# Face Recognition Web App Welcome to the Face Recognition Web App! This application allows users to upload images and detect faces within the images using advanced facial recognition technology. ## Table of Contents - [Introduction](#introduction) - [Features](#features) - [Technologies](#technologies) - [Setup](#setup) - [Usage](#usage) - [Contributing](#contributing) - [License](#license) ## Introduction The Face Recognition Web App is a full-stack application built to demonstrate facial recognition capabilities. It provides a user-friendly interface for uploading images, and the backend processes these images to identify and mark faces in the images. ## Features - User-friendly interface for uploading images. - Advanced facial recognition for detecting faces within the images. - Secure authentication and authorization mechanisms. - Efficient storage and retrieval of user data and images. - Responsive design for seamless usage across devices. ## Technologies The project uses the following technologies: ### Frontend - React: JavaScript library for building user interfaces. - Tachyons: CSS toolkit for creating fast and responsive interfaces. ### Backend - Node.js: JavaScript runtime for building server-side applications. - Express.js: Web application framework for Node.js. - PostgreSQL: Open-source relational database management system. ## Setup 1. Clone this repository to your local machine. 2. Navigate to the `frontend` directory and run `npm install` to install frontend dependencies. 3. Navigate to the `backend` directory and run `npm install` to install backend dependencies. 4. Set up a PostgreSQL database and update the database configuration in the `backend/config/config.js` file. 5. Run the frontend and backend servers simultaneously using `npm start` in their respective directories. ## Usage 1. Access the application by visiting `http://localhost:3000` in your web browser. 2. Sign up or log in to your account. 3. Upload an image through the user interface. 4. The application will process the image and identify faces within it. 5. The processed image with marked faces will be displayed. ## Contributing Contributions are welcome! If you'd like to contribute to the project, please follow these steps: 1. Fork the repository. 2. Create a new branch for your feature or bug fix. 3. Develop and test your changes. 4. Submit a pull request explaining the changes you've made. ## License This project is licensed under the [MIT License](LICENSE).