https://github.com/salim4n/fire_detection

Entrainement sur YOLOV8 pour qu'il puisse detecter du feu
https://github.com/salim4n/fire_detection

Last synced: 5 days ago
JSON representation

Entrainement sur YOLOV8 pour qu'il puisse detecter du feu

• Host: GitHub
• URL: https://github.com/salim4n/fire_detection
• Owner: salim4n
• Created: 2023-08-16T20:57:12.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-16T22:14:53.000Z (over 1 year ago)
• Last Synced: 2023-08-16T22:24:39.055Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 7.44 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Fire Detection using YOLOv8

[Fire Detection]

This repository contains an implementation of YOLOv8 trained to detect fire. The YOLO (You Only Look Once) algorithm is a real-time object detection system.

## Getting Started

1. **Clone the Repository**: Clone this repository to your local machine using `git clone https://github.com/salim4n/Fire_Detection.git`.

2. **Install Python**: Make sure you have Python installed on your computer.

3. **Run the Code**: Open a terminal/command prompt, navigate to the cloned repository, and run the command `python main.py` to start the fire detection application.

## Demo

Check out this demo video to see the fire detection in action:

[Watch the Demo Video](https://youtube.com/shorts/RobJMNTdx6E?feature=share)

## Usage

- The `main.py` script processes a video stream in real-time, detecting fire using the trained YOLOv8 model.

- Use the webcam or provide a video file as input for detection.

- Detected fires are highlighted in the video with bounding boxes.

- Feel free to experiment with different video sources and scenarios.

## License

This project is licensed under the [MIT License](LICENSE).