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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*/
#ifndef __OPENCV_LEGACY_HPP__
#define __OPENCV_LEGACY_HPP__
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#ifdef __cplusplus
extern "C" {
#endif
CVAPI(CvSeq*) cvSegmentImage( const CvArr* srcarr, CvArr* dstarr,
double canny_threshold,
double ffill_threshold,
CvMemStorage* storage );
/****************************************************************************************\
* Eigen objects *
\****************************************************************************************/
typedef int (CV_CDECL * CvCallback)(int index, void* buffer, void* user_data);
typedef union
{
CvCallback callback;
void* data;
}
CvInput;
#define CV_EIGOBJ_NO_CALLBACK 0
#define CV_EIGOBJ_INPUT_CALLBACK 1
#define CV_EIGOBJ_OUTPUT_CALLBACK 2
#define CV_EIGOBJ_BOTH_CALLBACK 3
/* Calculates covariation matrix of a set of arrays */
CVAPI(void) cvCalcCovarMatrixEx( int nObjects, void* input, int ioFlags,
int ioBufSize, uchar* buffer, void* userData,
IplImage* avg, float* covarMatrix );
/* Calculates eigen values and vectors of covariation matrix of a set of
arrays */
CVAPI(void) cvCalcEigenObjects( int nObjects, void* input, void* output,
int ioFlags, int ioBufSize, void* userData,
CvTermCriteria* calcLimit, IplImage* avg,
float* eigVals );
/* Calculates dot product (obj - avg) * eigObj (i.e. projects image to eigen vector) */
CVAPI(double) cvCalcDecompCoeff( IplImage* obj, IplImage* eigObj, IplImage* avg );
/* Projects image to eigen space (finds all decomposion coefficients */
CVAPI(void) cvEigenDecomposite( IplImage* obj, int nEigObjs, void* eigInput,
int ioFlags, void* userData, IplImage* avg,
float* coeffs );
/* Projects original objects used to calculate eigen space basis to that space */
CVAPI(void) cvEigenProjection( void* eigInput, int nEigObjs, int ioFlags,
void* userData, float* coeffs, IplImage* avg,
IplImage* proj );
/****************************************************************************************\
* 1D/2D HMM *
\****************************************************************************************/
typedef struct CvImgObsInfo
{
int obs_x;
int obs_y;
int obs_size;
float* obs;//consequtive observations
int* state;/* arr of pairs superstate/state to which observation belong */
int* mix; /* number of mixture to which observation belong */
} CvImgObsInfo;/*struct for 1 image*/
typedef CvImgObsInfo Cv1DObsInfo;
typedef struct CvEHMMState
{
int num_mix; /*number of mixtures in this state*/
float* mu; /*mean vectors corresponding to each mixture*/
float* inv_var; /* square root of inversed variances corresp. to each mixture*/
float* log_var_val; /* sum of 0.5 (LN2PI + ln(variance[i]) ) for i=1,n */
float* weight; /*array of mixture weights. Summ of all weights in state is 1. */
} CvEHMMState;
typedef struct CvEHMM
{
int level; /* 0 - lowest(i.e its states are real states), ..... */
int num_states; /* number of HMM states */
float* transP;/*transition probab. matrices for states */
float** obsProb; /* if level == 0 - array of brob matrices corresponding to hmm
if level == 1 - martix of matrices */
union
{
CvEHMMState* state; /* if level == 0 points to real states array,
if not - points to embedded hmms */
struct CvEHMM* ehmm; /* pointer to an embedded model or NULL, if it is a leaf */
} u;
} CvEHMM;
/*CVAPI(int) icvCreate1DHMM( CvEHMM** this_hmm,
int state_number, int* num_mix, int obs_size );
CVAPI(int) icvRelease1DHMM( CvEHMM** phmm );
CVAPI(int) icvUniform1DSegm( Cv1DObsInfo* obs_info, CvEHMM* hmm );
CVAPI(int) icvInit1DMixSegm( Cv1DObsInfo** obs_info_array, int num_img, CvEHMM* hmm);
CVAPI(int) icvEstimate1DHMMStateParams( CvImgObsInfo** obs_info_array, int num_img, CvEHMM* hmm);
CVAPI(int) icvEstimate1DObsProb( CvImgObsInfo* obs_info, CvEHMM* hmm );
CVAPI(int) icvEstimate1DTransProb( Cv1DObsInfo** obs_info_array,
int num_seq,
CvEHMM* hmm );
CVAPI(float) icvViterbi( Cv1DObsInfo* obs_info, CvEHMM* hmm);
CVAPI(int) icv1DMixSegmL2( CvImgObsInfo** obs_info_array, int num_img, CvEHMM* hmm );*/
/*********************************** Embedded HMMs *************************************/
/* Creates 2D HMM */
CVAPI(CvEHMM*) cvCreate2DHMM( int* stateNumber, int* numMix, int obsSize );
/* Releases HMM */
CVAPI(void) cvRelease2DHMM( CvEHMM** hmm );
#define CV_COUNT_OBS(roi, win, delta, numObs ) \
{ \
(numObs)->width =((roi)->width -(win)->width +(delta)->width)/(delta)->width; \
(numObs)->height =((roi)->height -(win)->height +(delta)->height)/(delta)->height;\
}
/* Creates storage for observation vectors */
CVAPI(CvImgObsInfo*) cvCreateObsInfo( CvSize numObs, int obsSize );
/* Releases storage for observation vectors */
CVAPI(void) cvReleaseObsInfo( CvImgObsInfo** obs_info );
/* The function takes an image on input and and returns the sequnce of observations
to be used with an embedded HMM; Each observation is top-left block of DCT
coefficient matrix */
CVAPI(void) cvImgToObs_DCT( const CvArr* arr, float* obs, CvSize dctSize,
CvSize obsSize, CvSize delta );
/* Uniformly segments all observation vectors extracted from image */
CVAPI(void) cvUniformImgSegm( CvImgObsInfo* obs_info, CvEHMM* ehmm );
/* Does mixture segmentation of the states of embedded HMM */
CVAPI(void) cvInitMixSegm( CvImgObsInfo** obs_info_array,
int num_img, CvEHMM* hmm );
/* Function calculates means, variances, weights of every Gaussian mixture
of every low-level state of embedded HMM */
CVAPI(void) cvEstimateHMMStateParams( CvImgObsInfo** obs_info_array,
int num_img, CvEHMM* hmm );
/* Function computes transition probability matrices of embedded HMM
given observations segmentation */
CVAPI(void) cvEstimateTransProb( CvImgObsInfo** obs_info_array,
int num_img, CvEHMM* hmm );
/* Function computes probabilities of appearing observations at any state
(i.e. computes P(obs|state) for every pair(obs,state)) */
CVAPI(void) cvEstimateObsProb( CvImgObsInfo* obs_info,
CvEHMM* hmm );
/* Runs Viterbi algorithm for embedded HMM */
CVAPI(float) cvEViterbi( CvImgObsInfo* obs_info, CvEHMM* hmm );
/* Function clusters observation vectors from several images
given observations segmentation.
Euclidean distance used for clustering vectors.
Centers of clusters are given means of every mixture */
CVAPI(void) cvMixSegmL2( CvImgObsInfo** obs_info_array,
int num_img, CvEHMM* hmm );
/****************************************************************************************\
* A few functions from old stereo gesture recognition demosions *
\****************************************************************************************/
/* Creates hand mask image given several points on the hand */
CVAPI(void) cvCreateHandMask( CvSeq* hand_points,
IplImage *img_mask, CvRect *roi);
/* Finds hand region in range image data */
CVAPI(void) cvFindHandRegion (CvPoint3D32f* points, int count,
CvSeq* indexs,
float* line, CvSize2D32f size, int flag,
CvPoint3D32f* center,
CvMemStorage* storage, CvSeq **numbers);
/* Finds hand region in range image data (advanced version) */
CVAPI(void) cvFindHandRegionA( CvPoint3D32f* points, int count,
CvSeq* indexs,
float* line, CvSize2D32f size, int jc,
CvPoint3D32f* center,
CvMemStorage* storage, CvSeq **numbers);
/* Calculates the cooficients of the homography matrix */
CVAPI(void) cvCalcImageHomography( float* line, CvPoint3D32f* center,
float* intrinsic, float* homography );
/****************************************************************************************\
* Additional operations on Subdivisions *
\****************************************************************************************/
// paints voronoi diagram: just demo function
CVAPI(void) icvDrawMosaic( CvSubdiv2D* subdiv, IplImage* src, IplImage* dst );
// checks planar subdivision for correctness. It is not an absolute check,
// but it verifies some relations between quad-edges
CVAPI(int) icvSubdiv2DCheck( CvSubdiv2D* subdiv );
// returns squared distance between two 2D points with floating-point coordinates.
CV_INLINE double icvSqDist2D32f( CvPoint2D32f pt1, CvPoint2D32f pt2 )
{
double dx = pt1.x - pt2.x;
double dy = pt1.y - pt2.y;
return dx*dx + dy*dy;
}
/****************************************************************************************\
* More operations on sequences *
\****************************************************************************************/
/*****************************************************************************************/
#define CV_CURRENT_INT( reader ) (*((int *)(reader).ptr))
#define CV_PREV_INT( reader ) (*((int *)(reader).prev_elem))
#define CV_GRAPH_WEIGHTED_VERTEX_FIELDS() CV_GRAPH_VERTEX_FIELDS()\
float weight;
#define CV_GRAPH_WEIGHTED_EDGE_FIELDS() CV_GRAPH_EDGE_FIELDS()
typedef struct CvGraphWeightedVtx
{
CV_GRAPH_WEIGHTED_VERTEX_FIELDS()
} CvGraphWeightedVtx;
typedef struct CvGraphWeightedEdge
{
CV_GRAPH_WEIGHTED_EDGE_FIELDS()
} CvGraphWeightedEdge;
typedef enum CvGraphWeightType
{
CV_NOT_WEIGHTED,
CV_WEIGHTED_VTX,
CV_WEIGHTED_EDGE,
CV_WEIGHTED_ALL
} CvGraphWeightType;
/* Calculates histogram of a contour */
CVAPI(void) cvCalcPGH( const CvSeq* contour, CvHistogram* hist );
#define CV_DOMINANT_IPAN 1
/* Finds high-curvature points of the contour */
CVAPI(CvSeq*) cvFindDominantPoints( CvSeq* contour, CvMemStorage* storage,
int method CV_DEFAULT(CV_DOMINANT_IPAN),
double parameter1 CV_DEFAULT(0),
double parameter2 CV_DEFAULT(0),
double parameter3 CV_DEFAULT(0),
double parameter4 CV_DEFAULT(0));
/*****************************************************************************************/
/*******************************Stereo correspondence*************************************/
typedef struct CvCliqueFinder
{
CvGraph* graph;
int** adj_matr;
int N; //graph size
// stacks, counters etc/
int k; //stack size
int* current_comp;
int** All;
int* ne;
int* ce;
int* fixp; //node with minimal disconnections
int* nod;
int* s; //for selected candidate
int status;
int best_score;
int weighted;
int weighted_edges;
float best_weight;
float* edge_weights;
float* vertex_weights;
float* cur_weight;
float* cand_weight;
} CvCliqueFinder;
#define CLIQUE_TIME_OFF 2
#define CLIQUE_FOUND 1
#define CLIQUE_END 0
/*CVAPI(void) cvStartFindCliques( CvGraph* graph, CvCliqueFinder* finder, int reverse,
int weighted CV_DEFAULT(0), int weighted_edges CV_DEFAULT(0));
CVAPI(int) cvFindNextMaximalClique( CvCliqueFinder* finder, int* clock_rest CV_DEFAULT(0) );
CVAPI(void) cvEndFindCliques( CvCliqueFinder* finder );
CVAPI(void) cvBronKerbosch( CvGraph* graph );*/
/*F///////////////////////////////////////////////////////////////////////////////////////
//
// Name: cvSubgraphWeight
// Purpose: finds weight of subgraph in a graph
// Context:
// Parameters:
// graph - input graph.
// subgraph - sequence of pairwise different ints. These are indices of vertices of subgraph.
// weight_type - describes the way we measure weight.
// one of the following:
// CV_NOT_WEIGHTED - weight of a clique is simply its size
// CV_WEIGHTED_VTX - weight of a clique is the sum of weights of its vertices
// CV_WEIGHTED_EDGE - the same but edges
// CV_WEIGHTED_ALL - the same but both edges and vertices
// weight_vtx - optional vector of floats, with size = graph->total.
// If weight_type is either CV_WEIGHTED_VTX or CV_WEIGHTED_ALL
// weights of vertices must be provided. If weight_vtx not zero
// these weights considered to be here, otherwise function assumes
// that vertices of graph are inherited from CvGraphWeightedVtx.
// weight_edge - optional matrix of floats, of width and height = graph->total.
// If weight_type is either CV_WEIGHTED_EDGE or CV_WEIGHTED_ALL
// weights of edges ought to be supplied. If weight_edge is not zero
// function finds them here, otherwise function expects
// edges of graph to be inherited from CvGraphWeightedEdge.
// If this parameter is not zero structure of the graph is determined from matrix
// rather than from CvGraphEdge's. In particular, elements corresponding to
// absent edges should be zero.
// Returns:
// weight of subgraph.
// Notes:
//F*/
/*CVAPI(float) cvSubgraphWeight( CvGraph *graph, CvSeq *subgraph,
CvGraphWeightType weight_type CV_DEFAULT(CV_NOT_WEIGHTED),
CvVect32f weight_vtx CV_DEFAULT(0),
CvMatr32f weight_edge CV_DEFAULT(0) );*/
/*F///////////////////////////////////////////////////////////////////////////////////////
//
// Name: cvFindCliqueEx
// Purpose: tries to find clique with maximum possible weight in a graph
// Context:
// Parameters:
// graph - input graph.
// storage - memory storage to be used by the result.
// is_complementary - optional flag showing whether function should seek for clique
// in complementary graph.
// weight_type - describes our notion about weight.
// one of the following:
// CV_NOT_WEIGHTED - weight of a clique is simply its size
// CV_WEIGHTED_VTX - weight of a clique is the sum of weights of its vertices
// CV_WEIGHTED_EDGE - the same but edges
// CV_WEIGHTED_ALL - the same but both edges and vertices
// weight_vtx - optional vector of floats, with size = graph->total.
// If weight_type is either CV_WEIGHTED_VTX or CV_WEIGHTED_ALL
// weights of vertices must be provided. If weight_vtx not zero
// these weights considered to be here, otherwise function assumes
// that vertices of graph are inherited from CvGraphWeightedVtx.
// weight_edge - optional matrix of floats, of width and height = graph->total.
// If weight_type is either CV_WEIGHTED_EDGE or CV_WEIGHTED_ALL
// weights of edges ought to be supplied. If weight_edge is not zero
// function finds them here, otherwise function expects
// edges of graph to be inherited from CvGraphWeightedEdge.
// Note that in case of CV_WEIGHTED_EDGE or CV_WEIGHTED_ALL
// nonzero is_complementary implies nonzero weight_edge.
// start_clique - optional sequence of pairwise different ints. They are indices of
// vertices that shall be present in the output clique.
// subgraph_of_ban - optional sequence of (maybe equal) ints. They are indices of
// vertices that shall not be present in the output clique.
// clique_weight_ptr - optional output parameter. Weight of found clique stored here.
// num_generations - optional number of generations in evolutionary part of algorithm,
// zero forces to return first found clique.
// quality - optional parameter determining degree of required quality/speed tradeoff.
// Must be in the range from 0 to 9.
// 0 is fast and dirty, 9 is slow but hopefully yields good clique.
// Returns:
// sequence of pairwise different ints.
// These are indices of vertices that form found clique.
// Notes:
// in cases of CV_WEIGHTED_EDGE and CV_WEIGHTED_ALL weights should be nonnegative.
// start_clique has a priority over subgraph_of_ban.
//F*/
/*CVAPI(CvSeq*) cvFindCliqueEx( CvGraph *graph, CvMemStorage *storage,
int is_complementary CV_DEFAULT(0),
CvGraphWeightType weight_type CV_DEFAULT(CV_NOT_WEIGHTED),
CvVect32f weight_vtx CV_DEFAULT(0),
CvMatr32f weight_edge CV_DEFAULT(0),
CvSeq *start_clique CV_DEFAULT(0),
CvSeq *subgraph_of_ban CV_DEFAULT(0),
float *clique_weight_ptr CV_DEFAULT(0),
int num_generations CV_DEFAULT(3),
int quality CV_DEFAULT(2) );*/
#define CV_UNDEF_SC_PARAM 12345 //default value of parameters
#define CV_IDP_BIRCHFIELD_PARAM1 25
#define CV_IDP_BIRCHFIELD_PARAM2 5
#define CV_IDP_BIRCHFIELD_PARAM3 12
#define CV_IDP_BIRCHFIELD_PARAM4 15
#define CV_IDP_BIRCHFIELD_PARAM5 25
#define CV_DISPARITY_BIRCHFIELD 0
/*F///////////////////////////////////////////////////////////////////////////
//
// Name: cvFindStereoCorrespondence
// Purpose: find stereo correspondence on stereo-pair
// Context:
// Parameters:
// leftImage - left image of stereo-pair (format 8uC1).
// rightImage - right image of stereo-pair (format 8uC1).
// mode - mode of correspondence retrieval (now CV_DISPARITY_BIRCHFIELD only)
// dispImage - destination disparity image
// maxDisparity - maximal disparity
// param1, param2, param3, param4, param5 - parameters of algorithm
// Returns:
// Notes:
// Images must be rectified.
// All images must have format 8uC1.
//F*/
CVAPI(void)
cvFindStereoCorrespondence(
const CvArr* leftImage, const CvArr* rightImage,
int mode,
CvArr* dispImage,
int maxDisparity,
double param1 CV_DEFAULT(CV_UNDEF_SC_PARAM),
double param2 CV_DEFAULT(CV_UNDEF_SC_PARAM),
double param3 CV_DEFAULT(CV_UNDEF_SC_PARAM),
double param4 CV_DEFAULT(CV_UNDEF_SC_PARAM),
double param5 CV_DEFAULT(CV_UNDEF_SC_PARAM) );
/*****************************************************************************************/
/************ Epiline functions *******************/
typedef struct CvStereoLineCoeff
{
double Xcoef;
double XcoefA;
double XcoefB;
double XcoefAB;
double Ycoef;
double YcoefA;
double YcoefB;
double YcoefAB;
double Zcoef;
double ZcoefA;
double ZcoefB;
double ZcoefAB;
}CvStereoLineCoeff;
typedef struct CvCamera
{
float imgSize[2]; /* size of the camera view, used during calibration */
float matrix[9]; /* intinsic camera parameters: [ fx 0 cx; 0 fy cy; 0 0 1 ] */
float distortion[4]; /* distortion coefficients - two coefficients for radial distortion
and another two for tangential: [ k1 k2 p1 p2 ] */
float rotMatr[9];
float transVect[3]; /* rotation matrix and transition vector relatively
to some reference point in the space. */
} CvCamera;
typedef struct CvStereoCamera
{
CvCamera* camera[2]; /* two individual camera parameters */
float fundMatr[9]; /* fundamental matrix */
/* New part for stereo */
CvPoint3D32f epipole[2];
CvPoint2D32f quad[2][4]; /* coordinates of destination quadrangle after
epipolar geometry rectification */
double coeffs[2][3][3];/* coefficients for transformation */
CvPoint2D32f border[2][4];
CvSize warpSize;
CvStereoLineCoeff* lineCoeffs;
int needSwapCameras;/* flag set to 1 if need to swap cameras for good reconstruction */
float rotMatrix[9];
float transVector[3];
} CvStereoCamera;
typedef struct CvContourOrientation
{
float egvals[2];
float egvects[4];
float max, min; // minimum and maximum projections
int imax, imin;
} CvContourOrientation;
#define CV_CAMERA_TO_WARP 1
#define CV_WARP_TO_CAMERA 2
CVAPI(int) icvConvertWarpCoordinates(double coeffs[3][3],
CvPoint2D32f* cameraPoint,
CvPoint2D32f* warpPoint,
int direction);
CVAPI(int) icvGetSymPoint3D( CvPoint3D64f pointCorner,
CvPoint3D64f point1,
CvPoint3D64f point2,
CvPoint3D64f *pointSym2);
CVAPI(void) icvGetPieceLength3D(CvPoint3D64f point1,CvPoint3D64f point2,double* dist);
CVAPI(int) icvCompute3DPoint( double alpha,double betta,
CvStereoLineCoeff* coeffs,
CvPoint3D64f* point);
CVAPI(int) icvCreateConvertMatrVect( CvMatr64d rotMatr1,
CvMatr64d transVect1,
CvMatr64d rotMatr2,
CvMatr64d transVect2,
CvMatr64d convRotMatr,
CvMatr64d convTransVect);
CVAPI(int) icvConvertPointSystem(CvPoint3D64f M2,
CvPoint3D64f* M1,
CvMatr64d rotMatr,
CvMatr64d transVect
);
CVAPI(int) icvComputeCoeffForStereo( CvStereoCamera* stereoCamera);
CVAPI(int) icvGetCrossPieceVector(CvPoint2D32f p1_start,CvPoint2D32f p1_end,CvPoint2D32f v2_start,CvPoint2D32f v2_end,CvPoint2D32f *cross);
CVAPI(int) icvGetCrossLineDirect(CvPoint2D32f p1,CvPoint2D32f p2,float a,float b,float c,CvPoint2D32f* cross);
CVAPI(float) icvDefinePointPosition(CvPoint2D32f point1,CvPoint2D32f point2,CvPoint2D32f point);
CVAPI(int) icvStereoCalibration( int numImages,
int* nums,
CvSize imageSize,
CvPoint2D32f* imagePoints1,
CvPoint2D32f* imagePoints2,
CvPoint3D32f* objectPoints,
CvStereoCamera* stereoparams
);
CVAPI(int) icvComputeRestStereoParams(CvStereoCamera *stereoparams);
CVAPI(void) cvComputePerspectiveMap( const double coeffs[3][3], CvArr* rectMapX, CvArr* rectMapY );
CVAPI(int) icvComCoeffForLine( CvPoint2D64f point1,
CvPoint2D64f point2,
CvPoint2D64f point3,
CvPoint2D64f point4,
CvMatr64d camMatr1,
CvMatr64d rotMatr1,
CvMatr64d transVect1,
CvMatr64d camMatr2,
CvMatr64d rotMatr2,
CvMatr64d transVect2,
CvStereoLineCoeff* coeffs,
int* needSwapCameras);
CVAPI(int) icvGetDirectionForPoint( CvPoint2D64f point,
CvMatr64d camMatr,
CvPoint3D64f* direct);
CVAPI(int) icvGetCrossLines(CvPoint3D64f point11,CvPoint3D64f point12,
CvPoint3D64f point21,CvPoint3D64f point22,
CvPoint3D64f* midPoint);
CVAPI(int) icvComputeStereoLineCoeffs( CvPoint3D64f pointA,
CvPoint3D64f pointB,
CvPoint3D64f pointCam1,
double gamma,
CvStereoLineCoeff* coeffs);
/*CVAPI(int) icvComputeFundMatrEpipoles ( CvMatr64d camMatr1,
CvMatr64d rotMatr1,
CvVect64d transVect1,
CvMatr64d camMatr2,
CvMatr64d rotMatr2,
CvVect64d transVect2,
CvPoint2D64f* epipole1,
CvPoint2D64f* epipole2,
CvMatr64d fundMatr);*/
CVAPI(int) icvGetAngleLine( CvPoint2D64f startPoint, CvSize imageSize,CvPoint2D64f *point1,CvPoint2D64f *point2);
CVAPI(void) icvGetCoefForPiece( CvPoint2D64f p_start,CvPoint2D64f p_end,
double *a,double *b,double *c,
int* result);
/*CVAPI(void) icvGetCommonArea( CvSize imageSize,
CvPoint2D64f epipole1,CvPoint2D64f epipole2,
CvMatr64d fundMatr,
CvVect64d coeff11,CvVect64d coeff12,
CvVect64d coeff21,CvVect64d coeff22,
int* result);*/
CVAPI(void) icvComputeeInfiniteProject1(CvMatr64d rotMatr,
CvMatr64d camMatr1,
CvMatr64d camMatr2,
CvPoint2D32f point1,
CvPoint2D32f *point2);
CVAPI(void) icvComputeeInfiniteProject2(CvMatr64d rotMatr,
CvMatr64d camMatr1,
CvMatr64d camMatr2,
CvPoint2D32f* point1,
CvPoint2D32f point2);
CVAPI(void) icvGetCrossDirectDirect( CvVect64d direct1,CvVect64d direct2,
CvPoint2D64f *cross,int* result);
CVAPI(void) icvGetCrossPieceDirect( CvPoint2D64f p_start,CvPoint2D64f p_end,
double a,double b,double c,
CvPoint2D64f *cross,int* result);
CVAPI(void) icvGetCrossPiecePiece( CvPoint2D64f p1_start,CvPoint2D64f p1_end,
CvPoint2D64f p2_start,CvPoint2D64f p2_end,
CvPoint2D64f* cross,
int* result);
CVAPI(void) icvGetPieceLength(CvPoint2D64f point1,CvPoint2D64f point2,double* dist);
CVAPI(void) icvGetCrossRectDirect( CvSize imageSize,
double a,double b,double c,
CvPoint2D64f *start,CvPoint2D64f *end,
int* result);
CVAPI(void) icvProjectPointToImage( CvPoint3D64f point,
CvMatr64d camMatr,CvMatr64d rotMatr,CvVect64d transVect,
CvPoint2D64f* projPoint);
CVAPI(void) icvGetQuadsTransform( CvSize imageSize,
CvMatr64d camMatr1,
CvMatr64d rotMatr1,
CvVect64d transVect1,
CvMatr64d camMatr2,
CvMatr64d rotMatr2,
CvVect64d transVect2,
CvSize* warpSize,
double quad1[4][2],
double quad2[4][2],
CvMatr64d fundMatr,
CvPoint3D64f* epipole1,
CvPoint3D64f* epipole2
);
CVAPI(void) icvGetQuadsTransformStruct( CvStereoCamera* stereoCamera);
CVAPI(void) icvComputeStereoParamsForCameras(CvStereoCamera* stereoCamera);
CVAPI(void) icvGetCutPiece( CvVect64d areaLineCoef1,CvVect64d areaLineCoef2,
CvPoint2D64f epipole,
CvSize imageSize,
CvPoint2D64f* point11,CvPoint2D64f* point12,
CvPoint2D64f* point21,CvPoint2D64f* point22,
int* result);
CVAPI(void) icvGetMiddleAnglePoint( CvPoint2D64f basePoint,
CvPoint2D64f point1,CvPoint2D64f point2,
CvPoint2D64f* midPoint);
CVAPI(void) icvGetNormalDirect(CvVect64d direct,CvPoint2D64f point,CvVect64d normDirect);
CVAPI(double) icvGetVect(CvPoint2D64f basePoint,CvPoint2D64f point1,CvPoint2D64f point2);
CVAPI(void) icvProjectPointToDirect( CvPoint2D64f point,CvVect64d lineCoeff,
CvPoint2D64f* projectPoint);
CVAPI(void) icvGetDistanceFromPointToDirect( CvPoint2D64f point,CvVect64d lineCoef,double*dist);
CVAPI(IplImage*) icvCreateIsometricImage( IplImage* src, IplImage* dst,
int desired_depth, int desired_num_channels );
CVAPI(void) cvDeInterlace( const CvArr* frame, CvArr* fieldEven, CvArr* fieldOdd );
/*CVAPI(int) icvSelectBestRt( int numImages,
int* numPoints,
CvSize imageSize,
CvPoint2D32f* imagePoints1,
CvPoint2D32f* imagePoints2,
CvPoint3D32f* objectPoints,
CvMatr32f cameraMatrix1,
CvVect32f distortion1,
CvMatr32f rotMatrs1,
CvVect32f transVects1,
CvMatr32f cameraMatrix2,
CvVect32f distortion2,
CvMatr32f rotMatrs2,
CvVect32f transVects2,
CvMatr32f bestRotMatr,
CvVect32f bestTransVect
);*/
/****************************************************************************************\
* Contour Tree *
\****************************************************************************************/
/* Contour tree header */
typedef struct CvContourTree
{
CV_SEQUENCE_FIELDS()
CvPoint p1; /* the first point of the binary tree root segment */
CvPoint p2; /* the last point of the binary tree root segment */
} CvContourTree;
/* Builds hierarhical representation of a contour */
CVAPI(CvContourTree*) cvCreateContourTree( const CvSeq* contour,
CvMemStorage* storage,
double threshold );
/* Reconstruct (completelly or partially) contour a from contour tree */
CVAPI(CvSeq*) cvContourFromContourTree( const CvContourTree* tree,
CvMemStorage* storage,
CvTermCriteria criteria );
/* Compares two contour trees */
enum { CV_CONTOUR_TREES_MATCH_I1 = 1 };
CVAPI(double) cvMatchContourTrees( const CvContourTree* tree1,
const CvContourTree* tree2,
int method, double threshold );
/****************************************************************************************\
* Contour Morphing *
\****************************************************************************************/
/* finds correspondence between two contours */
CvSeq* cvCalcContoursCorrespondence( const CvSeq* contour1,
const CvSeq* contour2,
CvMemStorage* storage);
/* morphs contours using the pre-calculated correspondence:
alpha=0 ~ contour1, alpha=1 ~ contour2 */
CvSeq* cvMorphContours( const CvSeq* contour1, const CvSeq* contour2,
CvSeq* corr, double alpha,
CvMemStorage* storage );
/****************************************************************************************\
* Active Contours *
\****************************************************************************************/
#define CV_VALUE 1
#define CV_ARRAY 2
/* Updates active contour in order to minimize its cummulative
(internal and external) energy. */
CVAPI(void) cvSnakeImage( const IplImage* image, CvPoint* points,
int length, float* alpha,
float* beta, float* gamma,
int coeff_usage, CvSize win,
CvTermCriteria criteria, int calc_gradient CV_DEFAULT(1));
/****************************************************************************************\
* Texture Descriptors *
\****************************************************************************************/
#define CV_GLCM_OPTIMIZATION_NONE -2
#define CV_GLCM_OPTIMIZATION_LUT -1
#define CV_GLCM_OPTIMIZATION_HISTOGRAM 0
#define CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST 10
#define CV_GLCMDESC_OPTIMIZATION_ALLOWTRIPLENEST 11
#define CV_GLCMDESC_OPTIMIZATION_HISTOGRAM 4
#define CV_GLCMDESC_ENTROPY 0
#define CV_GLCMDESC_ENERGY 1
#define CV_GLCMDESC_HOMOGENITY 2
#define CV_GLCMDESC_CONTRAST 3
#define CV_GLCMDESC_CLUSTERTENDENCY 4
#define CV_GLCMDESC_CLUSTERSHADE 5
#define CV_GLCMDESC_CORRELATION 6
#define CV_GLCMDESC_CORRELATIONINFO1 7
#define CV_GLCMDESC_CORRELATIONINFO2 8
#define CV_GLCMDESC_MAXIMUMPROBABILITY 9
#define CV_GLCM_ALL 0
#define CV_GLCM_GLCM 1
#define CV_GLCM_DESC 2
typedef struct CvGLCM CvGLCM;
CVAPI(CvGLCM*) cvCreateGLCM( const IplImage* srcImage,
int stepMagnitude,
const int* stepDirections CV_DEFAULT(0),
int numStepDirections CV_DEFAULT(0),
int optimizationType CV_DEFAULT(CV_GLCM_OPTIMIZATION_NONE));
CVAPI(void) cvReleaseGLCM( CvGLCM** GLCM, int flag CV_DEFAULT(CV_GLCM_ALL));
CVAPI(void) cvCreateGLCMDescriptors( CvGLCM* destGLCM,
int descriptorOptimizationType
CV_DEFAULT(CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST));
CVAPI(double) cvGetGLCMDescriptor( CvGLCM* GLCM, int step, int descriptor );
CVAPI(void) cvGetGLCMDescriptorStatistics( CvGLCM* GLCM, int descriptor,
double* average, double* standardDeviation );
CVAPI(IplImage*) cvCreateGLCMImage( CvGLCM* GLCM, int step );
/****************************************************************************************\
* Face eyes&mouth tracking *
\****************************************************************************************/
typedef struct CvFaceTracker CvFaceTracker;
#define CV_NUM_FACE_ELEMENTS 3
enum CV_FACE_ELEMENTS
{
CV_FACE_MOUTH = 0,
CV_FACE_LEFT_EYE = 1,
CV_FACE_RIGHT_EYE = 2
};
CVAPI(CvFaceTracker*) cvInitFaceTracker(CvFaceTracker* pFaceTracking, const IplImage* imgGray,
CvRect* pRects, int nRects);
CVAPI(int) cvTrackFace( CvFaceTracker* pFaceTracker, IplImage* imgGray,
CvRect* pRects, int nRects,
CvPoint* ptRotate, double* dbAngleRotate);
CVAPI(void) cvReleaseFaceTracker(CvFaceTracker** ppFaceTracker);
typedef struct CvFace
{
CvRect MouthRect;
CvRect LeftEyeRect;
CvRect RightEyeRect;
} CvFaceData;
CvSeq * cvFindFace(IplImage * Image,CvMemStorage* storage);
CvSeq * cvPostBoostingFindFace(IplImage * Image,CvMemStorage* storage);
/****************************************************************************************\
* 3D Tracker *
\****************************************************************************************/
typedef unsigned char CvBool;
typedef struct
{
int id;
CvPoint2D32f p; // pgruebele: So we do not loose precision, this needs to be float
} Cv3dTracker2dTrackedObject;
CV_INLINE Cv3dTracker2dTrackedObject cv3dTracker2dTrackedObject(int id, CvPoint2D32f p)
{
Cv3dTracker2dTrackedObject r;
r.id = id;
r.p = p;
return r;
}
typedef struct
{
int id;
CvPoint3D32f p; // location of the tracked object
} Cv3dTrackerTrackedObject;
CV_INLINE Cv3dTrackerTrackedObject cv3dTrackerTrackedObject(int id, CvPoint3D32f p)
{
Cv3dTrackerTrackedObject r;
r.id = id;
r.p = p;
return r;
}
typedef struct
{
CvBool valid;
float mat[4][4]; /* maps camera coordinates to world coordinates */
CvPoint2D32f principal_point; /* copied from intrinsics so this structure */
/* has all the info we need */
} Cv3dTrackerCameraInfo;
typedef struct
{
CvPoint2D32f principal_point;
float focal_length[2];
float distortion[4];
} Cv3dTrackerCameraIntrinsics;
CVAPI(CvBool) cv3dTrackerCalibrateCameras(int num_cameras,
const Cv3dTrackerCameraIntrinsics camera_intrinsics[], /* size is num_cameras */
CvSize etalon_size,
float square_size,
IplImage *samples[], /* size is num_cameras */
Cv3dTrackerCameraInfo camera_info[]); /* size is num_cameras */
CVAPI(int) cv3dTrackerLocateObjects(int num_cameras, int num_objects,
const Cv3dTrackerCameraInfo camera_info[], /* size is num_cameras */
const Cv3dTracker2dTrackedObject tracking_info[], /* size is num_objects*num_cameras */
Cv3dTrackerTrackedObject tracked_objects[]); /* size is num_objects */
/****************************************************************************************
tracking_info is a rectangular array; one row per camera, num_objects elements per row.
The id field of any unused slots must be -1. Ids need not be ordered or consecutive. On
completion, the return value is the number of objects located; i.e., the number of objects
visible by more than one camera. The id field of any unused slots in tracked objects is
set to -1.
****************************************************************************************/
/****************************************************************************************\
* Skeletons and Linear-Contour Models *
\****************************************************************************************/
typedef enum CvLeeParameters
{
CV_LEE_INT = 0,
CV_LEE_FLOAT = 1,
CV_LEE_DOUBLE = 2,
CV_LEE_AUTO = -1,
CV_LEE_ERODE = 0,
CV_LEE_ZOOM = 1,
CV_LEE_NON = 2
} CvLeeParameters;
#define CV_NEXT_VORONOISITE2D( SITE ) ((SITE)->edge[0]->site[((SITE)->edge[0]->site[0] == (SITE))])
#define CV_PREV_VORONOISITE2D( SITE ) ((SITE)->edge[1]->site[((SITE)->edge[1]->site[0] == (SITE))])
#define CV_FIRST_VORONOIEDGE2D( SITE ) ((SITE)->edge[0])
#define CV_LAST_VORONOIEDGE2D( SITE ) ((SITE)->edge[1])
#define CV_NEXT_VORONOIEDGE2D( EDGE, SITE ) ((EDGE)->next[(EDGE)->site[0] != (SITE)])
#define CV_PREV_VORONOIEDGE2D( EDGE, SITE ) ((EDGE)->next[2 + ((EDGE)->site[0] != (SITE))])
#define CV_VORONOIEDGE2D_BEGINNODE( EDGE, SITE ) ((EDGE)->node[((EDGE)->site[0] != (SITE))])
#define CV_VORONOIEDGE2D_ENDNODE( EDGE, SITE ) ((EDGE)->node[((EDGE)->site[0] == (SITE))])
#define CV_TWIN_VORONOISITE2D( SITE, EDGE ) ( (EDGE)->site[((EDGE)->site[0] == (SITE))])
#define CV_VORONOISITE2D_FIELDS() \
struct CvVoronoiNode2D *node[2]; \
struct CvVoronoiEdge2D *edge[2];
typedef struct CvVoronoiSite2D
{
CV_VORONOISITE2D_FIELDS()
struct CvVoronoiSite2D *next[2];
} CvVoronoiSite2D;
#define CV_VORONOIEDGE2D_FIELDS() \
struct CvVoronoiNode2D *node[2]; \
struct CvVoronoiSite2D *site[2]; \
struct CvVoronoiEdge2D *next[4];
typedef struct CvVoronoiEdge2D
{
CV_VORONOIEDGE2D_FIELDS()
} CvVoronoiEdge2D;
#define CV_VORONOINODE2D_FIELDS() \
CV_SET_ELEM_FIELDS(CvVoronoiNode2D) \
CvPoint2D32f pt; \
float radius;
typedef struct CvVoronoiNode2D
{
CV_VORONOINODE2D_FIELDS()
} CvVoronoiNode2D;
#define CV_VORONOIDIAGRAM2D_FIELDS() \
CV_GRAPH_FIELDS() \
CvSet *sites;
typedef struct CvVoronoiDiagram2D
{
CV_VORONOIDIAGRAM2D_FIELDS()
} CvVoronoiDiagram2D;
/* Computes Voronoi Diagram for given polygons with holes */
CVAPI(int) cvVoronoiDiagramFromContour(CvSeq* ContourSeq,
CvVoronoiDiagram2D** VoronoiDiagram,
CvMemStorage* VoronoiStorage,
CvLeeParameters contour_type CV_DEFAULT(CV_LEE_INT),
int contour_orientation CV_DEFAULT(-1),
int attempt_number CV_DEFAULT(10));
/* Computes Voronoi Diagram for domains in given image */
CVAPI(int) cvVoronoiDiagramFromImage(IplImage* pImage,
CvSeq** ContourSeq,
CvVoronoiDiagram2D** VoronoiDiagram,
CvMemStorage* VoronoiStorage,
CvLeeParameters regularization_method CV_DEFAULT(CV_LEE_NON),
float approx_precision CV_DEFAULT(CV_LEE_AUTO));
/* Deallocates the storage */
CVAPI(void) cvReleaseVoronoiStorage(CvVoronoiDiagram2D* VoronoiDiagram,
CvMemStorage** pVoronoiStorage);
/*********************** Linear-Contour Model ****************************/
struct CvLCMEdge;
struct CvLCMNode;
typedef struct CvLCMEdge
{
CV_GRAPH_EDGE_FIELDS()
CvSeq* chain;
float width;
int index1;
int index2;
} CvLCMEdge;
typedef struct CvLCMNode
{
CV_GRAPH_VERTEX_FIELDS()
CvContour* contour;
} CvLCMNode;
/* Computes hybrid model from Voronoi Diagram */
CVAPI(CvGraph*) cvLinearContorModelFromVoronoiDiagram(CvVoronoiDiagram2D* VoronoiDiagram,
float maxWidth);
/* Releases hybrid model storage */
CVAPI(int) cvReleaseLinearContorModelStorage(CvGraph** Graph);
/* two stereo-related functions */
CVAPI(void) cvInitPerspectiveTransform( CvSize size, const CvPoint2D32f vertex[4], double matrix[3][3],
CvArr* rectMap );
/*CVAPI(void) cvInitStereoRectification( CvStereoCamera* params,
CvArr* rectMap1, CvArr* rectMap2,
int do_undistortion );*/
/*************************** View Morphing Functions ************************/
/* The order of the function corresponds to the order they should appear in
the view morphing pipeline */
/* Finds ending points of scanlines on left and right images of stereo-pair */
CVAPI(void) cvMakeScanlines( const CvMatrix3* matrix, CvSize img_size,
int* scanlines1, int* scanlines2,
int* lengths1, int* lengths2,
int* line_count );
/* Grab pixel values from scanlines and stores them sequentially
(some sort of perspective image transform) */
CVAPI(void) cvPreWarpImage( int line_count,
IplImage* img,
uchar* dst,
int* dst_nums,
int* scanlines);
/* Approximate each grabbed scanline by a sequence of runs
(lossy run-length compression) */
CVAPI(void) cvFindRuns( int line_count,
uchar* prewarp1,
uchar* prewarp2,
int* line_lengths1,
int* line_lengths2,
int* runs1,
int* runs2,
int* num_runs1,
int* num_runs2);
/* Compares two sets of compressed scanlines */
CVAPI(void) cvDynamicCorrespondMulti( int line_count,
int* first,
int* first_runs,
int* second,
int* second_runs,
int* first_corr,
int* second_corr);
/* Finds scanline ending coordinates for some intermediate "virtual" camera position */
CVAPI(void) cvMakeAlphaScanlines( int* scanlines1,
int* scanlines2,
int* scanlinesA,
int* lengths,
int line_count,
float alpha);
/* Blends data of the left and right image scanlines to get
pixel values of "virtual" image scanlines */
CVAPI(void) cvMorphEpilinesMulti( int line_count,
uchar* first_pix,
int* first_num,
uchar* second_pix,
int* second_num,
uchar* dst_pix,
int* dst_num,
float alpha,
int* first,
int* first_runs,
int* second,
int* second_runs,
int* first_corr,
int* second_corr);
/* Does reverse warping of the morphing result to make
it fill the destination image rectangle */
CVAPI(void) cvPostWarpImage( int line_count,
uchar* src,
int* src_nums,
IplImage* img,
int* scanlines);
/* Deletes Moire (missed pixels that appear due to discretization) */
CVAPI(void) cvDeleteMoire( IplImage* img );
typedef struct CvConDensation
{
int MP;
int DP;
float* DynamMatr; /* Matrix of the linear Dynamics system */
float* State; /* Vector of State */
int SamplesNum; /* Number of the Samples */
float** flSamples; /* arr of the Sample Vectors */
float** flNewSamples; /* temporary array of the Sample Vectors */
float* flConfidence; /* Confidence for each Sample */
float* flCumulative; /* Cumulative confidence */
float* Temp; /* Temporary vector */
float* RandomSample; /* RandomVector to update sample set */
struct CvRandState* RandS; /* Array of structures to generate random vectors */
} CvConDensation;
/* Creates ConDensation filter state */
CVAPI(CvConDensation*) cvCreateConDensation( int dynam_params,
int measure_params,
int sample_count );
/* Releases ConDensation filter state */
CVAPI(void) cvReleaseConDensation( CvConDensation** condens );
/* Updates ConDensation filter by time (predict future state of the system) */
CVAPI(void) cvConDensUpdateByTime( CvConDensation* condens);
/* Initializes ConDensation filter samples */
CVAPI(void) cvConDensInitSampleSet( CvConDensation* condens, CvMat* lower_bound, CvMat* upper_bound );
CV_INLINE int iplWidth( const IplImage* img )
{
return !img ? 0 : !img->roi ? img->width : img->roi->width;
}
CV_INLINE int iplHeight( const IplImage* img )
{
return !img ? 0 : !img->roi ? img->height : img->roi->height;
}
#ifdef __cplusplus
}
#endif
#ifdef __cplusplus
/****************************************************************************************\
* Calibration engine *
\****************************************************************************************/
typedef enum CvCalibEtalonType
{
CV_CALIB_ETALON_USER = -1,
CV_CALIB_ETALON_CHESSBOARD = 0,
CV_CALIB_ETALON_CHECKERBOARD = CV_CALIB_ETALON_CHESSBOARD
}
CvCalibEtalonType;
class CV_EXPORTS CvCalibFilter
{
public:
/* Constructor & destructor */
CvCalibFilter();
virtual ~CvCalibFilter();
/* Sets etalon type - one for all cameras.
etalonParams is used in case of pre-defined etalons (such as chessboard).
Number of elements in etalonParams is determined by etalonType.
E.g., if etalon type is CV_ETALON_TYPE_CHESSBOARD then:
etalonParams[0] is number of squares per one side of etalon
etalonParams[1] is number of squares per another side of etalon
etalonParams[2] is linear size of squares in the board in arbitrary units.
pointCount & points are used in case of
CV_CALIB_ETALON_USER (user-defined) etalon. */
virtual bool
SetEtalon( CvCalibEtalonType etalonType, double* etalonParams,
int pointCount = 0, CvPoint2D32f* points = 0 );
/* Retrieves etalon parameters/or and points */
virtual CvCalibEtalonType
GetEtalon( int* paramCount = 0, const double** etalonParams = 0,
int* pointCount = 0, const CvPoint2D32f** etalonPoints = 0 ) const;
/* Sets number of cameras calibrated simultaneously. It is equal to 1 initially */
virtual void SetCameraCount( int cameraCount );
/* Retrieves number of cameras */
int GetCameraCount() const { return cameraCount; }
/* Starts cameras calibration */
virtual bool SetFrames( int totalFrames );
/* Stops cameras calibration */
virtual void Stop( bool calibrate = false );
/* Retrieves number of cameras */
bool IsCalibrated() const { return isCalibrated; }
/* Feeds another serie of snapshots (one per each camera) to filter.
Etalon points on these images are found automatically.
If the function can't locate points, it returns false */
virtual bool FindEtalon( IplImage** imgs );
/* The same but takes matrices */
virtual bool FindEtalon( CvMat** imgs );
/* Lower-level function for feeding filter with already found etalon points.
Array of point arrays for each camera is passed. */
virtual bool Push( const CvPoint2D32f** points = 0 );
/* Returns total number of accepted frames and, optionally,
total number of frames to collect */
virtual int GetFrameCount( int* framesTotal = 0 ) const;
/* Retrieves camera parameters for specified camera.
If camera is not calibrated the function returns 0 */
virtual const CvCamera* GetCameraParams( int idx = 0 ) const;
virtual const CvStereoCamera* GetStereoParams() const;
/* Sets camera parameters for all cameras */
virtual bool SetCameraParams( CvCamera* params );
/* Saves all camera parameters to file */
virtual bool SaveCameraParams( const char* filename );
/* Loads all camera parameters from file */
virtual bool LoadCameraParams( const char* filename );
/* Undistorts images using camera parameters. Some of src pointers can be NULL. */
virtual bool Undistort( IplImage** src, IplImage** dst );
/* Undistorts images using camera parameters. Some of src pointers can be NULL. */
virtual bool Undistort( CvMat** src, CvMat** dst );
/* Returns array of etalon points detected/partally detected
on the latest frame for idx-th camera */
virtual bool GetLatestPoints( int idx, CvPoint2D32f** pts,
int* count, bool* found );
/* Draw the latest detected/partially detected etalon */
virtual void DrawPoints( IplImage** dst );
/* Draw the latest detected/partially detected etalon */
virtual void DrawPoints( CvMat** dst );
virtual bool Rectify( IplImage** srcarr, IplImage** dstarr );
virtual bool Rectify( CvMat** srcarr, CvMat** dstarr );
protected:
enum { MAX_CAMERAS = 3 };
/* etalon data */
CvCalibEtalonType etalonType;
int etalonParamCount;
double* etalonParams;
int etalonPointCount;
CvPoint2D32f* etalonPoints;
CvSize imgSize;
CvMat* grayImg;
CvMat* tempImg;
CvMemStorage* storage;
/* camera data */
int cameraCount;
CvCamera cameraParams[MAX_CAMERAS];
CvStereoCamera stereo;
CvPoint2D32f* points[MAX_CAMERAS];
CvMat* undistMap[MAX_CAMERAS][2];
CvMat* undistImg;
int latestCounts[MAX_CAMERAS];
CvPoint2D32f* latestPoints[MAX_CAMERAS];
CvMat* rectMap[MAX_CAMERAS][2];
/* Added by Valery */
//CvStereoCamera stereoParams;
int maxPoints;
int framesTotal;
int framesAccepted;
bool isCalibrated;
};
#include <iosfwd>
#include <limits>
class CV_EXPORTS CvImage
{
public:
CvImage() : image(0), refcount(0) {}
CvImage( CvSize size, int depth, int channels )
{
image = cvCreateImage( size, depth, channels );
refcount = image ? new int(1) : 0;
}
CvImage( IplImage* img ) : image(img)
{
refcount = image ? new int(1) : 0;
}
CvImage( const CvImage& img ) : image(img.image), refcount(img.refcount)
{
if( refcount ) ++(*refcount);
}
CvImage( const char* filename, const char* imgname=0, int color=-1 ) : image(0), refcount(0)
{ load( filename, imgname, color ); }
CvImage( CvFileStorage* fs, const char* mapname, const char* imgname ) : image(0), refcount(0)
{ read( fs, mapname, imgname ); }
CvImage( CvFileStorage* fs, const char* seqname, int idx ) : image(0), refcount(0)
{ read( fs, seqname, idx ); }
~CvImage()
{
if( refcount && !(--*refcount) )
{
cvReleaseImage( &image );
delete refcount;
}
}
CvImage clone() { return CvImage(image ? cvCloneImage(image) : 0); }
void create( CvSize size, int depth, int channels )
{
if( !image || !refcount ||
image->width != size.width || image->height != size.height ||
image->depth != depth || image->nChannels != channels )
attach( cvCreateImage( size, depth, channels ));
}
void release() { detach(); }
void clear() { detach(); }
void attach( IplImage* img, bool use_refcount=true )
{
if( refcount && --*refcount == 0 )
{
cvReleaseImage( &image );
delete refcount;
}
image = img;
refcount = use_refcount && image ? new int(1) : 0;
}
void detach()
{
if( refcount && --*refcount == 0 )
{
cvReleaseImage( &image );
delete refcount;
}
image = 0;
refcount = 0;
}
bool load( const char* filename, const char* imgname=0, int color=-1 );
bool read( CvFileStorage* fs, const char* mapname, const char* imgname );
bool read( CvFileStorage* fs, const char* seqname, int idx );
void save( const char* filename, const char* imgname, const int* params=0 );
void write( CvFileStorage* fs, const char* imgname );
void show( const char* window_name );
bool is_valid() { return image != 0; }
int width() const { return image ? image->width : 0; }
int height() const { return image ? image->height : 0; }
CvSize size() const { return image ? cvSize(image->width, image->height) : cvSize(0,0); }
CvSize roi_size() const
{
return !image ? cvSize(0,0) :
!image->roi ? cvSize(image->width,image->height) :
cvSize(image->roi->width, image->roi->height);
}
CvRect roi() const
{
return !image ? cvRect(0,0,0,0) :
!image->roi ? cvRect(0,0,image->width,image->height) :
cvRect(image->roi->xOffset,image->roi->yOffset,
image->roi->width,image->roi->height);
}
int coi() const { return !image || !image->roi ? 0 : image->roi->coi; }
void set_roi(CvRect roi) { cvSetImageROI(image,roi); }
void reset_roi() { cvResetImageROI(image); }
void set_coi(int coi) { cvSetImageCOI(image,coi); }
int depth() const { return image ? image->depth : 0; }
int channels() const { return image ? image->nChannels : 0; }
int pix_size() const { return image ? ((image->depth & 255)>>3)*image->nChannels : 0; }
uchar* data() { return image ? (uchar*)image->imageData : 0; }
const uchar* data() const { return image ? (const uchar*)image->imageData : 0; }
int step() const { return image ? image->widthStep : 0; }
int origin() const { return image ? image->origin : 0; }
uchar* roi_row(int y)
{
assert(0<=y);
assert(!image ?
1 : image->roi ?
y<image->roi->height : y<image->height);
return !image ? 0 :
!image->roi ?
(uchar*)(image->imageData + y*image->widthStep) :
(uchar*)(image->imageData + (y+image->roi->yOffset)*image->widthStep +
image->roi->xOffset*((image->depth & 255)>>3)*image->nChannels);
}
const uchar* roi_row(int y) const
{
assert(0<=y);
assert(!image ?
1 : image->roi ?
y<image->roi->height : y<image->height);
return !image ? 0 :
!image->roi ?
(const uchar*)(image->imageData + y*image->widthStep) :
(const uchar*)(image->imageData + (y+image->roi->yOffset)*image->widthStep +
image->roi->xOffset*((image->depth & 255)>>3)*image->nChannels);
}
operator const IplImage* () const { return image; }
operator IplImage* () { return image; }
CvImage& operator = (const CvImage& img)
{
if( img.refcount )
++*img.refcount;
if( refcount && !(--*refcount) )
cvReleaseImage( &image );
image=img.image;
refcount=img.refcount;
return *this;
}
protected:
IplImage* image;
int* refcount;
};
class CV_EXPORTS CvMatrix
{
public:
CvMatrix() : matrix(0) {}
CvMatrix( int rows, int cols, int type )
{ matrix = cvCreateMat( rows, cols, type ); }
CvMatrix( int rows, int cols, int type, CvMat* hdr,
void* data=0, int step=CV_AUTOSTEP )
{ matrix = cvInitMatHeader( hdr, rows, cols, type, data, step ); }
CvMatrix( int rows, int cols, int type, CvMemStorage* storage, bool alloc_data=true );
CvMatrix( int rows, int cols, int type, void* data, int step=CV_AUTOSTEP )
{ matrix = cvCreateMatHeader( rows, cols, type );
cvSetData( matrix, data, step ); }
CvMatrix( CvMat* m )
{ matrix = m; }
CvMatrix( const CvMatrix& m )
{
matrix = m.matrix;
addref();
}
CvMatrix( const char* filename, const char* matname=0, int color=-1 ) : matrix(0)
{ load( filename, matname, color ); }
CvMatrix( CvFileStorage* fs, const char* mapname, const char* matname ) : matrix(0)
{ read( fs, mapname, matname ); }
CvMatrix( CvFileStorage* fs, const char* seqname, int idx ) : matrix(0)
{ read( fs, seqname, idx ); }
~CvMatrix()
{
release();
}
CvMatrix clone() { return CvMatrix(matrix ? cvCloneMat(matrix) : 0); }
void set( CvMat* m, bool add_ref )
{
release();
matrix = m;
if( add_ref )
addref();
}
void create( int rows, int cols, int type )
{
if( !matrix || !matrix->refcount ||
matrix->rows != rows || matrix->cols != cols ||
CV_MAT_TYPE(matrix->type) != type )
set( cvCreateMat( rows, cols, type ), false );
}
void addref() const
{
if( matrix )
{
if( matrix->hdr_refcount )
++matrix->hdr_refcount;
else if( matrix->refcount )
++*matrix->refcount;
}
}
void release()
{
if( matrix )
{
if( matrix->hdr_refcount )
{
if( --matrix->hdr_refcount == 0 )
cvReleaseMat( &matrix );
}
else if( matrix->refcount )
{
if( --*matrix->refcount == 0 )
cvFree( &matrix->refcount );
}
matrix = 0;
}
}
void clear()
{
release();
}
bool load( const char* filename, const char* matname=0, int color=-1 );
bool read( CvFileStorage* fs, const char* mapname, const char* matname );
bool read( CvFileStorage* fs, const char* seqname, int idx );
void save( const char* filename, const char* matname, const int* params=0 );
void write( CvFileStorage* fs, const char* matname );
void show( const char* window_name );
bool is_valid() { return matrix != 0; }
int rows() const { return matrix ? matrix->rows : 0; }
int cols() const { return matrix ? matrix->cols : 0; }
CvSize size() const
{
return !matrix ? cvSize(0,0) : cvSize(matrix->rows,matrix->cols);
}
int type() const { return matrix ? CV_MAT_TYPE(matrix->type) : 0; }
int depth() const { return matrix ? CV_MAT_DEPTH(matrix->type) : 0; }
int channels() const { return matrix ? CV_MAT_CN(matrix->type) : 0; }
int pix_size() const { return matrix ? CV_ELEM_SIZE(matrix->type) : 0; }
uchar* data() { return matrix ? matrix->data.ptr : 0; }
const uchar* data() const { return matrix ? matrix->data.ptr : 0; }
int step() const { return matrix ? matrix->step : 0; }
void set_data( void* data, int step=CV_AUTOSTEP )
{ cvSetData( matrix, data, step ); }
uchar* row(int i) { return !matrix ? 0 : matrix->data.ptr + i*matrix->step; }
const uchar* row(int i) const
{ return !matrix ? 0 : matrix->data.ptr + i*matrix->step; }
operator const CvMat* () const { return matrix; }
operator CvMat* () { return matrix; }
CvMatrix& operator = (const CvMatrix& _m)
{
_m.addref();
release();
matrix = _m.matrix;
return *this;
}
protected:
CvMat* matrix;
};
/****************************************************************************************\
* CamShiftTracker *
\****************************************************************************************/
class CV_EXPORTS CvCamShiftTracker
{
public:
CvCamShiftTracker();
virtual ~CvCamShiftTracker();
/**** Characteristics of the object that are calculated by track_object method *****/
float get_orientation() const // orientation of the object in degrees
{ return m_box.angle; }
float get_length() const // the larger linear size of the object
{ return m_box.size.height; }
float get_width() const // the smaller linear size of the object
{ return m_box.size.width; }
CvPoint2D32f get_center() const // center of the object
{ return m_box.center; }
CvRect get_window() const // bounding rectangle for the object
{ return m_comp.rect; }
/*********************** Tracking parameters ************************/
int get_threshold() const // thresholding value that applied to back project
{ return m_threshold; }
int get_hist_dims( int* dims = 0 ) const // returns number of histogram dimensions and sets
{ return m_hist ? cvGetDims( m_hist->bins, dims ) : 0; }
int get_min_ch_val( int channel ) const // get the minimum allowed value of the specified channel
{ return m_min_ch_val[channel]; }
int get_max_ch_val( int channel ) const // get the maximum allowed value of the specified channel
{ return m_max_ch_val[channel]; }
// set initial object rectangle (must be called before initial calculation of the histogram)
bool set_window( CvRect window)
{ m_comp.rect = window; return true; }
bool set_threshold( int threshold ) // threshold applied to the histogram bins
{ m_threshold = threshold; return true; }
bool set_hist_bin_range( int dim, int min_val, int max_val );
bool set_hist_dims( int c_dims, int* dims );// set the histogram parameters
bool set_min_ch_val( int channel, int val ) // set the minimum allowed value of the specified channel
{ m_min_ch_val[channel] = val; return true; }
bool set_max_ch_val( int channel, int val ) // set the maximum allowed value of the specified channel
{ m_max_ch_val[channel] = val; return true; }
/************************ The processing methods *********************************/
// update object position
virtual bool track_object( const IplImage* cur_frame );
// update object histogram
virtual bool update_histogram( const IplImage* cur_frame );
// reset histogram
virtual void reset_histogram();
/************************ Retrieving internal data *******************************/
// get back project image
virtual IplImage* get_back_project()
{ return m_back_project; }
float query( int* bin ) const
{ return m_hist ? (float)cvGetRealND(m_hist->bins, bin) : 0.f; }
protected:
// internal method for color conversion: fills m_color_planes group
virtual void color_transform( const IplImage* img );
CvHistogram* m_hist;
CvBox2D m_box;
CvConnectedComp m_comp;
float m_hist_ranges_data[CV_MAX_DIM][2];
float* m_hist_ranges[CV_MAX_DIM];
int m_min_ch_val[CV_MAX_DIM];
int m_max_ch_val[CV_MAX_DIM];
int m_threshold;
IplImage* m_color_planes[CV_MAX_DIM];
IplImage* m_back_project;
IplImage* m_temp;
IplImage* m_mask;
};
//#include "cvvidsurv.hpp"
#endif
#endif
/* End of file. */
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