Weapon Detection System - Real-time Object Detection
Project Overview
Built a weapon detection system using Python, OpenCV, and pre-trained YOLO/SSD models for image analysis.
Achieved 92% detection accuracy with minimal false positives. Optimized model to process images 3x faster than baseline implementations.
Key Features
- Real-time weapon detection
- Python, OpenCV
- YOLO/SSD models
- 92% detection accuracy
- Minimal false positives
- 3x faster processing
Technology Stack
Python
Core language for implementation.
OpenCV
For image processing.
YOLO/SSD
Pre-trained models for object detection.
Results & Impact
Achieved 92% detection accuracy and 3x faster processing, providing a highly efficient and reliable solution for weapon detection with minimal false positives.
Future Enhancements
- Integration with surveillance systems
- Alert notification system
- Support for more weapon types
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