Code for the paper [Bridging the Gap in Lesion Segmentation: RL-Assisted SAM Segmentation in Diverse Medical Imaging Modalities ()]
- python 3.6.5
- numpy 1.14.5
- scipy 1.1.0
- Pytorch 0.4.0
The folder 'scripts' contains the different bash scripts that could be used to train the same models used in the paper, for both Camvid and Cityscapes datasets.
- launch_baseline.sh: To train the baselines 'random'.
- launch_train_ralis.sh: To train the 'SAM RL agent' model.
- launch_test_ralis.sh: To test the 'SAM RL agent' model.