OpenCV  4.2.0
Open Source Computer Vision
Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
cv::LDA Class Reference

Linear Discriminant Analysis. More...

#include <opencv2/core.hpp>

Public Member Functions

 LDA (int num_components=0)
 constructor Initializes a LDA with num_components (default 0). More...
 
 LDA (InputArrayOfArrays src, InputArray labels, int num_components=0)
 
 ~LDA ()
 
void compute (InputArrayOfArrays src, InputArray labels)
 
Mat eigenvalues () const
 
Mat eigenvectors () const
 
void load (const String &filename)
 
void load (const FileStorage &node)
 
Mat project (InputArray src)
 
Mat reconstruct (InputArray src)
 
void save (const String &filename) const
 
void save (FileStorage &fs) const
 

Static Public Member Functions

static Mat subspaceProject (InputArray W, InputArray mean, InputArray src)
 
static Mat subspaceReconstruct (InputArray W, InputArray mean, InputArray src)
 

Protected Member Functions

void lda (InputArrayOfArrays src, InputArray labels)
 

Protected Attributes

Mat _eigenvalues
 
Mat _eigenvectors
 
int _num_components
 

Detailed Description

Linear Discriminant Analysis.

Todo:
document this class

Constructor & Destructor Documentation

◆ LDA() [1/2]

cv::LDA::LDA ( int  num_components = 0)
explicit

constructor Initializes a LDA with num_components (default 0).

◆ LDA() [2/2]

cv::LDA::LDA ( InputArrayOfArrays  src,
InputArray  labels,
int  num_components = 0 
)

Initializes and performs a Discriminant Analysis with Fisher's Optimization Criterion on given data in src and corresponding labels in labels. If 0 (or less) number of components are given, they are automatically determined for given data in computation.

◆ ~LDA()

cv::LDA::~LDA ( )

destructor

Member Function Documentation

◆ compute()

void cv::LDA::compute ( InputArrayOfArrays  src,
InputArray  labels 
)

Compute the discriminants for data in src (row aligned) and labels.

◆ eigenvalues()

Mat cv::LDA::eigenvalues ( ) const
inline

Returns the eigenvalues of this LDA.

◆ eigenvectors()

Mat cv::LDA::eigenvectors ( ) const
inline

Returns the eigenvectors of this LDA.

◆ lda()

void cv::LDA::lda ( InputArrayOfArrays  src,
InputArray  labels 
)
protected

◆ load() [1/2]

void cv::LDA::load ( const String filename)

Deserializes this object from a given filename.

◆ load() [2/2]

void cv::LDA::load ( const FileStorage node)

Deserializes this object from a given cv::FileStorage.

◆ project()

Mat cv::LDA::project ( InputArray  src)

Projects samples into the LDA subspace. src may be one or more row aligned samples.

◆ reconstruct()

Mat cv::LDA::reconstruct ( InputArray  src)

Reconstructs projections from the LDA subspace. src may be one or more row aligned projections.

◆ save() [1/2]

void cv::LDA::save ( const String filename) const

Serializes this object to a given filename.

◆ save() [2/2]

void cv::LDA::save ( FileStorage fs) const

Serializes this object to a given cv::FileStorage.

◆ subspaceProject()

static Mat cv::LDA::subspaceProject ( InputArray  W,
InputArray  mean,
InputArray  src 
)
static

◆ subspaceReconstruct()

static Mat cv::LDA::subspaceReconstruct ( InputArray  W,
InputArray  mean,
InputArray  src 
)
static

Member Data Documentation

◆ _eigenvalues

Mat cv::LDA::_eigenvalues
protected

◆ _eigenvectors

Mat cv::LDA::_eigenvectors
protected

◆ _num_components

int cv::LDA::_num_components
protected

The documentation for this class was generated from the following file: