Struct FacemarkKazemi_Params

pub struct FacemarkKazemi_Params { /* private fields */ }

Implementations

impl FacemarkKazemi_Params

pub fn default() -> Result<FacemarkKazemi_Params>

\brief Constructor

Trait Implementations

impl Boxed for FacemarkKazemi_Params

unsafe fn from_raw( ptr: <FacemarkKazemi_Params as OpenCVFromExtern>::ExternReceive, ) -> Self

Wrap the specified raw pointer

fn into_raw( self, ) -> <FacemarkKazemi_Params as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw( &self, ) -> <FacemarkKazemi_Params as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self, ) -> <FacemarkKazemi_Params as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for FacemarkKazemi_Params

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Drop for FacemarkKazemi_Params

fn drop(&mut self)

Executes the destructor for this type.

impl FacemarkKazemi_ParamsTrait for FacemarkKazemi_Params

fn as_raw_mut_FacemarkKazemi_Params(&mut self) -> *mut c_void

fn set_cascade_depth(&mut self, val: u32)

cascade_depth This stores the deapth of cascade used for training.

fn set_tree_depth(&mut self, val: u32)

tree_depth This stores the max height of the regression tree built.

fn set_num_trees_per_cascade_level(&mut self, val: u32)

num_trees_per_cascade_level This stores number of trees fit per cascade level.

fn set_learning_rate(&mut self, val: f32)

learning_rate stores the learning rate in gradient boosting, also referred as shrinkage.

fn set_oversampling_amount(&mut self, val: u32)

oversampling_amount stores number of initialisations used to create training samples.

fn set_num_test_coordinates(&mut self, val: u32)

num_test_coordinates stores number of test coordinates.

fn set_lambda(&mut self, val: f32)

lambda stores a value to calculate probability of closeness of two coordinates.

fn set_num_test_splits(&mut self, val: u32)

num_test_splits stores number of random test splits generated.

fn set_configfile(&mut self, val: &str)

configfile stores the name of the file containing the values of training parameters

impl FacemarkKazemi_ParamsTraitConst for FacemarkKazemi_Params

fn as_raw_FacemarkKazemi_Params(&self) -> *const c_void

fn cascade_depth(&self) -> u32

cascade_depth This stores the deapth of cascade used for training.

fn tree_depth(&self) -> u32

tree_depth This stores the max height of the regression tree built.

fn num_trees_per_cascade_level(&self) -> u32

num_trees_per_cascade_level This stores number of trees fit per cascade level.

fn learning_rate(&self) -> f32

learning_rate stores the learning rate in gradient boosting, also referred as shrinkage.

fn oversampling_amount(&self) -> u32

oversampling_amount stores number of initialisations used to create training samples.

fn num_test_coordinates(&self) -> u32

num_test_coordinates stores number of test coordinates.

fn lambda(&self) -> f32

lambda stores a value to calculate probability of closeness of two coordinates.

fn num_test_splits(&self) -> u32

num_test_splits stores number of random test splits generated.

fn configfile(&self) -> String

configfile stores the name of the file containing the values of training parameters

impl Send for FacemarkKazemi_Params