| import torch | |
| from configs import global_config, paths_config | |
| from scripts.latent_creators.base_latent_creator import BaseLatentCreator | |
| from training.projectors import w_projector | |
| class SG2LatentCreator(BaseLatentCreator): | |
| def __init__(self, use_wandb=False, projection_steps=600): | |
| super().__init__(paths_config.sg2_results_keyword, use_wandb=use_wandb) | |
| self.projection_steps = projection_steps | |
| def run_projection(self, fname, image): | |
| image = torch.squeeze((image.to(global_config.device) + 1) / 2) * 255 | |
| w = w_projector.project(self.old_G, image, device=torch.device(global_config.device), | |
| num_steps=self.projection_steps, w_name=fname, use_wandb=self.use_wandb) | |
| return w | |
| if __name__ == '__main__': | |
| id_change_report = SG2LatentCreator() | |
| id_change_report.create_latents() | |