testPoseRansac2.cpp

/****************************************************************************
 *
 * This file is part of the ViSP software.
 * Copyright (C) 2005 - 2017 by Inria. All rights reserved.
 *
 * This software is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License
 * ("GPL") version 2 as published by the Free Software Foundation.
 * See the file LICENSE.txt at the root directory of this source
 * distribution for additional information about the GNU GPL.
 *
 * For using ViSP with software that can not be combined with the GNU
 * GPL, please contact Inria about acquiring a ViSP Professional
 * Edition License.
 *
 * See http://visp.inria.fr for more information.
 *
 * This software was developed at:
 * Inria Rennes - Bretagne Atlantique
 * Campus Universitaire de Beaulieu
 * 35042 Rennes Cedex
 * France
 *
 * If you have questions regarding the use of this file, please contact
 * Inria at visp@inria.fr
 *
 * This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
 * WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
 *
 * Description:
 * Compute the pose of a 3D object using the RANSAC method.
 *
 * Author:
 * Souriya Trinh
 *
 *****************************************************************************/

#include <iomanip>
#include <sstream>
#include <algorithm>
#include <map>
#include <visp3/vision/vpPose.h>
#include <visp3/core/vpPoint.h>
#include <visp3/core/vpMath.h>
#include <visp3/core/vpGaussRand.h>
#include <visp3/core/vpHomogeneousMatrix.h>

//Stanford Bunny Model points
const std::string file_content =
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    "-0.080437 0.137229 0.049095 "
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bool samePoints(const vpPoint &pt1, const vpPoint &pt2) {
  return vpMath::equal(pt1.get_oX(), pt2.get_oX(), std::numeric_limits<double>::epsilon()) &&
      vpMath::equal(pt1.get_oY(), pt2.get_oY(), std::numeric_limits<double>::epsilon()) &&
      vpMath::equal(pt1.get_oZ(), pt2.get_oZ(), std::numeric_limits<double>::epsilon()) &&
      vpMath::equal(pt1.get_x(), pt2.get_x(), std::numeric_limits<double>::epsilon()) &&
      vpMath::equal(pt1.get_y(), pt2.get_y(), std::numeric_limits<double>::epsilon());
}

int checkInlierIndex(const std::vector<unsigned int> &vectorOfFoundInlierIndex, const std::vector<bool> &vectorOfOutlierFlags) {
  int nbInlierIndexOk = 0;

  for(std::vector<unsigned int>::const_iterator it = vectorOfFoundInlierIndex.begin();
      it != vectorOfFoundInlierIndex.end(); ++it) {
    if(!vectorOfOutlierFlags[*it]) {
      nbInlierIndexOk++;
    }
  }

  return nbInlierIndexOk;
}

bool checkInlierPoints(const std::vector<vpPoint> &vectorOfFoundInlierPoints, const std::vector<unsigned int> &vectorOfFoundInlierIndex,
                       const std::vector<vpPoint> &bunnyModelPoints_noisy) {
  for(size_t i = 0; i < vectorOfFoundInlierPoints.size(); i++) {
    if(!samePoints(vectorOfFoundInlierPoints[i], bunnyModelPoints_noisy[vectorOfFoundInlierIndex[i]])) {
      std::cerr << "Problem with the inlier index and the corresponding inlier point !" << std::endl;
      return false;
    }
  }

  return true;
}

void readBunnyModelPoints(std::vector<vpPoint> &bunnyModelPoints, std::vector<vpPoint> &bunnyModelPoints_noisy) {
  //Read the string
  std::istringstream iss_file_content(file_content);

//  vpTranslationVector translation(-0.1, 0.15, 1.0);
  vpTranslationVector translation(-0.14568, 0.154567, 1.4462);
//  vpRzyxVector zyxVector(vpMath::rad(10.0f), vpMath::rad(-15.0f), vpMath::rad(38.0f));
  vpRzyxVector zyxVector(vpMath::rad(12.4146f), vpMath::rad(-75.5478f), vpMath::rad(138.5607f));
  vpThetaUVector thetau(zyxVector);

  vpHomogeneousMatrix cMo_groundTruth(translation, thetau);

  vpGaussRand gaussian_noise(0.0002, 0.0/*, time(NULL)*/);
  while (iss_file_content) {
    double oX, oY, oZ;
    iss_file_content >> oX >> oY >> oZ;

    vpPoint pt(oX, oY, oZ);
    pt.project(cMo_groundTruth);
    bunnyModelPoints.push_back(pt);

    //Add a small gaussian noise to data to be a little more realistic
    pt.set_x(pt.get_x() + gaussian_noise());
    pt.set_y(pt.get_y() + gaussian_noise());
    bunnyModelPoints_noisy.push_back(pt);
  }

  //Print the number of model points
  std::cout << "The raw model contains " << bunnyModelPoints.size() << " points." << std::endl;
  std::cout << "cMo_groundTruth=\n" << cMo_groundTruth << std::endl << std::endl;
}

bool testRansac(const std::vector<vpPoint> &bunnyModelPoints_original, const std::vector<vpPoint> &bunnyModelPoints_noisy_original,
                const size_t nb_model_points, const bool test_duplicate, const bool test_degenerate) {
  std::vector<vpPoint> bunnyModelPoints = bunnyModelPoints_original;
  std::vector<vpPoint> bunnyModelPoints_noisy = bunnyModelPoints_noisy_original;
  //Resize
  if (nb_model_points > 0) {
    bunnyModelPoints.resize(nb_model_points);
    bunnyModelPoints_noisy.resize(nb_model_points);
  }

  vpPose ground_truth_pose, real_pose;
  ground_truth_pose.addPoints(bunnyModelPoints);
  real_pose.addPoints(bunnyModelPoints_noisy);

  vpHomogeneousMatrix cMo_dementhon, cMo_lagrange;
  real_pose.computePose(vpPose::DEMENTHON, cMo_dementhon);
  real_pose.computePose(vpPose::LAGRANGE, cMo_lagrange);
  double r_dementhon = real_pose.computeResidual(cMo_dementhon);
  double r_lagrange = real_pose.computeResidual(cMo_lagrange);

  vpHomogeneousMatrix cMo_estimated;
  if(r_lagrange < r_dementhon) {
    cMo_estimated = cMo_lagrange;
  } else {
    cMo_estimated = cMo_dementhon;
  }
  real_pose.computePose(vpPose::VIRTUAL_VS, cMo_estimated);
  double r_vvs = ground_truth_pose.computeResidual(cMo_estimated);

  std::cout << "\ncMo estimated using VVS on data with small gaussian noise:\n" << cMo_estimated << std::endl;
  std::cout << "Corresponding residual: " << r_vvs << std::endl;


  size_t nbOutliers = (size_t) (0.35 * bunnyModelPoints_noisy.size());
  vpGaussRand noise(0.01, 0.008/*, time(NULL)*/);
  //Vector that indicates if the point is an outlier or not
  std::vector<bool> vectorOfOutlierFlags(bunnyModelPoints_noisy.size(), false);
  //Generate outliers points
  for(size_t i = 0; i < nbOutliers; i++) {
    bunnyModelPoints_noisy[i].set_x(bunnyModelPoints_noisy[i].get_x() + noise());
    bunnyModelPoints_noisy[i].set_y(bunnyModelPoints_noisy[i].get_y() + noise());
    vectorOfOutlierFlags[i] = true;
  }

  if (test_duplicate) {
    //Add some duplicate points
    size_t nbDuplicatePoints = 100;
    for (size_t i = 0; i < nbDuplicatePoints; i++) {
      size_t index = (size_t) rand() % bunnyModelPoints_noisy.size();
      vpPoint duplicatePoint = bunnyModelPoints_noisy[index];
      bunnyModelPoints_noisy.push_back(duplicatePoint);
      vectorOfOutlierFlags.push_back(true);
    }
  }

  if (test_degenerate) {
    //Add some degenerate points
    size_t nbDegeneratePoints = 100;
    double degenerate_tolerence = 9.999e-7; //1e-6 is used in the code to detect if a point is degenerate or not
    std::vector<vpPoint> listOfDegeneratePoints;
    for(size_t i = 0; i < nbDegeneratePoints; i++) {
      size_t index = (size_t) rand() % bunnyModelPoints_noisy.size();
      vpPoint degeneratePoint = bunnyModelPoints_noisy[index];

      //Object point is degenerate
      degeneratePoint.set_oX(degeneratePoint.get_oX() + degenerate_tolerence);
      degeneratePoint.set_oY(degeneratePoint.get_oY() + degenerate_tolerence);
      degeneratePoint.set_oZ(degeneratePoint.get_oZ() - degenerate_tolerence);

      //Add duplicate 3D points
      listOfDegeneratePoints.push_back(degeneratePoint);


      //Image point is degenerate
      index = (size_t) rand() % bunnyModelPoints_noisy.size();
      degeneratePoint = bunnyModelPoints_noisy[index];

      degeneratePoint.set_x(degeneratePoint.get_x() + degenerate_tolerence);
      degeneratePoint.set_y(degeneratePoint.get_y() - degenerate_tolerence);

      //Add duplicate 2D points
      listOfDegeneratePoints.push_back(degeneratePoint);
    }

    for (std::vector<vpPoint>::const_iterator it_degenerate = listOfDegeneratePoints.begin();
         it_degenerate != listOfDegeneratePoints.end(); ++it_degenerate) {
      bunnyModelPoints_noisy.push_back(*it_degenerate);
      vectorOfOutlierFlags.push_back(true);
    }
  }

  //Shuffle the data vector
  std::vector<size_t> vectorOfIndex(bunnyModelPoints_noisy.size());
  for(size_t i = 0; i < vectorOfIndex.size(); i++) {
    vectorOfIndex[i] = i;
  }
  std::random_shuffle(vectorOfIndex.begin(), vectorOfIndex.end());

  std::vector<vpPoint> bunnyModelPoints_noisy_tmp = bunnyModelPoints_noisy;
  bunnyModelPoints_noisy.clear();
  std::vector<bool> vectorOfOutlierFlags_tmp = vectorOfOutlierFlags;
  vectorOfOutlierFlags.clear();
  for(std::vector<size_t>::const_iterator it = vectorOfIndex.begin(); it != vectorOfIndex.end(); ++it) {
    bunnyModelPoints_noisy.push_back(bunnyModelPoints_noisy_tmp[*it]);
    vectorOfOutlierFlags.push_back(vectorOfOutlierFlags_tmp[*it]);
  }

  //Add data to vpPose
  vpPose pose;
  vpPose pose_ransac, pose_ransac2;

#if defined (VISP_HAVE_PTHREAD) || (defined (_WIN32) && !defined(WINRT_8_0)) || defined (VISP_HAVE_OPENMP)
#  define TEST_PARALLEL_RANSAC
#endif

#ifdef TEST_PARALLEL_RANSAC
  vpPose pose_ransac_parallel, pose_ransac_parallel2;
  pose_ransac_parallel.setUseParallelRansac(true);
  pose_ransac_parallel2.setUseParallelRansac(true);

  pose_ransac_parallel.setRansacFilterFlags(vpPose::PREFILTER_DUPLICATE_POINTS + vpPose::CHECK_DEGENERATE_POINTS);
  pose_ransac_parallel2.setRansacFilterFlags(vpPose::PREFILTER_DUPLICATE_POINTS + vpPose::CHECK_DEGENERATE_POINTS);

#if !defined (VISP_HAVE_OPENMP)
  pose_ransac_parallel.setNbParallelRansacThreads(2);
  pose_ransac_parallel2.setNbParallelRansacThreads(2);
#endif
#endif
  pose_ransac.setRansacFilterFlags(vpPose::PREFILTER_DUPLICATE_POINTS + vpPose::CHECK_DEGENERATE_POINTS);
  pose_ransac2.setRansacFilterFlags(vpPose::PREFILTER_DUPLICATE_POINTS + vpPose::CHECK_DEGENERATE_POINTS);
  for(std::vector<vpPoint>::const_iterator it = bunnyModelPoints_noisy.begin();
      it != bunnyModelPoints_noisy.end(); ++it) {
    pose.addPoint(*it);
  }
  //Test addPoints
  pose_ransac.addPoints(bunnyModelPoints_noisy);
  pose_ransac2.addPoints(bunnyModelPoints_noisy);
#ifdef TEST_PARALLEL_RANSAC
  pose_ransac_parallel.addPoints(bunnyModelPoints_noisy);
  pose_ransac_parallel2.addPoints(bunnyModelPoints_noisy);
#endif

  //Print the number of points in the final data vector
  std::cout << "\nNumber of model points in the noisy data vector: "
            << bunnyModelPoints_noisy.size() << " points." << std::endl << std::endl;

  unsigned int nbInlierToReachConsensus = (unsigned int)(60.0 * (double)(bunnyModelPoints_noisy.size()) / 100.0);
  double threshold = 0.001;

  //RANSAC with 1000 iterations
  pose_ransac.setRansacNbInliersToReachConsensus(nbInlierToReachConsensus);
  pose_ransac.setRansacThreshold(threshold);
  pose_ransac.setRansacMaxTrials(1000);
#ifdef TEST_PARALLEL_RANSAC
  pose_ransac_parallel.setRansacNbInliersToReachConsensus(nbInlierToReachConsensus);
  pose_ransac_parallel.setRansacThreshold(threshold);
  pose_ransac_parallel.setRansacMaxTrials(1000);

  pose_ransac_parallel2.setRansacNbInliersToReachConsensus(nbInlierToReachConsensus);
  pose_ransac_parallel2.setRansacThreshold(threshold);
  pose_ransac_parallel2.setRansacMaxTrials(vpPose::computeRansacIterations(0.99, 0.4, 4, -1));
#endif

  //RANSAC with p=0.99, epsilon=0.4
  pose_ransac2.setRansacNbInliersToReachConsensus(nbInlierToReachConsensus);
  pose_ransac2.setRansacThreshold(threshold);
  int ransac_iterations = vpPose::computeRansacIterations(0.99, 0.4, 4, -1);
  pose_ransac2.setRansacMaxTrials(ransac_iterations);
  std::cout << "Number of RANSAC iterations to ensure p=0.99 and epsilon=0.4: " << ransac_iterations << std::endl;

  vpHomogeneousMatrix cMo_estimated_RANSAC;
  double t_RANSAC = vpTime::measureTimeMs();
  pose_ransac.computePose(vpPose::RANSAC, cMo_estimated_RANSAC);
  t_RANSAC = vpTime::measureTimeMs() - t_RANSAC;

  std::cout << "\ncMo estimated with RANSAC (1000 iterations) on noisy data:\n" << cMo_estimated_RANSAC << std::endl;
  std::cout << "Computation time: " << t_RANSAC << " ms" << std::endl;

  double r_RANSAC_estimated = ground_truth_pose.computeResidual(cMo_estimated_RANSAC);
  std::cout << "Corresponding residual (1000 iterations): " << r_RANSAC_estimated << std::endl;

  vpHomogeneousMatrix cMo_estimated_RANSAC_2;
  t_RANSAC = vpTime::measureTimeMs();
  pose_ransac2.computePose(vpPose::RANSAC, cMo_estimated_RANSAC_2);
  t_RANSAC = vpTime::measureTimeMs() - t_RANSAC;

  std::cout << "\ncMo estimated with RANSAC (" << ransac_iterations << " iterations) on noisy data:\n"
            << cMo_estimated_RANSAC_2 << std::endl;
  std::cout << "Computation time: " << t_RANSAC << " ms" << std::endl;

  double r_RANSAC_estimated_2 = ground_truth_pose.computeResidual(cMo_estimated_RANSAC_2);
  std::cout << "Corresponding residual (" << ransac_iterations << " iterations): " << r_RANSAC_estimated_2 << std::endl;


  pose.computePose(vpPose::DEMENTHON, cMo_dementhon);
  pose.computePose(vpPose::LAGRANGE, cMo_lagrange);
  r_dementhon = pose.computeResidual(cMo_dementhon);
  r_lagrange = pose.computeResidual(cMo_lagrange);

  if(r_lagrange < r_dementhon) {
    cMo_estimated = cMo_lagrange;
  } else {
    cMo_estimated = cMo_dementhon;
  }

  pose.computePose(vpPose::VIRTUAL_VS, cMo_estimated);
  std::cout << "\ncMo estimated with only VVS on noisy data:\n" << cMo_estimated << std::endl;

  double r_estimated = ground_truth_pose.computeResidual(cMo_estimated);
  std::cout << "Corresponding residual: " << r_estimated << std::endl;

#ifdef TEST_PARALLEL_RANSAC
  vpHomogeneousMatrix cMo_estimated_RANSAC_parallel;
  double t_RANSAC_parallel = vpTime::measureTimeMs();
  pose_ransac_parallel.computePose(vpPose::RANSAC, cMo_estimated_RANSAC_parallel);
  t_RANSAC_parallel = vpTime::measureTimeMs() - t_RANSAC_parallel;

  std::cout << "\ncMo estimated with parallel RANSAC (1000 iterations) on noisy data:\n" << cMo_estimated_RANSAC_parallel << std::endl;
  std::cout << "Computation time: " << t_RANSAC_parallel << " ms" << std::endl;

  double r_RANSAC_estimated_parallel = ground_truth_pose.computeResidual(cMo_estimated_RANSAC_parallel);
  std::cout << "Corresponding residual (1000 iterations): " << r_RANSAC_estimated_parallel << std::endl;

  vpHomogeneousMatrix cMo_estimated_RANSAC_parallel2;
  double t_RANSAC_parallel2 = vpTime::measureTimeMs();
  pose_ransac_parallel2.computePose(vpPose::RANSAC, cMo_estimated_RANSAC_parallel2);
  t_RANSAC_parallel2 = vpTime::measureTimeMs() - t_RANSAC_parallel2;

  std::cout << "\ncMo estimated with parallel RANSAC (" << ransac_iterations << " iterations) on noisy data:\n" << cMo_estimated_RANSAC_parallel2 << std::endl;
  std::cout << "Computation time: " << t_RANSAC_parallel2 << " ms" << std::endl;

  double r_RANSAC_estimated_parallel2 = ground_truth_pose.computeResidual(cMo_estimated_RANSAC_parallel2);
  std::cout << "Corresponding residual (" << ransac_iterations << " iterations): " << r_RANSAC_estimated_parallel2 << std::endl;
#endif


  //Check inlier index
  std::vector<unsigned int> vectorOfFoundInlierIndex = pose_ransac.getRansacInlierIndex();
  int nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex, vectorOfOutlierFlags);

  int nbTrueInlierIndex = (int) std::count(vectorOfOutlierFlags.begin(), vectorOfOutlierFlags.end(), false);
  std::cout << "\nThere are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex.size()
            << " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;

  //Check inlier points returned
  std::vector<vpPoint> vectorOfFoundInlierPoints = pose_ransac.getRansacInliers();

  if(vectorOfFoundInlierPoints.size() != vectorOfFoundInlierIndex.size()) {
    std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
    return false;
  }
  if (!checkInlierPoints(vectorOfFoundInlierPoints, vectorOfFoundInlierIndex, bunnyModelPoints_noisy)) {
    return false;
  }


  //Check for RANSAC with p=0.99, epsilon=0.4
  //Check inlier index
  std::cout << "\nCheck for RANSAC iterations: " << ransac_iterations << std::endl;
  std::vector<unsigned int> vectorOfFoundInlierIndex_2 = pose_ransac2.getRansacInlierIndex();
  nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex_2, vectorOfOutlierFlags);

  std::cout << "There are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex_2.size()
            << " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;

  //Check inlier points returned
  std::vector<vpPoint> vectorOfFoundInlierPoints_2 = pose_ransac2.getRansacInliers();
  if(vectorOfFoundInlierPoints_2.size() != vectorOfFoundInlierIndex_2.size()) {
    std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
    return false;
  }
  if (!checkInlierPoints(vectorOfFoundInlierPoints_2, vectorOfFoundInlierIndex_2, bunnyModelPoints_noisy)) {
    return false;
  }


#ifdef TEST_PARALLEL_RANSAC
  //Check for parallel RANSAC
  //Check inlier index
  std::cout << "\nCheck for parallel RANSAC (1000 iterations)" << std::endl;
  std::vector<unsigned int> vectorOfFoundInlierIndex_parallel = pose_ransac_parallel.getRansacInlierIndex();
  nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex_parallel, vectorOfOutlierFlags);

  std::cout << "There are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex_parallel.size()
            << " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;

  //Check inlier points returned
  std::vector<vpPoint> vectorOfFoundInlierPoints_parallel = pose_ransac_parallel.getRansacInliers();
  if(vectorOfFoundInlierPoints_parallel.size() != vectorOfFoundInlierIndex_parallel.size()) {
    std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
    return false;
  }
  if (!checkInlierPoints(vectorOfFoundInlierPoints_parallel, vectorOfFoundInlierIndex_parallel, bunnyModelPoints_noisy)) {
    return false;
  }

  //Check for parallel RANSAC 2
  //Check inlier index
  std::cout << "\nCheck for parallel RANSAC (" << ransac_iterations << " iterations)" << std::endl;
  std::vector<unsigned int> vectorOfFoundInlierIndex_parallel2 = pose_ransac_parallel2.getRansacInlierIndex();
  nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex_parallel2, vectorOfOutlierFlags);

  std::cout << "There are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex_parallel2.size()
            << " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;

  //Check inlier points returned
  std::vector<vpPoint> vectorOfFoundInlierPoints_parallel2 = pose_ransac_parallel2.getRansacInliers();
  if(vectorOfFoundInlierPoints_parallel2.size() != vectorOfFoundInlierIndex_parallel2.size()) {
    std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
    return false;
  }
  if (!checkInlierPoints(vectorOfFoundInlierPoints_parallel2, vectorOfFoundInlierIndex_parallel2, bunnyModelPoints_noisy)) {
    return false;
  }
#endif


  if(r_RANSAC_estimated > threshold /*|| r_RANSAC_estimated_2 > threshold*/) {
    std::cerr << "The pose estimated with the RANSAC method is badly estimated!" << std::endl;
    std::cerr << "r_RANSAC_estimated=" << r_RANSAC_estimated << std::endl;
    std::cerr << "threshold=" << threshold << std::endl;
    return false;
  } else {
#ifdef TEST_PARALLEL_RANSAC
    if (r_RANSAC_estimated_parallel > threshold) {
      std::cerr << "The pose estimated with the parallel RANSAC method is badly estimated!" << std::endl;
      std::cerr << "r_RANSAC_estimated_parallel=" << r_RANSAC_estimated_parallel << std::endl;
      std::cerr << "threshold=" << threshold << std::endl;
      return false;
    }
    #endif
    std::cout << "The pose estimated with the RANSAC method is well estimated!" << std::endl;
  }

  return true;
}

int main() {
  //vpPose::computeRansacIterations
  int sample_sizes[] = {2, 3, 4, 5, 6, 7, 8};
  double epsilon[] = {0.05, 0.1, 0.2, 0.25, 0.3, 0.4, 0.5};

  //Format output
  std::cout << "       ";
  for (int cpt2 = 0; cpt2 < 7; cpt2++) {
    std::cout << std::setfill(' ') << std::setw(5) << epsilon[cpt2] << " ";
  }
  std::cout << std::endl;

  std::cout << std::setfill(' ') << std::setw(7) << "+";
  for (int cpt2 = 0; cpt2 < 6; cpt2++) {
    std::cout << std::setw(7) << "-------";
  }
  std::cout << std::endl;

  for (int cpt1 = 0; cpt1 < 7; cpt1++) {
    std::cout << std::setfill(' ') << std::setw(6) << sample_sizes[cpt1] << "|";

    for (int cpt2 = 0; cpt2 < 7; cpt2++) {
      int ransac_iters = vpPose::computeRansacIterations(0.99, epsilon[cpt2], sample_sizes[cpt1], -1);
      std::cout << std::setfill(' ') << std::setw(6) << ransac_iters;
    }
    std::cout << std::endl;
  }
  std::cout << std::endl;

  try {
    size_t model_sizes[] = {10, 20, 50, 100, 200, 500, 1000, 0, 0};
    bool duplicates[] = {false, false, false, false, false, false, false, false, true};
    bool degenerates[] = {false, false, false, false, false, false, true, true, true};
    int nb = 9;

    std::vector<vpPoint> bunnyModelPoints, bunnyModelPoints_noisy_original;
    readBunnyModelPoints(bunnyModelPoints, bunnyModelPoints_noisy_original);

    for (int cpt = 0; cpt < nb; cpt++) {
      std::cout << "\n\n====================================================================" << std::endl;
      if (model_sizes[cpt] == 0) {
        std::cout << "Test on " << bunnyModelPoints_noisy_original.size() << " model points." << std::endl;
      } else {
        std::cout << "Test on " << model_sizes[cpt] << " model points." << std::endl;
      }
      std::cout << "Test duplicate: " << duplicates[cpt] << " ; Test degenerate: " << degenerates[cpt] << std::endl;

      if ( !testRansac(bunnyModelPoints, bunnyModelPoints_noisy_original, model_sizes[cpt], duplicates[cpt], degenerates[cpt]) ) {
        return EXIT_FAILURE;
      }
    }

    std::cout << "\n\ntestPoseRansac2 is ok!" << std::endl;
    return EXIT_SUCCESS;
  }
  catch(vpException &e) {
    std::cout << "Catch an exception: " << e << std::endl;
    return EXIT_FAILURE;
  }
}