def export_single(filename, cameras, camera_names, filenames):
filenames = transpose_lists(filenames)
data = struct(cameras=export_cameras(camera_names, cameras),
image_sets=export_images(camera_names, filenames))
with open(filename, 'w') as outfile:
json.dump(to_dicts(data), outfile, indent=2)
def calibration_points(boards, detections):
board_detections = transpose_lists(detections)
board_points = [board_correspondences(board, detections) for board, detections
in zip(boards, board_detections)]
return reduce(operator.add, board_points)
def export(filename, calib, names, filenames, master=None):
if master is not None:
calib = calib.with_master(master)
camera_poses = calib.camera_poses.pose_table
filenames = transpose_lists(filenames)
data = struct(
cameras = export_cameras(names.camera, calib.cameras),
# camera_poses = export_sequential(names.camera, camera_poses),
camera_poses = export_camera_poses(names.camera, camera_poses)\
if master is None else export_relative(names.camera, camera_poses, master),
image_sets = export_images(names.camera, filenames)
)
with open(filename, 'w') as outfile:
json.dump(to_dicts(data), outfile, indent=2)
def calibrate_cameras(boards, points, image_sizes, **kwargs):
with ThreadPool() as pool:
f = partial(Camera.calibrate, boards, **kwargs)
return transpose_lists(pool.starmap(f, zip(points, image_sizes)))