- Django/Python (REST APIs, Websockets and ML functionalities), opencv, face-recognition
- Nextjs, Typescript, TailwindCSS
docsfolder includes university project documentation made with overleaf
- Clone the repo
- Go to the backend folder
- Create a virtual environment using
python -m venv .venv - Activate the virtual environment using
.venv\Scripts\activate - Install the dependencies using
pip install -r requirements.txt - Copy the
.env.examplefile to.envand fill the values - Run the migrations using
python manage.py migrate - Create a superuser using
python manage.py createsuperuser - Run the server using
python manage.py runserverordaphne presence.asgi:applicationto run the server with asgi configuration to handle both http and websocket requests
- Create a virtual environment using
- Go to the frontend folder
- Install the dependencies using
yarn install - Copy the
.env.examplefile to.env.local - Run the server using
yarn dev
- Install the dependencies using
- Go to
localhost:3000to see the app running
-
Student View
Student can submit images which then will be used to train the model -
Admin View
Admin can train the model using the images submitted by the students
Admin can take attendance using the webcam, it will recognize the student and mark their attendance
Admin can see the list of students and can remove or add them




