The Tasmanian Orange Roughy Stereo Image Machine Learning Dataset is a collection of annotated stereo image pairs collected by a net-attached Acoustic and Optical System (AOS) during orange roughy (Hoplostethus atlanticus) biomass surveys off the northeast coast of Tasmania, Australia in July 2019. The dataset consists of expertly annotated imagery from six AOS deployments (OP12, OP16, OP20, OP23, OP24, and OP32), representing a variety of conditions including different fish densities, benthic substrates, and altitudes above the seafloor. Each image was manually annotated with bounding boxes identifying orange roughy and other marine species. For all annotated images, paired stereo images from the opposite camera have been included where available to enable stereo vision analysis. This dataset was specifically developed to investigate the effectiveness of machine learning-based object detection techniques for automating fish detection under variable real-world conditions, providing valuable resources for advancing automated image processing in fisheries science.
Tasmanian Orange Roughy Stereo Image Machine Learning Dataset