Projected GAN

• https://arxiv.org/abs/2111.01007

• https://github.com/autonomousvision/projected_gan

• weights

  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/art_painting.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/church.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/bedroom.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/cityscapes.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/clevr.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/ffhq.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/flowers.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/landscape.pkl
  • https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/pokemon.pkl

import pathlib
import pickle
import sys

sys.path.insert(0, '~/codes/clones/projected_gan')

import dnnlib
import legacy

paths = sorted(pathlib.Path('orig'))

out_dir = pathlib.Path('models')
out_dir.mkdir()

for path in paths:
    with dnnlib.util.open_url(path.as_posix()) as f:
        model = legacy.load_network_pkl(f)['G_ema'].to('cpu')
    ckpt = {'G_ema': model}
    outpath = out_dir / path.name
    with open(outpath, 'wb') as f:
        pickle.dump(ckpt, f)