License Plate Recognition System

This project is a License Plate Recognition system that utilizes a combination of computer vision and machine learning techniques to identify and process license plates from video footage.

Project Structure

The project is organized as follows:

• main.py: The main script that provides a GUI for uploading videos, processing them, and exporting the results.
• models/: Contains the pre-trained models for license plate detection and object detection.
  • license_plate_detector.pt: The model for detecting license plates.
  • yolov8n.pt: The YOLO model for object detection.
• sort/: Implements the SORT algorithm for object tracking.
  • sort.py: The main SORT algorithm implementation.
  • data/: Training data for the SORT algorithm.
• src/: Contains the core functionality for processing videos and license plates.
  • get_plates.py: Functions for extracting license plate data.
  • interpolate.py: Interpolation utilities for smoothing bounding box coordinates.
  • process.py: Core processing functions for video and license plate recognition.
  • util.py: Utility functions.
  • visualize.py: Functions for visualizing the results.

Setup

To set up the project, follow these steps:

1. Ensure Python 3.8 or higher is installed.
2. Install the required Python packages by running pip install -r requirements.txt.
3. Download the pre-trained models and place them in the models/ directory.

Usage

To use the system, run main.py and follow the GUI prompts:

1. Upload a video file.
2. Click "Process Video" to start the license plate recognition process.
3. Export the results to an Excel file or visualize the processed video.

Dependencies

• filterpy
• scikit-image
• pandas
• ultralytics
• easyocr
• scipy
• lap
• opencv-python

License

This project is licensed under the MIT License - see the LICENSE file for details.