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import torch
from configs import paths_config
from editings import ganspace
from utils.data_utils import tensor2im
class LatentEditor(object):
def apply_ganspace(self, latent, ganspace_pca, edit_directions):
edit_latents = ganspace.edit(latent, ganspace_pca, edit_directions)
return edit_latents
def apply_interfacegan(self, latent, direction, factor=1, factor_range=None):
edit_latents = []
if factor_range is not None: # Apply a range of editing factors. for example, (-5, 5)
for f in range(*factor_range):
edit_latent = latent + f * direction
edit_latents.append(edit_latent)
edit_latents = torch.cat(edit_latents)
else:
edit_latents = latent + factor * direction
return edit_latents
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