Core functionality

Modules
	Basic structures
	C structures and operations
	Operations on arrays
	Asynchronous API
	XML/YAML Persistence
	Clustering
	Utility and system functions and macros
	OpenGL interoperability
	Intel IPP Asynchronous C/C++ Converters
	Optimization Algorithms
	DirectX interoperability
	Eigen support
	OpenCL support
	Intel VA-API/OpenCL (CL-VA) interoperability
	Hardware Acceleration Layer

Namespaces
	cv::traits

Classes
class	cv::Affine3< T >
	Affine transform. More...
class	cv::BufferPoolController
class	cv::WImage< T >
	Image class which provides a thin layer around an IplImage. More...
class	cv::WImageBuffer< T >
class	cv::WImageBufferC< T, C >
class	cv::WImageC< T, C >
class	cv::WImageView< T >
class	cv::WImageViewC< T, C >

Typedefs
typedef Affine3< double >	cv::Affine3d
typedef Affine3< float >	cv::Affine3f
typedef WImageC< short, 1 >	cv::WImage1_16s
typedef WImageC< ushort, 1 >	cv::WImage1_16u
typedef WImageC< uchar, 1 >	cv::WImage1_b
typedef WImageC< float, 1 >	cv::WImage1_f
typedef WImageC< short, 3 >	cv::WImage3_16s
typedef WImageC< ushort, 3 >	cv::WImage3_16u
typedef WImageC< uchar, 3 >	cv::WImage3_b
typedef WImageC< float, 3 >	cv::WImage3_f
typedef WImage< short >	cv::WImage_16s
typedef WImage< ushort >	cv::WImage_16u
typedef WImage< uchar >	cv::WImage_b
typedef WImage< float >	cv::WImage_f
typedef WImageBufferC< short, 1 >	cv::WImageBuffer1_16s
typedef WImageBufferC< ushort, 1 >	cv::WImageBuffer1_16u
typedef WImageBufferC< uchar, 1 >	cv::WImageBuffer1_b
typedef WImageBufferC< float, 1 >	cv::WImageBuffer1_f
typedef WImageBufferC< short, 3 >	cv::WImageBuffer3_16s
typedef WImageBufferC< ushort, 3 >	cv::WImageBuffer3_16u
typedef WImageBufferC< uchar, 3 >	cv::WImageBuffer3_b
typedef WImageBufferC< float, 3 >	cv::WImageBuffer3_f
typedef WImageBuffer< short >	cv::WImageBuffer_16s
typedef WImageBuffer< ushort >	cv::WImageBuffer_16u
typedef WImageBuffer< uchar >	cv::WImageBuffer_b
typedef WImageBuffer< float >	cv::WImageBuffer_f
typedef WImageViewC< short, 1 >	cv::WImageView1_16s
typedef WImageViewC< ushort, 1 >	cv::WImageView1_16u
typedef WImageViewC< uchar, 1 >	cv::WImageView1_b
typedef WImageViewC< float, 1 >	cv::WImageView1_f
typedef WImageViewC< short, 3 >	cv::WImageView3_16s
typedef WImageViewC< ushort, 3 >	cv::WImageView3_16u
typedef WImageViewC< uchar, 3 >	cv::WImageView3_b
typedef WImageViewC< float, 3 >	cv::WImageView3_f
typedef WImageView< short >	cv::WImageView_16s
typedef WImageView< ushort >	cv::WImageView_16u
typedef WImageView< uchar >	cv::WImageView_b
typedef WImageView< float >	cv::WImageView_f

Enumerations
enum	cv::CovarFlags {   cv::COVAR_SCRAMBLED = 0,   cv::COVAR_NORMAL = 1,   cv::COVAR_USE_AVG = 2,   cv::COVAR_SCALE = 4,   cv::COVAR_ROWS = 8,   cv::COVAR_COLS = 16 }
	Covariation flags. More...
enum	cv::HersheyFonts {   cv::FONT_HERSHEY_SIMPLEX = 0,   cv::FONT_HERSHEY_PLAIN = 1,   cv::FONT_HERSHEY_DUPLEX = 2,   cv::FONT_HERSHEY_COMPLEX = 3,   cv::FONT_HERSHEY_TRIPLEX = 4,   cv::FONT_HERSHEY_COMPLEX_SMALL = 5,   cv::FONT_HERSHEY_SCRIPT_SIMPLEX = 6,   cv::FONT_HERSHEY_SCRIPT_COMPLEX = 7,   cv::FONT_ITALIC = 16 }
	Only a subset of Hershey fonts https://en.wikipedia.org/wiki/Hershey_fonts are supported. More...
enum	cv::KmeansFlags {   cv::KMEANS_RANDOM_CENTERS = 0,   cv::KMEANS_PP_CENTERS = 2,   cv::KMEANS_USE_INITIAL_LABELS = 1 }
	k-Means flags More...
enum	cv::LineTypes {   cv::FILLED = -1,   cv::LINE_4 = 4,   cv::LINE_8 = 8,   cv::LINE_AA = 16 }
	type of line More...
enum	cv::ReduceTypes {   cv::REDUCE_SUM = 0,   cv::REDUCE_AVG = 1,   cv::REDUCE_MAX = 2,   cv::REDUCE_MIN = 3 }

Functions
	cv::WImageView< T >::WImageView (WImage< T > *img, int c, int r, int width, int height)
	cv::WImageView< T >::WImageView (T *data, int width, int height, int channels, int width_step=-1)
	cv::WImageViewC< T, C >::WImageViewC ()
	cv::WImageViewC< T, C >::WImageViewC (WImageC< T, C > *img, int c, int r, int width, int height)
	cv::WImageViewC< T, C >::WImageViewC (T *data, int width, int height, int width_step=-1)
virtual	cv::WImage< T >::~WImage ()=0
virtual	cv::WImageC< T, C >::~WImageC ()=0
void	cv::WImageBuffer< T >::Allocate (int width, int height, int nchannels)
void	cv::WImageBufferC< T, C >::Allocate (int width, int height)
template<typename T >
static Affine3< T >	cv::operator* (const Affine3< T > &affine1, const Affine3< T > &affine2)
template<typename T , typename V >
static V	cv::operator* (const Affine3< T > &affine, const V &vector)
	V is a 3-element vector with member fields x, y and z. More...
static Vec3f	cv::operator* (const Affine3f &affine, const Vec3f &vector)
static Vec3d	cv::operator* (const Affine3d &affine, const Vec3d &vector)
void	cv::swap (Mat &a, Mat &b)
	Swaps two matrices. More...
void	cv::swap (UMat &a, UMat &b)
WImageView< T >	cv::WImage< T >::View (int c, int r, int width, int height)
WImageViewC< T, C >	cv::WImageC< T, C >::View (int c, int r, int width, int height)

Detailed Description

Typedef Documentation

Affine3d

typedef Affine3<double> cv::Affine3d

#include <opencv2/core/affine.hpp>

Affine3f

typedef Affine3<float> cv::Affine3f

#include <opencv2/core/affine.hpp>

WImage1_16s

typedef WImageC<short, 1> cv::WImage1_16s

#include <opencv2/core/wimage.hpp>

WImage1_16u

typedef WImageC<ushort, 1> cv::WImage1_16u

#include <opencv2/core/wimage.hpp>

WImage1_b

typedef WImageC<uchar, 1> cv::WImage1_b

#include <opencv2/core/wimage.hpp>

WImage1_f

typedef WImageC<float, 1> cv::WImage1_f

#include <opencv2/core/wimage.hpp>

WImage3_16s

typedef WImageC<short, 3> cv::WImage3_16s

#include <opencv2/core/wimage.hpp>

WImage3_16u

typedef WImageC<ushort, 3> cv::WImage3_16u

#include <opencv2/core/wimage.hpp>

WImage3_b

typedef WImageC<uchar, 3> cv::WImage3_b

#include <opencv2/core/wimage.hpp>

WImage3_f

typedef WImageC<float, 3> cv::WImage3_f

#include <opencv2/core/wimage.hpp>

WImage_16s

typedef WImage<short> cv::WImage_16s

#include <opencv2/core/wimage.hpp>

WImage_16u

typedef WImage<ushort> cv::WImage_16u

#include <opencv2/core/wimage.hpp>

WImage_b

typedef WImage<uchar> cv::WImage_b

#include <opencv2/core/wimage.hpp>

WImage_f

typedef WImage<float> cv::WImage_f

#include <opencv2/core/wimage.hpp>

WImageBuffer1_16s

typedef WImageBufferC<short, 1> cv::WImageBuffer1_16s

#include <opencv2/core/wimage.hpp>

WImageBuffer1_16u

typedef WImageBufferC<ushort, 1> cv::WImageBuffer1_16u

#include <opencv2/core/wimage.hpp>

WImageBuffer1_b

typedef WImageBufferC<uchar, 1> cv::WImageBuffer1_b

#include <opencv2/core/wimage.hpp>

WImageBuffer1_f

typedef WImageBufferC<float, 1> cv::WImageBuffer1_f

#include <opencv2/core/wimage.hpp>

WImageBuffer3_16s

typedef WImageBufferC<short, 3> cv::WImageBuffer3_16s

#include <opencv2/core/wimage.hpp>

WImageBuffer3_16u

typedef WImageBufferC<ushort, 3> cv::WImageBuffer3_16u

#include <opencv2/core/wimage.hpp>

WImageBuffer3_b

typedef WImageBufferC<uchar, 3> cv::WImageBuffer3_b

#include <opencv2/core/wimage.hpp>

WImageBuffer3_f

typedef WImageBufferC<float, 3> cv::WImageBuffer3_f

#include <opencv2/core/wimage.hpp>

WImageBuffer_16s

typedef WImageBuffer<short> cv::WImageBuffer_16s

#include <opencv2/core/wimage.hpp>

WImageBuffer_16u

typedef WImageBuffer<ushort> cv::WImageBuffer_16u

#include <opencv2/core/wimage.hpp>

WImageBuffer_b

typedef WImageBuffer<uchar> cv::WImageBuffer_b

#include <opencv2/core/wimage.hpp>

WImageBuffer_f

typedef WImageBuffer<float> cv::WImageBuffer_f

#include <opencv2/core/wimage.hpp>

WImageView1_16s

typedef WImageViewC<short, 1> cv::WImageView1_16s

#include <opencv2/core/wimage.hpp>

WImageView1_16u

typedef WImageViewC<ushort, 1> cv::WImageView1_16u

#include <opencv2/core/wimage.hpp>

WImageView1_b

typedef WImageViewC<uchar, 1> cv::WImageView1_b

#include <opencv2/core/wimage.hpp>

WImageView1_f

typedef WImageViewC<float, 1> cv::WImageView1_f

#include <opencv2/core/wimage.hpp>

WImageView3_16s

typedef WImageViewC<short, 3> cv::WImageView3_16s

#include <opencv2/core/wimage.hpp>

WImageView3_16u

typedef WImageViewC<ushort, 3> cv::WImageView3_16u

#include <opencv2/core/wimage.hpp>

WImageView3_b

typedef WImageViewC<uchar, 3> cv::WImageView3_b

#include <opencv2/core/wimage.hpp>

WImageView3_f

typedef WImageViewC<float, 3> cv::WImageView3_f

#include <opencv2/core/wimage.hpp>

WImageView_16s

typedef WImageView<short> cv::WImageView_16s

#include <opencv2/core/wimage.hpp>

WImageView_16u

typedef WImageView<ushort> cv::WImageView_16u

#include <opencv2/core/wimage.hpp>

WImageView_b

typedef WImageView<uchar> cv::WImageView_b

#include <opencv2/core/wimage.hpp>

WImageView_f

typedef WImageView<float> cv::WImageView_f

#include <opencv2/core/wimage.hpp>

Enumeration Type Documentation

CovarFlags

enum cv::CovarFlags

#include <opencv2/core.hpp>

Covariation flags.

Enumerator
COVAR_SCRAMBLED  Python: cv.COVAR_SCRAMBLED	The output covariance matrix is calculated as: \[\texttt{scale} \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...]^T \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...],\] The covariance matrix will be nsamples x nsamples. Such an unusual covariance matrix is used for fast PCA of a set of very large vectors (see, for example, the EigenFaces technique for face recognition). Eigenvalues of this "scrambled" matrix match the eigenvalues of the true covariance matrix. The "true" eigenvectors can be easily calculated from the eigenvectors of the "scrambled" covariance matrix.
COVAR_NORMAL  Python: cv.COVAR_NORMAL	The output covariance matrix is calculated as: \[\texttt{scale} \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...] \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...]^T,\] covar will be a square matrix of the same size as the total number of elements in each input vector. One and only one of COVAR_SCRAMBLED and COVAR_NORMAL must be specified.
COVAR_USE_AVG  Python: cv.COVAR_USE_AVG	If the flag is specified, the function does not calculate mean from the input vectors but, instead, uses the passed mean vector. This is useful if mean has been pre-calculated or known in advance, or if the covariance matrix is calculated by parts. In this case, mean is not a mean vector of the input sub-set of vectors but rather the mean vector of the whole set.
COVAR_SCALE  Python: cv.COVAR_SCALE	If the flag is specified, the covariance matrix is scaled. In the "normal" mode, scale is 1./nsamples . In the "scrambled" mode, scale is the reciprocal of the total number of elements in each input vector. By default (if the flag is not specified), the covariance matrix is not scaled ( scale=1 ).
COVAR_ROWS  Python: cv.COVAR_ROWS	If the flag is specified, all the input vectors are stored as rows of the samples matrix. mean should be a single-row vector in this case.
COVAR_COLS  Python: cv.COVAR_COLS	If the flag is specified, all the input vectors are stored as columns of the samples matrix. mean should be a single-column vector in this case.

HersheyFonts

enum cv::HersheyFonts

#include <opencv2/core.hpp>

Only a subset of Hershey fonts https://en.wikipedia.org/wiki/Hershey_fonts are supported.

Enumerator
FONT_HERSHEY_SIMPLEX  Python: cv.FONT_HERSHEY_SIMPLEX	normal size sans-serif font
FONT_HERSHEY_PLAIN  Python: cv.FONT_HERSHEY_PLAIN	small size sans-serif font
FONT_HERSHEY_DUPLEX  Python: cv.FONT_HERSHEY_DUPLEX	normal size sans-serif font (more complex than FONT_HERSHEY_SIMPLEX)
FONT_HERSHEY_COMPLEX  Python: cv.FONT_HERSHEY_COMPLEX	normal size serif font
FONT_HERSHEY_TRIPLEX  Python: cv.FONT_HERSHEY_TRIPLEX	normal size serif font (more complex than FONT_HERSHEY_COMPLEX)
FONT_HERSHEY_COMPLEX_SMALL  Python: cv.FONT_HERSHEY_COMPLEX_SMALL	smaller version of FONT_HERSHEY_COMPLEX
FONT_HERSHEY_SCRIPT_SIMPLEX  Python: cv.FONT_HERSHEY_SCRIPT_SIMPLEX	hand-writing style font
FONT_HERSHEY_SCRIPT_COMPLEX  Python: cv.FONT_HERSHEY_SCRIPT_COMPLEX	more complex variant of FONT_HERSHEY_SCRIPT_SIMPLEX
FONT_ITALIC  Python: cv.FONT_ITALIC	flag for italic font

KmeansFlags

enum cv::KmeansFlags

#include <opencv2/core.hpp>

k-Means flags

Enumerator
KMEANS_RANDOM_CENTERS  Python: cv.KMEANS_RANDOM_CENTERS	Select random initial centers in each attempt.
KMEANS_PP_CENTERS  Python: cv.KMEANS_PP_CENTERS	Use kmeans++ center initialization by Arthur and Vassilvitskii [Arthur2007].
KMEANS_USE_INITIAL_LABELS  Python: cv.KMEANS_USE_INITIAL_LABELS	During the first (and possibly the only) attempt, use the user-supplied labels instead of computing them from the initial centers. For the second and further attempts, use the random or semi-random centers. Use one of KMEANS_*_CENTERS flag to specify the exact method.

LineTypes

enum cv::LineTypes

#include <opencv2/core.hpp>

type of line

Enumerator
FILLED  Python: cv.FILLED
LINE_4  Python: cv.LINE_4	4-connected line
LINE_8  Python: cv.LINE_8	8-connected line
LINE_AA  Python: cv.LINE_AA	antialiased line

ReduceTypes

enum cv::ReduceTypes

#include <opencv2/core.hpp>

Enumerator
REDUCE_SUM  Python: cv.REDUCE_SUM	the output is the sum of all rows/columns of the matrix.
REDUCE_AVG  Python: cv.REDUCE_AVG	the output is the mean vector of all rows/columns of the matrix.
REDUCE_MAX  Python: cv.REDUCE_MAX	the output is the maximum (column/row-wise) of all rows/columns of the matrix.
REDUCE_MIN  Python: cv.REDUCE_MIN	the output is the minimum (column/row-wise) of all rows/columns of the matrix.

Function Documentation

WImageView() [1/2]

template<typename T >

cv::WImageView< T >::WImageView	(	WImage< T > *	img,
		int	c,
		int	r,
		int	width,
		int	height
	)

#include <opencv2/core/wimage.hpp>

WImageView() [2/2]

template<typename T >

cv::WImageView< T >::WImageView	(	T *	data,
		int	width,
		int	height,
		int	channels,
		int	width_step = -1
	)

#include <opencv2/core/wimage.hpp>

WImageViewC() [1/3]

template<typename T , int C>

cv::WImageViewC< T, C >::WImageViewC

(

)

#include <opencv2/core/wimage.hpp>

WImageViewC() [2/3]

template<typename T , int C>

cv::WImageViewC< T, C >::WImageViewC	(	WImageC< T, C > *	img,
		int	c,
		int	r,
		int	width,
		int	height
	)

#include <opencv2/core/wimage.hpp>

WImageViewC() [3/3]

template<typename T , int C>

cv::WImageViewC< T, C >::WImageViewC	(	T *	data,
		int	width,
		int	height,
		int	width_step = -1
	)

#include <opencv2/core/wimage.hpp>

~WImage()

template<typename T >

cv::WImage< T >::~WImage ( )

inlinepure virtual

#include <opencv2/core/wimage.hpp>

~WImageC()

template<typename T , int C>

cv::WImageC< T, C >::~WImageC ( )

inlinepure virtual

#include <opencv2/core/wimage.hpp>

Allocate() [1/2]

template<typename T >

void cv::WImageBuffer< T >::Allocate ( int  width, int  height, int  nchannels  )

inline

#include <opencv2/core/wimage.hpp>

Allocate() [2/2]

template<typename T , int C>

void cv::WImageBufferC< T, C >::Allocate ( int  width, int  height  )

inline

#include <opencv2/core/wimage.hpp>

operator*() [1/4]

template<typename T >

static Affine3<T> cv::operator* ( const Affine3< T > &  affine1, const Affine3< T > &  affine2  )

static

#include <opencv2/core/affine.hpp>

operator*() [2/4]

template<typename T , typename V >

static V cv::operator* ( const Affine3< T > &  affine, const V &  vector  )

static

#include <opencv2/core/affine.hpp>

V is a 3-element vector with member fields x, y and z.

operator*() [3/4]

static Vec3f cv::operator* ( const Affine3f &  affine, const Vec3f &  vector  )

static

#include <opencv2/core/affine.hpp>

operator*() [4/4]

static Vec3d cv::operator* ( const Affine3d &  affine, const Vec3d &  vector  )

static

#include <opencv2/core/affine.hpp>

swap() [1/2]

void cv::swap	(	Mat &	a,
		Mat &	b
	)

#include <opencv2/core.hpp>

Swaps two matrices.

swap() [2/2]

void cv::swap	(	UMat &	a,
		UMat &	b
	)

#include <opencv2/core.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

View() [1/2]

template<typename T >

WImageView< T > cv::WImage< T >::View	(	int	c,
		int	r,
		int	width,
		int	height
	)

#include <opencv2/core/wimage.hpp>

View() [2/2]

template<typename T , int C>

WImageViewC< T, C > cv::WImageC< T, C >::View	(	int	c,
		int	r,
		int	width,
		int	height
	)

#include <opencv2/core/wimage.hpp>