Vehicle-Number-Plate-Detection-using-OpenCV

Automatic-Number-Plate-Detection Project helps to Find and allow the Only register Vehicles inside your Campus or Your Private Place.

Working:

This Python project employs OpenCV and Haarcascade for automatic number plate detection. Initially, vehicle registration is facilitated through a registration page, storing pertinent information in MongoDB. Subsequently, a live stream monitoring page displays real-time vehicle license plate detections. Each detection triggers a comparison with the database; if a match is found, access is granted; otherwise, a beep alarm is activated.

OpenCV serves as the cornerstone for computer vision tasks, enabling image, video, and object detection. Haarcascade, a pre-trained algorithm within OpenCV, specializes in identifying number plates on vehicles. Following detection,

EasyOCR steps in, utilizing a deep learning model to accurately extract alphanumeric characters from the license plate image.

MongoDB serves as the repository for all vehicle information, ensuring efficient data management and retrieval throughout the system's operation.

=>Pre-Install Softwares:

1. Python 3.12
2. cmake
3. vscode
4. node
5. MongoDB

=>Installation Steps:

Open command Prompt. (windows)

1. create virtualenv

command: virtualenv numberplate_detection

2. Activate virtualenv

command: numberplate_detection\Scripts\Activate

3. Install Requerements

command: pip install -r requerements.txt

4. Run python script

command: python main.py

=> It Will start the backend API.

Start Frontend:

1. open code in vscode
2. npm i
3. npm start

=> It will start the frontend

Any Doubts: Reach Me: narayananhm123@gmail.com