Primitive drawing checking method and system based on deep learning

A deep learning and verification technology, applied in the fields of instruments, biological neural network models, character and pattern recognition, etc., can solve problems such as time-consuming and laborious, and achieve the effect of avoiding unreasonable situations and improving quality.

Pending Publication Date: 2020-04-28
STATE GRID LIAONING ELECTRIC POWER RES INST +2
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Problems solved by technology

[0005] Aiming at the problems existing in the above prior art, the present invention proposes a method and system for checking drawings of primitives based on deep learning, the purpose of which is to solve the time-consuming and laborious process of engineering designers in the process of checking drawings in the prior art. problems, thereby improving work efficiency

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  • Primitive drawing checking method and system based on deep learning
  • Primitive drawing checking method and system based on deep learning

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Embodiment Construction

[0034] The implementation mode of the present invention is illustrated by specific specific examples below, and those who are familiar with this technology can easily understand other advantages and effects of the present invention from the contents disclosed in this description. Obviously, the described embodiments are a part of the present invention. , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0035] figure 1 It is a flow chart of a deep learning-based primitive drawing verification method provided in the embodiment of the present invention, see figure 1 , including the following steps:

[0036] S1. Obtain the picture file of the graphics element drawing to be checked;

[0037] S2. Cut the picture file to be checked into schematic diagram and text information according to the propor...

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Abstract

The invention belongs to the technical field of artificial intelligence and image processing, and particularly relates to a primitive drawing checking method and system based on deep learning. The method comprises the steps of obtaining a to-be-checked primitive drawing picture file; cutting the to-be-checked picture file into a schematic diagram and a text information part according to a proportion, and recording corresponding information; inputting the text information picture part into a pre-constructed text recognition model to obtain detected text information; and checking whether the corresponding schematic diagram is reasonable or not by adopting an image processing method according to the text information, and outputting result information. According to the method, the primitive drawing picture file is checked, so that the unreasonable situation after drawing is avoided, the engineering design quality is improved, and a guarantee is provided for subsequent work.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and image processing, and in particular relates to a method and system for checking primitive drawings based on deep learning. Background technique [0002] The traditional checking of engineering drawings is carried out by "experience", which is a cumbersome task for engineering designers. However, this process is usually time-consuming and labor-intensive, and the verification results are greatly affected by subjective factors, and no quantitative indicators have been formed. [0003] The concept of deep learning was first proposed by Professor Hinton of the University of Toronto in Canada in 2006. In the next 10 years, deep learning has continuously made breakthroughs in many fields such as computer vision. Deep learning pre-defines calculation rules, transfers data from the input layer to the output layer through a hierarchical network structure, and automatically learns the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/20G06N3/02
CPCG06N3/02G06V30/422G06V10/22
Inventor 赵东旭陈刚耿宝宏栗罡李胜川赵义松包蕊郎福成蒋苏南张琳范永刚程辉王飞鸣李惺宇金元元吴晗序王祎菲邰晓雪赵丹王雅楠韩佳妤
Owner STATE GRID LIAONING ELECTRIC POWER RES INST
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