Image processing method and device, computer equipment and storage medium

Abstract

The invention discloses an image processing method and device, computer equipment and a storage medium, and the method comprises the steps: carrying out the feature extraction of a received first image, and obtaining a plurality of image original features of the first image; generating an identity identification feature of the first image by using the plurality of image original features, determining a feature distance between each image original feature and the identity identification feature, and determining an optimization parameter according to the feature distance; and updating a loss function output result used for iterative training of the image recognition model by using the optimization parameter, wherein the trained image recognition model is used for performing image recognition processing on a to-be-recognized second image. The device can comprise an original feature extraction module, an identification feature generation module, an optimization parameter determination module and a loss output updating module. Compared with the prior art, the image recognition processing capability of the image recognition model can be remarkably improved, and the image recognition effect is remarkably improved.

Description

technical field [0001] The present invention relates to the technical field of computer vision, and more specifically, the present invention can provide an image processing method, device, computer equipment and storage medium. Background technique [0002] At present, the technology of obtaining an image recognition model by training a neural network has been widely used. However, in order to improve the performance of the image recognition model, the complexity of the neural network structure is increasing, resulting in a decrease in the real-time responsiveness of image processing. Therefore, someone introduced the method of knowledge distillation. The main idea of ​​knowledge distillation is to train a small-scale model to imitate a large-scale model, so that the small-scale model has a certain accuracy and has an uncomplicated network. In this way, neural Image recognition model with low network complexity. Although a small-scale image recognition model with certain p...

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Problems solved by technology

[0003] In order to solve the problem that the image recognition effect based on the traditional image recognition model is difficult to improve, the present invention can provide an image processing method, device, computer equipment and storage medium, so as to further improve the technical purpose of image recognition processing performance, etc.

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