InvokeAI/invokeai/app/invocations/primitives.py
psychedelicious 43fbac26df feat: move board logic to save_image node
- 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`
2023-09-22 10:11:20 -04:00

482 lines
14 KiB
Python

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