This project is a web application designed to help farmers and agriculturalists recognize plant diseases using Machine Learning and Computer Vision. The application allows users to upload images of plants, detects diseases.
- Disease Detection: Uses a trained deep learning model to classify plant diseases from uploaded images.
- Responsive Design: User-friendly web interface built with HTML, CSS, and JavaScript.
- Frontend: HTML, CSS, JavaScript
- Backend: Flask
- Machine Learning Libraries: TensorFlow, NumPy, OpenCV, Pillow, Matplotlib
- Deployment: Docker, Google Cloud
- Python 3.7+
- Docker
- Google Cloud Platform account
├── Dockerfile # Docker configuration for containerizing the app
├── app/ # Main application code
│ ├── main.py # Flask app file
│ ├── models/ # Pre-trained ML model(s)
│ ├── static/ # Static assets (CSS, JavaScript, images)
│ └── templates/
│ └── index.html # Frontend HTML file
├── requirements.txt # Python dependencies
└── README.md # Project documentation