[−][src]Trait opencv::hub_prelude::ERFilter

pub trait ERFilter: AlgorithmTrait {
    fn as_raw_ERFilter(&self) -> *mut c_void;

    fn run(
        &mut self, 
        image: &dyn ToInputArray, 
        regions: &mut VectorOfERStat
    ) -> Result<()> { ... }

    fn set_callback(&mut self, cb: &PtrOfERFilter_Callback) -> Result<()> { ... }

    fn set_threshold_delta(&mut self, threshold_delta: i32) -> Result<()> { ... }

    fn set_min_area(&mut self, min_area: f32) -> Result<()> { ... }

    fn set_max_area(&mut self, max_area: f32) -> Result<()> { ... }

    fn set_min_probability(&mut self, min_probability: f32) -> Result<()> { ... }

    fn set_min_probability_diff(
        &mut self, 
        min_probability_diff: f32
    ) -> Result<()> { ... }

    fn set_non_max_suppression(
        &mut self, 
        non_max_suppression: bool
    ) -> Result<()> { ... }

    fn get_num_rejected(&self) -> Result<i32> { ... }
}

Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm Neumann12. :

Extracts the component tree (if needed) and filter the extremal regions (ER's) by using a given classifier.

Required methods

fn as_raw_ERFilter(&self) -> *mut c_void

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Provided methods

fn run(
    &mut self,
    image: &dyn ToInputArray,
    regions: &mut VectorOfERStat
) -> Result<()>

The key method of ERFilter algorithm.

Takes image on input and returns the selected regions in a vector of ERStat only distinctive ERs which correspond to characters are selected by a sequential classifier

Parameters

  • image: Single channel image CV_8UC1

  • regions: Output for the 1st stage and Input/Output for the 2nd. The selected Extremal Regions are stored here.

Extracts the component tree (if needed) and filter the extremal regions (ER's) by using a given classifier.

fn set_callback(&mut self, cb: &PtrOfERFilter_Callback) -> Result<()>

set/get methods to set the algorithm properties,

fn set_threshold_delta(&mut self, threshold_delta: i32) -> Result<()>

fn set_min_area(&mut self, min_area: f32) -> Result<()>

fn set_max_area(&mut self, max_area: f32) -> Result<()>

fn set_min_probability(&mut self, min_probability: f32) -> Result<()>

fn set_min_probability_diff(&mut self, min_probability_diff: f32) -> Result<()>

fn set_non_max_suppression(&mut self, non_max_suppression: bool) -> Result<()>

fn get_num_rejected(&self) -> Result<i32>

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Implementors

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