No abstract

Amphipods of the Hyalella genus are aquatic macroinvertebrates of interest in areas such as limnology and ecotoxicology that use data on the number of Hyalella individuals and their allometric measurements to assess the environmental dynamics of aquatic ecosystems. We introduce the software HyACS, aimed at counting individuals and extracting morphological metrics of the Hyalella genus by means of artificial vision based on YOLOv3 and digital image processing techniques. The software detects body metrics of length, arc length, maximum width, eccentricity, perimeter, and area of Hyalella individuals, using basic imaging capture equipment. The method requires images for training and prediction stages. Results show high prediction levels with HyACS, reaching metrics above 90%, in the correct identification of individuals, performing up to five times faster than traditional visual counting, and offering precise morphological measurements of Hyalella individuals that may improve further studies of the species populations and boost their use as bioindicators of water quality.