"基于Python Django的人脸表情识别算法设计与实现"。

基于python Django人脸表情的分类算法设计与实现.docx是一份关于利用Python Django框架技术开发人脸表情识别系统的文档。在当下的数据化信息时代，人们的日常生活几乎都被数字化所覆盖，而人脸识别技术作为信息验证、密码安全等方面的应用已经非常成熟。过去几十年，研究人员在人脸轮廓识别和面部表情识别方面取得了非常深入的研究经验。 人脸表情识别是根据人们的面部特征位置，包括眉毛、眼睛、脸型等，进行特征提取和面部识别确认的过程。本次文档描述了如何利用Python Django框架技术开发一款人脸表情识别系统，实现对高兴、愤怒、悲伤等多种表情的有效识别。该系统利用了分类网络，通过计算机的深度学习和训练制作出相关的识别模型，再通过分类操作对人脸的表情进行有效的分类，从而实现有效的人脸表情识别的功能应用。 关键词：人脸表情识别；Python；Django；人脸特征 Abstract: The document "Design and Implementation of Face Expression Classification Algorithm based on Python Django" is a guide to developing a facial expression recognition system using the Python Django framework. In today's data-driven information age, almost every aspect of people's daily lives is covered by digitalization, and facial recognition technology is a very mature and deep application in information verification, password security, and more. Over the past few decades, researchers have gained very deep research experience in basic facial contour recognition and facial expression recognition. Facial expression recognition is based on the extraction of facial features such as eyebrows, eyes, face shape, and the confirmation of facial recognition. This document describes how to use the Python Django framework technology to develop a facial expression recognition system, which can effectively recognize various expressions such as happiness, anger, and sadness. The system uses a classification network to create samples and utilizes computer deep learning and training to create relevant recognition models, and then effectively classifies facial expressions through classification operations, thus achieving the functionality of effective facial expression recognition. Keywords: facial expression recognition; Python; Django; facial features.