pub trait EdgeAwareInterpolator: EdgeAwareInterpolatorConst + SparseMatchInterpolator {
Show 14 methods
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> { ... }
}Required Methods
fn as_raw_mut_EdgeAwareInterpolator(&mut self) -> *mut c_void
Provided Methods
sourcefn set_cost_map(&mut self, _cost_map: &Mat) -> Result<()>
fn set_cost_map(&mut self, _cost_map: &Mat) -> 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
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.
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.
sourcefn set_lambda(&mut self, _lambda: f32) -> Result<()>
fn set_lambda(&mut self, _lambda: f32) -> Result<()>
Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.
sourcefn get_lambda(&mut self) -> Result<f32>
fn get_lambda(&mut self) -> Result<f32>
See also
setLambda
sourcefn set_use_post_processing(&mut self, _use_post_proc: bool) -> Result<()>
fn set_use_post_processing(&mut self, _use_post_proc: bool) -> Result<()>
Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.
sourcefn get_use_post_processing(&mut self) -> Result<bool>
fn get_use_post_processing(&mut self) -> Result<bool>
See also
setUsePostProcessing
sourcefn set_fgs_lambda(&mut self, _lambda: f32) -> Result<()>
fn set_fgs_lambda(&mut self, _lambda: f32) -> Result<()>
Sets the respective fastGlobalSmootherFilter() parameter.
sourcefn get_fgs_lambda(&mut self) -> Result<f32>
fn get_fgs_lambda(&mut self) -> Result<f32>
See also
setFGSLambda
sourcefn get_fgs_sigma(&mut self) -> Result<f32>
fn get_fgs_sigma(&mut self) -> Result<f32>
See also
setFGSLambda