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![Project Header](/figures/project_header.png)
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# Fire Detection
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Project for the `AI Lab: Computer Vision and NLP` course.
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## Abstract
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Our aim is to use videocamera to detect fire, improving range respect to thermal and smoke based detectors
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Forest fires represent an important threat to natural ecosystems. Early
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detection is essential to prevent extensive damage and reduce risks associated with them. Conventional
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fire detection systems primarily rely on smoke or temperature-based sensors. These approaches have inherent limitations that restrict their effectiveness,
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particularly in outdoor environments and forested areas.
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Our approach attempts to combine the feed obtained from traditional video or surveillance cameras with
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a motion detection algorithm and a model to predict forest fires in real-time. This approach is
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more cost-effective and requires less human intervention than other methods.
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## Implementation
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We use a Motion Detection Algorithm that uses a **background subtraction** method with **recursive updates** of thresholds and estimated backgrounds.
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![Motion Detection Algorithm](/figures/motion_detection_algorithm.png)
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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.
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![Model Training](/figures/model_training.png)
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## Installation
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First, create a `conda` environment using:
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```sh
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conda create --name FireDetection --file requirements.txt
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```
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Activate the environment using:
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```sh
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conda activate FireDetection
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```
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## Usage
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The file `main.py` in the `src` directory contains a simple interface for using the program.
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To execute, use:
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```sh
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python ./src/main.py
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```
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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.
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Additionally, the algorithm can be tested with a live feed from http://66.119.104.155/mjpg/video.mjpg.
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The example video was sourced from: [Fire: Fountaingrove in Santa Rosa (Monday, Oct. 9)](https://www.youtube.com/watch?v=TR-9IdfqaKY)
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## Authors
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:link: [Alessio Olivieri](https://github.com/Lexyo14)
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:link: [Robert Li](https://github.com/mediolanum1)
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:link: [Emilio Soriano Chávez](https://github.com/ami-sc)
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