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This project demonstrates face detection using OpenCV, it uses a pre-trained Haar cascade classifier to detect faces in images or video streams. It provides a simple and efficient solution for identifying human faces using speech automated commands.

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dhanvina/FaceTrackEDU

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Face Recognition Attandance System

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Recognize The faces And Take Automatic Attandance. ✨

The project has enabled different technologies and features with images and audio. It is been developed for teachers having disablities to easily use. The project is very efficent in varying weather conditions.

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GitHub

Motivation 😲


We seek to provide a valuable attendance service for both teachers and students. Reduce manual process errors by provide automated and a reliable attendance system uses face recognition technology.

Features 📋


  • Check Camera
  • Capture Faces
  • Train Faces
  • Recognize Faces & Attendance

Screenshots 📷


Tech Used 💻


Build With -

  • Python 3

Module Used -

All The Module are Latest Version.

  • OpenCV Contrib
  • Numpy
  • Pandas

Face Recognition Algorithms -

  • Haar Cascade
  • LBPH (Local Binary Pattern Histogram)

Software Used -

  • Pycharm
  • VS CODE
  • Git

Installation 🔑


Download or Clone the project

First Download or Clone the Project on Your Local Machine.To download the project from github press Download Zip

You can clone the project with git bash.To clone the project using git bash first open the git bash and write the following code

git clone https://github.com/dhanvina/face-recognition-attendance-management-system.git

After download, Open the project using Pycharm or VSCODE. Then we have to create an python enviroment to run the program.

create enviroment

First open the terminal or command line in the IDE.Then write the following code.

python -m venv env

Then activate the enviroment using the code below for windows.

.\env\Scripts\activate

[ Notice: If your pc don't have virtual enviroment or pip install the follow this link. How to create Virtual Enviroment ]

Installing the packages


After creating the enviroment on your project let's install the necessary packages.

To install those package open the terminal or command line and paste the code from below

pip install opencv-contrib-python
pip install numpy
pip install pandas

Test Run 🚴


After creating the enviroment and installing the packages, open the IDE terminal/command line to run the program. Using the code below.

py main.py

How To Use? 📝


If you want to use it just follow the steps below.

  1. First download or clone the project
  2. Import the project to your favourit IDE
  3. Create an python enviroment
  4. Install all the packages
  5. Run the project using your IDE Run Button

Contribute ❤️


If you want to contribute in this project feel free to do that.

Licence 📜


MIT © dhanvina

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This project demonstrates face detection using OpenCV, it uses a pre-trained Haar cascade classifier to detect faces in images or video streams. It provides a simple and efficient solution for identifying human faces using speech automated commands.

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