Download Udemy – Complete Face Recognition attendance software Python OpenCV 2023-1

1. Python
2. Pyqt5
3. Pyqt5-Tools
4. Open CV
5. In front of the code
6. DB browser

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

1. Login process
2. learning process
3. The process of entering presence and absence of face recognition
4. Reporting process

In the process of creating the interface, you will learn how to create controls for our needs

1. QLabel
2. QTabWidget
3. QPush button
4. QLineEdit
5. QTableWidget
6. QDateEdit
7. QFrame

The main process you will learn when designing forms

1. How to present images
2. How to fit images with QLabel
3. How to get password using python GUI window
4. How to style all controls
5. How to provide floating effects to controls in qt designer.

Connect the Qt Designer UI file with Python

1. You will then learn how to interface Python code with the pyqt5 GUI using QT Designer.

Create and connect SQLite

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

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

1. Login module: In this module, the admin enters the login password. The Python code checks whether 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 the input.

2. Training module: In this module, the administrator uses the haarcascade_frontalface_default.xml file to recognize the human face shown on the webcam. The camera is created using OpenCv. The image captured in gray scale and the waterfall classifier algorithm recognizes every face in the captured image. If the face is available, it will automatically create a directory and put the faces in 1.png, 2.png …. Like that saves up to the given number for training. If the face is not detected, the system will not save the image file.

3. Presence module: The member shows his face on the webcam. Now the system will create an LBPHFaceRecognizer model using the cv2 library and this model will be trained using the existing dataset we have already created image and label sets. Then this model predicts with the web cam page and records the person’s presence and absence in the trained database if the person is present. Attendance is recorded only if the person shows their face for the first time on the current date. If the person shows his face more than once, the system will not record the attendance. If a new person shows their face, it will show the message of the unknown person.

4. Report module: In the reports module, the system shows attendance records for the whole day. Admin can select specific date from date selection control, system will show attendance on selected date.

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

Installation guide

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