V-Attend: Automated Attendance Management System

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Traditional attendance methods, such as manual sign-in sheets or ID card tapping, are prone to errors and time-consuming processes, leading to inefficiencies in workforce management. These methods often suffer from issues like buddy punching and loss of cards, impacting accurate attendance tracking and organizational productivity.

V-Attend is an automated attendance management system. It utilizes facial recognition technology to mark attendance and provides real-time reports on attendance status.

Features

• Facial Recognition: Utilizes facial recognition technology to identify individuals and mark their attendance.
• Real-time Reporting: Provides real-time reports on attendance status, including present, absent, and on leave.
• Filtering Options: Allows users to filter attendance reports based on various criteria such as present, absent, and on leave.
• User Registration: Enables users to register themselves into the system by providing their name and registration number.
• Mobile Notifications: Students receive daily notifications on their mobile devices, informing them about their attendance status.

Technologies Used

• Python: The backend of the application is developed using Python programming language.
• Redis: Utilized as the database to store attendance logs and user registration data.
• Streamlit: Used for building the web application user interface with interactive features.
• Insightface:
• OpenCV: Integrated for facial recognition capabilities.
• NumPy and Pandas: Utilized for data manipulation and analysis.
• dotenv: Employed for managing environment variables.

Installation

To install and run the v-attend application locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/Precoder365/v-attend.git

2. Create a virtual environment and install the required libraries.

   python -m venv venv
   venv\Scripts\activate
   pip install -r requirements.txt

3. Add .env file

   REDIS_HOST =
   REDIS_PORT =
   REDIS_PASSWORD =
   
   TWILIO_ACCOUNT_SID =
   TWILIO_AUTH_TOKEN =
      
   VONAGE_API_KEY = 
   VONAGE_API_SECRET = 
   VONAGE_PHONE_NUMBER = 
   

4. Run the streamlit app

   streamlit run Home.py

Deployed link:

https://vattend-pren.streamlit.app/