Trait opencv::prelude::ERStatTrait

source · 
pub trait ERStatTrait: ERStatTraitConst {

Show 27 methods    fn as_raw_mut_ERStat(&mut self) -> *mut c_void;

    fn set_pixel(&mut self, val: i32) { ... }
    fn set_level(&mut self, val: i32) { ... }
    fn set_area(&mut self, val: i32) { ... }
    fn set_perimeter(&mut self, val: i32) { ... }
    fn set_euler(&mut self, val: i32) { ... }
    fn set_rect(&mut self, val: Rect) { ... }
    fn raw_moments(&mut self) -> &mut [f64; 2] { ... }
    fn central_moments(&mut self) -> &mut [f64; 3] { ... }
    fn set_med_crossings(&mut self, val: f32) { ... }
    fn set_hole_area_ratio(&mut self, val: f32) { ... }
    fn set_convex_hull_ratio(&mut self, val: f32) { ... }
    fn set_num_inflexion_points(&mut self, val: f32) { ... }
    fn set_probability(&mut self, val: f64) { ... }
    fn parent(&mut self) -> ERStat { ... }
    fn set_parent(&mut self, val: &mut ERStat) { ... }
    fn child(&mut self) -> ERStat { ... }
    fn set_child(&mut self, val: &mut ERStat) { ... }
    fn next(&mut self) -> ERStat { ... }
    fn set_next(&mut self, val: &mut ERStat) { ... }
    fn prev(&mut self) -> ERStat { ... }
    fn set_prev(&mut self, val: &mut ERStat) { ... }
    fn set_local_maxima(&mut self, val: bool) { ... }
    fn max_probability_ancestor(&mut self) -> ERStat { ... }
    fn set_max_probability_ancestor(&mut self, val: &mut ERStat) { ... }
    fn min_probability_ancestor(&mut self) -> ERStat { ... }
    fn set_min_probability_ancestor(&mut self, val: &mut ERStat) { ... }

}

Required Methods

Provided Methods

seed point and the threshold (max grey-level value)

incrementally computable features

Euler’s number

order 1 raw moments to derive the centroid

order 2 central moments to construct the covariance matrix

median of the crossings at three different height levels

2nd stage features

probability that the ER belongs to the class we are looking for

pointers preserving the tree structure of the component tree

pointers preserving the tree structure of the component tree

whenever the regions is a local maxima of the probability

Implementors