Bhutad Sonali, Patil Kailas
Vishwakarma University, Pune, India.
Data Brief. 2021 Dec 23;40:107752. doi: 10.1016/j.dib.2021.107752. eCollection 2022 Feb.
Clean water is one of the essential things in life. The running water in natural forms is considered as clean water. To avoid exposure to countless diseases, it is imperative to separate stagnant water from clean water. Thus the main objective of the proposed paper is to create an image dataset of stagnant water and wet surface to detect stagnant water. Accordingly, we considered stagnant water images in different forms and sizes to construct the dataset. In addition to that, brown and black earth surface is considered for the wet surface detection. The dataset consists of 1976 labeled images captured from various angles with annotated files. The dataset images are labelled for two classes, namely water and wet surface. This dataset is highly useful for deep learning experts working in the field of disease control management and post-rainfall earth surface monitoring.
清洁水是生活中必不可少的东西之一。自然形态的流动水被视为清洁水。为避免接触无数疾病，必须将积水与清洁水分离。因此，本文提出的主要目标是创建一个积水和潮湿表面的图像数据集，以检测积水。相应地，我们考虑了不同形式和大小的积水图像来构建数据集。除此之外，对于潮湿表面检测，考虑了棕色和黑色的地表。该数据集由1976张从不同角度拍摄的带注释文件的标记图像组成。数据集中的图像被标记为两个类别，即水和潮湿表面。该数据集对于在疾病控制管理和雨后地表监测领域工作的深度学习专家非常有用。
