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- # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
- # Builds ultralytics/yolov5:latest-arm64 image on DockerHub https://hub.docker.com/r/ultralytics/yolov5
- # Image is aarch64-compatible for Apple M1 and other ARM architectures i.e. Jetson Nano and Raspberry Pi
-
- # Start FROM Ubuntu image https://hub.docker.com/_/ubuntu
- FROM arm64v8/ubuntu:20.04
-
- # Downloads to user config dir
- ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Arial.Unicode.ttf /root/.config/Ultralytics/
-
- # Install linux packages
- RUN apt update
- RUN DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC apt install -y tzdata
- RUN apt install --no-install-recommends -y python3-pip git zip curl htop gcc \
- libgl1-mesa-glx libglib2.0-0 libpython3.8-dev
- # RUN alias python=python3
-
- # Install pip packages
- COPY requirements.txt .
- RUN python3 -m pip install --upgrade pip
- RUN pip install --no-cache -r requirements.txt gsutil notebook \
- tensorflow-aarch64
- # tensorflowjs \
- # onnx onnx-simplifier onnxruntime \
- # coremltools openvino-dev \
-
- # Create working directory
- RUN mkdir -p /usr/src/app
- WORKDIR /usr/src/app
-
- # Copy contents
- COPY . /usr/src/app
- RUN git clone https://github.com/ultralytics/yolov5 /usr/src/yolov5
-
-
- # Usage Examples -------------------------------------------------------------------------------------------------------
-
- # Build and Push
- # t=ultralytics/yolov5:latest-M1 && sudo docker build --platform linux/arm64 -f utils/docker/Dockerfile-arm64 -t $t . && sudo docker push $t
-
- # Pull and Run
- # 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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