def _reconstruction_from_rigs_and_assignments(data: DataSetBase):
assignments = data.load_rig_assignments()
models = data.load_rig_models()
if not data.reference_lla_exists():
data.invent_reference_lla()
base_rotation = np.zeros(3)
reconstructions = []
for rig_id, instances in assignments.items():
rig_cameras = models[rig_id]["rig_cameras"]
reconstruction = types.Reconstruction()
reconstruction.cameras = data.load_camera_models()
for instance in instances:
for image, camera_id in instance:
rig_camera = rig_cameras[camera_id]
rig_pose = pygeometry.Pose(base_rotation)
rig_pose.set_origin(
orec.get_image_metadata(data, image).gps_position.value)
rig_camera_pose = pygeometry.Pose(rig_camera["rotation"],
rig_camera["translation"])
d = data.load_exif(image)
shot = reconstruction.create_shot(image, d["camera"])
shot.pose = rig_camera_pose.compose(rig_pose)
shot.metadata = orec.get_image_metadata(data, image)
reconstructions.append(reconstruction)
return reconstructions
def _reconstruction_from_rigs_and_assignments(data: DataSetBase):
assignments = data.load_rig_assignments()
rig_cameras = data.load_rig_cameras()
data.init_reference()
reconstruction = types.Reconstruction()
reconstruction.cameras = data.load_camera_models()
for rig_instance_id, instance in assignments.items():
for image, rig_camera_id in instance:
rig_camera = rig_cameras[rig_camera_id]
reconstruction.add_rig_camera(
pymap.RigCamera(rig_camera.pose, rig_camera_id))
instance_obj = reconstruction.add_rig_instance(
pymap.RigInstance(rig_instance_id))
instance_obj.pose.set_origin(
helpers.get_image_metadata(data, image).gps_position.value)
d = data.load_exif(image)
shot = reconstruction.create_shot(
image,
camera_id=d["camera"],
rig_camera_id=rig_camera_id,
rig_instance_id=rig_instance_id,
)
shot.metadata = helpers.get_image_metadata(data, image)
return [reconstruction]
