Struct opencv::text::ERStat

pub struct ERStat { /* private fields */ }

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

Constructor

C++ default parameters

• level: 256
• pixel: 0
• x: 0
• y: 0

pub fn new_def() -> Result<ERStat>

Constructor

Note

This alternative version of [new] function uses the following default values for its arguments:

• level: 256
• pixel: 0
• x: 0
• y: 0

Trait Implementations

impl Boxed for ERStat

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

Wrap the specified raw pointer

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

Return the underlying raw pointer while consuming this wrapper.

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

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Debug for ERStat

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

Formats the value using the given formatter.

impl Drop for ERStat

fn drop(&mut self)

Executes the destructor for this type.

impl ERStatTrait for ERStat

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

fn set_pixel(&mut self, val: i32)

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

fn set_level(&mut self, val: i32)

fn set_area(&mut self, val: i32)

incrementally computable features

fn set_perimeter(&mut self, val: i32)

fn set_euler(&mut self, val: i32)

Euler’s number

fn set_rect(&mut self, val: Rect)

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

order 1 raw moments to derive the centroid

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

order 2 central moments to construct the covariance matrix

fn set_med_crossings(&mut self, val: f32)

median of the crossings at three different height levels

fn set_hole_area_ratio(&mut self, val: f32)

2nd stage features

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)

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

fn parent(&mut self) -> ERStat

pointers preserving the tree structure of the component tree

fn set_parent(&mut self, val: &impl ERStatTraitConst)

pointers preserving the tree structure of the component tree

fn child(&mut self) -> ERStat

fn set_child(&mut self, val: &impl ERStatTraitConst)

fn next(&mut self) -> ERStat

fn set_next(&mut self, val: &impl ERStatTraitConst)

fn prev(&mut self) -> ERStat

fn set_prev(&mut self, val: &impl ERStatTraitConst)

fn set_local_maxima(&mut self, val: bool)

whenever the regions is a local maxima of the probability

fn max_probability_ancestor(&mut self) -> ERStat

fn set_max_probability_ancestor(&mut self, val: &impl ERStatTraitConst)

fn min_probability_ancestor(&mut self) -> ERStat

fn set_min_probability_ancestor(&mut self, val: &impl ERStatTraitConst)

impl ERStatTraitConst for ERStat

fn as_raw_ERStat(&self) -> *const c_void

fn pixel(&self) -> i32

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

fn level(&self) -> i32

fn area(&self) -> i32

incrementally computable features

fn perimeter(&self) -> i32

fn euler(&self) -> i32

Euler’s number

fn rect(&self) -> Rect

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

order 1 raw moments to derive the centroid

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

order 2 central moments to construct the covariance matrix

fn med_crossings(&self) -> f32

median of the crossings at three different height levels

fn hole_area_ratio(&self) -> f32

2nd stage features

fn convex_hull_ratio(&self) -> f32

fn num_inflexion_points(&self) -> f32

fn probability(&self) -> f64

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

fn local_maxima(&self) -> bool

whenever the regions is a local maxima of the probability

impl Send for ERStat