This project is an Attendance marking application which uses the powerful face_recognition library of python.

The teacher or professor takes picture of the classroom from his mobile phone and sends that data to the backend and the backend uses the face reconition's library pre trained machine learning algoritms to detect faces from the image and mark the attendance accordingly.

The Mobile Application is a Cross-Platform application built using react-native and expo.

Backend is built using a light weight web framework flask.

Image data is procured, pre-processed and fed to the CNN based machine learning algorithms of face_recognition library which outputs a pickle file with encodings of each face.

The faces from the unknown images are then compared with the encodings and then and it predicts the faces from the image.

Install Cmake from https://cmake.org .

Make sure you have python 3.9 or 3.10 installed.

  git clone https://github.com/joyal-jij0/practicum

Go to the project directory

  cd attendEase

open this on your favorite Code Editer or IDE

for VS Code

  code .

Navigate to frontEnd/components/FormComponent.jsx

At line 14 add your IP Address

It should look like

const backendURL = "1xx.xx.xx.xx/upload";

Now Navigate to backEnd/app.py

At line 57 add your IP Address

It should look like

if __name__ == '__main__':
    app.run(debug=True, host='1xx.xx.xx.xx', port=8000)

Navigate back to frontEnd

  cd frontEnd

Install dependencies

  npm install

Start the server

  npx expo start

Follow the on screen instructions.

For more Info look into expo docs https://docs.expo.dev .

Navigate back to the backEnd

  cd backEnd

Create a Virtual Environment

  python3.10 -m venv venv

Activate Virtual Environment

  source venv/bin/activate

Install dependencies

python -m pip install -r requirements.txt

Start the server

  python3 app.py

Face Recognition Python Library Docs

Face Recognition Python Library Article

Expo Docs

React Native Docs

Flask Docs