This is a deep learning based fire detection system that is able to detect fire in real-time using a webcam or video feed. The system uses a convolutional neural network (CNN) trained on a dataset of images of fire and non-fire to detect fire in live video.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
You will need to have Python3 and the following libraries installed on your machine:
Tensorflow
Keras
OpenCV
Numpy
PIL
Tkinter
Clone the repository to your local machine
Change directory into the cloned repository
Install the required libraries
The model in Fire and Smoke Detetction.ipynb you can discover or change something you can get yours or just use the .h5 where the model already trained
if you wanna understand more go to :
https://machinelearningprojects.net/fire-and-smoke-detection/
To run the model, navigate to the root of the cloned repository and run Interface.py
You will get :
Click start detect
This will start the webcam and begin detecting fire in the video feed. The model will output the percentage of fire detection in the image
