Repository files navigation
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:
Setup virtual environment -- virtualenv <venv> -- Source
Activate virtual environment -- source <venv>/bin/activate
pip install dlib or conda install -c conda-forge dlib
pip3 install face_recognition or conda install -c conda-forge face_recognition
pip3 install opencv-python or conda install -c conda-forge opencv
pip3 install pyrebase
pip install mysql-connector-python
pip3 install streamlit or conda install -c conda-forge streamlit
streamlit run stapp.py
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.
You can’t perform that action at this time.