hoelee/stable-diffusion-webui
1
0
Fork 0
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git synced 2025-08-04 11:12:35 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

Merge pull request #5753 from calvinballing/master

Browse Source 
Fix various typos
This commit is contained in:
AUTOMATIC1111
2022-12-24 09:58:28 +03:00
committed by GitHub
parent 94450b8877 c0355caefe
commit fac92610d2
16 changed files with 68 additions and 68 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
modules/processing.py
View File

@@ -150,11 +150,11 @@ class StableDiffusionProcessing():
# 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)
image_conditioning = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image_conditioning))
image_conditioning = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image_conditioning))
# Add the fake full 1s mask to the first dimension.
image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0)
image_conditioning = image_conditioning.to(x.dtype)
image_conditioning = image_conditioning.to(x.dtype)
return image_conditioning
@@ -202,7 +202,7 @@ class StableDiffusionProcessing():
source_image * (1.0 - conditioning_mask),
getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight)
)
# Encode the new masked image using first stage of network.
conditioning_image = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(conditioning_image))
@@ -540,7 +540,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
for n in range(p.n_iter):
if state.skipped:
state.skipped = False
if state.interrupted:
break
@@ -615,7 +615,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
image.info["parameters"] = text
output_images.append(image)
del x_samples_ddim
del x_samples_ddim
devices.torch_gc()
@@ -707,7 +707,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
"""saves image before applying hires fix, if enabled in options; takes as an arguyment either an image or batch with latent space images"""
"""saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images"""
def save_intermediate(image, index):
if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix:
return
@@ -723,7 +723,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
# Avoid making the inpainting conditioning unless necessary as
# Avoid making the inpainting conditioning unless necessary as
# this does need some extra compute to decode / encode the image again.
if getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) < 1.0:
image_conditioning = self.img2img_image_conditioning(decode_first_stage(self.sd_model, samples), samples)