Overview
An advanced AI-powered video processing system designed for real-time video analysis and intelligent imaging. I re-engineered the core APIs and implemented cutting-edge computer vision capabilities, significantly reducing processing time while maintaining high accuracy across multiple video feeds.
The system performs face detection, object recognition, and intelligent video analytics. It's designed to handle multiple concurrent video feeds with minimal latency, making it suitable for security, surveillance, and monitoring applications.
Key Features
- Optimized Processing Pipeline: Re-engineered APIs reducing video and AI imaging processing time by 50%
- Multi-stream Support: Concurrent processing of multiple video feeds with efficient resource management
- Intelligent Analytics: Real-time insights and alerts based on video content analysis
- Scalable Architecture: Designed to handle increasing video loads and processing requirements
Technical Details
Role
Backend Engineer
Company
Zummit Infolabs
Type
AI/ML System
Technology Stack
Python
OpenCV
TensorFlow
PyTorch
Django
FastAPI
Key Achievements
- Reduced video and AI imaging processing time by 50% through API optimization
- Achieved 95% accuracy in face detection across 14+ simultaneous video feeds