Dataset of Stagnant Water and Wet Surface with Annotations

Published: 8 December 2021| Version 4 | DOI: 10.17632/y6zyrnxbfm.4
Kailas Patil, Sonali Bhutad


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 1976 images with annotations. The dataset consists of RGB labeled images (256 × 256 pixels) for two classes, namely water and wet surface. The images were taken from the top view and side view with varying daylight conditions. The rear camera of a mobile phone is used to capture images. The annotations are in the YOLO (You Only Look Once) format.



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