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41 lines
1.8 KiB
41 lines
1.8 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' 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++ |
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# RUN alias python=python3 |
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# Create working directory |
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RUN mkdir -p /usr/src/ultralytics |
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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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# 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 "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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# Pull and Run |
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# t=ultralytics/ultralytics:jetson && sudo docker pull $t && sudo docker run -it --runtime=nvidia $t
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