Dataset of Stagnant Water and Wet Surface with Annotations

Published: 21 July 2021| Version 2 | DOI: 10.17632/y6zyrnxbfm.2


Stagnant Water detection is a very challenging task due to mudding or reflection of surrounding . Therefore, to increase the accuracy of stagnant water detection by avoiding misclassification; additional images of wet surface are added. With this objective, we have created a dataset of 2000 images with annotations. Out of 2000 ,25 images are rotated by 90 degrees. The dataset consists of 2000 (256 × 256 pixels) RGB labeled images for two classes, namely water and wet surface. The images were taken from top view and side view with varying day-light conditions. The images are captured using rear camera of mobile phone. The images are annotated in the YOLO (You Only Look Once) format.



Computer Vision, Object Detection, Object Recognition, Machine Learning, Convolutional Neural Network, Deep Learning