The first stage is multi-level image-concept alignment and the second stage is explainable disease diagnosis. Please set the model path in mica.py after the first stage training.
# first stage training
python run.py \
-c ./configs/[dataset_pretrain_config_sample].yaml \
--train
# second stage training
python run.py \
-c ./configs/[dataset_classification_CBM_config_sample].yaml \
--train
The sample configurations and dataset loading logics are under the configs and datasets folder, respectively. Please adapt to custom dataset by replacing the dataset name and path in configuration files (.yaml) and constants.py. You can create the dataset loading and processing logic by modifying pretraining_dataset_derm.py and image_dataset_derm.py under the datasets folder. The class activation vecotor (CAV) file can be created by following the work here.