Controlnet implementation for sequential execution

This reverts commit e7a61e631a42190e4b64e0d5e22771c669c5b30c.

invokeai/app/api/routers/images.py

@@ -70,27 +70,25 @@ async def upload_image(
         raise HTTPException(status_code=500, detail="Failed to create image")
 
 
-@images_router.delete("/{image_origin}/{image_name}", operation_id="delete_image")
+@images_router.delete("/{image_name}", operation_id="delete_image")
 async def delete_image(
-    image_origin: ResourceOrigin = Path(description="The origin of image to delete"),
     image_name: str = Path(description="The name of the image to delete"),
 ) -> None:
     """Deletes an image"""
 
     try:
-        ApiDependencies.invoker.services.images.delete(image_origin, image_name)
+        ApiDependencies.invoker.services.images.delete(image_name)
     except Exception as e:
         # TODO: Does this need any exception handling at all?
         pass
 
 
 @images_router.patch(
-    "/{image_origin}/{image_name}",
+    "/{image_name}",
     operation_id="update_image",
     response_model=ImageDTO,
 )
 async def update_image(
-    image_origin: ResourceOrigin = Path(description="The origin of image to update"),
     image_name: str = Path(description="The name of the image to update"),
     image_changes: ImageRecordChanges = Body(
         description="The changes to apply to the image"
@@ -99,32 +97,29 @@ async def update_image(
     """Updates an image"""
 
     try:
-        return ApiDependencies.invoker.services.images.update(
-            image_origin, image_name, image_changes
-        )
+        return ApiDependencies.invoker.services.images.update(image_name, image_changes)
     except Exception as e:
         raise HTTPException(status_code=400, detail="Failed to update image")
 
 
 @images_router.get(
-    "/{image_origin}/{image_name}/metadata",
+    "/{image_name}/metadata",
     operation_id="get_image_metadata",
     response_model=ImageDTO,
 )
 async def get_image_metadata(
-    image_origin: ResourceOrigin = Path(description="The origin of image to get"),
     image_name: str = Path(description="The name of image to get"),
 ) -> ImageDTO:
     """Gets an image's metadata"""
 
     try:
-        return ApiDependencies.invoker.services.images.get_dto(image_origin, image_name)
+        return ApiDependencies.invoker.services.images.get_dto(image_name)
     except Exception as e:
         raise HTTPException(status_code=404)
 
 
 @images_router.get(
-    "/{image_origin}/{image_name}",
+    "/{image_name}",
     operation_id="get_image_full",
     response_class=Response,
     responses={
@@ -136,15 +131,12 @@ async def get_image_metadata(
     },
 )
 async def get_image_full(
-    image_origin: ResourceOrigin = Path(
-        description="The type of full-resolution image file to get"
-    ),
     image_name: str = Path(description="The name of full-resolution image file to get"),
 ) -> FileResponse:
     """Gets a full-resolution image file"""
 
     try:
-        path = ApiDependencies.invoker.services.images.get_path(image_origin, image_name)
+        path = ApiDependencies.invoker.services.images.get_path(image_name)
 
         if not ApiDependencies.invoker.services.images.validate_path(path):
             raise HTTPException(status_code=404)
@@ -160,7 +152,7 @@ async def get_image_full(
 
 
 @images_router.get(
-    "/{image_origin}/{image_name}/thumbnail",
+    "/{image_name}/thumbnail",
     operation_id="get_image_thumbnail",
     response_class=Response,
     responses={
@@ -172,14 +164,13 @@ async def get_image_full(
     },
 )
 async def get_image_thumbnail(
-    image_origin: ResourceOrigin = Path(description="The origin of thumbnail image file to get"),
     image_name: str = Path(description="The name of thumbnail image file to get"),
 ) -> FileResponse:
     """Gets a thumbnail image file"""
 
     try:
         path = ApiDependencies.invoker.services.images.get_path(
-            image_origin, image_name, thumbnail=True
+            image_name, thumbnail=True
         )
         if not ApiDependencies.invoker.services.images.validate_path(path):
             raise HTTPException(status_code=404)
@@ -192,25 +183,21 @@ async def get_image_thumbnail(
 
 
 @images_router.get(
-    "/{image_origin}/{image_name}/urls",
+    "/{image_name}/urls",
     operation_id="get_image_urls",
     response_model=ImageUrlsDTO,
 )
 async def get_image_urls(
-    image_origin: ResourceOrigin = Path(description="The origin of the image whose URL to get"),
     image_name: str = Path(description="The name of the image whose URL to get"),
 ) -> ImageUrlsDTO:
     """Gets an image and thumbnail URL"""
 
     try:
-        image_url = ApiDependencies.invoker.services.images.get_url(
-            image_origin, image_name
-        )
+        image_url = ApiDependencies.invoker.services.images.get_url(image_name)
         thumbnail_url = ApiDependencies.invoker.services.images.get_url(
-            image_origin, image_name, thumbnail=True
+            image_name, thumbnail=True
         )
         return ImageUrlsDTO(
-            image_origin=image_origin,
             image_name=image_name,
             image_url=image_url,
             thumbnail_url=thumbnail_url,

invokeai/app/invocations/controlnet_image_processors.py

@@ -1,7 +1,7 @@
 # InvokeAI nodes for ControlNet image preprocessors
 # initial implementation by Gregg Helt, 2023
 # heavily leverages controlnet_aux package: https://github.com/patrickvonplaten/controlnet_aux
-from builtins import float
+from builtins import float, bool
 
 import numpy as np
 from typing import Literal, Optional, Union, List
@@ -94,6 +94,7 @@ CONTROLNET_DEFAULT_MODELS = [
 ]
 
 CONTROLNET_NAME_VALUES = Literal[tuple(CONTROLNET_DEFAULT_MODELS)]
+CONTROLNET_MODE_VALUES = Literal[tuple(["balanced", "more_prompt", "more_control", "unbalanced"])]
 
 class ControlField(BaseModel):
     image: ImageField = Field(default=None, description="The control image")
@@ -104,6 +105,8 @@ class ControlField(BaseModel):
                                       description="When the ControlNet is first applied (% of total steps)")
     end_step_percent: float = Field(default=1, ge=0, le=1,
                                     description="When the ControlNet is last applied (% of total steps)")
+    control_mode: CONTROLNET_MODE_VALUES = Field(default="balanced", description="The contorl mode to use")
+
     @validator("control_weight")
     def abs_le_one(cls, v):
         """validate that all abs(values) are <=1"""
@@ -144,11 +147,11 @@ class ControlNetInvocation(BaseInvocation):
     control_model: CONTROLNET_NAME_VALUES = Field(default="lllyasviel/sd-controlnet-canny",
                                                   description="control model used")
     control_weight: Union[float, List[float]] = Field(default=1.0, description="The weight given to the ControlNet")
-    # TODO: add support in backend core for begin_step_percent, end_step_percent, guess_mode
     begin_step_percent: float = Field(default=0, ge=0, le=1,
                                       description="When the ControlNet is first applied (% of total steps)")
     end_step_percent: float = Field(default=1, ge=0, le=1,
                                     description="When the ControlNet is last applied (% of total steps)")
+    control_mode: CONTROLNET_MODE_VALUES = Field(default="balanced", description="The control mode used")
     # fmt: on
 
     class Config(InvocationConfig):
@@ -166,7 +169,6 @@ class ControlNetInvocation(BaseInvocation):
         }
 
     def invoke(self, context: InvocationContext) -> ControlOutput:
-
         return ControlOutput(
             control=ControlField(
                 image=self.image,
@@ -174,6 +176,7 @@ class ControlNetInvocation(BaseInvocation):
                 control_weight=self.control_weight,
                 begin_step_percent=self.begin_step_percent,
                 end_step_percent=self.end_step_percent,
+                control_mode=self.control_mode,
             ),
         )
 
@@ -193,9 +196,7 @@ class ImageProcessorInvocation(BaseInvocation, PILInvocationConfig):
         return image
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        raw_image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        raw_image = context.services.images.get_pil_image(self.image.image_name)
         # image type should be PIL.PngImagePlugin.PngImageFile ?
         processed_image = self.run_processor(raw_image)
 
@@ -216,10 +217,7 @@ class ImageProcessorInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         """Builds an ImageOutput and its ImageField"""
-        processed_image_field = ImageField(
-            image_name=image_dto.image_name,
-            image_origin=image_dto.image_origin,
-        )
+        processed_image_field = ImageField(image_name=image_dto.image_name)
         return ImageOutput(
             image=processed_image_field,
             # width=processed_image.width,

invokeai/app/invocations/cv.py

@@ -36,12 +36,8 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
-        mask = context.services.images.get_pil_image(
-            self.mask.image_origin, self.mask.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
+        mask = context.services.images.get_pil_image(self.mask.image_name)
 
         # Convert to cv image/mask
         # TODO: consider making these utility functions
@@ -65,10 +61,7 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )

invokeai/app/invocations/generate.py

@@ -86,9 +86,7 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
         # loading controlnet image (currently requires pre-processed image)
         control_image = (
             None if self.control_image is None
-            else context.services.images.get_pil_image(
-                self.control_image.image_origin, self.control_image.image_name
-            )
+            else context.services.images.get_pil_image(self.control_image.image_name)
         )
         # loading controlnet model
         if (self.control_model is None or self.control_model==''):
@@ -128,10 +126,7 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -169,9 +164,7 @@ class ImageToImageInvocation(TextToImageInvocation):
         image = (
             None
             if self.image is None
-            else context.services.images.get_pil_image(
-                self.image.image_origin, self.image.image_name
-            )
+            else context.services.images.get_pil_image(self.image.image_name)
         )
 
         if self.fit:
@@ -209,10 +202,7 @@ class ImageToImageInvocation(TextToImageInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -282,14 +272,12 @@ class InpaintInvocation(ImageToImageInvocation):
         image = (
             None
             if self.image is None
-            else context.services.images.get_pil_image(
-                self.image.image_origin, self.image.image_name
-            )
+            else context.services.images.get_pil_image(self.image.image_name)
         )
         mask = (
             None
             if self.mask is None
-            else context.services.images.get_pil_image(self.mask.image_origin, self.mask.image_name)
+            else context.services.images.get_pil_image(self.mask.image_name)
         )
 
         # Handle invalid model parameter
@@ -325,10 +313,7 @@ class InpaintInvocation(ImageToImageInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )

invokeai/app/invocations/image.py

@@ -72,13 +72,10 @@ class LoadImageInvocation(BaseInvocation):
     )
     # fmt: on
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_origin, self.image.image_name)
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         return ImageOutput(
-            image=ImageField(
-                image_name=self.image.image_name,
-                image_origin=self.image.image_origin,
-            ),
+            image=ImageField(image_name=self.image.image_name),
             width=image.width,
             height=image.height,
         )
@@ -95,19 +92,14 @@ class ShowImageInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
         if image:
             image.show()
 
         # TODO: how to handle failure?
 
         return ImageOutput(
-            image=ImageField(
-                image_name=self.image.image_name,
-                image_origin=self.image.image_origin,
-            ),
+            image=ImageField(image_name=self.image.image_name),
             width=image.width,
             height=image.height,
         )
@@ -128,9 +120,7 @@ class ImageCropInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         image_crop = Image.new(
             mode="RGBA", size=(self.width, self.height), color=(0, 0, 0, 0)
@@ -147,10 +137,7 @@ class ImageCropInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -171,19 +158,13 @@ class ImagePasteInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        base_image = context.services.images.get_pil_image(
-            self.base_image.image_origin, self.base_image.image_name
-        )
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        base_image = context.services.images.get_pil_image(self.base_image.image_name)
+        image = context.services.images.get_pil_image(self.image.image_name)
         mask = (
             None
             if self.mask is None
             else ImageOps.invert(
-                context.services.images.get_pil_image(
-                    self.mask.image_origin, self.mask.image_name
-                )
+                context.services.images.get_pil_image(self.mask.image_name)
             )
         )
         # TODO: probably shouldn't invert mask here... should user be required to do it?
@@ -209,10 +190,7 @@ class ImagePasteInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -230,9 +208,7 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> MaskOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         image_mask = image.split()[-1]
         if self.invert:
@@ -248,9 +224,7 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return MaskOutput(
-            mask=ImageField(
-                image_origin=image_dto.image_origin, image_name=image_dto.image_name
-            ),
+            mask=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -268,12 +242,8 @@ class ImageMultiplyInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image1 = context.services.images.get_pil_image(
-            self.image1.image_origin, self.image1.image_name
-        )
-        image2 = context.services.images.get_pil_image(
-            self.image2.image_origin, self.image2.image_name
-        )
+        image1 = context.services.images.get_pil_image(self.image1.image_name)
+        image2 = context.services.images.get_pil_image(self.image2.image_name)
 
         multiply_image = ImageChops.multiply(image1, image2)
 
@@ -287,9 +257,7 @@ class ImageMultiplyInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_origin=image_dto.image_origin, image_name=image_dto.image_name
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -310,9 +278,7 @@ class ImageChannelInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         channel_image = image.getchannel(self.channel)
 
@@ -326,9 +292,7 @@ class ImageChannelInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_origin=image_dto.image_origin, image_name=image_dto.image_name
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -349,9 +313,7 @@ class ImageConvertInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         converted_image = image.convert(self.mode)
 
@@ -365,9 +327,7 @@ class ImageConvertInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_origin=image_dto.image_origin, image_name=image_dto.image_name
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -386,9 +346,7 @@ class ImageBlurInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         blur = (
             ImageFilter.GaussianBlur(self.radius)
@@ -407,10 +365,7 @@ class ImageBlurInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -450,9 +405,7 @@ class ImageResizeInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
 
@@ -471,10 +424,7 @@ class ImageResizeInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -493,9 +443,7 @@ class ImageScaleInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
         width = int(image.width * self.scale_factor)
@@ -516,10 +464,7 @@ class ImageScaleInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -538,9 +483,7 @@ class ImageLerpInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         image_arr = numpy.asarray(image, dtype=numpy.float32) / 255
         image_arr = image_arr * (self.max - self.min) + self.max
@@ -557,10 +500,7 @@ class ImageLerpInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -579,9 +519,7 @@ class ImageInverseLerpInvocation(BaseInvocation, PILInvocationConfig):
     # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         image_arr = numpy.asarray(image, dtype=numpy.float32)
         image_arr = (
@@ -603,10 +541,7 @@ class ImageInverseLerpInvocation(BaseInvocation, PILInvocationConfig):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )

invokeai/app/invocations/infill.py

@@ -134,9 +134,7 @@ class InfillColorInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         solid_bg = Image.new("RGBA", image.size, self.color.tuple())
         infilled = Image.alpha_composite(solid_bg, image.convert("RGBA"))
@@ -153,10 +151,7 @@ class InfillColorInvocation(BaseInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -179,9 +174,7 @@ class InfillTileInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         infilled = tile_fill_missing(
             image.copy(), seed=self.seed, tile_size=self.tile_size
@@ -198,10 +191,7 @@ class InfillTileInvocation(BaseInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )
@@ -217,9 +207,7 @@ class InfillPatchMatchInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         if PatchMatch.patchmatch_available():
             infilled = infill_patchmatch(image.copy())
@@ -236,10 +224,7 @@ class InfillPatchMatchInvocation(BaseInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )

invokeai/app/invocations/latent.py

@@ -5,7 +5,7 @@ import einops
 from typing import Literal, Optional, Union, List
 
 from compel import Compel
-from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
+from diffusers.pipelines.controlnet import MultiControlNetModel
 
 from pydantic import BaseModel, Field, validator
 import torch
@@ -282,19 +282,14 @@ class TextToLatentsInvocation(BaseInvocation):
         control_height_resize = latents_shape[2] * 8
         control_width_resize = latents_shape[3] * 8
         if control_input is None:
-            # print("control input is None")
             control_list = None
         elif isinstance(control_input, list) and len(control_input) == 0:
-            # print("control input is empty list")
             control_list = None
         elif isinstance(control_input, ControlField):
-            # print("control input is ControlField")
             control_list = [control_input]
         elif isinstance(control_input, list) and len(control_input) > 0 and isinstance(control_input[0], ControlField):
-            # print("control input is list[ControlField]")
             control_list = control_input
         else:
-            # print("input control is unrecognized:", type(self.control))
             control_list = None
         if (control_list is None):
             control_data = None
@@ -321,8 +316,7 @@ class TextToLatentsInvocation(BaseInvocation):
                                                                     torch_dtype=model.unet.dtype).to(model.device)
                 control_models.append(control_model)
                 control_image_field = control_info.image
-                input_image = context.services.images.get_pil_image(control_image_field.image_origin,
-                                                                    control_image_field.image_name)
+                input_image = context.services.images.get_pil_image(control_image_field.image_name)
                 # self.image.image_type, self.image.image_name
                 # FIXME: still need to test with different widths, heights, devices, dtypes
                 #        and add in batch_size, num_images_per_prompt?
@@ -337,12 +331,15 @@ class TextToLatentsInvocation(BaseInvocation):
                     # num_images_per_prompt=num_images_per_prompt,
                     device=control_model.device,
                     dtype=control_model.dtype,
+                    control_mode=control_info.control_mode,
                 )
                 control_item = ControlNetData(model=control_model,
                                               image_tensor=control_image,
                                               weight=control_info.control_weight,
                                               begin_step_percent=control_info.begin_step_percent,
-                                              end_step_percent=control_info.end_step_percent)
+                                              end_step_percent=control_info.end_step_percent,
+                                              control_mode=control_info.control_mode,
+                                              )
                 control_data.append(control_item)
                 # MultiControlNetModel has been refactored out, just need list[ControlNetData]
         return control_data
@@ -502,10 +499,7 @@ class LatentsToImageInvocation(BaseInvocation):
             )
 
             return ImageOutput(
-                image=ImageField(
-                    image_name=image_dto.image_name,
-                    image_origin=image_dto.image_origin,
-                ),
+                image=ImageField(image_name=image_dto.image_name),
                 width=image_dto.width,
                 height=image_dto.height,
             )
@@ -601,9 +595,7 @@ class ImageToLatentsInvocation(BaseInvocation):
         # image = context.services.images.get(
         #     self.image.image_type, self.image.image_name
         # )
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         # TODO: this only really needs the vae
         model_info = choose_model(context.services.model_manager, self.model)

invokeai/app/invocations/prompt.py

@@ -2,8 +2,8 @@ from typing import Literal
 
 from pydantic.fields import Field
 
-from .baseinvocation import BaseInvocationOutput
-
+from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
+from dynamicprompts.generators import RandomPromptGenerator, CombinatorialPromptGenerator
 
 class PromptOutput(BaseInvocationOutput):
     """Base class for invocations that output a prompt"""
@@ -20,3 +20,38 @@ class PromptOutput(BaseInvocationOutput):
                 'prompt',
             ]
         }
+
+
+class PromptCollectionOutput(BaseInvocationOutput):
+    """Base class for invocations that output a collection of prompts"""
+
+    # fmt: off
+    type: Literal["prompt_collection_output"] = "prompt_collection_output"
+
+    prompt_collection: list[str] = Field(description="The output prompt collection")
+    count: int = Field(description="The size of the prompt collection")
+    # fmt: on
+
+    class Config:
+        schema_extra = {"required": ["type", "prompt_collection", "count"]}
+
+
+class DynamicPromptInvocation(BaseInvocation):
+    """Parses a prompt using adieyal/dynamicprompts' random or combinatorial generator"""
+
+    type: Literal["dynamic_prompt"] = "dynamic_prompt"
+    prompt: str = Field(description="The prompt to parse with dynamicprompts")
+    max_prompts: int = Field(default=1, description="The number of prompts to generate")
+    combinatorial: bool = Field(
+        default=False, description="Whether to use the combinatorial generator"
+    )
+
+    def invoke(self, context: InvocationContext) -> PromptCollectionOutput:
+        if self.combinatorial:
+            generator = CombinatorialPromptGenerator()
+            prompts = generator.generate(self.prompt, max_prompts=self.max_prompts)
+        else:
+            generator = RandomPromptGenerator()
+            prompts = generator.generate(self.prompt, num_images=self.max_prompts)
+
+        return PromptCollectionOutput(prompt_collection=prompts, count=len(prompts))

invokeai/app/invocations/reconstruct.py

@@ -28,9 +28,7 @@ class RestoreFaceInvocation(BaseInvocation):
         }
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
         results = context.services.restoration.upscale_and_reconstruct(
             image_list=[[image, 0]],
             upscale=None,
@@ -51,10 +49,7 @@ class RestoreFaceInvocation(BaseInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )

invokeai/app/invocations/upscale.py

@@ -30,9 +30,7 @@ class UpscaleInvocation(BaseInvocation):
         }
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
+        image = context.services.images.get_pil_image(self.image.image_name)
         results = context.services.restoration.upscale_and_reconstruct(
             image_list=[[image, 0]],
             upscale=(self.level, self.strength),
@@ -53,10 +51,7 @@ class UpscaleInvocation(BaseInvocation):
         )
 
         return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
+            image=ImageField(image_name=image_dto.image_name),
             width=image_dto.width,
             height=image_dto.height,
         )

invokeai/app/models/image.py

@@ -66,13 +66,10 @@ class InvalidImageCategoryException(ValueError):
 class ImageField(BaseModel):
     """An image field used for passing image objects between invocations"""
 
-    image_origin: ResourceOrigin = Field(
-        default=ResourceOrigin.INTERNAL, description="The type of the image"
-    )
     image_name: Optional[str] = Field(default=None, description="The name of the image")
 
     class Config:
-        schema_extra = {"required": ["image_origin", "image_name"]}
+        schema_extra = {"required": ["image_name"]}
 
 
 class ColorField(BaseModel):

invokeai/app/services/image_file_storage.py

@@ -1,5 +1,4 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
-import os
 from abc import ABC, abstractmethod
 from pathlib import Path
 from queue import Queue
@@ -40,14 +39,12 @@ class ImageFileStorageBase(ABC):
     """Low-level service responsible for storing and retrieving image files."""
 
     @abstractmethod
-    def get(self, image_origin: ResourceOrigin, image_name: str) -> PILImageType:
+    def get(self, image_name: str) -> PILImageType:
         """Retrieves an image as PIL Image."""
         pass
 
     @abstractmethod
-    def get_path(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
+    def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         """Gets the internal path to an image or thumbnail."""
         pass
 
@@ -62,7 +59,6 @@ class ImageFileStorageBase(ABC):
     def save(
         self,
         image: PILImageType,
-        image_origin: ResourceOrigin,
         image_name: str,
         metadata: Optional[ImageMetadata] = None,
         thumbnail_size: int = 256,
@@ -71,7 +67,7 @@ class ImageFileStorageBase(ABC):
         pass
 
     @abstractmethod
-    def delete(self, image_origin: ResourceOrigin, image_name: str) -> None:
+    def delete(self, image_name: str) -> None:
         """Deletes an image and its thumbnail (if one exists)."""
         pass
 
@@ -79,31 +75,26 @@ class ImageFileStorageBase(ABC):
 class DiskImageFileStorage(ImageFileStorageBase):
     """Stores images on disk"""
 
-    __output_folder: str
+    __output_folder: Path
     __cache_ids: Queue  # TODO: this is an incredibly naive cache
-    __cache: Dict[str, PILImageType]
+    __cache: Dict[Path, PILImageType]
     __max_cache_size: int
 
-    def __init__(self, output_folder: str):
-        self.__output_folder = output_folder
+    def __init__(self, output_folder: str | Path):
         self.__cache = dict()
         self.__cache_ids = Queue()
         self.__max_cache_size = 10  # TODO: get this from config
 
-        Path(output_folder).mkdir(parents=True, exist_ok=True)
+        self.__output_folder: Path = output_folder if isinstance(output_folder, Path) else Path(output_folder)
+        self.__thumbnails_folder = self.__output_folder / 'thumbnails'
 
-        # TODO: don't hard-code. get/save/delete should maybe take subpath?
-        for image_origin in ResourceOrigin:
-            Path(os.path.join(output_folder, image_origin)).mkdir(
-                parents=True, exist_ok=True
-            )
-            Path(os.path.join(output_folder, image_origin, "thumbnails")).mkdir(
-                parents=True, exist_ok=True
-            )
+        # Validate required output folders at launch
+        self.__validate_storage_folders()
 
-    def get(self, image_origin: ResourceOrigin, image_name: str) -> PILImageType:
+    def get(self, image_name: str) -> PILImageType:
         try:
-            image_path = self.get_path(image_origin, image_name)
+            image_path = self.get_path(image_name)
+            
             cache_item = self.__get_cache(image_path)
             if cache_item:
                 return cache_item
@@ -117,13 +108,13 @@ class DiskImageFileStorage(ImageFileStorageBase):
     def save(
         self,
         image: PILImageType,
-        image_origin: ResourceOrigin,
         image_name: str,
         metadata: Optional[ImageMetadata] = None,
         thumbnail_size: int = 256,
     ) -> None:
         try:
-            image_path = self.get_path(image_origin, image_name)
+            self.__validate_storage_folders()
+            image_path = self.get_path(image_name)
 
             if metadata is not None:
                 pnginfo = PngImagePlugin.PngInfo()
@@ -133,7 +124,7 @@ class DiskImageFileStorage(ImageFileStorageBase):
                 image.save(image_path, "PNG")
 
             thumbnail_name = get_thumbnail_name(image_name)
-            thumbnail_path = self.get_path(image_origin, thumbnail_name, thumbnail=True)
+            thumbnail_path = self.get_path(thumbnail_name, thumbnail=True)
             thumbnail_image = make_thumbnail(image, thumbnail_size)
             thumbnail_image.save(thumbnail_path)
 
@@ -142,20 +133,19 @@ class DiskImageFileStorage(ImageFileStorageBase):
         except Exception as e:
             raise ImageFileSaveException from e
 
-    def delete(self, image_origin: ResourceOrigin, image_name: str) -> None:
+    def delete(self, image_name: str) -> None:
         try:
-            basename = os.path.basename(image_name)
-            image_path = self.get_path(image_origin, basename)
+            image_path = self.get_path(image_name)
 
-            if os.path.exists(image_path):
+            if image_path.exists():
                 send2trash(image_path)
             if image_path in self.__cache:
                 del self.__cache[image_path]
 
             thumbnail_name = get_thumbnail_name(image_name)
-            thumbnail_path = self.get_path(image_origin, thumbnail_name, True)
+            thumbnail_path = self.get_path(thumbnail_name, True)
 
-            if os.path.exists(thumbnail_path):
+            if thumbnail_path.exists():
                 send2trash(thumbnail_path)
             if thumbnail_path in self.__cache:
                 del self.__cache[thumbnail_path]
@@ -163,41 +153,33 @@ class DiskImageFileStorage(ImageFileStorageBase):
             raise ImageFileDeleteException from e
 
     # TODO: make this a bit more flexible for e.g. cloud storage
-    def get_path(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
-        # strip out any relative path shenanigans
-        basename = os.path.basename(image_name)
-
+    def get_path(self, image_name: str, thumbnail: bool = False) -> Path:
+        path = self.__output_folder / image_name
+        
         if thumbnail:
-            thumbnail_name = get_thumbnail_name(basename)
-            path = os.path.join(
-                self.__output_folder, image_origin, "thumbnails", thumbnail_name
-            )
-        else:
-            path = os.path.join(self.__output_folder, image_origin, basename)
+            thumbnail_name = get_thumbnail_name(image_name)
+            path = self.__thumbnails_folder / thumbnail_name
 
-        abspath = os.path.abspath(path)
+        return path
 
-        return abspath
-
-    def validate_path(self, path: str) -> bool:
+    def validate_path(self, path: str | Path) -> bool:
         """Validates the path given for an image or thumbnail."""
-        try:
-            os.stat(path)
-            return True
-        except:
-            return False
+        path = path if isinstance(path, Path) else Path(path)
+        return path.exists()
+    
+    def __validate_storage_folders(self) -> None:
+        """Checks if the required output folders exist and create them if they don't"""
+        folders: list[Path] = [self.__output_folder, self.__thumbnails_folder]
+        for folder in folders:
+            folder.mkdir(parents=True, exist_ok=True)
 
-    def __get_cache(self, image_name: str) -> PILImageType | None:
+    def __get_cache(self, image_name: Path) -> PILImageType | None:
         return None if image_name not in self.__cache else self.__cache[image_name]
 
-    def __set_cache(self, image_name: str, image: PILImageType):
+    def __set_cache(self, image_name: Path, image: PILImageType):
         if not image_name in self.__cache:
             self.__cache[image_name] = image
-            self.__cache_ids.put(
-                image_name
-            )  # TODO: this should refresh position for LRU cache
+            self.__cache_ids.put(image_name)  # TODO: this should refresh position for LRU cache
             if len(self.__cache) > self.__max_cache_size:
                 cache_id = self.__cache_ids.get()
                 if cache_id in self.__cache:

invokeai/app/services/image_record_storage.py

@@ -21,6 +21,7 @@ from invokeai.app.services.models.image_record import (
 
 T = TypeVar("T", bound=BaseModel)
 
+
 class OffsetPaginatedResults(GenericModel, Generic[T]):
     """Offset-paginated results"""
 
@@ -60,7 +61,7 @@ class ImageRecordStorageBase(ABC):
     # TODO: Implement an `update()` method
 
     @abstractmethod
-    def get(self, image_origin: ResourceOrigin, image_name: str) -> ImageRecord:
+    def get(self, image_name: str) -> ImageRecord:
         """Gets an image record."""
         pass
 
@@ -68,7 +69,6 @@ class ImageRecordStorageBase(ABC):
     def update(
         self,
         image_name: str,
-        image_origin: ResourceOrigin,
         changes: ImageRecordChanges,
     ) -> None:
         """Updates an image record."""
@@ -89,7 +89,7 @@ class ImageRecordStorageBase(ABC):
     # TODO: The database has a nullable `deleted_at` column, currently unused.
     # Should we implement soft deletes? Would need coordination with ImageFileStorage.
     @abstractmethod
-    def delete(self, image_origin: ResourceOrigin, image_name: str) -> None:
+    def delete(self, image_name: str) -> None:
         """Deletes an image record."""
         pass
 
@@ -196,9 +196,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
             """
         )
 
-    def get(
-        self, image_origin: ResourceOrigin, image_name: str
-    ) -> Union[ImageRecord, None]:
+    def get(self, image_name: str) -> Union[ImageRecord, None]:
         try:
             self._lock.acquire()
 
@@ -225,7 +223,6 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
     def update(
         self,
         image_name: str,
-        image_origin: ResourceOrigin,
         changes: ImageRecordChanges,
     ) -> None:
         try:
@@ -294,9 +291,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
 
             if categories is not None:
                 ## Convert the enum values to unique list of strings
-                category_strings = list(
-                    map(lambda c: c.value, set(categories))
-                )
+                category_strings = list(map(lambda c: c.value, set(categories)))
                 # Create the correct length of placeholders
                 placeholders = ",".join("?" * len(category_strings))
                 query_conditions += f"AND image_category IN ( {placeholders} )\n"
@@ -337,7 +332,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
             items=images, offset=offset, limit=limit, total=count
         )
 
-    def delete(self, image_origin: ResourceOrigin, image_name: str) -> None:
+    def delete(self, image_name: str) -> None:
         try:
             self._lock.acquire()
             self._cursor.execute(

invokeai/app/services/images.py

@@ -57,7 +57,6 @@ class ImageServiceABC(ABC):
     @abstractmethod
     def update(
         self,
-        image_origin: ResourceOrigin,
         image_name: str,
         changes: ImageRecordChanges,
     ) -> ImageDTO:
@@ -65,22 +64,22 @@ class ImageServiceABC(ABC):
         pass
 
     @abstractmethod
-    def get_pil_image(self, image_origin: ResourceOrigin, image_name: str) -> PILImageType:
+    def get_pil_image(self, image_name: str) -> PILImageType:
         """Gets an image as a PIL image."""
         pass
 
     @abstractmethod
-    def get_record(self, image_origin: ResourceOrigin, image_name: str) -> ImageRecord:
+    def get_record(self, image_name: str) -> ImageRecord:
         """Gets an image record."""
         pass
 
     @abstractmethod
-    def get_dto(self, image_origin: ResourceOrigin, image_name: str) -> ImageDTO:
+    def get_dto(self, image_name: str) -> ImageDTO:
         """Gets an image DTO."""
         pass
 
     @abstractmethod
-    def get_path(self, image_origin: ResourceOrigin, image_name: str) -> str:
+    def get_path(self, image_name: str) -> str:
         """Gets an image's path."""
         pass
 
@@ -90,9 +89,7 @@ class ImageServiceABC(ABC):
         pass
 
     @abstractmethod
-    def get_url(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
+    def get_url(self, image_name: str, thumbnail: bool = False) -> str:
         """Gets an image's or thumbnail's URL."""
         pass
 
@@ -109,7 +106,7 @@ class ImageServiceABC(ABC):
         pass
 
     @abstractmethod
-    def delete(self, image_origin: ResourceOrigin, image_name: str):
+    def delete(self, image_name: str):
         """Deletes an image."""
         pass
 
@@ -206,16 +203,13 @@ class ImageService(ImageServiceABC):
             )
 
             self._services.files.save(
-                image_origin=image_origin,
                 image_name=image_name,
                 image=image,
                 metadata=metadata,
             )
 
-            image_url = self._services.urls.get_image_url(image_origin, image_name)
-            thumbnail_url = self._services.urls.get_image_url(
-                image_origin, image_name, True
-            )
+            image_url = self._services.urls.get_image_url(image_name)
+            thumbnail_url = self._services.urls.get_image_url(image_name, True)
 
             return ImageDTO(
                 # Non-nullable fields
@@ -249,13 +243,12 @@ class ImageService(ImageServiceABC):
 
     def update(
         self,
-        image_origin: ResourceOrigin,
         image_name: str,
         changes: ImageRecordChanges,
     ) -> ImageDTO:
         try:
-            self._services.records.update(image_name, image_origin, changes)
-            return self.get_dto(image_origin, image_name)
+            self._services.records.update(image_name, changes)
+            return self.get_dto(image_name)
         except ImageRecordSaveException:
             self._services.logger.error("Failed to update image record")
             raise
@@ -263,9 +256,9 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem updating image record")
             raise e
 
-    def get_pil_image(self, image_origin: ResourceOrigin, image_name: str) -> PILImageType:
+    def get_pil_image(self, image_name: str) -> PILImageType:
         try:
-            return self._services.files.get(image_origin, image_name)
+            return self._services.files.get(image_name)
         except ImageFileNotFoundException:
             self._services.logger.error("Failed to get image file")
             raise
@@ -273,9 +266,9 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem getting image file")
             raise e
 
-    def get_record(self, image_origin: ResourceOrigin, image_name: str) -> ImageRecord:
+    def get_record(self, image_name: str) -> ImageRecord:
         try:
-            return self._services.records.get(image_origin, image_name)
+            return self._services.records.get(image_name)
         except ImageRecordNotFoundException:
             self._services.logger.error("Image record not found")
             raise
@@ -283,14 +276,14 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem getting image record")
             raise e
 
-    def get_dto(self, image_origin: ResourceOrigin, image_name: str) -> ImageDTO:
+    def get_dto(self, image_name: str) -> ImageDTO:
         try:
-            image_record = self._services.records.get(image_origin, image_name)
+            image_record = self._services.records.get(image_name)
 
             image_dto = image_record_to_dto(
                 image_record,
-                self._services.urls.get_image_url(image_origin, image_name),
-                self._services.urls.get_image_url(image_origin, image_name, True),
+                self._services.urls.get_image_url(image_name),
+                self._services.urls.get_image_url(image_name, True),
             )
 
             return image_dto
@@ -301,11 +294,9 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem getting image DTO")
             raise e
 
-    def get_path(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
+    def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         try:
-            return self._services.files.get_path(image_origin, image_name, thumbnail)
+            return self._services.files.get_path(image_name, thumbnail)
         except Exception as e:
             self._services.logger.error("Problem getting image path")
             raise e
@@ -317,11 +308,9 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem validating image path")
             raise e
 
-    def get_url(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
+    def get_url(self, image_name: str, thumbnail: bool = False) -> str:
         try:
-            return self._services.urls.get_image_url(image_origin, image_name, thumbnail)
+            return self._services.urls.get_image_url(image_name, thumbnail)
         except Exception as e:
             self._services.logger.error("Problem getting image path")
             raise e
@@ -347,10 +336,8 @@ class ImageService(ImageServiceABC):
                 map(
                     lambda r: image_record_to_dto(
                         r,
-                        self._services.urls.get_image_url(r.image_origin, r.image_name),
-                        self._services.urls.get_image_url(
-                            r.image_origin, r.image_name, True
-                        ),
+                        self._services.urls.get_image_url(r.image_name),
+                        self._services.urls.get_image_url(r.image_name, True),
                     ),
                     results.items,
                 )
@@ -366,10 +353,10 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem getting paginated image DTOs")
             raise e
 
-    def delete(self, image_origin: ResourceOrigin, image_name: str):
+    def delete(self, image_name: str):
         try:
-            self._services.files.delete(image_origin, image_name)
-            self._services.records.delete(image_origin, image_name)
+            self._services.files.delete(image_name)
+            self._services.records.delete(image_name)
         except ImageRecordDeleteException:
             self._services.logger.error(f"Failed to delete image record")
             raise

invokeai/app/services/latent_storage.py

@@ -1,6 +1,5 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-import os
 from abc import ABC, abstractmethod
 from pathlib import Path
 from queue import Queue
@@ -70,24 +69,26 @@ class ForwardCacheLatentsStorage(LatentsStorageBase):
 class DiskLatentsStorage(LatentsStorageBase):
     """Stores latents in a folder on disk without caching"""
 
-    __output_folder: str
+    __output_folder: str | Path
 
-    def __init__(self, output_folder: str):
-        self.__output_folder = output_folder
-        Path(output_folder).mkdir(parents=True, exist_ok=True)
+    def __init__(self, output_folder: str | Path):
+        self.__output_folder = output_folder if isinstance(output_folder, Path) else Path(output_folder)
+        self.__output_folder.mkdir(parents=True, exist_ok=True)
 
     def get(self, name: str) -> torch.Tensor:
         latent_path = self.get_path(name)
         return torch.load(latent_path)
 
     def save(self, name: str, data: torch.Tensor) -> None:
+        self.__output_folder.mkdir(parents=True, exist_ok=True)
         latent_path = self.get_path(name)
         torch.save(data, latent_path)
 
     def delete(self, name: str) -> None:
         latent_path = self.get_path(name)
-        os.remove(latent_path)
+        latent_path.unlink()
+        
 
-    def get_path(self, name: str) -> str:
-        return os.path.join(self.__output_folder, name)
+    def get_path(self, name: str) -> Path:
+        return self.__output_folder / name
     

invokeai/app/services/models/image_record.py

@@ -79,8 +79,6 @@ class ImageUrlsDTO(BaseModel):
 
     image_name: str = Field(description="The unique name of the image.")
     """The unique name of the image."""
-    image_origin: ResourceOrigin = Field(description="The type of the image.")
-    """The origin of the image."""
     image_url: str = Field(description="The URL of the image.")
     """The URL of the image."""
     thumbnail_url: str = Field(description="The URL of the image's thumbnail.")

invokeai/app/services/urls.py

@@ -1,17 +1,12 @@
 import os
 from abc import ABC, abstractmethod
 
-from invokeai.app.models.image import ResourceOrigin
-from invokeai.app.util.thumbnails import get_thumbnail_name
-
 
 class UrlServiceBase(ABC):
     """Responsible for building URLs for resources."""
 
     @abstractmethod
-    def get_image_url(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
+    def get_image_url(self, image_name: str, thumbnail: bool = False) -> str:
         """Gets the URL for an image or thumbnail."""
         pass
 
@@ -20,15 +15,11 @@ class LocalUrlService(UrlServiceBase):
     def __init__(self, base_url: str = "api/v1"):
         self._base_url = base_url
 
-    def get_image_url(
-        self, image_origin: ResourceOrigin, image_name: str, thumbnail: bool = False
-    ) -> str:
+    def get_image_url(self, image_name: str, thumbnail: bool = False) -> str:
         image_basename = os.path.basename(image_name)
 
         # These paths are determined by the routes in invokeai/app/api/routers/images.py
         if thumbnail:
-            return (
-                f"{self._base_url}/images/{image_origin.value}/{image_basename}/thumbnail"
-            )
+            return f"{self._base_url}/images/{image_basename}/thumbnail"
 
-        return f"{self._base_url}/images/{image_origin.value}/{image_basename}"
+        return f"{self._base_url}/images/{image_basename}"

invokeai/backend/generator/txt2img.py

@@ -6,7 +6,7 @@ import torch
 
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 from diffusers.models.controlnet import ControlNetModel, ControlNetOutput
-from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
+from diffusers.pipelines.controlnet import MultiControlNetModel
 
 from ..stable_diffusion import (
     ConditioningData,

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -23,7 +23,7 @@ from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
 from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import (
     StableDiffusionPipeline,
 )
-from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
+from diffusers.pipelines.controlnet import MultiControlNetModel
 
 from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img import (
     StableDiffusionImg2ImgPipeline,
@@ -46,6 +46,7 @@ from .diffusion import (
     AttentionMapSaver,
     InvokeAIDiffuserComponent,
     PostprocessingSettings,
+    ControlNetData,
 )
 from .offloading import FullyLoadedModelGroup, LazilyLoadedModelGroup, ModelGroup
 from .textual_inversion_manager import TextualInversionManager
@@ -214,13 +215,6 @@ class GeneratorToCallbackinator(Generic[ParamType, ReturnType, CallbackType]):
             raise AssertionError("why was that an empty generator?")
         return result
 
-@dataclass
-class ControlNetData:
-    model: ControlNetModel = Field(default=None)
-    image_tensor: torch.Tensor= Field(default=None)
-    weight: Union[float, List[float]]= Field(default=1.0)
-    begin_step_percent: float = Field(default=0.0)
-    end_step_percent: float = Field(default=1.0)
 
 @dataclass(frozen=True)
 class ConditioningData:
@@ -656,69 +650,18 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
 
         # TODO: should this scaling happen here or inside self._unet_forward?
         #     i.e. before or after passing it to InvokeAIDiffuserComponent
-        latent_model_input = self.scheduler.scale_model_input(latents, timestep)
-
-        # default is no controlnet, so set controlnet processing output to None
-        down_block_res_samples, mid_block_res_sample = None, None
-
-        if control_data is not None:
-            # FIXME: make sure guidance_scale < 1.0 is handled correctly if doing per-step guidance setting
-            # if conditioning_data.guidance_scale > 1.0:
-            if conditioning_data.guidance_scale is not None:
-                # expand the latents input to control model if doing classifier free guidance
-                #    (which I think for now is always true, there is conditional elsewhere that stops execution if
-                #     classifier_free_guidance is <= 1.0 ?)
-                latent_control_input = torch.cat([latent_model_input] * 2)
-            else:
-                latent_control_input = latent_model_input
-            # control_data should be type List[ControlNetData]
-            # this loop covers both ControlNet (one ControlNetData in list)
-            #      and MultiControlNet (multiple ControlNetData in list)
-            for i, control_datum in enumerate(control_data):
-                # print("controlnet", i, "==>", type(control_datum))
-                first_control_step = math.floor(control_datum.begin_step_percent * total_step_count)
-                last_control_step = math.ceil(control_datum.end_step_percent * total_step_count)
-                # only apply controlnet if current step is within the controlnet's begin/end step range
-                if step_index >= first_control_step and step_index <= last_control_step:
-                    # print("running controlnet", i, "for step", step_index)
-                    if isinstance(control_datum.weight, list):
-                        # if controlnet has multiple weights, use the weight for the current step
-                        controlnet_weight = control_datum.weight[step_index]
-                    else:
-                        # if controlnet has a single weight, use it for all steps
-                        controlnet_weight = control_datum.weight
-                    down_samples, mid_sample = control_datum.model(
-                        sample=latent_control_input,
-                        timestep=timestep,
-                        encoder_hidden_states=torch.cat([conditioning_data.unconditioned_embeddings,
-                                                         conditioning_data.text_embeddings]),
-                        controlnet_cond=control_datum.image_tensor,
-                        conditioning_scale=controlnet_weight,
-                        # cross_attention_kwargs,
-                        guess_mode=False,
-                        return_dict=False,
-                    )
-                    if down_block_res_samples is None and mid_block_res_sample is None:
-                        down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
-                    else:
-                        # add controlnet outputs together if have multiple controlnets
-                        down_block_res_samples = [
-                            samples_prev + samples_curr
-                            for samples_prev, samples_curr in zip(down_block_res_samples, down_samples)
-                        ]
-                        mid_block_res_sample += mid_sample
+        unet_latent_input = self.scheduler.scale_model_input(latents, timestep)
 
         # predict the noise residual
         noise_pred = self.invokeai_diffuser.do_diffusion_step(
-            latent_model_input,
-            t,
-            conditioning_data.unconditioned_embeddings,
-            conditioning_data.text_embeddings,
-            conditioning_data.guidance_scale,
+            x=unet_latent_input,
+            sigma=t,
+            unconditioning=conditioning_data.unconditioned_embeddings,
+            conditioning=conditioning_data.text_embeddings,
+            unconditional_guidance_scale=conditioning_data.guidance_scale,
+            control_data=control_data,
             step_index=step_index,
             total_step_count=total_step_count,
-            down_block_additional_residuals=down_block_res_samples,  # from controlnet(s)
-            mid_block_additional_residual=mid_block_res_sample,      # from controlnet(s)
         )
 
         # compute the previous noisy sample x_t -> x_t-1
@@ -1038,6 +981,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         device="cuda",
         dtype=torch.float16,
         do_classifier_free_guidance=True,
+        control_mode="balanced"
     ):
 
         if not isinstance(image, torch.Tensor):
@@ -1068,6 +1012,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             repeat_by = num_images_per_prompt
         image = image.repeat_interleave(repeat_by, dim=0)
         image = image.to(device=device, dtype=dtype)
-        if do_classifier_free_guidance:
-            image = torch.cat([image] * 2)
+        #cfg_injection = (control_mode == "more_control" or control_mode == "unbalanced")
+        #if do_classifier_free_guidance and not cfg_injection:
+        #    image = torch.cat([image] * 2)
         return image

invokeai/backend/stable_diffusion/diffusion/__init__.py

@@ -3,4 +3,4 @@ Initialization file for invokeai.models.diffusion
 """
 from .cross_attention_control import InvokeAICrossAttentionMixin
 from .cross_attention_map_saving import AttentionMapSaver
-from .shared_invokeai_diffusion import InvokeAIDiffuserComponent, PostprocessingSettings
+from .shared_invokeai_diffusion import InvokeAIDiffuserComponent, PostprocessingSettings, ControlNetData

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -1,11 +1,14 @@
 from contextlib import contextmanager
 from dataclasses import dataclass
+from pydantic import Field
 from math import ceil
 from typing import Any, Callable, Dict, Optional, Union, List
 
 import numpy as np
 import torch
+import math
 from diffusers import UNet2DConditionModel
+from diffusers.models.controlnet import ControlNetModel
 from diffusers.models.attention_processor import AttentionProcessor
 from typing_extensions import TypeAlias
 
@@ -40,6 +43,17 @@ class PostprocessingSettings:
     v_symmetry_time_pct: Optional[float]
 
 
+# TODO: pydantic Field work with dataclasses?
+@dataclass
+class ControlNetData:
+    model: ControlNetModel = Field(default=None)
+    image_tensor: torch.Tensor = Field(default=None)
+    weight: Union[float, List[float]] = Field(default=1.0)
+    begin_step_percent: float = Field(default=0.0)
+    end_step_percent: float = Field(default=1.0)
+    control_mode: str = Field(default="balanced")
+
+
 class InvokeAIDiffuserComponent:
     """
     The aim of this component is to provide a single place for code that can be applied identically to
@@ -182,8 +196,9 @@ class InvokeAIDiffuserComponent:
         conditioning: Union[torch.Tensor, dict],
         # unconditional_guidance_scale: float,
         unconditional_guidance_scale: Union[float, List[float]],
-        step_index: Optional[int] = None,
-        total_step_count: Optional[int] = None,
+        step_index: int,
+        total_step_count: int,
+        control_data: Optional[List[ControlNetData]],
         **kwargs,
     ):
         """
@@ -213,31 +228,56 @@ class InvokeAIDiffuserComponent:
                 )
             )
 
+        if self.sequential_guidance:
+            down_block_res_samples, mid_block_res_sample = self._run_controlnet_sequentially(
+                unconditioning=unconditioning,
+                conditioning=conditioning,
+                control_data=control_data,
+                sample=x,
+                timestep=sigma,
+                step_index=step_index,
+                total_step_count=total_step_count,
+            )
+        else:
+            down_block_res_samples, mid_block_res_sample = self._run_controlnet_normally(
+                unconditioning=unconditioning,
+                conditioning=conditioning,
+                control_data=control_data,
+                sample=x,
+                timestep=sigma,
+                step_index=step_index,
+                total_step_count=total_step_count,
+            )
+
         wants_cross_attention_control = len(cross_attention_control_types_to_do) > 0
         wants_hybrid_conditioning = isinstance(conditioning, dict)
 
         if wants_hybrid_conditioning:
             unconditioned_next_x, conditioned_next_x = self._apply_hybrid_conditioning(
-                x, sigma, unconditioning, conditioning, **kwargs,
+                x, sigma, unconditioning, conditioning,
+                down_block_additional_residuals=down_block_res_samples,  # from controlnet(s)
+                mid_block_additional_residual=mid_block_res_sample,      # from controlnet(s)
+                **kwargs,
             )
         elif wants_cross_attention_control:
             (
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_cross_attention_controlled_conditioning(
-                x,
-                sigma,
-                unconditioning,
-                conditioning,
-                cross_attention_control_types_to_do,
+                x, sigma, unconditioning, conditioning, cross_attention_control_types_to_do,
+                down_block_additional_residuals=down_block_res_samples,  # from controlnet(s)
+                mid_block_additional_residual=mid_block_res_sample,      # from controlnet(s)
                 **kwargs,
             )
-        elif self.sequential_guidance:
+        elif True: #self.sequential_guidance:
             (
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_standard_conditioning_sequentially(
-                x, sigma, unconditioning, conditioning, **kwargs,
+                x, sigma, unconditioning, conditioning,
+                down_block_additional_residuals=down_block_res_samples,  # from controlnet(s)
+                mid_block_additional_residual=mid_block_res_sample,      # from controlnet(s)
+                 **kwargs,
             )
 
         else:
@@ -245,7 +285,10 @@ class InvokeAIDiffuserComponent:
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_standard_conditioning(
-                x, sigma, unconditioning, conditioning, **kwargs,
+                x, sigma, unconditioning, conditioning,
+                down_block_additional_residuals=down_block_res_samples,  # from controlnet(s)
+                mid_block_additional_residual=mid_block_res_sample,      # from controlnet(s)
+                **kwargs,
             )
 
         combined_next_x = self._combine(
@@ -293,16 +336,160 @@ class InvokeAIDiffuserComponent:
 
     # methods below are called from do_diffusion_step and should be considered private to this class.
 
-    def _apply_standard_conditioning(self, x, sigma, unconditioning, conditioning, **kwargs):
+    def _run_controlnet_normally(
+        self,
+        unconditioning: torch.Tensor,
+        conditioning: torch.Tensor,
+        control_data: List[ControlNetData],
+        sample: torch.Tensor,
+        timestep: torch.Tensor,
+        step_index: int,
+        total_step_count: int,
+    ):
+        if control_data is None:
+            return (None, None)
+
+        down_block_res_samples, mid_block_res_sample = None, None
+
+        for i, control_datum in enumerate(control_data):
+            control_mode = control_datum.control_mode
+            soft_injection = (control_mode == "more_prompt" or control_mode == "more_control")
+            cfg_injection = (control_mode == "more_control" or control_mode == "unbalanced")
+
+            first_control_step = math.floor(control_datum.begin_step_percent * total_step_count)
+            last_control_step = math.ceil(control_datum.end_step_percent * total_step_count)
+            # only apply controlnet if current step is within the controlnet's begin/end step range
+            if step_index >= first_control_step and step_index <= last_control_step:
+
+                if cfg_injection:
+                    control_sample = sample
+                    control_timestep = timestep
+                    control_image_tensor = control_datum.image_tensor
+                    encoder_hidden_states = conditioning  # TODO: ask bug
+                else:
+                    control_sample = torch.cat([sample] * 2)
+                    control_timestep = torch.cat([timestep] * 2)
+                    control_image_tensor = torch.cat([control_datum.image_tensor] * 2)
+                    encoder_hidden_states = torch.cat([unconditioning, conditioning])
+
+                if isinstance(control_datum.weight, list):
+                    weight = control_datum.weight[step_index]
+                else:
+                    weight = control_datum.weight
+
+                # controlnet(s) inference
+                down_samples, mid_sample = control_datum.model(
+                    sample=control_sample,
+                    timestep=control_timestep,
+                    encoder_hidden_states=encoder_hidden_states,
+                    controlnet_cond=control_image_tensor,
+                    conditioning_scale=weight, # controlnet specific, NOT the guidance scale
+                    guess_mode=soft_injection, # this is still called guess_mode in diffusers ControlNetModel
+                    return_dict=False,
+                )
+
+                if cfg_injection:
+                    down_samples = [torch.cat([torch.zeros_like(d), d]) for d in down_samples]
+                    mid_sample = torch.cat([torch.zeros_like(mid_sample), mid_sample])
+
+                if down_block_res_samples is None and mid_block_res_sample is None:
+                    down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
+                else:
+                    down_block_res_samples = [
+                        samples_prev + samples_curr
+                        for samples_prev, samples_curr in zip(down_block_res_samples, down_samples)
+                    ]
+                    mid_block_res_sample += mid_sample
+
+        return down_block_res_samples, mid_block_res_sample
+
+    def _run_controlnet_sequentially(
+        self,
+        unconditioning: torch.Tensor,
+        conditioning: torch.Tensor,
+        control_data: List[ControlNetData],
+        sample: torch.Tensor,
+        timestep: torch.Tensor,
+        step_index: int,
+        total_step_count: int,
+    ):
+        if control_data is None:
+            return (None, None)
+
+        down_block_res_samples, mid_block_res_sample = None, None
+
+        for i, control_datum in enumerate(control_data):
+            control_mode = control_datum.control_mode
+            soft_injection = (control_mode == "more_prompt" or control_mode == "more_control")
+            cfg_injection = (control_mode == "more_control" or control_mode == "unbalanced")
+
+            first_control_step = math.floor(control_datum.begin_step_percent * total_step_count)
+            last_control_step = math.ceil(control_datum.end_step_percent * total_step_count)
+            # only apply controlnet if current step is within the controlnet's begin/end step range
+            if step_index >= first_control_step and step_index <= last_control_step:
+
+                if isinstance(control_datum.weight, list):
+                    weight = control_datum.weight[step_index]
+                else:
+                    weight = control_datum.weight
+
+                # controlnet(s) inference
+                cond_down_samples, cond_mid_sample = control_datum.model(
+                    sample=sample,
+                    timestep=timestep,
+                    encoder_hidden_states=conditioning, # TODO: ask bug
+                    controlnet_cond=control_datum.image_tensor,
+                    conditioning_scale=weight, # controlnet specific, NOT the guidance scale
+                    guess_mode=soft_injection, # this is still called guess_mode in diffusers ControlNetModel
+                    return_dict=False,
+                )
+
+                if cfg_injection:
+                    uncond_down_samples = [torch.zeros_like(d) for d in cond_down_samples]
+                    uncond_mid_sample = torch.zeros_like(cond_mid_sample)
+
+                else:
+                    uncond_down_samples, uncond_mid_sample = control_datum.model(
+                        sample=sample,
+                        timestep=timestep,
+                        encoder_hidden_states=unconditioning,
+                        controlnet_cond=control_datum.image_tensor,
+                        conditioning_scale=weight, # controlnet specific, NOT the guidance scale
+                        guess_mode=soft_injection, # this is still called guess_mode in diffusers ControlNetModel
+                        return_dict=False,
+                    )
+
+                down_samples = [torch.cat([ud, cd]) for ud, cd in zip(uncond_down_samples, cond_down_samples)]
+                mid_sample = torch.cat([uncond_mid_sample, cond_mid_sample])
+
+                if down_block_res_samples is None and mid_block_res_sample is None:
+                    down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
+                else:
+                    down_block_res_samples = [
+                        samples_prev + samples_curr
+                        for samples_prev, samples_curr in zip(down_block_res_samples, down_samples)
+                    ]
+                    mid_block_res_sample += mid_sample
+
+        return down_block_res_samples, mid_block_res_sample
+
+    def _apply_standard_conditioning(
+        self,
+        x: torch.Tensor,
+        sigma: torch.Tensor,
+        unconditioning: torch.Tensor,
+        conditioning: torch.Tensor,
+        **kwargs
+    ):
         # fast batched path
         x_twice = torch.cat([x] * 2)
         sigma_twice = torch.cat([sigma] * 2)
         both_conditionings = torch.cat([unconditioning, conditioning])
-        both_results = self.model_forward_callback(
-            x_twice, sigma_twice, both_conditionings, **kwargs,
-        )
+
+        both_results = self.model_forward_callback(x_twice, sigma_twice, both_conditionings, **kwargs)
         unconditioned_next_x, conditioned_next_x = both_results.chunk(2)
         if conditioned_next_x.device.type == "mps":
+            # TODO: check if this still present
             # prevent a result filled with zeros. seems to be a torch bug.
             conditioned_next_x = conditioned_next_x.clone()
         return unconditioned_next_x, conditioned_next_x
@@ -310,15 +497,43 @@ class InvokeAIDiffuserComponent:
     def _apply_standard_conditioning_sequentially(
         self,
         x: torch.Tensor,
-        sigma,
+        sigma: torch.Tensor,
         unconditioning: torch.Tensor,
         conditioning: torch.Tensor,
+        down_block_additional_residuals,  # from controlnet(s)
+        mid_block_additional_residual,      # from controlnet(s)
         **kwargs,
     ):
+        # split controlnet data to cond and uncond
+        if down_block_additional_residuals is None:
+            uncond_down_block_res_samples = None
+            cond_down_block_res_samples = None
+            uncond_mid_block_res_sample = None
+            cond_mid_block_res_sample = None
+
+        else:
+            uncond_down_block_res_samples = []
+            cond_down_block_res_samples = []
+            for d in down_block_additional_residuals:
+                ud, cd = d.chunk(2)
+                uncond_down_block_res_samples.append(ud)
+                cond_down_block_res_samples.append(cd)
+
+            uncond_mid_block_res_sample, cond_mid_block_res_sample = mid_block_additional_residual.chunk(2)
+
         # low-memory sequential path
-        unconditioned_next_x = self.model_forward_callback(x, sigma, unconditioning, **kwargs)
-        conditioned_next_x = self.model_forward_callback(x, sigma, conditioning, **kwargs)
+        unconditioned_next_x = self.model_forward_callback(
+            x, sigma, unconditioning, **kwargs,
+            down_block_additional_residuals=uncond_down_block_res_samples,
+            mid_block_additional_residual=uncond_mid_block_res_sample,
+        )
+        conditioned_next_x = self.model_forward_callback(
+            x, sigma, conditioning, **kwargs,
+            down_block_additional_residuals=cond_down_block_res_samples,
+            mid_block_additional_residual=cond_mid_block_res_sample,
+        )
         if conditioned_next_x.device.type == "mps":
+            # TODO: check if still present
             # prevent a result filled with zeros. seems to be a torch bug.
             conditioned_next_x = conditioned_next_x.clone()
         return unconditioned_next_x, conditioned_next_x

invokeai/frontend/web/package.json

@@ -62,10 +62,12 @@
     "@dagrejs/graphlib": "^2.1.12",
     "@dnd-kit/core": "^6.0.8",
     "@dnd-kit/modifiers": "^6.0.1",
-    "@emotion/react": "^11.10.6",
+    "@emotion/react": "^11.11.1",
     "@emotion/styled": "^11.10.6",
     "@floating-ui/react-dom": "^2.0.0",
     "@fontsource/inter": "^4.5.15",
+    "@mantine/core": "^6.0.13",
+    "@mantine/hooks": "^6.0.13",
     "@reduxjs/toolkit": "^1.9.5",
     "@roarr/browser-log-writer": "^1.1.5",
     "chakra-ui-contextmenu": "^1.0.5",

invokeai/frontend/web/public/locales/en.json

@@ -524,7 +524,8 @@
         "initialImage": "Initial Image",
         "showOptionsPanel": "Show Options Panel",
         "hidePreview": "Hide Preview",
-        "showPreview": "Show Preview"
+        "showPreview": "Show Preview",
+        "controlNetControlMode": "Control Mode"
     },
     "settings": {
         "models": "Models",

invokeai/frontend/web/src/app/components/ThemeLocaleProvider.tsx

@@ -3,11 +3,11 @@ import {
   createLocalStorageManager,
   extendTheme,
 } from '@chakra-ui/react';
+import { RootState } from 'app/store/store';
+import { useAppSelector } from 'app/store/storeHooks';
 import { ReactNode, useEffect } from 'react';
 import { useTranslation } from 'react-i18next';
 import { theme as invokeAITheme } from 'theme/theme';
-import { RootState } from 'app/store/store';
-import { useAppSelector } from 'app/store/storeHooks';
 
 import { greenTeaThemeColors } from 'theme/colors/greenTea';
 import { invokeAIThemeColors } from 'theme/colors/invokeAI';
@@ -15,6 +15,8 @@ import { lightThemeColors } from 'theme/colors/lightTheme';
 import { oceanBlueColors } from 'theme/colors/oceanBlue';
 
 import '@fontsource/inter/variable.css';
+import { MantineProvider } from '@mantine/core';
+import { mantineTheme } from 'mantine-theme/theme';
 import 'overlayscrollbars/overlayscrollbars.css';
 import 'theme/css/overlayscrollbars.css';
 
@@ -51,9 +53,11 @@ function ThemeLocaleProvider({ children }: ThemeLocaleProviderProps) {
   }, [direction]);
 
   return (
-    <ChakraProvider theme={theme} colorModeManager={manager}>
-      {children}
-    </ChakraProvider>
+    <MantineProvider withGlobalStyles theme={mantineTheme}>
+      <ChakraProvider theme={theme} colorModeManager={manager}>
+        {children}
+      </ChakraProvider>
+    </MantineProvider>
   );
 }
 

invokeai/frontend/web/src/app/constants.ts

@@ -22,9 +22,9 @@ export const SCHEDULERS = [
 export type Scheduler = (typeof SCHEDULERS)[number];
 
 // Valid upscaling levels
-export const UPSCALING_LEVELS: Array<{ key: string; value: number }> = [
-  { key: '2x', value: 2 },
-  { key: '4x', value: 4 },
+export const UPSCALING_LEVELS: Array<{ label: string; value: string }> = [
+  { label: '2x', value: '2' },
+  { label: '4x', value: '4' },
 ];
 export const NUMPY_RAND_MIN = 0;
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts

@@ -34,10 +34,7 @@ export const addControlNetImageProcessedListener = () => {
           [controlNet.processorNode.id]: {
             ...controlNet.processorNode,
             is_intermediate: true,
-            image: pick(controlNet.controlImage, [
-              'image_name',
-              'image_origin',
-            ]),
+            image: pick(controlNet.controlImage, ['image_name']),
           },
         },
       };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts

@@ -25,7 +25,7 @@ export const addRequestedImageDeletionListener = () => {
     effect: (action, { dispatch, getState }) => {
       const { image, imageUsage } = action.payload;
 
-      const { image_name, image_origin } = image;
+      const { image_name } = image;
 
       const state = getState();
       const selectedImage = state.gallery.selectedImage;
@@ -79,9 +79,7 @@ export const addRequestedImageDeletionListener = () => {
       dispatch(imageRemoved(image_name));
 
       // Delete from server
-      dispatch(
-        imageDeleted({ imageName: image_name, imageOrigin: image_origin })
-      );
+      dispatch(imageDeleted({ imageName: image_name }));
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageMetadataReceived.ts

@@ -20,7 +20,6 @@ export const addImageMetadataReceivedFulfilledListener = () => {
         dispatch(
           imageUpdated({
             imageName: image.image_name,
-            imageOrigin: image.image_origin,
             requestBody: { is_intermediate: false },
           })
         );

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts

@@ -36,13 +36,12 @@ export const addInvocationCompleteEventListener = () => {
 
       // This complete event has an associated image output
       if (isImageOutput(result) && !nodeDenylist.includes(node.type)) {
-        const { image_name, image_origin } = result.image;
+        const { image_name } = result.image;
 
         // Get its metadata
         dispatch(
           imageMetadataReceived({
             imageName: image_name,
-            imageOrigin: image_origin,
           })
         );
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved.ts

@@ -11,12 +11,11 @@ export const addStagingAreaImageSavedListener = () => {
   startAppListening({
     actionCreator: stagingAreaImageSaved,
     effect: async (action, { dispatch, getState, take }) => {
-      const { image_name, image_origin } = action.payload;
+      const { image_name } = action.payload;
 
       dispatch(
         imageUpdated({
           imageName: image_name,
-          imageOrigin: image_origin,
           requestBody: {
             is_intermediate: false,
           },

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateImageUrlsOnConnect.ts

@@ -80,11 +80,10 @@ export const addUpdateImageUrlsOnConnectListener = () => {
         `Fetching new image URLs for ${allUsedImages.length} images`
       );
 
-      allUsedImages.forEach(({ image_name, image_origin }) => {
+      allUsedImages.forEach(({ image_name }) => {
         dispatch(
           imageUrlsReceived({
             imageName: image_name,
-            imageOrigin: image_origin,
           })
         );
       });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/userInvokedCanvas.ts

@@ -116,7 +116,6 @@ export const addUserInvokedCanvasListener = () => {
         // Update the base node with the image name and type
         baseNode.image = {
           image_name: baseImageDTO.image_name,
-          image_origin: baseImageDTO.image_origin,
         };
       }
 
@@ -143,7 +142,6 @@ export const addUserInvokedCanvasListener = () => {
         // Update the base node with the image name and type
         baseNode.mask = {
           image_name: maskImageDTO.image_name,
-          image_origin: maskImageDTO.image_origin,
         };
       }
 
@@ -160,7 +158,6 @@ export const addUserInvokedCanvasListener = () => {
         dispatch(
           imageUpdated({
             imageName: baseNode.image.image_name,
-            imageOrigin: baseNode.image.image_origin,
             requestBody: { session_id: sessionId },
           })
         );
@@ -171,7 +168,6 @@ export const addUserInvokedCanvasListener = () => {
         dispatch(
           imageUpdated({
             imageName: baseNode.mask.image_name,
-            imageOrigin: baseNode.mask.image_origin,
             requestBody: { session_id: sessionId },
           })
         );

invokeai/frontend/web/src/common/components/IAICustomSelect.tsx

@@ -1,256 +0,0 @@
-import { CheckIcon, ChevronUpIcon } from '@chakra-ui/icons';
-import {
-  Box,
-  Flex,
-  FormControl,
-  FormControlProps,
-  FormLabel,
-  Grid,
-  GridItem,
-  List,
-  ListItem,
-  Text,
-  Tooltip,
-  TooltipProps,
-} from '@chakra-ui/react';
-import { autoUpdate, offset, shift, useFloating } from '@floating-ui/react-dom';
-import { useSelect } from 'downshift';
-import { isString } from 'lodash-es';
-import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
-
-import { memo, useLayoutEffect, useMemo } from 'react';
-import { getInputOutlineStyles } from 'theme/util/getInputOutlineStyles';
-
-export type ItemTooltips = { [key: string]: string };
-
-export type IAICustomSelectOption = {
-  value: string;
-  label: string;
-  tooltip?: string;
-};
-
-type IAICustomSelectProps = {
-  label?: string;
-  value: string;
-  data: IAICustomSelectOption[] | string[];
-  onChange: (v: string) => void;
-  withCheckIcon?: boolean;
-  formControlProps?: FormControlProps;
-  tooltip?: string;
-  tooltipProps?: Omit<TooltipProps, 'children'>;
-  ellipsisPosition?: 'start' | 'end';
-  isDisabled?: boolean;
-};
-
-const IAICustomSelect = (props: IAICustomSelectProps) => {
-  const {
-    label,
-    withCheckIcon,
-    formControlProps,
-    tooltip,
-    tooltipProps,
-    ellipsisPosition = 'end',
-    data,
-    value,
-    onChange,
-    isDisabled = false,
-  } = props;
-
-  const values = useMemo(() => {
-    return data.map<IAICustomSelectOption>((v) => {
-      if (isString(v)) {
-        return { value: v, label: v };
-      }
-      return v;
-    });
-  }, [data]);
-
-  const stringValues = useMemo(() => {
-    return values.map((v) => v.value);
-  }, [values]);
-
-  const valueData = useMemo(() => {
-    return values.find((v) => v.value === value);
-  }, [values, value]);
-
-  const {
-    isOpen,
-    getToggleButtonProps,
-    getLabelProps,
-    getMenuProps,
-    highlightedIndex,
-    getItemProps,
-  } = useSelect({
-    items: stringValues,
-    selectedItem: value,
-    onSelectedItemChange: ({ selectedItem: newSelectedItem }) => {
-      newSelectedItem && onChange(newSelectedItem);
-    },
-  });
-
-  const { refs, floatingStyles, update } = useFloating<HTMLButtonElement>({
-    // whileElementsMounted: autoUpdate,
-    middleware: [offset(4), shift({ crossAxis: true, padding: 8 })],
-  });
-
-  useLayoutEffect(() => {
-    if (isOpen && refs.reference.current && refs.floating.current) {
-      return autoUpdate(refs.reference.current, refs.floating.current, update);
-    }
-  }, [isOpen, update, refs.floating, refs.reference]);
-
-  const labelTextDirection = useMemo(() => {
-    if (ellipsisPosition === 'start') {
-      return document.dir === 'rtl' ? 'ltr' : 'rtl';
-    }
-
-    return document.dir;
-  }, [ellipsisPosition]);
-
-  return (
-    <FormControl sx={{ w: 'full' }} {...formControlProps}>
-      {label && (
-        <FormLabel
-          {...getLabelProps()}
-          onClick={() => {
-            refs.floating.current && refs.floating.current.focus();
-          }}
-        >
-          {label}
-        </FormLabel>
-      )}
-      <Tooltip label={tooltip} {...tooltipProps}>
-        <Flex
-          {...getToggleButtonProps({ ref: refs.reference })}
-          sx={{
-            alignItems: 'center',
-            userSelect: 'none',
-            cursor: 'pointer',
-            overflow: 'hidden',
-            width: 'full',
-            py: 1,
-            px: 2,
-            gap: 2,
-            justifyContent: 'space-between',
-            pointerEvents: isDisabled ? 'none' : undefined,
-            opacity: isDisabled ? 0.5 : undefined,
-            ...getInputOutlineStyles(),
-          }}
-        >
-          <Text
-            sx={{
-              fontSize: 'sm',
-              fontWeight: 500,
-              color: 'base.100',
-              whiteSpace: 'nowrap',
-              overflow: 'hidden',
-              textOverflow: 'ellipsis',
-              direction: labelTextDirection,
-            }}
-          >
-            {valueData?.label}
-          </Text>
-          <ChevronUpIcon
-            sx={{
-              color: 'base.300',
-              transform: isOpen ? 'rotate(0deg)' : 'rotate(180deg)',
-              transitionProperty: 'common',
-              transitionDuration: 'normal',
-            }}
-          />
-        </Flex>
-      </Tooltip>
-      <Box {...getMenuProps()}>
-        {isOpen && (
-          <List
-            as={Flex}
-            ref={refs.floating}
-            sx={{
-              ...floatingStyles,
-              top: 0,
-              insetInlineStart: 0,
-              flexDirection: 'column',
-              zIndex: 2,
-              bg: 'base.800',
-              borderRadius: 'base',
-              border: '1px',
-              borderColor: 'base.700',
-              shadow: 'dark-lg',
-              py: 2,
-              px: 0,
-              h: 'fit-content',
-              maxH: 64,
-              minW: 48,
-            }}
-          >
-            <OverlayScrollbarsComponent>
-              {values.map((v, index) => {
-                const isSelected = value === v.value;
-                const isHighlighted = highlightedIndex === index;
-                const fontWeight = isSelected ? 700 : 500;
-                const bg = isHighlighted
-                  ? 'base.700'
-                  : isSelected
-                  ? 'base.750'
-                  : undefined;
-                return (
-                  <Tooltip
-                    isDisabled={!v.tooltip}
-                    key={`${v.value}${index}`}
-                    label={v.tooltip}
-                    hasArrow
-                    placement="right"
-                  >
-                    <ListItem
-                      sx={{
-                        bg,
-                        py: 1,
-                        paddingInlineStart: 3,
-                        paddingInlineEnd: 6,
-                        cursor: 'pointer',
-                        transitionProperty: 'common',
-                        transitionDuration: '0.15s',
-                      }}
-                      {...getItemProps({ item: v.value, index })}
-                    >
-                      {withCheckIcon ? (
-                        <Grid gridTemplateColumns="1.25rem auto">
-                          <GridItem>
-                            {isSelected && <CheckIcon boxSize={2} />}
-                          </GridItem>
-                          <GridItem>
-                            <Text
-                              sx={{
-                                fontSize: 'sm',
-                                color: 'base.100',
-                                fontWeight,
-                              }}
-                            >
-                              {v.label}
-                            </Text>
-                          </GridItem>
-                        </Grid>
-                      ) : (
-                        <Text
-                          sx={{
-                            fontSize: 'sm',
-                            color: 'base.50',
-                            fontWeight,
-                          }}
-                        >
-                          {v.label}
-                        </Text>
-                      )}
-                    </ListItem>
-                  </Tooltip>
-                );
-              })}
-            </OverlayScrollbarsComponent>
-          </List>
-        )}
-      </Box>
-    </FormControl>
-  );
-};
-
-export default memo(IAICustomSelect);

invokeai/frontend/web/src/common/components/IAIMantineSelect.tsx

@@ -0,0 +1,76 @@
+import { Tooltip } from '@chakra-ui/react';
+import { Select, SelectProps } from '@mantine/core';
+import { memo } from 'react';
+
+export type IAISelectDataType = {
+  value: string;
+  label: string;
+  tooltip?: string;
+};
+
+type IAISelectProps = SelectProps & {
+  tooltip?: string;
+};
+
+const IAIMantineSelect = (props: IAISelectProps) => {
+  const { searchable = true, tooltip, ...rest } = props;
+  return (
+    <Tooltip label={tooltip} placement="top" hasArrow>
+      <Select
+        searchable={searchable}
+        styles={() => ({
+          label: {
+            color: 'var(--invokeai-colors-base-300)',
+            fontWeight: 'normal',
+          },
+          input: {
+            backgroundColor: 'var(--invokeai-colors-base-900)',
+            borderWidth: '2px',
+            borderColor: 'var(--invokeai-colors-base-800)',
+            color: 'var(--invokeai-colors-base-100)',
+            paddingRight: 24,
+            fontWeight: 600,
+            '&:hover': { borderColor: 'var(--invokeai-colors-base-700)' },
+            '&:focus': {
+              borderColor: 'var(--invokeai-colors-accent-600)',
+            },
+          },
+          dropdown: {
+            backgroundColor: 'var(--invokeai-colors-base-800)',
+            borderColor: 'var(--invokeai-colors-base-700)',
+          },
+          item: {
+            backgroundColor: 'var(--invokeai-colors-base-800)',
+            color: 'var(--invokeai-colors-base-200)',
+            padding: 6,
+            '&[data-hovered]': {
+              color: 'var(--invokeai-colors-base-100)',
+              backgroundColor: 'var(--invokeai-colors-base-750)',
+            },
+            '&[data-active]': {
+              backgroundColor: 'var(--invokeai-colors-base-750)',
+              '&:hover': {
+                color: 'var(--invokeai-colors-base-100)',
+                backgroundColor: 'var(--invokeai-colors-base-750)',
+              },
+            },
+            '&[data-selected]': {
+              color: 'var(--invokeai-colors-base-50)',
+              backgroundColor: 'var(--invokeai-colors-accent-650)',
+              fontWeight: 600,
+              '&:hover': {
+                backgroundColor: 'var(--invokeai-colors-accent-600)',
+              },
+            },
+          },
+          rightSection: {
+            width: 24,
+          },
+        })}
+        {...rest}
+      />
+    </Tooltip>
+  );
+};
+
+export default memo(IAIMantineSelect);

invokeai/frontend/web/src/common/components/IAIScrollArea.tsx

@@ -0,0 +1,12 @@
+import { ScrollArea, ScrollAreaProps } from '@mantine/core';
+
+type IAIScrollArea = ScrollAreaProps;
+
+export default function IAIScrollArea(props: IAIScrollArea) {
+  const { ...rest } = props;
+  return (
+    <ScrollArea w="100%" {...rest}>
+      {props.children}
+    </ScrollArea>
+  );
+}

invokeai/frontend/web/src/features/canvas/components/IAICanvasToolbar/IAICanvasToolbar.tsx

@@ -2,7 +2,6 @@ import { Box, ButtonGroup, Flex } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIIconButton from 'common/components/IAIIconButton';
-import IAISelect from 'common/components/IAISelect';
 import useImageUploader from 'common/hooks/useImageUploader';
 import { useSingleAndDoubleClick } from 'common/hooks/useSingleAndDoubleClick';
 import {
@@ -25,7 +24,13 @@ import { getCanvasBaseLayer } from 'features/canvas/util/konvaInstanceProvider';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import { isEqual } from 'lodash-es';
 
-import { ChangeEvent } from 'react';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
+import {
+  canvasCopiedToClipboard,
+  canvasDownloadedAsImage,
+  canvasMerged,
+  canvasSavedToGallery,
+} from 'features/canvas/store/actions';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 import {
@@ -43,12 +48,6 @@ import IAICanvasRedoButton from './IAICanvasRedoButton';
 import IAICanvasSettingsButtonPopover from './IAICanvasSettingsButtonPopover';
 import IAICanvasToolChooserOptions from './IAICanvasToolChooserOptions';
 import IAICanvasUndoButton from './IAICanvasUndoButton';
-import {
-  canvasCopiedToClipboard,
-  canvasDownloadedAsImage,
-  canvasMerged,
-  canvasSavedToGallery,
-} from 'features/canvas/store/actions';
 
 export const selector = createSelector(
   [systemSelector, canvasSelector, isStagingSelector],
@@ -197,8 +196,8 @@ const IAICanvasToolbar = () => {
     dispatch(canvasDownloadedAsImage());
   };
 
-  const handleChangeLayer = (e: ChangeEvent<HTMLSelectElement>) => {
-    const newLayer = e.target.value as CanvasLayer;
+  const handleChangeLayer = (v: string) => {
+    const newLayer = v as CanvasLayer;
     dispatch(setLayer(newLayer));
     if (newLayer === 'mask' && !isMaskEnabled) {
       dispatch(setIsMaskEnabled(true));
@@ -214,13 +213,12 @@ const IAICanvasToolbar = () => {
       }}
     >
       <Box w={24}>
-        <IAISelect
+        <IAIMantineSelect
           tooltip={`${t('unifiedCanvas.layer')} (Q)`}
-          tooltipProps={{ hasArrow: true, placement: 'top' }}
           value={layer}
-          validValues={LAYER_NAMES_DICT}
+          data={LAYER_NAMES_DICT}
           onChange={handleChangeLayer}
-          isDisabled={isStaging}
+          disabled={isStaging}
         />
       </Box>
 

invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts

@@ -866,8 +866,7 @@ export const canvasSlice = createSlice({
     });
 
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_origin, image_url, thumbnail_url } =
-        action.payload;
+      const { image_name, image_url, thumbnail_url } = action.payload;
 
       state.layerState.objects.forEach((object) => {
         if (object.kind === 'image') {

invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts

@@ -4,8 +4,8 @@ import { RgbaColor } from 'react-colorful';
 import { ImageDTO } from 'services/api';
 
 export const LAYER_NAMES_DICT = [
-  { key: 'Base', value: 'base' },
-  { key: 'Mask', value: 'mask' },
+  { label: 'Base', value: 'base' },
+  { label: 'Mask', value: 'mask' },
 ];
 
 export const LAYER_NAMES = ['base', 'mask'] as const;
@@ -13,9 +13,9 @@ export const LAYER_NAMES = ['base', 'mask'] as const;
 export type CanvasLayer = (typeof LAYER_NAMES)[number];
 
 export const BOUNDING_BOX_SCALES_DICT = [
-  { key: 'Auto', value: 'auto' },
-  { key: 'Manual', value: 'manual' },
-  { key: 'None', value: 'none' },
+  { label: 'Auto', value: 'auto' },
+  { label: 'Manual', value: 'manual' },
+  { label: 'None', value: 'none' },
 ];
 
 export const BOUNDING_BOX_SCALES = ['none', 'auto', 'manual'] as const;

invokeai/frontend/web/src/features/controlNet/components/ControlNet.tsx

@@ -1,26 +1,27 @@
+import { Box, ChakraProps, Flex } from '@chakra-ui/react';
+import { useAppDispatch } from 'app/store/storeHooks';
 import { memo, useCallback } from 'react';
+import { FaCopy, FaTrash } from 'react-icons/fa';
 import {
   ControlNetConfig,
   controlNetAdded,
   controlNetRemoved,
   controlNetToggled,
 } from '../store/controlNetSlice';
-import { useAppDispatch } from 'app/store/storeHooks';
 import ParamControlNetModel from './parameters/ParamControlNetModel';
 import ParamControlNetWeight from './parameters/ParamControlNetWeight';
-import { Flex, Box, ChakraProps } from '@chakra-ui/react';
-import { FaCopy, FaTrash } from 'react-icons/fa';
 
-import ParamControlNetBeginEnd from './parameters/ParamControlNetBeginEnd';
-import ControlNetImagePreview from './ControlNetImagePreview';
-import IAIIconButton from 'common/components/IAIIconButton';
-import { v4 as uuidv4 } from 'uuid';
-import { useToggle } from 'react-use';
-import ParamControlNetProcessorSelect from './parameters/ParamControlNetProcessorSelect';
-import ControlNetProcessorComponent from './ControlNetProcessorComponent';
-import IAISwitch from 'common/components/IAISwitch';
 import { ChevronUpIcon } from '@chakra-ui/icons';
+import IAIIconButton from 'common/components/IAIIconButton';
+import IAISwitch from 'common/components/IAISwitch';
+import { useToggle } from 'react-use';
+import { v4 as uuidv4 } from 'uuid';
+import ControlNetImagePreview from './ControlNetImagePreview';
+import ControlNetProcessorComponent from './ControlNetProcessorComponent';
 import ParamControlNetShouldAutoConfig from './ParamControlNetShouldAutoConfig';
+import ParamControlNetBeginEnd from './parameters/ParamControlNetBeginEnd';
+import ParamControlNetControlMode from './parameters/ParamControlNetControlMode';
+import ParamControlNetProcessorSelect from './parameters/ParamControlNetProcessorSelect';
 
 const expandedControlImageSx: ChakraProps['sx'] = { maxH: 96 };
 
@@ -36,6 +37,7 @@ const ControlNet = (props: ControlNetProps) => {
     weight,
     beginStepPct,
     endStepPct,
+    controlMode,
     controlImage,
     processedControlImage,
     processorNode,
@@ -137,45 +139,51 @@ const ControlNet = (props: ControlNetProps) => {
       </Flex>
       {isEnabled && (
         <>
-          <Flex sx={{ gap: 4, w: 'full' }}>
-            <Flex
-              sx={{
-                flexDir: 'column',
-                gap: 2,
-                w: 'full',
-                h: isExpanded ? 28 : 24,
-                paddingInlineStart: 1,
-                paddingInlineEnd: isExpanded ? 1 : 0,
-                pb: 2,
-                justifyContent: 'space-between',
-              }}
-            >
-              <ParamControlNetWeight
-                controlNetId={controlNetId}
-                weight={weight}
-                mini={!isExpanded}
-              />
-              <ParamControlNetBeginEnd
-                controlNetId={controlNetId}
-                beginStepPct={beginStepPct}
-                endStepPct={endStepPct}
-                mini={!isExpanded}
-              />
-            </Flex>
-            {!isExpanded && (
+          <Flex sx={{ w: 'full', flexDirection: 'column' }}>
+            <Flex sx={{ gap: 4, w: 'full' }}>
               <Flex
                 sx={{
-                  alignItems: 'center',
-                  justifyContent: 'center',
-                  h: 24,
-                  w: 24,
-                  aspectRatio: '1/1',
+                  flexDir: 'column',
+                  gap: 3,
+                  w: 'full',
+                  paddingInlineStart: 1,
+                  paddingInlineEnd: isExpanded ? 1 : 0,
+                  pb: 2,
+                  justifyContent: 'space-between',
                 }}
               >
-                <ControlNetImagePreview controlNet={props.controlNet} />
+                <ParamControlNetWeight
+                  controlNetId={controlNetId}
+                  weight={weight}
+                  mini={!isExpanded}
+                />
+                <ParamControlNetBeginEnd
+                  controlNetId={controlNetId}
+                  beginStepPct={beginStepPct}
+                  endStepPct={endStepPct}
+                  mini={!isExpanded}
+                />
               </Flex>
-            )}
+              {!isExpanded && (
+                <Flex
+                  sx={{
+                    alignItems: 'center',
+                    justifyContent: 'center',
+                    h: 24,
+                    w: 24,
+                    aspectRatio: '1/1',
+                  }}
+                >
+                  <ControlNetImagePreview controlNet={props.controlNet} />
+                </Flex>
+              )}
+            </Flex>
+            <ParamControlNetControlMode
+              controlNetId={controlNetId}
+              controlMode={controlMode}
+            />
           </Flex>
+
           {isExpanded && (
             <>
               <Box mt={2}>

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetControlMode.tsx

@@ -0,0 +1,45 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
+import {
+  ControlModes,
+  controlNetControlModeChanged,
+} from 'features/controlNet/store/controlNetSlice';
+import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+
+type ParamControlNetControlModeProps = {
+  controlNetId: string;
+  controlMode: string;
+};
+
+const CONTROL_MODE_DATA = [
+  { label: 'Balanced', value: 'balanced' },
+  { label: 'Prompt', value: 'more_prompt' },
+  { label: 'Control', value: 'more_control' },
+  { label: 'Mega Control', value: 'unbalanced' },
+];
+
+export default function ParamControlNetControlMode(
+  props: ParamControlNetControlModeProps
+) {
+  const { controlNetId, controlMode = false } = props;
+  const dispatch = useAppDispatch();
+
+  const { t } = useTranslation();
+
+  const handleControlModeChange = useCallback(
+    (controlMode: ControlModes) => {
+      dispatch(controlNetControlModeChanged({ controlNetId, controlMode }));
+    },
+    [controlNetId, dispatch]
+  );
+
+  return (
+    <IAIMantineSelect
+      label={t('parameters.controlNetControlMode')}
+      data={CONTROL_MODE_DATA}
+      value={String(controlMode)}
+      onChange={handleControlModeChange}
+    />
+  );
+}

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetModel.tsx

@@ -1,9 +1,8 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAICustomSelect, {
-  IAICustomSelectOption,
-} from 'common/components/IAICustomSelect';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect, {
+  IAISelectDataType,
+} from 'common/components/IAIMantineSelect';
 import { useIsReadyToInvoke } from 'common/hooks/useIsReadyToInvoke';
 import {
   CONTROLNET_MODELS,
@@ -12,7 +11,7 @@ import {
 import { controlNetModelChanged } from 'features/controlNet/store/controlNetSlice';
 import { configSelector } from 'features/system/store/configSelectors';
 import { map } from 'lodash-es';
-import { ChangeEvent, memo, useCallback } from 'react';
+import { memo, useCallback } from 'react';
 
 type ParamControlNetModelProps = {
   controlNetId: string;
@@ -20,17 +19,18 @@ type ParamControlNetModelProps = {
 };
 
 const selector = createSelector(configSelector, (config) => {
-  return map(CONTROLNET_MODELS, (m) => ({
-    key: m.label,
+  const controlNetModels: IAISelectDataType[] = map(CONTROLNET_MODELS, (m) => ({
+    label: m.label,
     value: m.type,
-  })).filter((d) => !config.sd.disabledControlNetModels.includes(d.value));
-});
+  })).filter(
+    (d) =>
+      !config.sd.disabledControlNetModels.includes(
+        d.value as ControlNetModelName
+      )
+  );
 
-// const DATA: IAICustomSelectOption[] = map(CONTROLNET_MODELS, (m) => ({
-//   value: m.type,
-//   label: m.label,
-//   tooltip: m.type,
-// }));
+  return controlNetModels;
+});
 
 const ParamControlNetModel = (props: ParamControlNetModelProps) => {
   const { controlNetId, model } = props;
@@ -39,47 +39,23 @@ const ParamControlNetModel = (props: ParamControlNetModelProps) => {
   const isReady = useIsReadyToInvoke();
 
   const handleModelChanged = useCallback(
-    (e: ChangeEvent<HTMLSelectElement>) => {
+    (val: string | null) => {
       // TODO: do not cast
-      const model = e.target.value as ControlNetModelName;
+      const model = val as ControlNetModelName;
       dispatch(controlNetModelChanged({ controlNetId, model }));
     },
     [controlNetId, dispatch]
   );
 
-  // const handleModelChanged = useCallback(
-  //   (val: string | null | undefined) => {
-  //     // TODO: do not cast
-  //     const model = val as ControlNetModelName;
-  //     dispatch(controlNetModelChanged({ controlNetId, model }));
-  //   },
-  //   [controlNetId, dispatch]
-  // );
-
   return (
-    <IAISelect
-      tooltip={model}
-      tooltipProps={{ placement: 'top', hasArrow: true }}
-      validValues={controlNetModels}
+    <IAIMantineSelect
+      data={controlNetModels}
       value={model}
       onChange={handleModelChanged}
-      isDisabled={!isReady}
-      // ellipsisPosition="start"
-      // withCheckIcon
+      disabled={!isReady}
+      tooltip={model}
     />
   );
-  // return (
-  //   <IAICustomSelect
-  //     tooltip={model}
-  //     tooltipProps={{ placement: 'top', hasArrow: true }}
-  //     data={DATA}
-  //     value={model}
-  //     onChange={handleModelChanged}
-  //     isDisabled={!isReady}
-  //     ellipsisPosition="start"
-  //     withCheckIcon
-  //   />
-  // );
 };
 
 export default memo(ParamControlNetModel);

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetProcessorSelect.tsx

@@ -1,64 +1,55 @@
-import IAICustomSelect, {
-  IAICustomSelectOption,
-} from 'common/components/IAICustomSelect';
-import { ChangeEvent, memo, useCallback } from 'react';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+
+import IAIMantineSelect, {
+  IAISelectDataType,
+} from 'common/components/IAIMantineSelect';
+import { map } from 'lodash-es';
+import { memo, useCallback } from 'react';
+import { CONTROLNET_PROCESSORS } from '../../store/constants';
+import { controlNetProcessorTypeChanged } from '../../store/controlNetSlice';
 import {
   ControlNetProcessorNode,
   ControlNetProcessorType,
 } from '../../store/types';
-import { controlNetProcessorTypeChanged } from '../../store/controlNetSlice';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { CONTROLNET_PROCESSORS } from '../../store/constants';
-import { map } from 'lodash-es';
 import { useIsReadyToInvoke } from 'common/hooks/useIsReadyToInvoke';
-import IAISelect from 'common/components/IAISelect';
 import { createSelector } from '@reduxjs/toolkit';
 import { configSelector } from 'features/system/store/configSelectors';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 
 type ParamControlNetProcessorSelectProps = {
   controlNetId: string;
   processorNode: ControlNetProcessorNode;
 };
 
-const CONTROLNET_PROCESSOR_TYPES = map(CONTROLNET_PROCESSORS, (p) => ({
-  value: p.type,
-  key: p.label,
-})).sort((a, b) =>
-  // sort 'none' to the top
-  a.value === 'none' ? -1 : b.value === 'none' ? 1 : a.key.localeCompare(b.key)
-);
-
-const selector = createSelector(configSelector, (config) => {
-  return map(CONTROLNET_PROCESSORS, (p) => ({
-    value: p.type,
-    key: p.label,
-  }))
-    .sort((a, b) =>
-      // sort 'none' to the top
-      a.value === 'none'
-        ? -1
-        : b.value === 'none'
-        ? 1
-        : a.key.localeCompare(b.key)
+const selector = createSelector(
+  configSelector,
+  (config) => {
+    const controlNetProcessors: IAISelectDataType[] = map(
+      CONTROLNET_PROCESSORS,
+      (p) => ({
+        value: p.type,
+        label: p.label,
+      })
     )
-    .filter((d) => !config.sd.disabledControlNetProcessors.includes(d.value));
-});
+      .sort((a, b) =>
+        // sort 'none' to the top
+        a.value === 'none'
+          ? -1
+          : b.value === 'none'
+          ? 1
+          : a.label.localeCompare(b.label)
+      )
+      .filter(
+        (d) =>
+          !config.sd.disabledControlNetProcessors.includes(
+            d.value as ControlNetProcessorType
+          )
+      );
 
-// const CONTROLNET_PROCESSOR_TYPES: IAICustomSelectOption[] = map(
-//   CONTROLNET_PROCESSORS,
-//   (p) => ({
-//     value: p.type,
-//     label: p.label,
-//     tooltip: p.description,
-//   })
-// ).sort((a, b) =>
-//   // sort 'none' to the top
-//   a.value === 'none'
-//     ? -1
-//     : b.value === 'none'
-//     ? 1
-//     : a.label.localeCompare(b.label)
-// );
+    return controlNetProcessors;
+  },
+  defaultSelectorOptions
+);
 
 const ParamControlNetProcessorSelect = (
   props: ParamControlNetProcessorSelectProps
@@ -69,47 +60,26 @@ const ParamControlNetProcessorSelect = (
   const controlNetProcessors = useAppSelector(selector);
 
   const handleProcessorTypeChanged = useCallback(
-    (e: ChangeEvent<HTMLSelectElement>) => {
+    (v: string | null) => {
       dispatch(
         controlNetProcessorTypeChanged({
           controlNetId,
-          processorType: e.target.value as ControlNetProcessorType,
+          processorType: v as ControlNetProcessorType,
         })
       );
     },
     [controlNetId, dispatch]
   );
-  // const handleProcessorTypeChanged = useCallback(
-  //   (v: string | null | undefined) => {
-  //     dispatch(
-  //       controlNetProcessorTypeChanged({
-  //         controlNetId,
-  //         processorType: v as ControlNetProcessorType,
-  //       })
-  //     );
-  //   },
-  //   [controlNetId, dispatch]
-  // );
 
   return (
-    <IAISelect
+    <IAIMantineSelect
       label="Processor"
       value={processorNode.type ?? 'canny_image_processor'}
-      validValues={controlNetProcessors}
+      data={controlNetProcessors}
       onChange={handleProcessorTypeChanged}
-      isDisabled={!isReady}
+      disabled={!isReady}
     />
   );
-  // return (
-  //   <IAICustomSelect
-  //     label="Processor"
-  //     value={processorNode.type ?? 'canny_image_processor'}
-  //     data={CONTROLNET_PROCESSOR_TYPES}
-  //     onChange={handleProcessorTypeChanged}
-  //     withCheckIcon
-  //     isDisabled={!isReady}
-  //   />
-  // );
 };
 
 export default memo(ParamControlNetProcessorSelect);

invokeai/frontend/web/src/features/controlNet/store/constants.ts

@@ -1,6 +1,5 @@
 import {
   ControlNetProcessorType,
-  RequiredCannyImageProcessorInvocation,
   RequiredControlNetProcessorNode,
 } from './types';
 
@@ -23,7 +22,7 @@ type ControlNetProcessorsDict = Record<
  *
  * TODO: Generate from the OpenAPI schema
  */
-export const CONTROLNET_PROCESSORS = {
+export const CONTROLNET_PROCESSORS: ControlNetProcessorsDict = {
   none: {
     type: 'none',
     label: 'none',
@@ -174,6 +173,8 @@ export const CONTROLNET_PROCESSORS = {
   },
 };
 
+type ControlNetModelsDict = Record<string, ControlNetModel>;
+
 type ControlNetModel = {
   type: string;
   label: string;
@@ -181,7 +182,7 @@ type ControlNetModel = {
   defaultProcessor?: ControlNetProcessorType;
 };
 
-export const CONTROLNET_MODELS = {
+export const CONTROLNET_MODELS: ControlNetModelsDict = {
   'lllyasviel/control_v11p_sd15_canny': {
     type: 'lllyasviel/control_v11p_sd15_canny',
     label: 'Canny',
@@ -190,6 +191,7 @@ export const CONTROLNET_MODELS = {
   'lllyasviel/control_v11p_sd15_inpaint': {
     type: 'lllyasviel/control_v11p_sd15_inpaint',
     label: 'Inpaint',
+    defaultProcessor: 'none',
   },
   'lllyasviel/control_v11p_sd15_mlsd': {
     type: 'lllyasviel/control_v11p_sd15_mlsd',
@@ -209,6 +211,7 @@ export const CONTROLNET_MODELS = {
   'lllyasviel/control_v11p_sd15_seg': {
     type: 'lllyasviel/control_v11p_sd15_seg',
     label: 'Segmentation',
+    defaultProcessor: 'none',
   },
   'lllyasviel/control_v11p_sd15_lineart': {
     type: 'lllyasviel/control_v11p_sd15_lineart',
@@ -223,6 +226,7 @@ export const CONTROLNET_MODELS = {
   'lllyasviel/control_v11p_sd15_scribble': {
     type: 'lllyasviel/control_v11p_sd15_scribble',
     label: 'Scribble',
+    defaultProcessor: 'none',
   },
   'lllyasviel/control_v11p_sd15_softedge': {
     type: 'lllyasviel/control_v11p_sd15_softedge',
@@ -242,10 +246,12 @@ export const CONTROLNET_MODELS = {
   'lllyasviel/control_v11f1e_sd15_tile': {
     type: 'lllyasviel/control_v11f1e_sd15_tile',
     label: 'Tile (experimental)',
+    defaultProcessor: 'none',
   },
   'lllyasviel/control_v11e_sd15_ip2p': {
     type: 'lllyasviel/control_v11e_sd15_ip2p',
     label: 'Pix2Pix (experimental)',
+    defaultProcessor: 'none',
   },
   'CrucibleAI/ControlNetMediaPipeFace': {
     type: 'CrucibleAI/ControlNetMediaPipeFace',

invokeai/frontend/web/src/features/controlNet/store/controlNetSlice.ts

@@ -1,36 +1,27 @@
-import { PayloadAction } from '@reduxjs/toolkit';
-import { createSlice } from '@reduxjs/toolkit';
+import { PayloadAction, createSlice } from '@reduxjs/toolkit';
 import { RootState } from 'app/store/store';
+import { forEach } from 'lodash-es';
 import { ImageDTO } from 'services/api';
-import {
-  ControlNetProcessorType,
-  RequiredCannyImageProcessorInvocation,
-  RequiredControlNetProcessorNode,
-} from './types';
+import { appSocketInvocationError } from 'services/events/actions';
+import { imageDeleted, imageUrlsReceived } from 'services/thunks/image';
+import { isAnySessionRejected } from 'services/thunks/session';
+import { controlNetImageProcessed } from './actions';
 import {
   CONTROLNET_MODELS,
   CONTROLNET_PROCESSORS,
   ControlNetModelName,
 } from './constants';
-import { controlNetImageProcessed } from './actions';
-import { imageDeleted, imageUrlsReceived } from 'services/thunks/image';
-import { forEach } from 'lodash-es';
-import { isAnySessionRejected } from 'services/thunks/session';
-import { appSocketInvocationError } from 'services/events/actions';
+import {
+  ControlNetProcessorType,
+  RequiredCannyImageProcessorInvocation,
+  RequiredControlNetProcessorNode,
+} from './types';
 
-export const initialControlNet: Omit<ControlNetConfig, 'controlNetId'> = {
-  isEnabled: true,
-  model: CONTROLNET_MODELS['lllyasviel/control_v11p_sd15_canny'].type,
-  weight: 1,
-  beginStepPct: 0,
-  endStepPct: 1,
-  controlImage: null,
-  processedControlImage: null,
-  processorType: 'canny_image_processor',
-  processorNode: CONTROLNET_PROCESSORS.canny_image_processor
-    .default as RequiredCannyImageProcessorInvocation,
-  shouldAutoConfig: true,
-};
+export type ControlModes =
+  | 'balanced'
+  | 'more_prompt'
+  | 'more_control'
+  | 'unbalanced';
 
 export type ControlNetConfig = {
   controlNetId: string;
@@ -39,6 +30,7 @@ export type ControlNetConfig = {
   weight: number;
   beginStepPct: number;
   endStepPct: number;
+  controlMode: ControlModes;
   controlImage: ImageDTO | null;
   processedControlImage: ImageDTO | null;
   processorType: ControlNetProcessorType;
@@ -46,6 +38,21 @@ export type ControlNetConfig = {
   shouldAutoConfig: boolean;
 };
 
+export const initialControlNet: Omit<ControlNetConfig, 'controlNetId'> = {
+  isEnabled: true,
+  model: CONTROLNET_MODELS['lllyasviel/control_v11p_sd15_canny'].type,
+  weight: 1,
+  beginStepPct: 0,
+  endStepPct: 1,
+  controlMode: 'balanced',
+  controlImage: null,
+  processedControlImage: null,
+  processorType: 'canny_image_processor',
+  processorNode: CONTROLNET_PROCESSORS.canny_image_processor
+    .default as RequiredCannyImageProcessorInvocation,
+  shouldAutoConfig: true,
+};
+
 export type ControlNetState = {
   controlNets: Record<string, ControlNetConfig>;
   isEnabled: boolean;
@@ -147,11 +154,13 @@ export const controlNetSlice = createSlice({
       state.controlNets[controlNetId].processedControlImage = null;
 
       if (state.controlNets[controlNetId].shouldAutoConfig) {
-        const processorType = CONTROLNET_MODELS[model].defaultProcessor;
+        const processorType =
+          CONTROLNET_MODELS[model as keyof typeof CONTROLNET_MODELS]
+            .defaultProcessor;
         if (processorType) {
           state.controlNets[controlNetId].processorType = processorType;
           state.controlNets[controlNetId].processorNode = CONTROLNET_PROCESSORS[
-            processorType
+            processorType as keyof typeof CONTROLNET_PROCESSORS
           ].default as RequiredControlNetProcessorNode;
         } else {
           state.controlNets[controlNetId].processorType = 'none';
@@ -181,6 +190,13 @@ export const controlNetSlice = createSlice({
       const { controlNetId, endStepPct } = action.payload;
       state.controlNets[controlNetId].endStepPct = endStepPct;
     },
+    controlNetControlModeChanged: (
+      state,
+      action: PayloadAction<{ controlNetId: string; controlMode: ControlModes }>
+    ) => {
+      const { controlNetId, controlMode } = action.payload;
+      state.controlNets[controlNetId].controlMode = controlMode;
+    },
     controlNetProcessorParamsChanged: (
       state,
       action: PayloadAction<{
@@ -210,7 +226,7 @@ export const controlNetSlice = createSlice({
       state.controlNets[controlNetId].processedControlImage = null;
       state.controlNets[controlNetId].processorType = processorType;
       state.controlNets[controlNetId].processorNode = CONTROLNET_PROCESSORS[
-        processorType
+        processorType as keyof typeof CONTROLNET_PROCESSORS
       ].default as RequiredControlNetProcessorNode;
       state.controlNets[controlNetId].shouldAutoConfig = false;
     },
@@ -227,12 +243,14 @@ export const controlNetSlice = createSlice({
       if (newShouldAutoConfig) {
         // manage the processor for the user
         const processorType =
-          CONTROLNET_MODELS[state.controlNets[controlNetId].model]
-            .defaultProcessor;
+          CONTROLNET_MODELS[
+            state.controlNets[controlNetId]
+              .model as keyof typeof CONTROLNET_MODELS
+          ].defaultProcessor;
         if (processorType) {
           state.controlNets[controlNetId].processorType = processorType;
           state.controlNets[controlNetId].processorNode = CONTROLNET_PROCESSORS[
-            processorType
+            processorType as keyof typeof CONTROLNET_PROCESSORS
           ].default as RequiredControlNetProcessorNode;
         } else {
           state.controlNets[controlNetId].processorType = 'none';
@@ -271,8 +289,7 @@ export const controlNetSlice = createSlice({
     });
 
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_origin, image_url, thumbnail_url } =
-        action.payload;
+      const { image_name, image_url, thumbnail_url } = action.payload;
 
       forEach(state.controlNets, (c) => {
         if (c.controlImage?.image_name === image_name) {
@@ -286,11 +303,11 @@ export const controlNetSlice = createSlice({
       });
     });
 
-    builder.addCase(appSocketInvocationError, (state, action) => {
+    builder.addCase(appSocketInvocationError, (state) => {
       state.pendingControlImages = [];
     });
 
-    builder.addMatcher(isAnySessionRejected, (state, action) => {
+    builder.addMatcher(isAnySessionRejected, (state) => {
       state.pendingControlImages = [];
     });
   },
@@ -308,6 +325,7 @@ export const {
   controlNetWeightChanged,
   controlNetBeginStepPctChanged,
   controlNetEndStepPctChanged,
+  controlNetControlModeChanged,
   controlNetProcessorParamsChanged,
   controlNetProcessorTypeChanged,
   controlNetReset,

invokeai/frontend/web/src/features/gallery/components/ImageMetaDataViewer/ImageMetadataViewer.tsx

@@ -9,15 +9,15 @@ import {
   Tooltip,
 } from '@chakra-ui/react';
 import { useAppDispatch } from 'app/store/storeHooks';
+import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
 import { setShouldShowImageDetails } from 'features/ui/store/uiSlice';
+import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 import { memo } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 import { FaCopy } from 'react-icons/fa';
 import { IoArrowUndoCircleOutline } from 'react-icons/io5';
-import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 import { ImageDTO } from 'services/api';
-import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
 
 type MetadataItemProps = {
   isLink?: boolean;
@@ -324,7 +324,7 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
               borderRadius: 'base',
               bg: 'whiteAlpha.500',
               _dark: { bg: 'blackAlpha.500' },
-              w: 'max-content',
+              w: 'full',
             }}
           >
             <pre>{metadataJSON}</pre>

invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts

@@ -59,8 +59,7 @@ export const gallerySlice = createSlice({
       }
     });
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_origin, image_url, thumbnail_url } =
-        action.payload;
+      const { image_name, image_url, thumbnail_url } = action.payload;
 
       if (state.selectedImage?.image_name === image_name) {
         state.selectedImage.image_url = image_url;

invokeai/frontend/web/src/features/gallery/store/imagesSlice.ts

@@ -86,8 +86,7 @@ const imagesSlice = createSlice({
       imagesAdapter.removeOne(state, imageName);
     });
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_origin, image_url, thumbnail_url } =
-        action.payload;
+      const { image_name, image_url, thumbnail_url } = action.payload;
 
       imagesAdapter.updateOne(state, {
         id: image_name,

invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts

@@ -103,8 +103,7 @@ const nodesSlice = createSlice({
     });
 
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_origin, image_url, thumbnail_url } =
-        action.payload;
+      const { image_name, image_url, thumbnail_url } = action.payload;
 
       state.nodes.forEach((node) => {
         forEach(node.data.inputs, (input) => {

invokeai/frontend/web/src/features/nodes/util/addControlNetToLinearGraph.ts

@@ -45,6 +45,7 @@ export const addControlNetToLinearGraph = (
         processedControlImage,
         beginStepPct,
         endStepPct,
+        controlMode,
         model,
         processorType,
         weight,
@@ -60,23 +61,22 @@ export const addControlNetToLinearGraph = (
         type: 'controlnet',
         begin_step_percent: beginStepPct,
         end_step_percent: endStepPct,
+        control_mode: controlMode,
         control_model: model as ControlNetInvocation['control_model'],
         control_weight: weight,
       };
 
       if (processedControlImage && processorType !== 'none') {
         // We've already processed the image in the app, so we can just use the processed image
-        const { image_name, image_origin } = processedControlImage;
+        const { image_name } = processedControlImage;
         controlNetNode.image = {
           image_name,
-          image_origin,
         };
       } else if (controlImage) {
         // The control image is preprocessed
-        const { image_name, image_origin } = controlImage;
+        const { image_name } = controlImage;
         controlNetNode.image = {
           image_name,
-          image_origin,
         };
       } else {
         // Skip ControlNets without an unprocessed image - should never happen if everything is working correctly

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildImageToImageGraph.ts

@@ -354,7 +354,6 @@ export const buildImageToImageGraph = (state: RootState): Graph => {
       type: 'img_resize',
       image: {
         image_name: initialImage.image_name,
-        image_origin: initialImage.image_origin,
       },
       is_intermediate: true,
       height,
@@ -392,7 +391,6 @@ export const buildImageToImageGraph = (state: RootState): Graph => {
     // We are not resizing, so we need to set the image on the `IMAGE_TO_LATENTS` node explicitly
     set(graph.nodes[IMAGE_TO_LATENTS], 'image', {
       image_name: initialImage.image_name,
-      image_origin: initialImage.image_origin,
     });
 
     // Pass the image's dimensions to the `NOISE` node

invokeai/frontend/web/src/features/nodes/util/nodeBuilders/buildImageToImageNode.ts

@@ -57,8 +57,7 @@ export const buildImg2ImgNode = (
     }
 
     imageToImageNode.image = {
-      image_name: initialImage.name,
-      image_origin: initialImage.type,
+      image_name: initialImage.image_name,
     };
   }
 

invokeai/frontend/web/src/features/parameters/components/Parameters/Canvas/InfillAndScaling/ParamInfillMethod.tsx

@@ -1,12 +1,12 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
 import { setInfillMethod } from 'features/parameters/store/generationSlice';
 import { systemSelector } from 'features/system/store/systemSelectors';
 
-import { ChangeEvent, memo, useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
 const selector = createSelector(
@@ -30,17 +30,17 @@ const ParamInfillMethod = () => {
   const { t } = useTranslation();
 
   const handleChange = useCallback(
-    (e: ChangeEvent<HTMLSelectElement>) => {
-      dispatch(setInfillMethod(e.target.value));
+    (v: string) => {
+      dispatch(setInfillMethod(v));
     },
     [dispatch]
   );
 
   return (
-    <IAISelect
+    <IAIMantineSelect
       label={t('parameters.infillMethod')}
       value={infillMethod}
-      validValues={infillMethods}
+      data={infillMethods}
       onChange={handleChange}
     />
   );

invokeai/frontend/web/src/features/parameters/components/Parameters/Canvas/InfillAndScaling/ParamScaleBeforeProcessing.tsx

@@ -1,15 +1,15 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
 import { canvasSelector } from 'features/canvas/store/canvasSelectors';
 import { setBoundingBoxScaleMethod } from 'features/canvas/store/canvasSlice';
 import {
-  BoundingBoxScale,
   BOUNDING_BOX_SCALES_DICT,
+  BoundingBoxScale,
 } from 'features/canvas/store/canvasTypes';
 
-import { ChangeEvent, memo } from 'react';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 
 const selector = createSelector(
@@ -30,16 +30,14 @@ const ParamScaleBeforeProcessing = () => {
 
   const { t } = useTranslation();
 
-  const handleChangeBoundingBoxScaleMethod = (
-    e: ChangeEvent<HTMLSelectElement>
-  ) => {
-    dispatch(setBoundingBoxScaleMethod(e.target.value as BoundingBoxScale));
+  const handleChangeBoundingBoxScaleMethod = (v: string) => {
+    dispatch(setBoundingBoxScaleMethod(v as BoundingBoxScale));
   };
 
   return (
-    <IAISelect
+    <IAIMantineSelect
       label={t('parameters.scaleBeforeProcessing')}
-      validValues={BOUNDING_BOX_SCALES_DICT}
+      data={BOUNDING_BOX_SCALES_DICT}
       value={boundingBoxScale}
       onChange={handleChangeBoundingBoxScaleMethod}
     />

invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamScheduler.tsx

@@ -2,23 +2,20 @@ import { createSelector } from '@reduxjs/toolkit';
 import { Scheduler } from 'app/constants';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
-import IAICustomSelect from 'common/components/IAICustomSelect';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect, {
+  IAISelectDataType,
+} from 'common/components/IAIMantineSelect';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
 import { setScheduler } from 'features/parameters/store/generationSlice';
 import { uiSelector } from 'features/ui/store/uiSelectors';
-import { ChangeEvent, memo, useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
 const selector = createSelector(
   [uiSelector, generationSelector],
   (ui, generation) => {
-    // TODO: DPMSolverSinglestepScheduler is fixed in https://github.com/huggingface/diffusers/pull/3413
-    // but we need to wait for the next release before removing this special handling.
-    const allSchedulers = ui.schedulers
-      .filter((scheduler) => {
-        return !['dpmpp_2s'].includes(scheduler);
-      })
+    const allSchedulers: string[] = ui.schedulers
+      .slice()
       .sort((a, b) => a.localeCompare(b));
 
     return {
@@ -36,39 +33,23 @@ const ParamScheduler = () => {
   const { t } = useTranslation();
 
   const handleChange = useCallback(
-    (e: ChangeEvent<HTMLSelectElement>) => {
-      dispatch(setScheduler(e.target.value as Scheduler));
+    (v: string | null) => {
+      if (!v) {
+        return;
+      }
+      dispatch(setScheduler(v as Scheduler));
     },
     [dispatch]
   );
-  // const handleChange = useCallback(
-  //   (v: string | null | undefined) => {
-  //     if (!v) {
-  //       return;
-  //     }
-  //     dispatch(setScheduler(v as Scheduler));
-  //   },
-  //   [dispatch]
-  // );
 
   return (
-    <IAISelect
+    <IAIMantineSelect
       label={t('parameters.scheduler')}
       value={scheduler}
-      validValues={allSchedulers}
+      data={allSchedulers}
       onChange={handleChange}
     />
   );
-
-  // return (
-  //   <IAICustomSelect
-  //     label={t('parameters.scheduler')}
-  //     value={scheduler}
-  //     data={allSchedulers}
-  //     onChange={handleChange}
-  //     withCheckIcon
-  //   />
-  // );
 };
 
 export default memo(ParamScheduler);

invokeai/frontend/web/src/features/parameters/components/Parameters/FaceRestore/FaceRestoreType.tsx

@@ -1,12 +1,11 @@
 import { FACETOOL_TYPES } from 'app/constants';
 import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
 import {
   FacetoolType,
   setFacetoolType,
 } from 'features/parameters/store/postprocessingSlice';
-import { ChangeEvent } from 'react';
 import { useTranslation } from 'react-i18next';
 
 export default function FaceRestoreType() {
@@ -17,13 +16,13 @@ export default function FaceRestoreType() {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
 
-  const handleChangeFacetoolType = (e: ChangeEvent<HTMLSelectElement>) =>
-    dispatch(setFacetoolType(e.target.value as FacetoolType));
+  const handleChangeFacetoolType = (v: string) =>
+    dispatch(setFacetoolType(v as FacetoolType));
 
   return (
-    <IAISelect
+    <IAIMantineSelect
       label={t('parameters.type')}
-      validValues={FACETOOL_TYPES.concat()}
+      data={FACETOOL_TYPES.concat()}
       value={facetoolType}
       onChange={handleChangeFacetoolType}
     />

invokeai/frontend/web/src/features/parameters/components/Parameters/Upscale/UpscaleScale.tsx

@@ -1,12 +1,11 @@
 import { UPSCALING_LEVELS } from 'app/constants';
 import type { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
 import {
-  setUpscalingLevel,
   UpscalingLevel,
+  setUpscalingLevel,
 } from 'features/parameters/store/postprocessingSlice';
-import type { ChangeEvent } from 'react';
 import { useTranslation } from 'react-i18next';
 
 export default function UpscaleScale() {
@@ -21,16 +20,16 @@ export default function UpscaleScale() {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
 
-  const handleChangeLevel = (e: ChangeEvent<HTMLSelectElement>) =>
-    dispatch(setUpscalingLevel(Number(e.target.value) as UpscalingLevel));
+  const handleChangeLevel = (v: string) =>
+    dispatch(setUpscalingLevel(Number(v) as UpscalingLevel));
 
   return (
-    <IAISelect
-      isDisabled={!isESRGANAvailable}
+    <IAIMantineSelect
+      disabled={!isESRGANAvailable}
       label={t('parameters.scale')}
-      value={upscalingLevel}
+      value={String(upscalingLevel)}
       onChange={handleChangeLevel}
-      validValues={UPSCALING_LEVELS}
+      data={UPSCALING_LEVELS}
     />
   );
 }

invokeai/frontend/web/src/features/parameters/store/actions.ts

@@ -1,11 +1,5 @@
 import { createAction } from '@reduxjs/toolkit';
-import { isObject } from 'lodash-es';
-import { ImageDTO, ResourceOrigin } from 'services/api';
-
-export type ImageNameAndOrigin = {
-  image_name: string;
-  image_origin: ResourceOrigin;
-};
+import { ImageDTO } from 'services/api';
 
 export const initialImageSelected = createAction<ImageDTO | string | undefined>(
   'generation/initialImageSelected'

invokeai/frontend/web/src/features/parameters/store/generationSlice.ts

@@ -234,8 +234,7 @@ export const generationSlice = createSlice({
     });
 
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_origin, image_url, thumbnail_url } =
-        action.payload;
+      const { image_name, image_url, thumbnail_url } = action.payload;
 
       if (state.initialImage?.image_name === image_name) {
         state.initialImage.image_url = image_url;

invokeai/frontend/web/src/features/system/components/ModelSelect.tsx

@@ -1,17 +1,16 @@
 import { createSelector } from '@reduxjs/toolkit';
-import { ChangeEvent, memo, useCallback } from 'react';
 import { isEqual } from 'lodash-es';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { selectModelsAll, selectModelsById } from '../store/modelSlice';
 import { RootState } from 'app/store/store';
-import { modelSelected } from 'features/parameters/store/generationSlice';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import IAIMantineSelect, {
+  IAISelectDataType,
+} from 'common/components/IAIMantineSelect';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
-import IAICustomSelect, {
-  IAICustomSelectOption,
-} from 'common/components/IAICustomSelect';
-import IAISelect from 'common/components/IAISelect';
+import { modelSelected } from 'features/parameters/store/generationSlice';
+import { selectModelsAll, selectModelsById } from '../store/modelSlice';
 
 const selector = createSelector(
   [(state: RootState) => state, generationSelector],
@@ -19,18 +18,11 @@ const selector = createSelector(
     const selectedModel = selectModelsById(state, generation.model);
 
     const modelData = selectModelsAll(state)
-      .map((m) => ({
+      .map<IAISelectDataType>((m) => ({
         value: m.name,
-        key: m.name,
+        label: m.name,
       }))
-      .sort((a, b) => a.key.localeCompare(b.key));
-    // const modelData = selectModelsAll(state)
-    //   .map<IAICustomSelectOption>((m) => ({
-    //     value: m.name,
-    //     label: m.name,
-    //     tooltip: m.description,
-    //   }))
-    //   .sort((a, b) => a.label.localeCompare(b.label));
+      .sort((a, b) => a.label.localeCompare(b.label));
     return {
       selectedModel,
       modelData,
@@ -48,43 +40,25 @@ const ModelSelect = () => {
   const { t } = useTranslation();
   const { selectedModel, modelData } = useAppSelector(selector);
   const handleChangeModel = useCallback(
-    (e: ChangeEvent<HTMLSelectElement>) => {
-      dispatch(modelSelected(e.target.value));
+    (v: string | null) => {
+      if (!v) {
+        return;
+      }
+      dispatch(modelSelected(v));
     },
     [dispatch]
   );
-  // const handleChangeModel = useCallback(
-  //   (v: string | null | undefined) => {
-  //     if (!v) {
-  //       return;
-  //     }
-  //     dispatch(modelSelected(v));
-  //   },
-  //   [dispatch]
-  // );
 
   return (
-    <IAISelect
-      label={t('modelManager.model')}
+    <IAIMantineSelect
       tooltip={selectedModel?.description}
-      validValues={modelData}
+      label={t('modelManager.model')}
       value={selectedModel?.name ?? ''}
+      placeholder="Pick one"
+      data={modelData}
       onChange={handleChangeModel}
-      tooltipProps={{ placement: 'top', hasArrow: true }}
     />
   );
-
-  // return (
-  //   <IAICustomSelect
-  //     label={t('modelManager.model')}
-  //     tooltip={selectedModel?.description}
-  //     data={modelData}
-  //     value={selectedModel?.name ?? ''}
-  //     onChange={handleChangeModel}
-  //     withCheckIcon={true}
-  //     tooltipProps={{ placement: 'top', hasArrow: true }}
-  //   />
-  // );
 };
 
 export default memo(ModelSelect);

invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsModal.tsx

@@ -13,19 +13,21 @@ import {
   useDisclosure,
 } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
+import { VALID_LOG_LEVELS } from 'app/logging/useLogger';
+import { LOCALSTORAGE_KEYS, LOCALSTORAGE_PREFIX } from 'app/store/constants';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
 import IAISwitch from 'common/components/IAISwitch';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import {
+  SystemState,
   consoleLogLevelChanged,
   setEnableImageDebugging,
   setShouldConfirmOnDelete,
   setShouldDisplayGuides,
   shouldAntialiasProgressImageChanged,
   shouldLogToConsoleChanged,
-  SystemState,
 } from 'features/system/store/systemSlice';
 import { uiSelector } from 'features/ui/store/uiSelectors';
 import {
@@ -37,15 +39,13 @@ import { UIState } from 'features/ui/store/uiTypes';
 import { isEqual } from 'lodash-es';
 import {
   ChangeEvent,
-  cloneElement,
   ReactElement,
+  cloneElement,
   useCallback,
   useEffect,
 } from 'react';
 import { useTranslation } from 'react-i18next';
-import { VALID_LOG_LEVELS } from 'app/logging/useLogger';
 import { LogLevelName } from 'roarr';
-import { LOCALSTORAGE_KEYS, LOCALSTORAGE_PREFIX } from 'app/store/constants';
 import SettingsSchedulers from './SettingsSchedulers';
 
 const selector = createSelector(
@@ -157,8 +157,8 @@ const SettingsModal = ({ children, config }: SettingsModalProps) => {
   }, [onSettingsModalClose, onRefreshModalOpen]);
 
   const handleLogLevelChanged = useCallback(
-    (e: ChangeEvent<HTMLSelectElement>) => {
-      dispatch(consoleLogLevelChanged(e.target.value as LogLevelName));
+    (v: string) => {
+      dispatch(consoleLogLevelChanged(v as LogLevelName));
     },
     [dispatch]
   );
@@ -255,14 +255,12 @@ const SettingsModal = ({ children, config }: SettingsModalProps) => {
                     isChecked={shouldLogToConsole}
                     onChange={handleLogToConsoleChanged}
                   />
-                  <IAISelect
-                    horizontal
-                    spaceEvenly
-                    isDisabled={!shouldLogToConsole}
+                  <IAIMantineSelect
+                    disabled={!shouldLogToConsole}
                     label={t('settings.consoleLogLevel')}
                     onChange={handleLogLevelChanged}
                     value={consoleLogLevel}
-                    validValues={VALID_LOG_LEVELS.concat()}
+                    data={VALID_LOG_LEVELS.concat()}
                   />
                   <IAISwitch
                     label={t('settings.enableImageDebugging')}

invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsSchedulers.tsx

@@ -1,5 +1,4 @@
 import {
-  Box,
   Menu,
   MenuButton,
   MenuItemOption,
@@ -13,7 +12,6 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
 import { setSchedulers } from 'features/ui/store/uiSlice';
 import { isArray } from 'lodash-es';
-import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 import { useTranslation } from 'react-i18next';
 
 export default function SettingsSchedulers() {

invokeai/frontend/web/src/features/ui/components/ParametersDrawer.tsx

@@ -1,21 +1,21 @@
+import { Flex } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
-import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { memo, useMemo } from 'react';
-import { Box, Flex } from '@chakra-ui/react';
+import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
 import InvokeAILogoComponent from 'features/system/components/InvokeAILogoComponent';
-import OverlayScrollable from './common/OverlayScrollable';
-import { PARAMETERS_PANEL_WIDTH } from 'theme/util/constants';
 import {
   activeTabNameSelector,
   uiSelector,
 } from 'features/ui/store/uiSelectors';
 import { setShouldShowParametersPanel } from 'features/ui/store/uiSlice';
-import ResizableDrawer from './common/ResizableDrawer/ResizableDrawer';
+import { memo, useMemo } from 'react';
+import { PARAMETERS_PANEL_WIDTH } from 'theme/util/constants';
 import PinParametersPanelButton from './PinParametersPanelButton';
-import TextToImageTabParameters from './tabs/TextToImage/TextToImageTabParameters';
+import OverlayScrollable from './common/OverlayScrollable';
+import ResizableDrawer from './common/ResizableDrawer/ResizableDrawer';
 import ImageToImageTabParameters from './tabs/ImageToImage/ImageToImageTabParameters';
-import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
+import TextToImageTabParameters from './tabs/TextToImage/TextToImageTabParameters';
 import UnifiedCanvasParameters from './tabs/UnifiedCanvas/UnifiedCanvasParameters';
 
 const selector = createSelector(

invokeai/frontend/web/src/features/ui/components/ParametersPinnedWrapper.tsx

@@ -1,11 +1,11 @@
 import { Box, Flex } from '@chakra-ui/react';
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
 import { PropsWithChildren, memo } from 'react';
 import { PARAMETERS_PANEL_WIDTH } from 'theme/util/constants';
-import OverlayScrollable from './common/OverlayScrollable';
-import PinParametersPanelButton from './PinParametersPanelButton';
-import { createSelector } from '@reduxjs/toolkit';
 import { uiSelector } from '../store/uiSelectors';
-import { useAppSelector } from 'app/store/storeHooks';
+import PinParametersPanelButton from './PinParametersPanelButton';
+import OverlayScrollable from './common/OverlayScrollable';
 
 const selector = createSelector(uiSelector, (ui) => {
   const { shouldPinParametersPanel, shouldShowParametersPanel } = ui;
@@ -35,19 +35,27 @@ const ParametersPinnedWrapper = (props: ParametersPinnedWrapperProps) => {
         flexShrink: 0,
       }}
     >
-      <OverlayScrollable>
-        <Flex
-          sx={{
-            gap: 2,
-            flexDirection: 'column',
-            h: 'full',
-            w: 'full',
-            position: 'absolute',
-          }}
-        >
-          {props.children}
-        </Flex>
-      </OverlayScrollable>
+      <Flex
+        sx={{
+          gap: 2,
+          flexDirection: 'column',
+          h: 'full',
+          w: 'full',
+          position: 'absolute',
+        }}
+      >
+        <OverlayScrollable>
+          <Flex
+            sx={{
+              flexDirection: 'column',
+              gap: 2,
+            }}
+          >
+            {props.children}
+          </Flex>
+        </OverlayScrollable>
+      </Flex>
+
       <PinParametersPanelButton
         sx={{ position: 'absolute', top: 0, insetInlineEnd: 0 }}
       />

invokeai/frontend/web/src/features/ui/components/common/OverlayScrollable.tsx

@@ -1,6 +1,5 @@
 import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 import { PropsWithChildren, memo } from 'react';
-
 const OverlayScrollable = (props: PropsWithChildren) => {
   return (
     <OverlayScrollbarsComponent
@@ -20,5 +19,4 @@ const OverlayScrollable = (props: PropsWithChildren) => {
     </OverlayScrollbarsComponent>
   );
 };
-
 export default memo(OverlayScrollable);

invokeai/frontend/web/src/features/ui/components/tabs/ImageToImage/ImageToImageTab.tsx

@@ -1,14 +1,17 @@
 import { Box, Flex } from '@chakra-ui/react';
-import { memo, useCallback, useRef } from 'react';
-import { Panel, PanelGroup } from 'react-resizable-panels';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale';
-import ResizeHandle from '../ResizeHandle';
-import ImageToImageTabParameters from './ImageToImageTabParameters';
-import TextToImageTabMain from '../TextToImage/TextToImageTabMain';
-import { ImperativePanelGroupHandle } from 'react-resizable-panels';
-import ParametersPinnedWrapper from '../../ParametersPinnedWrapper';
 import InitialImageDisplay from 'features/parameters/components/Parameters/ImageToImage/InitialImageDisplay';
+import { memo, useCallback, useRef } from 'react';
+import {
+  ImperativePanelGroupHandle,
+  Panel,
+  PanelGroup,
+} from 'react-resizable-panels';
+import ParametersPinnedWrapper from '../../ParametersPinnedWrapper';
+import ResizeHandle from '../ResizeHandle';
+import TextToImageTabMain from '../TextToImage/TextToImageTabMain';
+import ImageToImageTabParameters from './ImageToImageTabParameters';
 
 const ImageToImageTab = () => {
   const dispatch = useAppDispatch();

invokeai/frontend/web/src/features/ui/components/tabs/TextToImage/TextToImageTab.tsx

@@ -1,8 +1,8 @@
 import { Flex } from '@chakra-ui/react';
 import { memo } from 'react';
+import ParametersPinnedWrapper from '../../ParametersPinnedWrapper';
 import TextToImageTabMain from './TextToImageTabMain';
 import TextToImageTabParameters from './TextToImageTabParameters';
-import ParametersPinnedWrapper from '../../ParametersPinnedWrapper';
 
 const TextToImageTab = () => {
   return (

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolbar/UnifiedCanvasLayerSelect.tsx

@@ -1,6 +1,6 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAISelect from 'common/components/IAISelect';
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
 import {
   canvasSelector,
   isStagingSelector,
@@ -12,7 +12,6 @@ import {
 } from 'features/canvas/store/canvasTypes';
 import { isEqual } from 'lodash-es';
 
-import { ChangeEvent } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 
@@ -51,22 +50,22 @@ export default function UnifiedCanvasLayerSelect() {
     [layer]
   );
 
-  const handleChangeLayer = (e: ChangeEvent<HTMLSelectElement>) => {
-    const newLayer = e.target.value as CanvasLayer;
+  const handleChangeLayer = (v: string) => {
+    const newLayer = v as CanvasLayer;
     dispatch(setLayer(newLayer));
     if (newLayer === 'mask' && !isMaskEnabled) {
       dispatch(setIsMaskEnabled(true));
     }
   };
   return (
-    <IAISelect
+    <IAIMantineSelect
       tooltip={`${t('unifiedCanvas.layer')} (Q)`}
       aria-label={`${t('unifiedCanvas.layer')} (Q)`}
-      tooltipProps={{ hasArrow: true, placement: 'top' }}
       value={layer}
-      validValues={LAYER_NAMES_DICT}
+      data={LAYER_NAMES_DICT}
       onChange={handleChangeLayer}
-      isDisabled={isStaging}
+      disabled={isStaging}
+      w="full"
     />
   );
 }

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolbarBeta.tsx

@@ -2,6 +2,7 @@ import { Flex } from '@chakra-ui/react';
 
 import IAICanvasRedoButton from 'features/canvas/components/IAICanvasToolbar/IAICanvasRedoButton';
 import IAICanvasUndoButton from 'features/canvas/components/IAICanvasToolbar/IAICanvasUndoButton';
+import UnifiedCanvasSettings from './UnifiedCanvasToolSettings/UnifiedCanvasSettings';
 import UnifiedCanvasCopyToClipboard from './UnifiedCanvasToolbar/UnifiedCanvasCopyToClipboard';
 import UnifiedCanvasDownloadImage from './UnifiedCanvasToolbar/UnifiedCanvasDownloadImage';
 import UnifiedCanvasFileUploader from './UnifiedCanvasToolbar/UnifiedCanvasFileUploader';
@@ -13,11 +14,10 @@ import UnifiedCanvasResetCanvas from './UnifiedCanvasToolbar/UnifiedCanvasResetC
 import UnifiedCanvasResetView from './UnifiedCanvasToolbar/UnifiedCanvasResetView';
 import UnifiedCanvasSaveToGallery from './UnifiedCanvasToolbar/UnifiedCanvasSaveToGallery';
 import UnifiedCanvasToolSelect from './UnifiedCanvasToolbar/UnifiedCanvasToolSelect';
-import UnifiedCanvasSettings from './UnifiedCanvasToolSettings/UnifiedCanvasSettings';
 
 const UnifiedCanvasToolbarBeta = () => {
   return (
-    <Flex flexDirection="column" rowGap={2}>
+    <Flex flexDirection="column" rowGap={2} width="min-content">
       <UnifiedCanvasLayerSelect />
       <UnifiedCanvasToolSelect />
 

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasTab.tsx

@@ -1,8 +1,8 @@
 import { Flex } from '@chakra-ui/react';
 import { memo } from 'react';
+import ParametersPinnedWrapper from '../../ParametersPinnedWrapper';
 import UnifiedCanvasContent from './UnifiedCanvasContent';
 import UnifiedCanvasParameters from './UnifiedCanvasParameters';
-import ParametersPinnedWrapper from '../../ParametersPinnedWrapper';
 
 const UnifiedCanvasTab = () => {
   return (

invokeai/frontend/web/src/mantine-theme/theme.ts

@@ -0,0 +1,23 @@
+import { MantineThemeOverride } from '@mantine/core';
+
+export const mantineTheme: MantineThemeOverride = {
+  colorScheme: 'dark',
+  fontFamily: `'InterVariable', sans-serif`,
+  components: {
+    ScrollArea: {
+      defaultProps: {
+        scrollbarSize: 10,
+      },
+      styles: {
+        scrollbar: {
+          '&:hover': {
+            backgroundColor: 'var(--invokeai-colors-baseAlpha-300)',
+          },
+        },
+        thumb: {
+          backgroundColor: 'var(--invokeai-colors-baseAlpha-300)',
+        },
+      },
+    },
+  },
+};

invokeai/frontend/web/src/services/api/index.ts

@@ -24,9 +24,11 @@ export type { CreateModelRequest } from './models/CreateModelRequest';
 export type { CvInpaintInvocation } from './models/CvInpaintInvocation';
 export type { DiffusersModelInfo } from './models/DiffusersModelInfo';
 export type { DivideInvocation } from './models/DivideInvocation';
+export type { DynamicPromptInvocation } from './models/DynamicPromptInvocation';
 export type { Edge } from './models/Edge';
 export type { EdgeConnection } from './models/EdgeConnection';
 export type { FloatCollectionOutput } from './models/FloatCollectionOutput';
+export type { FloatLinearRangeInvocation } from './models/FloatLinearRangeInvocation';
 export type { FloatOutput } from './models/FloatOutput';
 export type { Graph } from './models/Graph';
 export type { GraphExecutionState } from './models/GraphExecutionState';
@@ -85,6 +87,7 @@ export type { PaginatedResults_GraphExecutionState_ } from './models/PaginatedRe
 export type { ParamFloatInvocation } from './models/ParamFloatInvocation';
 export type { ParamIntInvocation } from './models/ParamIntInvocation';
 export type { PidiImageProcessorInvocation } from './models/PidiImageProcessorInvocation';
+export type { PromptCollectionOutput } from './models/PromptCollectionOutput';
 export type { PromptOutput } from './models/PromptOutput';
 export type { RandomIntInvocation } from './models/RandomIntInvocation';
 export type { RandomRangeInvocation } from './models/RandomRangeInvocation';
@@ -95,6 +98,7 @@ export type { ResourceOrigin } from './models/ResourceOrigin';
 export type { RestoreFaceInvocation } from './models/RestoreFaceInvocation';
 export type { ScaleLatentsInvocation } from './models/ScaleLatentsInvocation';
 export type { ShowImageInvocation } from './models/ShowImageInvocation';
+export type { StepParamEasingInvocation } from './models/StepParamEasingInvocation';
 export type { SubtractInvocation } from './models/SubtractInvocation';
 export type { TextToImageInvocation } from './models/TextToImageInvocation';
 export type { TextToLatentsInvocation } from './models/TextToLatentsInvocation';

invokeai/frontend/web/src/services/api/models/AddInvocation.ts

@@ -24,4 +24,3 @@ export type AddInvocation = {
    */
   'b'?: number;
 };
-

invokeai/frontend/web/src/services/api/models/Body_upload_image.ts

@@ -5,4 +5,3 @@
 export type Body_upload_image = {
   file: Blob;
 };
-

invokeai/frontend/web/src/services/api/models/CannyImageProcessorInvocation.ts

@@ -30,4 +30,3 @@ export type CannyImageProcessorInvocation = {
    */
   high_threshold?: number;
 };
-

invokeai/frontend/web/src/services/api/models/CkptModelInfo.ts

@@ -29,4 +29,3 @@ export type CkptModelInfo = {
    */
   height?: number;
 };
-

invokeai/frontend/web/src/services/api/models/CollectInvocation.ts

@@ -24,4 +24,3 @@ export type CollectInvocation = {
    */
   collection?: Array<any>;
 };
-

invokeai/frontend/web/src/services/api/models/CollectInvocationOutput.ts

@@ -12,4 +12,3 @@ export type CollectInvocationOutput = {
    */
   collection: Array<any>;
 };
-

invokeai/frontend/web/src/services/api/models/ColorField.ts

@@ -20,4 +20,3 @@ export type ColorField = {
    */
   'a': number;
 };
-

invokeai/frontend/web/src/services/api/models/CompelInvocation.ts

@@ -24,4 +24,3 @@ export type CompelInvocation = {
    */
   model?: string;
 };
-

invokeai/frontend/web/src/services/api/models/CompelOutput.ts

@@ -14,4 +14,3 @@ export type CompelOutput = {
    */
   conditioning?: ConditioningField;
 };
-

invokeai/frontend/web/src/services/api/models/ConditioningField.ts

@@ -8,4 +8,3 @@ export type ConditioningField = {
    */
   conditioning_name: string;
 };
-

invokeai/frontend/web/src/services/api/models/ContentShuffleImageProcessorInvocation.ts

@@ -42,4 +42,3 @@ export type ContentShuffleImageProcessorInvocation = {
    */
   'f'?: number;
 };
-

invokeai/frontend/web/src/services/api/models/ControlField.ts

@@ -16,7 +16,7 @@ export type ControlField = {
   /**
    * The weight given to the ControlNet
    */
-  control_weight: number;
+  control_weight: (number | Array<number>);
   /**
    * When the ControlNet is first applied (% of total steps)
    */
@@ -25,5 +25,8 @@ export type ControlField = {
    * When the ControlNet is last applied (% of total steps)
    */
   end_step_percent: number;
+  /**
+   * The contorl mode to use
+   */
+  control_mode?: 'balanced' | 'more_prompt' | 'more_control' | 'unbalanced';
 };
-

invokeai/frontend/web/src/services/api/models/ControlNetInvocation.ts

@@ -22,13 +22,13 @@ export type ControlNetInvocation = {
    */
   image?: ImageField;
   /**
-   * The ControlNet model to use
+   * control model used
    */
   control_model?: 'lllyasviel/sd-controlnet-canny' | 'lllyasviel/sd-controlnet-depth' | 'lllyasviel/sd-controlnet-hed' | 'lllyasviel/sd-controlnet-seg' | 'lllyasviel/sd-controlnet-openpose' | 'lllyasviel/sd-controlnet-scribble' | 'lllyasviel/sd-controlnet-normal' | 'lllyasviel/sd-controlnet-mlsd' | 'lllyasviel/control_v11p_sd15_canny' | 'lllyasviel/control_v11p_sd15_openpose' | 'lllyasviel/control_v11p_sd15_seg' | 'lllyasviel/control_v11f1p_sd15_depth' | 'lllyasviel/control_v11p_sd15_normalbae' | 'lllyasviel/control_v11p_sd15_scribble' | 'lllyasviel/control_v11p_sd15_mlsd' | 'lllyasviel/control_v11p_sd15_softedge' | 'lllyasviel/control_v11p_sd15s2_lineart_anime' | 'lllyasviel/control_v11p_sd15_lineart' | 'lllyasviel/control_v11p_sd15_inpaint' | 'lllyasviel/control_v11e_sd15_shuffle' | 'lllyasviel/control_v11e_sd15_ip2p' | 'lllyasviel/control_v11f1e_sd15_tile' | 'thibaud/controlnet-sd21-openpose-diffusers' | 'thibaud/controlnet-sd21-canny-diffusers' | 'thibaud/controlnet-sd21-depth-diffusers' | 'thibaud/controlnet-sd21-scribble-diffusers' | 'thibaud/controlnet-sd21-hed-diffusers' | 'thibaud/controlnet-sd21-zoedepth-diffusers' | 'thibaud/controlnet-sd21-color-diffusers' | 'thibaud/controlnet-sd21-openposev2-diffusers' | 'thibaud/controlnet-sd21-lineart-diffusers' | 'thibaud/controlnet-sd21-normalbae-diffusers' | 'thibaud/controlnet-sd21-ade20k-diffusers' | 'CrucibleAI/ControlNetMediaPipeFace,diffusion_sd15' | 'CrucibleAI/ControlNetMediaPipeFace';
   /**
    * The weight given to the ControlNet
    */
-  control_weight?: number;
+  control_weight?: (number | Array<number>);
   /**
    * When the ControlNet is first applied (% of total steps)
    */
@@ -37,5 +37,8 @@ export type ControlNetInvocation = {
    * When the ControlNet is last applied (% of total steps)
    */
   end_step_percent?: number;
+  /**
+   * The control mode used
+   */
+  control_mode?: 'balanced' | 'more_prompt' | 'more_control' | 'unbalanced';
 };
-

invokeai/frontend/web/src/services/api/models/ControlOutput.ts

@@ -10,8 +10,7 @@ import type { ControlField } from './ControlField';
 export type ControlOutput = {
   type?: 'control_output';
   /**
-   * The output control image
+   * The control info
    */
   control?: ControlField;
 };
-

invokeai/frontend/web/src/services/api/models/CreateModelRequest.ts

@@ -15,4 +15,3 @@ export type CreateModelRequest = {
    */
   info: (CkptModelInfo | DiffusersModelInfo);
 };
-

invokeai/frontend/web/src/services/api/models/CvInpaintInvocation.ts

@@ -26,4 +26,3 @@ export type CvInpaintInvocation = {
    */
   mask?: ImageField;
 };
-

invokeai/frontend/web/src/services/api/models/DiffusersModelInfo.ts

@@ -23,4 +23,3 @@ export type DiffusersModelInfo = {
    */
   path?: string;
 };
-

invokeai/frontend/web/src/services/api/models/DivideInvocation.ts

@@ -24,4 +24,3 @@ export type DivideInvocation = {
    */
   'b'?: number;
 };
-

invokeai/frontend/web/src/services/api/models/DynamicPromptInvocation.ts

@@ -0,0 +1,30 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * Parses a prompt using adieyal/dynamicprompts' random or combinatorial generator
+ */
+export type DynamicPromptInvocation = {
+  /**
+   * The id of this node. Must be unique among all nodes.
+   */
+  id: string;
+  /**
+   * Whether or not this node is an intermediate node.
+   */
+  is_intermediate?: boolean;
+  type?: 'dynamic_prompt';
+  /**
+   * The prompt to parse with dynamicprompts
+   */
+  prompt: string;
+  /**
+   * The number of prompts to generate
+   */
+  max_prompts?: number;
+  /**
+   * Whether to use the combinatorial generator
+   */
+  combinatorial?: boolean;
+};

invokeai/frontend/web/src/services/api/models/Edge.ts

@@ -14,4 +14,3 @@ export type Edge = {
    */
   destination: EdgeConnection;
 };
-

invokeai/frontend/web/src/services/api/models/EdgeConnection.ts

@@ -12,4 +12,3 @@ export type EdgeConnection = {
    */
   field: string;
 };
-

invokeai/frontend/web/src/services/api/models/FloatCollectionOutput.ts

@@ -12,4 +12,3 @@ export type FloatCollectionOutput = {
    */
   collection?: Array<number>;
 };
-

invokeai/frontend/web/src/services/api/models/FloatLinearRangeInvocation.ts

@@ -0,0 +1,30 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * Creates a range
+ */
+export type FloatLinearRangeInvocation = {
+  /**
+   * The id of this node. Must be unique among all nodes.
+   */
+  id: string;
+  /**
+   * Whether or not this node is an intermediate node.
+   */
+  is_intermediate?: boolean;
+  type?: 'float_range';
+  /**
+   * The first value of the range
+   */
+  start?: number;
+  /**
+   * The last value of the range
+   */
+  stop?: number;
+  /**
+   * number of values to interpolate over (including start and stop)
+   */
+  steps?: number;
+};

invokeai/frontend/web/src/services/api/models/FloatOutput.ts

@@ -12,4 +12,3 @@ export type FloatOutput = {
    */
   param?: number;
 };
-

invokeai/frontend/web/src/services/api/models/Graph.ts

@@ -10,7 +10,9 @@ import type { ContentShuffleImageProcessorInvocation } from './ContentShuffleIma
 import type { ControlNetInvocation } from './ControlNetInvocation';
 import type { CvInpaintInvocation } from './CvInpaintInvocation';
 import type { DivideInvocation } from './DivideInvocation';
+import type { DynamicPromptInvocation } from './DynamicPromptInvocation';
 import type { Edge } from './Edge';
+import type { FloatLinearRangeInvocation } from './FloatLinearRangeInvocation';
 import type { GraphInvocation } from './GraphInvocation';
 import type { HedImageProcessorInvocation } from './HedImageProcessorInvocation';
 import type { ImageBlurInvocation } from './ImageBlurInvocation';
@@ -55,6 +57,7 @@ import type { ResizeLatentsInvocation } from './ResizeLatentsInvocation';
 import type { RestoreFaceInvocation } from './RestoreFaceInvocation';
 import type { ScaleLatentsInvocation } from './ScaleLatentsInvocation';
 import type { ShowImageInvocation } from './ShowImageInvocation';
+import type { StepParamEasingInvocation } from './StepParamEasingInvocation';
 import type { SubtractInvocation } from './SubtractInvocation';
 import type { TextToImageInvocation } from './TextToImageInvocation';
 import type { TextToLatentsInvocation } from './TextToLatentsInvocation';
@@ -69,10 +72,9 @@ export type Graph = {
   /**
    * The nodes in this graph
    */
-  nodes?: Record<string, (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation)>;
+  nodes?: Record<string, (RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | CompelInvocation | LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | CvInpaintInvocation | TextToImageInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | DynamicPromptInvocation | RestoreFaceInvocation | UpscaleInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | ImageToImageInvocation | LatentsToLatentsInvocation | InpaintInvocation)>;
   /**
    * The connections between nodes and their fields in this graph
    */
   edges?: Array<Edge>;
 };
-

invokeai/frontend/web/src/services/api/models/GraphExecutionState.ts

@@ -16,6 +16,7 @@ import type { IterateInvocationOutput } from './IterateInvocationOutput';
 import type { LatentsOutput } from './LatentsOutput';
 import type { MaskOutput } from './MaskOutput';
 import type { NoiseOutput } from './NoiseOutput';
+import type { PromptCollectionOutput } from './PromptCollectionOutput';
 import type { PromptOutput } from './PromptOutput';
 
 /**
@@ -45,7 +46,7 @@ export type GraphExecutionState = {
   /**
    * The results of node executions
    */
-  results: Record<string, (ImageOutput | MaskOutput | ControlOutput | PromptOutput | CompelOutput | IntOutput | FloatOutput | LatentsOutput | NoiseOutput | IntCollectionOutput | FloatCollectionOutput | GraphInvocationOutput | IterateInvocationOutput | CollectInvocationOutput)>;
+  results: Record<string, (IntCollectionOutput | FloatCollectionOutput | CompelOutput | ImageOutput | MaskOutput | ControlOutput | LatentsOutput | NoiseOutput | IntOutput | FloatOutput | PromptOutput | PromptCollectionOutput | GraphInvocationOutput | IterateInvocationOutput | CollectInvocationOutput)>;
   /**
    * Errors raised when executing nodes
    */
@@ -59,4 +60,3 @@ export type GraphExecutionState = {
    */
   source_prepared_mapping: Record<string, Array<string>>;
 };
-

invokeai/frontend/web/src/services/api/models/GraphInvocation.ts

@@ -22,4 +22,3 @@ export type GraphInvocation = {
    */
   graph?: Graph;
 };
-

invokeai/frontend/web/src/services/api/models/GraphInvocationOutput.ts

@@ -8,4 +8,3 @@
 export type GraphInvocationOutput = {
   type: 'graph_output';
 };
-

invokeai/frontend/web/src/services/api/models/HTTPValidationError.ts

@@ -7,4 +7,3 @@ import type { ValidationError } from './ValidationError';
 export type HTTPValidationError = {
   detail?: Array<ValidationError>;
 };
-