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| import numpy as np | |
| import torch | |
| from huggan.pytorch.lightweight_gan import LightweightGAN | |
| def carga_modelo(model_name='ceyda/butterfly_cropped_uniq1K_512',model_version=None): | |
| gan=LightweightGAN.from_pretrained(model_name,version=model_version) | |
| gan.eval() | |
| return gan | |
| def genera(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).deatch().cpu().numpy().astype(np.unit8) | |
| return ims |