Font style migration network training method and apparatus, device, and storage medium

An electronic device, comprising:

• one or more processors;
• and
• one or more memories communicatively connected to the one or more processors;
• wherein the one or more memories store instructions that can be executed by the one or more processors, and the one or more processors when executing the instructions implements:
• obtaining a typeface style conversion network, wherein the typeface style conversion network comprises a generative adversarial network;
• obtaining a character image sample set, wherein the character image sample set comprises first character image samples, and each of the first character image samples comprises a first original character image, sampling information of the first original character image, and a first target character image, wherein the first original character image and the sampling information of the first original character image serve as sample features, the first target character image serves as a sample label, and the first original character image and the first target character image in the same character image sample representing the same character;
• and
• training the typeface style conversion network using the character image sample set to obtain a target typeface style conversion network.

A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor, implements:

• obtaining a typeface style conversion network, wherein the typeface style conversion network comprises a generative adversarial network;
• obtaining a character image sample set, wherein the character image sample set comprises first character image samples, and each of the first character image samples comprises a first original character image, sampling information of the first original character image, and a first target character image, wherein the first original character image and the sampling information of the first original character image serve as sample features, the first target character image serves as a sample label, and the first original character image and the first target character image in the same character image sample representing the same character;
• and
• training the typeface style conversion network using the character image sample set to obtain a target typeface style conversion network.