DefocusOTFPerturber

class nrtk.impls.perturb_image.pybsm.defocus_otf_perturber.DefocusOTFPerturber(sensor: PybsmSensor | None = None, scenario: PybsmScenario | None = None, w_x: float | None = None, w_y: float | None = None, interp: bool = True, box_alignment_mode: str = 'extent')

DefocusOTFPerturber applies optical defocus perturbations to input images based on specified sensor and scenario configurations. The perturbation uses the Optical Transfer Function (OTF) and Point Spread Function (PSF) for simulation.

Attributes:: sensor (PybsmSensor | None): The sensor configuration for the simulation. scenario (PybsmScenario | None): The scenario configuration, such as altitude and ground range. w_x (float | None): Defocus parameter in the x-direction. w_y (float | None): Defocus parameter in the y-direction. interp (bool): Whether to interpolate atmosphere data. mtf_wavelengths (np.ndarray): Array of wavelengths used for Modulation Transfer Function (MTF). D (float): Lens diameter in meters. slant_range (float): Slant range in meters, calculated from altitude and ground range. ifov (float): Instantaneous Field of View (IFOV).
Methods:: perturb: Applies the defocus effect to the input image. __call__: Alias for the perturb method. get_default_config: Provides the default configuration for the perturber. from_config: Instantiates the perturber from a configuration dictionary. get_config: Retrieves the current configuration of the perturber instance.

Methods

`from_config`	Instantiates a DefocusOTFPerturber from a configuration dictionary.
`get_config`	Returns the current configuration of the DefocusOTFPerturber instance.
`get_default_config`	Provides the default configuration for DefocusOTFPerturber instances.
`get_impls`	Discover and return a set of classes that implement the calling class.
`get_type_string`	Returns the fully qualified type string of the PerturbImage class or its subclass.
`is_usable`	Checks if the necessary dependencies pyBSM is available.
`perturb`

__init__(sensor: PybsmSensor | None = None, scenario: PybsmScenario | None = None, w_x: float | None = None, w_y: float | None = None, interp: bool = True, box_alignment_mode: str = 'extent') → None

Initializes a DefocusOTFPerturber instance with the specified parameters.

Args:

sensor (PybsmSensor | None): Sensor configuration for the simulation. scenario (PybsmScenario | None): Scenario configuration (altitude, ground range, etc.). w_x (float | None): the 1/e blur spot radii in the x direction. Defaults to the sensor’s value if provided. w_y (float | None): the 1/e blur spot radii in the y direction. Defaults to the sensor’s value if provided. interp (bool): Whether to interpolate atmosphere data. Defaults to True. box_alignment_mode (string) Mode for how to handle how bounding boxes change.

Should be one of the following options:
extent: a new axis-aligned bounding box that encases the transformed misaligned box extant: a new axis-aligned bounding box that is encased inside the transformed misaligned box median: median between extent and extant

Default value is extent

classmethod from_config(config_dict: dict, merge_default: bool = True) → Self

Instantiates a DefocusOTFPerturber from a configuration dictionary.

Args:: config_dict (dict): Configuration dictionary with initialization parameters. merge_default (bool, optional): Whether to merge with default configuration. Defaults to True.
Returns:: C: An instance of DefocusOTFPerturber configured according to config_dict.

get_config() → dict[str, Any]

Returns the current configuration of the DefocusOTFPerturber instance.

Returns:: dict[str, Any]: Configuration dictionary with current settings.

classmethod get_default_config() → dict[str, Any]

Provides the default configuration for DefocusOTFPerturber instances.

Returns:: dict[str, Any]: A dictionary with the default configuration values.

classmethod is_usable() → bool

Checks if the necessary dependencies pyBSM is available.

Returns:: bool: True if pyBSM is available; False otherwise.

perturb(image: np.ndarray, boxes: Iterable[tuple[AxisAlignedBoundingBox, dict[Hashable, float]]] | None = None, additional_params: dict[str, Any] | None = None) → tuple[np.ndarray, Iterable[tuple[AxisAlignedBoundingBox, dict[Hashable, float]]] | None]

Raises:: ValueError if ‘img_gsd’ not present in additional_params