diff --git a/comfy/controlnet.py b/comfy/controlnet.py
index ea219c7e5..5d7699fba 100644
--- a/comfy/controlnet.py
+++ b/comfy/controlnet.py
@@ -30,6 +30,7 @@ def broadcast_image_to(tensor, target_batch_size, batched_number):
 
 class ControlBase:
     def __init__(self, device=None):
+        self.scaled_weight = None
         self.cond_hint_original = None
         self.cond_hint = None
         self.strength = 1.0
@@ -41,13 +42,17 @@ class ControlBase:
         self.device = device
         self.previous_controlnet = None
         self.global_average_pooling = False
-
-    def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(1.0, 0.0)):
+        self.soft_injection = False
+    def set_cond_hint(self, cond_hint, strength=1.0, soft_injection=False, timestep_percent_range=(1.0, 0.0)):
         self.cond_hint_original = cond_hint
         self.strength = strength
         self.timestep_percent_range = timestep_percent_range
+        self.soft_injection = soft_injection
         return self
 
+    def set_cond_scaled_weight(self, scaled_weight):
+        self.scaled_weight = scaled_weight #Added an object to keep the scaled weights
+
     def pre_run(self, model, percent_to_timestep_function):
         self.timestep_range = (percent_to_timestep_function(self.timestep_percent_range[0]), percent_to_timestep_function(self.timestep_percent_range[1]))
         if self.previous_controlnet is not None:
@@ -127,9 +132,10 @@ class ControlBase:
         return out
 
 class ControlNet(ControlBase):
-    def __init__(self, control_model, global_average_pooling=False, device=None):
+    def __init__(self, control_model, soft_inject=False, global_average_pooling=False, device=None):
         super().__init__(device)
         self.control_model = control_model
+        self.soft_injection = soft_inject
         self.control_model_wrapped = comfy.model_patcher.ModelPatcher(self.control_model, load_device=comfy.model_management.get_torch_device(), offload_device=comfy.model_management.unet_offload_device())
         self.global_average_pooling = global_average_pooling
 
@@ -160,6 +166,8 @@ class ControlNet(ControlBase):
         if y is not None:
             y = y.to(self.control_model.dtype)
         control = self.control_model(x=x_noisy.to(self.control_model.dtype), hint=self.cond_hint, timesteps=t, context=context.to(self.control_model.dtype), y=y)
+        if self.soft_injection:
+            control = [c * scale for c, scale in zip(control, self.scaled_weight)]
         return self.control_merge(None, control, control_prev, output_dtype)
 
     def copy(self):