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

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comfyanonymous
2023-07-24 18:29:00 -04:00
parent 7ff14b62f8
commit 5f75d784a1
2 changed files with 14 additions and 9 deletions
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16
nodes.py
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@@ -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