/*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( double* rotMatr1, double* transVect1, double* rotMatr2, double* transVect2, double* convRotMatr, double* convTransVect); CVAPI(int) icvConvertPointSystem(CvPoint3D64f M2, CvPoint3D64f* M1, double* rotMatr, double* 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, double* camMatr1, double* rotMatr1, double* transVect1, double* camMatr2, double* rotMatr2, double* transVect2, CvStereoLineCoeff* coeffs, int* needSwapCameras); CVAPI(int) icvGetDirectionForPoint( CvPoint2D64f point, double* 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 ( double* camMatr1, double* rotMatr1, double* transVect1, double* camMatr2, double* rotMatr2, double* transVect2, CvPoint2D64f* epipole1, CvPoint2D64f* epipole2, double* 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, double* fundMatr, double* coeff11,double* coeff12, double* coeff21,double* coeff22, int* result);*/ CVAPI(void) icvComputeeInfiniteProject1(double* rotMatr, double* camMatr1, double* camMatr2, CvPoint2D32f point1, CvPoint2D32f *point2); CVAPI(void) icvComputeeInfiniteProject2(double* rotMatr, double* camMatr1, double* camMatr2, CvPoint2D32f* point1, CvPoint2D32f point2); CVAPI(void) icvGetCrossDirectDirect( double* direct1,double* 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, double* camMatr,double* rotMatr,double* transVect, CvPoint2D64f* projPoint); CVAPI(void) icvGetQuadsTransform( CvSize imageSize, double* camMatr1, double* rotMatr1, double* transVect1, double* camMatr2, double* rotMatr2, double* transVect2, CvSize* warpSize, double quad1[4][2], double quad2[4][2], double* fundMatr, CvPoint3D64f* epipole1, CvPoint3D64f* epipole2 ); CVAPI(void) icvGetQuadsTransformStruct( CvStereoCamera* stereoCamera); CVAPI(void) icvComputeStereoParamsForCameras(CvStereoCamera* stereoCamera); CVAPI(void) icvGetCutPiece( double* areaLineCoef1,double* 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(double* direct,CvPoint2D64f point,double* normDirect); CVAPI(double) icvGetVect(CvPoint2D64f basePoint,CvPoint2D64f point1,CvPoint2D64f point2); CVAPI(void) icvProjectPointToDirect( CvPoint2D64f point,double* lineCoeff, CvPoint2D64f* projectPoint); CVAPI(void) icvGetDistanceFromPointToDirect( CvPoint2D64f point,double* 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 ************************/ typedef struct CvMatrix3 { float m[3][3]; } CvMatrix3; /* 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 #include 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 ? yroi->height : yheight); 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 ? yroi->height : yheight); 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. */