/* ************************************************************************* */ TEST( dataSet, writeBALfromValues_Dubrovnik){ ///< Read a file using the unit tested readBAL const string filenameToRead = findExampleDataFile("dubrovnik-3-7-pre"); SfM_data readData; readBAL(filenameToRead, readData); Pose3 poseChange = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.3,0.1,0.3)); Values value; for(size_t i=0; i < readData.number_cameras(); i++){ // for each camera Key poseKey = symbol('x',i); Pose3 pose = poseChange.compose(readData.cameras[i].pose()); value.insert(poseKey, pose); } for(size_t j=0; j < readData.number_tracks(); j++){ // for each point Key pointKey = P(j); Point3 point = poseChange.transform_from( readData.tracks[j].p ); value.insert(pointKey, point); } // Write values and readData to a file const string filenameToWrite = createRewrittenFileName(filenameToRead); writeBALfromValues(filenameToWrite, readData, value); // Read the file we wrote SfM_data writtenData; readBAL(filenameToWrite, writtenData); // Check that the reprojection errors are the same and the poses are correct // Check number of things EXPECT_LONGS_EQUAL(3,writtenData.number_cameras()); EXPECT_LONGS_EQUAL(7,writtenData.number_tracks()); const SfM_Track& track0 = writtenData.tracks[0]; EXPECT_LONGS_EQUAL(3,track0.number_measurements()); // Check projection of a given point EXPECT_LONGS_EQUAL(0,track0.measurements[0].first); const SfM_Camera& camera0 = writtenData.cameras[0]; Point2 expected = camera0.project(track0.p), actual = track0.measurements[0].second; EXPECT(assert_equal(expected,actual,12)); Pose3 expectedPose = camera0.pose(); Key poseKey = symbol('x',0); Pose3 actualPose = value.at<Pose3>(poseKey); EXPECT(assert_equal(expectedPose,actualPose, 1e-7)); Point3 expectedPoint = track0.p; Key pointKey = P(0); Point3 actualPoint = value.at<Point3>(pointKey); EXPECT(assert_equal(expectedPoint,actualPoint, 1e-6)); }
int main(int argc, char** argv){ Values initial_estimate; NonlinearFactorGraph graph; const noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(3,1); string calibration_loc = findExampleDataFile("VO_calibration.txt"); string pose_loc = findExampleDataFile("VO_camera_poses_large.txt"); string factor_loc = findExampleDataFile("VO_stereo_factors_large.txt"); //read camera calibration info from file // focal lengths fx, fy, skew s, principal point u0, v0, baseline b double fx, fy, s, u0, v0, b; ifstream calibration_file(calibration_loc.c_str()); cout << "Reading calibration info" << endl; calibration_file >> fx >> fy >> s >> u0 >> v0 >> b; //create stereo camera calibration object const Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(fx,fy,s,u0,v0,b)); ifstream pose_file(pose_loc.c_str()); cout << "Reading camera poses" << endl; int pose_id; MatrixRowMajor m(4,4); //read camera pose parameters and use to make initial estimates of camera poses while (pose_file >> pose_id) { for (int i = 0; i < 16; i++) { pose_file >> m.data()[i]; } initial_estimate.insert(Symbol('x', pose_id), Pose3(m)); } // camera and landmark keys size_t x, l; // pixel coordinates uL, uR, v (same for left/right images due to rectification) // landmark coordinates X, Y, Z in camera frame, resulting from triangulation double uL, uR, v, X, Y, Z; ifstream factor_file(factor_loc.c_str()); cout << "Reading stereo factors" << endl; //read stereo measurement details from file and use to create and add GenericStereoFactor objects to the graph representation while (factor_file >> x >> l >> uL >> uR >> v >> X >> Y >> Z) { graph.push_back( GenericStereoFactor<Pose3, Point3>(StereoPoint2(uL, uR, v), model, Symbol('x', x), Symbol('l', l), K)); //if the landmark variable included in this factor has not yet been added to the initial variable value estimate, add it if (!initial_estimate.exists(Symbol('l', l))) { Pose3 camPose = initial_estimate.at<Pose3>(Symbol('x', x)); //transform_from() transforms the input Point3 from the camera pose space, camPose, to the global space Point3 worldPoint = camPose.transform_from(Point3(X, Y, Z)); initial_estimate.insert(Symbol('l', l), worldPoint); } } Pose3 first_pose = initial_estimate.at<Pose3>(Symbol('x',1)); //constrain the first pose such that it cannot change from its original value during optimization // NOTE: NonlinearEquality forces the optimizer to use QR rather than Cholesky // QR is much slower than Cholesky, but numerically more stable graph.push_back(NonlinearEquality<Pose3>(Symbol('x',1),first_pose)); cout << "Optimizing" << endl; //create Levenberg-Marquardt optimizer to optimize the factor graph LevenbergMarquardtOptimizer optimizer = LevenbergMarquardtOptimizer(graph, initial_estimate); Values result = optimizer.optimize(); cout << "Final result sample:" << endl; Values pose_values = result.filter<Pose3>(); pose_values.print("Final camera poses:\n"); return 0; }