基于图形识别技术的植物自动辨识系统

基于图像识别技术的植物自动辨识系统摘要植物资源作为生态系统内部构成要素之一，但应为各种原因导致大规模的植物资源遭遇了不可逆的损坏，应积极引导并推进植物生态资源的保护，以期实现资源循环利用与保护的共同发展。随着人们对于环境生态保护意识的不断加强，人们对于植物的认知逐渐呈现出匮乏的状态，跟不上保护意识的提升，如何提升现阶段人民对于植物的认知了解是一项重要的任务，可以通过多种途径和方法来实现。随着互联网技术的发展和数字化信息技术的普及，人们获取知识和知识的途径随之转移到网络上，尤其是智能手机的不断更新，手机APP的应用层出不穷，智能手机的APP许锡模式已经成为人们必不可少的学习工具。所以手机APP在教学和科研上的应用越来越多，各学校也在关注。因此智能手机APP在用于辅助大学植物学教育和生态教学具有多方面的价值，比如在教学实践和实习教育的过程中，学生可以很方便的通过手机快速的地识别未知植物的种类，在一定程度上减轻了野外教学实践带队教师的植物认知和教学压力：可以很方便的对课程的内容进行拓展，对学生课程知识的巩固以及帮助科研训练提供的帮助。本研究旨在辅助用户提高对植物资源的认知、拓展或教学，通过基于深度学习中的resnet算法设计并实现一个基于微信小程序的植物自动识别程序，以使用户能够快速简洁的对于未知的花朵进行分辨，并输出识别的花朵的相关信息。该系统分为前台模块和后台模块，其中后台采用Python语言编写，使用flask框架，利用先进的ResNet算法实现对花朵物图片的类别进行自动识别。用户可以通过上传花朵的照片，系统就可以快速识别花朵种类，并提供较为详细的花朵信息，包括形态特征、生长习性、分布范围、培育养殖、主要价值等内容。数据库采用mysq1,数据库中存放了102个花朵的相关信息，共有6个属性。该系统将极大地方便植物爱好者、园艺爱好者和生态保护者，让他们更轻松地了解、认知和保护植物世界。通过本研究的实施，预期能够提高植物识别的准确性和效率，促进公众对植物保护和生态环境的关注与认知，推动生态文明建设和可持续发展的进程。关键词：深度学习：resnet:python:mysql:图片识别AbstractPlant resources are one of the internal components of ecosystems.However,due tovarious reasons,a large number of plant resources have been destroyed.It is imperative tovigorously promote the ecological conservation of plant resources to achieve coordinateddevelopment between resource utilization and protection.With the increasing strengthening ofenvironmental awareness,people's understanding of plants is gradually becoming deficient,failing to keep pace with the enhancement of conservation consciousness.Enhancing thecurrent stage of people's understanding of plants is an important task that can be achievedthrough various approaches and methods.With the development of Internet technology andthe popularization of digital information technology.The means by which people acquireknowledge have shifted to the internet,especially with the continuous updates of smartphonesand the proliferation of mobile apps.The app-centric mode of smartphones has become anindispensable learning tool for people.Consequently,the application of mobile apps inteaching and research is increasing,and various schools are paying attention to and adoptingthem.Therefore,the use of smartphone apps to assist university-level botany and ecologyteaching has multifaceted value.For example,during experiments and fieldwork,students caneasily identify plant species through their phones,significantly alleviating the pressure onfieldwork instructors for plant identification and guidance.It also facilitates convenientexpansion of course content,providing significant assistance for students to consolidatecourse knowledge and engage in research training.This study aims to assist users in enhancing their understanding,expanding,or teachingabout plant resources.It proposes the design and implementation of a plant automaticidentification program based on the ResNet algorithm within a WeChat mini-program,enabling users to quickly and succinctly distinguish unknown flowers and output relevantinformation about identified flowers.The system is divided into front-end and back-endmodules,with the back-end de