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In order to reduce the development and promotion cost of developers and accelerate the development speed of developers, emotion recognition technology is widely used in Internet and other scenarios, and an emotion recognition open platform based on deep learning is proposed. This article provides a detailed introduction to the design and implementation of an open emotion recognition platform. Overall, the platform has the following characteristics: it uses the Struts2+Spring+JPA framework, adopts interface-oriented programming, and has good scalability; The Convolutional neural network in the deep learning technology is used to realize expression recognition, which has good recognition accuracy; OpenID+OAuth authentication and authorization scheme is adopted to make the platform have better security. The results show that the ck+ dataset, which is different from the training dataset, is used to test, and the contempt emotion in ck+ is removed. The last three faces in each directory are regarded as the same emotion, corresponding to the emotion file, and the first face in each directory is regarded as the natural emotion. There are seven emotional types in total: anger, jealousy, fear, happiness, sadness, surprise and nature. After that, the face of each picture is extracted, and then the platform interface is used to identify it. Compared with the real tag corresponding to the picture, the accuracy rate is 72.2%. The open platform of emotion recognition based on deep learning enables external programs to use emotion recognition services through open API, providing more convenient and faster development methods for developers, thus promoting the wide application and promotion of emotion recognition technology. The next step is to further strengthen the robustness of the platform, and constantly optimize the emotion recognition algorithm to improve the recognition accuracy.
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