Abstract: A method for generating a human-computer interactive abstract image includes: S1: obtaining and preprocessing the original abstract images used as a training dataset B to obtain edge shape feature maps used as a training dataset A; S2: using the training dataset A and the training dataset B as cycle generative objects of a Cycle-GAN model, and training the Cycle-GAN model to capture a mapping relationship between the edge shape feature maps and the original abstract images; S3: obtaining a line shape image drawn by a user; and S4: according to the mapping relationship, intercepting a generative part in the Cycle-GAN model that the dataset B is generated from the dataset A, discarding a cycle generative part and a discrimination part in the Cycle-GAN model, and generating a complete abstract image based on the line shape image to generate the human-computer interactive abstract image.

Abstract: A method for generating a human-computer interactive abstract image includes: S1: obtaining and preprocessing the original abstract images used as a training dataset B to obtain edge shape feature maps used as a training dataset A; S2: using the training dataset A and the training dataset B as cycle generative objects of a Cycle-GAN model, and training the Cycle-GAN model to capture a mapping relationship between the edge shape feature maps and the original abstract images; S3: obtaining a line shape image drawn by a user; and S4: according to the mapping relationship, intercepting a generative part in the Cycle-GAN model that the dataset B is generated from the dataset A, discarding a cycle generative part and a discrimination part in the Cycle-GAN model, and generating a complete abstract image based on the line shape image to generate the human-computer interactive abstract image.