Traffic Signal Light Status Recognition Dataset

With the continuous development of urban traffic, the management and recognition of traffic signal lights have become significant challenges in the field of transportation. Existing signal light recognition systems lack accuracy and real-time performance in complex environments, leading to inefficient traffic flow and frequent accidents. This dataset aims to provide extensive traffic signal light status data to help researchers and developers train more efficient object detection models. The dataset includes traffic signal light images collected from different cities and weather conditions, with multiple rounds of annotation and expert review to ensure the accuracy and consistency of the annotations. The data is stored in JPG format, organized by time and location for easy use and analysis. The core advantage of the dataset is high-quality annotations and diverse scene coverage, with annotation accuracy exceeding 95%. It outperforms existing datasets under complex lighting and weather conditions, enhancing the accuracy and robustness of object detection models, and meeting the practical needs of intelligent traffic and autonomous driving.