一个基于PaddlePaddle深度学习框架的口罩佩戴图像识别模型

A Mask Wearing Image Recognition Model Based on PaddlePaddle Deep Learning Framework

后疫情时代的到来,口罩佩戴已经成为学校、商场、食堂等各公共场所的常规防控手段。为提高防控效率和准确率,研究搭建一个基于百度飞浆深度学习平台的口罩佩戴图像识别模型。该文先收集口罩佩戴人像图片样本,采用卷积神经网络VGG算法训练模型,实现判断该静态人像是否规范佩戴口罩的检测功能,并对判断结果的准确性进行了评估。实验结果表明,VGG卷积神经网络对判断人像是否佩戴口罩,具有比较快速、准确的识别能力,具备广泛应用的价值。

With the advent of the post epidemic era,mask wearing has become a routine means of prevention and control in schools,shopping malls,canteens and other public places.In order to improve the efficiency and accuracy of prevention and control,a mask wearing image recognition model based on Baidu flying slurry deep learning platform is studied and built.Firstly,this paper collects the picture samples of the mask wearing portrait,uses the convolutional neural network VGG algorithm to train the model,realizes the detection function of judging whether the static portrait wears the mask normally,and evaluates the accuracy of the judgment results.The experimental results show that VGG convolutional neural network has a relatively fast and accurate recognition ability to judge whether the portrait wears a mask,and has the value of wide application.