fix(nodes): fix uploading image metadata retention

was causing failure to save images

invokeai/app/invocations/baseinvocation.py

@@ -372,8 +372,9 @@ class UIConfigBase(BaseModel):
     decorators, though you may add this class to a node definition to specify the title and tags.
     """
 
-    tags: Optional[list[str]] = Field(default_factory=None, description="The tags to display in the UI")
-    title: Optional[str] = Field(default=None, description="The display name of the node")
+    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")
 
 
 class InvocationContext:
@@ -469,6 +470,8 @@ class BaseInvocation(ABC, BaseModel):
                 schema["title"] = uiconfig.title
             if uiconfig and hasattr(uiconfig, "tags"):
                 schema["tags"] = uiconfig.tags
+            if uiconfig and hasattr(uiconfig, "category"):
+                schema["category"] = uiconfig.category
             if "required" not in schema or not isinstance(schema["required"], list):
                 schema["required"] = list()
             schema["required"].extend(["type", "id"])
@@ -558,3 +561,39 @@ def tags(*tags: str) -> Callable[[Type[T]], Type[T]]:
         return cls
 
     return wrapper
+
+
+def category(category: str) -> Callable[[Type[T]], Type[T]]:
+    """Adds a category to the invocation. This is used to group invocations in the UI."""
+
+    def wrapper(cls: Type[T]) -> Type[T]:
+        uiconf_name = cls.__qualname__ + ".UIConfig"
+        if not hasattr(cls, "UIConfig") or cls.UIConfig.__qualname__ != uiconf_name:
+            cls.UIConfig = type(uiconf_name, (UIConfigBase,), dict())
+        cls.UIConfig.category = category
+        return cls
+
+    return wrapper
+
+
+def node(
+    title: Optional[str] = None, tags: Optional[list[str]] = None, category: Optional[str] = None
+) -> Callable[[Type[T]], Type[T]]:
+    """
+    Adds metadata to the invocation as a decorator.
+
+    :param Optional[str] title: Adds a title to the node. Use if the auto-generated title isn't quite right. Defaults to None.
+    :param Optional[list[str]] tags: Adds tags to the node. Nodes may be searched for by their tags. Defaults to None.
+    :param Optional[str] category: Adds a category to the node. Used to group the nodes in the UI. Defaults to None.
+    """
+
+    def wrapper(cls: Type[T]) -> Type[T]:
+        uiconf_name = cls.__qualname__ + ".UIConfig"
+        if not hasattr(cls, "UIConfig") or cls.UIConfig.__qualname__ != uiconf_name:
+            cls.UIConfig = type(uiconf_name, (UIConfigBase,), dict())
+        cls.UIConfig.title = title
+        cls.UIConfig.tags = tags
+        cls.UIConfig.category = category
+        return cls
+
+    return wrapper

invokeai/app/invocations/collections.py

@@ -8,11 +8,10 @@ from pydantic import validator
 from invokeai.app.invocations.primitives import IntegerCollectionOutput
 from invokeai.app.util.misc import SEED_MAX, get_random_seed
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, node
 
 
-@title("Integer Range")
-@tags("collection", "integer", "range")
+@node(title="Integer Range", tags=["collection", "integer", "range"], category="collections")
 class RangeInvocation(BaseInvocation):
     """Creates a range of numbers from start to stop with step"""
 
@@ -33,8 +32,7 @@ class RangeInvocation(BaseInvocation):
         return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
 
 
-@title("Integer Range of Size")
-@tags("range", "integer", "size", "collection")
+@node(title="Integer Range of Size", tags=["collection", "integer", "size", "range"], category="collections")
 class RangeOfSizeInvocation(BaseInvocation):
     """Creates a range from start to start + size with step"""
 
@@ -49,8 +47,7 @@ class RangeOfSizeInvocation(BaseInvocation):
         return IntegerCollectionOutput(collection=list(range(self.start, self.start + self.size, self.step)))
 
 
-@title("Random Range")
-@tags("range", "integer", "random", "collection")
+@node(title="Random Range", tags=["range", "integer", "random", "collection"], category="collections")
 class RandomRangeInvocation(BaseInvocation):
     """Creates a collection of random numbers"""
 

invokeai/app/invocations/compel.py

@@ -26,6 +26,7 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIComponent,
+    category,
     tags,
     title,
 )
@@ -44,8 +45,9 @@ class ConditioningFieldData:
 #    PerpNeg = "perp_neg"
 
 
-@title("Compel Prompt")
+@title("Prompt")
 @tags("prompt", "compel")
+@category("conditioning")
 class CompelInvocation(BaseInvocation):
     """Parse prompt using compel package to conditioning."""
 
@@ -265,8 +267,9 @@ class SDXLPromptInvocationBase:
         return c, c_pooled, ec
 
 
-@title("SDXL Compel Prompt")
+@title("SDXL Prompt")
 @tags("sdxl", "compel", "prompt")
+@category("conditioning")
 class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
 
@@ -324,8 +327,9 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
         )
 
 
-@title("SDXL Refiner Compel Prompt")
+@title("SDXL Refiner Prompt")
 @tags("sdxl", "compel", "prompt")
+@category("conditioning")
 class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
 
@@ -381,6 +385,7 @@ class ClipSkipInvocationOutput(BaseInvocationOutput):
 
 @title("CLIP Skip")
 @tags("clipskip", "clip", "skip")
+@category("conditioning")
 class ClipSkipInvocation(BaseInvocation):
     """Skip layers in clip text_encoder model."""
 

invokeai/app/invocations/controlnet_image_processors.py

@@ -40,6 +40,8 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIType,
+    category,
+    node,
     tags,
     title,
 )
@@ -96,8 +98,7 @@ class ControlOutput(BaseInvocationOutput):
     control: ControlField = OutputField(description=FieldDescriptions.control)
 
 
-@title("ControlNet")
-@tags("controlnet")
+@node(title="ControlNet", tags=["controlnet"], category="controlnet")
 class ControlNetInvocation(BaseInvocation):
     """Collects ControlNet info to pass to other nodes"""
 
@@ -177,6 +178,7 @@ class ImageProcessorInvocation(BaseInvocation):
 
 @title("Canny Processor")
 @tags("controlnet", "canny")
+@category("controlnet")
 class CannyImageProcessorInvocation(ImageProcessorInvocation):
     """Canny edge detection for ControlNet"""
 
@@ -198,6 +200,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("HED (softedge) Processor")
 @tags("controlnet", "hed", "softedge")
+@category("controlnet")
 class HedImageProcessorInvocation(ImageProcessorInvocation):
     """Applies HED edge detection to image"""
 
@@ -225,6 +228,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Lineart Processor")
 @tags("controlnet", "lineart")
+@category("controlnet")
 class LineartImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art processing to image"""
 
@@ -245,6 +249,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Lineart Anime Processor")
 @tags("controlnet", "lineart", "anime")
+@category("controlnet")
 class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art anime processing to image"""
 
@@ -266,6 +271,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Openpose Processor")
 @tags("controlnet", "openpose", "pose")
+@category("controlnet")
 class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Openpose processing to image"""
 
@@ -289,6 +295,7 @@ class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Midas (Depth) Processor")
 @tags("controlnet", "midas", "depth")
+@category("controlnet")
 class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Midas depth processing to image"""
 
@@ -314,6 +321,7 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Normal BAE Processor")
 @tags("controlnet", "normal", "bae")
+@category("controlnet")
 class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies NormalBae processing to image"""
 
@@ -333,6 +341,7 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("MLSD Processor")
 @tags("controlnet", "mlsd")
+@category("controlnet")
 class MlsdImageProcessorInvocation(ImageProcessorInvocation):
     """Applies MLSD processing to image"""
 
@@ -358,6 +367,7 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("PIDI Processor")
 @tags("controlnet", "pidi")
+@category("controlnet")
 class PidiImageProcessorInvocation(ImageProcessorInvocation):
     """Applies PIDI processing to image"""
 
@@ -383,6 +393,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Content Shuffle Processor")
 @tags("controlnet", "contentshuffle")
+@category("controlnet")
 class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     """Applies content shuffle processing to image"""
 
@@ -411,6 +422,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
 # should work with controlnet_aux >= 0.0.4 and timm <= 0.6.13
 @title("Zoe (Depth) Processor")
 @tags("controlnet", "zoe", "depth")
+@category("controlnet")
 class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Zoe depth processing to image"""
 
@@ -424,6 +436,7 @@ class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Mediapipe Face Processor")
 @tags("controlnet", "mediapipe", "face")
+@category("controlnet")
 class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     """Applies mediapipe face processing to image"""
 
@@ -445,6 +458,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
 
 @title("Leres (Depth) Processor")
 @tags("controlnet", "leres", "depth")
+@category("controlnet")
 class LeresImageProcessorInvocation(ImageProcessorInvocation):
     """Applies leres processing to image"""
 
@@ -472,6 +486,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
 
 @title("Tile Resample Processor")
 @tags("controlnet", "tile")
+@category("controlnet")
 class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     """Tile resampler processor"""
 
@@ -510,6 +525,7 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation):
 
 @title("Segment Anything Processor")
 @tags("controlnet", "segmentanything")
+@category("controlnet")
 class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
     """Applies segment anything processing to image"""
 

invokeai/app/invocations/cv.py

@@ -8,11 +8,12 @@ from PIL import Image, ImageOps
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 
 from invokeai.app.models.image import ImageCategory, ResourceOrigin
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, category, tags, title
 
 
 @title("OpenCV Inpaint")
 @tags("opencv", "inpaint")
+@category("inpaint")
 class CvInpaintInvocation(BaseInvocation):
     """Simple inpaint using opencv."""
 

invokeai/app/services/image_file_storage.py

@@ -119,13 +119,20 @@ class DiskImageFileStorage(ImageFileStorageBase):
 
             pnginfo = PngImagePlugin.PngInfo()
 
-            if metadata is not None:
-                pnginfo.add_text("invokeai_metadata", json.dumps(metadata))
-            if workflow is not None:
-                pnginfo.add_text("invokeai_workflow", workflow)
-            # For uploaded images, we want to retain metadata. PIL strips it on save; manually add it back
-            for item_name, item in image.info.items():
-                pnginfo.add_text(item_name, item)
+            if metadata is not None or workflow is not None:
+                if metadata is not None:
+                    pnginfo.add_text("invokeai_metadata", json.dumps(metadata))
+                if workflow is not None:
+                    pnginfo.add_text("invokeai_workflow", workflow)
+            else:
+                # For uploaded images, we want to retain metadata. PIL strips it on save; manually add it back
+                # TODO: retain non-invokeai metadata on save...
+                original_metadata = image.info.get("invokeai_metadata", None)
+                if original_metadata is not None:
+                    pnginfo.add_text("invokeai_metadata", original_metadata)
+                original_workflow = image.info.get("invokeai_workflow", None)
+                if original_workflow is not None:
+                    pnginfo.add_text("invokeai_workflow", original_workflow)
 
             image.save(image_path, "PNG", pnginfo=pnginfo)