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Add NVIDIA Jetpack4 and Jetpack5 Docker Images (#13100)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Lakshantha <lakshantha@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Ahmed Mahfouz 2024-06-11 02:17:38 +02:00 • committed by GitHub
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# Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds ultralytics/ultralytics:jetson-jetson-jetpack5 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Supports JetPack5.x for YOLOv8 on Jetson Xavier NX, AGX Xavier, AGX Orin, Orin Nano and Orin NX
# Start FROM https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-pytorch
FROM nvcr.io/nvidia/l4t-pytorch:r35.2.1-pth2.0-py3
# Set environment variables
ENV APP_HOME /usr/src/ultralytics
# 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
# g++ required to build 'tflite_support' and 'lap' packages
# libusb-1.0-0 required for 'tflite_support' package when exporting to TFLite
# pkg-config and libhdf5-dev (not included) are needed to build 'h5py==3.11.0' aarch64 wheel required by 'tensorflow'
RUN apt update \
&& apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
# Create working directory
WORKDIR $APP_HOME
# Copy contents and assign permissions
COPY . $APP_HOME
RUN git remote set-url origin https://github.com/ultralytics/ultralytics.git
ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $APP_HOME
# Remove opencv-python from Ultralytics dependencies as it conflicts with opencv-python installed in base image
RUN grep -v "opencv-python" pyproject.toml > temp.toml && mv temp.toml pyproject.toml
# Download onnxruntime-gpu 1.15.1 for Jetson Linux 35.2.1 (JetPack 5.1). Other versions can be seen in https://elinux.org/Jetson_Zoo#ONNX_Runtime
ADD https://nvidia.box.com/shared/static/mvdcltm9ewdy2d5nurkiqorofz1s53ww.whl onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
# Install pip packages manually for TensorRT compatibility https://github.com/NVIDIA/TensorRT/issues/2567
RUN python3 -m pip install --upgrade pip wheel
RUN pip install onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
RUN pip install --no-cache-dir -e ".[export]"
# Usage Examples -------------------------------------------------------------------------------------------------------
# Build and Push
# t=ultralytics/ultralytics:latest-jetson-jetpack5 && sudo docker build --platform linux/arm64 -f docker/Dockerfile-jetson-jetpack5 -t $t . && sudo docker push $t
# Run
# t=ultralytics/ultralytics:latest-jetson-jetpack5 && sudo docker run -it --ipc=host $t
# Pull and Run
# t=ultralytics/ultralytics:latest-jetson-jetpack5 && sudo docker pull $t && sudo docker run -it --ipc=host $t
# Pull and Run with NVIDIA runtime
# t=ultralytics/ultralytics:latest-jetson-jetpack5 && sudo docker pull $t && sudo docker run -it --ipc=host --runtime=nvidia $t