SBSMStack

class xaitk_saliency.impls.gen_image_similarity_blackbox_sal.sbsm.SBSMStack(window_size: tuple[int, int] = (50, 50), stride: tuple[int, int] = (20, 20), proximity_metric: str = 'euclidean', fill: int | Sequence[int] | ndarray | None = None, threads: int | None = None)

Encapsulation of the perturbation-occlusion method using specifically the sliding window image perturbation and similarity scoring algorithms to generate similarity-based visual saliency maps. See the documentation of SlidingWindow and SimilarityScoring for details.

Methods

from_config	Instantiate a new instance of this class given the configuration JSON-compliant dictionary encapsulating initialization arguments.
generate	Generates visual saliency maps based on the similarity of the reference image to each query image determined by the output of the blackbox feature vector generator.
get_config	Get the configuration dictionary of the SBSMStack instance.
get_default_config	Returns the default configuration for the SBSMStack.
get_impls	Discover and return a set of classes that implement the calling class.
is_usable	Check whether this class is available for use.

__init__(window_size: tuple[int, int] = (50, 50), stride: tuple[int, int] = (20, 20), proximity_metric: str = 'euclidean', fill: int | Sequence[int] | ndarray | None = None, threads: int | None = None) → None

Encapsulation of the perturbation-occlusion method using specifically the sliding window image perturbation

Parameters:

• window_size – The block window size as a tuple with format (height, width).

• stride – The sliding window striding step as a tuple with format (height_step, width_step).

• proximity_metric –

  The type of comparison metric used to determine proximity in feature space. The type of comparison metric supported is restricted by scipy’s cdist() function. The following metrics are supported in scipy.

  ‘braycurtis’, ‘canberra’, ‘chebyshev’, ‘cityblock’, ‘correlation’, ‘cosine’, ‘dice’, ‘euclidean’, ‘hamming’, ‘jaccard’, ‘jensenshannon’, ‘kulsinski’, ‘mahalanobis’, ‘matching’, ‘minkowski’, ‘rogerstanimoto’, ‘russellrao’, ‘seuclidean’, ‘sokalmichener’, ‘sokalsneath’, ‘sqeuclidean’, ‘wminkowski’, ‘yule’.

• threads – Optional number threads to use to enable parallelism in applying perturbation masks to an input image. If 0, a negative value, or None, work will be performed on the main-thread in-line.

property fill: int | Sequence[int] | ndarray | None

Gets the fill value

get_config() → dict[str, Any]

Get the configuration dictionary of the SBSMStack instance.

Returns:

dict[str, Any]: Configuration dictionary.

classmethod get_default_config() → dict[str, Any]

Returns the default configuration for the SBSMStack.

This method provides a default configuration dictionary, specifying default values for key parameters in the factory. It can be used to create an instance of the factory with preset configurations.

Returns:

dict[str, Any]: A dictionary containing default configuration parameters.