The results aren't coming out well about dualstylegan HOT 4 CLOSED

I think this is not a problem of the code.
It is the problem of package installtion.
You can search on Google with the key words like Your compiler (c++) is not compatible with the compiler Pytorch was built with for this platform to see if there are solutions.

For example, I found related issues here
rosinality/stylegan2-pytorch#220
NVIDIA/apex#974

from dualstylegan.

Well, I solved the package installation problem as you told me, but the results keep coming out like the picture above.

Below is the output of the terminal after solving the package installation

(dualstylegan_env) [lucass@nipa2019-0211 DualStyleGAN]$ python style_transfer.py
Load options
align_face: False
content: ./data/content/081680.jpg
data_path: ./data/
exstyle_name: exstyle_code.npy
model_name: generator.pt
model_path: ./checkpoint/
name: cartoon_transfer
output_path: ./output/
preserve_color: False
style: cartoon
style_id: 1
truncation: 0.75
weight: [0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]

Loading pSp from checkpoint: ./checkpoint/encoder.pt
Load models successfully!
Generate images successfully!
Save images successfully!
(dualstylegan_env) [lucass@nipa2019-0211 DualStyleGAN]$ gcc --version
gcc (GCC) 8.3.1 20190311 (Red Hat 8.3.1-3)
Copyright (C) 2018 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

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I'm not sure what the problem is.
The second image is a pure reconstructed image by pSp encoder and StyleGAN, which is not related to DualStyleGAN.
Can you successfully generate images by StyleGAN in https://github.com/rosinality/stylegan2-pytorch?
If not, I think there is still something wrong with your enironment/model.

Maybe you can try style transfer with DualStyleGAN on the colab platform:
http://colab.research.google.com/github/williamyang1991/DualStyleGAN/blob/master/notebooks/inference_playground.ipynb

from dualstylegan.

This probably too late but I got the same issue as you when tried running the demo. The code executed successfully, but the returned images are just wrong. I am using pytorch 1.12 and cuda 11.3. The problem is probably with the pytorch native version of fused_leaky_relu, which seemed to return very small number. After replacing the function fused_leaky_relu with what this thread said:

rosinality/stylegan2-pytorch#81

I was able to get the ouput correctly. I think it has something to do with cuda version mismatch, since cuda 10 seemed to work, but anyway that was what helped solve my problem.

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