def reconstruction_to_json()

in opensfm/io.py [0:0]

• 31 lines of code
• 13 McCabe index (conditional complexity)

def reconstruction_to_json(reconstruction: types.Reconstruction) -> Dict[str, Any]:
    """
    Write a reconstruction to a json object
    """
    obj = {"cameras": {}, "shots": {}, "points": {}, "biases": {}}

    # Extract cameras
    for camera in reconstruction.cameras.values():
        obj["cameras"][camera.id] = camera_to_json(camera)

    # Extract cameras biases
    for camera_id, bias in reconstruction.biases.items():
        obj["biases"][camera_id] = bias_to_json(bias)

    # Extract rig models
    if len(reconstruction.rig_cameras):
        obj["rig_cameras"] = {}
    for rig_camera in reconstruction.rig_cameras.values():
        obj["rig_cameras"][rig_camera.id] = rig_camera_to_json(rig_camera)
    if len(reconstruction.rig_instances):
        obj["rig_instances"] = {}
    for rig_instance in reconstruction.rig_instances.values():
        obj["rig_instances"][rig_instance.id] = rig_instance_to_json(rig_instance)

    # Extract shots
    for shot in reconstruction.shots.values():
        obj["shots"][shot.id] = shot_to_json(shot)

    # Extract points
    for point in reconstruction.points.values():
        obj["points"][point.id] = point_to_json(point)

    # Extract pano_shots
    if hasattr(reconstruction, "pano_shots"):
        if len(reconstruction.pano_shots) > 0:
            obj["pano_shots"] = {}
            for shot in reconstruction.pano_shots.values():
                obj["pano_shots"][shot.id] = shot_to_json(shot)

    # Extract reference topocentric frame
    if reconstruction.reference:
        ref = reconstruction.reference
        obj["reference_lla"] = {
            "latitude": ref.lat,
            "longitude": ref.lon,
            "altitude": ref.alt,
        }

    return obj