Struct opencv::core::LDA

pub struct LDA { /* fields omitted */ }

Linear Discriminant Analysis @todo document this class

Implementations

impl LDA

pub fn as_raw_LDA(&self) -> *const c_void

pub fn as_raw_mut_LDA(&mut self) -> *mut c_void

impl LDA

pub fn new(num_components: i32) -> Result<LDA>

constructor Initializes a LDA with num_components (default 0).

C++ default parameters

• num_components: 0

pub fn new_with_data(
    src: &dyn ToInputArray,
    labels: &dyn ToInputArray,
    num_components: i32
) -> Result<LDA>

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.

C++ default parameters

• num_components: 0

pub fn subspace_project(
    w: &dyn ToInputArray,
    mean: &dyn ToInputArray,
    src: &dyn ToInputArray
) -> Result<Mat>

pub fn subspace_reconstruct(
    w: &dyn ToInputArray,
    mean: &dyn ToInputArray,
    src: &dyn ToInputArray
) -> Result<Mat>

Trait Implementations

impl Boxed for LDA

pub unsafe fn from_raw(ptr: *mut c_void) -> Self

Wrap the specified raw pointer

pub fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

pub fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

pub fn as_raw_mut(&mut self) -> *mut c_void

Return the underlying mutable raw pointer

impl Drop for LDA

pub fn drop(&mut self)

Executes the destructor for this type.

impl LDATrait for LDA

pub fn as_raw_LDA(&self) -> *const c_void

pub fn as_raw_mut_LDA(&mut self) -> *mut c_void

pub fn save(&self, filename: &str) -> Result<()>

Serializes this object to a given filename.

pub fn load(&mut self, filename: &str) -> Result<()>

Deserializes this object from a given filename.

pub fn save_1(&self, fs: &mut FileStorage) -> Result<()>

Serializes this object to a given cv::FileStorage.

pub fn load_1(&mut self, node: &FileStorage) -> Result<()>

Deserializes this object from a given cv::FileStorage.

pub fn compute(
    &mut self,
    src: &dyn ToInputArray,
    labels: &dyn ToInputArray
) -> Result<()>

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

pub fn project(&mut self, src: &dyn ToInputArray) -> Result<Mat>

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

pub fn reconstruct(&mut self, src: &dyn ToInputArray) -> Result<Mat>

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

pub fn eigenvectors(&self) -> Result<Mat>

Returns the eigenvectors of this LDA.

pub fn eigenvalues(&self) -> Result<Mat>

Returns the eigenvalues of this LDA.

impl Send for LDA