diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index e90df9b8cd..b77363ceb8 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -1235,8 +1235,8 @@ class CropLatentsCoreInvocation(BaseInvocation): class IdealSizeOutput(BaseInvocationOutput): """Base class for invocations that output an image""" - width: int = OutputField(description="The ideal width of the image in pixels") - height: int = OutputField(description="The ideal height of the image in pixels") + width: int = OutputField(description="The ideal width of the image (in pixels)") + height: int = OutputField(description="The ideal height of the image (in pixels)") @invocation( @@ -1248,10 +1248,13 @@ class IdealSizeOutput(BaseInvocationOutput): class IdealSizeInvocation(BaseInvocation): """Calculates the ideal size for generation to avoid duplication""" - width: int = InputField(default=1024, description="Target width") - height: int = InputField(default=576, description="Target height") - unet: UNetField = InputField(default=None, description="UNet submodel") - multiplier: float = InputField(default=1.0, description="Dimensional multiplier") + width: int = InputField(default=1024, description="Final image width") + height: int = InputField(default=576, description="Final image height") + unet: UNetField = InputField(default=None, description=FieldDescriptions.unet) + multiplier: float = InputField( + default=1.0, + description="Amount to multiply the model's dimensions by when calculating the ideal size (may result in initial generation artifacts if too large)", + ) def trim_to_multiple_of(self, *args, multiple_of=LATENT_SCALE_FACTOR): return tuple((x - x % multiple_of) for x in args)