Method and device for identifying style of commodity

Abstract

The present application provides a method and device for recognizing the style of a commodity. The method includes: obtaining sample pictures of commodities, processing the sample pictures according to a preset method to form a sample training set; initializing parameters of a preset deep convolutional neural network, and storing the sample pictures in the sample training set in the sample training set. The picture style recognition model is obtained by training in the deep convolutional neural network after the above parameters are initialized; the picture style recognition model is used to identify the picture of the commodity to be identified to obtain the probability vector that the picture of the commodity to be identified belongs to different style types, and the probability The sum of the probability values ​​in the vector is 1; the style type of the commodity to be identified is identified according to the set commodity style judgment rules and the probability vector. By using the technical solutions provided by the embodiments of the present application, automatic and accurate identification of commodity style types can be realized, the accuracy and efficiency of commodity style identification can be improved, and the work intensity of operators can be reduced.

Description

technical field [0001] The present application belongs to the technical field of image information processing, and in particular relates to a method and device for recognizing the style of commodities. Background technique [0002] With the development of the Internet consumption era, consumers can choose their favorite products online, which greatly facilitates users to shop. For example, consumers can choose their favorite product types through the product pictures displayed by online merchants. [0003] Generally, when consumers purchase goods online, they are often influenced by various conceptual factors, such as brand, price, color, style, etc. These conceptual factors can generally be manually set by the merchant on the service operation platform. Among the many conceptual factors, some factors such as clothing brand, price, color, etc. are usually easy to define, and generally have relatively clear and standardized boundaries for distinction. For some other commodi...

AI Technical Summary

Problems solved by technology

However, both merchants and consumers will often have large deviations due to subjective factors when judging the style type of the product to be filled in. Therefore, concepts such as product style type often cause confusion and ambiguity among merchants and consumers. Affect the style classification of merchant products or the selection of consumer product styles, reducing the effect of product marketing

This not only affects the transaction conversion rate, but also reduces the user experience

At the same time, due to the wide variety of online products, generally the amount of information involved in the processing of product styles is relatively large, which will also consume a lot of working time and labor of operators

[0004] In the prior art, the use of manual subjective judgment to identify product styles often leads to large differences in product style recognition results, making it difficult to perform accurate, reasonable and unified style recognition

At the same time, the judgment method of manual recognition has also increased the work intensity of the operator's commodity style recognition and reduced the efficiency of commodity style recognition

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