Visual LED Status Dataset for Machine Learning Applications
Visual LED Status Dataset is a collection of high-quality images of LEDs captured in different environments and under various lighting conditions. The dataset includes images of normal LEDs, bike and car lights, signal lights, and LEDs of different colors. The images were captured using a high-end resolution camera to ensure high-quality images suitable for machine learning applications. The dataset is divided into five sub-folders containing images of normal LEDs, coloured LEDs, bike lights, car lights and signal lights labelled accordingly. The purpose of this dataset is to develop an image classification model that can accurately determine whether an LED is on or off based on its visual appearance. It is designed to support the development of machine learning models for LED status classification and recognition. The dataset can be used for training, testing, and validation of machine learning models, as well as for research and educational purposes. The proposed dataset provides a valuable resource for industries that use LED technology, particularly in quality control and manufacturing settings. The dataset could be used to develop automated inspection systems for vehicles, electronic devices, or other products that incorporate LEDs. Overall, the LED Status Classification Dataset can be used to improve quality control and efficiency in various industries that use LED technology.