使用CycleGAN网络模型实现无匹配数据的风格迁移，将真实人脸图片转换为漫画头像，主要参考了这篇博客。
| 名称 | 版本 |
|---|---|
| GPU | GeForce GTX 1080 Ti |
| CUDA | 9.0 |
| CUDNN | 7.1.4 |
| Python | 3.6.4 |
| tensorflow-gpu | 1.9.0 |
| torch | 1.1.0 |
| torchvision | 0.3.0 |
| face-alignment | 1.0.0 |
| dlib | 19.17.0 |
| numpy | 1.18.4 |
| opencv-python | 4.1.0.25 |
train.py进行模型的训练
test.py测试模型的转换效果
junyanz/CycleGAN仓库
J. Zhu, T. Park, P. Isola and A. A. Efros, "Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks," 2017 IEEE International Conference on Computer Vision (ICCV), Venice, 2017, pp. 2242-2251, doi: 10.1109/ICCV.2017.244.
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