/* ************************************************************************* */
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;
}
