nbutter/nnunet repository overview

# Pull base image.
FROM nvidia/cuda:10.2-devel-ubuntu16.04
MAINTAINER Nathaniel Butterworth USYD SIH

#Create some directories to work with on Artmeis
RUN mkdir /project && mkdir /scratch 

Install ubuntu libraires and packages
RUN apt-get update -y && \
apt-get install git curl -y && \
rm -rf /var/lib/apt/lists/*

#Set some environemnt variables we will need
ENV PATH="/build/miniconda3/bin:${PATH}"
ARG PATH="/build/miniconda3/bin:${PATH}"
WORKDIR /build

#Install Python3 we can use
RUN curl -O https://repo.anaconda.com/miniconda/Miniconda3-py38_4.8.3-Linux-x86_64.sh &&\
mkdir /build/.conda && \
bash Miniconda3-py38_4.8.3-Linux-x86_64.sh -b -p /build/miniconda3 &&\
rm -rf /Miniconda3-py38_4.8.3-Linux-x86_64.sh 

WORKDIR /build
#Install packages
RUN conda install pip
RUN pip install --upgrade pip
RUN pip install nnunet

sudo singularity build nnunet.img docker://nbutter/nnunet

#To build the new repo
docker build . -t nnunet
#The push it here
docker push nbutter/nnunet:tagname

#Pull the image and build it as a "sandbox" containter so you can make changes to it
ubuntu@sing:~$ sudo singularity build --sandbox pyslowfast.img docker://nbutter/pyfastslow

#Run the image interactively, with write permission, so you can install additional packages
ubuntu@sing:~$ sudo singularity shell --writable pyslowfast.img

#Inside the container make any required changes, i.e:
Singularity> pip install nnunet
Singularity> exit

#OPTIONAL: After exiting the container, now rebuild as non-writeable image
ubuntu@sing:~$ sudo singularity build nnunet.img pyslowfast.img

singularity exec nnunet.simg /bin/bash -c "export nnUNet_raw_data_base='/project/Training/PROJECTS/singularity_pytorch_maryam/nnUNet_raw' && export nnUNet_preprocessed='/project/Training/PROJECTS/singularity_pytorch_maryam/nnUNet_preprocessed' && export RESULTS_FOLDER='/project/Training/PROJECTS/singularity_pytorch_maryam/nnUNet_trained_models' && nnUNet_convert_decathlon_task -i Task05_Prostate/"