added control over minimum rank in ShonanAveraging example, and resolved hard-coded sigma in FrobeniusFactor
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3734039bf5
commit
6567422ec5
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@ -25,6 +25,8 @@
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* Read 3D dataset sphere25000.txt and output to shonan.g2o (default)
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* ./ShonanAveragingCLI -i spere2500.txt
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*
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* If you prefer using a robust Huber loss, you can add the option "-h true", for instance"
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* ./ShonanAveragingCLI -i spere2500.txt -u true
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*/
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#include <gtsam/base/timing.h>
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@ -43,7 +45,8 @@ int main(int argc, char* argv[]) {
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string datasetName;
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string inputFile;
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string outputFile;
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int d, seed;
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int d, seed, pMin;
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bool useHuberLoss;
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po::options_description desc(
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"Shonan Rotation Averaging CLI reads a *pose* graph, extracts the "
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"rotation constraints, and runs the Shonan algorithm.");
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@ -58,6 +61,10 @@ int main(int argc, char* argv[]) {
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"Write solution to the specified file")(
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"dimension,d", po::value<int>(&d)->default_value(3),
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"Optimize over 2D or 3D rotations")(
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"useHuberLoss,h", po::value<bool>(&useHuberLoss)->default_value(false),
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"set True to use Huber loss")(
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"pMin,p", po::value<int>(&pMin)->default_value(3),
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"set to use desired rank pMin")(
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"seed,s", po::value<int>(&seed)->default_value(42),
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"Random seed for initial estimate");
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po::variables_map vm;
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@ -85,11 +92,14 @@ int main(int argc, char* argv[]) {
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NonlinearFactorGraph::shared_ptr inputGraph;
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Values::shared_ptr posesInFile;
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Values poses;
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auto lmParams = LevenbergMarquardtParams::CeresDefaults();
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if (d == 2) {
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cout << "Running Shonan averaging for SO(2) on " << inputFile << endl;
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ShonanAveraging2 shonan(inputFile);
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ShonanAveraging2::Parameters parameters(lmParams);
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parameters.setUseHuber(useHuberLoss);
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ShonanAveraging2 shonan(inputFile,parameters);
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auto initial = shonan.initializeRandomly(rng);
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auto result = shonan.run(initial);
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auto result = shonan.run(initial,pMin);
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// Parse file again to set up translation problem, adding a prior
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boost::tie(inputGraph, posesInFile) = load2D(inputFile);
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@ -101,9 +111,11 @@ int main(int argc, char* argv[]) {
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poses = initialize::computePoses<Pose2>(result.first, &poseGraph);
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} else if (d == 3) {
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cout << "Running Shonan averaging for SO(3) on " << inputFile << endl;
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ShonanAveraging3 shonan(inputFile);
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ShonanAveraging3::Parameters parameters(lmParams);
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parameters.setUseHuber(useHuberLoss);
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ShonanAveraging3 shonan(inputFile,parameters);
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auto initial = shonan.initializeRandomly(rng);
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auto result = shonan.run(initial);
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auto result = shonan.run(initial,pMin);
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// Parse file again to set up translation problem, adding a prior
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boost::tie(inputGraph, posesInFile) = load3D(inputFile);
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@ -118,7 +130,7 @@ int main(int argc, char* argv[]) {
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return 1;
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}
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cout << "Writing result to " << outputFile << endl;
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writeG2o(NonlinearFactorGraph(), poses, outputFile);
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writeG2o(*inputGraph, poses, outputFile);
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return 0;
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}
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@ -30,11 +30,11 @@ ConvertNoiseModel(const SharedNoiseModel &model, size_t d, bool defaultToUnit) {
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const auto &robust = boost::dynamic_pointer_cast<noiseModel::Robust>(model);
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Vector sigmas;
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if(robust){
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sigma = 1; // Rot2
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goto exit;
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} //else:
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sigmas = robust->noise()->sigmas();
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} else{
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sigmas = model->sigmas();
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}
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sigmas = model->sigmas();
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size_t n = sigmas.size();
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if (n == 1) {
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sigma = sigmas(0); // Rot2
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