Merge branch 'main' into textfontimage

Author: Millu

docs/contributing/INVOCATIONS.md

@@ -244,8 +244,12 @@ copy-paste the template above.
 We can use the `@invocation` decorator to provide some additional info to the
 UI, like a custom title, tags and category.
 
+We also encourage providing a version. This must be a
+[semver](https://semver.org/) version string ("$MAJOR.$MINOR.$PATCH"). The UI
+will let users know if their workflow is using a mismatched version of the node.
+
 ```python
-@invocation("resize", title="My Resizer", tags=["resize", "image"], category="My Invocations")
+@invocation("resize", title="My Resizer", tags=["resize", "image"], category="My Invocations", version="1.0.0")
 class ResizeInvocation(BaseInvocation):
     """Resizes an image"""
 
@@ -279,8 +283,6 @@ take a look a at our [contributing nodes overview](contributingNodes).
 
 ## Advanced
 
--->
-
 ### Custom Output Types
 
 Like with custom inputs, sometimes you might find yourself needing custom

docs/nodes/communityNodes.md

@@ -109,6 +109,73 @@ a Text-Generation-Webui instance (might work remotely too, but I never tried it)
 
 This node works best with SDXL models, especially as the style can be described independantly of the LLM's output.
 
+--------------------------------
+### Depth Map from Wavefront OBJ
+
+**Description:** Render depth maps from Wavefront .obj files (triangulated) using this simple 3D renderer utilizing numpy and matplotlib to compute and color the scene. There are simple parameters to change the FOV, camera position, and model orientation.
+
+To be imported, an .obj must use triangulated meshes, so make sure to enable that option if exporting from a 3D modeling program. This renderer makes each triangle a solid color based on its average depth, so it will cause anomalies if your .obj has large triangles. In Blender, the Remesh modifier can be helpful to subdivide a mesh into small pieces that work well given these limitations.
+
+**Node Link:** https://github.com/dwringer/depth-from-obj-node
+
+**Example Usage:**
+![depth from obj usage graph](https://raw.githubusercontent.com/dwringer/depth-from-obj-node/main/depth_from_obj_usage.jpg)
+
+--------------------------------
+### Enhance Image (simple adjustments)
+
+**Description:** Boost or reduce color saturation, contrast, brightness, sharpness, or invert colors of any image at any stage with this simple wrapper for pillow [PIL]'s ImageEnhance module.
+
+Color inversion is toggled with a simple switch, while each of the four enhancer modes are activated by entering a value other than 1 in each corresponding input field. Values less than 1 will reduce the corresponding property, while values greater than 1 will enhance it.
+
+**Node Link:** https://github.com/dwringer/image-enhance-node
+
+**Example Usage:**
+![enhance image usage graph](https://raw.githubusercontent.com/dwringer/image-enhance-node/main/image_enhance_usage.jpg)
+
+--------------------------------
+### Generative Grammar-Based Prompt Nodes
+
+**Description:** This set of 3 nodes generates prompts from simple user-defined grammar rules (loaded from custom files - examples provided below). The prompts are made by recursively expanding a special template string, replacing nonterminal "parts-of-speech" until no more nonterminal terms remain in the string.
+
+This includes 3 Nodes:
+- *Lookup Table from File* - loads a YAML file "prompt" section (or of a whole folder of YAML's) into a JSON-ified dictionary (Lookups output)
+- *Lookups Entry from Prompt* - places a single entry in a new Lookups output under the specified heading
+- *Prompt from Lookup Table* - uses a Collection of Lookups as grammar rules from which to randomly generate prompts.
+
+**Node Link:** https://github.com/dwringer/generative-grammar-prompt-nodes
+
+**Example Usage:**
+![lookups usage example graph](https://raw.githubusercontent.com/dwringer/generative-grammar-prompt-nodes/main/lookuptables_usage.jpg)
+
+--------------------------------
+### Image and Mask Composition Pack
+
+**Description:** This is a pack of nodes for composing masks and images, including a simple text mask creator and both image and latent offset nodes. The offsets wrap around, so these can be used in conjunction with the Seamless node to progressively generate centered on different parts of the seamless tiling.
+
+This includes 4 Nodes:
+- *Text Mask (simple 2D)* - create and position a white on black (or black on white) line of text using any font locally available to Invoke.
+- *Image Compositor* - Take a subject from an image with a flat backdrop and layer it on another image using a chroma key or flood select background removal.
+- *Offset Latents* - Offset a latents tensor in the vertical and/or horizontal dimensions, wrapping it around.
+- *Offset Image* - Offset an image in the vertical and/or horizontal dimensions, wrapping it around.
+
+**Node Link:** https://github.com/dwringer/composition-nodes
+
+**Example Usage:**
+![composition nodes usage graph](https://raw.githubusercontent.com/dwringer/composition-nodes/main/composition_nodes_usage.jpg)
+
+--------------------------------
+### Size Stepper Nodes
+
+**Description:** This is a set of nodes for calculating the necessary size increments for doing upscaling workflows. Use the *Final Size & Orientation* node to enter your full size dimensions and orientation (portrait/landscape/random), then plug that and your initial generation dimensions into the *Ideal Size Stepper* and get 1, 2, or 3 intermediate pairs of dimensions for upscaling. Note this does not output the initial size or full size dimensions: the 1, 2, or 3 outputs of this node are only the intermediate sizes.
+
+A third node is included, *Random Switch (Integers)*, which is just a generic version of Final Size with no orientation selection.
+
+**Node Link:** https://github.com/dwringer/size-stepper-nodes
+
+**Example Usage:**
+![size stepper usage graph](https://raw.githubusercontent.com/dwringer/size-stepper-nodes/main/size_nodes_usage.jpg)
+
 --------------------------------
 
 ### Text font to Image

docs/nodes/defaultNodes.md

@@ -35,13 +35,13 @@ The table below contains a list of the default nodes shipped with InvokeAI and t
 |Inverse Lerp Image 			| Inverse linear interpolation of all pixels of an image|
 |Image Primitive 			| An image primitive value|
 |Lerp Image 			| Linear interpolation of all pixels of an image|
-|Image Luminosity Adjustment 			| Adjusts the Luminosity (Value) of an image.|
+|Offset Image Channel 			| Add to or subtract from an image color channel by a uniform value.|
+|Multiply Image Channel 			| Multiply or Invert an image color channel by a scalar value.|
 |Multiply Images 			| Multiplies two images together using `PIL.ImageChops.multiply()`.|
 |Blur NSFW Image 			| Add blur to NSFW-flagged images|
 |Paste Image 			| Pastes an image into another image.|
 |ImageProcessor 			| Base class for invocations that preprocess images for ControlNet|
 |Resize Image 			| Resizes an image to specific dimensions|
-|Image Saturation Adjustment 			| Adjusts the Saturation of an image.|
 |Scale Image 			| Scales an image by a factor|
 |Image to Latents 			| Encodes an image into latents.|
 |Add Invisible Watermark 			| Add an invisible watermark to an image|

invokeai/app/api/routers/app_info.py

@@ -1,19 +1,19 @@
 import typing
 from enum import Enum
+from pathlib import Path
+
 from fastapi import Body
 from fastapi.routing import APIRouter
-from pathlib import Path
 from pydantic import BaseModel, Field
 
+from invokeai.app.invocations.upscale import ESRGAN_MODELS
+from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.patchmatch import PatchMatch
 from invokeai.backend.image_util.safety_checker import SafetyChecker
-from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
-from invokeai.app.invocations.upscale import ESRGAN_MODELS
-
+from invokeai.backend.util.logging import logging
 from invokeai.version import __version__
 
 from ..dependencies import ApiDependencies
-from invokeai.backend.util.logging import logging
 
 
 class LogLevel(int, Enum):
@@ -55,7 +55,7 @@ async def get_version() -> AppVersion:
 
 @app_router.get("/config", operation_id="get_config", status_code=200, response_model=AppConfig)
 async def get_config() -> AppConfig:
-    infill_methods = ["tile", "lama"]
+    infill_methods = ["tile", "lama", "cv2"]
     if PatchMatch.patchmatch_available():
         infill_methods.append("patchmatch")
 

invokeai/app/invocations/baseinvocation.py

@@ -26,11 +26,16 @@
 from pydantic import BaseModel, Field, validator
 from pydantic.fields import Undefined, ModelField
 from pydantic.typing import NoArgAnyCallable
+import semver
 
 if TYPE_CHECKING:
     from ..services.invocation_services import InvocationServices
 
 
+class InvalidVersionError(ValueError):
+    pass
+
+
 class FieldDescriptions:
     denoising_start = "When to start denoising, expressed a percentage of total steps"
     denoising_end = "When to stop denoising, expressed a percentage of total steps"
@@ -105,24 +110,39 @@ class UIType(str, Enum):
     """
 
     # region Primitives
-    Integer = "integer"
-    Float = "float"
     Boolean = "boolean"
-    String = "string"
-    Array = "array"
-    Image = "ImageField"
-    Latents = "LatentsField"
+    Color = "ColorField"
     Conditioning = "ConditioningField"
     Control = "ControlField"
-    Color = "ColorField"
-    ImageCollection = "ImageCollection"
-    ConditioningCollection = "ConditioningCollection"
+    Float = "float"
+    Image = "ImageField"
+    Integer = "integer"
+    Latents = "LatentsField"
+    String = "string"
+    # endregion
+
+    # region Collection Primitives
+    BooleanCollection = "BooleanCollection"
     ColorCollection = "ColorCollection"
-    LatentsCollection = "LatentsCollection"
-    IntegerCollection = "IntegerCollection"
+    ConditioningCollection = "ConditioningCollection"
+    ControlCollection = "ControlCollection"
     FloatCollection = "FloatCollection"
+    ImageCollection = "ImageCollection"
+    IntegerCollection = "IntegerCollection"
+    LatentsCollection = "LatentsCollection"
     StringCollection = "StringCollection"
-    BooleanCollection = "BooleanCollection"
+    # endregion
+
+    # region Polymorphic Primitives
+    BooleanPolymorphic = "BooleanPolymorphic"
+    ColorPolymorphic = "ColorPolymorphic"
+    ConditioningPolymorphic = "ConditioningPolymorphic"
+    ControlPolymorphic = "ControlPolymorphic"
+    FloatPolymorphic = "FloatPolymorphic"
+    ImagePolymorphic = "ImagePolymorphic"
+    IntegerPolymorphic = "IntegerPolymorphic"
+    LatentsPolymorphic = "LatentsPolymorphic"
+    StringPolymorphic = "StringPolymorphic"
     # endregion
 
     # region Models
@@ -176,6 +196,7 @@ class _InputField(BaseModel):
     ui_type: Optional[UIType]
     ui_component: Optional[UIComponent]
     ui_order: Optional[int]
+    item_default: Optional[Any]
 
 
 class _OutputField(BaseModel):
@@ -223,6 +244,7 @@ def InputField(
     ui_component: Optional[UIComponent] = None,
     ui_hidden: bool = False,
     ui_order: Optional[int] = None,
+    item_default: Optional[Any] = None,
     **kwargs: Any,
 ) -> Any:
     """
@@ -249,6 +271,11 @@ def InputField(
       For this case, you could provide `UIComponent.Textarea`.
 
     : param bool ui_hidden: [False] Specifies whether or not this field should be hidden in the UI.
+
+    : param int ui_order: [None] Specifies the order in which this field should be rendered in the UI. \
+
+    : param bool item_default: [None] Specifies the default item value, if this is a collection input. \
+      Ignored for non-collection fields..
     """
     return Field(
         *args,
@@ -282,6 +309,7 @@ def InputField(
         ui_component=ui_component,
         ui_hidden=ui_hidden,
         ui_order=ui_order,
+        item_default=item_default,
         **kwargs,
     )
 
@@ -332,6 +360,8 @@ def OutputField(
       `UIType.SDXLMainModelField` to indicate that the field is an SDXL main model field.
 
     : param bool ui_hidden: [False] Specifies whether or not this field should be hidden in the UI. \
+
+    : param int ui_order: [None] Specifies the order in which this field should be rendered in the UI. \
     """
     return Field(
         *args,
@@ -376,6 +406,9 @@ class UIConfigBase(BaseModel):
     tags: Optional[list[str]] = Field(default_factory=None, description="The node's tags")
     title: Optional[str] = Field(default=None, description="The node's display name")
     category: Optional[str] = Field(default=None, description="The node's category")
+    version: Optional[str] = Field(
+        default=None, description='The node\'s version. Should be a valid semver string e.g. "1.0.0" or "3.8.13".'
+    )
 
 
 class InvocationContext:
@@ -474,6 +507,8 @@ def schema_extra(schema: dict[str, Any], model_class: Type[BaseModel]) -> None:
                 schema["tags"] = uiconfig.tags
             if uiconfig and hasattr(uiconfig, "category"):
                 schema["category"] = uiconfig.category
+            if uiconfig and hasattr(uiconfig, "version"):
+                schema["version"] = uiconfig.version
             if "required" not in schema or not isinstance(schema["required"], list):
                 schema["required"] = list()
             schema["required"].extend(["type", "id"])
@@ -542,7 +577,11 @@ def validate_workflow_is_json(cls, v):
 
 
 def invocation(
-    invocation_type: str, title: Optional[str] = None, tags: Optional[list[str]] = None, category: Optional[str] = None
+    invocation_type: str,
+    title: Optional[str] = None,
+    tags: Optional[list[str]] = None,
+    category: Optional[str] = None,
+    version: Optional[str] = None,
 ) -> Callable[[Type[GenericBaseInvocation]], Type[GenericBaseInvocation]]:
     """
     Adds metadata to an invocation.
@@ -569,6 +608,12 @@ def wrapper(cls: Type[GenericBaseInvocation]) -> Type[GenericBaseInvocation]:
             cls.UIConfig.tags = tags
         if category is not None:
             cls.UIConfig.category = category
+        if version is not None:
+            try:
+                semver.Version.parse(version)
+            except ValueError as e:
+                raise InvalidVersionError(f'Invalid version string for node "{invocation_type}": "{version}"') from e
+            cls.UIConfig.version = version
 
         # Add the invocation type to the pydantic model of the invocation
         invocation_type_annotation = Literal[invocation_type]  # type: ignore

invokeai/app/invocations/collections.py

@@ -10,7 +10,9 @@
 from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 
 
-@invocation("range", title="Integer Range", tags=["collection", "integer", "range"], category="collections")
+@invocation(
+    "range", title="Integer Range", tags=["collection", "integer", "range"], category="collections", version="1.0.0"
+)
 class RangeInvocation(BaseInvocation):
     """Creates a range of numbers from start to stop with step"""
 
@@ -33,6 +35,7 @@ def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
     title="Integer Range of Size",
     tags=["collection", "integer", "size", "range"],
     category="collections",
+    version="1.0.0",
 )
 class RangeOfSizeInvocation(BaseInvocation):
     """Creates a range from start to start + size with step"""
@@ -50,6 +53,7 @@ def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
     title="Random Range",
     tags=["range", "integer", "random", "collection"],
     category="collections",
+    version="1.0.0",
 )
 class RandomRangeInvocation(BaseInvocation):
     """Creates a collection of random numbers"""

invokeai/app/invocations/compel.py

@@ -44,7 +44,7 @@ class ConditioningFieldData:
 #    PerpNeg = "perp_neg"
 
 
-@invocation("compel", title="Prompt", tags=["prompt", "compel"], category="conditioning")
+@invocation("compel", title="Prompt", tags=["prompt", "compel"], category="conditioning", version="1.0.0")
 class CompelInvocation(BaseInvocation):
     """Parse prompt using compel package to conditioning."""
 
@@ -267,6 +267,7 @@ def _lora_loader():
     title="SDXL Prompt",
     tags=["sdxl", "compel", "prompt"],
     category="conditioning",
+    version="1.0.0",
 )
 class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
@@ -351,6 +352,7 @@ def invoke(self, context: InvocationContext) -> ConditioningOutput:
     title="SDXL Refiner Prompt",
     tags=["sdxl", "compel", "prompt"],
     category="conditioning",
+    version="1.0.0",
 )
 class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
@@ -403,7 +405,7 @@ class ClipSkipInvocationOutput(BaseInvocationOutput):
     clip: ClipField = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@invocation("clip_skip", title="CLIP Skip", tags=["clipskip", "clip", "skip"], category="conditioning")
+@invocation("clip_skip", title="CLIP Skip", tags=["clipskip", "clip", "skip"], category="conditioning", version="1.0.0")
 class ClipSkipInvocation(BaseInvocation):
     """Skip layers in clip text_encoder model."""