The system accurately recognizes and classifies faces in everyday scenarios and supports multiple input options, including pictures, picture folders, video files, and real-time camera monitoring. It also features heat map analysis, identification box labeled, class statistics, adjustable confidence, IOU parameters, and result visualization. In addition, the system includes a SQLite-based user registration and login interface, model toggle buttons, and an easy-to-customize Pyside6 user interface.
The development of datasets is also an important factor driving the advancement of face detection technology. Early face detection research relied on datasets such as FDDB and WIDER FACE, which played an important role in the improvement and evaluation of algorithms at the time4. In recent years, more high-quality and diverse datasets have been developed, such as CASIA-WebFace and MS-Celeb-1M. These datasets not only far exceed the earlier datasets in size, but also have been greatly improved in diversity and complexity, making them more suitable for training and testing modern deep learning models
If you have any questions or need the full code or data or need customized development requirements, you can contact me Email Mail me : slowlon@foxmail.com
We use the most advanced YOLOv8 algorithm as the core to implement efficient and accurate face detection in daily scenarios. Compared with earlier deep learning models such as CNN and ResNet, YOLOv8 shows better performance, especially in processing time and detection accuracy. This paper not only introduces the working principle of YOLOv8 algorithm in detail, but also compares the effects of different versions of YOLOv7, YOLOv6, YOLOv5 on face detection tasks through experiments, providing readers with a comprehensive performance evaluation report.
We successfully built a user-friendly face detection system interface using the PySide6 library. This innovation makes face detection in daily scenarios more intuitive and convenient, maximization promotes the popularity of YOLOv8 algorithm in practical applications. The system interface is designed to provide users with a concise and clear operation experience, while ensuring enough functionality and flexibility to meet the needs of different users.
In order to enhance the security and personalized service of the system, we specially designed the login management function. This design not only protects the user’s personal information security, but also leaves room for the introduction of more customized functions in the future, showing the extensible nature of the system.
In order to facilitate the reader’s understanding and application, this paper also provides a complete set of data sets and code resource packages. These resources cover the whole process from training to testing, allowing readers to easily reproduce experimental results and conduct further research and development on this basis.
If you have any questions or need the full code or data or need customized development requirements, you can contact me Email Mail me : slowlon@foxmail.com