Struct opencv::ccalib::CustomPattern

pub struct CustomPattern { /* fields omitted */ }

Methods

impl CustomPattern

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

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

impl CustomPattern

pub fn default() -> Result<CustomPattern>

pub fn create(
    &mut self,
    pattern: &dyn ToInputArray,
    board_size: Size2f,
    output: &mut dyn ToOutputArray
) -> Result<bool>

C++ default parameters

• output: noArray()

pub fn find_pattern(
    &mut self,
    image: &dyn ToInputArray,
    matched_features: &mut dyn ToOutputArray,
    pattern_points: &mut dyn ToOutputArray,
    ratio: f64,
    proj_error: f64,
    refine_position: bool,
    out: &mut dyn ToOutputArray,
    h: &mut dyn ToOutputArray,
    pattern_corners: &mut dyn ToOutputArray
) -> Result<bool>

C++ default parameters

• ratio: 0.7
• proj_error: 8.0
• refine_position: false
• out: noArray()
• h: noArray()
• pattern_corners: noArray()

pub fn is_initialized(&mut self) -> Result<bool>

pub fn get_pattern_points(
    &mut self,
    original_points: &mut VectorOfKeyPoint
) -> Result<()>

pub fn get_pixel_size(&mut self) -> Result<f64>

< Returns a vector of the original points.

pub fn set_feature_detector(
    &mut self,
    feature_detector: &PtrOfFeature2D
) -> Result<bool>

< Get the pixel size of the pattern

pub fn set_descriptor_extractor(
    &mut self,
    extractor: &PtrOfFeature2D
) -> Result<bool>

pub fn set_descriptor_matcher(
    &mut self,
    matcher: &PtrOfDescriptorMatcher
) -> Result<bool>

pub fn get_feature_detector(&mut self) -> Result<PtrOfFeature2D>

pub fn get_descriptor_extractor(&mut self) -> Result<PtrOfFeature2D>

pub fn get_descriptor_matcher(&mut self) -> Result<PtrOfDescriptorMatcher>

pub fn calibrate(
    &mut self,
    object_points: &dyn ToInputArray,
    image_points: &dyn ToInputArray,
    image_size: Size,
    camera_matrix: &mut dyn ToInputOutputArray,
    dist_coeffs: &mut dyn ToInputOutputArray,
    rvecs: &mut dyn ToOutputArray,
    tvecs: &mut dyn ToOutputArray,
    flags: i32,
    criteria: &TermCriteria
) -> Result<f64>

C++ default parameters

• flags: 0
• criteria: TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON)

pub fn find_rt(
    &mut self,
    object_points: &dyn ToInputArray,
    image_points: &dyn ToInputArray,
    camera_matrix: &dyn ToInputArray,
    dist_coeffs: &dyn ToInputArray,
    rvec: &mut dyn ToInputOutputArray,
    tvec: &mut dyn ToInputOutputArray,
    use_extrinsic_guess: bool,
    flags: i32
) -> Result<bool>

< Calls the calirateCamera function with the same inputs.

C++ default parameters

• use_extrinsic_guess: false
• flags: SOLVEPNP_ITERATIVE

pub fn find_rt_1(
    &mut self,
    image: &dyn ToInputArray,
    camera_matrix: &dyn ToInputArray,
    dist_coeffs: &dyn ToInputArray,
    rvec: &mut dyn ToInputOutputArray,
    tvec: &mut dyn ToInputOutputArray,
    use_extrinsic_guess: bool,
    flags: i32
) -> Result<bool>

C++ default parameters

• use_extrinsic_guess: false
• flags: SOLVEPNP_ITERATIVE

pub fn find_rt_ransac(
    &mut self,
    object_points: &dyn ToInputArray,
    image_points: &dyn ToInputArray,
    camera_matrix: &dyn ToInputArray,
    dist_coeffs: &dyn ToInputArray,
    rvec: &mut dyn ToInputOutputArray,
    tvec: &mut dyn ToInputOutputArray,
    use_extrinsic_guess: bool,
    iterations_count: i32,
    reprojection_error: f32,
    min_inliers_count: i32,
    inliers: &mut dyn ToOutputArray,
    flags: i32
) -> Result<bool>

< Uses solvePnP to find the rotation and translation of the pattern with respect to the camera frame.

C++ default parameters

• use_extrinsic_guess: false
• iterations_count: 100
• reprojection_error: 8.0
• min_inliers_count: 100
• inliers: noArray()
• flags: SOLVEPNP_ITERATIVE

pub fn find_rt_ransac_1(
    &mut self,
    image: &dyn ToInputArray,
    camera_matrix: &dyn ToInputArray,
    dist_coeffs: &dyn ToInputArray,
    rvec: &mut dyn ToInputOutputArray,
    tvec: &mut dyn ToInputOutputArray,
    use_extrinsic_guess: bool,
    iterations_count: i32,
    reprojection_error: f32,
    min_inliers_count: i32,
    inliers: &mut dyn ToOutputArray,
    flags: i32
) -> Result<bool>

C++ default parameters

• use_extrinsic_guess: false
• iterations_count: 100
• reprojection_error: 8.0
• min_inliers_count: 100
• inliers: noArray()
• flags: SOLVEPNP_ITERATIVE

pub fn draw_orientation(
    &mut self,
    image: &mut dyn ToInputOutputArray,
    tvec: &dyn ToInputArray,
    rvec: &dyn ToInputArray,
    camera_matrix: &dyn ToInputArray,
    dist_coeffs: &dyn ToInputArray,
    axis_length: f64,
    axis_width: i32
) -> Result<()>

< Uses solvePnPRansac()

C++ default parameters

• axis_length: 3
• axis_width: 2

Trait Implementations

impl AlgorithmTrait for CustomPattern

fn as_raw_Algorithm(&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: &PtrOfFileStorage, name: &str) -> Result<()>

simplified API for language bindings

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 Drop for CustomPattern

fn drop(&mut self)

Executes the destructor for this type.

impl Send for CustomPattern