This paper presents an effective method for object detection in YOLOv7 (You Only Look Once version 7) for number plate recognition. The process entails precisely localising number plates and identifying automobiles in photos. With the help of transfer learning, YOLOv7 is trained on a unique dataset featuring a variety of number plate types and lighting situations. The system, which has been tested in difficult situations like occluded plates and complicated backgrounds, combines high accuracy with real-time processing. This methodical approach improves automatic vehicle identification systems, which in turn helps with parking management, law enforcement, and traffic monitoring, all of which lead to increased road safety and security.