Trait opencv::core::SVDTrait

pub trait SVDTrait {
    pub fn as_raw_SVD(&self) -> *const c_void;
    pub fn as_raw_mut_SVD(&mut self) -> *mut c_void;

    pub fn u(&mut self) -> Mat { ... }
    pub fn set_u(&mut self, val: Mat) { ... }
    pub fn w(&mut self) -> Mat { ... }
    pub fn set_w(&mut self, val: Mat) { ... }
    pub fn vt(&mut self) -> Mat { ... }
    pub fn set_vt(&mut self, val: Mat) { ... }
    pub fn back_subst(
        &self, 
        rhs: &dyn ToInputArray, 
        dst: &mut dyn ToOutputArray
    ) -> Result<()> { ... }
}

Singular Value Decomposition

Class for computing Singular Value Decomposition of a floating-point matrix. The Singular Value Decomposition is used to solve least-square problems, under-determined linear systems, invert matrices, compute condition numbers, and so on.

If you want to compute a condition number of a matrix or an absolute value of its determinant, you do not need u and vt. You can pass flags=SVD::NO_UV|... . Another flag SVD::FULL_UV indicates that full-size u and vt must be computed, which is not necessary most of the time.

See also

invert, solve, eigen, determinant

Required methods

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

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

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Provided methods

pub fn u(&mut self) -> Mat

pub fn set_u(&mut self, val: Mat)

pub fn w(&mut self) -> Mat

pub fn set_w(&mut self, val: Mat)

pub fn vt(&mut self) -> Mat

pub fn set_vt(&mut self, val: Mat)

pub fn back_subst(
    &self,
    rhs: &dyn ToInputArray,
    dst: &mut dyn ToOutputArray
) -> Result<()>

performs a singular value back substitution.

The method calculates a back substitution for the specified right-hand side:

Using this technique you can either get a very accurate solution of the convenient linear system, or the best (in the least-squares terms) pseudo-solution of an overdetermined linear system.

Parameters

• rhs: right-hand side of a linear system (u*w*v')*dst = rhs to be solved, where A has been previously decomposed.

• dst: found solution of the system.

Note: Explicit SVD with the further back substitution only makes sense if you need to solve many linear systems with the same left-hand side (for example, src ). If all you need is to solve a single system (possibly with multiple rhs immediately available), simply call solve add pass #DECOMP_SVD there. It does absolutely the same thing.

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Implementors

impl SVDTrait for SVD

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

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

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