/******************************************************************************
 * Author:   Laurent Kneip                                                    *
 * Contact:  kneip.laurent@gmail.com                                          *
 * License:  Copyright (c) 2013 Laurent Kneip, ANU. All rights reserved.      *
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 * are met:                                                                   *
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 *   documentation and/or other materials provided with the distribution.     *
 * * Neither the name of ANU nor the names of its contributors may be         *
 *   used to endorse or promote products derived from this software without   *
 *   specific prior written permission.                                       *
 *                                                                            *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"*
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#include <stdlib.h>
#include <stdio.h>
#include <iostream>
#include <iomanip>
#include <opengv/relative_pose/methods.hpp>
#include <opengv/relative_pose/CentralRelativeAdapter.hpp>
#include <opengv/sac/Ransac.hpp>
#include <opengv/sac/Lmeds.hpp>
#include <opengv/sac_problems/relative_pose/EigensolverSacProblem.hpp>
#include <sstream>
#include <fstream>

#include "random_generators.hpp"
#include "experiment_helpers.hpp"
#include "time_measurement.hpp"


using namespace std;
using namespace Eigen;
using namespace opengv;

int main( int argc, char** argv )
{
  // initialize random seed
  initializeRandomSeed();

  //set experiment parameters
  double noise = 0.5;
  double outlierFraction = 0.1;
  size_t numberPoints = 100;

  //generate a random pose for viewpoint 1
  translation_t position1 = Eigen::Vector3d::Zero();
  rotation_t rotation1 = Eigen::Matrix3d::Identity();

  //generate a random pose for viewpoint 2
  translation_t position2 = generateRandomDirectionTranslation(0.1);
  rotation_t rotation2 = generateRandomRotation(0.5);

  //create a fake central camera
  translations_t camOffsets;
  rotations_t camRotations;
  generateCentralCameraSystem( camOffsets, camRotations );

  //derive correspondences based on random point-cloud
  bearingVectors_t bearingVectors1;
  bearingVectors_t bearingVectors2;
  std::vector<int> camCorrespondences1; //unused in the central case
  std::vector<int> camCorrespondences2; //unused in the central case
  Eigen::MatrixXd gt(3,numberPoints);
  generateRandom2D2DCorrespondences(
      position1, rotation1, position2, rotation2,
      camOffsets, camRotations, numberPoints, noise, outlierFraction,
      bearingVectors1, bearingVectors2,
      camCorrespondences1, camCorrespondences2, gt );

  //Extract the relative pose
  translation_t position; rotation_t rotation;
  extractRelativePose(
      position1, position2, rotation1, rotation2, position, rotation );

  //print experiment characteristics
  printExperimentCharacteristics( position, rotation, noise, outlierFraction );

  //create a central relative adapter
  relative_pose::CentralRelativeAdapter adapter(
      bearingVectors1,
      bearingVectors2,
      rotation);

  //Create an EigensolverSacProblem and Ransac
  //The number of samples can be configured
  sac::Ransac<
      sac_problems::relative_pose::EigensolverSacProblem> ransac;
  std::shared_ptr<
      sac_problems::relative_pose::EigensolverSacProblem> eigenproblem_ptr(
      new sac_problems::relative_pose::EigensolverSacProblem(adapter,10));
  ransac.sac_model_ = eigenproblem_ptr;
  ransac.threshold_ = 1.0;
  ransac.max_iterations_ = 100;

  //Run the experiment
  struct timeval tic;
  struct timeval toc;
  gettimeofday( &tic, 0 );
  ransac.computeModel();
  gettimeofday( &toc, 0 );
  double ransac_time = TIMETODOUBLE(timeval_minus(toc,tic));

  //do final polishing of the model over all inliers
  sac_problems::relative_pose::EigensolverSacProblem::model_t optimizedModel;
  eigenproblem_ptr->optimizeModelCoefficients(
      ransac.inliers_,
      ransac.model_coefficients_,
      optimizedModel);

  //print the results
  std::cout << "the ransac results is: " << std::endl;
  std::cout << ransac.model_coefficients_.rotation << std::endl << std::endl;
  std::cout << "Ransac needed " << ransac.iterations_ << " iterations and ";
  std::cout << ransac_time << " seconds" << std::endl << std::endl;
  std::cout << "the number of inliers is: " << ransac.inliers_.size();
  std::cout << std::endl << std::endl;
  std::cout << "the found inliers are: " << std::endl;
  for(size_t i = 0; i < ransac.inliers_.size(); i++)
    std::cout << ransac.inliers_[i] << " ";
  std::cout << std::endl << std::endl;
  std::cout << "the optimized result is: " << std::endl;
  std::cout << optimizedModel.rotation << std::endl;

  // Create Lmeds
  sac::Lmeds<sac_problems::relative_pose::EigensolverSacProblem> lmeds;
  lmeds.sac_model_ = eigenproblem_ptr;
  lmeds.threshold_ = 1.0;
  lmeds.max_iterations_ = 50;

  //Run the experiment
  gettimeofday( &tic, 0 );
  lmeds.computeModel();
  gettimeofday( &toc, 0 );
  double lmeds_time = TIMETODOUBLE(timeval_minus(toc,tic));

  //print the results
  std::cout << "the lmeds results is: " << std::endl;
  std::cout << lmeds.model_coefficients_.rotation << std::endl << std::endl;
  std::cout << "lmeds needed " << lmeds.iterations_ << " iterations and ";
  std::cout << lmeds_time << " seconds" << std::endl << std::endl;
  std::cout << "the number of inliers is: " << lmeds.inliers_.size();
  std::cout << std::endl << std::endl;
  std::cout << "the found inliers are: " << std::endl;
  for(size_t i = 0; i < lmeds.inliers_.size(); i++)
    std::cout << lmeds.inliers_[i] << " ";
  std::cout << std::endl << std::endl;
}
