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add actual latent upscalers

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Vladimir Mandic
2023-09-25 11:23:04 -04:00
parent 4ba2e23dd2
commit ff28ac35e0
11 changed files with 494 additions and 91 deletions
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modules/processing_diffusers.py
+8 -1
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@@ -443,6 +443,12 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
# shared.log.warning(f'Refiner requires image size to be divisible by 8: {image.shape}')
# results.append(image)
# return results
noise_level = round(350 * p.denoising_strength)
output_type='latent' if hasattr(shared.sd_refiner, 'vae') else 'np',
if shared.sd_refiner.__class__.__name__ == 'StableDiffusionUpscalePipeline':
image = vae_decode(latents=image, model=shared.sd_model, full_quality=p.full_quality, output_type='pil')
p.extra_generation_params['Noise level'] = noise_level
output_type = 'np'
refiner_args = set_pipeline_args(
model=shared.sd_refiner,
prompts=[p.refiner_prompt] if len(p.refiner_prompt) > 0 else prompts[i],
@@ -450,12 +456,13 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
num_inference_steps=int(p.refiner_steps // (1 - p.refiner_start)) if p.refiner_start > 0 and p.refiner_start < 1 and refiner_is_sdxl else int(p.refiner_steps // p.denoising_strength + 1) if refiner_is_sdxl else p.refiner_steps,
eta=shared.opts.scheduler_eta,
strength=p.denoising_strength,
noise_level=noise_level, # StableDiffusionUpscalePipeline only
guidance_scale=p.image_cfg_scale if p.image_cfg_scale is not None else p.cfg_scale,
guidance_rescale=p.diffusers_guidance_rescale,
denoising_start=p.refiner_start if p.refiner_start > 0 and p.refiner_start < 1 else None,
denoising_end=1 if p.refiner_start > 0 and p.refiner_start < 1 else None,
image=image,
output_type='latent' if hasattr(shared.sd_refiner, 'vae') else 'np',
output_type=output_type,
clip_skip=p.clip_skip,
desc='Refiner',
)