Read the paper here. View code and data here.
.. info:: iEAT @ FAccT 2021 - Slides - Paper
# gather the dependencies for running scripts in this repo
conda env update environment.yml
conda activate ieat
# install the weat package locally
pip install -e weat
# install the ieat package locally
pip install -e .The ieat package does not have a CLI. Use it programmatically by accessing the API module (ieat.api).
To run a basic test on a set of images, use the test function in ieat.api.
SimCLR is downloaded automatically - but you must download a pre-trained version of iGPT yourself.
For an example of how to use the API programmatically, see the documentation and tutorials.
This repo uses Colab scripts in the notebooks/ directory. Check out notebooks/README.md for a full description.
To open a .ipynb file in Colab, navigate to Colab's Github Interface and search for this repo.
Documentation for the ieat API is published at rbsteed.com/ieat.
To generate the documentation, use pdoc3:
pdoc3 --html --output-dir docs --force ieat --template-dir docs/templates
git subtree push --prefix docs/ieat origin gh-pages
data/- images and other data used for bias tests in the paperembeddings/- location for caching computed embeddings - includes pre-computed embeddings for convenience; to generate your own, use thefrom_cache=Falseoptionieat/- software package for generating image embeddings and testing for biasnotebooks/- Colab notebooks containing tutorials and data explorationoutput/- location for storing results tablesenvironment.yml- Conda environment file with dependencies for Jupyter, etc.docs/ieat- source for documentation