README.md

Online-attendance-tool

Head over to registration branch for students registration

Head over to chrome_extension branch for Chrome Extension installation on local system instructions

Head over to dashboard branch to view the dashboard for overall attendance of students

To use the streamlit code:

1. Setup virtual environment -- virtualenv <venv> -- Source
2. Activate virtual environment -- source <venv>/bin/activate
3. pip install dlib or conda install -c conda-forge dlib
4. pip3 install face_recognition or conda install -c conda-forge face_recognition
5. pip3 install opencv-python or conda install -c conda-forge opencv
6. pip3 install pyrebase
7. pip install mysql-connector-python
8. pip3 install streamlit or conda install -c conda-forge streamlit
9. streamlit run stapp.py

Demo:

Publications

• Parhi, M., Roul, A., Ghosh, B. (2022). An Intelligent Online Attendance Tracking System Through Facial Recognition Technique Using Edge Computing. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 286. Springer, Singapore. https://doi.org/10.1007/978-981-16-9873-6_1

• M. . Parhi, A. . Roul, B. Ghosh, and A. Pati, “IOATS: an Intelligent Online Attendance Tracking System based on Facial Recognition and Edge Computing”, Int J Intell Syst Appl Eng, vol. 10, no. 2, pp. 252–259, May 2022.