gtsam/python/gtsam/tests/test_SfmData.py

122 lines
3.9 KiB
Python

"""
GTSAM Copyright 2010-2019, Georgia Tech Research Corporation,
Atlanta, Georgia 30332-0415
All Rights Reserved
See LICENSE for the license information
Unit tests for testing dataset access.
Author: Frank Dellaert (Python: Sushmita Warrier)
"""
# pylint: disable=invalid-name, no-name-in-module, no-member
from __future__ import print_function
import unittest
import gtsam
import numpy as np
from gtsam import Point2, Point3, SfmData, SfmTrack
from gtsam.utils.test_case import GtsamTestCase
class TestSfmData(GtsamTestCase):
"""Tests for SfmData and SfmTrack modules."""
def setUp(self):
"""Initialize SfmData and SfmTrack"""
self.data = SfmData()
# initialize SfmTrack with 3D point
self.tracks = SfmTrack()
def test_tracks(self):
"""Test functions in SfmTrack"""
# measurement is of format (camera_idx, imgPoint)
# create arbitrary camera indices for two cameras
i1, i2 = 4, 5
# create arbitrary image measurements for cameras i1 and i2
uv_i1 = Point2(12.6, 82)
# translating point uv_i1 along X-axis
uv_i2 = Point2(24.88, 82)
# add measurements to the track
self.tracks.addMeasurement(i1, uv_i1)
self.tracks.addMeasurement(i2, uv_i2)
# Number of measurements in the track is 2
self.assertEqual(self.tracks.numberMeasurements(), 2)
# camera_idx in the first measurement of the track corresponds to i1
cam_idx, img_measurement = self.tracks.measurement(0)
self.assertEqual(cam_idx, i1)
np.testing.assert_array_almost_equal(
Point3(0., 0., 0.),
self.tracks.point3()
)
def test_data(self):
"""Test functions in SfmData"""
# Create new track with 3 measurements
i1, i2, i3 = 3, 5, 6
uv_i1 = Point2(21.23, 45.64)
# translating along X-axis
uv_i2 = Point2(45.7, 45.64)
uv_i3 = Point2(68.35, 45.64)
# add measurements and arbitrary point to the track
measurements = [(i1, uv_i1), (i2, uv_i2), (i3, uv_i3)]
pt = Point3(1.0, 6.0, 2.0)
track2 = SfmTrack(pt)
track2.addMeasurement(i1, uv_i1)
track2.addMeasurement(i2, uv_i2)
track2.addMeasurement(i3, uv_i3)
self.data.addTrack(self.tracks)
self.data.addTrack(track2)
# Number of tracks in SfmData is 2
self.assertEqual(self.data.numberTracks(), 2)
# camera idx of first measurement of second track corresponds to i1
cam_idx, img_measurement = self.data.track(1).measurement(0)
self.assertEqual(cam_idx, i1)
def test_Balbianello(self):
""" Check that we can successfully read a bundler file and create a
factor graph from it
"""
# The structure where we will save the SfM data
filename = gtsam.findExampleDataFile("Balbianello.out")
sfm_data = SfmData.FromBundlerFile(filename)
# Check number of things
self.assertEqual(5, sfm_data.numberCameras())
self.assertEqual(544, sfm_data.numberTracks())
track0 = sfm_data.track(0)
self.assertEqual(3, track0.numberMeasurements())
# Check projection of a given point
self.assertEqual(0, track0.measurement(0)[0])
camera0 = sfm_data.camera(0)
expected = camera0.project(track0.point3())
actual = track0.measurement(0)[1]
self.gtsamAssertEquals(expected, actual, 1)
# We share *one* noiseModel between all projection factors
model = gtsam.noiseModel.Isotropic.Sigma(
2, 1.0) # one pixel in u and v
# Convert to NonlinearFactorGraph
graph = sfm_data.sfmFactorGraph(model)
self.assertEqual(1419, graph.size()) # regression
# Get initial estimate
values = gtsam.initialCamerasAndPointsEstimate(sfm_data)
self.assertEqual(549, values.size()) # regression
if __name__ == '__main__':
unittest.main()