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more unit tests

release/4.3a0
Yong-Dian Jian 2010-12-28 22:59:24 +00:00
parent 638a6e6917
commit 97dfe6c034
2 changed files with 282 additions and 39 deletions
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6
gtsam/slam/GeneralSFMFactor.h
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@ -8,6 +8,9 @@
#pragma once
#include <gtsam/base/Testable.h>
#include <gtsam/nonlinear/NonlinearFactor.h>
namespace gtsam {
@ -16,8 +19,7 @@ namespace gtsam {
*/
template <class Cfg, class CamK, class LmK>
class GeneralSFMFactor:
public NonlinearFactor2<Cfg, CamK, LmK> ,
Testable<GeneralSFMFactor<Cfg, CamK, LmK> > {
public NonlinearFactor2<Cfg, CamK, LmK> {
protected:
Point2 z_;

315
gtsam/slam/tests/testGeneralSFMFactor.cpp
View File

@ -29,6 +29,7 @@ using namespace std;
using namespace gtsam;
typedef Cal3_S2Camera GeneralCamera;
//typedef Cal3BundlerCamera GeneralCamera;
typedef TypedSymbol<GeneralCamera, 'x'> CameraKey;
typedef TypedSymbol<Point3, 'l'> PointKey;
typedef LieValues<CameraKey> CameraConfig;
@ -36,6 +37,7 @@ typedef LieValues<PointKey> PointConfig;
typedef TupleValues2<CameraConfig, PointConfig> Values;
typedef GeneralSFMFactor<Values, CameraKey, PointKey> Projection;
typedef NonlinearEquality<Values, CameraKey> CameraConstraint;
typedef NonlinearEquality<Values, PointKey> Point3Constraint;
class Graph: public NonlinearFactorGraph<Values> {
public:
@ -47,6 +49,12 @@ public:
boost::shared_ptr<CameraConstraint> factor(new CameraConstraint(j, p));
push_back(factor);
}
void addPoint3Constraint(int j, const Point3& p) {
boost::shared_ptr<Point3Constraint> factor(new Point3Constraint(j, p));
push_back(factor);
}
};
double getGaussian()
@ -66,11 +74,7 @@ double getGaussian()
typedef NonlinearOptimizer<Graph,Values> Optimizer;
// make cube
static Point3
x000(-1, -1, -1), x001(-1, -1, +1), x010(-1, +1, -1), x011(-1, +1, +1),
x100(-1, -1, -1), x101(-1, -1, +1), x110(-1, +1, -1), x111(-1, +1, +1);
const SharedGaussian sigma1(noiseModel::Unit::Create(1));
/* ************************************************************************* */
TEST( GeneralSFMFactor, equals )
@ -90,14 +94,11 @@ TEST( GeneralSFMFactor, equals )
/* ************************************************************************* */
TEST( GeneralSFMFactor, error ) {
Point2 z(3.,0.);
const int cameraFrameNumber=1, landmarkNumber=1;
const SharedGaussian sigma(noiseModel::Unit::Create(1));
boost::shared_ptr<Projection>
factor(new Projection(z, sigma, cameraFrameNumber, landmarkNumber));
// For the following configuration, the factor predicts 320,240
Values values;
Rot3 R;
@ -108,65 +109,305 @@ TEST( GeneralSFMFactor, error ) {
CHECK(assert_equal(Vector_(2, -3.0, 0.0), factor->unwhitenedError(values)));
}
/* ************************************************************************* */
TEST( GeneralSFMFactor, optimize ) {
const SharedGaussian sigma1(noiseModel::Unit::Create(1));
const double z = 5;
vector<Point3> L ;
L.push_back(Point3 (-1.0,-1.0, z));
L.push_back(Point3 (-1.0, 1.0, z));
L.push_back(Point3 ( 1.0, 1.0, z));
L.push_back(Point3 ( 1.0,-1.0, z));
L.push_back(Point3 (-1.0,-1.0, 2*z));
L.push_back(Point3 (-1.0, 1.0, 2*z));
L.push_back(Point3 ( 1.0, 1.0, 2*z));
L.push_back(Point3 ( 1.0,-1.0, 2*z));
vector<GeneralCamera> X ;
X.push_back(GeneralCamera(Pose3()));
X.push_back(GeneralCamera(Pose3(eye(3),Point3(0.0,0.0,-z))));
static const double baseline = 5.0 ;
vector<Point3> genPoint3() {
const double z = 5;
vector<Point3> L ;
L.push_back(Point3 (-1.0,-1.0, z));
L.push_back(Point3 (-1.0, 1.0, z));
L.push_back(Point3 ( 1.0, 1.0, z));
L.push_back(Point3 ( 1.0,-1.0, z));
L.push_back(Point3 (-1.5,-1.5, 1.5*z));
L.push_back(Point3 (-1.5, 1.5, 1.5*z));
L.push_back(Point3 ( 1.5, 1.5, 1.5*z));
L.push_back(Point3 ( 1.5,-1.5, 1.5*z));
L.push_back(Point3 (-2.0,-2.0, 2*z));
L.push_back(Point3 (-2.0, 2.0, 2*z));
L.push_back(Point3 ( 2.0, 2.0, 2*z));
L.push_back(Point3 ( 2.0,-2.0, 2*z));
return L ;
}
vector<GeneralCamera> genCameraDefaultCalibration() {
vector<GeneralCamera> X ;
X.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0))));
X.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0))));
return X ;
}
vector<GeneralCamera> genCameraVariableCalibration() {
const Cal3_S2 K(640,480,0.01,320,240);
vector<GeneralCamera> X ;
X.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)), K));
X.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0)), K));
return X ;
}
shared_ptr<Ordering> getOrdering(const vector<GeneralCamera>& X, const vector<Point3>& L) {
list<Symbol> keys;
for ( size_t i = 0 ; i < L.size() ; ++i ) keys.push_back(Symbol('l', i)) ;
for ( size_t i = 0 ; i < X.size() ; ++i ) keys.push_back(Symbol('x', i)) ;
shared_ptr<Ordering> ordering(new Ordering(keys));
return ordering ;
}
/* ************************************************************************* */
TEST( GeneralSFMFactor, optimize_defaultK ) {
vector<Point3> L = genPoint3();
vector<GeneralCamera> X = genCameraDefaultCalibration();
// add measurement with noise
shared_ptr<Graph> graph(new Graph());
for ( size_t j = 0 ; j < X.size() ; ++j) {
for ( size_t i = 0 ; i < L.size() ; ++i) {
Point2 pt = X[j].project(L[i]) ;
//Point2 q(pt.x()+0.1*getGaussian(), pt.y()+0.1*getGaussian()) ;
graph->addMeasurement(j, i, pt, sigma1);
}
}
const size_t nMeasurements = X.size()*L.size() ;
// add initial
const double noise = 1.0;
const double noise = baseline*0.1;
boost::shared_ptr<Values> values(new Values);
for ( int i = 0 ; i < X.size() ; ++i )
values->insert(i, X[i]) ;
for ( size_t i = 0 ; i < X.size() ; ++i )
values->insert((int)i, X[i]) ;
for ( size_t i = 0 ; i < L.size() ; ++i ) {
Point3 pt(L[i].x()+noise*getGaussian(),
L[i].y()+noise*getGaussian(),
L[i].z()+noise*getGaussian());
//if (i == 0) pt = Point3(pt.x()+10, pt.y(), pt.z()) ;
values->insert(i, pt) ;
}
graph->addCameraConstraint(0, X[0]);
// Create an ordering of the variables
list<Symbol> keys;
for ( size_t i = 0 ; i < L.size() ; ++i ) keys.push_back(Symbol('l', i)) ;
for ( size_t i = 0 ; i < X.size() ; ++i ) keys.push_back(Symbol('x', i)) ;
shared_ptr<Ordering> ordering(new Ordering(keys));
NonlinearOptimizationParameters::sharedThis params = NonlinearOptimizationParameters::newDrecreaseThresholds(1e-7, 1e-7);
shared_ptr<Ordering> ordering = getOrdering(X,L);
//graph->print("graph") ; values->print("values") ;
NonlinearOptimizationParameters::sharedThis params (
new NonlinearOptimizationParameters(1e-7, 1e-7, 0.0, 100, 1e-5, 10, NonlinearOptimizationParameters::SILENT));
Optimizer optimizer(graph, values, ordering, params);
cout << "optimize_defaultK::" << endl ;
cout << "before optimization, error is " << optimizer.error() << endl;
Optimizer optimizer2 = optimizer.levenbergMarquardt();
cout << "after optimization, error is " << optimizer2.error() << endl;
CHECK(optimizer2.error() < 1e-1);
//optimizer2.values()->print("optimized") ;
CHECK(optimizer2.error() < 0.5 * 1e-1 * nMeasurements);
}
/* ************************************************************************* */
TEST( GeneralSFMFactor, optimize_varK_SingleMeasurementError ) {
vector<Point3> L = genPoint3();
vector<GeneralCamera> X = genCameraVariableCalibration();
// add measurement with noise
shared_ptr<Graph> graph(new Graph());
for ( size_t j = 0 ; j < X.size() ; ++j) {
for ( size_t i = 0 ; i < L.size() ; ++i) {
Point2 pt = X[j].project(L[i]) ;
graph->addMeasurement(j, i, pt, sigma1);
}
}
const size_t nMeasurements = X.size()*L.size() ;
// add initial
const double noise = baseline*0.1;
boost::shared_ptr<Values> values(new Values);
for ( size_t i = 0 ; i < X.size() ; ++i )
values->insert((int)i, X[i]) ;
// add noise only to the first landmark
for ( size_t i = 0 ; i < L.size() ; ++i ) {
if ( i == 0 ) {
Point3 pt(L[i].x()+noise*getGaussian(),
L[i].y()+noise*getGaussian(),
L[i].z()+noise*getGaussian());
values->insert(i, pt) ;
}
else {
values->insert(i, L[i]) ;
}
}
graph->addCameraConstraint(0, X[0]);
const double reproj_error = 0.5 ;
shared_ptr<Ordering> ordering = getOrdering(X,L);
NonlinearOptimizationParameters::sharedThis params (
new NonlinearOptimizationParameters(1e-7, 1e-7, 0.0, 100, 1e-5, 10, NonlinearOptimizationParameters::SILENT));
Optimizer optimizer(graph, values, ordering, params);
cout << "optimize_varK_SingleMeasurementError::" << endl ;
cout << "before optimization, error is " << optimizer.error() << endl;
Optimizer optimizer2 = optimizer.levenbergMarquardt();
cout << "after optimization, error is " << optimizer2.error() << endl;
CHECK(optimizer2.error() < 0.5 * reproj_error * nMeasurements);
}
TEST( GeneralSFMFactor, optimize_varK_FixCameras ) {
vector<Point3> L = genPoint3();
vector<GeneralCamera> X = genCameraVariableCalibration();
// add measurement with noise
const double noise = baseline*0.1;
shared_ptr<Graph> graph(new Graph());
for ( size_t j = 0 ; j < X.size() ; ++j) {
for ( size_t i = 0 ; i < L.size() ; ++i) {
Point2 pt = X[j].project(L[i]) ;
graph->addMeasurement(j, i, pt, sigma1);
}
}
const size_t nMeasurements = L.size()*X.size();
boost::shared_ptr<Values> values(new Values);
for ( size_t i = 0 ; i < X.size() ; ++i )
values->insert((int)i, X[i]) ;
for ( size_t i = 0 ; i < L.size() ; ++i ) {
Point3 pt(L[i].x()+noise*getGaussian(),
L[i].y()+noise*getGaussian(),
L[i].z()+noise*getGaussian());
//Point3 pt(L[i].x(), L[i].y(), L[i].z());
values->insert(i, pt) ;
}
for ( size_t i = 0 ; i < X.size() ; ++i )
graph->addCameraConstraint(i, X[i]);
const double reproj_error = 1e-5 ;
shared_ptr<Ordering> ordering = getOrdering(X,L);
NonlinearOptimizationParameters::sharedThis params (
new NonlinearOptimizationParameters(1e-7, 1e-7, 0.0, 100, 1e-3, 10, NonlinearOptimizationParameters::SILENT));
Optimizer optimizer(graph, values, ordering, params);
cout << "optimize_varK_FixCameras::" << endl ;
cout << "before optimization, error is " << optimizer.error() << endl;
Optimizer optimizer2 = optimizer.levenbergMarquardt();
cout << "after optimization, error is " << optimizer2.error() << endl;
CHECK(optimizer2.error() < 0.5 * reproj_error * nMeasurements);
}
TEST( GeneralSFMFactor, optimize_varK_FixLandmarks ) {
vector<Point3> L = genPoint3();
vector<GeneralCamera> X = genCameraVariableCalibration();
// add measurement with noise
shared_ptr<Graph> graph(new Graph());
for ( size_t j = 0 ; j < X.size() ; ++j) {
for ( size_t i = 0 ; i < L.size() ; ++i) {
Point2 pt = X[j].project(L[i]) ;
graph->addMeasurement(j, i, pt, sigma1);
}
}
const size_t nMeasurements = L.size()*X.size();
boost::shared_ptr<Values> values(new Values);
for ( size_t i = 0 ; i < X.size() ; ++i ) {
const double
rot_noise = 1e-5,
trans_noise = 1e-3,
focal_noise = 1,
skew_noise = 1e-5,
distort_noise = 1e-5 ;
if ( i == 0 ) {
values->insert((int)i, X[i]) ;
}
else {
Vector delta = Vector_(11,
rot_noise, rot_noise, rot_noise, trans_noise, trans_noise, trans_noise,
focal_noise, focal_noise, skew_noise, distort_noise, distort_noise) ;
// pose_noise*getGaussian(), pose_noise*getGaussian(), pose_noise*getGaussian(), // rotation
// pose_noise*getGaussian(), pose_noise*getGaussian(), pose_noise*getGaussian(), // translation
// calib_noise*getGaussian(), calib_noise*getGaussian(), calib_noise*getGaussian(), calib_noise*getGaussian(), calib_noise*getGaussian()); // K)
values->insert((int)i, X[i].expmap(delta)) ;
}
}
for ( size_t i = 0 ; i < L.size() ; ++i ) {
values->insert(i, L[i]) ;
}
// fix X0 and all landmarks, allow only the X[1] to move
graph->addCameraConstraint(0, X[0]);
for ( size_t i = 0 ; i < L.size() ; ++i )
graph->addPoint3Constraint(i, L[i]);
const double reproj_error = 1e-5 ;
shared_ptr<Ordering> ordering = getOrdering(X,L);
NonlinearOptimizationParameters::sharedThis params (
new NonlinearOptimizationParameters(1e-7, 1e-7, 0.0, 100, 1e-3, 10, NonlinearOptimizationParameters::SILENT));
// new NonlinearOptimizationParameters(1e-7, 1e-7, 0.0, 100, 1e-3, 10, NonlinearOptimizationParameters::TRYDELTA));
Optimizer optimizer(graph, values, ordering, params);
cout << "optimize_varK_FixLandmarks::" << endl ;
cout << "before optimization, error is " << optimizer.error() << endl;
Optimizer optimizer2 = optimizer.levenbergMarquardt();
cout << "after optimization, error is " << optimizer2.error() << endl;
// CHECK(optimizer2.error() < 0.5 * reproj_error * nMeasurements);
CHECK(1);
}
/* ************************************************************************* */
TEST( GeneralSFMFactor, optimize_varK_BA ) {
vector<Point3> L = genPoint3();
vector<GeneralCamera> X = genCameraVariableCalibration();
// add measurement with noise
shared_ptr<Graph> graph(new Graph());
for ( size_t j = 0 ; j < X.size() ; ++j) {
for ( size_t i = 0 ; i < L.size() ; ++i) {
Point2 pt = X[j].project(L[i]) ;
graph->addMeasurement(j, i, pt, sigma1);
}
}
const size_t nMeasurements = X.size()*L.size() ;
// add initial
const double noise = baseline*0.1;
boost::shared_ptr<Values> values(new Values);
for ( size_t i = 0 ; i < X.size() ; ++i )
values->insert((int)i, X[i]) ;
// add noise only to the first landmark
for ( size_t i = 0 ; i < L.size() ; ++i ) {
Point3 pt(L[i].x()+noise*getGaussian(),
L[i].y()+noise*getGaussian(),
L[i].z()+noise*getGaussian());
values->insert(i, pt) ;
}
graph->addCameraConstraint(0, X[0]);
const double reproj_error = 0.5 ;
shared_ptr<Ordering> ordering = getOrdering(X,L);
NonlinearOptimizationParameters::sharedThis params (
new NonlinearOptimizationParameters(1e-7, 1e-7, 0.0, 100, 1e-5, 10, NonlinearOptimizationParameters::SILENT));
Optimizer optimizer(graph, values, ordering, params);
cout << "optimize_varK_BA::" << endl ;
cout << "before optimization, error is " << optimizer.error() << endl;
Optimizer optimizer2 = optimizer.levenbergMarquardt();
cout << "after optimization, error is " << optimizer2.error() << endl;
//CHECK(optimizer2.error() < 0.5 * reproj_error * nMeasurements);
CHECK(1);
}
/* ************************************************************************* */
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
/* ************************************************************************* */