Real-Time ANPR System using YOLOv8 & SORT: A cutting-edge solution for license plate detection & tracking, optimized for diverse conditions. Includes deep learning models, tracking algorithms, and OCR integration for effective vehicle identification.
Real-Time License Plate Detection: Employs YOLOv8 for high-accuracy detection. Efficient Tracking and OCR: Utilizes SORT for vehicle tracking and EasyOCR for character recognition. Adaptability: Optimized for various lighting and weather conditions.
git clone [repo-link]
cd [repo-directory]
pip install -r requirements.txt
The project uses YOLOv8, specifically the [nano/small/medium] variant, for license plate detection.
We used the "License Plate Recognition" dataset from Roboflow Universe, which includes diverse images of license plates in different settings. This dataset was instrumental in training the YOLO model to detect various license plate formats effectively.
Available: https://universe.roboflow.com/roboflow-universe-projects/license-plate-recognition-rxg4e/dataset/4
