Research on Face Gender Recognition System Based on PaddleHub

Machine vision is one of the important application areas of face recognition technology. In order to reduce the size of computer recognition models and optimize the accuracy of algorithm execution, this project proposes a study of a face gender detection system based on PaddleHub. The model programs in Python and uses OpenCV which use face images and videos as input variables for image processing. The results show that the face facial features extraction ability of the enhanced images can be marked significantly and correctly. This model extracts image feature mapping more effectively and greatly improve the recognition speed, accuracy and precision about recognizing face gender detection. It obtains more representative and better classification results, saves human and material resources costs. All in all, it can be more widely used in public security field, military field, intelligent surveillance, etc.