mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
512 lines
16 KiB
Python
512 lines
16 KiB
Python
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
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from typing import Optional
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import torch
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from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
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from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
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from invokeai.app.invocations.fields import (
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BoundingBoxField,
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ColorField,
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ConditioningField,
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DenoiseMaskField,
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FieldDescriptions,
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ImageField,
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Input,
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InputField,
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LatentsField,
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OutputField,
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TensorField,
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UIComponent,
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)
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from invokeai.app.services.images.images_common import ImageDTO
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from invokeai.app.services.shared.invocation_context import InvocationContext
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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="1.0.1"
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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="1.0.2",
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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=[], 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="1.0.1"
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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="1.0.2",
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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=[], 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="1.0.1")
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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="1.0.2",
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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=[], 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="1.0.1")
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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="1.0.2",
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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=[], 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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@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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@classmethod
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def build(cls, image_dto: ImageDTO) -> "ImageOutput":
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return cls(
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image=ImageField(image_name=image_dto.image_name),
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width=image_dto.width,
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height=image_dto.height,
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)
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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="1.0.2")
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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.images.get_pil(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="1.0.1",
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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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@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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@classmethod
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def build(
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cls, mask_name: str, masked_latents_name: Optional[str] = None, gradient: bool = False
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) -> "DenoiseMaskOutput":
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return cls(
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denoise_mask=DenoiseMaskField(
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mask_name=mask_name, masked_latents_name=masked_latents_name, gradient=gradient
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),
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)
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# endregion
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# region 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(description=FieldDescriptions.latents)
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width: int = OutputField(description=FieldDescriptions.width)
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height: int = OutputField(description=FieldDescriptions.height)
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@classmethod
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def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
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return cls(
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latents=LatentsField(latents_name=latents_name, seed=seed),
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width=latents.size()[3] * LATENT_SCALE_FACTOR,
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height=latents.size()[2] * LATENT_SCALE_FACTOR,
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)
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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="1.0.2"
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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.tensors.load(self.latents.latents_name)
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return LatentsOutput.build(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="1.0.1",
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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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# endregion
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# region Color
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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="1.0.1")
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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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@invocation_output("mask_output")
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class MaskOutput(BaseInvocationOutput):
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"""A torch mask tensor."""
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mask: TensorField = OutputField(description="The mask.")
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width: int = OutputField(description="The width of the mask in pixels.")
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height: int = OutputField(description="The height of the mask in pixels.")
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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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@classmethod
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def build(cls, conditioning_name: str) -> "ConditioningOutput":
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return cls(conditioning=ConditioningField(conditioning_name=conditioning_name))
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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="1.0.1",
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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="1.0.2",
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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=[],
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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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# region BoundingBox
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@invocation_output("bounding_box_output")
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class BoundingBoxOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single bounding box"""
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bounding_box: BoundingBoxField = OutputField(description="The output bounding box.")
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@invocation_output("bounding_box_collection_output")
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class BoundingBoxCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of bounding boxes"""
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collection: list[BoundingBoxField] = OutputField(description="The output bounding boxes.", title="Bounding Boxes")
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@invocation(
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"bounding_box",
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title="Bounding Box",
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tags=["primitives", "segmentation", "collection", "bounding box"],
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category="primitives",
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version="1.0.0",
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)
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class BoundingBoxInvocation(BaseInvocation):
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"""Create a bounding box manually by supplying box coordinates"""
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x_min: int = InputField(default=0, description="x-coordinate of the bounding box's top left vertex")
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y_min: int = InputField(default=0, description="y-coordinate of the bounding box's top left vertex")
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x_max: int = InputField(default=0, description="x-coordinate of the bounding box's bottom right vertex")
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y_max: int = InputField(default=0, description="y-coordinate of the bounding box's bottom right vertex")
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def invoke(self, context: InvocationContext) -> BoundingBoxOutput:
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bounding_box = BoundingBoxField(x_min=self.x_min, y_min=self.y_min, x_max=self.x_max, y_max=self.y_max)
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return BoundingBoxOutput(bounding_box=bounding_box)
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# endregion
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