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);
};

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 );

353
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);
// 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;
}
// 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

28
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()
@ -342,20 +342,20 @@ 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)
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;
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
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
setup(_retinaParameters);
@ -419,16 +419,17 @@ bool Retina::_convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::
if(imageNumberOfChannels==4)
{
// create a cv::Mat table (for RGBA planes)
cv::Mat planes[] =
cv::Mat planes[4] =
{
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)
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)
}
else if (imageNumberOfChannels==3)
{
// create a cv::Mat table (for RGB planes)
cv::Mat planes[] =
@ -439,7 +440,8 @@ bool Retina::_convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::
};
// split color cv::Mat in 3 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 3> >(inputMatToConvert), planes);
}else if(imageNumberOfChannels==1)
}
else if(imageNumberOfChannels==1)
{
// create a cv::Mat header for the valarray
cv::Mat dst(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]);

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;
}

22
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
@ -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
{
@ -851,11 +851,11 @@ void cv::SpinImageModel::repackSpinImages(const vector<uchar>& mask, Mat& spinIm
for (; first != last; ++first)
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);
}
}

10
modules/contrib/src/stereovar.cpp
View File

@ -204,10 +204,10 @@ void StereoVar::VariationalSolver(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level)
break;
}
float fi = Fi;
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);}
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]);
@ -219,8 +219,8 @@ void StereoVar::VariationalSolver(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level)
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) ;
+ _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];

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;

4
modules/core/include/opencv2/core/core_c.h
View File

@ -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;
}

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

35
modules/core/include/opencv2/core/internal.hpp
View File

@ -104,17 +104,21 @@ CV_INLINE IppiSize ippiSize(int width, int height)
}
#endif
#if defined __SSE2__ || _MSC_VER >= 1300
#if defined __SSE2__ || (defined _MSC_VER && _MSC_VER >= 1300)
# include "emmintrin.h"
# define CV_SSE 1
# define CV_SSE2 1
#if defined __SSE3__ || _MSC_VER >= 1500
# 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
@ -123,7 +127,7 @@ CV_INLINE IppiSize ippiSize(int width, int height)
# define CV_SSSE3 0
#endif
#if defined ANDROID && defined __ARM_NEON__ && defined __GNUC__
#if defined ANDROID && defined __ARM_NEON__
# include "arm_neon.h"
# define CV_NEON 1
@ -135,12 +139,6 @@ CV_INLINE IppiSize ippiSize(int width, int height)
# define CPU_HAS_NEON_FEATURE (false)
#endif
#ifdef CV_ICC
#define CV_ENABLE_UNROLLED 0
#else
#define CV_ENABLE_UNROLLED 1
#endif
#ifndef IPPI_CALL
# define IPPI_CALL(func) CV_Assert((func) >= 0)
#endif
@ -164,9 +162,10 @@ CV_INLINE IppiSize ippiSize(int width, int height)
#ifdef __cplusplus
#ifdef HAVE_TBB
namespace cv
{
#ifdef HAVE_TBB
typedef tbb::blocked_range<int> BlockedRange;
template<typename Body> static inline
@ -191,10 +190,7 @@ CV_INLINE IppiSize ippiSize(int width, int height)
typedef tbb::concurrent_vector<Rect> ConcurrentRectVector;
typedef tbb::concurrent_vector<double> ConcurrentDoubleVector;
}
#else
namespace cv
{
class BlockedRange
{
public:
@ -230,9 +226,8 @@ CV_INLINE IppiSize ippiSize(int width, int height)
{
body(range);
}
}
#endif
} //namespace cv
#define CV_INIT_ALGORITHM(classname, algname, memberinit) \
static Algorithm* create##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
@ -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__

24
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
@ -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()

13
modules/core/include/opencv2/core/opengl_interop.hpp
View File

@ -70,9 +70,9 @@ namespace cv
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 create(Size size, int type, Usage usage);
void create(int rows, int cols, int type);
void create(Size size, int type);
void release();
@ -130,7 +130,7 @@ namespace cv
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 create(Size size, int type);
void release();
//! copy from host/device memory
@ -318,6 +318,11 @@ namespace cv
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

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;
}

16
modules/core/include/opencv2/core/types_c.h
View File

@ -43,12 +43,15 @@
#ifndef __OPENCV_CORE_TYPES_H__
#define __OPENCV_CORE_TYPES_H__
#if !defined _CRT_SECURE_NO_DEPRECATE && _MSC_VER > 1300
#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>
@ -70,7 +73,13 @@
# define CV_ICC __INTEL_COMPILER
#endif
#if (_MSC_VER >= 1400 && defined _M_X64) || (__GNUC__ >= 4 && defined __x86_64__)
#if defined CV_ICC && !defined CV_ENABLE_UNROLLED
# define CV_ENABLE_UNROLLED 0
#else
# define CV_ENABLE_UNROLLED 1
#endif
#if (defined _M_X64 && defined _MSC_VER && _MSC_VER >= 1400) || (__GNUC__ >= 4 && defined __x86_64__)
# if defined WIN32
# include <intrin.h>
# endif
@ -96,6 +105,7 @@
#elif defined __IPL_H__
# define HAVE_IPL
#endif
#endif // SKIP_INCLUDES
#if defined WIN32 || defined _WIN32
@ -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);
}

2
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 )
{

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;

26
modules/core/src/copy.cpp
View File

@ -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;
}

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);
}

20
modules/core/src/matmul.cpp
View File

@ -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 );
@ -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();
}
@ -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' )

138
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);
@ -489,7 +489,7 @@ 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 +
@ -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);
}
}
@ -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 )
{
@ -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;

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

@ -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)_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
}
@ -594,10 +594,10 @@ void cv::GlBuffer::copyFrom(InputArray 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)
{
@ -926,32 +926,32 @@ 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
}
@ -963,8 +963,8 @@ cv::GlTexture::GlTexture(InputArray mat_, bool bgra) : rows_(0), cols_(0), type_
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
}
@ -1035,10 +1035,10 @@ void cv::GlTexture::copyFrom(InputArray mat_, bool 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
}

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 )

5
modules/core/src/precomp.hpp
View File

@ -43,11 +43,6 @@
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#if defined _MSC_VER && _MSC_VER >= 1200
// disable warnings related to inline functions
#pragma warning( disable: 4251 4711 4710 4514 )
#endif
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif

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

@ -962,7 +962,7 @@ static const uchar popCountTable4[] =
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
};
int normHamming(const uchar* a, int n)
static int normHamming(const uchar* a, int n)
{
int i = 0, result = 0;
#if CV_NEON
@ -1020,7 +1020,7 @@ int normHamming(const uchar* a, const uchar* b, int n)
return result;
}
int normHamming(const uchar* a, int n, int cellSize)
static int normHamming(const uchar* a, int n, int cellSize)
{
if( cellSize == 1 )
return normHamming(a, n);

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