This minor release expands our documentation and examples pool. We additionally provide an the D-RISE implementation for the GenerateDetectorProposalSaliency interface.

Updates / New Features


  • Added workflow for test running some example notebooks.

  • Update CodeCov action used to version 2.


  • Added text discussing white box methods to introduction.rst.

  • Added some review process documentation.

  • Add initial FAQ documentation file.

  • Add background material for saliency maps to introduction.rst.

  • Added API docs section, which includes descriptions of all interfaces.

  • Added content to the CONTRIBUTING.md file on:

    • including notes here for added updates, features and fixes

    • Jupyter notebook CI workflow inclusion

  • Add implementations section.

  • Update example Jupyter notebooks to work with Google Colab.


  • Add example notebook using classifier-based interfaces and implementations with scikit-learn on the MNIST dataset.

  • Edited notebook examples.


  • Add DRISEScoring implementation of the GenerateDetectorProposalSaliency interface using detection output and associated occlusion masks.

  • Add SlidingRadial implementation of the PerturbImage interface that slides radial occlusion areas across an image.


  • Removed use of unittest.TestCase as it is not utilized directly in any way that PyTest does not provide.


  • Add type annotation, documentation and unit-tests for using image matrices as the fill option instead of just a solid color.

  • Add format_detection helper function to form the input for GenerateDetectorProposalSaliency from separated components.

  • Add example notebook showing the use of SlidingRadial perturbation and the use of occlude_image_batch with blurred-image alpha blending.



  • Fixed ValueError messages raised in the SimilarityScoring implementation. Added unittests to check the raising and message content.