Dockerfile

# Use an official Python runtime as a parent image
FROM python:3.10.12

# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user

# Create the app directory and set the correct permissions
RUN mkdir -p /home/user/app && chown -R user:user /home/user/app

# 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

# Try and run pip command after setting the user with `USER user` to avoid permission issues with Python
RUN pip install --no-cache-dir --upgrade pip

# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/app

# # Download and install dcm2niix
# RUN wget https://github.com/rordenlab/dcm2niix/releases/latest/download/dcm2niix_lnx.zip && \
#     unzip dcm2niix_lnx.zip && \
#     cp dcm2niix /home/user/.local/bin


# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Download files as the non-root user
# RUN curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/scaling_factors.csv
# RUN curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/metadata_only_model.zip
# RUN curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_only_model.zip
# RUN curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_and_metadata_model.zip

# RUN unzip "metadata_only_model.zip" -d "metadata_only_model/"
# RUN unzip "images_only_model.zip" -d "images_only_model/"
# RUN unzip "images_and_metadata_model.zip" -d "images_and_metadata_model/"

# Create the .streamlit directory
RUN mkdir -p .streamlit

# Create the config.toml file and set the maxMessageSize
RUN echo "\
[server]\n\
maxMessageSize = 2000\n\
" > .streamlit/config.toml

# Make port 8501 available to the world outside this container
EXPOSE 8501

# Run filter_data_app.py when the container launches
CMD streamlit run app.py