AI-Facial-Attendence
AI-Facial-Attendence copied to clipboard
Complete Web App for taking online attendance using AI based Facial Recognition.
Complete Web App for taking online attendance using AI based Facial Recognition. Designed from scratch using React + Tailwind with Python backend. OpenCV used for Face detection and recognition.
Setup
1. Install Front-end
To run the front-end:
-
Clone the repository.
-
Navigate to the cloned repository and install dependencies by running:
npm install
- Now, start the server
npm start
2. Install Back-end
-
The project requires python 3.7. Other versions may create issues.
-
Install MongoDB using their documentation and start the MongoDB server.
-
Navigate to
backend/
folder and install the python dependencies:
pip install -r requirements.txt
- Run main.py
3. Connect front-end to back-end
- Note the local host url the backend server is running at (as given in the terminal output).
Paste this url in
config/api.js
eg:
// End point of your flask api.
export const apiEndPoint = 'http://127.0.0.1:5000/';
Preview







WorkFlow
- User(Teacher) signs in.
- Teacher creates a new course by giving information, and dataset.
- Dataset includes a folder having pictures of students enrolled in the course, shot by their webcams.
- Upon creation, the data is sent to the backend and model is trained for the given course.
- To take attendence, the teacher starts a new session of the course.
- A unique code is generated which teacher sends out to the students.
- Students navigate to
/markattendence
page and paste the code. - Students are then shown a page where they allow webcam, capture a shot and mark attendence. Using the trained model, their attendance is marked.
- Teacher can download attendence reports of a course in form of csv from the sessions page.