Start is now 0.0 and end is now 1.0 for the timestep ranges.

comfy/sd.py

@@ -713,7 +713,6 @@ class ControlBase:
         out = []
         if self.previous_controlnet is not None:
             out += self.previous_controlnet.get_models()
-        out.append(self.control_model)
         return out
 
     def copy_to(self, c):
@@ -791,6 +790,12 @@ class ControlNet(ControlBase):
         self.copy_to(c)
         return c
 
+    def get_models(self):
+        out = super().get_models()
+        out.append(self.control_model)
+        return out
+
+
 def load_controlnet(ckpt_path, model=None):
     controlnet_data = utils.load_torch_file(ckpt_path, safe_load=True)
 

nodes.py

@@ -208,8 +208,8 @@ class ConditioningSetTimestepRange:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": {"conditioning": ("CONDITIONING", ),
-                             "start": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
-                             "end": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001})
+                             "start": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
+                             "end": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
                              }}
     RETURN_TYPES = ("CONDITIONING",)
     FUNCTION = "set_range"
@@ -220,8 +220,8 @@ class ConditioningSetTimestepRange:
         c = []
         for t in conditioning:
             d = t[1].copy()
-            d['start_percent'] = start
-            d['end_percent'] = end
+            d['start_percent'] = 1.0 - start
+            d['end_percent'] = 1.0 - end
             n = [t[0], d]
             c.append(n)
         return (c, )
@@ -615,8 +615,8 @@ class ControlNetApplyAdvanced:
                              "control_net": ("CONTROL_NET", ),
                              "image": ("IMAGE", ),
                              "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
-                             "start": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
-                             "end": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001})
+                             "start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
+                             "end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
                              }}
 
     RETURN_TYPES = ("CONDITIONING","CONDITIONING")
@@ -625,7 +625,7 @@ class ControlNetApplyAdvanced:
 
     CATEGORY = "conditioning"
 
-    def apply_controlnet(self, positive, negative, control_net, image, strength, start, end):
+    def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent):
         if strength == 0:
             return (positive, negative)
 
@@ -642,7 +642,7 @@ class ControlNetApplyAdvanced:
                 if prev_cnet in cnets:
                     c_net = cnets[prev_cnet]
                 else:
-                    c_net = control_net.copy().set_cond_hint(control_hint, strength, (start, end))
+                    c_net = control_net.copy().set_cond_hint(control_hint, strength, (1.0 - start_percent, 1.0 - end_percent))
                     c_net.set_previous_controlnet(prev_cnet)
                     cnets[prev_cnet] = c_net