Flood Amateur Video for Semantic Segmentation Dataset

This dataset is flood data in the city of Parepare, South Sulawesi Province, which contains video data collected from social media Instagram. This dataset was created to develop deep learning methods for recognizing floods and surrounding objects, specializing in semantic segmentation methods. This dataset consists of three folders, namely raw video data collected from Instagram, image data resulting from splitting the video into several images, and annotation data containing images that have been color-labeled according to their objects. There are 6 object classifications based on color labels, namely: floods (blue light), buildings (red), plants (green), people (sage), vehicles (orange), and sky (dark blue). This dataset has data in image (JPEG/PNG) and video (MP4) formats. This dataset is suitable for object recognition tasks with the semantic segmentation method. In addition, because this dataset contains original data in the form of videos and images, it can be developed for other purposes in the future. As a note, if you intend to use this dataset, please ensure that you comply with applicable copyright, privacy, and regulatory requirements. If you intend to read the paper about this dataset, please visit this link: https://doi.org/10.1016/j.dib.2023.109768

本数据集为南苏拉威西省帕雷帕雷市的洪涝相关数据集，包含从社交媒体平台Instagram采集的视频数据。本数据集旨在开发用于识别洪涝及周边物体的深度学习方法，尤其聚焦语义分割（semantic segmentation）技术。本数据集包含三个文件夹，分别为从Instagram采集的原始视频数据、将视频拆解为多帧后得到的图像数据，以及按物体类别完成色彩标注的标注图像数据。本次标注共设置6类物体类别，对应色彩标签如下：洪涝（浅蓝色）、建筑物（红色）、植被（绿色）、行人（苍绿色）、交通工具（橙色）、天空（深蓝色）。本数据集涵盖图像（JPEG/PNG格式）与视频（MP4格式）两类数据。本数据集适用于基于语义分割方法的物体识别任务。此外，由于本数据集包含原始视频与图像数据，未来可拓展至其他应用场景。请注意，若您计划使用本数据集，请确保遵守相关版权、隐私及监管合规要求。若您希望查阅本数据集的相关研究论文，请访问以下链接：https://doi.org/10.1016/j.dib.2023.109768