Multi-task Semi-supervised Learning for Lobe Segmentation Introduction for several directories with their specific functions: data (training datasets are saved here) futils (common used functions and models including building models, compute metrics) logs (save monitor metrics during training) models (save trained models) results (save the training/validation/testing results including Dice, MSD, Hausdorff distance, false positive, etfc.) Introduction for each files Use python train_ori_fit_rec_epoch.py to train model. Use write_preds_save_dice.py to evaluate the trained model. Modify set_parameters.py to set custom parameters. Scipts files script* are used to submit job to HPC cluster. plot_curve* are used to plot training loss curve.