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Update util.py in stable diffusion to avoid Sizes of tensors error #278

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Update util.py in stable diffusion to avoid Sizes of tensors error #278

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b82be61
Update image_to_image.py
CatManJr Nov 28, 2024
d1a341b
Update image_to_image.py
CatManJr Nov 28, 2024
46e4c3e
Update util.py in stable diffusion to avoid Sizes of tensors error
CatManJr Nov 28, 2024
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3 changes: 3 additions & 0 deletions labml_nn/diffusion/stable_diffusion/scripts/image_to_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
from pathlib import Path

import torch
from torchvision import transforms

from labml import lab, monit
from labml_nn.diffusion.stable_diffusion.sampler.ddim import DDIMSampler
Expand Down Expand Up @@ -69,6 +70,8 @@ def __call__(self, *,
orig_image = load_img(orig_img).to(self.device)
# Encode the image in the latent space and make `batch_size` copies of it
orig = self.model.autoencoder_encode(orig_image).repeat(batch_size, 1, 1, 1)
# Encode the image in the latent space and make `batch_size` copies of it
orig = self.model.autoencoder_encode(orig_image).repeat(batch_size, 1, 1, 1)

# Get the number of steps to diffuse the original
assert 0. <= strength <= 1., 'can only work with strength in [0.0, 1.0]'
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6 changes: 3 additions & 3 deletions labml_nn/diffusion/stable_diffusion/util.py
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Expand Up @@ -115,9 +115,9 @@ def load_img(path: str):
image = Image.open(path).convert("RGB")
# Get image size
w, h = image.size
# Resize to a multiple of 32
w = w - w % 32
h = h - h % 32
# Resize to a multiple of 64
w = w - w % 64
h = h - h % 64
image = image.resize((w, h), resample=PIL.Image.LANCZOS)
# Convert to numpy and map to `[-1, 1]` for `[0, 255]`
image = np.array(image).astype(np.float32) * (2. / 255.0) - 1
Expand Down