https://github.com/blacksujit/forest-fire-prediction

This project aims to predict the occurrence of forest fires using machine learning. The project includes a Flask-based application that serves both backend (for model training and prediction) and frontend Created using Threejs (for user interaction).
https://github.com/blacksujit/forest-fire-prediction

algorithms backend-api cool-projects fire-prediction forest forest-fire-detection frontend learning-by-doing machine machine-learning-algorithms python-project self-project self-project-idea

Last synced: 25 days ago
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This project aims to predict the occurrence of forest fires using machine learning. The project includes a Flask-based application that serves both backend (for model training and prediction) and frontend Created using Threejs (for user interaction).

• Host: GitHub
• URL: https://github.com/blacksujit/forest-fire-prediction
• Owner: Blacksujit
• Created: 2024-06-26T10:24:28.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-21T13:02:37.000Z (5 months ago)
• Last Synced: 2024-12-01T12:19:36.126Z (25 days ago)
• Topics: algorithms, backend-api, cool-projects, fire-prediction, forest, forest-fire-detection, frontend, learning-by-doing, machine, machine-learning-algorithms, python-project, self-project, self-project-idea
• Language: Python
• Homepage: https://forest-fire-prediction-of6q.onrender.com/
• Size: 946 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Forest Fire Prediction

This project aims to predict the occurrence of forest fires using machine learning. The project includes a Flask-based application that serves both backend (for model training and prediction) and frontend (for user interaction).

# Link For Project:

https://forest-fire-prediction-of6q.onrender.com/

# Web Page: (Created with ❤ using Threejs Models)

![alt text](image.png)

## Folder Structure

- `app.py`: Main application file combining both frontend and backend.

- `model/`: Contains the trained model and script to train the model.

- `requirements.txt`: Dependencies for the project.

- `static/`: Static files (CSS, JS).

- `templates/`: HTML templates.

- `data/`: Folder containing the dataset.

## DATASET  INFORMATION:

Download the dataset from [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Forest+Fires) and place the `forestfires.csv` file in the `data/` folder.

## Installation

1. Clone the repository:

     ```bash

     git clone https://github.com/Blacksujit/Forest_fire_Prediction.git

     ```

2. Install the dependencies:

    ```bash

    pip install -r requirements.txt

    ```

3. Run the application:

    ```bash

    python app.py

    ```

4. Open your browser and go to `http://127.0.0.1:5000` to use the application.

## License

This project is licensed under the MIT License.