Explainability Requires Interactivity In Python
This repository contains the code to train all custom models used in the paper Explainability Requires Interactivity as well as to create all static explanations (heat maps and generative). For our interactive framework, see the sister repositor.
Precomputed generative explanations are located at static_generative_explanations.
Requirements
Install the conda environment via conda env create -f env.yml (depending on your system you might need to change some versions, e.g. for pytorch, cudatoolkit and pytorch-lightning).
For some parts you will need the FairFace model, which can be downloaded from the authors’ repo. You will only need the res34_fair_align_multi_7_20190809.pt file.
Training classification networks
CelebA dataset
You first need to download and decompress the