Picture-based text generation method and device

Abstract

The invention provides a picture-based text generation method and device, and the method comprises the steps: determining at least one target vertical field, and obtaining the picture content information corresponding to a to-be-edited picture and the picture classification information corresponding to the to-be-edited picture according to the target vertical field to which the to-be-edited picture belongs; generating picture accurate information corresponding to the to-be-edited picture according to the picture content information corresponding to the to-be-edited picture and the picture classification information corresponding to the to-be-edited picture; and generating a picture editing text corresponding to the to-be-edited picture through the text generation model according to the picture accurate information corresponding to the to-be-edited picture. According to the method, the picture accurate information corresponding to the to-be-edited picture is acquired for the target vertical field, and the picture editing text with professional reference value is edited in combination with the target vertical field, so that a user is assisted in efficiently and accurately completingprofessional document editing and writing work in the field.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular to an image-based text generation method, device, computing device, and computer-readable storage medium. Background technique [0002] When users create articles such as writing, such as news writing, they need to convert the picture information taken on the spot into text. This process requires users to have high observation ability and prior knowledge. If the picture information in the picture cannot be accurately identified , there will be errors in the user's understanding of the picture, and it will affect the accuracy of the article expression and writing efficiency. In the existing technology, the main ways to convert picture information into text include manual description and open-domain picture recognition and text conversion. Among them, manual description means that users manually edit the content of pictures by observing pictures, and open...

AI Technical Summary

Problems solved by technology

[0002] When users create articles such as writing, such as news writing, they need to convert the picture information taken on the spot into text. This process requires users to have high observation ability and prior knowledge. If the picture information in the picture cannot be accurately identified , there will be errors in the user's understanding of the picture, and it will affect the accuracy of the article expression and writing efficiency

In the existing technology, the main ways to convert picture information into text include manual description and open-domain picture recognition and text conversion. Among them, manual description means that users manually edit the content of pictures by observing pictures, and open-domain pictures Recognition and text conversion means to list the content in the picture for the user to use by detecting the target of the picture. However, the problem with the existing technology is that the manual description requires the user to have a lot of professional knowledge, and the accuracy is difficult to guarantee. The image recognition and text conversion in the open domain is only a simple list of targets, and cannot return accurate image information for a certain vertical field. At the same time, because the returned text content is a simple list of target names in the image, it cannot be directly used by users. less efficient

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