/Drone-Surveillance-System

Primary LanguagePython

Drone Surveillance System

Overview

This project uses YOLOv8 for real-time object detection from various video sources (webcam, local files, YouTube) with a PyQt5-based GUI. Detected objects are annotated on the video stream.

Features

  • Multiple Video Sources: Webcam, local video files, YouTube.
  • Real-Time Object Detection: Powered by YOLOv8.
  • User-Friendly GUI: Built with PyQt5.
  • Error Handling: Displays and logs errors related to video sources and model processing.

Requirements

  • Python 3.x
  • opencv-python, PyQt5, numpy, yt-dlp, ultralytics

Installation

  1. Clone the repository:

    git clone https://github.com/shahinur-alam/Drone-Surveillance-System.git
cd Drone-Surveillance-System

  2. Install dependencies:

    pip install -r requirements.txt

  3. Download the YOLOv8 model (yolov8n.pt) if necessary.

How to Run

  1. Run the application:

    python drone_surveillance.py

  2. Select a video source (Camera, Video File, or YouTube URL).

  3. Click Start to begin and Stop to end the video feed.

Key Components

  • YOLO Model: YOLOv8 is loaded for object detection.
  • Video Source: Select from webcam, local files, or YouTube URLs.
  • Real-Time Annotations: Detected objects are displayed on the video feed.
  • Error Handling: Errors are displayed and logged.

Future Improvements

  • Support for custom YOLO models.
  • Option to save video with annotations.
  • More robust YouTube stream handling.