This repository presents a system for the early diagnosis of pneumonia based on chest X-ray images. The system provides a graphical interface that allows you to predict the presence of pneumonia based on image analysis performed by a trained neural network.
This system can be used on any operating system where Docker is installed.
- backend: Contains backend code in С++.
- db: Database related files and scripts.
- frontend: Frontend code and resources.
- ml: Machine learning models and notebooks.
- py_backend: Additional backend code in Python.
- docker-compose.yml: Docker Compose file for container orchestration.
- Docker
- Docker Compose
- Clone the repository:
git clone https://github.com/OdincovMD/Practice.git
cd Practice- Build and run the Docker containers:
docker-compose up --build- The application will be available at http://localhost:3000.
- To stop and remove containers, use the command:
docker-compose down- The backend services are located in the backend and py_backend directories.
- Database setup and configurations are in the db directory.
- The frontend application is located in the frontend directory.
- Machine learning models, weights and train Jupyter notebook are in the ml directory.
Contributions are welcome! Please open an issue or submit a pull request.