Enroll Course: https://www.udemy.com/course/complete-face-recognition-attendance-software-python-opencv/
Are you looking to develop a robust and intelligent attendance tracking system? This Udemy course, ‘Complete Face Recognition attendance software Python OpenCV’, is your comprehensive guide to building a professional-grade face recognition attendance software from scratch. Leveraging the power of Python, PyQt5, OpenCV, and machine learning, this course equips you with the skills to create a seamless solution for businesses or companies.
The course begins with a thorough walkthrough of essential software installations, including Python, PyQt5, PyQt5-tools, OpenCV, VS Code, and DB Browser for SQLite. You’ll then dive into designing intuitive user interfaces using Qt Designer for key functionalities: a secure login process, a user training module, the core face recognition attendance entry, and a detailed reports section.
Throughout the interface design, you’ll master the use of various PyQt5 controls like QLabel, QTabWidget, QPushButton, QLineEdit, QTableWidget, QDateEdit, and QFrame. You’ll learn how to effectively manage images within your GUI, ensure proper image fitting, and securely capture passwords. The course also covers styling your application with hover effects for a polished user experience.
A significant portion of the course is dedicated to connecting your Qt Designer UI files with Python code, enabling dynamic functionality. You’ll learn to create and manage an SQLite database, including setting up tables and inserting records directly from your user interface, with practical verification using DB Browser.
The project is broken down into practical modules:
1. **Login Module:** Securely control access to the system by implementing a password-protected login.
2. **Training Module:** Utilize OpenCV’s Haar Cascade classifier to detect faces from webcam feeds. Captured faces are saved and organized for training purposes, ensuring only detected faces are processed.
3. **Attendance Module:** Employ OpenCV’s LBPHFaceRecognizer model to identify individuals. The system records attendance only upon the first successful face recognition for a given day, preventing duplicate entries and identifying unknown individuals.
4. **Reports Module:** Generate daily attendance records. Users can select a specific date to view attendance data, providing valuable insights.
By the end of this course, you will not only have a fully functional face recognition attendance system but also a deep understanding of integrating GUI development with powerful machine learning libraries. You’ll be proficient in database management, report generation, and connecting front-end design with back-end logic. This course is highly recommended for anyone looking to build practical, real-world applications with Python and computer vision.
Enroll Course: https://www.udemy.com/course/complete-face-recognition-attendance-software-python-opencv/