DEEP Development Environment

This is a Docker image for developing new modules


Model

Published by DEEP-Hybrid-DataCloud Consortium
Created: - Updated:

Model Description

Build Status

This is a Docker image for developing new modules. It comes preinstalled with DEEPaaS, Jupyter Lab, Tensorflow, and a number of other tools (see here) As you have access to the terminal of Jupyter Lab, you can develop and debug your application, add your preferred tools.

Test this module

You can test and execute this module in various ways.

Excecute locally on your computer using Docker

You can run this module directly on your computer, assuming that you have Docker installed, by following these steps:

$ docker pull deephdc/deep-oc-generic-dev
$ docker run -ti -p 5000:5000 deephdc/deep-oc-generic-dev

Execute on your computer using udocker

If you do not have Docker available or you do not want to install it, you can use udocker within a Python virtualenv:

$ virtualenv udocker
$ source udocker/bin/activate
$ git clone https://github.com/indigo-dc/udocker
$ cd udocker
$ pip install .
$ udocker pull deephdc/deep-oc-generic-dev
$ udocker create deephdc/deep-oc-generic-dev
$ udocker run -p 5000:5000  deephdc/deep-oc-generic-dev

In either case, once the module is running, point your browser to http://127.0.0.1:5000/ and you will see the API documentation, where you can test the module functionality, as well as perform other actions (such as training).

For more information, refer to the user documentation.

Categories

development, tensorflow, jupyterlab, api-v2

License

License: MIT

Get the code

Github Docker Hub