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fix noisy latent handling

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This commit is contained in:
Stephan Auerhahn
2023-08-06 21:08:19 +00:00
parent 451c76ada1
commit f2fba1dfa2
2 changed files with 45 additions and 23 deletions
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54
sgm/inference/api.py
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@@ -226,15 +226,17 @@ class SamplingPipeline:
negative_prompt: str = "",
samples: int = 1,
return_latents: bool = False,
stage2strength=None,
noise_strength=None,
):
sampler = get_sampler_config(params)
if stage2strength is not None:
sampler.discretization = Txt2NoisyDiscretizationWrapper(
sampler.discretization,
strength=stage2strength,
original_steps=params.steps,
)
sampler.discretization = self.wrap_discretization(
sampler.discretization,
image_strength=None,
noise_strength=noise_strength,
steps=params.steps,
)
value_dict = asdict(params)
value_dict["prompt"] = prompt
value_dict["negative_prompt"] = negative_prompt
@@ -262,11 +264,15 @@ class SamplingPipeline:
negative_prompt: str = "",
samples: int = 1,
return_latents: bool = False,
noise_strength=None,
):
sampler = get_sampler_config(params)
sampler.discretization = self.wrap_discretization(
sampler.discretization, strength=params.img2img_strength
sampler.discretization,
image_strength=params.img2img_strength,
noise_strength=noise_strength,
steps=params.steps,
)
height, width = image.shape[2], image.shape[3]
@@ -286,12 +292,29 @@ class SamplingPipeline:
filter=None,
)
def wrap_discretization(self, discretization, strength=1.0):
if (
not isinstance(discretization, Img2ImgDiscretizationWrapper)
and strength < 1.0
def wrap_discretization(
self, discretization, image_strength=None, noise_strength=None, steps=None
):
if isinstance(discretization, Img2ImgDiscretizationWrapper) or isinstance(
discretization, Txt2NoisyDiscretizationWrapper
):
return Img2ImgDiscretizationWrapper(discretization, strength=strength)
return discretization # Already wrapped
if image_strength is not None and image_strength < 1.0 and image_strength > 0.0:
discretization = Img2ImgDiscretizationWrapper(
discretization, strength=image_strength
)
if (
noise_strength is not None
and noise_strength < 1.0
and noise_strength > 0.0
and steps is not None
):
discretization = Txt2NoisyDiscretizationWrapper(
discretization,
strength=noise_strength,
original_steps=steps,
)
return discretization
def refiner(
@@ -300,7 +323,7 @@ class SamplingPipeline:
prompt: str,
negative_prompt: str = "",
params: SamplingParams = SamplingParams(
sampler=Sampler.EULER_EDM, steps=40, img2img_strength=0.2
sampler=Sampler.EULER_EDM, steps=40, img2img_strength=0.15
),
samples: int = 1,
return_latents: bool = False,
@@ -320,7 +343,7 @@ class SamplingPipeline:
}
sampler.discretization = self.wrap_discretization(
sampler.discretization, strength=params.img2img_strength
sampler.discretization, image_strength=params.img2img_strength
)
return do_img2img(
@@ -332,6 +355,7 @@ class SamplingPipeline:
skip_encode=True,
return_latents=return_latents,
filter=None,
add_noise=False,
)