This is a license plate recognition application based on PySide6 and deep learning models. The application can recognize license plates through images, videos, or real-time camera input and display the recognition results.
- Image Recognition: Users can upload an image containing a license plate, and the system will display the recognized license plate number.
- Video Recognition: Users can upload a video file, and the system will analyze and recognize the license plates frame by frame.
- Real-time Recognition: Users can turn on the camera, and the system will recognize and display license plate numbers in real-time.
- Data Logging: Recognition results can be logged and saved to a CSV file.
- User Management: Supports user registration, login, and auto-login functionality.
- Python: Primary programming language.
- PySide6: Used for building the graphical user interface.
- OpenCV: Handles video and image files.
- YOLOv5: License plate detection.
- LPRNet: License plate character recognition.
- Clone the repository '''git clone https://github.com/Luchanaaaaa/PlateDetect-QT-YOLOv5-LPRNe.git'''
- Install dependencies: ''' pip install -r requirements.txt '''
- Run the application: ''' python main.py '''
- Upon starting the application, users need to register or log in first.
- After logging in, choose the recognition mode (Image, Video, Real-time).
- For images and videos, upload the files using the file dialog.
- Real-time recognition will automatically enable the camera.
- Recognition results will be displayed on the main interface, with an option to save the results.
main.py: Entry point file for the application.LogInPage_UI.py,SignUpPage_UI.py,SelectPage_UI.py,RecognitionWindow_UI.py: Layout files for each interface.OperationDB.py: Handles database operations for user data.myYOLODetector.py,myLPRNeDetector.py: Implementation of license plate detection and recognition.utils/: Contains auxiliary functions such as plotting.
Thank you for using this application! Looking forward to your feedback and suggestions!