IRansacKernel.hpp

// This file is part of the AliceVision project.
// Copyright (c) 2016 AliceVision contributors.
// This Source Code Form is subject to the terms of the Mozilla Public License,
// v. 2.0. If a copy of the MPL was not distributed with this file,
// You can obtain one at https://mozilla.org/MPL/2.0/.
 
#pragma once
 
#include <aliceVision/numeric/numeric.hpp>
 
#include <vector>
 
namespace aliceVision {
namespace robustEstimation {
 
template<typename ModelT>
class IRansacKernel
{
  public:
    virtual std::size_t getMinimumNbRequiredSamples() const = 0;
 
    virtual std::size_t getMinimumNbRequiredSamplesLS() const = 0;
 
    virtual std::size_t getMaximumNbModels() const = 0;
 
    virtual void fit(const std::vector<std::size_t>& samples, std::vector<ModelT>& models) const = 0;
 
    virtual void fitLS(const std::vector<std::size_t>& inliers, std::vector<ModelT>& models, const std::vector<double>* weights = nullptr) const = 0;
 
    virtual void computeWeights(const ModelT& model,
                                const std::vector<std::size_t>& inliers,
                                std::vector<double>& weights,
                                const double eps = 0.001) const = 0;
 
    virtual double error(std::size_t sample, const ModelT& model) const = 0;
 
    virtual void errors(const ModelT& model, std::vector<double>& errors) const = 0;
 
    virtual void unnormalize(ModelT& model) const = 0;
 
    virtual std::size_t nbSamples() const = 0;
 
    virtual double logalpha0() const = 0;
 
    virtual double errorVectorDimension() const = 0;
    virtual double unormalizeError(double val) const = 0;
    virtual Mat3 normalizer1() const = 0;
    virtual double thresholdNormalizer() const = 0;
};
 
}  // namespace robustEstimation
}  // namespace aliceVision