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Last pushed: a year ago
Short Description
Tensorflow and Jupyter running in docker container on Raspberry Pi 3B
Full Description

Docker image for the Raspbery Pi which contains Tensorflow, Jupyter and three tensorflow
notebooks copied from the official Google docker Tensorflow build..

This is not an official tensorflow port, so don't ask for or expect
support from the tensorflow team.

Running the image

This run instruction expects a directory called myNotebooks within your
home directory.

If you save an IPython notebook to the myNotebooks sub-directory
while running your container, it will get saved to the myNotebooks
directory on your Pi.

Notebooks saved to that directory will be persistent - in other words,
they will still be there when the container is stopped and restarted.

Execute this command in a terminal:

docker run -it -p 8888:8888 -v ~/myNotebooks:/notebooks/myNotebooks romilly/rpi-docker-tensorflow

Previously there were some spurious warnings when the container started but the latest resin image fixes these.
(Thanks, resinators!)

You can probably ignore the warnings about the insecurity of the IPython server configuration so long as you do not store any sensitive data or code in your notebooks.

Connecting to the notebooks

Open a browser on http://raspberrypi:8888 where raspberrypi is the
hostname of the Pi on which the docker image is running, or on
http://localhost:8888 on the Pi itself.

Stopping the image

In the terminal session where you ran the container, type Ctr-C twice in
quick succession. The container will stop.


  1. Docker:
  2. Base image: from a post by the chaps at
  3. Pi tensorflow whl file
    from Sam Abrahm's Github project
  4. Notebooks and notebook config from The Tensorflow Docker Build on Github
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