Target detection method and device, electronic equipment and storage medium

Abstract

The invention discloses a target detection method and device, electronic equipment and a storage medium, and the specific implementation scheme comprises the steps: responding to collection processing, and obtaining a to-be-processed picture containing a target text; inputting the to-be-processed picture into a pre-trained target detection network to obtain at least two candidate detection boxes containing the target text and a part of text in the target text, the part of text being a text region completely or partially overlapped with the target text and containing at least one row of text sequences; and performing operation according to the overlapping region of the at least two candidate detection boxes to obtain a classification index, and performing classification screening on the atleast two candidate detection boxes according to the classification index to remove the candidate detection boxes containing part of the text in the target text to obtain a target detection box. According to the invention, the accuracy of target detection can be improved.

Description

technical field [0001] The present application relates to the technical field of computer vision, and in particular to a target detection method, device, electronic equipment and storage medium. Background technique [0002] As electronic devices such as portable devices and mobile terminals become more intelligent than before, the analysis capability of the chip is stronger. Computer vision technology can be used to efficiently analyze graphic information, video information, etc., and to analyze graphic information, video information, etc. Wait for the target object to be detected. [0003] Taking the application scenario of layout analysis as an example, in the pictures collected during the layout analysis process, most of the target objects are text information. Since the texture features of text information lack shape information, compared with such as video information, it is not easy to identify Therefore, the accuracy rate of target detection for text information is ...

AI Technical Summary

Problems solved by technology

[0003] Taking the application scenario of layout analysis as an example, in the pictures collected during the layout analysis process, most of the target objects are text information. Since the texture features of text information lack shape information, compared with such as video information, it is not easy to identify Therefore, the accuracy rate of target detection for text information is low, which ultimately affects the accuracy rate of layout analysis. In related technologies, there is no effective solution for how to improve the target detection accuracy rate of text information. Program

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