fn project_to(&self, vec: &dyn core::ToInputArray, result: &mut dyn core::ToOutputArray) -> Result<()> {
		input_array_arg!(vec);
		output_array_arg!(result);
		unsafe { sys::cv_PCA_project_const_const__InputArrayX_const__OutputArrayX(self.as_raw_PCA(), vec.as_raw__InputArray(), result.as_raw__OutputArray()) }.into_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).
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.
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 .
fn project_to(&self, vec: &dyn core::ToInputArray, result: &mut dyn core::ToOutputArray) -> Result<()> {
		input_array_arg!(vec);
		output_array_arg!(result);
		unsafe { sys::cv_PCA_project_const_const__InputArrayX_const__OutputArrayX(self.as_raw_PCA(), vec.as_raw__InputArray(), result.as_raw__OutputArray()) }.into_result()
	}
fn project_to ( & self , vec : & dyn core :: ToInputArray , result : & mut dyn core :: ToOutputArray ) -> Result < ( ) > { input_array_arg ! ( vec ) ; output_array_arg ! ( result ) ; unsafe { sys :: cv_PCA_project_const_const__InputArrayX_const__OutputArrayX ( self . as_raw_PCA ( ) , vec . as_raw__InputArray ( ) , result . as_raw__OutputArray ( ) ) } . into_result ( ) }
Projects vector(s) to the principal component subspace.
Projects vector ( s ) to the principal component subspace .
&self
vec
&dyn core::ToInputArray
result
&mut dyn core::ToOutputArray
overloaded parameters
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).
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 ) .