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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.ipynb with the data set dataset = '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
The text was updated successfully, but these errors were encountered:
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
nbs/01b_tutorial_image_classification.ipynb
with the data setdataset = 'oxford_flowers'
possible improvements:
The text was updated successfully, but these errors were encountered: