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Update pipeline_stable_diffusion_inpaint_legacy.py resize to integer multiple of 8 instead of 32 for init image and mask #2350

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Merged
merged 1 commit into from
Mar 3, 2023
Merged

Update pipeline_stable_diffusion_inpaint_legacy.py resize to integer multiple of 8 instead of 32 for init image and mask #2350

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6 changes: 3 additions & 3 deletions src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@

def preprocess_image(image):
w, h = image.size
w, h = map(lambda x: x - x % 32, (w, h)) # resize to integer multiple of 32
w, h = map(lambda x: x - x % 8, (w, h)) # resize to integer multiple of 8
image = image.resize((w, h), resample=PIL_INTERPOLATION["lanczos"])
image = np.array(image).astype(np.float32) / 255.0
image = image[None].transpose(0, 3, 1, 2)
Expand All @@ -47,7 +47,7 @@ def preprocess_mask(mask, scale_factor=8):
if not isinstance(mask, torch.FloatTensor):
mask = mask.convert("L")
w, h = mask.size
w, h = map(lambda x: x - x % 32, (w, h)) # resize to integer multiple of 32
w, h = map(lambda x: x - x % 8, (w, h)) # resize to integer multiple of 8
mask = mask.resize((w // scale_factor, h // scale_factor), resample=PIL_INTERPOLATION["nearest"])
mask = np.array(mask).astype(np.float32) / 255.0
mask = np.tile(mask, (4, 1, 1))
Expand All @@ -69,7 +69,7 @@ def preprocess_mask(mask, scale_factor=8):
# (potentially) reduce mask channel dimension from 3 to 1 for broadcasting to latent shape
mask = mask.mean(dim=1, keepdim=True)
h, w = mask.shape[-2:]
h, w = map(lambda x: x - x % 32, (h, w)) # resize to integer multiple of 32
h, w = map(lambda x: x - x % 8, (h, w)) # resize to integer multiple of 8
mask = torch.nn.functional.interpolate(mask, (h // scale_factor, w // scale_factor))
return mask

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