The ANPR-Civil-Military system is a specialized solution for Automatic Number Plate Recognition (ANPR) designed for civil and Indian military applications. This project leverages advanced computer vision and deep learning technologies to detect, extract, and store text from license plates, including military unit numbers, with high accuracy.
- YOLO Models: Utilizes YOLOv8, YOLOv9 and YOLOv11 variants for efficient plate detection.
- PaddleOCR Integration: Extracts textual data from license plates with precision.
- Real-Time Video and Image Processing: Works seamlessly on both videos and static images.
- Custom Military Detection: Enhanced recognition for Indian military-specific number plates and unit markings.
- Confidential Data Handling: Secure storage and processing for sensitive information.
📂 ANPR-Civil-Military
├── YOLOV11m/ # YOLOv11 model files
├── Yolov8n_OCR/ # YOLOv8 model optimized for OCR
├── test_images/ # Sample test images
├── test_videos/ # Sample test videos
├── image_inference.py # Script for image processing
├── nplate_inference_video.py # Script for video processing
├── PaddleOCR.py # PaddleOCR integration
├── LICENSE.md # License details
├── README.md # Project documentation
└── requirements.txt # Dependency list
This project is licensed under the Military ANPR System License (MASL) v1.0. See the LICENSE.md file for details.
Contributions to this project are not currently accepted due to its military-specific nature. For any suggestions or inquiries, please contact the repository owner.
- Ultralytics for YOLO models.
- PaddleOCR for OCR integration.
- Special thanks to contributors of the open-source computer vision community.