Please download these datasets and save to datapath
(user-defined).
It can be publicly available datasets (e.g., LiTS) or your private datasets. Currently, we only take data formatted in nii.gz. Download these datasets and save it to the datapath directory.
wget https://huggingface.co/datasets/qicq1c/Pubilcdataset/resolve/main/10_Decathlon/Task03_Liver.tar.gz?download=true # Task03_Liver.tar.gz (28.7 GB)
wget https://huggingface.co/datasets/qicq1c/Pubilcdataset/resolve/main/10_Decathlon/Task07_Pancreas.tar.gz?download=true # Task07_Pancreas.tar.gz (28.7 GB)
wget https://huggingface.co/datasets/qicq1c/Pubilcdataset/tree/main/05_KiTS.tar.gz?download=true # KiTS.tar.gz (28 GB)
The code is tested on python 3.8, Pytorch 1.12
.
[Optional] If You are using Agave/Sol
module load anaconda3/5.3.0 # only for Agave
module load mamba/latest # only for Sol
mamba create -n difftumor python=3.8
conda create -n difftumor python=3.8
source activate difftumor # or conda activate difftumor
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
pip install -r requirements.txt