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Merge branch 'main' into feat/solid-infill

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Lincoln Stein 2023-01-31 18:02:17 -05:00 committed by GitHub
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1 changed files with 9 additions and 3 deletions
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12
ldm/invoke/generator/diffusers_pipeline.py
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@ -544,6 +544,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
init_image = image_resized_to_grid_as_tensor(init_image.convert('RGB')) init_image = image_resized_to_grid_as_tensor(init_image.convert('RGB'))
init_image = init_image.to(device=device, dtype=latents_dtype) init_image = init_image.to(device=device, dtype=latents_dtype)
mask = mask.to(device=device, dtype=latents_dtype)
if init_image.dim() == 3: if init_image.dim() == 3:
init_image = init_image.unsqueeze(0) init_image = init_image.unsqueeze(0)
@ -562,17 +563,22 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
if mask.dim() == 3: if mask.dim() == 3:
mask = mask.unsqueeze(0) mask = mask.unsqueeze(0)
mask = tv_resize(mask, init_image_latents.shape[-2:], T.InterpolationMode.BILINEAR) \ latent_mask = tv_resize(mask, init_image_latents.shape[-2:], T.InterpolationMode.BILINEAR) \
.to(device=device, dtype=latents_dtype) .to(device=device, dtype=latents_dtype)
guidance: List[Callable] = [] guidance: List[Callable] = []
if is_inpainting_model(self.unet): if is_inpainting_model(self.unet):
# You'd think the inpainting model wouldn't be paying attention to the area it is going to repaint
# (that's why there's a mask!) but it seems to really want that blanked out.
masked_init_image = init_image * torch.where(mask < 0.5, 1, 0)
masked_latents = self.non_noised_latents_from_image(masked_init_image, device=device, dtype=latents_dtype)
# TODO: we should probably pass this in so we don't have to try/finally around setting it. # TODO: we should probably pass this in so we don't have to try/finally around setting it.
self.invokeai_diffuser.model_forward_callback = \ self.invokeai_diffuser.model_forward_callback = \
AddsMaskLatents(self._unet_forward, mask, init_image_latents) AddsMaskLatents(self._unet_forward, latent_mask, masked_latents)
else: else:
guidance.append(AddsMaskGuidance(mask, init_image_latents, self.scheduler, noise)) guidance.append(AddsMaskGuidance(latent_mask, init_image_latents, self.scheduler, noise))
try: try:
result_latents, result_attention_maps = self.latents_from_embeddings( result_latents, result_attention_maps = self.latents_from_embeddings(