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This repository contains a Python project for managing attendance using face recognition technology. The system allows users to register faces, mark attendance, and generate reports, providing a convenient and efficient solution for tracking attendance in various settings such as classrooms or workplaces.

Python 100.00%
attendance-management-system face-recognition machine-learning opencv python tkinter

facewise's Introduction

FaceWise

"FaceWise: Streamlining Attendance with Facial Recognition Technology"

Overview

FaceWise is a face-based attendance system implemented using Python and OpenCV. It provides a convenient way to automate attendance tracking by recognizing faces in images or live video streams.

Features

  • Face Detection: Utilizes OpenCV's face detection algorithms to locate faces within images or video frames.
  • Face Recognition: Recognizes faces using pre-trained deep learning models to identify individuals accurately.
  • Attendance Logging: Records attendance automatically by matching recognized faces with a database of registered individuals.
  • User-Friendly Interface: Simple and intuitive interface for easy interaction.

Technologies Used

  • Python
  • OpenCV
  • Deep Learning Models for Face Recognition

Libraries Used

  • numpy
  • opencv-contrib-python
  • opencv-python
  • openpyxl
  • pandas
  • Pillow
  • pyttsx3

Getting Started

Installation

To install FaceWise, follow these steps:

  1. Clone the repository:

    git clone https://github.com/ashutosh786palhare/FaceWise.git
  2. Navigate to the project directory:

    cd FaceWise
  3. Install the required dependencies:

    pip install -r requirements.txt

What steps you have to follow??

  • Download or clone my Repository to your device
  • type pip install -r requirements.txt in command prompt(this will install required package for project)
  • Create a TrainingImage folder in a project folder.
  • open attendance.py and automaticAttendance.py, change all the path accoriding to your system
  • Run attandance.py file

Project flow & explaination

  • After you run the project you have to register your face so that system can identify you, so click on register new student
  • After you click a small window will pop up in that you have to enter you ID and name and then click on Take Image button
  • After clicking Take Image button A camera window will pop up and it will detect your Face and take upto 50 Images(you can change the number of Image it can take) and stored in the folder named TrainingImage. more you give the image to system, the better it will perform while recognising the face.
  • Then you have to click on Train Image button, It will train the model and convert all the Image into numeric format so that computer can understand. we are training the image so that next time when we will show the same face to the computer it will easily identify the face.
  • It will take some time(depends on you system).
  • After training model click on Automatic Attendance ,you have to enter the subject name and then it can fill attendace by your face using our trained model.
  • it will create .csv file for every subject you enter and seperate every .csv file accoriding the subject
  • You can view the attendance after clicking View Attendance button. It will show record in tabular format.

ScreenShots

UI

Home

Take Image

Take image

Filling Attendance

Filling Attendance

Contribution Guidelines

If you'd like to contribute or suggest improvements, feel free to open an issue or submit a pull request. Your feedback and contributions are highly appreciated!

Here's how you can contribute to FaceWise:

  1. Fork the repository.
  2. Create your feature branch: git checkout -b feature/new-feature.
  3. Commit your changes: git commit -am 'Add some feature'.
  4. Push to the branch: git push origin feature/new-feature.
  5. Submit a pull request.

Contact Information

For any further information, collaborations, or inquiries, feel free to reach out to me:

Acknowledgments

  • Special thanks to the developers of OpenCV for their amazing library.
  • Thanks to the Python community for their continuous support and contributions.

Credit

Modified by: ME

Made by: This Guy Big thanks to @Patelrahul4884

Thank-You

Thank you for visiting my repository and exploring my portfolio website!

facewise's People

Contributors

ashutosh786palhare avatar patelrahul4884 avatar

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