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#pragma once

#include "colmap/util/eigen_alignment.h"

#include <vector>

#include <Eigen/Core>

namespace colmap {

// Direct linear transformation algorithm to compute the homography between
// point pairs. This algorithm computes the least squares estimate for
// the homography from at least 4 correspondences.
class HomographyMatrixEstimator {
 public:
  using X_t = Eigen::Vector2d;
  using Y_t = Eigen::Vector2d;
  using M_t = Eigen::Matrix3d;

  // The minimum number of samples needed to estimate a model.
  static const int kMinNumSamples = 4;

  // Estimate the projective transformation (homography).
  //
  // The number of corresponding points must be at least 4.
  //
  // @param points1    First set of corresponding points.
  // @param points2    Second set of corresponding points.
  //
  // @return         3x3 homogeneous transformation matrix.
  static void Estimate(const std::vector<X_t>& points1,
                       const std::vector<Y_t>& points2,
                       std::vector<M_t>* models);

  // Calculate the transformation error for each corresponding point pair.
  //
  // Residuals are defined as the squared transformation error when
  // transforming the source to the destination coordinates.
  //
  // @param points1    First set of corresponding points.
  // @param points2    Second set of corresponding points.
  // @param H          3x3 projective matrix.
  // @param residuals  Output vector of residuals.
  static void Residuals(const std::vector<X_t>& points1,
                        const std::vector<Y_t>& points2,
                        const M_t& H,
                        std::vector<double>* residuals);
};

}  // namespace colmap
