Automated species annotation in turbid waters

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Project Description

The project’s aim was to create an automated image-annotation pipeline to monitor the ecological status of vulnerable marine habitats according to the goals of multiple European Directives. The variability of the image quality and the diversity of the species made this project challenging.

Training a semantic segmentation model was not possible because they did not have enough ground-truth masks. However, they had a good amount of point annotations, which we could use as the prompt for the SAM2 model. We provided a pipeline for applicants to utilise their point prompts to produce instance segmentation masks automatically, and then export the selected masks into COCO format, which was compatible with the BIIGLE that they are using as their main image and annotations platform.