def test_bundle_projection_fixed_internals(scene_synthetic):
reference = scene_synthetic[0].get_reconstruction()
camera_priors = {c.id: c for c in scene_synthetic[0].cameras}
graph = tracking.as_graph(scene_synthetic[5])
# Create the connnections in the reference
for point_id in reference.points.keys():
if point_id in graph:
for shot_id, g_obs in graph[point_id].items():
color = g_obs["feature_color"]
pt = g_obs["feature"]
obs = pysfm.Observation(
pt[0],
pt[1],
g_obs["feature_scale"],
g_obs["feature_id"],
color[0],
color[1],
color[2],
)
reference.map.add_observation(shot_id, point_id, obs)
orig_camera = copy.deepcopy(reference.cameras["1"])
custom_config = config.default_config()
custom_config["bundle_use_gps"] = False
custom_config["optimize_camera_parameters"] = False
reconstruction.bundle(reference, camera_priors, [], custom_config)
assert _projection_errors_std(reference.points) < 5e-3
assert reference.cameras["1"].focal == orig_camera.focal
assert reference.cameras["1"].k1 == orig_camera.k1
assert reference.cameras["1"].k2 == orig_camera.k2
def test_bundle_projection_fixed_internals(scene_synthetic):
reference = scene_synthetic[0].get_reconstruction()
camera_priors = {c.id: c for c in scene_synthetic[0].cameras}
graph = tracking.as_graph(scene_synthetic[5])
adjusted = copy.deepcopy(reference)
custom_config = config.default_config()
custom_config['bundle_use_gps'] = False
custom_config['optimize_camera_parameters'] = False
reconstruction.bundle(graph, adjusted, camera_priors, {}, custom_config)
assert _projection_errors_std(adjusted.points) < 5e-3
assert reference.cameras['1'].focal == adjusted.cameras['1'].focal
assert reference.cameras['1'].k1 == adjusted.cameras['1'].k1
assert reference.cameras['1'].k2 == adjusted.cameras['1'].k2
def run(self, args):
start = time.time()
data = dataset.DataSet(args.dataset)
tracks_manager = data.load_tracks_manager()
graph = tracking.as_graph(tracks_manager)
reconstructions = data.load_reconstruction(args.input)
camera_priors = data.load_camera_models()
gcp = data.load_ground_control_points()
for reconstruction in reconstructions:
orec.bundle(graph, reconstruction, camera_priors, gcp, data.config)
end = time.time()
with open(data.profile_log(), 'a') as fout:
fout.write('bundle: {0}\n'.format(end - start))
data.save_reconstruction(reconstructions, args.output)
