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Introduce setUpClass, python snake_case variables 

Test case fails if object depth z is not equal 1.
release/4.3a0
roderick-koehle 2021-07-09 11:14:10 +02:00 committed by GitHub
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103
python/gtsam/tests/test_Cal3Fisheye.py
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@ -5,8 +5,9 @@ All Rights Reserved
See LICENSE for the license information
Cal3Unified unit tests.
Cal3Fisheye unit tests.
Author: Frank Dellaert & Duy Nguyen Ta (Python)
Refactored: Roderick Koehle
"""
import unittest
@ -14,78 +15,80 @@ import numpy as np
import gtsam
from gtsam.utils.test_case import GtsamTestCase
from gtsam.symbol_shorthand import K, L, P
class TestCal3Fisheye(GtsamTestCase):
@classmethod
def setUpClass(cls):
"""
Equidistant fisheye projection
An equidistant fisheye projection with focal length f is defined
as the relation r/f = tan(theta), with r being the radius in the
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!
u, v = np.arctan2(x, z), 0.0
cls.obj_point = np.array([x, y, z])
cls.img_point = np.array([u, v])
def test_Cal3Fisheye(self):
K = gtsam.Cal3Fisheye()
self.assertEqual(K.fx(), 1.)
self.assertEqual(K.fy(), 1.)
def test_distortion(self):
"Equidistant fisheye model of focal length f, defined as r/f = tan(theta)"
"""Fisheye distortion and rectification"""
equidistant = gtsam.Cal3Fisheye()
x, y, z = 1, 0, 1
u, v = equidistant.uncalibrate([x, y])
x2, y2 = equidistant.calibrate([u, v])
self.assertAlmostEqual(u, np.arctan2(x, z))
self.assertAlmostEqual(v, 0)
self.assertAlmostEqual(x2, x)
self.assertAlmostEqual(y2, 0)
perspective_pt = self.obj_point[0:2]/self.obj_point[2]
distorted_pt = equidistant.uncalibrate(perspective_pt)
rectified_pt = equidistant.calibrate(distorted_pt)
self.gtsamAssertEquals(distorted_pt, self.img_point)
self.gtsamAssertEquals(rectified_pt, perspective_pt)
def test_pinhole(self):
"Spatial equidistant camera projection"
x, y, z = 1.0, 0.0, 1.0
u, v = np.arctan2(x, z), 0.0
"""Spatial equidistant camera projection"""
camera = gtsam.PinholeCameraCal3Fisheye()
pt1 = camera.Project([x, y, z])
pt1 = camera.Project(self.obj_point) # Perspective projection
pt2 = camera.project(self.obj_point) # Equidistant projection
x, y, z = self.obj_point
obj1 = camera.backproject(self.img_point, z)
r1 = camera.range(self.obj_point)
r = np.linalg.norm(self.obj_point)
self.gtsamAssertEquals(pt1, np.array([x/z, y/z]))
pt2 = camera.project([x, y, z])
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, np.linalg.norm([x, y, z]))
self.gtsamAssertEquals(pt2, self.img_point)
self.gtsamAssertEquals(obj1, self.obj_point)
self.assertEqual(r1, r)
def test_generic_factor(self):
"Evaluate residual using pose and point as state variables"
objPoint = np.array([1, 0, 1])
imgPoint = np.array([np.arctan2(objPoint[0], objPoint[2]), 0])
"""Evaluate residual using pose and point as state variables"""
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)
measured = self.img_point
noise_model = gtsam.noiseModel.Isotropic.Sigma(2, 1)
pose_key, point_key = P(0), L(0)
k = gtsam.Cal3Fisheye()
state.insert_pose3(poseKey, gtsam.Pose3())
state.insert_point3(pointKey, gtsam.Point3(objPoint))
factor = gtsam.GenericProjectionFactorCal3Fisheye(measured, noiseModel, poseKey, pointKey, k)
state.insert_pose3(pose_key, gtsam.Pose3())
state.insert_point3(point_key, self.obj_point)
factor = gtsam.GenericProjectionFactorCal3Fisheye(measured, noise_model, pose_key, point_key, 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"
objPoint = np.array([1, 0, 1])
imgPoint = np.array([np.arctan2(objPoint[0], objPoint[2]), 0])
"""Evaluate residual with camera, pose and point as state variables"""
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)
measured = self.img_point
noise_model = gtsam.noiseModel.Isotropic.Sigma(2, 1)
camera_key, pose_key, landmark_key = K(0), P(0), L(0)
k = gtsam.Cal3Fisheye()
state.insert_cal3fisheye(cameraKey, k)
state.insert_pose3(poseKey, gtsam.Pose3())
state.insert_point3(landmarkKey, gtsam.Point3(objPoint))
factor = gtsam.GeneralSFMFactor2Cal3Fisheye(measured, noiseModel, poseKey, landmarkKey, cameraKey)
state.insert_cal3fisheye(camera_key, k)
state.insert_pose3(pose_key, gtsam.Pose3())
state.insert_point3(landmark_key, gtsam.Point3(self.obj_point))
factor = gtsam.GeneralSFMFactor2Cal3Fisheye(measured, noise_model, pose_key, landmark_key, camera_key)
graph.add(factor)
score = graph.error(state)
self.assertAlmostEqual(score, 0)
@ -93,12 +96,12 @@ class TestCal3Fisheye(GtsamTestCase):
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)
K = gtsam.Cal3Fisheye(100, 105, 0.0, 320, 240,
k = gtsam.Cal3Fisheye(100, 105, 0.0, 320, 240,
1e-3, 2.0*1e-3, 3.0*1e-3, 4.0*1e-3)
d = np.array([2, 3, 4, 5, 6, 7, 8, 9, 10], order='F')
actual = K.retract(d)
actual = k.retract(d)
self.gtsamAssertEquals(actual, expected)
np.testing.assert_allclose(d, K.localCoordinates(actual))
np.testing.assert_allclose(d, k.localCoordinates(actual))
if __name__ == "__main__":