Product defect detection data processing method, device, system and equipment

Abstract

The invention relates to a product defect detection data processing method, device, system and equipment. The method comprises the steps of receiving a product defect detection model generation request, wherein the product defect detection model generation request carries model training parameters, the model training parameters are determined according to parameter configuration operation of a user, and the model training parameters comprise at least one of defect learning categories or training picture information; obtaining a corresponding training picture according to the model training parameters and obtaining a defect category corresponding to the training picture to obtain a training sample; and carrying out model training according to the training sample to generate a target defectdetection model, the target defect detection model being used for carrying out defect detection on the to-be-detected product according to a to-be-detected picture corresponding to the to-be-detectedproduct to obtain a defect detection result of the to-be-detected product. The model obtained by the method is high in product defect detection efficiency and high in flexibility.

Description

technical field [0001] The present application relates to the field of product inspection, in particular to a data processing method, device, system and equipment for product defect inspection. Background technique [0002] Product quality is one of the most important production indicators in the manufacturing industry. In order to ensure product quality, defect detection of products has become an indispensable process in the production process. For example, in the camera production workshop, it is necessary to sort out the defective cameras produced during the production process, so as to prevent the defective cameras from flowing directly into the next process. [0003] At present, when performing defect detection on products, technical workers are relied on for visual recognition. Manual recognition has factors such as individual differences in understanding of defect detection standards and fatigue, resulting in low defect recognition efficiency. Contents of the invent...

AI Technical Summary

Problems solved by technology

[0004] Based on this, it is necessary to provide a product defect detection data processing method, device, system and equipment for the above-mentioned problem of low defect recognition efficiency

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