Forest Fire Prediction Web App

A Flask-based web application for predicting the Forest Fire Weather Index (FWI) using machine learning. Enter weather and environmental data to get instant FWI predictions. The app features a modern Bootstrap UI and easy deployment.

Features

• Predict Forest Fire Weather Index (FWI) using ML model
• User-friendly, responsive Bootstrap interface
• Input validation and error handling
• Ready for deployment

Getting Started

1. Clone the repository

git clone https://github.com/nsrawat0333/forest---fire-predictor.git
cd forest---fire-predictor

2. Create and activate a virtual environment (recommended)

python -m venv venv
# Windows
venv\Scripts\activate
# Linux/Mac
source venv/bin/activate
### 3. Install dependencies
```bash
pip install -r requirements.txt

4. Make sure model files are present

• Place ridge.pkl and scaler.pkl in the Models/ folder.

5. Run the application

python application.py

• The app will be available at http://localhost:5000

6. Usage

• Open the app in your browser.
• Enter the required weather and environmental parameters.
• Click Predict to get the FWI prediction.

Project Structure

application.py
requirements.txt
Models/
    ridge.pkl
    scaler.pkl
templates/
    home.html
    index.html
Notebook/
    ...
project/
    ...

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contributors:

• Neeraj Singh

forest---fire-predictor

A Flask-based web application for predicting the Forest Fire Weather Index (FWI) using machine learning. Users can input weather and environmental parameters to get instant FWI predictions. The app features a modern Bootstrap UI and supports model deployment with scikit-learn.