Dockerfile

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


ENV DEBIAN_FRONTEND=noninteractive

# stupid sklearn name
ENV SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True

# Install dependencies
RUN pip install --upgrade pip
RUN pip install SimpleITK evalutils==0.3.0 matplotlib nnunet==1.7.0 SimpleITK==2.2.1 picai_prep==2.1.2 picai_baseline==0.8.1 gradio jinja2==3.0.0

# copy nnUNetTrainerV2_focalLoss file to nnunet pip installation  training/network_training/nnUNet_variants/loss_function/
COPY nnUNetTrainerV2_focalLoss.py /tmp/nnUNetTrainerV2_focalLoss.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"

# copy nnUNetTrainerV2_Loss_FL_and_CE file to nnunet pip installation  training/network_training/nnUNet_variants/loss_function/
COPY nnUNetTrainerV2_Loss_FL_and_CE.py /tmp/nnUNetTrainerV2_Loss_FL_and_CE.py
RUN SITE_PKG=`pip3 show nnunet | grep "Location:" | awk '{print $2}'` && \
    mv /tmp/nnUNetTrainerV2_Loss_FL_and_CE.py "$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

RUN ls -lsa
CMD ["python", "/home/user/app/main.py"]