diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 51784134b5..f94b3fbede 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -51,8 +51,6 @@ class ControlOutput(BaseInvocationOutput):
     # fmt: off
     type: Literal["control_output"] = "control_output"
     control: Optional[ControlField] = Field(default=None, description="The control info dict")
-    # raw_processed_image: ImageField = Field(default=None,
-    #                                        description="outputs just the image info (also included in control output)")
     # fmt: on
 
 
@@ -100,6 +98,7 @@ class ImageProcessorInvocation(BaseInvocation, PILInvocationConfig):
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         raw_image = context.services.images.get(
+
             self.image.image_type, self.image.image_name
         )
         # image type should be PIL.PngImagePlugin.PngImageFile ?
@@ -117,6 +116,7 @@ class ImageProcessorInvocation(BaseInvocation, PILInvocationConfig):
         context.services.images.save(image_type, image_name, processed_image, metadata)
 
         """Builds an ImageOutput and its ImageField"""
+
         processed_image_field = ImageField(
             image_name=image_name,
             image_type=image_type,
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 15f580b23a..20e4ab2ee3 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -342,21 +342,32 @@ class TextToLatentsInvocation(BaseInvocation):
             multi_control = MultiControlNetModel(control_models)
             model.control_model = multi_control
 
-        # loading controlnet model
-        if (self.control_model is None or self.control_model==''):
-            control_model = None
+        print("type of control input: ", type(self.control))
+
+        if (self.control is None):
+            control_model_name = None
+            control_image_field = None
+            control_weight = None
         else:
+            control_model_name = self.control.control_model
+            control_image_field = self.control.image
+            control_weight = self.control.control_weight
+
+        # # loading controlnet model
+        # if (self.control_model is None or self.control_model==''):
+        #     control_model = None
+        # else:
             # FIXME: change this to dropdown menu?
             # FIXME: generalize so don't have to hardcode torch_dtype and device
-            control_model = ControlNetModel.from_pretrained(self.control_model,
+            control_model = ControlNetModel.from_pretrained(control_model_name,
                                                             torch_dtype=torch.float16).to("cuda")
         model.control_model = control_model
 
         # loading controlnet image (currently requires pre-processed image)
         control_image = (
-            None if self.control_image is None
+            None if control_image_field is None
             else context.services.images.get(
-                self.control_image.image_type, self.control_image.image_name
+                control_image_field.image_type, control_image_field.image_name
             )
         )