generic-library/opencv
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Merge with master and fix conflicts

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This commit is contained in:
mshabunin 2014-08-13 18:24:11 +04:00
commit 3ed89a8879
778 changed files with 40820 additions and 452349 deletions
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2
3rdparty/libjpeg/CMakeLists.txt vendored
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@ -9,7 +9,7 @@ ocv_include_directories(${CMAKE_CURRENT_SOURCE_DIR})
file(GLOB lib_srcs *.c)
file(GLOB lib_hdrs *.h)
if(ANDROID OR IOS)
if(ANDROID OR IOS OR APPLE)
ocv_list_filterout(lib_srcs jmemansi.c)
else()
ocv_list_filterout(lib_srcs jmemnobs.c)

10
3rdparty/readme.txt vendored
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@ -1,5 +1,5 @@
This folder contains libraries and headers of a few very popular still image codecs
used by highgui module.
used by imgcodecs module.
The libraries and headers are preferably to build Win32 and Win64 versions of OpenCV.
On UNIX systems all the libraries are automatically detected by configure script.
In order to use these versions of libraries instead of system ones on UNIX systems you
@ -11,7 +11,7 @@ libjpeg 8d (8.4) - The Independent JPEG Group's JPEG software.
See IGJ home page http://www.ijg.org
for details and links to the source code
HAVE_JPEG preprocessor flag must be set to make highgui use libjpeg.
HAVE_JPEG preprocessor flag must be set to make imgcodecs use libjpeg.
On UNIX systems configure script takes care of it.
------------------------------------------------------------------------------------
libpng 1.5.12 - Portable Network Graphics library.
@ -19,7 +19,7 @@ libpng 1.5.12 - Portable Network Graphics library.
See libpng home page http://www.libpng.org
for details and links to the source code
HAVE_PNG preprocessor flag must be set to make highgui use libpng.
HAVE_PNG preprocessor flag must be set to make imgcodecs use libpng.
On UNIX systems configure script takes care of it.
------------------------------------------------------------------------------------
libtiff 4.0.2 - Tag Image File Format (TIFF) Software
@ -28,7 +28,7 @@ libtiff 4.0.2 - Tag Image File Format (TIFF) Software
See libtiff home page http://www.remotesensing.org/libtiff/
for details and links to the source code
HAVE_TIFF preprocessor flag must be set to make highgui use libtiff.
HAVE_TIFF preprocessor flag must be set to make imgcodecs use libtiff.
On UNIX systems configure script takes care of it.
In this build support for ZIP (LZ77 compression) is turned on.
------------------------------------------------------------------------------------
@ -37,7 +37,7 @@ zlib 1.2.7 - General purpose LZ77 compression library
See zlib home page http://www.zlib.net
for details and links to the source code
No preprocessor definition is needed to make highgui use this library -
No preprocessor definition is needed to make imgcodecs use this library -
it is included automatically if either libpng or libtiff are used.
------------------------------------------------------------------------------------
jasper-1.900.1 - JasPer is a collection of software

48
CMakeLists.txt
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@ -6,6 +6,8 @@
#
# ----------------------------------------------------------------------------
include(cmake/OpenCVMinDepVersions.cmake)
if(CMAKE_GENERATOR MATCHES Xcode AND XCODE_VERSION VERSION_GREATER 4.3)
@ -135,6 +137,7 @@ OCV_OPTION(WITH_WEBP "Include WebP support" ON
OCV_OPTION(WITH_OPENEXR "Include ILM support via OpenEXR" ON IF (NOT IOS) )
OCV_OPTION(WITH_OPENGL "Include OpenGL support" OFF IF (NOT ANDROID) )
OCV_OPTION(WITH_OPENNI "Include OpenNI support" OFF IF (NOT ANDROID AND NOT IOS) )
OCV_OPTION(WITH_OPENNI2 "Include OpenNI2 support" OFF IF (NOT ANDROID AND NOT IOS) )
OCV_OPTION(WITH_PNG "Include PNG support" ON)
OCV_OPTION(WITH_PVAPI "Include Prosilica GigE support" ON IF (NOT ANDROID AND NOT IOS) )
OCV_OPTION(WITH_GIGEAPI "Include Smartek GigE support" ON IF (NOT ANDROID AND NOT IOS) )
@ -148,8 +151,8 @@ OCV_OPTION(WITH_TIFF "Include TIFF support" ON
OCV_OPTION(WITH_UNICAP "Include Unicap support (GPL)" OFF IF (UNIX AND NOT APPLE AND NOT ANDROID) )
OCV_OPTION(WITH_V4L "Include Video 4 Linux support" ON IF (UNIX AND NOT ANDROID) )
OCV_OPTION(WITH_LIBV4L "Use libv4l for Video 4 Linux support" ON IF (UNIX AND NOT ANDROID) )
OCV_OPTION(WITH_DSHOW "Build HighGUI with DirectShow support" ON IF (WIN32 AND NOT ARM) )
OCV_OPTION(WITH_MSMF "Build HighGUI with Media Foundation support" OFF IF WIN32 )
OCV_OPTION(WITH_DSHOW "Build VideoIO with DirectShow support" ON IF (WIN32 AND NOT ARM) )
OCV_OPTION(WITH_MSMF "Build VideoIO with Media Foundation support" OFF IF WIN32 )
OCV_OPTION(WITH_XIMEA "Include XIMEA cameras support" OFF IF (NOT ANDROID AND NOT APPLE) )
OCV_OPTION(WITH_XINE "Include Xine support (GPL)" OFF IF (UNIX AND NOT APPLE AND NOT ANDROID) )
OCV_OPTION(WITH_CLP "Include Clp support (EPL)" OFF)
@ -335,6 +338,9 @@ if(DEFINED CMAKE_DEBUG_POSTFIX)
set(OPENCV_DEBUG_POSTFIX "${CMAKE_DEBUG_POSTFIX}")
endif()
if(INSTALL_CREATE_DISTRIB AND BUILD_SHARED_LIBS AND NOT DEFINED BUILD_opencv_world)
set(BUILD_opencv_world ON CACHE INTERNAL "")
endif()
# ----------------------------------------------------------------------------
# Path for build/platform -specific headers
@ -552,7 +558,6 @@ endif()
# ----------------------------------------------------------------------------
# Finalization: generate configuration-based files
# ----------------------------------------------------------------------------
ocv_track_build_dependencies()
# Generate platform-dependent and configuration-dependent headers
include(cmake/OpenCVGenHeaders.cmake)
@ -872,6 +877,11 @@ if(DEFINED WITH_OPENNI)
THEN "YES (${OPENNI_PRIME_SENSOR_MODULE})" ELSE NO)
endif(DEFINED WITH_OPENNI)
if(DEFINED WITH_OPENNI2)
status(" OpenNI2:" HAVE_OPENNI2 THEN "YES (ver ${OPENNI2_VERSION_STRING}, build ${OPENNI2_VERSION_BUILD})"
ELSE NO)
endif(DEFINED WITH_OPENNI2)
if(DEFINED WITH_PVAPI)
status(" PvAPI:" HAVE_PVAPI THEN YES ELSE NO)
endif(DEFINED WITH_PVAPI)
@ -998,18 +1008,34 @@ endif()
# ========================== python ==========================
status("")
status(" Python:")
status(" Interpreter:" PYTHONINTERP_FOUND THEN "${PYTHON_EXECUTABLE} (ver ${PYTHON_VERSION_STRING})" ELSE NO)
if(BUILD_opencv_python)
if(PYTHONLIBS_VERSION_STRING)
status(" Libraries:" HAVE_opencv_python THEN "${PYTHON_LIBRARIES} (ver ${PYTHONLIBS_VERSION_STRING})" ELSE NO)
status(" Python 2:")
status(" Interpreter:" PYTHON2INTERP_FOUND THEN "${PYTHON2_EXECUTABLE} (ver ${PYTHON2_VERSION_STRING})" ELSE NO)
if(BUILD_opencv_python2)
if(PYTHON2LIBS_VERSION_STRING)
status(" Libraries:" HAVE_opencv_python2 THEN "${PYTHON2_LIBRARIES} (ver ${PYTHON2LIBS_VERSION_STRING})" ELSE NO)
else()
status(" Libraries:" HAVE_opencv_python THEN "${PYTHON_LIBRARIES}" ELSE NO)
status(" Libraries:" HAVE_opencv_python2 THEN "${PYTHON2_LIBRARIES}" ELSE NO)
endif()
status(" numpy:" PYTHON_NUMPY_INCLUDE_DIRS THEN "${PYTHON_NUMPY_INCLUDE_DIRS} (ver ${PYTHON_NUMPY_VERSION})" ELSE "NO (Python wrappers can not be generated)")
status(" packages path:" PYTHON_EXECUTABLE THEN "${PYTHON_PACKAGES_PATH}" ELSE "-")
status(" numpy:" PYTHON2_NUMPY_INCLUDE_DIRS THEN "${PYTHON2_NUMPY_INCLUDE_DIRS} (ver ${PYTHON2_NUMPY_VERSION})" ELSE "NO (Python wrappers can not be generated)")
status(" packages path:" PYTHON2_EXECUTABLE THEN "${PYTHON2_PACKAGES_PATH}" ELSE "-")
endif()
status("")
status(" Python 3:")
status(" Interpreter:" PYTHON3INTERP_FOUND THEN "${PYTHON3_EXECUTABLE} (ver ${PYTHON3_VERSION_STRING})" ELSE NO)
if(BUILD_opencv_python3)
if(PYTHON3LIBS_VERSION_STRING)
status(" Libraries:" HAVE_opencv_python3 THEN "${PYTHON3_LIBRARIES} (ver ${PYTHON3LIBS_VERSION_STRING})" ELSE NO)
else()
status(" Libraries:" HAVE_opencv_python3 THEN "${PYTHON3_LIBRARIES}" ELSE NO)
endif()
status(" numpy:" PYTHON3_NUMPY_INCLUDE_DIRS THEN "${PYTHON3_NUMPY_INCLUDE_DIRS} (ver ${PYTHON3_NUMPY_VERSION})" ELSE "NO (Python3 wrappers can not be generated)")
status(" packages path:" PYTHON3_EXECUTABLE THEN "${PYTHON3_PACKAGES_PATH}" ELSE "-")
endif()
status("")
status(" Python (for build):" PYTHON_DEFAULT_AVAILABLE THEN "${PYTHON_DEFAULT_EXECUTABLE}" ELSE NO)
# ========================== java ==========================
status("")
status(" Java:")

27
apps/traincascade/CMakeLists.txt
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@ -1,4 +1,4 @@
set(OPENCV_TRAINCASCADE_DEPS opencv_core opencv_ml opencv_imgproc opencv_photo opencv_objdetect opencv_highgui opencv_calib3d opencv_video opencv_features2d)
set(OPENCV_TRAINCASCADE_DEPS opencv_core opencv_imgproc opencv_objdetect opencv_imgcodecs opencv_highgui opencv_calib3d opencv_features2d)
ocv_check_dependencies(${OPENCV_TRAINCASCADE_DEPS})
if(NOT OCV_DEPENDENCIES_FOUND)
@ -6,21 +6,18 @@ if(NOT OCV_DEPENDENCIES_FOUND)
endif()
project(traincascade)
ocv_include_directories("${CMAKE_CURRENT_SOURCE_DIR}" "${OpenCV_SOURCE_DIR}/include/opencv")
ocv_include_modules(${OPENCV_TRAINCASCADE_DEPS})
set(traincascade_files traincascade.cpp
cascadeclassifier.cpp cascadeclassifier.h
boost.cpp boost.h features.cpp traincascade_features.h
haarfeatures.cpp haarfeatures.h
lbpfeatures.cpp lbpfeatures.h
HOGfeatures.cpp HOGfeatures.h
imagestorage.cpp imagestorage.h)
set(the_target opencv_traincascade)
add_executable(${the_target} ${traincascade_files})
target_link_libraries(${the_target} ${OPENCV_TRAINCASCADE_DEPS})
ocv_target_include_directories(${the_target} PRIVATE "${CMAKE_CURRENT_SOURCE_DIR}" "${OpenCV_SOURCE_DIR}/include/opencv")
ocv_target_include_modules(${the_target} ${OPENCV_TRAINCASCADE_DEPS})
file(GLOB SRCS *.cpp)
file(GLOB HDRS *.h*)
set(traincascade_files ${SRCS} ${HDRS})
ocv_add_executable(${the_target} ${traincascade_files})
ocv_target_link_libraries(${the_target} ${OPENCV_TRAINCASCADE_DEPS})
set_target_properties(${the_target} PROPERTIES
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"

2
apps/traincascade/boost.h
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@ -2,7 +2,7 @@
#define _OPENCV_BOOST_H_
#include "traincascade_features.h"
#include "ml.h"
#include "old_ml.hpp"
struct CvCascadeBoostParams : CvBoostParams
{

2
apps/traincascade/cascadeclassifier.h
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@ -7,8 +7,6 @@
#include "lbpfeatures.h"
#include "HOGfeatures.h" //new
#include "boost.h"
#include "cv.h"
#include "cxcore.h"
#define CC_CASCADE_FILENAME "cascade.xml"
#define CC_PARAMS_FILENAME "params.xml"

3
apps/traincascade/imagestorage.cpp
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@ -1,6 +1,7 @@
#include "opencv2/core.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgcodecs.hpp"
#include "imagestorage.h"
#include <stdio.h>

3
apps/traincascade/imagestorage.h
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@ -1,9 +1,6 @@
#ifndef _OPENCV_IMAGESTORAGE_H_
#define _OPENCV_IMAGESTORAGE_H_
#include "highgui.h"
class CvCascadeImageReader
{

2165
apps/traincascade/old_ml.hpp Normal file
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2162
apps/traincascade/old_ml_boost.cpp Normal file
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792
apps/traincascade/old_ml_data.cpp Normal file
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@ -0,0 +1,792 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "old_ml_precomp.hpp"
#include <ctype.h>
#define MISS_VAL FLT_MAX
#define CV_VAR_MISS 0
CvTrainTestSplit::CvTrainTestSplit()
{
train_sample_part_mode = CV_COUNT;
train_sample_part.count = -1;
mix = false;
}
CvTrainTestSplit::CvTrainTestSplit( int _train_sample_count, bool _mix )
{
train_sample_part_mode = CV_COUNT;
train_sample_part.count = _train_sample_count;
mix = _mix;
}
CvTrainTestSplit::CvTrainTestSplit( float _train_sample_portion, bool _mix )
{
train_sample_part_mode = CV_PORTION;
train_sample_part.portion = _train_sample_portion;
mix = _mix;
}
////////////////
CvMLData::CvMLData()
{
values = missing = var_types = var_idx_mask = response_out = var_idx_out = var_types_out = 0;
train_sample_idx = test_sample_idx = 0;
header_lines_number = 0;
sample_idx = 0;
response_idx = -1;
train_sample_count = -1;
delimiter = ',';
miss_ch = '?';
//flt_separator = '.';
rng = &cv::theRNG();
}
CvMLData::~CvMLData()
{
clear();
}
void CvMLData::free_train_test_idx()
{
cvReleaseMat( &train_sample_idx );
cvReleaseMat( &test_sample_idx );
sample_idx = 0;
}
void CvMLData::clear()
{
class_map.clear();
cvReleaseMat( &values );
cvReleaseMat( &missing );
cvReleaseMat( &var_types );
cvReleaseMat( &var_idx_mask );
cvReleaseMat( &response_out );
cvReleaseMat( &var_idx_out );
cvReleaseMat( &var_types_out );
free_train_test_idx();
total_class_count = 0;
response_idx = -1;
train_sample_count = -1;
}
void CvMLData::set_header_lines_number( int idx )
{
header_lines_number = std::max(0, idx);
}
int CvMLData::get_header_lines_number() const
{
return header_lines_number;
}
static char *fgets_chomp(char *str, int n, FILE *stream)
{
char *head = fgets(str, n, stream);
if( head )
{
for(char *tail = head + strlen(head) - 1; tail >= head; --tail)
{
if( *tail != '\r' && *tail != '\n' )
break;
*tail = '\0';
}
}
return head;
}
int CvMLData::read_csv(const char* filename)
{
const int M = 1000000;
const char str_delimiter[3] = { ' ', delimiter, '\0' };
FILE* file = 0;
CvMemStorage* storage;
CvSeq* seq;
char *ptr;
float* el_ptr;
CvSeqReader reader;
int cols_count = 0;
uchar *var_types_ptr = 0;
clear();
file = fopen( filename, "rt" );
if( !file )
return -1;
std::vector<char> _buf(M);
char* buf = &_buf[0];
// skip header lines
for( int i = 0; i < header_lines_number; i++ )
{
if( fgets( buf, M, file ) == 0 )
{
fclose(file);
return -1;
}
}
// read the first data line and determine the number of variables
if( !fgets_chomp( buf, M, file ))
{
fclose(file);
return -1;
}
ptr = buf;
while( *ptr == ' ' )
ptr++;
for( ; *ptr != '\0'; )
{
if(*ptr == delimiter || *ptr == ' ')
{
cols_count++;
ptr++;
while( *ptr == ' ' ) ptr++;
}
else
ptr++;
}
cols_count++;
if ( cols_count == 0)
{
fclose(file);
return -1;
}
// create temporary memory storage to store the whole database
el_ptr = new float[cols_count];
storage = cvCreateMemStorage();
seq = cvCreateSeq( 0, sizeof(*seq), cols_count*sizeof(float), storage );
var_types = cvCreateMat( 1, cols_count, CV_8U );
cvZero( var_types );
var_types_ptr = var_types->data.ptr;
for(;;)
{
char *token = NULL;
int type;
token = strtok(buf, str_delimiter);
if (!token)
break;
for (int i = 0; i < cols_count-1; i++)
{
str_to_flt_elem( token, el_ptr[i], type);
var_types_ptr[i] |= type;
token = strtok(NULL, str_delimiter);
if (!token)
{
fclose(file);
delete [] el_ptr;
return -1;
}
}
str_to_flt_elem( token, el_ptr[cols_count-1], type);
var_types_ptr[cols_count-1] |= type;
cvSeqPush( seq, el_ptr );
if( !fgets_chomp( buf, M, file ) )
break;
}
fclose(file);
values = cvCreateMat( seq->total, cols_count, CV_32FC1 );
missing = cvCreateMat( seq->total, cols_count, CV_8U );
var_idx_mask = cvCreateMat( 1, values->cols, CV_8UC1 );
cvSet( var_idx_mask, cvRealScalar(1) );
train_sample_count = seq->total;
cvStartReadSeq( seq, &reader );
for(int i = 0; i < seq->total; i++ )
{
const float* sdata = (float*)reader.ptr;
float* ddata = values->data.fl + cols_count*i;
uchar* dm = missing->data.ptr + cols_count*i;
for( int j = 0; j < cols_count; j++ )
{
ddata[j] = sdata[j];
dm[j] = ( fabs( MISS_VAL - sdata[j] ) <= FLT_EPSILON );
}
CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
}
if ( cvNorm( missing, 0, CV_L1 ) <= FLT_EPSILON )
cvReleaseMat( &missing );
cvReleaseMemStorage( &storage );
delete []el_ptr;
return 0;
}
const CvMat* CvMLData::get_values() const
{
return values;
}
const CvMat* CvMLData::get_missing() const
{
CV_FUNCNAME( "CvMLData::get_missing" );
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
__END__;
return missing;
}
const std::map<cv::String, int>& CvMLData::get_class_labels_map() const
{
return class_map;
}
void CvMLData::str_to_flt_elem( const char* token, float& flt_elem, int& type)
{
char* stopstring = NULL;
flt_elem = (float)strtod( token, &stopstring );
assert( stopstring );
type = CV_VAR_ORDERED;
if ( *stopstring == miss_ch && strlen(stopstring) == 1 ) // missed value
{
flt_elem = MISS_VAL;
type = CV_VAR_MISS;
}
else
{
if ( (*stopstring != 0) && (*stopstring != '\n') && (strcmp(stopstring, "\r\n") != 0) ) // class label
{
int idx = class_map[token];
if ( idx == 0)
{
total_class_count++;
idx = total_class_count;
class_map[token] = idx;
}
flt_elem = (float)idx;
type = CV_VAR_CATEGORICAL;
}
}
}
void CvMLData::set_delimiter(char ch)
{
CV_FUNCNAME( "CvMLData::set_delimited" );
__BEGIN__;
if (ch == miss_ch /*|| ch == flt_separator*/)
CV_ERROR(CV_StsBadArg, "delimited, miss_character and flt_separator must be different");
delimiter = ch;
__END__;
}
char CvMLData::get_delimiter() const
{
return delimiter;
}
void CvMLData::set_miss_ch(char ch)
{
CV_FUNCNAME( "CvMLData::set_miss_ch" );
__BEGIN__;
if (ch == delimiter/* || ch == flt_separator*/)
CV_ERROR(CV_StsBadArg, "delimited, miss_character and flt_separator must be different");
miss_ch = ch;
__END__;
}
char CvMLData::get_miss_ch() const
{
return miss_ch;
}
void CvMLData::set_response_idx( int idx )
{
CV_FUNCNAME( "CvMLData::set_response_idx" );
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
if ( idx >= values->cols)
CV_ERROR( CV_StsBadArg, "idx value is not correct" );
if ( response_idx >= 0 )
chahge_var_idx( response_idx, true );
if ( idx >= 0 )
chahge_var_idx( idx, false );
response_idx = idx;
__END__;
}
int CvMLData::get_response_idx() const
{
CV_FUNCNAME( "CvMLData::get_response_idx" );
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
__END__;
return response_idx;
}
void CvMLData::change_var_type( int var_idx, int type )
{
CV_FUNCNAME( "CvMLData::change_var_type" );
__BEGIN__;
int var_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
var_count = values->cols;
if ( var_idx < 0 || var_idx >= var_count)
CV_ERROR( CV_StsBadArg, "var_idx is not correct" );
if ( type != CV_VAR_ORDERED && type != CV_VAR_CATEGORICAL)
CV_ERROR( CV_StsBadArg, "type is not correct" );
assert( var_types );
if ( var_types->data.ptr[var_idx] == CV_VAR_CATEGORICAL && type == CV_VAR_ORDERED)
CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
var_types->data.ptr[var_idx] = (uchar)type;
__END__;
return;
}
void CvMLData::set_var_types( const char* str )
{
CV_FUNCNAME( "CvMLData::set_var_types" );
__BEGIN__;
const char* ord = 0, *cat = 0;
int var_count = 0, set_var_type_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
var_count = values->cols;
assert( var_types );
ord = strstr( str, "ord" );
cat = strstr( str, "cat" );
if ( !ord && !cat )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
if ( !ord && strlen(cat) == 3 ) // str == "cat"
{
cvSet( var_types, cvScalarAll(CV_VAR_CATEGORICAL) );
return;
}
if ( !cat && strlen(ord) == 3 ) // str == "ord"
{
cvSet( var_types, cvScalarAll(CV_VAR_ORDERED) );
return;
}
if ( ord ) // parse ord str
{
char* stopstring = NULL;
if ( ord[3] != '[')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
ord += 4; // pass "ord["
do
{
int b1 = (int)strtod( ord, &stopstring );
if ( *stopstring == 0 || (*stopstring != ',' && *stopstring != ']' && *stopstring != '-') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
ord = stopstring + 1;
if ( (stopstring[0] == ',') || (stopstring[0] == ']'))
{
if ( var_types->data.ptr[b1] == CV_VAR_CATEGORICAL)
CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
var_types->data.ptr[b1] = CV_VAR_ORDERED;
set_var_type_count++;
}
else
{
if ( stopstring[0] == '-')
{
int b2 = (int)strtod( ord, &stopstring);
if ( (*stopstring == 0) || (*stopstring != ',' && *stopstring != ']') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
ord = stopstring + 1;
for (int i = b1; i <= b2; i++)
{
if ( var_types->data.ptr[i] == CV_VAR_CATEGORICAL)
CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
var_types->data.ptr[i] = CV_VAR_ORDERED;
}
set_var_type_count += b2 - b1 + 1;
}
else
CV_ERROR( CV_StsBadArg, "types string is not correct" );
}
}
while (*stopstring != ']');
if ( stopstring[1] != '\0' && stopstring[1] != ',')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
}
if ( cat ) // parse cat str
{
char* stopstring = NULL;
if ( cat[3] != '[')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
cat += 4; // pass "cat["
do
{
int b1 = (int)strtod( cat, &stopstring );
if ( *stopstring == 0 || (*stopstring != ',' && *stopstring != ']' && *stopstring != '-') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
cat = stopstring + 1;
if ( (stopstring[0] == ',') || (stopstring[0] == ']'))
{
var_types->data.ptr[b1] = CV_VAR_CATEGORICAL;
set_var_type_count++;
}
else
{
if ( stopstring[0] == '-')
{
int b2 = (int)strtod( cat, &stopstring);
if ( (*stopstring == 0) || (*stopstring != ',' && *stopstring != ']') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
cat = stopstring + 1;
for (int i = b1; i <= b2; i++)
var_types->data.ptr[i] = CV_VAR_CATEGORICAL;
set_var_type_count += b2 - b1 + 1;
}
else
CV_ERROR( CV_StsBadArg, "types string is not correct" );
}
}
while (*stopstring != ']');
if ( stopstring[1] != '\0' && stopstring[1] != ',')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
}
if (set_var_type_count != var_count)
CV_ERROR( CV_StsBadArg, "types string is not correct" );
__END__;
}
const CvMat* CvMLData::get_var_types()
{
CV_FUNCNAME( "CvMLData::get_var_types" );
__BEGIN__;
uchar *var_types_out_ptr = 0;
int avcount, vt_size;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
assert( var_idx_mask );
avcount = cvFloor( cvNorm( var_idx_mask, 0, CV_L1 ) );
vt_size = avcount + (response_idx >= 0);
if ( avcount == values->cols || (avcount == values->cols-1 && response_idx == values->cols-1) )
return var_types;
if ( !var_types_out || ( var_types_out && var_types_out->cols != vt_size ) )
{
cvReleaseMat( &var_types_out );
var_types_out = cvCreateMat( 1, vt_size, CV_8UC1 );
}
var_types_out_ptr = var_types_out->data.ptr;
for( int i = 0; i < var_types->cols; i++)
{
if (i == response_idx || !var_idx_mask->data.ptr[i]) continue;
*var_types_out_ptr = var_types->data.ptr[i];
var_types_out_ptr++;
}
if ( response_idx >= 0 )
*var_types_out_ptr = var_types->data.ptr[response_idx];
__END__;
return var_types_out;
}
int CvMLData::get_var_type( int var_idx ) const
{
return var_types->data.ptr[var_idx];
}
const CvMat* CvMLData::get_responses()
{
CV_FUNCNAME( "CvMLData::get_responses_ptr" );
__BEGIN__;
int var_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
var_count = values->cols;
if ( response_idx < 0 || response_idx >= var_count )
return 0;
if ( !response_out )
response_out = cvCreateMatHeader( values->rows, 1, CV_32FC1 );
else
cvInitMatHeader( response_out, values->rows, 1, CV_32FC1);
cvGetCol( values, response_out, response_idx );
__END__;
return response_out;
}
void CvMLData::set_train_test_split( const CvTrainTestSplit * spl)
{
CV_FUNCNAME( "CvMLData::set_division" );
__BEGIN__;
int sample_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
sample_count = values->rows;
float train_sample_portion;
if (spl->train_sample_part_mode == CV_COUNT)
{
train_sample_count = spl->train_sample_part.count;
if (train_sample_count > sample_count)
CV_ERROR( CV_StsBadArg, "train samples count is not correct" );
train_sample_count = train_sample_count<=0 ? sample_count : train_sample_count;
}
else // dtype.train_sample_part_mode == CV_PORTION
{
train_sample_portion = spl->train_sample_part.portion;
if ( train_sample_portion > 1)
CV_ERROR( CV_StsBadArg, "train samples count is not correct" );
train_sample_portion = train_sample_portion <= FLT_EPSILON ||
1 - train_sample_portion <= FLT_EPSILON ? 1 : train_sample_portion;
train_sample_count = std::max(1, cvFloor( train_sample_portion * sample_count ));
}
if ( train_sample_count == sample_count )
{
free_train_test_idx();
return;
}
if ( train_sample_idx && train_sample_idx->cols != train_sample_count )
free_train_test_idx();
if ( !sample_idx)
{
int test_sample_count = sample_count- train_sample_count;
sample_idx = (int*)cvAlloc( sample_count * sizeof(sample_idx[0]) );
for (int i = 0; i < sample_count; i++ )
sample_idx[i] = i;
train_sample_idx = cvCreateMatHeader( 1, train_sample_count, CV_32SC1 );
*train_sample_idx = cvMat( 1, train_sample_count, CV_32SC1, &sample_idx[0] );
CV_Assert(test_sample_count > 0);
test_sample_idx = cvCreateMatHeader( 1, test_sample_count, CV_32SC1 );
*test_sample_idx = cvMat( 1, test_sample_count, CV_32SC1, &sample_idx[train_sample_count] );
}
mix = spl->mix;
if ( mix )
mix_train_and_test_idx();
__END__;
}
const CvMat* CvMLData::get_train_sample_idx() const
{
CV_FUNCNAME( "CvMLData::get_train_sample_idx" );
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
__END__;
return train_sample_idx;
}
const CvMat* CvMLData::get_test_sample_idx() const
{
CV_FUNCNAME( "CvMLData::get_test_sample_idx" );
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
__END__;
return test_sample_idx;
}
void CvMLData::mix_train_and_test_idx()
{
CV_FUNCNAME( "CvMLData::mix_train_and_test_idx" );
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
__END__;
if ( !sample_idx)
return;
if ( train_sample_count > 0 && train_sample_count < values->rows )
{
int n = values->rows;
for (int i = 0; i < n; i++)
{
int a = (*rng)(n);
int b = (*rng)(n);
int t;
CV_SWAP( sample_idx[a], sample_idx[b], t );
}
}
}
const CvMat* CvMLData::get_var_idx()
{
CV_FUNCNAME( "CvMLData::get_var_idx" );
__BEGIN__;
int avcount = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
assert( var_idx_mask );
avcount = cvFloor( cvNorm( var_idx_mask, 0, CV_L1 ) );
int* vidx;
if ( avcount == values->cols )
return 0;
if ( !var_idx_out || ( var_idx_out && var_idx_out->cols != avcount ) )
{
cvReleaseMat( &var_idx_out );
var_idx_out = cvCreateMat( 1, avcount, CV_32SC1);
if ( response_idx >=0 )
var_idx_mask->data.ptr[response_idx] = 0;
}
vidx = var_idx_out->data.i;
for(int i = 0; i < var_idx_mask->cols; i++)
if ( var_idx_mask->data.ptr[i] )
{
*vidx = i;
vidx++;
}
__END__;
return var_idx_out;
}
void CvMLData::chahge_var_idx( int vi, bool state )
{
change_var_idx( vi, state );
}
void CvMLData::change_var_idx( int vi, bool state )
{
CV_FUNCNAME( "CvMLData::change_var_idx" );
__BEGIN__;
int var_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
var_count = values->cols;
if ( vi < 0 || vi >= var_count)
CV_ERROR( CV_StsBadArg, "variable index is not correct" );
assert( var_idx_mask );
var_idx_mask->data.ptr[vi] = state;
__END__;
}
/* End of file. */

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apps/traincascade/old_ml_precomp.hpp Normal file
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@ -0,0 +1,376 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#include "opencv2/core.hpp"
#include "old_ml.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/private.hpp"
#include <assert.h>
#include <float.h>
#include <limits.h>
#include <math.h>
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <time.h>
#define ML_IMPL CV_IMPL
#define __BEGIN__ __CV_BEGIN__
#define __END__ __CV_END__
#define EXIT __CV_EXIT__
#define CV_MAT_ELEM_FLAG( mat, type, comp, vect, tflag ) \
(( tflag == CV_ROW_SAMPLE ) \
? (CV_MAT_ELEM( mat, type, comp, vect )) \
: (CV_MAT_ELEM( mat, type, vect, comp )))
/* Convert matrix to vector */
#define ICV_MAT2VEC( mat, vdata, vstep, num ) \
if( MIN( (mat).rows, (mat).cols ) != 1 ) \
CV_ERROR( CV_StsBadArg, "" ); \
(vdata) = ((mat).data.ptr); \
if( (mat).rows == 1 ) \
{ \
(vstep) = CV_ELEM_SIZE( (mat).type ); \
(num) = (mat).cols; \
} \
else \
{ \
(vstep) = (mat).step; \
(num) = (mat).rows; \
}
/* get raw data */
#define ICV_RAWDATA( mat, flags, rdata, sstep, cstep, m, n ) \
(rdata) = (mat).data.ptr; \
if( CV_IS_ROW_SAMPLE( flags ) ) \
{ \
(sstep) = (mat).step; \
(cstep) = CV_ELEM_SIZE( (mat).type ); \
(m) = (mat).rows; \
(n) = (mat).cols; \
} \
else \
{ \
(cstep) = (mat).step; \
(sstep) = CV_ELEM_SIZE( (mat).type ); \
(n) = (mat).rows; \
(m) = (mat).cols; \
}
#define ICV_IS_MAT_OF_TYPE( mat, mat_type) \
(CV_IS_MAT( mat ) && CV_MAT_TYPE( mat->type ) == (mat_type) && \
(mat)->cols > 0 && (mat)->rows > 0)
/*
uchar* data; int sstep, cstep; - trainData->data
uchar* classes; int clstep; int ncl;- trainClasses
uchar* tmask; int tmstep; int ntm; - typeMask
uchar* missed;int msstep, mcstep; -missedMeasurements...
int mm, mn; == m,n == size,dim
uchar* sidx;int sistep; - sampleIdx
uchar* cidx;int cistep; - compIdx
int k, l; == n,m == dim,size (length of cidx, sidx)
int m, n; == size,dim
*/
#define ICV_DECLARE_TRAIN_ARGS() \
uchar* data; \
int sstep, cstep; \
uchar* classes; \
int clstep; \
int ncl; \
uchar* tmask; \
int tmstep; \
int ntm; \
uchar* missed; \
int msstep, mcstep; \
int mm, mn; \
uchar* sidx; \
int sistep; \
uchar* cidx; \
int cistep; \
int k, l; \
int m, n; \
\
data = classes = tmask = missed = sidx = cidx = NULL; \
sstep = cstep = clstep = ncl = tmstep = ntm = msstep = mcstep = mm = mn = 0; \
sistep = cistep = k = l = m = n = 0;
#define ICV_TRAIN_DATA_REQUIRED( param, flags ) \
if( !ICV_IS_MAT_OF_TYPE( (param), CV_32FC1 ) ) \
{ \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
else \
{ \
ICV_RAWDATA( *(param), (flags), data, sstep, cstep, m, n ); \
k = n; \
l = m; \
}
#define ICV_TRAIN_CLASSES_REQUIRED( param ) \
if( !ICV_IS_MAT_OF_TYPE( (param), CV_32FC1 ) ) \
{ \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
else \
{ \
ICV_MAT2VEC( *(param), classes, clstep, ncl ); \
if( m != ncl ) \
{ \
CV_ERROR( CV_StsBadArg, "Unmatched sizes" ); \
} \
}
#define ICV_ARG_NULL( param ) \
if( (param) != NULL ) \
{ \
CV_ERROR( CV_StsBadArg, #param " parameter must be NULL" ); \
}
#define ICV_MISSED_MEASUREMENTS_OPTIONAL( param, flags ) \
if( param ) \
{ \
if( !ICV_IS_MAT_OF_TYPE( param, CV_8UC1 ) ) \
{ \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
else \
{ \
ICV_RAWDATA( *(param), (flags), missed, msstep, mcstep, mm, mn ); \
if( mm != m || mn != n ) \
{ \
CV_ERROR( CV_StsBadArg, "Unmatched sizes" ); \
} \
} \
}
#define ICV_COMP_IDX_OPTIONAL( param ) \
if( param ) \
{ \
if( !ICV_IS_MAT_OF_TYPE( param, CV_32SC1 ) ) \
{ \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
else \
{ \
ICV_MAT2VEC( *(param), cidx, cistep, k ); \
if( k > n ) \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
}
#define ICV_SAMPLE_IDX_OPTIONAL( param ) \
if( param ) \
{ \
if( !ICV_IS_MAT_OF_TYPE( param, CV_32SC1 ) ) \
{ \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
else \
{ \
ICV_MAT2VEC( *sampleIdx, sidx, sistep, l ); \
if( l > m ) \
CV_ERROR( CV_StsBadArg, "Invalid " #param " parameter" ); \
} \
}
/****************************************************************************************/
#define ICV_CONVERT_FLOAT_ARRAY_TO_MATRICE( array, matrice ) \
{ \
CvMat a, b; \
int dims = (matrice)->cols; \
int nsamples = (matrice)->rows; \
int type = CV_MAT_TYPE((matrice)->type); \
int i, offset = dims; \
\
CV_ASSERT( type == CV_32FC1 || type == CV_64FC1 ); \
offset *= ((type == CV_32FC1) ? sizeof(float) : sizeof(double));\
\
b = cvMat( 1, dims, CV_32FC1 ); \
cvGetRow( matrice, &a, 0 ); \
for( i = 0; i < nsamples; i++, a.data.ptr += offset ) \
{ \
b.data.fl = (float*)array[i]; \
CV_CALL( cvConvert( &b, &a ) ); \
} \
}
/****************************************************************************************\
* Auxiliary functions declarations *
\****************************************************************************************/
/* Generates a set of classes centers in quantity <num_of_clusters> that are generated as
uniform random vectors in parallelepiped, where <data> is concentrated. Vectors in
<data> should have horizontal orientation. If <centers> != NULL, the function doesn't
allocate any memory and stores generated centers in <centers>, returns <centers>.
If <centers> == NULL, the function allocates memory and creates the matrice. Centers
are supposed to be oriented horizontally. */
CvMat* icvGenerateRandomClusterCenters( int seed,
const CvMat* data,
int num_of_clusters,
CvMat* centers CV_DEFAULT(0));
/* Fills the <labels> using <probs> by choosing the maximal probability. Outliers are
fixed by <oulier_tresh> and have cluster label (-1). Function also controls that there
weren't "empty" clusters by filling empty clusters with the maximal probability vector.
If probs_sums != NULL, filles it with the sums of probabilities for each sample (it is
useful for normalizing probabilities' matrice of FCM) */
void icvFindClusterLabels( const CvMat* probs, float outlier_thresh, float r,
const CvMat* labels );
typedef struct CvSparseVecElem32f
{
int idx;
float val;
}
CvSparseVecElem32f;
/* Prepare training data and related parameters */
#define CV_TRAIN_STATMODEL_DEFRAGMENT_TRAIN_DATA 1
#define CV_TRAIN_STATMODEL_SAMPLES_AS_ROWS 2
#define CV_TRAIN_STATMODEL_SAMPLES_AS_COLUMNS 4
#define CV_TRAIN_STATMODEL_CATEGORICAL_RESPONSE 8
#define CV_TRAIN_STATMODEL_ORDERED_RESPONSE 16
#define CV_TRAIN_STATMODEL_RESPONSES_ON_OUTPUT 32
#define CV_TRAIN_STATMODEL_ALWAYS_COPY_TRAIN_DATA 64
#define CV_TRAIN_STATMODEL_SPARSE_AS_SPARSE 128
int
cvPrepareTrainData( const char* /*funcname*/,
const CvMat* train_data, int tflag,
const CvMat* responses, int response_type,
const CvMat* var_idx,
const CvMat* sample_idx,
bool always_copy_data,
const float*** out_train_samples,
int* _sample_count,
int* _var_count,
int* _var_all,
CvMat** out_responses,
CvMat** out_response_map,
CvMat** out_var_idx,
CvMat** out_sample_idx=0 );
void
cvSortSamplesByClasses( const float** samples, const CvMat* classes,
int* class_ranges, const uchar** mask CV_DEFAULT(0) );
void
cvCombineResponseMaps (CvMat* _responses,
const CvMat* old_response_map,
CvMat* new_response_map,
CvMat** out_response_map);
void
cvPreparePredictData( const CvArr* sample, int dims_all, const CvMat* comp_idx,
int class_count, const CvMat* prob, float** row_sample,
int as_sparse CV_DEFAULT(0) );
/* copies clustering [or batch "predict"] results
(labels and/or centers and/or probs) back to the output arrays */
void
cvWritebackLabels( const CvMat* labels, CvMat* dst_labels,
const CvMat* centers, CvMat* dst_centers,
const CvMat* probs, CvMat* dst_probs,
const CvMat* sample_idx, int samples_all,
const CvMat* comp_idx, int dims_all );
#define cvWritebackResponses cvWritebackLabels
#define XML_FIELD_NAME "_name"
CvFileNode* icvFileNodeGetChild(CvFileNode* father, const char* name);
CvFileNode* icvFileNodeGetChildArrayElem(CvFileNode* father, const char* name,int index);
CvFileNode* icvFileNodeGetNext(CvFileNode* n, const char* name);
void cvCheckTrainData( const CvMat* train_data, int tflag,
const CvMat* missing_mask,
int* var_all, int* sample_all );
CvMat* cvPreprocessIndexArray( const CvMat* idx_arr, int data_arr_size, bool check_for_duplicates=false );
CvMat* cvPreprocessVarType( const CvMat* type_mask, const CvMat* var_idx,
int var_all, int* response_type );
CvMat* cvPreprocessOrderedResponses( const CvMat* responses,
const CvMat* sample_idx, int sample_all );
CvMat* cvPreprocessCategoricalResponses( const CvMat* responses,
const CvMat* sample_idx, int sample_all,
CvMat** out_response_map, CvMat** class_counts=0 );
const float** cvGetTrainSamples( const CvMat* train_data, int tflag,
const CvMat* var_idx, const CvMat* sample_idx,
int* _var_count, int* _sample_count,
bool always_copy_data=false );
namespace cv
{
struct DTreeBestSplitFinder
{
DTreeBestSplitFinder(){ splitSize = 0, tree = 0; node = 0; }
DTreeBestSplitFinder( CvDTree* _tree, CvDTreeNode* _node);
DTreeBestSplitFinder( const DTreeBestSplitFinder& finder, Split );
virtual ~DTreeBestSplitFinder() {}
virtual void operator()(const BlockedRange& range);
void join( DTreeBestSplitFinder& rhs );
Ptr<CvDTreeSplit> bestSplit;
Ptr<CvDTreeSplit> split;
int splitSize;
CvDTree* tree;
CvDTreeNode* node;
};
struct ForestTreeBestSplitFinder : DTreeBestSplitFinder
{
ForestTreeBestSplitFinder() : DTreeBestSplitFinder() {}
ForestTreeBestSplitFinder( CvForestTree* _tree, CvDTreeNode* _node );
ForestTreeBestSplitFinder( const ForestTreeBestSplitFinder& finder, Split );
virtual void operator()(const BlockedRange& range);
};
}
#endif /* __ML_H__ */

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apps/traincascade/traincascade.cpp
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@ -1,6 +1,4 @@
#include "opencv2/core.hpp"
#include "cv.h"
#include "cascadeclassifier.h"
using namespace std;
@ -13,6 +11,7 @@ int main( int argc, char* argv[] )
int numPos = 2000;
int numNeg = 1000;
int numStages = 20;
int numThreads = getNumThreads();
int precalcValBufSize = 256,
precalcIdxBufSize = 256;
bool baseFormatSave = false;
@ -36,6 +35,7 @@ int main( int argc, char* argv[] )
cout << " [-precalcValBufSize <precalculated_vals_buffer_size_in_Mb = " << precalcValBufSize << ">]" << endl;
cout << " [-precalcIdxBufSize <precalculated_idxs_buffer_size_in_Mb = " << precalcIdxBufSize << ">]" << endl;
cout << " [-baseFormatSave]" << endl;
cout << " [-numThreads <max_number_of_threads = " << numThreads << ">]" << endl;
cascadeParams.printDefaults();
stageParams.printDefaults();
for( int fi = 0; fi < fc; fi++ )
@ -82,6 +82,10 @@ int main( int argc, char* argv[] )
{
baseFormatSave = true;
}
else if( !strcmp( argv[i], "-numThreads" ) )
{
numThreads = atoi(argv[++i]);
}
else if ( cascadeParams.scanAttr( argv[i], argv[i+1] ) ) { i++; }
else if ( stageParams.scanAttr( argv[i], argv[i+1] ) ) { i++; }
else if ( !set )
@ -98,6 +102,7 @@ int main( int argc, char* argv[] )
}
}
setNumThreads( numThreads );
classifier.train( cascadeDirName,
vecName,
bgName,

3
apps/traincascade/traincascade_features.h
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@ -2,9 +2,6 @@
#define _OPENCV_FEATURES_H_
#include "imagestorage.h"
#include "cxcore.h"
#include "cv.h"
#include "ml.h"
#include <stdio.h>
#define FEATURES "features"

2
cmake/OpenCVConfig.cmake
View File

@ -11,7 +11,7 @@
#
# Or you can search for specific OpenCV modules:
#
# FIND_PACKAGE(OpenCV REQUIRED core highgui)
# FIND_PACKAGE(OpenCV REQUIRED core imgcodecs)
#
# If the module is found then OPENCV_<MODULE>_FOUND is set to TRUE.
#

7
cmake/OpenCVDetectAndroidSDK.cmake
View File

@ -280,9 +280,6 @@ macro(add_android_project target path)
string(REGEX REPLACE "LOCAL_MODULE[ ]*:=[ ]*([a-zA-Z_][a-zA-Z_0-9]*)[ ]*" "\\1" JNI_LIB_NAME "${JNI_LIB_NAME}")
if(JNI_LIB_NAME)
ocv_include_modules_recurse(${android_proj_NATIVE_DEPS})
ocv_include_directories("${path}/jni")
if(NATIVE_APP_GLUE)
include_directories(${ANDROID_NDK}/sources/android/native_app_glue)
list(APPEND android_proj_jni_files ${ANDROID_NDK}/sources/android/native_app_glue/android_native_app_glue.c)
@ -291,7 +288,9 @@ macro(add_android_project target path)
endif()
add_library(${JNI_LIB_NAME} MODULE ${android_proj_jni_files})
target_link_libraries(${JNI_LIB_NAME} ${OPENCV_LINKER_LIBS} ${android_proj_NATIVE_DEPS})
ocv_target_include_modules_recurse(${JNI_LIB_NAME} ${android_proj_NATIVE_DEPS})
ocv_target_include_directories(${JNI_LIB_NAME} "${path}/jni")
ocv_target_link_libraries(${JNI_LIB_NAME} ${OPENCV_LINKER_LIBS} ${android_proj_NATIVE_DEPS})
set_target_properties(${JNI_LIB_NAME} PROPERTIES
OUTPUT_NAME "${JNI_LIB_NAME}"

233
cmake/OpenCVDetectPython.cmake
View File

@ -1,9 +1,43 @@
if(WIN32 AND NOT PYTHON_EXECUTABLE)
# Find specified Python version
# Arguments:
# preferred_version (value): Version to check for first
# min_version (value): Minimum supported version
# library_env (value): Name of Python library ENV variable to check
# include_dir_env (value): Name of Python include directory ENV variable to check
# found (variable): Set if interpreter found
# executable (variable): Output of executable found
# version_string (variable): Output of found version
# version_major (variable): Output of found major version
# version_minor (variable): Output of found minor version
# libs_found (variable): Set if libs found
# libs_version_string (variable): Output of found libs version
# libraries (variable): Output of found Python libraries
# library (variable): Output of found Python library
# debug_libraries (variable): Output of found Python debug libraries
# debug_library (variable): Output of found Python debug library
# include_path (variable): Output of found Python include path
# include_dir (variable): Output of found Python include dir
# include_dir2 (variable): Output of found Python include dir2
# packages_path (variable): Output of found Python packages path
# numpy_include_dirs (variable): Output of found Python Numpy include dirs
# numpy_version (variable): Output of found Python Numpy version
function(find_python preferred_version min_version library_env include_dir_env
found executable version_string version_major version_minor
libs_found libs_version_string libraries library debug_libraries
debug_library include_path include_dir include_dir2 packages_path
numpy_include_dirs numpy_version)
ocv_check_environment_variables(${executable})
if(${executable})
set(PYTHON_EXECUTABLE "${${executable}}")
endif()
if(WIN32 AND NOT ${executable})
# search for executable with the same bitness as resulting binaries
# standard FindPythonInterp always prefers executable from system path
# this is really important because we are using the interpreter for numpy search and for choosing the install location
foreach(_CURRENT_VERSION ${Python_ADDITIONAL_VERSIONS} 2.7 "${MIN_VER_PYTHON}")
find_host_program(PYTHON_EXECUTABLE
foreach(_CURRENT_VERSION ${Python_ADDITIONAL_VERSIONS} "${preferred_version}" "${min_version}")
find_host_program(executable
NAMES python${_CURRENT_VERSION} python
PATHS
[HKEY_LOCAL_MACHINE\\\\SOFTWARE\\\\Python\\\\PythonCore\\\\${_CURRENT_VERSION}\\\\InstallPath]
@ -12,90 +46,195 @@ if(WIN32 AND NOT PYTHON_EXECUTABLE)
)
endforeach()
endif()
find_host_package(PythonInterp 2.7)
find_host_package(PythonInterp "${preferred_version}")
if(NOT PYTHONINTERP_FOUND)
find_host_package(PythonInterp "${MIN_VER_PYTHON}")
find_host_package(PythonInterp "${min_version}")
endif()
unset(HAVE_SPHINX CACHE)
if(PYTHONINTERP_FOUND)
set(PYTHON_VERSION_MAJOR_MINOR "${PYTHON_VERSION_MAJOR}.${PYTHON_VERSION_MINOR}")
# Copy outputs
set(_found ${PYTHONINTERP_FOUND})
set(_executable ${PYTHON_EXECUTABLE})
set(_version_string ${PYTHON_VERSION_STRING})
set(_version_major ${PYTHON_VERSION_MAJOR})
set(_version_minor ${PYTHON_VERSION_MINOR})
set(_version_patch ${PYTHON_VERSION_PATCH})
# Clear find_host_package side effects
unset(PYTHONINTERP_FOUND)
unset(PYTHON_EXECUTABLE CACHE)
unset(PYTHON_VERSION_STRING)
unset(PYTHON_VERSION_MAJOR)
unset(PYTHON_VERSION_MINOR)
unset(PYTHON_VERSION_PATCH)
endif()
if(_found)
set(_version_major_minor "${_version_major}.${_version_minor}")
if(NOT ANDROID AND NOT IOS)
ocv_check_environment_variables(PYTHON_LIBRARY PYTHON_INCLUDE_DIR)
# not using PYTHON_VERSION_STRING here, because it might not conform to the CMake version format
find_host_package(PythonLibs "${PYTHON_VERSION_MAJOR_MINOR}.${PYTHON_VERSION_PATCH}" EXACT)
ocv_check_environment_variables(${library_env} ${include_dir_env})
if(${library})
set(PYTHON_LIBRARY "${${library_env}}")
endif()
if(${include_dir})
set(PYTHON_INCLUDE_DIR "${${include_dir_env}}")
endif()
# not using _version_string here, because it might not conform to the CMake version format
find_host_package(PythonLibs "${_version_major_minor}.${_version_patch}" EXACT)
if(PYTHONLIBS_FOUND)
# Copy outputs
set(_libs_found ${PYTHONLIBS_FOUND})
set(_libraries ${PYTHON_LIBRARIES})
set(_include_path ${PYTHON_INCLUDE_PATH})
set(_include_dirs ${PYTHON_INCLUDE_DIRS})
set(_debug_libraries ${PYTHON_DEBUG_LIBRARIES})
set(_libs_version_string ${PYTHONLIBS_VERSION_STRING})
set(_debug_library ${PYTHON_DEBUG_LIBRARY})
set(_library ${PYTHON_LIBRARY})
set(_library_debug ${PYTHON_LIBRARY_DEBUG})
set(_library_release ${PYTHON_LIBRARY_RELEASE})
set(_include_dir ${PYTHON_INCLUDE_DIR})
set(_include_dir2 ${PYTHON_INCLUDE_DIR2})
# Clear find_host_package side effects
unset(PYTHONLIBS_FOUND)
unset(PYTHON_LIBRARIES)
unset(PYTHON_INCLUDE_PATH)
unset(PYTHON_INCLUDE_DIRS)
unset(PYTHON_DEBUG_LIBRARIES)
unset(PYTHONLIBS_VERSION_STRING)
unset(PYTHON_DEBUG_LIBRARY CACHE)
unset(PYTHON_LIBRARY)
unset(PYTHON_LIBRARY_DEBUG)
unset(PYTHON_LIBRARY_RELEASE)
unset(PYTHON_LIBRARY CACHE)
unset(PYTHON_LIBRARY_DEBUG CACHE)
unset(PYTHON_LIBRARY_RELEASE CACHE)
unset(PYTHON_INCLUDE_DIR CACHE)
unset(PYTHON_INCLUDE_DIR2 CACHE)
endif()
endif()
if(NOT ANDROID AND NOT IOS)
if(CMAKE_HOST_UNIX)
execute_process(COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import *; print(get_python_lib())"
RESULT_VARIABLE PYTHON_CVPY_PROCESS
OUTPUT_VARIABLE PYTHON_STD_PACKAGES_PATH
execute_process(COMMAND ${_executable} -c "from distutils.sysconfig import *; print(get_python_lib())"
RESULT_VARIABLE _cvpy_process
OUTPUT_VARIABLE _std_packages_path
OUTPUT_STRIP_TRAILING_WHITESPACE)
if("${PYTHON_STD_PACKAGES_PATH}" MATCHES "site-packages")
set(_PYTHON_PACKAGES_PATH "python${PYTHON_VERSION_MAJOR_MINOR}/site-packages")
if("${_std_packages_path}" MATCHES "site-packages")
set(_packages_path "python${_version_major_minor}/site-packages")
else() #debian based assumed, install to the dist-packages.
set(_PYTHON_PACKAGES_PATH "python${PYTHON_VERSION_MAJOR_MINOR}/dist-packages")
set(_packages_path "python${_version_major_minor}/dist-packages")
endif()
if(EXISTS "${CMAKE_INSTALL_PREFIX}/lib${LIB_SUFFIX}/${PYTHON_PACKAGES_PATH}")
set(_PYTHON_PACKAGES_PATH "lib${LIB_SUFFIX}/${_PYTHON_PACKAGES_PATH}")
if(EXISTS "${CMAKE_INSTALL_PREFIX}/lib${LIB_SUFFIX}/${${packages_path}}")
set(_packages_path "lib${LIB_SUFFIX}/${_packages_path}")
else()
set(_PYTHON_PACKAGES_PATH "lib/${_PYTHON_PACKAGES_PATH}")
set(_packages_path "lib/${_packages_path}")
endif()
elseif(CMAKE_HOST_WIN32)
get_filename_component(PYTHON_PATH "${PYTHON_EXECUTABLE}" PATH)
file(TO_CMAKE_PATH "${PYTHON_PATH}" PYTHON_PATH)
if(NOT EXISTS "${PYTHON_PATH}/Lib/site-packages")
unset(PYTHON_PATH)
get_filename_component(PYTHON_PATH "[HKEY_LOCAL_MACHINE\\SOFTWARE\\Python\\PythonCore\\${PYTHON_VERSION_MAJOR_MINOR}\\InstallPath]" ABSOLUTE)
if(NOT PYTHON_PATH)
get_filename_component(PYTHON_PATH "[HKEY_CURRENT_USER\\SOFTWARE\\Python\\PythonCore\\${PYTHON_VERSION_MAJOR_MINOR}\\InstallPath]" ABSOLUTE)
get_filename_component(_path "${_executable}" PATH)
file(TO_CMAKE_PATH "${_path}" _path)
if(NOT EXISTS "${_path}/Lib/site-packages")
unset(_path)
get_filename_component(_path "[HKEY_LOCAL_MACHINE\\SOFTWARE\\Python\\PythonCore\\${_version_major_minor}\\InstallPath]" ABSOLUTE)
if(NOT _path)
get_filename_component(_path "[HKEY_CURRENT_USER\\SOFTWARE\\Python\\PythonCore\\${_version_major_minor}\\InstallPath]" ABSOLUTE)
endif()
file(TO_CMAKE_PATH "${PYTHON_PATH}" PYTHON_PATH)
file(TO_CMAKE_PATH "${_path}" _path)
endif()
set(_PYTHON_PACKAGES_PATH "${PYTHON_PATH}/Lib/site-packages")
set(_packages_path "${_path}/Lib/site-packages")
unset(_path)
endif()
SET(PYTHON_PACKAGES_PATH "${_PYTHON_PACKAGES_PATH}" CACHE PATH "Where to install the python packages.")
if(NOT PYTHON_NUMPY_INCLUDE_DIRS)
set(_numpy_include_dirs ${${numpy_include_dirs}})
if(NOT _numpy_include_dirs)
if(CMAKE_CROSSCOMPILING)
message(STATUS "Cannot probe for Python/Numpy support (because we are cross-compiling OpenCV)")
message(STATUS "If you want to enable Python/Numpy support, set the following variables:")
message(STATUS " PYTHON_INCLUDE_PATH")
message(STATUS " PYTHON_LIBRARIES")
message(STATUS " PYTHON_NUMPY_INCLUDE_DIRS")
message(STATUS " PYTHON2_INCLUDE_PATH")
message(STATUS " PYTHON2_LIBRARIES")
message(STATUS " PYTHON2_NUMPY_INCLUDE_DIRS")
message(STATUS " PYTHON3_INCLUDE_PATH")
message(STATUS " PYTHON3_LIBRARIES")
message(STATUS " PYTHON3_NUMPY_INCLUDE_DIRS")
else()
# Attempt to discover the NumPy include directory. If this succeeds, then build python API with NumPy
execute_process(COMMAND "${PYTHON_EXECUTABLE}" -c "import os; os.environ['DISTUTILS_USE_SDK']='1'; import numpy.distutils; print(os.pathsep.join(numpy.distutils.misc_util.get_numpy_include_dirs()))"
RESULT_VARIABLE PYTHON_NUMPY_PROCESS
OUTPUT_VARIABLE PYTHON_NUMPY_INCLUDE_DIRS
execute_process(COMMAND "${_executable}" -c "import os; os.environ['DISTUTILS_USE_SDK']='1'; import numpy.distutils; print(os.pathsep.join(numpy.distutils.misc_util.get_numpy_include_dirs()))"
RESULT_VARIABLE _numpy_process
OUTPUT_VARIABLE _numpy_include_dirs
OUTPUT_STRIP_TRAILING_WHITESPACE)
if(NOT PYTHON_NUMPY_PROCESS EQUAL 0)
unset(PYTHON_NUMPY_INCLUDE_DIRS)
if(NOT _numpy_process EQUAL 0)
unset(_numpy_include_dirs)
endif()
endif()
endif()
if(PYTHON_NUMPY_INCLUDE_DIRS)
file(TO_CMAKE_PATH "${PYTHON_NUMPY_INCLUDE_DIRS}" _PYTHON_NUMPY_INCLUDE_DIRS)
set(PYTHON_NUMPY_INCLUDE_DIRS ${_PYTHON_NUMPY_INCLUDE_DIRS} CACHE PATH "Path to numpy headers")
if(_numpy_include_dirs)
file(TO_CMAKE_PATH "${_numpy_include_dirs}" _numpy_include_dirs)
if(CMAKE_CROSSCOMPILING)
if(NOT PYTHON_NUMPY_VERSION)
set(PYTHON_NUMPY_VERSION "undefined - cannot be probed because of the cross-compilation")
if(NOT _numpy_version)
set(_numpy_version "undefined - cannot be probed because of the cross-compilation")
endif()
else()
execute_process(COMMAND "${PYTHON_EXECUTABLE}" -c "import numpy; print(numpy.version.version)"
RESULT_VARIABLE PYTHON_NUMPY_PROCESS
OUTPUT_VARIABLE PYTHON_NUMPY_VERSION
execute_process(COMMAND "${_executable}" -c "import numpy; print(numpy.version.version)"
RESULT_VARIABLE _numpy_process
OUTPUT_VARIABLE _numpy_version
OUTPUT_STRIP_TRAILING_WHITESPACE)
endif()
endif()
endif(NOT ANDROID AND NOT IOS)
endif()
# Export return values
set(${found} "${_found}" PARENT_SCOPE)
set(${executable} "${_executable}" CACHE FILEPATH "Path to Python interpretor")
set(${version_string} "${_version_string}" PARENT_SCOPE)
set(${version_major} "${_version_major}" PARENT_SCOPE)
set(${version_minor} "${_version_minor}" PARENT_SCOPE)
set(${libs_found} "${_libs_found}" PARENT_SCOPE)
set(${libs_version_string} "${_libs_version_string}" PARENT_SCOPE)
set(${libraries} "${_libraries}" PARENT_SCOPE)
set(${library} "${_library}" CACHE FILEPATH "Path to Python library")
set(${debug_libraries} "${_debug_libraries}" PARENT_SCOPE)
set(${debug_library} "${_debug_library}" CACHE FILEPATH "Path to Python debug")
set(${include_path} "${_include_path}" PARENT_SCOPE)
set(${include_dir} "${_include_dir}" CACHE PATH "Python include dir")
set(${include_dir2} "${_include_dir2}" CACHE PATH "Python include dir 2")
set(${packages_path} "${_packages_path}" CACHE PATH "Where to install the python packages.")
set(${numpy_include_dirs} ${_numpy_include_dirs} CACHE PATH "Path to numpy headers")
set(${numpy_version} "${_numpy_version}" PARENT_SCOPE)
endfunction(find_python)
find_python(2.7 "${MIN_VER_PYTHON2}" PYTHON2_LIBRARY PYTHON2_INCLUDE_DIR
PYTHON2INTERP_FOUND PYTHON2_EXECUTABLE PYTHON2_VERSION_STRING
PYTHON2_VERSION_MAJOR PYTHON2_VERSION_MINOR PYTHON2LIBS_FOUND
PYTHON2LIBS_VERSION_STRING PYTHON2_LIBRARIES PYTHON2_LIBRARY
PYTHON2_DEBUG_LIBRARIES PYTHON2_LIBRARY_DEBUG PYTHON2_INCLUDE_PATH
PYTHON2_INCLUDE_DIR PYTHON2_INCLUDE_DIR2 PYTHON2_PACKAGES_PATH
PYTHON2_NUMPY_INCLUDE_DIRS PYTHON2_NUMPY_VERSION)
find_python(3.4 "${MIN_VER_PYTHON3}" PYTHON3_LIBRARY PYTHON3_INCLUDE_DIR
PYTHON3INTERP_FOUND PYTHON3_EXECUTABLE PYTHON3_VERSION_STRING
PYTHON3_VERSION_MAJOR PYTHON3_VERSION_MINOR PYTHON3LIBS_FOUND
PYTHON3LIBS_VERSION_STRING PYTHON3_LIBRARIES PYTHON3_LIBRARY
PYTHON3_DEBUG_LIBRARIES PYTHON3_LIBRARY_DEBUG PYTHON3_INCLUDE_PATH
PYTHON3_INCLUDE_DIR PYTHON3_INCLUDE_DIR2 PYTHON3_PACKAGES_PATH
PYTHON3_NUMPY_INCLUDE_DIRS PYTHON3_NUMPY_VERSION)
# Use Python 2 as default Python interpreter
if(PYTHON2LIBS_FOUND)
set(PYTHON_DEFAULT_AVAILABLE "TRUE")
set(PYTHON_DEFAULT_EXECUTABLE "${PYTHON2_EXECUTABLE}")
endif()
unset(HAVE_SPHINX CACHE)
if(BUILD_DOCS)
find_host_program(SPHINX_BUILD sphinx-build)
find_host_program(PLANTUML plantuml)

20
cmake/OpenCVFindLibsVideo.cmake
View File

@ -131,7 +131,7 @@ if(WITH_1394)
if(HAVE_DC1394_2)
ocv_parse_pkg("libdc1394-2" "${DC1394_2_LIB_DIR}/pkgconfig" "")
ocv_include_directories(${DC1394_2_INCLUDE_PATH})
set(HIGHGUI_LIBRARIES ${HIGHGUI_LIBRARIES}
set(VIDEOIO_LIBRARIES ${VIDEOIO_LIBRARIES}
"${DC1394_2_LIB_DIR}/libdc1394.a"
"${CMU1394_LIB_DIR}/lib1394camera.a")
endif(HAVE_DC1394_2)
@ -166,6 +166,11 @@ if(WITH_OPENNI)
include("${OpenCV_SOURCE_DIR}/cmake/OpenCVFindOpenNI.cmake")
endif(WITH_OPENNI)
ocv_clear_vars(HAVE_OPENNI2)
if(WITH_OPENNI2)
include("${OpenCV_SOURCE_DIR}/cmake/OpenCVFindOpenNI2.cmake")
endif(WITH_OPENNI2)
# --- XIMEA ---
ocv_clear_vars(HAVE_XIMEA)
if(WITH_XIMEA)
@ -234,7 +239,7 @@ if(WITH_FFMPEG)
endif()
endif(FFMPEG_INCLUDE_DIR)
if(HAVE_FFMPEG)
set(HIGHGUI_LIBRARIES ${HIGHGUI_LIBRARIES} "${FFMPEG_LIB_DIR}/libavcodec.a"
set(VIDEOIO_LIBRARIES ${VIDEOIO_LIBRARIES} "${FFMPEG_LIB_DIR}/libavcodec.a"
"${FFMPEG_LIB_DIR}/libavformat.a" "${FFMPEG_LIB_DIR}/libavutil.a"
"${FFMPEG_LIB_DIR}/libswscale.a")
ocv_include_directories(${FFMPEG_INCLUDE_DIR})
@ -253,14 +258,15 @@ if(WITH_MSMF)
check_include_file(Mfapi.h HAVE_MSMF)
endif(WITH_MSMF)
# --- Extra HighGUI libs on Windows ---
# --- Extra HighGUI and VideoIO libs on Windows ---
if(WIN32)
list(APPEND HIGHGUI_LIBRARIES comctl32 gdi32 ole32 setupapi ws2_32 vfw32)
list(APPEND HIGHGUI_LIBRARIES comctl32 gdi32 ole32 setupapi ws2_32)
list(APPEND VIDEOIO_LIBRARIES vfw32)
if(MINGW64)
list(APPEND HIGHGUI_LIBRARIES avifil32 avicap32 winmm msvfw32)
list(REMOVE_ITEM HIGHGUI_LIBRARIES vfw32)
list(APPEND VIDEOIO_LIBRARIES avifil32 avicap32 winmm msvfw32)
list(REMOVE_ITEM VIDEOIO_LIBRARIES vfw32)
elseif(MINGW)
list(APPEND HIGHGUI_LIBRARIES winmm)
list(APPEND VIDEOIO_LIBRARIES winmm)
endif()
endif(WIN32)

61
cmake/OpenCVFindOpenNI2.cmake Normal file
View File

@ -0,0 +1,61 @@
# Main variables:
# OPENNI2_LIBRARY and OPENNI2_INCLUDES to link OpenCV modules with OpenNI2
# HAVE_OPENNI2 for conditional compilation OpenCV with/without OpenNI2
if(NOT "${OPENNI2_LIB_DIR}" STREQUAL "${OPENNI2_LIB_DIR_INTERNAL}")
unset(OPENNI2_LIBRARY CACHE)
unset(OPENNI2_LIB_DIR CACHE)
endif()
if(NOT "${OPENNI2_INCLUDE_DIR}" STREQUAL "${OPENNI2_INCLUDE_DIR_INTERNAL}")
unset(OPENNI2_INCLUDES CACHE)
unset(OPENNI2_INCLUDE_DIR CACHE)
endif()
if(WIN32)
if(NOT (MSVC64 OR MINGW64))
find_file(OPENNI2_INCLUDES "OpenNI.h" PATHS "$ENV{OPEN_NI_INSTALL_PATH}Include" DOC "OpenNI2 c++ interface header")
find_library(OPENNI2_LIBRARY "OpenNI2" PATHS $ENV{OPENNI2_LIB} DOC "OpenNI2 library")
else()
find_file(OPENNI2_INCLUDES "OpenNI.h" PATHS "$ENV{OPEN_NI_INSTALL_PATH64}Include" DOC "OpenNI2 c++ interface header")
find_library(OPENNI2_LIBRARY "OpenNI2" PATHS $ENV{OPENNI2_LIB64} DOC "OpenNI2 library")
endif()
elseif(UNIX OR APPLE)
find_file(OPENNI2_INCLUDES "OpenNI.h" PATHS "/usr/include/ni2" "/usr/include/openni2" DOC "OpenNI2 c++ interface header")
find_library(OPENNI2_LIBRARY "OpenNI2" PATHS "/usr/lib" DOC "OpenNI2 library")
endif()
if(OPENNI2_LIBRARY AND OPENNI2_INCLUDES)
set(HAVE_OPENNI2 TRUE)
endif() #if(OPENNI2_LIBRARY AND OPENNI2_INCLUDES)
get_filename_component(OPENNI2_LIB_DIR "${OPENNI2_LIBRARY}" PATH)
get_filename_component(OPENNI2_INCLUDE_DIR ${OPENNI2_INCLUDES} PATH)
if(HAVE_OPENNI2)
set(OPENNI2_LIB_DIR "${OPENNI2_LIB_DIR}" CACHE PATH "Path to OpenNI2 libraries" FORCE)
set(OPENNI2_INCLUDE_DIR "${OPENNI2_INCLUDE_DIR}" CACHE PATH "Path to OpenNI2 headers" FORCE)
endif()
if(OPENNI2_LIBRARY)
set(OPENNI2_LIB_DIR_INTERNAL "${OPENNI2_LIB_DIR}" CACHE INTERNAL "This is the value of the last time OPENNI_LIB_DIR was set successfully." FORCE)
else()
message( WARNING, " OpenNI2 library directory (set by OPENNI2_LIB_DIR variable) is not found or does not have OpenNI2 libraries." )
endif()
if(OPENNI2_INCLUDES)
set(OPENNI2_INCLUDE_DIR_INTERNAL "${OPENNI2_INCLUDE_DIR}" CACHE INTERNAL "This is the value of the last time OPENNI2_INCLUDE_DIR was set successfully." FORCE)
else()
message( WARNING, " OpenNI2 include directory (set by OPENNI2_INCLUDE_DIR variable) is not found or does not have OpenNI2 include files." )
endif()
mark_as_advanced(FORCE OPENNI2_LIBRARY)
mark_as_advanced(FORCE OPENNI2_INCLUDES)
if(HAVE_OPENNI2)
ocv_parse_header("${OPENNI2_INCLUDE_DIR}/OniVersion.h" ONI_VERSION_LINE ONI_VERSION_MAJOR ONI_VERSION_MINOR ONI_VERSION_MAINTENANCE ONI_VERSION_BUILD)
if(ONI_VERSION_MAJOR)
set(OPENNI2_VERSION_STRING ${ONI_VERSION_MAJOR}.${ONI_VERSION_MINOR}.${ONI_VERSION_MAINTENANCE} CACHE INTERNAL "OpenNI2 version")
set(OPENNI2_VERSION_BUILD ${ONI_VERSION_BUILD} CACHE INTERNAL "OpenNI2 build version")
endif()
endif()

3
cmake/OpenCVGenInfoPlist.cmake
View File

@ -1,4 +1,7 @@
if(IOS)
configure_file("${OpenCV_SOURCE_DIR}/platforms/ios/Info.plist.in"
"${CMAKE_BINARY_DIR}/ios/Info.plist")
elseif(APPLE)
configure_file("${OpenCV_SOURCE_DIR}/platforms/osx/Info.plist.in"
"${CMAKE_BINARY_DIR}/osx/Info.plist")
endif()

3
cmake/OpenCVMinDepVersions.cmake
View File

@ -1,5 +1,6 @@
set(MIN_VER_CMAKE 2.8.7)
set(MIN_VER_CUDA 4.2)
set(MIN_VER_PYTHON 2.6)
set(MIN_VER_PYTHON2 2.6)
set(MIN_VER_PYTHON3 3.2)
set(MIN_VER_ZLIB 1.2.3)
set(MIN_VER_GTK 2.18.0)

342
cmake/OpenCVModule.cmake
View File

@ -6,16 +6,19 @@
# Global variables:
#
# OPENCV_MODULE_${the_module}_LOCATION
# OPENCV_MODULE_${the_module}_BINARY_DIR
# OPENCV_MODULE_${the_module}_DESCRIPTION
# OPENCV_MODULE_${the_module}_CLASS - PUBLIC|INTERNAL|BINDINGS
# OPENCV_MODULE_${the_module}_HEADERS
# OPENCV_MODULE_${the_module}_SOURCES
# OPENCV_MODULE_${the_module}_DEPS - final flattened set of module dependencies
# OPENCV_MODULE_${the_module}_DEPS_TO_LINK - differs from above for world build only
# OPENCV_MODULE_${the_module}_DEPS_EXT - non-module dependencies
# OPENCV_MODULE_${the_module}_REQ_DEPS
# OPENCV_MODULE_${the_module}_OPT_DEPS
# OPENCV_MODULE_${the_module}_PRIVATE_REQ_DEPS
# OPENCV_MODULE_${the_module}_PRIVATE_OPT_DEPS
# OPENCV_MODULE_${the_module}_IS_PART_OF_WORLD
# HAVE_${the_module} - for fast check of module availability
# To control the setup of the module you could also set:
@ -53,6 +56,7 @@ foreach(mod ${OPENCV_MODULES_BUILD} ${OPENCV_MODULES_DISABLED_USER} ${OPENCV_MOD
unset(OPENCV_MODULE_${mod}_OPT_DEPS CACHE)
unset(OPENCV_MODULE_${mod}_PRIVATE_REQ_DEPS CACHE)
unset(OPENCV_MODULE_${mod}_PRIVATE_OPT_DEPS CACHE)
unset(OPENCV_MODULE_${mod}_LINK_DEPS CACHE)
endforeach()
# clean modules info which needs to be recalculated
@ -61,6 +65,7 @@ set(OPENCV_MODULES_BUILD "" CACHE INTERNAL "List of OpenCV modules incl
set(OPENCV_MODULES_DISABLED_USER "" CACHE INTERNAL "List of OpenCV modules explicitly disabled by user")
set(OPENCV_MODULES_DISABLED_AUTO "" CACHE INTERNAL "List of OpenCV modules implicitly disabled due to dependencies")
set(OPENCV_MODULES_DISABLED_FORCE "" CACHE INTERNAL "List of OpenCV modules which can not be build in current configuration")
unset(OPENCV_WORLD_MODULES CACHE)
# adds dependencies to OpenCV module
# Usage:
@ -68,6 +73,7 @@ set(OPENCV_MODULES_DISABLED_FORCE "" CACHE INTERNAL "List of OpenCV modules whic
# Notes:
# * <list of dependencies> - can include full names of modules or full pathes to shared/static libraries or cmake targets
macro(ocv_add_dependencies full_modname)
ocv_debug_message("ocv_add_dependencies(" ${full_modname} ${ARGN} ")")
#we don't clean the dependencies here to allow this macro several times for every module
foreach(d "REQUIRED" ${ARGN})
if(d STREQUAL "REQUIRED")
@ -105,6 +111,7 @@ endmacro()
# Example:
# ocv_add_module(yaom INTERNAL opencv_core opencv_highgui opencv_flann OPTIONAL opencv_cuda)
macro(ocv_add_module _name)
ocv_debug_message("ocv_add_module(" ${_name} ${ARGN} ")")
string(TOLOWER "${_name}" name)
string(REGEX REPLACE "^opencv_" "" ${name} "${name}")
set(the_module opencv_${name})
@ -134,6 +141,8 @@ macro(ocv_add_module _name)
set(OPENCV_MODULE_${the_module}_DESCRIPTION "${the_description}" CACHE INTERNAL "Brief description of ${the_module} module")
set(OPENCV_MODULE_${the_module}_LOCATION "${CMAKE_CURRENT_SOURCE_DIR}" CACHE INTERNAL "Location of ${the_module} module sources")
set(OPENCV_MODULE_${the_module}_LINK_DEPS "" CACHE INTERNAL "")
# parse list of dependencies
if("${ARGV1}" STREQUAL "INTERNAL" OR "${ARGV1}" STREQUAL "BINDINGS")
set(OPENCV_MODULE_${the_module}_CLASS "${ARGV1}" CACHE INTERNAL "The category of the module")
@ -150,8 +159,14 @@ macro(ocv_add_module _name)
endif()
# add self to the world dependencies
if(NOT DEFINED OPENCV_MODULE_IS_PART_OF_WORLD AND NOT OPENCV_MODULE_${the_module}_CLASS STREQUAL "BINDINGS" OR OPENCV_MODULE_IS_PART_OF_WORLD)
if((NOT DEFINED OPENCV_MODULE_IS_PART_OF_WORLD AND NOT OPENCV_MODULE_${the_module}_CLASS STREQUAL "BINDINGS"
AND NOT OPENCV_PROCESSING_EXTRA_MODULES)
OR OPENCV_MODULE_IS_PART_OF_WORLD
)
set(OPENCV_MODULE_${the_module}_IS_PART_OF_WORLD ON CACHE INTERNAL "")
ocv_add_dependencies(opencv_world OPTIONAL ${the_module})
else()
set(OPENCV_MODULE_${the_module}_IS_PART_OF_WORLD OFF CACHE INTERNAL "")
endif()
if(BUILD_${the_module})
@ -164,12 +179,15 @@ macro(ocv_add_module _name)
# stop processing of current file
return()
else(OPENCV_INITIAL_PASS)
else()
set(OPENCV_MODULE_${the_module}_BINARY_DIR "${CMAKE_CURRENT_BINARY_DIR}" CACHE INTERNAL "")
if(NOT BUILD_${the_module})
return() # extra protection from redefinition
endif()
if((NOT OPENCV_MODULE_${the_module}_IS_PART_OF_WORLD AND NOT ${the_module} STREQUAL opencv_world) OR NOT ${BUILD_opencv_world})
project(${the_module})
endif(OPENCV_INITIAL_PASS)
endif()
endif()
endmacro()
# excludes module from current configuration
@ -200,7 +218,11 @@ macro(ocv_glob_modules)
# collect modules
set(OPENCV_INITIAL_PASS ON)
set(OPENCV_PROCESSING_EXTRA_MODULES 0)
foreach(__path ${ARGN})
if("${__path}" STREQUAL "EXTRA")
set(OPENCV_PROCESSING_EXTRA_MODULES 1)
endif()
get_filename_component(__path "${__path}" ABSOLUTE)
list(FIND __directories_observed "${__path}" __pathIdx)
@ -222,17 +244,8 @@ macro(ocv_glob_modules)
endif()
list(APPEND __directories_observed "${__modpath}")
if(OCV_MODULE_RELOCATE_ON_INITIAL_PASS)
file(MAKE_DIRECTORY "${CMAKE_CURRENT_BINARY_DIR}/${mod}/.${mod}")
file(COPY "${__modpath}/CMakeLists.txt" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/${mod}/.${mod}")
add_subdirectory("${CMAKE_CURRENT_BINARY_DIR}/${mod}/.${mod}" "${CMAKE_CURRENT_BINARY_DIR}/${mod}/.${mod}")
if("${OPENCV_MODULE_opencv_${mod}_LOCATION}" STREQUAL "${CMAKE_CURRENT_BINARY_DIR}/${mod}/.${mod}")
set(OPENCV_MODULE_opencv_${mod}_LOCATION "${__modpath}" CACHE PATH "" FORCE)
endif()
else()
add_subdirectory("${__modpath}" "${CMAKE_CURRENT_BINARY_DIR}/${mod}/.${mod}")
endif()
endif()
endforeach()
endif()
endforeach()
@ -244,6 +257,21 @@ macro(ocv_glob_modules)
# create modules
set(OPENCV_INITIAL_PASS OFF PARENT_SCOPE)
set(OPENCV_INITIAL_PASS OFF)
if(${BUILD_opencv_world})
add_subdirectory("${OPENCV_MODULE_opencv_world_LOCATION}" "${CMAKE_CURRENT_BINARY_DIR}/world")
foreach(m ${OPENCV_MODULES_BUILD})
if(NOT OPENCV_MODULE_${m}_IS_PART_OF_WORLD AND NOT ${m} STREQUAL opencv_world)
message(STATUS "Processing module ${m}...")
if(m MATCHES "^opencv_")
string(REGEX REPLACE "^opencv_" "" __shortname "${m}")
add_subdirectory("${OPENCV_MODULE_${m}_LOCATION}" "${CMAKE_CURRENT_BINARY_DIR}/${__shortname}")
else()
message(WARNING "Check module name: ${m}")
add_subdirectory("${OPENCV_MODULE_${m}_LOCATION}" "${CMAKE_CURRENT_BINARY_DIR}/${m}")
endif()
endif()
endforeach()
else()
foreach(m ${OPENCV_MODULES_BUILD})
if(m MATCHES "^opencv_")
string(REGEX REPLACE "^opencv_" "" __shortname "${m}")
@ -253,6 +281,7 @@ macro(ocv_glob_modules)
add_subdirectory("${OPENCV_MODULE_${m}_LOCATION}" "${CMAKE_CURRENT_BINARY_DIR}/${m}")
endif()
endforeach()
endif()
unset(__shortname)
endmacro()
@ -394,11 +423,36 @@ function(__ocv_resolve_dependencies)
__ocv_sort_modules_by_deps(OPENCV_MODULE_${m}_DEPS)
ocv_list_sort(OPENCV_MODULE_${m}_DEPS_EXT)
set(LINK_DEPS ${OPENCV_MODULE_${m}_DEPS})
# process world
if(BUILD_opencv_world)
if(OPENCV_MODULE_${m}_IS_PART_OF_WORLD)
list(APPEND OPENCV_WORLD_MODULES ${m})
endif()
foreach(m2 ${OPENCV_MODULES_BUILD})
if(OPENCV_MODULE_${m2}_IS_PART_OF_WORLD)
if(";${LINK_DEPS};" MATCHES ";${m2};")
list(REMOVE_ITEM LINK_DEPS ${m2})
if(NOT (";${LINK_DEPS};" MATCHES ";opencv_world;") AND NOT (${m} STREQUAL opencv_world))
list(APPEND LINK_DEPS opencv_world)
endif()
endif()
if(${m} STREQUAL opencv_world)
list(APPEND OPENCV_MODULE_opencv_world_DEPS_EXT ${OPENCV_MODULE_${m2}_DEPS_EXT})
endif()
endif()
endforeach()
endif()
set(OPENCV_MODULE_${m}_DEPS ${OPENCV_MODULE_${m}_DEPS} CACHE INTERNAL "Flattened dependencies of ${m} module")
set(OPENCV_MODULE_${m}_DEPS_EXT ${OPENCV_MODULE_${m}_DEPS_EXT} CACHE INTERNAL "Extra dependencies of ${m} module")
set(OPENCV_MODULE_${m}_DEPS_TO_LINK ${LINK_DEPS} CACHE INTERNAL "Flattened dependencies of ${m} module (for linker)")
# message(STATUS " module deps: ${OPENCV_MODULE_${m}_DEPS}")
# message(STATUS " extra deps: ${OPENCV_MODULE_${m}_DEPS_EXT}")
# message(STATUS " module deps of ${m}: ${OPENCV_MODULE_${m}_DEPS}")
# message(STATUS " module link deps of ${m}: ${OPENCV_MODULE_${m}_DEPS_TO_LINK}")
# message(STATUS " extra deps of ${m}: ${OPENCV_MODULE_${m}_DEPS_EXT}")
# message(STATUS "")
endforeach()
__ocv_sort_modules_by_deps(OPENCV_MODULES_BUILD)
@ -406,6 +460,7 @@ function(__ocv_resolve_dependencies)
set(OPENCV_MODULES_PUBLIC ${OPENCV_MODULES_PUBLIC} CACHE INTERNAL "List of OpenCV modules marked for export")
set(OPENCV_MODULES_BUILD ${OPENCV_MODULES_BUILD} CACHE INTERNAL "List of OpenCV modules included into the build")
set(OPENCV_MODULES_DISABLED_AUTO ${OPENCV_MODULES_DISABLED_AUTO} CACHE INTERNAL "List of OpenCV modules implicitly disabled due to dependencies")
set(OPENCV_WORLD_MODULES ${OPENCV_WORLD_MODULES} CACHE INTERNAL "List of OpenCV modules included into the world")
endfunction()
@ -422,18 +477,31 @@ macro(ocv_include_modules)
endforeach()
endmacro()
# setup include paths for the list of passed modules and recursively add dependent modules
macro(ocv_include_modules_recurse)
# setup include paths for the list of passed modules
macro(ocv_target_include_modules target)
foreach(d ${ARGN})
if(d MATCHES "^opencv_" AND HAVE_${d})
if (EXISTS "${OPENCV_MODULE_${d}_LOCATION}/include")
ocv_include_directories("${OPENCV_MODULE_${d}_LOCATION}/include")
endif()
if(OPENCV_MODULE_${d}_DEPS)
ocv_include_modules(${OPENCV_MODULE_${d}_DEPS})
ocv_target_include_directories(${target} "${OPENCV_MODULE_${d}_LOCATION}/include")
endif()
elseif(EXISTS "${d}")
ocv_include_directories("${d}")
ocv_target_include_directories(${target} "${d}")
endif()
endforeach()
endmacro()
# setup include paths for the list of passed modules and recursively add dependent modules
macro(ocv_target_include_modules_recurse target)
foreach(d ${ARGN})
if(d MATCHES "^opencv_" AND HAVE_${d})
if (EXISTS "${OPENCV_MODULE_${d}_LOCATION}/include")
ocv_target_include_directories(${target} "${OPENCV_MODULE_${d}_LOCATION}/include")
endif()
if(OPENCV_MODULE_${d}_DEPS)
ocv_target_include_modules(${target} ${OPENCV_MODULE_${d}_DEPS})
endif()
elseif(EXISTS "${d}")
ocv_target_include_directories(${target} "${d}")
endif()
endforeach()
endmacro()
@ -441,11 +509,12 @@ endmacro()
# setup include path for OpenCV headers for specified module
# ocv_module_include_directories(<extra include directories/extra include modules>)
macro(ocv_module_include_directories)
ocv_include_directories("${OPENCV_MODULE_${the_module}_LOCATION}/include"
ocv_target_include_directories(${the_module}
"${OPENCV_MODULE_${the_module}_LOCATION}/include"
"${OPENCV_MODULE_${the_module}_LOCATION}/src"
"${CMAKE_CURRENT_BINARY_DIR}" # for precompiled headers
)
ocv_include_modules(${OPENCV_MODULE_${the_module}_DEPS} ${ARGN})
ocv_target_include_modules(${the_module} ${OPENCV_MODULE_${the_module}_DEPS} ${ARGN})
endmacro()
@ -454,6 +523,8 @@ endmacro()
# Usage:
# ocv_set_module_sources([HEADERS] <list of files> [SOURCES] <list of files>)
macro(ocv_set_module_sources)
ocv_debug_message("ocv_set_module_sources(" ${ARGN} ")")
set(OPENCV_MODULE_${the_module}_HEADERS "")
set(OPENCV_MODULE_${the_module}_SOURCES "")
@ -481,31 +552,50 @@ endmacro()
# Usage:
# ocv_glob_module_sources([EXCLUDE_CUDA] <extra sources&headers in the same format as used in ocv_set_module_sources>)
macro(ocv_glob_module_sources)
ocv_debug_message("ocv_glob_module_sources(" ${ARGN} ")")
set(_argn ${ARGN})
list(FIND _argn "EXCLUDE_CUDA" exclude_cuda)
if(NOT exclude_cuda EQUAL -1)
list(REMOVE_AT _argn ${exclude_cuda})
endif()
file(GLOB_RECURSE lib_srcs "src/*.cpp")
file(GLOB_RECURSE lib_int_hdrs "src/*.hpp" "src/*.h")
file(GLOB lib_hdrs "include/opencv2/*.hpp" "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
file(GLOB lib_hdrs_detail "include/opencv2/${name}/detail/*.hpp" "include/opencv2/${name}/detail/*.h")
file(GLOB_RECURSE lib_srcs_apple "src/*.mm")
file(GLOB_RECURSE lib_srcs
"${CMAKE_CURRENT_LIST_DIR}/src/*.cpp"
)
file(GLOB_RECURSE lib_int_hdrs
"${CMAKE_CURRENT_LIST_DIR}/src/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/src/*.h"
)
file(GLOB lib_hdrs
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/*.h"
)
file(GLOB lib_hdrs_detail
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/detail/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/detail/*.h"
)
if (APPLE)
file(GLOB_RECURSE lib_srcs_apple
"${CMAKE_CURRENT_LIST_DIR}/src/*.mm"
)
list(APPEND lib_srcs ${lib_srcs_apple})
endif()
ocv_source_group("Src" DIRBASE "${CMAKE_CURRENT_SOURCE_DIR}/src" FILES ${lib_srcs} ${lib_int_hdrs})
ocv_source_group("Include" DIRBASE "${CMAKE_CURRENT_SOURCE_DIR}/include" FILES ${lib_hdrs} ${lib_hdrs_detail})
ocv_source_group("Src" DIRBASE "${CMAKE_CURRENT_LIST_DIR}/src" FILES ${lib_srcs} ${lib_int_hdrs})
ocv_source_group("Include" DIRBASE "${CMAKE_CURRENT_LIST_DIR}/include" FILES ${lib_hdrs} ${lib_hdrs_detail})
if (exclude_cuda EQUAL -1)
file(GLOB lib_cuda_srcs "src/cuda/*.cu")
file(GLOB lib_cuda_srcs
"${CMAKE_CURRENT_LIST_DIR}/src/cuda/*.cu"
)
set(cuda_objs "")
set(lib_cuda_hdrs "")
if(HAVE_CUDA)
ocv_include_directories(${CUDA_INCLUDE_DIRS})
file(GLOB lib_cuda_hdrs "src/cuda/*.hpp")
file(GLOB lib_cuda_hdrs
"${CMAKE_CURRENT_LIST_DIR}/src/cuda/*.hpp"
)
ocv_cuda_compile(cuda_objs ${lib_cuda_srcs} ${lib_cuda_hdrs})
source_group("Src\\Cuda" FILES ${lib_cuda_srcs} ${lib_cuda_hdrs})
@ -516,17 +606,19 @@ macro(ocv_glob_module_sources)
set(lib_cuda_hdrs "")
endif()
file(GLOB cl_kernels "src/opencl/*.cl")
file(GLOB cl_kernels
"${CMAKE_CURRENT_LIST_DIR}/src/opencl/*.cl"
)
if(cl_kernels)
set(OCL_NAME opencl_kernels_${name})
ocv_include_directories(${OPENCL_INCLUDE_DIRS})
string(REGEX REPLACE "opencv_" "" the_module_barename "${the_module}")
add_custom_command(
OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.hpp"
COMMAND ${CMAKE_COMMAND} -DMODULE_NAME="${the_module_barename}" -DCL_DIR="${CMAKE_CURRENT_SOURCE_DIR}/src/opencl" -DOUTPUT="${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" -P "${OpenCV_SOURCE_DIR}/cmake/cl2cpp.cmake"
OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.cpp" "${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.hpp"
COMMAND ${CMAKE_COMMAND} -DMODULE_NAME="${name}" -DCL_DIR="${CMAKE_CURRENT_LIST_DIR}/src/opencl" -DOUTPUT="${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.cpp" -P "${OpenCV_SOURCE_DIR}/cmake/cl2cpp.cmake"
DEPENDS ${cl_kernels} "${OpenCV_SOURCE_DIR}/cmake/cl2cpp.cmake")
ocv_source_group("Src\\opencl\\kernels" FILES ${cl_kernels})
ocv_source_group("Src\\opencl\\kernels\\autogenerated" FILES "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.hpp")
list(APPEND lib_srcs ${cl_kernels} "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.hpp")
ocv_source_group("Src\\opencl\\kernels\\autogenerated" FILES "${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.cpp" "${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.hpp")
list(APPEND lib_srcs ${cl_kernels} "${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.cpp" "${CMAKE_CURRENT_BINARY_DIR}/${OCL_NAME}.hpp")
endif()
ocv_set_module_sources(${_argn} HEADERS ${lib_hdrs} ${lib_hdrs_detail}
@ -537,29 +629,39 @@ endmacro()
# creates new target, configures standard dependencies, compilers flags, install rules
# Usage:
# ocv_create_module(<extra link dependencies>)
# ocv_create_module(SKIP_LINK)
# ocv_create_module()
macro(ocv_create_module)
ocv_debug_message("ocv_create_module(" ${ARGN} ")")
set(OPENCV_MODULE_${the_module}_LINK_DEPS "${OPENCV_MODULE_${the_module}_LINK_DEPS};${ARGN}" CACHE INTERNAL "")
if(${BUILD_opencv_world} AND OPENCV_MODULE_${the_module}_IS_PART_OF_WORLD)
# nothing
set(the_module_target opencv_world)
else()
_ocv_create_module(${ARGN})
set(the_module_target ${the_module})
endif()
endmacro()
macro(_ocv_create_module)
# The condition we ought to be testing here is whether ocv_add_precompiled_headers will
# be called at some point in the future. We can't look into the future, though,
# so this will have to do.
if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/src/precomp.hpp")
if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/src/precomp.hpp" AND NOT ${the_module} STREQUAL opencv_world)
get_native_precompiled_header(${the_module} precomp.hpp)
endif()
add_library(${the_module} ${OPENCV_MODULE_TYPE} ${OPENCV_MODULE_${the_module}_HEADERS} ${OPENCV_MODULE_${the_module}_SOURCES}
ocv_add_library(${the_module} ${OPENCV_MODULE_TYPE} ${OPENCV_MODULE_${the_module}_HEADERS} ${OPENCV_MODULE_${the_module}_SOURCES}
"${OPENCV_CONFIG_FILE_INCLUDE_DIR}/cvconfig.h" "${OPENCV_CONFIG_FILE_INCLUDE_DIR}/opencv2/opencv_modules.hpp"
${${the_module}_pch})
if(NOT the_module STREQUAL opencv_ts)
set_target_properties(${the_module} PROPERTIES COMPILE_DEFINITIONS OPENCV_NOSTL)
endif()
if(NOT "${ARGN}" STREQUAL "SKIP_LINK")
target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS})
target_link_libraries(${the_module} LINK_INTERFACE_LIBRARIES ${OPENCV_MODULE_${the_module}_DEPS})
target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS_EXT} ${OPENCV_LINKER_LIBS} ${IPP_LIBS} ${ARGN})
ocv_target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS_TO_LINK})
ocv_target_link_libraries(${the_module} LINK_INTERFACE_LIBRARIES ${OPENCV_MODULE_${the_module}_DEPS_TO_LINK})
ocv_target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS_EXT} ${OPENCV_LINKER_LIBS} ${IPP_LIBS} ${ARGN})
if (HAVE_CUDA)
target_link_libraries(${the_module} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
endif()
ocv_target_link_libraries(${the_module} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
endif()
add_dependencies(opencv_modules ${the_module})
@ -614,13 +716,16 @@ macro(ocv_create_module)
endif()
endforeach()
endif()
_ocv_add_precompiled_headers(${the_module})
endmacro()
# opencv precompiled headers macro (can add pch to modules and tests)
# this macro must be called after any "add_definitions" commands, otherwise precompiled headers will not work
# Usage:
# ocv_add_precompiled_headers(${the_module})
macro(ocv_add_precompiled_headers the_target)
macro(_ocv_add_precompiled_headers the_target)
ocv_debug_message("ocv_add_precompiled_headers(" ${the_target} ${ARGN} ")")
if("${the_target}" MATCHES "^opencv_test_.*$")
SET(pch_path "test/test_")
elseif("${the_target}" MATCHES "^opencv_perf_.*$")
@ -637,6 +742,7 @@ endmacro()
# Usage:
# ocv_define_module(module_name [INTERNAL] [EXCLUDE_CUDA] [REQUIRED] [<list of dependencies>] [OPTIONAL <list of optional dependencies>])
macro(ocv_define_module module_name)
ocv_debug_message("ocv_define_module(" ${module_name} ${ARGN} ")")
set(_argn ${ARGN})
set(exclude_cuda "")
foreach(arg ${_argn})
@ -647,10 +753,9 @@ macro(ocv_define_module module_name)
endforeach()
ocv_add_module(${module_name} ${_argn})
ocv_module_include_directories()
ocv_glob_module_sources(${exclude_cuda})
ocv_module_include_directories()
ocv_create_module()
ocv_add_precompiled_headers(${the_module})
ocv_add_accuracy_tests()
ocv_add_perf_tests()
@ -685,7 +790,7 @@ macro(__ocv_parse_test_sources tests_type)
set(__file_group_name "")
set(__file_group_sources "")
elseif(arg STREQUAL "DEPENDS_ON")
set(__currentvar "OPENCV_TEST_${the_module}_DEPS")
set(__currentvar "OPENCV_${tests_type}_${the_module}_DEPS")
elseif("${__currentvar}" STREQUAL "__file_group_sources" AND NOT __file_group_name)
set(__file_group_name "${arg}")
else()
@ -700,20 +805,20 @@ endmacro()
# this is a command for adding OpenCV performance tests to the module
# ocv_add_perf_tests(<extra_dependencies>)
function(ocv_add_perf_tests)
set(perf_path "${CMAKE_CURRENT_SOURCE_DIR}/perf")
ocv_debug_message("ocv_add_perf_tests(" ${ARGN} ")")
set(perf_path "${CMAKE_CURRENT_LIST_DIR}/perf")
if(BUILD_PERF_TESTS AND EXISTS "${perf_path}")
__ocv_parse_test_sources(PERF ${ARGN})
# opencv_highgui is required for imread/imwrite
set(perf_deps ${the_module} opencv_ts opencv_highgui ${OPENCV_PERF_${the_module}_DEPS} ${OPENCV_MODULE_opencv_ts_DEPS})
# opencv_imgcodecs is required for imread/imwrite
set(perf_deps ${the_module} opencv_ts opencv_imgcodecs ${OPENCV_MODULE_${the_module}_DEPS} ${OPENCV_MODULE_opencv_ts_DEPS})
ocv_check_dependencies(${perf_deps})
if(OCV_DEPENDENCIES_FOUND)
set(the_target "opencv_perf_${name}")
# project(${the_target})
ocv_module_include_directories(${perf_deps} "${perf_path}")
if(NOT OPENCV_PERF_${the_module}_SOURCES)
file(GLOB_RECURSE perf_srcs "${perf_path}/*.cpp")
file(GLOB_RECURSE perf_hdrs "${perf_path}/*.hpp" "${perf_path}/*.h")
@ -722,10 +827,13 @@ function(ocv_add_perf_tests)
set(OPENCV_PERF_${the_module}_SOURCES ${perf_srcs} ${perf_hdrs})
endif()
if(NOT BUILD_opencv_world)
get_native_precompiled_header(${the_target} perf_precomp.hpp)
endif()
add_executable(${the_target} ${OPENCV_PERF_${the_module}_SOURCES} ${${the_target}_pch})
target_link_libraries(${the_target} ${OPENCV_MODULE_${the_module}_DEPS} ${perf_deps} ${OPENCV_LINKER_LIBS})
ocv_add_executable(${the_target} ${OPENCV_PERF_${the_module}_SOURCES} ${${the_target}_pch})
ocv_target_include_modules(${the_target} ${perf_deps} "${perf_path}")
ocv_target_link_libraries(${the_target} ${OPENCV_MODULE_${the_module}_DEPS} ${perf_deps} ${OPENCV_LINKER_LIBS})
add_dependencies(opencv_perf_tests ${the_target})
# Additional target properties
@ -738,8 +846,9 @@ function(ocv_add_perf_tests)
set_target_properties(${the_target} PROPERTIES FOLDER "tests performance")
endif()
ocv_add_precompiled_headers(${the_target})
if(NOT BUILD_opencv_world)
_ocv_add_precompiled_headers(${the_target})
endif()
else(OCV_DEPENDENCIES_FOUND)
# TODO: warn about unsatisfied dependencies
endif(OCV_DEPENDENCIES_FOUND)
@ -752,21 +861,19 @@ endfunction()
# this is a command for adding OpenCV accuracy/regression tests to the module
# ocv_add_accuracy_tests([FILES <source group name> <list of sources>] [DEPENDS_ON] <list of extra dependencies>)
function(ocv_add_accuracy_tests)
set(test_path "${CMAKE_CURRENT_SOURCE_DIR}/test")
ocv_check_dependencies(${test_deps})
ocv_debug_message("ocv_add_accuracy_tests(" ${ARGN} ")")
set(test_path "${CMAKE_CURRENT_LIST_DIR}/test")
if(BUILD_TESTS AND EXISTS "${test_path}")
__ocv_parse_test_sources(TEST ${ARGN})
# opencv_highgui is required for imread/imwrite
set(test_deps ${the_module} opencv_ts opencv_highgui ${OPENCV_TEST_${the_module}_DEPS} ${OPENCV_MODULE_opencv_ts_DEPS})
# opencv_imgcodecs is required for imread/imwrite
set(test_deps ${the_module} opencv_ts opencv_imgcodecs opencv_videoio ${OPENCV_MODULE_${the_module}_DEPS} ${OPENCV_MODULE_opencv_ts_DEPS})
ocv_check_dependencies(${test_deps})
if(OCV_DEPENDENCIES_FOUND)
set(the_target "opencv_test_${name}")
# project(${the_target})
ocv_module_include_directories(${test_deps} "${test_path}")
if(NOT OPENCV_TEST_${the_module}_SOURCES)
file(GLOB_RECURSE test_srcs "${test_path}/*.cpp")
file(GLOB_RECURSE test_hdrs "${test_path}/*.hpp" "${test_path}/*.h")
@ -775,10 +882,13 @@ function(ocv_add_accuracy_tests)
set(OPENCV_TEST_${the_module}_SOURCES ${test_srcs} ${test_hdrs})
endif()
if(NOT BUILD_opencv_world)
get_native_precompiled_header(${the_target} test_precomp.hpp)
add_executable(${the_target} ${OPENCV_TEST_${the_module}_SOURCES} ${${the_target}_pch})
endif()
target_link_libraries(${the_target} ${OPENCV_MODULE_${the_module}_DEPS} ${test_deps} ${OPENCV_LINKER_LIBS})
ocv_add_executable(${the_target} ${OPENCV_TEST_${the_module}_SOURCES} ${${the_target}_pch})
ocv_target_include_modules(${the_target} ${test_deps} "${test_path}")
ocv_target_link_libraries(${the_target} ${OPENCV_MODULE_${the_module}_DEPS} ${test_deps} ${OPENCV_LINKER_LIBS})
add_dependencies(opencv_tests ${the_target})
# Additional target properties
@ -795,7 +905,9 @@ function(ocv_add_accuracy_tests)
get_target_property(LOC ${the_target} LOCATION)
add_test(${the_target} "${LOC}")
ocv_add_precompiled_headers(${the_target})
if(NOT BUILD_opencv_world)
_ocv_add_precompiled_headers(${the_target})
endif()
else(OCV_DEPENDENCIES_FOUND)
# TODO: warn about unsatisfied dependencies
endif(OCV_DEPENDENCIES_FOUND)
@ -807,24 +919,25 @@ function(ocv_add_accuracy_tests)
endfunction()
function(ocv_add_samples)
ocv_debug_message("ocv_add_samples(" ${ARGN} ")")
set(samples_path "${CMAKE_CURRENT_SOURCE_DIR}/samples")
string(REGEX REPLACE "^opencv_" "" module_id ${the_module})
if(BUILD_EXAMPLES AND EXISTS "${samples_path}")
set(samples_deps ${the_module} ${OPENCV_MODULE_${the_module}_DEPS} opencv_highgui ${ARGN})
set(samples_deps ${the_module} ${OPENCV_MODULE_${the_module}_DEPS} opencv_imgcodecs opencv_videoio opencv_highgui ${ARGN})
ocv_check_dependencies(${samples_deps})
if(OCV_DEPENDENCIES_FOUND)
file(GLOB sample_sources "${samples_path}/*.cpp")
ocv_include_modules(${OPENCV_MODULE_${the_module}_DEPS})
foreach(source ${sample_sources})
get_filename_component(name "${source}" NAME_WE)
set(the_target "example_${module_id}_${name}")
add_executable(${the_target} "${source}")
target_link_libraries(${the_target} ${samples_deps})
ocv_add_executable(${the_target} "${source}")
ocv_target_include_modules(${the_target} ${samples_deps})
ocv_target_link_libraries(${the_target} ${samples_deps})
set_target_properties(${the_target} PROPERTIES PROJECT_LABEL "(sample) ${name}")
if(ENABLE_SOLUTION_FOLDERS)
@ -847,82 +960,3 @@ function(ocv_add_samples)
PERMISSIONS OWNER_READ GROUP_READ WORLD_READ COMPONENT samples)
endif()
endfunction()
# internal macro; finds all link dependencies of the module
# should be used at the end of CMake processing
macro(__ocv_track_module_link_dependencies the_module optkind)
set(${the_module}_MODULE_DEPS_${optkind} "")
set(${the_module}_EXTRA_DEPS_${optkind} "")
get_target_property(__module_type ${the_module} TYPE)
if(__module_type STREQUAL "STATIC_LIBRARY")
#in case of static library we have to inherit its dependencies (in right order!!!)
if(NOT DEFINED ${the_module}_LIB_DEPENDS_${optkind})
ocv_split_libs_list(${the_module}_LIB_DEPENDS ${the_module}_LIB_DEPENDS_DBG ${the_module}_LIB_DEPENDS_OPT)
endif()
set(__resolved_deps "")
set(__mod_depends ${${the_module}_LIB_DEPENDS_${optkind}})
set(__has_cycle FALSE)
while(__mod_depends)
list(GET __mod_depends 0 __dep)
list(REMOVE_AT __mod_depends 0)
if(__dep STREQUAL the_module)
set(__has_cycle TRUE)
else()#if("${OPENCV_MODULES_BUILD}" MATCHES "(^|;)${__dep}(;|$)")
ocv_regex_escape(__rdep "${__dep}")
if(__resolved_deps MATCHES "(^|;)${__rdep}(;|$)")
#all dependencies of this module are already resolved
list(APPEND ${the_module}_MODULE_DEPS_${optkind} "${__dep}")
else()
get_target_property(__module_type ${__dep} TYPE)
if(__module_type STREQUAL "STATIC_LIBRARY")
if(NOT DEFINED ${__dep}_LIB_DEPENDS_${optkind})
ocv_split_libs_list(${__dep}_LIB_DEPENDS ${__dep}_LIB_DEPENDS_DBG ${__dep}_LIB_DEPENDS_OPT)
endif()
list(INSERT __mod_depends 0 ${${__dep}_LIB_DEPENDS_${optkind}} ${__dep})
list(APPEND __resolved_deps "${__dep}")
elseif(NOT __module_type)
list(APPEND ${the_module}_EXTRA_DEPS_${optkind} "${__dep}")
endif()
endif()
#else()
# get_target_property(__dep_location "${__dep}" LOCATION)
endif()
endwhile()
ocv_list_unique(${the_module}_MODULE_DEPS_${optkind})
#ocv_list_reverse(${the_module}_MODULE_DEPS_${optkind})
ocv_list_unique(${the_module}_EXTRA_DEPS_${optkind})
#ocv_list_reverse(${the_module}_EXTRA_DEPS_${optkind})
if(__has_cycle)
# not sure if it can work
list(APPEND ${the_module}_MODULE_DEPS_${optkind} "${the_module}")
endif()
unset(__dep_location)
unset(__mod_depends)
unset(__resolved_deps)
unset(__has_cycle)
unset(__rdep)
endif()#STATIC_LIBRARY
unset(__module_type)
#message("${the_module}_MODULE_DEPS_${optkind}")
#message(" ${${the_module}_MODULE_DEPS_${optkind}}")
#message(" ${OPENCV_MODULE_${the_module}_DEPS}")
#message("")
#message("${the_module}_EXTRA_DEPS_${optkind}")
#message(" ${${the_module}_EXTRA_DEPS_${optkind}}")
#message("")
endmacro()
# creates lists of build dependencies needed for external projects
macro(ocv_track_build_dependencies)
foreach(m ${OPENCV_MODULES_BUILD})
__ocv_track_module_link_dependencies("${m}" OPT)
__ocv_track_module_link_dependencies("${m}" DBG)
endforeach()
endmacro()

12
cmake/OpenCVPCHSupport.cmake
View File

@ -68,6 +68,15 @@ MACRO(_PCH_GET_COMPILE_FLAGS _out_compile_flags)
endif()
ENDFOREACH(item)
get_target_property(DIRINC ${_PCH_current_target} 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)
GET_DIRECTORY_PROPERTY(_global_definitions DIRECTORY ${OpenCV_SOURCE_DIR} DEFINITIONS)
#MESSAGE("_directory_flags ${_directory_flags} ${_global_definitions}" )
@ -254,6 +263,9 @@ MACRO(ADD_PRECOMPILED_HEADER _targetName _input)
endif()
endif()
get_target_property(DIRINC ${_targetName} INCLUDE_DIRECTORIES)
set_target_properties(${_targetName}_pch_dephelp PROPERTIES INCLUDE_DIRECTORIES "${DIRINC}")
#MESSAGE("_compile_FLAGS: ${_compile_FLAGS}")
#message("COMMAND ${CMAKE_CXX_COMPILER} ${_compile_FLAGS} -x c++-header -o ${_output} ${_input}")

89
cmake/OpenCVUtils.cmake
View File

@ -42,6 +42,11 @@ macro(ocv_assert)
endif()
endmacro()
macro(ocv_debug_message)
# string(REPLACE ";" " " __msg "${ARGN}")
# message(STATUS "${__msg}")
endmacro()
macro(ocv_check_environment_variables)
foreach(_var ${ARGN})
if(NOT DEFINED ${_var} AND DEFINED ENV{${_var}})
@ -53,8 +58,18 @@ macro(ocv_check_environment_variables)
endforeach()
endmacro()
# rename modules target to world if needed
macro(_ocv_fix_target target_var)
if(BUILD_opencv_world)
if(OPENCV_MODULE_${${target_var}}_IS_PART_OF_WORLD)
set(${target_var} opencv_world)
endif()
endif()
endmacro()
# adds include directories in such way that directories from the OpenCV source tree go first
function(ocv_include_directories)
ocv_debug_message("ocv_include_directories( ${ARGN} )")
set(__add_before "")
foreach(dir ${ARGN})
get_filename_component(__abs_dir "${dir}" ABSOLUTE)
@ -67,6 +82,30 @@ function(ocv_include_directories)
include_directories(BEFORE ${__add_before})
endfunction()
# adds include directories in such way that directories from the OpenCV source tree go first
function(ocv_target_include_directories target)
_ocv_fix_target(target)
set(__params "")
foreach(dir ${ARGN})
get_filename_component(__abs_dir "${dir}" ABSOLUTE)
if("${__abs_dir}" MATCHES "^${OpenCV_SOURCE_DIR}" OR "${__abs_dir}" MATCHES "^${OpenCV_BINARY_DIR}")
list(APPEND __params "${__abs_dir}")
else()
list(APPEND __params "${dir}")
endif()
endforeach()
if(CMAKE_VERSION VERSION_LESS 2.8.11)
include_directories(${__params})
else()
if(TARGET ${target})
target_include_directories(${target} PRIVATE ${__params})
else()
set(__new_inc "${OCV_TARGET_INCLUDE_DIRS_${target}};${__params}")
set(OCV_TARGET_INCLUDE_DIRS_${target} "${__new_inc}" CACHE INTERNAL "")
endif()
endif()
endfunction()
# clears all passed variables
macro(ocv_clear_vars)
foreach(_var ${ARGN})
@ -265,16 +304,19 @@ macro(CHECK_MODULE module_name define)
set(${define} 1)
foreach(P "${ALIAS_INCLUDE_DIRS}")
if(${P})
list(APPEND VIDEOIO_INCLUDE_DIRS ${${P}})
list(APPEND HIGHGUI_INCLUDE_DIRS ${${P}})
endif()
endforeach()
foreach(P "${ALIAS_LIBRARY_DIRS}")
if(${P})
list(APPEND VIDEOIO_LIBRARY_DIRS ${${P}})
list(APPEND HIGHGUI_LIBRARY_DIRS ${${P}})
endif()
endforeach()
list(APPEND VIDEOIO_LIBRARIES ${${ALIAS_LIBRARIES}})
list(APPEND HIGHGUI_LIBRARIES ${${ALIAS_LIBRARIES}})
endif()
endif()
@ -292,8 +334,8 @@ endfunction()
macro(ocv_finalize_status)
if(NOT OPENCV_SKIP_STATUS_FINALIZATION)
if(TARGET opencv_core)
execute_process(COMMAND ${CMAKE_COMMAND} -E copy_if_different "${OPENCV_BUILD_INFO_FILE}" "${opencv_core_BINARY_DIR}/version_string.inc" OUTPUT_QUIET)
if(DEFINED OPENCV_MODULE_opencv_core_BINARY_DIR)
execute_process(COMMAND ${CMAKE_COMMAND} -E copy_if_different "${OPENCV_BUILD_INFO_FILE}" "${OPENCV_MODULE_opencv_core_BINARY_DIR}/version_string.inc" OUTPUT_QUIET)
endif()
endif()
endmacro()
@ -530,6 +572,7 @@ function(ocv_install_target)
# message(STATUS "Process ${__target} dst=${__dst}...")
if(DEFINED __dst)
if(CMAKE_VERSION VERSION_LESS 2.8.12)
get_target_property(fname ${__target} LOCATION_DEBUG)
if(fname MATCHES "\\.lib$")
string(REGEX REPLACE "\\.lib$" ".pdb" fname "${fname}")
@ -541,6 +584,9 @@ function(ocv_install_target)
string(REGEX REPLACE "\\.lib$" ".pdb" fname "${fname}")
install(FILES ${fname} DESTINATION ${__dst} CONFIGURATIONS Release)
endif()
else()
# CMake 2.8.12 brokes PDB support in STATIC libraries for MSVS
endif()
endif()
endif()
endif()
@ -634,6 +680,9 @@ endmacro()
################################################################################################
# short command to setup source group
function(ocv_source_group group)
if(BUILD_opencv_world AND OPENCV_MODULE_${the_module}_IS_PART_OF_WORLD)
set(group "${the_module}\\${group}")
endif()
cmake_parse_arguments(SG "" "DIRBASE" "GLOB;GLOB_RECURSE;FILES" ${ARGN})
set(files "")
if(SG_FILES)
@ -666,3 +715,39 @@ function(ocv_source_group group)
source_group(${group} FILES ${files})
endif()
endfunction()
function(ocv_target_link_libraries target)
_ocv_fix_target(target)
set(LINK_DEPS ${ARGN})
# process world
if(BUILD_opencv_world)
foreach(m ${OPENCV_MODULES_BUILD})
if(OPENCV_MODULE_${m}_IS_PART_OF_WORLD)
if(";${LINK_DEPS};" MATCHES ";${m};")
list(REMOVE_ITEM LINK_DEPS ${m})
if(NOT (";${LINK_DEPS};" MATCHES ";opencv_world;"))
list(APPEND LINK_DEPS opencv_world)
endif()
endif()
endif()
endforeach()
endif()
target_link_libraries(${target} ${LINK_DEPS})
endfunction()
function(_ocv_append_target_includes target)
if(DEFINED OCV_TARGET_INCLUDE_DIRS_${target})
target_include_directories(${target} PRIVATE ${OCV_TARGET_INCLUDE_DIRS_${target}})
unset(OCV_TARGET_INCLUDE_DIRS_${target} CACHE)
endif()
endfunction()
function(ocv_add_executable target)
add_executable(${target} ${ARGN})
_ocv_append_target_includes(${target})
endfunction()
function(ocv_add_library target)
add_library(${target} ${ARGN})
_ocv_append_target_includes(${target})
endfunction()

39
cmake/templates/OpenCVConfig.cmake.in
View File

@ -12,7 +12,7 @@
#
# Or you can search for specific OpenCV modules:
#
# find_package(OpenCV REQUIRED core highgui)
# find_package(OpenCV REQUIRED core videoio)
#
# If the module is found then OPENCV_<MODULE>_FOUND is set to TRUE.
#
@ -141,6 +141,7 @@ SET(OpenCV_VERSION_STATUS "@OPENCV_VERSION_STATUS@")
# ====================================================================
SET(OpenCV_LIB_COMPONENTS @OPENCV_MODULES_CONFIGCMAKE@)
SET(OpenCV_WORLD_COMPONENTS @OPENCV_WORLD_MODULES@)
# ==============================================================
# Extra include directories, needed by OpenCV 2 new structure
@ -200,8 +201,8 @@ foreach(__cvcomponent ${OpenCV_FIND_COMPONENTS})
message(WARNING "${__cvcomponent} is required but was not found")
endif()
#indicate that module is NOT found
string(TOUPPER "${__cvcomponent}" __cvcomponent)
set(${__cvcomponent}_FOUND "${__cvcomponent}_FOUND-NOTFOUND")
string(TOUPPER "${__cvcomponent}" __cvcomponentUP)
set(${__cvcomponentUP}_FOUND "${__cvcomponentUP}_FOUND-NOTFOUND")
else()
list(APPEND OpenCV_FIND_COMPONENTS_ ${__cvcomponent})
# Not using list(APPEND) here, because OpenCV_LIBS may not exist yet.
@ -209,8 +210,31 @@ foreach(__cvcomponent ${OpenCV_FIND_COMPONENTS})
# to find_package(OpenCV) with different component lists add up.
set(OpenCV_LIBS ${OpenCV_LIBS} "${__cvcomponent}")
#indicate that module is found
string(TOUPPER "${__cvcomponent}" __cvcomponent)
set(${__cvcomponent}_FOUND 1)
string(TOUPPER "${__cvcomponent}" __cvcomponentUP)
set(${__cvcomponentUP}_FOUND 1)
endif()
if(OpenCV_SHARED AND ";${OpenCV_WORLD_COMPONENTS};" MATCHES ";${__cvcomponent};" AND NOT TARGET ${__cvcomponent})
get_target_property(__implib_dbg opencv_world IMPORTED_IMPLIB_DEBUG)
get_target_property(__implib_release opencv_world IMPORTED_IMPLIB_RELEASE)
get_target_property(__location_dbg opencv_world IMPORTED_LOCATION_DEBUG)
get_target_property(__location_release opencv_world IMPORTED_LOCATION_RELEASE)
add_library(${__cvcomponent} SHARED IMPORTED)
if(__location_dbg)
set_property(TARGET ${__cvcomponent} APPEND PROPERTY IMPORTED_CONFIGURATIONS DEBUG)
set_target_properties(${__cvcomponent} PROPERTIES
IMPORTED_IMPLIB_DEBUG "${__implib_dbg}"
IMPORTED_LINK_INTERFACE_LIBRARIES_DEBUG ""
IMPORTED_LOCATION_DEBUG "${__location_dbg}"
)
endif()
if(__location_release)
set_property(TARGET ${__cvcomponent} APPEND PROPERTY IMPORTED_CONFIGURATIONS RELEASE)
set_target_properties(${__cvcomponent} PROPERTIES
IMPORTED_IMPLIB_RELEASE "${__implib_release}"
IMPORTED_LINK_INTERFACE_LIBRARIES_RELEASE ""
IMPORTED_LOCATION_RELEASE "${__location_release}"
)
endif()
endif()
endforeach()
set(OpenCV_FIND_COMPONENTS ${OpenCV_FIND_COMPONENTS_})
@ -321,6 +345,7 @@ macro(ocv_check_dependencies)
set(OCV_DEPENDENCIES_FOUND TRUE)
foreach(d ${ARGN})
if(NOT TARGET ${d})
message(WARNING "OpenCV: Can't resolve dependency: ${d}")
set(OCV_DEPENDENCIES_FOUND FALSE)
break()
endif()
@ -346,6 +371,10 @@ macro(ocv_include_modules)
include_directories(BEFORE "${OpenCV_INCLUDE_DIRS}")
endmacro()
macro(ocv_target_link_libraries)
target_link_libraries(${ARGN})
endmacro()
# remove all matching elements from the list
macro(ocv_list_filterout lst regex)
foreach(item ${${lst}})

3
cmake/templates/cvconfig.h.in
View File

@ -132,6 +132,9 @@
/* OpenNI library */
#cmakedefine HAVE_OPENNI
/* OpenNI library */
#cmakedefine HAVE_OPENNI2
/* PNG codec */
#cmakedefine HAVE_PNG

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6
doc/CMakeLists.txt
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@ -33,7 +33,7 @@ if(BUILD_DOCS AND HAVE_SPHINX)
endif()
endforeach()
set(FIXED_ORDER_MODULES core imgproc highgui video calib3d features2d objdetect ml flann photo stitching nonfree contrib legacy)
set(FIXED_ORDER_MODULES core imgproc imgcodecs videoio highgui video calib3d features2d objdetect ml flann photo stitching)
list(REMOVE_ITEM BASE_MODULES ${FIXED_ORDER_MODULES})
@ -105,8 +105,8 @@ if(BUILD_DOCS AND HAVE_SPHINX)
COMMAND ${SPHINX_BUILD} ${BUILD_PLANTUML} -b latex -c "${CMAKE_CURRENT_SOURCE_DIR}" "${DOC_FAKE_ROOT}" .
COMMAND ${CMAKE_COMMAND} -E copy_directory ${CMAKE_CURRENT_SOURCE_DIR}/pics ${CMAKE_CURRENT_BINARY_DIR}/doc/opencv1/pics
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${CMAKE_CURRENT_SOURCE_DIR}/mymath.sty ${CMAKE_CURRENT_BINARY_DIR}
COMMAND ${PYTHON_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/patch_refman_latex.py" opencv2refman.tex
COMMAND ${PYTHON_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/patch_refman_latex.py" opencv2manager.tex
COMMAND ${PYTHON_DEFAULT_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/patch_refman_latex.py" opencv2refman.tex
COMMAND ${PYTHON_DEFAULT_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/patch_refman_latex.py" opencv2manager.tex
COMMAND ${CMAKE_COMMAND} -E echo "Generating opencv2refman.pdf"
COMMAND ${PDFLATEX_COMPILER} -interaction=batchmode opencv2refman.tex
COMMAND ${PDFLATEX_COMPILER} -interaction=batchmode opencv2refman.tex

4
doc/check_docs.py
View File

@ -14,6 +14,8 @@ opencv_hdr_list = [
"../modules/video/include/opencv2/video/tracking.hpp",
"../modules/video/include/opencv2/video/background_segm.hpp",
"../modules/objdetect/include/opencv2/objdetect.hpp",
"../modules/imgcodecs/include/opencv2/imgcodecs.hpp",
"../modules/videoio/include/opencv2/videoio.hpp",
"../modules/highgui/include/opencv2/highgui.hpp",
]
@ -24,6 +26,8 @@ opencv_module_list = [
"features2d",
"video",
"objdetect",
"imgcodecs",
"videoio",
"highgui",
"ml"
]

12
doc/conf.py
View File

@ -302,14 +302,16 @@ man_pages = [
extlinks = {
'basicstructures' : ('http://docs.opencv.org/modules/core/doc/basic_structures.html#%s', None),
'oldbasicstructures' : ('http://docs.opencv.org/modules/core/doc/old_basic_structures.html#%s', None),
'readwriteimagevideo' : ('http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html#%s', None),
'readwriteimage' : ('http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html#%s', None),
'readwritevideo' : ('http://docs.opencv.org/modules/videoio/doc/reading_and_writing_video.html#%s', None),
'operationsonarrays' : ('http://docs.opencv.org/modules/core/doc/operations_on_arrays.html#%s', None),
'utilitysystemfunctions' : ('http://docs.opencv.org/modules/core/doc/utility_and_system_functions_and_macros.html#%s', None),
'imgprocfilter' : ('http://docs.opencv.org/modules/imgproc/doc/filtering.html#%s', None),
'svms' : ('http://docs.opencv.org/modules/ml/doc/support_vector_machines.html#%s', None),
'drawingfunc' : ('http://docs.opencv.org/modules/core/doc/drawing_functions.html#%s', None),
'xmlymlpers' : ('http://docs.opencv.org/modules/core/doc/xml_yaml_persistence.html#%s', None),
'hgvideo' : ('http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html#%s', None),
'rwimg' : ('http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html#%s', None),
'hgvideo' : ('http://docs.opencv.org/modules/videoio/doc/reading_and_writing_video.html#%s', None),
'gpuinit' : ('http://docs.opencv.org/modules/gpu/doc/initalization_and_information.html#%s', None),
'gpudatastructure' : ('http://docs.opencv.org/modules/gpu/doc/data_structures.html#%s', None),
'gpuopmatrices' : ('http://docs.opencv.org/modules/gpu/doc/operations_on_matrices.html#%s', None),
@ -329,8 +331,8 @@ extlinks = {
'how_to_contribute' : ('http://code.opencv.org/projects/opencv/wiki/How_to_contribute/%s', None),
'cvt_color' : ('http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html?highlight=cvtcolor#cvtcolor%s', None),
'imread' : ('http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html?highlight=imread#imread%s', None),
'imwrite' : ('http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html?highlight=imwrite#imwrite%s', None),
'imread' : ('http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html?highlight=imread#imread%s', None),
'imwrite' : ('http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html?highlight=imwrite#imwrite%s', None),
'imshow' : ('http://docs.opencv.org/modules/highgui/doc/user_interface.html?highlight=imshow#imshow%s', None),
'named_window' : ('http://docs.opencv.org/modules/highgui/doc/user_interface.html?highlight=namedwindow#namedwindow%s', None),
'wait_key' : ('http://docs.opencv.org/modules/highgui/doc/user_interface.html?highlight=waitkey#waitkey%s', None),
@ -418,7 +420,7 @@ extlinks = {
'background_subtractor' : ('http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html?highlight=backgroundsubtractor#backgroundsubtractor%s', None),
'background_subtractor_mog' : ('http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html?highlight=backgroundsubtractorMOG#backgroundsubtractormog%s', None),
'background_subtractor_mog_two' : ('http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html?highlight=backgroundsubtractorMOG2#backgroundsubtractormog2%s', None),
'video_capture' : ('http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html?highlight=videocapture#videocapture%s', None),
'video_capture' : ('http://docs.opencv.org/modules/videoio/doc/reading_and_writing_video.html?highlight=videocapture#videocapture%s', None),
'ippa_convert': ('http://docs.opencv.org/modules/core/doc/ipp_async_converters.html#%s', None),
'ptr':('http://docs.opencv.org/modules/core/doc/basic_structures.html?highlight=Ptr#Ptr%s', None)
}

6
doc/opencv_cheatsheet.tex
View File

@ -522,9 +522,9 @@ samples on what are the contours and how to use them.
\begin{tabbing}
\textbf{Wr}\=\textbf{iting and reading raster images}\\
\texttt{\href{http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html\#imwrite}{imwrite}("myimage.jpg", image);}\\
\texttt{Mat image\_color\_copy = \href{http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html\#imread}{imread}("myimage.jpg", 1);}\\
\texttt{Mat image\_grayscale\_copy = \href{http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html\#imread}{imread}("myimage.jpg", 0);}\\
\texttt{\href{http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html\#imwrite}{imwrite}("myimage.jpg", image);}\\
\texttt{Mat image\_color\_copy = \href{http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html\#imread}{imread}("myimage.jpg", 1);}\\
\texttt{Mat image\_grayscale\_copy = \href{http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html\#imread}{imread}("myimage.jpg", 0);}\\
\end{tabbing}
\emph{The functions can read/write images in the following formats: \textbf{BMP (.bmp), JPEG (.jpg, .jpeg), TIFF (.tif, .tiff), PNG (.png), PBM/PGM/PPM (.p?m), Sun Raster (.sr), JPEG 2000 (.jp2)}. Every format supports 8-bit, 1- or 3-channel images. Some formats (PNG, JPEG 2000) support 16 bits per channel.}

2
doc/py_tutorials/py_gui/py_video_display/py_video_display.rst
View File

@ -46,7 +46,7 @@ To capture a video, you need to create a **VideoCapture** object. Its argument c
Sometimes, ``cap`` may not have initialized the capture. In that case, this code shows error. You can check whether it is initialized or not by the method **cap.isOpened()**. If it is True, OK. Otherwise open it using **cap.open()**.
You can also access some of the features of this video using **cap.get(propId)** method where propId is a number from 0 to 18. Each number denotes a property of the video (if it is applicable to that video) and full details can be seen here: `Property Identifier <http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html#videocapture-get>`_. Some of these values can be modified using **cap.set(propId, value)**. Value is the new value you want.
You can also access some of the features of this video using **cap.get(propId)** method where propId is a number from 0 to 18. Each number denotes a property of the video (if it is applicable to that video) and full details can be seen here: `Property Identifier <http://docs.opencv.org/modules/highgui/doc/reading_and_writing_video.html#videocapture-get>`_. Some of these values can be modified using **cap.set(propId, value)**. Value is the new value you want.
For example, I can check the frame width and height by ``cap.get(3)`` and ``cap.get(4)``. It gives me 640x480 by default. But I want to modify it to 320x240. Just use ``ret = cap.set(3,320)`` and ``ret = cap.set(4,240)``.

2
doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.rst
View File

@ -25,7 +25,7 @@ Here's a sample usage of :operationsonarrays:`dft() <dft>` :
:language: cpp
:linenos:
:tab-width: 4
:lines: 1-3, 5, 19-20, 23-78
:lines: 1-4, 6, 20-21, 24-79
Explanation
===========

12
doc/tutorials/core/how_to_scan_images/how_to_scan_images.rst
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@ -45,7 +45,7 @@ The final argument is optional. If given the image will be loaded in gray scale
.. literalinclude:: ../../../../samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
:language: cpp
:tab-width: 4
:lines: 48-60
:lines: 49-61
Here we first use the C++ *stringstream* class to convert the third command line argument from text to an integer format. Then we use a simple look and the upper formula to calculate the lookup table. No OpenCV specific stuff here.
@ -99,7 +99,7 @@ When it comes to performance you cannot beat the classic C style operator[] (poi
.. literalinclude:: ../../../../samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
:language: cpp
:tab-width: 4
:lines: 125-152
:lines: 126-153
Here we basically just acquire a pointer to the start of each row and go through it until it ends. In the special case that the matrix is stored in a continues manner we only need to request the pointer a single time and go all the way to the end. We need to look out for color images: we have three channels so we need to pass through three times more items in each row.
@ -122,7 +122,7 @@ In case of the efficient way making sure that you pass through the right amount
.. literalinclude:: ../../../../samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
:language: cpp
:tab-width: 4
:lines: 154-182
:lines: 155-183
In case of color images we have three uchar items per column. This may be considered a short vector of uchar items, that has been baptized in OpenCV with the *Vec3b* name. To access the n-th sub column we use simple operator[] access. It's important to remember that OpenCV iterators go through the columns and automatically skip to the next row. Therefore in case of color images if you use a simple *uchar* iterator you'll be able to access only the blue channel values.
@ -134,7 +134,7 @@ The final method isn't recommended for scanning. It was made to acquire or modif
.. literalinclude:: ../../../../samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
:language: cpp
:tab-width: 4
:lines: 184-216
:lines: 185-217
The functions takes your input type and coordinates and calculates on the fly the address of the queried item. Then returns a reference to that. This may be a constant when you *get* the value and non-constant when you *set* the value. As a safety step in **debug mode only*** there is performed a check that your input coordinates are valid and does exist. If this isn't the case you'll get a nice output message of this on the standard error output stream. Compared to the efficient way in release mode the only difference in using this is that for every element of the image you'll get a new row pointer for what we use the C operator[] to acquire the column element.
@ -148,14 +148,14 @@ This is a bonus method of achieving lookup table modification in an image. Becau
.. literalinclude:: ../../../../samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
:language: cpp
:tab-width: 4
:lines: 107-110
:lines: 108-111
Finally call the function (I is our input image and J the output one):
.. literalinclude:: ../../../../samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
:language: cpp
:tab-width: 4
:lines: 115
:lines: 116
Performance Difference
======================

10
doc/tutorials/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.rst
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@ -77,7 +77,7 @@ Now that you have the basics done :download:`here's <../../../../samples/cpp/tut
:language: cpp
:linenos:
:tab-width: 4
:lines: 1-9, 22-25, 27-44
:lines: 1-10, 23-26, 29-46
Here you can observe that with the new structure we have no pointer problems, although it is possible to use the old functions and in the end just transform the result to a *Mat* object.
@ -85,7 +85,7 @@ Here you can observe that with the new structure we have no pointer problems, al
:language: cpp
:linenos:
:tab-width: 4
:lines: 46-51
:lines: 48-53
Because, we want to mess around with the images luma component we first convert from the default RGB to the YUV color space and then split the result up into separate planes. Here the program splits: in the first example it processes each plane using one of the three major image scanning algorithms in OpenCV (C [] operator, iterator, individual element access). In a second variant we add to the image some Gaussian noise and then mix together the channels according to some formula.
@ -95,7 +95,7 @@ The scanning version looks like:
:language: cpp
:linenos:
:tab-width: 4
:lines: 55-75
:lines: 57-77
Here you can observe that we may go through all the pixels of an image in three fashions: an iterator, a C pointer and an individual element access style. You can read a more in-depth description of these in the :ref:`howToScanImagesOpenCV` tutorial. Converting from the old function names is easy. Just remove the cv prefix and use the new *Mat* data structure. Here's an example of this by using the weighted addition function:
@ -103,7 +103,7 @@ Here you can observe that we may go through all the pixels of an image in three
:language: cpp
:linenos:
:tab-width: 4
:lines: 79-112
:lines: 81-113
As you may observe the *planes* variable is of type *Mat*. However, converting from *Mat* to *IplImage* is easy and made automatically with a simple assignment operator.
@ -111,7 +111,7 @@ As you may observe the *planes* variable is of type *Mat*. However, converting f
:language: cpp
:linenos:
:tab-width: 4
:lines: 115-127
:lines: 117-129
The new *imshow* highgui function accepts both the *Mat* and *IplImage* data structures. Compile and run the program and if the first image below is your input you may get either the first or second as output:

2
doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.rst
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@ -86,7 +86,7 @@ Each of the building components has their own valid domains. This leads to the d
Creating a *Mat* object explicitly
==================================
In the :ref:`Load_Save_Image` tutorial you have already learned how to write a matrix to an image file by using the :readwriteimagevideo:`imwrite() <imwrite>` function. However, for debugging purposes it's much more convenient to see the actual values. You can do this using the << operator of *Mat*. Be aware that this only works for two dimensional matrices.
In the :ref:`Load_Save_Image` tutorial you have already learned how to write a matrix to an image file by using the :readwriteimage:`imwrite() <imwrite>` function. However, for debugging purposes it's much more convenient to see the actual values. You can do this using the << operator of *Mat*. Be aware that this only works for two dimensional matrices.
Although *Mat* works really well as an image container, it is also a general matrix class. Therefore, it is possible to create and manipulate multidimensional matrices. You can create a Mat object in multiple ways:

3
doc/tutorials/core/table_of_content_core/table_of_content_core.rst
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@ -200,7 +200,6 @@ Here you will learn the about the basic building blocks of the library. A must r
:height: 90pt
:width: 90pt
=============== ======================================================
+
.. tabularcolumns:: m{100pt} m{300pt}
.. cssclass:: toctableopencv
@ -221,8 +220,6 @@ Here you will learn the about the basic building blocks of the library. A must r
:width: 90pt
.. |Author_ElenaG| unicode:: Elena U+0020 Gvozdeva
=============== ======================================================
.. raw:: latex
\pagebreak

161
doc/tutorials/features2d/akaze_matching/akaze_matching.rst Normal file
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@ -0,0 +1,161 @@
.. _akazeMatching:
AKAZE local features matching
******************************
Introduction
------------------
In this tutorial we will learn how to use [AKAZE]_ local features to detect and match keypoints on two images.
We will find keypoints on a pair of images with given homography matrix,
match them and count the number of inliers (i. e. matches that fit in the given homography).
You can find expanded version of this example here: https://github.com/pablofdezalc/test_kaze_akaze_opencv
.. [AKAZE] Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces. Pablo F. Alcantarilla, Jesús Nuevo and Adrien Bartoli. In British Machine Vision Conference (BMVC), Bristol, UK, September 2013.
Data
------------------
We are going to use images 1 and 3 from *Graffity* sequence of Oxford dataset.
.. image:: images/graf.png
:height: 200pt
:width: 320pt
:alt: Graffity
:align: center
Homography is given by a 3 by 3 matrix:
.. code-block:: none
7.6285898e-01 -2.9922929e-01 2.2567123e+02
3.3443473e-01 1.0143901e+00 -7.6999973e+01
3.4663091e-04 -1.4364524e-05 1.0000000e+00
You can find the images (*graf1.png*, *graf3.png*) and homography (*H1to3p.xml*) in *opencv/samples/cpp*.
Source Code
===========
.. literalinclude:: ../../../../samples/cpp/tutorial_code/features2D/AKAZE_match.cpp
:language: cpp
:linenos:
:tab-width: 4
Explanation
===========
1. **Load images and homography**
.. code-block:: cpp
Mat img1 = imread("graf1.png", IMREAD_GRAYSCALE);
Mat img2 = imread("graf3.png", IMREAD_GRAYSCALE);
Mat homography;
FileStorage fs("H1to3p.xml", FileStorage::READ);
fs.getFirstTopLevelNode() >> homography;
We are loading grayscale images here. Homography is stored in the xml created with FileStorage.
2. **Detect keypoints and compute descriptors using AKAZE**
.. code-block:: cpp
vector<KeyPoint> kpts1, kpts2;
Mat desc1, desc2;
AKAZE akaze;
akaze(img1, noArray(), kpts1, desc1);
akaze(img2, noArray(), kpts2, desc2);
We create AKAZE object and use it's *operator()* functionality. Since we don't need the *mask* parameter, *noArray()* is used.
3. **Use brute-force matcher to find 2-nn matches**
.. code-block:: cpp
BFMatcher matcher(NORM_HAMMING);
vector< vector<DMatch> > nn_matches;
matcher.knnMatch(desc1, desc2, nn_matches, 2);
We use Hamming distance, because AKAZE uses binary descriptor by default.
4. **Use 2-nn matches to find correct keypoint matches**
.. code-block:: cpp
for(size_t i = 0; i < nn_matches.size(); i++) {
DMatch first = nn_matches[i][0];
float dist1 = nn_matches[i][0].distance;
float dist2 = nn_matches[i][1].distance;
if(dist1 < nn_match_ratio * dist2) {
matched1.push_back(kpts1[first.queryIdx]);
matched2.push_back(kpts2[first.trainIdx]);
}
}
If the closest match is *ratio* closer than the second closest one, then the match is correct.
5. **Check if our matches fit in the homography model**
.. code-block:: cpp
for(int i = 0; i < matched1.size(); i++) {
Mat col = Mat::ones(3, 1, CV_64F);
col.at<double>(0) = matched1[i].pt.x;
col.at<double>(1) = matched1[i].pt.y;
col = homography * col;
col /= col.at<double>(2);
float dist = sqrt( pow(col.at<double>(0) - matched2[i].pt.x, 2) +
pow(col.at<double>(1) - matched2[i].pt.y, 2));
if(dist < inlier_threshold) {
int new_i = inliers1.size();
inliers1.push_back(matched1[i]);
inliers2.push_back(matched2[i]);
good_matches.push_back(DMatch(new_i, new_i, 0));
}
}
If the distance from first keypoint's projection to the second keypoint is less than threshold, then it it fits in the homography.
We create a new set of matches for the inliers, because it is required by the drawing function.
6. **Output results**
.. code-block:: cpp
Mat res;
drawMatches(img1, inliers1, img2, inliers2, good_matches, res);
imwrite("res.png", res);
...
Here we save the resulting image and print some statistics.
Results
=======
Found matches
--------------
.. image:: images/res.png
:height: 200pt
:width: 320pt
:alt: Matches
:align: center
A-KAZE Matching Results
--------------------------
Keypoints 1: 2943
Keypoints 2: 3511
Matches: 447
Inliers: 308
Inliers Ratio: 0.689038

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23
doc/tutorials/features2d/feature_description/feature_description.rst
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@ -23,7 +23,7 @@ Theory
Code
====
This tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/features2D/SURF_descriptor.cpp>`_
This tutorial code's is shown lines below.
.. code-block:: cpp
@ -32,9 +32,10 @@ This tutorial code's is shown lines below. You can also download it from `here <
#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/nonfree.hpp"
#include "opencv2/xfeatures2d.hpp"
using namespace cv;
using namespace cv::xfeatures2d;
void readme();
@ -50,25 +51,19 @@ This tutorial code's is shown lines below. You can also download it from `here <
if( !img_1.data || !img_2.data )
{ return -1; }
//-- Step 1: Detect the keypoints using SURF Detector
//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
Ptr<SURF> detector = SURF::create();
detector->setMinHessian(minHessian);
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector.detect( img_1, keypoints_1 );
detector.detect( img_2, keypoints_2 );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;
extractor.compute( img_1, keypoints_1, descriptors_1 );
extractor.compute( img_2, keypoints_2, descriptors_2 );
detector->detectAndCompute( img_1, keypoints_1, descriptors_1 );
detector->detectAndCompute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors with a brute force matcher
//-- Step 2: Matching descriptor vectors with a brute force matcher
BFMatcher matcher(NORM_L2);
std::vector< DMatch > matches;
matcher.match( descriptors_1, descriptors_2, matches );

12
doc/tutorials/features2d/feature_detection/feature_detection.rst
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@ -22,7 +22,7 @@ Theory
Code
====
This tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/features2D/SURF_detector.cpp>`_
This tutorial code's is shown lines below.
.. code-block:: cpp
@ -30,11 +30,11 @@ This tutorial code's is shown lines below. You can also download it from `here <
#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/xfeatures2d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/nonfree.hpp"
using namespace cv;
using namespace cv::xfeatures2d;
void readme();
@ -53,12 +53,12 @@ This tutorial code's is shown lines below. You can also download it from `here <
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
Ptr<SURF> detector = SURF::create( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector.detect( img_1, keypoints_1 );
detector.detect( img_2, keypoints_2 );
detector->detect( img_1, keypoints_1 );
detector->detect( img_2, keypoints_2 );
//-- Draw keypoints
Mat img_keypoints_1; Mat img_keypoints_2;

112
doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst
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@ -19,10 +19,116 @@ Theory
Code
====
This tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp>`_
This tutorial code's is shown lines below.
.. code-block:: cpp
/**
* @file SURF_FlannMatcher
* @brief SURF detector + descriptor + FLANN Matcher
* @author A. Huaman
*/
#include <stdio.h>
#include <iostream>
#include <stdio.h>
#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/xfeatures2d.hpp"
using namespace std;
using namespace cv;
using namespace cv::xfeatures2d;
void readme();
/**
* @function main
* @brief Main function
*/
int main( int argc, char** argv )
{
if( argc != 3 )
{ readme(); return -1; }
Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
if( !img_1.data || !img_2.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector.detect( img_1, keypoints_1 );
detector.detect( img_2, keypoints_2 );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;
extractor.compute( img_1, keypoints_1, descriptors_1 );
extractor.compute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_1, descriptors_2, matches );
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors_1.rows; i++ )
{ double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
printf("-- Max dist : %f \n", max_dist );
printf("-- Min dist : %f \n", min_dist );
//-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist,
//-- or a small arbitary value ( 0.02 ) in the event that min_dist is very
//-- small)
//-- PS.- radiusMatch can also be used here.
std::vector< DMatch > good_matches;
for( int i = 0; i < descriptors_1.rows; i++ )
{ if( matches[i].distance <= max(2*min_dist, 0.02) )
{ good_matches.push_back( matches[i]); }
}
//-- Draw only "good" matches
Mat img_matches;
drawMatches( img_1, keypoints_1, img_2, keypoints_2,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Show detected matches
imshow( "Good Matches", img_matches );
for( int i = 0; i < (int)good_matches.size(); i++ )
{ printf( "-- Good Match [%d] Keypoint 1: %d -- Keypoint 2: %d \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }
waitKey(0);
return 0;
}
/**
* @function readme
*/
void readme()
{ std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }
.. literalinclude:: ../../../../samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp
:language: cpp
Explanation
============

5
doc/tutorials/features2d/feature_homography/feature_homography.rst
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@ -20,7 +20,7 @@ Theory
Code
====
This tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/features2D/SURF_Homography.cpp>`_
This tutorial code's is shown lines below.
.. code-block:: cpp
@ -30,9 +30,10 @@ This tutorial code's is shown lines below. You can also download it from `here <
#include "opencv2/features2d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/nonfree.hpp"
#include "opencv2/xfeatures2d.hpp"
using namespace cv;
using namespace cv::xfeatures2d;
void readme();

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doc/tutorials/features2d/table_of_content_features2d/images/AKAZE_Match_Tutorial_Cover.png Executable file
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20
doc/tutorials/features2d/table_of_content_features2d/table_of_content_features2d.rst
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@ -183,6 +183,25 @@ Learn about how to use the feature points detectors, descriptors and matching f
:height: 90pt
:width: 90pt
+
.. tabularcolumns:: m{100pt} m{300pt}
.. cssclass:: toctableopencv
===================== ==============================================
|AkazeMatch| **Title:** :ref:`akazeMatching`
*Compatibility:* > OpenCV 3.0
*Author:* Fedor Morozov
Use *AKAZE* local features to find correspondence between two images.
===================== ==============================================
.. |AkazeMatch| image:: images/AKAZE_Match_Tutorial_Cover.png
:height: 90pt
:width: 90pt
.. raw:: latex
\pagebreak
@ -201,3 +220,4 @@ Learn about how to use the feature points detectors, descriptors and matching f
../feature_flann_matcher/feature_flann_matcher
../feature_homography/feature_homography
../detection_of_planar_objects/detection_of_planar_objects
../akaze_matching/akaze_matching

2
doc/tutorials/highgui/video-input-psnr-ssim/video-input-psnr-ssim.rst
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@ -22,7 +22,7 @@ As a test case where to show off these using OpenCV I've created a small program
:language: cpp
:linenos:
:tab-width: 4
:lines: 1-14, 28-29, 31-205
:lines: 1-15, 29-31, 33-208
How to read a video stream (online-camera or offline-file)?
===========================================================

2
doc/tutorials/introduction/android_binary_package/android_dev_intro.rst
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@ -5,7 +5,7 @@
Introduction into Android Development
*************************************
This guide was designed to help you in learning Android development basics and seting up your
This guide was designed to help you in learning Android development basics and setting up your
working environment quickly. It was written with Windows 7 in mind, though it would work with Linux
(Ubuntu), Mac OS X and any other OS supported by Android SDK.

2
doc/tutorials/introduction/clojure_dev_intro/clojure_dev_intro.rst
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@ -656,7 +656,7 @@ classes we're going to use:
Results: Stored in vars *1, *2, *3, an exception in *e
user=> (import '[org.opencv.core Mat Size CvType]
'[org.opencv.highgui Highgui]
'[org.opencv.imgcodecs Imgcodecs]
'[org.opencv.imgproc Imgproc])
org.opencv.imgproc.Imgproc

6
doc/tutorials/introduction/desktop_java/java_dev_intro.rst
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@ -373,7 +373,7 @@ Now modify src/main/java/HelloOpenCV.java so it contains the following Java code
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.objdetect.CascadeClassifier;
//
@ -387,7 +387,7 @@ Now modify src/main/java/HelloOpenCV.java so it contains the following Java code
// Create a face detector from the cascade file in the resources
// directory.
CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("/lbpcascade_frontalface.xml").getPath());
Mat image = Highgui.imread(getClass().getResource("/lena.png").getPath());
Mat image = Imgcodecs.imread(getClass().getResource("/lena.png").getPath());
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
@ -404,7 +404,7 @@ Now modify src/main/java/HelloOpenCV.java so it contains the following Java code
// Save the visualized detection.
String filename = "faceDetection.png";
System.out.println(String.format("Writing %s", filename));
Highgui.imwrite(filename, image);
Imgcodecs.imwrite(filename, image);
}
}

16
doc/tutorials/introduction/display_image/display_image.rst
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@ -39,28 +39,28 @@ You'll almost always end up using the:
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:tab-width: 4
:lines: 1-3
:lines: 1-4
We also include the *iostream* to facilitate console line output and input. To avoid data structure and function name conflicts with other libraries, OpenCV has its own namespace: *cv*. To avoid the need appending prior each of these the *cv::* keyword you can import the namespace in the whole file by using the lines:
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:tab-width: 4
:lines: 5-6
:lines: 6-7
This is true for the STL library too (used for console I/O). Now, let's analyze the *main* function. We start up assuring that we acquire a valid image name argument from the command line.
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:tab-width: 4
:lines: 10-14
:lines: 11-15
Then create a *Mat* object that will store the data of the loaded image.
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:tab-width: 4
:lines: 16
:lines: 17
Now we call the :imread:`imread <>` function which loads the image name specified by the first argument (*argv[1]*). The second argument specifies the format in what we want the image. This may be:
@ -73,7 +73,7 @@ Now we call the :imread:`imread <>` function which loads the image name specifie
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:tab-width: 4
:lines: 17
:lines: 18
.. note::
@ -88,21 +88,21 @@ After checking that the image data was loaded correctly, we want to display our
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:lines: 25
:lines: 26
:tab-width: 4
Finally, to update the content of the OpenCV window with a new image use the :imshow:`imshow <>` function. Specify the OpenCV window name to update and the image to use during this operation:
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:lines: 26
:lines: 27
:tab-width: 4
Because we want our window to be displayed until the user presses a key (otherwise the program would end far too quickly), we use the :wait_key:`waitKey <>` function whose only parameter is just how long should it wait for a user input (measured in milliseconds). Zero means to wait forever.
.. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
:language: cpp
:lines: 28
:lines: 29
:tab-width: 4
Result

10
doc/tutorials/introduction/how_to_write_a_tutorial/how_to_write_a_tutorial.rst
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@ -349,7 +349,7 @@ Now here's our recommendation for the structure of the tutorial (although, remem
:language: cpp
:linenos:
:tab-width: 4
:lines: 1-8, 21-22, 24-
:lines: 1-8, 21-23, 25-
After the directive you specify a relative path to the file from what to import. It has four options: the language to use, if you add the ``:linenos:`` the line numbers will be shown, you can specify the tab size with the ``:tab-width:`` and you do not need to load the whole file, you can show just the important lines. Use the *lines* option to do not show redundant information (such as the *help* function). Here basically you specify ranges, if the second range line number is missing than that means that until the end of the file. The ranges specified here do no need to be in an ascending order, you may even reorganize the structure of how you want to show your sample inside the tutorial.
@ -361,16 +361,16 @@ Now here's our recommendation for the structure of the tutorial (although, remem
# ---- External links for tutorials -----------------
extlinks = {
'hgvideo' : ('http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html#%s', None)
'rwimg' : ('http://docs.opencv.org/modules/imgcodecs/doc/reading_and_writing_images.html#%s', None)
}
In short here we defined a new **hgvideo** directive that refers to an external webpage link. Its usage is:
In short here we defined a new **rwimg** directive that refers to an external webpage link. Its usage is:
.. code-block:: rst
A sample function of the highgui modules image write and read page is the :hgvideo:`imread() function <imread>`.
A sample function of the highgui modules image write and read page is the :rwimg:`imread() function <imread>`.
Which turns to: A sample function of the highgui modules image write and read page is the :hgvideo:`imread() function <imread>`. The argument you give between the <> will be put in place of the ``%s`` in the upper definition, and as the link will anchor to the correct function. To find out the anchor of a given function just open up a web page, search for the function and click on it. In the address bar it should appear like: ``http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html#imread`` . Look here for the name of the directives for each page of the OpenCV reference manual. If none present for one of them feel free to add one for it.
Which turns to: A sample function of the highgui modules image write and read page is the :rwimg:`imread() function <imread>`. The argument you give between the <> will be put in place of the ``%s`` in the upper definition, and as the link will anchor to the correct function. To find out the anchor of a given function just open up a web page, search for the function and click on it. In the address bar it should appear like: ``http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images.html#imread`` . Look here for the name of the directives for each page of the OpenCV reference manual. If none present for one of them feel free to add one for it.
For formulas you can add LATEX code that will translate in the web pages into images. You do this by using the *math* directive. A usage tip:

12
doc/tutorials/introduction/load_save_image/load_save_image.rst
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@ -5,7 +5,7 @@ Load, Modify, and Save an Image
.. note::
We assume that by now you know how to load an image using :readwriteimagevideo:`imread <imread>` and to display it in a window (using :user_interface:`imshow <imshow>`). Read the :ref:`Display_Image` tutorial otherwise.
We assume that by now you know how to load an image using :readwriteimage:`imread <imread>` and to display it in a window (using :user_interface:`imshow <imshow>`). Read the :ref:`Display_Image` tutorial otherwise.
Goals
======
@ -14,9 +14,9 @@ In this tutorial you will learn how to:
.. container:: enumeratevisibleitemswithsquare
* Load an image using :readwriteimagevideo:`imread <imread>`
* Load an image using :readwriteimage:`imread <imread>`
* Transform an image from BGR to Grayscale format by using :miscellaneous_transformations:`cvtColor <cvtcolor>`
* Save your transformed image in a file on disk (using :readwriteimagevideo:`imwrite <imwrite>`)
* Save your transformed image in a file on disk (using :readwriteimage:`imwrite <imwrite>`)
Code
======
@ -62,7 +62,7 @@ Here it is:
Explanation
============
#. We begin by loading an image using :readwriteimagevideo:`imread <imread>`, located in the path given by *imageName*. For this example, assume you are loading a RGB image.
#. We begin by loading an image using :readwriteimage:`imread <imread>`, located in the path given by *imageName*. For this example, assume you are loading a RGB image.
#. Now we are going to convert our image from BGR to Grayscale format. OpenCV has a really nice function to do this kind of transformations:
@ -76,9 +76,9 @@ Explanation
* a source image (*image*)
* a destination image (*gray_image*), in which we will save the converted image.
* an additional parameter that indicates what kind of transformation will be performed. In this case we use **CV_BGR2GRAY** (because of :readwriteimagevideo:`imread <imread>` has BGR default channel order in case of color images).
* an additional parameter that indicates what kind of transformation will be performed. In this case we use **CV_BGR2GRAY** (because of :readwriteimage:`imread <imread>` has BGR default channel order in case of color images).
#. So now we have our new *gray_image* and want to save it on disk (otherwise it will get lost after the program ends). To save it, we will use a function analagous to :readwriteimagevideo:`imread <imread>`: :readwriteimagevideo:`imwrite <imwrite>`
#. So now we have our new *gray_image* and want to save it on disk (otherwise it will get lost after the program ends). To save it, we will use a function analagous to :readwriteimage:`imread <imread>`: :readwriteimage:`imwrite <imwrite>`
.. code-block:: cpp

2
doc/tutorials/introduction/windows_visual_studio_image_watch/windows_visual_studio_image_watch.rst
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@ -32,7 +32,7 @@ Image Watch works with any existing project that uses OpenCV image objects (for
#include <iostream> // std::cout
#include <opencv2/core/core.hpp> // cv::Mat
#include <opencv2/highgui/highgui.hpp> // cv::imread()
#include <opencv2/imgcodecs/imgcodecs.hpp> // cv::imread()
#include <opencv2/imgproc/imgproc.hpp> // cv::Canny()
using namespace std;

2
doc/tutorials/ios/video_processing/video_processing.rst
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@ -80,7 +80,7 @@ We add a camera controller to the view controller and initialize it when the vie
.. code-block:: objc
:linenos:
#import <opencv2/highgui/cap_ios.h>
#import <opencv2/videoio/cap_ios.h>
using namespace cv;

2
doc/tutorials/ml/non_linear_svms/non_linear_svms.rst
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@ -73,7 +73,7 @@ You may also find the source code and these video file in the :file:`samples/cpp
:language: cpp
:linenos:
:tab-width: 4
:lines: 1-11, 22-23, 26-
:lines: 1-12, 23-24, 27-
Explanation
===========

6
doc/user_guide/ug_traincascade.rst
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@ -200,6 +200,12 @@ Command line arguments of ``opencv_traincascade`` application grouped by purpose
This argument is actual in case of Haar-like features. If it is specified, the cascade will be saved in the old format.
* ``-numThreads <max_number_of_threads>``
Maximum number of threads to use during training. Notice that
the actual number of used threads may be lower, depending on
your machine and compilation options.
#.
Cascade parameters:

2
include/opencv2/opencv.hpp
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@ -50,6 +50,8 @@
#include "opencv2/features2d.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/ml.hpp"

2
modules/CMakeLists.txt
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@ -4,4 +4,4 @@ if(NOT OPENCV_MODULES_PATH)
set(OPENCV_MODULES_PATH "${CMAKE_CURRENT_SOURCE_DIR}")
endif()
ocv_glob_modules(${OPENCV_MODULES_PATH} ${OPENCV_EXTRA_MODULES_PATH})
ocv_glob_modules(${OPENCV_MODULES_PATH} EXTRA ${OPENCV_EXTRA_MODULES_PATH})

2
modules/androidcamera/camera_wrapper/CMakeLists.txt
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@ -46,7 +46,7 @@ ADD_LIBRARY(${the_target} SHARED camera_wrapper.h camera_wrapper.cpp)
string(REGEX REPLACE "[.]" "_" LIBRARY_DEF ${ANDROID_VERSION})
add_definitions(-DANDROID_r${LIBRARY_DEF})
target_link_libraries(${the_target} c m dl utils camera_client binder log)
ocv_target_link_libraries(${the_target} c m dl utils camera_client binder log)
if(NOT ANDROID_VERSION VERSION_LESS "3.0.0")
target_link_libraries(${the_target} gui )

383
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
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@ -760,6 +760,27 @@ They are
:math:`[R_2, -t]`.
By decomposing ``E``, you can only get the direction of the translation, so the function returns unit ``t``.
decomposeHomographyMat
--------------------------
Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).
.. ocv:function:: int decomposeHomographyMat( InputArray H, InputArray K, OutputArrayOfArrays rotations, OutputArrayOfArrays translations, OutputArrayOfArrays normals)
:param H: The input homography matrix between two images.
:param K: The input intrinsic camera calibration matrix.
:param rotations: Array of rotation matrices.
:param translations: Array of translation matrices.
:param normals: Array of plane normal matrices.
This function extracts relative camera motion between two views observing a planar object from the homography ``H`` induced by the plane.
The intrinsic camera matrix ``K`` must also be provided. The function may return up to four mathematical solution sets. At least two of the
solutions may further be invalidated if point correspondences are available by applying positive depth constraint (all points must be in front of the camera).
The decomposition method is described in detail in [Malis]_.
recoverPose
---------------
@ -885,7 +906,7 @@ if there are no outliers and the noise is rather small, use the default method (
The function is used to find initial intrinsic and extrinsic matrices.
Homography matrix is determined up to a scale. Thus, it is normalized so that
:math:`h_{33}=1` .
:math:`h_{33}=1`. Note that whenever an H matrix cannot be estimated, an empty one will be returned.
.. seealso::
@ -1500,6 +1521,364 @@ The function reconstructs 3-dimensional points (in homogeneous coordinates) by u
:ocv:func:`reprojectImageTo3D`
fisheye
----------
The methods in this namespace use a so-called fisheye camera model. ::
namespace fisheye
{
//! projects 3D points using fisheye model
void projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine,
InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
//! projects points using fisheye model
void projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec,
InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
//! distorts 2D points using fisheye model
void distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0);
//! undistorts 2D points using fisheye model
void undistortPoints(InputArray distorted, OutputArray undistorted,
InputArray K, InputArray D, InputArray R = noArray(), InputArray P = noArray());
//! computing undistortion and rectification maps for image transform by cv::remap()
//! If D is empty zero distortion is used, if R or P is empty identity matrixes are used
void initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P,
const cv::Size& size, int m1type, OutputArray map1, OutputArray map2);
//! undistorts image, optionally changes resolution and camera matrix.
void undistortImage(InputArray distorted, OutputArray undistorted,
InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size());
//! estimates new camera matrix for undistortion or rectification
void estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R,
OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0);
//! performs camera calibaration
double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size,
InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
//! stereo rectification estimation
void stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec,
OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(),
double balance = 0.0, double fov_scale = 1.0);
//! performs stereo calibration
double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize,
OutputArray R, OutputArray T, int flags = CALIB_FIX_INTRINSIC,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
};
Definitions:
Let P be a point in 3D of coordinates X in the world reference frame (stored in the matrix X)
The coordinate vector of P in the camera reference frame is:
.. class:: center
.. math::
Xc = R X + T
where R is the rotation matrix corresponding to the rotation vector om: R = rodrigues(om);
call x, y and z the 3 coordinates of Xc:
.. class:: center
.. math::
x = Xc_1 \\
y = Xc_2 \\
z = Xc_3
The pinehole projection coordinates of P is [a; b] where
.. class:: center
.. math::
a = x / z \ and \ b = y / z \\
r^2 = a^2 + b^2 \\
\theta = atan(r)
Fisheye distortion:
.. class:: center
.. math::
\theta_d = \theta (1 + k_1 \theta^2 + k_2 \theta^4 + k_3 \theta^6 + k_4 \theta^8)
The distorted point coordinates are [x'; y'] where
..class:: center
.. math::
x' = (\theta_d / r) x \\
y' = (\theta_d / r) y
Finally, convertion into pixel coordinates: The final pixel coordinates vector [u; v] where:
.. class:: center
.. math::
u = f_x (x' + \alpha y') + c_x \\
v = f_y yy + c_y
fisheye::projectPoints
---------------------------
Projects points using fisheye model
.. ocv:function:: void fisheye::projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine, InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray())
.. ocv:function:: void fisheye::projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec, InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray())
:param objectPoints: Array of object points, 1xN/Nx1 3-channel (or ``vector<Point3f>`` ), where N is the number of points in the view.
:param rvec: Rotation vector. See :ocv:func:`Rodrigues` for details.
:param tvec: Translation vector.
:param K: Camera matrix :math:`K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}`.
:param D: Input vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param alpha: The skew coefficient.
:param imagePoints: Output array of image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, or ``vector<Point2f>``.
:param jacobian: Optional output 2Nx15 jacobian matrix of derivatives of image points with respect to components of the focal lengths, coordinates of the principal point, distortion coefficients, rotation vector, translation vector, and the skew. In the old interface different components of the jacobian are returned via different output parameters.
The function computes projections of 3D points to the image plane given intrinsic and extrinsic camera parameters. Optionally, the function computes Jacobians - matrices of partial derivatives of image points coordinates (as functions of all the input parameters) with respect to the particular parameters, intrinsic and/or extrinsic.
fisheye::distortPoints
-------------------------
Distorts 2D points using fisheye model.
.. ocv:function:: void fisheye::distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0)
:param undistorted: Array of object points, 1xN/Nx1 2-channel (or ``vector<Point2f>`` ), where N is the number of points in the view.
:param K: Camera matrix :math:`K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}`.
:param D: Input vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param alpha: The skew coefficient.
:param distorted: Output array of image points, 1xN/Nx1 2-channel, or ``vector<Point2f>`` .
fisheye::undistortPoints
-----------------------------
Undistorts 2D points using fisheye model
.. ocv:function:: void fisheye::undistortPoints(InputArray distorted, OutputArray undistorted, InputArray K, InputArray D, InputArray R = noArray(), InputArray P = noArray())
:param distorted: Array of object points, 1xN/Nx1 2-channel (or ``vector<Point2f>`` ), where N is the number of points in the view.
:param K: Camera matrix :math:`K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}`.
:param D: Input vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param R: Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3 1-channel or 1x1 3-channel
:param P: New camera matrix (3x3) or new projection matrix (3x4)
:param undistorted: Output array of image points, 1xN/Nx1 2-channel, or ``vector<Point2f>`` .
fisheye::initUndistortRectifyMap
-------------------------------------
Computes undistortion and rectification maps for image transform by cv::remap(). If D is empty zero distortion is used, if R or P is empty identity matrixes are used.
.. ocv:function:: void fisheye::initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P, const cv::Size& size, int m1type, OutputArray map1, OutputArray map2)
:param K: Camera matrix :math:`K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}`.
:param D: Input vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param R: Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3 1-channel or 1x1 3-channel
:param P: New camera matrix (3x3) or new projection matrix (3x4)
:param size: Undistorted image size.
:param m1type: Type of the first output map that can be CV_32FC1 or CV_16SC2 . See convertMaps() for details.
:param map1: The first output map.
:param map2: The second output map.
fisheye::undistortImage
-----------------------
Transforms an image to compensate for fisheye lens distortion.
.. ocv:function:: void fisheye::undistortImage(InputArray distorted, OutputArray undistorted, InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size())
:param distorted: image with fisheye lens distortion.
:param K: Camera matrix :math:`K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}`.
:param D: Input vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param Knew: Camera matrix of the distorted image. By default, it is the identity matrix but you may additionally scale and shift the result by using a different matrix.
:param undistorted: Output image with compensated fisheye lens distortion.
The function transforms an image to compensate radial and tangential lens distortion.
The function is simply a combination of
:ocv:func:`fisheye::initUndistortRectifyMap` (with unity ``R`` ) and
:ocv:func:`remap` (with bilinear interpolation). See the former function for details of the transformation being performed.
See below the results of undistortImage.
* a\) result of :ocv:func:`undistort` of perspective camera model (all possible coefficients (k_1, k_2, k_3, k_4, k_5, k_6) of distortion were optimized under calibration)
* b\) result of :ocv:func:`fisheye::undistortImage` of fisheye camera model (all possible coefficients (k_1, k_2, k_3, k_4) of fisheye distortion were optimized under calibration)
* c\) original image was captured with fisheye lens
Pictures a) and b) almost the same. But if we consider points of image located far from the center of image, we can notice that on image a) these points are distorted.
.. image:: pics/fisheye_undistorted.jpg
fisheye::estimateNewCameraMatrixForUndistortRectify
----------------------------------------------------------
Estimates new camera matrix for undistortion or rectification.
.. ocv:function:: void fisheye::estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R, OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0)
:param K: Camera matrix :math:`K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}`.
:param D: Input vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param R: Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3 1-channel or 1x1 3-channel
:param P: New camera matrix (3x3) or new projection matrix (3x4)
:param balance: Sets the new focal length in range between the min focal length and the max focal length. Balance is in range of [0, 1].
:param fov_scale: Divisor for new focal length.
fisheye::stereoRectify
------------------------------
Stereo rectification for fisheye camera model
.. ocv:function:: void fisheye::stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec, OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(), double balance = 0.0, double fov_scale = 1.0)
:param K1: First camera matrix.
:param K2: Second camera matrix.
:param D1: First camera distortion parameters.
:param D2: Second camera distortion parameters.
:param imageSize: Size of the image used for stereo calibration.
:param rotation: Rotation matrix between the coordinate systems of the first and the second cameras.
:param tvec: Translation vector between coordinate systems of the cameras.
:param R1: Output 3x3 rectification transform (rotation matrix) for the first camera.
:param R2: Output 3x3 rectification transform (rotation matrix) for the second camera.
:param P1: Output 3x4 projection matrix in the new (rectified) coordinate systems for the first camera.
:param P2: Output 3x4 projection matrix in the new (rectified) coordinate systems for the second camera.
:param Q: Output :math:`4 \times 4` disparity-to-depth mapping matrix (see :ocv:func:`reprojectImageTo3D` ).
:param flags: Operation flags that may be zero or ``CV_CALIB_ZERO_DISPARITY`` . If the flag is set, the function makes the principal points of each camera have the same pixel coordinates in the rectified views. And if the flag is not set, the function may still shift the images in the horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the useful image area.
:param alpha: Free scaling parameter. If it is -1 or absent, the function performs the default scaling. Otherwise, the parameter should be between 0 and 1. ``alpha=0`` means that the rectified images are zoomed and shifted so that only valid pixels are visible (no black areas after rectification). ``alpha=1`` means that the rectified image is decimated and shifted so that all the pixels from the original images from the cameras are retained in the rectified images (no source image pixels are lost). Obviously, any intermediate value yields an intermediate result between those two extreme cases.
:param newImageSize: New image resolution after rectification. The same size should be passed to :ocv:func:`initUndistortRectifyMap` (see the ``stereo_calib.cpp`` sample in OpenCV samples directory). When (0,0) is passed (default), it is set to the original ``imageSize`` . Setting it to larger value can help you preserve details in the original image, especially when there is a big radial distortion.
:param roi1: Optional output rectangles inside the rectified images where all the pixels are valid. If ``alpha=0`` , the ROIs cover the whole images. Otherwise, they are likely to be smaller (see the picture below).
:param roi2: Optional output rectangles inside the rectified images where all the pixels are valid. If ``alpha=0`` , the ROIs cover the whole images. Otherwise, they are likely to be smaller (see the picture below).
:param balance: Sets the new focal length in range between the min focal length and the max focal length. Balance is in range of [0, 1].
:param fov_scale: Divisor for new focal length.
fisheye::calibrate
----------------------------
Performs camera calibaration
.. ocv:function:: double fisheye::calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size, InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON))
:param objectPoints: vector of vectors of calibration pattern points in the calibration pattern coordinate space.
:param imagePoints: vector of vectors of the projections of calibration pattern points. ``imagePoints.size()`` and ``objectPoints.size()`` and ``imagePoints[i].size()`` must be equal to ``objectPoints[i].size()`` for each ``i``.
:param image_size: Size of the image used only to initialize the intrinsic camera matrix.
:param K: Output 3x3 floating-point camera matrix :math:`A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}` . If ``fisheye::CALIB_USE_INTRINSIC_GUESS``/ is specified, some or all of ``fx, fy, cx, cy`` must be initialized before calling the function.
:param D: Output vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)`.
:param rvecs: Output vector of rotation vectors (see :ocv:func:`Rodrigues` ) estimated for each pattern view. That is, each k-th rotation vector together with the corresponding k-th translation vector (see the next output parameter description) brings the calibration pattern from the model coordinate space (in which object points are specified) to the world coordinate space, that is, a real position of the calibration pattern in the k-th pattern view (k=0.. *M* -1).
:param tvecs: Output vector of translation vectors estimated for each pattern view.
:param flags: Different flags that may be zero or a combination of the following values:
* **fisheye::CALIB_USE_INTRINSIC_GUESS** ``cameraMatrix`` contains valid initial values of ``fx, fy, cx, cy`` that are optimized further. Otherwise, ``(cx, cy)`` is initially set to the image center ( ``imageSize`` is used), and focal distances are computed in a least-squares fashion.
* **fisheye::CALIB_RECOMPUTE_EXTRINSIC** Extrinsic will be recomputed after each iteration of intrinsic optimization.
* **fisheye::CALIB_CHECK_COND** The functions will check validity of condition number.
* **fisheye::CALIB_FIX_SKEW** Skew coefficient (alpha) is set to zero and stay zero.
* **fisheye::CALIB_FIX_K1..4** Selected distortion coefficients are set to zeros and stay zero.
:param criteria: Termination criteria for the iterative optimization algorithm.
fisheye::stereoCalibrate
----------------------------
Performs stereo calibration
.. ocv:function:: double fisheye::stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize, OutputArray R, OutputArray T, int flags = CALIB_FIX_INTRINSIC, TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON))
:param objectPoints: Vector of vectors of the calibration pattern points.
:param imagePoints1: Vector of vectors of the projections of the calibration pattern points, observed by the first camera.
:param imagePoints2: Vector of vectors of the projections of the calibration pattern points, observed by the second camera.
:param K1: Input/output first camera matrix: :math:`\vecthreethree{f_x^{(j)}}{0}{c_x^{(j)}}{0}{f_y^{(j)}}{c_y^{(j)}}{0}{0}{1}` , :math:`j = 0,\, 1` . If any of ``fisheye::CALIB_USE_INTRINSIC_GUESS`` , ``fisheye::CV_CALIB_FIX_INTRINSIC`` are specified, some or all of the matrix components must be initialized.
:param D1: Input/output vector of distortion coefficients :math:`(k_1, k_2, k_3, k_4)` of 4 elements.
:param K2: Input/output second camera matrix. The parameter is similar to ``K1`` .
:param D2: Input/output lens distortion coefficients for the second camera. The parameter is similar to ``D1`` .
:param imageSize: Size of the image used only to initialize intrinsic camera matrix.
:param R: Output rotation matrix between the 1st and the 2nd camera coordinate systems.
:param T: Output translation vector between the coordinate systems of the cameras.
:param flags: Different flags that may be zero or a combination of the following values:
* **fisheye::CV_CALIB_FIX_INTRINSIC** Fix ``K1, K2?`` and ``D1, D2?`` so that only ``R, T`` matrices are estimated.
* **fisheye::CALIB_USE_INTRINSIC_GUESS** ``K1, K2`` contains valid initial values of ``fx, fy, cx, cy`` that are optimized further. Otherwise, ``(cx, cy)`` is initially set to the image center (``imageSize`` is used), and focal distances are computed in a least-squares fashion.
* **fisheye::CALIB_RECOMPUTE_EXTRINSIC** Extrinsic will be recomputed after each iteration of intrinsic optimization.
* **fisheye::CALIB_CHECK_COND** The functions will check validity of condition number.
* **fisheye::CALIB_FIX_SKEW** Skew coefficient (alpha) is set to zero and stay zero.
* **fisheye::CALIB_FIX_K1..4** Selected distortion coefficients are set to zeros and stay zero.
:param criteria: Termination criteria for the iterative optimization algorithm.
.. [BT98] Birchfield, S. and Tomasi, C. A pixel dissimilarity measure that is insensitive to image sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1998.
@ -1518,3 +1897,5 @@ The function reconstructs 3-dimensional points (in homogeneous coordinates) by u
.. [Slabaugh] Slabaugh, G.G. Computing Euler angles from a rotation matrix. http://www.soi.city.ac.uk/~sbbh653/publications/euler.pdf (verified: 2013-04-15)
.. [Zhang2000] Z. Zhang. A Flexible New Technique for Camera Calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000.
.. [Malis] Malis, E. and Vargas, M. Deeper understanding of the homography decomposition for vision-based control, Research Report 6303, INRIA (2007)

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modules/calib3d/include/opencv2/calib3d.hpp
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#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/core/affine.hpp"
namespace cv
{
@ -314,6 +315,11 @@ CV_EXPORTS_W int estimateAffine3D(InputArray src, InputArray dst,
double ransacThreshold = 3, double confidence = 0.99);
CV_EXPORTS_W int decomposeHomographyMat(InputArray H,
InputArray K,
OutputArrayOfArrays rotations,
OutputArrayOfArrays translations,
OutputArrayOfArrays normals);
class CV_EXPORTS_W StereoMatcher : public Algorithm
{
@ -411,6 +417,66 @@ CV_EXPORTS_W Ptr<StereoSGBM> createStereoSGBM(int minDisparity, int numDispariti
int speckleWindowSize = 0, int speckleRange = 0,
int mode = StereoSGBM::MODE_SGBM);
namespace fisheye
{
enum{
CALIB_USE_INTRINSIC_GUESS = 1,
CALIB_RECOMPUTE_EXTRINSIC = 2,
CALIB_CHECK_COND = 4,
CALIB_FIX_SKEW = 8,
CALIB_FIX_K1 = 16,
CALIB_FIX_K2 = 32,
CALIB_FIX_K3 = 64,
CALIB_FIX_K4 = 128,
CALIB_FIX_INTRINSIC = 256
};
//! projects 3D points using fisheye model
CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine,
InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
//! projects points using fisheye model
CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec,
InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
//! distorts 2D points using fisheye model
CV_EXPORTS void distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0);
//! undistorts 2D points using fisheye model
CV_EXPORTS void undistortPoints(InputArray distorted, OutputArray undistorted,
InputArray K, InputArray D, InputArray R = noArray(), InputArray P = noArray());
//! computing undistortion and rectification maps for image transform by cv::remap()
//! If D is empty zero distortion is used, if R or P is empty identity matrixes are used
CV_EXPORTS void initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P,
const cv::Size& size, int m1type, OutputArray map1, OutputArray map2);
//! undistorts image, optionally changes resolution and camera matrix. If Knew zero identity matrix is used
CV_EXPORTS void undistortImage(InputArray distorted, OutputArray undistorted,
InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size());
//! estimates new camera matrix for undistortion or rectification
CV_EXPORTS void estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R,
OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0);
//! performs camera calibaration
CV_EXPORTS double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size,
InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
//! stereo rectification estimation
CV_EXPORTS void stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec,
OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(),
double balance = 0.0, double fov_scale = 1.0);
//! performs stereo calibaration
CV_EXPORTS double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize,
OutputArray R, OutputArray T, int flags = CALIB_FIX_INTRINSIC,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
}
} // cv
#endif

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//
//M*/
#include "perf_precomp.hpp"
#include "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL

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#include "opencv2/ts.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY

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modules/calib3d/src/circlesgrid.cpp
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//
//M*/
#include "precomp.hpp"
#include "circlesgrid.hpp"
#include <limits>
//#define DEBUG_CIRCLES

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#ifndef FISHEYE_INTERNAL_H
#define FISHEYE_INTERNAL_H
#include "precomp.hpp"
namespace cv { namespace internal {
struct CV_EXPORTS IntrinsicParams
{
Vec2d f;
Vec2d c;
Vec4d k;
double alpha;
std::vector<int> isEstimate;
IntrinsicParams();
IntrinsicParams(Vec2d f, Vec2d c, Vec4d k, double alpha = 0);
IntrinsicParams operator+(const Mat& a);
IntrinsicParams& operator =(const Mat& a);
void Init(const cv::Vec2d& f, const cv::Vec2d& c, const cv::Vec4d& k = Vec4d(0,0,0,0), const double& alpha = 0);
};
void projectPoints(cv::InputArray objectPoints, cv::OutputArray imagePoints,
cv::InputArray _rvec,cv::InputArray _tvec,
const IntrinsicParams& param, cv::OutputArray jacobian);
void ComputeExtrinsicRefine(const Mat& imagePoints, const Mat& objectPoints, Mat& rvec,
Mat& tvec, Mat& J, const int MaxIter,
const IntrinsicParams& param, const double thresh_cond);
CV_EXPORTS Mat ComputeHomography(Mat m, Mat M);
CV_EXPORTS Mat NormalizePixels(const Mat& imagePoints, const IntrinsicParams& param);
void InitExtrinsics(const Mat& _imagePoints, const Mat& _objectPoints, const IntrinsicParams& param, Mat& omckk, Mat& Tckk);
void CalibrateExtrinsics(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints,
const IntrinsicParams& param, const int check_cond,
const double thresh_cond, InputOutputArray omc, InputOutputArray Tc);
void ComputeJacobians(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints,
const IntrinsicParams& param, InputArray omc, InputArray Tc,
const int& check_cond, const double& thresh_cond, Mat& JJ2_inv, Mat& ex3);
CV_EXPORTS void EstimateUncertainties(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints,
const IntrinsicParams& params, InputArray omc, InputArray Tc,
IntrinsicParams& errors, Vec2d& std_err, double thresh_cond, int check_cond, double& rms);
void dAB(cv::InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB);
void JRodriguesMatlab(const Mat& src, Mat& dst);
void compose_motion(InputArray _om1, InputArray _T1, InputArray _om2, InputArray _T2,
Mat& om3, Mat& T3, Mat& dom3dom1, Mat& dom3dT1, Mat& dom3dom2,
Mat& dom3dT2, Mat& dT3dom1, Mat& dT3dT1, Mat& dT3dom2, Mat& dT3dT2);
double median(const Mat& row);
Vec3d median3d(InputArray m);
}}
#endif

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@ -0,0 +1,482 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// This is a homography decomposition implementation contributed to OpenCV
// by Samson Yilma. It implements the homography decomposition algorithm
// descriped in the research report:
// Malis, E and Vargas, M, "Deeper understanding of the homography decomposition
// for vision-based control", Research Report 6303, INRIA (2007)
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, Samson Yilma¸ (samson_yilma@yahoo.com), all rights reserved.
//
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <memory>
namespace cv
{
namespace HomographyDecomposition
{
//struct to hold solutions of homography decomposition
typedef struct _CameraMotion {
cv::Matx33d R; //!< rotation matrix
cv::Vec3d n; //!< normal of the plane the camera is looking at
cv::Vec3d t; //!< translation vector
} CameraMotion;
inline int signd(const double x)
{
return ( x >= 0 ? 1 : -1 );
}
class HomographyDecomp {
public:
HomographyDecomp() {}
virtual ~HomographyDecomp() {}
virtual void decomposeHomography(const cv::Matx33d& H, const cv::Matx33d& K,
std::vector<CameraMotion>& camMotions);
bool isRotationValid(const cv::Matx33d& R, const double epsilon=0.01);
protected:
bool passesSameSideOfPlaneConstraint(CameraMotion& motion);
virtual void decompose(std::vector<CameraMotion>& camMotions) = 0;
const cv::Matx33d& getHnorm() const {
return _Hnorm;
}
private:
cv::Matx33d normalize(const cv::Matx33d& H, const cv::Matx33d& K);
void removeScale();
cv::Matx33d _Hnorm;
};
class HomographyDecompZhang : public HomographyDecomp {
public:
HomographyDecompZhang():HomographyDecomp() {}
virtual ~HomographyDecompZhang() {}
private:
virtual void decompose(std::vector<CameraMotion>& camMotions);
bool findMotionFrom_tstar_n(const cv::Vec3d& tstar, const cv::Vec3d& n, CameraMotion& motion);
};
class HomographyDecompInria : public HomographyDecomp {
public:
HomographyDecompInria():HomographyDecomp() {}
virtual ~HomographyDecompInria() {}
private:
virtual void decompose(std::vector<CameraMotion>& camMotions);
double oppositeOfMinor(const cv::Matx33d& M, const int row, const int col);
void findRmatFrom_tstar_n(const cv::Vec3d& tstar, const cv::Vec3d& n, const double v, cv::Matx33d& R);
};
// normalizes homography with intrinsic camera parameters
Matx33d HomographyDecomp::normalize(const Matx33d& H, const Matx33d& K)
{
return K.inv() * H * K;
}
void HomographyDecomp::removeScale()
{
Mat W;
SVD::compute(_Hnorm, W);
_Hnorm = _Hnorm * (1.0/W.at<double>(1));
}
/*! This checks that the input is a pure rotation matrix 'm'.
* The conditions for this are: R' * R = I and det(R) = 1 (proper rotation matrix)
*/
bool HomographyDecomp::isRotationValid(const Matx33d& R, const double epsilon)
{
Matx33d RtR = R.t() * R;
Matx33d I(1,0,0, 0,1,0, 0,0,1);
if (norm(RtR, I, NORM_INF) > epsilon)
return false;
return (fabs(determinant(R) - 1.0) < epsilon);
}
bool HomographyDecomp::passesSameSideOfPlaneConstraint(CameraMotion& motion)
{
typedef Matx<double, 1, 1> Matx11d;
Matx31d t = Matx31d(motion.t);
Matx31d n = Matx31d(motion.n);
Matx11d proj = n.t() * motion.R.t() * t;
if ( (1 + proj(0, 0) ) <= 0 )
return false;
return true;
}
//!main routine to decompose homography
void HomographyDecomp::decomposeHomography(const Matx33d& H, const cv::Matx33d& K,
std::vector<CameraMotion>& camMotions)
{
//normalize homography matrix with intrinsic camera matrix
_Hnorm = normalize(H, K);
//remove scale of the normalized homography
removeScale();
//apply decomposition
decompose(camMotions);
}
/* function computes R&t from tstar, and plane normal(n) using
R = H * inv(I + tstar*transpose(n) );
t = R * tstar;
returns true if computed R&t is a valid solution
*/
bool HomographyDecompZhang::findMotionFrom_tstar_n(const cv::Vec3d& tstar, const cv::Vec3d& n, CameraMotion& motion)
{
Matx31d tstar_m = Mat(tstar);
Matx31d n_m = Mat(n);
Matx33d temp = tstar_m * n_m.t();
temp(0, 0) += 1.0;
temp(1, 1) += 1.0;
temp(2, 2) += 1.0;
motion.R = getHnorm() * temp.inv();
motion.t = motion.R * tstar;
motion.n = n;
return passesSameSideOfPlaneConstraint(motion);
}
void HomographyDecompZhang::decompose(std::vector<CameraMotion>& camMotions)
{
Mat W, U, Vt;
SVD::compute(getHnorm(), W, U, Vt);
double lambda1=W.at<double>(0);
double lambda3=W.at<double>(2);
double lambda1m3 = (lambda1-lambda3);
double lambda1m3_2 = lambda1m3*lambda1m3;
double lambda1t3 = lambda1*lambda3;
double t1 = 1.0/(2.0*lambda1t3);
double t2 = sqrt(1.0+4.0*lambda1t3/lambda1m3_2);
double t12 = t1*t2;
double e1 = -t1 + t12; //t1*(-1.0f + t2 );
double e3 = -t1 - t12; //t1*(-1.0f - t2);
double e1_2 = e1*e1;
double e3_2 = e3*e3;
double nv1p = sqrt(e1_2*lambda1m3_2 + 2*e1*(lambda1t3-1) + 1.0);
double nv3p = sqrt(e3_2*lambda1m3_2 + 2*e3*(lambda1t3-1) + 1.0);
double v1p[3], v3p[3];
v1p[0]=Vt.at<double>(0)*nv1p, v1p[1]=Vt.at<double>(1)*nv1p, v1p[2]=Vt.at<double>(2)*nv1p;
v3p[0]=Vt.at<double>(6)*nv3p, v3p[1]=Vt.at<double>(7)*nv3p, v3p[2]=Vt.at<double>(8)*nv3p;
/*The eight solutions are
(A): tstar = +- (v1p - v3p)/(e1 -e3), n = +- (e1*v3p - e3*v1p)/(e1-e3)
(B): tstar = +- (v1p + v3p)/(e1 -e3), n = +- (e1*v3p + e3*v1p)/(e1-e3)
*/
double v1pmv3p[3], v1ppv3p[3];
double e1v3me3v1[3], e1v3pe3v1[3];
double inv_e1me3 = 1.0/(e1-e3);
for(int kk=0;kk<3;++kk){
v1pmv3p[kk] = v1p[kk]-v3p[kk];
v1ppv3p[kk] = v1p[kk]+v3p[kk];
}
for(int kk=0; kk<3; ++kk){
double e1v3 = e1*v3p[kk];
double e3v1=e3*v1p[kk];
e1v3me3v1[kk] = e1v3-e3v1;
e1v3pe3v1[kk] = e1v3+e3v1;
}
Vec3d tstar_p, tstar_n;
Vec3d n_p, n_n;
///Solution group A
for(int kk=0; kk<3; ++kk) {
tstar_p[kk] = v1pmv3p[kk]*inv_e1me3;
tstar_n[kk] = -tstar_p[kk];
n_p[kk] = e1v3me3v1[kk]*inv_e1me3;
n_n[kk] = -n_p[kk];
}
CameraMotion cmotion;
//(A) Four different combinations for solution A
// (i) (+, +)
if (findMotionFrom_tstar_n(tstar_p, n_p, cmotion))
camMotions.push_back(cmotion);
// (ii) (+, -)
if (findMotionFrom_tstar_n(tstar_p, n_n, cmotion))
camMotions.push_back(cmotion);
// (iii) (-, +)
if (findMotionFrom_tstar_n(tstar_n, n_p, cmotion))
camMotions.push_back(cmotion);
// (iv) (-, -)
if (findMotionFrom_tstar_n(tstar_n, n_n, cmotion))
camMotions.push_back(cmotion);
//////////////////////////////////////////////////////////////////
///Solution group B
for(int kk=0;kk<3;++kk){
tstar_p[kk] = v1ppv3p[kk]*inv_e1me3;
tstar_n[kk] = -tstar_p[kk];
n_p[kk] = e1v3pe3v1[kk]*inv_e1me3;
n_n[kk] = -n_p[kk];
}
//(B) Four different combinations for solution B
// (i) (+, +)
if (findMotionFrom_tstar_n(tstar_p, n_p, cmotion))
camMotions.push_back(cmotion);
// (ii) (+, -)
if (findMotionFrom_tstar_n(tstar_p, n_n, cmotion))
camMotions.push_back(cmotion);
// (iii) (-, +)
if (findMotionFrom_tstar_n(tstar_n, n_p, cmotion))
camMotions.push_back(cmotion);
// (iv) (-, -)
if (findMotionFrom_tstar_n(tstar_n, n_n, cmotion))
camMotions.push_back(cmotion);
}
double HomographyDecompInria::oppositeOfMinor(const Matx33d& M, const int row, const int col)
{
int x1 = col == 0 ? 1 : 0;
int x2 = col == 2 ? 1 : 2;
int y1 = row == 0 ? 1 : 0;
int y2 = row == 2 ? 1 : 2;
return (M(y1, x2) * M(y2, x1) - M(y1, x1) * M(y2, x2));
}
//computes R = H( I - (2/v)*te_star*ne_t )
void HomographyDecompInria::findRmatFrom_tstar_n(const cv::Vec3d& tstar, const cv::Vec3d& n, const double v, cv::Matx33d& R)
{
Matx31d tstar_m = Matx31d(tstar);
Matx31d n_m = Matx31d(n);
Matx33d I(1.0, 0.0, 0.0,
0.0, 1.0, 0.0,
0.0, 0.0, 1.0);
R = getHnorm() * (I - (2/v) * tstar_m * n_m.t() );
}
void HomographyDecompInria::decompose(std::vector<CameraMotion>& camMotions)
{
const double epsilon = 0.001;
Matx33d S;
//S = H'H - I
S = getHnorm().t() * getHnorm();
S(0, 0) -= 1.0;
S(1, 1) -= 1.0;
S(2, 2) -= 1.0;
//check if H is rotation matrix
if( norm(S, NORM_INF) < epsilon) {
CameraMotion motion;
motion.R = Matx33d(getHnorm());
motion.t = Vec3d(0, 0, 0);
motion.n = Vec3d(0, 0, 0);
camMotions.push_back(motion);
return;
}
//! Compute nvectors
Vec3d npa, npb;
double M00 = oppositeOfMinor(S, 0, 0);
double M11 = oppositeOfMinor(S, 1, 1);
double M22 = oppositeOfMinor(S, 2, 2);
double rtM00 = sqrt(M00);
double rtM11 = sqrt(M11);
double rtM22 = sqrt(M22);
double M01 = oppositeOfMinor(S, 0, 1);
double M12 = oppositeOfMinor(S, 1, 2);
double M02 = oppositeOfMinor(S, 0, 2);
int e12 = signd(M12);
int e02 = signd(M02);
int e01 = signd(M01);
double nS00 = abs(S(0, 0));
double nS11 = abs(S(1, 1));
double nS22 = abs(S(2, 2));
//find max( |Sii| ), i=0, 1, 2
int indx = 0;
if(nS00 < nS11){
indx = 1;
if( nS11 < nS22 )
indx = 2;
}
else {
if(nS00 < nS22 )
indx = 2;
}
switch (indx) {
case 0:
npa[0] = S(0, 0), npb[0] = S(0, 0);
npa[1] = S(0, 1) + rtM22, npb[1] = S(0, 1) - rtM22;
npa[2] = S(0, 2) + e12 * rtM11, npb[2] = S(0, 2) - e12 * rtM11;
break;
case 1:
npa[0] = S(0, 1) + rtM22, npb[0] = S(0, 1) - rtM22;
npa[1] = S(1, 1), npb[1] = S(1, 1);
npa[2] = S(1, 2) - e02 * rtM00, npb[2] = S(1, 2) + e02 * rtM00;
break;
case 2:
npa[0] = S(0, 2) + e01 * rtM11, npb[0] = S(0, 2) - e01 * rtM11;
npa[1] = S(1, 2) + rtM00, npb[1] = S(1, 2) - rtM00;
npa[2] = S(2, 2), npb[2] = S(2, 2);
break;
default:
break;
}
double traceS = S(0, 0) + S(1, 1) + S(2, 2);
double v = 2.0 * sqrt(1 + traceS - M00 - M11 - M22);
double ESii = signd(S(indx, indx)) ;
double r_2 = 2 + traceS + v;
double nt_2 = 2 + traceS - v;
double r = sqrt(r_2);
double n_t = sqrt(nt_2);
Vec3d na = npa / norm(npa);
Vec3d nb = npb / norm(npb);
double half_nt = 0.5 * n_t;
double esii_t_r = ESii * r;
Vec3d ta_star = half_nt * (esii_t_r * nb - n_t * na);
Vec3d tb_star = half_nt * (esii_t_r * na - n_t * nb);
camMotions.resize(4);
Matx33d Ra, Rb;
Vec3d ta, tb;
//Ra, ta, na
findRmatFrom_tstar_n(ta_star, na, v, Ra);
ta = Ra * ta_star;
camMotions[0].R = Ra;
camMotions[0].t = ta;
camMotions[0].n = na;
//Ra, -ta, -na
camMotions[1].R = Ra;
camMotions[1].t = -ta;
camMotions[1].n = -na;
//Rb, tb, nb
findRmatFrom_tstar_n(tb_star, nb, v, Rb);
tb = Rb * tb_star;
camMotions[2].R = Rb;
camMotions[2].t = tb;
camMotions[2].n = nb;
//Rb, -tb, -nb
camMotions[3].R = Rb;
camMotions[3].t = -tb;
camMotions[3].n = -nb;
}
} //namespace HomographyDecomposition
// function decomposes image-to-image homography to rotation and translation matrices
int decomposeHomographyMat(InputArray _H,
InputArray _K,
OutputArrayOfArrays _rotations,
OutputArrayOfArrays _translations,
OutputArrayOfArrays _normals)
{
using namespace std;
using namespace HomographyDecomposition;
Mat H = _H.getMat().reshape(1, 3);
CV_Assert(H.cols == 3 && H.rows == 3);
Mat K = _K.getMat().reshape(1, 3);
CV_Assert(K.cols == 3 && K.rows == 3);
auto_ptr<HomographyDecomp> hdecomp(new HomographyDecompInria);
vector<CameraMotion> motions;
hdecomp->decomposeHomography(H, K, motions);
int nsols = static_cast<int>(motions.size());
int depth = CV_64F; //double precision matrices used in CameraMotion struct
if (_rotations.needed()) {
_rotations.create(nsols, 1, depth);
for (int k = 0; k < nsols; ++k ) {
_rotations.getMatRef(k) = Mat(motions[k].R);
}
}
if (_translations.needed()) {
_translations.create(nsols, 1, depth);
for (int k = 0; k < nsols; ++k ) {
_translations.getMatRef(k) = Mat(motions[k].t);
}
}
if (_normals.needed()) {
_normals.create(nsols, 1, depth);
for (int k = 0; k < nsols; ++k ) {
_normals.getMatRef(k) = Mat(motions[k].n);
}
}
return nsols;
}
} //namespace cv

44
modules/calib3d/src/solvepnp.cpp
View File

@ -139,11 +139,13 @@ namespace cv
CameraParameters camera;
};
template <typename OpointType, typename IpointType>
static void pnpTask(const std::vector<char>& pointsMask, const Mat& objectPoints, const Mat& imagePoints,
const Parameters& params, std::vector<int>& inliers, Mat& rvec, Mat& tvec,
const Mat& rvecInit, const Mat& tvecInit, Mutex& resultsMutex)
{
Mat modelObjectPoints(1, MIN_POINTS_COUNT, CV_32FC3), modelImagePoints(1, MIN_POINTS_COUNT, CV_32FC2);
Mat modelObjectPoints(1, MIN_POINTS_COUNT, CV_MAKETYPE(DataDepth<OpointType>::value, 3));
Mat modelImagePoints(1, MIN_POINTS_COUNT, CV_MAKETYPE(DataDepth<IpointType>::value, 2));
for (int i = 0, colIndex = 0; i < (int)pointsMask.size(); i++)
{
if (pointsMask[i])
@ -162,7 +164,7 @@ namespace cv
for (int i = 0; i < MIN_POINTS_COUNT; i++)
for (int j = i + 1; j < MIN_POINTS_COUNT; j++)
{
if (norm(modelObjectPoints.at<Vec3f>(0, i) - modelObjectPoints.at<Vec3f>(0, j)) < eps)
if (norm(modelObjectPoints.at<Vec<OpointType,3> >(0, i) - modelObjectPoints.at<Vec<OpointType,3> >(0, j)) < eps)
num_same_points++;
}
if (num_same_points > 0)
@ -176,7 +178,7 @@ namespace cv
params.useExtrinsicGuess, params.flags);
std::vector<Point2f> projected_points;
std::vector<Point_<OpointType> > projected_points;
projected_points.resize(objectPoints.cols);
projectPoints(objectPoints, localRvec, localTvec, params.camera.intrinsics, params.camera.distortion, projected_points);
@ -186,9 +188,11 @@ namespace cv
std::vector<int> localInliers;
for (int i = 0; i < objectPoints.cols; i++)
{
Point2f p(imagePoints.at<Vec2f>(0, i)[0], imagePoints.at<Vec2f>(0, i)[1]);
//Although p is a 2D point it needs the same type as the object points to enable the norm calculation
Point_<OpointType> p((OpointType)imagePoints.at<Vec<IpointType,2> >(0, i)[0],
(OpointType)imagePoints.at<Vec<IpointType,2> >(0, i)[1]);
if ((norm(p - projected_points[i]) < params.reprojectionError)
&& (rotatedPoints.at<Vec3f>(0, i)[2] > 0)) //hack
&& (rotatedPoints.at<Vec<OpointType,3> >(0, i)[2] > 0)) //hack
{
localInliers.push_back(i);
}
@ -208,6 +212,30 @@ namespace cv
}
}
static void pnpTask(const std::vector<char>& pointsMask, const Mat& objectPoints, const Mat& imagePoints,
const Parameters& params, std::vector<int>& inliers, Mat& rvec, Mat& tvec,
const Mat& rvecInit, const Mat& tvecInit, Mutex& resultsMutex)
{
CV_Assert(objectPoints.depth() == CV_64F || objectPoints.depth() == CV_32F);
CV_Assert(imagePoints.depth() == CV_64F || imagePoints.depth() == CV_32F);
const bool objectDoublePrecision = objectPoints.depth() == CV_64F;
const bool imageDoublePrecision = imagePoints.depth() == CV_64F;
if(objectDoublePrecision)
{
if(imageDoublePrecision)
pnpTask<double, double>(pointsMask, objectPoints, imagePoints, params, inliers, rvec, tvec, rvecInit, tvecInit, resultsMutex);
else
pnpTask<double, float>(pointsMask, objectPoints, imagePoints, params, inliers, rvec, tvec, rvecInit, tvecInit, resultsMutex);
}
else
{
if(imageDoublePrecision)
pnpTask<float, double>(pointsMask, objectPoints, imagePoints, params, inliers, rvec, tvec, rvecInit, tvecInit, resultsMutex);
else
pnpTask<float, float>(pointsMask, objectPoints, imagePoints, params, inliers, rvec, tvec, rvecInit, tvecInit, resultsMutex);
}
}
class PnPSolver
{
public:
@ -283,10 +311,10 @@ void cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
CV_Assert(opoints.isContinuous());
CV_Assert(opoints.depth() == CV_32F);
CV_Assert(opoints.depth() == CV_32F || opoints.depth() == CV_64F);
CV_Assert((opoints.rows == 1 && opoints.channels() == 3) || opoints.cols*opoints.channels() == 3);
CV_Assert(ipoints.isContinuous());
CV_Assert(ipoints.depth() == CV_32F);
CV_Assert(ipoints.depth() == CV_32F || ipoints.depth() == CV_64F);
CV_Assert((ipoints.rows == 1 && ipoints.channels() == 2) || ipoints.cols*ipoints.channels() == 2);
_rvec.create(3, 1, CV_64FC1);
@ -322,7 +350,7 @@ void cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
if (flags != P3P)
{
int i, pointsCount = (int)localInliers.size();
Mat inlierObjectPoints(1, pointsCount, CV_32FC3), inlierImagePoints(1, pointsCount, CV_32FC2);
Mat inlierObjectPoints(1, pointsCount, CV_MAKE_TYPE(opoints.depth(), 3)), inlierImagePoints(1, pointsCount, CV_MAKE_TYPE(ipoints.depth(), 2));
for (i = 0; i < pointsCount; i++)
{
int index = localInliers[i];

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

@ -48,7 +48,7 @@
#include "precomp.hpp"
#include <stdio.h>
#include <limits>
#include "opencl_kernels.hpp"
#include "opencl_kernels_calib3d.hpp"
namespace cv
{

2
modules/calib3d/test/opencl/test_stereobm.cpp
View File

@ -40,7 +40,7 @@
//
//M*/
#include "test_precomp.hpp"
#include "../test_precomp.hpp"
#include "cvconfig.h"
#include "opencv2/ts/ocl_test.hpp"

613
modules/calib3d/test/test_fisheye.cpp Normal file
View File

@ -0,0 +1,613 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
#include <opencv2/ts/cuda_test.hpp>
#include "../src/fisheye.hpp"
class fisheyeTest : public ::testing::Test {
protected:
const static cv::Size imageSize;
const static cv::Matx33d K;
const static cv::Vec4d D;
const static cv::Matx33d R;
const static cv::Vec3d T;
std::string datasets_repository_path;
virtual void SetUp() {
datasets_repository_path = combine(cvtest::TS::ptr()->get_data_path(), "cv/cameracalibration/fisheye");
}
protected:
std::string combine(const std::string& _item1, const std::string& _item2);
cv::Mat mergeRectification(const cv::Mat& l, const cv::Mat& r);
};
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// TESTS::
TEST_F(fisheyeTest, projectPoints)
{
double cols = this->imageSize.width,
rows = this->imageSize.height;
const int N = 20;
cv::Mat distorted0(1, N*N, CV_64FC2), undist1, undist2, distorted1, distorted2;
undist2.create(distorted0.size(), CV_MAKETYPE(distorted0.depth(), 3));
cv::Vec2d* pts = distorted0.ptr<cv::Vec2d>();
cv::Vec2d c(this->K(0, 2), this->K(1, 2));
for(int y = 0, k = 0; y < N; ++y)
for(int x = 0; x < N; ++x)
{
cv::Vec2d point(x*cols/(N-1.f), y*rows/(N-1.f));
pts[k++] = (point - c) * 0.85 + c;
}
cv::fisheye::undistortPoints(distorted0, undist1, this->K, this->D);
cv::Vec2d* u1 = undist1.ptr<cv::Vec2d>();
cv::Vec3d* u2 = undist2.ptr<cv::Vec3d>();
for(int i = 0; i < (int)distorted0.total(); ++i)
u2[i] = cv::Vec3d(u1[i][0], u1[i][1], 1.0);
cv::fisheye::distortPoints(undist1, distorted1, this->K, this->D);
cv::fisheye::projectPoints(undist2, distorted2, cv::Vec3d::all(0), cv::Vec3d::all(0), this->K, this->D);
EXPECT_MAT_NEAR(distorted0, distorted1, 1e-10);
EXPECT_MAT_NEAR(distorted0, distorted2, 1e-10);
}
TEST_F(fisheyeTest, DISABLED_undistortImage)
{
cv::Matx33d K = this->K;
cv::Mat D = cv::Mat(this->D);
std::string file = combine(datasets_repository_path, "/calib-3_stereo_from_JY/left/stereo_pair_014.jpg");
cv::Matx33d newK = K;
cv::Mat distorted = cv::imread(file), undistorted;
{
newK(0, 0) = 100;
newK(1, 1) = 100;
cv::fisheye::undistortImage(distorted, undistorted, K, D, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "new_f_100.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "new_f_100.png"), undistorted));
else
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
}
{
double balance = 1.0;
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(K, D, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, K, D, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "balance_1.0.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "balance_1.0.png"), undistorted));
else
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
}
{
double balance = 0.0;
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(K, D, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, K, D, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "balance_0.0.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "balance_0.0.png"), undistorted));
else
EXPECT_MAT_NEAR(correct, undistorted, 1e-10);
}
}
TEST_F(fisheyeTest, jacobians)
{
int n = 10;
cv::Mat X(1, n, CV_64FC3);
cv::Mat om(3, 1, CV_64F), T(3, 1, CV_64F);
cv::Mat f(2, 1, CV_64F), c(2, 1, CV_64F);
cv::Mat k(4, 1, CV_64F);
double alpha;
cv::RNG r;
r.fill(X, cv::RNG::NORMAL, 2, 1);
X = cv::abs(X) * 10;
r.fill(om, cv::RNG::NORMAL, 0, 1);
om = cv::abs(om);
r.fill(T, cv::RNG::NORMAL, 0, 1);
T = cv::abs(T); T.at<double>(2) = 4; T *= 10;
r.fill(f, cv::RNG::NORMAL, 0, 1);
f = cv::abs(f) * 1000;
r.fill(c, cv::RNG::NORMAL, 0, 1);
c = cv::abs(c) * 1000;
r.fill(k, cv::RNG::NORMAL, 0, 1);
k*= 0.5;
alpha = 0.01*r.gaussian(1);
cv::Mat x1, x2, xpred;
cv::Matx33d K(f.at<double>(0), alpha * f.at<double>(0), c.at<double>(0),
0, f.at<double>(1), c.at<double>(1),
0, 0, 1);
cv::Mat jacobians;
cv::fisheye::projectPoints(X, x1, om, T, K, k, alpha, jacobians);
//test on T:
cv::Mat dT(3, 1, CV_64FC1);
r.fill(dT, cv::RNG::NORMAL, 0, 1);
dT *= 1e-9*cv::norm(T);
cv::Mat T2 = T + dT;
cv::fisheye::projectPoints(X, x2, om, T2, K, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(11,14) * dT).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
//test on om:
cv::Mat dom(3, 1, CV_64FC1);
r.fill(dom, cv::RNG::NORMAL, 0, 1);
dom *= 1e-9*cv::norm(om);
cv::Mat om2 = om + dom;
cv::fisheye::projectPoints(X, x2, om2, T, K, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(8,11) * dom).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
//test on f:
cv::Mat df(2, 1, CV_64FC1);
r.fill(df, cv::RNG::NORMAL, 0, 1);
df *= 1e-9*cv::norm(f);
cv::Matx33d K2 = K + cv::Matx33d(df.at<double>(0), df.at<double>(0) * alpha, 0, 0, df.at<double>(1), 0, 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, T, K2, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(0,2) * df).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
//test on c:
cv::Mat dc(2, 1, CV_64FC1);
r.fill(dc, cv::RNG::NORMAL, 0, 1);
dc *= 1e-9*cv::norm(c);
K2 = K + cv::Matx33d(0, 0, dc.at<double>(0), 0, 0, dc.at<double>(1), 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, T, K2, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(2,4) * dc).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
//test on k:
cv::Mat dk(4, 1, CV_64FC1);
r.fill(dk, cv::RNG::NORMAL, 0, 1);
dk *= 1e-9*cv::norm(k);
cv::Mat k2 = k + dk;
cv::fisheye::projectPoints(X, x2, om, T, K, k2, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(4,8) * dk).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
//test on alpha:
cv::Mat dalpha(1, 1, CV_64FC1);
r.fill(dalpha, cv::RNG::NORMAL, 0, 1);
dalpha *= 1e-9*cv::norm(f);
double alpha2 = alpha + dalpha.at<double>(0);
K2 = K + cv::Matx33d(0, f.at<double>(0) * dalpha.at<double>(0), 0, 0, 0, 0, 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, T, K, k, alpha2, cv::noArray());
xpred = x1 + cv::Mat(jacobians.col(14) * dalpha).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
}
TEST_F(fisheyeTest, Calibration)
{
const int n_images = 34;
std::vector<std::vector<cv::Point2d> > imagePoints(n_images);
std::vector<std::vector<cv::Point3d> > objectPoints(n_images);
const std::string folder =combine(datasets_repository_path, "calib-3_stereo_from_JY");
cv::FileStorage fs_left(combine(folder, "left.xml"), cv::FileStorage::READ);
CV_Assert(fs_left.isOpened());
for(int i = 0; i < n_images; ++i)
fs_left[cv::format("image_%d", i )] >> imagePoints[i];
fs_left.release();
cv::FileStorage fs_object(combine(folder, "object.xml"), cv::FileStorage::READ);
CV_Assert(fs_object.isOpened());
for(int i = 0; i < n_images; ++i)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
int flag = 0;
flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
flag |= cv::fisheye::CALIB_CHECK_COND;
flag |= cv::fisheye::CALIB_FIX_SKEW;
cv::Matx33d K;
cv::Vec4d D;
cv::fisheye::calibrate(objectPoints, imagePoints, imageSize, K, D,
cv::noArray(), cv::noArray(), flag, cv::TermCriteria(3, 20, 1e-6));
EXPECT_MAT_NEAR(K, this->K, 1e-10);
EXPECT_MAT_NEAR(D, this->D, 1e-10);
}
TEST_F(fisheyeTest, Homography)
{
const int n_images = 1;
std::vector<std::vector<cv::Point2d> > imagePoints(n_images);
std::vector<std::vector<cv::Point3d> > objectPoints(n_images);
const std::string folder =combine(datasets_repository_path, "calib-3_stereo_from_JY");
cv::FileStorage fs_left(combine(folder, "left.xml"), cv::FileStorage::READ);
CV_Assert(fs_left.isOpened());
for(int i = 0; i < n_images; ++i)
fs_left[cv::format("image_%d", i )] >> imagePoints[i];
fs_left.release();
cv::FileStorage fs_object(combine(folder, "object.xml"), cv::FileStorage::READ);
CV_Assert(fs_object.isOpened());
for(int i = 0; i < n_images; ++i)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
cv::internal::IntrinsicParams param;
param.Init(cv::Vec2d(cv::max(imageSize.width, imageSize.height) / CV_PI, cv::max(imageSize.width, imageSize.height) / CV_PI),
cv::Vec2d(imageSize.width / 2.0 - 0.5, imageSize.height / 2.0 - 0.5));
cv::Mat _imagePoints (imagePoints[0]);
cv::Mat _objectPoints(objectPoints[0]);
cv::Mat imagePointsNormalized = NormalizePixels(_imagePoints, param).reshape(1).t();
_objectPoints = _objectPoints.reshape(1).t();
cv::Mat objectPointsMean, covObjectPoints;
int Np = imagePointsNormalized.cols;
cv::calcCovarMatrix(_objectPoints, covObjectPoints, objectPointsMean, cv::COVAR_NORMAL | cv::COVAR_COLS);
cv::SVD svd(covObjectPoints);
cv::Mat R(svd.vt);
if (cv::norm(R(cv::Rect(2, 0, 1, 2))) < 1e-6)
R = cv::Mat::eye(3,3, CV_64FC1);
if (cv::determinant(R) < 0)
R = -R;
cv::Mat T = -R * objectPointsMean;
cv::Mat X_new = R * _objectPoints + T * cv::Mat::ones(1, Np, CV_64FC1);
cv::Mat H = cv::internal::ComputeHomography(imagePointsNormalized, X_new.rowRange(0, 2));
cv::Mat M = cv::Mat::ones(3, X_new.cols, CV_64FC1);
X_new.rowRange(0, 2).copyTo(M.rowRange(0, 2));
cv::Mat mrep = H * M;
cv::divide(mrep, cv::Mat::ones(3,1, CV_64FC1) * mrep.row(2).clone(), mrep);
cv::Mat merr = (mrep.rowRange(0, 2) - imagePointsNormalized).t();
cv::Vec2d std_err;
cv::meanStdDev(merr.reshape(2), cv::noArray(), std_err);
std_err *= sqrt((double)merr.reshape(2).total() / (merr.reshape(2).total() - 1));
cv::Vec2d correct_std_err(0.00516740156010384, 0.00644205331553901);
EXPECT_MAT_NEAR(std_err, correct_std_err, 1e-12);
}
TEST_F(fisheyeTest, EtimateUncertainties)
{
const int n_images = 34;
std::vector<std::vector<cv::Point2d> > imagePoints(n_images);
std::vector<std::vector<cv::Point3d> > objectPoints(n_images);
const std::string folder =combine(datasets_repository_path, "calib-3_stereo_from_JY");
cv::FileStorage fs_left(combine(folder, "left.xml"), cv::FileStorage::READ);
CV_Assert(fs_left.isOpened());
for(int i = 0; i < n_images; ++i)
fs_left[cv::format("image_%d", i )] >> imagePoints[i];
fs_left.release();
cv::FileStorage fs_object(combine(folder, "object.xml"), cv::FileStorage::READ);
CV_Assert(fs_object.isOpened());
for(int i = 0; i < n_images; ++i)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
int flag = 0;
flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
flag |= cv::fisheye::CALIB_CHECK_COND;
flag |= cv::fisheye::CALIB_FIX_SKEW;
cv::Matx33d K;
cv::Vec4d D;
std::vector<cv::Vec3d> rvec;
std::vector<cv::Vec3d> tvec;
cv::fisheye::calibrate(objectPoints, imagePoints, imageSize, K, D,
rvec, tvec, flag, cv::TermCriteria(3, 20, 1e-6));
cv::internal::IntrinsicParams param, errors;
cv::Vec2d err_std;
double thresh_cond = 1e6;
int check_cond = 1;
param.Init(cv::Vec2d(K(0,0), K(1,1)), cv::Vec2d(K(0,2), K(1, 2)), D);
param.isEstimate = std::vector<int>(9, 1);
param.isEstimate[4] = 0;
errors.isEstimate = param.isEstimate;
double rms;
cv::internal::EstimateUncertainties(objectPoints, imagePoints, param, rvec, tvec,
errors, err_std, thresh_cond, check_cond, rms);
EXPECT_MAT_NEAR(errors.f, cv::Vec2d(1.29837104202046, 1.31565641071524), 1e-10);
EXPECT_MAT_NEAR(errors.c, cv::Vec2d(0.890439368129246, 0.816096854937896), 1e-10);
EXPECT_MAT_NEAR(errors.k, cv::Vec4d(0.00516248605191506, 0.0168181467500934, 0.0213118690274604, 0.00916010877545648), 1e-10);
EXPECT_MAT_NEAR(err_std, cv::Vec2d(0.187475975266883, 0.185678953263995), 1e-10);
CV_Assert(abs(rms - 0.263782587133546) < 1e-10);
CV_Assert(errors.alpha == 0);
}
TEST_F(fisheyeTest, rectify)
{
const std::string folder =combine(datasets_repository_path, "calib-3_stereo_from_JY");
cv::Size calibration_size = this->imageSize, requested_size = calibration_size;
cv::Matx33d K1 = this->K, K2 = K1;
cv::Mat D1 = cv::Mat(this->D), D2 = D1;
cv::Vec3d T = this->T;
cv::Matx33d R = this->R;
double balance = 0.0, fov_scale = 1.1;
cv::Mat R1, R2, P1, P2, Q;
cv::fisheye::stereoRectify(K1, D1, K2, D2, calibration_size, R, T, R1, R2, P1, P2, Q,
cv::CALIB_ZERO_DISPARITY, requested_size, balance, fov_scale);
cv::Mat lmapx, lmapy, rmapx, rmapy;
//rewrite for fisheye
cv::fisheye::initUndistortRectifyMap(K1, D1, R1, P1, requested_size, CV_32F, lmapx, lmapy);
cv::fisheye::initUndistortRectifyMap(K2, D2, R2, P2, requested_size, CV_32F, rmapx, rmapy);
cv::Mat l, r, lundist, rundist;
cv::VideoCapture lcap(combine(folder, "left/stereo_pair_%03d.jpg")),
rcap(combine(folder, "right/stereo_pair_%03d.jpg"));
for(int i = 0;; ++i)
{
lcap >> l; rcap >> r;
if (l.empty() || r.empty())
break;
int ndisp = 128;
cv::rectangle(l, cv::Rect(255, 0, 829, l.rows-1), cv::Scalar(0, 0, 255));
cv::rectangle(r, cv::Rect(255, 0, 829, l.rows-1), cv::Scalar(0, 0, 255));
cv::rectangle(r, cv::Rect(255-ndisp, 0, 829+ndisp ,l.rows-1), cv::Scalar(0, 0, 255));
cv::remap(l, lundist, lmapx, lmapy, cv::INTER_LINEAR);
cv::remap(r, rundist, rmapx, rmapy, cv::INTER_LINEAR);
cv::Mat rectification = mergeRectification(lundist, rundist);
cv::Mat correct = cv::imread(combine(datasets_repository_path, cv::format("rectification_AB_%03d.png", i)));
if (correct.empty())
cv::imwrite(combine(datasets_repository_path, cv::format("rectification_AB_%03d.png", i)), rectification);
else
EXPECT_MAT_NEAR(correct, rectification, 1e-10);
}
}
TEST_F(fisheyeTest, stereoCalibrate)
{
const int n_images = 34;
const std::string folder =combine(datasets_repository_path, "calib-3_stereo_from_JY");
std::vector<std::vector<cv::Point2d> > leftPoints(n_images);
std::vector<std::vector<cv::Point2d> > rightPoints(n_images);
std::vector<std::vector<cv::Point3d> > objectPoints(n_images);
cv::FileStorage fs_left(combine(folder, "left.xml"), cv::FileStorage::READ);
CV_Assert(fs_left.isOpened());
for(int i = 0; i < n_images; ++i)
fs_left[cv::format("image_%d", i )] >> leftPoints[i];
fs_left.release();
cv::FileStorage fs_right(combine(folder, "right.xml"), cv::FileStorage::READ);
CV_Assert(fs_right.isOpened());
for(int i = 0; i < n_images; ++i)
fs_right[cv::format("image_%d", i )] >> rightPoints[i];
fs_right.release();
cv::FileStorage fs_object(combine(folder, "object.xml"), cv::FileStorage::READ);
CV_Assert(fs_object.isOpened());
for(int i = 0; i < n_images; ++i)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
cv::Matx33d K1, K2, R;
cv::Vec3d T;
cv::Vec4d D1, D2;
int flag = 0;
flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
flag |= cv::fisheye::CALIB_CHECK_COND;
flag |= cv::fisheye::CALIB_FIX_SKEW;
// flag |= cv::fisheye::CALIB_FIX_INTRINSIC;
cv::fisheye::stereoCalibrate(objectPoints, leftPoints, rightPoints,
K1, D1, K2, D2, imageSize, R, T, flag,
cv::TermCriteria(3, 12, 0));
cv::Matx33d R_correct( 0.9975587205950972, 0.06953016383322372, 0.006492709911733523,
-0.06956823121068059, 0.9975601387249519, 0.005833595226966235,
-0.006071257768382089, -0.006271040135405457, 0.9999619062167968);
cv::Vec3d T_correct(-0.099402724724121, 0.00270812139265413, 0.00129330292472699);
cv::Matx33d K1_correct (561.195925927249, 0, 621.282400272412,
0, 562.849402029712, 380.555455380889,
0, 0, 1);
cv::Matx33d K2_correct (560.395452535348, 0, 678.971652040359,
0, 561.90171021422, 380.401340535339,
0, 0, 1);
cv::Vec4d D1_correct (-7.44253716539556e-05, -0.00702662033932424, 0.00737569823650885, -0.00342230256441771);
cv::Vec4d D2_correct (-0.0130785435677431, 0.0284434505383497, -0.0360333869900506, 0.0144724062347222);
EXPECT_MAT_NEAR(R, R_correct, 1e-10);
EXPECT_MAT_NEAR(T, T_correct, 1e-10);
EXPECT_MAT_NEAR(K1, K1_correct, 1e-10);
EXPECT_MAT_NEAR(K2, K2_correct, 1e-10);
EXPECT_MAT_NEAR(D1, D1_correct, 1e-10);
EXPECT_MAT_NEAR(D2, D2_correct, 1e-10);
}
TEST_F(fisheyeTest, stereoCalibrateFixIntrinsic)
{
const int n_images = 34;
const std::string folder =combine(datasets_repository_path, "calib-3_stereo_from_JY");
std::vector<std::vector<cv::Point2d> > leftPoints(n_images);
std::vector<std::vector<cv::Point2d> > rightPoints(n_images);
std::vector<std::vector<cv::Point3d> > objectPoints(n_images);
cv::FileStorage fs_left(combine(folder, "left.xml"), cv::FileStorage::READ);
CV_Assert(fs_left.isOpened());
for(int i = 0; i < n_images; ++i)
fs_left[cv::format("image_%d", i )] >> leftPoints[i];
fs_left.release();
cv::FileStorage fs_right(combine(folder, "right.xml"), cv::FileStorage::READ);
CV_Assert(fs_right.isOpened());
for(int i = 0; i < n_images; ++i)
fs_right[cv::format("image_%d", i )] >> rightPoints[i];
fs_right.release();
cv::FileStorage fs_object(combine(folder, "object.xml"), cv::FileStorage::READ);
CV_Assert(fs_object.isOpened());
for(int i = 0; i < n_images; ++i)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
cv::Matx33d R;
cv::Vec3d T;
int flag = 0;
flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
flag |= cv::fisheye::CALIB_CHECK_COND;
flag |= cv::fisheye::CALIB_FIX_SKEW;
flag |= cv::fisheye::CALIB_FIX_INTRINSIC;
cv::Matx33d K1 (561.195925927249, 0, 621.282400272412,
0, 562.849402029712, 380.555455380889,
0, 0, 1);
cv::Matx33d K2 (560.395452535348, 0, 678.971652040359,
0, 561.90171021422, 380.401340535339,
0, 0, 1);
cv::Vec4d D1 (-7.44253716539556e-05, -0.00702662033932424, 0.00737569823650885, -0.00342230256441771);
cv::Vec4d D2 (-0.0130785435677431, 0.0284434505383497, -0.0360333869900506, 0.0144724062347222);
cv::fisheye::stereoCalibrate(objectPoints, leftPoints, rightPoints,
K1, D1, K2, D2, imageSize, R, T, flag,
cv::TermCriteria(3, 12, 0));
cv::Matx33d R_correct( 0.9975587205950972, 0.06953016383322372, 0.006492709911733523,
-0.06956823121068059, 0.9975601387249519, 0.005833595226966235,
-0.006071257768382089, -0.006271040135405457, 0.9999619062167968);
cv::Vec3d T_correct(-0.099402724724121, 0.00270812139265413, 0.00129330292472699);
EXPECT_MAT_NEAR(R, R_correct, 1e-10);
EXPECT_MAT_NEAR(T, T_correct, 1e-10);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/// fisheyeTest::
const cv::Size fisheyeTest::imageSize(1280, 800);
const cv::Matx33d fisheyeTest::K(558.478087865323, 0, 620.458515360843,
0, 560.506767351568, 381.939424848348,
0, 0, 1);
const cv::Vec4d fisheyeTest::D(-0.0014613319981768, -0.00329861110580401, 0.00605760088590183, -0.00374209380722371);
const cv::Matx33d fisheyeTest::R ( 9.9756700084424932e-01, 6.9698277640183867e-02, 1.4929569991321144e-03,
-6.9711825162322980e-02, 9.9748249845531767e-01, 1.2997180766418455e-02,
-5.8331736398316541e-04,-1.3069635393884985e-02, 9.9991441852366736e-01);
const cv::Vec3d fisheyeTest::T(-9.9217369356044638e-02, 3.1741831972356663e-03, 1.8551007952921010e-04);
std::string fisheyeTest::combine(const std::string& _item1, const std::string& _item2)
{
std::string item1 = _item1, item2 = _item2;
std::replace(item1.begin(), item1.end(), '\\', '/');
std::replace(item2.begin(), item2.end(), '\\', '/');
if (item1.empty())
return item2;
if (item2.empty())
return item1;
char last = item1[item1.size()-1];
return item1 + (last != '/' ? "/" : "") + item2;
}
cv::Mat fisheyeTest::mergeRectification(const cv::Mat& l, const cv::Mat& r)
{
CV_Assert(l.type() == r.type() && l.size() == r.size());
cv::Mat merged(l.rows, l.cols * 2, l.type());
cv::Mat lpart = merged.colRange(0, l.cols);
cv::Mat rpart = merged.colRange(l.cols, merged.cols);
l.copyTo(lpart);
r.copyTo(rpart);
for(int i = 0; i < l.rows; i+=20)
cv::line(merged, cv::Point(0, i), cv::Point(merged.cols, i), cv::Scalar(0, 255, 0));
return merged;
}

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modules/calib3d/test/test_homography_decomp.cpp Normal file
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// This is a test file for the function decomposeHomography contributed to OpenCV
// by Samson Yilma.
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, Samson Yilma¸ (samson_yilma@yahoo.com), all rights reserved.
//
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
#include "opencv2/calib3d.hpp"
#include <vector>
using namespace cv;
using namespace std;
class CV_HomographyDecompTest: public cvtest::BaseTest {
public:
CV_HomographyDecompTest()
{
buildTestDataSet();
}
protected:
void run(int)
{
vector<Mat> rotations;
vector<Mat> translations;
vector<Mat> normals;
decomposeHomographyMat(_H, _K, rotations, translations, normals);
//there should be at least 1 solution
ASSERT_GT(static_cast<int>(rotations.size()), 0);
ASSERT_GT(static_cast<int>(translations.size()), 0);
ASSERT_GT(static_cast<int>(normals.size()), 0);
ASSERT_EQ(rotations.size(), normals.size());
ASSERT_EQ(translations.size(), normals.size());
ASSERT_TRUE(containsValidMotion(rotations, translations, normals));
decomposeHomographyMat(_H, _K, rotations, noArray(), noArray());
ASSERT_GT(static_cast<int>(rotations.size()), 0);
}
private:
void buildTestDataSet()
{
_K = Matx33d(640, 0.0, 320,
0, 640, 240,
0, 0, 1);
_H = Matx33d(2.649157564634028, 4.583875997496426, 70.694447785121326,
-1.072756858861583, 3.533262150437228, 1513.656999614321649,
0.001303887589576, 0.003042206876298, 1.000000000000000
);
//expected solution for the given homography and intrinsic matrices
_R = Matx33d(0.43307983549125, 0.545749113549648, -0.717356090899523,
-0.85630229674426, 0.497582023798831, -0.138414255706431,
0.281404038139784, 0.67421809131173, 0.682818960388909);
_t = Vec3d(1.826751712278038, 1.264718492450820, 0.195080809998819);
_n = Vec3d(0.244875830334816, 0.480857890778889, 0.841909446789566);
}
bool containsValidMotion(std::vector<Mat>& rotations,
std::vector<Mat>& translations,
std::vector<Mat>& normals
)
{
double max_error = 1.0e-3;
vector<Mat>::iterator riter = rotations.begin();
vector<Mat>::iterator titer = translations.begin();
vector<Mat>::iterator niter = normals.begin();
for (;
riter != rotations.end() && titer != translations.end() && niter != normals.end();
++riter, ++titer, ++niter) {
double rdist = norm(*riter, _R, NORM_INF);
double tdist = norm(*titer, _t, NORM_INF);
double ndist = norm(*niter, _n, NORM_INF);
if ( rdist < max_error
&& tdist < max_error
&& ndist < max_error )
return true;
}
return false;
}
Matx33d _R, _K, _H;
Vec3d _t, _n;
};
TEST(Calib3d_DecomposeHomography, regression) { CV_HomographyDecompTest test; test.safe_run(); }

2
modules/calib3d/test/test_precomp.hpp
View File

@ -13,7 +13,7 @@
#include "opencv2/ts.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgcodecs.hpp"
namespace cvtest
{

5
modules/core/CMakeLists.txt
View File

@ -1,6 +1,5 @@
set(the_description "The Core Functionality")
ocv_add_module(core PRIVATE_REQUIRED ${ZLIB_LIBRARIES} "${OPENCL_LIBRARIES}" OPTIONAL opencv_cudev)
ocv_module_include_directories(${ZLIB_INCLUDE_DIRS})
if(HAVE_WINRT_CX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /ZW")
@ -19,11 +18,11 @@ file(GLOB lib_cuda_hdrs_detail "include/opencv2/${name}/cuda/detail/*.hpp" "incl
source_group("Cuda Headers" FILES ${lib_cuda_hdrs})
source_group("Cuda Headers\\Detail" FILES ${lib_cuda_hdrs_detail})
ocv_glob_module_sources(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc"
ocv_glob_module_sources(SOURCES "${OPENCV_MODULE_opencv_core_BINARY_DIR}/version_string.inc"
HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail})
ocv_module_include_directories(${the_module} ${ZLIB_INCLUDE_DIRS})
ocv_create_module()
ocv_add_precompiled_headers(${the_module})
ocv_add_accuracy_tests()
ocv_add_perf_tests()

78
modules/core/doc/basic_structures.rst
View File

@ -845,7 +845,6 @@ For convenience, the following types from the OpenCV C API already have such a s
that calls the appropriate release function:
* ``CvCapture``
* :ocv:struct:`CvDTreeSplit`
* :ocv:struct:`CvFileStorage`
* ``CvHaarClassifierCascade``
* :ocv:struct:`CvMat`
@ -2326,6 +2325,69 @@ Returns the matrix iterator and sets it to the after-last matrix element.
The methods return the matrix read-only or read-write iterators, set to the point following the last matrix element.
Mat::forEach
------------
Invoke with arguments functor, and runs the functor over all matrix element.
.. ocv:function:: template<typename _Tp, typename Functor> void Mat::forEach(Functor operation)
.. ocv:function:: template<typename _Tp, typename Functor> void Mat::forEach(Functor operation) const
The methos runs operation in parallel. Operation is passed by arguments. Operation have to be a function pointer, a function object or a lambda(C++11).
All of below operation is equal. Put 0xFF to first channel of all matrix elements. ::
Mat image(1920, 1080, CV_8UC3);
typedef cv::Point3_<uint8_t> Pixel;
// first. raw pointer access.
for (int r = 0; r < image.rows; ++r) {
Pixel* ptr = image.ptr<Pixel>(0, r);
const Pixel* ptr_end = ptr + image.cols;
for (; ptr != ptr_end; ++ptr) {
ptr->x = 255;
}
}
// Using MatIterator. (Simple but there are a Iterator's overhead)
for (Pixel &p : cv::Mat_<Pixel>(image)) {
p.x = 255;
}
// Parallel execution with function object.
struct Operator {
void operator ()(Pixel &pixel, const int * position) {
pixel.x = 255;
}
};
image.forEach<Pixel>(Operator());
// Parallel execution using C++11 lambda.
image.forEach<Pixel>([](Pixel &p, const int * position) -> void {
p.x = 255;
});
position parameter is index of current pixel. ::
// Creating 3D matrix (255 x 255 x 255) typed uint8_t,
// and initialize all elements by the value which equals elements position.
// i.e. pixels (x,y,z) = (1,2,3) is (b,g,r) = (1,2,3).
int sizes[] = { 255, 255, 255 };
typedef cv::Point3_<uint8_t> Pixel;
Mat_<Pixel> image = Mat::zeros(3, sizes, CV_8UC3);
image.forEachWithPosition([&](Pixel& pixel, const int position[]) -> void{
pixel.x = position[0];
pixel.y = position[1];
pixel.z = position[2];
});
Mat\_
-----
.. ocv:class:: Mat_
@ -2981,20 +3043,20 @@ The class provides the following features for all derived classes:
* so called "virtual constructor". That is, each Algorithm derivative is registered at program start and you can get the list of registered algorithms and create instance of a particular algorithm by its name (see ``Algorithm::create``). If you plan to add your own algorithms, it is good practice to add a unique prefix to your algorithms to distinguish them from other algorithms.
* setting/retrieving algorithm parameters by name. If you used video capturing functionality from OpenCV highgui module, you are probably familar with ``cvSetCaptureProperty()``, ``cvGetCaptureProperty()``, ``VideoCapture::set()`` and ``VideoCapture::get()``. ``Algorithm`` provides similar method where instead of integer id's you specify the parameter names as text strings. See ``Algorithm::set`` and ``Algorithm::get`` for details.
* setting/retrieving algorithm parameters by name. If you used video capturing functionality from OpenCV videoio module, you are probably familar with ``cvSetCaptureProperty()``, ``cvGetCaptureProperty()``, ``VideoCapture::set()`` and ``VideoCapture::get()``. ``Algorithm`` provides similar method where instead of integer id's you specify the parameter names as text strings. See ``Algorithm::set`` and ``Algorithm::get`` for details.
* reading and writing parameters from/to XML or YAML files. Every Algorithm derivative can store all its parameters and then read them back. There is no need to re-implement it each time.
Here is example of SIFT use in your application via Algorithm interface: ::
#include "opencv2/opencv.hpp"
#include "opencv2/nonfree.hpp"
#include "opencv2/xfeatures2d.hpp"
using namespace cv::xfeatures2d;
...
initModule_nonfree(); // to load SURF/SIFT etc.
Ptr<Feature2D> sift = Algorithm::create<Feature2D>("Feature2D.SIFT");
Ptr<Feature2D> sift = SIFT::create();
FileStorage fs("sift_params.xml", FileStorage::READ);
if( fs.isOpened() ) // if we have file with parameters, read them
@ -3004,7 +3066,7 @@ Here is example of SIFT use in your application via Algorithm interface: ::
}
else // else modify the parameters and store them; user can later edit the file to use different parameters
{
sift->set("contrastThreshold", 0.01f); // lower the contrast threshold, compared to the default value
sift->setContrastThreshold(0.01f); // lower the contrast threshold, compared to the default value
{
WriteStructContext ws(fs, "sift_params", CV_NODE_MAP);
@ -3014,7 +3076,7 @@ Here is example of SIFT use in your application via Algorithm interface: ::
Mat image = imread("myimage.png", 0), descriptors;
vector<KeyPoint> keypoints;
(*sift)(image, noArray(), keypoints, descriptors);
sift->detectAndCompute(image, noArray(), keypoints, descriptors);
Algorithm::name
---------------

31
modules/core/doc/drawing_functions.rst
View File

@ -361,6 +361,37 @@ The function ``line`` draws the line segment between ``pt1`` and ``pt2`` points
Antialiased lines are drawn using Gaussian filtering.
arrowedLine
----------------
Draws a arrow segment pointing from the first point to the second one.
.. ocv:function:: void arrowedLine(InputOutputArray img, Point pt1, Point pt2, const Scalar& color, int thickness=1, int lineType=8, int shift=0, double tipLength=0.1)
:param img: Image.
:param pt1: The point the arrow starts from.
:param pt2: The point the arrow points to.
:param color: Line color.
:param thickness: Line thickness.
:param lineType: Type of the line:
* **8** (or omitted) - 8-connected line.
* **4** - 4-connected line.
* **CV_AA** - antialiased line.
:param shift: Number of fractional bits in the point coordinates.
:param tipLength: The length of the arrow tip in relation to the arrow length
The function ``arrowedLine`` draws an arrow between ``pt1`` and ``pt2`` points in the image. See also :ocv:func:`line`.
LineIterator
------------
.. ocv:class:: LineIterator

3
modules/core/doc/intro.rst
View File

@ -14,7 +14,8 @@ OpenCV has a modular structure, which means that the package includes several sh
* **calib3d** - basic multiple-view geometry algorithms, single and stereo camera calibration, object pose estimation, stereo correspondence algorithms, and elements of 3D reconstruction.
* **features2d** - salient feature detectors, descriptors, and descriptor matchers.
* **objdetect** - detection of objects and instances of the predefined classes (for example, faces, eyes, mugs, people, cars, and so on).
* **highgui** - an easy-to-use interface to video capturing, image and video codecs, as well as simple UI capabilities.
* **highgui** - an easy-to-use interface to simple UI capabilities.
* **videoio** - an easy-to-use interface to video capturing and video codecs.
* **gpu** - GPU-accelerated algorithms from different OpenCV modules.
* ... some other helper modules, such as FLANN and Google test wrappers, Python bindings, and others.

58
modules/core/include/opencv2/core.hpp
View File

@ -510,6 +510,10 @@ CV_EXPORTS_W void randShuffle(InputOutputArray dst, double iterFactor = 1., RNG*
CV_EXPORTS_W void line(InputOutputArray img, Point pt1, Point pt2, const Scalar& color,
int thickness = 1, int lineType = LINE_8, int shift = 0);
//! draws an arrow from pt1 to pt2 in the image
CV_EXPORTS_W void arrowedLine(InputOutputArray img, Point pt1, Point pt2, const Scalar& color,
int thickness=1, int line_type=8, int shift=0, double tipLength=0.1);
//! draws the rectangle outline or a solid rectangle with the opposite corners pt1 and pt2 in the image
CV_EXPORTS_W void rectangle(InputOutputArray img, Point pt1, Point pt2,
const Scalar& color, int thickness = 1,
@ -686,7 +690,61 @@ public:
Mat mean; //!< mean value subtracted before the projection and added after the back projection
};
// Linear Discriminant Analysis
class CV_EXPORTS LDA
{
public:
// Initializes a LDA with num_components (default 0) and specifies how
// samples are aligned (default dataAsRow=true).
explicit LDA(int num_components = 0);
// Initializes and performs a Discriminant Analysis with Fisher's
// Optimization Criterion on given data in src and corresponding labels
// in labels. If 0 (or less) number of components are given, they are
// automatically determined for given data in computation.
LDA(InputArrayOfArrays src, InputArray labels, int num_components = 0);
// Serializes this object to a given filename.
void save(const String& filename) const;
// Deserializes this object from a given filename.
void load(const String& filename);
// Serializes this object to a given cv::FileStorage.
void save(FileStorage& fs) const;
// Deserializes this object from a given cv::FileStorage.
void load(const FileStorage& node);
// Destructor.
~LDA();
//! Compute the discriminants for data in src and labels.
void compute(InputArrayOfArrays src, InputArray labels);
// Projects samples into the LDA subspace.
Mat project(InputArray src);
// Reconstructs projections from the LDA subspace.
Mat reconstruct(InputArray src);
// Returns the eigenvectors of this LDA.
Mat eigenvectors() const { return _eigenvectors; }
// Returns the eigenvalues of this LDA.
Mat eigenvalues() const { return _eigenvalues; }
static Mat subspaceProject(InputArray W, InputArray mean, InputArray src);
static Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src);
protected:
bool _dataAsRow;
int _num_components;
Mat _eigenvectors;
Mat _eigenvalues;
void lda(InputArrayOfArrays src, InputArray labels);
};
/*!
Singular Value Decomposition class

2
modules/core/include/opencv2/core/core_c.h
View File

@ -1122,7 +1122,7 @@ CV_INLINE CvSetElem* cvSetNew( CvSet* set_header )
set_header->active_count++;
}
else
cvSetAdd( set_header, NULL, (CvSetElem**)&elem );
cvSetAdd( set_header, NULL, &elem );
return elem;
}

8
modules/core/include/opencv2/core/cuda.hpp
View File

@ -261,8 +261,8 @@ public:
int* refcount;
//! helper fields used in locateROI and adjustROI
uchar* datastart;
uchar* dataend;
const uchar* datastart;
const uchar* dataend;
//! allocator
Allocator* allocator;
@ -349,8 +349,8 @@ public:
uchar* data;
int* refcount;
uchar* datastart;
uchar* dataend;
const uchar* datastart;
const uchar* dataend;
AllocType alloc_type;
};

1
modules/core/include/opencv2/core/cvdef.h
View File

@ -244,6 +244,7 @@ typedef signed char schar;
/* fundamental constants */
#define CV_PI 3.1415926535897932384626433832795
#define CV_2PI 6.283185307179586476925286766559
#define CV_LOG2 0.69314718055994530941723212145818
/****************************************************************************************\

41
modules/core/include/opencv2/core/mat.hpp
View File

@ -360,7 +360,7 @@ struct CV_EXPORTS UMatData
{
enum { COPY_ON_MAP=1, HOST_COPY_OBSOLETE=2,
DEVICE_COPY_OBSOLETE=4, TEMP_UMAT=8, TEMP_COPIED_UMAT=24,
USER_ALLOCATED=32 };
USER_ALLOCATED=32, DEVICE_MEM_MAPPED=64};
UMatData(const MatAllocator* allocator);
~UMatData();
@ -370,11 +370,13 @@ struct CV_EXPORTS UMatData
bool hostCopyObsolete() const;
bool deviceCopyObsolete() const;
bool deviceMemMapped() const;
bool copyOnMap() const;
bool tempUMat() const;
bool tempCopiedUMat() const;
void markHostCopyObsolete(bool flag);
void markDeviceCopyObsolete(bool flag);
void markDeviceMemMapped(bool flag);
const MatAllocator* prevAllocator;
const MatAllocator* currAllocator;
@ -393,7 +395,7 @@ struct CV_EXPORTS UMatData
struct CV_EXPORTS UMatDataAutoLock
{
UMatDataAutoLock(UMatData* u);
explicit UMatDataAutoLock(UMatData* u);
~UMatDataAutoLock();
UMatData* u;
};
@ -401,7 +403,7 @@ struct CV_EXPORTS UMatDataAutoLock
struct CV_EXPORTS MatSize
{
MatSize(int* _p);
explicit MatSize(int* _p);
Size operator()() const;
const int& operator[](int i) const;
int& operator[](int i);
@ -415,7 +417,7 @@ struct CV_EXPORTS MatSize
struct CV_EXPORTS MatStep
{
MatStep();
MatStep(size_t s);
explicit MatStep(size_t s);
const size_t& operator[](int i) const;
size_t& operator[](int i);
operator size_t() const;
@ -898,6 +900,11 @@ public:
template<typename _Tp> MatConstIterator_<_Tp> begin() const;
template<typename _Tp> MatConstIterator_<_Tp> end() const;
//! template methods for for operation over all matrix elements.
// the operations take care of skipping gaps in the end of rows (if any)
template<typename _Tp, typename Functor> void forEach(const Functor& operation);
template<typename _Tp, typename Functor> void forEach(const Functor& operation) const;
enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG };
enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 };
@ -916,9 +923,9 @@ public:
uchar* data;
//! helper fields used in locateROI and adjustROI
uchar* datastart;
uchar* dataend;
uchar* datalimit;
const uchar* datastart;
const uchar* dataend;
const uchar* datalimit;
//! custom allocator
MatAllocator* allocator;
@ -932,6 +939,7 @@ public:
MatStep step;
protected:
template<typename _Tp, typename Functor> void forEach_impl(const Functor& operation);
};
@ -1041,6 +1049,11 @@ public:
const_iterator begin() const;
const_iterator end() const;
//! template methods for for operation over all matrix elements.
// the operations take care of skipping gaps in the end of rows (if any)
template<typename Functor> void forEach(const Functor& operation);
template<typename Functor> void forEach(const Functor& operation) const;
//! equivalent to Mat::create(_rows, _cols, DataType<_Tp>::type)
void create(int _rows, int _cols);
//! equivalent to Mat::create(_size, DataType<_Tp>::type)
@ -1802,9 +1815,9 @@ public:
//! copy operator
MatConstIterator& operator = (const MatConstIterator& it);
//! returns the current matrix element
uchar* operator *() const;
const uchar* operator *() const;
//! returns the i-th matrix element, relative to the current
uchar* operator [](ptrdiff_t i) const;
const uchar* operator [](ptrdiff_t i) const;
//! shifts the iterator forward by the specified number of elements
MatConstIterator& operator += (ptrdiff_t ofs);
@ -1829,9 +1842,9 @@ public:
const Mat* m;
size_t elemSize;
uchar* ptr;
uchar* sliceStart;
uchar* sliceEnd;
const uchar* ptr;
const uchar* sliceStart;
const uchar* sliceEnd;
};
@ -1915,9 +1928,9 @@ public:
//! constructor that sets the iterator to the specified element of the matrix
MatIterator_(Mat_<_Tp>* _m, int _row, int _col=0);
//! constructor that sets the iterator to the specified element of the matrix
MatIterator_(const Mat_<_Tp>* _m, Point _pt);
MatIterator_(Mat_<_Tp>* _m, Point _pt);
//! constructor that sets the iterator to the specified element of the matrix
MatIterator_(const Mat_<_Tp>* _m, const int* _idx);
MatIterator_(Mat_<_Tp>* _m, const int* _idx);
//! copy constructor
MatIterator_(const MatIterator_& it);
//! copy operator

60
modules/core/include/opencv2/core/mat.inl.hpp
View File

@ -438,7 +438,7 @@ Mat::Mat(const std::vector<_Tp>& vec, bool copyData)
if( !copyData )
{
step[0] = step[1] = sizeof(_Tp);
data = datastart = (uchar*)&vec[0];
datastart = data = (uchar*)&vec[0];
datalimit = dataend = datastart + rows * step[0];
}
else
@ -453,7 +453,7 @@ Mat::Mat(const Vec<_Tp, n>& vec, bool copyData)
if( !copyData )
{
step[0] = step[1] = sizeof(_Tp);
data = datastart = (uchar*)vec.val;
datastart = data = (uchar*)vec.val;
datalimit = dataend = datastart + rows * step[0];
}
else
@ -470,7 +470,7 @@ Mat::Mat(const Matx<_Tp,m,n>& M, bool copyData)
{
step[0] = cols * sizeof(_Tp);
step[1] = sizeof(_Tp);
data = datastart = (uchar*)M.val;
datastart = data = (uchar*)M.val;
datalimit = dataend = datastart + rows * step[0];
}
else
@ -485,7 +485,7 @@ Mat::Mat(const Point_<_Tp>& pt, bool copyData)
if( !copyData )
{
step[0] = step[1] = sizeof(_Tp);
data = datastart = (uchar*)&pt.x;
datastart = data = (uchar*)&pt.x;
datalimit = dataend = datastart + rows * step[0];
}
else
@ -504,7 +504,7 @@ Mat::Mat(const Point3_<_Tp>& pt, bool copyData)
if( !copyData )
{
step[0] = step[1] = sizeof(_Tp);
data = datastart = (uchar*)&pt.x;
datastart = data = (uchar*)&pt.x;
datalimit = dataend = datastart + rows * step[0];
}
else
@ -642,8 +642,9 @@ inline void Mat::release()
if( u && CV_XADD(&u->refcount, -1) == 1 )
deallocate();
u = NULL;
data = datastart = dataend = datalimit = 0;
size.p[0] = 0;
datastart = dataend = datalimit = data = 0;
for(int i = 0; i < dims; i++)
size.p[i] = 0;
}
inline
@ -999,6 +1000,17 @@ MatIterator_<_Tp> Mat::end()
return it;
}
template<typename _Tp, typename Functor> inline
void Mat::forEach(const Functor& operation) {
this->forEach_impl<_Tp>(operation);
};
template<typename _Tp, typename Functor> inline
void Mat::forEach(const Functor& operation) const {
// call as not const
(const_cast<Mat*>(this))->forEach<const _Tp>(operation);
};
template<typename _Tp> inline
Mat::operator std::vector<_Tp>() const
{
@ -1044,7 +1056,7 @@ void Mat::push_back(const _Tp& elem)
}
CV_Assert(DataType<_Tp>::type == type() && cols == 1
/* && dims == 2 (cols == 1 implies dims == 2) */);
uchar* tmp = dataend + step[0];
const uchar* tmp = dataend + step[0];
if( !isSubmatrix() && isContinuous() && tmp <= datalimit )
{
*(_Tp*)(data + (size.p[0]++) * step.p[0]) = elem;
@ -1584,6 +1596,15 @@ MatIterator_<_Tp> Mat_<_Tp>::end()
return Mat::end<_Tp>();
}
template<typename _Tp> template<typename Functor> inline
void Mat_<_Tp>::forEach(const Functor& operation) {
Mat::forEach<_Tp, Functor>(operation);
}
template<typename _Tp> template<typename Functor> inline
void Mat_<_Tp>::forEach(const Functor& operation) const {
Mat::forEach<_Tp, Functor>(operation);
}
///////////////////////////// SparseMat /////////////////////////////
@ -2148,7 +2169,7 @@ MatConstIterator& MatConstIterator::operator = (const MatConstIterator& it )
}
inline
uchar* MatConstIterator::operator *() const
const uchar* MatConstIterator::operator *() const
{
return ptr;
}
@ -2281,7 +2302,7 @@ MatConstIterator operator - (const MatConstIterator& a, ptrdiff_t ofs)
inline
uchar* MatConstIterator::operator [](ptrdiff_t i) const
const uchar* MatConstIterator::operator [](ptrdiff_t i) const
{
return *(*this + i);
}
@ -2453,12 +2474,12 @@ MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, int _row, int _col)
{}
template<typename _Tp> inline
MatIterator_<_Tp>::MatIterator_(const Mat_<_Tp>* _m, Point _pt)
MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, Point _pt)
: MatConstIterator_<_Tp>(_m, _pt)
{}
template<typename _Tp> inline
MatIterator_<_Tp>::MatIterator_(const Mat_<_Tp>* _m, const int* _idx)
MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, const int* _idx)
: MatConstIterator_<_Tp>(_m, _idx)
{}
@ -2592,7 +2613,7 @@ inline SparseMatConstIterator& SparseMatConstIterator::operator = (const SparseM
template<typename _Tp> inline
const _Tp& SparseMatConstIterator::value() const
{
return *(_Tp*)ptr;
return *(const _Tp*)ptr;
}
inline
@ -2733,7 +2754,7 @@ SparseMatConstIterator_<_Tp>& SparseMatConstIterator_<_Tp>::operator ++()
template<typename _Tp> inline
SparseMatConstIterator_<_Tp> SparseMatConstIterator_<_Tp>::operator ++(int)
{
SparseMatConstIterator it = *this;
SparseMatConstIterator_<_Tp> it = *this;
SparseMatConstIterator::operator ++();
return it;
}
@ -2785,7 +2806,7 @@ SparseMatIterator_<_Tp>& SparseMatIterator_<_Tp>::operator ++()
template<typename _Tp> inline
SparseMatIterator_<_Tp> SparseMatIterator_<_Tp>::operator ++(int)
{
SparseMatIterator it = *this;
SparseMatIterator_<_Tp> it = *this;
SparseMatConstIterator::operator ++();
return it;
}
@ -3350,10 +3371,19 @@ size_t UMat::total() const
inline bool UMatData::hostCopyObsolete() const { return (flags & HOST_COPY_OBSOLETE) != 0; }
inline bool UMatData::deviceCopyObsolete() const { return (flags & DEVICE_COPY_OBSOLETE) != 0; }
inline bool UMatData::deviceMemMapped() const { return (flags & DEVICE_MEM_MAPPED) != 0; }
inline bool UMatData::copyOnMap() const { return (flags & COPY_ON_MAP) != 0; }
inline bool UMatData::tempUMat() const { return (flags & TEMP_UMAT) != 0; }
inline bool UMatData::tempCopiedUMat() const { return (flags & TEMP_COPIED_UMAT) == TEMP_COPIED_UMAT; }
inline void UMatData::markDeviceMemMapped(bool flag)
{
if(flag)
flags |= DEVICE_MEM_MAPPED;
else
flags &= ~DEVICE_MEM_MAPPED;
}
inline void UMatData::markHostCopyObsolete(bool flag)
{
if(flag)

3
modules/core/include/opencv2/core/ocl.hpp
View File

@ -636,6 +636,9 @@ protected:
CV_EXPORTS MatAllocator* getOpenCLAllocator();
CV_EXPORTS_W bool isPerformanceCheckBypassed();
#define OCL_PERFORMANCE_CHECK(condition) (cv::ocl::isPerformanceCheckBypassed() || (condition))
}}
#endif

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