Trait opencv::ximgproc::EdgeAwareInterpolator[−][src]

pub trait EdgeAwareInterpolator: SparseMatchInterpolator {
    fn as_raw_EdgeAwareInterpolator(&self) -> *const c_void;

    fn as_raw_mut_EdgeAwareInterpolator(&mut self) -> *mut c_void;

    fn set_cost_map(&mut self, _cost_map: &Mat) -> Result<()> { ... }

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

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

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

    fn get_sigma(&mut self) -> Result<f32> { ... }

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

    fn get_lambda(&mut self) -> Result<f32> { ... }

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

    fn get_use_post_processing(&mut self) -> Result<bool> { ... }

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

    fn get_fgs_lambda(&mut self) -> Result<f32> { ... }

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

    fn get_fgs_sigma(&mut self) -> Result<f32> { ... }
}

Sparse match interpolation algorithm based on modified locally-weighted affine estimator from Revaud2015 and Fast Global Smoother as post-processing filter.

Required methods

fn as_raw_EdgeAwareInterpolator(&self) -> *const c_void[src]

fn as_raw_mut_EdgeAwareInterpolator(&mut self) -> *mut c_void[src]

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Provided methods

fn set_cost_map(&mut self, _cost_map: &Mat) -> Result<()>[src]

Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.

Parameters

  • _costMap: a type CV_32FC1 Mat is required.

See also

cv::ximgproc::createSuperpixelSLIC

fn set_k(&mut self, _k: i32) -> Result<()>[src]

Parameter to tune the approximate size of the superpixel used for oversegmentation.

See also

cv::ximgproc::createSuperpixelSLIC / K is a number of nearest-neighbor matches considered, when fitting a locally affine model. Usually it should be around 128. However, lower values would make the interpolation noticeably faster.

fn get_k(&mut self) -> Result<i32>[src]

See also

setK

fn set_sigma(&mut self, _sigma: f32) -> Result<()>[src]

Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow.

fn get_sigma(&mut self) -> Result<f32>[src]

See also

setSigma

fn set_lambda(&mut self, _lambda: f32) -> Result<()>[src]

Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.

fn get_lambda(&mut self) -> Result<f32>[src]

See also

setLambda

fn set_use_post_processing(&mut self, _use_post_proc: bool) -> Result<()>[src]

Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.

fn get_use_post_processing(&mut self) -> Result<bool>[src]

See also

setUsePostProcessing

fn set_fgs_lambda(&mut self, _lambda: f32) -> Result<()>[src]

Sets the respective fastGlobalSmootherFilter() parameter.

fn get_fgs_lambda(&mut self) -> Result<f32>[src]

See also

setFGSLambda

fn set_fgs_sigma(&mut self, _sigma: f32) -> Result<()>[src]

See also

setFGSLambda

fn get_fgs_sigma(&mut self) -> Result<f32>[src]

See also

setFGSLambda

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Implementors

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