C structures and operations
Overview
// typedefs typedef void(CV_STDCALL* Cv_iplAllocateImageData)( IplImage *, int, int ); typedef IplImage*(CV_STDCALL* Cv_iplCloneImage)(const IplImage *); typedef IplImage*(CV_STDCALL* Cv_iplCreateImageHeader)( int, int, int, char *, char *, int, int, int, int, int, IplROI *, IplImage *, void *, IplTileInfo * ); typedef IplROI*(CV_STDCALL* Cv_iplCreateROI)( int, int, int, int, int ); typedef void(CV_STDCALL* Cv_iplDeallocate)( IplImage *, int ); typedef int (*CvCmpFunc)( const void *a, const void *b, void *userdata ); typedef int (*CvErrorCallback)( int status, const char *func_name, const char *err_msg, const char *file_name, int line, void *userdata ); typedef struct CvFileStorage CvFileStorage; typedef void CvArr; typedef void* (*CvCloneFunc)(const void *struct_ptr); typedef struct CvGenericHash CvFileNodeHash; typedef int CvHistType; typedef int (*CvIsInstanceFunc)(const void *struct_ptr); typedef CvContour CvPoint2DSeq; typedef void* (*CvReadFunc)( CvFileStorage *storage, CvFileNode *node ); typedef void (*CvReleaseFunc)(void **struct_dblptr); typedef uint64 CvRNG; typedef int CVStatus; typedef void (*CvWriteFunc)( CvFileStorage *storage, const char *name, const void *struct_ptr, CvAttrList attributes ); typedef struct _IplTileInfo IplTileInfo; // enums enum { @53::CV_StsOk = 0, @53::CV_StsBackTrace = -1, @53::CV_StsError = -2, @53::CV_StsInternal = -3, @53::CV_StsNoMem = -4, @53::CV_StsBadArg = -5, @53::CV_StsBadFunc = -6, @53::CV_StsNoConv = -7, @53::CV_StsAutoTrace = -8, @53::CV_HeaderIsNull = -9, @53::CV_BadImageSize = -10, @53::CV_BadOffset = -11, @53::CV_BadDataPtr = -12, @53::CV_BadStep = -13, @53::CV_BadModelOrChSeq = -14, @53::CV_BadNumChannels = -15, @53::CV_BadNumChannel1U = -16, @53::CV_BadDepth = -17, @53::CV_BadAlphaChannel = -18, @53::CV_BadOrder = -19, @53::CV_BadOrigin = -20, @53::CV_BadAlign = -21, @53::CV_BadCallBack = -22, @53::CV_BadTileSize = -23, @53::CV_BadCOI = -24, @53::CV_BadROISize = -25, @53::CV_MaskIsTiled = -26, @53::CV_StsNullPtr = -27, @53::CV_StsVecLengthErr = -28, @53::CV_StsFilterStructContentErr = -29, @53::CV_StsKernelStructContentErr = -30, @53::CV_StsFilterOffsetErr = -31, @53::CV_StsBadSize = -201, @53::CV_StsDivByZero = -202, @53::CV_StsInplaceNotSupported = -203, @53::CV_StsObjectNotFound = -204, @53::CV_StsUnmatchedFormats = -205, @53::CV_StsBadFlag = -206, @53::CV_StsBadPoint = -207, @53::CV_StsBadMask = -208, @53::CV_StsUnmatchedSizes = -209, @53::CV_StsUnsupportedFormat = -210, @53::CV_StsOutOfRange = -211, @53::CV_StsParseError = -212, @53::CV_StsNotImplemented = -213, @53::CV_StsBadMemBlock = -214, @53::CV_StsAssert = -215, @53::CV_GpuNotSupported = -216, @53::CV_GpuApiCallError = -217, @53::CV_OpenGlNotSupported = -218, @53::CV_OpenGlApiCallError = -219, @53::CV_OpenCLApiCallError = -220, @53::CV_OpenCLDoubleNotSupported = -221, @53::CV_OpenCLInitError = -222, @53::CV_OpenCLNoAMDBlasFft = -223, }; // structs struct CvAttrList; struct CvBox2D; struct CvChain; struct CvContour; struct CvFileNode; struct CvGraph; struct CvGraphEdge; struct CvGraphScanner; struct CvGraphVtx; struct CvGraphVtx2D; struct CvHistogram; struct CvLineIterator; struct CvMat; struct CvMatND; struct CvMemBlock; struct CvMemStorage; struct CvMemStoragePos; struct CvModuleInfo; struct CvNArrayIterator; struct CvPluginFuncInfo; struct CvPoint; struct CvPoint2D32f; struct CvPoint2D64f; struct CvPoint3D32f; struct CvPoint3D64f; struct CvRect; struct CvScalar; struct CvSeq; struct CvSeqBlock; struct CvSeqReader; struct CvSeqWriter; struct CvSet; struct CvSetElem; struct CvSize; struct CvSize2D32f; struct CvSlice; struct CvSparseMat; struct CvSparseMatIterator; struct CvSparseNode; struct CvString; struct CvStringHashNode; struct CvTermCriteria; struct CvTreeNodeIterator; struct CvTypeInfo; struct IplConvKernel; struct IplConvKernelFP; struct IplImage; struct IplROI; // global functions void cvAbsDiff( const CvArr* src1, const CvArr* src2, CvArr* dst ); void cvAbsDiffS( const CvArr* src, CvArr* dst, CvScalar value ); void cvAdd( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL ); void cvAddS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL ); void cvAddWeighted( const CvArr* src1, double alpha, const CvArr* src2, double beta, double gamma, CvArr* dst ); void* cvAlloc(size_t size); void cvAnd( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL ); void cvAndS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL ); const char* cvAttrValue( const CvAttrList* attr, const char* attr_name ); CvScalar cvAvg( const CvArr* arr, const CvArr* mask = NULL ); void cvAvgSdv( const CvArr* arr, CvScalar* mean, CvScalar* std_dev, const CvArr* mask = NULL ); void cvBackProjectPCA( const CvArr* proj, const CvArr* mean, const CvArr* eigenvects, CvArr* result ); void cvCalcCovarMatrix( const CvArr** vects, int count, CvArr* cov_mat, CvArr* avg, int flags ); void cvCalcPCA( const CvArr* data, CvArr* mean, CvArr* eigenvals, CvArr* eigenvects, int flags ); void cvCartToPolar( const CvArr* x, const CvArr* y, CvArr* magnitude, CvArr* angle = NULL, int angle_in_degrees = 0 ); float cvCbrt(float value); void cvChangeSeqBlock( void* reader, int direction ); int cvCheckArr( const CvArr* arr, int flags = 0, double min_val = 0, double max_val = 0 ); int cvCheckHardwareSupport(int feature); CvTermCriteria cvCheckTermCriteria( CvTermCriteria criteria, double default_eps, int default_max_iters ); void cvClearGraph(CvGraph* graph); void cvClearMemStorage(CvMemStorage* storage); void cvClearND( CvArr* arr, const int* idx ); void cvClearSeq(CvSeq* seq); void cvClearSet(CvSet* set_header); void* cvClone(const void* struct_ptr); CvGraph* cvCloneGraph( const CvGraph* graph, CvMemStorage* storage ); IplImage* cvCloneImage(const IplImage* image); CvMat* cvCloneMat(const CvMat* mat); CvMatND* cvCloneMatND(const CvMatND* mat); CvSeq* cvCloneSeq( const CvSeq* seq, CvMemStorage* storage = NULL ); CvSparseMat* cvCloneSparseMat(const CvSparseMat* mat); void cvCmp( const CvArr* src1, const CvArr* src2, CvArr* dst, int cmp_op ); void cvCmpS( const CvArr* src, double value, CvArr* dst, int cmp_op ); void cvCompleteSymm( CvMat* matrix, int LtoR = 0 ); void cvConvertScale( const CvArr* src, CvArr* dst, double scale = 1, double shift = 0 ); void cvConvertScaleAbs( const CvArr* src, CvArr* dst, double scale = 1, double shift = 0 ); void cvCopy( const CvArr* src, CvArr* dst, const CvArr* mask = NULL ); int cvCountNonZero(const CvArr* arr); CvMemStorage* cvCreateChildMemStorage(CvMemStorage* parent); void cvCreateData(CvArr* arr); CvGraph* cvCreateGraph( int graph_flags, int header_size, int vtx_size, int edge_size, CvMemStorage* storage ); CvGraphScanner* cvCreateGraphScanner( CvGraph* graph, CvGraphVtx* vtx = NULL, int mask = -1 ); IplImage* cvCreateImage( CvSize size, int depth, int channels ); IplImage* cvCreateImageHeader( CvSize size, int depth, int channels ); CvMat* cvCreateMat( int rows, int cols, int type ); CvMat* cvCreateMatHeader( int rows, int cols, int type ); CvMatND* cvCreateMatND( int dims, const int* sizes, int type ); CvMatND* cvCreateMatNDHeader( int dims, const int* sizes, int type ); CvMemStorage* cvCreateMemStorage(int block_size = 0); CvSeq* cvCreateSeq( int seq_flags, size_t header_size, size_t elem_size, CvMemStorage* storage ); void cvCreateSeqBlock(CvSeqWriter* writer); CvSet* cvCreateSet( int set_flags, int header_size, int elem_size, CvMemStorage* storage ); CvSparseMat* cvCreateSparseMat( int dims, const int* sizes, int type ); void cvCrossProduct( const CvArr* src1, const CvArr* src2, CvArr* dst ); void* cvCvtSeqToArray( const CvSeq* seq, void* elements, CvSlice slice = CV_WHOLE_SEQ ); void cvDCT( const CvArr* src, CvArr* dst, int flags ); void cvDecRefData(CvArr* arr); double cvDet(const CvArr* mat); void cvDFT( const CvArr* src, CvArr* dst, int flags, int nonzero_rows = 0 ); void cvDiv( const CvArr* src1, const CvArr* src2, CvArr* dst, double scale = 1 ); double cvDotProduct( const CvArr* src1, const CvArr* src2 ); void cvEigenVV( CvArr* mat, CvArr* evects, CvArr* evals, double eps = 0, int lowindex = -1, int highindex = -1 ); CvSeq* cvEndWriteSeq(CvSeqWriter* writer); void cvEndWriteStruct(CvFileStorage* fs); void cvError( int status, const char* func_name, const char* err_msg, const char* file_name, int line ); int cvErrorFromIppStatus(int ipp_status); const char* cvErrorStr(int status); void cvExp( const CvArr* src, CvArr* dst ); float cvFastArctan( float y, float x ); CvGraphEdge* cvFindGraphEdge( const CvGraph* graph, int start_idx, int end_idx ); CvGraphEdge* cvFindGraphEdgeByPtr( const CvGraph* graph, const CvGraphVtx* start_vtx, const CvGraphVtx* end_vtx ); CvTypeInfo* cvFindType(const char* type_name); CvTypeInfo* cvFirstType(void); void cvFlip( const CvArr* src, CvArr* dst = NULL, int flip_mode = 0 ); void cvFlushSeqWriter(CvSeqWriter* writer); void cvFree_(void* ptr); void cvGEMM( const CvArr* src1, const CvArr* src2, double alpha, const CvArr* src3, double beta, CvArr* dst, int tABC = 0 ); CvScalar cvGet1D( const CvArr* arr, int idx0 ); CvScalar cvGet2D( const CvArr* arr, int idx0, int idx1 ); CvScalar cvGet3D( const CvArr* arr, int idx0, int idx1, int idx2 ); CvMat* cvGetCol( const CvArr* arr, CvMat* submat, int col ); CvMat* cvGetCols( const CvArr* arr, CvMat* submat, int start_col, int end_col ); CvMat* cvGetDiag( const CvArr* arr, CvMat* submat, int diag = 0 ); int cvGetDims( const CvArr* arr, int* sizes = NULL ); int cvGetDimSize( const CvArr* arr, int index ); int cvGetElemType(const CvArr* arr); int cvGetErrInfo( const char** errcode_desc, const char** description, const char** filename, int* line ); int cvGetErrMode(void); int cvGetErrStatus(void); CvFileNode* cvGetFileNode( CvFileStorage* fs, CvFileNode* map, const CvStringHashNode* key, int create_missing = 0 ); CvFileNode* cvGetFileNodeByName( const CvFileStorage* fs, const CvFileNode* map, const char* name ); const char* cvGetFileNodeName(const CvFileNode* node); CvStringHashNode* cvGetHashedKey( CvFileStorage* fs, const char* name, int len = -1, int create_missing = 0 ); IplImage* cvGetImage( const CvArr* arr, IplImage* image_header ); int cvGetImageCOI(const IplImage* image); CvRect cvGetImageROI(const IplImage* image); CvMat* cvGetMat( const CvArr* arr, CvMat* header, int* coi = NULL, int allowND = 0 ); CvScalar cvGetND( const CvArr* arr, const int* idx ); CvSparseNode* cvGetNextSparseNode(CvSparseMatIterator* mat_iterator); int cvGetNumThreads(void); int cvGetOptimalDFTSize(int size0); void cvGetRawData( const CvArr* arr, uchar** data, int* step = NULL, CvSize* roi_size = NULL ); double cvGetReal1D( const CvArr* arr, int idx0 ); double cvGetReal2D( const CvArr* arr, int idx0, int idx1 ); double cvGetReal3D( const CvArr* arr, int idx0, int idx1, int idx2 ); double cvGetRealND( const CvArr* arr, const int* idx ); CvFileNode* cvGetRootFileNode( const CvFileStorage* fs, int stream_index = 0 ); CvMat* cvGetRow( const CvArr* arr, CvMat* submat, int row ); CvMat* cvGetRows( const CvArr* arr, CvMat* submat, int start_row, int end_row, int delta_row = 1 ); schar* cvGetSeqElem( const CvSeq* seq, int index ); int cvGetSeqReaderPos(CvSeqReader* reader); CvSetElem* cvGetSetElem( const CvSet* set_header, int idx ); CvSize cvGetSize(const CvArr* arr); CvMat* cvGetSubRect( const CvArr* arr, CvMat* submat, CvRect rect ); int cvGetThreadNum(void); int64 cvGetTickCount(void); double cvGetTickFrequency(void); int cvGraphAddEdge( CvGraph* graph, int start_idx, int end_idx, const CvGraphEdge* edge = NULL, CvGraphEdge** inserted_edge = NULL ); int cvGraphAddEdgeByPtr( CvGraph* graph, CvGraphVtx* start_vtx, CvGraphVtx* end_vtx, const CvGraphEdge* edge = NULL, CvGraphEdge** inserted_edge = NULL ); int cvGraphAddVtx( CvGraph* graph, const CvGraphVtx* vtx = NULL, CvGraphVtx** inserted_vtx = NULL ); void cvGraphRemoveEdge( CvGraph* graph, int start_idx, int end_idx ); void cvGraphRemoveEdgeByPtr( CvGraph* graph, CvGraphVtx* start_vtx, CvGraphVtx* end_vtx ); int cvGraphRemoveVtx( CvGraph* graph, int index ); int cvGraphRemoveVtxByPtr( CvGraph* graph, CvGraphVtx* vtx ); int cvGraphVtxDegree( const CvGraph* graph, int vtx_idx ); int cvGraphVtxDegreeByPtr( const CvGraph* graph, const CvGraphVtx* vtx ); int cvGuiBoxReport( int status, const char* func_name, const char* err_msg, const char* file_name, int line, void* userdata ); int cvIncRefData(CvArr* arr); IplImage* cvInitImageHeader( IplImage* image, CvSize size, int depth, int channels, int origin = 0, int align = 4 ); CvMat* cvInitMatHeader( CvMat* mat, int rows, int cols, int type, void* data = NULL, int step = 0x7fffffff ); CvMatND* cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes, int type, void* data = NULL ); int cvInitNArrayIterator( int count, CvArr** arrs, const CvArr* mask, CvMatND* stubs, CvNArrayIterator* array_iterator, int flags = 0 ); CvSparseNode* cvInitSparseMatIterator( const CvSparseMat* mat, CvSparseMatIterator* mat_iterator ); void cvInitTreeNodeIterator( CvTreeNodeIterator* tree_iterator, const void* first, int max_level ); void cvInRange( const CvArr* src, const CvArr* lower, const CvArr* upper, CvArr* dst ); void cvInRangeS( const CvArr* src, CvScalar lower, CvScalar upper, CvArr* dst ); void cvInsertNodeIntoTree( void* node, void* parent, void* frame ); double cvInvert( const CvArr* src, CvArr* dst, int method = 0 ); int cvKMeans2( const CvArr* samples, int cluster_count, CvArr* labels, CvTermCriteria termcrit, int attempts = 1, CvRNG* rng = 0, int flags = 0, CvArr* _centers = 0, double* compactness = 0 ); void* cvLoad( const char* filename, CvMemStorage* memstorage = NULL, const char* name = NULL, const char** real_name = NULL ); void cvLog( const CvArr* src, CvArr* dst ); void cvLUT( const CvArr* src, CvArr* dst, const CvArr* lut ); double cvMahalanobis( const CvArr* vec1, const CvArr* vec2, const CvArr* mat ); CvSeq* cvMakeSeqHeaderForArray( int seq_type, int header_size, int elem_size, void* elements, int total, CvSeq* seq, CvSeqBlock* block ); void cvMax( const CvArr* src1, const CvArr* src2, CvArr* dst ); void cvMaxS( const CvArr* src, double value, CvArr* dst ); void* cvMemStorageAlloc( CvMemStorage* storage, size_t size ); CvString cvMemStorageAllocString( CvMemStorage* storage, const char* ptr, int len = -1 ); void cvMerge( const CvArr* src0, const CvArr* src1, const CvArr* src2, const CvArr* src3, CvArr* dst ); void cvMin( const CvArr* src1, const CvArr* src2, CvArr* dst ); void cvMinMaxLoc( const CvArr* arr, double* min_val, double* max_val, CvPoint* min_loc = NULL, CvPoint* max_loc = NULL, const CvArr* mask = NULL ); void cvMinS( const CvArr* src, double value, CvArr* dst ); void cvMixChannels( const CvArr** src, int src_count, CvArr** dst, int dst_count, const int* from_to, int pair_count ); void cvMul( const CvArr* src1, const CvArr* src2, CvArr* dst, double scale = 1 ); void cvMulSpectrums( const CvArr* src1, const CvArr* src2, CvArr* dst, int flags ); void cvMulTransposed( const CvArr* src, CvArr* dst, int order, const CvArr* delta = NULL, double scale = 1. ); int cvNextGraphItem(CvGraphScanner* scanner); int cvNextNArraySlice(CvNArrayIterator* array_iterator); void* cvNextTreeNode(CvTreeNodeIterator* tree_iterator); double cvNorm( const CvArr* arr1, const CvArr* arr2 = NULL, int norm_type = 4, const CvArr* mask = NULL ); void cvNormalize( const CvArr* src, CvArr* dst, double a = 1., double b = 0., int norm_type = 4, const CvArr* mask = NULL ); void cvNot( const CvArr* src, CvArr* dst ); int cvNulDevReport( int status, const char* func_name, const char* err_msg, const char* file_name, int line, void* userdata ); CvFileStorage* cvOpenFileStorage( const char* filename, CvMemStorage* memstorage, int flags, const char* encoding = NULL ); void cvOr( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL ); void cvOrS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL ); void cvPerspectiveTransform( const CvArr* src, CvArr* dst, const CvMat* mat ); void cvPolarToCart( const CvArr* magnitude, const CvArr* angle, CvArr* x, CvArr* y, int angle_in_degrees = 0 ); void cvPow( const CvArr* src, CvArr* dst, double power ); void* cvPrevTreeNode(CvTreeNodeIterator* tree_iterator); void cvProjectPCA( const CvArr* data, const CvArr* mean, const CvArr* eigenvects, CvArr* result ); uchar* cvPtr1D( const CvArr* arr, int idx0, int* type = NULL ); uchar* cvPtr2D( const CvArr* arr, int idx0, int idx1, int* type = NULL ); uchar* cvPtr3D( const CvArr* arr, int idx0, int idx1, int idx2, int* type = NULL ); uchar* cvPtrND( const CvArr* arr, const int* idx, int* type = NULL, int create_node = 1, unsigned* precalc_hashval = NULL ); void cvRandArr( CvRNG* rng, CvArr* arr, int dist_type, CvScalar param1, CvScalar param2 ); void cvRandShuffle( CvArr* mat, CvRNG* rng, double iter_factor = 1. ); CvArr* cvRange( CvArr* mat, double start, double end ); void cvRawDataToScalar( const void* data, int type, CvScalar* scalar ); void* cvRead( CvFileStorage* fs, CvFileNode* node, CvAttrList* attributes = NULL ); void* cvReadByName( CvFileStorage* fs, const CvFileNode* map, const char* name, CvAttrList* attributes = NULL ); int cvReadInt( const CvFileNode* node, int default_value = 0 ); int cvReadIntByName( const CvFileStorage* fs, const CvFileNode* map, const char* name, int default_value = 0 ); void cvReadRawData( const CvFileStorage* fs, const CvFileNode* src, void* dst, const char* dt ); void cvReadRawDataSlice( const CvFileStorage* fs, CvSeqReader* reader, int count, void* dst, const char* dt ); double cvReadReal( const CvFileNode* node, double default_value = 0. ); double cvReadRealByName( const CvFileStorage* fs, const CvFileNode* map, const char* name, double default_value = 0. ); const char* cvReadString( const CvFileNode* node, const char* default_value = NULL ); const char* cvReadStringByName( const CvFileStorage* fs, const CvFileNode* map, const char* name, const char* default_value = NULL ); CvErrorCallback cvRedirectError( CvErrorCallback error_handler, void* userdata = NULL, void** prev_userdata = NULL ); void cvReduce( const CvArr* src, CvArr* dst, int dim = -1, int op = 0 ); void cvRegisterType(const CvTypeInfo* info); void cvRelease(void** struct_ptr); void cvReleaseData(CvArr* arr); void cvReleaseFileStorage(CvFileStorage** fs); void cvReleaseGraphScanner(CvGraphScanner** scanner); void cvReleaseImage(IplImage** image); void cvReleaseImageHeader(IplImage** image); void cvReleaseMat(CvMat** mat); void cvReleaseMatND(CvMatND** mat); void cvReleaseMemStorage(CvMemStorage** storage); void cvReleaseSparseMat(CvSparseMat** mat); void cvRemoveNodeFromTree( void* node, void* frame ); void cvRepeat( const CvArr* src, CvArr* dst ); void cvResetImageROI(IplImage* image); CvMat* cvReshape( const CvArr* arr, CvMat* header, int new_cn, int new_rows = 0 ); CvArr* cvReshapeMatND( const CvArr* arr, int sizeof_header, CvArr* header, int new_cn, int new_dims, int* new_sizes ); void cvRestoreMemStoragePos( CvMemStorage* storage, CvMemStoragePos* pos ); void cvSave( const char* filename, const void* struct_ptr, const char* name = NULL, const char* comment = NULL, CvAttrList attributes = cvAttrList() ); void cvSaveMemStoragePos( const CvMemStorage* storage, CvMemStoragePos* pos ); void cvScalarToRawData( const CvScalar* scalar, void* data, int type, int extend_to_12 = 0 ); void cvScaleAdd( const CvArr* src1, CvScalar scale, const CvArr* src2, CvArr* dst ); int cvSeqElemIdx( const CvSeq* seq, const void* element, CvSeqBlock** block = NULL ); schar* cvSeqInsert( CvSeq* seq, int before_index, const void* element = NULL ); void cvSeqInsertSlice( CvSeq* seq, int before_index, const CvArr* from_arr ); void cvSeqInvert(CvSeq* seq); int cvSeqPartition( const CvSeq* seq, CvMemStorage* storage, CvSeq** labels, CvCmpFunc is_equal, void* userdata ); void cvSeqPop( CvSeq* seq, void* element = NULL ); void cvSeqPopFront( CvSeq* seq, void* element = NULL ); void cvSeqPopMulti( CvSeq* seq, void* elements, int count, int in_front = 0 ); schar* cvSeqPush( CvSeq* seq, const void* element = NULL ); schar* cvSeqPushFront( CvSeq* seq, const void* element = NULL ); void cvSeqPushMulti( CvSeq* seq, const void* elements, int count, int in_front = 0 ); void cvSeqRemove( CvSeq* seq, int index ); void cvSeqRemoveSlice( CvSeq* seq, CvSlice slice ); schar* cvSeqSearch( CvSeq* seq, const void* elem, CvCmpFunc func, int is_sorted, int* elem_idx, void* userdata = NULL ); CvSeq* cvSeqSlice( const CvSeq* seq, CvSlice slice, CvMemStorage* storage = NULL, int copy_data = 0 ); void cvSeqSort( CvSeq* seq, CvCmpFunc func, void* userdata = NULL ); void cvSet( CvArr* arr, CvScalar value, const CvArr* mask = NULL ); void cvSet1D( CvArr* arr, int idx0, CvScalar value ); void cvSet2D( CvArr* arr, int idx0, int idx1, CvScalar value ); void cvSet3D( CvArr* arr, int idx0, int idx1, int idx2, CvScalar value ); int cvSetAdd( CvSet* set_header, CvSetElem* elem = NULL, CvSetElem** inserted_elem = NULL ); void cvSetData( CvArr* arr, void* data, int step ); int cvSetErrMode(int mode); void cvSetErrStatus(int status); void cvSetIdentity( CvArr* mat, CvScalar value = cvRealScalar(1) ); void cvSetImageCOI( IplImage* image, int coi ); void cvSetImageROI( IplImage* image, CvRect rect ); void cvSetIPLAllocators( Cv_iplCreateImageHeader create_header, Cv_iplAllocateImageData allocate_data, Cv_iplDeallocate deallocate, Cv_iplCreateROI create_roi, Cv_iplCloneImage clone_image ); void cvSetND( CvArr* arr, const int* idx, CvScalar value ); CvSetElem* cvSetNew(CvSet* set_header); void cvSetNumThreads(int threads = 0); void cvSetReal1D( CvArr* arr, int idx0, double value ); void cvSetReal2D( CvArr* arr, int idx0, int idx1, double value ); void cvSetReal3D( CvArr* arr, int idx0, int idx1, int idx2, double value ); void cvSetRealND( CvArr* arr, const int* idx, double value ); void cvSetRemove( CvSet* set_header, int index ); void cvSetRemoveByPtr( CvSet* set_header, void* elem ); void cvSetSeqBlockSize( CvSeq* seq, int delta_elems ); void cvSetSeqReaderPos( CvSeqReader* reader, int index, int is_relative = 0 ); void cvSetZero(CvArr* arr); int cvSliceLength( CvSlice slice, const CvSeq* seq ); int cvSolve( const CvArr* src1, const CvArr* src2, CvArr* dst, int method = 0 ); int cvSolveCubic( const CvMat* coeffs, CvMat* roots ); void cvSolvePoly( const CvMat* coeffs, CvMat* roots2, int maxiter = 20, int fig = 100 ); void cvSort( const CvArr* src, CvArr* dst = NULL, CvArr* idxmat = NULL, int flags = 0 ); void cvSplit( const CvArr* src, CvArr* dst0, CvArr* dst1, CvArr* dst2, CvArr* dst3 ); void cvStartAppendToSeq( CvSeq* seq, CvSeqWriter* writer ); void cvStartNextStream(CvFileStorage* fs); void cvStartReadRawData( const CvFileStorage* fs, const CvFileNode* src, CvSeqReader* reader ); void cvStartReadSeq( const CvSeq* seq, CvSeqReader* reader, int reverse = 0 ); void cvStartWriteSeq( int seq_flags, int header_size, int elem_size, CvMemStorage* storage, CvSeqWriter* writer ); void cvStartWriteStruct( CvFileStorage* fs, const char* name, int struct_flags, const char* type_name = NULL, CvAttrList attributes = cvAttrList() ); int cvStdErrReport( int status, const char* func_name, const char* err_msg, const char* file_name, int line, void* userdata ); void cvSub( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL ); void cvSubRS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL ); void cvSubS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL ); CvScalar cvSum(const CvArr* arr); void cvSVBkSb( const CvArr* W, const CvArr* U, const CvArr* V, const CvArr* B, CvArr* X, int flags ); void cvSVD( CvArr* A, CvArr* W, CvArr* U = NULL, CvArr* V = NULL, int flags = 0 ); CvScalar cvTrace(const CvArr* mat); void cvTransform( const CvArr* src, CvArr* dst, const CvMat* transmat, const CvMat* shiftvec = NULL ); void cvTranspose( const CvArr* src, CvArr* dst ); CvSeq* cvTreeToNodeSeq( const void* first, int header_size, CvMemStorage* storage ); CvTypeInfo* cvTypeOf(const void* struct_ptr); void cvUnregisterType(const char* type_name); int cvUseOptimized(int on_off); void cvWrite( CvFileStorage* fs, const char* name, const void* ptr, CvAttrList attributes = cvAttrList() ); void cvWriteComment( CvFileStorage* fs, const char* comment, int eol_comment ); void cvWriteFileNode( CvFileStorage* fs, const char* new_node_name, const CvFileNode* node, int embed ); void cvWriteInt( CvFileStorage* fs, const char* name, int value ); void cvWriteRawData( CvFileStorage* fs, const void* src, int len, const char* dt ); void cvWriteRawDataBase64( CvFileStorage* fs, const void* src, int len, const char* dt ); void cvWriteReal( CvFileStorage* fs, const char* name, double value ); void cvWriteString( CvFileStorage* fs, const char* name, const char* str, int quote = 0 ); void cvXor( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL ); void cvXorS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL ); CvAttrList cvAttrList( const char** attr = NULL, CvAttrList* next = NULL ); CvSparseMat* cvCreateSparseMat(const cv::SparseMat& m); int cvIplDepth(int type); CvMat cvMat( int rows, int cols, int type, void* data = NULL ); double cvmGet( const CvMat* mat, int row, int col ); void cvmSet( CvMat* mat, int row, int col, double value ); CvPoint cvPoint( int x, int y ); CvPoint2D32f cvPoint2D32f( double x, double y ); CvPoint2D64f cvPoint2D64f( double x, double y ); CvPoint3D32f cvPoint3D32f( double x, double y, double z ); CvPoint3D64f cvPoint3D64f( double x, double y, double z ); CvPoint cvPointFrom32f(CvPoint2D32f point); CvPoint2D32f cvPointTo32f(CvPoint point); unsigned cvRandInt(CvRNG* rng); double cvRandReal(CvRNG* rng); CvScalar cvRealScalar(double val0); CvRect cvRect( int x, int y, int width, int height ); IplROI cvRectToROI( CvRect rect, int coi ); CvRNG cvRNG(int64 seed = -1); CvRect cvROIToRect(IplROI roi); CvScalar cvScalar( double val0, double val1 = 0, double val2 = 0, double val3 = 0 ); CvScalar cvScalarAll(double val0123); CvSize cvSize( int width, int height ); CvSize2D32f cvSize2D32f( double width, double height ); CvSlice cvSlice( int start, int end ); CvTermCriteria cvTermCriteria( int type, int max_iter, double epsilon ); // macros #define CV_ARE_CNS_EQ( \ mat1, \ mat2 \ ) #define CV_ARE_DEPTHS_EQ( \ mat1, \ mat2 \ ) #define CV_ARE_SIZES_EQ( \ mat1, \ mat2 \ ) #define CV_ARE_TYPES_EQ( \ mat1, \ mat2 \ ) #define CV_ASSERT(Condition) #define CV_AUTOSTEP #define CV_AUTO_STEP #define CV_BACK #define CV_C #define CV_CALL(Func) #define CV_CHECK() #define CV_CHECK_QUIET #define CV_CHECK_RANGE #define CV_CHOLESKY #define CV_CMP( \ a, \ b \ ) #define CV_CMP_EQ #define CV_CMP_GE #define CV_CMP_GT #define CV_CMP_LE #define CV_CMP_LT #define CV_CMP_NE #define CV_CONTOUR_FIELDS() #define CV_COVAR_COLS #define CV_COVAR_NORMAL #define CV_COVAR_ROWS #define CV_COVAR_SCALE #define CV_COVAR_SCRAMBLED #define CV_COVAR_USE_AVG #define CV_CURRENT_POINT(reader) #define CV_DIFF #define CV_DIFF_C #define CV_DIFF_L1 #define CV_DIFF_L2 #define CV_DXT_FORWARD #define CV_DXT_INVERSE #define CV_DXT_INVERSE_SCALE #define CV_DXT_INV_SCALE #define CV_DXT_MUL_CONJ #define CV_DXT_ROWS #define CV_DXT_SCALE #define CV_ERROR( \ Code, \ Msg \ ) #define CV_ErrModeLeaf #define CV_ErrModeParent #define CV_ErrModeSilent #define CV_FRONT #define CV_FUNCNAME(Name) #define CV_GEMM_A_T #define CV_GEMM_B_T #define CV_GEMM_C_T #define CV_GET_SEQ_ELEM( \ elem_type, \ seq, \ index \ ) #define CV_GRAPH #define CV_GRAPH_ALL_ITEMS #define CV_GRAPH_ANY_EDGE #define CV_GRAPH_BACKTRACKING #define CV_GRAPH_BACK_EDGE #define CV_GRAPH_CROSS_EDGE #define CV_GRAPH_EDGE_FIELDS() #define CV_GRAPH_FIELDS() #define CV_GRAPH_FLAG_ORIENTED #define CV_GRAPH_FORWARD_EDGE #define CV_GRAPH_FORWARD_EDGE_FLAG #define CV_GRAPH_ITEM_VISITED_FLAG #define CV_GRAPH_NEW_TREE #define CV_GRAPH_OVER #define CV_GRAPH_SEARCH_TREE_NODE_FLAG #define CV_GRAPH_TREE_EDGE #define CV_GRAPH_VERTEX #define CV_GRAPH_VERTEX_FIELDS() #define CV_HIST_ARRAY #define CV_HIST_HAS_RANGES(hist) #define CV_HIST_MAGIC_VAL #define CV_HIST_RANGES_FLAG #define CV_HIST_SPARSE #define CV_HIST_TREE #define CV_HIST_UNIFORM #define CV_HIST_UNIFORM_FLAG #define CV_IABS(a) #define CV_IMAGE_ELEM( \ image, \ elemtype, \ row, \ col \ ) #define CV_IMAX( \ a, \ b \ ) #define CV_IMIN( \ a, \ b \ ) #define CV_IS_GRAPH(seq) #define CV_IS_GRAPH_EDGE_VISITED(edge) #define CV_IS_GRAPH_ORIENTED(seq) #define CV_IS_GRAPH_VERTEX_VISITED(vtx) #define CV_IS_HIST(hist) #define CV_IS_IMAGE(img) #define CV_IS_IMAGE_HDR(img) #define CV_IS_MASK_ARR(mat) #define CV_IS_MAT(mat) #define CV_IS_MATND(mat) #define CV_IS_MATND_HDR(mat) #define CV_IS_MAT_CONST(mat) #define CV_IS_MAT_HDR(mat) #define CV_IS_MAT_HDR_Z(mat) #define CV_IS_SEQ(seq) #define CV_IS_SEQ_CHAIN(seq) #define CV_IS_SEQ_CHAIN_CONTOUR(seq) #define CV_IS_SEQ_CLOSED(seq) #define CV_IS_SEQ_CONTOUR(seq) #define CV_IS_SEQ_CONVEX(seq) #define CV_IS_SEQ_CURVE(seq) #define CV_IS_SEQ_HOLE(seq) #define CV_IS_SEQ_INDEX(seq) #define CV_IS_SEQ_POINT_SET(seq) #define CV_IS_SEQ_POINT_SUBSET(seq) #define CV_IS_SEQ_POLYGON(seq) #define CV_IS_SEQ_POLYGON_TREE(seq) #define CV_IS_SEQ_POLYLINE(seq) #define CV_IS_SEQ_SIMPLE(seq) #define CV_IS_SET(set) #define CV_IS_SET_ELEM(ptr) #define CV_IS_SPARSE_HIST(hist) #define CV_IS_SPARSE_MAT(mat) #define CV_IS_SPARSE_MAT_HDR(mat) #define CV_IS_STORAGE(storage) #define CV_IS_SUBDIV2D(seq) #define CV_IS_UNIFORM_HIST(hist) #define CV_KMEANS_USE_INITIAL_LABELS #define CV_L1 #define CV_L2 #define CV_LU #define CV_MAGIC_MASK #define CV_MATND_MAGIC_VAL #define CV_MAT_ELEM( \ mat, \ elemtype, \ row, \ col \ ) #define CV_MAT_ELEM_PTR( \ mat, \ row, \ col \ ) #define CV_MAT_ELEM_PTR_FAST( \ mat, \ row, \ col, \ pix_size \ ) #define CV_MAT_MAGIC_VAL #define CV_MAX_ARR #define CV_MAX_DIM #define CV_MAX_DIM_HEAP #define CV_MINMAX #define CV_NEXT_GRAPH_EDGE( \ edge, \ vertex \ ) #define CV_NEXT_SEQ_ELEM( \ elem_size, \ reader \ ) #define CV_NODE_EMPTY #define CV_NODE_FLOAT #define CV_NODE_FLOW #define CV_NODE_HAS_NAME(flags) #define CV_NODE_IDX( \ mat, \ node \ ) #define CV_NODE_INT #define CV_NODE_INTEGER #define CV_NODE_IS_COLLECTION(flags) #define CV_NODE_IS_EMPTY(flags) #define CV_NODE_IS_FLOW(flags) #define CV_NODE_IS_INT(flags) #define CV_NODE_IS_MAP(flags) #define CV_NODE_IS_REAL(flags) #define CV_NODE_IS_SEQ(flags) #define CV_NODE_IS_STRING(flags) #define CV_NODE_IS_USER(flags) #define CV_NODE_MAP #define CV_NODE_NAMED #define CV_NODE_NONE #define CV_NODE_REAL #define CV_NODE_REF #define CV_NODE_SEQ #define CV_NODE_SEQ_IS_SIMPLE(seq) #define CV_NODE_SEQ_SIMPLE #define CV_NODE_STR #define CV_NODE_STRING #define CV_NODE_TYPE(flags) #define CV_NODE_TYPE_MASK #define CV_NODE_USER #define CV_NODE_VAL( \ mat, \ node \ ) #define CV_NORMAL #define CV_NORM_MASK #define CV_NO_CN_CHECK #define CV_NO_DEPTH_CHECK #define CV_NO_SIZE_CHECK #define CV_ORIENTED_GRAPH #define CV_PCA_DATA_AS_COL #define CV_PCA_DATA_AS_ROW #define CV_PCA_USE_AVG #define CV_PREV_POINT(reader) #define CV_PREV_SEQ_ELEM( \ elem_size, \ reader \ ) #define CV_QR #define CV_RAND_NORMAL #define CV_RAND_UNI #define CV_READ_CHAIN_POINT( \ _pt, \ reader \ ) #define CV_READ_EDGE( \ pt1, \ pt2, \ reader \ ) #define CV_READ_SEQ_ELEM( \ elem, \ reader \ ) #define CV_REDUCE_AVG #define CV_REDUCE_MAX #define CV_REDUCE_MIN #define CV_REDUCE_SUM #define CV_RELATIVE #define CV_RELATIVE_C #define CV_RELATIVE_L1 #define CV_RELATIVE_L2 #define CV_REV_READ_SEQ_ELEM( \ elem, \ reader \ ) #define CV_RNG_COEFF #define CV_SEQUENCE_FIELDS() #define CV_SEQ_CHAIN #define CV_SEQ_CHAIN_CONTOUR #define CV_SEQ_CONNECTED_COMP #define CV_SEQ_CONTOUR #define CV_SEQ_ELEM( \ seq, \ elem_type, \ index \ ) #define CV_SEQ_ELTYPE(seq) #define CV_SEQ_ELTYPE_BITS #define CV_SEQ_ELTYPE_CODE #define CV_SEQ_ELTYPE_CONNECTED_COMP #define CV_SEQ_ELTYPE_GENERIC #define CV_SEQ_ELTYPE_GRAPH_EDGE #define CV_SEQ_ELTYPE_GRAPH_VERTEX #define CV_SEQ_ELTYPE_INDEX #define CV_SEQ_ELTYPE_MASK #define CV_SEQ_ELTYPE_POINT #define CV_SEQ_ELTYPE_POINT3D #define CV_SEQ_ELTYPE_PPOINT #define CV_SEQ_ELTYPE_PTR #define CV_SEQ_ELTYPE_TRIAN_ATR #define CV_SEQ_FLAG_CLOSED #define CV_SEQ_FLAG_CONVEX #define CV_SEQ_FLAG_HOLE #define CV_SEQ_FLAG_SHIFT #define CV_SEQ_FLAG_SIMPLE #define CV_SEQ_INDEX #define CV_SEQ_KIND(seq) #define CV_SEQ_KIND_BIN_TREE #define CV_SEQ_KIND_BITS #define CV_SEQ_KIND_CURVE #define CV_SEQ_KIND_GENERIC #define CV_SEQ_KIND_GRAPH #define CV_SEQ_KIND_MASK #define CV_SEQ_KIND_SUBDIV2D #define CV_SEQ_MAGIC_VAL #define CV_SEQ_POINT3D_SET #define CV_SEQ_POINT_SET #define CV_SEQ_POLYGON #define CV_SEQ_POLYGON_TREE #define CV_SEQ_POLYLINE #define CV_SEQ_READER_FIELDS() #define CV_SEQ_SIMPLE_POLYGON #define CV_SEQ_WRITER_FIELDS() #define CV_SET_ELEM_FIELDS(elem_type) #define CV_SET_ELEM_FREE_FLAG #define CV_SET_ELEM_IDX_MASK #define CV_SET_FIELDS() #define CV_SET_MAGIC_VAL #define CV_SIGN(a) #define CV_SORT_ASCENDING #define CV_SORT_DESCENDING #define CV_SORT_EVERY_COLUMN #define CV_SORT_EVERY_ROW #define CV_SPARSE_MAT_MAGIC_VAL #define CV_STORAGE_APPEND #define CV_STORAGE_BASE64 #define CV_STORAGE_FORMAT_AUTO #define CV_STORAGE_FORMAT_JSON #define CV_STORAGE_FORMAT_MASK #define CV_STORAGE_FORMAT_XML #define CV_STORAGE_FORMAT_YAML #define CV_STORAGE_MAGIC_VAL #define CV_STORAGE_MEMORY #define CV_STORAGE_READ #define CV_STORAGE_WRITE #define CV_STORAGE_WRITE_BASE64 #define CV_STORAGE_WRITE_BINARY #define CV_STORAGE_WRITE_TEXT #define CV_SVD #define CV_SVD_MODIFY_A #define CV_SVD_SYM #define CV_SVD_U_T #define CV_SVD_V_T #define CV_SWAP( \ a, \ b, \ t \ ) #define CV_TERMCRIT_EPS #define CV_TERMCRIT_ITER #define CV_TERMCRIT_NUMBER #define CV_TREE_NODE_FIELDS(node_type) #define CV_TURN_ON_IPL_COMPATIBILITY() #define CV_TYPE_NAME_GRAPH #define CV_TYPE_NAME_IMAGE #define CV_TYPE_NAME_MAT #define CV_TYPE_NAME_MATND #define CV_TYPE_NAME_SEQ #define CV_TYPE_NAME_SEQ_TREE #define CV_TYPE_NAME_SPARSE_MAT #define CV_WHOLE_ARR #define CV_WHOLE_SEQ #define CV_WHOLE_SEQ_END_INDEX #define CV_WRITE_SEQ_ELEM( \ elem, \ writer \ ) #define CV_WRITE_SEQ_ELEM_VAR( \ elem_ptr, \ writer \ ) #define IPL2CV_DEPTH(depth) #define IPL_ALIGN_16BYTES #define IPL_ALIGN_32BYTES #define IPL_ALIGN_4BYTES #define IPL_ALIGN_8BYTES #define IPL_ALIGN_DWORD #define IPL_ALIGN_QWORD #define IPL_BORDER_CONSTANT #define IPL_BORDER_REFLECT #define IPL_BORDER_REFLECT_101 #define IPL_BORDER_REPLICATE #define IPL_BORDER_TRANSPARENT #define IPL_BORDER_WRAP #define IPL_DATA_ORDER_PIXEL #define IPL_DATA_ORDER_PLANE #define IPL_DEPTH_16S #define IPL_DEPTH_16U #define IPL_DEPTH_1U #define IPL_DEPTH_32F #define IPL_DEPTH_32S #define IPL_DEPTH_64F #define IPL_DEPTH_8S #define IPL_DEPTH_8U #define IPL_DEPTH_SIGN #define IPL_IMAGE_DATA #define IPL_IMAGE_HEADER #define IPL_IMAGE_MAGIC_VAL #define IPL_IMAGE_ROI #define IPL_ORIGIN_BL #define IPL_ORIGIN_TL #define OPENCV_ASSERT( \ expr, \ func, \ context \ ) #define OPENCV_CALL(Func) #define OPENCV_ERROR( \ status, \ func, \ context \ ) #define __CV_BEGIN__ #define __CV_END__ #define __CV_EXIT__ #define cvAXPY( \ A, \ real_scalar, \ B, \ C \ ) #define cvAbs( \ src, \ dst \ ) #define cvCheckArray #define cvConvert( \ src, \ dst \ ) #define cvCvtScale #define cvCvtScaleAbs #define cvFFT #define cvFree(ptr) #define cvGetGraphVtx( \ graph, \ idx \ ) #define cvGetSubArr #define cvGraphEdgeIdx( \ graph, \ edge \ ) #define cvGraphFindEdge #define cvGraphFindEdgeByPtr #define cvGraphGetEdgeCount(graph) #define cvGraphGetVtxCount(graph) #define cvGraphVtxIdx( \ graph, \ vtx \ ) #define cvInv #define cvInvSqrt(value) #define cvMahalonobis #define cvMatMul( \ src1, \ src2, \ dst \ ) #define cvMatMulAdd( \ src1, \ src2, \ src3, \ dst \ ) #define cvMatMulAddEx #define cvMatMulAddS #define cvMirror #define cvReshapeND( \ arr, \ header, \ new_cn, \ new_dims, \ new_sizes \ ) #define cvScale #define cvSqrt(value) #define cvT #define cvZero
Detailed Documentation
Enum Values
CV_StsOk
everything is ok
CV_StsBackTrace
pseudo error for back trace
CV_StsError
unknown /unspecified error
CV_StsInternal
internal error (bad state)
CV_StsNoMem
insufficient memory
CV_StsBadArg
function arg/param is bad
CV_StsBadFunc
unsupported function
CV_StsNoConv
iter. didn’t converge
CV_StsAutoTrace
tracing
CV_HeaderIsNull
image header is NULL
CV_BadImageSize
image size is invalid
CV_BadOffset
offset is invalid
CV_BadStep
image step is wrong, this may happen for a non-continuous matrix
CV_BadNumChannels
bad number of channels, for example, some functions accept only single channel matrices
CV_BadDepth
input image depth is not supported by the function
CV_BadOrder
number of dimensions is out of range
CV_BadOrigin
incorrect input origin
CV_BadAlign
incorrect input align
CV_BadCOI
input COI is not supported
CV_BadROISize
incorrect input roi
CV_StsNullPtr
null pointer
CV_StsVecLengthErr
incorrect vector length
CV_StsFilterStructContentErr
incorrect filter structure content
CV_StsKernelStructContentErr
incorrect transform kernel content
CV_StsFilterOffsetErr
incorrect filter offset value
CV_StsBadSize
the input/output structure size is incorrect
CV_StsDivByZero
division by zero
CV_StsInplaceNotSupported
in-place operation is not supported
CV_StsObjectNotFound
request can’t be completed
CV_StsUnmatchedFormats
formats of input/output arrays differ
CV_StsBadFlag
flag is wrong or not supported
CV_StsBadPoint
bad CvPoint
CV_StsBadMask
bad format of mask (neither 8uC1 nor 8sC1)
CV_StsUnmatchedSizes
sizes of input/output structures do not match
CV_StsUnsupportedFormat
the data format/type is not supported by the function
CV_StsOutOfRange
some of parameters are out of range
CV_StsParseError
invalid syntax/structure of the parsed file
CV_StsNotImplemented
the requested function/feature is not implemented
CV_StsBadMemBlock
an allocated block has been corrupted
CV_StsAssert
assertion failed
CV_GpuNotSupported
no CUDA support
CV_GpuApiCallError
GPU API call error
CV_OpenGlNotSupported
no OpenGL support
CV_OpenGlApiCallError
OpenGL API call error
CV_OpenCLApiCallError
OpenCL API call error
CV_OpenCLInitError
OpenCL initialization error
Typedefs
typedef int (*CvCmpFunc)( const void *a, const void *b, void *userdata )
a < b ? -1 : a > b ? 1 : 0
typedef struct CvFileStorage CvFileStorage
“black box” representation of the file storage associated with a file on disk.
Several functions that are described below take CvFileStorage* as inputs and allow the user to save or to load hierarchical collections that consist of scalar values, standard CXCore objects (such as matrices, sequences, graphs), and user-defined objects.
OpenCV can read and write data in XML (http://www.w3c.org/XML), YAML (http://www.yaml.org) or JSON (http://www.json.org/) formats. Below is an example of 3x3 floating-point identity matrix A, stored in XML and YAML files using CXCore functions: XML:
<?xml version="1.0"> <opencv_storage> <A type_id="opencv-matrix"> <rows>3</rows> <cols>3</cols> <dt>f</dt> <data>1. 0. 0. 0. 1. 0. 0. 0. 1.</data> </A> </opencv_storage>
YAML:
%YAML:1.0 A: !!opencv-matrix rows: 3 cols: 3 dt: f data: [ 1., 0., 0., 0., 1., 0., 0., 0., 1.]
As it can be seen from the examples, XML uses nested tags to represent hierarchy, while YAML uses indentation for that purpose (similar to the Python programming language).
The same functions can read and write data in both formats; the particular format is determined by the extension of the opened file, “.xml” for XML files, “.yml” or “.yaml” for YAML and “.json” for JSON.
typedef void CvArr
This is the “metatype” used only as a function parameter.
It denotes that the function accepts arrays of multiple types, such as IplImage*, CvMat* or even CvSeq* sometimes. The particular array type is determined at runtime by analyzing the first 4 bytes of the header. In C++ interface the role of CvArr is played by InputArray and OutputArray.
Global Functions
void cvAbsDiff( const CvArr* src1, const CvArr* src2, CvArr* dst )
dst(x,y,c) = abs(src1(x,y,c) - src2(x,y,c))
void cvAbsDiffS( const CvArr* src, CvArr* dst, CvScalar value )
dst(x,y,c) = abs(src(x,y,c) - value(c))
void cvAdd( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL )
dst(mask) = src1(mask) + src2(mask)
void cvAddS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL )
dst(mask) = src(mask) + value
void cvAddWeighted( const CvArr* src1, double alpha, const CvArr* src2, double beta, double gamma, CvArr* dst )
dst = src1 * alpha + src2 * beta + gamma
void* cvAlloc(size_t size)
malloc
wrapper. If there is no enough memory, the function (as well as other OpenCV functions that call cvAlloc) raises an error.
void cvAnd( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL )
dst(idx) = src1(idx) & src2(idx)
void cvAndS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL )
dst(idx) = src(idx) & value
const char* cvAttrValue( const CvAttrList* attr, const char* attr_name )
returns attribute value or 0 (NULL) if there is no such attribute
CvScalar cvAvg( const CvArr* arr, const CvArr* mask = NULL )
Calculates mean value of array elements
void cvAvgSdv( const CvArr* arr, CvScalar* mean, CvScalar* std_dev, const CvArr* mask = NULL )
Calculates mean and standard deviation of pixel values
void cvCalcCovarMatrix( const CvArr** vects, int count, CvArr* cov_mat, CvArr* avg, int flags )
Calculates covariation matrix for a set of vectors
See also:
flags
void cvCartToPolar( const CvArr* x, const CvArr* y, CvArr* magnitude, CvArr* angle = NULL, int angle_in_degrees = 0 )
Does cartesian->polar coordinates conversion. Either of output components (magnitude or angle) is optional
float cvCbrt(float value)
Fast cubic root calculation
int cvCheckArr( const CvArr* arr, int flags = 0, double min_val = 0, double max_val = 0 )
Checks array values for NaNs, Infs or simply for too large numbers (if CV_CHECK_RANGE is set). If CV_CHECK_QUIET is set, no runtime errors is raised (function returns zero value in case of “bad” values). Otherwise cvError is called
CvTermCriteria cvCheckTermCriteria( CvTermCriteria criteria, double default_eps, int default_max_iters )
checks termination criteria validity and sets eps to default_eps (if it is not set), max_iter to default_max_iters (if it is not set)
void cvClearGraph(CvGraph* graph)
Remove all vertices and edges from the graph
void cvClearMemStorage(CvMemStorage* storage)
Clears memory storage. This is the only way(!!!) (besides cvRestoreMemStoragePos) to reuse memory allocated for the storage - cvClearSeq,cvClearSet … do not free any memory. A child storage returns all the blocks to the parent when it is cleared
void cvClearND( CvArr* arr, const int* idx )
clears element of ND dense array, in case of sparse arrays it deletes the specified node
void cvClearSeq(CvSeq* seq)
Removes all the elements from the sequence. The freed memory can be reused later only by the same sequence unless cvClearMemStorage or cvRestoreMemStoragePos is called
void cvClearSet(CvSet* set_header)
Removes all the elements from the set
void* cvClone(const void* struct_ptr)
Makes a clone of an object.
The function finds the type of a given object and calls clone with the passed object. Of course, if you know the object type, for example, struct_ptr is CvMat*, it is faster to call the specific function, like cvCloneMat.
Parameters:
struct_ptr | The object to clone |
CvGraph* cvCloneGraph( const CvGraph* graph, CvMemStorage* storage )
Creates a copy of graph
IplImage* cvCloneImage(const IplImage* image)
Creates a copy of IPL image (widthStep may differ)
CvMat* cvCloneMat(const CvMat* mat)
Creates an exact copy of the input matrix (except, may be, step value)
CvMatND* cvCloneMatND(const CvMatND* mat)
Creates a copy of CvMatND (except, may be, steps)
CvSparseMat* cvCloneSparseMat(const CvSparseMat* mat)
Creates a copy of CvSparseMat (except, may be, zero items)
void cvCmp( const CvArr* src1, const CvArr* src2, CvArr* dst, int cmp_op )
The comparison operation support single-channel arrays only. Destination image should be 8uC1 or 8sC1 dst(idx) = src1(idx) cmp_op src2(idx)
void cvCmpS( const CvArr* src, double value, CvArr* dst, int cmp_op )
dst(idx) = src1(idx) cmp_op value
void cvCompleteSymm( CvMat* matrix, int LtoR = 0 )
Completes the symmetric matrix from the lower (LtoR=0) or from the upper (LtoR!=0) part
void cvConvertScale( const CvArr* src, CvArr* dst, double scale = 1, double shift = 0 )
Converts one array to another with optional linear transformation.
The function has several different purposes, and thus has several different names. It copies one array to another with optional scaling, which is performed first, and/or optional type conversion, performed after:
All the channels of multi-channel arrays are processed independently.
The type of conversion is done with rounding and saturation, that is if the result of scaling + conversion can not be represented exactly by a value of the destination array element type, it is set to the nearest representable value on the real axis.
Parameters:
src | Source array |
dst | Destination array |
scale | Scale factor |
shift | Value added to the scaled source array elements |
void cvConvertScaleAbs( const CvArr* src, CvArr* dst, double scale = 1, double shift = 0 )
Performs linear transformation on every source array element, stores absolute value of the result: dst(x,y,c) = abs(scale*src(x,y,c)+shift). destination array must have 8u type. In other cases one may use cvConvertScale + cvAbsDiffS
void cvCopy( const CvArr* src, CvArr* dst, const CvArr* mask = NULL )
Copies one array to another.
The function copies selected elements from an input array to an output array:
If any of the passed arrays is of IplImage type, then its ROI and COI fields are used. Both arrays must have the same type, the same number of dimensions, and the same size. The function can also copy sparse arrays (mask is not supported in this case).
Parameters:
src | The source array |
dst | The destination array |
mask | Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed |
int cvCountNonZero(const CvArr* arr)
Calculates number of non-zero pixels
CvMemStorage* cvCreateChildMemStorage(CvMemStorage* parent)
Creates a memory storage that will borrow memory blocks from parent storage
void cvCreateData(CvArr* arr)
Allocates array data.
The function allocates image, matrix or multi-dimensional dense array data. Note that in the case of matrix types OpenCV allocation functions are used. In the case of IplImage they are used unless CV_TURN_ON_IPL_COMPATIBILITY() has been called before. In the latter case IPL functions are used to allocate the data.
Parameters:
arr | Array header |
CvGraph* cvCreateGraph( int graph_flags, int header_size, int vtx_size, int edge_size, CvMemStorage* storage )
Creates new graph
CvGraphScanner* cvCreateGraphScanner( CvGraph* graph, CvGraphVtx* vtx = NULL, int mask = -1 )
Creates new graph scanner.
IplImage* cvCreateImage( CvSize size, int depth, int channels )
Creates an image header and allocates the image data.
This function call is equivalent to the following code:
header = cvCreateImageHeader(size, depth, channels); cvCreateData(header);
Parameters:
size | Image width and height |
depth | Bit depth of image elements. See IplImage for valid depths. |
channels | Number of channels per pixel. See IplImage for details. This function only creates images with interleaved channels. |
IplImage* cvCreateImageHeader( CvSize size, int depth, int channels )
Creates an image header but does not allocate the image data.
Parameters:
size | Image width and height |
depth | Image depth (see cvCreateImage ) |
channels | Number of channels (see cvCreateImage ) |
CvMat* cvCreateMat( int rows, int cols, int type )
Creates a matrix header and allocates the matrix data.
The function call is equivalent to the following code:
CvMat* mat = cvCreateMatHeader(rows, cols, type); cvCreateData(mat);
Parameters:
rows | Number of rows in the matrix |
cols | Number of columns in the matrix |
type | The type of the matrix elements in the form CV_<bit depth><S|U|F>C<number of channels> , where S=signed, U=unsigned, F=float. For example, CV _ 8UC1 means the elements are 8-bit unsigned and the there is 1 channel, and CV _ 32SC2 means the elements are 32-bit signed and there are 2 channels. |
CvMat* cvCreateMatHeader( int rows, int cols, int type )
Creates a matrix header but does not allocate the matrix data.
The function allocates a new matrix header and returns a pointer to it. The matrix data can then be allocated using cvCreateData or set explicitly to user-allocated data via cvSetData.
Parameters:
rows | Number of rows in the matrix |
cols | Number of columns in the matrix |
type | Type of the matrix elements, see cvCreateMat |
CvMatND* cvCreateMatND( int dims, const int* sizes, int type )
Creates the header and allocates the data for a multi-dimensional dense array.
This function call is equivalent to the following code:
CvMatND* mat = cvCreateMatNDHeader(dims, sizes, type); cvCreateData(mat);
Parameters:
dims | Number of array dimensions. This must not exceed CV_MAX_DIM (32 by default, but can be changed at build time). |
sizes | Array of dimension sizes. |
type | Type of array elements, see cvCreateMat . |
CvMatND* cvCreateMatNDHeader( int dims, const int* sizes, int type )
Creates a new matrix header but does not allocate the matrix data.
The function allocates a header for a multi-dimensional dense array. The array data can further be allocated using cvCreateData or set explicitly to user-allocated data via cvSetData.
Parameters:
dims | Number of array dimensions |
sizes | Array of dimension sizes |
type | Type of array elements, see cvCreateMat |
CvMemStorage* cvCreateMemStorage(int block_size = 0)
Creates new memory storage. block_size == 0 means that default, somewhat optimal size, is used (currently, it is 64K)
CvSeq* cvCreateSeq( int seq_flags, size_t header_size, size_t elem_size, CvMemStorage* storage )
Creates new empty sequence that will reside in the specified storage
CvSet* cvCreateSet( int set_flags, int header_size, int elem_size, CvMemStorage* storage )
Creates a new set
CvSparseMat* cvCreateSparseMat( int dims, const int* sizes, int type )
Creates sparse array.
The function allocates a multi-dimensional sparse array. Initially the array contain no elements, that is PtrND and other related functions will return 0 for every index.
Parameters:
dims | Number of array dimensions. In contrast to the dense matrix, the number of dimensions is practically unlimited (up to \(2^{16}\)). |
sizes | Array of dimension sizes |
type | Type of array elements. The same as for CvMat |
void cvCrossProduct( const CvArr* src1, const CvArr* src2, CvArr* dst )
Calculates the cross product of two 3D vectors.
The function calculates the cross product of two 3D vectors:
or:
Parameters:
src1 | The first source vector |
src2 | The second source vector |
dst | The destination vector |
void* cvCvtSeqToArray( const CvSeq* seq, void* elements, CvSlice slice = CV_WHOLE_SEQ )
Copies sequence content to a continuous piece of memory
void cvDCT( const CvArr* src, CvArr* dst, int flags )
Discrete Cosine Transform
See also:
core_c_DftFlags “flags”
void cvDecRefData(CvArr* arr)
Decrements an array data reference counter.
The function decrements the data reference counter in a CvMat or CvMatND if the reference counter
pointer is not NULL. If the counter reaches zero, the data is deallocated. In the current implementation the reference counter is not NULL only if the data was allocated using the cvCreateData function. The counter will be NULL in other cases such as: external data was assigned to the header using cvSetData, header is part of a larger matrix or image, or the header was converted from an image or n-dimensional matrix header.
Parameters:
arr | Pointer to an array header |
double cvDet(const CvArr* mat)
Calculates determinant of input matrix
void cvDFT( const CvArr* src, CvArr* dst, int flags, int nonzero_rows = 0 )
Discrete Fourier Transform: complex->complex, real->ccs (forward), ccs->real (inverse)
See also:
core_c_DftFlags “flags”
void cvDiv( const CvArr* src1, const CvArr* src2, CvArr* dst, double scale = 1 )
element-wise division/inversion with scaling: dst(idx) = src1(idx) * scale / src2(idx) or dst(idx) = scale / src2(idx) if src1 == 0
double cvDotProduct( const CvArr* src1, const CvArr* src2 )
Calculates the dot product of two arrays in Euclidean metrics.
The function calculates and returns the Euclidean dot product of two arrays.
In the case of multiple channel arrays, the results for all channels are accumulated. In particular, cvDotProduct(a,a) where a is a complex vector, will return \(||\texttt{a}||^2\). The function can process multi-dimensional arrays, row by row, layer by layer, and so on.
Parameters:
src1 | The first source array |
src2 | The second source array |
void cvEigenVV( CvArr* mat, CvArr* evects, CvArr* evals, double eps = 0, int lowindex = -1, int highindex = -1 )
Finds eigen values and vectors of a symmetric matrix
CvSeq* cvEndWriteSeq(CvSeqWriter* writer)
Closes sequence writer, updates sequence header and returns pointer to the resultant sequence (which may be useful if the sequence was created using cvStartWriteSeq))
void cvEndWriteStruct(CvFileStorage* fs)
Finishes writing to a file node collection.
Parameters:
fs | File storage |
See also:
void cvError( int status, const char* func_name, const char* err_msg, const char* file_name, int line )
Sets error status and performs some additional actions (displaying message box, writing message to stderr, terminating application etc.) depending on the current error mode
int cvErrorFromIppStatus(int ipp_status)
Maps IPP error codes to the counterparts from OpenCV
const char* cvErrorStr(int status)
Retrieves textual description of the error given its code
void cvExp( const CvArr* src, CvArr* dst )
Does exponention: dst(idx) = exp(src(idx)). Overflow is not handled yet. Underflow is handled. Maximal relative error is ~7e-6 for single-precision input
float cvFastArctan( float y, float x )
Fast arctangent calculation
CvGraphEdge* cvFindGraphEdge( const CvGraph* graph, int start_idx, int end_idx )
Find edge connecting two vertices
CvTypeInfo* cvFindType(const char* type_name)
Finds a type by its name.
The function finds a registered type by its name. It returns NULL if there is no type with the specified name.
Parameters:
type_name | Type name |
CvTypeInfo* cvFirstType(void)
Returns the beginning of a type list.
The function returns the first type in the list of registered types. Navigation through the list can be done via the prev and next fields of the CvTypeInfo structure.
void cvFlip( const CvArr* src, CvArr* dst = NULL, int flip_mode = 0 )
Mirror array data around horizontal (flip=0), vertical (flip=1) or both(flip=-1) axises: cvFlip(src) flips images vertically and sequences horizontally (inplace)
void cvFlushSeqWriter(CvSeqWriter* writer)
Updates sequence header. May be useful to get access to some of previously written elements via cvGetSeqElem or sequence reader
void cvFree_(void* ptr)
free
wrapper. Here and further all the memory releasing functions (that all call cvFree) take double pointer in order to to clear pointer to the data after releasing it. Passing pointer to NULL pointer is Ok: nothing happens in this case
void cvGEMM( const CvArr* src1, const CvArr* src2, double alpha, const CvArr* src3, double beta, CvArr* dst, int tABC = 0 )
Extended matrix transform: dst = alpha*op(A)*op(B) + beta*op(C), where op(X) is X or X^T
CvScalar cvGet1D( const CvArr* arr, int idx0 )
Return a specific array element.
The functions return a specific array element. In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).
Parameters:
arr | Input array |
idx0 | The first zero-based component of the element index |
CvScalar cvGet2D( const CvArr* arr, int idx0, int idx1 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
CvScalar cvGet3D( const CvArr* arr, int idx0, int idx1, int idx2 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
CvMat* cvGetCol( const CvArr* arr, CvMat* submat, int col )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array |
submat | Pointer to the resulting sub-array header |
col | Zero-based index of the selected column |
CvMat* cvGetCols( const CvArr* arr, CvMat* submat, int start_col, int end_col )
Returns one of more array columns.
The functions return the header, corresponding to a specified column span of the input array. That
is, no data is copied. Therefore, any modifications of the submatrix will affect the original array. If you need to copy the columns, use cvCloneMat. cvGetCol(arr, submat, col) is a shortcut for cvGetCols(arr, submat, col, col+1).
Parameters:
arr | Input array |
submat | Pointer to the resulting sub-array header |
start_col | Zero-based index of the starting column (inclusive) of the span |
end_col | Zero-based index of the ending column (exclusive) of the span |
CvMat* cvGetDiag( const CvArr* arr, CvMat* submat, int diag = 0 )
Returns one of array diagonals.
The function returns the header, corresponding to a specified diagonal of the input array.
Parameters:
arr | Input array |
submat | Pointer to the resulting sub-array header |
diag | Index of the array diagonal. Zero value corresponds to the main diagonal, -1 corresponds to the diagonal above the main, 1 corresponds to the diagonal below the main, and so forth. |
int cvGetDims( const CvArr* arr, int* sizes = NULL )
Return number of array dimensions.
The function returns the array dimensionality and the array of dimension sizes. In the case of IplImage or CvMat it always returns 2 regardless of number of image/matrix rows. For example, the following code calculates total number of array elements:
int sizes[CV_MAX_DIM]; int i, total = 1; int dims = cvGetDims(arr, size); for(i = 0; i < dims; i++ ) total *= sizes[i];
Parameters:
arr | Input array |
sizes | Optional output vector of the array dimension sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next. |
int cvGetDimSize( const CvArr* arr, int index )
Returns array size along the specified dimension.
Parameters:
arr | Input array |
index | Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width) |
int cvGetElemType(const CvArr* arr)
Returns type of array elements.
The function returns type of the array elements. In the case of IplImage the type is converted to CvMat-like representation. For example, if the image has been created as:
IplImage* img = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 3);
The code cvGetElemType(img) will return CV_8UC3.
Parameters:
arr | Input array |
int cvGetErrInfo( const char** errcode_desc, const char** description, const char** filename, int* line )
Retrieves detailed information about the last error occurred
int cvGetErrMode(void)
Retrives current error processing mode
int cvGetErrStatus(void)
Get current OpenCV error status
CvFileNode* cvGetFileNode( CvFileStorage* fs, CvFileNode* map, const CvStringHashNode* key, int create_missing = 0 )
Finds a node in a map or file storage.
The function finds a file node. It is a faster version of cvGetFileNodeByName (see cvGetHashedKey discussion). Also, the function can insert a new node, if it is not in the map yet.
Parameters:
fs | File storage |
map | The parent map. If it is NULL, the function searches a top-level node. If both map and key are NULLs, the function returns the root file node - a map that contains top-level nodes. |
key | Unique pointer to the node name, retrieved with cvGetHashedKey |
create_missing | Flag that specifies whether an absent node should be added to the map |
CvFileNode* cvGetFileNodeByName( const CvFileStorage* fs, const CvFileNode* map, const char* name )
Finds a node in a map or file storage.
The function finds a file node by name. The node is searched either in map or, if the pointer is NULL, among the top-level file storage nodes. Using this function for maps and cvGetSeqElem (or sequence reader) for sequences, it is possible to navigate through the file storage. To speed up multiple queries for a certain key (e.g., in the case of an array of structures) one may use a combination of cvGetHashedKey and cvGetFileNode.
Parameters:
fs | File storage |
map | The parent map. If it is NULL, the function searches in all the top-level nodes (streams), starting with the first one. |
name | The file node name |
const char* cvGetFileNodeName(const CvFileNode* node)
Returns the name of a file node.
The function returns the name of a file node or NULL, if the file node does not have a name or if node is NULL.
Parameters:
node | File node |
CvStringHashNode* cvGetHashedKey( CvFileStorage* fs, const char* name, int len = -1, int create_missing = 0 )
Returns a unique pointer for a given name.
The function returns a unique pointer for each particular file node name. This pointer can be then passed to the cvGetFileNode function that is faster than cvGetFileNodeByName because it compares text strings by comparing pointers rather than the strings’ content.
Consider the following example where an array of points is encoded as a sequence of 2-entry maps:
points: - { x: 10, y: 10 } - { x: 20, y: 20 } - { x: 30, y: 30 } # ...
Then, it is possible to get hashed “x” and “y” pointers to speed up decoding of the points. :
#include "cxcore.h" int main( int argc, char** argv ) { CvFileStorage* fs = cvOpenFileStorage( "points.yml", 0, CV_STORAGE_READ ); CvStringHashNode* x_key = cvGetHashedNode( fs, "x", -1, 1 ); CvStringHashNode* y_key = cvGetHashedNode( fs, "y", -1, 1 ); CvFileNode* points = cvGetFileNodeByName( fs, 0, "points" ); if( CV_NODE_IS_SEQ(points->tag) ) { CvSeq* seq = points->data.seq; int i, total = seq->total; CvSeqReader reader; cvStartReadSeq( seq, &reader, 0 ); for( i = 0; i < total; i++ ) { CvFileNode* pt = (CvFileNode*)reader.ptr; #if 1 // faster variant CvFileNode* xnode = cvGetFileNode( fs, pt, x_key, 0 ); CvFileNode* ynode = cvGetFileNode( fs, pt, y_key, 0 ); assert( xnode && CV_NODE_IS_INT(xnode->tag) && ynode && CV_NODE_IS_INT(ynode->tag)); int x = xnode->data.i; // or x = cvReadInt( xnode, 0 ); int y = ynode->data.i; // or y = cvReadInt( ynode, 0 ); #elif 1 // slower variant; does not use x_key & y_key CvFileNode* xnode = cvGetFileNodeByName( fs, pt, "x" ); CvFileNode* ynode = cvGetFileNodeByName( fs, pt, "y" ); assert( xnode && CV_NODE_IS_INT(xnode->tag) && ynode && CV_NODE_IS_INT(ynode->tag)); int x = xnode->data.i; // or x = cvReadInt( xnode, 0 ); int y = ynode->data.i; // or y = cvReadInt( ynode, 0 ); #else // the slowest yet the easiest to use variant int x = cvReadIntByName( fs, pt, "x", 0 ); int y = cvReadIntByName( fs, pt, "y", 0 ); #endif CV_NEXT_SEQ_ELEM( seq->elem_size, reader ); printf(" } } cvReleaseFileStorage( &fs ); return 0; }
Please note that whatever method of accessing a map you are using, it is still much slower than using plain sequences; for example, in the above example, it is more efficient to encode the points as pairs of integers in a single numeric sequence.
Parameters:
fs | File storage |
name | Literal node name |
len | Length of the name (if it is known apriori), or -1 if it needs to be calculated |
create_missing | Flag that specifies, whether an absent key should be added into the hash table |
IplImage* cvGetImage( const CvArr* arr, IplImage* image_header )
Returns image header for arbitrary array.
The function returns the image header for the input array that can be a matrix (CvMat) or image (IplImage). In the case of an image the function simply returns the input pointer. In the case of CvMat it initializes an image_header structure with the parameters of the input matrix. Note that if we transform IplImage to CvMat using cvGetMat and then transform CvMat back to IplImage using this function, we will get different headers if the ROI is set in the original image.
Parameters:
arr | Input array |
image_header | Pointer to IplImage structure used as a temporary buffer |
int cvGetImageCOI(const IplImage* image)
Returns the index of the channel of interest.
Returns the channel of interest of in an IplImage. Returned values correspond to the coi in cvSetImageCOI.
Parameters:
image | A pointer to the image header |
CvRect cvGetImageROI(const IplImage* image)
Returns the image ROI.
If there is no ROI set, cvRect(0,0,image->width,image->height) is returned.
Parameters:
image | A pointer to the image header |
CvMat* cvGetMat( const CvArr* arr, CvMat* header, int* coi = NULL, int allowND = 0 )
Returns matrix header for arbitrary array.
The function returns a matrix header for the input array that can be a matrix - CvMat, an image - IplImage, or a multi-dimensional dense array - CvMatND (the third option is allowed only if allowND != 0) . In the case of matrix the function simply returns the input pointer. In the case of IplImage* or CvMatND it initializes the header structure with parameters of the current image ROI and returns &header. Because COI is not supported by CvMat, it is returned separately.
The function provides an easy way to handle both types of arrays - IplImage and CvMat using the same code. Input array must have non-zero data pointer, otherwise the function will report an error.
If the input array is IplImage with planar data layout and COI set, the function returns the pointer to the selected plane and COI == 0. This feature allows user to process IplImage structures with planar data layout, even though OpenCV does not support such images.
Parameters:
arr | Input array |
header | Pointer to CvMat structure used as a temporary buffer |
coi | Optional output parameter for storing COI |
allowND | If non-zero, the function accepts multi-dimensional dense arrays (CvMatND*) and returns 2D matrix (if CvMatND has two dimensions) or 1D matrix (when CvMatND has 1 dimension or more than 2 dimensions). The CvMatND array must be continuous. |
See also:
cvGetImage, cvarrToMat.
CvScalar cvGetND( const CvArr* arr, const int* idx )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array |
idx | Array of the element indices |
CvSparseNode* cvGetNextSparseNode(CvSparseMatIterator* mat_iterator)
Returns the next sparse matrix element.
The function moves iterator to the next sparse matrix element and returns pointer to it. In the current version there is no any particular order of the elements, because they are stored in the hash table. The sample below demonstrates how to iterate through the sparse matrix:
// print all the non-zero sparse matrix elements and compute their sum double sum = 0; int i, dims = cvGetDims(sparsemat); CvSparseMatIterator it; CvSparseNode* node = cvInitSparseMatIterator(sparsemat, &it); for(; node != 0; node = cvGetNextSparseNode(&it)) { int* idx = CV_NODE_IDX(array, node); float val = *(float*)CV_NODE_VAL(array, node); printf("M"); for(i = 0; i < dims; i++ ) printf("[%d]", idx[i]); printf("=%g\n", val); sum += val; } printf("nTotal sum = %g\n", sum);
Parameters:
mat_iterator | Sparse array iterator |
int cvGetNumThreads(void)
retrieve/set the number of threads used in OpenMP implementations
int cvGetOptimalDFTSize(int size0)
Finds optimal DFT vector size >= size0
void cvGetRawData( const CvArr* arr, uchar** data, int* step = NULL, CvSize* roi_size = NULL )
Retrieves low-level information about the array.
The function fills output variables with low-level information about the array data. All output
parameters are optional, so some of the pointers may be set to NULL. If the array is IplImage with ROI set, the parameters of ROI are returned.
The following example shows how to get access to array elements. It computes absolute values of the array elements :
float* data; int step; CvSize size; cvGetRawData(array, (uchar**)&data, &step, &size); step /= sizeof(data[0]); for(int y = 0; y < size.height; y++, data += step ) for(int x = 0; x < size.width; x++ ) data[x] = (float)fabs(data[x]);
Parameters:
arr | Array header |
data | Output pointer to the whole image origin or ROI origin if ROI is set |
step | Output full row length in bytes |
roi_size | Output ROI size |
double cvGetReal1D( const CvArr* arr, int idx0 )
Return a specific element of single-channel 1D, 2D, 3D or nD array.
Returns a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that Get?D functions can be used safely for both single-channel and multiple-channel arrays though they are a bit slower.
In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).
Parameters:
arr | Input array. Must have a single channel. |
idx0 | The first zero-based component of the element index |
double cvGetReal2D( const CvArr* arr, int idx0, int idx1 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
double cvGetReal3D( const CvArr* arr, int idx0, int idx1, int idx2 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
double cvGetRealND( const CvArr* arr, const int* idx )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array. Must have a single channel. |
idx | Array of the element indices |
CvFileNode* cvGetRootFileNode( const CvFileStorage* fs, int stream_index = 0 )
Retrieves one of the top-level nodes of the file storage.
The function returns one of the top-level file nodes. The top-level nodes do not have a name, they correspond to the streams that are stored one after another in the file storage. If the index is out of range, the function returns a NULL pointer, so all the top-level nodes can be iterated by subsequent calls to the function with stream_index=0,1,…, until the NULL pointer is returned. This function can be used as a base for recursive traversal of the file storage.
Parameters:
fs | File storage |
stream_index | Zero-based index of the stream. See cvStartNextStream . In most cases, there is only one stream in the file; however, there can be several. |
CvMat* cvGetRow( const CvArr* arr, CvMat* submat, int row )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array |
submat | Pointer to the resulting sub-array header |
row | Zero-based index of the selected row |
CvMat* cvGetRows( const CvArr* arr, CvMat* submat, int start_row, int end_row, int delta_row = 1 )
Returns array row or row span.
The functions return the header, corresponding to a specified row/row span of the input array. cvGetRow(arr, submat, row) is a shortcut for cvGetRows(arr, submat, row, row+1).
Parameters:
arr | Input array |
submat | Pointer to the resulting sub-array header |
start_row | Zero-based index of the starting row (inclusive) of the span |
end_row | Zero-based index of the ending row (exclusive) of the span |
delta_row | Index step in the row span. That is, the function extracts every delta_row -th row from start_row and up to (but not including) end_row . |
schar* cvGetSeqElem( const CvSeq* seq, int index )
Retrieves pointer to specified sequence element. Negative indices are supported and mean counting from the end (e.g -1 means the last sequence element)
int cvGetSeqReaderPos(CvSeqReader* reader)
Returns current sequence reader position (currently observed sequence element)
CvSetElem* cvGetSetElem( const CvSet* set_header, int idx )
Returns a set element by index. If the element doesn’t belong to the set, NULL is returned
CvSize cvGetSize(const CvArr* arr)
Returns size of matrix or image ROI.
The function returns number of rows (CvSize::height) and number of columns (CvSize::width) of the input matrix or image. In the case of image the size of ROI is returned.
Parameters:
arr | array header |
CvMat* cvGetSubRect( const CvArr* arr, CvMat* submat, CvRect rect )
Returns matrix header corresponding to the rectangular sub-array of input image or matrix.
The function returns header, corresponding to a specified rectangle of the input array. In other
words, it allows the user to treat a rectangular part of input array as a stand-alone array. ROI is taken into account by the function so the sub-array of ROI is actually extracted.
Parameters:
arr | Input array |
submat | Pointer to the resultant sub-array header |
rect | Zero-based coordinates of the rectangle of interest |
int cvGetThreadNum(void)
get index of the thread being executed
int64 cvGetTickCount(void)
helper functions for RNG initialization and accurate time measurement: uses internal clock counter on x86
int cvGraphAddEdge( CvGraph* graph, int start_idx, int end_idx, const CvGraphEdge* edge = NULL, CvGraphEdge** inserted_edge = NULL )
Link two vertices specifed by indices or pointers if they are not connected or return pointer to already existing edge connecting the vertices. Functions return 1 if a new edge was created, 0 otherwise
int cvGraphAddVtx( CvGraph* graph, const CvGraphVtx* vtx = NULL, CvGraphVtx** inserted_vtx = NULL )
Adds new vertex to the graph
void cvGraphRemoveEdge( CvGraph* graph, int start_idx, int end_idx )
Remove edge connecting two vertices
int cvGraphRemoveVtx( CvGraph* graph, int index )
Removes vertex from the graph together with all incident edges
int cvGraphVtxDegree( const CvGraph* graph, int vtx_idx )
Count number of edges incident to the vertex
int cvGuiBoxReport( int status, const char* func_name, const char* err_msg, const char* file_name, int line, void* userdata )
Output to MessageBox(WIN32)
int cvIncRefData(CvArr* arr)
Increments array data reference counter.
The function increments CvMat or CvMatND data reference counter and returns the new counter value if the reference counter pointer is not NULL, otherwise it returns zero.
Parameters:
arr | Array header |
IplImage* cvInitImageHeader( IplImage* image, CvSize size, int depth, int channels, int origin = 0, int align = 4 )
Initializes an image header that was previously allocated.
The returned IplImage* points to the initialized header.
Parameters:
image | Image header to initialize |
size | Image width and height |
depth | Image depth (see cvCreateImage ) |
channels | Number of channels (see cvCreateImage ) |
origin | Top-left IPL_ORIGIN_TL or bottom-left IPL_ORIGIN_BL |
align | Alignment for image rows, typically 4 or 8 bytes |
CvMat* cvInitMatHeader( CvMat* mat, int rows, int cols, int type, void* data = NULL, int step = 0x7fffffff )
Initializes a pre-allocated matrix header.
This function is often used to process raw data with OpenCV matrix functions. For example, the following code computes the matrix product of two matrices, stored as ordinary arrays:
double a[] = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }; double b[] = { 1, 5, 9, 2, 6, 10, 3, 7, 11, 4, 8, 12 }; double c[9]; CvMat Ma, Mb, Mc ; cvInitMatHeader(&Ma, 3, 4, CV_64FC1, a); cvInitMatHeader(&Mb, 4, 3, CV_64FC1, b); cvInitMatHeader(&Mc, 3, 3, CV_64FC1, c); cvMatMulAdd(&Ma, &Mb, 0, &Mc); // the c array now contains the product of a (3x4) and b (4x3)
Parameters:
mat | A pointer to the matrix header to be initialized |
rows | Number of rows in the matrix |
cols | Number of columns in the matrix |
type | Type of the matrix elements, see cvCreateMat . |
data | Optional: data pointer assigned to the matrix header |
step | Optional: full row width in bytes of the assigned data. By default, the minimal possible step is used which assumes there are no gaps between subsequent rows of the matrix. |
CvMatND* cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes, int type, void* data = NULL )
Initializes a pre-allocated multi-dimensional array header.
Parameters:
mat | A pointer to the array header to be initialized |
dims | The number of array dimensions |
sizes | An array of dimension sizes |
type | Type of array elements, see cvCreateMat |
data | Optional data pointer assigned to the matrix header |
int cvInitNArrayIterator( int count, CvArr** arrs, const CvArr* mask, CvMatND* stubs, CvNArrayIterator* array_iterator, int flags = 0 )
initializes iterator that traverses through several arrays simulteneously (the function together with cvNextArraySlice is used for N-ari element-wise operations)
CvSparseNode* cvInitSparseMatIterator( const CvSparseMat* mat, CvSparseMatIterator* mat_iterator )
Initializes sparse array elements iterator.
The function initializes iterator of sparse array elements and returns pointer to the first element, or NULL if the array is empty.
Parameters:
mat | Input array |
mat_iterator | Initialized iterator |
void cvInRange( const CvArr* src, const CvArr* lower, const CvArr* upper, CvArr* dst )
dst(idx) = lower(idx) <= src(idx) < upper(idx)
void cvInRangeS( const CvArr* src, CvScalar lower, CvScalar upper, CvArr* dst )
dst(idx) = lower <= src(idx) < upper
void cvInsertNodeIntoTree( void* node, void* parent, void* frame )
Inserts sequence into tree with specified “parent” sequence. If parent is equal to frame (e.g. the most external contour), then added contour will have null pointer to parent.
double cvInvert( const CvArr* src, CvArr* dst, int method = 0 )
Inverts matrix
void* cvLoad( const char* filename, CvMemStorage* memstorage = NULL, const char* name = NULL, const char** real_name = NULL )
Loads an object from a file.
The function loads an object from a file. It basically reads the specified file, find the first top-level node and calls cvRead for that node. If the file node does not have type information or the type information can not be found by the type name, the function returns NULL. After the object is loaded, the file storage is closed and all the temporary buffers are deleted. Thus, to load a dynamic structure, such as a sequence, contour, or graph, one should pass a valid memory storage destination to the function.
Parameters:
filename | File name |
memstorage | Memory storage for dynamic structures, such as CvSeq or CvGraph. It is not used for matrices or images. |
name | Optional object name. If it is NULL, the first top-level object in the storage will be loaded. |
real_name | Optional output parameter that will contain the name of the loaded object (useful if name=NULL ) |
void cvLog( const CvArr* src, CvArr* dst )
Calculates natural logarithms: dst(idx) = log(abs(src(idx))). Logarithm of 0 gives large negative number(~-700) Maximal relative error is ~3e-7 for single-precision output
void cvLUT( const CvArr* src, CvArr* dst, const CvArr* lut )
Does look-up transformation. Elements of the source array (that should be 8uC1 or 8sC1) are used as indexes in lutarr 256-element table
double cvMahalanobis( const CvArr* vec1, const CvArr* vec2, const CvArr* mat )
Calculates Mahalanobis(weighted) distance
CvSeq* cvMakeSeqHeaderForArray( int seq_type, int header_size, int elem_size, void* elements, int total, CvSeq* seq, CvSeqBlock* block )
Creates sequence header for array. After that all the operations on sequences that do not alter the content can be applied to the resultant sequence
void cvMax( const CvArr* src1, const CvArr* src2, CvArr* dst )
dst(idx) = max(src1(idx),src2(idx))
void cvMaxS( const CvArr* src, double value, CvArr* dst )
dst(idx) = max(src(idx),value)
void* cvMemStorageAlloc( CvMemStorage* storage, size_t size )
Allocates continuous buffer of the specified size in the storage
CvString cvMemStorageAllocString( CvMemStorage* storage, const char* ptr, int len = -1 )
Allocates string in memory storage
void cvMerge( const CvArr* src0, const CvArr* src1, const CvArr* src2, const CvArr* src3, CvArr* dst )
Merges a set of single-channel arrays into the single multi-channel array or inserts one particular [color] plane to the array
void cvMin( const CvArr* src1, const CvArr* src2, CvArr* dst )
dst(idx) = min(src1(idx),src2(idx))
void cvMinMaxLoc( const CvArr* arr, double* min_val, double* max_val, CvPoint* min_loc = NULL, CvPoint* max_loc = NULL, const CvArr* mask = NULL )
Finds global minimum, maximum and their positions
void cvMinS( const CvArr* src, double value, CvArr* dst )
dst(idx) = min(src(idx),value)
void cvMixChannels( const CvArr** src, int src_count, CvArr** dst, int dst_count, const int* from_to, int pair_count )
Copies several channels from input arrays to certain channels of output arrays
void cvMul( const CvArr* src1, const CvArr* src2, CvArr* dst, double scale = 1 )
dst(idx) = src1(idx) * src2(idx) * scale (scaled element-wise multiplication of 2 arrays)
void cvMulSpectrums( const CvArr* src1, const CvArr* src2, CvArr* dst, int flags )
Multiply results of DFTs: DFT(X)*DFT(Y) or DFT(X)*conj(DFT(Y))
See also:
core_c_DftFlags “flags”
void cvMulTransposed( const CvArr* src, CvArr* dst, int order, const CvArr* delta = NULL, double scale = 1. )
Calculates (A-delta)*(A-delta)^T (order=0) or (A-delta)^T*(A-delta) (order=1)
int cvNextGraphItem(CvGraphScanner* scanner)
Get next graph element
int cvNextNArraySlice(CvNArrayIterator* array_iterator)
returns zero value if iteration is finished, non-zero (slice length) otherwise
double cvNorm( const CvArr* arr1, const CvArr* arr2 = NULL, int norm_type = 4, const CvArr* mask = NULL )
Finds norm, difference norm or relative difference norm for an array (or two arrays)
See also:
ref core_c_NormFlags “flags”
void cvNormalize( const CvArr* src, CvArr* dst, double a = 1., double b = 0., int norm_type = 4, const CvArr* mask = NULL )
See also:
ref core_c_NormFlags “flags”
void cvNot( const CvArr* src, CvArr* dst )
dst(idx) = ~src(idx)
int cvNulDevReport( int status, const char* func_name, const char* err_msg, const char* file_name, int line, void* userdata )
Output nothing
CvFileStorage* cvOpenFileStorage( const char* filename, CvMemStorage* memstorage, int flags, const char* encoding = NULL )
Opens file storage for reading or writing data.
The function opens file storage for reading or writing data. In the latter case, a new file is created or an existing file is rewritten. The type of the read or written file is determined by the filename extension: .xml for XML, .yml or .yaml for YAML and .json for JSON.
At the same time, it also supports adding parameters like “example.xml?base64”. The three ways are the same:
fs = cvOpenFileStorage( "example.yml?base64", 0, CV_STORAGE_WRITE );
fs = cvOpenFileStorage( "example.yml" , 0, CV_STORAGE_WRITE_BASE64 );
fs = cvOpenFileStorage( "example.yml" , 0, CV_STORAGE_WRITE | CV_STORAGE_BASE64 );
The function returns a pointer to the CvFileStorage structure. If the file cannot be opened then the function returns NULL.
Parameters:
filename | Name of the file associated with the storage |
memstorage | Memory storage used for temporary data and for : storing dynamic structures, such as CvSeq or CvGraph. If it is NULL, a temporary memory storage is created and used. |
flags | Can be one of the following: * CV_STORAGE_READ the storage is open for reading
(use CV_STORAGE_WRITE | CV_STORAGE_WRITE_BASE64 to write rawdata in Base64) |
encoding |
void cvOr( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL )
dst(idx) = src1(idx) | src2(idx)
void cvOrS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL )
dst(idx) = src(idx) | value
void cvPerspectiveTransform( const CvArr* src, CvArr* dst, const CvMat* mat )
Does perspective transform on every element of input array
void cvPolarToCart( const CvArr* magnitude, const CvArr* angle, CvArr* x, CvArr* y, int angle_in_degrees = 0 )
Does polar->cartesian coordinates conversion. Either of output components (magnitude or angle) is optional. If magnitude is missing it is assumed to be all 1’s
void cvPow( const CvArr* src, CvArr* dst, double power )
Does powering: dst(idx) = src(idx)^power
uchar* cvPtr1D( const CvArr* arr, int idx0, int* type = NULL )
Return pointer to a particular array element.
The functions return a pointer to a specific array element. Number of array dimension should match to the number of indices passed to the function except for cvPtr1D function that can be used for sequential access to 1D, 2D or nD dense arrays.
The functions can be used for sparse arrays as well - if the requested node does not exist they create it and set it to zero.
All these as well as other functions accessing array elements ( cvGetND , cvGetRealND , cvSet , cvSetND , cvSetRealND ) raise an error in case if the element index is out of range.
Parameters:
arr | Input array |
idx0 | The first zero-based component of the element index |
type | Optional output parameter: type of matrix elements |
uchar* cvPtr2D( const CvArr* arr, int idx0, int idx1, int* type = NULL )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
uchar* cvPtr3D( const CvArr* arr, int idx0, int idx1, int idx2, int* type = NULL )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
uchar* cvPtrND( const CvArr* arr, const int* idx, int* type = NULL, int create_node = 1, unsigned* precalc_hashval = NULL )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array |
idx | Array of the element indices |
type | Optional output parameter: type of matrix elements |
create_node | Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. |
precalc_hashval | Optional input parameter for sparse matrices. If the pointer is not NULL, the function does not recalculate the node hash value, but takes it from the specified location. It is useful for speeding up pair-wise operations (TODO: provide an example) |
void cvRandArr( CvRNG* rng, CvArr* arr, int dist_type, CvScalar param1, CvScalar param2 )
Fills an array with random numbers and updates the RNG state.
The function fills the destination array with uniformly or normally distributed random numbers.
Parameters:
rng | CvRNG state initialized by cvRNG |
arr | The destination array |
dist_type | Distribution type * CV_RAND_UNI uniform distribution
|
param1 | The first parameter of the distribution. In the case of a uniform distribution it is the inclusive lower boundary of the random numbers range. In the case of a normal distribution it is the mean value of the random numbers. |
param2 | The second parameter of the distribution. In the case of a uniform distribution it is the exclusive upper boundary of the random numbers range. In the case of a normal distribution it is the standard deviation of the random numbers. |
See also:
randu, randn, RNG::fill.
CvArr* cvRange( CvArr* mat, double start, double end )
Fills matrix with given range of numbers
void* cvRead( CvFileStorage* fs, CvFileNode* node, CvAttrList* attributes = NULL )
Decodes an object and returns a pointer to it.
The function decodes a user object (creates an object in a native representation from the file storage subtree) and returns it. The object to be decoded must be an instance of a registered type that supports the read method (see CvTypeInfo). The type of the object is determined by the type name that is encoded in the file. If the object is a dynamic structure, it is created either in memory storage and passed to cvOpenFileStorage or, if a NULL pointer was passed, in temporary memory storage, which is released when cvReleaseFileStorage is called. Otherwise, if the object is not a dynamic structure, it is created in a heap and should be released with a specialized function or by using the generic cvRelease.
Parameters:
fs | File storage |
node | The root object node |
attributes | Unused parameter |
void* cvReadByName( CvFileStorage* fs, const CvFileNode* map, const char* name, CvAttrList* attributes = NULL )
Finds an object by name and decodes it.
The function is a simple superposition of cvGetFileNodeByName and cvRead.
Parameters:
fs | File storage |
map | The parent map. If it is NULL, the function searches a top-level node. |
name | The node name |
attributes | Unused parameter |
int cvReadInt( const CvFileNode* node, int default_value = 0 )
Retrieves an integer value from a file node.
The function returns an integer that is represented by the file node. If the file node is NULL, the default_value is returned (thus, it is convenient to call the function right after cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_INT, then node->data.i is returned. If the file node has type CV_NODE_REAL, then node->data.f is converted to an integer and returned. Otherwise the error is reported.
Parameters:
node | File node |
default_value | The value that is returned if node is NULL |
int cvReadIntByName( const CvFileStorage* fs, const CvFileNode* map, const char* name, int default_value = 0 )
Finds a file node and returns its value.
The function is a simple superposition of cvGetFileNodeByName and cvReadInt.
Parameters:
fs | File storage |
map | The parent map. If it is NULL, the function searches a top-level node. |
name | The node name |
default_value | The value that is returned if the file node is not found |
void cvReadRawData( const CvFileStorage* fs, const CvFileNode* src, void* dst, const char* dt )
Reads multiple numbers.
The function reads elements from a file node that represents a sequence of scalars.
Parameters:
fs | File storage |
src | The file node (a sequence) to read numbers from |
dst | Pointer to the destination array |
dt | Specification of each array element. It has the same format as in cvWriteRawData . |
void cvReadRawDataSlice( const CvFileStorage* fs, CvSeqReader* reader, int count, void* dst, const char* dt )
Initializes file node sequence reader.
The function reads one or more elements from the file node, representing a sequence, to a user-specified array. The total number of read sequence elements is a product of total and the number of components in each array element. For example, if dt=2if, the function will read total*3 sequence elements. As with any sequence, some parts of the file node sequence can be skipped or read repeatedly by repositioning the reader using cvSetSeqReaderPos.
Parameters:
fs | File storage |
reader | The sequence reader. Initialize it with cvStartReadRawData . |
count | The number of elements to read |
dst | Pointer to the destination array |
dt | Specification of each array element. It has the same format as in cvWriteRawData . |
double cvReadReal( const CvFileNode* node, double default_value = 0. )
Retrieves a floating-point value from a file node.
The function returns a floating-point value that is represented by the file node. If the file node is NULL, the default_value is returned (thus, it is convenient to call the function right after cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_REAL , then node->data.f is returned. If the file node has type CV_NODE_INT , then node-:math:>data.f is converted to floating-point and returned. Otherwise the result is not determined.
Parameters:
node | File node |
default_value | The value that is returned if node is NULL |
double cvReadRealByName( const CvFileStorage* fs, const CvFileNode* map, const char* name, double default_value = 0. )
Finds a file node and returns its value.
The function is a simple superposition of cvGetFileNodeByName and cvReadReal .
Parameters:
fs | File storage |
map | The parent map. If it is NULL, the function searches a top-level node. |
name | The node name |
default_value | The value that is returned if the file node is not found |
const char* cvReadString( const CvFileNode* node, const char* default_value = NULL )
Retrieves a text string from a file node.
The function returns a text string that is represented by the file node. If the file node is NULL, the default_value is returned (thus, it is convenient to call the function right after cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_STR , then node-:math:>data.str.ptr is returned. Otherwise the result is not determined.
Parameters:
node | File node |
default_value | The value that is returned if node is NULL |
const char* cvReadStringByName( const CvFileStorage* fs, const CvFileNode* map, const char* name, const char* default_value = NULL )
Finds a file node by its name and returns its value.
The function is a simple superposition of cvGetFileNodeByName and cvReadString .
Parameters:
fs | File storage |
map | The parent map. If it is NULL, the function searches a top-level node. |
name | The node name |
default_value | The value that is returned if the file node is not found |
CvErrorCallback cvRedirectError( CvErrorCallback error_handler, void* userdata = NULL, void** prev_userdata = NULL )
Assigns a new error-handling function
void cvReduce( const CvArr* src, CvArr* dst, int dim = -1, int op = 0 )
See also:
flags
void cvRegisterType(const CvTypeInfo* info)
Registers a new type.
The function registers a new type, which is described by info . The function creates a copy of the structure, so the user should delete it after calling the function.
Parameters:
info | Type info structure |
void cvRelease(void** struct_ptr)
Releases an object.
The function finds the type of a given object and calls release with the double pointer.
Parameters:
struct_ptr | Double pointer to the object |
void cvReleaseData(CvArr* arr)
Releases array data.
The function releases the array data. In the case of CvMat or CvMatND it simply calls cvDecRefData(), that is the function can not deallocate external data. See also the note to cvCreateData .
Parameters:
arr | Array header |
void cvReleaseFileStorage(CvFileStorage** fs)
Releases file storage.
The function closes the file associated with the storage and releases all the temporary structures. It must be called after all I/O operations with the storage are finished.
Parameters:
fs | Double pointer to the released file storage |
void cvReleaseGraphScanner(CvGraphScanner** scanner)
Releases graph scanner.
void cvReleaseImage(IplImage** image)
Deallocates the image header and the image data.
This call is a shortened form of :
if(*image ) { cvReleaseData(*image); cvReleaseImageHeader(image); }
Parameters:
image | Double pointer to the image header |
void cvReleaseImageHeader(IplImage** image)
Deallocates an image header.
This call is an analogue of :
if(image ) { iplDeallocate(*image, IPL_IMAGE_HEADER | IPL_IMAGE_ROI); *image = 0; }
but it does not use IPL functions by default (see the CV_TURN_ON_IPL_COMPATIBILITY macro).
Parameters:
image | Double pointer to the image header |
void cvReleaseMat(CvMat** mat)
Deallocates a matrix.
The function decrements the matrix data reference counter and deallocates matrix header. If the data reference counter is 0, it also deallocates the data. :
if(*mat ) cvDecRefData(*mat); cvFree((void**)mat);
Parameters:
mat | Double pointer to the matrix |
void cvReleaseMatND(CvMatND** mat)
Deallocates a multi-dimensional array.
The function decrements the array data reference counter and releases the array header. If the reference counter reaches 0, it also deallocates the data. :
if(*mat ) cvDecRefData(*mat); cvFree((void**)mat);
Parameters:
mat | Double pointer to the array |
void cvReleaseMemStorage(CvMemStorage** storage)
Releases memory storage. All the children of a parent must be released before the parent. A child storage returns all the blocks to parent when it is released
void cvReleaseSparseMat(CvSparseMat** mat)
Deallocates sparse array.
The function releases the sparse array and clears the array pointer upon exit.
Parameters:
mat | Double pointer to the array |
void cvRemoveNodeFromTree( void* node, void* frame )
Removes contour from tree (together with the contour children).
void cvRepeat( const CvArr* src, CvArr* dst )
Repeats source 2d array several times in both horizontal and vertical direction to fill destination array
void cvResetImageROI(IplImage* image)
Resets the image ROI to include the entire image and releases the ROI structure.
This produces a similar result to the following, but in addition it releases the ROI structure. :
cvSetImageROI(image, cvRect(0, 0, image->width, image->height )); cvSetImageCOI(image, 0);
Parameters:
image | A pointer to the image header |
CvMat* cvReshape( const CvArr* arr, CvMat* header, int new_cn, int new_rows = 0 )
Changes shape of matrix/image without copying data.
The function initializes the CvMat header so that it points to the same data as the original array but has a different shape - different number of channels, different number of rows, or both.
The following example code creates one image buffer and two image headers, the first is for a 320x240x3 image and the second is for a 960x240x1 image:
IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3); CvMat gray_mat_hdr; IplImage gray_img_hdr, *gray_img; cvReshape(color_img, &gray_mat_hdr, 1); gray_img = cvGetImage(&gray_mat_hdr, &gray_img_hdr);
And the next example converts a 3x3 matrix to a single 1x9 vector:
CvMat* mat = cvCreateMat(3, 3, CV_32F); CvMat row_header, *row; row = cvReshape(mat, &row_header, 0, 1);
Parameters:
arr | Input array |
header | Output header to be filled |
new_cn | New number of channels. ‘new_cn = 0’ means that the number of channels remains unchanged. |
new_rows | New number of rows. ‘new_rows = 0’ means that the number of rows remains unchanged unless it needs to be changed according to new_cn value. |
CvArr* cvReshapeMatND( const CvArr* arr, int sizeof_header, CvArr* header, int new_cn, int new_dims, int* new_sizes )
Changes the shape of a multi-dimensional array without copying the data.
The function is an advanced version of cvReshape that can work with multi-dimensional arrays as well (though it can work with ordinary images and matrices) and change the number of dimensions.
Below are the two samples from the cvReshape description rewritten using cvReshapeMatND:
IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3); IplImage gray_img_hdr, *gray_img; gray_img = (IplImage*)cvReshapeMatND(color_img, sizeof(gray_img_hdr), &gray_img_hdr, 1, 0, 0); ... int size[] = { 2, 2, 2 }; CvMatND* mat = cvCreateMatND(3, size, CV_32F); CvMat row_header, *row; row = (CvMat*)cvReshapeMatND(mat, sizeof(row_header), &row_header, 0, 1, 0);
In C, the header file for this function includes a convenient macro cvReshapeND that does away with the sizeof_header parameter. So, the lines containing the call to cvReshapeMatND in the examples may be replaced as follow:
gray_img = (IplImage*)cvReshapeND(color_img, &gray_img_hdr, 1, 0, 0); ... row = (CvMat*)cvReshapeND(mat, &row_header, 0, 1, 0);
Parameters:
arr | Input array |
sizeof_header | Size of output header to distinguish between IplImage, CvMat and CvMatND output headers |
header | Output header to be filled |
new_cn | New number of channels. new_cn = 0 means that the number of channels remains unchanged. |
new_dims | New number of dimensions. new_dims = 0 means that the number of dimensions remains the same. |
new_sizes | Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used. |
void cvRestoreMemStoragePos( CvMemStorage* storage, CvMemStoragePos* pos )
Restore a storage “free memory” position
void cvSave( const char* filename, const void* struct_ptr, const char* name = NULL, const char* comment = NULL, CvAttrList attributes = cvAttrList() )
Saves an object to a file.
The function saves an object to a file. It provides a simple interface to cvWrite .
Parameters:
filename | File name |
struct_ptr | Object to save |
name | Optional object name. If it is NULL, the name will be formed from filename . |
comment | Optional comment to put in the beginning of the file |
attributes | Optional attributes passed to cvWrite |
void cvSaveMemStoragePos( const CvMemStorage* storage, CvMemStoragePos* pos )
Remember a storage “free memory” position
void cvScalarToRawData( const CvScalar* scalar, void* data, int type, int extend_to_12 = 0 )
low-level scalar <-> raw data conversion functions
void cvScaleAdd( const CvArr* src1, CvScalar scale, const CvArr* src2, CvArr* dst )
dst = src1 * scale + src2
int cvSeqElemIdx( const CvSeq* seq, const void* element, CvSeqBlock** block = NULL )
Calculates index of the specified sequence element. Returns -1 if element does not belong to the sequence
schar* cvSeqInsert( CvSeq* seq, int before_index, const void* element = NULL )
Inserts a new element in the middle of sequence. cvSeqInsert(seq,0,elem) == cvSeqPushFront(seq,elem)
void cvSeqInsertSlice( CvSeq* seq, int before_index, const CvArr* from_arr )
Inserts a sequence or array into another sequence
void cvSeqInvert(CvSeq* seq)
Reverses order of sequence elements in-place
int cvSeqPartition( const CvSeq* seq, CvMemStorage* storage, CvSeq** labels, CvCmpFunc is_equal, void* userdata )
Splits sequence into one or more equivalence classes using the specified criteria
void cvSeqPop( CvSeq* seq, void* element = NULL )
Removes the last element from sequence and optionally saves it
void cvSeqPopFront( CvSeq* seq, void* element = NULL )
Removes the first element from sequence and optioanally saves it
void cvSeqPopMulti( CvSeq* seq, void* elements, int count, int in_front = 0 )
Removes several elements from the end of sequence and optionally saves them
schar* cvSeqPush( CvSeq* seq, const void* element = NULL )
Adds new element to the end of sequence. Returns pointer to the element
schar* cvSeqPushFront( CvSeq* seq, const void* element = NULL )
Adds new element to the beginning of sequence. Returns pointer to it
void cvSeqPushMulti( CvSeq* seq, const void* elements, int count, int in_front = 0 )
Adds several new elements to the end of sequence
void cvSeqRemove( CvSeq* seq, int index )
Removes specified sequence element
void cvSeqRemoveSlice( CvSeq* seq, CvSlice slice )
Removes sequence slice
schar* cvSeqSearch( CvSeq* seq, const void* elem, CvCmpFunc func, int is_sorted, int* elem_idx, void* userdata = NULL )
Finds element in a [sorted] sequence
CvSeq* cvSeqSlice( const CvSeq* seq, CvSlice slice, CvMemStorage* storage = NULL, int copy_data = 0 )
Extracts sequence slice (with or without copying sequence elements)
void cvSeqSort( CvSeq* seq, CvCmpFunc func, void* userdata = NULL )
Sorts sequence in-place given element comparison function
void cvSet( CvArr* arr, CvScalar value, const CvArr* mask = NULL )
Sets every element of an array to a given value.
The function copies the scalar value to every selected element of the destination array:
If array arr is of IplImage type, then is ROI used, but COI must not be set.
Parameters:
arr | The destination array |
value | Fill value |
mask | Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed |
void cvSet1D( CvArr* arr, int idx0, CvScalar value )
Change the particular array element.
The functions assign the new value to a particular array element. In the case of a sparse array the functions create the node if it does not exist yet.
Parameters:
arr | Input array |
idx0 | The first zero-based component of the element index |
value | The assigned value |
void cvSet2D( CvArr* arr, int idx0, int idx1, CvScalar value )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
void cvSet3D( CvArr* arr, int idx0, int idx1, int idx2, CvScalar value )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
int cvSetAdd( CvSet* set_header, CvSetElem* elem = NULL, CvSetElem** inserted_elem = NULL )
Adds new element to the set and returns pointer to it
void cvSetData( CvArr* arr, void* data, int step )
Assigns user data to the array header.
The function assigns user data to the array header. Header should be initialized before using cvCreateMatHeader, cvCreateImageHeader, cvCreateMatNDHeader, cvInitMatHeader, cvInitImageHeader or cvInitMatNDHeader.
Parameters:
arr | Array header |
data | User data |
step | Full row length in bytes |
int cvSetErrMode(int mode)
Sets error processing mode, returns previously used mode
void cvSetErrStatus(int status)
Sets error status silently
void cvSetIdentity( CvArr* mat, CvScalar value = cvRealScalar(1) )
- Finds selected eigen values and vectors of a symmetric matrix */ Makes an identity matrix (mat_ij = i == j)
void cvSetImageCOI( IplImage* image, int coi )
Sets the channel of interest in an IplImage.
If the ROI is set to NULL and the coi is not 0, the ROI is allocated. Most OpenCV functions do not* support the COI setting, so to process an individual image/matrix channel one may copy (via cvCopy or cvSplit) the channel to a separate image/matrix, process it and then copy the result back (via cvCopy or cvMerge) if needed.
Parameters:
image | A pointer to the image header |
coi | The channel of interest. 0 - all channels are selected, 1 - first channel is selected, etc. Note that the channel indices become 1-based. |
void cvSetImageROI( IplImage* image, CvRect rect )
Sets an image Region Of Interest (ROI) for a given rectangle.
If the original image ROI was NULL and the rect is not the whole image, the ROI structure is allocated.
Most OpenCV functions support the use of ROI and treat the image rectangle as a separate image. For example, all of the pixel coordinates are counted from the top-left (or bottom-left) corner of the ROI, not the original image.
Parameters:
image | A pointer to the image header |
rect | The ROI rectangle |
void cvSetIPLAllocators( Cv_iplCreateImageHeader create_header, Cv_iplAllocateImageData allocate_data, Cv_iplDeallocate deallocate, Cv_iplCreateROI create_roi, Cv_iplCloneImage clone_image )
Makes OpenCV use IPL functions for allocating IplImage and IplROI structures.
Normally, the function is not called directly. Instead, a simple macro CV_TURN_ON_IPL_COMPATIBILITY() is used that calls cvSetIPLAllocators and passes there pointers to IPL allocation functions. :
... CV_TURN_ON_IPL_COMPATIBILITY() ...
Parameters:
create_header | pointer to a function, creating IPL image header. |
allocate_data | pointer to a function, allocating IPL image data. |
deallocate | pointer to a function, deallocating IPL image. |
create_roi | pointer to a function, creating IPL image ROI (i.e. Region of Interest). |
clone_image | pointer to a function, cloning an IPL image. |
void cvSetND( CvArr* arr, const int* idx, CvScalar value )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array |
idx | Array of the element indices |
value | The assigned value |
CvSetElem* cvSetNew(CvSet* set_header)
Fast variant of cvSetAdd
void cvSetReal1D( CvArr* arr, int idx0, double value )
Change a specific array element.
The functions assign a new value to a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that the Set*D function can be used safely for both single-channel and multiple-channel arrays, though they are a bit slower.
In the case of a sparse array the functions create the node if it does not yet exist.
Parameters:
arr | Input array |
idx0 | The first zero-based component of the element index |
value | The assigned value |
void cvSetReal2D( CvArr* arr, int idx0, int idx1, double value )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
void cvSetReal3D( CvArr* arr, int idx0, int idx1, int idx2, double value )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
void cvSetRealND( CvArr* arr, const int* idx, double value )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
arr | Input array |
idx | Array of the element indices |
value | The assigned value |
void cvSetRemove( CvSet* set_header, int index )
Removes element from the set by its index
void cvSetRemoveByPtr( CvSet* set_header, void* elem )
Removes set element given its pointer
void cvSetSeqBlockSize( CvSeq* seq, int delta_elems )
Changes default size (granularity) of sequence blocks. The default size is ~1Kbyte
void cvSetSeqReaderPos( CvSeqReader* reader, int index, int is_relative = 0 )
Changes sequence reader position. It may seek to an absolute or to relative to the current position
void cvSetZero(CvArr* arr)
Clears the array.
The function clears the array. In the case of dense arrays (CvMat, CvMatND or IplImage), cvZero(array) is equivalent to cvSet(array,cvScalarAll(0),0). In the case of sparse arrays all the elements are removed.
Parameters:
arr | Array to be cleared |
int cvSliceLength( CvSlice slice, const CvSeq* seq )
Calculates length of sequence slice (with support of negative indices).
int cvSolve( const CvArr* src1, const CvArr* src2, CvArr* dst, int method = 0 )
Solves linear system (src1)*(dst) = (src2) (returns 0 if src1 is a singular and CV_LU method is used)
int cvSolveCubic( const CvMat* coeffs, CvMat* roots )
Finds real roots of a cubic equation
void cvSolvePoly( const CvMat* coeffs, CvMat* roots2, int maxiter = 20, int fig = 100 )
Finds all real and complex roots of a polynomial equation
void cvSplit( const CvArr* src, CvArr* dst0, CvArr* dst1, CvArr* dst2, CvArr* dst3 )
Splits a multi-channel array into the set of single-channel arrays or extracts particular [color] plane
void cvStartAppendToSeq( CvSeq* seq, CvSeqWriter* writer )
Initializes sequence writer. The new elements will be added to the end of sequence
void cvStartNextStream(CvFileStorage* fs)
Starts the next stream.
The function finishes the currently written stream and starts the next stream. In the case of XML the file with multiple streams looks like this:
<opencv_storage> <!-- stream #1 data --> </opencv_storage> <opencv_storage> <!-- stream #2 data --> </opencv_storage> ...
The YAML file will look like this:
%YAML 1.0 # stream #1 data ... --- # stream #2 data
This is useful for concatenating files or for resuming the writing process.
Parameters:
fs | File storage |
void cvStartReadRawData( const CvFileStorage* fs, const CvFileNode* src, CvSeqReader* reader )
Initializes the file node sequence reader.
The function initializes the sequence reader to read data from a file node. The initialized reader can be then passed to cvReadRawDataSlice.
Parameters:
fs | File storage |
src | The file node (a sequence) to read numbers from |
reader | Pointer to the sequence reader |
void cvStartReadSeq( const CvSeq* seq, CvSeqReader* reader, int reverse = 0 )
Initializes sequence reader. The sequence can be read in forward or backward direction
void cvStartWriteSeq( int seq_flags, int header_size, int elem_size, CvMemStorage* storage, CvSeqWriter* writer )
Combination of cvCreateSeq and cvStartAppendToSeq
void cvStartWriteStruct( CvFileStorage* fs, const char* name, int struct_flags, const char* type_name = NULL, CvAttrList attributes = cvAttrList() )
Starts writing a new structure.
The function starts writing a compound structure (collection) that can be a sequence or a map. After all the structure fields, which can be scalars or structures, are written, cvEndWriteStruct should be called. The function can be used to group some objects or to implement the write function for a some user object (see CvTypeInfo).
Parameters:
fs | File storage |
name | Name of the written structure. The structure can be accessed by this name when the storage is read. |
struct_flags | A combination one of the following values:
|
type_name | Optional parameter - the object type name. In case of XML it is written as a type_id attribute of the structure opening tag. In the case of YAML it is written after a colon following the structure name (see the example in CvFileStorage description). In case of JSON it is written as a name/value pair. Mainly it is used with user objects. When the storage is read, the encoded type name is used to determine the object type (see CvTypeInfo and cvFindType ). |
attributes | This parameter is not used in the current implementation |
int cvStdErrReport( int status, const char* func_name, const char* err_msg, const char* file_name, int line, void* userdata )
Output to console(fprintf(stderr,…))
void cvSub( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL )
dst(mask) = src1(mask) - src2(mask)
void cvSubRS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL )
dst(mask) = value - src(mask)
void cvSubS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL )
dst(mask) = src(mask) - value = src(mask) + (-value)
CvScalar cvSum(const CvArr* arr)
Finds sum of array elements
void cvSVBkSb( const CvArr* W, const CvArr* U, const CvArr* V, const CvArr* B, CvArr* X, int flags )
Performs Singular Value Back Substitution (solves A*X = B): flags must be the same as in cvSVD
void cvSVD( CvArr* A, CvArr* W, CvArr* U = NULL, CvArr* V = NULL, int flags = 0 )
Performs Singular Value Decomposition of a matrix
CvScalar cvTrace(const CvArr* mat)
Calculates trace of the matrix (sum of elements on the main diagonal)
void cvTransform( const CvArr* src, CvArr* dst, const CvMat* transmat, const CvMat* shiftvec = NULL )
Transforms each element of source array and stores resultant vectors in destination array
void cvTranspose( const CvArr* src, CvArr* dst )
Tranposes matrix. Square matrices can be transposed in-place
CvSeq* cvTreeToNodeSeq( const void* first, int header_size, CvMemStorage* storage )
Gathers pointers to all the sequences, accessible from the first
, to the single sequence
CvTypeInfo* cvTypeOf(const void* struct_ptr)
Returns the type of an object.
The function finds the type of a given object. It iterates through the list of registered types and calls the is_instance function/method for every type info structure with that object until one of them returns non-zero or until the whole list has been traversed. In the latter case, the function returns NULL.
Parameters:
struct_ptr | The object pointer |
void cvUnregisterType(const char* type_name)
Unregisters the type.
The function unregisters a type with a specified name. If the name is unknown, it is possible to locate the type info by an instance of the type using cvTypeOf or by iterating the type list, starting from cvFirstType, and then calling cvUnregisterType(info->typeName).
Parameters:
type_name | Name of an unregistered type |
int cvUseOptimized(int on_off)
Loads optimized functions from IPP, MKL etc. or switches back to pure C code
void cvWrite( CvFileStorage* fs, const char* name, const void* ptr, CvAttrList attributes = cvAttrList() )
Writes an object to file storage.
The function writes an object to file storage. First, the appropriate type info is found using cvTypeOf. Then, the write method associated with the type info is called.
Attributes are used to customize the writing procedure. The standard types support the following attributes (all the dt attributes have the same format as in cvWriteRawData):
- CvSeq
- header_dt description of user fields of the sequence header that follow CvSeq, or CvChain (if the sequence is a Freeman chain) or CvContour (if the sequence is a contour or point sequence)
- dt description of the sequence elements.
- recursive if the attribute is present and is not equal to “0” or “false”, the whole tree of sequences (contours) is stored.
- CvGraph
- header_dt description of user fields of the graph header that follows CvGraph;
- vertex_dt description of user fields of graph vertices
- edge_dt description of user fields of graph edges (note that the edge weight is always written, so there is no need to specify it explicitly)
Below is the code that creates the YAML file shown in the CvFileStorage description:
#include "cxcore.h" int main( int argc, char** argv ) { CvMat* mat = cvCreateMat( 3, 3, CV_32F ); CvFileStorage* fs = cvOpenFileStorage( "example.yml", 0, CV_STORAGE_WRITE ); cvSetIdentity( mat ); cvWrite( fs, "A", mat, cvAttrList(0,0) ); cvReleaseFileStorage( &fs ); cvReleaseMat( &mat ); return 0; }
Parameters:
fs | File storage |
name | Name of the written object. Should be NULL if and only if the parent structure is a sequence. |
ptr | Pointer to the object |
attributes | The attributes of the object. They are specific for each particular type (see the discussion below). |
void cvWriteComment( CvFileStorage* fs, const char* comment, int eol_comment )
Writes a comment.
The function writes a comment into file storage. The comments are skipped when the storage is read.
Parameters:
fs | File storage |
comment | The written comment, single-line or multi-line |
eol_comment | If non-zero, the function tries to put the comment at the end of current line. If the flag is zero, if the comment is multi-line, or if it does not fit at the end of the current line, the comment starts a new line. |
void cvWriteFileNode( CvFileStorage* fs, const char* new_node_name, const CvFileNode* node, int embed )
Writes a file node to another file storage.
The function writes a copy of a file node to file storage. Possible applications of the function are merging several file storages into one and conversion between XML, YAML and JSON formats.
Parameters:
fs | Destination file storage |
new_node_name | New name of the file node in the destination file storage. To keep the existing name, use cvcvGetFileNodeName |
node | The written node |
embed | If the written node is a collection and this parameter is not zero, no extra level of hierarchy is created. Instead, all the elements of node are written into the currently written structure. Of course, map elements can only be embedded into another map, and sequence elements can only be embedded into another sequence. |
void cvWriteInt( CvFileStorage* fs, const char* name, int value )
Writes an integer value.
The function writes a single integer value (with or without a name) to the file storage.
Parameters:
fs | File storage |
name | Name of the written value. Should be NULL if and only if the parent structure is a sequence. |
value | The written value |
void cvWriteRawData( CvFileStorage* fs, const void* src, int len, const char* dt )
Writes multiple numbers.
The function writes an array, whose elements consist of single or multiple numbers. The function call can be replaced with a loop containing a few cvWriteInt and cvWriteReal calls, but a single call is more efficient. Note that because none of the elements have a name, they should be written to a sequence rather than a map.
Parameters:
fs | File storage |
src | Pointer to the written array |
len | Number of the array elements to write |
dt | Specification of each array element, see format specification |
void cvWriteRawDataBase64( CvFileStorage* fs, const void* src, int len, const char* dt )
Writes multiple numbers in Base64.
If either CV_STORAGE_WRITE_BASE64 or cv::FileStorage::WRITE_BASE64 is used, this function will be the same as cvWriteRawData. If neither, the main difference is that it outputs a sequence in Base64 encoding rather than in plain text.
This function can only be used to write a sequence with a type “binary”.
Consider the following two examples where their output is the same:
CvFileStorage* fs = cvOpenFileStorage( "example.xml", 0, CV_STORAGE_WRITE ); // both CV_NODE_SEQ and "binary" are necessary. cvStartWriteStruct(fs, "rawdata", CV_NODE_SEQ | CV_NODE_FLOW, "binary"); cvWriteRawDataBase64(fs, rawdata.data(), static_cast<int>(rawdata.size()), "i"); cvEndWriteStruct(fs); cvReleaseFileStorage( &fs );
and
CvFileStorage* fs = cvOpenFileStorage( "example.xml", 0, CV_STORAGE_WRITE_BASE64); // parameter, typename "binary" could be omitted. cvStartWriteStruct(fs, "rawdata", CV_NODE_SEQ | CV_NODE_FLOW); cvWriteRawData(fs, rawdata.data(), static_cast<int>(rawdata.size()), "i"); cvEndWriteStruct(fs); cvReleaseFileStorage( &fs );
Parameters:
fs | File storage |
src | Pointer to the written array |
len | Number of the array elements to write |
dt | Specification of each array element, see format specification |
void cvWriteReal( CvFileStorage* fs, const char* name, double value )
Writes a floating-point value.
The function writes a single floating-point value (with or without a name) to file storage. Special values are encoded as follows: NaN (Not A Number) as .NaN, infinity as +.Inf or -.Inf.
The following example shows how to use the low-level writing functions to store custom structures, such as termination criteria, without registering a new type. :
void write_termcriteria( CvFileStorage* fs, const char* struct_name, CvTermCriteria* termcrit ) { cvStartWriteStruct( fs, struct_name, CV_NODE_MAP, NULL, cvAttrList(0,0)); cvWriteComment( fs, "termination criteria", 1 ); // just a description if( termcrit->type & CV_TERMCRIT_ITER ) cvWriteInteger( fs, "max_iterations", termcrit->max_iter ); if( termcrit->type & CV_TERMCRIT_EPS ) cvWriteReal( fs, "accuracy", termcrit->epsilon ); cvEndWriteStruct( fs ); }
Parameters:
fs | File storage |
name | Name of the written value. Should be NULL if and only if the parent structure is a sequence. |
value | The written value |
void cvWriteString( CvFileStorage* fs, const char* name, const char* str, int quote = 0 )
Writes a text string.
The function writes a text string to file storage.
Parameters:
fs | File storage |
name | Name of the written string . Should be NULL if and only if the parent structure is a sequence. |
str | The written text string |
quote | If non-zero, the written string is put in quotes, regardless of whether they are required. Otherwise, if the flag is zero, quotes are used only when they are required (e.g. when the string starts with a digit or contains spaces). |
void cvXor( const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask = NULL )
dst(idx) = src1(idx) ^ src2(idx)
void cvXorS( const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask = NULL )
dst(idx) = src(idx) ^ value
CvAttrList cvAttrList( const char** attr = NULL, CvAttrList* next = NULL )
initializes CvAttrList structure
CvMat cvMat( int rows, int cols, int type, void* data = NULL )
Inline constructor. No data is allocated internally!!! (Use together with cvCreateData, or use cvCreateMat instead to get a matrix with allocated data):
double cvmGet( const CvMat* mat, int row, int col )
Returns the particular element of single-channel floating-point matrix.
The function is a fast replacement for cvGetReal2D in the case of single-channel floating-point matrices. It is faster because it is inline, it does fewer checks for array type and array element type, and it checks for the row and column ranges only in debug mode.
Parameters:
mat | Input matrix |
row | The zero-based index of row |
col | The zero-based index of column |
void cvmSet( CvMat* mat, int row, int col, double value )
Sets a specific element of a single-channel floating-point matrix.
The function is a fast replacement for cvSetReal2D in the case of single-channel floating-point matrices. It is faster because it is inline, it does fewer checks for array type and array element type, and it checks for the row and column ranges only in debug mode.
Parameters:
mat | The matrix |
row | The zero-based index of row |
col | The zero-based index of column |
value | The new value of the matrix element |
CvPoint cvPoint( int x, int y )
constructs CvPoint structure.
CvPoint2D32f cvPoint2D32f( double x, double y )
constructs CvPoint2D32f structure.
CvPoint2D64f cvPoint2D64f( double x, double y )
constructs CvPoint2D64f structure.
CvPoint3D32f cvPoint3D32f( double x, double y, double z )
constructs CvPoint3D32f structure.
CvPoint3D64f cvPoint3D64f( double x, double y, double z )
constructs CvPoint3D64f structure.
CvPoint cvPointFrom32f(CvPoint2D32f point)
converts CvPoint2D32f to CvPoint.
CvPoint2D32f cvPointTo32f(CvPoint point)
converts CvPoint to CvPoint2D32f.
unsigned cvRandInt(CvRNG* rng)
Returns a 32-bit unsigned integer and updates RNG.
The function returns a uniformly-distributed random 32-bit unsigned integer and updates the RNG state. It is similar to the rand() function from the C runtime library, except that OpenCV functions always generates a 32-bit random number, regardless of the platform.
Parameters:
rng | CvRNG state initialized by cvRNG. |
double cvRandReal(CvRNG* rng)
Returns a floating-point random number and updates RNG.
The function returns a uniformly-distributed random floating-point number between 0 and 1 (1 is not included).
Parameters:
rng | RNG state initialized by cvRNG |
CvRect cvRect( int x, int y, int width, int height )
constructs CvRect structure.
CvRNG cvRNG(int64 seed = -1)
Initializes a random number generator state.
The function initializes a random number generator and returns the state. The pointer to the state can be then passed to the cvRandInt, cvRandReal and cvRandArr functions. In the current implementation a multiply-with-carry generator is used.
Parameters:
seed | 64-bit value used to initiate a random sequence |
See also:
the C++ class RNG replaced CvRNG.
CvSize cvSize( int width, int height )
constructs CvSize structure.
CvSize2D32f cvSize2D32f( double width, double height )
constructs CvSize2D32f structure.
Macros
#define CV_ASSERT(Condition)
Runtime assertion macro
#define CV_CALL(Func)
CV_CALL macro calls CV (or IPL) function, checks error status and signals a error if the function failed. Useful in “parent node” error procesing mode
#define CV_CHECK()
CV_CHECK macro checks error status after CV (or IPL) function call. If error detected, control will be transferred to the exit label.
#define CV_COVAR_COLS
flag for cvCalcCovarMatrix, all the input vectors are stored in a single matrix, as its columns
#define CV_COVAR_NORMAL
flag for cvCalcCovarMatrix, [v1-avg, v2-avg,…] * transpose([v1-avg,v2-avg,…])
#define CV_COVAR_ROWS
flag for cvCalcCovarMatrix, all the input vectors are stored in a single matrix, as its rows
#define CV_COVAR_SCALE
flag for cvCalcCovarMatrix, scale the covariance matrix coefficients by number of the vectors
#define CV_COVAR_SCRAMBLED
flag for cvCalcCovarMatrix, transpose([v1-avg, v2-avg,…]) * [v1-avg,v2-avg,…]
#define CV_COVAR_USE_AVG
flag for cvCalcCovarMatrix, do not calc average (i.e. mean vector) - use the input vector instead (useful for calculating covariance matrix by parts)
#define CV_DXT_MUL_CONJ
conjugate the second argument of cvMulSpectrums
#define CV_DXT_ROWS
transform each row individually
#define CV_DXT_SCALE
divide result by size of array
#define CV_ERROR( \ Code, \ Msg \ )
CV_ERROR macro unconditionally raises error with passed code and message. After raising error, control will be transferred to the exit label.
#define CV_FUNCNAME(Name)
CV_FUNCNAME macro defines icvFuncName constant which is used by CV_ERROR macro
#define CV_GRAPH_FIELDS()
Graph is “derived” from the set (this is set a of vertices) and includes another set (edges)
#define CV_GRAPH_FLAG_ORIENTED
flags for graphs
#define CV_GRAPH_ITEM_VISITED_FLAG
flags for graph vertices and edges
#define CV_HIST_RANGES_FLAG
indicates whether bin ranges are set already or not
#define CV_HIST_UNIFORM
should be used as a parameter only, it turns to CV_HIST_UNIFORM_FLAG of hist->type
#define CV_IABS(a)
absolute value without jumps
#define CV_IMAGE_ELEM( \ image, \ elemtype, \ row, \ col \ )
get reference to pixel at (col,row), for multi-channel images (col) should be multiplied by number of channels
#define CV_IMIN( \ a, \ b \ )
min & max without jumps
#define CV_IS_SEQ_INDEX(seq)
flag checking
#define CV_IS_SEQ_POINT_SET(seq)
type checking macros
#define CV_IS_SET_ELEM(ptr)
Checks whether the element pointed by ptr belongs to a set or not
#define CV_KMEANS_USE_INITIAL_LABELS
The function implements the K-means algorithm for clustering an array of sample vectors in a specified number of classes
#define CV_NEXT_GRAPH_EDGE( \ edge, \ vertex \ )
Return next graph edge for given vertex:
#define CV_NEXT_SEQ_ELEM( \ elem_size, \ reader \ )
Move reader position forward:
#define CV_NODE_FLOW
file node flags Used only for writing structures in YAML format.
#define CV_NODE_REF
not used
#define CV_PREV_SEQ_ELEM( \ elem_size, \ reader \ )
Move reader position backward:
#define CV_READ_SEQ_ELEM( \ elem, \ reader \ )
Read element and move read position forward:
#define CV_REV_READ_SEQ_ELEM( \ elem, \ reader \ )
Read element and move read position backward:
#define CV_SEQUENCE_FIELDS()
Read/Write sequence. Elements can be dynamically inserted to or deleted from the sequence.Pointer to the first sequence block.
#define CV_SEQ_CHAIN
chain-coded curves
#define CV_SEQ_CONNECTED_COMP
sequence of the connected components
#define CV_SEQ_ELTYPE_CODE
freeman code: 0..7
#define CV_SEQ_ELTYPE_CONNECTED_COMP
connected component
#define CV_SEQ_ELTYPE_GRAPH_EDGE
&next_o, &next_d, &vtx_o, &vtx_d
#define CV_SEQ_ELTYPE_GRAPH_VERTEX
first_edge, &(x,y)
#define CV_SEQ_ELTYPE_INDEX
#(x,y)
#define CV_SEQ_ELTYPE_POINT
(x,y)
#define CV_SEQ_ELTYPE_POINT3D
(x,y,z)
#define CV_SEQ_ELTYPE_PPOINT
&(x,y)
#define CV_SEQ_ELTYPE_TRIAN_ATR
vertex of the binary tree
#define CV_SEQ_FLAG_CLOSED
flags for curves
#define CV_SEQ_INDEX
sequence of the integer numbers
#define CV_SEQ_KIND_GENERIC
types of sequences
#define CV_SEQ_KIND_GRAPH
types of sparse sequences (sets)
#define CV_SEQ_POINT_SET
point sets
#define CV_SEQ_POLYGON_TREE
binary tree for the contour
#define CV_SEQ_READER_FIELDS()
pointer to previous element
#define CV_SEQ_WRITER_FIELDS()
pointer to the end of block
#define CV_SET_ELEM_FIELDS(elem_type)
Set Order is not preserved. There can be gaps between sequence elements. After the element has been inserted it stays in the same place all the time. The MSB(most-significant or sign bit) of the first field (flags) is 0 iff the element exists.
#define CV_STORAGE_READ
Storage flags:
#define CV_TREE_NODE_FIELDS(node_type)
2nd next sequence.
#define CV_WRITE_SEQ_ELEM_VAR( \ elem_ptr, \ writer \ )
Add element to sequence:
#define IPL_BORDER_REFLECT_101
extra border mode
#define IPL_DEPTH_64F
for storing double-precision floating point data in IplImage ‘s
#define cvGetGraphVtx( \ graph, \ idx \ )
Retrieves graph vertex by given index
#define cvGraphEdgeIdx( \ graph, \ edge \ )
Retrieves index of a graph edge given its pointer
#define cvGraphVtxIdx( \ graph, \ vtx \ )
Retrieves index of a graph vertex given its pointer
#define cvMatMulAdd( \ src1, \ src2, \ src3, \ dst \ )
Matrix transform: dst = A*B + C, C is optional