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

16
nodes.py
View File

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