72 lines
		
	
	
		
			2.2 KiB
		
	
	
	
		
			C++
		
	
	
			
		
		
	
	
			72 lines
		
	
	
		
			2.2 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 testGeneralSFMFactorB.cpp
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 * @author Frank Dellaert
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 * @brief test general SFM class, with nonlinear optimization and BAL files
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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/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/NonlinearOptimizer.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/linear/NoiseModel.h>
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#include <CppUnitLite/Failure.h>
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#include <CppUnitLite/Test.h>
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#include <CppUnitLite/TestRegistry.h>
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#include <CppUnitLite/TestResult.h>
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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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typedef GeneralSFMFactor<PinholeCamera<Cal3Bundler>, Point3> sfmFactor;
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using symbol_shorthand::P;
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/* ************************************************************************* */
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TEST(PinholeCamera, BAL) {
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  string filename = findExampleDataFile("dubrovnik-3-7-pre");
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  SfmData db;
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  bool success = readBAL(filename, db);
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  if (!success) throw runtime_error("Could not access file!");
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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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    for (const SfmMeasurement& m: db.tracks[j].measurements)
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      graph.emplace_shared<sfmFactor>(m.second, unit2, m.first, P(j));
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  }
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  Values initial = initialCamerasAndPointsEstimate(db);
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  LevenbergMarquardtOptimizer lm(graph, initial);
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  Values actual = lm.optimize();
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  double actualError = graph.error(actual);
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  EXPECT_DOUBLES_EQUAL(0.0199833, actualError, 1e-5);
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}
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/* ************************************************************************* */
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int main() {
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  TestResult tr;
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  return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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