نظام ذكي لرصد الدخول والخروج باستخدام تتبع الرؤوس

Real-Time Head-Based Entry-Exit Detection

This project implements a real-time entry and exit monitoring system using YOLO object detection and tracking. It detects human heads and accurately counts people entering or exiting a defined area by tracking their movement across a virtual line, with full event logging and visual feedback.

Project Overview

This intelligent surveillance solution leverages YOLO with object tracking to monitor people crossing a predefined horizontal line. By maintaining persistent tracking IDs across frames, the system reliably determines entry and exit events. Each crossing is logged with a timestamp and person ID, making the solution ideal for audits, access control, and analytics.

Key Features

Real-Time Head Detection

• 🧠 Uses YOLO for accurate and efficient human head detection.
• ⚡ Optimized for real-time performance in dynamic environments.

Entry / Exit Counting

• 📏 Detects movement across a virtual horizontal line.
• 🚪 Classifies each crossing as Entry or Exit.

Persistent ID Tracking

• 🆔 Assigns a unique ID to each tracked person.
• 🔁 Maintains identity consistency across video frames.

Event Logging & Visualization

• 🧾 Logs entry/exit events with timestamps into a CSV file.
• 📊 Displays FPS, counters, bounding boxes, head labels, and movement direction.
• 🎥 Supports live camera feeds and recorded video files.

Technology Stack

• 🐍 Programming Language: Python
• 🎥 Computer Vision: OpenCV
• 🧠 Object Detection & Tracking: YOLO (Ultralytics)
• 📊 Data Logging: Pandas (CSV-based logging)

Use Cases

• 🏭 Factory & Workplace Monitoring – Track worker entry and exit.
• 🎓 Campus & Classroom Logging – Monitor student movement.
• 🏬 Retail Analytics – Measure customer inflow and outflow.
• 🔒 Secure Facilities – Log personnel movement in restricted areas.
• 🚦 Event Management – Analyze crowd flow and congestion.

Conclusion

This project delivers a powerful yet lightweight solution for real-time entry and exit monitoring using computer vision. With accurate head-based detection, reliable tracking, detailed logging, and clear visualization, it is well-suited for access control, footfall analytics, and smart surveillance systems. The modular design allows easy extension with dashboards, alerts, and multi-camera support.