Comments (5)
These are a bit tricky to release since they were trained on some proprietary images and I'm not sure about the legalities involved. I'll ask but it might take some time. If you just want to use them on your own images, our replicate version has them set up.
from stylegan-nada.
Thank you for your reply.
- Could I knoe how you train those results?
Is it something likes this? (only change target_class)
python train.py --size 1024
--batch 2
--n_sample 4
--output_dir /path/to/output/dir
--lr 0.002
--frozen_gen_ckpt /path/to/stylegan2-ffhq-config-f.pt
--iter 301
--source_class "photo"
--target_class "shrek"
--auto_layer_k 18
--auto_layer_iters 1
--auto_layer_batch 8
--output_interval 50
--clip_models "ViT-B/32" "ViT-B/16"
--clip_model_weights 1.0 1.0
--mixing 0.0
--save_interval 150
-
what is diiferent between 'image' in red and 'text' in red in the following figure?
-
You used ffhq pretrained Restyle instead of training it for each face domain, am I right?
from stylegan-nada.
The examples under the image block used a target image (i.e. using the --style_img_dir /path/to/img/dir
option. I can't supply the images since they were shamelessly taken from the internet and I do not own the rights. The images under the text block used zero-shot text targeting.
Differences between your command and what we used for the image-based examples are just in the number of training iterations (and the need for style image targets):
Shrek: --iter 601
Witcher: --iter 401
Joker: --iter 601
Thanos --iter 601
For the text target ones - those should be available in our drive, and the parameters for most of them are in our paper's supplementary, If you want one that isn't in the drive / want me to look up the specific commands to train them, let me know and I'll have a look.
from stylegan-nada.
Regarding ReStyle - yes, we used the pre-trained FFHQ versions. ReStyle-e4e (and e4e itself) typically have better results than the pSp variants. You can also have a look at HyperStyle which works with NADA models as well.
from stylegan-nada.
Thank you for your detailed reply.
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Related Issues (20)
- Gradio related inquiry HOT 1
- Question about specifying the style HOT 4
- About the bug when running Demo HOT 7
- Style transfer of "White Walker" HOT 1
- How to use style mapper HOT 1
- A specific domain changes in global direction HOT 1
- Sample Code for retraining OASIS HOT 2
- Control eye position HOT 2
- Question about gradient of transforms HOT 2
- Unexpexted output when providing randomly sampled latents HOT 1
- clip_model_weights and auto_layer_k HOT 3
- Nvidia error when running docker-compose up HOT 1
- Cross-domain image interpolation HOT 3
- When choose other than 'ffhq' for source model type
- i want to add eyeglasses boundary from stylegan ffhq . HOT 1
- unauthorized: authentication required on docker compose up
- Ajout de nouvelle couche dans le modèle de stylegan_nada(transfert learning)
- image2image
- Migration with a specific content image HOT 5
- Performance Metric Missing HOT 2
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