Underwater images collected by a Kite surf in Pointe-Esny, Mauritius - 2018-01-03

This dataset was collected by a Kite surf in Pointe-Esny, Mauritius - 2018-01-03. Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps. This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. Methods, tools and scientific objectives are also described in a dedicated data paper. GPS information: GPX file from Garmin watch. Generic folder structure YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM : folder to store videos and photos depending on the media collected. ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. │ ├── BASE : files coming from rtk station or any static positioning instrument. │ └── DEVICE : files coming from the device. ├── METADATA : folder with general information files about the session. ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). Software All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!本数据集由一名风筝冲浪爱好者于2018年1月3日在毛里求斯埃斯尼角采集。 科研人员与民众采集的水下或航拍图像，可广泛应用于科学研究、资源管理与生态保护等领域。此类图像可经标注后共享，用于训练人工智能（AI）模型，以实现图像内目标的自动识别与预测。本团队提供一套软硬件工具集，可用于海洋数据采集、物种/栖息地识别以及专题地图制作。 本数据集隶属于涵盖海量水下与航拍图像的大型数据集Seatizen Atlas（Seatizen图集），相关研究方法、工具集及科学目标已在专属数据论文中详细阐述。 GPS信息： 来自佳明（Garmin）品牌手表的GPX文件。 通用文件夹命名与结构： YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM ：用于存储本次采集的视频与照片的媒体文件夹。 ├── GPS ：用于存储各类定位相关文件的文件夹。若可对文件进行定位校正（例如基于RINEX星历数据的后处理运动学校正），则需区分基准站数据与设备采集数据；若仅存在设备定位数据且无法通过后处理技术校正（例如GPX文件），则无需区分基准站与设备数据，直接将文件置于GPS文件夹根目录下。 │ ├── BASE ：来自实时动态差分（RTK）基站或其他静态定位仪器的文件。 │ └── DEVICE ：来自采集设备的定位文件。 ├── METADATA ：存储本次任务通用元数据文件的文件夹。 ├── PROCESSED_DATA ：用于存储本次任务数据处理结果的各级子文件夹，包含： │ ├── BATHY ：从任务日志中提取的测深原始数据的输出文件夹。 │ ├── FRAMES ：从DCIM文件夹内视频中提取的地理参考帧的输出文件夹。 │ ├── IA ：图像识别预测结果的存储目录。 │ └── PHOTOGRAMMETRY ：摄影测量重建模型的存储目录。 └── SENSORS ：用于存储其他来源文件的文件夹，例如回声测深仪采集的测深数据、自动驾驶仪日志文件、任务规划文件等。 软件说明： 本批次所有原始数据均通过自研工作流完成处理，所有预测结果均由自研推理管线生成。您可在本仓库中获取下载该数据集所需的全部脚本。祝您顺利使用SeatizenDOI开展研究！