config.yml

#get desc-nnunet_dseg.nii.gz images from hippunfold as lbl, and T1w as input img
hippunfold_img: '../hippunfold_T1w_model-b1000_newatlas/work/sub-{subject}/anat/sub-{subject}_hemi-L_space-corobl_desc-cropped_T1w.nii.gz'
hippunfold_lbl: '../hippunfold_T1w_model-b1000_newatlas/work/sub-{subject}/seg_T1w/sub-{subject}_hemi-L_space-corobl_desc-nnunet_dseg.nii.gz'

training_subjects: 'subjects.tsv' 

hemis:
  - L 




pretrained_model: '/scratch/akhanf/1_dev/retrain_nnunet/trained_models/nnUNet/3d_fullres/Task104_hcp1200_b1000/nnUNetTrainerV2__nnUNetPlansv2.1/fold_0/model_best.model'





out_resolution: '128x256x128'
task: Task204_hcp1200_b1000_finetune_dhcp_T1w #must be Task###_name where ### is >= 100
trainer: nnUNetTrainerV2
architecture: 3d_fullres
checkpoint: model_best

nnunet_env:
  nnUNet_raw_data_base: 'raw_data'
  nnUNet_preprocessed: 'preprocessed'
  RESULTS_FOLDER: 'trained_models'

nnunet_env_tmp:
  nnUNet_raw_data_base: 'raw_data'
  nnUNet_preprocessed: '$TMPDIR/preprocessed'
  RESULTS_FOLDER: 'trained_models'