lllyasviel/stable-diffusion-webui-forge
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inpaint done!

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lllyasviel
2024-01-30 15:13:26 -08:00
parent c708d8a239
commit 66e563fe03
2 changed files with 23 additions and 0 deletions
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10
extensions-builtin/forge_preprocessor_inpaint/scripts/preprocessor_inpaint.py
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@@ -28,6 +28,7 @@ class PreprocessorInpaintOnly(PreprocessorInpaint):
self.name = 'inpaint_only'
self.image = None
self.mask = None
self.latent = None
def process_before_every_sampling(self, process, cond, *args, **kwargs):
self.image = kwargs['cond_before_inpaint_fix'][:, 0:3]
@@ -55,6 +56,8 @@ class PreprocessorInpaintOnly(PreprocessorInpaint):
unet.set_model_sampler_post_cfg_function(post_cfg)
process.sd_model.forge_objects.unet = unet
self.latent = latent_image
return
def process_after_every_sampling(self, process, params, *args, **kwargs):
@@ -128,6 +131,13 @@ class PreprocessorInpaintLama(PreprocessorInpaintOnly):
result = np.concatenate([fin_color, raw_mask], axis=2)
return result
def process_before_every_sampling(self, process, cond, *args, **kwargs):
super().process_before_every_sampling(process, cond, *args, **kwargs)
sigma_max = process.sd_model.forge_objects.unet.model.model_sampling.sigma_max
original_noise = kwargs['noise']
process.modified_noise = original_noise + self.latent.to(original_noise) / sigma_max.to(original_noise)
return
add_supported_preprocessor(PreprocessorInpaint())

13
modules/processing.py
View File

@@ -257,6 +257,7 @@ class StableDiffusionProcessing:
self.cached_c = StableDiffusionProcessing.cached_c
self.extra_result_images = []
self.modified_noise = None
@property
def sd_model(self):
@@ -1256,6 +1257,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
c=conditioning,
uc=unconditional_conditioning)
if self.modified_noise is not None:
x = self.modified_noise
self.modified_noise = None
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
del x
@@ -1365,6 +1370,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
c=self.hr_c,
uc=self.hr_uc)
if self.modified_noise is not None:
noise = self.modified_noise
self.modified_noise = None
samples = self.sampler.sample_img2img(self, samples, noise, self.hr_c, self.hr_uc, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio())
@@ -1676,6 +1685,10 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
c=conditioning,
uc=unconditional_conditioning)
if self.modified_noise is not None:
x = self.modified_noise
self.modified_noise = None
samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)
if self.mask is not None: