SimpleGenericGenerator

class nrtk.impls.gen_object_detector_blackbox_response.simple_generic_generator.SimpleGenericGenerator(images: Sequence[ndarray[Any, Any]], ground_truth: Sequence[Sequence[tuple[AxisAlignedBoundingBox, dict[Hashable, float]]]])

Example implementation of the GenerateObjectDetectorBlackboxResponse interface.

Methods

from_config	Instantiate a new instance of this class given the configuration JSON-compliant dictionary encapsulating initialization arguments.
generate	Generate item-response curves for given parameters.
get_config	Generates a serializable configuration for the instance.
get_default_config	Generate and return a default configuration dictionary for this class.
get_impls	Discover and return a set of classes that implement the calling class.
is_usable	Check whether this class is available for use.

__getitem__(idx: int) → tuple[ndarray[Any, Any], Sequence[tuple[AxisAlignedBoundingBox, dict[Hashable, float]]], dict[str, Any]]

Get the image and ground_truth pair for a specific index.

Parameters:

idx – Index of desired data pair.

Raises:

IndexError – The given index does not exist.

Data pair corresponding to the given index.

__init__(images: Sequence[ndarray[Any, Any]], ground_truth: Sequence[Sequence[tuple[AxisAlignedBoundingBox, dict[Hashable, float]]]]) → None

Generate response curve for given images and ground_truth.

Parameters:

• images – Sequence of images to generate responses for.

• ground_truth – Sequence of sequences of detections corresponsing to each image.

Raises:

ValueError – Images and ground_truth data have a size mismatch.

__len__() → int

Number of image/ground_truth pairs this generator holds.

get_config() → dict[str, Any]

Generates a serializable configuration for the instance.

Returns:

dict[str, Any]: Configuration dictionary containing instance parameters.