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Switch to a continous blend for cond. image.

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random_thoughtss
2022-10-25 13:15:08 -07:00
parent 605d27687f
commit 8b4f32779f
3 changed files with 8 additions and 8 deletions
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9
modules/processing.py
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@@ -769,9 +769,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
# Create another latent image, this time with a masked version of the original input.
conditioning_mask = conditioning_mask.to(image.device)
conditioning_image = image
if getattr(self, "inpainting_mask_image", shared.opts.inpainting_mask_image):
conditioning_image = conditioning_image * (1.0 - conditioning_mask)
# Smoothly interpolate between the masked and unmasked latent conditioning image.
conditioning_image = torch.lerp(
image,
image * (1.0 - conditioning_mask),
getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight)
)
conditioning_image = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(conditioning_image))

2
modules/shared.py
View File

@@ -320,7 +320,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
"inpainting_mask_image": OptionInfo(True, "Mask original image for conditioning used by inpainting model."),
"inpainting_mask_weight": OptionInfo(1.0, "Blend betweeen an unmasked and masked conditioning image for inpainting models.", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
}))