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RoboVAI OCR 🚗🆔👤

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PyPI Version Python Version License Build Status

RoboVAI OCR is a high-performance, enterprise-grade Computer Vision and OCR framework built for Automatic License Plate Recognition (ALPR), National ID Card Parsing, and Driver Facial Verification.

Designed for seamless deployment in Smart Parking Systems, Barrier Gate Controls, Fleet Management, and Access Security, RoboVAI OCR provides an intuitive Python SDK, a high-throughput Async Pipeline, and a production-ready FastAPI REST & WebSocket Server.


🖥️ Live Control Center Dashboard

RoboVAI OCR National ID Dashboard Preview RoboVAI OCR ALPR Dashboard Preview

RoboVAI OCR Gate Control Dashboard RoboVAI OCR Face Match Preview


🔥 Key Capabilities (v3.0 SOTA Enterprise)

  • ALPR 3.0 Ultra: Multi-country plate recognition (Egyptian, Gulf/GCC: KSA 🇸🇦, UAE 🇦🇪, Kuwait 🇰🇼, and International), 4-point perspective dewarping, multi-plate simultaneous detection.
  • National ID Front/Back & Driving License OCR: Complete 14-digit mathematical decoding (DOB, Governorate, Gender), Full Name, Address, Job/Profession, Marital Status, Religion, Issue/Expiry Dates, Serial Numbers, and Driving License grades.
  • Biometric Face Recognition & Anti-Spoofing: 512D deep feature vectors, Cosine Similarity matching, FFT Moiré screen detection + LBP texture anti-spoofing, and DNN Age/Gender demographics.
  • Smart Parking Operating System (SPOS): Real-time 16-slot multi-zone occupancy grid, automated barrier decision logic, dynamic tariff billing (grace periods, hourly tiers, emergency waivers), and digital passes with cryptographic QR codes.
  • HSE Industrial Safety Command Center: PPE Compliance detection (Safety Helmet, Reflective Vest, Gloves, Goggles, Boots), Restricted Danger Zone polygon geofencing with intrusion sirens, and Fire/Smoke AI hazard detection.
  • Developer First: Comprehensive Python SDK, interactive Web Dashboard, CLI tools, OpenAPI docs, and Webhooks for automated barrier & industrial alert dispatch.

⚡ Quick Start

Installation

Install the latest release directly from PyPI:

pip install --upgrade robovai-ocr

Or install from source for development:

git clone https://github.com/m0shaban/robovai_ocr_system.git
cd robovai_ocr_system
pip install -e .

💻 Developer Guide & Usage Examples

1. Python SDK Integration

from robovai_ocr import RoboVAIEngine

# Initialize engine (auto-detects CPU/GPU)
engine = RoboVAIEngine()

# --- License Plate Recognition ---
plate_res = engine.read_license_plate("car.jpg")
print(plate_res["plate_number"])  # e.g. "س ط أ 1 2 3"
print(plate_res["confidence"])    # e.g. 0.96

# --- Egyptian National ID Extraction ---
id_res = engine.extract_national_id("national_id.jpg")
print(id_res["national_id"])     # e.g. "29901010100123"
print(id_res["full_name"])       # e.g. "أحمد محمد علي"
print(id_res["governorate"])     # e.g. "Cairo"

# --- Driver Face Verification ---
face_res = engine.verify_driver_face("driver.jpg", db_path="data/driver_faces")
print(face_res["match"])         # True / False

2. High-Throughput Async Pipeline

import asyncio
from robovai_ocr.core.pipeline import AsyncOCRPipeline

async def main():
    pipeline = AsyncOCRPipeline()
    await pipeline.start()
    
    # Submit frame for non-blocking processing
    job_id = await pipeline.submit_frame(frame_bytes)
    result = await pipeline.get_result(job_id)
    print(result)

asyncio.run(main())

3. Command Line Interface (CLI)

# Run ALPR on single image
robovai-cli alpr --image path/to/car.jpg

# Extract National ID fields
robovai-cli idcard --image path/to/id.jpg

# Start REST API & Web Control Dashboard
robovai-server --host 0.0.0.0 --port 8500

📡 REST API & WebSockets

Deploy as a standalone microservice:

robovai-server --port 8500
Endpoint Method Description
/api/v1/alpr POST Process license plate image with OCR & bounding box visualization
/api/v1/id-card POST Extract structured fields from National ID / Driver License
/api/v1/face POST Match driver face photo against registered driver database
/api/v1/pipeline POST Asynchronous background processing queue
/ws/stream WebSocket Real-time RTSP/Webcam video stream processing

🛠️ Architecture Overview

                               +-----------------------------+
                               |     RTSP Stream / Image     |
                               +--------------+--------------+
                                              |
                                              v
                               +--------------+--------------+
                               |    RoboVAI OCR Engine SDK   |
                               +--------------+--------------+
                                              |
            +---------------------------------+---------------------------------+
            |                                 |                                 |
            v                                 v
   +--------+--------+               +--------+--------+               +--------+--------+
   |   ALPREngine    |               |    IDEngine     |               |   FaceEngine    |
   | (YOLO + EasyOCR)|               | (3x YOLO Models)|               | (Face Match DB) |
   +--------+--------+               +--------+--------+               +--------+--------+
            |                                 |                                 |
            +---------------------------------+---------------------------------+
                                              |
                                              v
                               +--------------+--------------+
                               | FastAPI REST & WebSockets   |
                               +--------------+--------------+
                                              |
                                              v
                               +--------------+--------------+
                               | Smart Barrier Gate / Webhook|
                               +-----------------------------+

🤝 Contributing

We welcome contributions from the open-source community! Whether you are fixing bugs, improving docs, or proposing new features:

  1. Fork the Repository on GitHub.
  2. Create a Feature Branch: git checkout -b feature/amazing-feature
  3. Commit Your Changes: git commit -m 'Add amazing feature'
  4. Push to Branch: git push origin feature/amazing-feature
  5. Open a Pull Request.

📜 License

This project is licensed under the MIT License.


👤 Author & Connect

Developed by Mohamed Shaban (محمد شعبان العتماني) — Founder & AI Architect at RoboVAI.

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