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47 lines
2.2 KiB
47 lines
2.2 KiB
# Ultralytics YOLO 🚀, AGPL-3.0 license
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# Builds ultralytics/ultralytics:jetson image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
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# Supports JetPack for YOLOv8 on Jetson Nano, TX1/TX2, Xavier NX, AGX Xavier, AGX Orin, and Orin NX
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# Start FROM https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-pytorch
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FROM nvcr.io/nvidia/l4t-pytorch:r35.2.1-pth2.0-py3
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# Downloads to user config dir
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ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Arial.Unicode.ttf /root/.config/Ultralytics/
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# Install linux packages
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# g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package
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RUN apt update \
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&& apt install --no-install-recommends -y gcc git zip curl htop libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0
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# RUN alias python=python3
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# Create working directory
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WORKDIR /usr/src/ultralytics
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# Copy contents
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# COPY . /usr/src/app (issues as not a .git directory)
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RUN git clone https://github.com/ultralytics/ultralytics /usr/src/ultralytics
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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt /usr/src/ultralytics/
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# Remove opencv-python from requirements.txt as it conflicts with opencv-python installed in base image
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RUN grep -v '^opencv-python' requirements.txt > tmp.txt && mv tmp.txt requirements.txt
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# Install pip packages manually for TensorRT compatibility https://github.com/NVIDIA/TensorRT/issues/2567
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RUN python3 -m pip install --upgrade pip wheel
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RUN pip install --no-cache tqdm matplotlib pyyaml psutil pandas onnx thop "numpy==1.23"
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RUN pip install --no-cache -e .
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# Set environment variables
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ENV OMP_NUM_THREADS=1
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/ultralytics:latest-jetson && sudo docker build --platform linux/arm64 -f docker/Dockerfile-jetson -t $t . && sudo docker push $t
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# Run
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# t=ultralytics/ultralytics:latest-jetson && 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 && sudo docker pull $t && sudo docker run -it --ipc=host --runtime=nvidia $t
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