Training method and device of image recognition model

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a training method and device for an image recognition model, and the method comprises the steps: obtaining to-be-recognized images collected by image collection equipment; for each to-be-identified image, based on a trained coordinate detection model, taking any to-be-identified image as an input parameter, identifying coordinates of a to-be-identified object in the to-be-identified image, and obtaining position information of the to-be-identified object; adding each to-be-identified image, the corresponding position information and a preset object label into a training sample set, the object label being determined based on an image name of a to-be-identified object included in the to-be-identified image; and training an image recognition model based on the training sample set, and obtaining the trained image recognition model, so that the to-be-recognized image is standardized through the trainedcoordinate detection model, the image labeling efficiency can be improved, and the training efficiency of the image recognition model is improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to a training method and device for an image recognition model. Background technique [0002] In recent years, with the popularization of mobile payment, more and more unmanned mechanical retail containers are installed in areas with heavy traffic, such as stations, office buildings, shopping malls, etc., see figure 1 As shown, it is a schematic diagram of a mechanical retail container in the prior art. However, the mechanical retail container has the problems of occupying a large area and the types of goods sold are limited. Therefore, how to reduce the floor area of ​​the retail container and expand the sales volume The range of commodity categories has become an urgent problem to be solved. [0003] With the development of artificial intelligence (Artificial Intelligence, AI) technology, in order to solve the above problems, many manufacturers have intr...

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Problems solved by technology

[0002] In recent years, with the popularization of mobile payment, more and more unmanned mechanical retail containers are set up in areas with heavy traffic, such as stations, office buildings, shopping malls, etc., see figure 1 As shown, it is a schematic diagram of a mechanical retail container in the prior art. However, the mechanical retail container has the problems of occupying a large area and the types of goods sold are limited. Therefore, how to reduce the floor space of the retail container and expand the sales volume The range of commodity categories has become an urgent problem to be solved

[0003] With the development of artificial intelligence (Artificial Intelligence, AI) technology, in order to solve the above problems, many manufacturers have introduced AI smart containers that use artificial intelligence computer vision technology to realize automatic product identification, see figure 2 As shown, it is a schematic diagram of an AI smart container in the prior art. The AI ​​smart container is based on an image recognition model to complete the identification of commodities. However, when training the image recognition model in the prior art, it is necessary to manually collect the Therefore, the time-consuming of this model training method in the prior art is very long, and the training efficiency of the image recognition model is not high

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