Merge pull request #13055 from vpisarev:remove_old_haar

modules/objdetect/include/opencv2/objdetect/objdetect_c.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.
-//
-//
-//                          License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
-// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#ifndef OPENCV_OBJDETECT_C_H
-#define OPENCV_OBJDETECT_C_H
-
-#include "opencv2/core/core_c.h"
-
-#ifdef __cplusplus
-#include <deque>
-#include <vector>
-
-extern "C" {
-#endif
-
-/** @addtogroup objdetect_c
-  @{
-  */
-
-/****************************************************************************************\
-*                         Haar-like Object Detection functions                           *
-\****************************************************************************************/
-
-#define CV_HAAR_MAGIC_VAL    0x42500000
-#define CV_TYPE_NAME_HAAR    "opencv-haar-classifier"
-
-#define CV_IS_HAAR_CLASSIFIER( haar )                                                    \
-    ((haar) != NULL &&                                                                   \
-    (((const CvHaarClassifierCascade*)(haar))->flags & CV_MAGIC_MASK)==CV_HAAR_MAGIC_VAL)
-
-#define CV_HAAR_FEATURE_MAX  3
-#define CV_HAAR_STAGE_MAX 1000
-
-typedef struct CvHaarFeature
-{
-    int tilted;
-    struct
-    {
-        CvRect r;
-        float weight;
-    } rect[CV_HAAR_FEATURE_MAX];
-} CvHaarFeature;
-
-typedef struct CvHaarClassifier
-{
-    int count;
-    CvHaarFeature* haar_feature;
-    float* threshold;
-    int* left;
-    int* right;
-    float* alpha;
-} CvHaarClassifier;
-
-typedef struct CvHaarStageClassifier
-{
-    int  count;
-    float threshold;
-    CvHaarClassifier* classifier;
-
-    int next;
-    int child;
-    int parent;
-} CvHaarStageClassifier;
-
-typedef struct CvHidHaarClassifierCascade CvHidHaarClassifierCascade;
-
-typedef struct CvHaarClassifierCascade
-{
-    int  flags;
-    int  count;
-    CvSize orig_window_size;
-    CvSize real_window_size;
-    double scale;
-    CvHaarStageClassifier* stage_classifier;
-    CvHidHaarClassifierCascade* hid_cascade;
-} CvHaarClassifierCascade;
-
-typedef struct CvAvgComp
-{
-    CvRect rect;
-    int neighbors;
-} CvAvgComp;
-
-/* Loads haar classifier cascade from a directory.
-   It is obsolete: convert your cascade to xml and use cvLoad instead */
-CVAPI(CvHaarClassifierCascade*) cvLoadHaarClassifierCascade(
-                    const char* directory, CvSize orig_window_size);
-
-CVAPI(void) cvReleaseHaarClassifierCascade( CvHaarClassifierCascade** cascade );
-
-#define CV_HAAR_DO_CANNY_PRUNING    1
-#define CV_HAAR_SCALE_IMAGE         2
-#define CV_HAAR_FIND_BIGGEST_OBJECT 4
-#define CV_HAAR_DO_ROUGH_SEARCH     8
-
-CVAPI(CvSeq*) cvHaarDetectObjects( const CvArr* image,
-                     CvHaarClassifierCascade* cascade, CvMemStorage* storage,
-                     double scale_factor CV_DEFAULT(1.1),
-                     int min_neighbors CV_DEFAULT(3), int flags CV_DEFAULT(0),
-                     CvSize min_size CV_DEFAULT(cvSize(0,0)), CvSize max_size CV_DEFAULT(cvSize(0,0)));
-
-/* sets images for haar classifier cascade */
-CVAPI(void) cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* cascade,
-                                                const CvArr* sum, const CvArr* sqsum,
-                                                const CvArr* tilted_sum, double scale );
-
-/* runs the cascade on the specified window */
-CVAPI(int) cvRunHaarClassifierCascade( const CvHaarClassifierCascade* cascade,
-                                       CvPoint pt, int start_stage CV_DEFAULT(0));
-
-/** @} objdetect_c */
-
-#ifdef __cplusplus
-}
-
-CV_EXPORTS CvSeq* cvHaarDetectObjectsForROC( const CvArr* image,
-                     CvHaarClassifierCascade* cascade, CvMemStorage* storage,
-                     std::vector<int>& rejectLevels, std::vector<double>& levelWeightds,
-                     double scale_factor = 1.1,
-                     int min_neighbors = 3, int flags = 0,
-                     CvSize min_size = cvSize(0, 0), CvSize max_size = cvSize(0, 0),
-                     bool outputRejectLevels = false );
-
-#endif
-
-#endif /* OPENCV_OBJDETECT_C_H */

modules/objdetect/src/cascadedetect.cpp

@@ -44,7 +44,6 @@
 #include <iostream>
 
 #include "cascadedetect.hpp"
-#include "opencv2/objdetect/objdetect_c.h"
 #include "opencl_kernels_objdetect.hpp"
 
 namespace cv
@@ -1071,9 +1070,6 @@ public:
 };
 
 
-struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
-struct getNeighbors { int operator ()(const CvAvgComp& e) const { return e.neighbors; } };
-
 #ifdef HAVE_OPENCL
 bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<float>& scales,
                                                             std::vector<Rect>& candidates )
@@ -1227,24 +1223,6 @@ void* CascadeClassifierImpl::getOldCascade()
     return oldCascade;
 }
 
-static void detectMultiScaleOldFormat( const Mat& image, Ptr<CvHaarClassifierCascade> oldCascade,
-                                       std::vector<Rect>& objects,
-                                       std::vector<int>& rejectLevels,
-                                       std::vector<double>& levelWeights,
-                                       std::vector<CvAvgComp>& vecAvgComp,
-                                       double scaleFactor, int minNeighbors,
-                                       int flags, Size minObjectSize, Size maxObjectSize,
-                                       bool outputRejectLevels = false )
-{
-    MemStorage storage(cvCreateMemStorage(0));
-    CvMat _image = cvMat(image);
-    CvSeq* _objects = cvHaarDetectObjectsForROC( &_image, oldCascade, storage, rejectLevels, levelWeights, scaleFactor,
-                                                 minNeighbors, flags, cvSize(minObjectSize), cvSize(maxObjectSize), outputRejectLevels );
-    Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
-    objects.resize(vecAvgComp.size());
-    std::transform(vecAvgComp.begin(), vecAvgComp.end(), objects.begin(), getRect());
-}
-
 void CascadeClassifierImpl::detectMultiScaleNoGrouping( InputArray _image, std::vector<Rect>& candidates,
                                                     std::vector<int>& rejectLevels, std::vector<double>& levelWeights,
                                                     double scaleFactor, Size minObjectSize, Size maxObjectSize,
@@ -1374,7 +1352,7 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
                                           std::vector<int>& rejectLevels,
                                           std::vector<double>& levelWeights,
                                           double scaleFactor, int minNeighbors,
-                                          int flags, Size minObjectSize, Size maxObjectSize,
+                                          int /*flags*/, Size minObjectSize, Size maxObjectSize,
                                           bool outputRejectLevels )
 {
     CV_INSTRUMENT_REGION();
@@ -1384,15 +1362,6 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
     if( empty() )
         return;
 
-    if( isOldFormatCascade() )
-    {
-        Mat image = _image.getMat();
-        std::vector<CvAvgComp> fakeVecAvgComp;
-        detectMultiScaleOldFormat( image, oldCascade, objects, rejectLevels, levelWeights, fakeVecAvgComp, scaleFactor,
-                                   minNeighbors, flags, minObjectSize, maxObjectSize, outputRejectLevels );
-    }
-    else
-    {
     detectMultiScaleNoGrouping( _image, objects, rejectLevels, levelWeights, scaleFactor, minObjectSize, maxObjectSize,
                                 outputRejectLevels );
     const double GROUP_EPS = 0.2;
@@ -1404,7 +1373,6 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
     {
         groupRectangles( objects, minNeighbors, GROUP_EPS );
     }
-    }
 }
 
 void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rect>& objects,
@@ -1421,7 +1389,7 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
 
 void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rect>& objects,
                                           std::vector<int>& numDetections, double scaleFactor,
-                                          int minNeighbors, int flags, Size minObjectSize,
+                                          int minNeighbors, int /*flags*/, Size minObjectSize,
                                           Size maxObjectSize )
 {
     CV_INSTRUMENT_REGION();
@@ -1434,20 +1402,10 @@ void CascadeClassifierImpl::detectMultiScale( InputArray _image, std::vector<Rec
 
     std::vector<int> fakeLevels;
     std::vector<double> fakeWeights;
-    if( isOldFormatCascade() )
-    {
-        std::vector<CvAvgComp> vecAvgComp;
-        detectMultiScaleOldFormat( image, oldCascade, objects, fakeLevels, fakeWeights, vecAvgComp, scaleFactor,
-                                   minNeighbors, flags, minObjectSize, maxObjectSize );
-        numDetections.resize(vecAvgComp.size());
-        std::transform(vecAvgComp.begin(), vecAvgComp.end(), numDetections.begin(), getNeighbors());
-    }
-    else
-    {
+
     detectMultiScaleNoGrouping( image, objects, fakeLevels, fakeWeights, scaleFactor, minObjectSize, maxObjectSize );
     const double GROUP_EPS = 0.2;
     groupRectangles( objects, numDetections, minNeighbors, GROUP_EPS );
-    }
 }
 
 
@@ -1613,9 +1571,6 @@ bool CascadeClassifierImpl::read_(const FileNode& root)
     return featureEvaluator->read(fn, data.origWinSize);
 }
 
-void DefaultDeleter<CvHaarClassifierCascade>::operator ()(CvHaarClassifierCascade* obj) const { cvReleaseHaarClassifierCascade(&obj); }
-
-
 BaseCascadeClassifier::~BaseCascadeClassifier()
 {
 }

modules/objdetect/src/haar.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.
-//
-//
-//                        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*/
-
-/* Haar features calculation */
-
-#ifndef OPENCV_OBJDETECT_HAAR_HPP
-#define OPENCV_OBJDETECT_HAAR_HPP
-
-#define CV_HAAR_FEATURE_MAX_LOCAL 3
-
-typedef int sumtype;
-typedef double sqsumtype;
-
-typedef struct CvHidHaarFeature
-{
-    struct
-    {
-        sumtype *p0, *p1, *p2, *p3;
-        float weight;
-    }
-    rect[CV_HAAR_FEATURE_MAX_LOCAL];
-} CvHidHaarFeature;
-
-
-typedef struct CvHidHaarTreeNode
-{
-    CvHidHaarFeature feature;
-    float threshold;
-    int left;
-    int right;
-} CvHidHaarTreeNode;
-
-
-typedef struct CvHidHaarClassifier
-{
-    int count;
-    //CvHaarFeature* orig_feature;
-    CvHidHaarTreeNode* node;
-    float* alpha;
-} CvHidHaarClassifier;
-
-#define calc_sumf(rect,offset) \
-    static_cast<float>((rect).p0[offset] - (rect).p1[offset] - (rect).p2[offset] + (rect).p3[offset])
-
-namespace cv_haar_avx
-{
-#if 0 /*CV_TRY_AVX*/
-    #define CV_HAAR_USE_AVX 1
-#else
-    #define CV_HAAR_USE_AVX 0
-#endif
-
-#if CV_HAAR_USE_AVX
-    // AVX version icvEvalHidHaarClassifier.  Process 8 CvHidHaarClassifiers per call. Check AVX support before invocation!!
-    double icvEvalHidHaarClassifierAVX(CvHidHaarClassifier* classifier, double variance_norm_factor, size_t p_offset);
-    double icvEvalHidHaarStumpClassifierAVX(CvHidHaarClassifier* classifier, double variance_norm_factor, size_t p_offset);
-    double icvEvalHidHaarStumpClassifierTwoRectAVX(CvHidHaarClassifier* classifier, double variance_norm_factor, size_t p_offset);
-#endif
-}
-
-#endif
-
-/* End of file. */

modules/objdetect/test/test_cascadeandhog.cpp

@@ -404,7 +404,6 @@ protected:
     virtual void readDetector( const FileNode& fn );
     virtual void writeDetector( FileStorage& fs, int di );
     virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects );
-    virtual int detectMultiScale_C( const string& filename, int di, const Mat& img, vector<Rect>& objects );
     vector<int> flags;
 };
 
@@ -434,36 +433,6 @@ void CV_CascadeDetectorTest::writeDetector( FileStorage& fs, int di )
     fs << C_SCALE_CASCADE << sc;
 }
 
-
-int CV_CascadeDetectorTest::detectMultiScale_C( const string& filename,
-                                                int di, const Mat& img,
-                                                vector<Rect>& objects )
-{
-    Ptr<CvHaarClassifierCascade> c_cascade(cvLoadHaarClassifierCascade(filename.c_str(), cvSize(0,0)));
-    Ptr<CvMemStorage> storage(cvCreateMemStorage());
-
-    if( !c_cascade )
-    {
-        ts->printf( cvtest::TS::LOG, "cascade %s can not be opened");
-        return cvtest::TS::FAIL_INVALID_TEST_DATA;
-    }
-    Mat grayImg;
-    cvtColor( img, grayImg, COLOR_BGR2GRAY );
-    equalizeHist( grayImg, grayImg );
-
-    CvMat c_gray = cvMat(grayImg);
-    CvSeq* rs = cvHaarDetectObjects(&c_gray, c_cascade, storage, 1.1, 3, flags[di] );
-
-    objects.clear();
-    for( int i = 0; i < rs->total; i++ )
-    {
-        Rect r = *(Rect*)cvGetSeqElem(rs, i);
-        objects.push_back(r);
-    }
-
-    return cvtest::TS::OK;
-}
-
 int CV_CascadeDetectorTest::detectMultiScale( int di, const Mat& img,
                                               vector<Rect>& objects)
 {
@@ -471,11 +440,6 @@ int CV_CascadeDetectorTest::detectMultiScale( int di, const Mat& img,
     filename = dataPath + detectorFilenames[di];
     const string pattern = "haarcascade_frontalface_default.xml";
 
-    if( filename.size() >= pattern.size() &&
-        strcmp(filename.c_str() + (filename.size() - pattern.size()),
-              pattern.c_str()) == 0 )
-        return detectMultiScale_C(filename, di, img, objects);
-
     CascadeClassifier cascade( filename );
     if( cascade.empty() )
     {

modules/objdetect/test/test_precomp.hpp

@@ -6,6 +6,5 @@
 
 #include "opencv2/ts.hpp"
 #include "opencv2/objdetect.hpp"
-#include "opencv2/objdetect/objdetect_c.h"
 
 #endif