rename: Inpaint Mask to Denoise Mask

invokeai/app/invocations/latent.py

@@ -21,10 +21,10 @@ from torchvision.transforms.functional import resize as tv_resize
 
 from invokeai.app.invocations.metadata import CoreMetadata
 from invokeai.app.invocations.primitives import (
+    DenoiseMaskField,
+    DenoiseMaskOutput,
     ImageField,
     ImageOutput,
-    InpaintMaskField,
-    InpaintMaskOutput,
     LatentsField,
     LatentsOutput,
     build_latents_output,
@@ -57,16 +57,16 @@ DEFAULT_PRECISION = choose_precision(choose_torch_device())
 SAMPLER_NAME_VALUES = Literal[tuple(list(SCHEDULER_MAP.keys()))]
 
 
-@title("Create Inpaint Mask")
-@tags("mask", "inpaint")
-class CreateInpaintMaskInvocation(BaseInvocation):
-    """Creates mask for inpaint model run."""
+@title("Create Denoise Mask")
+@tags("mask", "denoise")
+class CreateDenoiseMaskInvocation(BaseInvocation):
+    """Creates mask for denoising model run."""
 
     # Metadata
-    type: Literal["create_inpaint_mask"] = "create_inpaint_mask"
+    type: Literal["create_denoise_mask"] = "create_denoise_mask"
 
     # Inputs
-    image: Optional[ImageField] = InputField(default=None, description="Image which will be inpainted")
+    image: Optional[ImageField] = InputField(default=None, description="Image which will be masked")
     mask: ImageField = InputField(description="The mask to use when pasting")
     vae: VaeField = InputField(
         description=FieldDescriptions.vae,
@@ -86,7 +86,7 @@ class CreateInpaintMaskInvocation(BaseInvocation):
         return mask_tensor
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> InpaintMaskOutput:
+    def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
         if self.image is not None:
             image = context.services.images.get_pil_image(self.image.image_name)
             image = image_resized_to_grid_as_tensor(image.convert("RGB"))
@@ -118,8 +118,8 @@ class CreateInpaintMaskInvocation(BaseInvocation):
         mask_name = f"{context.graph_execution_state_id}__{self.id}_mask"
         context.services.latents.save(mask_name, mask)
 
-        return InpaintMaskOutput(
-            inpaint_mask=InpaintMaskField(
+        return DenoiseMaskOutput(
+            denoise_mask=DenoiseMaskField(
                 mask_name=mask_name,
                 masked_latents_name=masked_latents_name,
             ),
@@ -189,7 +189,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         default=None, description=FieldDescriptions.control, input=Input.Connection, ui_order=5
     )
     latents: Optional[LatentsField] = InputField(description=FieldDescriptions.latents, input=Input.Connection)
-    mask: Optional[InpaintMaskField] = InputField(
+    denoise_mask: Optional[DenoiseMaskField] = InputField(
         default=None,
         description=FieldDescriptions.mask,
     )
@@ -403,13 +403,13 @@ class DenoiseLatentsInvocation(BaseInvocation):
         return num_inference_steps, timesteps, init_timestep
 
     def prep_inpaint_mask(self, context, latents):
-        if self.mask is None:
+        if self.denoise_mask is None:
             return None, None
 
-        mask = context.services.latents.get(self.mask.mask_name)
+        mask = context.services.latents.get(self.denoise_mask.mask_name)
         mask = tv_resize(mask, latents.shape[-2:], T.InterpolationMode.BILINEAR)
-        if self.mask.masked_latents_name is not None:
-            masked_latents = context.services.latents.get(self.mask.masked_latents_name)
+        if self.denoise_mask.masked_latents_name is not None:
+            masked_latents = context.services.latents.get(self.denoise_mask.masked_latents_name)
         else:
             masked_latents = None
 

invokeai/app/invocations/primitives.py

@@ -296,21 +296,21 @@ class ImageCollectionInvocation(BaseInvocation):
 
 # endregion
 
-# region InpaintMask
+# region DenoiseMask
 
 
-class InpaintMaskField(BaseModel):
+class DenoiseMaskField(BaseModel):
     """An inpaint mask field"""
 
     mask_name: str = Field(description="The name of the mask image")
     masked_latents_name: Optional[str] = Field(description="The name of the masked image latents")
 
 
-class InpaintMaskOutput(BaseInvocationOutput):
+class DenoiseMaskOutput(BaseInvocationOutput):
     """Base class for nodes that output a single image"""
 
-    type: Literal["inpaint_mask_output"] = "inpaint_mask_output"
-    inpaint_mask: InpaintMaskField = OutputField(description="Mask for inpaint model run")
+    type: Literal["denoise_mask_output"] = "denoise_mask_output"
+    denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run")
 
 
 # endregion