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Testing CameraSet and triangulatePoint3 

Currently triangulatePoint3 returns wrong results for fisheye models. The template for PinholePose may be implemented for a fixed size of variable dimensions.
release/4.3a0
roderick-koehle 2021-07-11 14:11:40 +02:00 committed by GitHub
parent 0a73961f5a
commit 941594c94b
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python/gtsam/tests/test_Cal3Fisheye.py
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@ -29,7 +29,7 @@ class TestCal3Fisheye(GtsamTestCase):
image plane and theta the incident angle of the object point.
"""
x, y, z = 1.0, 0.0, 1.0
# x, y, z = 0.5, 0.0, 2.0 <== Note: this example fails!
# x, y, z = 0.5, 0.0, 2.0
u, v = np.arctan2(x, z), 0.0
cls.obj_point = np.array([x, y, z])
cls.img_point = np.array([u, v])
@ -93,6 +93,44 @@ class TestCal3Fisheye(GtsamTestCase):
score = graph.error(state)
self.assertAlmostEqual(score, 0)
@unittest.skip("triangulatePoint3 currently seems to require perspective projections.")
def test_triangulation_skipped(self):
"""Estimate spatial point from image measurements"""
p1 = [-1.0, 0.0, -1.0]
p2 = [ 1.0, 0.0, -1.0]
q1 = gtsam.Rot3(1.0, 0.0, 0.0, 0.0)
q2 = gtsam.Rot3(1.0, 0.0, 0.0, 0.0)
obj_point = np.array([0.0, 0.0, 0.0])
pose1 = gtsam.Pose3(q1, p1)
pose2 = gtsam.Pose3(q2, p2)
camera1 = gtsam.PinholeCameraCal3Fisheye(pose1)
camera2 = gtsam.PinholeCameraCal3Fisheye(pose2)
cameras = gtsam.CameraSetCal3Fisheye([camera1, camera2])
measurements = gtsam.Point2Vector([k.project(obj_point) for k in cameras])
triangulated = gtsam.triangulatePoint3(cameras, measurements, rank_tol=1e-9, optimize=True)
self.gtsamAssertEquals(measurements[0], self.img_point)
self.gtsamAssertEquals(triangulated, obj_point)
def test_triangulation_rectify(self):
"""Estimate spatial point from image measurements using rectification"""
p1 = [-1.0, 0.0, -1.0]
p2 = [ 1.0, 0.0, -1.0]
q1 = gtsam.Rot3(1.0, 0.0, 0.0, 0.0)
q2 = gtsam.Rot3(1.0, 0.0, 0.0, 0.0)
obj_point = np.array([0.0, 0.0, 0.0])
pose1 = gtsam.Pose3(q1, p1)
pose2 = gtsam.Pose3(q2, p2)
camera1 = gtsam.PinholeCameraCal3Fisheye(pose1)
camera2 = gtsam.PinholeCameraCal3Fisheye(pose2)
cameras = gtsam.CameraSetCal3Fisheye([camera1, camera2])
measurements = gtsam.Point2Vector([k.project(obj_point) for k in cameras])
rectified = gtsam.Point2Vector([k.calibration().calibrate(pt) for k, pt in zip(cameras, measurements)])
shared_cal = gtsam.Cal3_S2()
poses = gtsam.Pose3Vector([pose1, pose2])
triangulated = gtsam.triangulatePoint3(poses, shared_cal, rectified, rank_tol=1e-9, optimize=False)
self.gtsamAssertEquals(measurements[0], self.img_point)
self.gtsamAssertEquals(triangulated, obj_point)
def test_retract(self):
expected = gtsam.Cal3Fisheye(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)