def get_camera_info_for_robot(robot_name: str) -> CameraInfo:
"""
Returns a CameraInfo object for the given robot.
This is in a good format to pass to PinholeCameraModel:
self.pcm = PinholeCameraModel()
self.pcm.fromCameraInfo(self.ci)
The fields are simply lists (not array or matrix).
Raises:
NoCameraInfoAvailable if no info available
InvalidCameraInfo if the info exists but is invalid
"""
if robot_name == dtu.DuckietownConstants.ROBOT_NAME_FOR_TESTS:
calib_data = dtu.yaml_load(default_camera_info)
fn = None
else:
# find the file
fn = get_camera_info_config_file(robot_name)
# load the YAML
calib_data = dtu.yaml_load_file(fn, plain_yaml=True)
# convert the YAML
try:
camera_info = camera_info_from_yaml(calib_data)
except InvalidCameraInfo as e:
msg = f"Invalid data in file {fn}"
raise InvalidCameraInfo(msg) from e
check_camera_info_sane_for_DB17(camera_info)
return camera_info
def get_homography_for_robot(robot_name: str) -> np.ndarray:
dtu.check_isinstance(robot_name, str)
# find the file
fn = get_homography_info_config_file(robot_name)
# load the YAML
data = dtu.yaml_load_file(fn, plain_yaml=True) # True means "plain"
# convert the YAML
homography = homography_from_yaml(data)
return homography
def get_logs_cloud():
cloud_file = dtu.require_resource("cloud2.yaml")
with dtu.timeit_wall("loading DB"):
dtu.logger.info(f"Loading cloud DB {dtu.friendly_path(cloud_file)}")
with dtu.timeit_wall("YAML load file"):
data = dtu.yaml_load_file(cloud_file, plain_yaml=True)
dtu.logger.debug("Conversion")
logs = logs_from_yaml(data)
logs = dict(logs)
dtu.logger.info(f"Loaded cloud DB with {len(logs)} entries.")
return logs
def load_board_info(filename: str = None) -> dict:
"""Load calibration checkerboard info"""
if filename is None:
root = dru.get_ros_package_path("duckietown")
filename = root + "/config/baseline/ground_projection/ground_projection/default.yaml"
if not os.path.isfile(filename):
msg = f"No such file: {filename}"
raise dtu.DTException(msg)
target_data = dtu.yaml_load_file(filename)
target_info = {
"width": target_data["board_w"],
"height": target_data["board_h"],
"square_size": target_data["square_size"],
"x_offset": target_data["x_offset"],
"y_offset": target_data["y_offset"],
"offset": np.array([target_data["x_offset"], -target_data["y_offset"]]),
"size": (target_data["board_w"], target_data["board_h"]),
}
dtu.logger.info("Loaded checkerboard parameters")
return target_info