|
#!/bin/bash -l |
|
|
|
|
|
|
|
export data_raw="/home/woody/iwi5/iwi5039h/data_raw" |
|
export nnUNet_raw_data_base="/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_raw_data_base/" |
|
export nnUNet_preprocessed="/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_preprocessed/" |
|
export RESULTS_FOLDER="/home/woody/iwi5/iwi5039h/nnUNet_data/RESULTS_FOLDER" |
|
|
|
cd nnunet_glacer |
|
pwd |
|
conda activate nnunet |
|
|
|
|
|
python3 nnunet/experiment_planning/nnUNet_plan_and_preprocess.py -t 504 -pl3d None -pl2d ExperimentPlanner2D_mtl |
|
|
|
python3 nnunet/run/run_training.py 2d nnUNetTrainerMTLrecon 504 0 -p nnUNetPlans_mtl --disable_postprocessing_on_folds |
|
python3 nnunet/inference/predict_simple.py -i $nnUNet_raw_data_base/nnUNet_raw_data/Task504_Glacier_mtl_recon/imagesTs -o $RESULTS_FOLDER/test_predictions/Task504_Glacier_mtl_recon/fold_0 -t 504 -m 2d -f 0 -p nnUNetPlans_mtl -tr nnUNetTrainerMTLrecon |
|
python3 nnunet/dataset_conversion/Task504_Glacier_mtl_recon_reverse.py -i $RESULTS_FOLDER/test_predictions/Task504_Glacier_mtl_recon/fold_0 |
|
python3 ./evaluate_nnUNet.py --predictions $RESULTS_FOLDER/test_predictions/Task504_Glacier_mtl_recon/fold_0/pngs --labels_fronts $data_raw/fronts/test --labels_zones $data_raw/zones/test --sar_images $data_raw/sar_images/test |
|
|
