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水稻病虫害自动识别系统

介绍

本识别项目通过对于用户所上传的水稻图片进行分析，识别出相应的病虫害，通过这种方法帮助种植用户进行虫害的识别

技术栈

开发语言 python，java
前端 layui,thymeleaf
后端 java,flask
数据库 Mysql
机器学习 TensorFlow2.0
服务器 Centos（腾讯云）+Ubuntu（阿里云）

项目结构

JavaWeb项目：

​ image-20210801201703641

js/css+静态页面

image-20210801201745493

为了方便起见，python写的flask项目直接丢的在resource内

image-20210801201831922

使用方式

  1. 修改controller类中UploadController中的路径（修改为本地存储路径，虽然最后会删除，所以不占地方）

    image-20210801202025044

    image-20210801202040645

  2. 修改application.properties配置文件中的mysql配置

    image-20210801202240554

  3. 修改tool内中的接口

    由于这个预测接口被我放在了服务器上，所以需要修改成自己的才可以

    详细原理介绍可以看我写的博客

    https://www.cnblogs.com/printwangzhe/p/15087444.html

    image-20210801202652183

功能介绍

1.病虫害识别

图片上传

image-20210801195727047

image-20210801195756390

图片识别

image-20210801195710399

2.用户登录注册

用户登录

image-20210801203212044

用户注册

image-20210801203238213

3.病虫害百科查询

image-20210801203327139

4.系统首页

image-20210801203419432

5.用户反馈

image-20210801203448494

6.用户搜索历史

image-20210801203514601

7.用户中心

image-20210801203546871

8.用户管理--后台

image-20210801203645880

9.病虫害管理--后台

image-20210801203708903

10.评论管理--后台

image-20210801203729978

项目中的用户

image-20210801203928082

1.管理员

管理员为系统的维护者，能够对数据库进行增删改等操作

2.客服

客服能够对问题进行回复

3.普通用户

一般注册后的用户都是普通用户

4.游客

未经注册的用户

项目亮点

1.图像识别率高

训练后的识别准确率可以达到93%左右

image-20210801204411768

image-20210801204518517

2.采用双服务器进行负载均衡

由于作为学生，经费有限，同时采用两台服务器进行部署项目，让项目有较高的响应速度

identification_of_rice's People

Contributors

magicpwz avatar

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