Trait opencv::core::PCATraitConst

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pub trait PCATraitConst {
    // Required method
    fn as_raw_PCA(&self) -> *const c_void;

    // Provided methods
    fn eigenvectors(&self) -> Mat { ... }
    fn eigenvalues(&self) -> Mat { ... }
    fn mean(&self) -> Mat { ... }
    fn project(&self, vec: &impl ToInputArray) -> Result<Mat> { ... }
    fn project_to(
        &self,
        vec: &impl ToInputArray,
        result: &mut impl ToOutputArray
    ) -> Result<()> { ... }
    fn back_project(&self, vec: &impl ToInputArray) -> Result<Mat> { ... }
    fn back_project_to(
        &self,
        vec: &impl ToInputArray,
        result: &mut impl ToOutputArray
    ) -> Result<()> { ... }
    fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()> { ... }
}

Expand description

Constant methods for core::PCA

Required Methods§

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fn as_raw_PCA(&self) -> *const c_void

Provided Methods§

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fn eigenvectors(&self) -> Mat

eigenvectors of the covariation matrix

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fn eigenvalues(&self) -> Mat

eigenvalues of the covariation matrix

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fn mean(&self) -> Mat

mean value subtracted before the projection and added after the back projection

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fn project(&self, vec: &impl ToInputArray) -> Result<Mat>

Projects vector(s) to the principal component subspace.

The methods project one or more vectors to the principal component subspace, where each vector projection is represented by coefficients in the principal component basis. The first form of the method returns the matrix that the second form writes to the result. So the first form can be used as a part of expression while the second form can be more efficient in a processing loop.

§Parameters

vec: input vector(s); must have the same dimensionality and the same layout as the input data used at %PCA phase, that is, if DATA_AS_ROW are specified, then vec.cols==data.cols (vector dimensionality) and vec.rows is the number of vectors to project, and the same is true for the PCA::DATA_AS_COL case.

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fn project_to( &self, vec: &impl ToInputArray, result: &mut impl ToOutputArray ) -> Result<()>

Projects vector(s) to the principal component subspace.

The methods project one or more vectors to the principal component subspace, where each vector projection is represented by coefficients in the principal component basis. The first form of the method returns the matrix that the second form writes to the result. So the first form can be used as a part of expression while the second form can be more efficient in a processing loop.

§Parameters

vec: input vector(s); must have the same dimensionality and the same layout as the input data used at %PCA phase, that is, if DATA_AS_ROW are specified, then vec.cols==data.cols (vector dimensionality) and vec.rows is the number of vectors to project, and the same is true for the PCA::DATA_AS_COL case.

§Overloaded parameters

vec: input vector(s); must have the same dimensionality and the same layout as the input data used at PCA phase, that is, if DATA_AS_ROW are specified, then vec.cols==data.cols (vector dimensionality) and vec.rows is the number of vectors to project, and the same is true for the PCA::DATA_AS_COL case.
result: output vectors; in case of PCA::DATA_AS_COL, the output matrix has as many columns as the number of input vectors, this means that result.cols==vec.cols and the number of rows match the number of principal components (for example, maxComponents parameter passed to the constructor).

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fn back_project(&self, vec: &impl ToInputArray) -> Result<Mat>

Reconstructs vectors from their PC projections.

The methods are inverse operations to PCA::project. They take PC coordinates of projected vectors and reconstruct the original vectors. Unless all the principal components have been retained, the reconstructed vectors are different from the originals. But typically, the difference is small if the number of components is large enough (but still much smaller than the original vector dimensionality). As a result, PCA is used.

§Parameters

vec: coordinates of the vectors in the principal component subspace, the layout and size are the same as of PCA::project output vectors.

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fn back_project_to( &self, vec: &impl ToInputArray, result: &mut impl ToOutputArray ) -> Result<()>

Reconstructs vectors from their PC projections.

The methods are inverse operations to PCA::project. They take PC coordinates of projected vectors and reconstruct the original vectors. Unless all the principal components have been retained, the reconstructed vectors are different from the originals. But typically, the difference is small if the number of components is large enough (but still much smaller than the original vector dimensionality). As a result, PCA is used.

§Parameters

vec: coordinates of the vectors in the principal component subspace, the layout and size are the same as of PCA::project output vectors.

§Overloaded parameters

vec: coordinates of the vectors in the principal component subspace, the layout and size are the same as of PCA::project output vectors.
result: reconstructed vectors; the layout and size are the same as of PCA::project input vectors.

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