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Initial implementation of IP-Adapter "begin_step_percent" and "end_step_percent" for controlling on which steps IP-Adapter is applied in the denoising loop.

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user1
2023-09-16 08:24:12 -07:00
parent 834751e877
commit ced297ed21
4 changed files with 45 additions and 5 deletions
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10
invokeai/app/invocations/ip_adapter.py
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@ -34,6 +34,8 @@ class IPAdapterField(BaseModel):
ip_adapter_model: IPAdapterModelField = Field(description="The IP-Adapter model to use.")
image_encoder_model: CLIPVisionModelField = Field(description="The name of the CLIP image encoder model.")
weight: float = Field(default=1.0, ge=0, description="The weight of the IP-Adapter.")
begin_step_percent: float = Field(default=0.0, ge=0, le=1.0)
end_step_percent: float = Field(default=1.0, ge=0, le=1.0)
@invocation_output("ip_adapter_output")
@ -54,6 +56,12 @@ class IPAdapterInvocation(BaseInvocation):
input=Input.Direct,
)
weight: float = InputField(default=1.0, description="The weight of the IP-Adapter.", ui_type=UIType.Float)
begin_step_percent: float = InputField(
default=0, ge=-1, le=2, description="When the IP-Adapter is first applied (% of total steps)"
)
end_step_percent: float = InputField(
default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
)
def invoke(self, context: InvocationContext) -> IPAdapterOutput:
# Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
@ -80,5 +88,7 @@ class IPAdapterInvocation(BaseInvocation):
ip_adapter_model=self.ip_adapter_model,
image_encoder_model=image_encoder_model,
weight=self.weight,
begin_step_percent=self.begin_step_percent,
end_step_percent=self.end_step_percent,
),
)