Patent ID: 11928183
Assignee: LEMON INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. An image processing method, comprising:
acquiring a set of training image samples for training an attribute recognition model, wherein the set of training image samples comprises a first subset of training image samples with category labels and a second subset of training image samples without category labels;
training a sample prediction model using the first subset of training image samples with category labels, and predicting categories of the training image samples in the second subset of training image samples without category labels using the trained sample prediction model;
determining a category distribution of the set of training image samples based on the category labels of the first subset of training image samples and the predicted categories of the second subset of training image samples; and
acquiring a new training image sample directionally if the determined category distribution does not conform to a certain category distribution, and updating the set of training image samples by adding the acquired new training image sample to the set of training image samples so that the category distribution of the updated set of training image samples conforms to the certain category distribution, wherein the certain category distribution is a certain number or a certain ratio in the determined category distribution;
wherein the conforming of the determined category distribution to the certain category distribution comprises:
determining a category which does not reach a certain number or a certain ratio in the determined category distribution, which indicates the determined category distribution does not conform to the certain category distribution; and
acquiring the new training image sample of the category that does not reach the certain number or the certain ratio.