Real-Time Threat Detection using YOLOv8

This project implements a real-time threat detection system using YOLOv8 (You Only Look Once) for object detection. The system uses a webcam feed to monitor for suspicious objects, and it triggers an alert when a suspicious object, such as a "knife," is detected. The system employs Python, OpenCV, and the Ultralytics YOLO model to detect objects and track activities in real-time.

Features

• Real-Time Monitoring: Continuously captures video from the webcam.
• Object Detection: Utilizes YOLOv8 to detect objects from a list of predefined classes.
• Suspicious Activity Detection: Alerts when a suspicious object (e.g., "knife") is detected, triggering an immediate exit of the program.
• Bounding Boxes: Displays bounding boxes around detected objects with class labels and confidence scores.

Requirements

• Python 3.x
• OpenCV
• Ultralytics YOLOv8 Model

Example Output

Image