How can we just transfer image style rather than get similar image? about pixel2style2pixel

[yuval-alaluf]

Hi @maxrumi ,
A few questions:

1. Are you still training with no labeled data?
2. How do the results look on the train set?

Since it appears that you are using a different StyleGAN for a different task, using our toonify parameter settings as is probably will not lead to optimal results right from the start. You should play around a bit more with the parameters settings.
In any case, please provide a few more details about how you are training and maybe a few more results on the train set and I will hopefully be able to provide you with more concrete recommendations.

[maxrumi]

1,Are you still training with no labeled data?
Answer: Our psp model trained on paired data, the source domain dataset is ffhq dataset, and the target domain dataset is transfered ffhq dataset(by using other style transfer method), and our stylegan2 is trained on transfered ffhq dataset too.
2,How do the results look on the train set?
Answer: The picture showed on page top is the psp results on train data.

So, we just want to know how to change the parameter setting to make the psp results have same shape and texture just like the input data, and just transfer the input to some kind of cartoon style(like cycle gan).
Can you give us some parameter setting sample, suppose you just want to transfer the input image to cartoon style and don't want to change it's shape and texture.
We want to know how to change these parameters setting, thanks a lot:
--lpips_lambda=0.08
--l2_lambda=0.001
--lpips_lambda_crop=0.8
--l2_lambda_crop=0.01
--id_lambda=1
--w_norm_lambda=0.005

[yuval-alaluf]

While I don't know exactly what loss settings will work best for you, I can try giving you some recommendations:

1. Please note that it seems like you copied these parameter settings from the frontalization task, which is not really what you want in your task. You should consider starting with the parameters used in the toonification task (the lambda values are provided in the README).
2. With that said, our toonification training is done with no paired data, so you will most likely need to play around some more with the loss settings, but this should be a good starting point.

Does this help answer your question?

[yuval-alaluf]

Closing due to inactivity

[goldwater668]

我们的psp模型是在paired data上训练的，源域数据集是ffhq数据集，目标域数据集是transferred ffhq数据集（通过其他风格迁移方法），我们的stylegan2也是在transferred ffhq数据集上训练的。

@maxrumi
Hello, how did you generate your paired data set? Is this effect obtained by directly using the psp network model to train the paired data? Can you tell me about the implementation process?