A Contactless Attendance System where your face is identified for Attendance. ✨
Motivation 😲
This Repository was created as a part of MINeD Hackathon, a national level hackathon organized by Centre of Excellence in Data Science at the CSE Department of Nirma University.
We seek to provide a valuable attendance service for employees. Reduce manual process errors by provide automated and a reliable attendance system uses facial recognition technology.
Features 📋
- Check Camera
- Capture Faces
- Train Faces
- Recognize Faces & Attendance
- Automatic Email
For more Updates check the GitHub Repository:
dhhruv / Contactless-Attendance-System
✨ A Contactless Attendance System where your face is identified for Attendance.
Screenshots 📷
1. GUI
2. Command Line Interface
3. Checking Camera
4. Recognize Image
5. Automail
Tech Stack Used 💻
Build With -
- Python 3.8
Modules Used -
- OpenCV Contrib
- Pillow
- Numpy
- Pandas
- Shutil
- CSV
- yagmail
- Tkinter
Facial Recognition Algorithms -
- Haar Cascade
- LBPH (Local Binary Pattern Histogram)
Softwares Used -
- Pycharm 2019.2
- VS CODE
- Jupyter Notebook
- Git
Installation 🔑
Create Environment
First open the terminal or command line in the IDE and copy the following code.
python -m venv venv
Then activate the virtual enviroment using the code below for windows.
.\venv\Scripts\activate
Note: 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 -r requirements.txt
Note: During the package installation, sometimes it shows errors due to package dependencies and to avoid those error you can install those packages as admin.
Test Run 🚴
After creating the virtual environment and installing the packages, open the IDE terminal to run the program.
- To use Command Line Version Use:
py main.py
- To use GUI Version Use:
py main_gui.py
Test Run for CAS as shown below:-
How To Use? 📝
If you want to use it then follow the steps below:
- First download or clone the repository.
- Import the project to your preferable IDE. Recommended : PyCharm
- Create a python virtual environment.
- Install all the packages from requirements.txt.
- Change the mail information in the Info.py.
- Run the project using the Command Prompt or PowerShell or your IDE Terminal Button.
Top comments (1)
Wonderful project! Although, I have tried a ton with OpenCV but the detection is just not as accurate as for eg. Using Tensorflow.