DenseRLOFOpticalFlowTrait

opencv::optflow

Trait DenseRLOFOpticalFlowTrait 

Source 
pub trait DenseRLOFOpticalFlowTrait: DenseRLOFOpticalFlowTraitConst + DenseOpticalFlowTrait {

Show 14 methods    // Required method
    fn as_raw_mut_DenseRLOFOpticalFlow(&mut self) -> *mut c_void;

    // Provided methods
    fn set_rlof_optical_flow_parameter(
        &mut self,
        val: Ptr<RLOFOpticalFlowParameter>,
    ) -> Result<()> { ... }
    fn set_forward_backward(&mut self, val: f32) -> Result<()> { ... }
    fn set_grid_step(&mut self, val: Size) -> Result<()> { ... }
    fn set_interpolation(&mut self, val: InterpolationType) -> Result<()> { ... }
    fn set_epick(&mut self, val: i32) -> Result<()> { ... }
    fn set_epic_sigma(&mut self, val: f32) -> Result<()> { ... }
    fn set_epic_lambda(&mut self, val: f32) -> Result<()> { ... }
    fn set_fgs_lambda(&mut self, val: f32) -> Result<()> { ... }
    fn set_fgs_sigma(&mut self, val: f32) -> Result<()> { ... }
    fn set_use_post_proc(&mut self, val: bool) -> Result<()> { ... }
    fn set_use_variational_refinement(&mut self, val: bool) -> Result<()> { ... }
    fn set_ricsp_size(&mut self, val: i32) -> Result<()> { ... }
    fn set_ricslic_type(&mut self, val: i32) -> Result<()> { ... }

}
Expand description

Mutable methods for crate::optflow::DenseRLOFOpticalFlow

Required Methods§

Source

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

Provided Methods§

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fn set_rlof_optical_flow_parameter( &mut self, val: Ptr<RLOFOpticalFlowParameter>, ) -> Result<()>

Configuration of the RLOF alogrithm.

§See also

optflow::RLOFOpticalFlowParameter, getRLOFOpticalFlowParameter

Source

fn set_forward_backward(&mut self, val: f32) -> Result<()>

Threshold for the forward backward confidence check For each grid point inline formula a motion vector inline formula is computed. * If the forward backward error block formula * is larger than threshold given by this function then the motion vector will not be used by the following * vector field interpolation. inline formula denotes the backward flow. Note, the forward backward test * will only be applied if the threshold > 0. This may results into a doubled runtime for the motion estimation. * see also: getForwardBackward, setGridStep

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fn set_grid_step(&mut self, val: Size) -> Result<()>

Size of the grid to spawn the motion vectors. For each grid point a motion vector is computed. Some motion vectors will be removed due to the forwatd backward * threshold (if set >0). The rest will be the base of the vector field interpolation. * getForwardBackward, setGridStep

§See also

getGridStep

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fn set_interpolation(&mut self, val: InterpolationType) -> Result<()>

Interpolation used to compute the dense optical flow. Two interpolation algorithms are supported * - INTERP_GEO applies the fast geodesic interpolation, see Geistert2016. * - INTERP_EPIC_RESIDUAL applies the edge-preserving interpolation, see Revaud2015,Geistert2016. * see also: ximgproc::EdgeAwareInterpolator, getInterpolation

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fn set_epick(&mut self, val: i32) -> Result<()>

see ximgproc::EdgeAwareInterpolator() K value. 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. * ximgproc::EdgeAwareInterpolator, setEPICK

§See also

ximgproc::EdgeAwareInterpolator, getEPICK

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fn set_epic_sigma(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator() sigma value. 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. * ximgproc::EdgeAwareInterpolator, setEPICSigma

§See also

ximgproc::EdgeAwareInterpolator, getEPICSigma

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fn set_epic_lambda(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator() lambda value. Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, * should be in the range of 0 to 1000. * ximgproc::EdgeAwareInterpolator, setEPICSigma

§See also

ximgproc::EdgeAwareInterpolator, getEPICLambda

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fn set_fgs_lambda(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator(). Sets the respective fastGlobalSmootherFilter() parameter. * ximgproc::EdgeAwareInterpolator, setFgsLambda

§See also

ximgproc::EdgeAwareInterpolator, ximgproc::fastGlobalSmootherFilter, getFgsLambda

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fn set_fgs_sigma(&mut self, val: f32) -> Result<()>

see ximgproc::EdgeAwareInterpolator(). Sets the respective fastGlobalSmootherFilter() parameter. * ximgproc::EdgeAwareInterpolator, ximgproc::fastGlobalSmootherFilter, setFgsSigma

§See also

ximgproc::EdgeAwareInterpolator, ximgproc::fastGlobalSmootherFilter, getFgsSigma

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

enables ximgproc::fastGlobalSmootherFilter

  • see also: getUsePostProc
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fn set_use_variational_refinement(&mut self, val: bool) -> Result<()>

enables VariationalRefinement

  • see also: getUseVariationalRefinement
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fn set_ricsp_size(&mut self, val: i32) -> Result<()>

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

  • see also: cv::ximgproc::createSuperpixelSLIC, cv::ximgproc::RICInterpolator
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fn set_ricslic_type(&mut self, val: i32) -> Result<()>

Parameter to choose superpixel algorithm variant to use:

  • cv::ximgproc::SLICType SLIC segments image using a desired region_size (value: 100)
  • cv::ximgproc::SLICType SLICO will optimize using adaptive compactness factor (value: 101)
  • cv::ximgproc::SLICType MSLIC will optimize using manifold methods resulting in more content-sensitive superpixels (value: 102).
§See also

cv::ximgproc::createSuperpixelSLIC, cv::ximgproc::RICInterpolator

Dyn Compatibility§

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors§