The purpose of this container is to create a Python 3.4 Deep Learning environment with Jupyter Lab for use with Raspberry Pi 4 (armv7l).
Note that you should be building and using this container only on a Raspberry Pi 4.
Before you may build this docker image, you will need to cross compile Tensorflow for the Raspberry Pi. Note when you compile Tensorflow, you have to compile on a x86 computer (not on a Raspberry Pi or any ARMv7 CPU).
git clone https://github.com/tensorflow/tensorflow.git
cd tensorflow
git checkout r1.14
tensorflow/tools/ci_build/ci_build.sh PI \
tensorflow/tools/ci_build/pi/build_raspberry_pi.sh PI_ONEAfter you are done, place the $TENSORFLOW/output-artifacts into this directory, where $TENSORFLOW is the path to where you checked out the Tensorflow git repository. Additionally, rename tensorflow-1.14.1-cp34-none-linux_armv7l.whl to tensorflow-1.14.1-cp36-none-linux_armv7l.whl.
Build it.
./build.shRun it (plain).
docker run -it -p 8888:8888 rpi-deeplearning:localRun it (with host mount).
docker run -it \
-p 8888:8888 \
-v $HOME/git/docker-containers/rpi-deeplearning/ipynb:/ipynb \
rpi-deeplearning:localRun it (with Jupyter Notebook instead of Jupyter lab)
docker run -it \
-p 8888:8888 \
-v $HOME/git/docker-containers/rpi-deeplearning/ipynb:/ipynb \
-e JUPYTER_TYPE=notebook \
rpi-deeplearning:localObserve it.
- https://stackoverflow.com/questions/33622613/tensorflow-installation-error-not-a-supported-wheel-on-this-platform
- https://askubuntu.com/questions/183312/how-are-so-files-used-in-ubuntu
Check out John Backus.
@misc{oneoffcoder_rpi_deeplearning_2019,
title={Docker container with Tensorflow for Raspberry Pi 4},
url={https://github.com/oneoffcoder/docker-containers/tree/master/rpi-deeplearning},
journal={GitHub},
author={One-Off Coder},
year={2019},
month={Jul}}
