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103 lines
4.0 KiB
Python
103 lines
4.0 KiB
Python
from typing import Union
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from pydantic import BaseModel, Field, field_validator, model_validator
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from invokeai.app.invocations.baseinvocation import (
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BaseInvocation,
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BaseInvocationOutput,
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invocation,
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invocation_output,
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)
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from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, OutputField
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from invokeai.app.invocations.model import ModelIdentifierField
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from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES
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from invokeai.backend.model_manager.taxonomy import BaseModelType, ModelType
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class T2IAdapterField(BaseModel):
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image: ImageField = Field(description="The T2I-Adapter image prompt.")
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t2i_adapter_model: ModelIdentifierField = Field(description="The T2I-Adapter model to use.")
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weight: Union[float, list[float]] = Field(default=1, description="The weight given to the T2I-Adapter")
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begin_step_percent: float = Field(
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default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
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)
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end_step_percent: float = Field(
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default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
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)
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resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
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@field_validator("weight")
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@classmethod
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def validate_ip_adapter_weight(cls, v):
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validate_weights(v)
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return v
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@model_validator(mode="after")
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def validate_begin_end_step_percent(self):
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validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
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return self
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@invocation_output("t2i_adapter_output")
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class T2IAdapterOutput(BaseInvocationOutput):
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t2i_adapter: T2IAdapterField = OutputField(description=FieldDescriptions.t2i_adapter, title="T2I Adapter")
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@invocation(
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"t2i_adapter",
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title="T2I-Adapter - SD1.5, SDXL",
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tags=["t2i_adapter", "control"],
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category="conditioning",
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version="1.0.4",
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)
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class T2IAdapterInvocation(BaseInvocation):
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"""Collects T2I-Adapter info to pass to other nodes."""
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# Inputs
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image: ImageField = InputField(description="The IP-Adapter image prompt.")
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t2i_adapter_model: ModelIdentifierField = InputField(
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description="The T2I-Adapter model.",
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title="T2I-Adapter Model",
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ui_order=-1,
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ui_model_base=[BaseModelType.StableDiffusion1, BaseModelType.StableDiffusionXL],
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ui_model_type=ModelType.T2IAdapter,
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)
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weight: Union[float, list[float]] = InputField(
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default=1, ge=0, description="The weight given to the T2I-Adapter", title="Weight"
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)
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begin_step_percent: float = InputField(
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default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
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)
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end_step_percent: float = InputField(
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default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
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)
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resize_mode: CONTROLNET_RESIZE_VALUES = InputField(
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default="just_resize",
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description="The resize mode applied to the T2I-Adapter input image so that it matches the target output size.",
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)
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@field_validator("weight")
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@classmethod
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def validate_ip_adapter_weight(cls, v):
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validate_weights(v)
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return v
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@model_validator(mode="after")
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def validate_begin_end_step_percent(self):
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validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
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return self
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def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
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return T2IAdapterOutput(
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t2i_adapter=T2IAdapterField(
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image=self.image,
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t2i_adapter_model=self.t2i_adapter_model,
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weight=self.weight,
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begin_step_percent=self.begin_step_percent,
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end_step_percent=self.end_step_percent,
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resize_mode=self.resize_mode,
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)
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)
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