413 lines
18 KiB
Text
413 lines
18 KiB
Text
/*
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* feature_based_registration implementation
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*
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* Copyright (C) HamidReza Houshiar
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*
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* Released under the GPL version 3.
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*
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*/
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#include <stdio.h>
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#include <fstream>
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#include "slam6d/fbr/fbr_global.h"
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#include "slam6d/fbr/scan_cv.h"
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#include "slam6d/fbr/panorama.h"
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#include "slam6d/fbr/feature.h"
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#include "slam6d/fbr/feature_matcher.h"
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#include "slam6d/fbr/registration.h"
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using namespace std;
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using namespace fbr;
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struct information{
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string local_time;
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string dir, outDir;
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int iWidth, iHeight, nImages, minDistance, minError, minInlier, fScanNumber, sScanNumber, verbose;
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double pParam, mParam;
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IOType sFormat;
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projection_method pMethod;
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feature_detector_method fMethod;
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feature_descriptor_method dMethod;
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matcher_method mMethod;
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registration_method rMethod;
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int fSPoints, sSPoints, fFNum, sFNum, mNum, filteredMNum;
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double fSTime, sSTime, fPTime, sPTime, fFTime, sFTime, fDTime, sDTime, mTime, rTime;
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} info;
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/**
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* usage : explains how to use the program CMD
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*/
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void usage(int argc, char** argv){
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printf("\n");
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printf("USAGE: %s dir firstScanNumber secondScanNumber \n", argv[0]);
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printf("\n");
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printf("\n");
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printf("\tOptions:\n");
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printf("\t\t-F scanFormat\t\t input scan file format [RIEGL_TXT|RXP|ALL SLAM6D SCAN_IO]\n");
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printf("\t\t-W iWidth\t\t panorama image width\n");
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printf("\t\t-H iHeight\t\t panorama image height\n");
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printf("\t\t-p pMethod\t\t projection method [EQUIRECTANGULAR|CYLINDRICAL|MERCATOR|RECTILINEAR|PANNINI|STEREOGRAPHIC|ZAXIS]\n");
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printf("\t\t-N nImage\t\t number of images used for some projections\n");
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printf("\t\t-P pParam\t\t special projection parameter (d for Pannini and r for stereographic)\n");
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printf("\t\t-f fMethod\t\t feature detection method [SURF|SIFT|ORB|FAST|STAR]\n");
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printf("\t\t-d dMethod\t\t feature description method [SURF|SIFT|ORB]\n");
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printf("\t\t-m mMethod\t\t feature matching method [BRUTEFORCE|FLANN|KNN|RADIUS|RATIO]\n");
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printf("\t\t-D minDistance \t\t threshold for min distance in registration process\n");
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printf("\t\t-E minError \t\t threshold for min error in registration process\n");
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printf("\t\t-I minInlier \t\t threshold for min number of inliers in registration process\n");
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printf("\t\t-M mParam \t\t special matching paameter (knn for KNN and r for radius)\n");
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printf("\t\t-r registration \t registration method [ALL|ransac]\n");
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printf("\t\t-V verbose \t\t level of verboseness\n");
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printf("\t\t-O outDir \t\t output directory if not stated same as input\n");
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printf("\n");
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printf("\tExamples:\n");
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printf("\tUsing Bremen City dataset:\n");
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printf("\tLoading scan000.txt and scan001.txt:\n");
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printf("\t\t %s ~/dir/to/bremen_city 0 1\n", argv[0]);
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printf("\tLoading scan005.txt and scan006.txt and output panorma images and feature images and match images in ~/dir/to/bremen_city/out dir:\n");
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printf("\t\t %s -V 1 -O ~/dir/to/bremen_city/out/ ~/dir/to/bremen_city 5 6 \n", argv[0]);
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printf("\tLoading scan010.txt and scan011.txt using Mercator projection and SURF feature detector and SIFT descriptor:\n");
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printf("\t\t %s -p MERCATOR -f SURF -d SIFT -O ~/dir/to/bremen_city/out/ ~/dir/to/bremen_city 10 11 \n", argv[0]);
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printf("\n");
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exit(1);
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}
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void parssArgs(int argc, char** argv, information& info){
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cout<<"parssArgs"<<endl;
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time_t rawtime;
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struct tm *timeinfo;
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time(&rawtime);
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char time[50];
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timeinfo = localtime (&rawtime);
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sprintf(time, "%d-%d-%d-%d:%d:%d", timeinfo->tm_year + 1900, timeinfo->tm_mon + 1, timeinfo->tm_mday, timeinfo->tm_hour, timeinfo->tm_min, timeinfo->tm_sec);
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info.local_time = time;
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//default values
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info.iWidth = 3600;
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info.iHeight = 1000;
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info.nImages = 1;
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info.minDistance = 50;
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info.minError = 50;
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info.minInlier = 5;
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info.verbose = 0;
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//depend on the projection method
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info.pParam = 0;
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info.mParam = 0;
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//===============================
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info.sFormat = RIEGL_TXT;
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info.pMethod = EQUIRECTANGULAR;
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info.fMethod = SIFT_DET;
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info.dMethod = SIFT_DES;
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info.mMethod = RATIO;
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info.rMethod = RANSAC;
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info.outDir = "";
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int c;
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opterr = 0;
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//reade the command line and get the options
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while ((c = getopt (argc, argv, "F:W:H:p:N:P:f:d:m:D:E:I:M:r:V:O:")) != -1)
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switch (c)
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{
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case 'F':
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info.sFormat = stringToScanFormat(optarg);
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break;
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case 'W':
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info.iWidth = atoi(optarg);
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break;
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case 'H':
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info.iHeight = atoi(optarg);
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break;
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case 'p':
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info.pMethod = stringToProjectionMethod(optarg);
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break;
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case 'N':
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info.nImages = atoi(optarg);
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break;
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case 'P':
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info.pParam = atoi(optarg);
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break;
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case 'f':
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info.fMethod = stringToFeatureDetectorMethod(optarg);
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break;
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case 'd':
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info.dMethod = stringToFeatureDescriptorMethod(optarg);
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break;
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case 'm':
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info.mMethod = stringToMatcherMethod(optarg);
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break;
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case 'D':
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info.minDistance = atoi(optarg);
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break;
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case 'E':
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info.minError = atoi(optarg);
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break;
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case 'I':
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info.minInlier = atoi(optarg);
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break;
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case 'M':
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info.mParam = atoi(optarg);
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break;
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case 'r':
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info.rMethod = stringToRegistrationMethod(optarg);
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break;
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case 'V':
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cout<<"verboos"<<endl;
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info.verbose = atoi(optarg);
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break;
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case 'O':
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info.outDir = optarg;
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break;
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case '?':
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cout<<"Unknown option character "<<optopt<<endl;
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usage(argc, argv);
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break;
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default:
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usage(argc, argv);
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}
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if(info.pMethod == PANNINI && info.pParam == 0){
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info.pParam = 1;
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if(info.nImages < 3) info.nImages = 3;
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}
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if(info.pMethod == STEREOGRAPHIC && info.pParam == 0){
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info.pParam = 2;
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if(info.nImages < 3) info.nImages = 3;
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}
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if(info.pMethod == RECTILINEAR && info.nImages < 3)
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info.nImages = 3;
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if(info.mMethod == KNN && info.mParam == 0)
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info.mParam = 3;
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if(info.mMethod == RADIUS && info.mParam == 0)
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info.mParam = 100;
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if(info.dMethod == ORB_DES && info.fMethod == SIFT_DET){
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cout<<"Error: SIFT feature doesn't work with ORB descriptor."<<endl;
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usage(argc, argv);
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}
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if(info.mMethod == FLANN && info.dMethod == ORB_DES){
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cout<<"Error: ORB descriptoronly works with BRUTEFORCE matcher."<<endl;
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usage(argc, argv);
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}
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if (optind > argc - 3)
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{
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cout<<"Too few input arguments. At least dir and two scan numbers are required."<<endl;
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usage(argc, argv);
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}
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info.dir = argv[optind];
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info.fScanNumber = atoi(argv[optind+1]);
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info.sScanNumber = atoi(argv[optind+2]);
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if(info.outDir.empty()) info.outDir = info.dir;
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else if(info.outDir.compare(info.outDir.size()-1, 1, "/") != 0) info.outDir += "/";
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}
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void informationDescription(information info){
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cout<<"program parameters are:"<<endl;
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cout<<endl;
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cout<<"local time: "<<info.local_time<<endl;
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cout<<"input dir: "<<info.dir<<endl;
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cout<<"output dir: "<<info.outDir<<endl;
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cout<<"first scan number: "<<info.fScanNumber<<endl;
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cout<<"second scan number: "<<info.sScanNumber<<endl;
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cout<<"scan format: "<<scanFormatToString(info.sFormat)<<endl;
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cout<<endl;
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cout<<"image width: "<<info.iWidth<<endl;
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cout<<"image height: "<<info.iHeight<<endl;
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cout<<"number of images: "<<info.nImages<<endl;
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cout<<"projection parameter: "<<info.pParam<<endl;
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cout<<"projection method: "<<projectionMethodToString(info.pMethod)<<endl;
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cout<<endl;
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cout<<"feature detector method: "<<featureDetectorMethodToString(info.fMethod)<<endl;
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cout<<"feature descriptor method: "<<featureDescriptorMethodToString(info.dMethod)<<endl;
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cout<<endl;
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cout<<"matcher parameter: "<<info.mParam<<endl;
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cout<<"matcher method: "<<matcherMethodToString(info.mMethod)<<endl;
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cout<<endl;
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cout<<"min distacne: "<<info.minDistance<<endl;
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cout<<"min error: "<<info.minError<<endl;
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cout<<"min inlier: "<<info.minInlier<<endl;
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cout<<"registration method: "<<registrationMethodToString(info.rMethod)<<endl;
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cout<<endl;
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}
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void info_yml(information info, double bError, double bErrorIdx, double* bAlign){
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cv::Mat align(16, 1, CV_32FC(1), cv::Scalar::all(0));
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for(int i = 0 ; i < 16 ; i++)
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align.at<float>(i,0) = bAlign[i];
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string yml;
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yml = info.outDir+"fbr-yml.yml";
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cv::FileStorage fs(yml.c_str(), cv::FileStorage::APPEND);
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fs << "feature_bas_registration" << "{";
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fs << "pair" << "{" << "scan" << to_string(info.fScanNumber, 3);
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fs << "scan" << to_string(info.sScanNumber, 3) << "}";
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fs << "time" << "{" << "local_time" << info.local_time << "}";
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fs << "param" << "{";
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fs << "DIR" << info.dir;
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fs << "sFormat" << scanFormatToString(info.sFormat);
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fs << "pMethod" << projectionMethodToString(info.pMethod);
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fs << "nImage" << info.nImages;
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fs << "pParam" << info.pParam;
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fs << "iWidth" << info.iWidth;
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fs << "iHeight" << info.iHeight;
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fs << "fMethod" << featureDetectorMethodToString(info.fMethod);
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fs << "dMethod" << featureDescriptorMethodToString(info.dMethod);
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fs << "mMethod" << matcherMethodToString(info.mMethod);
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fs << "mParam" << info.mParam;
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fs << "rMethod" << registrationMethodToString(info.rMethod);
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fs << "minDistance" << info.minDistance;
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fs << "minInlier" << info.minInlier;
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fs << "minError" << info.minError;
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fs << "}";
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fs << "input" << "{";
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fs << "first_input" << "{";
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fs << "name" << "{" << "scan" << to_string(info.fScanNumber, 3) << "}";
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fs << "point" << "{" << "amount" << info.fSPoints << "time" << info.fSTime << "}";
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fs << "projection" << "{" << "time" << info.fPTime << "}";
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fs << "feature" << "{" << "amount" << info.fFNum << "fTime" << info.fFTime << "dTime" << info.fDTime << "}";
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fs << "}";
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fs << "second_input" << "{";
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fs << "name" << "{" << "scan" << to_string(info.sScanNumber, 3) << "}";
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fs << "point" << "{" << "amount" << info.sSPoints << "time" << info.sSTime << "}";
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fs << "projection" << "{" << "time" << info.sPTime << "}";
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fs << "feature" << "{" << "amount" << info.sFNum << "fTime" << info.sFTime << "dTime" << info.sDTime << "}";
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fs << "}";
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fs << "}";
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fs << "matches" << "{";
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fs << "amount" << info.mNum << "filteration" << info.filteredMNum << "time" << info.mTime << "}";
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fs << "reg" << "{";
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fs << "bestError" << bError << "bestErrorIdx" << bErrorIdx << "time" << info.rTime << "bAlign" << align << "}";
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fs << "}";
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}
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int main(int argc, char** argv){
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string out;
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cv::Mat outImage;
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parssArgs(argc, argv, info);
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cout<<"out of parssArgs"<<endl;
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if(info.verbose >= 1) informationDescription(info);
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scan_cv fScan (info.dir, info.fScanNumber, info.sFormat);
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if(info.verbose >= 4) info.fSTime = (double)cv::getTickCount();
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fScan.convertScanToMat();
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if(info.verbose >= 4) info.fSTime = ((double)cv::getTickCount() - info.fSTime)/cv::getTickFrequency();
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if(info.verbose >= 2) fScan.getDescription();
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panorama fPanorama (info.iWidth, info.iHeight, info.pMethod, info.nImages, info.pParam);
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if(info.verbose >= 4) info.fPTime = (double)cv::getTickCount();
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fPanorama.createPanorama(fScan.getMatScan());
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if(info.verbose >= 4) info.fPTime = ((double)cv::getTickCount() - info.fPTime)/cv::getTickFrequency();
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if(info.verbose >= 2) fPanorama.getDescription();
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//write panorama to image
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if(info.verbose >= 1){
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out = info.outDir+info.local_time+"_scan"+to_string(info.fScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+".jpg";
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imwrite(out, fPanorama.getReflectanceImage());
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}
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feature fFeature;
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if(info.verbose >= 4) info.fFTime = (double)cv::getTickCount();
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fFeature.featureDetection(fPanorama.getReflectanceImage(), info.fMethod);
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if(info.verbose >= 4) info.fFTime = ((double)cv::getTickCount() - info.fFTime)/cv::getTickFrequency();
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//write panorama with keypoints to image
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if(info.verbose >= 1){
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cv::drawKeypoints(fPanorama.getReflectanceImage(), fFeature.getFeatures(), outImage, cv::Scalar::all(-1), cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS );
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out = info.outDir+info.local_time+"_scan"+to_string(info.fScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+"_"+featureDetectorMethodToString(info.fMethod)+".jpg";
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imwrite(out, outImage);
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outImage.release();
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}
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if(info.verbose >= 4) info.fDTime = (double)cv::getTickCount();
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fFeature.featureDescription(fPanorama.getReflectanceImage(), info.dMethod);
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if(info.verbose >= 4) info.fDTime = ((double)cv::getTickCount() - info.fDTime)/cv::getTickFrequency();
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if(info.verbose >= 2) fFeature.getDescription();
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scan_cv sScan (info.dir, info.sScanNumber, info.sFormat);
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if(info.verbose >= 4) info.sSTime = (double)cv::getTickCount();
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sScan.convertScanToMat();
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if(info.verbose >= 4) info.sSTime = ((double)cv::getTickCount() - info.sSTime)/cv::getTickFrequency();
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if(info.verbose >= 2) sScan.getDescription();
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panorama sPanorama (info.iWidth, info.iHeight, info.pMethod, info.nImages, info.pParam);
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if(info.verbose >= 4) info.sPTime = (double)cv::getTickCount();
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sPanorama.createPanorama(sScan.getMatScan());
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if(info.verbose >= 4) info.sPTime = ((double)cv::getTickCount() - info.sPTime)/cv::getTickFrequency();
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if(info.verbose >= 2) sPanorama.getDescription();
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//write panorama to image
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if(info.verbose >= 1){
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out = info.outDir+info.local_time+"_scan"+to_string(info.sScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+".jpg";
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imwrite(out, sPanorama.getReflectanceImage());
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}
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feature sFeature;
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if(info.verbose >= 4) info.sFTime = (double)cv::getTickCount();
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sFeature.featureDetection(sPanorama.getReflectanceImage(), info.fMethod);
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if(info.verbose >= 4) info.sFTime = ((double)cv::getTickCount() - info.sFTime)/cv::getTickFrequency();
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//write panorama with keypoints to image
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if(info.verbose >= 1){
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cv::drawKeypoints(sPanorama.getReflectanceImage(), sFeature.getFeatures(), outImage, cv::Scalar::all(-1), cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS );
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out = info.outDir+info.local_time+"_scan"+to_string(info.sScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+"_"+featureDetectorMethodToString(info.fMethod)+".jpg";
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imwrite(out, outImage);
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outImage.release();
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}
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if(info.verbose >= 4) info.sDTime = (double)cv::getTickCount();
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sFeature.featureDescription(sPanorama.getReflectanceImage(), info.dMethod);
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if(info.verbose >= 4) info.sDTime = ((double)cv::getTickCount() - info.sDTime)/cv::getTickFrequency();
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if(info.verbose >= 2) sFeature.getDescription();
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feature_matcher matcher (info.mMethod, info.mParam);
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if(info.verbose >= 4) info.mTime = (double)cv::getTickCount();
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matcher.match(fFeature, sFeature);
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if(info.verbose >= 4) info.mTime = ((double)cv::getTickCount() - info.mTime)/cv::getTickFrequency();
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if(info.verbose >= 2) matcher.getDescription();
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//write matcheed feature to image
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if(info.verbose >= 1){
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cv::drawMatches(fPanorama.getReflectanceImage(), fFeature.getFeatures(), sPanorama.getReflectanceImage(), sFeature.getFeatures(), matcher.getMatches(), outImage, cv::Scalar::all(-1), cv::Scalar::all(-1), vector<char>(), cv::DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
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out = info.outDir+info.local_time+"_scan"+to_string(info.fScanNumber, 3)+"_scan"+to_string(info.sScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+"_"+featureDetectorMethodToString(info.fMethod)+"_"+featureDescriptorMethodToString(info.dMethod)+"_"+matcherMethodToString(info.mMethod)+".jpg";
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imwrite(out, outImage);
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outImage.release();
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}
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registration reg (info.minDistance, info.minError, info.minInlier, info.rMethod);
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if(info.verbose >= 4) info.rTime = (double)cv::getTickCount();
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reg.findRegistration(fPanorama.getMap(), fFeature.getFeatures(), sPanorama.getMap(), sFeature.getFeatures(), matcher.getMatches());
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if(info.verbose >= 4) info.rTime = ((double)cv::getTickCount() - info.rTime)/cv::getTickFrequency();
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if(info.verbose >= 2) reg.getDescription();
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|
|
|
//write .dat and .frames files
|
|
if(info.verbose >= 0){
|
|
double *bAlign = reg.getBestAlign();
|
|
|
|
out = info.outDir+info.local_time+"_scan"+to_string(info.fScanNumber, 3)+"_scan"+to_string(info.sScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+"_"+featureDetectorMethodToString(info.fMethod)+"_"+featureDescriptorMethodToString(info.dMethod)+"_"+matcherMethodToString(info.mMethod)+"_"+registrationMethodToString(info.rMethod)+".dat";
|
|
ofstream dat(out.c_str());
|
|
dat << bAlign[0] << " " << bAlign[4] << " " << bAlign[8] << " " << bAlign[12] <<endl;
|
|
dat << bAlign[1] << " " << bAlign[5] << " " << bAlign[9] << " " << bAlign[13] <<endl;
|
|
dat << bAlign[2] << " " << bAlign[6] << " " << bAlign[10] << " " << bAlign[14] <<endl;
|
|
dat << bAlign[3] << " " << bAlign[7] << " " << bAlign[11] << " " << bAlign[15] <<endl;
|
|
dat.close();
|
|
|
|
out = info.outDir+info.local_time+"_scan"+to_string(info.fScanNumber, 3)+"_scan"+to_string(info.sScanNumber, 3)+"_"+projectionMethodToString(info.pMethod)+"_"+to_string(info.iWidth)+"x"+to_string(info.iHeight)+"_"+featureDetectorMethodToString(info.fMethod)+"_"+featureDescriptorMethodToString(info.dMethod)+"_"+matcherMethodToString(info.mMethod)+"_"+registrationMethodToString(info.rMethod)+".frames";
|
|
ofstream frames(out.c_str());
|
|
for (int n = 0 ; n < 2 ; n++)
|
|
{
|
|
for(int i = 0; i < 16; i++)
|
|
frames << bAlign[i] <<" ";
|
|
frames << "2" << endl;
|
|
}
|
|
frames.close();
|
|
}
|
|
|
|
if(info.verbose >= 3){
|
|
info.fSPoints = fScan.getNumberOfPoints();
|
|
info.sSPoints = sScan.getNumberOfPoints();
|
|
info.fFNum = fFeature.getNumberOfFeatures();
|
|
info.sFNum = sFeature.getNumberOfFeatures();
|
|
info.mNum = matcher.getNumberOfMatches();
|
|
info.filteredMNum = matcher.getNumberOfFilteredMatches();
|
|
|
|
info_yml(info, reg.getBestError(), reg.getBestErrorIndex(), reg.getBestAlign());
|
|
}
|
|
|
|
return 0;
|
|
}
|