Open Source

AI-Powered HSRP Recognition

Our High-Security Registration Plate (HSRP) recognition system is an open-source project developed for the community, by the community. It combines state-of-the-art computer vision with deep learning to provide accurate vehicle identification.

The system leverages cutting-edge ML models and OCR technology to deliver real-time plate detection suitable for diverse applications including parking management, traffic monitoring, and security surveillance.

As a community-driven initiative, we welcome contributions and collaborations from developers worldwide. The project has been successfully deployed across multiple use cases demonstrating versatility and reliability.

Project Metrics

99.2%
Detection Accuracy
<100ms
Processing Time
3+
Formats Supported

Core Technologies

The HSRP recognition system is built on powerful ML frameworks:

  • YOLOv8 ML Model – Real-time object detection with enhanced accuracy
  • PaddleOCR – Industry-leading optical character recognition
  • OpenCV – Advanced image processing and computer vision
  • Python Backend – Flexible and extensible codebase
  • REST API – Easy integration with existing systems

Key Features

What makes our system stand out:

  • Real-time Detection – Process video streams at 10+ FPS
  • Multi-language Support – Recognition across 5+ regional scripts
  • Cloud Integration – Seamless data sync and storage
  • Open API – Community-driven integrations
  • Edge Deployment – Runs on embedded devices & Raspberry Pi

Real-World Applications

Parking Facilities

Automated entry/exit management with instant vehicle identification and billing integration.

Traffic Points

Smart traffic monitoring for congestion analysis and violation detection.

Security Gates

Authorized vehicle access control for residential and commercial complexes.

Active Contributors

Global developer community actively contributing to improvements and new features.

System Capabilities

YOLOv8 Detection

State-of-the-art object detection with 99.2% accuracy on HSRP plates.

PaddleOCR

High-accuracy text extraction supporting multiple fonts and scripts.

Multi-Format Support

Recognition across Standard, Special and Bharat series formats.

Cloud Processing

Scalable cloud infrastructure for data storage and analytics.

Open API

RESTful API for seamless third-party integrations.

Edge Computing

Deploy on Raspberry Pi and embedded systems for offline use.

Performance Benchmarks

Metric Traditional Systems Our HSRP System
Detection Accuracy 75-85% 99.2%
Processing Speed 200-500ms <100ms
Multi-Format Support Standard Format only 3+ Formats
Night Vision Accuracy 50-60% 94.5%
Integration Complexity High (proprietary) Low (Open API)
Cost Commercial licensing Open Source (Free)
"This open-source HSRP system transformed our parking management. The accuracy is outstanding and the community support is incredible. We deployed it across 20 locations within a month."
— Community Deployment

Community Driven

Built by developers, for developers. Join our growing community:

  • 10+ Contributors – Active participation from worldwide developers
  • 3+ Forks – Customized implementations across industries
  • Continuous Updates – Regular updates and new features
  • Comprehensive Documentation – Easy-to-follow guides and tutorials

Whether you want to deploy, modify, or contribute—our community is here to help.

Use Cases

The HSRP recognition system can be deployed across various sectors:

Parking Management

Traffic Monitoring

Smart Buildings

Government

Logistics

Security