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Use the existence of initial latents to decide whether we are doing image-to-image in the FLUX denoising node. Previously we were using the denoising_start value, but in some cases with an inpaintin mask you may want to run image-to-image from densoising_start=0.

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This commit is contained in:
Ryan Dick 2024-08-30 15:09:55 +00:00
parent 75d0558241
commit 480c62320c
1 changed files with 12 additions and 5 deletions
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17
invokeai/app/invocations/flux_text_to_image.py
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@ -131,10 +131,14 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
)
# Prepare input latent image.
if self.denoising_start > 1e-5:
# If denoising_start > 0, we are doing image-to-image.
if init_latents is None:
raise ValueError("latents must be provided if denoising_start > 0.")
if init_latents is not None:
# If init_latents is provided, we are doing image-to-image.
if is_schnell:
context.logger.warning(
"Running image-to-image with a FLUX schnell model. This is not recommended. The results are likely "
"to be poor. Consider using a FLUX dev model instead."
)
# Clip the timesteps schedule based on denoising_start.
# TODO(ryand): Should we apply denoising_start in timestep-space rather than timestep-index-space?
@ -145,7 +149,10 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
t_0 = timesteps[0]
x = t_0 * noise + (1.0 - t_0) * init_latents
else:
# We are not doing image-to-image, so start from noise.
# init_latents are not provided, so we are not doing image-to-image (i.e. we are starting from pure noise).
if self.denoising_start > 1e-5:
raise ValueError("denoising_start should be 0 when initial latents are not provided.")
x = noise
inpaint_mask = self._prep_inpaint_mask(context, x)