基于Python Django的人脸表情分类算法

archers have accumulated very mature research experience in basic face contour recognition and other aspects. There is also a very in-depth research on the recognition of facial expressions. In facial expression recognition, it is based on the position of the facial features, including eyebrows, eyes, facial size and position, to extract features and confirm the face recognition. By using script features to form the overall features of the face to achieve more accurate facial recognition. This time, a facial expression recognition system is developed using the Django framework technology. Through the development of this system, effective recognition of various expressions such as happiness, anger, and sadness made by people can be achieved. In this recognition, a classification network is used to construct the samples. By using deep learning and training of the computer, relevant recognition models are created, and then the face expressions are effectively classified through the classification operation, thus achieving the effective application of facial expression recognition. Keywords: facial expression recognition; Python; Django; facial features.