Underwater images collected by an Underwater Vision Census in Toliara, Madagascar - 2021-03-11

This dataset was collected by an Underwater Vision Census in Toliara, Madagascar - 2021-03-11.

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: Not enough information in metadata to get camera information.

Number of images: 185

Total size: 0.01 Gb

Mission start: 2021:03:11 05:13:10

Mission end: 2021:03:11 05:42:38

Mission duration: 0h 29min 28sec

Total distance: 976 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3月11日在马达加斯加图利亚拉（Toliara）开展的水下视觉普查采集。

科学家或公众采集的水下与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，用于训练人工智能模型，进而实现影像内目标的自动识别。本套件提供一套软硬件工具，可用于海洋数据采集、物种/生境识别以及地图生成。

调查信息

相机：元数据中未提供足够信息以获取相机参数。
影像总数：185张
总数据量：0.01吉字节（Gb）
任务开始时间：2021年3月11日 05:13:10
任务结束时间：2021年3月11日 05:42:38
任务时长：0小时29分28秒
总行进距离：976米

GPS定位信息：
本次调查于小潮低潮时段在水深不足20米的珊瑚礁区域开展。一台置于水面漂浮防水袋内的GPS设备，沿潜水员行进路径每2秒记录一次定位坐标。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GPS定位袋。借助影像元数据内嵌的时间戳，通过时间同步算法将GPS定位数据插值至每张影像，以获取其拍摄位置。影像采集方法的详细细节可参阅本论文。

通用文件夹结构
YYYYMMDD_国家代码-可选地点_设备_会话-编号
├── DCIM：用于存储采集所得的视频与照片文件，具体内容取决于采集的媒体类型。
├── GPS：用于存储所有与定位相关的文件。若可对文件进行各类校正（例如基于RINEX数据的后处理运动学校正），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格式文件），则无需区分基准与设备数据，直接将文件置于GPS文件夹根目录下。
│ ├── BASE：存储来自RTK基站或其他静态定位仪器的文件。
│ └── DEVICE：存储来自采集设备的定位文件。
├── METADATA：用于存储本次任务的通用信息文件。
├── PROCESSED_DATA：用于存储本次任务数据处理后的各类结果文件。
│ ├── CPCE_ANNOTATION：存储使用CPCe软件生成的所有CPC格式标注文件。
│ ├── IA：用于存储图像识别模型的预测结果。
│ └── PHOTOGRAMMETRY：用于存储摄影测量重建所得的三维模型文件。

软件工具
所有原始数据均通过本团队的工作流完成处理。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工具顺利开展研究！