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+# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# aarch64-compatible YOLOv5 Docker image for use with Apple M1 and other ARM architectures like 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 -y python3-pip git zip curl htop screen libgl1-mesa-glx libglib2.0-0
+# 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-M1 -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