Complete Face Recognition attendance software| Python OpenCV

About Complete Face Recognition attendance software| Python OpenCV

Hello Students 

Welcome to the course Complete Face Recognition attendance software using Python, Pyqt5,  OpenCv and Machine Learning using Qt Designer with SQLite database

In this course you will learn how to create a complete software to implement face recognition attendance system for a company or for a business to record daily attendance.

First you will learn how to install the required software for our project

Python

Pyqt5

Pyqt5-tools

Open Cv

Vs Code

Db Browser

Then you will learn how to create beautiful interfaces for the following process

Login process

Training process

Face recognition attendance entry process

Reports process

In the interface creation process you will learn how to create controls for our requirements

QLabel

QTabWidget

QPushButton

QLineEdit

QTableWidget

QDateEdit

QFrame

The main process you will learn while designing the forms

How to provide images

How to  fit images properly with QLabel

How to capture passwords using Python GUI window.

How to provide styles to all controls

How to provide hover effects to controls in the  qt designer.

Connect Qt Designer ui file with Python

Then you will learn how to connect python code with pyqt5 designed GUI using QT Designer.

Create and connect SQLite

Then you will learn how to create sqlite3 database and tables using python code and check the database with db browser.

These are the following modules we will develop in this project.

1. Login Module

In this module, the admin will enter the password to enter into the system. The the python code will check if the entered password is correct or not. If it is correct, it will open the next form. We will use python if condition and user defined functions to check login.

2. Training Module

In this module, the admin will use haarcascade_frontalface_default.xml file to detect the human face shown in the webcam. The camera is capture is created using OpenCv. The captured image contverted to gray scale and Cascade Classifier algorithm will detect any face available in the captured image. If face is available, it will automatically create a directory and store the faces in 1.png, 2.png.... like that till the given number for training. If the face is not detected, then the system will not save the image file.

3. Attendance Module

The member will show their face in the web cam. Now the system will create a LBPHFaceRecognizer model using cv2 library and this model will be trained using the existing dataset we already created image and label set. Then this model will predict with the web cam face and if the person is there in the trained database, it will record the attendance for the person. The attendance will be recorded only if the person is showing their face first time in the current date. If the person is showing their face more than one time, the system will not record the attendance. If a new person is showing their face, it will show unknown person message.

4. Reports Module

In the reports module, the system will show the attendance records of all the day. The admin can select a particular date from the date select control, the system will show the attendance for the selected date.

By doing this course, you will learn how to create a complete python GUI project using face recognition of OpenCV Library and use LBPHFaceRecognizer model. You will also learn how to create database, tables and insert records from the user interface. You will learn how to generate reports from the database and how to connect GUI and python code.

Thank you for your interest in this course...

I will see you in the course...