causal_models

Code for counterfactual image generation

The code in this folder is adapted from the official code associated with the
'High Fidelity Image Counterfactuals with Probabilistic Causal Models' paper. Original code: https://github.com/biomedia-mira/causal-gen.

Train the counterfactual inference model

To train the counterfactual inference models in the paper you can simply run python causal_models/main.py --hps embed --exp_name your_exp_name replace by padchest if you want to train on chest x-rays. All associated hyperparameters are stored in causal_models/hps.py.

This assumes you have already set up your data folders as per the main repository.

Generating and saving counterfactuals for contrastive training

To generate all possible domain counterfactuals given a trained model, you can use our predefined scripts: save_embed_scanner_cf.py andsave_padchest_scanner_cf.py. Simply pass your checkpoint path and your target saving directory as command line arguments.