ipyannotator 0.8.1

The infinitely hackable annotation framework

Ipyannotator - the infinitely hackable annotation framework

Ipyannotator is a flexible annotation system. The library contains some pre-defined annotators that can be used out of the box, but it also can be extend and customized according to the users needs.

We hope this repository helps you to explore how annotation UI's can be quickly built using only python code and leveraging many awesome libraries (ipywidgets, voila, ipycanvas, etc.) from the jupyter Eco-system.

At https://palaimon.io we have used the concepts underlying Ipyannotator internally for various projects and this is our attempt to contribute back to the OSS community some of the benefits we have had using OOS software.

Please star, fork and open issues!

Please let us know if you find this repository useful. Your feedback will help us to turn this proof of concept into a comprehensive library.

Install

pip install ipyannotator

dependencies (should be handled by pip)

python = "^3.7"
traitlets = '=4.3.3'
ipycanvas = "^0.5.1"
ipyevents = "^0.8.0"
ipywidgets = "^7.5.1"

Run ipyannotator as stand-alone web app using voila

Using poetry:

install:

cd {project_root}
poetry install --no-dev
poetry run pip install voila

and run simple ipyannotator standalone example:

poetry run voila nbs/09_voila_example.ipynb --enable_nbextensions=True

Same with pip:

   cd {project_root}
   
   pip install . 
   pip install voila
   
   voila nbs/09_voila_example.ipynb --enable_nbextensions=True

Documentation

This library has been written in the literate programming style popularized for jupyter notebooks by nbdev. Please explore the jupyter notebooks in nbs/ to learn more about the inner working of ipyannotator.

The notebooks contains the development dependencies: pytest and ipytest, if you want to run the notebooks remove the tests or install the libraries mentioned.

Also check out the following notebook for a more high level overview.

• Tutorial demonstrating how ipyannotator can be seamlessly integrated in your data science workflow. nbs/08_tutorial_road_damage.ipynb
• Recoding of jupytercon 2020 talk explaining the high level concepts / vision of ipyannotator.

Jupyter lab trouble shooting

For clean (re)install make sure to have all the lab extencions active:

jupyter lab clean to remove the staging and static directories from the lab

ipywidgets:

jupyter labextension install @jupyter-widgets/jupyterlab-manager

ipycanvas:

jupyter labextension install @jupyter-widgets/jupyterlab-manager ipycanvas

ipyevents:

jupyter labextension install @jupyter-widgets/jupyterlab-manager ipyevents

nbdime:

nbdime extensions --enable [--sys-prefix/--user/--system]

viola:

jupyter labextension install @jupyter-voila/jupyterlab-preview

How to contribute

Check out CONTRIBUTING.md and since ipyannotator is build using nbdev reading the nbdev tutorial and related docs will be very helpful.

Additional resources

• jupytercon 2020 talk.

##Acknowledgements

The authors acknowledge the financial support by the Federal Ministry for Digital and Transport of Germany under the program mFUND (project number 19F2160A).

Copyright

Copyright 2020 onwards, Palaimon GmbH. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this project's files except in compliance with the License. A copy of the License is provided in the LICENSE file in this repository.