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CovarFlags

Core and matricesclassOpenCV 5.0.0
import { CovarFlags } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

ARGUMENTSConstructor or factory
CLASSCovarFlags
RETURN TYPEOwned native handle
Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

Native object: release it with using or delete(). Factories can return null; check before calling methods.

core_utils

Covariation flags

Constructors and members

static COVAR_SCRAMBLED

The output covariance matrix is calculated as:

COVAR_SCRAMBLED: CovarFlagsValue<0>,

static 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_NORMAL: CovarFlagsValue<1>,

static 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_USE_AVG: CovarFlagsValue<2>,

static 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_SCALE: CovarFlagsValue<4>,

static 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_ROWS: CovarFlagsValue<8>,

static 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.

COVAR_COLS: CovarFlagsValue<16>

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