def validation_step(self, batch, batch_idx):
input_photo = batch
log_images(
self, {
'input/real': input_photo,
'generate/anime': self.generator(input_photo)
})
def validation_step(self, batch: Tuple[torch.Tensor, torch.Tensor],
batch_idx):
input_photo = torch.cat(batch)
generator_img = self.generator(input_photo)
log_images(self, {
'input/real': input_photo,
'generate/anime': generator_img,
}, 8)
def validation_step(self, batch, batch_idx):
input_photo, input_cartoon = batch
d = {}
d['input/real'] = input_photo
d['input/cartoon'] = input_cartoon
for i, idx in enumerate(self.hparams.layer_indexs):
d[f'gen/{self.vgg_names[idx-1]}_real'] = self.real_generators[i](input_photo)
d[f'gen/{self.vgg_names[idx-1]}_cartoon'] = self.real_generators[i](input_cartoon)
log_images(self, d)
def validation_step(self, batch: Tuple[torch.Tensor, torch.Tensor], batch_idx):
input_photo = torch.cat(batch)
generator_img = self.generator(input_photo)
output = self.guided_filter(input_photo, generator_img, r=1)
blur_fake = self.guided_filter(output, output, r=5, eps=2e-1)
gray_fake, = self.colorshift(output)
input_superpixel = torch.from_numpy(
simple_superpixel(output.detach().permute((0, 2, 3, 1)).cpu().numpy(),
self.superpixel_fn)
).to(self.device).permute((0, 3, 1, 2))
log_images(self, {
'input/real': input_photo,
'input/superpix': input_superpixel,
'generate/anime': generator_img,
'generate/filtered': output,
'generate/gray': gray_fake,
'generate/blur': blur_fake,
}, num=8)
def validation_step(self, batch, batch_idx):
real_A, real_B = batch
fake_A2B, _, fake_A2B_heatmap = self.genA2B(real_A)
# fake_A2B2A, _, fake_A2B2A_heatmap = self.genB2A(fake_A2B)
# fake_A2A, _, fake_A2A_heatmap = self.genB2A(real_A)
log_images(self, {'gen/A/fake_A2B': fake_A2B})