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Fixed issue where batched inpainting (batch size > 1) wouldn't work because of mismatched tensor sizes. The 'already_decoded' decoded case should also be handled correctly (tested indirectly).

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CodeHatchling
2023-12-04 19:42:59 -07:00
parent b32a334e3d
commit 6fc12428e3
2 changed files with 71 additions and 18 deletions
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23
modules/processing.py
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@@ -883,20 +883,27 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if getattr(samples_ddim, 'already_decoded', False):
x_samples_ddim = samples_ddim
# todo: generate adaptive masks based on pixel differences.
# if p.masks_for_overlay is used, it will already be populated with masks
if getattr(p, "image_mask", None) is not None and getattr(p, "soft_inpainting", None) is not None:
si.apply_masks(soft_inpainting=p.soft_inpainting,
nmask=p.nmask,
overlay_images=p.overlay_images,
masks_for_overlay=p.masks_for_overlay,
width=p.width,
height=p.height,
paste_to=p.paste_to)
else:
if opts.sd_vae_decode_method != 'Full':
p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method
# Generate the mask(s) based on similarity between the original and denoised latent vectors
if getattr(p, "image_mask", None) is not None and getattr(p, "soft_inpainting", None) is not None:
si.generate_adaptive_masks(latent_orig=p.init_latent,
latent_processed=samples_ddim,
overlay_images=p.overlay_images,
masks_for_overlay=p.masks_for_overlay,
width=p.width,
height=p.height,
paste_to=p.paste_to)
si.apply_adaptive_masks(latent_orig=p.init_latent,
latent_processed=samples_ddim,
overlay_images=p.overlay_images,
masks_for_overlay=p.masks_for_overlay,
width=p.width,
height=p.height,
paste_to=p.paste_to)
x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True)