Underwater images collected by an Underwater Vision Census in Salary, Madagascar - 2021-09-03

This dataset was collected by an Underwater Vision Census in Salary, Madagascar - 2021-09-03. 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. Survey information Camera: NIKON CORPORATION COOLPIX W300 Number of images: 164 Total size: 0.5 Gb Mission start: 2021:09:03 09:14:23 Mission end: 2021:09:03 09:38:20 Mission duration: 0h 23min 57sec Total distance: 334 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2021年9月3日在马达加斯加萨利（Salary）开展的水下视觉普查项目采集。 由科研人员或公众采集的水下、航空影像可广泛应用于科学研究、资源管理与生态保护领域。此类影像可经标注与共享后，用于训练人工智能（AI）模型，以实现影像内目标的自动识别预测。我们提供一套配套工具（含硬件与软件），可用于海洋数据采集、物种/栖息地识别以及地图生成。 ### 调查概况 相机：尼康（NIKON CORPORATION）COOLPIX W300相机 影像总数：164张 总数据量：0.5 GB 任务开始时间：2021年9月3日 09:14:23 任务结束时间：2021年9月3日 09:38:20 任务时长：0小时23分57秒 总行进距离：334米 ### GPS相关信息 本次调查于低潮大潮期间在水深不足20米的礁区开展。一台全球定位系统（GPS）设备置于水面的防水浮袋中，沿潜水员行进路径每2秒记录一次位置。一名潜水员以罗盘定向，每行进5米拍摄一张底栖照片，另一名潜水员则在水面操控GPS浮袋。通过影像元数据内嵌的时间戳进行时间同步，结合GPS数据对影像拍摄位置进行插值补全。本采集方法的详细细节可参阅相关论文。 ### 通用文件夹结构 命名格式：YYYYMMDD_COUNTRYCODE-可选地点_设备_会话-编号 ├── DCIM：用于存储采集所得视频与照片的文件夹。 ├── GPS：用于存储所有与定位相关文件的文件夹。若可对文件进行各类校正（例如基于星历数据（rinex data）进行后处理运动学校正），则需区分基站数据与设备数据；若仅存在设备位置数据且无法通过后处理技术校正文件（例如GPX文件），则无需区分基站与设备数据，文件直接置于GPS文件夹根目录下。 │ ├── BASE：来自实时动态差分（RTK）基站或静态定位仪器的文件。 │ └── DEVICE：来自采集设备的文件。 ├── METADATA：存储本次任务通用信息文件的文件夹。 ├── PROCESSED_DATA：用于存储当前任务数据处理结果的所有相关子文件夹。 │ ├── CPCE_ANNOTATION：使用CPCe标注软件生成的所有CPC格式标注文件。 │ ├── IA：存储图像识别预测结果的目标文件夹。 │ └── 摄影测量（Photogrammetry）：存储摄影测量重建模型的目标文件夹。 ### 软件说明 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代码。祝您使用SeatizenDOI数据集顺利！