Dataset of Stagnant Water and Wet Surface with Annotations

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

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.

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Categories

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

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