Skip to content

Latest commit

 

History

History
92 lines (69 loc) · 3.59 KB

README.md

File metadata and controls

92 lines (69 loc) · 3.59 KB

Smart Attendance System

Smart Attendance Management System is an application developed for daily attendance of student/ staff in colleges or schools or any other organizations. This project attempts to record attendance through face detection and live location. The objective of this project is to develop a system for managing attendance that can be used by all individuals in educational institutions or in any organization. This software requires to store the user's own image to be detected. The system will load the user’s image at the sign-up step. For giving attendance the user needs to sign in and the real time image of the user will be captured to take the attendance and it will be matched with the stored image of the person. The proposed system records attendance without allowing any chance of proxy attendance by the students. The administrator maintains the database. After verifying the user, the attendance will be taken, and it will be saved in an excel sheet with their live location and time of attendance. In this approach, face recognition and face detection are used. This face detection differentiates faces from non-faces and is therefore essential for accurate attendance. The other strategy involves face recognition for marking the accurate attendance of the students.

Table of Contents

Features

  • Facial Recognition: Utilizes the face-recognition library to recognize faces for attendance tracking.
  • Responsive UI: A responsive and dynamic user interface developed using React, Redux, and Material UI.
  • Database: Stores data in a PostgreSQL database for efficient data management.
  • Cloudinary Integration: Manages photo storage using Cloudinary, ensuring scalability and accessibility.

Prerequisites

Before you begin, ensure you have met the following requirements:

  • Node.js and yarn installed on your system.
  • Python and pip should be installed in your system (Documentation).
  • Make sure you have installed Django globally or have a Django virtual environment.
  • Create a cloudinary account.
  • Enable unsigned uploading to cloudinary (Documentation).

Installation

  1. Clone the repository:
git clone [email protected]:asheshmandal2003/smart-attendance-system.git
  1. Navigate to the project directory:
cd smart-attendance-system

  1. Setup the .env files using .example.env file in the corresponding directory.

  2. Run the backend server

cd server
pip install -r requirements.txt
python manage.py runserver
  1. Run the frontend server:
cd client
yarn
yarn dev --port 3000
  1. Open your browser and navigate to http://localhost:3000.

Technologies Used

  • Backend: Django, face-recognition library, Django REST Framework
  • Frontend: React.js, React Router Dom, Redux.js, Material UI
  • Database: PostgreSQL
  • Photo Storage: Cloudinary

Contributing

  • Fork the repository.
  • Create a new branch: git checkout -b feature/new-feature.
  • Make your changes and commit them: git commit -m 'Add new feature'.
  • Push to the branch: git push origin feature/new-feature.
  • Submit a pull request.

License

This project is licensed under the MIT License.