/** * * Copyright (C) Jacobs University Bremen * * @author Vaibhav Kumar Mehta * @file calc_normals.cc */ #include #include #include #include #include #include #include #include #include "slam6d/fbr/panorama.h" #include #include #ifdef _MSC_VER #define strcasecmp _stricmp #define strncasecmp _strnicmp #else #include #endif namespace po = boost::program_options; using namespace std; enum normal_method {AKNN, ADAPTIVE_AKNN, PANORAMA, PANORAMA_FAST}; /* * validates normal calculation method specification */ void validate(boost::any& v, const std::vector& values, normal_method*, int) { if (values.size() == 0) throw std::runtime_error("Invalid model specification"); string arg = values.at(0); if(strcasecmp(arg.c_str(), "AKNN") == 0) v = AKNN; else if(strcasecmp(arg.c_str(), "ADAPTIVE_AKNN") == 0) v = ADAPTIVE_AKNN; else if(strcasecmp(arg.c_str(), "PANORAMA") == 0) v = PANORAMA; else if(strcasecmp(arg.c_str(), "PANORAMA_FAST") == 0) v = PANORAMA_FAST; else throw std::runtime_error(std::string("normal calculation method ") + arg + std::string(" is unknown")); } /// validate IO types void validate(boost::any& v, const std::vector& values, IOType*, int) { if (values.size() == 0) throw std::runtime_error("Invalid model specification"); string arg = values.at(0); try { v = formatname_to_io_type(arg.c_str()); } catch (...) { // runtime_error throw std::runtime_error("Format " + arg + " unknown."); } } /// Parse commandline options void parse_options(int argc, char **argv, int &start, int &end, bool &scanserver, int &max_dist, int &min_dist, string &dir, IOType &iotype, int &k1, int &k2, normal_method &ntype,int &width,int &height) { /// ---------------------------------- /// set up program commandline options /// ---------------------------------- po::options_description cmd_options("Usage: calculateNormals where options are (default values in brackets)"); cmd_options.add_options() ("help,?", "Display this help message") ("start,s", po::value(&start)->default_value(0), "Start at scan number ") ("end,e", po::value(&end)->default_value(-1), "Stop at scan number ") ("scanserver,S", po::value(&scanserver)->default_value(false), "Use the scanserver as an input method") ("format,f", po::value(&iotype)->default_value(UOS), "using shared library for input. (chose format from [uos|uosr|uos_map|" "uos_rgb|uos_frames|uos_map_frames|old|rts|rts_map|ifp|" "riegl_txt|riegl_rgb|riegl_bin|zahn|ply])") ("max,M", po::value(&max_dist)->default_value(-1),"neglegt all data points with a distance larger than 'units") ("min,m", po::value(&min_dist)->default_value(-1),"neglegt all data points with a distance smaller than 'units") ("normal,g", po::value(&ntype)->default_value(AKNN), "normal calculation method " "(AKNN, ADAPTIVE_AKNN, PANORAMA, PANORAMA_FAST)") ("K1,k", po::value(&k1)->default_value(20), " value of K value used in the nearest neighbor search of ANN or" "kmin for k-adaptation") ("K2,K", po::value(&k2)->default_value(20), " value of Kmax for k-adaptation") ("width,w", po::value(&width)->default_value(1280),"width of panorama image") ("height,h", po::value(&height)->default_value(960),"height of panorama image") ; po::options_description hidden("Hidden options"); hidden.add_options() ("input-dir", po::value(&dir), "input dir"); po::positional_options_description pd; pd.add("input-dir", 1); po::options_description all; all.add(cmd_options).add(hidden); po::variables_map vmap; po::store(po::command_line_parser(argc, argv).options(all).positional(pd).run(), vmap); po::notify(vmap); if (vmap.count("help")) { cout << cmd_options << endl << endl; cout << "SAMPLE COMMAND FOR CALCULATING NORMALS" << endl; cout << " bin/normals -s 0 -e 0 -f UOS -g AKNN -k 20 dat/" < &points, vector &normals, int scanNumber) { string ofilename = dir + "/scan" + to_string(scanNumber, 3) + ".3d"; ofstream normptsout(ofilename.c_str()); for (size_t i=0; i::iterator it = Scan::allScans.begin(); int scanNumber = 0; for( ; it != Scan::allScans.end(); ++it) { Scan* scan = *it; // apply optional filtering scan->setRangeFilter(max_dist, min_dist); const double* rPos = scan->get_rPos(); const double* rPosTheta = scan->get_rPosTheta(); /// read scan into points DataXYZ xyz(scan->get("xyz")); vector points; points.reserve(xyz.size()); vector normals; normals.reserve(xyz.size()); for(unsigned int j = 0; j < xyz.size(); j++) { points.push_back(Point(xyz[j][0], xyz[j][1], xyz[j][2])); } if(ntype == AKNN) calculateNormalsAKNN(normals,points, k1, rPos); else if(ntype == ADAPTIVE_AKNN) calculateNormalsAdaptiveAKNN(normals,points, k1, k2, rPos); else { // create panorama fbr::panorama fPanorama(width, height, fbr::EQUIRECTANGULAR, 1, 0, fbr::EXTENDED); fPanorama.createPanorama(scan2mat(scan)); // the range image has to be converted from float to uchar img = fPanorama.getRangeImage(); img = float2uchar(img, 0, 0.0); if(ntype == PANORAMA) calculateNormalsPANORAMA(normals,points,fPanorama.getExtendedMap(), rPos); else if(ntype == PANORAMA_FAST) cout << "PANORAMA_FAST is not working yet" << endl; // calculateNormalsFAST(normals,points,img,fPanorama.getExtendedMap()); } // pose file (repeated for the number of segments writePoseFiles(normdir, rPos, rPosTheta, scanNumber); // scan files for all segments writeScanFiles(normdir, points,normals,scanNumber); scanNumber++; } // shutdown everything if (scanserver) ClientInterface::destroy(); Scan::closeDirectory(); cout << "Normal program end" << endl; return 0; }