基于卷积神经网络的宠物识别

Pet Recognition Based on Convolutional Neural Network

宠物在人们的生活当中,已经变成了人们日常生活不可分割的一部分,越来越多的人会去饲养宠物,伴随着人们智能化的不断提升,智能家居的全面发展,也对于宠物的管理提出了更高的要求,所以对于宠物识别技术的研究也有着很高的实际意义。该文提出一种基于神经网络的实时宠物识别,技术路线,使用Opencv,Pycharm,Python,采用神经网络的宠物面部监测和分类功能。对实时采集到的宠物图片进行处理,与训练好的模型进行比对,克服了以前宠物识别效率低下,成功率低等问题。

Pets have become an integral part of people’s daily life.More and more people will raise pets.With the continuous improvement of people’s intelligence and the comprehensive development of smart home,pet management also puts forward higher requirements,so the research of pet recognition technology has high practical significance.This paper presents a real-time pet recognition technology based on neural network,which uses Opencv,Pycharm,Python and neural network to monitor and classify pet faces.The PET images collected in real time are processed and compared with the trained models,which overcomes the problems of low efficiency and low success rate of pet recognition in the past.