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# Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds ultralytics/ultralytics:latest-jupyter image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Image provides JupyterLab interface for interactive YOLO development and includes tutorial notebooks
# Start from Python-based Ultralytics image for full Python environment
FROM ultralytics/ultralytics:latest-python
# Install JupyterLab for interactive development
RUN uv pip install --system jupyterlab
# Create persistent data directory structure
RUN mkdir /data
# Configure YOLO directories
RUN mkdir /data/{datasets,weights,runs} && \
yolo settings datasets_dir="/data/datasets" weights_dir="/data/weights" runs_dir="/data/runs"
# Start JupyterLab with tutorial notebook
ENTRYPOINT ["/usr/local/bin/jupyter", "lab", "--allow-root", "--ip=*", "/ultralytics/examples/tutorial.ipynb"]
# Usage Examples -------------------------------------------------------------------------------------------------------
# Build and Push
# t=ultralytics/ultralytics:latest-jupyter && sudo docker build -f docker/Dockerfile-jupyter -t $t . && sudo docker push $t
# Run
# t=ultralytics/ultralytics:latest-jupyter && sudo docker run -it --ipc=host -p 8888:8888 $t
# Pull and Run
# t=ultralytics/ultralytics:latest-jupyter && sudo docker pull $t && sudo docker run -it --ipc=host -p 8888:8888 $t
# Pull and Run with local volume mounted
# t=ultralytics/ultralytics:latest-jupyter && sudo docker pull $t && sudo docker run -it --ipc=host -p 8888:8888 -v "$(pwd)"/datasets:/data/datasets $t
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