Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images
To run the code first download the liver data from here: Liver Dataand place it in the data/ folder.
The run training by calling 'trainer.py' with a specificed config file, for example:
python trainer.py -c cfgs/full_supervision_vib.json
This will write the model, logged info, and a copy of the config file to a folder in experiments/, such as experiments/liver/vib__vib_burnin__noise/.
To run inference, call eval.py with the config file, for example:
python eval.py -c experiments/liver/vib__vib_burnin__noise/full_supervision_vib.json
This will write the predicted correspondence points and uncertainty values to the experiment directory.