Taking attendance in a class with more than 100 students can be a challenging and time-consuming task for teachers. It may require them to manually call out each student's name and mark their attendance on a paper or an attendance register.
Facetech automates the manual and time-consuming process of taking attendance, which is often prone to errors. To achieve this, we have developed an attendance management system that utilizes an automated face detection system based on a CNN-based network called the Siamese network.
- Download Visual studio
- Select c++ development kit while installing Visual Studio
- Install the dependencies from requirements.txt
pip install -r requirements.txt - Run app.py
- Click on index.html to get started
- Midatana Sai Praneetha: Worked on designing the application's front end along with the product's documentation.
- Sayantan Chatterjee: Worked on the backend of the application and explored different APIs to compile the overall project.
- Pramod Goyal: Worked on the machine learning model responsible for the recognition of the face and built the interface in python.
- Trisha Chatterjee: Data set accumulation and database management.
- Jay Solanki: Data set accumulation and database management.
- With a safe assumption that live video feeds through CCTVs are widely available. This means that there is a possibility to access real-time video footage from many locations. We can utilize facial recognition features directly from the live video feed to automate the process of identifying people. This will reduce the need for manual picture-taking and save time.
- Expanding the accessibility scope of our idea, we would implement this solution as a mobile application instead of a web app.