ipyannotator
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Improve image labeling for large number of classes
Motivation
ipyannotator currently support image labeling. However, for data sets with a very large number of classes it's very difficult to quickly match the image to the right class.
Showing an visual representation for all possible classes and there textual description right next to the image could considerable improve the process. Currently only a textual or a visual representation can be displayed.
Explore the current difficulties
- run the notebook
nbs/01b_tutorial_image_classification.ipynbwith the data setdataset = 'oxford_flowers'

possible improvements:
- make it easy to show the class name instead of the number (requires mapping from class id to class name)
- show both visual and textual description
- if the data set is already annotated, provide an option to take the visual example right from the data set