Struct opencv::text::ERStat

pub struct ERStat { /* fields omitted */ }

The ERStat structure represents a class-specific Extremal Region (ER).

An ER is a 4-connected set of pixels with all its grey-level values smaller than the values in its outer boundary. A class-specific ER is selected (using a classifier) from all the ER's in the component tree of the image. :

Implementations

impl ERStat

pub fn as_raw_ERStat(&self) -> *const c_void

pub fn as_raw_mut_ERStat(&mut self) -> *mut c_void

impl ERStat

pub fn new(level: i32, pixel: i32, x: i32, y: i32) -> Result<ERStat>

Constructor

C++ default parameters

• level: 256
• pixel: 0
• x: 0
• y: 0

Trait Implementations

impl Boxed for ERStat

pub unsafe fn from_raw(ptr: *mut c_void) -> Self

Wrap the specified raw pointer

pub fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

pub fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

pub fn as_raw_mut(&mut self) -> *mut c_void

Return the underlying mutable raw pointer

impl Drop for ERStat

pub fn drop(&mut self)

Executes the destructor for this type.

impl ERStatTrait for ERStat

pub fn as_raw_ERStat(&self) -> *const c_void

pub fn as_raw_mut_ERStat(&mut self) -> *mut c_void

pub fn pixel(&self) -> i32

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

pub fn set_pixel(&mut self, val: i32)

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

pub fn level(&self) -> i32

pub fn set_level(&mut self, val: i32)

pub fn area(&self) -> i32

incrementally computable features

pub fn set_area(&mut self, val: i32)

incrementally computable features

pub fn perimeter(&self) -> i32

pub fn set_perimeter(&mut self, val: i32)

pub fn euler(&self) -> i32

Euler's number

pub fn set_euler(&mut self, val: i32)

Euler's number

pub fn rect(&self) -> Rect

pub fn set_rect(&mut self, val: Rect)

pub fn raw_moments(&mut self) -> &mut [f64; 2]

order 1 raw moments to derive the centroid

pub fn central_moments(&mut self) -> &mut [f64; 3]

order 2 central moments to construct the covariance matrix

pub fn med_crossings(&self) -> f32

median of the crossings at three different height levels

pub fn set_med_crossings(&mut self, val: f32)

median of the crossings at three different height levels

pub fn hole_area_ratio(&self) -> f32

2nd stage features

pub fn set_hole_area_ratio(&mut self, val: f32)

2nd stage features

pub fn convex_hull_ratio(&self) -> f32

pub fn set_convex_hull_ratio(&mut self, val: f32)

pub fn num_inflexion_points(&self) -> f32

pub fn set_num_inflexion_points(&mut self, val: f32)

pub fn probability(&self) -> f64

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

pub fn set_probability(&mut self, val: f64)

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

pub fn parent(&mut self) -> ERStat

pointers preserving the tree structure of the component tree

pub fn set_parent(&mut self, val: &mut ERStat)

pointers preserving the tree structure of the component tree

pub fn child(&mut self) -> ERStat

pub fn set_child(&mut self, val: &mut ERStat)

pub fn next(&mut self) -> ERStat

pub fn set_next(&mut self, val: &mut ERStat)

pub fn prev(&mut self) -> ERStat

pub fn set_prev(&mut self, val: &mut ERStat)

pub fn local_maxima(&self) -> bool

whenever the regions is a local maxima of the probability

pub fn set_local_maxima(&mut self, val: bool)

whenever the regions is a local maxima of the probability

pub fn max_probability_ancestor(&mut self) -> ERStat

pub fn set_max_probability_ancestor(&mut self, val: &mut ERStat)

pub fn min_probability_ancestor(&mut self) -> ERStat

pub fn set_min_probability_ancestor(&mut self, val: &mut ERStat)

impl Send for ERStat

impl VectorElement for ERStat where
    Vector<ERStat>: VectorExtern<ERStat>, 

pub fn opencv_vector_to_vec(v: &Vector<ERStat>) -> Vec<ERStat>