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Dockerfile-jupyter 1.6 KB

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  1. # Ultralytics YOLO 🚀, AGPL-3.0 license
  2. # Builds ultralytics/ultralytics:latest-jupyter image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
  3. # Image provides JupyterLab interface for interactive YOLO development and includes tutorial notebooks
  4. # Start from Python-based Ultralytics image for full Python environment
  5. FROM ultralytics/ultralytics:latest-python
  6. # Install JupyterLab for interactive development
  7. RUN /usr/local/bin/pip install jupyterlab
  8. # Create persistent data directory structure
  9. RUN mkdir /data
  10. # Configure YOLO directory paths
  11. RUN mkdir /data/datasets && /usr/local/bin/yolo settings datasets_dir="/data/datasets"
  12. RUN mkdir /data/weights && /usr/local/bin/yolo settings weights_dir="/data/weights"
  13. RUN mkdir /data/runs && /usr/local/bin/yolo settings runs_dir="/data/runs"
  14. # Start JupyterLab with tutorial notebook
  15. ENTRYPOINT ["/usr/local/bin/jupyter", "lab", "--allow-root", "--ip=*", "/ultralytics/examples/tutorial.ipynb"]
  16. # Usage Examples -------------------------------------------------------------------------------------------------------
  17. # Build and Push
  18. # t=ultralytics/ultralytics:latest-jupyter && sudo docker build -f docker/Dockerfile-jupyter -t $t . && sudo docker push $t
  19. # Run
  20. # t=ultralytics/ultralytics:latest-jupyter && sudo docker run -it --ipc=host -p 8888:8888 $t
  21. # Pull and Run
  22. # t=ultralytics/ultralytics:latest-jupyter && sudo docker pull $t && sudo docker run -it --ipc=host -p 8888:8888 $t
  23. # Pull and Run with local volume mounted
  24. # 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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