From Australian Oceans Data Network
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OzFish Dataset - Machine learning dataset for Baited Remote Underwater Video Stations

Created 23/06/2025

Updated 23/06/2025

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This dataset has been developed as part of the Australian Research Data Commons Data Discoveries program (https://ardc.edu.au/project/machine-learning-dataset-creation-for-australian-fish-species-from-baited-remote-underwater-videos-bruv/), with the aim to futher advance research into machine learning for the automated detection of fish from video. The dataset was generated from over 3000 videos which were historically analysed with the Event Measure software package and sourced from the Australian Institute of Marine Science (AIMS), University of Western Australia (UWA) and Curtin University of Technology. The dataset is comprised of the following: - ~80k labelled crops of fish extracted from the videos, from over 500 species, 200 genera and 70 families - ~45k bounding box annotations (suitable for YOLO,RetinaNet) of fish/no fish across 1800 frames

Files and APIs

Additional Info

Field Value
Title OzFish Dataset - Machine learning dataset for Baited Remote Underwater Video Stations
Language eng
Licence Not Specified
Landing Page https://data.gov.au/data/dataset/6db7f1a3-c931-4743-b5f2-fcbd95cbed71
Contact Point
Australian Ocean Data Network
reception@aims.gov.au
Reference Period 30/01/2020
Geospatial Coverage
Map data © OpenStreetMap contributors
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Data Portal Australian Oceans Data Network

Data Source

This dataset was originally found on Australian Oceans Data Network "OzFish Dataset - Machine learning dataset for Baited Remote Underwater Video Stations". Please visit the source to access the original metadata of the dataset:
https://catalogue.aodn.org.au/geonetwork/srv/eng/csw/dataset/ozfish-dataset-machine-learning-dataset-for-baited-remote-underwater-video-stations