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Extend unit testing of omnidirectional projection 

Test projection function and factors using a stereoscopic (xi=1) reference model, i.e the image height is given by y = 2 f tan(theta/2).
release/4.3a0
roderick-koehle 2021-07-08 19:59:56 +02:00 committed by GitHub
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python/gtsam/tests/test_Cal3Unified.py
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@ -23,6 +23,89 @@ class TestCal3Unified(GtsamTestCase):
self.assertEqual(K.fx(), 1.)
self.assertEqual(K.fx(), 1.)
def test_distortion(self):
"Stereographic fisheye model of focal length f, defined as r/f = 2*tan(theta/2)"
fx, fy, s, u0, v0 = 2, 2, 0, 0, 0
k1, k2, p1, p2 = 0, 0, 0, 0
xi = 1
stereographic = gtsam.Cal3Unified(fx, fy, s, u0, v0, k1, k2, p1, p2, xi)
x, y, z = 1, 0, 1
u, v = stereographic.uncalibrate([x, y])
r = np.linalg.norm([x, y, z])
# Note: 2*tan(atan2(x, z)/2) = 2/(1+sqrt(x^2+z^2))
self.assertAlmostEqual(2*np.tan(np.arctan2(x, z)/2), 2/(1+r))
self.assertAlmostEqual(u, 2/(1+r))
x2, y2 = stereographic.calibrate([u, v])
self.assertAlmostEqual(x2, x)
def test_pinhole(self):
"Spatial stereographic camera projection"
x, y, z = 1.0, 0.0, 1.0
r = np.linalg.norm([x, y, z])
u, v = 2/(1+r), 0.0
objPoint = np.array([x, y, z])
imgPoint = np.array([u, v])
fx, fy, s, u0, v0 = 2, 2, 0, 0, 0
k1, k2, p1, p2 = 0, 0, 0, 0
xi = 1
stereographic = gtsam.Cal3Unified(fx, fy, s, u0, v0, k1, k2, p1, p2, xi)
pose = gtsam.Pose3()
camera = gtsam.PinholeCameraCal3Unified(pose, stereographic)
pt1 = camera.Project(objPoint)
self.gtsamAssertEquals(pt1, np.array([x/z, y/z]))
pt2 = camera.project(objPoint)
self.gtsamAssertEquals(pt2, np.array([u, v]))
obj1 = camera.backproject([u, v], z)
self.gtsamAssertEquals(obj1, np.array([x, y, z]))
r1 = camera.range(np.array([x, y, z]))
self.assertEqual(r1, r)
def test_generic_factor(self):
"Evaluate residual using pose and point as state variables"
fx, fy, s, u0, v0 = 2, 2, 0, 0, 0
k1, k2, p1, p2 = 0, 0, 0, 0
xi = 1
objPoint = np.array([1, 0, 1])
r = np.linalg.norm(objPoint)
imgPoint = np.array([2/(1+r), 0])
graph = gtsam.NonlinearFactorGraph()
state = gtsam.Values()
measured = imgPoint
noiseModel = gtsam.noiseModel.Isotropic.Sigma(2, 1)
poseKey = gtsam.symbol_shorthand.P(0)
pointKey = gtsam.symbol_shorthand.L(0)
k = gtsam.Cal3Unified(fx, fy, s, u0, v0, k1, k2, p1, p2, xi)
state.insert_pose3(poseKey, gtsam.Pose3())
state.insert_point3(pointKey, gtsam.Point3(objPoint))
factor = gtsam.GenericProjectionFactorCal3Unified(measured, noiseModel, poseKey, pointKey, k)
graph.add(factor)
score = graph.error(state)
self.assertAlmostEqual(score, 0)
def test_sfm_factor2(self):
"Evaluate residual with camera, pose and point as state variables"
fx, fy, s, u0, v0 = 2, 2, 0, 0, 0
k1, k2, p1, p2 = 0, 0, 0, 0
xi = 1
objPoint = np.array([1, 0, 1])
r = np.linalg.norm(objPoint)
imgPoint = np.array([2/(1+r), 0])
graph = gtsam.NonlinearFactorGraph()
state = gtsam.Values()
measured = imgPoint
noiseModel = gtsam.noiseModel.Isotropic.Sigma(2, 1)
cameraKey = gtsam.symbol_shorthand.K(0)
poseKey = gtsam.symbol_shorthand.P(0)
landmarkKey = gtsam.symbol_shorthand.L(0)
k = gtsam.Cal3Unified(fx, fy, s, u0, v0, k1, k2, p1, p2, xi)
state.insert_cal3unified(cameraKey, k)
state.insert_pose3(poseKey, gtsam.Pose3())
state.insert_point3(landmarkKey, gtsam.Point3(objPoint))
factor = gtsam.GeneralSFMFactor2Cal3Unified(measured, noiseModel, poseKey, landmarkKey, cameraKey)
graph.add(factor)
score = graph.error(state)
self.assertAlmostEqual(score, 0)
def test_retract(self):
expected = gtsam.Cal3Unified(100 + 2, 105 + 3, 0.0 + 4, 320 + 5, 240 + 6,
1e-3 + 7, 2.0*1e-3 + 8, 3.0*1e-3 + 9, 4.0*1e-3 + 10, 0.1 + 1)