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import numpy as np | |
import torch | |
from huggan.pytorch.lightweight_gan.lighweight_gan import LightWeightGAN | |
def load_model(model_name='ceyda/butterfly_cropped_uniq1K_512', model_version=None): | |
gan = LightWeightGAN.from_pretrained(model_name, version=model_version) | |
gan.eval() | |
return gan | |
def generate(gan, batch_size=1): | |
with torch.no_grad(): | |
ims = gan.G(torch.randn(batch_size, gan.latent_dim)).clamp_(0.0, 1.0) * 255 | |
ims = ims.permute(0,2,3,1).detach().cpu().numpy().astype(np.uint8) | |
return ims |