[−][src]Trait opencv::face::prelude::FacemarkKazemi_ParamsTrait

pub trait FacemarkKazemi_ParamsTrait {
    pub fn as_raw_FacemarkKazemi_Params(&self) -> *const c_void;

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

    pub fn cascade_depth(&self) -> u32 { ... }

    pub fn set_cascade_depth(&mut self, val: u32) { ... }

    pub fn tree_depth(&self) -> u32 { ... }

    pub fn set_tree_depth(&mut self, val: u32) { ... }

    pub fn num_trees_per_cascade_level(&self) -> u32 { ... }

    pub fn set_num_trees_per_cascade_level(&mut self, val: u32) { ... }

    pub fn learning_rate(&self) -> f32 { ... }

    pub fn set_learning_rate(&mut self, val: f32) { ... }

    pub fn oversampling_amount(&self) -> u32 { ... }

    pub fn set_oversampling_amount(&mut self, val: u32) { ... }

    pub fn num_test_coordinates(&self) -> u32 { ... }

    pub fn set_num_test_coordinates(&mut self, val: u32) { ... }

    pub fn lambda(&self) -> f32 { ... }

    pub fn set_lambda(&mut self, val: f32) { ... }

    pub fn num_test_splits(&self) -> u32 { ... }

    pub fn set_num_test_splits(&mut self, val: u32) { ... }

    pub fn configfile(&self) -> String { ... }

    pub fn set_configfile(&mut self, val: &str) { ... }
}

Required methods

pub fn as_raw_FacemarkKazemi_Params(&self) -> *const c_void[src]

pub fn as_raw_mut_FacemarkKazemi_Params(&mut self) -> *mut c_void[src]

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Provided methods

pub fn cascade_depth(&self) -> u32[src]

cascade_depth This stores the deapth of cascade used for training.

pub fn set_cascade_depth(&mut self, val: u32)[src]

cascade_depth This stores the deapth of cascade used for training.

pub fn tree_depth(&self) -> u32[src]

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

pub fn set_tree_depth(&mut self, val: u32)[src]

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

pub fn num_trees_per_cascade_level(&self) -> u32[src]

num_trees_per_cascade_level This stores number of trees fit per cascade level.

pub fn set_num_trees_per_cascade_level(&mut self, val: u32)[src]

num_trees_per_cascade_level This stores number of trees fit per cascade level.

pub fn learning_rate(&self) -> f32[src]

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

pub fn set_learning_rate(&mut self, val: f32)[src]

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

pub fn oversampling_amount(&self) -> u32[src]

oversampling_amount stores number of initialisations used to create training samples.

pub fn set_oversampling_amount(&mut self, val: u32)[src]

oversampling_amount stores number of initialisations used to create training samples.

pub fn num_test_coordinates(&self) -> u32[src]

num_test_coordinates stores number of test coordinates.

pub fn set_num_test_coordinates(&mut self, val: u32)[src]

num_test_coordinates stores number of test coordinates.

pub fn lambda(&self) -> f32[src]

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

pub fn set_lambda(&mut self, val: f32)[src]

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

pub fn num_test_splits(&self) -> u32[src]

num_test_splits stores number of random test splits generated.

pub fn set_num_test_splits(&mut self, val: u32)[src]

num_test_splits stores number of random test splits generated.

pub fn configfile(&self) -> String[src]

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

pub fn set_configfile(&mut self, val: &str)[src]

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

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Implementors

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