distance-explainer 0.4.0

XAI method to explain distances in embedded spaces

distance_explainer

XAI method to explain distances in embedded spaces.

Installation

To install distance_explainer from GitHub repository, do:

git clone [e-mail]:dianna-ai/distance_explainer.git
cd distance_explainer
python3 -m pip install .

How to use

See our tutorial how to use this package. In short:

image1 = np.random.random((100, 100, 3))
image2 = np.random.random((100, 100, 3))

image2_embedded = model(image2)
explainer = DistanceExplainer(axis_labels={2: 'channels'})
attribution_map = explainer.explain_image_distance(model, image1, image2_embedded)

Contributing

If you want to contribute to the development of distance_explainer, have a look at the contribution guidelines.

Credits

This package was created with Cookiecutter and the NLeSC/python-template.