feat: add a Dockerfile

docker/Dockerfile

@@ -0,0 +1,41 @@
+FROM nvidia/opengl:1.2-glvnd-devel-ubuntu22.04
+
+WORKDIR /app
+
+# Avoid buffering the server URL
+ENV PYTHONUNBUFFERED=1
+
+# Prevent apt from prompting us about various decisions
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Allow driver to do rendering
+ENV NVIDIA_DRIVER_CAPABILITIES=all
+ENV NVIDIA_VISIBLE_DEVICES=all
+
+# Install trame-slicer dependencies and pyenv build dependencies
+RUN apt-get update && apt-get install -y libturbojpeg \
+    make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev curl git
+    libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev
+
+# Install Pyenv
+ENV HOME=/root
+ENV PYENV_DIR="${HOME}/.pyenv"
+RUN curl -fsSL https://pyenv.run | bash && \
+    echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc && \
+    echo '[[ -d $PYENV_ROOT/bin ]] && export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc && \
+    echo 'eval "$(pyenv init - bash)"' >> ~/.bashrc
+ENV PATH="${PYENV_DIR}/shims:${PYENV_DIR}/bin:${PATH}"
+
+# Install SHARED Python3.10
+RUN PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install 3.10.18 && \
+    pyenv global 3.10.18 && \
+    python -m pip install --upgrade pip
+
+# Install trame-slicer
+RUN mkdir trame_slicer
+COPY . trame_slicer
+RUN pip install --no-cache-dir ./trame_slicer && \
+    pip install --no-cache-dir https://github.com/KitwareMedical/trame-slicer/releases/download/v1.4.0/vtk_mrml-9.4.0-cp310-cp310-manylinux_2_35_x86_64.whl
+
+RUN chmod +x /app/trame_slicer/docker_run.sh
+ENTRYPOINT ["/app/trame_slicer/docker_run.sh"]

docker/README

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+This builds an image launching the medical_viewer_app example in a container with GPU capacities, on 127.0.0.1:8080.
+
+You need nvidia-container-toolkit and up to date NVIDIA drivers to run it.
+
+To build it, use `docker build . -f {Dockerfile_path} -t trame-slicer`
+
+The run command depends on the image:
+
+- WSL
+
+    - To use EGL:
+
+        `docker run -p 8080:8080 -it -e MESA_D3D12_DEFAULT_ADAPTER_NAME=NVIDIA -e VTK_DEFAULT_OPENGL_WINDOW=vtkEGLRenderWindow -e LD_LIBRARY_PATH=/usr/lib/wsl/lib -v /usr/lib/wsl:/usr/lib/wsl trame-slicer`
+
+    - To use X server: This image is supposed to allow using X server with the following command, but it still uses EGL
+
+        `docker run -p 8080:8080 -it -e MESA_D3D12_DEFAULT_ADAPTER_NAME=NVIDIA -e DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix -e LD_LIBRARY_PATH=/usr/lib/wsl/lib -v /usr/lib/wsl:/usr/lib/wsl trame-slicer`
+
+    - To use MESA: After removing NVIDIA_DRIVER_CAPABILITIES and NVIDIA_VISIBLE_DEVICES declarations from the Dockerfile
+
+        `docker run -p 8080:8080 -it trame-slicer`
+
+- Linux
+
+    - To use EGL:
+
+        `docker run -it -p 8080:8080 --runtime=nvidia -e VTK_DEFAULT_OPENGL_WINDOW=vtkEGLRenderWindow trame-slicer`
+
+    - To use X server:
+
+        `docker run -it -p 8080:8080 --runtime=nvidia -v {path to your Xauthority}:/root/.Xauthority -e DISPLAY=$DISPLAY --net host trame-slicer`
+
+    - To use MESA: After removing NVIDIA_DRIVER_CAPABILITIES and NVIDIA_VISIBLE_DEVICES declarations from the Dockerfile
+
+        `docker run -p 8080:8080 -it trame-slicer`

docker/docker_run.sh

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+#!/bin/bash
+python trame_slicer/examples/medical_viewer_app.py --host 0.0.0.0
+
+# Forcer le code de retour à 0
+exit 0