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fix(save): handle already-decoded images in save_intermediate

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CalamitousFelicitousness
2026-04-30 03:42:11 +01:00
parent 079776bda6
commit ae0cb1600c
1 changed files with 10 additions and 5 deletions
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modules/processing_helpers.py
+10 -5
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@@ -562,12 +562,17 @@ def apply_circular(enable: bool, model):
def save_intermediate(p, latents, suffix):
for i in range(len(latents)):
from modules.processing import create_infotext
info=create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, [], iteration=p.iteration, position_in_batch=i)
from modules.processing import create_infotext
from modules.image import convert
is_latent = torch.is_tensor(latents) and latents.shape[-1] != 3
if is_latent:
decoded = processing_vae.vae_decode(latents=latents, model=shared.sd_model, output_type='pil', vae_type=p.vae_type, width=p.width, height=p.height)
for j in range(len(decoded)):
images.save_image(decoded[j], path=p.outpath_samples, basename="", seed=p.seeds[i], prompt=p.prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix=suffix)
else:
items = latents if isinstance(latents, list) else ([latents[j] for j in range(latents.shape[0])] if hasattr(latents, 'shape') else [latents])
decoded = [convert.to_pil(img) if not hasattr(img, 'width') else img for img in items]
for i in range(len(decoded)):
info = create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, [], iteration=p.iteration, position_in_batch=i)
images.save_image(decoded[i], path=p.outpath_samples, basename="", seed=p.seeds[i], prompt=p.prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix=suffix)
def update_sampler(p, sd_model, second_pass=False):