[][src]Trait opencv::features2d::GFTTDetector

pub trait GFTTDetector: Feature2D {
    fn as_raw_GFTTDetector(&self) -> *mut c_void;

    fn set_max_features(&mut self, max_features: i32) -> Result<()> { ... }
fn get_max_features(&self) -> Result<i32> { ... }
fn set_quality_level(&mut self, qlevel: f64) -> Result<()> { ... }
fn get_quality_level(&self) -> Result<f64> { ... }
fn set_min_distance(&mut self, min_distance: f64) -> Result<()> { ... }
fn get_min_distance(&self) -> Result<f64> { ... }
fn set_block_size(&mut self, block_size: i32) -> Result<()> { ... }
fn get_block_size(&self) -> Result<i32> { ... }
fn set_harris_detector(&mut self, val: bool) -> Result<()> { ... }
fn get_harris_detector(&self) -> Result<bool> { ... }
fn set_k(&mut self, k: f64) -> Result<()> { ... }
fn get_k(&self) -> Result<f64> { ... }
fn get_default_name(&self) -> Result<String> { ... } }

Wrapping class for feature detection using the goodFeaturesToTrack function. :

Required methods

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Provided methods

fn set_max_features(&mut self, max_features: i32) -> Result<()>

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

fn set_quality_level(&mut self, qlevel: f64) -> Result<()>

fn get_quality_level(&self) -> Result<f64>

fn set_min_distance(&mut self, min_distance: f64) -> Result<()>

fn get_min_distance(&self) -> Result<f64>

fn set_block_size(&mut self, block_size: i32) -> Result<()>

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

fn set_harris_detector(&mut self, val: bool) -> Result<()>

fn get_harris_detector(&self) -> Result<bool>

fn set_k(&mut self, k: f64) -> Result<()>

fn get_k(&self) -> Result<f64>

fn get_default_name(&self) -> Result<String>

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Methods

impl<'_> dyn GFTTDetector + '_[src]

pub fn create(
    max_corners: i32,
    quality_level: f64,
    min_distance: f64,
    block_size: i32,
    use_harris_detector: bool,
    k: f64
) -> Result<PtrOfGFTTDetector>
[src]

C++ default parameters

  • max_corners: 1000
  • quality_level: 0.01
  • min_distance: 1
  • block_size: 3
  • use_harris_detector: false
  • k: 0.04

pub fn create_with_gradient(
    max_corners: i32,
    quality_level: f64,
    min_distance: f64,
    block_size: i32,
    gradiant_size: i32,
    use_harris_detector: bool,
    k: f64
) -> Result<PtrOfGFTTDetector>
[src]

C++ default parameters

  • use_harris_detector: false
  • k: 0.04

Implementors

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