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使用GAN生成汉字字体

License: MIT License

Python 100.00%

w-net-pytorch's Introduction

基于Wnet的字体生成

训练：

python main.py

图例：

python main.py inference

现阶段的训练结果：

原始字体（黑体加粗）protype

目标字体（一个batch里面混合了多种字体）real

生成字体 fake

与原论文的差别

Discriminator中没有使用LayerNorm，而是用了BatchNorm
没有额外再训练一个VGG分类模型，而是用Discriminator替代

TODO:

推理代码完善
添加更多字体
添加对字体支持汉字的检测功能 / 使用mask屏蔽掉不支持的字符对loss的影响
自定义字符集

待添加的一些tricks:

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