mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
43fbac26df
- Remove the add-to-board node - Create `BoardField` field type & add it to `save_image` node - Add UI for `BoardField` - Tighten up some loose types - Make `save_image` node, in workflow editor, default to not intermediate - Patch bump `save_image`
482 lines
14 KiB
Python
482 lines
14 KiB
Python
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
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from typing import Optional, Tuple
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import torch
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from pydantic import BaseModel, Field
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from .baseinvocation import (
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BaseInvocation,
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BaseInvocationOutput,
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FieldDescriptions,
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Input,
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InputField,
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InvocationContext,
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OutputField,
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UIComponent,
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invocation,
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invocation_output,
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)
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"""
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Primitives: Boolean, Integer, Float, String, Image, Latents, Conditioning, Color
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- primitive nodes
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- primitive outputs
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- primitive collection outputs
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"""
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# region Boolean
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@invocation_output("boolean_output")
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class BooleanOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single boolean"""
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value: bool = OutputField(description="The output boolean")
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@invocation_output("boolean_collection_output")
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class BooleanCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of booleans"""
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collection: list[bool] = OutputField(
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description="The output boolean collection",
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)
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@invocation(
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"boolean", title="Boolean Primitive", tags=["primitives", "boolean"], category="primitives", version="1.0.0"
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)
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class BooleanInvocation(BaseInvocation):
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"""A boolean primitive value"""
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value: bool = InputField(default=False, description="The boolean value")
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def invoke(self, context: InvocationContext) -> BooleanOutput:
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return BooleanOutput(value=self.value)
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@invocation(
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"boolean_collection",
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title="Boolean Collection Primitive",
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tags=["primitives", "boolean", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class BooleanCollectionInvocation(BaseInvocation):
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"""A collection of boolean primitive values"""
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collection: list[bool] = InputField(default_factory=list, description="The collection of boolean values")
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def invoke(self, context: InvocationContext) -> BooleanCollectionOutput:
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return BooleanCollectionOutput(collection=self.collection)
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# endregion
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# region Integer
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@invocation_output("integer_output")
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class IntegerOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single integer"""
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value: int = OutputField(description="The output integer")
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@invocation_output("integer_collection_output")
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class IntegerCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of integers"""
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collection: list[int] = OutputField(
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description="The int collection",
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)
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@invocation(
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"integer", title="Integer Primitive", tags=["primitives", "integer"], category="primitives", version="1.0.0"
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)
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class IntegerInvocation(BaseInvocation):
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"""An integer primitive value"""
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value: int = InputField(default=0, description="The integer value")
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def invoke(self, context: InvocationContext) -> IntegerOutput:
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return IntegerOutput(value=self.value)
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@invocation(
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"integer_collection",
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title="Integer Collection Primitive",
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tags=["primitives", "integer", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class IntegerCollectionInvocation(BaseInvocation):
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"""A collection of integer primitive values"""
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collection: list[int] = InputField(default_factory=list, description="The collection of integer values")
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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return IntegerCollectionOutput(collection=self.collection)
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# endregion
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# region Float
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@invocation_output("float_output")
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class FloatOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single float"""
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value: float = OutputField(description="The output float")
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@invocation_output("float_collection_output")
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class FloatCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of floats"""
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collection: list[float] = OutputField(
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description="The float collection",
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)
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@invocation("float", title="Float Primitive", tags=["primitives", "float"], category="primitives", version="1.0.0")
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class FloatInvocation(BaseInvocation):
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"""A float primitive value"""
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value: float = InputField(default=0.0, description="The float value")
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def invoke(self, context: InvocationContext) -> FloatOutput:
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return FloatOutput(value=self.value)
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@invocation(
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"float_collection",
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title="Float Collection Primitive",
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tags=["primitives", "float", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class FloatCollectionInvocation(BaseInvocation):
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"""A collection of float primitive values"""
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collection: list[float] = InputField(default_factory=list, description="The collection of float values")
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def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
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return FloatCollectionOutput(collection=self.collection)
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# endregion
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# region String
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@invocation_output("string_output")
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class StringOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single string"""
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value: str = OutputField(description="The output string")
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@invocation_output("string_collection_output")
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class StringCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of strings"""
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collection: list[str] = OutputField(
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description="The output strings",
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)
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@invocation("string", title="String Primitive", tags=["primitives", "string"], category="primitives", version="1.0.0")
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class StringInvocation(BaseInvocation):
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"""A string primitive value"""
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value: str = InputField(default="", description="The string value", ui_component=UIComponent.Textarea)
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def invoke(self, context: InvocationContext) -> StringOutput:
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return StringOutput(value=self.value)
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@invocation(
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"string_collection",
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title="String Collection Primitive",
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tags=["primitives", "string", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class StringCollectionInvocation(BaseInvocation):
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"""A collection of string primitive values"""
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collection: list[str] = InputField(default_factory=list, description="The collection of string values")
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def invoke(self, context: InvocationContext) -> StringCollectionOutput:
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return StringCollectionOutput(collection=self.collection)
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# endregion
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# region Image
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class ImageField(BaseModel):
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"""An image primitive field"""
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image_name: str = Field(description="The name of the image")
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class BoardField(BaseModel):
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"""A board primitive field"""
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board_id: str = Field(description="The id of the board")
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@invocation_output("image_output")
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class ImageOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single image"""
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image: ImageField = OutputField(description="The output image")
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width: int = OutputField(description="The width of the image in pixels")
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height: int = OutputField(description="The height of the image in pixels")
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@invocation_output("image_collection_output")
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class ImageCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of images"""
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collection: list[ImageField] = OutputField(
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description="The output images",
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)
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@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives", version="1.0.0")
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class ImageInvocation(BaseInvocation):
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"""An image primitive value"""
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image: ImageField = InputField(description="The image to load")
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get_pil_image(self.image.image_name)
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return ImageOutput(
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image=ImageField(image_name=self.image.image_name),
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width=image.width,
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height=image.height,
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)
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@invocation(
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"image_collection",
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title="Image Collection Primitive",
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tags=["primitives", "image", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class ImageCollectionInvocation(BaseInvocation):
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"""A collection of image primitive values"""
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collection: list[ImageField] = InputField(description="The collection of image values")
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def invoke(self, context: InvocationContext) -> ImageCollectionOutput:
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return ImageCollectionOutput(collection=self.collection)
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# endregion
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# region DenoiseMask
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class DenoiseMaskField(BaseModel):
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"""An inpaint mask field"""
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mask_name: str = Field(description="The name of the mask image")
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masked_latents_name: Optional[str] = Field(description="The name of the masked image latents")
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@invocation_output("denoise_mask_output")
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class DenoiseMaskOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single image"""
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denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run")
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# endregion
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# region Latents
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class LatentsField(BaseModel):
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"""A latents tensor primitive field"""
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latents_name: str = Field(description="The name of the latents")
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seed: Optional[int] = Field(default=None, description="Seed used to generate this latents")
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@invocation_output("latents_output")
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class LatentsOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single latents tensor"""
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latents: LatentsField = OutputField(
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description=FieldDescriptions.latents,
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)
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width: int = OutputField(description=FieldDescriptions.width)
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height: int = OutputField(description=FieldDescriptions.height)
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@invocation_output("latents_collection_output")
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class LatentsCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of latents tensors"""
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collection: list[LatentsField] = OutputField(
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description=FieldDescriptions.latents,
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)
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@invocation(
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"latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives", version="1.0.0"
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)
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class LatentsInvocation(BaseInvocation):
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"""A latents tensor primitive value"""
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latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
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def invoke(self, context: InvocationContext) -> LatentsOutput:
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latents = context.services.latents.get(self.latents.latents_name)
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return build_latents_output(self.latents.latents_name, latents)
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@invocation(
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"latents_collection",
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title="Latents Collection Primitive",
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tags=["primitives", "latents", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class LatentsCollectionInvocation(BaseInvocation):
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"""A collection of latents tensor primitive values"""
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collection: list[LatentsField] = InputField(
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description="The collection of latents tensors",
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)
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def invoke(self, context: InvocationContext) -> LatentsCollectionOutput:
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return LatentsCollectionOutput(collection=self.collection)
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def build_latents_output(latents_name: str, latents: torch.Tensor, seed: Optional[int] = None):
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return LatentsOutput(
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latents=LatentsField(latents_name=latents_name, seed=seed),
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width=latents.size()[3] * 8,
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height=latents.size()[2] * 8,
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)
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# endregion
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# region Color
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class ColorField(BaseModel):
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"""A color primitive field"""
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r: int = Field(ge=0, le=255, description="The red component")
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g: int = Field(ge=0, le=255, description="The green component")
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b: int = Field(ge=0, le=255, description="The blue component")
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a: int = Field(ge=0, le=255, description="The alpha component")
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def tuple(self) -> Tuple[int, int, int, int]:
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return (self.r, self.g, self.b, self.a)
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@invocation_output("color_output")
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class ColorOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single color"""
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color: ColorField = OutputField(description="The output color")
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@invocation_output("color_collection_output")
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class ColorCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of colors"""
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collection: list[ColorField] = OutputField(
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description="The output colors",
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)
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@invocation("color", title="Color Primitive", tags=["primitives", "color"], category="primitives", version="1.0.0")
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class ColorInvocation(BaseInvocation):
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"""A color primitive value"""
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color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color value")
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def invoke(self, context: InvocationContext) -> ColorOutput:
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return ColorOutput(color=self.color)
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# endregion
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# region Conditioning
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class ConditioningField(BaseModel):
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"""A conditioning tensor primitive value"""
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conditioning_name: str = Field(description="The name of conditioning tensor")
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@invocation_output("conditioning_output")
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class ConditioningOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single conditioning tensor"""
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conditioning: ConditioningField = OutputField(description=FieldDescriptions.cond)
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@invocation_output("conditioning_collection_output")
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class ConditioningCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of conditioning tensors"""
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collection: list[ConditioningField] = OutputField(
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description="The output conditioning tensors",
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)
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@invocation(
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"conditioning",
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title="Conditioning Primitive",
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tags=["primitives", "conditioning"],
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category="primitives",
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version="1.0.0",
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)
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class ConditioningInvocation(BaseInvocation):
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"""A conditioning tensor primitive value"""
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conditioning: ConditioningField = InputField(description=FieldDescriptions.cond, input=Input.Connection)
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def invoke(self, context: InvocationContext) -> ConditioningOutput:
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return ConditioningOutput(conditioning=self.conditioning)
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@invocation(
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"conditioning_collection",
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title="Conditioning Collection Primitive",
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tags=["primitives", "conditioning", "collection"],
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category="primitives",
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version="1.0.0",
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)
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class ConditioningCollectionInvocation(BaseInvocation):
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"""A collection of conditioning tensor primitive values"""
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collection: list[ConditioningField] = InputField(
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default_factory=list,
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description="The collection of conditioning tensors",
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)
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def invoke(self, context: InvocationContext) -> ConditioningCollectionOutput:
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return ConditioningCollectionOutput(collection=self.collection)
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# endregion
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