run_preproc_pipeline_train.sh

#!/bin/bash
eval "$(conda shell.bash hook)"
conda activate cta 

# define the folder containing the data
# for training/evaluation, the scans should be in a folder called "og"
# and the labels in a folder called "og_label"

# for testing on unnanotated data, please refer to the other pipeline file

# define the path to your data here 
export path_base="/data/aneurysm/hospital"

export path_og="${path_base}/og"
export path_label_og="${path_base}/og_label"
export path_resampled=${path_og}_0.4 
export path_label_resampled=${path_label_og}_0.4
export path_vessel_seg="${path_base}/crop_0.4_vessel"
export path_crop="${path_base}/crop_0.4"
export path_label_crop="${path_base}/crop_0.4_label"
export path_edt="${path_base}/crop_0.4_vessel_edt"
export path_annotations="${path_base}/annotations.csv"
export path_cvs_outputs="${path_base}/cvs_temp"
export path_cvs_masks="${path_base}/cvs_mask"
export path_cvs_bbox="${path_base}/cvs_bbox"


# Resample scans to 0.4mm spacing and crop them
python src/preprocess/resample_scans.py ${path_og} ${path_label_og}
python src/preprocess/crop_scans.py ${path_resampled} ${path_crop}
python src/preprocess/crop_scans.py ${path_label_resampled} ${path_label_crop}

# Run vessel segmentation
sudo docker run --gpus all -it --rm -v ${path_vessel_seg}_temp/:/Data/aneurysmDetection/output_path/  -v ${path_crop}/:/Data/aneurysmDetection/input_cta/ --shm-size=24g --ulimit memlock=-1 vessel_seg:latest python /Work/scripts/extractVessels.py -d /Data/aneurysmDetection/input_cta/ /Data/aneurysmDetection/output_path -m 'Prediction' -t 16 -s 0.5 -g 1 -v 1150

# Keep only relevant files 
mkdir ${path_vessel_seg}
sudo rm  ${path_vessel_seg}_temp/Predictions/CA_*
sudo rm ${path_vessel_seg}_temp/Predictions/*.json 
cp ${path_vessel_seg}_temp/Predictions/* ${path_vessel_seg}/
sudo rm -rf ${path_vessel_seg}_temp
# Compute distance maps
python src/preprocess/compute_distance_maps.py ${path_vessel_seg} ${path_edt}
# Obtain bbox csv from segmentation files 

# get annotations
python src/preprocess/get_bbox_csv.py ${path_label_crop}  ${path_annotations}