Add JetPack6 Docker for NVIDIA Jetson Orin Series (#14707)
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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4 changed files with 67 additions and 7 deletions
7
.github/workflows/docker.yaml
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.github/workflows/docker.yaml
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@ -23,6 +23,10 @@ on:
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type: boolean
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type: boolean
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description: Use Dockerfile-arm64
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description: Use Dockerfile-arm64
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default: true
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default: true
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Dockerfile-jetson-jetpack6:
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type: boolean
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description: Use Dockerfile-jetson-jetpack6
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default: true
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Dockerfile-jetson-jetpack5:
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Dockerfile-jetson-jetpack5:
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type: boolean
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type: boolean
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description: Use Dockerfile-jetson-jetpack5
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description: Use Dockerfile-jetson-jetpack5
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@ -62,6 +66,9 @@ jobs:
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- dockerfile: "Dockerfile-arm64"
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- dockerfile: "Dockerfile-arm64"
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tags: "latest-arm64"
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tags: "latest-arm64"
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platforms: "linux/arm64"
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platforms: "linux/arm64"
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- dockerfile: "Dockerfile-jetson-jetpack6"
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tags: "latest-jetson-jetpack6"
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platforms: "linux/arm64"
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- dockerfile: "Dockerfile-jetson-jetpack5"
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- dockerfile: "Dockerfile-jetson-jetpack5"
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tags: "latest-jetson-jetpack5"
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tags: "latest-jetson-jetpack5"
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platforms: "linux/arm64"
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platforms: "linux/arm64"
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@ -34,20 +34,20 @@ COPY . $APP_HOME
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RUN chown -R root:root $APP_HOME
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RUN chown -R root:root $APP_HOME
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ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $APP_HOME
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ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $APP_HOME
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# Download onnxruntime-gpu, TensorRT, PyTorch and Torchvision
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# Download onnxruntime-gpu 1.8.0 and tensorrt 8.2.0.6
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# Other versions can be seen in https://elinux.org/Jetson_Zoo and https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048
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# Other versions can be seen in https://elinux.org/Jetson_Zoo and https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048
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ADD https://nvidia.box.com/shared/static/gjqofg7rkg97z3gc8jeyup6t8n9j8xjw.whl onnxruntime_gpu-1.8.0-cp38-cp38-linux_aarch64.whl
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ADD https://nvidia.box.com/shared/static/gjqofg7rkg97z3gc8jeyup6t8n9j8xjw.whl onnxruntime_gpu-1.8.0-cp38-cp38-linux_aarch64.whl
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ADD https://forums.developer.nvidia.com/uploads/short-url/hASzFOm9YsJx6VVFrDW1g44CMmv.whl tensorrt-8.2.0.6-cp38-none-linux_aarch64.whl
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ADD https://forums.developer.nvidia.com/uploads/short-url/hASzFOm9YsJx6VVFrDW1g44CMmv.whl tensorrt-8.2.0.6-cp38-none-linux_aarch64.whl
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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/torch-1.11.0a0+gitbc2c6ed-cp38-cp38-linux_aarch64.whl \
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torch-1.11.0a0+gitbc2c6ed-cp38-cp38-linux_aarch64.whl
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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/torchvision-0.12.0a0+9b5a3fe-cp38-cp38-linux_aarch64.whl \
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torchvision-0.12.0a0+9b5a3fe-cp38-cp38-linux_aarch64.whl
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# Install pip packages
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# Install pip packages
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RUN python3 -m pip install --upgrade pip wheel
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RUN python3 -m pip install --upgrade pip wheel
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RUN pip install onnxruntime_gpu-1.8.0-cp38-cp38-linux_aarch64.whl tensorrt-8.2.0.6-cp38-none-linux_aarch64.whl \
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RUN pip install --no-cache-dir \
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torch-1.11.0a0+gitbc2c6ed-cp38-cp38-linux_aarch64.whl torchvision-0.12.0a0+9b5a3fe-cp38-cp38-linux_aarch64.whl
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onnxruntime_gpu-1.8.0-cp38-cp38-linux_aarch64.whl \
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tensorrt-8.2.0.6-cp38-none-linux_aarch64.whl \
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https://github.com/ultralytics/assets/releases/download/v0.0.0/torch-1.11.0a0+gitbc2c6ed-cp38-cp38-linux_aarch64.whl \
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https://github.com/ultralytics/assets/releases/download/v0.0.0/torchvision-0.12.0a0+9b5a3fe-cp38-cp38-linux_aarch64.whl
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RUN pip install --no-cache-dir -e ".[export]"
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RUN pip install --no-cache-dir -e ".[export]"
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RUN rm *.whl
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Usage Examples -------------------------------------------------------------------------------------------------------
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@ -38,6 +38,7 @@ ADD https://nvidia.box.com/shared/static/mvdcltm9ewdy2d5nurkiqorofz1s53ww.whl on
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RUN python3 -m pip install --upgrade pip wheel
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RUN python3 -m pip install --upgrade pip wheel
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RUN pip install onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
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RUN pip install onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
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RUN pip install --no-cache-dir -e ".[export]"
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RUN pip install --no-cache-dir -e ".[export]"
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RUN rm *.whl
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Usage Examples -------------------------------------------------------------------------------------------------------
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52
docker/Dockerfile-jetson-jetpack6
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52
docker/Dockerfile-jetson-jetpack6
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@ -0,0 +1,52 @@
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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# Builds ultralytics/ultralytics:jetson-jetpack6 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
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# Supports JetPack6.x for YOLOv8 on Jetson AGX Orin, Orin NX and Orin Nano Series
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# Start FROM https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-jetpack
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FROM nvcr.io/nvidia/l4t-jetpack:r36.3.0
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# Set environment variables
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ENV APP_HOME /usr/src/ultralytics
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# Downloads to user config dir
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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
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https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.Unicode.ttf \
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/root/.config/Ultralytics/
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# Install dependencies
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RUN apt update && \
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apt install --no-install-recommends -y git python3-pip libopenmpi-dev libopenblas-base libomp-dev
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# Create working directory
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WORKDIR $APP_HOME
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# Copy contents and assign permissions
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COPY . $APP_HOME
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RUN chown -R root:root $APP_HOME
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ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $APP_HOME
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# Download onnxruntime-gpu 1.18.0 from https://elinux.org/Jetson_Zoo and https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048
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ADD https://nvidia.box.com/shared/static/48dtuob7meiw6ebgfsfqakc9vse62sg4.whl onnxruntime_gpu-1.18.0-cp310-cp310-linux_aarch64.whl
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# Pip install onnxruntime-gpu, torch, torchvision and ultralytics
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RUN python3 -m pip install --upgrade pip wheel
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RUN pip install --no-cache-dir \
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onnxruntime_gpu-1.18.0-cp310-cp310-linux_aarch64.whl \
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https://github.com/ultralytics/assets/releases/download/v0.0.0/torch-2.3.0-cp310-cp310-linux_aarch64.whl \
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https://github.com/ultralytics/assets/releases/download/v0.0.0/torchvision-0.18.0a0+6043bc2-cp310-cp310-linux_aarch64.whl
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RUN pip install --no-cache-dir -e ".[export]"
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RUN rm *.whl
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/ultralytics:latest-jetson-jetpack6 && sudo docker build --platform linux/arm64 -f docker/Dockerfile-jetson-jetpack6 -t $t . && sudo docker push $t
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# Run
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# t=ultralytics/ultralytics:latest-jetson-jetpack6 && sudo docker run -it --ipc=host $t
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# Pull and Run
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# t=ultralytics/ultralytics:latest-jetson-jetpack6 && sudo docker pull $t && sudo docker run -it --ipc=host $t
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# Pull and Run with NVIDIA runtime
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# t=ultralytics/ultralytics:latest-jetson-jetpack6 && sudo docker pull $t && sudo docker run -it --ipc=host --runtime=nvidia $t
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