Image classification model training method and device, electronic equipment and storage medium

Abstract

The invention discloses an image classification model training method and device, electronic equipment and a storage medium. An image classification model comprises a plurality of image classificationmodules, each image classification module corresponds to different image classification scenes, and a training data set is acquired; feature extraction is performed on each image sample classification label to obtain a feature image corresponding to each image sample; taking the feature image corresponding to each image sample as input data, taking the sample classification label corresponding toeach image sample as output data, and respectively training the plurality of image classification modules to obtain a plurality of trained image classification modules; and obtaining a trained imageclassification model based on the plurality of trained image classification modules. Since each trained image classification module classifies each image classification scene, each image classification module in the trained image classification model can accurately and efficiently classify the image corresponding to each image classification scene.

Description

technical field [0001] The present application relates to the technical field of image classification, and more specifically, to a training method, device, electronic equipment and storage medium for an image classification model. Background technique [0002] When a user takes pictures, when the number of pictures taken is huge, in order to facilitate management, it is necessary to classify the pictures taken. The usual method is for the user to manually classify the pictures one by one, resulting in low picture classification efficiency and accuracy. Contents of the invention [0003] In view of the above problems, the present application proposes a training method, device, electronic equipment, and storage medium for an image classification model, which can improve image classification efficiency and classification accuracy. [0004] In the first aspect, the embodiment of the present application provides a training method for an image classification model, the image cla...

AI Technical Summary

Problems solved by technology

[0002] When the user takes pictures, when the number of pictures taken is huge, in order to facilitate management, it is necessary to classify the pictures taken. The usual method is to manually classify the pictures one by one by the user, resulting in low efficiency and accuracy of picture classification

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