基于深度学习与百度AI的菜谱推荐与健康分析微信小程序设计

Miniprogram design of recipe recommendation and health analysis based on deep learning and Baidu AI

本作品贴合当下时代潮流,以深度学习为核心,建立能够实现菜谱推荐与健康分析的微信小程序。使用基于TensorFlow搭建的神经网络模型,上传部署至腾讯云云函数,用以对用户在前端页面的选择进行预测并排序;调用微信相关接口,实现基于百度AI的菜品识别功能对用户的卡路里摄入动态监控,在页面中显示今日摄入的卡路里总和;使用WeUI相关组件显示近一周卡路里摄入变化曲线,更加简洁。综上,本作品能够对用户的健康起到一定的监督作用。

This work is in line with the current trend of the times,with deep learning as the core,to establish a WeChat applet that can realize recipe recommendation and health analysis.This paper uses the neural network model based on TensorFlow,which is uploaded and deployed to cloud function of Tencent Cloud,in order to predict and sort the user’s selection on the front-end page.Meanwhile,the paper calls WeChat related interfaces to realize the dynamic monitoring of user’s calorie intake based on Baidu AI’s dish recognition function,and displays the total calorie intake today on the page.Therefore,WeUI related components are used to display the change curve of calorie intake in the past week.The display effect is more concise.The conclusion of the paper is the work can play a certain role in monitoring the health of users.