Computer Vision
YOLOv11
Helmet Detection System
Advanced helmet detection in images and videos using YOLOv11 object detection with real-time safety monitoring capabilities
Advanced helmet detection in images and videos using YOLOv11 object detection with real-time safety monitoring capabilities
A sophisticated computer vision project that detects helmets in images and videos using the YOLOv11 object detection algorithm. This system is designed for workplace safety monitoring and compliance verification.
The project demonstrates advanced computer vision techniques with real-time detection capabilities, accuracy metrics visualization, and comprehensive evaluation using confusion matrices. Built with Python, OpenCV, and YOLOv11 for high-performance helmet detection in various scenarios.
Accuracy
Model Version
Detection
Compliance
Advanced YOLOv11 model achieving 95% accuracy in helmet detection across various scenarios
Fast detection and processing capabilities for live video streams and image analysis
Detailed metrics visualization including confusion matrices and accuracy graphs
Process both static images and dynamic video content with consistent accuracy
Advanced evaluation with confidence scores, detection labels, and statistical analysis
Streamlit web interface for easy deployment and user interaction
Load the pre-trained YOLOv11 model optimized for helmet detection tasks
Resize and preprocess input images or video frames for optimal detection
Pass frames through YOLOv11 model to detect and classify helmets
Generate annotated images with bounding boxes and confidence scores
Store results in CSV format with detection labels and metrics
Generate confusion matrices and accuracy graphs for evaluation
Core helmet detection functionality with image upload and real-time processing
Try DemoAdvanced version with helmet and license plate detection capabilities
Try Extended DemoMonitor construction sites and industrial areas for helmet compliance
Detect helmet usage among motorcyclists for safety enforcement
Monitor helmet usage in contact sports and recreational activities
Integrate with security cameras for automated safety monitoring