Type Definition opencv::types::PtrOfGeneralizedHoughBallard

type PtrOfGeneralizedHoughBallard = Ptr<dyn GeneralizedHoughBallard>;

Implementations

impl PtrOfGeneralizedHoughBallard

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

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

Trait Implementations

impl AlgorithmTrait for PtrOfGeneralizedHoughBallard

fn as_raw_Algorithm(&self) -> *const c_void

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

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn write(&self, fs: &mut FileStorage) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

simplified API for language bindings Stores algorithm parameters in a file storage

fn read(&mut self, fn_: &FileNode) -> Result<()>

Reads algorithm parameters from a file storage

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

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

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

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl GeneralizedHough for PtrOfGeneralizedHoughBallard

fn as_raw_GeneralizedHough(&self) -> *const c_void

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

fn set_template(
    &mut self,
    templ: &dyn ToInputArray,
    templ_center: Point
) -> Result<()>

set template to search

fn set_template_1(
    &mut self,
    edges: &dyn ToInputArray,
    dx: &dyn ToInputArray,
    dy: &dyn ToInputArray,
    templ_center: Point
) -> Result<()>

C++ default parameters * templ_center: Point(-1,-1)

fn detect(
    &mut self,
    image: &dyn ToInputArray,
    positions: &mut dyn ToOutputArray,
    votes: &mut dyn ToOutputArray
) -> Result<()>

find template on image

fn detect_with_edges(
    &mut self,
    edges: &dyn ToInputArray,
    dx: &dyn ToInputArray,
    dy: &dyn ToInputArray,
    positions: &mut dyn ToOutputArray,
    votes: &mut dyn ToOutputArray
) -> Result<()>

C++ default parameters * votes: noArray()

fn set_canny_low_thresh(&mut self, canny_low_thresh: i32) -> Result<()>

Canny low threshold.

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

fn set_canny_high_thresh(&mut self, canny_high_thresh: i32) -> Result<()>

Canny high threshold.

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

fn set_min_dist(&mut self, min_dist: f64) -> Result<()>

Minimum distance between the centers of the detected objects.

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

fn set_dp(&mut self, dp: f64) -> Result<()>

Inverse ratio of the accumulator resolution to the image resolution.

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

fn set_max_buffer_size(&mut self, max_buffer_size: i32) -> Result<()>

Maximal size of inner buffers.

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

impl GeneralizedHoughBallard for PtrOfGeneralizedHoughBallard

fn as_raw_GeneralizedHoughBallard(&self) -> *const c_void

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

fn set_levels(&mut self, levels: i32) -> Result<()>

R-Table levels.

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

fn set_votes_threshold(&mut self, votes_threshold: i32) -> Result<()>

The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected.

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