A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

Awesome Pretrained StyleGAN2

A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

Note the readme is a bit out of date, there are more models linked in the issues.

If you have a publically accessible model which you know of, or would like to share please see the contributing section. Hint: the simplest way to submit a model is to fill in this form.

Table of Contents

car (config-e)

car (config-f)

cat

church

faces (FFHQ config-e)

faces (FFHQ config-e 256x256)

faces (FFHQ config-f)

faces (FFHQ config-f 512x512)

horse

Imagenet

WikiArt

Anime portraits

microscope images

wildlife

modern art

trypophobia

Abstract art

Maps

cakes

CIFAR 10

CIFAR 100

faces (FFHQ slim 256x256)

obama

grumpy cat

panda

fursona

my little pony

painting faces

ukiyoe faces

beetles

textures

more abstract art

flowers

Doors

floor plans

figure drawings

Notes

  • The configuration "slim" refers to the reduced feature map model used in the Karras limited data and Zhao data efficient papers.
  • Each row in the sample grids above use a different level of trunction: 0.25, 0.5, 0.75, 1 from top to bottom.
  • Style mixing figure and interpolation video generated using truncation of 0.75

Contributing

TLDR: You can either edit the models.json file or fill out this form.

This readme is automatically generated using Jinja, please do not try and edit it directly. Information about the models is stored in models.json please add your model to this file. Preview images are generated automatically and the process is used to test the link so please only edit the json file.

Comments
  • 256x256 FFHQ StyleGAN-V2

    256x256 FFHQ StyleGAN-V2

    Hi, I was wondering if you're aware of a pretrained 256x256 FFHQ StyleGANv2 model available? I think it would be really be helpful for tasks where the full model is too big to start with.

  • gen-art-project project

    gen-art-project project

    new edition from @StuartWaller

    https://github.com/StuartWaller/gen-art-project

    model https://drive.google.com/file/d/1AUVmc1wYSJ01JFvqGa4Bb0OERLdA0fXg/view?usp=sharing

  • generated images using the provided pretrained model contain colorful specks.???

    generated images using the provided pretrained model contain colorful specks.???

    the generated images using the provided pretrained model in these links contain colorful specks. For example, dataset: faces (FFHQ config-f). Anybody knows what's wrong with this? 2VUHC27r9J

  • Add architecture model

    Add architecture model

    From Gabriel Syme on the TPU podcast discord:

    Hello everyone! Given that I'm still struggling to get colab TPUs going, and I don't think I'll be spending more credits on vastai for this right now, I decided to share my Stylegan2-ada-pytorch model trained on about 3,000 real and stylistic images of architectural buildings, across 18 diverse architectural practices. Class (practice) information was not used during training, this is a 512x512 model and has been trained for a bit over 3kimg. I will eventually work on building a larger data set in the future across more practices but for now this is it.

    The model isn't as good as I would like it to be, but it can still generate quite nice images. Maybe someone finds a cool seed!

    pkl file: https://storage.googleapis.com/pretrained-stylegan2/stylegan-ada-pytorch-buildings-3kimg.pkl dataset: https://storage.googleapis.com/pretrained-stylegan2/Buildings.rar

    This is a model from the new stylegan-ada-pytorch repo

  • About blending 'ffhq' model and 'anime face' model

    About blending 'ffhq' model and 'anime face' model

    Hi ,Really thanks for your work. From your blog I notice that blending needs a base model and a fine-tuned model from that. So I try it and, I want to know that if there is a fine-tuned model for Anime Face in stylegan2 ? The Aaron Gokaslan's anime mode is not fine-tuned and can't be used for blending with ffhq. So if it's possible to use a 512-f-ffhq model fine-tuning an anime-face dataset so that the new anime face model can be used for blending?

  • How to run the script?

    How to run the script?

    Can anyone tell me how to run the script to generate a new image? I've already downloaded the weights. How to create new images using GAN with the script?

  • Getting permissions to use in professional work

    Getting permissions to use in professional work

    Hi,

    Firstly thanks for the repo, it is indeed awesome :)

    A couple of questions:

    • do you have a contact for @krrrl, author of the lifedrawings dataset? I'm struggling to reach them.

    • do you have any thoughts on ethical issues around using the lifedrawings dataset in 'professional' work? I'm a musician working on an audiovisual commission (aimed much more at a musical audience than a visual art audience) and I REALLY want to use that dataset for one sub-piece in it. I would be significantly altering the appearance of the images, but still using them without the author's permission feels a bit wrong. I was wondering if you knew of their intention in making the dataset publicly available, if there was any intention behind it all.

    Best wishes,

    Mark

  • Add mapdreamer model

    Add mapdreamer model

    Add model trained on maps

    See:

    • https://twitter.com/tjukanov/status/1270980969210826752
    • https://medium.com/@tjukanov/mapdreamer-ai-cartography-4f2f6a40ef55
  • add ffhq 256 config e model

    add ffhq 256 config e model

    Trained a 256x256 config-e model on the FFHQ dataset (see #2)

    Training was done on Colab, so in a few sessions using 1 GPU.

    pkl taken at a FID of 11.2. In theory it should be much better than this, but I found the default learning rate to be slightly unstable, and dropping any lower and progress was very slow.

    fakes003810

    ffhq-256-e-fid

  • I resume training and init fakes has wrong colours

    I resume training and init fakes has wrong colours

    Hi, i want to resume training with car config-f, when I started the training after the first tick, if i preview the init fakes they have messed up colours. Is this normal or is there some conflict with a colour space I can choose somehow? Thanks

  • Impressionist landscape painting

    Impressionist landscape painting

    !gdown --id 1AHKufJ5o4dQFThFN0A-pJRRC2lzxEH2J image

    Source: https://towardsdatascience.com/ganscapes-using-ai-to-create-new-impressionist-paintings-d6af1cf94c56

  • Cannot process pkl files using legacy.load_network_pkl

    Cannot process pkl files using legacy.load_network_pkl

    I am running a notebook called "structured dreaming". The notebook loads the pkl file using this:

    print('Loading networks from "%s"...' % network_pkl) device = torch.device('cuda') with dnnlib.util.open_url(network_pkl) as f: G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore

    For network_pkl, this works:

    https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/ffhq.pkl'

    but when I try one of your pkl files, for instance:

    https://github.com/justinpinkney/awesome-pretrained-stylegan2#faces-FFHQ-config-f-512x512 (after downloading it first and then putting it into Gdrive), I get:

    `Loading networks from "/content/drive/MyDrive/pretrained/ffhq-512-avg-tpurun1.pkl"...


    ValueError Traceback (most recent call last)

    in () 5 device = torch.device('cuda') 6 with dnnlib.util.open_url(network_pkl) as f: ----> 7 G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore 8 # 9 # Read the data from the file

    1 frames

    /content/stylegan2-ada-pytorch/legacy.py in convert_tf_generator(tf_G) 153 unknown_kwargs = list(set(tf_kwargs.keys()) - known_kwargs) 154 if len(unknown_kwargs) > 0: --> 155 raise ValueError('Unknown TensorFlow kwarg', unknown_kwargs[0]) 156 157 # Collect params.

    ValueError: ('Unknown TensorFlow kwarg', 'resolution_h')

    `

    Do you have any suggestions? Your list of pretrained networks is great!

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