This project presents a comprehensive Face Recognition Web Application that integrates modern web technologies with AI capabilities. The application offers features such as user registration, login, and authentication using facial recognition technology. It utilizes React.js for the frontend, Node.js and Express.js for the backend, and incorporates the face-api.js library for face recognition. The deployment is achieved through a serverless architecture, with the backend hosted on Render.com and the frontend on GitHub Pages.

The main objective of this project is to showcase proficiency in various aspects of full-stack web development, AI integration, and serverless deployment. By developing a Face Recognition Web Application, this project demonstrates the ability to create interactive, real-time applications that harness cloud resources and leverage advancements in machine learning for an intuitive user experience.

• React.js: The user interface is built using React.js, a popular JavaScript library for building interactive UIs.
• Live Webcam Feed: The application incorporates a live webcam feed, allowing users to interact with real-time expressions data.
• Visual Feedback: Visual feedback is provided when a face is detected and recognized, enhancing the user expressions.
• User Registration and Login: The application implements a user-friendly registration and login process, with face recognition functionality for authentication.

• Node.js and Express.js: The backend server is developed using Node.js and Express.js, facilitating the handling of API requests.
• Real-time Data Processing: The backend efficiently processes real-time data, ensuring responsive handling of requests.
• AI Model Integration: The application integrates the face-api.js library for face recognition, enabling accurate detection and recognition of faces.
• Data Management: Data storage and retrieval are managed efficiently using MongoDB and Mongoose, adhering to privacy and security best practices.

• Face Recognition Library: The project utilizes face-api.js, an open-source JavaScript library for face recognition.
• Detection Accuracy: The application accurately detects faces in various conditions, including different angles and lighting scenarios.

• Backend Deployment: The backend is deployed to Render.com, a serverless platform that simplifies deployment and scaling.
• Frontend Deployment: The frontend is deployed to GitHub Pages, providing easy access to the application.
• Deployment Documentation: The deployment process is documented, covering the setup and configuration of serverless services used.

1. Clone the Repository: Clone the repository to your local machine using the command git clone https://github.com/ishiprayadav/codebugged-assignment.git.
2. Navigate to Project Directory: Change directory to the project directory using cd frontend | cd frontend.
3. Install Dependencies: Install dependencies for both the frontend and backend by running npm install in the frontend and backend directories.
4. Start the Backend Server: Start the backend server by running npm start in the backend directory.
5. Start the Frontend Server: Start the frontend server by running npm start in the frontend directory.
6. Access the Application: Open your web browser and navigate to http://localhost:3000 to access the application.