feat(nodes): refactor parameter/primitive nodes

Refine concept of "parameter" nodes to "primitives":
- integer
- float
- string
- boolean
- image
- latents
- conditioning
- color

Each primitive has:
- A field definition, if it is not already python primitive value. The field is how this primitive value is passed between nodes. Collections are lists of the field in node definitions. ex: `ImageField` & `list[ImageField]`
- A single output class. ex: `ImageOutput`
- A collection output class. ex: `ImageCollectionOutput`
- A node, which functions to load or pass on the primitive value. ex: `ImageInvocation` (in this case, `ImageInvocation` replaces `LoadImage`)

Plus a number of related changes:
- Reorganize these into `primitives.py`
- Update all nodes and logic to use primitives
- Consolidate "prompt" outputs into "string" & "mask" into "image" (there's no reason for these to be different, the function identically)
- Update default graphs & tests
- Regen frontend types & minor frontend tidy related to changes

invokeai/app/invocations/image.py

@@ -8,34 +8,14 @@ import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
 from invokeai.app.invocations.metadata import CoreMetadata
+from invokeai.app.invocations.primitives import ImageField, ImageOutput
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
-from ..models.image import ImageCategory, ImageField, ImageOutput, MaskOutput, ResourceOrigin
+from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, tags, title
 
 
-@title("Load Image")
-@tags("image")
-class LoadImageInvocation(BaseInvocation):
-    """Load an image and provide it as output."""
-
-    # Metadata
-    type: Literal["load_image"] = "load_image"
-
-    # Inputs
-    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,
-        )
-
-
 @title("Show Image")
 @tags("image")
 class ShowImageInvocation(BaseInvocation):
@@ -162,7 +142,7 @@ class MaskFromAlphaInvocation(BaseInvocation):
     image: ImageField = InputField(description="The image to create the mask from")
     invert: bool = InputField(default=False, description="Whether or not to invert the mask")
 
-    def invoke(self, context: InvocationContext) -> MaskOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get_pil_image(self.image.image_name)
 
         image_mask = image.split()[-1]
@@ -178,8 +158,8 @@ class MaskFromAlphaInvocation(BaseInvocation):
             is_intermediate=self.is_intermediate,
         )
 
-        return MaskOutput(
-            mask=ImageField(image_name=image_dto.image_name),
+        return ImageOutput(
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -608,7 +588,7 @@ class MaskEdgeInvocation(BaseInvocation):
         description="Second threshold for the hysteresis procedure in Canny edge detection"
     )
 
-    def invoke(self, context: InvocationContext) -> MaskOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         mask = context.services.images.get_pil_image(self.image.image_name)
 
         npimg = numpy.asarray(mask, dtype=numpy.uint8)
@@ -633,8 +613,8 @@ class MaskEdgeInvocation(BaseInvocation):
             is_intermediate=self.is_intermediate,
         )
 
-        return MaskOutput(
-            mask=ImageField(image_name=image_dto.image_name),
+        return ImageOutput(
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )