From 1e69bd5118ef41b10ad315e9d13f8556be06eec4 Mon Sep 17 00:00:00 2001
From: Alexey Kazakov <no@email>
Date: Fri, 22 Apr 2011 16:11:35 +0000
Subject: [PATCH] class MeanshiftGrouping replaced from objdetect.hpp to
 cascadedetect.cpp

---
 .../include/opencv2/objdetect/objdetect.hpp   |  31 ---
 modules/objdetect/src/cascadedetect.cpp       | 148 +++++++++++++++
 modules/objdetect/src/ms_grouping.cpp         | 177 ------------------
 3 files changed, 148 insertions(+), 208 deletions(-)
 delete mode 100644 modules/objdetect/src/ms_grouping.cpp

diff --git a/modules/objdetect/include/opencv2/objdetect/objdetect.hpp b/modules/objdetect/include/opencv2/objdetect/objdetect.hpp
index cc0e85c61..34cc5885a 100644
--- a/modules/objdetect/include/opencv2/objdetect/objdetect.hpp
+++ b/modules/objdetect/include/opencv2/objdetect/objdetect.hpp
@@ -297,37 +297,6 @@ CV_EXPORTS void groupRectangles(vector<Rect>& rectList, vector<int>& rejectLevel
 CV_EXPORTS void groupRectangles_meanshift(vector<Rect>& rectList, vector<double>& foundWeights, vector<double>& foundScales, 
 										  double detectThreshold = 0.0, Size winDetSize = Size(64, 128));
 
-class MeanshiftGrouping
-{
-public:
-	MeanshiftGrouping(const Point3d& densKer, const vector<Point3d>& posV, 
-		const vector<double>& wV, double modeEps = 1e-4,
-		int maxIt = 20);
-	
-	void getModes(vector<Point3d>& modesV, vector<double>& resWeightsV, const double eps); 
-
-protected:
-	vector<Point3d> positionsV;
-	vector<double> weightsV;
-
-	Point3d densityKernel;
-	int positionsCount;
-
-	vector<Point3d> meanshiftV;
-	vector<Point3d> distanceV;
-	int iterMax;
-	double modeEps;
-
-	Point3d getNewValue(const Point3d& inPt) const;
-
-	double getResultWeight(const Point3d& inPt) const; 
-
-	Point3d moveToMode(Point3d aPt) const; 
-
-	double getDistance(Point3d p1, Point3d p2) const; 
-};
-
-
         
 class CV_EXPORTS FeatureEvaluator
 {
diff --git a/modules/objdetect/src/cascadedetect.cpp b/modules/objdetect/src/cascadedetect.cpp
index e36d67040..788784f76 100644
--- a/modules/objdetect/src/cascadedetect.cpp
+++ b/modules/objdetect/src/cascadedetect.cpp
@@ -164,6 +164,154 @@ static void groupRectangles(vector<Rect>& rectList, int groupThreshold, double e
     }
 }
 
+class MeanshiftGrouping
+{
+public:
+	MeanshiftGrouping(const Point3d& densKer, const vector<Point3d>& posV, 
+		const vector<double>& wV, double modeEps = 1e-4, int maxIter = 20)
+    {
+	    densityKernel = densKer;
+        weightsV = wV;
+        positionsV = posV;
+        positionsCount = posV.size();
+	    meanshiftV.resize(positionsCount);
+        distanceV.resize(positionsCount);
+        modeEps = modeEps;
+	    iterMax = maxIter;
+        
+	    for (unsigned i = 0; i<positionsV.size(); i++)
+	    {
+		    meanshiftV[i] = getNewValue(positionsV[i]);
+
+		    distanceV[i] = moveToMode(meanshiftV[i]);
+
+		    meanshiftV[i] -= positionsV[i];
+	    }
+    }
+	
+	void getModes(vector<Point3d>& modesV, vector<double>& resWeightsV, const double eps)
+    {
+	    for (size_t i=0; i <distanceV.size(); i++)
+	    {
+		    bool is_found = false;
+		    for(size_t j=0; j<modesV.size(); j++)
+		    {
+			    if ( getDistance(distanceV[i], modesV[j]) < eps)
+			    {
+				    is_found=true;
+				    break;
+			    }
+		    }
+		    if (!is_found)
+		    {
+			    modesV.push_back(distanceV[i]);
+		    }
+	    }
+    	
+	    resWeightsV.resize(modesV.size());
+
+	    for (size_t i=0; i<modesV.size(); i++)
+	    {
+		    resWeightsV[i] = getResultWeight(modesV[i]);
+	    }
+    }
+
+protected:
+	vector<Point3d> positionsV;
+	vector<double> weightsV;
+
+	Point3d densityKernel;
+	int positionsCount;
+
+	vector<Point3d> meanshiftV;
+	vector<Point3d> distanceV;
+	int iterMax;
+	double modeEps;
+
+	Point3d getNewValue(const Point3d& inPt) const
+    {
+	    Point3d resPoint(.0);
+	    Point3d ratPoint(.0);
+	    for (size_t i=0; i<positionsV.size(); i++)
+	    {
+		    Point3d aPt= positionsV[i];
+		    Point3d bPt = inPt;
+		    Point3d sPt = densityKernel;
+    		
+		    sPt.x *= exp(aPt.z);
+		    sPt.y *= exp(aPt.z);
+    		
+		    aPt.x /= sPt.x;
+		    aPt.y /= sPt.y;
+		    aPt.z /= sPt.z;
+
+		    bPt.x /= sPt.x;
+		    bPt.y /= sPt.y;
+		    bPt.z /= sPt.z;
+    		
+		    double w = (weightsV[i])*std::exp(-((aPt-bPt).dot(aPt-bPt))/2)/std::sqrt(sPt.dot(Point3d(1,1,1)));
+    		
+		    resPoint += w*aPt;
+
+		    ratPoint.x += w/sPt.x;
+		    ratPoint.y += w/sPt.y;
+		    ratPoint.z += w/sPt.z;
+	    }
+	    resPoint.x /= ratPoint.x;
+	    resPoint.y /= ratPoint.y;
+	    resPoint.z /= ratPoint.z;
+	    return resPoint;
+    }
+
+	double getResultWeight(const Point3d& inPt) const
+    {
+	    double sumW=0;
+	    for (size_t i=0; i<positionsV.size(); i++)
+	    {
+		    Point3d aPt = positionsV[i];
+		    Point3d sPt = densityKernel;
+
+		    sPt.x *= exp(aPt.z);
+		    sPt.y *= exp(aPt.z);
+
+		    aPt -= inPt;
+    		
+		    aPt.x /= sPt.x;
+		    aPt.y /= sPt.y;
+		    aPt.z /= sPt.z;
+    		
+		    sumW+=(weightsV[i])*std::exp(-(aPt.dot(aPt))/2)/std::sqrt(sPt.dot(Point3d(1,1,1)));
+	    }
+	    return sumW;
+    }
+    
+	Point3d moveToMode(Point3d aPt) const
+    {
+	    Point3d bPt;
+	    for (int i = 0; i<iterMax; i++)
+	    {
+		    bPt = aPt;
+		    aPt = getNewValue(bPt);
+		    if ( getDistance(aPt, bPt) <= modeEps )
+		    {
+			    break;
+		    }
+	    }
+	    return aPt;
+    }
+
+    double getDistance(Point3d p1, Point3d p2) const
+    {
+	    Point3d ns = densityKernel;
+	    ns.x *= exp(p2.z);
+	    ns.y *= exp(p2.z);
+	    p2 -= p1;
+	    p2.x /= ns.x;
+	    p2.y /= ns.y;
+	    p2.z /= ns.z;
+	    return p2.dot(p2);
+    }
+};
 //new grouping function with using meanshift
 static void groupRectangles_meanshift(vector<Rect>& rectList, double detectThreshold, vector<double>* foundWeights, 
 									  vector<double>& scales, Size winDetSize)
diff --git a/modules/objdetect/src/ms_grouping.cpp b/modules/objdetect/src/ms_grouping.cpp
deleted file mode 100644
index 0b9a41f6a..000000000
--- a/modules/objdetect/src/ms_grouping.cpp
+++ /dev/null
@@ -1,177 +0,0 @@
-/*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;
-
-MeanshiftGrouping::MeanshiftGrouping(const Point3d& densKer, const vector<Point3d>& posV, 
-					 const vector<double>& wV, double modeEps, int maxIter)
-{
-	densityKernel = densKer;
-    weightsV = wV;
-    positionsV = posV;
-    positionsCount = posV.size();
-	meanshiftV.resize(positionsCount);
-    distanceV.resize(positionsCount);
-    modeEps = modeEps;
-	iterMax = maxIter;
-    
-	for (unsigned i=0; i<positionsV.size(); i++)
-	{
-		meanshiftV[i] = getNewValue(positionsV[i]);
-
-		distanceV[i] = moveToMode(meanshiftV[i]);
-
-		meanshiftV[i] -= positionsV[i];
-	}
-}
-
-void MeanshiftGrouping::getModes(vector<Point3d>& modesV, vector<double>& resWeightsV, double eps)
-{
-	for (size_t i=0; i <distanceV.size(); i++)
-	{
-		bool is_found = false;
-		for(size_t j=0; j<modesV.size(); j++)
-		{
-			if ( getDistance(distanceV[i], modesV[j]) < eps)
-			{
-				is_found=true;
-				break;
-			}
-		}
-		if (!is_found)
-		{
-			modesV.push_back(distanceV[i]);
-		}
-	}
-	
-	resWeightsV.resize(modesV.size());
-
-	for (size_t i=0; i<modesV.size(); i++)
-	{
-		resWeightsV[i] = getResultWeight(modesV[i]);
-	}
-}
-
-Point3d MeanshiftGrouping::moveToMode(Point3d aPt) const
-{
-	Point3d bPt;
-	for (int i = 0; i<iterMax; i++)
-	{
-		bPt = aPt;
-		aPt = getNewValue(bPt);
-		if ( getDistance(aPt, bPt) <= modeEps )
-		{
-			break;
-		}
-	}
-	return aPt;
-}
-
-Point3d MeanshiftGrouping::getNewValue(const Point3d& inPt) const
-{
-	Point3d resPoint(.0);
-	Point3d ratPoint(.0);
-	for (size_t i=0; i<positionsV.size(); i++)
-	{
-		Point3d aPt= positionsV[i];
-		Point3d bPt = inPt;
-		Point3d sPt = densityKernel;
-		
-		sPt.x *= exp(aPt.z);
-		sPt.y *= exp(aPt.z);
-		
-		aPt.x /= sPt.x;
-		aPt.y /= sPt.y;
-		aPt.z /= sPt.z;
-
-		bPt.x /= sPt.x;
-		bPt.y /= sPt.y;
-		bPt.z /= sPt.z;
-		
-		double w = (weightsV[i])*std::exp(-((aPt-bPt).dot(aPt-bPt))/2)/std::sqrt(sPt.dot(Point3d(1,1,1)));
-		
-		resPoint += w*aPt;
-
-		ratPoint.x += w/sPt.x;
-		ratPoint.y += w/sPt.y;
-		ratPoint.z += w/sPt.z;
-	}
-	resPoint.x /= ratPoint.x;
-	resPoint.y /= ratPoint.y;
-	resPoint.z /= ratPoint.z;
-	return resPoint;
-} 
-
-double MeanshiftGrouping::getResultWeight(const Point3d& inPt) const
-{
-	double sumW=0;
-	for (size_t i=0; i<positionsV.size(); i++)
-	{
-		Point3d aPt = positionsV[i];
-		Point3d sPt = densityKernel;
-
-		sPt.x *= exp(aPt.z);
-		sPt.y *= exp(aPt.z);
-
-		aPt -= inPt;
-		
-		aPt.x /= sPt.x;
-		aPt.y /= sPt.y;
-		aPt.z /= sPt.z;
-		
-		sumW+=(weightsV[i])*std::exp(-(aPt.dot(aPt))/2)/std::sqrt(sPt.dot(Point3d(1,1,1)));
-	}
-	return sumW;
-}
-
-double MeanshiftGrouping::getDistance(Point3d p1, Point3d p2) const 
-{
-	Point3d ns = densityKernel;
-	ns.x *= exp(p2.z);
-	ns.y *= exp(p2.z);
-	p2 -= p1;
-	p2.x /= ns.x;
-	p2.y /= ns.y;
-	p2.z /= ns.z;
-	return p2.dot(p2);
-}