Underwater images collected by a Kite surf in Le-Morne, Mauritius - 2018-03-12

This dataset was collected by a Kite surf in Le-Morne, Mauritius - 2018-03-12. 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!本数据集由风筝冲浪者于2018年3月12日在毛里求斯勒莫尔（Le-Morne）采集。 由科研人员与公众采集的水下及航空影像，可广泛应用于科学研究、资源管理与生态保护等场景。此类影像经标注与共享后，可用于训练人工智能（AI）模型以识别影像中的目标物体。本项目提供一套软硬件工具集，可实现海洋数据采集、物种/栖息地识别及地图生成功能。 本数据集隶属于包含海量水下与航空影像的大型数据集集合Seatizen 图集（Seatizen Atlas）。相关研究方法、工具及科学目标已在专属数据论文中详细阐述。 GPS信息： 采用佳明（Garmin）运动手表生成的GPX文件。 通用文件夹结构 通用命名格式：YYYYMMDD_COUNTRYCODE-[可选地点]_设备_会话-编号 ├── DCIM：用于存储本次采集的各类视频与照片文件。 ├── GPS：用于存储所有定位相关文件。若可对文件进行定位校正（例如基于RINEX数据开展后处理运动解算（Post-Processed Kinematic）），则需区分设备原始数据与基准站数据；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。 │ ├── BASE：来自RTK基准站或其他静态定位仪器的文件。 │ └── DEVICE：来自采集设备的文件。 ├── METADATA：用于存储本次采集会话的通用信息文件。 ├── PROCESSED_DATA：用于存储当前会话数据处理后的各类结果，包含以下子文件夹： │ ├── BATHY：存储从任务日志中提取的水深测量原始数据的输出目录。 │ ├── FRAMES：存储从DCIM文件夹内视频中提取的带地理坐标帧的输出目录。 │ ├── IA：存储图像识别预测结果的目标目录。 │ └── PHOTOGRAMMETRY：存储摄影测量重建模型的目标目录。 └── SENSORS：用于存储其他来源的文件（例如回声测深仪获取的水深数据、自动驾驶仪日志文件、任务规划文件等）。 软件 所有原始数据均通过本团队自研的工作流完成处理，所有预测结果均由本团队的推理流水线生成。您可在本代码仓库中获取下载该数据集所需的全部脚本文件。祝您使用SeatizenDOI开展研究顺利！