86 lines
2.6 KiB
C++
86 lines
2.6 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file timeSFMBAL.cpp
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* @brief time structure from motion with BAL file
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* @author Frank Dellaert
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* @date June 6, 2015
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*/
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#include <gtsam/slam/dataset.h>
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#include <gtsam/slam/GeneralSFMFactor.h>
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#include <gtsam/geometry/Cal3Bundler.h>
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#include <gtsam/geometry/PinholeCamera.h>
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#include <gtsam/geometry/Point3.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/linear/NoiseModel.h>
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#include <gtsam/inference/FactorGraph.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/base/timing.h>
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#include <boost/foreach.hpp>
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#include <stddef.h>
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#include <stdexcept>
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#include <string>
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using namespace std;
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using namespace gtsam;
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//#define TERNARY
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int main(int argc, char* argv[]) {
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typedef GeneralSFMFactor<PinholeCamera<Cal3Bundler>, Point3> sfmFactor;
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using symbol_shorthand::P;
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// Load BAL file (default is tiny)
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string defaultFilename = findExampleDataFile("dubrovnik-3-7-pre");
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SfM_data db;
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bool success = readBAL(argc > 1 ? argv[1] : defaultFilename, db);
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if (!success) throw runtime_error("Could not access file!");
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// Build graph
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SharedNoiseModel unit2 = noiseModel::Unit::Create(2);
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NonlinearFactorGraph graph;
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for (size_t j = 0; j < db.number_tracks(); j++) {
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BOOST_FOREACH (const SfM_Measurement& m, db.tracks[j].measurements)
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graph.push_back(sfmFactor(m.second, unit2, m.first, P(j)));
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}
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Values initial = initialCamerasAndPointsEstimate(db);
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// Create Schur-complement ordering
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#ifdef CCOLAMD
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vector<Key> pointKeys;
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for (size_t j = 0; j < db.number_tracks(); j++) pointKeys.push_back(P(j));
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Ordering ordering = Ordering::colamdConstrainedFirst(graph, pointKeys, true);
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#else
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Ordering ordering;
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for (size_t j = 0; j < db.number_tracks(); j++) ordering.push_back(P(j));
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for (size_t i = 0; i < db.number_cameras(); i++) ordering.push_back(i);
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#endif
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// Optimize
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LevenbergMarquardtParams params;
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params.setOrdering(ordering);
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params.setVerbosity("ERROR");
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params.setVerbosityLM("TRYLAMBDA");
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LevenbergMarquardtOptimizer lm(graph, initial, params);
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Values actual = lm.optimize();
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tictoc_finishedIteration_();
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tictoc_print_();
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return 0;
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}
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