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mirror of https://github.com/vladmandic/automatic synced 2026-08-28 16:11:02 +02:00
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fix upscale and add some compile options

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Vladimir Mandic
2023-11-17 16:59:30 -05:00
parent 7ef41af090
commit d46dddd024
6 changed files with 27 additions and 25 deletions
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modules/processing_diffusers.py
+8 -10
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@@ -42,16 +42,14 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
if latent_upscaler is not None:
latents = torch.nn.functional.interpolate(latents, size=(p.hr_upscale_to_y // 8, p.hr_upscale_to_x // 8), mode=latent_upscaler["mode"], antialias=latent_upscaler["antialias"])
first_pass_images = vae_decode(latents=latents, model=shared.sd_model, full_quality=p.full_quality, output_type='pil')
p.init_images = []
resized_images = []
for img in first_pass_images:
if latent_upscaler is None:
init_image = images.resize_image(1, img, p.hr_upscale_to_x, p.hr_upscale_to_y, upscaler_name=p.hr_upscaler)
resized_image = images.resize_image(1, img, p.hr_upscale_to_x, p.hr_upscale_to_y, upscaler_name=p.hr_upscaler)
else:
init_image = img
# if is_refiner_enabled:
# init_image = vae_encode(init_image, model=shared.sd_model, full_quality=p.full_quality)
p.init_images.append(init_image)
return p.init_images
resized_image = img
resized_images.append(resized_image)
return resized_images
def save_intermediate(latents, suffix):
for i in range(len(latents)):
@@ -489,7 +487,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
return results
# optional hires pass
if p.enable_hr and p.hr_upscaler != 'None' and p.denoising_strength > 0 and len(getattr(p, 'init_images', [])) == 0:
if p.enable_hr and getattr(p, 'hr_upscaler', 'None') != 'None' and len(getattr(p, 'init_images', [])) == 0:
p.is_hr_pass = True
latent_scale_mode = shared.latent_upscale_modes.get(p.hr_upscaler, None) if (hasattr(p, "hr_upscaler") and p.hr_upscaler is not None) else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "None")
if p.is_hr_pass:
@@ -501,7 +499,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
save_intermediate(latents=output.images, suffix="-before-hires")
shared.state.job = 'upscale'
output.images = hires_resize(latents=output.images)
if latent_scale_mode is not None or p.hr_force:
if (latent_scale_mode is not None or p.hr_force) and p.denoising_strength > 0:
p.ops.append('hires')
shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.IMAGE_2_IMAGE)
recompile_model(hires=True)
@@ -518,7 +516,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
guidance_rescale=p.diffusers_guidance_rescale,
output_type='latent' if hasattr(shared.sd_model, 'vae') else 'np',
clip_skip=p.clip_skip,
image=p.init_images,
image=output.images,
strength=p.denoising_strength,
desc='Hires',
)