mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
feat(nodes): add version to node schemas
The `@invocation` decorator is extended with an optional `version` arg. On execution of the decorator, the version string is parsed using the `semver` package (this was an indirect dependency and has been added to `pyproject.toml`). All built-in nodes are set with `version="1.0.0"`. The version is added to the OpenAPI Schema for consumption by the client.
This commit is contained in:
psychedelicious
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@ -26,6 +26,7 @@ from typing import (
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from pydantic import BaseModel, Field, validator
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from pydantic.fields import Undefined, ModelField
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from pydantic.typing import NoArgAnyCallable
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import semver
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if TYPE_CHECKING:
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from ..services.invocation_services import InvocationServices
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@ -401,6 +402,9 @@ class UIConfigBase(BaseModel):
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tags: Optional[list[str]] = Field(default_factory=None, description="The node's tags")
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title: Optional[str] = Field(default=None, description="The node's display name")
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category: Optional[str] = Field(default=None, description="The node's category")
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version: Optional[str] = Field(
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default=None, description='The node\'s version. Should be a valid semver string e.g. "1.0.0" or "3.8.13".'
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)
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class InvocationContext:
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@ -499,6 +503,8 @@ class BaseInvocation(ABC, BaseModel):
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schema["tags"] = uiconfig.tags
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if uiconfig and hasattr(uiconfig, "category"):
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schema["category"] = uiconfig.category
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if uiconfig and hasattr(uiconfig, "version"):
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schema["version"] = uiconfig.version
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if "required" not in schema or not isinstance(schema["required"], list):
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schema["required"] = list()
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schema["required"].extend(["type", "id"])
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@ -567,7 +573,11 @@ GenericBaseInvocation = TypeVar("GenericBaseInvocation", bound=BaseInvocation)
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def invocation(
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invocation_type: str, title: Optional[str] = None, tags: Optional[list[str]] = None, category: Optional[str] = None
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invocation_type: str,
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title: Optional[str] = None,
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tags: Optional[list[str]] = None,
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category: Optional[str] = None,
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version: Optional[str] = None,
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) -> Callable[[Type[GenericBaseInvocation]], Type[GenericBaseInvocation]]:
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"""
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Adds metadata to an invocation.
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@ -594,6 +604,9 @@ def invocation(
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cls.UIConfig.tags = tags
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if category is not None:
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cls.UIConfig.category = category
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if version is not None:
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semver.Version.parse(version) # raises ValueError if invalid semver
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cls.UIConfig.version = version
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# Add the invocation type to the pydantic model of the invocation
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invocation_type_annotation = Literal[invocation_type] # type: ignore
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@ -10,7 +10,9 @@ from invokeai.app.util.misc import SEED_MAX, get_random_seed
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from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
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@invocation("range", title="Integer Range", tags=["collection", "integer", "range"], category="collections")
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@invocation(
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"range", title="Integer Range", tags=["collection", "integer", "range"], category="collections", version="1.0.0"
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)
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class RangeInvocation(BaseInvocation):
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"""Creates a range of numbers from start to stop with step"""
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@ -33,6 +35,7 @@ class RangeInvocation(BaseInvocation):
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title="Integer Range of Size",
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tags=["collection", "integer", "size", "range"],
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category="collections",
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version="1.0.0",
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)
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class RangeOfSizeInvocation(BaseInvocation):
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"""Creates a range from start to start + size with step"""
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@ -50,6 +53,7 @@ class RangeOfSizeInvocation(BaseInvocation):
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title="Random Range",
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tags=["range", "integer", "random", "collection"],
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category="collections",
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version="1.0.0",
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)
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class RandomRangeInvocation(BaseInvocation):
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"""Creates a collection of random numbers"""
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@ -44,7 +44,7 @@ class ConditioningFieldData:
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# PerpNeg = "perp_neg"
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@invocation("compel", title="Prompt", tags=["prompt", "compel"], category="conditioning")
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@invocation("compel", title="Prompt", tags=["prompt", "compel"], category="conditioning", version="1.0.0")
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class CompelInvocation(BaseInvocation):
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"""Parse prompt using compel package to conditioning."""
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@ -267,6 +267,7 @@ class SDXLPromptInvocationBase:
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title="SDXL Prompt",
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tags=["sdxl", "compel", "prompt"],
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category="conditioning",
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version="1.0.0",
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)
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class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
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"""Parse prompt using compel package to conditioning."""
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@ -351,6 +352,7 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
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title="SDXL Refiner Prompt",
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tags=["sdxl", "compel", "prompt"],
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category="conditioning",
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version="1.0.0",
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)
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class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
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"""Parse prompt using compel package to conditioning."""
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@ -403,7 +405,7 @@ class ClipSkipInvocationOutput(BaseInvocationOutput):
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clip: ClipField = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
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@invocation("clip_skip", title="CLIP Skip", tags=["clipskip", "clip", "skip"], category="conditioning")
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@invocation("clip_skip", title="CLIP Skip", tags=["clipskip", "clip", "skip"], category="conditioning", version="1.0.0")
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class ClipSkipInvocation(BaseInvocation):
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"""Skip layers in clip text_encoder model."""
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@ -95,7 +95,7 @@ class ControlOutput(BaseInvocationOutput):
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control: ControlField = OutputField(description=FieldDescriptions.control)
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@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet")
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@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.0.0")
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class ControlNetInvocation(BaseInvocation):
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"""Collects ControlNet info to pass to other nodes"""
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@ -127,7 +127,9 @@ class ControlNetInvocation(BaseInvocation):
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)
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@invocation("image_processor", title="Base Image Processor", tags=["controlnet"], category="controlnet")
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@invocation(
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"image_processor", title="Base Image Processor", tags=["controlnet"], category="controlnet", version="1.0.0"
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)
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class ImageProcessorInvocation(BaseInvocation):
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"""Base class for invocations that preprocess images for ControlNet"""
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@ -171,6 +173,7 @@ class ImageProcessorInvocation(BaseInvocation):
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title="Canny Processor",
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tags=["controlnet", "canny"],
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category="controlnet",
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version="1.0.0",
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)
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class CannyImageProcessorInvocation(ImageProcessorInvocation):
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"""Canny edge detection for ControlNet"""
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@ -193,6 +196,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
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title="HED (softedge) Processor",
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tags=["controlnet", "hed", "softedge"],
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category="controlnet",
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version="1.0.0",
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)
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class HedImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies HED edge detection to image"""
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@ -221,6 +225,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation):
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title="Lineart Processor",
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tags=["controlnet", "lineart"],
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category="controlnet",
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version="1.0.0",
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)
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class LineartImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies line art processing to image"""
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@ -242,6 +247,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation):
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title="Lineart Anime Processor",
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tags=["controlnet", "lineart", "anime"],
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category="controlnet",
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version="1.0.0",
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)
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class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies line art anime processing to image"""
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@ -264,6 +270,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
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title="Openpose Processor",
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tags=["controlnet", "openpose", "pose"],
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category="controlnet",
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version="1.0.0",
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)
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class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies Openpose processing to image"""
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@ -288,6 +295,7 @@ class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
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title="Midas Depth Processor",
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tags=["controlnet", "midas"],
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category="controlnet",
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version="1.0.0",
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)
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class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies Midas depth processing to image"""
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@ -314,6 +322,7 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
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title="Normal BAE Processor",
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tags=["controlnet"],
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category="controlnet",
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version="1.0.0",
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)
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class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies NormalBae processing to image"""
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@ -329,7 +338,9 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
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return processed_image
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@invocation("mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet")
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@invocation(
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"mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.0.0"
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)
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class MlsdImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies MLSD processing to image"""
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@ -350,7 +361,9 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation):
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return processed_image
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@invocation("pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet")
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@invocation(
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"pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.0.0"
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)
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class PidiImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies PIDI processing to image"""
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@ -376,6 +389,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation):
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title="Content Shuffle Processor",
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tags=["controlnet", "contentshuffle"],
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category="controlnet",
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version="1.0.0",
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)
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class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies content shuffle processing to image"""
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@ -405,6 +419,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
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title="Zoe (Depth) Processor",
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tags=["controlnet", "zoe", "depth"],
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category="controlnet",
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version="1.0.0",
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)
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class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies Zoe depth processing to image"""
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@ -420,6 +435,7 @@ class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
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title="Mediapipe Face Processor",
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tags=["controlnet", "mediapipe", "face"],
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category="controlnet",
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version="1.0.0",
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)
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class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
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"""Applies mediapipe face processing to image"""
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@ -442,6 +458,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
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title="Leres (Depth) Processor",
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tags=["controlnet", "leres", "depth"],
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category="controlnet",
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version="1.0.0",
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)
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class LeresImageProcessorInvocation(ImageProcessorInvocation):
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"""Applies leres processing to image"""
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@ -470,6 +487,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
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title="Tile Resample Processor",
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tags=["controlnet", "tile"],
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category="controlnet",
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version="1.0.0",
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)
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class TileResamplerProcessorInvocation(ImageProcessorInvocation):
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"""Tile resampler processor"""
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@ -509,6 +527,7 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation):
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title="Segment Anything Processor",
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tags=["controlnet", "segmentanything"],
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category="controlnet",
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version="1.0.0",
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)
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class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
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"""Applies segment anything processing to image"""
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@ -10,12 +10,7 @@ from invokeai.app.models.image import ImageCategory, ResourceOrigin
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from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
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@invocation(
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"cv_inpaint",
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title="OpenCV Inpaint",
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tags=["opencv", "inpaint"],
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category="inpaint",
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)
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@invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.0.0")
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class CvInpaintInvocation(BaseInvocation):
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"""Simple inpaint using opencv."""
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@ -16,7 +16,7 @@ from ..models.image import ImageCategory, ResourceOrigin
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from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, invocation
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@invocation("show_image", title="Show Image", tags=["image"], category="image")
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@invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.0")
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class ShowImageInvocation(BaseInvocation):
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"""Displays a provided image using the OS image viewer, and passes it forward in the pipeline."""
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@ -36,7 +36,7 @@ class ShowImageInvocation(BaseInvocation):
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)
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@invocation("blank_image", title="Blank Image", tags=["image"], category="image")
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@invocation("blank_image", title="Blank Image", tags=["image"], category="image", version="1.0.0")
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class BlankImageInvocation(BaseInvocation):
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"""Creates a blank image and forwards it to the pipeline"""
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@ -65,7 +65,7 @@ class BlankImageInvocation(BaseInvocation):
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)
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@invocation("img_crop", title="Crop Image", tags=["image", "crop"], category="image")
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@invocation("img_crop", title="Crop Image", tags=["image", "crop"], category="image", version="1.0.0")
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class ImageCropInvocation(BaseInvocation):
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"""Crops an image to a specified box. The box can be outside of the image."""
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@ -98,7 +98,7 @@ class ImageCropInvocation(BaseInvocation):
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)
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@invocation("img_paste", title="Paste Image", tags=["image", "paste"], category="image")
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@invocation("img_paste", title="Paste Image", tags=["image", "paste"], category="image", version="1.0.0")
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class ImagePasteInvocation(BaseInvocation):
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"""Pastes an image into another image."""
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@ -146,7 +146,7 @@ class ImagePasteInvocation(BaseInvocation):
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)
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@invocation("tomask", title="Mask from Alpha", tags=["image", "mask"], category="image")
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@invocation("tomask", title="Mask from Alpha", tags=["image", "mask"], category="image", version="1.0.0")
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class MaskFromAlphaInvocation(BaseInvocation):
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"""Extracts the alpha channel of an image as a mask."""
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@ -177,7 +177,7 @@ class MaskFromAlphaInvocation(BaseInvocation):
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)
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@invocation("img_mul", title="Multiply Images", tags=["image", "multiply"], category="image")
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@invocation("img_mul", title="Multiply Images", tags=["image", "multiply"], category="image", version="1.0.0")
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class ImageMultiplyInvocation(BaseInvocation):
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"""Multiplies two images together using `PIL.ImageChops.multiply()`."""
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@ -210,7 +210,7 @@ class ImageMultiplyInvocation(BaseInvocation):
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IMAGE_CHANNELS = Literal["A", "R", "G", "B"]
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@invocation("img_chan", title="Extract Image Channel", tags=["image", "channel"], category="image")
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@invocation("img_chan", title="Extract Image Channel", tags=["image", "channel"], category="image", version="1.0.0")
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class ImageChannelInvocation(BaseInvocation):
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"""Gets a channel from an image."""
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@ -242,7 +242,7 @@ class ImageChannelInvocation(BaseInvocation):
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IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
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@invocation("img_conv", title="Convert Image Mode", tags=["image", "convert"], category="image")
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@invocation("img_conv", title="Convert Image Mode", tags=["image", "convert"], category="image", version="1.0.0")
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class ImageConvertInvocation(BaseInvocation):
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"""Converts an image to a different mode."""
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@ -271,7 +271,7 @@ class ImageConvertInvocation(BaseInvocation):
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)
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@invocation("img_blur", title="Blur Image", tags=["image", "blur"], category="image")
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@invocation("img_blur", title="Blur Image", tags=["image", "blur"], category="image", version="1.0.0")
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class ImageBlurInvocation(BaseInvocation):
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"""Blurs an image"""
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@ -325,7 +325,7 @@ PIL_RESAMPLING_MAP = {
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}
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@invocation("img_resize", title="Resize Image", tags=["image", "resize"], category="image")
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@invocation("img_resize", title="Resize Image", tags=["image", "resize"], category="image", version="1.0.0")
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class ImageResizeInvocation(BaseInvocation):
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"""Resizes an image to specific dimensions"""
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@ -365,7 +365,7 @@ class ImageResizeInvocation(BaseInvocation):
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)
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@invocation("img_scale", title="Scale Image", tags=["image", "scale"], category="image")
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@invocation("img_scale", title="Scale Image", tags=["image", "scale"], category="image", version="1.0.0")
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class ImageScaleInvocation(BaseInvocation):
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"""Scales an image by a factor"""
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@ -406,7 +406,7 @@ class ImageScaleInvocation(BaseInvocation):
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)
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@invocation("img_lerp", title="Lerp Image", tags=["image", "lerp"], category="image")
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@invocation("img_lerp", title="Lerp Image", tags=["image", "lerp"], category="image", version="1.0.0")
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class ImageLerpInvocation(BaseInvocation):
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"""Linear interpolation of all pixels of an image"""
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@ -439,7 +439,7 @@ class ImageLerpInvocation(BaseInvocation):
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)
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@invocation("img_ilerp", title="Inverse Lerp Image", tags=["image", "ilerp"], category="image")
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@invocation("img_ilerp", title="Inverse Lerp Image", tags=["image", "ilerp"], category="image", version="1.0.0")
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class ImageInverseLerpInvocation(BaseInvocation):
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"""Inverse linear interpolation of all pixels of an image"""
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@ -472,7 +472,7 @@ class ImageInverseLerpInvocation(BaseInvocation):
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)
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@invocation("img_nsfw", title="Blur NSFW Image", tags=["image", "nsfw"], category="image")
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@invocation("img_nsfw", title="Blur NSFW Image", tags=["image", "nsfw"], category="image", version="1.0.0")
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class ImageNSFWBlurInvocation(BaseInvocation):
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"""Add blur to NSFW-flagged images"""
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@ -517,7 +517,9 @@ class ImageNSFWBlurInvocation(BaseInvocation):
|
||||
return caution.resize((caution.width // 2, caution.height // 2))
|
||||
|
||||
|
||||
@invocation("img_watermark", title="Add Invisible Watermark", tags=["image", "watermark"], category="image")
|
||||
@invocation(
|
||||
"img_watermark", title="Add Invisible Watermark", tags=["image", "watermark"], category="image", version="1.0.0"
|
||||
)
|
||||
class ImageWatermarkInvocation(BaseInvocation):
|
||||
"""Add an invisible watermark to an image"""
|
||||
|
||||
@ -548,7 +550,7 @@ class ImageWatermarkInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("mask_edge", title="Mask Edge", tags=["image", "mask", "inpaint"], category="image")
|
||||
@invocation("mask_edge", title="Mask Edge", tags=["image", "mask", "inpaint"], category="image", version="1.0.0")
|
||||
class MaskEdgeInvocation(BaseInvocation):
|
||||
"""Applies an edge mask to an image"""
|
||||
|
||||
@ -593,7 +595,9 @@ class MaskEdgeInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("mask_combine", title="Combine Masks", tags=["image", "mask", "multiply"], category="image")
|
||||
@invocation(
|
||||
"mask_combine", title="Combine Masks", tags=["image", "mask", "multiply"], category="image", version="1.0.0"
|
||||
)
|
||||
class MaskCombineInvocation(BaseInvocation):
|
||||
"""Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`."""
|
||||
|
||||
@ -623,7 +627,7 @@ class MaskCombineInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("color_correct", title="Color Correct", tags=["image", "color"], category="image")
|
||||
@invocation("color_correct", title="Color Correct", tags=["image", "color"], category="image", version="1.0.0")
|
||||
class ColorCorrectInvocation(BaseInvocation):
|
||||
"""
|
||||
Shifts the colors of a target image to match the reference image, optionally
|
||||
@ -728,7 +732,7 @@ class ColorCorrectInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("img_hue_adjust", title="Adjust Image Hue", tags=["image", "hue"], category="image")
|
||||
@invocation("img_hue_adjust", title="Adjust Image Hue", tags=["image", "hue"], category="image", version="1.0.0")
|
||||
class ImageHueAdjustmentInvocation(BaseInvocation):
|
||||
"""Adjusts the Hue of an image."""
|
||||
|
||||
@ -774,6 +778,7 @@ class ImageHueAdjustmentInvocation(BaseInvocation):
|
||||
title="Adjust Image Luminosity",
|
||||
tags=["image", "luminosity", "hsl"],
|
||||
category="image",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ImageLuminosityAdjustmentInvocation(BaseInvocation):
|
||||
"""Adjusts the Luminosity (Value) of an image."""
|
||||
@ -826,6 +831,7 @@ class ImageLuminosityAdjustmentInvocation(BaseInvocation):
|
||||
title="Adjust Image Saturation",
|
||||
tags=["image", "saturation", "hsl"],
|
||||
category="image",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ImageSaturationAdjustmentInvocation(BaseInvocation):
|
||||
"""Adjusts the Saturation of an image."""
|
||||
|
||||
@ -116,7 +116,7 @@ def tile_fill_missing(im: Image.Image, tile_size: int = 16, seed: Optional[int]
|
||||
return si
|
||||
|
||||
|
||||
@invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint")
|
||||
@invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint", version="1.0.0")
|
||||
class InfillColorInvocation(BaseInvocation):
|
||||
"""Infills transparent areas of an image with a solid color"""
|
||||
|
||||
@ -151,7 +151,7 @@ class InfillColorInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint")
|
||||
@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint", version="1.0.0")
|
||||
class InfillTileInvocation(BaseInvocation):
|
||||
"""Infills transparent areas of an image with tiles of the image"""
|
||||
|
||||
@ -187,7 +187,9 @@ class InfillTileInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint")
|
||||
@invocation(
|
||||
"infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint", version="1.0.0"
|
||||
)
|
||||
class InfillPatchMatchInvocation(BaseInvocation):
|
||||
"""Infills transparent areas of an image using the PatchMatch algorithm"""
|
||||
|
||||
@ -218,7 +220,7 @@ class InfillPatchMatchInvocation(BaseInvocation):
|
||||
)
|
||||
|
||||
|
||||
@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint")
|
||||
@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint", version="1.0.0")
|
||||
class LaMaInfillInvocation(BaseInvocation):
|
||||
"""Infills transparent areas of an image using the LaMa model"""
|
||||
|
||||
|
||||
@ -74,7 +74,7 @@ class SchedulerOutput(BaseInvocationOutput):
|
||||
scheduler: SAMPLER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler)
|
||||
|
||||
|
||||
@invocation("scheduler", title="Scheduler", tags=["scheduler"], category="latents")
|
||||
@invocation("scheduler", title="Scheduler", tags=["scheduler"], category="latents", version="1.0.0")
|
||||
class SchedulerInvocation(BaseInvocation):
|
||||
"""Selects a scheduler."""
|
||||
|
||||
@ -86,7 +86,9 @@ class SchedulerInvocation(BaseInvocation):
|
||||
return SchedulerOutput(scheduler=self.scheduler)
|
||||
|
||||
|
||||
@invocation("create_denoise_mask", title="Create Denoise Mask", tags=["mask", "denoise"], category="latents")
|
||||
@invocation(
|
||||
"create_denoise_mask", title="Create Denoise Mask", tags=["mask", "denoise"], category="latents", version="1.0.0"
|
||||
)
|
||||
class CreateDenoiseMaskInvocation(BaseInvocation):
|
||||
"""Creates mask for denoising model run."""
|
||||
|
||||
@ -186,6 +188,7 @@ def get_scheduler(
|
||||
title="Denoise Latents",
|
||||
tags=["latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"],
|
||||
category="latents",
|
||||
version="1.0.0",
|
||||
)
|
||||
class DenoiseLatentsInvocation(BaseInvocation):
|
||||
"""Denoises noisy latents to decodable images"""
|
||||
@ -544,7 +547,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
|
||||
return build_latents_output(latents_name=name, latents=result_latents, seed=seed)
|
||||
|
||||
|
||||
@invocation("l2i", title="Latents to Image", tags=["latents", "image", "vae", "l2i"], category="latents")
|
||||
@invocation(
|
||||
"l2i", title="Latents to Image", tags=["latents", "image", "vae", "l2i"], category="latents", version="1.0.0"
|
||||
)
|
||||
class LatentsToImageInvocation(BaseInvocation):
|
||||
"""Generates an image from latents."""
|
||||
|
||||
@ -641,7 +646,7 @@ class LatentsToImageInvocation(BaseInvocation):
|
||||
LATENTS_INTERPOLATION_MODE = Literal["nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"]
|
||||
|
||||
|
||||
@invocation("lresize", title="Resize Latents", tags=["latents", "resize"], category="latents")
|
||||
@invocation("lresize", title="Resize Latents", tags=["latents", "resize"], category="latents", version="1.0.0")
|
||||
class ResizeLatentsInvocation(BaseInvocation):
|
||||
"""Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8."""
|
||||
|
||||
@ -685,7 +690,7 @@ class ResizeLatentsInvocation(BaseInvocation):
|
||||
return build_latents_output(latents_name=name, latents=resized_latents, seed=self.latents.seed)
|
||||
|
||||
|
||||
@invocation("lscale", title="Scale Latents", tags=["latents", "resize"], category="latents")
|
||||
@invocation("lscale", title="Scale Latents", tags=["latents", "resize"], category="latents", version="1.0.0")
|
||||
class ScaleLatentsInvocation(BaseInvocation):
|
||||
"""Scales latents by a given factor."""
|
||||
|
||||
@ -721,7 +726,9 @@ class ScaleLatentsInvocation(BaseInvocation):
|
||||
return build_latents_output(latents_name=name, latents=resized_latents, seed=self.latents.seed)
|
||||
|
||||
|
||||
@invocation("i2l", title="Image to Latents", tags=["latents", "image", "vae", "i2l"], category="latents")
|
||||
@invocation(
|
||||
"i2l", title="Image to Latents", tags=["latents", "image", "vae", "i2l"], category="latents", version="1.0.0"
|
||||
)
|
||||
class ImageToLatentsInvocation(BaseInvocation):
|
||||
"""Encodes an image into latents."""
|
||||
|
||||
@ -801,7 +808,7 @@ class ImageToLatentsInvocation(BaseInvocation):
|
||||
return build_latents_output(latents_name=name, latents=latents, seed=None)
|
||||
|
||||
|
||||
@invocation("lblend", title="Blend Latents", tags=["latents", "blend"], category="latents")
|
||||
@invocation("lblend", title="Blend Latents", tags=["latents", "blend"], category="latents", version="1.0.0")
|
||||
class BlendLatentsInvocation(BaseInvocation):
|
||||
"""Blend two latents using a given alpha. Latents must have same size."""
|
||||
|
||||
|
||||
@ -7,7 +7,7 @@ from invokeai.app.invocations.primitives import IntegerOutput
|
||||
from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, invocation
|
||||
|
||||
|
||||
@invocation("add", title="Add Integers", tags=["math", "add"], category="math")
|
||||
@invocation("add", title="Add Integers", tags=["math", "add"], category="math", version="1.0.0")
|
||||
class AddInvocation(BaseInvocation):
|
||||
"""Adds two numbers"""
|
||||
|
||||
@ -18,7 +18,7 @@ class AddInvocation(BaseInvocation):
|
||||
return IntegerOutput(value=self.a + self.b)
|
||||
|
||||
|
||||
@invocation("sub", title="Subtract Integers", tags=["math", "subtract"], category="math")
|
||||
@invocation("sub", title="Subtract Integers", tags=["math", "subtract"], category="math", version="1.0.0")
|
||||
class SubtractInvocation(BaseInvocation):
|
||||
"""Subtracts two numbers"""
|
||||
|
||||
@ -29,7 +29,7 @@ class SubtractInvocation(BaseInvocation):
|
||||
return IntegerOutput(value=self.a - self.b)
|
||||
|
||||
|
||||
@invocation("mul", title="Multiply Integers", tags=["math", "multiply"], category="math")
|
||||
@invocation("mul", title="Multiply Integers", tags=["math", "multiply"], category="math", version="1.0.0")
|
||||
class MultiplyInvocation(BaseInvocation):
|
||||
"""Multiplies two numbers"""
|
||||
|
||||
@ -40,7 +40,7 @@ class MultiplyInvocation(BaseInvocation):
|
||||
return IntegerOutput(value=self.a * self.b)
|
||||
|
||||
|
||||
@invocation("div", title="Divide Integers", tags=["math", "divide"], category="math")
|
||||
@invocation("div", title="Divide Integers", tags=["math", "divide"], category="math", version="1.0.0")
|
||||
class DivideInvocation(BaseInvocation):
|
||||
"""Divides two numbers"""
|
||||
|
||||
@ -51,7 +51,7 @@ class DivideInvocation(BaseInvocation):
|
||||
return IntegerOutput(value=int(self.a / self.b))
|
||||
|
||||
|
||||
@invocation("rand_int", title="Random Integer", tags=["math", "random"], category="math")
|
||||
@invocation("rand_int", title="Random Integer", tags=["math", "random"], category="math", version="1.0.0")
|
||||
class RandomIntInvocation(BaseInvocation):
|
||||
"""Outputs a single random integer."""
|
||||
|
||||
|
||||
@ -98,7 +98,9 @@ class MetadataAccumulatorOutput(BaseInvocationOutput):
|
||||
metadata: CoreMetadata = OutputField(description="The core metadata for the image")
|
||||
|
||||
|
||||
@invocation("metadata_accumulator", title="Metadata Accumulator", tags=["metadata"], category="metadata")
|
||||
@invocation(
|
||||
"metadata_accumulator", title="Metadata Accumulator", tags=["metadata"], category="metadata", version="1.0.0"
|
||||
)
|
||||
class MetadataAccumulatorInvocation(BaseInvocation):
|
||||
"""Outputs a Core Metadata Object"""
|
||||
|
||||
|
||||
@ -73,7 +73,7 @@ class LoRAModelField(BaseModel):
|
||||
base_model: BaseModelType = Field(description="Base model")
|
||||
|
||||
|
||||
@invocation("main_model_loader", title="Main Model", tags=["model"], category="model")
|
||||
@invocation("main_model_loader", title="Main Model", tags=["model"], category="model", version="1.0.0")
|
||||
class MainModelLoaderInvocation(BaseInvocation):
|
||||
"""Loads a main model, outputting its submodels."""
|
||||
|
||||
@ -173,7 +173,7 @@ class LoraLoaderOutput(BaseInvocationOutput):
|
||||
clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
|
||||
|
||||
|
||||
@invocation("lora_loader", title="LoRA", tags=["model"], category="model")
|
||||
@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.0")
|
||||
class LoraLoaderInvocation(BaseInvocation):
|
||||
"""Apply selected lora to unet and text_encoder."""
|
||||
|
||||
@ -244,7 +244,7 @@ class SDXLLoraLoaderOutput(BaseInvocationOutput):
|
||||
clip2: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP 2")
|
||||
|
||||
|
||||
@invocation("sdxl_lora_loader", title="SDXL LoRA", tags=["lora", "model"], category="model")
|
||||
@invocation("sdxl_lora_loader", title="SDXL LoRA", tags=["lora", "model"], category="model", version="1.0.0")
|
||||
class SDXLLoraLoaderInvocation(BaseInvocation):
|
||||
"""Apply selected lora to unet and text_encoder."""
|
||||
|
||||
@ -338,7 +338,7 @@ class VaeLoaderOutput(BaseInvocationOutput):
|
||||
vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
|
||||
|
||||
|
||||
@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model")
|
||||
@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.0")
|
||||
class VaeLoaderInvocation(BaseInvocation):
|
||||
"""Loads a VAE model, outputting a VaeLoaderOutput"""
|
||||
|
||||
@ -376,7 +376,7 @@ class SeamlessModeOutput(BaseInvocationOutput):
|
||||
vae: Optional[VaeField] = OutputField(description=FieldDescriptions.vae, title="VAE")
|
||||
|
||||
|
||||
@invocation("seamless", title="Seamless", tags=["seamless", "model"], category="model")
|
||||
@invocation("seamless", title="Seamless", tags=["seamless", "model"], category="model", version="1.0.0")
|
||||
class SeamlessModeInvocation(BaseInvocation):
|
||||
"""Applies the seamless transformation to the Model UNet and VAE."""
|
||||
|
||||
|
||||
@ -78,7 +78,7 @@ def build_noise_output(latents_name: str, latents: torch.Tensor, seed: int):
|
||||
)
|
||||
|
||||
|
||||
@invocation("noise", title="Noise", tags=["latents", "noise"], category="latents")
|
||||
@invocation("noise", title="Noise", tags=["latents", "noise"], category="latents", version="1.0.0")
|
||||
class NoiseInvocation(BaseInvocation):
|
||||
"""Generates latent noise."""
|
||||
|
||||
|
||||
@ -56,7 +56,7 @@ ORT_TO_NP_TYPE = {
|
||||
PRECISION_VALUES = Literal[tuple(list(ORT_TO_NP_TYPE.keys()))]
|
||||
|
||||
|
||||
@invocation("prompt_onnx", title="ONNX Prompt (Raw)", tags=["prompt", "onnx"], category="conditioning")
|
||||
@invocation("prompt_onnx", title="ONNX Prompt (Raw)", tags=["prompt", "onnx"], category="conditioning", version="1.0.0")
|
||||
class ONNXPromptInvocation(BaseInvocation):
|
||||
prompt: str = InputField(default="", description=FieldDescriptions.raw_prompt, ui_component=UIComponent.Textarea)
|
||||
clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
|
||||
@ -143,6 +143,7 @@ class ONNXPromptInvocation(BaseInvocation):
|
||||
title="ONNX Text to Latents",
|
||||
tags=["latents", "inference", "txt2img", "onnx"],
|
||||
category="latents",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ONNXTextToLatentsInvocation(BaseInvocation):
|
||||
"""Generates latents from conditionings."""
|
||||
@ -319,6 +320,7 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
|
||||
title="ONNX Latents to Image",
|
||||
tags=["latents", "image", "vae", "onnx"],
|
||||
category="image",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ONNXLatentsToImageInvocation(BaseInvocation):
|
||||
"""Generates an image from latents."""
|
||||
@ -403,7 +405,7 @@ class OnnxModelField(BaseModel):
|
||||
model_type: ModelType = Field(description="Model Type")
|
||||
|
||||
|
||||
@invocation("onnx_model_loader", title="ONNX Main Model", tags=["onnx", "model"], category="model")
|
||||
@invocation("onnx_model_loader", title="ONNX Main Model", tags=["onnx", "model"], category="model", version="1.0.0")
|
||||
class OnnxModelLoaderInvocation(BaseInvocation):
|
||||
"""Loads a main model, outputting its submodels."""
|
||||
|
||||
|
||||
@ -45,7 +45,7 @@ from invokeai.app.invocations.primitives import FloatCollectionOutput
|
||||
from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
|
||||
|
||||
|
||||
@invocation("float_range", title="Float Range", tags=["math", "range"], category="math")
|
||||
@invocation("float_range", title="Float Range", tags=["math", "range"], category="math", version="1.0.0")
|
||||
class FloatLinearRangeInvocation(BaseInvocation):
|
||||
"""Creates a range"""
|
||||
|
||||
@ -96,7 +96,7 @@ EASING_FUNCTION_KEYS = Literal[tuple(list(EASING_FUNCTIONS_MAP.keys()))]
|
||||
|
||||
|
||||
# actually I think for now could just use CollectionOutput (which is list[Any]
|
||||
@invocation("step_param_easing", title="Step Param Easing", tags=["step", "easing"], category="step")
|
||||
@invocation("step_param_easing", title="Step Param Easing", tags=["step", "easing"], category="step", version="1.0.0")
|
||||
class StepParamEasingInvocation(BaseInvocation):
|
||||
"""Experimental per-step parameter easing for denoising steps"""
|
||||
|
||||
|
||||
@ -44,7 +44,9 @@ class BooleanCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("boolean", title="Boolean Primitive", tags=["primitives", "boolean"], category="primitives")
|
||||
@invocation(
|
||||
"boolean", title="Boolean Primitive", tags=["primitives", "boolean"], category="primitives", version="1.0.0"
|
||||
)
|
||||
class BooleanInvocation(BaseInvocation):
|
||||
"""A boolean primitive value"""
|
||||
|
||||
@ -59,6 +61,7 @@ class BooleanInvocation(BaseInvocation):
|
||||
title="Boolean Collection Primitive",
|
||||
tags=["primitives", "boolean", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class BooleanCollectionInvocation(BaseInvocation):
|
||||
"""A collection of boolean primitive values"""
|
||||
@ -90,7 +93,9 @@ class IntegerCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("integer", title="Integer Primitive", tags=["primitives", "integer"], category="primitives")
|
||||
@invocation(
|
||||
"integer", title="Integer Primitive", tags=["primitives", "integer"], category="primitives", version="1.0.0"
|
||||
)
|
||||
class IntegerInvocation(BaseInvocation):
|
||||
"""An integer primitive value"""
|
||||
|
||||
@ -105,6 +110,7 @@ class IntegerInvocation(BaseInvocation):
|
||||
title="Integer Collection Primitive",
|
||||
tags=["primitives", "integer", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class IntegerCollectionInvocation(BaseInvocation):
|
||||
"""A collection of integer primitive values"""
|
||||
@ -136,7 +142,7 @@ class FloatCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("float", title="Float Primitive", tags=["primitives", "float"], category="primitives")
|
||||
@invocation("float", title="Float Primitive", tags=["primitives", "float"], category="primitives", version="1.0.0")
|
||||
class FloatInvocation(BaseInvocation):
|
||||
"""A float primitive value"""
|
||||
|
||||
@ -151,6 +157,7 @@ class FloatInvocation(BaseInvocation):
|
||||
title="Float Collection Primitive",
|
||||
tags=["primitives", "float", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class FloatCollectionInvocation(BaseInvocation):
|
||||
"""A collection of float primitive values"""
|
||||
@ -182,7 +189,7 @@ class StringCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("string", title="String Primitive", tags=["primitives", "string"], category="primitives")
|
||||
@invocation("string", title="String Primitive", tags=["primitives", "string"], category="primitives", version="1.0.0")
|
||||
class StringInvocation(BaseInvocation):
|
||||
"""A string primitive value"""
|
||||
|
||||
@ -197,6 +204,7 @@ class StringInvocation(BaseInvocation):
|
||||
title="String Collection Primitive",
|
||||
tags=["primitives", "string", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class StringCollectionInvocation(BaseInvocation):
|
||||
"""A collection of string primitive values"""
|
||||
@ -236,7 +244,7 @@ class ImageCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives")
|
||||
@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives", version="1.0.0")
|
||||
class ImageInvocation(BaseInvocation):
|
||||
"""An image primitive value"""
|
||||
|
||||
@ -257,6 +265,7 @@ class ImageInvocation(BaseInvocation):
|
||||
title="Image Collection Primitive",
|
||||
tags=["primitives", "image", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ImageCollectionInvocation(BaseInvocation):
|
||||
"""A collection of image primitive values"""
|
||||
@ -318,7 +327,9 @@ class LatentsCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives")
|
||||
@invocation(
|
||||
"latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives", version="1.0.0"
|
||||
)
|
||||
class LatentsInvocation(BaseInvocation):
|
||||
"""A latents tensor primitive value"""
|
||||
|
||||
@ -335,6 +346,7 @@ class LatentsInvocation(BaseInvocation):
|
||||
title="Latents Collection Primitive",
|
||||
tags=["primitives", "latents", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class LatentsCollectionInvocation(BaseInvocation):
|
||||
"""A collection of latents tensor primitive values"""
|
||||
@ -388,7 +400,7 @@ class ColorCollectionOutput(BaseInvocationOutput):
|
||||
)
|
||||
|
||||
|
||||
@invocation("color", title="Color Primitive", tags=["primitives", "color"], category="primitives")
|
||||
@invocation("color", title="Color Primitive", tags=["primitives", "color"], category="primitives", version="1.0.0")
|
||||
class ColorInvocation(BaseInvocation):
|
||||
"""A color primitive value"""
|
||||
|
||||
@ -430,6 +442,7 @@ class ConditioningCollectionOutput(BaseInvocationOutput):
|
||||
title="Conditioning Primitive",
|
||||
tags=["primitives", "conditioning"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ConditioningInvocation(BaseInvocation):
|
||||
"""A conditioning tensor primitive value"""
|
||||
@ -445,6 +458,7 @@ class ConditioningInvocation(BaseInvocation):
|
||||
title="Conditioning Collection Primitive",
|
||||
tags=["primitives", "conditioning", "collection"],
|
||||
category="primitives",
|
||||
version="1.0.0",
|
||||
)
|
||||
class ConditioningCollectionInvocation(BaseInvocation):
|
||||
"""A collection of conditioning tensor primitive values"""
|
||||
|
||||
@ -10,7 +10,7 @@ from invokeai.app.invocations.primitives import StringCollectionOutput
|
||||
from .baseinvocation import BaseInvocation, InputField, InvocationContext, UIComponent, invocation
|
||||
|
||||
|
||||
@invocation("dynamic_prompt", title="Dynamic Prompt", tags=["prompt", "collection"], category="prompt")
|
||||
@invocation("dynamic_prompt", title="Dynamic Prompt", tags=["prompt", "collection"], category="prompt", version="1.0.0")
|
||||
class DynamicPromptInvocation(BaseInvocation):
|
||||
"""Parses a prompt using adieyal/dynamicprompts' random or combinatorial generator"""
|
||||
|
||||
@ -29,7 +29,7 @@ class DynamicPromptInvocation(BaseInvocation):
|
||||
return StringCollectionOutput(collection=prompts)
|
||||
|
||||
|
||||
@invocation("prompt_from_file", title="Prompts from File", tags=["prompt", "file"], category="prompt")
|
||||
@invocation("prompt_from_file", title="Prompts from File", tags=["prompt", "file"], category="prompt", version="1.0.0")
|
||||
class PromptsFromFileInvocation(BaseInvocation):
|
||||
"""Loads prompts from a text file"""
|
||||
|
||||
|
||||
@ -33,7 +33,7 @@ class SDXLRefinerModelLoaderOutput(BaseInvocationOutput):
|
||||
vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
|
||||
|
||||
|
||||
@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model")
|
||||
@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.0")
|
||||
class SDXLModelLoaderInvocation(BaseInvocation):
|
||||
"""Loads an sdxl base model, outputting its submodels."""
|
||||
|
||||
@ -119,6 +119,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
|
||||
title="SDXL Refiner Model",
|
||||
tags=["model", "sdxl", "refiner"],
|
||||
category="model",
|
||||
version="1.0.0",
|
||||
)
|
||||
class SDXLRefinerModelLoaderInvocation(BaseInvocation):
|
||||
"""Loads an sdxl refiner model, outputting its submodels."""
|
||||
|
||||
@ -23,7 +23,7 @@ ESRGAN_MODELS = Literal[
|
||||
]
|
||||
|
||||
|
||||
@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan")
|
||||
@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan", version="1.0.0")
|
||||
class ESRGANInvocation(BaseInvocation):
|
||||
"""Upscales an image using RealESRGAN."""
|
||||
|
||||
|
||||
@ -74,6 +74,7 @@ dependencies = [
|
||||
"rich~=13.3",
|
||||
"safetensors==0.3.1",
|
||||
"scikit-image~=0.21.0",
|
||||
"semver~=3.0.1",
|
||||
"send2trash",
|
||||
"test-tube~=0.7.5",
|
||||
"torch~=2.0.1",
|
||||
|
||||
Loading…
Reference in New Issue
Block a user