Trait EdgeAwareInterpolatorTrait

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pub trait EdgeAwareInterpolatorTrait: EdgeAwareInterpolatorTraitConst + SparseMatchInterpolatorTrait {
Show 14 methods    // Required method
    fn as_raw_mut_EdgeAwareInterpolator(&mut self) -> *mut c_void;

    // Provided methods
    fn set_cost_map(&mut self, _cost_map: &impl MatTraitConst) -> 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> { ... }
}

Expand description

Mutable methods for crate::ximgproc::EdgeAwareInterpolator

Required Methods§

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

Provided Methods§

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fn set_cost_map(&mut self, _cost_map: &impl MatTraitConst) -> Result<()>

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

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

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.

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

§See also

setK

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

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.

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