遇见数据集

Aerial images collected by an Unmanned Aerial Vehicle in St-Leu-Port, Réunion - 2024-04-07

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Zenodo2025-07-07 更新2026-05-26 收录
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This dataset was collected by an Unmanned Aerial Vehicle in St-Leu-Port, Réunion - 2024-04-07. 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. Survey information Camera: Hasselblad L1D-20c Number of images: 284 Total size: 2.55 Gb Flight start: 2024:04:07 04:45:07 Flight end: 2024:04:07 04:56:11 Flight duration: 0h 11min 4sec Median height: 59.9 m Area covered: 3.67 a Photogrammetry OpenDroneMap software was used to create an orthophoto from the raw images. Here is the list of parameters different from the default values for the orthophoto generation. For more details, you can read the log.json file or the 000_photogrammatry_report.pdf report. {'auto_boundary': True, 'cog': True, 'fast_orthophoto': True, 'feature_quality': 'ultra', 'max_concurrency': 128, 'optimize_disk_space': True, 'orthophoto_resolution': 1.0, 'rolling_shutter': True, 'skip_3dmodel': True, 'use_exif': True} 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!

本数据集由无人驾驶航空器(Unmanned Aerial Vehicle,UAV)于留尼旺圣勒港采集,采集日期为2024年4月7日。 科学家与民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领域。这些影像可经标注后共享,用于训练人工智能(Artificial Intelligence,AI)模型,以实现影像内目标的自动识别。我们提供一套包含硬件与软件的工具集,可用于海洋数据采集、物种/栖息地识别以及地图生成。 本数据集是收录大量水下与航空影像的大型数据集集合Seatizen Atlas(Seatizen图集)的一部分。相关方法、工具及科学目标已在专属数据集论文中详细阐述。 ### 采集信息 相机:哈苏L1D-20c(Hasselblad L1D-20c) 影像总数:284张 总大小:2.55吉字节(GB) 飞行开始时间:2024年4月7日 04:45:07 飞行结束时间:2024年4月7日 04:56:11 飞行时长:0小时11分4秒 平均飞行高度:59.9米 覆盖面积:3.67公亩 ### 摄影测量 本数据集采用OpenDroneMap软件对原始影像进行处理,生成正射影像(Orthophoto)。以下为正射影像生成过程中与默认参数存在差异的配置项: { "自动边界生成": true, "云优化GeoTIFF(Cloud Optimized GeoTIFF,COG)": true, "快速正射影像生成": true, "特征提取质量": "极高", "最大并发数": 128, "磁盘空间优化": true, "正射影像分辨率": 1.0, "卷帘快门补偿": true, "跳过三维模型生成": true, "使用EXIF信息": true } 如需了解更多细节,可查阅log.json文件或000_photogrammetry_report.pdf报告。 ### 通用文件夹结构 文件夹命名格式:YYYYMMDD_COUNTRYCODE-可选地点_设备_会话-编号 ├── DCIM:用于存储采集得到的视频与照片文件的目录。 ├── GPS:用于存储所有与定位相关文件的目录。若文件可进行校正(例如基于RINEX数据的后处理运动学校正),则需区分设备数据与基准站数据;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,文件直接存放于GPS目录根目录下。 │ ├── BASE:存储来自RTK基准站(Real-Time Kinematic Station)或静态定位仪器的文件。 │ └── DEVICE:存储来自采集设备的定位文件。 ├── METADATA:存储本次采集任务通用信息文件的目录。 ├── PROCESSED_DATA:用于存储本次采集任务数据处理结果的各级目录集合。 │ ├── BATHY:存储从任务日志中提取的水深原始数据的输出目录。 │ ├── FRAMES:存储从DCIM目录下视频中提取的地理配准帧的输出目录。 │ ├── 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:用于存储其他来源文件的目录,例如回声测深仪(Echosounder)获取的水深数据、自动驾驶仪日志文件、任务规划文件等。 ### 软件说明 所有原始数据均通过我们的标准化工作流进行处理,所有预测结果均由我们的推理管线生成。您可在本代码仓库中获取下载该数据集所需的全部脚本。祝您使用SeatizenDOI(Seatizen数字对象标识符)顺利!

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Zenodo
创建时间:
2025-07-07
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