👁️KDS - A Web Application for Keratitis Classification using Deep Learning

KDS is a web application that utilizes deep learning models based on denseNet and resNet to classify keratitis. The application consists of a frontend developed using react.js and a backend developed using flask and pytorch.

💽Installation

1. Clone the repository: git clone https://github.com/Az0s/KDS.git.
2. Install the required packages: pip install -r requirements.txt.
3. Start the Flask server: python server.py.
4. Start the React app: cd frontend && yarn install && npm start.

🚀Usage

Once the application is running, users can upload an image of a keratitis lesion and the deep learning model will classify it based on the denseNet and resNet models. The results will be displayed on the web page.

⚒️Development

To contribute to the development of KDS, follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b my-feature-branch.
3. Make changes and commit them: git commit -am 'Add new feature'.
4. Push to the branch: git push origin my-feature-branch.
5. Create a pull request.

Dirs

.  
├── README.md  
├── backend             -- backend  
├── frontend            -- Desktop frontend  
├── frontend_mobile     -- Mobile frontend   
├── pyqt_deploy         -- PyQt source file  
└── server.py           -- Entry file for backend server

📝 License

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

📫 Contact

If you have any questions or comments about KDS, please feel free to contact us.