Acne category identification method and device thereof, computer equipment and storage medium

Abstract

The invention discloses an acne category identification method. The method comprises the following steps: acquiring a target image containing acnes; taking the target image as input of an acne recognition model, the acne recognition model comprising a generator, a discriminator and a classifier, performing feature extraction on the target image through a first convolution layer of the generator to obtain a first feature map, and outputting a generated image having similar features with the target image through an output layer of the generator; performing feature extraction on the generated image through a second convolution layer of the discriminator to obtain a second feature map; wherein a corresponding third convolution layer in the classifier is used for performing feature extraction on the first feature map and the second feature map to obtain a third feature map; and classifying the poxes in the target image through a classification layer of the classifier according to the third feature map to obtain a classification result. The acne category identification method is high in accuracy and has robustness. In addition, the invention further provides an acne category recognition device, computer equipment and a storage medium.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method, device, computer equipment and storage medium for identifying types of acne. Background technique [0002] With the rapid development of mobile communication technology and the improvement of people's living standards, various smart terminals have been widely used in people's daily work and life, making people more and more accustomed to using APP and other software, making beauty selfies, taking pictures and measuring skin There are more and more APP demands for such functions, so many users hope that this APP can automatically analyze the acne situation on the face, and propose targeted skin improvement solutions according to the acne category, but there are limitations. Because the acne category has the characteristics of large intra-class differences and small inter-class differences, it is easily affected by environmental factors, resulting in inaccurate ...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of mobile communication technology and the improvement of people's living standards, various smart terminals have been widely used in people's daily work and life, making people more and more accustomed to using software such as APP, making beauty selfies, taking pictures and measuring skin There are more and more APP demands for such functions, so many users hope that this APP can automatically analyze the acne situation on the face, and propose targeted skin improvement solutions according to the acne category, but there are limitations. The acne category has the characteristics of large intra-class differences and small inter-class differences, and is easily affected by environmental factors, resulting in inaccurate recognition of existing classification models and lack of robustness

Images