| 12345678910111213141516171819202122232425262728293031323334353637383940 |
- # Ultralytics YOLO 🚀, AGPL-3.0 license
- # Builds ultralytics/ultralytics:latest-conda image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
- # Image is optimized for Ultralytics Anaconda (https://anaconda.org/conda-forge/ultralytics) installation and usage
- # Start FROM miniconda3 image https://hub.docker.com/r/continuumio/miniconda3
- FROM continuumio/miniconda3:latest
- # Downloads to user config dir
- ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
- https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.Unicode.ttf \
- /root/.config/Ultralytics/
- # Install linux packages
- RUN apt update \
- && apt install --no-install-recommends -y libgl1
- # Copy contents
- ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt .
- # Install conda packages
- # mkl required to fix 'OSError: libmkl_intel_lp64.so.2: cannot open shared object file: No such file or directory'
- RUN conda config --set solver libmamba && \
- conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia && \
- conda install -c conda-forge ultralytics mkl
- # conda install -c pytorch -c nvidia -c conda-forge pytorch torchvision pytorch-cuda=12.1 ultralytics mkl
- # Usage Examples -------------------------------------------------------------------------------------------------------
- # Build and Push
- # t=ultralytics/ultralytics:latest-conda && sudo docker build -f docker/Dockerfile-cpu -t $t . && sudo docker push $t
- # Run
- # t=ultralytics/ultralytics:latest-conda && sudo docker run -it --ipc=host $t
- # Pull and Run
- # t=ultralytics/ultralytics:latest-conda && sudo docker pull $t && sudo docker run -it --ipc=host $t
- # Pull and Run with local volume mounted
- # t=ultralytics/ultralytics:latest-conda && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/shared/datasets:/usr/src/datasets $t
|
