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# DFUC24 Baselines
This repository contains baseline models for the DFUC24 challenge. Two approaches were investigated:
1. Training a supervised segmentation head (using the DFUC22 dataset) on frozen image embeddings of the self-supervised pre-trained DINOv2 image backbone.
2. Using GroundedDINO + SAM in combination to achieve ulcer detection, which serves as a prompt for the SegmentAnything (SAM) model, as well as fine-tuned (using the DFUC22 dataset) versions of GroundedDINO and SAM.
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