removed contrib, legacy and softcsscade modules; removed latentsvm and…

removed contrib, legacy and softcsscade modules; removed latentsvm and datamatrix detector from objdetect. removed haartraining and sft apps.
some of the stuff will be moved to opencv_contrib module.
in order to make this PR pass buildbot, please, comment off opencv_legacy, opencv_contrib and opencv_softcascade test runs.

apps/CMakeLists.txt

 add_definitions(-D__OPENCV_BUILD=1)
 link_libraries(${OPENCV_LINKER_LIBS})
 
-add_subdirectory(haartraining)
 add_subdirectory(traincascade)
-add_subdirectory(sft)

apps/haartraining/CMakeLists.txt

-SET(OPENCV_HAARTRAINING_DEPS opencv_core opencv_imgproc opencv_photo opencv_ml opencv_highgui opencv_objdetect opencv_calib3d opencv_video opencv_features2d opencv_flann opencv_legacy)
-ocv_check_dependencies(${OPENCV_HAARTRAINING_DEPS})
-
-if(NOT OCV_DEPENDENCIES_FOUND)
-  return()
-endif()
-
-project(haartraining)
-
-ocv_include_directories("${CMAKE_CURRENT_SOURCE_DIR}" "${OpenCV_SOURCE_DIR}/include/opencv")
-ocv_include_modules(${OPENCV_HAARTRAINING_DEPS})
-
-if(WIN32)
-  link_directories(${CMAKE_CURRENT_BINARY_DIR})
-endif()
-
-link_libraries(${OPENCV_HAARTRAINING_DEPS} opencv_haartraining_engine)
-
-# -----------------------------------------------------------
-#  Library
-# -----------------------------------------------------------
-set(cvhaartraining_lib_src
-  _cvcommon.h
-  cvclassifier.h
-  _cvhaartraining.h
-  cvhaartraining.h
-  cvboost.cpp
-  cvcommon.cpp
-  cvhaarclassifier.cpp
-  cvhaartraining.cpp
-  cvsamples.cpp
-  )
-
-add_library(opencv_haartraining_engine STATIC ${cvhaartraining_lib_src})
-set_target_properties(opencv_haartraining_engine PROPERTIES
-                      DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-                      ARCHIVE_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH}
-                      RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH}
-                      INSTALL_NAME_DIR lib
-                     )
-
-# -----------------------------------------------------------
-#  haartraining
-# -----------------------------------------------------------
-
-add_executable(opencv_haartraining cvhaartraining.h haartraining.cpp)
-set_target_properties(opencv_haartraining PROPERTIES
-                      DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-                      OUTPUT_NAME "opencv_haartraining")
-
-# -----------------------------------------------------------
-#  createsamples
-# -----------------------------------------------------------
-
-add_executable(opencv_createsamples cvhaartraining.h createsamples.cpp)
-set_target_properties(opencv_createsamples PROPERTIES
-                      DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-                      OUTPUT_NAME "opencv_createsamples")
-
-# -----------------------------------------------------------
-#  performance
-# -----------------------------------------------------------
-add_executable(opencv_performance performance.cpp)
-set_target_properties(opencv_performance PROPERTIES
-                      DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-                      OUTPUT_NAME "opencv_performance")
-
-# -----------------------------------------------------------
-#  Install part
-# -----------------------------------------------------------
-
-if(INSTALL_CREATE_DISTRIB)
-  if(BUILD_SHARED_LIBS)
-    install(TARGETS opencv_haartraining RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
-    install(TARGETS opencv_createsamples RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
-    install(TARGETS opencv_performance RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
-  endif()
-else()
-  install(TARGETS opencv_haartraining RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
-  install(TARGETS opencv_createsamples RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
-  install(TARGETS opencv_performance RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
-endif()
-
-if(ENABLE_SOLUTION_FOLDERS)
-  set_target_properties(opencv_performance PROPERTIES FOLDER "applications")
-  set_target_properties(opencv_createsamples PROPERTIES FOLDER "applications")
-  set_target_properties(opencv_haartraining PROPERTIES FOLDER "applications")
-  set_target_properties(opencv_haartraining_engine PROPERTIES FOLDER "applications")
-endif()

apps/haartraining/_cvcommon.h

-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                        Intel License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of Intel Corporation may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef __CVCOMMON_H_
-#define __CVCOMMON_H_
-
-#include "opencv2/core.hpp"
-
-#include "cxcore.h"
-#include "cv.h"
-#include "cxmisc.h"
-
-#define __BEGIN__ __CV_BEGIN__
-#define __END__  __CV_END__
-#define EXIT __CV_EXIT__
-
-#ifndef PATH_MAX
-#define PATH_MAX 512
-#endif /* PATH_MAX */
-
-int icvMkDir( const char* filename );
-
-/* returns index at specified position from index matrix of any type.
-   if matrix is NULL, then specified position is returned */
-CV_INLINE
-int icvGetIdxAt( CvMat* idx, int pos );
-
-CV_INLINE
-int icvGetIdxAt( CvMat* idx, int pos )
-{
-    if( idx == NULL )
-    {
-        return pos;
-    }
-    else
-    {
-        CvScalar sc;
-        int type;
-
-        type = CV_MAT_TYPE( idx->type );
-        cvRawDataToScalar( idx->data.ptr + pos *
-            ( (idx->rows == 1) ? CV_ELEM_SIZE( type ) : idx->step ), type, &sc );
-
-        return (int) sc.val[0];
-    }
-}
-
-/* debug functions */
-
-#define CV_DEBUG_SAVE( ptr ) icvSave( ptr, __FILE__, __LINE__ );
-
-void icvSave( const CvArr* ptr, const char* filename, int line );
-
-#endif /* __CVCOMMON_H_ */

apps/haartraining/createsamples.cpp

-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                        Intel License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of Intel Corporation may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-/*
- * createsamples.cpp
- *
- * Create test/training samples
- */
-
-#include <cstdio>
-#include <cstring>
-#include <cstdlib>
-#include <cmath>
-#include <ctime>
-
-using namespace std;
-
-#include "cvhaartraining.h"
-
-int main( int argc, char* argv[] )
-{
-    int i = 0;
-    char* nullname   = (char*)"(NULL)";
-    char* vecname    = NULL; /* .vec file name */
-    char* infoname   = NULL; /* file name with marked up image descriptions */
-    char* imagename  = NULL; /* single sample image */
-    char* bgfilename = NULL; /* background */
-    int num = 1000;
-    int bgcolor = 0;
-    int bgthreshold = 80;
-    int invert = 0;
-    int maxintensitydev = 40;
-    double maxxangle = 1.1;
-    double maxyangle = 1.1;
-    double maxzangle = 0.5;
-    int showsamples = 0;
-    /* the samples are adjusted to this scale in the sample preview window */
-    double scale = 4.0;
-    int width  = 24;
-    int height = 24;
-
-    srand((unsigned int)time(0));
-
-    if( argc == 1 )
-    {
-        printf( "Usage: %s\n  [-info <collection_file_name>]\n"
-                "  [-img <image_file_name>]\n"
-                "  [-vec <vec_file_name>]\n"
-                "  [-bg <background_file_name>]\n  [-num <number_of_samples = %d>]\n"
-                "  [-bgcolor <background_color = %d>]\n"
-                "  [-inv] [-randinv] [-bgthresh <background_color_threshold = %d>]\n"
-                "  [-maxidev <max_intensity_deviation = %d>]\n"
-                "  [-maxxangle <max_x_rotation_angle = %f>]\n"
-                "  [-maxyangle <max_y_rotation_angle = %f>]\n"
-                "  [-maxzangle <max_z_rotation_angle = %f>]\n"
-                "  [-show [<scale = %f>]]\n"
-                "  [-w <sample_width = %d>]\n  [-h <sample_height = %d>]\n",
-                argv[0], num, bgcolor, bgthreshold, maxintensitydev,
-                maxxangle, maxyangle, maxzangle, scale, width, height );
-
-        return 0;
-    }
-
-    for( i = 1; i < argc; ++i )
-    {
-        if( !strcmp( argv[i], "-info" ) )
-        {
-            infoname = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-img" ) )
-        {
-            imagename = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-vec" ) )
-        {
-            vecname = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-bg" ) )
-        {
-            bgfilename = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-num" ) )
-        {
-            num = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-bgcolor" ) )
-        {
-            bgcolor = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-bgthresh" ) )
-        {
-            bgthreshold = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-inv" ) )
-        {
-            invert = 1;
-        }
-        else if( !strcmp( argv[i], "-randinv" ) )
-        {
-            invert = CV_RANDOM_INVERT;
-        }
-        else if( !strcmp( argv[i], "-maxidev" ) )
-        {
-            maxintensitydev = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-maxxangle" ) )
-        {
-            maxxangle = atof( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-maxyangle" ) )
-        {
-            maxyangle = atof( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-maxzangle" ) )
-        {
-            maxzangle = atof( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-show" ) )
-        {
-            showsamples = 1;
-            if( i+1 < argc && strlen( argv[i+1] ) > 0 && argv[i+1][0] != '-' )
-            {
-                double d;
-                d = strtod( argv[i+1], 0 );
-                if( d != -HUGE_VAL && d != HUGE_VAL && d > 0 ) scale = d;
-                ++i;
-            }
-        }
-        else if( !strcmp( argv[i], "-w" ) )
-        {
-            width = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-h" ) )
-        {
-            height = atoi( argv[++i] );
-        }
-    }
-
-    printf( "Info file name: %s\n", ((infoname == NULL) ?   nullname : infoname ) );
-    printf( "Img file name: %s\n",  ((imagename == NULL) ?  nullname : imagename ) );
-    printf( "Vec file name: %s\n",  ((vecname == NULL) ?    nullname : vecname ) );
-    printf( "BG  file name: %s\n",  ((bgfilename == NULL) ? nullname : bgfilename ) );
-    printf( "Num: %d\n", num );
-    printf( "BG color: %d\n", bgcolor );
-    printf( "BG threshold: %d\n", bgthreshold );
-    printf( "Invert: %s\n", (invert == CV_RANDOM_INVERT) ? "RANDOM"
-                                : ( (invert) ? "TRUE" : "FALSE" ) );
-    printf( "Max intensity deviation: %d\n", maxintensitydev );
-    printf( "Max x angle: %g\n", maxxangle );
-    printf( "Max y angle: %g\n", maxyangle );
-    printf( "Max z angle: %g\n", maxzangle );
-    printf( "Show samples: %s\n", (showsamples) ? "TRUE" : "FALSE" );
-    if( showsamples )
-    {
-        printf( "Scale: %g\n", scale );
-    }
-    printf( "Width: %d\n", width );
-    printf( "Height: %d\n", height );
-
-    /* determine action */
-    if( imagename && vecname )
-    {
-        printf( "Create training samples from single image applying distortions...\n" );
-
-        cvCreateTrainingSamples( vecname, imagename, bgcolor, bgthreshold, bgfilename,
-                                 num, invert, maxintensitydev,
-                                 maxxangle, maxyangle, maxzangle,
-                                 showsamples, width, height );
-
-        printf( "Done\n" );
-    }
-    else if( imagename && bgfilename && infoname )
-    {
-        printf( "Create test samples from single image applying distortions...\n" );
-
-        cvCreateTestSamples( infoname, imagename, bgcolor, bgthreshold, bgfilename, num,
-            invert, maxintensitydev,
-            maxxangle, maxyangle, maxzangle, showsamples, width, height );
-
-        printf( "Done\n" );
-    }
-    else if( infoname && vecname )
-    {
-        int total;
-
-        printf( "Create training samples from images collection...\n" );
-
-        total = cvCreateTrainingSamplesFromInfo( infoname, vecname, num, showsamples,
-                                                 width, height );
-
-        printf( "Done. Created %d samples\n", total );
-    }
-    else if( vecname )
-    {
-        printf( "View samples from vec file (press ESC to exit)...\n" );
-
-        cvShowVecSamples( vecname, width, height, scale );
-
-        printf( "Done\n" );
-    }
-    else
-    {
-        printf( "Nothing to do\n" );
-    }
-
-    return 0;
-}

apps/haartraining/cvcommon.cpp

-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                        Intel License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of Intel Corporation may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "_cvcommon.h"
-
-#include <cstring>
-#include <ctime>
-
-#include <sys/stat.h>
-#include <sys/types.h>
-#ifdef _WIN32
-#include <direct.h>
-#endif /* _WIN32 */
-
-int icvMkDir( const char* filename )
-{
-    char path[PATH_MAX];
-    char* p;
-    int pos;
-
-#ifdef _WIN32
-    struct _stat st;
-#else /* _WIN32 */
-    struct stat st;
-    mode_t mode;
-
-    mode = 0755;
-#endif /* _WIN32 */
-
-    strcpy( path, filename );
-
-    p = path;
-    for( ; ; )
-    {
-        pos = (int)strcspn( p, "/\\" );
-
-        if( pos == (int) strlen( p ) ) break;
-        if( pos != 0 )
-        {
-            p[pos] = '\0';
-
-#ifdef _WIN32
-            if( p[pos-1] != ':' )
-            {
-                if( _stat( path, &st ) != 0 )
-                {
-                    if( _mkdir( path ) != 0 ) return 0;
-                }
-            }
-#else /* _WIN32 */
-            if( stat( path, &st ) != 0 )
-            {
-                if( mkdir( path, mode ) != 0 ) return 0;
-            }
-#endif /* _WIN32 */
-        }
-
-        p[pos] = '/';
-
-        p += pos + 1;
-    }
-
-    return 1;
-}
-
-#if 0
-/* debug functions */
-void icvSave( const CvArr* ptr, const char* filename, int line )
-{
-    CvFileStorage* fs;
-    char buf[PATH_MAX];
-    const char* name;
-
-    name = strrchr( filename, '\\' );
-    if( !name ) name = strrchr( filename, '/' );
-    if( !name ) name = filename;
-    else name++; /* skip '/' or '\\' */
-
-    sprintf( buf, "%s-%d-%d", name, line, time( NULL ) );
-    fs = cvOpenFileStorage( buf, NULL, CV_STORAGE_WRITE_TEXT );
-    if( !fs ) return;
-    cvWrite( fs, "debug", ptr );
-    cvReleaseFileStorage( &fs );
-}
-#endif // #if 0
-
-/* End of file. */

apps/haartraining/cvhaartraining.h

-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                        Intel License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of Intel Corporation may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-/*
- * cvhaartraining.h
- *
- * haar training functions
- */
-
-#ifndef _CVHAARTRAINING_H_
-#define _CVHAARTRAINING_H_
-
-/*
- * cvCreateTrainingSamples
- *
- * Create training samples applying random distortions to sample image and
- * store them in .vec file
- *
- * filename        - .vec file name
- * imgfilename     - sample image file name
- * bgcolor         - background color for sample image
- * bgthreshold     - background color threshold. Pixels those colors are in range
- *   [bgcolor-bgthreshold, bgcolor+bgthreshold] are considered as transparent
- * bgfilename      - background description file name. If not NULL samples
- *   will be put on arbitrary background
- * count           - desired number of samples
- * invert          - if not 0 sample foreground pixels will be inverted
- *   if invert == CV_RANDOM_INVERT then samples will be inverted randomly
- * maxintensitydev - desired max intensity deviation of foreground samples pixels
- * maxxangle       - max rotation angles
- * maxyangle
- * maxzangle
- * showsamples     - if not 0 samples will be shown
- * winwidth        - desired samples width
- * winheight       - desired samples height
- */
-#define CV_RANDOM_INVERT 0x7FFFFFFF
-
-void cvCreateTrainingSamples( const char* filename,
-                              const char* imgfilename, int bgcolor, int bgthreshold,
-                              const char* bgfilename, int count,
-                              int invert = 0, int maxintensitydev = 40,
-                              double maxxangle = 1.1,
-                              double maxyangle = 1.1,
-                              double maxzangle = 0.5,
-                              int showsamples = 0,
-                              int winwidth = 24, int winheight = 24 );
-
-void cvCreateTestSamples( const char* infoname,
-                          const char* imgfilename, int bgcolor, int bgthreshold,
-                          const char* bgfilename, int count,
-                          int invert, int maxintensitydev,
-                          double maxxangle, double maxyangle, double maxzangle,
-                          int showsamples,
-                          int winwidth, int winheight );
-
-/*
- * cvCreateTrainingSamplesFromInfo
- *
- * Create training samples from a set of marked up images and store them into .vec file
- * infoname    - file in which marked up image descriptions are stored
- * num         - desired number of samples
- * showsamples - if not 0 samples will be shown
- * winwidth    - sample width
- * winheight   - sample height
- *
- * Return number of successfully created samples
- */
-int cvCreateTrainingSamplesFromInfo( const char* infoname, const char* vecfilename,
-                                     int num,
-                                     int showsamples,
-                                     int winwidth, int winheight );
-
-/*
- * cvShowVecSamples
- *
- * Shows samples stored in .vec file
- *
- * filename
- *   .vec file name
- * winwidth
- *   sample width
- * winheight
- *   sample height
- * scale
- *   the scale each sample is adjusted to
- */
-void cvShowVecSamples( const char* filename, int winwidth, int winheight, double scale );
-
-
-/*
- * cvCreateCascadeClassifier
- *
- * Create cascade classifier
- * dirname          - directory name in which cascade classifier will be created.
- *   It must exist and contain subdirectories 0, 1, 2, ... (nstages-1).
- * vecfilename      - name of .vec file with object's images
- * bgfilename       - name of background description file
- * bg_vecfile       - true if bgfilename represents a vec file with discrete negatives
- * npos             - number of positive samples used in training of each stage
- * nneg             - number of negative samples used in training of each stage
- * nstages          - number of stages
- * numprecalculated - number of features being precalculated. Each precalculated feature
- *   requires (number_of_samples*(sizeof( float ) + sizeof( short ))) bytes of memory
- * numsplits        - number of binary splits in each weak classifier
- *   1 - stumps, 2 and more - trees.
- * minhitrate       - desired min hit rate of each stage
- * maxfalsealarm    - desired max false alarm of each stage
- * weightfraction   - weight trimming parameter
- * mode             - 0 - BASIC = Viola
- *                    1 - CORE  = All upright
- *                    2 - ALL   = All features
- * symmetric        - if not 0 vertical symmetry is assumed
- * equalweights     - if not 0 initial weights of all samples will be equal
- * winwidth         - sample width
- * winheight        - sample height
- * boosttype        - type of applied boosting algorithm
- *   0 - Discrete AdaBoost
- *   1 - Real AdaBoost
- *   2 - LogitBoost
- *   3 - Gentle AdaBoost
- * stumperror       - type of used error if Discrete AdaBoost algorithm is applied
- *   0 - misclassification error
- *   1 - gini error
- *   2 - entropy error
- */
-void cvCreateCascadeClassifier( const char* dirname,
-                                const char* vecfilename,
-                                const char* bgfilename,
-                                int npos, int nneg, int nstages,
-                                int numprecalculated,
-                                int numsplits,
-                                float minhitrate = 0.995F, float maxfalsealarm = 0.5F,
-                                float weightfraction = 0.95F,
-                                int mode = 0, int symmetric = 1,
-                                int equalweights = 1,
-                                int winwidth = 24, int winheight = 24,
-                                int boosttype = 3, int stumperror = 0 );
-
-void cvCreateTreeCascadeClassifier( const char* dirname,
-                                    const char* vecfilename,
-                                    const char* bgfilename,
-                                    int npos, int nneg, int nstages,
-                                    int numprecalculated,
-                                    int numsplits,
-                                    float minhitrate, float maxfalsealarm,
-                                    float weightfraction,
-                                    int mode, int symmetric,
-                                    int equalweights,
-                                    int winwidth, int winheight,
-                                    int boosttype, int stumperror,
-                                    int maxtreesplits, int minpos, bool bg_vecfile = false );
-
-#endif /* _CVHAARTRAINING_H_ */

apps/haartraining/haartraining.cpp

-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                        Intel License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of Intel Corporation may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-/*
- * haartraining.cpp
- *
- * Train cascade classifier
- */
-
-#include <cstdio>
-#include <cstring>
-#include <cstdlib>
-
-using namespace std;
-
-#include "cvhaartraining.h"
-
-int main( int argc, char* argv[] )
-{
-    int i = 0;
-    char* nullname = (char*)"(NULL)";
-
-    char* vecname = NULL;
-    char* dirname = NULL;
-    char* bgname  = NULL;
-
-    bool bg_vecfile = false;
-    int npos    = 2000;
-    int nneg    = 2000;
-    int nstages = 14;
-    int mem     = 200;
-    int nsplits = 1;
-    float minhitrate     = 0.995F;
-    float maxfalsealarm  = 0.5F;
-    float weightfraction = 0.95F;
-    int mode         = 0;
-    int symmetric    = 1;
-    int equalweights = 0;
-    int width  = 24;
-    int height = 24;
-    const char* boosttypes[] = { "DAB", "RAB", "LB", "GAB" };
-    int boosttype = 3;
-    const char* stumperrors[] = { "misclass", "gini", "entropy" };
-    int stumperror = 0;
-    int maxtreesplits = 0;
-    int minpos = 500;
-
-    if( argc == 1 )
-    {
-        printf( "Usage: %s\n  -data <dir_name>\n"
-                "  -vec <vec_file_name>\n"
-                "  -bg <background_file_name>\n"
-                "  [-bg-vecfile]\n"
-                "  [-npos <number_of_positive_samples = %d>]\n"
-                "  [-nneg <number_of_negative_samples = %d>]\n"
-                "  [-nstages <number_of_stages = %d>]\n"
-                "  [-nsplits <number_of_splits = %d>]\n"
-                "  [-mem <memory_in_MB = %d>]\n"
-                "  [-sym (default)] [-nonsym]\n"
-                "  [-minhitrate <min_hit_rate = %f>]\n"
-                "  [-maxfalsealarm <max_false_alarm_rate = %f>]\n"
-                "  [-weighttrimming <weight_trimming = %f>]\n"
-                "  [-eqw]\n"
-                "  [-mode <BASIC (default) | CORE | ALL>]\n"
-                "  [-w <sample_width = %d>]\n"
-                "  [-h <sample_height = %d>]\n"
-                "  [-bt <DAB | RAB | LB | GAB (default)>]\n"
-                "  [-err <misclass (default) | gini | entropy>]\n"
-                "  [-maxtreesplits <max_number_of_splits_in_tree_cascade = %d>]\n"
-                "  [-minpos <min_number_of_positive_samples_per_cluster = %d>]\n",
-                argv[0], npos, nneg, nstages, nsplits, mem,
-                minhitrate, maxfalsealarm, weightfraction, width, height,
-                maxtreesplits, minpos );
-
-        return 0;
-    }
-
-    for( i = 1; i < argc; i++ )
-    {
-        if( !strcmp( argv[i], "-data" ) )
-        {
-            dirname = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-vec" ) )
-        {
-            vecname = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-bg" ) )
-        {
-            bgname = argv[++i];
-        }
-        else if( !strcmp( argv[i], "-bg-vecfile" ) )
-        {
-            bg_vecfile = true;
-        }
-        else if( !strcmp( argv[i], "-npos" ) )
-        {
-            npos = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-nneg" ) )
-        {
-            nneg = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-nstages" ) )
-        {
-            nstages = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-nsplits" ) )
-        {
-            nsplits = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-mem" ) )
-        {
-            mem = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-sym" ) )
-        {
-            symmetric = 1;
-        }
-        else if( !strcmp( argv[i], "-nonsym" ) )
-        {
-            symmetric = 0;
-        }
-        else if( !strcmp( argv[i], "-minhitrate" ) )
-        {
-            minhitrate = (float) atof( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-maxfalsealarm" ) )
-        {
-            maxfalsealarm = (float) atof( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-weighttrimming" ) )
-        {
-            weightfraction = (float) atof( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-eqw" ) )
-        {
-            equalweights = 1;
-        }
-        else if( !strcmp( argv[i], "-mode" ) )
-        {
-            char* tmp = argv[++i];
-
-            if( !strcmp( tmp, "CORE" ) )
-            {
-                mode = 1;
-            }
-            else if( !strcmp( tmp, "ALL" ) )
-            {
-                mode = 2;
-            }
-            else
-            {
-                mode = 0;
-            }
-        }
-        else if( !strcmp( argv[i], "-w" ) )
-        {
-            width = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-h" ) )
-        {
-            height = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-bt" ) )
-        {
-            i++;
-            if( !strcmp( argv[i], boosttypes[0] ) )
-            {
-                boosttype = 0;
-            }
-            else if( !strcmp( argv[i], boosttypes[1] ) )
-            {
-                boosttype = 1;
-            }
-            else if( !strcmp( argv[i], boosttypes[2] ) )
-            {
-                boosttype = 2;
-            }
-            else
-            {
-                boosttype = 3;
-            }
-        }
-        else if( !strcmp( argv[i], "-err" ) )
-        {
-            i++;
-            if( !strcmp( argv[i], stumperrors[0] ) )
-            {
-                stumperror = 0;
-            }
-            else if( !strcmp( argv[i], stumperrors[1] ) )
-            {
-                stumperror = 1;
-            }
-            else
-            {
-                stumperror = 2;
-            }
-        }
-        else if( !strcmp( argv[i], "-maxtreesplits" ) )
-        {
-            maxtreesplits = atoi( argv[++i] );
-        }
-        else if( !strcmp( argv[i], "-minpos" ) )
-        {
-            minpos = atoi( argv[++i] );
-        }
-    }
-
-    printf( "Data dir name: %s\n", ((dirname == NULL) ? nullname : dirname ) );
-    printf( "Vec file name: %s\n", ((vecname == NULL) ? nullname : vecname ) );
-    printf( "BG  file name: %s, is a vecfile: %s\n", ((bgname == NULL) ? nullname : bgname ), bg_vecfile ? "yes" : "no" );
-    printf( "Num pos: %d\n", npos );
-    printf( "Num neg: %d\n", nneg );
-    printf( "Num stages: %d\n", nstages );
-    printf( "Num splits: %d (%s as weak classifier)\n", nsplits,
-        (nsplits == 1) ? "stump" : "tree" );
-    printf( "Mem: %d MB\n", mem );
-    printf( "Symmetric: %s\n", (symmetric) ? "TRUE" : "FALSE" );
-    printf( "Min hit rate: %f\n", minhitrate );
-    printf( "Max false alarm rate: %f\n", maxfalsealarm );
-    printf( "Weight trimming: %f\n", weightfraction );
-    printf( "Equal weights: %s\n", (equalweights) ? "TRUE" : "FALSE" );
-    printf( "Mode: %s\n", ( (mode == 0) ? "BASIC" : ( (mode == 1) ? "CORE" : "ALL") ) );
-    printf( "Width: %d\n", width );
-    printf( "Height: %d\n", height );
-    //printf( "Max num of precalculated features: %d\n", numprecalculated );
-    printf( "Applied boosting algorithm: %s\n", boosttypes[boosttype] );
-    printf( "Error (valid only for Discrete and Real AdaBoost): %s\n",
-            stumperrors[stumperror] );
-
-    printf( "Max number of splits in tree cascade: %d\n", maxtreesplits );
-    printf( "Min number of positive samples per cluster: %d\n", minpos );
-
-    cvCreateTreeCascadeClassifier( dirname, vecname, bgname,
-                               npos, nneg, nstages, mem,
-                               nsplits,
-                               minhitrate, maxfalsealarm, weightfraction,
-                               mode, symmetric,
-                               equalweights, width, height,
-                               boosttype, stumperror,
-                               maxtreesplits, minpos, bg_vecfile );
-
-    return 0;
-}

apps/sft/CMakeLists.txt

-set(name sft)
-set(the_target opencv_${name})
-
-set(OPENCV_${the_target}_DEPS opencv_core opencv_softcascade opencv_highgui opencv_imgproc opencv_ml)
-ocv_check_dependencies(${OPENCV_${the_target}_DEPS})
-
-if(NOT OCV_DEPENDENCIES_FOUND)
-  return()
-endif()
-
-project(${the_target})
-
-ocv_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include" "${OpenCV_SOURCE_DIR}/include/opencv")
-ocv_include_modules(${OPENCV_${the_target}_DEPS})
-
-file(GLOB ${the_target}_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
-
-add_executable(${the_target} ${${the_target}_SOURCES})
-
-target_link_libraries(${the_target} ${OPENCV_${the_target}_DEPS})
-
-set_target_properties(${the_target} PROPERTIES
-                      DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-                      ARCHIVE_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH}
-                      RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH}
-                      INSTALL_NAME_DIR lib
-                      OUTPUT_NAME "opencv_trainsoftcascade")
-
-if(ENABLE_SOLUTION_FOLDERS)
-  set_target_properties(${the_target} PROPERTIES FOLDER "applications")
-endif()
-
-install(TARGETS ${the_target} RUNTIME DESTINATION bin COMPONENT main)

apps/sft/config.cpp

-/*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) 2008-2012, 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 <sft/config.hpp>
-#include <iomanip>
-
-sft::Config::Config(): seed(0) {}
-
-void sft::Config::write(cv::FileStorage& fs) const
-{
-    fs << "{"
-       << "trainPath"    << trainPath
-       << "testPath"     << testPath
-
-       << "modelWinSize" << modelWinSize
-       << "offset"       << offset
-       << "octaves"      << octaves
-
-       << "positives"    << positives
-       << "negatives"    << negatives
-       << "btpNegatives" << btpNegatives
-
-       << "shrinkage"    << shrinkage
-
-       << "treeDepth"    << treeDepth
-       << "weaks"        << weaks
-       << "poolSize"     << poolSize
-
-       << "cascadeName"  << cascadeName
-       << "outXmlPath"   << outXmlPath
-
-       << "seed"         << seed
-       << "featureType"  << featureType
-       << "}";
-}
-
-void sft::Config::read(const cv::FileNode& node)
-{
-    trainPath = (string)node["trainPath"];
-    testPath  = (string)node["testPath"];
-
-    cv::FileNodeIterator  nIt = node["modelWinSize"].end();
-    modelWinSize = cv::Size((int)*(--nIt), (int)*(--nIt));
-
-    nIt = node["offset"].end();
-    offset = cv::Point2i((int)*(--nIt), (int)*(--nIt));
-
-    node["octaves"] >> octaves;
-
-    positives =    (int)node["positives"];
-    negatives =    (int)node["negatives"];
-    btpNegatives = (int)node["btpNegatives"];
-
-    shrinkage = (int)node["shrinkage"];
-
-    treeDepth = (int)node["treeDepth"];
-    weaks =     (int)node["weaks"];
-    poolSize =  (int)node["poolSize"];
-
-    cascadeName = (std::string)node["cascadeName"];
-    outXmlPath =  (std::string)node["outXmlPath"];
-
-    seed = (int)node["seed"];
-    featureType = (std::string)node["featureType"];
-}
-
-void sft::write(cv::FileStorage& fs, const string&, const Config& x)
-{
-    x.write(fs);
-}
-
-void sft::read(const cv::FileNode& node, Config& x, const Config& default_value)
-{
-    x = default_value;
-
-    if(!node.empty())
-        x.read(node);
-}
-
-namespace {
-
-struct Out
-{
-    Out(std::ostream& _out): out(_out) {}
-    template<typename T>
-    void operator ()(const T a) const {out << a << " ";}
-
-    std::ostream& out;
-private:
-    Out& operator=(Out const& other);
-};
-}
-
-std::ostream& sft::operator<<(std::ostream& out, const Config& m)
-{
-    out << std::setw(14) << std::left << "trainPath"    << m.trainPath     << std::endl
-        << std::setw(14) << std::left << "testPath"     << m.testPath      << std::endl
-
-        << std::setw(14) << std::left << "modelWinSize" << m.modelWinSize  << std::endl
-        << std::setw(14) << std::left << "offset"       << m.offset        << std::endl
-        << std::setw(14) << std::left << "octaves";
-
-    Out o(out);
-    for_each(m.octaves.begin(), m.octaves.end(), o);
-
-    out << std::endl
-        << std::setw(14) << std::left  << "positives"    << m.positives    << std::endl
-        << std::setw(14) << std::left  << "negatives"    << m.negatives    << std::endl
-        << std::setw(14) << std::left  << "btpNegatives" << m.btpNegatives << std::endl
-
-        << std::setw(14) << std::left  << "shrinkage"    << m.shrinkage    << std::endl
-
-        << std::setw(14) << std::left  << "treeDepth"    << m.treeDepth    << std::endl
-        << std::setw(14) << std::left  << "weaks"        << m.weaks        << std::endl
-        << std::setw(14) << std::left  << "poolSize"     << m.poolSize     << std::endl
-
-        << std::setw(14) << std::left  << "cascadeName"  << m.cascadeName  << std::endl
-        << std::setw(14) << std::left  << "outXmlPath"   << m.outXmlPath   << std::endl
-        << std::setw(14) << std::left  << "seed"         << m.seed         << std::endl
-        << std::setw(14) << std::left  << "featureType"  << m.featureType  << std::endl;
-
-    return out;
-}

apps/sft/dataset.cpp

-/*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) 2008-2012, 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 <sft/dataset.hpp>
-#include <opencv2/highgui.hpp>
-
-#include <iostream>
-#include <queue>
-
-// in the default case data folders should be aligned as following:
-// 1. positives: <train or test path>/octave_<octave number>/pos/*.png
-// 2. negatives: <train or test path>/octave_<octave number>/neg/*.png
-sft::ScaledDataset::ScaledDataset(const string& path, const int oct)
-{
-    dprintf("%s\n", "get dataset file names...");
-    dprintf("%s\n", "Positives globing...");
-    cv::glob(path + "/pos/octave_" + cv::format("%d", oct) + "/*.png", pos);
-
-    dprintf("%s\n", "Negatives globing...");
-    cv::glob(path + "/neg/octave_" + cv::format("%d", oct) + "/*.png", neg);
-
-    // Check: files not empty
-    CV_Assert(pos.size() != size_t(0));
-    CV_Assert(neg.size() != size_t(0));
-}
-
-cv::Mat sft::ScaledDataset::get(SampleType type, int idx) const
-{
-    const std::string& src = (type == POSITIVE)? pos[idx]: neg[idx];
-    return cv::imread(src);
-}
-
-int sft::ScaledDataset::available(SampleType type) const
-{
-    return (int)((type == POSITIVE)? pos.size():neg.size());
-}
-
-sft::ScaledDataset::~ScaledDataset(){}

apps/sft/include/sft/common.hpp

-/*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) 2008-2012, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef __SFT_COMMON_HPP__
-#define __SFT_COMMON_HPP__
-
-#include <opencv2/core.hpp>
-#include <opencv2/core/utility.hpp>
-#include <opencv2/softcascade.hpp>
-
-namespace cv {using namespace softcascade;}
-namespace sft
-{
-
-    using cv::Mat;
-    struct ICF;
-
-    typedef cv::String   string;
-
-    typedef std::vector<ICF>           Icfvector;
-    typedef std::vector<sft::string>   svector;
-    typedef std::vector<int>           ivector;
-}
-
-// used for noisy printfs
-//#define WITH_DEBUG_OUT
-
-#if defined WITH_DEBUG_OUT
-# include <stdio.h>
-# define dprintf(format, ...)  printf(format, ##__VA_ARGS__)
-#else
-# define dprintf(format, ...)
-#endif
-
-#endif

apps/sft/include/sft/config.hpp

-/*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) 2008-2012, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef __SFT_CONFIG_HPP__
-#define __SFT_CONFIG_HPP__
-
-#include <sft/common.hpp>
-
-#include <ostream>
-
-namespace sft {
-
-struct Config
-{
-    Config();
-
-    void write(cv::FileStorage& fs) const;
-
-    void read(const cv::FileNode& node);
-
-    // Scaled and shrunk model size.
-    cv::Size model(ivector::const_iterator it) const
-    {
-        float octave = powf(2.f, (float)(*it));
-        return cv::Size( cvRound(modelWinSize.width  * octave) / shrinkage,
-                         cvRound(modelWinSize.height * octave) / shrinkage );
-    }
-
-    // Scaled but, not shrunk bounding box for object in sample image.
-    cv::Rect bbox(ivector::const_iterator it) const
-    {
-        float octave = powf(2.f, (float)(*it));
-        return cv::Rect( cvRound(offset.x * octave), cvRound(offset.y * octave),
-            cvRound(modelWinSize.width  * octave), cvRound(modelWinSize.height * octave));
-    }
-
-    string resPath(ivector::const_iterator it) const
-    {
-        return cv::format("%s%d.xml",cascadeName.c_str(), *it);
-    }
-
-    // Paths to a rescaled data
-    string trainPath;
-    string testPath;
-
-    // Original model size.
-    cv::Size modelWinSize;
-
-    // example offset into positive image
-    cv::Point2i offset;
-
-    // List of octaves for which have to be trained cascades (a list of powers of two)
-    ivector octaves;
-
-    // Maximum number of positives that should be used during training
-    int positives;
-
-    // Initial number of negatives used during training.
-    int negatives;
-
-    // Number of weak negatives to add each bootstrapping step.
-    int btpNegatives;
-
-    // Inverse of scale for feature resizing
-    int shrinkage;
-
-    // Depth on weak classifier's decision tree
-    int treeDepth;
-
-    // Weak classifiers number in resulted cascade
-    int weaks;
-
-    // Feature random pool size
-    int poolSize;
-
-    // file name to store cascade
-    string cascadeName;
-
-    // path to resulting cascade
-    string outXmlPath;
-
-    // seed for random generation
-    int seed;
-
-    // channel feature type
-    string featureType;
-
-    // // bounding rectangle for actual example into example window
-    // cv::Rect exampleWindow;
-};
-
-// required for cv::FileStorage serialization
-void write(cv::FileStorage& fs, const string&, const Config& x);
-void read(const cv::FileNode& node, Config& x, const Config& default_value);
-std::ostream& operator<<(std::ostream& out, const Config& m);
-
-}
-
-#endif

apps/sft/include/sft/dataset.hpp

-/*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) 2008-2012, Willow Garage Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef __SFT_OCTAVE_HPP__
-#define __SFT_OCTAVE_HPP__
-
-#include <sft/common.hpp>
-namespace sft
-{
-
-using cv::softcascade::Dataset;
-
-class ScaledDataset : public Dataset
-{
-public:
-    ScaledDataset(const sft::string& path, const int octave);
-
-    virtual cv::Mat get(SampleType type, int idx) const;
-    virtual int available(SampleType type) const;
-    virtual ~ScaledDataset();
-
-private:
-    svector pos;
-    svector neg;
-};
-}
-
-#endif

apps/traincascade/CMakeLists.txt

-set(OPENCV_TRAINCASCADE_DEPS opencv_core opencv_ml opencv_imgproc opencv_photo opencv_objdetect opencv_highgui opencv_calib3d opencv_video opencv_features2d opencv_flann opencv_legacy)
+set(OPENCV_TRAINCASCADE_DEPS opencv_core opencv_ml opencv_imgproc opencv_photo opencv_objdetect opencv_highgui opencv_calib3d opencv_video opencv_features2d)
 ocv_check_dependencies(${OPENCV_TRAINCASCADE_DEPS})
 
 if(NOT OCV_DEPENDENCIES_FOUND)
@@ -20,7 +20,7 @@ set(traincascade_files traincascade.cpp
 
 set(the_target opencv_traincascade)
 add_executable(${the_target} ${traincascade_files})
-target_link_libraries(${the_target} ${OPENCV_TRAINCASCADE_DEPS} opencv_haartraining_engine)
+target_link_libraries(${the_target} ${OPENCV_TRAINCASCADE_DEPS})
 
 set_target_properties(${the_target} PROPERTIES
                       DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"

include/opencv/cv.h

@@ -65,8 +65,6 @@
 #include "opencv2/photo/photo_c.h"
 #include "opencv2/video/tracking_c.h"
 #include "opencv2/objdetect/objdetect_c.h"
-#include "opencv2/legacy.hpp"
-#include "opencv2/legacy/compat.hpp"
 
 #if !defined(CV_IMPL)
 #define CV_IMPL extern "C"

include/opencv2/opencv.hpp

@@ -51,7 +51,6 @@
 #include "opencv2/objdetect.hpp"
 #include "opencv2/calib3d.hpp"
 #include "opencv2/highgui.hpp"
-#include "opencv2/contrib.hpp"
 #include "opencv2/ml.hpp"
 
 #endif

modules/contrib/CMakeLists.txt

-ocv_define_module(contrib opencv_imgproc opencv_calib3d opencv_ml opencv_video opencv_objdetect OPTIONAL opencv_highgui opencv_nonfree)

modules/contrib/doc/contrib.rst

-***************************************
-contrib. Contributed/Experimental Stuff
-***************************************
-
-The module contains some recently added functionality that has not been stabilized, or functionality that is considered optional.
-
-.. toctree::
-    :maxdepth: 2
-
-    stereo
-    FaceRecognizer Documentation <facerec/index>
-    openfabmap

modules/contrib/doc/facerec/index.rst

-FaceRecognizer - Face Recognition with OpenCV
-##############################################
-
-OpenCV 2.4 now comes with the very new :ocv:class:`FaceRecognizer` class for face recognition. This documentation is going to explain you :doc:`the API <facerec_api>` in detail and it will give you a lot of help to get started (full source code examples). :doc:`Face Recognition with OpenCV <facerec_tutorial>` is the definite guide to the new :ocv:class:`FaceRecognizer`. There's also a :doc:`tutorial on gender classification <tutorial/facerec_gender_classification>`, a :doc:`tutorial for face recognition in videos <tutorial/facerec_video_recognition>` and it's shown :doc:`how to load & save your results <tutorial/facerec_save_load>`.
-
-These documents are the help I have wished for, when I was working myself into face recognition. I hope you also think the new :ocv:class:`FaceRecognizer` is a useful addition to OpenCV.
-
-Please issue any feature requests and/or bugs on the official OpenCV bug tracker at:
-
-  * http://code.opencv.org/projects/opencv/issues
-
-Contents
-========
-
-
-.. toctree::
-   :maxdepth: 1
-
-   FaceRecognizer API <facerec_api>
-   Guide to Face Recognition with OpenCV <facerec_tutorial>
-   Tutorial on Gender Classification <tutorial/facerec_gender_classification>
-   Tutorial on Face Recognition in Videos <tutorial/facerec_video_recognition>
-   Tutorial On Saving & Loading a FaceRecognizer <tutorial/facerec_save_load>
-   How to use Colormaps in OpenCV <colormaps>
-   Changelog <facerec_changelog>
-
-Indices and tables
-==================
-
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`