Start is now 0.0 and end is now 1.0 for the timestep ranges.
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7ff14b62f8
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@ -713,7 +713,6 @@ class ControlBase:
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out = []
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if self.previous_controlnet is not None:
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out += self.previous_controlnet.get_models()
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out.append(self.control_model)
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return out
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def copy_to(self, c):
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@ -791,6 +790,12 @@ class ControlNet(ControlBase):
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self.copy_to(c)
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return c
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def get_models(self):
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out = super().get_models()
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out.append(self.control_model)
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return out
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def load_controlnet(ckpt_path, model=None):
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controlnet_data = utils.load_torch_file(ckpt_path, safe_load=True)
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16
nodes.py
16
nodes.py
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@ -208,8 +208,8 @@ class ConditioningSetTimestepRange:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"conditioning": ("CONDITIONING", ),
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"start": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
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"end": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001})
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"start": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
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"end": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
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}}
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RETURN_TYPES = ("CONDITIONING",)
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FUNCTION = "set_range"
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@ -220,8 +220,8 @@ class ConditioningSetTimestepRange:
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c = []
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for t in conditioning:
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d = t[1].copy()
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d['start_percent'] = start
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d['end_percent'] = end
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d['start_percent'] = 1.0 - start
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d['end_percent'] = 1.0 - end
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n = [t[0], d]
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c.append(n)
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return (c, )
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@ -615,8 +615,8 @@ class ControlNetApplyAdvanced:
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"control_net": ("CONTROL_NET", ),
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"image": ("IMAGE", ),
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"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"start": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
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"end": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001})
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"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
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"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
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}}
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RETURN_TYPES = ("CONDITIONING","CONDITIONING")
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@ -625,7 +625,7 @@ class ControlNetApplyAdvanced:
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CATEGORY = "conditioning"
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def apply_controlnet(self, positive, negative, control_net, image, strength, start, end):
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def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent):
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if strength == 0:
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return (positive, negative)
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@ -642,7 +642,7 @@ class ControlNetApplyAdvanced:
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if prev_cnet in cnets:
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c_net = cnets[prev_cnet]
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else:
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c_net = control_net.copy().set_cond_hint(control_hint, strength, (start, end))
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c_net = control_net.copy().set_cond_hint(control_hint, strength, (1.0 - start_percent, 1.0 - end_percent))
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c_net.set_previous_controlnet(prev_cnet)
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cnets[prev_cnet] = c_net
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