Image processing method and device, image processing model training method and device, equipment and medium

Abstract

The invention discloses an image processing method and device, an image processing model training method and device, equipment and a medium, and relates to a computer vision technology in the technical field of artificial intelligence. The image processing method comprises the steps that a to-be-processed image of a reference object and a target image processing model are acquired, the target image processing model is obtained through training based on a sample image of the reference object and a label corresponding to the sample image, and the label corresponding to the sample image is used for indicating a first sample pixel point in the sample image; calling a target image processing model to carry out probability prediction on a representation image of the to-be-processed image to obtain a first probability graph; and obtaining an image of the target object based on the first probability graph. According to the mode, the efficiency of obtaining the target image is relatively high, the target image processing model can relatively accurately identify that the corresponding object category in the image is the pixel point of the target object, the reliability of the first probability graph obtained by calling the target image processing model is relatively high, and the precision of the image of the target object is relatively high.

Description

technical field [0001] The embodiments of the present application relate to the technical field of artificial intelligence, and in particular to an image processing and image processing model training method, device, equipment, and medium. Background technique [0002] With the development of artificial intelligence technology, there are more and more application scenarios for image processing. Wherein, one application scenario is: acquiring an image of a target object according to an image of a reference object, so as to perform tasks such as registration and image labeling using the image of the target object. Wherein, the target object is an object that satisfies the reference condition corresponding to the reference object. For example, meeting the reference condition means that there is no foreign matter attached to the contour and no hole exists inside. [0003] At present, the process of acquiring the image of the target object requires manual participation, the effi...

AI Technical Summary

Problems solved by technology

[0003] At present, the process of obtaining the image of the target object requires manual participation, the efficiency is low, and it is greatly affected by artificial subjective factors, and the accuracy of the obtained image of the target object is poor.

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