Dengue Outbreak Prediction 🌦️🦟<Python/Flask>

This application predicts the likelihood of a dengue outbreak based on weather conditions using a pre-trained model and real-time weather data. The app visualizes predictions on an interactive map of India.

Features

• User Inputs: Temperature, Humidity, Rainfall, and Wind data.
• Map Integration: India map visualization with color-coded dengue prediction zones.
• Real-Time Weather Data: Uses OpenWeather API to fetch live data.
• Prediction Model: Machine learning model trained to predict dengue likelihood.

Setup Instructions

Prerequisites

• Python 3.6+
• Joblib, Flask, Requests, Folium libraries

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/dengue-prediction-app.git
   cd dengue-prediction-app

2. Install dependencies:

   pip install -r requirements.txt

3. Add OpenWeather API Key: Replace API_KEY in app.py with your OpenWeather API key.

4. Place the ML model file: Make sure dengue_model.pkl is in the specified directory or update the path in app.py.

Usage

1. Run the Flask App:

   python app.py

2. Open in Browser: Navigate to http://127.0.0.1:5000/ to access the app.

   Here's the updated section for your GitHub README:

🚀 Getting Started

Open Using Daytona

1. Install Daytona: Follow the Daytona installation guide.
2. Create the Workspace:

   daytona create <SAMPLE_REPO_URL> 

3. Install Dependencies:
   Follow the setup instructions in the main README to install the required dependencies.
4. Start the Application:

   python app.py  

Files

• app.py: Main Flask application file.
• templates/index.html: HTML template with prediction form and map.
• static/style.css: Basic styling for the web app.
• dengue_model.pkl: Pre-trained machine learning model file.
• requirements.txt: List of dependencies required for the project.

Screenshots

Contributing

Feel free to open issues, contribute, or suggest improvements!