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minimal Dockerfile for running some edgetpu demos
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# 1) create this dockerfile | |
# 2) build: docker build -t "coral-edgetpu" . | |
# 3) run: docker run -it --privileged -v /dev/bus/usb:/dev/bus/usb coral-edgetpu /bin/bash | |
# 4) download install requriements: cd ~/tflite/python/examples/classification/ && bash install_requirements.sh | |
# 5) run example: python3 classify_image.py \ | |
# > --model models/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite \ | |
# > --labels models/inat_bird_labels.txt \ | |
# > --input images/parrot.jpg | |
FROM tensorflow/tensorflow:1.15.0-py3 | |
WORKDIR /home | |
ENV HOME /home | |
VOLUME /data | |
EXPOSE 8888 | |
RUN cd ~ | |
RUN apt-get update | |
RUN apt-get install -y git nano python-pip python-dev pkg-config wget usbutils | |
RUN echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" \ | |
| tee /etc/apt/sources.list.d/coral-edgetpu.list | |
RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - | |
RUN apt-get update | |
RUN apt-get install -y libedgetpu1-std | |
RUN wget https://dl.google.com/coral/python/tflite_runtime-2.1.0-cp36-cp36m-linux_x86_64.whl | |
RUN pip3 install tflite_runtime-2.1.0-cp36-cp36m-linux_x86_64.whl | |
RUN mkdir coral && cd coral | |
RUN git clone https://github.com/google-coral/tflite.git |
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