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fix syntax errors

release/4.3a0
John Lambert 2022-01-12 13:01:23 -05:00 committed by GitHub
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commit d66b1d7a84
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1 changed files with 71 additions and 67 deletions
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138
python/gtsam/tests/test_Triangulation.py
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@ -6,29 +6,39 @@ All Rights Reserved
See LICENSE for the license information
Test Triangulation
Author: Frank Dellaert & Fan Jiang (Python)
Authors: Frank Dellaert & Fan Jiang (Python) & Sushmita Warrier & John Lambert
"""
import unittest
from typing import Union
from typing import Optional, Union
import numpy as np
import gtsam
from gtsam import (Cal3_S2, Cal3Bundler, CameraSetCal3_S2,
CameraSetCal3Bundler, PinholeCameraCal3_S2,
PinholeCameraCal3Bundler, Point2Vector, Point3, Pose3,
Pose3Vector, Rot3)
from gtsam import (
Cal3_S2,
Cal3Bundler,
CameraSetCal3_S2,
CameraSetCal3Bundler,
PinholeCameraCal3_S2,
PinholeCameraCal3Bundler,
Point2,
Point2Vector,
Point3,
Pose3,
Pose3Vector,
Rot3,
)
from gtsam.utils.test_case import GtsamTestCase
UPRIGHT = Rot3.Ypr(-np.pi / 2, 0., -np.pi / 2)
UPRIGHT = Rot3.Ypr(-np.pi / 2, 0.0, -np.pi / 2)
class TestTriangulationExample(GtsamTestCase):
""" Tests for triangulation with shared and individual calibrations """
"""Tests for triangulation with shared and individual calibrations"""
def setUp(self):
""" Set up two camera poses """
"""Set up two camera poses"""
# Looking along X-axis, 1 meter above ground plane (x-y)
pose1 = Pose3(UPRIGHT, Point3(0, 0, 1))
@ -42,16 +52,22 @@ class TestTriangulationExample(GtsamTestCase):
# landmark ~5 meters infront of camera
self.landmark = Point3(5, 0.5, 1.2)
def generate_measurements(self, calibration: Union[Cal3Bundler, Cal3_S2], camera_model, cal_params, camera_set=None):
def generate_measurements(
self,
calibration: Union[Cal3Bundler, Cal3_S2],
camera_model,
cal_params,
camera_set: Optional[Union[CameraSetCal3Bundler, CameraSetCal3_S2]] = None,
):
"""
Generate vector of measurements for given calibration and camera model.
Args:
Args:
calibration: Camera calibration e.g. Cal3_S2
camera_model: Camera model e.g. PinholeCameraCal3_S2
cal_params: Iterable of camera parameters for `calibration` e.g. [K1, K2]
camera_set: Cameraset object (for individual calibrations)
Returns:
list of measurements and list/CameraSet object for cameras
"""
@ -71,19 +87,15 @@ class TestTriangulationExample(GtsamTestCase):
return measurements, cameras
def test_TriangulationExample(self) -> None:
""" Tests triangulation with shared Cal3_S2 calibration"""
"""Tests triangulation with shared Cal3_S2 calibration"""
# Some common constants
sharedCal = (1500, 1200, 0, 640, 480)
measurements, _ = self.generate_measurements(Cal3_S2,
PinholeCameraCal3_S2,
(sharedCal, sharedCal))
measurements, _ = self.generate_measurements(Cal3_S2, PinholeCameraCal3_S2, (sharedCal, sharedCal))
triangulated_landmark = gtsam.triangulatePoint3(self.poses,
Cal3_S2(sharedCal),
measurements,
rank_tol=1e-9,
optimize=True)
triangulated_landmark = gtsam.triangulatePoint3(
self.poses, Cal3_S2(sharedCal), measurements, rank_tol=1e-9, optimize=True
)
self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-9)
# Add some noise and try again: result should be ~ (4.995, 0.499167, 1.19814)
@ -91,59 +103,49 @@ class TestTriangulationExample(GtsamTestCase):
measurements_noisy.append(measurements[0] - np.array([0.1, 0.5]))
measurements_noisy.append(measurements[1] - np.array([-0.2, 0.3]))
triangulated_landmark = gtsam.triangulatePoint3(self.poses,
Cal3_S2(sharedCal),
measurements_noisy,
rank_tol=1e-9,
optimize=True)
triangulated_landmark = gtsam.triangulatePoint3(
self.poses, Cal3_S2(sharedCal), measurements_noisy, rank_tol=1e-9, optimize=True
)
self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-2)
def test_distinct_Ks(self) -> None:
""" Tests triangulation with individual Cal3_S2 calibrations """
"""Tests triangulation with individual Cal3_S2 calibrations"""
# two camera parameters
K1 = (1500, 1200, 0, 640, 480)
K2 = (1600, 1300, 0, 650, 440)
measurements, cameras = self.generate_measurements(Cal3_S2,
PinholeCameraCal3_S2,
(K1, K2),
camera_set=CameraSetCal3_S2)
measurements, cameras = self.generate_measurements(
Cal3_S2, PinholeCameraCal3_S2, (K1, K2), camera_set=CameraSetCal3_S2
)
triangulated_landmark = gtsam.triangulatePoint3(cameras,
measurements,
rank_tol=1e-9,
optimize=True)
triangulated_landmark = gtsam.triangulatePoint3(cameras, measurements, rank_tol=1e-9, optimize=True)
self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-9)
def test_distinct_Ks_Bundler(self) -> None:
""" Tests triangulation with individual Cal3Bundler calibrations"""
"""Tests triangulation with individual Cal3Bundler calibrations"""
# two camera parameters
K1 = (1500, 0, 0, 640, 480)
K2 = (1600, 0, 0, 650, 440)
measurements, cameras = self.generate_measurements(Cal3Bundler,
PinholeCameraCal3Bundler,
(K1, K2),
camera_set=CameraSetCal3Bundler)
measurements, cameras = self.generate_measurements(
Cal3Bundler, PinholeCameraCal3Bundler, (K1, K2), camera_set=CameraSetCal3Bundler
)
triangulated_landmark = gtsam.triangulatePoint3(cameras,
measurements,
rank_tol=1e-9,
optimize=True)
triangulated_landmark = gtsam.triangulatePoint3(cameras, measurements, rank_tol=1e-9, optimize=True)
self.gtsamAssertEquals(self.landmark, triangulated_landmark, 1e-9)
def test_triangulation_robust_three_poses(self) -> None:
"""Ensure triangulation with a robust model works."""
sharedCal = Cal3_S2(1500, 1200, 0, 640, 480)
# landmark ~5 meters infront of camera
landmark = Point3(5, 0.5, 1.2)
pose1 = Pose3(UPRIGHT, Point3(0, 0, 1))
pose2 = pose1 * Pose3(Rot3(), Point3(1, 0, 0))
pose3 = pose1 * Pose3(Rot3.Ypr(0.1, 0.2, 0.1), Point3(0.1, -2, -.1))
pose3 = pose1 * Pose3(Rot3.Ypr(0.1, 0.2, 0.1), Point3(0.1, -2, -0.1))
camera1 = PinholeCameraCal3_S2(pose1, sharedCal)
camera2 = PinholeCameraCal3_S2(pose2, sharedCal)
camera3 = PinholeCameraCal3_S2(pose3, sharedCal)
@ -151,34 +153,36 @@ class TestTriangulationExample(GtsamTestCase):
z1: Point2 = camera1.project(landmark)
z2: Point2 = camera2.project(landmark)
z3: Point2 = camera3.project(landmark)
poses = [pose1, pose2, pose3]
poses = gtsam.Pose3Vector([pose1, pose2, pose3])
measurements = Point2Vector([z1, z2, z3])
# noise free, so should give exactly the landmark
actual = gtsam.triangulatePoint3(poses, sharedCal, measurements)
self.assert_equal(landmark, actual, 1e-2)
actual = gtsam.triangulatePoint3(poses, sharedCal, measurements, rank_tol=1e-9, optimize=False)
self.assertTrue(np.allclose(landmark, actual, atol=1e-2))
# Add outlier
measurements.at(0) += Point2(100, 120) # very large pixel noise!
measurements[0] += Point2(100, 120) # very large pixel noise!
# now estimate does not match landmark
actual2 = gtsam.triangulatePoint3<Cal3_S2>(poses, sharedCal, measurements)
actual2 = gtsam.triangulatePoint3(poses, sharedCal, measurements, rank_tol=1e-9, optimize=False)
# DLT is surprisingly robust, but still off (actual error is around 0.26m)
self.assertTrue( (landmark - actual2).norm() >= 0.2)
self.assertTrue( (landmark - actual2).norm() <= 0.5)
self.assertTrue(np.linalg.norm(landmark - actual2) >= 0.2)
self.assertTrue(np.linalg.norm(landmark - actual2) <= 0.5)
# Again with nonlinear optimization
actual3 = gtsam.triangulatePoint3(poses, sharedCal, measurements, 1e-9, true)
actual3 = gtsam.triangulatePoint3(poses, sharedCal, measurements, rank_tol=1e-9, optimize=True)
# result from nonlinear (but non-robust optimization) is close to DLT and still off
self.assertEqual(actual2, actual3, 0.1)
self.assertTrue(np.allclose(actual2, actual3, atol=0.1))
# Again with nonlinear optimization, this time with robust loss
model = noiseModel.Robust.Create(noiseModel.mEstimator.Huber.Create(1.345), noiseModel.Unit.Create(2))
actual4 = gtsam.triangulatePoint3(poses, sharedCal, measurements, 1e-9, true, model)
model = gtsam.noiseModel.Robust.Create(
gtsam.noiseModel.mEstimator.Huber.Create(1.345), gtsam.noiseModel.Unit.Create(2)
)
actual4 = gtsam.triangulatePoint3(poses, sharedCal, measurements, rank_tol=1e-9, optimize=True, model=model)
# using the Huber loss we now have a quite small error!! nice!
self.assertEqual(landmark, actual4, 0.05)
self.assertTrue(np.allclose(landmark, actual4, atol=0.05))
if __name__ == "__main__":
unittest.main()