core.hpp File Reference

#include "opencv2/core/cvdef.h"
#include "opencv2/core/base.hpp"
#include "opencv2/core/cvstd.hpp"
#include "opencv2/core/traits.hpp"
#include "opencv2/core/matx.hpp"
#include "opencv2/core/types.hpp"
#include "opencv2/core/mat.hpp"
#include "opencv2/core/persistence.hpp"
#include "opencv2/core/operations.hpp"
#include "opencv2/core/cvstd.inl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/optim.hpp"

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Classes
class	cv::Algorithm
	This is a base class for all more or less complex algorithms in OpenCV. More...
class	cv::Formatted
class	cv::Formatter
class	cv::LDA
	Linear Discriminant Analysis. More...
struct	cv::ParamType< _Tp, _EnumTp >
struct	cv::ParamType< _Tp, typename std::enable_if< std::is_enum< _Tp >::value >::type >
struct	cv::ParamType< Algorithm >
struct	cv::ParamType< bool >
struct	cv::ParamType< double >
struct	cv::ParamType< float >
struct	cv::ParamType< Mat >
struct	cv::ParamType< Scalar >
struct	cv::ParamType< std::vector< Mat > >
struct	cv::ParamType< String >
struct	cv::ParamType< uchar >
struct	cv::ParamType< uint64 >
struct	cv::ParamType< unsigned >
class	cv::PCA
	Principal Component Analysis. More...
class	cv::RNG
	Random Number Generator. More...
class	cv::RNG_MT19937
	Mersenne Twister random number generator. More...
class	cv::SVD
	Singular Value Decomposition. More...

Namespaces
namespace	cv

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::KmeansFlags {   cv::KMEANS_RANDOM_CENTERS = 0 ,   cv::KMEANS_PP_CENTERS = 2 ,   cv::KMEANS_USE_INITIAL_LABELS = 1 }
	k-means flags More...
enum struct	cv::Param {   cv::Param::INT =0 ,   cv::Param::BOOLEAN =1 ,   cv::Param::REAL =2 ,   cv::Param::STRING =3 ,   cv::Param::MAT =4 ,   cv::Param::MAT_VECTOR =5 ,   cv::Param::ALGORITHM =6 ,   cv::Param::FLOAT =7 ,   cv::Param::UNSIGNED_INT =8 ,   cv::Param::UINT64 =9 ,   cv::Param::UCHAR =11 ,   cv::Param::SCALAR =12 }
enum	cv::ReduceTypes {   cv::REDUCE_SUM = 0 ,   cv::REDUCE_AVG = 1 ,   cv::REDUCE_MAX = 2 ,   cv::REDUCE_MIN = 3 ,   cv::REDUCE_SUM2 = 4 }
enum	cv::RotateFlags {   cv::ROTATE_90_CLOCKWISE = 0 ,   cv::ROTATE_180 = 1 ,   cv::ROTATE_90_COUNTERCLOCKWISE = 2 }
enum	cv::SortFlags {   cv::SORT_EVERY_ROW = 0 ,   cv::SORT_EVERY_COLUMN = 1 ,   cv::SORT_ASCENDING = 0 ,   cv::SORT_DESCENDING = 16 }

Functions
void	cv::absdiff (InputArray src1, InputArray src2, OutputArray dst)
	Calculates the per-element absolute difference between two arrays or between an array and a scalar.
void	cv::add (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
	Calculates the per-element sum of two arrays or an array and a scalar.
void	cv::addWeighted (InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst, int dtype=-1)
	Calculates the weighted sum of two arrays.
void	cv::batchDistance (InputArray src1, InputArray src2, OutputArray dist, int dtype, OutputArray nidx, int normType=NORM_L2, int K=0, InputArray mask=noArray(), int update=0, bool crosscheck=false)
	naive nearest neighbor finder
void	cv::bitwise_and (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
	computes bitwise conjunction of the two arrays (dst = src1 & src2) Calculates the per-element bit-wise conjunction of two arrays or an array and a scalar.
void	cv::bitwise_not (InputArray src, OutputArray dst, InputArray mask=noArray())
	Inverts every bit of an array.
void	cv::bitwise_or (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
	Calculates the per-element bit-wise disjunction of two arrays or an array and a scalar.
void	cv::bitwise_xor (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
	Calculates the per-element bit-wise "exclusive or" operation on two arrays or an array and a scalar.
int	cv::borderInterpolate (int p, int len, int borderType)
	Computes the source location of an extrapolated pixel.
void	cv::broadcast (InputArray src, const MatShape &shape, OutputArray dst)
	Broadcast the given Mat to the given shape.
void	cv::broadcast (InputArray src, InputArray shape, OutputArray dst)
	Broadcast the given Mat to the given shape.
void	cv::calcCovarMatrix (const Mat *samples, int nsamples, Mat &covar, Mat &mean, int flags, int ctype=6)
	Calculates the covariance matrix of a set of vectors.
void	cv::calcCovarMatrix (InputArray samples, OutputArray covar, InputOutputArray mean, int flags, int ctype=6)
void	cv::cartToPolar (InputArray x, InputArray y, OutputArray magnitude, OutputArray angle, bool angleInDegrees=false)
	Calculates the magnitude and angle of 2D vectors.
bool	cv::checkRange (InputArray a, bool quiet=true, Point *pos=0, double minVal=-DBL_MAX, double maxVal=DBL_MAX)
	Checks every element of an input array for invalid values.
void	cv::compare (InputArray src1, InputArray src2, OutputArray dst, int cmpop)
	Performs the per-element comparison of two arrays or an array and scalar value.
void	cv::completeSymm (InputOutputArray m, bool lowerToUpper=false)
	Copies the lower or the upper half of a square matrix to its another half.
void	cv::convertScaleAbs (InputArray src, OutputArray dst, double alpha=1, double beta=0)
	Scales, calculates absolute values, and converts the result to 8-bit.
void	cv::copyMakeBorder (InputArray src, OutputArray dst, int top, int bottom, int left, int right, int borderType, const Scalar &value=Scalar())
	Forms a border around an image.
void	cv::copyTo (InputArray src, OutputArray dst, InputArray mask)
	This is an overloaded member function, provided for convenience (python) Copies the matrix to another one. When the operation mask is specified, if the Mat::create call shown above reallocates the matrix, the newly allocated matrix is initialized with all zeros before copying the data.
int	cv::countNonZero (InputArray src)
	Counts non-zero array elements.
void	cv::dct (InputArray src, OutputArray dst, int flags=0)
	Performs a forward or inverse discrete Cosine transform of 1D or 2D array.
double	cv::determinant (InputArray mtx)
	Returns the determinant of a square floating-point matrix.
void	cv::dft (InputArray src, OutputArray dst, int flags=0, int nonzeroRows=0)
	Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.
void	cv::divide (double scale, InputArray src2, OutputArray dst, int dtype=-1)
void	cv::divide (InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
	Performs per-element division of two arrays or a scalar by an array.
bool	cv::eigen (InputArray src, OutputArray eigenvalues, OutputArray eigenvectors=noArray())
	Calculates eigenvalues and eigenvectors of a symmetric matrix.
void	cv::eigenNonSymmetric (InputArray src, OutputArray eigenvalues, OutputArray eigenvectors)
	Calculates eigenvalues and eigenvectors of a non-symmetric matrix (real eigenvalues only).
void	cv::exp (InputArray src, OutputArray dst)
	Calculates the exponent of every array element.
void	cv::extractChannel (InputArray src, OutputArray dst, int coi)
	Extracts a single channel from src (coi is 0-based index)
void	cv::findNonZero (InputArray src, OutputArray idx)
	Returns the list of locations of non-zero pixels.
void	cv::finiteMask (InputArray src, OutputArray mask)
	Generates a mask of finite float values, i.e. not NaNs nor Infs.
void	cv::flip (InputArray src, OutputArray dst, int flipCode)
	Flips a 2D array around vertical, horizontal, or both axes.
void	cv::flipND (InputArray src, OutputArray dst, int axis)
	Flips a n-dimensional at given axis.
void	cv::gemm (InputArray src1, InputArray src2, double alpha, InputArray src3, double beta, OutputArray dst, int flags=0)
	Performs generalized matrix multiplication.
int	cv::getOptimalDFTSize (int vecsize)
	Returns the optimal DFT size for a given vector size.
bool	cv::hasNonZero (InputArray src)
	Checks for the presence of at least one non-zero array element.
void	cv::hconcat (const Mat *src, size_t nsrc, OutputArray dst)
	Applies horizontal concatenation to given matrices.
void	cv::hconcat (InputArray src1, InputArray src2, OutputArray dst)
void	cv::hconcat (InputArrayOfArrays src, OutputArray dst)
void	cv::idct (InputArray src, OutputArray dst, int flags=0)
	Calculates the inverse Discrete Cosine Transform of a 1D or 2D array.
void	cv::idft (InputArray src, OutputArray dst, int flags=0, int nonzeroRows=0)
	Calculates the inverse Discrete Fourier Transform of a 1D or 2D array.
void	cv::inRange (InputArray src, InputArray lowerb, InputArray upperb, OutputArray dst)
	Checks if array elements lie between the elements of two other arrays.
void	cv::insertChannel (InputArray src, InputOutputArray dst, int coi)
	Inserts a single channel to dst (coi is 0-based index)
double	cv::invert (InputArray src, OutputArray dst, int flags=DECOMP_LU)
	Finds the inverse or pseudo-inverse of a matrix.
double	cv::kmeans (InputArray data, int K, InputOutputArray bestLabels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray())
	Finds centers of clusters and groups input samples around the clusters.
void	cv::log (InputArray src, OutputArray dst)
	Calculates the natural logarithm of every array element.
void	cv::LUT (InputArray src, InputArray lut, OutputArray dst)
	Performs a look-up table transform of an array.
void	cv::magnitude (InputArray x, InputArray y, OutputArray magnitude)
	Calculates the magnitude of 2D vectors.
double	cv::Mahalanobis (InputArray v1, InputArray v2, InputArray icovar)
	Calculates the Mahalanobis distance between two vectors.
void	cv::max (const Mat &src1, const Mat &src2, Mat &dst)
void	cv::max (const UMat &src1, const UMat &src2, UMat &dst)
void	cv::max (InputArray src1, InputArray src2, OutputArray dst)
	Calculates per-element maximum of two arrays or an array and a scalar.
Scalar	cv::mean (InputArray src, InputArray mask=noArray())
	Calculates an average (mean) of array elements.
void	cv::meanStdDev (InputArray src, OutputArray mean, OutputArray stddev, InputArray mask=noArray())
void	cv::merge (const Mat *mv, size_t count, OutputArray dst)
	Creates one multi-channel array out of several single-channel ones.
void	cv::merge (InputArrayOfArrays mv, OutputArray dst)
void	cv::min (const Mat &src1, const Mat &src2, Mat &dst)
void	cv::min (const UMat &src1, const UMat &src2, UMat &dst)
void	cv::min (InputArray src1, InputArray src2, OutputArray dst)
	Calculates per-element minimum of two arrays or an array and a scalar.
void	cv::minMaxIdx (InputArray src, double *minVal, double *maxVal=0, int *minIdx=0, int *maxIdx=0, InputArray mask=noArray())
	Finds the global minimum and maximum in an array.
void	cv::minMaxLoc (const SparseMat &a, double *minVal, double *maxVal, int *minIdx=0, int *maxIdx=0)
void	cv::minMaxLoc (InputArray src, double *minVal, double *maxVal=0, Point *minLoc=0, Point *maxLoc=0, InputArray mask=noArray())
	Finds the global minimum and maximum in an array.
void	cv::mixChannels (const Mat *src, size_t nsrcs, Mat *dst, size_t ndsts, const int *fromTo, size_t npairs)
	Copies specified channels from input arrays to the specified channels of output arrays.
void	cv::mixChannels (InputArrayOfArrays src, InputOutputArrayOfArrays dst, const int *fromTo, size_t npairs)
void	cv::mixChannels (InputArrayOfArrays src, InputOutputArrayOfArrays dst, const std::vector< int > &fromTo)
void	cv::mulSpectrums (InputArray a, InputArray b, OutputArray c, int flags, bool conjB=false)
	Performs the per-element multiplication of two Fourier spectrums.
void	cv::multiply (InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
	Calculates the per-element scaled product of two arrays.
void	cv::mulTransposed (InputArray src, OutputArray dst, bool aTa, InputArray delta=noArray(), double scale=1, int dtype=-1)
	Calculates the product of a matrix and its transposition.
double	cv::norm (const SparseMat &src, int normType)
double	cv::norm (InputArray src1, InputArray src2, int normType=NORM_L2, InputArray mask=noArray())
	Calculates an absolute difference norm or a relative difference norm.
double	cv::norm (InputArray src1, int normType=NORM_L2, InputArray mask=noArray())
	Calculates the absolute norm of an array.
void	cv::normalize (const SparseMat &src, SparseMat &dst, double alpha, int normType)
void	cv::normalize (InputArray src, InputOutputArray dst, double alpha=1, double beta=0, int norm_type=NORM_L2, int dtype=-1, InputArray mask=noArray())
	Normalizes the norm or value range of an array.
static String &	cv::operator<< (String &out, const Mat &mtx)
static String &	cv::operator<< (String &out, Ptr< Formatted > fmtd)
void	cv::patchNaNs (InputOutputArray a, double val=0)
	Replaces NaNs by given number.
void	cv::PCABackProject (InputArray data, InputArray mean, InputArray eigenvectors, OutputArray result)
void	cv::PCACompute (InputArray data, InputOutputArray mean, OutputArray eigenvectors, double retainedVariance)
void	cv::PCACompute (InputArray data, InputOutputArray mean, OutputArray eigenvectors, int maxComponents=0)
void	cv::PCACompute (InputArray data, InputOutputArray mean, OutputArray eigenvectors, OutputArray eigenvalues, double retainedVariance)
void	cv::PCACompute (InputArray data, InputOutputArray mean, OutputArray eigenvectors, OutputArray eigenvalues, int maxComponents=0)
void	cv::PCAProject (InputArray data, InputArray mean, InputArray eigenvectors, OutputArray result)
void	cv::perspectiveTransform (InputArray src, OutputArray dst, InputArray m)
	Performs the perspective matrix transformation of vectors.
void	cv::phase (InputArray x, InputArray y, OutputArray angle, bool angleInDegrees=false)
	Calculates the rotation angle of 2D vectors.
void	cv::polarToCart (InputArray magnitude, InputArray angle, OutputArray x, OutputArray y, bool angleInDegrees=false)
	Calculates x and y coordinates of 2D vectors from their magnitude and angle.
void	cv::pow (InputArray src, double power, OutputArray dst)
	Raises every array element to a power.
double	cv::PSNR (InputArray src1, InputArray src2, double R=255.)
	Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.
void	cv::randn (InputOutputArray dst, InputArray mean, InputArray stddev)
	Fills the array with normally distributed random numbers.
void	cv::randShuffle (InputOutputArray dst, double iterFactor=1., RNG *rng=0)
	Shuffles the array elements randomly.
void	cv::randu (InputOutputArray dst, InputArray low, InputArray high)
	Generates a single uniformly-distributed random number or an array of random numbers.
void	cv::reduce (InputArray src, OutputArray dst, int dim, int rtype, int dtype=-1)
	Reduces a matrix to a vector.
void	cv::reduceArgMax (InputArray src, OutputArray dst, int axis, bool lastIndex=false)
	Finds indices of max elements along provided axis.
void	cv::reduceArgMin (InputArray src, OutputArray dst, int axis, bool lastIndex=false)
	Finds indices of min elements along provided axis.
Mat	cv::repeat (const Mat &src, int ny, int nx)
void	cv::repeat (InputArray src, int ny, int nx, OutputArray dst)
	Fills the output array with repeated copies of the input array.
void	cv::rotate (InputArray src, OutputArray dst, int rotateCode)
	Rotates a 2D array in multiples of 90 degrees. The function cv::rotate rotates the array in one of three different ways: Rotate by 90 degrees clockwise (rotateCode = ROTATE_90_CLOCKWISE). Rotate by 180 degrees clockwise (rotateCode = ROTATE_180). Rotate by 270 degrees clockwise (rotateCode = ROTATE_90_COUNTERCLOCKWISE).
void	cv::scaleAdd (InputArray src1, double alpha, InputArray src2, OutputArray dst)
	Calculates the sum of a scaled array and another array.
void	cv::setIdentity (InputOutputArray mtx, const Scalar &s=Scalar(1))
	Initializes a scaled identity matrix.
void	cv::setRNGSeed (int seed)
	Sets state of default random number generator.
bool	cv::solve (InputArray src1, InputArray src2, OutputArray dst, int flags=DECOMP_LU)
	Solves one or more linear systems or least-squares problems.
int	cv::solveCubic (InputArray coeffs, OutputArray roots)
	Finds the real roots of a cubic equation.
double	cv::solvePoly (InputArray coeffs, OutputArray roots, int maxIters=300)
	Finds the real or complex roots of a polynomial equation.
void	cv::sort (InputArray src, OutputArray dst, int flags)
	Sorts each row or each column of a matrix.
void	cv::sortIdx (InputArray src, OutputArray dst, int flags)
	Sorts each row or each column of a matrix.
void	cv::split (const Mat &src, Mat *mvbegin)
	Divides a multi-channel array into several single-channel arrays.
void	cv::split (InputArray m, OutputArrayOfArrays mv)
void	cv::sqrt (InputArray src, OutputArray dst)
	Calculates a square root of array elements.
void	cv::subtract (InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
	Calculates the per-element difference between two arrays or array and a scalar.
Scalar	cv::sum (InputArray src)
	Calculates the sum of array elements.
void	cv::SVBackSubst (InputArray w, InputArray u, InputArray vt, InputArray rhs, OutputArray dst)
void	cv::SVDecomp (InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags=0)
void	cv::swap (Mat &a, Mat &b)
	Swaps two matrices.
void	cv::swap (UMat &a, UMat &b)
RNG &	cv::theRNG ()
	Returns the default random number generator.
Scalar	cv::trace (InputArray mtx)
	Returns the trace of a matrix.
void	cv::transform (InputArray src, OutputArray dst, InputArray m)
	Performs the matrix transformation of every array element.
void	cv::transpose (InputArray src, OutputArray dst)
	Transposes a matrix.
void	cv::transposeND (InputArray src, const std::vector< int > &order, OutputArray dst)
	Transpose for n-dimensional matrices.
void	cv::vconcat (const Mat *src, size_t nsrc, OutputArray dst)
	Applies vertical concatenation to given matrices.
void	cv::vconcat (InputArray src1, InputArray src2, OutputArray dst)
void	cv::vconcat (InputArrayOfArrays src, OutputArray dst)