| # 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. | |