This project is an Automatic Number Plate Recognition (ANPR) system designed to recognize and process vehicle license plates. The system utilizes computer vision and machine learning techniques to detect and extract license plate information from images or video streams.
The ANPR system involves several key components :-
- License Plate Detection : This module uses object detection algorithms to identify and localize license plates within images or frames from a video stream.
- Character Segmentation : Once a license plate is detected, individual characters on the plate are segmented for recognition.
- Character Recognition : Utilizing Optical Character Recognition (OCR) techniques, the system identifies and interprets the segmented characters to extract the license plate information.
- Data Processing and Storage : Extracted license plate information is processed, and the data is stored for further use or analysis.
- License Plate Detection : Utilizes state-of-the-art object detection models to accurately locate license plates within images or video frames.
- Character Segmentation : Segments characters from the detected license plates for efficient recognition.
- Character Recognition : Employs OCR techniques to accurately recognize and extract characters from the license plates.
- Multi-format Support : Capable of handling various license plate formats and designs used in different regions or countries.
- Scalability and Performance : Designed to be scalable and capable of processing real-time video streams efficiently.
To use the ANPR system, follow these steps :
- Prepare the input data, images or video containing vehicles and license plates.
- Run the ANPR system using the provided scripts or interfaces.
- Access the processed data or integrate the system into your application.
1: git clone https://github.com/Piyush0102/Automatic-Number-Plate-Recognition
2: cd Automatic-Number-Plate-Recognition
3: pip install -r requirements.txt