Designed a simple website integrated into the ML model for tracking the attendance of the hostellers.

1. MERN Stack
2. Face API

• Clone the repository:

git clone https://github.com/tansexe/Hostel-E-attendance.git

• Install dependencies:

cd Hostel-E-attendance
npm install

• Start the server:

npm start

The server will listen on port 3000 by default.

1. Backend-E-Attendance
2. Face-Detection
3. Frontend-Vite

The Frontend-Vite folder contains the folder for the frontend.

At the heart of the Frontend-Vite folder is the src folder. Within this folder, several subfolders have important roles:

1. Assets: This folder houses all the images utilized in the project.
2. Components: This folder includes reusable elements such as buttons, navigation bars, and headers.
3. Pages: This folder encompasses all the web pages of the website.

Additionally, App.jsx enlists the components to be rendered from different routes. For the routing of pages in React, React-Router-Dom, a third-party library, is integrated.

The Backend-E-attendance folder contains the folder for the backend.

This project has the following endpoints:

If you encounter any issues while using the Hostel-E-attendance, consider the following troubleshooting steps:

1. Check Dependencies: Ensure you have installed all required dependencies.
2. Review Error Messages: If you encounter any errors, carefully review the error messages to identify the source of the issue.

1. JavaScript API for Face Recognition in the Browser with tensorflow.js. Link
2. Github Repository of faceAPI.js. Link
3. Github Repository of face Detection. Link