Aquaculture Dataset: Black Tiger Prawn Segmentation

Understanding the growth and distribution of the prawns is critical for optimising the feed and harvest strategies. However, the most commonly adopted sampling practice, the cast net approach, is unable to sample the prawns at a high frequency as it is expensive and laborious. An alternative approach is to use computer vision techniques to sample prawns from feed trays that farm workers inspect multiple times each day. Being able to accurately detect and segment prawns is the very first step towards frequent prawn growth monitoring using computer vision techniques. However, there is no publicly available prawn segmentation data. This dataset is the very first dataset that provides polygon annotations (COCO format) for Black Tiger Prawns (Penaeus monodon).