🛸 Drone Detection and Tracking System
An AI-powered computer vision application built with Python, YOLO, OpenCV, Tkinter, and ByteTrack — delivering real-time drone detection, tracking, and speed analysis.
Whether using a live USB webcam, an IP/RTSP surveillance camera, or a prerecorded video, the system processes every frame in real time — combining deep learning with intelligent tracking through a simple, user-friendly interface built for researchers, developers, and security professionals.
🔍 Core Capabilities
AI-Powered Detection
YOLO analyzes every frame instantly, generating precise bounding boxes and confidence scores in real time.
Multi-Object Tracking
ByteTrack assigns each drone a persistent ID, tracking multiple drones even through overlaps.
Speed Estimation
Converts pixel movement into real-world speed (km/h) using configurable calibration.
Modern GUI
A Tkinter interface for camera selection, video loading, confidence tuning, and one-click control.
📊 Live Performance Dashboard
🎥 Supported Input Sources
External Camera
IP Camera
RTSP Stream
CCTV Feed
MP4 / AVI / MKV / MOV
🛠️ Technologies Used
YOLO (Ultralytics)
OpenCV
Tkinter
ByteTrack
Pillow (PIL)
NumPy
Multi-threading
🌍 Real-World Applications
🛡️ Border & Military Security
✈️ Airport & Airspace Protection
🏙️ Smart City Surveillance
🏭 Industrial Facility Monitoring
🔬 Research & Development
🚨 Critical Infrastructure Protection
✅ Project Highlights
🚀 Conclusion
The Drone Detection and Tracking System showcases the practical power of AI and computer vision in intelligent surveillance — combining real-time detection, tracking, and speed analysis into one complete, extensible monitoring solution ready for future upgrades like cloud monitoring and automated alerts.
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