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Shared data for triangulation unit tests

release/4.3a0
roderick-koehle 2021-07-13 22:00:21 +02:00 committed by GitHub
parent f53f5db4d1
commit 3402e46ad1
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1 changed files with 18 additions and 28 deletions
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46
python/gtsam/tests/test_Cal3Fisheye.py
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@ -34,6 +34,19 @@ class TestCal3Fisheye(GtsamTestCase):
cls.obj_point = np.array([x, y, z]) cls.obj_point = np.array([x, y, z])
cls.img_point = np.array([u, v]) cls.img_point = np.array([u, v])
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)
pose1 = gtsam.Pose3(q1, p1)
pose2 = gtsam.Pose3(q2, p2)
camera1 = gtsam.PinholeCameraCal3Fisheye(pose1)
camera2 = gtsam.PinholeCameraCal3Fisheye(pose2)
cls.origin = np.array([0.0, 0.0, 0.0])
cls.poses = gtsam.Pose3Vector([pose1, pose2])
cls.cameras = gtsam.CameraSetCal3Fisheye([camera1, camera2])
cls.measurements = gtsam.Point2Vector([k.project(cls.origin) for k in cls.cameras])
def test_Cal3Fisheye(self): def test_Cal3Fisheye(self):
K = gtsam.Cal3Fisheye() K = gtsam.Cal3Fisheye()
self.assertEqual(K.fx(), 1.) self.assertEqual(K.fx(), 1.)
@ -96,40 +109,17 @@ class TestCal3Fisheye(GtsamTestCase):
@unittest.skip("triangulatePoint3 currently seems to require perspective projections.") @unittest.skip("triangulatePoint3 currently seems to require perspective projections.")
def test_triangulation_skipped(self): def test_triangulation_skipped(self):
"""Estimate spatial point from image measurements""" """Estimate spatial point from image measurements"""
p1 = [-1.0, 0.0, -1.0] triangulated = gtsam.triangulatePoint3(self.cameras, self.measurements, rank_tol=1e-9, optimize=True)
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(measurements[0], self.img_point)
self.gtsamAssertEquals(triangulated, obj_point) self.gtsamAssertEquals(triangulated, self.origin)
def test_triangulation_rectify(self): def test_triangulation_rectify(self):
"""Estimate spatial point from image measurements using rectification""" """Estimate spatial point from image measurements using rectification"""
p1 = [-1.0, 0.0, -1.0] rectified = gtsam.Point2Vector([k.calibration().calibrate(pt) for k, pt in zip(self.cameras, self.measurements)])
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() shared_cal = gtsam.Cal3_S2()
poses = gtsam.Pose3Vector([pose1, pose2]) triangulated = gtsam.triangulatePoint3(self.poses, shared_cal, rectified, rank_tol=1e-9, optimize=False)
triangulated = gtsam.triangulatePoint3(poses, shared_cal, rectified, rank_tol=1e-9, optimize=False)
self.gtsamAssertEquals(measurements[0], self.img_point) self.gtsamAssertEquals(measurements[0], self.img_point)
self.gtsamAssertEquals(triangulated, obj_point) self.gtsamAssertEquals(triangulated, self.origin)
def test_retract(self): def test_retract(self):
expected = gtsam.Cal3Fisheye(100 + 2, 105 + 3, 0.0 + 4, 320 + 5, 240 + 6, expected = gtsam.Cal3Fisheye(100 + 2, 105 + 3, 0.0 + 4, 320 + 5, 240 + 6,