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updated readme and some small stylistic changes to code

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AUTOMATIC
2022-10-21 09:00:39 +03:00
parent 49533eed9e
commit 4587218190
3 changed files with 10 additions and 8 deletions
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14
modules/processing.py
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@@ -540,11 +540,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f
self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f
def create_dummy_mask(self, x, first_phase: bool = False):
def create_dummy_mask(self, x, width=None, height=None):
if self.sampler.conditioning_key in {'hybrid', 'concat'}:
height = self.firstphase_height if first_phase else self.height
width = self.firstphase_width if first_phase else self.width
height = height or self.height
width = width or self.width
# The "masked-image" in this case will just be all zeros since the entire image is masked.
image_conditioning = torch.zeros(x.shape[0], 3, height, width, device=x.device)
@@ -571,7 +570,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return samples
x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.create_dummy_mask(x, first_phase=True))
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.create_dummy_mask(x, self.firstphase_width, self.firstphase_height))
samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
@@ -634,6 +633,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.inpainting_mask_invert = inpainting_mask_invert
self.mask = None
self.nmask = None
self.image_conditioning = None
def init(self, all_prompts, all_seeds, all_subseeds):
self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, self.sd_model)
@@ -735,9 +735,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
elif self.inpainting_fill == 3:
self.init_latent = self.init_latent * self.mask
conditioning_key = self.sampler.conditioning_key
if conditioning_key in {'hybrid', 'concat'}:
if self.sampler.conditioning_key in {'hybrid', 'concat'}:
if self.image_mask is not None:
conditioning_mask = np.array(self.image_mask.convert("L"))
conditioning_mask = conditioning_mask.astype(np.float32) / 255.0