XAI method to explain distances in embedded spaces

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Maintainers

cwmeijer

These details have not been verified by PyPI

Development Status
- 2 - Pre-Alpha
Intended Audience
- Developers
License
- OSI Approved :: Apache Software License
Natural Language
- English
Programming Language

Project description

`distance_explainer`

XAI method to explain distances in embedded spaces.

overview schema

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.

Project details

These details have been verified by PyPI

Project links

GitHub Statistics

Maintainers

cwmeijer

These details have not been verified by PyPI

Development Status
- 2 - Pre-Alpha
Intended Audience
- Developers
License
- OSI Approved :: Apache Software License
Natural Language
- English
Programming Language

Release history Release notifications | RSS feed

This version

0.4.0

Nov 5, 2024

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