Distance explainer

Explainable AI tool for explaining models that create embeddings.

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What Distance explainer can do for you

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distance_explainer

XAI method to explain distances in embedded spaces.

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Installation

To install distance_explainer from GitHub repository, do:

git clone git@github.com: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.

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  • Python 75%
  • Jupyter Notebook 23%
  • Shell 2%
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