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Defect detection method and device based on Internet network, equipment and medium

A defect detection and network technology, applied in the computer field, can solve the problems of low production efficiency, slow detection speed, long labeling and training cycle, etc., and achieve the effect of improving production efficiency, good detection effect, and overcoming the long labeling and training cycle.

Pending Publication Date: 2020-07-28
维库(厦门)信息技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a defect detection method, device, equipment and medium based on the Internet, so as to solve the problem of long labeling and training period and slow detection speed in existing industrial surface defect detection, which lead to low production efficiency question

Method used

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  • Defect detection method and device based on Internet network, equipment and medium
  • Defect detection method and device based on Internet network, equipment and medium
  • Defect detection method and device based on Internet network, equipment and medium

Examples

Experimental program
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Embodiment 1

[0039] This embodiment provides a defect detection method based on the Internet, such as figure 1 As shown, the method is applied to a terminal, and the terminal may be, but not limited to, a PC, a mobile phone, a small workstation, etc., and the detection method includes:

[0040] Step S1, read the image file, mark the defect target in the image file, pack and transmit the marked image file data to the network server; the network server is a GPU cloud server, an AI cloud server, a local area network GPU server or LAN AI server;

[0041] Step S2, receiving the training weight file returned by the network server after performing deep neural network training based on the image file data;

[0042]Step S3, using the inference tool to load the training weight file to infer the image file, and obtain the coordinate position and category information of the image file. When the present invention is actually implemented, the inference tool inference.py in the tensorflow tool can be u...

Embodiment 2

[0050] In this embodiment, a defect detection device based on the Internet is provided, such as figure 2 As shown, the detection device includes an image labeling module, a weight file receiving module and an image reasoning module;

[0051] The image labeling module is used to read the image file, mark the defect target in the image file, and pack and transmit the marked image file data to the network server; the network server is a GPU cloud server and an AI cloud server , LAN GPU server or LAN AI server;

[0052] The weight file receiving module is used to receive the training weight file that the network server returns after carrying out deep neural network training based on the image file data;

[0053] The image reasoning module is used to use a reasoning tool to load the training weight file to reason the image file, and obtain the coordinate position and category information of the image file. When the present invention is actually implemented, the inference tool in...

Embodiment 3

[0062] This embodiment provides an electronic device, such as image 3 As shown, it includes a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, any implementation manner in Embodiment 1 can be realized.

[0063] Since the electronic device introduced in this embodiment is the device used to implement the method in Embodiment 1 of this application, based on the method described in Embodiment 1 of this application, those skilled in the art can understand the electronic device of this embodiment. Specific implementation methods and various variations thereof, so how the electronic device implements the method in the embodiment of the present application will not be described in detail here. As long as a person skilled in the art implements the equipment used by the method in the embodiment of the present application, it all belongs to the protection scope of the present application. ...

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Abstract

The invention provides a defect detection method, device and equipment based on the Internet, and a medium, and the method comprises the steps: S1, reading an image file, marking a defect target in the image file, packaging marked image file data, and transmitting the packaged marked image file data to a network server; S2, receiving a training weight file returned by the network server after deepneural network training based on the image file data; and S3, loading the training weight file by using an inference tool to carry out inference on the image file to obtain the coordinate position and category information of the image file. The method has the advantages that a better training weight model can be obtained through rapid updating, a better detection effect is achieved, and then theproduction efficiency is greatly improved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an Internet-based defect detection method, device, equipment and medium. Background technique [0002] The surface defect detection of industrial products is an important link in the industrial production process. Through defect detection, it is easy to find product and process defects in time and control the quality of products. At present, the surface defect detection technology based on machine vision has been widely used in all aspects of industrial production, which plays an important role in improving production efficiency and ensuring product quality in automated production. [0003] The detection of surface defects based on machine vision includes two main steps. The first is to perform high-definition imaging of the product to ensure that product defects can be displayed on the image, and the second is to analyze and process the image from the imaging device to inform ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/08G06N3/04
CPCG06T7/0004G06N3/08G06T2207/20104G06T2207/20081G06N3/045
Inventor 黄旭东林宇
Owner 维库(厦门)信息技术有限公司
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