This project is a web application designed to assist farmers in identifying plant diseases with ease. Utilizing advanced machine learning models, the application can accurately detect and classify diseases in various plants, providing valuable insights for better crop management.
- Disease Detection: Upload images of plants to receive real-time diagnosis of plant diseases.
- Multi-Plant Support: Currently supports disease detection for potatoes, corn, apples and grapes with additional plants planned.
- User-Friendly Interface: A modern, green-themed design tailored for ease of use by farmers.
- Responsive Design: Fully functional across different devices and screen sizes.
- Informative Website: Includes sections for Home, About, Information, and plant-specific details with a sleek, dark design.
- Flask: For the backend web framework.
- TensorFlow & Keras: For the disease detection models.
- HTML/CSS: For the frontend design.
- Python: For server-side logic and model operations.
Feel free to adjust the details to better fit your project specifics!
- Clone the Repository:
git clone https://github.com/your-username/plant-disease-detection.git - Install Dependencies: Ensure Python and required packages are installed.
- Run the Application: Start the Flask server with
python3 app.py.
Contributions are welcome! Please fork the repository and submit a pull request with improvements or bug fixes.