基于Django的鱼类目标识别与分类系统的设计与实现

Design and implementation of fish recognition and classification system based on Django

针对当前对鱼类识别和分类的研究较少的问题,文章设计了一种利用DjangoWEB开发框架实现的对图片中鱼类目标进行定位并进行分类的系统,后端主要使用深度学习模型YOLOv5s目标检测网络进行鱼类目标的定位,使用ResNet50网络进行目标的分类。前端使用HTML, CSS, JQuery, Bootstrap等语言设计进行用户交互和识别结果的展示。经过测试运行,该系统可以很好的对输入图片中的鱼类进行识别与分类,可以应用于实际生产中,能够对渔业发展和鱼类研究起到辅助作用。

Aiming at the problem that there is less research on fish recognition and classification at present, this paper designs a system to locate and classify fish targets in pictures by using Django web development framework. The back end mainly uses the deep learning model yolov5s target detection network to locate fish targets, and uses resnet50 network to classify targets.The front end uses HTML, CSS, j Query, bootstrap and other languages to design user interaction and display the recognition results. After testing and running, the system can identify and classify the fish in the input picture, can be applied to actual production, and can play an auxiliary role in fishery development and fish research.