Trait sample_consensus::Consensus

pub trait Consensus<E> where
    E: Estimator, {
    type Inliers: IntoIterator<Item = usize>;
    fn model(
        &mut self, 
        estimator: &E, 
        data: &[EstimatorData<E>]
    ) -> Option<E::Model>;
    fn model_inliers(
        &mut self, 
        estimator: &E, 
        data: &[EstimatorData<E>]
    ) -> Option<(E::Model, Self::Inliers)>;
}

A consensus algorithm extracts a consensus from an underlying model of data. This consensus includes a model of the data and which datapoints fit the model.

Note that all the consensus methods take a &mut self. This allows the consensus to store state such as an RNG or pre-allocted memory. This means multiple threads will be forced to create their own Consensus instance, which is most efficient.

Associated Types

type Inliers: IntoIterator<Item = usize>

Iterator over the indices of the inliers in the clonable iterator.

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Required methods

fn model(
    &mut self,
    estimator: &E,
    data: &[EstimatorData<E>]
) -> Option<E::Model>

Takes a slice over the data and an estimator instance. It returns None if no valid model could be found for the data and Some if a model was found.

fn model_inliers(
    &mut self,
    estimator: &E,
    data: &[EstimatorData<E>]
) -> Option<(E::Model, Self::Inliers)>

Takes a slice over the data and an estimator instance. It returns None if no valid model could be found for the data and Some if a model was found. It includes the inliers consistent with the model.

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Implementors

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