I am currently working on a problem where I don't have a plethora of labeled data. I therefore want to use active learning to try and label some of my data using the model and then have all images (in this case) with a low confidence threshold be sent off for annotation. Are there any built in or peripheral techniques/packages in the FluxML ecosystem that would enable this? I looked around but did not see active learning techniques mentioned at all for Flux. In PyTorch for example, one of the resources I use is this PyTorch for Active learning repo.
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