This container (based on ipython/scipystack) provides a containerised research environment suitable for scientific use with a particular emphasis on Computer Vision.
In addition to the packages pulled in via scipystack, this container also pulls
in a recent version of the Jupyter notebook server and installs OpenCV 3 for
both Python 3 and Python 2. The opencv_contrib
modules are also installed.
The container exposes a single port which the Jupyter notebook server runs on. Launch the container with an incantation similar to the following:
$ docker run -i -p 8888:8888/tcp rjw57/jupyter
By default the Jupyter notebook runs as a user which is given sudo
access
inside the container. NOTE THAT HAVING ROOT IN THE CONTAINER SHOULD BE VIEWED
AS HAVING ROOT ON THE HOST. The user logon name and id can be configured by
setting the USER
and USER_UID
environment variables. For example, to
launch the container for the current user:
$ docker run -i -p 8888:8888/tcp -e USER -e USER_UID=$(id -u) rjw57/jupyter
Some niceties of configuration include:
- A fresh version of OpenCV.
- Versions of
pip
for Python 2 and Python 3 are available viapip2
andpip3
. pip
is configured so thatpip install
will install the package into the user's home directory.- The user's profile is configured to put
~/.local/bin
on the path so packages installed viapip
which have command-line scripts will work as expected.
If you have Vagrant installed, the provided Vagrant file can be used to provision a virtual machine running the container.