AI-Based Number Plate Recognition Engine

Project Title:
Develop ANPR / ALPR Engine for Qatar and GCC Number Plates

Project Description:
We are looking for an experienced AI/computer vision developer or team to develop a custom ANPR/ALPR engine for Qatar and GCC vehicle number plates.

The engine must detect and recognize vehicle license plates from live CCTV/video streams and still images. It should support Qatar plates as the primary requirement, with future support for other GCC countries such as UAE, Saudi Arabia, Oman, Bahrain, and Kuwait.

Required Scope:

1. License plate detection from images and video streams
2. OCR/recognition of Qatar number plates
3. Support for Arabic and English plate characters where applicable
4. Handling different plate types, colors, sizes, and formats
5. Vehicle image capture with plate crop
6. Confidence score for each recognition result
7. API output in JSON format
8. Ability to process RTSP camera streams
9. Basic dashboard or test UI for demo and verification
10. Deployment on Windows or Linux server
11. Documentation for installation, API usage, and model retraining

Expected Output Example:

{
"plateNumber": "123456",
"country": "Qatar",
"plateType": "Private",
"confidence": 0.94,
"timestamp": "2026-07-07T10:30:00",
"cameraId": "CAM-01",
"plateImage": "path/to/plate.jpg",
"vehicleImage": "path/to/vehicle.jpg"
}

Important Requirements:

* Developer must have previous experience in ANPR, OCR, object detection, OpenCV, YOLO, PaddleOCR, EasyOCR, TensorFlow, PyTorch, or similar technologies.
* The system should be trainable/improvable using our own Qatar/GCC plate dataset.
* Accuracy should be tested in day, night, low-light, angled, and moving vehicle conditions.
* The final solution should not depend on expensive third-party cloud APIs.
* Source code must be provided.
* We prefer a modular engine that can later be integrated with our VMS, video gateway, PSIM, or command center platform.

Deliverables:

1. Working ANPR engine
2. REST API
3. RTSP stream processing support
4. Test/demo dashboard
5. Installation guide
6. Source code
7. Training/retraining instructions
8. Accuracy test report

Please Apply With:

* Your previous ANPR/ALPR project examples
* Technology stack you recommend
* Estimated timeline
* Estimated cost
* Expected accuracy level
* Whether you can support Qatar/GCC plate formats specifically