Seatizen Atlas 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 lebeled and unlabeled images. To access informations about the whole dataset, please visit the Zenodo repository and follow the download instructions provided.

Scientific Publication

If you use this dataset in your research, kindly cite the paper:

@article{seatizen-atlas,author = {Matteo Contini and Victor Illien and Mohan Julien and Mervyn Ravitchandirane and Victor Russias and others},title = {Seatizen Atlas: a collaborative dataset of underwater and aerial marine imagery},journal = {Scientific Data},year = {2024},}

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

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.