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opencv/modules/legacy/src/blobtrackanalysishist.cpp

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/*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 "precomp.hpp"
#define MAX_FV_SIZE 5
#define BLOB_NUM 5
typedef struct DefBlobFVN
{
CvBlob blob;
CvBlob BlobSeq[BLOB_NUM];
int state;
int LastFrame;
int FrameNum;
} DefBlobFVN;
class CvBlobTrackFVGenN: public CvBlobTrackFVGen
{
private:
CvBlobSeq m_BlobList;
CvMemStorage* m_pMem;
CvSeq* m_pFVSeq;
float m_FVMax[MAX_FV_SIZE];
float m_FVMin[MAX_FV_SIZE];
float m_FVVar[MAX_FV_SIZE];
int m_Dim;
CvBlob m_BlobSeq[BLOB_NUM];
int m_Frame;
int m_State;
int m_LastFrame;
int m_ClearFlag;
void Clear()
{
if(m_pMem)
{
cvClearMemStorage(m_pMem);
m_pFVSeq = cvCreateSeq(0,sizeof(CvSeq),sizeof(float)*(m_Dim+1), m_pMem);
m_ClearFlag = 1;
}
}
public:
CvBlobTrackFVGenN(int dim = 2 ):m_BlobList(sizeof(DefBlobFVN))
{
int i;
assert(dim <= MAX_FV_SIZE);
m_Dim = dim;
for(i=0; i<m_Dim; ++i)
{
m_FVVar[i] = 0.01f;
m_FVMax[i] = 1;
m_FVMin[i] = 0;
}
m_Frame = 0;
m_State = 0;
m_pMem = cvCreateMemStorage();
m_pFVSeq = NULL;
Clear();
switch(dim) {
case 2: SetModuleName("P"); break;
case 4: SetModuleName("PV"); break;
case 5: SetModuleName("PVS"); break;
}
};
~CvBlobTrackFVGenN()
{
if(m_pMem)cvReleaseMemStorage(&m_pMem);
};
void AddBlob(CvBlob* pBlob)
{
float FV[MAX_FV_SIZE+1];
DefBlobFVN* pFVBlob = (DefBlobFVN*)m_BlobList.GetBlobByID(CV_BLOB_ID(pBlob));
if(!m_ClearFlag) Clear();
if(pFVBlob==NULL)
{
DefBlobFVN BlobNew;
BlobNew.blob = pBlob[0];
BlobNew.LastFrame = m_Frame;
BlobNew.state = 0;;
BlobNew.FrameNum = 0;
m_BlobList.AddBlob((CvBlob*)&BlobNew);
pFVBlob = (DefBlobFVN*)m_BlobList.GetBlobByID(CV_BLOB_ID(pBlob));
} /* Add new record if necessary. */
pFVBlob->blob = pBlob[0];
/* Shift: */
for(int i=(BLOB_NUM-1); i>0; --i)
{
pFVBlob->BlobSeq[i] = pFVBlob->BlobSeq[i-1];
}
pFVBlob->BlobSeq[0] = pBlob[0];
if(m_Dim>0)
{ /* Calculate FV position: */
FV[0] = CV_BLOB_X(pBlob);
FV[1] = CV_BLOB_Y(pBlob);
}
if(m_Dim<=2)
{ /* Add new FV if position is enough: */
*(int*)(FV+m_Dim) = CV_BLOB_ID(pBlob);
cvSeqPush( m_pFVSeq, FV );
}
else if(pFVBlob->FrameNum > BLOB_NUM)
{ /* Calculate velocity for more complex FV: */
float AverVx = 0;
float AverVy = 0;
{ /* Average velocity: */
CvBlob* pBlobSeq = pFVBlob->BlobSeq;
for(int i=1;i<BLOB_NUM;++i)
{
AverVx += CV_BLOB_X(pBlobSeq+i-1)-CV_BLOB_X(pBlobSeq+i);
AverVy += CV_BLOB_Y(pBlobSeq+i-1)-CV_BLOB_Y(pBlobSeq+i);
}
AverVx /= BLOB_NUM-1;
AverVy /= BLOB_NUM-1;
FV[2] = AverVx;
FV[3] = AverVy;
}
if(m_Dim>4)
{ /* State duration: */
float T = (CV_BLOB_WX(pBlob)+CV_BLOB_WY(pBlob))*0.01f;
if( fabs(AverVx) < T && fabs(AverVy) < T)
pFVBlob->state++;
else
pFVBlob->state=0;
FV[4] = (float)pFVBlob->state;
} /* State duration. */
/* Add new FV: */
*(int*)(FV+m_Dim) = CV_BLOB_ID(pBlob);
cvSeqPush( m_pFVSeq, FV );
} /* If velocity is calculated. */
pFVBlob->FrameNum++;
pFVBlob->LastFrame = m_Frame;
}; /* AddBlob */
void Process(IplImage* pImg, IplImage* /*pFG*/)
{
int i;
if(!m_ClearFlag) Clear();
for(i=m_BlobList.GetBlobNum(); i>0; --i)
{ /* Delete unused blob: */
DefBlobFVN* pFVBlob = (DefBlobFVN*)m_BlobList.GetBlob(i-1);
if(pFVBlob->LastFrame < m_Frame)
{
m_BlobList.DelBlob(i-1);
}
} /* Check next blob in list. */
m_FVMin[0] = 0;
m_FVMin[1] = 0;
m_FVMax[0] = (float)(pImg->width-1);
m_FVMax[1] = (float)(pImg->height-1);
m_FVVar[0] = m_FVMax[0]*0.01f;
m_FVVar[1] = m_FVMax[1]*0.01f;
m_FVVar[2] = (float)(pImg->width-1)/1440.0f;
m_FVMax[2] = (float)(pImg->width-1)*0.02f;
m_FVMin[2] = -m_FVMax[2];
m_FVVar[3] = (float)(pImg->width-1)/1440.0f;
m_FVMax[3] = (float)(pImg->height-1)*0.02f;
m_FVMin[3] = -m_FVMax[3];
m_FVMax[4] = 25*32.0f; /* max state is 32 sec */
m_FVMin[4] = 0;
m_FVVar[4] = 10;
m_Frame++;
m_ClearFlag = 0;
};
virtual void Release(){delete this;};
virtual int GetFVSize(){return m_Dim;};
virtual int GetFVNum()
{
return m_pFVSeq->total;
};
virtual float* GetFV(int index, int* pFVID)
{
float* pFV = (float*)cvGetSeqElem( m_pFVSeq, index );
if(pFVID)pFVID[0] = *(int*)(pFV+m_Dim);
return pFV;
};
virtual float* GetFVMin(){return m_FVMin;}; /* returned pointer to array of minimal values of FV, if return 0 then FVrange is not exist */
virtual float* GetFVMax(){return m_FVMax;}; /* returned pointer to array of maximal values of FV, if return 0 then FVrange is not exist */
virtual float* GetFVVar(){return m_FVVar;}; /* returned pointer to array of maximal values of FV, if return 0 then FVrange is not exist */
};/* CvBlobTrackFVGenN */
inline CvBlobTrackFVGen* cvCreateFVGenP(){return (CvBlobTrackFVGen*)new CvBlobTrackFVGenN(2);}
inline CvBlobTrackFVGen* cvCreateFVGenPV(){return (CvBlobTrackFVGen*)new CvBlobTrackFVGenN(4);}
inline CvBlobTrackFVGen* cvCreateFVGenPVS(){return (CvBlobTrackFVGen*)new CvBlobTrackFVGenN(5);}
#undef MAX_FV_SIZE
#define MAX_FV_SIZE 4
class CvBlobTrackFVGenSS: public CvBlobTrackFVGen
{
private:
CvBlobSeq m_BlobList;
CvMemStorage* m_pMem;
CvSeq* m_pFVSeq;
float m_FVMax[MAX_FV_SIZE];
float m_FVMin[MAX_FV_SIZE];
float m_FVVar[MAX_FV_SIZE];
int m_Dim;
CvBlob m_BlobSeq[BLOB_NUM];
int m_Frame;
int m_State;
int m_LastFrame;
int m_ClearFlag;
void Clear()
{
cvClearMemStorage(m_pMem);
m_pFVSeq = cvCreateSeq(0,sizeof(CvSeq),sizeof(float)*(m_Dim+1), m_pMem);
m_ClearFlag = 1;
}
public:
CvBlobTrackFVGenSS(int dim = 2 ):m_BlobList(sizeof(DefBlobFVN))
{
int i;
assert(dim <= MAX_FV_SIZE);
m_Dim = dim;
for(i=0;i<m_Dim;++i)
{
m_FVVar[i] = 0.01f;
m_FVMax[i] = 1;
m_FVMin[i] = 0;
}
m_Frame = 0;
m_State = 0;
m_pMem = cvCreateMemStorage();
m_pFVSeq = NULL;
SetModuleName("SS");
};
~CvBlobTrackFVGenSS()
{
if(m_pMem)cvReleaseMemStorage(&m_pMem);
};
void AddBlob(CvBlob* pBlob)
{
//float FV[MAX_FV_SIZE+1];
DefBlobFVN* pFVBlob = (DefBlobFVN*)m_BlobList.GetBlobByID(CV_BLOB_ID(pBlob));
if(!m_ClearFlag) Clear();
if(pFVBlob==NULL)
{
DefBlobFVN BlobNew;
BlobNew.blob = pBlob[0];
BlobNew.LastFrame = m_Frame;
BlobNew.state = 0;;
BlobNew.FrameNum = 0;
m_BlobList.AddBlob((CvBlob*)&BlobNew);
pFVBlob = (DefBlobFVN*)m_BlobList.GetBlobByID(CV_BLOB_ID(pBlob));
} /* Add new record if necessary. */
/* Shift: */
for(int i=(BLOB_NUM-1); i>0; --i)
{
pFVBlob->BlobSeq[i] = pFVBlob->BlobSeq[i-1];
}
pFVBlob->BlobSeq[0] = pBlob[0];
if(pFVBlob->FrameNum > BLOB_NUM)
{ /* Average velocity: */
CvBlob* pBlobSeq = pFVBlob->BlobSeq;
float T = (CV_BLOB_WX(pBlob)+CV_BLOB_WY(pBlob))*0.01f;
float AverVx = 0;
float AverVy = 0;
for(int i=1; i<BLOB_NUM; ++i)
{
AverVx += CV_BLOB_X(pBlobSeq+i-1)-CV_BLOB_X(pBlobSeq+i);
AverVy += CV_BLOB_Y(pBlobSeq+i-1)-CV_BLOB_Y(pBlobSeq+i);
}
AverVx /= BLOB_NUM-1;
AverVy /= BLOB_NUM-1;
if( fabs(AverVx) < T && fabs(AverVy) < T)
pFVBlob->state++;
else
pFVBlob->state=0;
}
if(pFVBlob->state == 5)
{ /* Object is stopped: */
float FV[MAX_FV_SIZE];
FV[0] = pFVBlob->blob.x;
FV[1] = pFVBlob->blob.y;
FV[2] = pFVBlob->BlobSeq[0].x;
FV[3] = pFVBlob->BlobSeq[0].y;
*(int*)(FV+m_Dim) = CV_BLOB_ID(pBlob);
cvSeqPush( m_pFVSeq, FV );
} /* Object is stopped. */
pFVBlob->FrameNum++;
pFVBlob->LastFrame = m_Frame;
}; /* AddBlob */
void Process(IplImage* pImg, IplImage* /*pFG*/)
{
int i;
if(!m_ClearFlag) Clear();
for(i=m_BlobList.GetBlobNum();i>0;--i)
{ /* Delete unused blob: */
DefBlobFVN* pFVBlob = (DefBlobFVN*)m_BlobList.GetBlob(i-1);
if(pFVBlob->LastFrame < m_Frame)
{
float FV[MAX_FV_SIZE+1];
FV[0] = pFVBlob->blob.x;
FV[1] = pFVBlob->blob.y;
FV[2] = pFVBlob->BlobSeq[0].x;
FV[3] = pFVBlob->BlobSeq[0].y;
*(int*)(FV+m_Dim) = CV_BLOB_ID(pFVBlob);
cvSeqPush( m_pFVSeq, FV );
m_BlobList.DelBlob(i-1);
}
} /* Check next blob in list. */
/* Set max min range: */
m_FVMin[0] = 0;
m_FVMin[1] = 0;
m_FVMin[2] = 0;
m_FVMin[3] = 0;
m_FVMax[0] = (float)(pImg->width-1);
m_FVMax[1] = (float)(pImg->height-1);
m_FVMax[2] = (float)(pImg->width-1);
m_FVMax[3] = (float)(pImg->height-1);
m_FVVar[0] = m_FVMax[0]*0.01f;
m_FVVar[1] = m_FVMax[1]*0.01f;
m_FVVar[2] = m_FVMax[2]*0.01f;
m_FVVar[3] = m_FVMax[3]*0.01f;
m_Frame++;
m_ClearFlag = 0;
};
virtual void Release(){delete this;};
virtual int GetFVSize(){return m_Dim;};
virtual int GetFVNum()
{
return m_pFVSeq->total;
};
virtual float* GetFV(int index, int* pFVID)
{
float* pFV = (float*)cvGetSeqElem( m_pFVSeq, index );
if(pFVID)pFVID[0] = *(int*)(pFV+m_Dim);
return pFV;
};
virtual float* GetFVMin(){return m_FVMin;}; /* returned pointer to array of minimal values of FV, if return 0 then FVrange is not exist */
virtual float* GetFVMax(){return m_FVMax;}; /* returned pointer to array of maximal values of FV, if return 0 then FVrange is not exist */
virtual float* GetFVVar(){return m_FVVar;}; /* returned pointer to array of maximal values of FV, if return 0 then FVrange is not exist */
};/* CvBlobTrackFVGenSS */
inline CvBlobTrackFVGen* cvCreateFVGenSS(){return (CvBlobTrackFVGen*)new CvBlobTrackFVGenSS;}
/*======================= TRAJECTORY ANALYZER MODULES =====================*/
/* Trajectory Analyser module */
#define SPARSE 0
#define ND 1
#define BYSIZE -1
class DefMat
{
private:
CvSparseMatIterator m_SparseIterator;
CvSparseNode* m_pSparseNode;
int* m_IDXs;
int m_Dim;
public:
CvSparseMat* m_pSparse;
CvMatND* m_pND;
int m_Volume;
int m_Max;
DefMat(int dim = 0, int* sizes = NULL, int type = SPARSE)
{
/* Create sparse or ND matrix but not both: */
m_pSparseNode = NULL;
m_pSparse = NULL;
m_pND = NULL;
m_Volume = 0;
m_Max = 0;
m_IDXs = NULL;
m_Dim = 0;
if(dim>0 && sizes != 0)
Realloc(dim, sizes, type);
}
~DefMat()
{
if(m_pSparse)cvReleaseSparseMat(&m_pSparse);
if(m_pND)cvReleaseMatND(&m_pND);
if(m_IDXs) cvFree(&m_IDXs);
}
void Realloc(int dim, int* sizes, int type = SPARSE)
{
if(m_pSparse)cvReleaseSparseMat(&m_pSparse);
if(m_pND)cvReleaseMatND(&m_pND);
if(type == BYSIZE )
{
int size = 0;
int i;
for(size=1,i=0;i<dim;++i)
{
size *= sizes[i];
}
size *= sizeof(int);
if(size > (2<<20))
{ /* if size > 1M */
type = SPARSE;
}
else
{
type = ND;
}
} /* Define matrix type. */
if(type == SPARSE)
{
m_pSparse = cvCreateSparseMat( dim, sizes, CV_32SC1 );
m_Dim = dim;
}
if(type == ND )
{
m_pND = cvCreateMatND( dim, sizes, CV_32SC1 );
cvZero(m_pND);
m_IDXs = (int*)cvAlloc(sizeof(int)*dim);
m_Dim = dim;
}
m_Volume = 0;
m_Max = 0;
}
void Save(const char* File)
{
if(m_pSparse)cvSave(File, m_pSparse );
if(m_pND)cvSave(File, m_pND );
}
void Save(CvFileStorage* fs, const char* name)
{
if(m_pSparse)
{
cvWrite(fs, name, m_pSparse );
}
else if(m_pND)
{
cvWrite(fs, name, m_pND );
}
}
void Load(const char* File)
{
CvFileStorage* fs = cvOpenFileStorage( File, NULL, CV_STORAGE_READ );
if(fs)
{
void* ptr;
if(m_pSparse) cvReleaseSparseMat(&m_pSparse);
if(m_pND) cvReleaseMatND(&m_pND);
m_Volume = 0;
m_Max = 0;
ptr = cvLoad(File);
if(ptr && CV_IS_MATND_HDR(ptr)) m_pND = (CvMatND*)ptr;
if(ptr && CV_IS_SPARSE_MAT_HDR(ptr)) m_pSparse = (CvSparseMat*)ptr;
cvReleaseFileStorage(&fs);
}
AfterLoad();
} /* Load. */
void Load(CvFileStorage* fs, CvFileNode* node, const char* name)
{
CvFileNode* n = cvGetFileNodeByName(fs,node,name);
void* ptr = n?cvRead(fs,n):NULL;
if(ptr)
{
if(m_pSparse) cvReleaseSparseMat(&m_pSparse);
if(m_pND) cvReleaseMatND(&m_pND);
m_Volume = 0;
m_Max = 0;
if(CV_IS_MATND_HDR(ptr)) m_pND = (CvMatND*)ptr;
if(CV_IS_SPARSE_MAT_HDR(ptr)) m_pSparse = (CvSparseMat*)ptr;
}
else
{
printf("WARNING!!! Can't load %s matrix\n",name);
}
AfterLoad();
} /* Load. */
void AfterLoad()
{
m_Volume = 0;
m_Max = 0;
if(m_pSparse)
{ /* Calculate Volume of loaded hist: */
CvSparseMatIterator mat_iterator;
CvSparseNode* node = cvInitSparseMatIterator( m_pSparse, &mat_iterator );
for( ; node != 0; node = cvGetNextSparseNode( &mat_iterator ))
{
int val = *(int*)CV_NODE_VAL( m_pSparse, node ); /* get value of the element
(assume that the type is CV_32SC1) */
m_Volume += val;
if(m_Max < val)m_Max = val;
}
} /* Calculate Volume of loaded hist. */
if(m_pND)
{ /* Calculate Volume of loaded hist: */
CvMat mat;
double max_val;
double vol;
cvGetMat( m_pND, &mat, NULL, 1 );
vol = cvSum(&mat).val[0];
m_Volume = cvRound(vol);
cvMinMaxLoc( &mat, NULL, &max_val);
m_Max = cvRound(max_val);
/* MUST BE WRITTEN LATER */
} /* Calculate Volume of loaded hist. */
} /* AfterLoad. */
int* GetPtr(int* indx)
{
if(m_pSparse) return (int*)cvPtrND( m_pSparse, indx, NULL, 1, NULL);
if(m_pND) return (int*)cvPtrND( m_pND, indx, NULL, 1, NULL);
return NULL;
} /* GetPtr. */
int GetVal(int* indx)
{
int* p = GetPtr(indx);
if(p)return p[0];
return -1;
} /* GetVal. */
int Add(int* indx, int val)
{
int NewVal;
int* pVal = GetPtr(indx);
if(pVal == NULL) return -1;
pVal[0] += val;
NewVal = pVal[0];
m_Volume += val;
if(m_Max < NewVal)m_Max = NewVal;
return NewVal;
} /* Add. */
void Add(DefMat* pMatAdd)
{
int* pIDXS = NULL;
int Val = 0;
for(Val = pMatAdd->GetNext(&pIDXS, 1 );pIDXS;Val=pMatAdd->GetNext(&pIDXS, 0 ))
{
Add(pIDXS,Val);
}
} /* Add. */
int SetMax(int* indx, int val)
{
int NewVal;
int* pVal = GetPtr(indx);
if(pVal == NULL) return -1;
if(val > pVal[0])
{
m_Volume += val-pVal[0];
pVal[0] = val;
}
NewVal = pVal[0];
if(m_Max < NewVal)m_Max = NewVal;
return NewVal;
} /* Add. */
int GetNext(int** pIDXS, int init = 0)
{
int Val = 0;
pIDXS[0] = NULL;
if(m_pSparse)
{
m_pSparseNode = (init || m_pSparseNode==NULL)?
cvInitSparseMatIterator( m_pSparse, &m_SparseIterator ):
cvGetNextSparseNode( &m_SparseIterator );
if(m_pSparseNode)
{
int* pVal = (int*)CV_NODE_VAL( m_pSparse, m_pSparseNode );
if(pVal)Val = pVal[0];
pIDXS[0] = CV_NODE_IDX( m_pSparse, m_pSparseNode );
}
}/* Sparse matrix. */
if(m_pND)
{
int i;
if(init)
{
for(i=0;i<m_Dim;++i)
{
m_IDXs[i] = cvGetDimSize( m_pND, i )-1;
}
pIDXS[0] = m_IDXs;
Val = GetVal(m_IDXs);
}
else
{
for(i=0;i<m_Dim;++i)
{
if((m_IDXs[i]--)>0)
break;
m_IDXs[i] = cvGetDimSize( m_pND, i )-1;
}
if(i==m_Dim)
{
pIDXS[0] = NULL;
}
else
{
pIDXS[0] = m_IDXs;
Val = GetVal(m_IDXs);
}
} /* Get next ND. */
} /* Sparse matrix. */
return Val;
}; /* GetNext. */
};
#define FV_NUM 10
#define FV_SIZE 10
typedef struct DefTrackFG
{
CvBlob blob;
// CvBlobTrackFVGen* pFVGen;
int LastFrame;
float state;
DefMat* pHist;
} DefTrackFG;
class CvBlobTrackAnalysisHist : public CvBlobTrackAnalysis
{
/*---------------- Internal functions: --------------------*/
private:
int m_BinNumParam;
int m_SmoothRadius;
const char* m_SmoothKernel;
float m_AbnormalThreshold;
int m_TrackNum;
int m_Frame;
int m_BinNum;
char m_DataFileName[1024];
int m_Dim;
int* m_Sizes;
DefMat m_HistMat;
int m_HistVolumeSaved;
int* m_pFVi;
int* m_pFViVar;
int* m_pFViVarRes;
CvBlobSeq m_TrackFGList;
//CvBlobTrackFVGen* (*m_CreateFVGen)();
CvBlobTrackFVGen* m_pFVGen;
void SaveHist()
{
if(m_DataFileName[0])
{
m_HistMat.Save(m_DataFileName);
m_HistVolumeSaved = m_HistMat.m_Volume;
}
};
void LoadHist()
{
if(m_DataFileName[0])m_HistMat.Load(m_DataFileName);
m_HistVolumeSaved = m_HistMat.m_Volume;
}
void AllocData()
{ /* AllocData: */
m_pFVi = (int*)cvAlloc(sizeof(int)*m_Dim);
m_pFViVar = (int*)cvAlloc(sizeof(int)*m_Dim);
m_pFViVarRes = (int*)cvAlloc(sizeof(int)*m_Dim);
m_Sizes = (int*)cvAlloc(sizeof(int)*m_Dim);
{ /* Create init sparce matrix: */
int i;
for(i=0;i<m_Dim;++i)m_Sizes[i] = m_BinNum;
m_HistMat.Realloc(m_Dim,m_Sizes,SPARSE);
m_HistVolumeSaved = 0;
} /* Create init sparce matrix. */
} /* AllocData. */
void FreeData()
{ /* FreeData. */
int i;
for(i=m_TrackFGList.GetBlobNum();i>0;--i)
{
//DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlob(i-1);
// pF->pFVGen->Release();
m_TrackFGList.DelBlob(i-1);
}
cvFree(&m_pFVi);
cvFree(&m_pFViVar);
cvFree(&m_pFViVarRes);
cvFree(&m_Sizes);
} /* FreeData. */
virtual void ParamUpdate()
{
if(m_BinNum != m_BinNumParam)
{
FreeData();
m_BinNum = m_BinNumParam;
AllocData();
}
}
public:
CvBlobTrackAnalysisHist(CvBlobTrackFVGen* (*createFVGen)()):m_TrackFGList(sizeof(DefTrackFG))
{
m_pFVGen = createFVGen();
m_Dim = m_pFVGen->GetFVSize();
m_Frame = 0;
m_pFVi = 0;
m_TrackNum = 0;
m_BinNum = 32;
m_DataFileName[0] = 0;
m_AbnormalThreshold = 0.02f;
AddParam("AbnormalThreshold",&m_AbnormalThreshold);
CommentParam("AbnormalThreshold","If trajectory histogram value is lesst then <AbnormalThreshold*DataBaseTrackNum> then trajectory is abnormal");
m_SmoothRadius = 1;
AddParam("SmoothRadius",&m_SmoothRadius);
CommentParam("AbnormalThreshold","Radius (in bins) for histogram smoothing");
m_SmoothKernel = "L";
AddParam("SmoothKernel",&m_SmoothKernel);
CommentParam("SmoothKernel","L - Linear, G - Gaussian");
m_BinNumParam = m_BinNum;
AddParam("BinNum",&m_BinNumParam);
CommentParam("BinNum","Number of bin for each dimention of feature vector");
AllocData();
SetModuleName("Hist");
} /* Constructor. */
~CvBlobTrackAnalysisHist()
{
SaveHist();
FreeData();
m_pFVGen->Release();
} /* Destructor. */
/*----------------- Interface: --------------------*/
virtual void AddBlob(CvBlob* pBlob)
{
DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlobByID(CV_BLOB_ID(pBlob));
if(pF == NULL)
{ /* create new filter */
DefTrackFG F;
F.state = 0;
F.blob = pBlob[0];
F.LastFrame = m_Frame;
// F.pFVGen = m_CreateFVGen();
F.pHist = new DefMat(m_Dim,m_Sizes,SPARSE);
m_TrackFGList.AddBlob((CvBlob*)&F);
pF = (DefTrackFG*)m_TrackFGList.GetBlobByID(CV_BLOB_ID(pBlob));
}
assert(pF);
pF->blob = pBlob[0];
pF->LastFrame = m_Frame;
m_pFVGen->AddBlob(pBlob);
};
virtual void Process(IplImage* pImg, IplImage* pFG)
{
m_pFVGen->Process(pImg, pFG);
int SK = m_SmoothKernel[0];
for(int i=0; i<m_pFVGen->GetFVNum(); ++i)
{
int BlobID = 0;
float* pFV = m_pFVGen->GetFV(i,&BlobID);
float* pFVMax = m_pFVGen->GetFVMax();
float* pFVMin = m_pFVGen->GetFVMin();
DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlobByID(BlobID);
int HistVal = 1;
if(pFV==NULL) break;
pF->LastFrame = m_Frame;
{ /* Binarize FV: */
int j;
for(j=0; j<m_Dim; ++j)
{
int index;
float f0 = pFVMin?pFVMin[j]:0;
float f1 = pFVMax?pFVMax[j]:1;
assert(f1>f0);
index = cvRound((m_BinNum-1)*(pFV[j]-f0)/(f1-f0));
if(index<0)index=0;
if(index>=m_BinNum)index=m_BinNum-1;
m_pFVi[j] = index;
}
}
HistVal = m_HistMat.GetVal(m_pFVi);/* get bin value*/
pF->state = 0;
{ /* Calculate state: */
float T = m_HistMat.m_Max*m_AbnormalThreshold; /* calc threshold */
if(m_TrackNum>0) T = 256.0f * m_TrackNum*m_AbnormalThreshold;
if(T>0)
{
pF->state = (T - HistVal)/(T*0.2f) + 0.5f;
}
if(pF->state<0)pF->state=0;
if(pF->state>1)pF->state=1;
}
{ /* If it is a new FV then add it to trajectory histogram: */
int flag = 1;
int r = m_SmoothRadius;
// printf("BLob %3d NEW FV [", CV_BLOB_ID(pF));
// for(i=0;i<m_Dim;++i) printf("%d,", m_pFVi[i]);
// printf("]");
for(int k=0; k<m_Dim; ++k)
{
m_pFViVar[k]=-r;
}
while(flag)
{
float dist = 0;
int HistAdd = 0;
int good = 1;
for(int k=0; k<m_Dim; ++k)
{
m_pFViVarRes[k] = m_pFVi[k]+m_pFViVar[k];
if(m_pFViVarRes[k]<0) good= 0;
if(m_pFViVarRes[k]>=m_BinNum) good= 0;
dist += m_pFViVar[k]*m_pFViVar[k];
}/* Calculate next dimension. */
if(SK=='G' || SK=='g')
{
double dist2 = dist/(r*r);
HistAdd = cvRound(256*exp(-dist2)); /* Hist Add for (dist=1) = 25.6*/
}
else if(SK=='L' || SK=='l')
{
dist = (float)(sqrt(dist)/(r+1));
HistAdd = cvRound(256*(1-dist));
}
else
{
HistAdd = 255; /* Flat smoothing. */
}
if(good && HistAdd>0)
{ /* Update histogram: */
assert(pF->pHist);
pF->pHist->SetMax(m_pFViVarRes, HistAdd);
} /* Update histogram. */
int idx = 0;
for( ; idx<m_Dim; ++idx)
{ /* Next config: */
if((m_pFViVar[idx]++) < r)
break;
m_pFViVar[idx] = -r;
} /* Increase next dimension variable. */
if(idx==m_Dim)break;
} /* Next variation. */
} /* If new FV. */
} /* Next FV. */
{ /* Check all blobs on list: */
int i;
for(i=m_TrackFGList.GetBlobNum(); i>0; --i)
{ /* Add histogram and delete blob from list: */
DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlob(i-1);
if(pF->LastFrame+3 < m_Frame && pF->pHist)
{
m_HistMat.Add(pF->pHist);
delete pF->pHist;
m_TrackNum++;
m_TrackFGList.DelBlob(i-1);
}
}/* next blob */
}
m_Frame++;
if(m_Wnd)
{ /* Debug output: */
int* idxs = NULL;
int Val = 0;
IplImage* pI = cvCloneImage(pImg);
cvZero(pI);
for(Val = m_HistMat.GetNext(&idxs,1); idxs; Val=m_HistMat.GetNext(&idxs,0))
{ /* Draw all elements: */
if(!idxs) break;
if(Val == 0) continue;
float vf = (float)Val/(m_HistMat.m_Max?m_HistMat.m_Max:1);
int x = cvRound((float)(pI->width-1)*(float)idxs[0] / (float)m_BinNum);
int y = cvRound((float)(pI->height-1)*(float)idxs[1] / (float)m_BinNum);
cvCircle(pI, cvPoint(x,y), cvRound(vf*pI->height/(m_BinNum*2)),CV_RGB(255,0,0),CV_FILLED);
if(m_Dim > 3)
{
int dx = -2*(idxs[2]-m_BinNum/2);
int dy = -2*(idxs[3]-m_BinNum/2);
cvLine(pI,cvPoint(x,y),cvPoint(x+dx,y+dy),CV_RGB(0,cvRound(vf*255),1));
}
if( m_Dim==4 &&
m_pFVGen->GetFVMax()[0]==m_pFVGen->GetFVMax()[2] &&
m_pFVGen->GetFVMax()[1]==m_pFVGen->GetFVMax()[3])
{
int x1 = cvRound((float)(pI->width-1)*(float)idxs[2] / (float)m_BinNum);
int y1 = cvRound((float)(pI->height-1)*(float)idxs[3] / (float)m_BinNum);
cvCircle(pI, cvPoint(x1,y1), cvRound(vf*pI->height/(m_BinNum*2)),CV_RGB(0,0,255),CV_FILLED);
}
} /* Draw all elements. */
for(int i=m_TrackFGList.GetBlobNum();i>0;--i)
{
DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlob(i-1);
DefMat* pHist = pF?pF->pHist:NULL;
if(pHist==NULL) continue;
for(Val = pHist->GetNext(&idxs,1);idxs;Val=pHist->GetNext(&idxs,0))
{ /* Draw all elements: */
float vf;
int x,y;
if(!idxs) break;
if(Val == 0) continue;
vf = (float)Val/(pHist->m_Max?pHist->m_Max:1);
x = cvRound((float)(pI->width-1)*(float)idxs[0] / (float)m_BinNum);
y = cvRound((float)(pI->height-1)*(float)idxs[1] / (float)m_BinNum);
cvCircle(pI, cvPoint(x,y), cvRound(2*vf),CV_RGB(0,0,cvRound(255*vf)),CV_FILLED);
if(m_Dim > 3)
{
int dx = -2*(idxs[2]-m_BinNum/2);
int dy = -2*(idxs[3]-m_BinNum/2);
cvLine(pI,cvPoint(x,y),cvPoint(x+dx,y+dy),CV_RGB(0,0,255));
}
if( m_Dim==4 &&
m_pFVGen->GetFVMax()[0]==m_pFVGen->GetFVMax()[2] &&
m_pFVGen->GetFVMax()[1]==m_pFVGen->GetFVMax()[3])
{ /* if SS feature vector */
int x1 = cvRound((float)(pI->width-1)*(float)idxs[2] / (float)m_BinNum);
int y1 = cvRound((float)(pI->height-1)*(float)idxs[3] / (float)m_BinNum);
cvCircle(pI, cvPoint(x1,y1), cvRound(vf*pI->height/(m_BinNum*2)),CV_RGB(0,0,255),CV_FILLED);
}
} /* Draw all elements. */
} /* Next track. */
//cvNamedWindow("Hist",0);
//cvShowImage("Hist", pI);
cvReleaseImage(&pI);
}
};
float GetState(int BlobID)
{
DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlobByID(BlobID);
return pF?pF->state:0.0f;
};
/* Return 0 if trajectory is normal;
rreturn >0 if trajectory abnormal. */
virtual const char* GetStateDesc(int BlobID)
{
if(GetState(BlobID)>0.5) return "abnormal";
return NULL;
}
virtual void SetFileName(char* DataBaseName)
{
if(m_HistMat.m_Volume!=m_HistVolumeSaved)SaveHist();
m_DataFileName[0] = m_DataFileName[1000] = 0;
if(DataBaseName)
{
strncpy(m_DataFileName,DataBaseName,1000);
strcat(m_DataFileName, ".yml");
}
LoadHist();
};
virtual void SaveState(CvFileStorage* fs)
{
int b, bN = m_TrackFGList.GetBlobNum();
cvWriteInt(fs,"BlobNum",bN);
cvStartWriteStruct(fs,"BlobList",CV_NODE_SEQ);
for(b=0; b<bN; ++b)
{
DefTrackFG* pF = (DefTrackFG*)m_TrackFGList.GetBlob(b);
cvStartWriteStruct(fs,NULL,CV_NODE_MAP);
cvWriteStruct(fs,"Blob", &(pF->blob), "ffffi");
cvWriteInt(fs,"LastFrame",pF->LastFrame);
cvWriteReal(fs,"State",pF->state);
pF->pHist->Save(fs, "Hist");
cvEndWriteStruct(fs);
}
cvEndWriteStruct(fs);
m_HistMat.Save(fs, "Hist");
};
virtual void LoadState(CvFileStorage* fs, CvFileNode* node)
{
CvFileNode* pBLN = cvGetFileNodeByName(fs,node,"BlobList");
if(pBLN && CV_NODE_IS_SEQ(pBLN->tag))
{
int b, bN = pBLN->data.seq->total;
for(b=0; b<bN; ++b)
{
DefTrackFG* pF = NULL;
CvBlob Blob;
CvFileNode* pBN = (CvFileNode*)cvGetSeqElem(pBLN->data.seq,b);
assert(pBN);
cvReadStructByName(fs, pBN, "Blob", &Blob, "ffffi");
AddBlob(&Blob);
pF = (DefTrackFG*)m_TrackFGList.GetBlobByID(Blob.ID);
if(pF==NULL) continue;
assert(pF);
pF->state = (float)cvReadIntByName(fs,pBN,"State",cvRound(pF->state));
assert(pF->pHist);
pF->pHist->Load(fs,pBN,"Hist");
}
}
m_HistMat.Load(fs, node, "Hist");
}; /* LoadState */
virtual void Release(){ delete this; };
};
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisHistP()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisHist(cvCreateFVGenP);}
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisHistPV()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisHist(cvCreateFVGenPV);}
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisHistPVS()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisHist(cvCreateFVGenPVS);}
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisHistSS()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisHist(cvCreateFVGenSS);}
typedef struct DefTrackSVM
{
CvBlob blob;
// CvBlobTrackFVGen* pFVGen;
int LastFrame;
float state;
CvBlob BlobLast;
CvSeq* pFVSeq;
CvMemStorage* pMem;
} DefTrackSVM;
class CvBlobTrackAnalysisSVM : public CvBlobTrackAnalysis
{
/*---------------- Internal functions: --------------------*/
private:
CvMemStorage* m_pMem;
int m_TrackNum;
int m_Frame;
char m_DataFileName[1024];
int m_Dim;
float* m_pFV;
//CvStatModel* m_pStatModel;
void* m_pStatModel;
CvBlobSeq m_Tracks;
CvMat* m_pTrainData;
int m_LastTrainDataSize;
// CvBlobTrackFVGen* (*m_CreateFVGen)();
CvBlobTrackFVGen* m_pFVGen;
float m_NU;
float m_RBFWidth;
IplImage* m_pStatImg; /* for debug purpose */
CvSize m_ImgSize;
void RetrainStatModel()
{
///////// !!!!! TODO !!!!! Repair /////////////
#if 0
float nu = 0;
CvSVMModelParams SVMParams = {0};
CvStatModel* pM = NULL;
memset(&SVMParams,0,sizeof(SVMParams));
SVMParams.svm_type = CV_SVM_ONE_CLASS;
SVMParams.kernel_type = CV_SVM_RBF;
SVMParams.gamma = 2.0/(m_RBFWidth*m_RBFWidth);
SVMParams.nu = m_NU;
SVMParams.degree = 3;
SVMParams.criteria = cvTermCriteria(CV_TERMCRIT_EPS, 100, 1e-3 );
SVMParams.C = 1;
SVMParams.p = 0.1;
if(m_pTrainData == NULL) return;
{
int64 TickCount = cvGetTickCount();
printf("Frame: %d\n Retrain SVM\nData Size = %d\n",m_Frame, m_pTrainData->rows);
pM = cvTrainSVM( m_pTrainData,CV_ROW_SAMPLE, NULL, (CvStatModelParams*)&SVMParams, NULL, NULL);
TickCount = cvGetTickCount() - TickCount ;
printf("SV Count = %d\n",((CvSVMModel*)pM)->sv_total);
printf("Processing Time = %.1f(ms)\n",TickCount/(1000*cvGetTickFrequency()));
}
if(pM==NULL) return;
if(m_pStatModel) cvReleaseStatModel(&m_pStatModel);
m_pStatModel = pM;
if(m_pTrainData && m_Wnd)
{
float MaxVal = 0;
IplImage* pW = cvCreateImage(m_ImgSize,IPL_DEPTH_32F,1);
IplImage* pI = cvCreateImage(m_ImgSize,IPL_DEPTH_8U,1);
float* pFVVar = m_pFVGen->GetFVVar();
int i;
cvZero(pW);
for(i=0; i<m_pTrainData->rows; ++i)
{ /* Draw all elements: */
float* pFV = (float*)(m_pTrainData->data.ptr + m_pTrainData->step*i);
int x = cvRound(pFV[0]*pFVVar[0]);
int y = cvRound(pFV[1]*pFVVar[1]);
float r;
if(x<0)x=0;
if(x>=pW->width)x=pW->width-1;
if(y<0)y=0;
if(y>=pW->height)y=pW->height-1;
r = ((float*)(pW->imageData + y*pW->widthStep))[x];
r++;
((float*)(pW->imageData + y*pW->widthStep))[x] = r;
if(r>MaxVal)MaxVal=r;
} /* Next point. */
if(MaxVal>0)cvConvertScale(pW,pI,255/MaxVal,0);
cvNamedWindow("SVMData",0);
cvShowImage("SVMData",pI);
cvSaveImage("SVMData.bmp",pI);
cvReleaseImage(&pW);
cvReleaseImage(&pI);
} /* Prepare for debug. */
if(m_pStatModel && m_Wnd && m_Dim == 2)
{
float* pFVVar = m_pFVGen->GetFVVar();
int x,y;
if(m_pStatImg==NULL)
{
m_pStatImg = cvCreateImage(m_ImgSize,IPL_DEPTH_8U,1);
}
cvZero(m_pStatImg);
for(y=0; y<m_pStatImg->height; y+=1) for(x=0; x<m_pStatImg->width; x+=1)
{ /* Draw all elements: */
float res;
uchar* pData = (uchar*)m_pStatImg->imageData + x + y*m_pStatImg->widthStep;
CvMat FVmat;
float xy[2] = {x/pFVVar[0],y/pFVVar[1]};
cvInitMatHeader( &FVmat, 1, 2, CV_32F, xy );
res = cvStatModelPredict( m_pStatModel, &FVmat, NULL );
pData[0]=((res>0.5)?255:0);
} /* Next point. */
cvNamedWindow("SVMMask",0);
cvShowImage("SVMMask",m_pStatImg);
cvSaveImage("SVMMask.bmp",m_pStatImg);
} /* Prepare for debug. */
#endif
};
void SaveStatModel()
{
if(m_DataFileName[0])
{
if(m_pTrainData)cvSave(m_DataFileName, m_pTrainData);
}
};
void LoadStatModel()
{
if(m_DataFileName[0])
{
CvMat* pTrainData = (CvMat*)cvLoad(m_DataFileName);
if(CV_IS_MAT(pTrainData) && pTrainData->width == m_Dim)
{
if(m_pTrainData) cvReleaseMat(&m_pTrainData);
m_pTrainData = pTrainData;
RetrainStatModel();
}
}
}
public:
CvBlobTrackAnalysisSVM(CvBlobTrackFVGen* (*createFVGen)()):m_Tracks(sizeof(DefTrackSVM))
{
m_pFVGen = createFVGen();
m_Dim = m_pFVGen->GetFVSize();
m_pFV = (float*)cvAlloc(sizeof(float)*m_Dim);
m_Frame = 0;
m_TrackNum = 0;
m_pTrainData = NULL;
m_pStatModel = NULL;
m_DataFileName[0] = 0;
m_pStatImg = NULL;
m_LastTrainDataSize = 0;
m_NU = 0.2f;
AddParam("Nu",&m_NU);
CommentParam("Nu","Parameters that tunes SVM border elastic");
m_RBFWidth = 1;
AddParam("RBFWidth",&m_RBFWidth);
CommentParam("RBFWidth","Parameters that tunes RBF kernel function width.");
SetModuleName("SVM");
} /* Constructor. */
~CvBlobTrackAnalysisSVM()
{
int i;
SaveStatModel();
for(i=m_Tracks.GetBlobNum();i>0;--i)
{
DefTrackSVM* pF = (DefTrackSVM*)m_Tracks.GetBlob(i-1);
if(pF->pMem) cvReleaseMemStorage(&pF->pMem);
//pF->pFVGen->Release();
}
if(m_pStatImg)cvReleaseImage(&m_pStatImg);
cvFree(&m_pFV);
} /* Destructor. */
/*----------------- Interface: --------------------*/
virtual void AddBlob(CvBlob* pBlob)
{
DefTrackSVM* pF = (DefTrackSVM*)m_Tracks.GetBlobByID(CV_BLOB_ID(pBlob));
m_pFVGen->AddBlob(pBlob);
if(pF == NULL)
{ /* Create new record: */
DefTrackSVM F;
F.state = 0;
F.blob = pBlob[0];
F.LastFrame = m_Frame;
//F.pFVGen = m_CreateFVGen();
F.pMem = cvCreateMemStorage();
F.pFVSeq = cvCreateSeq(0,sizeof(CvSeq),sizeof(float)*m_Dim,F.pMem);
F.BlobLast.x = -1;
F.BlobLast.y = -1;
F.BlobLast.w = -1;
F.BlobLast.h = -1;
m_Tracks.AddBlob((CvBlob*)&F);
pF = (DefTrackSVM*)m_Tracks.GetBlobByID(CV_BLOB_ID(pBlob));
}
assert(pF);
pF->blob = pBlob[0];
pF->LastFrame = m_Frame;
};
virtual void Process(IplImage* pImg, IplImage* pFG)
{
int i;
float* pFVVar = m_pFVGen->GetFVVar();
m_pFVGen->Process(pImg, pFG);
m_ImgSize = cvSize(pImg->width,pImg->height);
for(i=m_pFVGen->GetFVNum(); i>0; --i)
{
int BlobID = 0;
float* pFV = m_pFVGen->GetFV(i,&BlobID);
DefTrackSVM* pF = (DefTrackSVM*)m_Tracks.GetBlobByID(BlobID);
if(pF && pFV)
{ /* Process: */
float dx,dy;
CvMat FVmat;
pF->state = 0;
if(m_pStatModel)
{
int j;
for(j=0; j<m_Dim; ++j)
{
m_pFV[j] = pFV[j]/pFVVar[j];
}
cvInitMatHeader( &FVmat, 1, m_Dim, CV_32F, m_pFV );
//pF->state = cvStatModelPredict( m_pStatModel, &FVmat, NULL )<0.5;
pF->state = 1.f;
}
dx = (pF->blob.x - pF->BlobLast.x);
dy = (pF->blob.y - pF->BlobLast.y);
if(pF->BlobLast.x<0 || (dx*dx+dy*dy) >= 2*2)
{ /* Add feature vector to train data base: */
pF->BlobLast = pF->blob;
cvSeqPush(pF->pFVSeq,pFV);
}
} /* Process one blob. */
} /* Next FV. */
for(i=m_Tracks.GetBlobNum(); i>0; --i)
{ /* Check each blob record: */
DefTrackSVM* pF = (DefTrackSVM*)m_Tracks.GetBlob(i-1);
if(pF->LastFrame+3 < m_Frame )
{ /* Retrain stat model and delete blob filter: */
int mult = 1+m_Dim;
int old_height = m_pTrainData?m_pTrainData->height:0;
int height = old_height + pF->pFVSeq->total*mult;
CvMat* pTrainData = cvCreateMat(height, m_Dim, CV_32F);
int j;
if(m_pTrainData && pTrainData)
{ /* Create new train data matrix: */
int h = pTrainData->height;
pTrainData->height = MIN(pTrainData->height, m_pTrainData->height);
cvCopy(m_pTrainData,pTrainData);
pTrainData->height = h;
}
for(j=0; j<pF->pFVSeq->total; ++j)
{ /* Copy new data to train data: */
float* pFVvar = m_pFVGen->GetFVVar();
float* pFV = (float*)cvGetSeqElem(pF->pFVSeq,j);
int k;
for(k=0; k<mult; ++k)
{
int t;
float* pTD = (float*)CV_MAT_ELEM_PTR( pTrainData[0], old_height+j*mult+k, 0);
memcpy(pTD,pFV,sizeof(float)*m_Dim);
if(pFVvar)for(t=0;t<m_Dim;++t)
{ /* Scale FV: */
pTD[t] /= pFVvar[t];
}
if(k>0)
{ /* Variate: */
for(t=0; t<m_Dim; ++t)
{
pTD[t] += m_RBFWidth*0.5f*(1-2.0f*rand()/(float)RAND_MAX);
}
}
}
} /* Next new datum. */
if(m_pTrainData) cvReleaseMat(&m_pTrainData);
m_pTrainData = pTrainData;
/* delete track record */
cvReleaseMemStorage(&pF->pMem);
m_TrackNum++;
m_Tracks.DelBlob(i-1);
} /* End delete. */
} /* Next track. */
/* Retrain data each 1 minute if new data exist: */
if(m_Frame%(25*60) == 0 && m_pTrainData && m_pTrainData->rows > m_LastTrainDataSize)
{
RetrainStatModel();
}
m_Frame++;
if(m_Wnd && m_Dim==2)
{ /* Debug output: */
int x,y;
IplImage* pI = cvCloneImage(pImg);
if(m_pStatModel && m_pStatImg)
for(y=0; y<pI->height; y+=2)
{
uchar* pStatData = (uchar*)m_pStatImg->imageData + y*m_pStatImg->widthStep;
uchar* pData = (uchar*)pI->imageData + y*pI->widthStep;
for(x=0;x<pI->width;x+=2)
{ /* Draw all elements: */
int d = pStatData[x];
d = (d<<8) | (d^0xff);
*(ushort*)(pData + x*3) = (ushort)d;
}
} /* Next line. */
//cvNamedWindow("SVMMap",0);
//cvShowImage("SVMMap", pI);
cvReleaseImage(&pI);
} /* Debug output. */
};
float GetState(int BlobID)
{
DefTrackSVM* pF = (DefTrackSVM*)m_Tracks.GetBlobByID(BlobID);
return pF?pF->state:0.0f;
};
/* Return 0 if trajectory is normal;
return >0 if trajectory abnormal. */
virtual const char* GetStateDesc(int BlobID)
{
if(GetState(BlobID)>0.5) return "abnormal";
return NULL;
}
virtual void SetFileName(char* DataBaseName)
{
if(m_pTrainData)SaveStatModel();
m_DataFileName[0] = m_DataFileName[1000] = 0;
if(DataBaseName)
{
strncpy(m_DataFileName,DataBaseName,1000);
strcat(m_DataFileName, ".yml");
}
LoadStatModel();
};
virtual void Release(){ delete this; };
}; /* CvBlobTrackAnalysisSVM. */
#if 0
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisSVMP()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisSVM(cvCreateFVGenP);}
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisSVMPV()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisSVM(cvCreateFVGenPV);}
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisSVMPVS()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisSVM(cvCreateFVGenPVS);}
CvBlobTrackAnalysis* cvCreateModuleBlobTrackAnalysisSVMSS()
{return (CvBlobTrackAnalysis*) new CvBlobTrackAnalysisSVM(cvCreateFVGenSS);}
#endif