/*************************************************************************** * Copyright (c) 2016 Werner Mayer * * * * This file is part of the FreeCAD CAx development system. * * * * This library is free software; you can redistribute it and/or * * modify it under the terms of the GNU Library General Public * * License as published by the Free Software Foundation; either * * version 2 of the License, or (at your option) any later version. * * * * This library is distributed in the hope that it will be useful, * * but WITHOUT ANY WARRANTY; without even the implied warranty of * * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * * GNU Library General Public License for more details. * * * * You should have received a copy of the GNU Library General Public * * License along with this library; see the file COPYING.LIB. If not, * * write to the Free Software Foundation, Inc., 59 Temple Place, * * Suite 330, Boston, MA 02111-1307, USA * * * ***************************************************************************/ #include "PreCompiled.h" #include "SampleConsensus.h" #include #include #include #if defined(HAVE_PCL_SAMPLE_CONSENSUS) #include #include #include using namespace std; using namespace Reen; using pcl::PointXYZ; using pcl::PointNormal; using pcl::PointCloud; SampleConsensus::SampleConsensus(const Points::PointKernel& pts) : myPoints(pts) { } double SampleConsensus::perform(std::vector& parameters) { pcl::PointCloud::Ptr cloud (new pcl::PointCloud); cloud->reserve(myPoints.size()); for (Points::PointKernel::const_iterator it = myPoints.begin(); it != myPoints.end(); ++it) { if (!boost::math::isnan(it->x) && !boost::math::isnan(it->y) && !boost::math::isnan(it->z)) cloud->push_back(pcl::PointXYZ(it->x, it->y, it->z)); } cloud->width = int (cloud->points.size ()); cloud->height = 1; cloud->is_dense = true; // created RandomSampleConsensus object and compute the appropriated model pcl::SampleConsensusModelPlane::Ptr model_p (new pcl::SampleConsensusModelPlane (cloud)); pcl::RandomSampleConsensus ransac (model_p); ransac.setDistanceThreshold (.01); ransac.computeModel(); //ransac.getInliers(inliers); //ransac.getModel (model); Eigen::VectorXf model_p_coefficients; ransac.getModelCoefficients (model_p_coefficients); for (int i=0; i