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Re-implemented soft inpainting via a script. Also fixed some mistakes with the previous hooks, removed unnecessary formatting changes, removed code that I had forgotten to.

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CodeHatchling
2023-12-06 22:25:53 -07:00
parent ac45789123
commit 2abc417834
4 changed files with 413 additions and 323 deletions
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23
modules/processing.py
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@@ -879,14 +879,13 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.scripts is not None:
ps = scripts.PostSampleArgs(samples_ddim)
p.scripts.post_sample(p, ps)
samples_ddim = pp.samples
samples_ddim = ps.samples
if getattr(samples_ddim, 'already_decoded', False):
x_samples_ddim = samples_ddim
else:
if opts.sd_vae_decode_method != 'Full':
p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method
x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True)
x_samples_ddim = torch.stack(x_samples_ddim).float()
@@ -944,7 +943,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.scripts is not None:
ppmo = scripts.PostProcessMaskOverlayArgs(i, mask_for_overlay, overlay_image)
p.scripts.postprocess_maskoverlay(p, ppmo)
mask_for_overlay, overlay_image = pp.mask_for_overlay, pp.overlay_image
mask_for_overlay, overlay_image = ppmo.mask_for_overlay, ppmo.overlay_image
if p.color_corrections is not None and i < len(p.color_corrections):
if save_samples and opts.save_images_before_color_correction:
@@ -959,7 +958,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
original_denoised_image = image.copy()
if p.paste_to is not None:
original_denoised_image = uncrop(original_denoised_image, (p.overlay_image.width, p.overlay_image.height), p.paste_to)
original_denoised_image = uncrop(original_denoised_image, (overlay_image.width, overlay_image.height), p.paste_to)
image = apply_overlay(image, p.paste_to, overlay_image)
@@ -1512,9 +1511,6 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
if self.overlay_images is not None:
self.overlay_images = self.overlay_images * self.batch_size
if self.masks_for_overlay is not None:
self.masks_for_overlay = self.masks_for_overlay * self.batch_size
if self.color_corrections is not None and len(self.color_corrections) == 1:
self.color_corrections = self.color_corrections * self.batch_size
@@ -1565,14 +1561,15 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)
blended_samples = samples * self.nmask + self.init_latent * self.mask
if self.mask is not None:
blended_samples = samples * self.nmask + self.init_latent * self.mask
if self.scripts is not None:
mba = scripts.MaskBlendArgs(self, samples, self.nmask, self.init_latent, self.mask, blended_samples, sigma=None, is_final_blend=True)
self.scripts.on_mask_blend(self, mba)
blended_samples = mba.blended_latent
if self.scripts is not None:
mba = scripts.MaskBlendArgs(samples, self.nmask, self.init_latent, self.mask, blended_samples)
self.scripts.on_mask_blend(self, mba)
blended_samples = mba.blended_latent
samples = blended_samples
samples = blended_samples
del x
devices.torch_gc()