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![Project Header](/figures/project_header.png)
# Fire Detection
Project for the `AI Lab: Computer Vision and NLP` course.
## Abstract
Our aim is to use videocamera to detect fire, improving range respect to thermal and smoke based detectors
Forest fires represent an important threat to natural ecosystems. Early
detection is essential to prevent extensive damage and reduce risks associated with them. Conventional
fire detection systems primarily rely on smoke or temperature-based sensors. These approaches have inherent limitations that restrict their effectiveness,
particularly in outdoor environments and forested areas.
Our approach attempts to combine the feed obtained from traditional video or surveillance cameras with
a motion detection algorithm and a model to predict forest fires in real-time. This approach is
more cost-effective and requires less human intervention than other methods.
## Implementation
We use a Motion Detection Algorithm that uses a **background subtraction** method with **recursive updates** of thresholds and estimated backgrounds.
![Motion Detection Algorithm](/figures/motion_detection_algorithm.png)
The used model is an XGBoost model pre-trained on labeled image datasets containing fire and non-fire images. A histogram was computed for the color channels to differentiate without using the entire images.
![Model Training](/figures/model_training.png)
## Installation
First, create a `conda` environment using:
```sh
conda create --name FireDetection --file requirements.txt
```
Activate the environment using:
```sh
conda activate FireDetection
```
## Usage
The file `main.py` in the `src` directory contains a simple interface for using the program.
To execute, use:
```sh
python ./src/main.py
```
To change the video that is being used for detection, replace the `video_path` value in line 18 of `main.py` with the path to your target video.
Additionally, the algorithm can be tested with a live feed from http://66.119.104.155/mjpg/video.mjpg.
The example video was sourced from: [Fire: Fountaingrove in Santa Rosa (Monday, Oct. 9)](https://www.youtube.com/watch?v=TR-9IdfqaKY)
## Authors
:link: [Alessio Olivieri](https://github.com/Lexyo14)
:link: [Robert Li](https://github.com/mediolanum1)
:link: [Emilio Soriano Chávez](https://github.com/ami-sc)

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