Garment classification and collocation recommending method and garment classification and collocation recommending system based on deep convolution neural network

Abstract

The invention proposes a garment classification and collocation recommending method and a garment classification and collocation recommending system based on a deep convolution neural network. The method comprises the following steps: adding batch-normalized and improved inception structures, adding a redundant classifier to improve an original GoogleNet convolution neural network, and extracting the features of garment images to get the classification result of the garment images; performing image augmentation on a collocation library training set in multiple ways, distorting and turning the garment images and transforming the color space of the garment images, and training an improved GoogleNet convolution neural network classification model; and looking for similar items and collocations thereof in a suit library, generating identity information for each garment image, comparing the identity information to get similar images, and recommending garment collocations according to the gender, style and function information corresponding to the garment images. Corresponding garment collocation advices can be given to consumers according to input garment images. The method and the system have the advantages of high speed and high precision.

Description

technical field [0001] The invention relates to the technical field of image classification, in particular to a clothing classification and matching recommendation method and system based on a deep convolutional neural network. Background technique [0002] Image recognition is a technology that acquires, analyzes, processes, and recognizes images in the field of computer vision to automatically obtain the main features of the object of interest in the target image. It is very important in many research fields such as object positioning, object classification, and gesture recognition. effect. In the industrial world, it also has excellent performance and extremely high commercial value in many application backgrounds such as face recognition, product recommendation, target tracking, and motion detection. In the field of artificial intelligence, such as unmanned driving, fully automatic robots and other fields, there are also good prospects for development. In the processin...

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