Underwater images collected by an Underwater Vision Census in Toliara, Madagascar - 2024-01-17

This dataset was collected by an Underwater Vision Census in Toliara, Madagascar - 2024-01-17. 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: 141 Total size: 0.42 Gb Mission start: 2024:01:17 07:22:14 Mission end: 2024:01:17 07:42:50 Mission duration: 0h 20min 36sec Total distance: 266 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2024年1月17日在马达加斯加图利亚拉开展的水下视觉普查项目采集。 科研人员或公民科学家拍摄的水下、航空影像可广泛应用于科学研究、资源管理与生态保护。此类影像经标注与共享后，可用于训练人工智能（Artificial Intelligence, AI）模型以实现图像目标识别。本数据集配套提供一套软硬件工具集，用于海洋数据采集、物种与生境识别以及测绘制图。 ### 调查详情 - 相机：尼康（NIKON）COOLPIX W300数码相机 - 图像总数：141张 - 总文件大小：0.42 GB - 任务起始时间：2024:01:17 07:22:14 - 任务结束时间：2024:01:17 07:42:50 - 任务持续时长：0小时20分36秒 - 总行进距离：266米 ### GPS定位详情 本次调查于春汛低潮期在水深不足20米的礁区开展。实验人员将GPS设备置于水面漂浮防水袋中，沿潜水员行进路径每2秒记录一次位置。一名潜水员借助定向罗盘，每行进5米拍摄一张底栖生物照片；另一名潜水员在水面操控搭载GPS设备的漂浮装置。通过同步图像元数据内嵌的时间戳，将图像位置与GPS定位数据进行插值匹配。本数据采集方法的详细细节可参阅相关论文。 ### 标准文件夹组织结构 文件夹命名格式为：`YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number` ├── DCIM：用于存储采集到的视频与照片文件的目录 ├── GPS：存储所有定位相关文件的目录。若可对文件进行差分定位校正（例如基于RINEX数据的后处理运动学解算），则需将基准站数据与设备端数据分别存放；若仅存在设备端定位数据且无法通过后处理技术校正（例如GPX格式文件），则无需区分基准站与设备端数据，直接将文件存放于GPS目录根目录下 │ ├── BASE：来自RTK基准站或其他静态定位仪器的数据文件 │ └── DEVICE：来自采集设备的定位数据文件 ├── METADATA：存储本次调查会话通用信息文件的目录 ├── PROCESSED_DATA：用于存储本次调查数据处理结果的目录 │ ├── CPCE_ANNOTATION：使用CPCe软件生成的所有CPC格式标注文件 │ ├── IA：图像识别模型预测结果的存储目录 │ └── PHOTOGRAMMETRY：摄影测量重建模型的存储目录 ### 配套软件工具 本数据集所有原始数据均通过标准工作流完成处理。用户可在本仓库中获取下载该数据集所需的全部脚本。祝您使用SeatizenDOI获取的科研数据顺利！