Dockerfile

FROM pytorch/pytorch:1.11.0-cuda11.3-cudnn8-runtime

ENV DEBIAN_FRONTEND=noninteractive
ENV SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True

RUN pip install --upgrade pip
RUN pip install SimpleITK evalutils==0.3.0 matplotlib nnunet==1.7.0 SimpleITK==2.2.1 picai_eval>=1.4.1 picai_prep>=2.0.0 picai_baseline>=0.5.2 gradio jinja2==3.0.0

COPY nnUNetTrainerV2_focalLoss.py /tmp/nnUNetTrainerV2_focalLoss.py
COPY nnUNetTrainerV2_Loss_CE_checkpoints.py /tmp/nnUNetTrainerV2_Loss_CE_checkpoints.py
COPY nnUNetTrainerV2_Loss_FL_and_CE.py /tmp/nnUNetTrainerV2_Loss_FL_and_CE.py

RUN SITE_PKG=`pip3 show nnunet | grep "Location:" | awk '{print $2}'` && \
    mv /tmp/nnUNetTrainerV2_focalLoss.py "$SITE_PKG/nnunet/training/network_training/nnUNet_variants/loss_function/nnUNetTrainerV2_focalLoss.py" && \
    mv /tmp/nnUNetTrainerV2_Loss_CE_checkpoints.py "$SITE_PKG/nnunet/training/network_training/nnUNetTrainerV2_Loss_CE_checkpoints.py" && \
    mv /tmp/nnUNetTrainerV2_Loss_FL_and_CE.py "$SITE_PKG/nnunet/training/network_training/nnUNetTrainerV2_Loss_FL_and_CE.py"


# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user
# Switch to the "user" user
USER user
# Set home to the user's home directory
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH

# Set the working directory to the user's home directory
WORKDIR $HOME/app

COPY --chown=user results/ $HOME/app/results/
COPY --chown=user main.py $HOME/app/main.py

CMD ["python", "/home/user/app/main.py"]