Students-Attendance-System

Project Overview

A computer vision-based project designed to recognize and identify individuals based on their facial features. The system utilizes state-of-the-art deep learning and image processing techniques to real-time face recognition. It is deployed using a Flask web application to facilitate attendance tracking through a Google Sheets spreadsheet.

Running the Project

1. Clone this Repo:

git clone https://github.com/MariamAmy/Students-Attendance-System

2. Install the required dependencies:

pip install -r requirements.txt

3. Hosting the Application

To host the application and make it accessible online, we used ngrok. Follow the steps below:

• Install ngrok:

  npm install ngrok -g
  

• Run the Flask application:

  python app.py
  

• In a separate terminal, run ngrok to expose the local server:

  ngrok http 5000
  

4. Access the Application:

• Once you have hosted the application using ngrok, you will receive a public URL.
• Open your web browser and navigate to the provided ngrok URL.

5. Utilize the Attendance System:

• The application interface will guide you through the attendance tracking process.
• Upload an image.
• The system will identify individuals and update the attendance records in the Google Sheets spreadsheet.

6. Monitor Attendance:

• Access the Google Sheets spreadsheet to view the real-time attendance data.
• The spreadsheet is automatically updated as students are recognized by the system.

Feel free to contribute to the project by submitting pull requests or reporting issues!