DOI: 10.5281/zenodo.12819156
title: Seatizen Atlas image dataset

description: Seatizen Atlas image dataset

This repository contains the resources and tools for accessing and utilizing the annotated images within the Seatizen Atlas dataset, as described in the paper Seatizen Atlas: a collaborative dataset of underwater and aerial marine imagery.

Download the Dataset

This annotated dataset is part of a bigger dataset composed of labeled and unlabeled images. To access information about the whole dataset, please visit the Zenodo repository and follow the download instructions provided.

If you are interested in training AI models using this dataset, you can directly access the processed version on Hugging Face.This version is already split into training, validation and test sets, and includes only the classes with more than 200 annotations for more robust model training.

An example of a trained model based on this dataset is DinoVdeau.

Scientific Publication

If you use this dataset in your research, please consider citing the associated paper:

@article{contini2025seatizen,  title={Seatizen Atlas: a collaborative dataset of underwater and aerial marine imagery},  author={Contini, Matteo and Illien, Victor and Julien, Mohan and Ravitchandirane, Mervyn and Russias, Victor and Lazennec, Arthur and Chevrier, Thomas and Rintz, Cam Ly and Carpentier, L{\'e}anne and Gogendeau, Pierre and others},  journal={Scientific Data},  volume={12},  number={1},  pages={67},  year={2025},  publisher={Nature Publishing Group UK London}}

For detailed information about the dataset and experimental results, please refer to the previous paper.

Overview

The Seatizen Atlas dataset includes 14,492 multilabel and 1,200 instance segmentation annotated images. These images are useful for training and evaluating AI models for marine biodiversity research. The annotations follow standards from the Global Coral Reef Monitoring Network (GCRMN).

Annotation Details



Annotation Types:

Multilabel Convention: Identifies all observed classes in an image.

Instance Segmentation: Highlights contours of each instance for each class.


List of Classes

Algae



Algal Assemblage

Algae Halimeda

Algae Coralline

Algae Turf


Coral



Acropora Branching

Acropora Digitate

Acropora Submassive

Acropora Tabular

Bleached Coral

Dead Coral

Gorgonian

Living Coral

Non-acropora Millepora

Non-acropora Branching

Non-acropora Encrusting

Non-acropora Foliose

Non-acropora Massive

Non-acropora Coral Free

Non-acropora Submassive


Seagrass



Syringodium Isoetifolium

Thalassodendron Ciliatum


Habitat



Rock

Rubble

Sand


Other Organisms



Thorny Starfish

Sea Anemone

Ascidians

Giant Clam

Fish

Other Starfish

Sea Cucumber

Sea Urchin

Sponges

Turtle


Custom Classes



Blurred

Homo Sapiens

Human Object

Trample

Useless

Waste


These classes reflect the biodiversity and variety of habitats captured in the Seatizen Atlas dataset, providing valuable resources for training AI models in marine biodiversity research.

Usage Notes

The annotated images are available for non-commercial use. Users are requested to cite the related publication in any resulting works. A GitHub repository has been set up to facilitate data reuse and sharing: GitHub Repository.

Code Availability

All related codes for data processing, downloading, and AI model training can be found in the following GitHub repositories:



Plancha Workflow

Zenodo Tools

DinoVdeau Model


Acknowledgements

This dataset and associated research have been supported by several organizations, including the Seychelles Islands Foundation, Réserve Naturelle Marine de la Réunion, and Monaco Explorations, among others.

For any questions or collaboration inquiries, please contact seatizen.ifremer@gmail.com.