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jupyter based annotator for multi-class multi-label image problems

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sugi-chan/multi_label_pigeon

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🐦 multi_label_pigeon

This repo is a simple multiclass image extenstion of the pigeon library by @agermanidis located here. Credit goes to them for building the annotate function for images, text, and regression for multi-class type problems. All I am doing is extending it to multi-label and multi-task type problems.

Installation

Can install with standard pip.

pip install multi-label-pigeon

Examples

from multi_label_pigeon import multi_label_annotate
from IPython.display import display, Image

annotations = multi_label_annotate(
    ['assets/altera.jpg', 'assets/chibi_gil.jpg','assets/chibi_saber.jpg'],
    options={'cute':['yes','no'], 'saber':['yes','no'],'colors':['blue','gold','white','red']},
    display_fn=lambda filename: display(Image(filename))
    )

Preview:

alt text

New in v0.3.0: colors!

Additional Notes

  • skip readded the old skip button for clarity. In the case you dont want to label any annotations for a sample you can press skip or done but having skip is probably more clear.

I added some additional buttons as well to the multi-label script. Since we want to be able to select more than one category I added a few extra buttons.

  • done to press after all relevant fields have been clicked.

  • back button in case you want to go back to a previous image. WARNING this will erase that item from the dictionary so you will have to click through all the classes you want to mark for that previous image again. back_example

  • clear current WARNING will delete the current image from the dictionary on the back end so you can re enter the classes in case you messed one up. clear_current

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