Dataset of Stagnant Water and Wet Surface with Annotations
Published: 8 December 2021| Version 4 | DOI: 10.17632/y6zyrnxbfm.4
Contributors:
Kailas Patil, Sonali BhutadDescription
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.
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Categories
Computer Vision, Object Detection, Object Recognition, Machine Learning, Convolutional Neural Network, Deep Learning