42 lines
1.6 KiB
Plaintext
42 lines
1.6 KiB
Plaintext
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# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
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# Builds ultralytics/yolov5:latest-arm64 image on DockerHub https://hub.docker.com/r/ultralytics/yolov5
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# Image is aarch64-compatible for Apple M1 and other ARM architectures i.e. Jetson Nano and Raspberry Pi
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# Start FROM Ubuntu image https://hub.docker.com/_/ubuntu
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FROM arm64v8/ubuntu:20.04
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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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RUN apt update
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RUN DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC apt install -y tzdata
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RUN apt install --no-install-recommends -y python3-pip git zip curl htop gcc libgl1-mesa-glx libglib2.0-0 libpython3-dev
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# RUN alias python=python3
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# Install pip packages
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COPY requirements.txt .
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RUN python3 -m pip install --upgrade pip wheel
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RUN pip install --no-cache -r requirements.txt gsutil notebook \
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tensorflow-aarch64
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# tensorflowjs \
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# onnx onnx-simplifier onnxruntime \
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# coremltools openvino-dev \
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# Create working directory
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RUN mkdir -p /usr/src/app
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WORKDIR /usr/src/app
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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/yolov5 /usr/src/app
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/yolov5:latest-M1 && sudo docker build --platform linux/arm64 -f utils/docker/Dockerfile-arm64 -t $t . && sudo docker push $t
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# Pull and Run
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# t=ultralytics/yolov5:latest-M1 && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t
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