Overview
The Watcher is a cutting-edge AI surveillance system that leverages deep learning to process real-time CCTV footage. Using a sophisticated combination of CLIP model and custom neural networks, it detects potentially dangerous situations including violence, crimes, and accidents. The system provides immediate alerts to authorities, creating a proactive approach to public safety and emergency response.
Technologies Used
PyTorchTensorFlowCLIP ModelOpenCVPythonReactStreamlitFlaskFastAPIBunJS
Key Features
- Real-time video processing with advanced anomaly detection
- Multi-model architecture combining CLIP and custom neural networks
- Automated alert system with priority-based notification
- Support for multiple event types including accidents, fights, and vandalism
- Continuous CCTV monitoring with minimal latency
- Distributed processing capabilities for multiple video streams
Key Highlights
- 1Custom-trained models for specific threat detection
- 2Real-time processing capability of 30+ FPS
- 3Scalable architecture supporting multiple CCTV feeds
- 4Low false-positive rate through ensemble learning
Challenges Overcome
- Optimizing real-time video processing while maintaining accuracy
- Balancing computational resources across multiple streams
- Implementing efficient alert prioritization system
- Managing high-volume data processing in real-time
Documentation
Setup
Comprehensive setup guide including model initialization
API Reference
RESTful API documentation for system integration
Usage
Detailed usage scenarios and best practices
Future Development
- Cloud infrastructure integration for scalable deployment
- Remote system access through secure cloud endpoints
- Real-time cloud processing for large-scale surveillance
- Latency optimization for live video analysis
- Edge computing integration for improved performance
Multi-tier architecture with dedicated processing units for video input, analysis, and alert generation
Ensemble of CLIP model and custom CNNs for comprehensive threat detection
Capable of processing multiple video streams with sub-second latency