Tail Light Detection Dataset

In the current industrial landscape, the proper installation and functionality of tail lights are critical for vehicle safety. However, misinstallation often leads to accidents and maintenance issues. Existing solutions such as manual inspections are time-consuming and prone to human error. This dataset aims to address the pressing need for automated tail light misinstallation detection systems by providing labeled images that can be used to train machine learning models. The data is collected using high-resolution cameras in controlled lighting conditions to ensure clarity and consistency. Quality control measures include multi-round annotations and expert reviews to maintain high standards. The dataset is organized in a JPG format, with images stored in designated folders according to their labels.