🛰️ Semi-Autonomous Drone Control with YOLO-Based Object Tracking

This project enables semi-autonomous person tracking for drones using a pretrained YOLO object detection model. The system detects and tracks a person in real time, dynamically adjusting the drone's position to follow the target while allowing manual override for safety and control.

🚀 Features

• 🎯 Real-time person detection using YOLOv5 or YOLOv8
• 🕹️ Semi-autonomous flight control logic (follow mode with manual override)
• 📡 Integration with drone SDKs (e.g., DJI Tello, MAVSDK)
• 🧠 Modular and customizable object tracking and control loop
• 🧩 Extendable for other object classes or autonomous behaviors

🛠️ Requirements

• Python 3.8+
• PyTorch (for YOLO model)
• OpenCV
• NumPy
• Drone SDK (djitellopy, mavsdk, or other)
• Optionally: pynput, matplotlib for visualization/debugging

Install dependencies:

pip install -r requirements.txt