Create rich data annotations in Jupyter notebooks with ipyannotations.
ipyannotations provides interactive UI elements, based on ipywidgets, to allow developers and scientists to label data right in the notebook.
ipyannotations supports many common data labelling tasks, such as image and text classification and annotation. It also supports custom data presentation by leveraging the Jupyter ecosystem.
To get started with ipyannotations, install with pip:
pip install ipyannotations
To start labelling data, import from the appropriate ipyannotations module. For example, for text span/entity labelling:
from ipyannotations import text widget = text.TextTagger() widget.display("This is a text tagging widget. Highlight words " "or phrases to tag them with a class.") widget
Or, if you would like to classify images:
from ipyannotations import images widget = images.ClassLabeller(options=["monkey", "ape"]) widget.display("img/baboon.png") widget
Throughout this documentation, UI elements can be interacted with (e.g. buttons can be clicked, sliders can be moved), but because there is no python process running in the background, the effect will mostly not be visible.
- Full widget list
- API documentation