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Added support for specifying which step iteration to start using

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each ControlNet, and which step to end using each controlnet (specified as fraction of total steps)
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user1 2023-05-12 04:01:35 -07:00 committed by Kent Keirsey
parent 11fc7e40a5
commit 754acec92f
2 changed files with 16 additions and 13 deletions
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25
invokeai/app/invocations/controlnet_image_processors.py
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@ -33,16 +33,16 @@ from .image import ImageOutput, build_image_output, PILInvocationConfig
class ControlField(BaseModel): class ControlField(BaseModel):
image: ImageField = Field(default=None, description="processed image") image: ImageField = Field(default=None, description="processed image")
# width: Optional[int] = Field(default=None, description="The width of the image in pixels")
# height: Optional[int] = Field(default=None, description="The height of the image in pixels")
# mode: Optional[str] = Field(default=None, description="The mode of the image")
control_model: Optional[str] = Field(default=None, description="control model used") control_model: Optional[str] = Field(default=None, description="control model used")
control_weight: Optional[float] = Field(default=None, description="weight given to controlnet") control_weight: Optional[float] = Field(default=None, description="weight given to controlnet")
begin_step_percent: float = Field(default=0, ge=0, le=1,
description="% of total steps at which controlnet is first applied")
end_step_percent: float = Field(default=1, ge=0, le=1,
description="% of total steps at which controlnet is last applied")
class Config: class Config:
schema_extra = { schema_extra = {
"required": ["image", "control_model", "control_weight"] "required": ["image", "control_model", "control_weight", "begin_step_percent", "end_step_percent"]
# "required": ["type", "image", "width", "height", "mode"]
} }
@ -62,12 +62,11 @@ class ControlNetInvocation(BaseInvocation):
image: ImageField = Field(default=None, description="image to process") image: ImageField = Field(default=None, description="image to process")
control_model: str = Field(default=None, description="control model to use") control_model: str = Field(default=None, description="control model to use")
control_weight: float = Field(default=0.5, ge=0, le=1, description="weight given to controlnet") control_weight: float = Field(default=0.5, ge=0, le=1, description="weight given to controlnet")
# TODO: support additional ControlNet parameters (mostly just passthroughs to other nodes with ControlField inputs) # TODO: add support in backend core for begin_step_percent, end_step_percent, guess_mode
# begin_step_percent: float = Field(default=0, ge=0, le=1, begin_step_percent: float = Field(default=0, ge=0, le=1,
# description="% of total steps at which controlnet is first applied") description="% of total steps at which controlnet is first applied")
# end_step_percent: float = Field(default=1, ge=0, le=1, end_step_percent: float = Field(default=1, ge=0, le=1,
# description="% of total steps at which controlnet is last applied") description="% of total steps at which controlnet is last applied")
# guess_mode: bool = Field(default=False, description="use guess mode (controlnet ignores prompt)")
# fmt: on # fmt: on
@ -77,7 +76,9 @@ class ControlNetInvocation(BaseInvocation):
control=ControlField( control=ControlField(
image=self.image, image=self.image,
control_model=self.control_model, control_model=self.control_model,
control_weight=self.control_weight control_weight=self.control_weight,
begin_step_percent=self.begin_step_percent,
end_step_percent=self.end_step_percent,
), ),
) )

4
invokeai/app/invocations/latent.py
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@ -312,7 +312,9 @@ class TextToLatentsInvocation(BaseInvocation):
) )
control_item = ControlNetData(model=control_model, control_item = ControlNetData(model=control_model,
image_tensor=control_image, image_tensor=control_image,
weight=control_info.control_weight) weight=control_info.control_weight,
begin_step_percent=control_info.begin_step_percent,
end_step_percent=control_info.end_step_percent)
control_data.append(control_item) control_data.append(control_item)
# multi_control = MultiControlNetModel(control_models) # multi_control = MultiControlNetModel(control_models)
# model.control_model = multi_control # model.control_model = multi_control