/**************************************************************************** * VCGLib o o * * Visual and Computer Graphics Library o o * * _ O _ * * Copyright(C) 2004-2012 \/)\/ * * Visual Computing Lab /\/| * * ISTI - Italian National Research Council | * * \ * * All rights reserved. * * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * * This program 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 General Public License (http://www.gnu.org/licenses/gpl.txt) * * for more details. * * * ****************************************************************************/ /*! \file trimesh_kdtree.cpp \ingroup code_sample \brief An example about using the kdtree and meshes KdTree are one of the Spatial indexing data structure available. They are tailored for storing point-based structures and performing k-neighbours queries. In this simple example we simply compute the average distance of a vertex from its neighbours. \ref spatial_indexing for more Details */ #include #include #include #include #include #include using namespace vcg; using namespace std; class MyEdge; class MyFace; class MyVertex; struct MyUsedTypes : public UsedTypes< Use ::AsVertexType, Use ::AsEdgeType, Use ::AsFaceType>{}; class MyVertex : public Vertex{}; class MyFace : public Face< MyUsedTypes, face::VertexRef, face::BitFlags > {}; class MyEdge : public Edge{}; class MyMesh : public tri::TriMesh< vector, vector , vector > {}; int main( int argc, char **argv ) { if(argc<2) argv[1]="../../meshes/torus_irregular.ply"; MyMesh m; if(tri::io::Importer::Open(m,argv[1])!=0) { printf("Error reading file %s\n",argv[1]); exit(0); } VertexConstDataWrapper ww(m); KdTree tree(ww); KdTree::PriorityQueue queue; for (int j = 0; j < m.VN(); j++) { tree.doQueryK(m.vert[j].cP(), 3, queue); int neighbours = queue.getNofElements(); float avgDist=0; for (int i = 0; i < neighbours; i++) { int neightId = queue.getIndex(i); avgDist += Distance(m.vert[j].cP(),m.vert[neightId].cP()); } m.vert[j].Q() = avgDist/=neighbours; } tri::UpdateColor::PerVertexQualityRamp(m); tri::io::ExporterPLY::Save(m,"out.ply",tri::io::Mask::IOM_VERTCOLOR+tri::io::Mask::IOM_VERTQUALITY); return 0; }