Underwater images collected by an Underwater Vision Census in Toliara, Madagascar - 2024-01-16

This dataset was collected by an Underwater Vision Census in Toliara, Madagascar - 2024-01-16. 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. Survey information Camera: NIKON CORPORATION COOLPIX W300 Number of images: 196 Total size: 0.6 Gb Mission start: 2024:01:16 07:46:23 Mission end: 2024:01:16 08:16:17 Mission duration: 0h 29min 54sec Total distance: 483 m GPS information: Surveys were conducted during low spring tides on reef areas less than 20 meters deep. A GPS device, kept in a floating waterproof bag at the surface, recorded a position every 2 seconds while following the diver's path. One diver took a benthic photo every 5 meters using a compass for direction, while a second diver guided the GPS bag from the surface. Image positions were interpolated with GPS data through time synchronization, using the timestamps embedded in the image metadata. Details of the acquisition method can be found in this paper. 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. │ ├── CPCE_ANNOTATION : All cpc files annotations made with the CPCe software. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. Software All the raw data was processed using our worflow. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!本数据集由马达加斯加图利亚拉的水下视觉普查项目于2024年1月16日采集完成。 科学家或普通民众采集的水下与空中影像，可广泛应用于科学研究、资源管理与生态保护等领域。此类影像经标注后可共享，用于训练人工智能（AI）模型，以实现影像内目标物体的自动识别与预测。我们提供一套涵盖硬件与软件的工具集，可用于海洋数据采集、物种/栖息地识别及地图生成。 调查信息 相机：尼康（NIKON CORPORATION）COOLPIX W300 相机 图像数量：196张 总大小：0.6 GB 任务起始时间：2024:01:16 07:46:23 任务结束时间：2024:01:16 08:16:17 任务持续时长：0小时29分54秒 总行进距离：483米 GPS定位信息： 本次调查于春汛低潮期在水深小于20米的珊瑚礁海域开展。一台置于水面漂浮防水袋内的GPS设备，每2秒记录一次定位坐标，同步跟随潜水员的行进轨迹。一名潜水员借助罗盘定向，每行进5米拍摄一张底栖生物影像；另一名潜水员在水面操控搭载GPS设备的防水袋。通过图像元数据内嵌的时间戳实现时间同步，结合GPS定位数据对图像拍摄位置进行插值补全。采集方法的详细细节可参阅本论文。 通用文件夹结构 YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM ：用于存储采集到的各类视频与照片的文件夹。 ├── GPS ：用于存储各类定位相关文件的文件夹。若可对文件进行校正（例如基于RINEX星历数据开展后处理运动学校正），则需区分基站数据与设备数据；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格式文件），则无需区分基站与设备数据，直接将文件置于GPS文件夹根目录下。 │ ├── BASE ：来自实时动态差分（Real-Time Kinematic, 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 ：存储本次调查会话通用信息文件的文件夹。 ├── PROCESSED_DATA ：用于存储当前会话数据处理结果的所有子文件夹。 │ ├── CPCE_ANNOTATION ：使用CPCe软件生成的全部CPC格式标注文件。 │ ├── IA ：人工智能（AI）识别预测结果存储目录。 │ └── PHOTOGRAMMETRY ：摄影测量重建模型存储目录。 软件工具 所有原始数据均通过我们的标准化工作流进行处理。您可在本代码仓库中获取下载该数据集所需的全部脚本。祝您使用SeatizenDOI顺利开展相关研究！