Metadata-Version: 2.1
Name: ipyannotator
Version: 0.8.1
Summary: The infinitely hackable annotation framework
Home-page: https://github.com/palaimon/ipyannotator
License: Apache-2.0
Author: palaimon.io
Author-email: oss@mail.palaimon.io
Requires-Python: >=3.8,<4.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: PyPubSub (>=4.0.3,<5.0.0)
Requires-Dist: ipycanvas (>=0.10.2,<0.11.0)
Requires-Dist: ipyevents (>=0.8.0,<0.9.0)
Requires-Dist: ipykernel (>=5.3.4,<6.0.0)
Requires-Dist: ipython (>=8.0.1,<9.0.0)
Requires-Dist: ipywidgets (>=7.5.1,<8.0.0)
Requires-Dist: matplotlib (>=3.4.3,<4.0.0)
Requires-Dist: nbdev (>=1.2.0,<2.0.0)
Requires-Dist: pandas (>=1.1.2,<2.0.0)
Requires-Dist: pooch (>=1.5.2,<2.0.0)
Requires-Dist: pydantic (>=1.8.2,<2.0.0)
Requires-Dist: scikit-image (>=0.18.3,<0.19.0)
Requires-Dist: tqdm (>=4.64.0,<5.0.0)
Requires-Dist: traitlets (>=5.1.1,<6.0.0)
Requires-Dist: voila (>=0.3.1,<0.4.0)
Project-URL: Repository, https://github.com/palaimon/ipyannotator
Description-Content-Type: text/markdown

# Ipyannotator - the infinitely hackable annotation framework

![CI-Badge](https://github.com/palaimon/ipyannotator/workflows/CI/badge.svg)

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](https://github.com/jupyter-widgets/ipywidgets), [voila](https://github.com/voila-dashboards/voila), [ipycanvas](https://github.com/martinRenou/ipycanvas), etc.) from the [jupyter Eco-system](https://jupyter.org/).

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:
```shell
cd {project_root}
poetry install --no-dev
poetry run pip install voila
```
and run simple ipyannotator standalone example:
```shell 
poetry run voila nbs/09_voila_example.ipynb --enable_nbextensions=True
```
  
Same with `pip`:

```shell
   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](https://en.wikipedia.org/wiki/Literate_programming) popularized for
jupyter notebooks by [nbdev](https://www.fast.ai/2019/12/02/nbdev/). Please explore the jupyter notebooks in `nbs/` to learn more about
the inner working of ipyannotator.

The notebooks contains the development dependencies: 
[pytest](https://docs.pytest.org/en/7.1.x/) and [ipytest](https://github.com/chmp/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](https://www.youtube.com/watch?v=jFAp1s1O8Hg) 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](https://nbdev.fast.ai/tutorial.html) and related docs will be very helpful.

## Additional resources

![jupytercon 2020](https://jupytercon.com/_nuxt/img/5035c8d.svg)

- [jupytercon 2020 talk](https://cfp.jupytercon.com/2020/schedule/presentation/237/ipyannotator-the-infinitely-hackable-annotation-framework/).

##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.



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