Cluster box features to help choose images to annotate

[bw4sz]

As part of an active learning workflow, we'd want a way to run a detector over the boxes, and cluster box features using something like Dino v3 and then have the workflow select either 1) exemplar images from k clusters, 2) images that are similar to a user supplied image. This kind of image query helps with rapid annotation.

[musaqlain]

This is a great feature idea, I have looking in deepforest to work on architectural work from the start. I would love to contribute on it, once the issue is fully documented... also I have been exploring CropModel pipeline and DINOV2 feature extraction, happy to help design and implement this

[vickysharma-prog]

Interesting idea! A couple of thoughts while this gets documented:

The ongoing work on CropModel (#1313, #1347) is already making the crop pipeline more flexible with multi-architecture support and custom normalization this could naturally extend to plugging in a DINO-family backbone for per-box feature extraction rather than classification.
One design consideration: since the end goal is selecting images to annotate, the pipeline would need a strategy to go from box-level feature vectors to image-level selection whether that's picking images that maximize cluster diversity, or aggregating box features per image for direct image-level clustering.

Happy to wait for full documentation before diving deeper!