Merge pull request #3348 from vpisarev:refactor_algorithms2

modules/calib3d/include/opencv2/calib3d.hpp

@@ -386,17 +386,19 @@ public:
 
     CV_WRAP virtual Rect getROI2() const = 0;
     CV_WRAP virtual void setROI2(Rect roi2) = 0;
-};
 
-CV_EXPORTS_W Ptr<StereoBM> createStereoBM(int numDisparities = 0, int blockSize = 21);
+    CV_WRAP static Ptr<StereoBM> create(int numDisparities = 0, int blockSize = 21);
+};
 
 
 class CV_EXPORTS_W StereoSGBM : public StereoMatcher
 {
 public:
-    enum { MODE_SGBM = 0,
-           MODE_HH   = 1
-         };
+    enum
+    {
+        MODE_SGBM = 0,
+        MODE_HH   = 1
+    };
 
     CV_WRAP virtual int getPreFilterCap() const = 0;
     CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
@@ -412,14 +414,13 @@ public:
 
     CV_WRAP virtual int getMode() const = 0;
     CV_WRAP virtual void setMode(int mode) = 0;
-};
-
 
-CV_EXPORTS_W Ptr<StereoSGBM> createStereoSGBM(int minDisparity, int numDisparities, int blockSize,
-                                            int P1 = 0, int P2 = 0, int disp12MaxDiff = 0,
-                                            int preFilterCap = 0, int uniquenessRatio = 0,
-                                            int speckleWindowSize = 0, int speckleRange = 0,
-                                            int mode = StereoSGBM::MODE_SGBM);
+    CV_WRAP static Ptr<StereoSGBM> create(int minDisparity, int numDisparities, int blockSize,
+                                          int P1 = 0, int P2 = 0, int disp12MaxDiff = 0,
+                                          int preFilterCap = 0, int uniquenessRatio = 0,
+                                          int speckleWindowSize = 0, int speckleRange = 0,
+                                          int mode = StereoSGBM::MODE_SGBM);
+};
 
 namespace fisheye
 {

modules/calib3d/perf/opencl/perf_stereobm.cpp

@@ -63,7 +63,7 @@ OCL_PERF_TEST_P(StereoBMFixture, StereoBM, ::testing::Combine(OCL_PERF_ENUM(32,
 
     declare.in(left, right);
 
-    Ptr<StereoBM> bm = createStereoBM( n_disp, winSize );
+    Ptr<StereoBM> bm = StereoBM::create( n_disp, winSize );
     bm->setPreFilterType(bm->PREFILTER_XSOBEL);
     bm->setTextureThreshold(0);
 

modules/calib3d/src/calib3d_init.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) 2009, 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 "precomp.hpp"
-
-using namespace cv;
-
-//////////////////////////////////////////////////////////////////////////////////////////////////////////
-
-
-//////////////////////////////////////////////////////////////////////////////////////////////////////////
-
-
-
-///////////////////////////////////////////////////////////////////////////////////////////////////////////
-
-#if 0
-bool cv::initModule_calib3d(void)
-{
-    bool all = true;
-    all &= !RANSACPointSetRegistrator_info_auto.name().empty();
-    all &= !LMeDSPointSetRegistrator_info_auto.name().empty();
-    all &= !LMSolverImpl_info_auto.name().empty();
-
-    return all;
-}
-#endif

modules/calib3d/src/compat_stereo.cpp

@@ -92,18 +92,18 @@ void cvFindStereoCorrespondenceBM( const CvArr* leftarr, const CvArr* rightarr,
 
     CV_Assert( state != 0 );
 
-    cv::Ptr<cv::StereoMatcher> sm = cv::createStereoBM(state->numberOfDisparities,
+    cv::Ptr<cv::StereoBM> sm = cv::StereoBM::create(state->numberOfDisparities,
                                                        state->SADWindowSize);
-    sm->set("preFilterType", state->preFilterType);
-    sm->set("preFilterSize", state->preFilterSize);
-    sm->set("preFilterCap", state->preFilterCap);
-    sm->set("SADWindowSize", state->SADWindowSize);
-    sm->set("numDisparities", state->numberOfDisparities > 0 ? state->numberOfDisparities : 64);
-    sm->set("textureThreshold", state->textureThreshold);
-    sm->set("uniquenessRatio", state->uniquenessRatio);
-    sm->set("speckleRange", state->speckleRange);
-    sm->set("speckleWindowSize", state->speckleWindowSize);
-    sm->set("disp12MaxDiff", state->disp12MaxDiff);
+    sm->setPreFilterType(state->preFilterType);
+    sm->setPreFilterSize(state->preFilterSize);
+    sm->setPreFilterCap(state->preFilterCap);
+    sm->setBlockSize(state->SADWindowSize);
+    sm->setNumDisparities(state->numberOfDisparities > 0 ? state->numberOfDisparities : 64);
+    sm->setTextureThreshold(state->textureThreshold);
+    sm->setUniquenessRatio(state->uniquenessRatio);
+    sm->setSpeckleRange(state->speckleRange);
+    sm->setSpeckleWindowSize(state->speckleWindowSize);
+    sm->setDisp12MaxDiff(state->disp12MaxDiff);
 
     sm->compute(left, right, disp);
 }

modules/calib3d/src/stereobm.cpp

@@ -1098,11 +1098,11 @@ public:
 
 const char* StereoBMImpl::name_ = "StereoMatcher.BM";
 
-}
-
-cv::Ptr<cv::StereoBM> cv::createStereoBM(int _numDisparities, int _SADWindowSize)
+Ptr<StereoBM> StereoBM::create(int _numDisparities, int _SADWindowSize)
 {
     return makePtr<StereoBMImpl>(_numDisparities, _SADWindowSize);
 }
 
+}
+
 /* End of file. */

modules/calib3d/src/stereosgbm.cpp

@@ -941,7 +941,7 @@ public:
 const char* StereoSGBMImpl::name_ = "StereoMatcher.SGBM";
 
 
-Ptr<StereoSGBM> createStereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
+Ptr<StereoSGBM> StereoSGBM::create(int minDisparity, int numDisparities, int SADWindowSize,
                                  int P1, int P2, int disp12MaxDiff,
                                  int preFilterCap, int uniquenessRatio,
                                  int speckleWindowSize, int speckleRange,

modules/calib3d/test/opencl/test_stereobm.cpp

@@ -79,7 +79,7 @@ PARAM_TEST_CASE(StereoBMFixture, int, int)
 
 OCL_TEST_P(StereoBMFixture, StereoBM)
 {
-    Ptr<StereoBM> bm = createStereoBM( n_disp, winSize);
+    Ptr<StereoBM> bm = StereoBM::create( n_disp, winSize);
     bm->setPreFilterType(bm->PREFILTER_XSOBEL);
     bm->setTextureThreshold(0);
 

modules/calib3d/test/test_stereomatching.cpp

@@ -717,7 +717,7 @@ protected:
         Mat leftImg; cvtColor( _leftImg, leftImg, COLOR_BGR2GRAY );
         Mat rightImg; cvtColor( _rightImg, rightImg, COLOR_BGR2GRAY );
 
-        Ptr<StereoBM> bm = createStereoBM( params.ndisp, params.winSize );
+        Ptr<StereoBM> bm = StereoBM::create( params.ndisp, params.winSize );
         Mat tempDisp;
         bm->compute( leftImg, rightImg, tempDisp );
         tempDisp.convertTo(leftDisp, CV_32F, 1./StereoMatcher::DISP_SCALE);
@@ -770,7 +770,7 @@ protected:
     {
         RunParams params = caseRunParams[caseIdx];
         assert( params.ndisp%16 == 0 );
-        Ptr<StereoSGBM> sgbm = createStereoSGBM( 0, params.ndisp, params.winSize,
+        Ptr<StereoSGBM> sgbm = StereoSGBM::create( 0, params.ndisp, params.winSize,
                                                  10*params.winSize*params.winSize,
                                                  40*params.winSize*params.winSize,
                                                  1, 63, 10, 100, 32, params.fullDP ?

modules/core/include/opencv2/core.hpp

@@ -874,9 +874,6 @@ public:
     virtual ~Algorithm();
     String name() const;
 
-    virtual void set(int, double);
-    virtual double get(int) const;
-
     template<typename _Tp> typename ParamType<_Tp>::member_type get(const String& name) const;
     template<typename _Tp> typename ParamType<_Tp>::member_type get(const char* name) const;
 

modules/core/src/algorithm.cpp

@@ -179,9 +179,6 @@ String Algorithm::name() const
     return info()->name();
 }
 
-void Algorithm::set(int, double) {}
-double Algorithm::get(int) const { return 0.; }
-
 void Algorithm::set(const String& parameter, int value)
 {
     info()->set(this, parameter.c_str(), ParamType<int>::type, &value);

modules/features2d/include/opencv2/features2d.hpp

@@ -163,17 +163,37 @@ public:
 class CV_EXPORTS_W ORB : public Feature2D
 {
 public:
-    // the size of the signature in bytes
-    enum
-    {
-        kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1,
-        NFEATURES=10000, SCALE_FACTOR=10001, NLEVELS=10002,
-        EDGE_THRESHOLD=10003, FIRST_LEVEL=10004, WTA_K=10005,
-        SCORE_TYPE=10006, PATCH_SIZE=10007, FAST_THRESHOLD=10008
-    };
+    enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
+
+    CV_WRAP static Ptr<ORB> create(int nfeatures=500, float scaleFactor=1.2f, int nlevels=8, int edgeThreshold=31,
+        int firstLevel=0, int WTA_K=2, int scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold=20);
+
+    CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0;
+    CV_WRAP virtual int getMaxFeatures() const = 0;
+
+    CV_WRAP virtual void setScaleFactor(double scaleFactor) = 0;
+    CV_WRAP virtual double getScaleFactor() const = 0;
+
+    CV_WRAP virtual void setNLevels(int nlevels) = 0;
+    CV_WRAP virtual int getNLevels() const = 0;
+
+    CV_WRAP virtual void setEdgeThreshold(int edgeThreshold) = 0;
+    CV_WRAP virtual int getEdgeThreshold() const = 0;
+
+    CV_WRAP virtual void setFirstLevel(int firstLevel) = 0;
+    CV_WRAP virtual int getFirstLevel() const = 0;
+
+    CV_WRAP virtual void setWTA_K(int wta_k) = 0;
+    CV_WRAP virtual int getWTA_K() const = 0;
+
+    CV_WRAP virtual void setScoreType(int scoreType) = 0;
+    CV_WRAP virtual int getScoreType() const = 0;
 
-    CV_WRAP static Ptr<ORB> create(int nfeatures = 500, float scaleFactor = 1.2f, int nlevels = 8, int edgeThreshold = 31,
-        int firstLevel = 0, int WTA_K=2, int scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold = 20);
+    CV_WRAP virtual void setPatchSize(int patchSize) = 0;
+    CV_WRAP virtual int getPatchSize() const = 0;
+
+    CV_WRAP virtual void setFastThreshold(int fastThreshold) = 0;
+    CV_WRAP virtual int getFastThreshold() const = 0;
 };
 
 /*!
@@ -188,13 +208,6 @@ public:
 class CV_EXPORTS_W MSER : public Feature2D
 {
 public:
-    enum
-    {
-        DELTA=10000, MIN_AREA=10001, MAX_AREA=10002, PASS2_ONLY=10003,
-        MAX_EVOLUTION=10004, AREA_THRESHOLD=10005,
-        MIN_MARGIN=10006, EDGE_BLUR_SIZE=10007
-    };
-
     //! the full constructor
     CV_WRAP static Ptr<MSER> create( int _delta=5, int _min_area=60, int _max_area=14400,
           double _max_variation=0.25, double _min_diversity=.2,
@@ -204,6 +217,18 @@ public:
     CV_WRAP virtual void detectRegions( InputArray image,
                                         std::vector<std::vector<Point> >& msers,
                                         std::vector<Rect>& bboxes ) = 0;
+
+    CV_WRAP virtual void setDelta(int delta) = 0;
+    CV_WRAP virtual int getDelta() const = 0;
+
+    CV_WRAP virtual void setMinArea(int minArea) = 0;
+    CV_WRAP virtual int getMinArea() const = 0;
+
+    CV_WRAP virtual void setMaxArea(int maxArea) = 0;
+    CV_WRAP virtual int getMaxArea() const = 0;
+
+    CV_WRAP virtual void setPass2Only(bool f) = 0;
+    CV_WRAP virtual bool getPass2Only() const = 0;
 };
 
 //! detects corners using FAST algorithm by E. Rosten
@@ -225,15 +250,40 @@ public:
     CV_WRAP static Ptr<FastFeatureDetector> create( int threshold=10,
                                                     bool nonmaxSuppression=true,
                                                     int type=FastFeatureDetector::TYPE_9_16 );
+
+    CV_WRAP virtual void setThreshold(int threshold) = 0;
+    CV_WRAP virtual int getThreshold() const = 0;
+
+    CV_WRAP virtual void setNonmaxSuppression(bool f) = 0;
+    CV_WRAP virtual bool getNonmaxSuppression() const = 0;
+
+    CV_WRAP virtual void setType(int type) = 0;
+    CV_WRAP virtual int getType() const = 0;
 };
 
 
 class CV_EXPORTS_W GFTTDetector : public Feature2D
 {
 public:
-    enum { USE_HARRIS_DETECTOR=10000 };
     CV_WRAP static Ptr<GFTTDetector> create( int maxCorners=1000, double qualityLevel=0.01, double minDistance=1,
                                              int blockSize=3, bool useHarrisDetector=false, double k=0.04 );
+    CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0;
+    CV_WRAP virtual int getMaxFeatures() const = 0;
+
+    CV_WRAP virtual void setQualityLevel(double qlevel) = 0;
+    CV_WRAP virtual double getQualityLevel() const = 0;
+
+    CV_WRAP virtual void setMinDistance(double minDistance) = 0;
+    CV_WRAP virtual double getMinDistance() const = 0;
+
+    CV_WRAP virtual void setBlockSize(int blockSize) = 0;
+    CV_WRAP virtual int getBlockSize() const = 0;
+
+    CV_WRAP virtual void setHarrisDetector(bool val) = 0;
+    CV_WRAP virtual bool getHarrisDetector() const = 0;
+
+    CV_WRAP virtual void setK(double k) = 0;
+    CV_WRAP virtual double getK() const = 0;
 };
 
 
@@ -289,8 +339,26 @@ public:
 
     CV_WRAP static Ptr<KAZE> create(bool extended=false, bool upright=false,
                                     float threshold = 0.001f,
-                                    int octaves = 4, int sublevels = 4,
+                                    int nOctaves = 4, int nOctaveLayers = 4,
                                     int diffusivity = KAZE::DIFF_PM_G2);
+
+    CV_WRAP virtual void setExtended(bool extended) = 0;
+    CV_WRAP virtual bool getExtended() const = 0;
+
+    CV_WRAP virtual void setUpright(bool upright) = 0;
+    CV_WRAP virtual bool getUpright() const = 0;
+
+    CV_WRAP virtual void setThreshold(double threshold) = 0;
+    CV_WRAP virtual double getThreshold() const = 0;
+
+    CV_WRAP virtual void setNOctaves(int octaves) = 0;
+    CV_WRAP virtual int getNOctaves() const = 0;
+
+    CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0;
+    CV_WRAP virtual int getNOctaveLayers() const = 0;
+
+    CV_WRAP virtual void setDiffusivity(int diff) = 0;
+    CV_WRAP virtual int getDiffusivity() const = 0;
 };
 
 /*!
@@ -310,8 +378,29 @@ public:
 
     CV_WRAP static Ptr<AKAZE> create(int descriptor_type=AKAZE::DESCRIPTOR_MLDB,
                                      int descriptor_size = 0, int descriptor_channels = 3,
-                                     float threshold = 0.001f, int octaves = 4,
-                                     int sublevels = 4, int diffusivity = KAZE::DIFF_PM_G2);
+                                     float threshold = 0.001f, int nOctaves = 4,
+                                     int nOctaveLayers = 4, int diffusivity = KAZE::DIFF_PM_G2);
+
+    CV_WRAP virtual void setDescriptorType(int dtype) = 0;
+    CV_WRAP virtual int getDescriptorType() const = 0;
+
+    CV_WRAP virtual void setDescriptorSize(int dsize) = 0;
+    CV_WRAP virtual int getDescriptorSize() const = 0;
+
+    CV_WRAP virtual void setDescriptorChannels(int dch) = 0;
+    CV_WRAP virtual int getDescriptorChannels() const = 0;
+
+    CV_WRAP virtual void setThreshold(double threshold) = 0;
+    CV_WRAP virtual double getThreshold() const = 0;
+
+    CV_WRAP virtual void setNOctaves(int octaves) = 0;
+    CV_WRAP virtual int getNOctaves() const = 0;
+
+    CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0;
+    CV_WRAP virtual int getNOctaveLayers() const = 0;
+
+    CV_WRAP virtual void setDiffusivity(int diff) = 0;
+    CV_WRAP virtual int getDiffusivity() const = 0;
 };
 
 /****************************************************************************************\

modules/features2d/src/akaze.cpp

@@ -77,6 +77,27 @@ namespace cv
 
         }
 
+        void setDescriptorType(int dtype) { descriptor = dtype; }
+        int getDescriptorType() const { return descriptor; }
+
+        void setDescriptorSize(int dsize) { descriptor_size = dsize; }
+        int getDescriptorSize() const { return descriptor_size; }
+
+        void setDescriptorChannels(int dch) { descriptor_channels = dch; }
+        int getDescriptorChannels() const { return descriptor_channels; }
+
+        void setThreshold(double threshold_) { threshold = (float)threshold_; }
+        double getThreshold() const { return threshold; }
+
+        void setNOctaves(int octaves_) { octaves = octaves_; }
+        int getNOctaves() const { return octaves; }
+
+        void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
+        int getNOctaveLayers() const { return sublevels; }
+
+        void setDiffusivity(int diff_) { diffusivity = diff_; }
+        int getDiffusivity() const { return diffusivity; }
+
         // returns the descriptor size in bytes
         int descriptorSize() const
         {

modules/features2d/src/brisk.cpp

@@ -2099,7 +2099,7 @@ BriskLayer::BriskLayer(const BriskLayer& layer, int mode)
 void
 BriskLayer::getAgastPoints(int threshold, std::vector<KeyPoint>& keypoints)
 {
-  fast_9_16_->set(FastFeatureDetector::THRESHOLD, threshold);
+  fast_9_16_->setThreshold(threshold);
   fast_9_16_->detect(img_, keypoints);
 
   // also write scores

modules/features2d/src/fast.cpp

@@ -407,6 +407,15 @@ public:
         return 0;
     }
 
+    void setThreshold(int threshold_) { threshold = threshold_; }
+    int getThreshold() const { return threshold; }
+
+    void setNonmaxSuppression(bool f) { nonmaxSuppression = f; }
+    bool getNonmaxSuppression() const { return nonmaxSuppression; }
+
+    void setType(int type_) { type = type_; }
+    int getType() const { return type; }
+
     int threshold;
     bool nonmaxSuppression;
     int type;

modules/features2d/src/gftt.cpp

@@ -55,23 +55,23 @@ public:
     {
     }
 
-    void set(int prop, double value)
-    {
-        if( prop == USE_HARRIS_DETECTOR )
-            useHarrisDetector = value != 0;
-        else
-            CV_Error(Error::StsBadArg, "");
-    }
+    void setMaxFeatures(int maxFeatures) { nfeatures = maxFeatures; }
+    int getMaxFeatures() const { return nfeatures; }
 
-    double get(int prop) const
-    {
-        double value = 0;
-        if( prop == USE_HARRIS_DETECTOR )
-            value = useHarrisDetector;
-        else
-            CV_Error(Error::StsBadArg, "");
-        return value;
-    }
+    void setQualityLevel(double qlevel) { qualityLevel = qlevel; }
+    double getQualityLevel() const { return qualityLevel; }
+
+    void setMinDistance(double minDistance_) { minDistance = minDistance_; }
+    double getMinDistance() const { return minDistance; }
+
+    void setBlockSize(int blockSize_) { blockSize = blockSize_; }
+    int getBlockSize() const { return blockSize; }
+
+    void setHarrisDetector(bool val) { useHarrisDetector = val; }
+    bool getHarrisDetector() const { return useHarrisDetector; }
+
+    void setK(double k_) { k = k_; }
+    double getK() const { return k; }
 
     void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask )
     {

modules/features2d/src/kaze.cpp

@@ -69,6 +69,24 @@ namespace cv
 
         virtual ~KAZE_Impl() {}
 
+        void setExtended(bool extended_) { extended = extended_; }
+        bool getExtended() const { return extended; }
+
+        void setUpright(bool upright_) { upright = upright_; }
+        bool getUpright() const { return upright; }
+
+        void setThreshold(double threshold_) { threshold = (float)threshold_; }
+        double getThreshold() const { return threshold; }
+
+        void setNOctaves(int octaves_) { octaves = octaves_; }
+        int getNOctaves() const { return octaves; }
+
+        void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
+        int getNOctaveLayers() const { return sublevels; }
+
+        void setDiffusivity(int diff_) { diffusivity = diff_; }
+        int getDiffusivity() const { return diffusivity; }
+
         // returns the descriptor size in bytes
         int descriptorSize() const
         {

modules/features2d/src/mser.cpp

@@ -86,35 +86,17 @@ public:
 
     virtual ~MSER_Impl() {}
 
-    void set(int propId, double value)
-    {
-        if( propId == DELTA )
-            params.delta = cvRound(value);
-        else if( propId == MIN_AREA )
-            params.minArea = cvRound(value);
-        else if( propId == MAX_AREA )
-            params.maxArea = cvRound(value);
-        else if( propId == PASS2_ONLY )
-            params.pass2Only = value != 0;
-        else
-            CV_Error(CV_StsBadArg, "Unknown parameter id");
-    }
+    void setDelta(int delta) { params.delta = delta; }
+    int getDelta() const { return params.delta; }
 
-    double get(int propId) const
-    {
-        double value = 0;
-        if( propId == DELTA )
-            value = params.delta;
-        else if( propId == MIN_AREA )
-            value = params.minArea;
-        else if( propId == MAX_AREA )
-            value = params.maxArea;
-        else if( propId == PASS2_ONLY )
-            value = params.pass2Only;
-        else
-            CV_Error(CV_StsBadArg, "Unknown parameter id");
-        return value;
-    }
+    void setMinArea(int minArea) { params.minArea = minArea; }
+    int getMinArea() const { return params.minArea; }
+
+    void setMaxArea(int maxArea) { params.maxArea = maxArea; }
+    int getMaxArea() const { return params.maxArea; }
+
+    void setPass2Only(bool f) { params.pass2Only = f; }
+    bool getPass2Only() const { return params.pass2Only; }
 
     enum { DIR_SHIFT = 29, NEXT_MASK = ((1<<DIR_SHIFT)-1)  };
 

modules/features2d/src/orb.cpp

@@ -660,55 +660,32 @@ public:
         scoreType(_scoreType), patchSize(_patchSize), fastThreshold(_fastThreshold)
     {}
 
-    void set(int prop, double value)
-    {
-        if( prop == NFEATURES )
-            nfeatures = cvRound(value);
-        else if( prop == SCALE_FACTOR )
-            scaleFactor = value;
-        else if( prop == NLEVELS )
-            nlevels = cvRound(value);
-        else if( prop == EDGE_THRESHOLD )
-            edgeThreshold = cvRound(value);
-        else if( prop == FIRST_LEVEL )
-            firstLevel = cvRound(value);
-        else if( prop == WTA_K )
-            wta_k = cvRound(value);
-        else if( prop == SCORE_TYPE )
-            scoreType = cvRound(value);
-        else if( prop == PATCH_SIZE )
-            patchSize = cvRound(value);
-        else if( prop == FAST_THRESHOLD )
-            fastThreshold = cvRound(value);
-        else
-            CV_Error(Error::StsBadArg, "");
-    }
+    void setMaxFeatures(int maxFeatures) { nfeatures = maxFeatures; }
+    int getMaxFeatures() const { return nfeatures; }
 
-    double get(int prop) const
-    {
-        double value = 0;
-        if( prop == NFEATURES )
-            value = nfeatures;
-        else if( prop == SCALE_FACTOR )
-            value = scaleFactor;
-        else if( prop == NLEVELS )
-            value = nlevels;
-        else if( prop == EDGE_THRESHOLD )
-            value = edgeThreshold;
-        else if( prop == FIRST_LEVEL )
-            value = firstLevel;
-        else if( prop == WTA_K )
-            value = wta_k;
-        else if( prop == SCORE_TYPE )
-            value = scoreType;
-        else if( prop == PATCH_SIZE )
-            value = patchSize;
-        else if( prop == FAST_THRESHOLD )
-            value = fastThreshold;
-        else
-            CV_Error(Error::StsBadArg, "");
-        return value;
-    }
+    void setScaleFactor(double scaleFactor_) { scaleFactor = scaleFactor_; }
+    double getScaleFactor() const { return scaleFactor; }
+
+    void setNLevels(int nlevels_) { nlevels = nlevels_; }
+    int getNLevels() const { return nlevels; }
+
+    void setEdgeThreshold(int edgeThreshold_) { edgeThreshold = edgeThreshold_; }
+    int getEdgeThreshold() const { return edgeThreshold; }
+
+    void setFirstLevel(int firstLevel_) { firstLevel = firstLevel_; }
+    int getFirstLevel() const { return firstLevel; }
+
+    void setWTA_K(int wta_k_) { wta_k = wta_k_; }
+    int getWTA_K() const { return wta_k; }
+
+    void setScoreType(int scoreType_) { scoreType = scoreType_; }
+    int getScoreType() const { return scoreType; }
+
+    void setPatchSize(int patchSize_) { patchSize = patchSize_; }
+    int getPatchSize() const { return patchSize; }
+
+    void setFastThreshold(int fastThreshold_) { fastThreshold = fastThreshold_; }
+    int getFastThreshold() const { return fastThreshold; }
 
     // returns the descriptor size in bytes
     int descriptorSize() const;

modules/features2d/test/test_descriptors_regression.cpp

@@ -255,8 +255,8 @@ protected:
             fs.open( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::WRITE );
             if( fs.isOpened() )
             {
-                ORB fd;
-                fd.detect(img, keypoints);
+                Ptr<ORB> fd = ORB::create();
+                fd->detect(img, keypoints);
                 write( fs, "keypoints", keypoints );
             }
             else

modules/features2d/test/test_detectors_regression.cpp

@@ -267,8 +267,8 @@ TEST( Features2d_Detector_GFTT, regression )
 
 TEST( Features2d_Detector_Harris, regression )
 {
-    Ptr<FeatureDetector> gftt = GFTTDetector::create();
-    gftt->set(GFTTDetector::USE_HARRIS_DETECTOR, 1);
+    Ptr<GFTTDetector> gftt = GFTTDetector::create();
+    gftt->setHarrisDetector(true);
     CV_FeatureDetectorTest test( "detector-harris", gftt);
     test.safe_run();
 }

modules/features2d/test/test_keypoints.cpp

@@ -140,8 +140,8 @@ TEST(Features2d_Detector_Keypoints_HARRIS, validation)
 
 TEST(Features2d_Detector_Keypoints_GFTT, validation)
 {
-    Ptr<FeatureDetector> gftt = GFTTDetector::create();
-    gftt->set(GFTTDetector::USE_HARRIS_DETECTOR, 1);
+    Ptr<GFTTDetector> gftt = GFTTDetector::create();
+    gftt->setHarrisDetector(true);
     CV_FeatureDetectorKeypointsTest test(gftt);
     test.safe_run();
 }

modules/java/generator/src/cpp/features2d_manual.hpp

@@ -132,8 +132,11 @@ public:
             fd = GFTTDetector::create();
             break;
         case HARRIS:
-            fd = GFTTDetector::create();
-            fd->set(GFTTDetector::USE_HARRIS_DETECTOR, 1);
+            {
+            Ptr<GFTTDetector> gftt = GFTTDetector::create();
+            gftt->setHarrisDetector(true);
+            fd = gftt;
+            }
             break;
         case SIMPLEBLOB:
             fd = SimpleBlobDetector::create();

modules/java/generator/src/cpp/jni_part.cpp

@@ -23,14 +23,6 @@ JNI_OnLoad(JavaVM* vm, void* )
     if (vm->GetEnv((void**) &env, JNI_VERSION_1_6) != JNI_OK)
         return -1;
 
-    bool init = true;
-#ifdef HAVE_OPENCV_VIDEO
-    init &= cv::initModule_video();
-#endif
-
-    if(!init)
-        return -1;
-
     /* get class with (*env)->FindClass */
     /* register methods with (*env)->RegisterNatives */
 

modules/ml/src/svm.cpp

@@ -1728,6 +1728,9 @@ public:
         FOR_IN_GRID(coef0, coef_grid)
         FOR_IN_GRID(degree, degree_grid)
         {
+            // make sure we updated the kernel and other parameters
+            setParams(params, Ptr<Kernel>() );
+
             double error = 0;
             for( k = 0; k < k_fold; k++ )
             {

modules/stitching/src/matchers.cpp

@@ -323,27 +323,31 @@ SurfFeaturesFinder::SurfFeaturesFinder(double hess_thresh, int num_octaves, int
 #ifdef HAVE_OPENCV_XFEATURES2D
     if (num_octaves_descr == num_octaves && num_layers_descr == num_layers)
     {
-        surf = SURF::create();
-        if( !surf )
+        Ptr<SURF> surf_ = SURF::create();
+        if( !surf_ )
             CV_Error( Error::StsNotImplemented, "OpenCV was built without SURF support" );
-        surf->set(SURF::HESSIAN_THRESHOLD, hess_thresh);
-        surf->set(SURF::NOCTAVES, num_octaves);
-        surf->set(SURF::NOCTAVE_LAYERS, num_layers);
+        surf_->setHessianThreshold(hess_thresh);
+        surf_->setNOctaves(num_octaves);
+        surf_->setNOctaveLayers(num_layers);
+        surf = surf_;
     }
     else
     {
-        detector_ = SURF::create();
-        extractor_ = SURF::create();
+        Ptr<SURF> sdetector_ = SURF::create();
+        Ptr<SURF> sextractor_ = SURF::create();
 
-        if( !detector_ || !extractor_ )
+        if( !sdetector_ || !sextractor_ )
             CV_Error( Error::StsNotImplemented, "OpenCV was built without SURF support" );
 
-        detector_->set(SURF::HESSIAN_THRESHOLD, hess_thresh);
-        detector_->set(SURF::NOCTAVES, num_octaves);
-        detector_->set(SURF::NOCTAVE_LAYERS, num_layers);
+        sdetector_->setHessianThreshold(hess_thresh);
+        sdetector_->setNOctaves(num_octaves);
+        sdetector_->setNOctaveLayers(num_layers);
 
-        extractor_->set(SURF::NOCTAVES, num_octaves_descr);
-        extractor_->set(SURF::NOCTAVE_LAYERS, num_layers_descr);
+        sextractor_->setNOctaves(num_octaves_descr);
+        sextractor_->setNOctaveLayers(num_layers_descr);
+
+        detector_ = sdetector_;
+        extractor_ = sextractor_;
     }
 #else
     CV_Error( Error::StsNotImplemented, "OpenCV was built without SURF support" );

modules/video/include/opencv2/video.hpp

@@ -47,9 +47,4 @@
 #include "opencv2/video/tracking.hpp"
 #include "opencv2/video/background_segm.hpp"
 
-namespace cv
-{
-CV_EXPORTS bool initModule_video(void);
-}
-
 #endif //__OPENCV_VIDEO_HPP__

modules/video/src/video_init.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) 2009, 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 "precomp.hpp"
-#include "opencv2/video.hpp"
-
-namespace cv
-{
-
-bool initModule_video(void)
-{
-    return true;
-}
-
-}

modules/world/src/world_init.cpp

@@ -44,9 +44,5 @@
 
 bool cv::initAll()
 {
-    return true
-#ifdef HAVE_OPENCV_VIDEO
-    && initModule_video()
-#endif
-    ;
+    return true;
 }

samples/cpp/stereo_match.cpp

@@ -67,8 +67,8 @@ int main(int argc, char** argv)
     bool no_display = false;
     float scale = 1.f;
 
-    Ptr<StereoBM> bm = createStereoBM(16,9);
-    Ptr<StereoSGBM> sgbm = createStereoSGBM(0,16,3);
+    Ptr<StereoBM> bm = StereoBM::create(16,9);
+    Ptr<StereoSGBM> sgbm = StereoSGBM::create(0,16,3);
 
     for( int i = 1; i < argc; i++ )
     {

samples/cpp/tutorial_code/calib3d/stereoBM/SBM_Sample.cpp

@@ -40,7 +40,7 @@ int main( int argc, char** argv )
   int ndisparities = 16*5;   /**< Range of disparity */
   int SADWindowSize = 21; /**< Size of the block window. Must be odd */
 
-  Ptr<StereoBM> sbm = createStereoBM( ndisparities, SADWindowSize );
+  Ptr<StereoBM> sbm = StereoBM::create( ndisparities, SADWindowSize );
 
   //-- 3. Calculate the disparity image
   sbm->compute( imgLeft, imgRight, imgDisparity16S );

samples/cpp/tutorial_code/features2D/AKAZE_tracking/planar_tracking.cpp

@@ -135,18 +135,19 @@ int main(int argc, char **argv)
         return 1;
     }
     fs["bounding_box"] >> bb;
-    Ptr<Feature2D> akaze = AKAZE::create();
+
+    Stats stats, akaze_stats, orb_stats;
+    Ptr<AKAZE> akaze = AKAZE::create();
     akaze->set("threshold", akaze_thresh);
-    Ptr<Feature2D> orb = ORB::create();
+    Ptr<ORB> orb = ORB::create();
+    orb->setMaxFeatures(stats.keypoints);
     Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-Hamming");
     Tracker akaze_tracker(akaze, matcher);
     Tracker orb_tracker(orb, matcher);
 
-    Stats stats, akaze_stats, orb_stats;
     Mat frame;
     video_in >> frame;
     akaze_tracker.setFirstFrame(frame, bb, "AKAZE", stats);
-    orb_tracker.getDetector()->set("nFeatures", stats.keypoints);
     orb_tracker.setFirstFrame(frame, bb, "ORB", stats);
 
     Stats akaze_draw_stats, orb_draw_stats;