yolov7_NPSNF

NOAA Pudget Sound Nearshore fish dataset(NPSNF)

This data set contains 77,739 images sampled from video collected on and around shellfish aquaculture farms in an estuary in the Northeast Pacific, in which 67,990 objects (fish and crustaceans) have been annotated on 30,384 images (the remainder have been annotated as “empty”). This data set was used to develop a computer vision model to detect fish, allowing specialists from NOAA to examine images in which fish were detected to classify and quantify their species more efficiently. Incorporating artificial intelligence into ecological and resource management fields will advance our understanding of potential changes in the marine environment in the context of fisheries and aquaculture expansion, shoreline development, and climate change.

Data Access link: https://lila.science/datasets/noaa-puget-sound-nearshore-fish

Model: YOLOv7

The model was trained using the default hyperparameters of YOLOv7 model. No pre-processing was done before training. The model was trained for 500 epochs and the model with the best validation mAP is uploaded to the repo.