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V3 ControlNet nodes: use io.NodeOutput; adjust code style

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bigcat88 2025-07-12 11:19:52 +03:00
parent 21c9d7b289
commit 535faa84f6
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1 changed files with 30 additions and 127 deletions
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157
comfy_extras/v3/nodes_controlnet.py
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@ -11,67 +11,25 @@ class ControlNetApplyAdvanced_V3(io.ComfyNodeV3):
display_name="Apply ControlNet _V3",
category="conditioning/controlnet",
inputs=[
io.Conditioning.Input(
"positive",
display_name="positive",
),
io.Conditioning.Input(
"negative",
display_name="negative",
),
io.ControlNet.Input(
"control_net",
display_name="control_net",
),
io.Image.Input(
"image",
display_name="image",
),
io.Float.Input(
"strength",
display_name="strength",
default=1.0,
min=0.0,
max=10.0,
step=0.01,
),
io.Float.Input(
"start_percent",
display_name="start percent",
default=0.0,
min=0.0,
max=1.0,
step=0.001,
),
io.Float.Input(
"end_percent",
display_name="end percent",
default=1.0,
min=0.0,
max=1.0,
step=0.001,
),
io.Vae.Input(
"vae",
optional=True,
),
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
io.ControlNet.Input("control_net"),
io.Image.Input("image"),
io.Float.Input("strength", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
io.Vae.Input("vae", optional=True),
],
outputs=[
io.Conditioning.Output(
"positive_out",
display_name="positive",
),
io.Conditioning.Output(
"negative_out",
display_name="negative",
),
io.Conditioning.Output("positive_out", display_name="positive"),
io.Conditioning.Output("negative_out", display_name="negative"),
],
)
@classmethod
def execute(cls, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[]):
def execute(cls, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[]) -> io.NodeOutput:
if strength == 0:
return (positive, negative)
return io.NodeOutput(positive, negative)
control_hint = image.movedim(-1,1)
cnets = {}
@ -95,7 +53,7 @@ class ControlNetApplyAdvanced_V3(io.ComfyNodeV3):
n = [t[0], d]
c.append(n)
out.append(c)
return (out[0], out[1])
return io.NodeOutput(out[0], out[1])
class SetUnionControlNetType_V3(io.ComfyNodeV3):
@ -105,25 +63,16 @@ class SetUnionControlNetType_V3(io.ComfyNodeV3):
node_id="SetUnionControlNetType_V3",
category="conditioning/controlnet",
inputs=[
io.ControlNet.Input(
"control_net",
display_name="control_net",
),
io.Combo.Input(
"type",
options=["auto"] + list(UNION_CONTROLNET_TYPES.keys()),
),
io.ControlNet.Input("control_net"),
io.Combo.Input("type", options=["auto"] + list(UNION_CONTROLNET_TYPES.keys())),
],
outputs=[
io.ControlNet.Output(
"control_net_out",
display_name="control_net",
),
io.ControlNet.Output("control_net_out"),
],
)
@classmethod
def execute(cls, control_net, type):
def execute(cls, control_net, type) -> io.NodeOutput:
control_net = control_net.copy()
type_number = UNION_CONTROLNET_TYPES.get(type, -1)
if type_number >= 0:
@ -131,7 +80,7 @@ class SetUnionControlNetType_V3(io.ComfyNodeV3):
else:
control_net.set_extra_arg("control_type", [])
return (control_net,)
return io.NodeOutput(control_net)
class ControlNetInpaintingAliMamaApply_V3(ControlNetApplyAdvanced_V3):
@ -141,70 +90,24 @@ class ControlNetInpaintingAliMamaApply_V3(ControlNetApplyAdvanced_V3):
node_id="ControlNetInpaintingAliMamaApply_V3",
category="conditioning/controlnet",
inputs=[
io.Conditioning.Input(
"positive",
display_name="positive",
),
io.Conditioning.Input(
"negative",
display_name="negative",
),
io.ControlNet.Input(
"control_net",
display_name="control_net",
),
io.Vae.Input(
"vae",
display_name="vae",
),
io.Image.Input(
"image",
display_name="image",
),
io.Mask.Input(
"mask",
display_name="mask",
),
io.Float.Input(
"strength",
display_name="strength",
default=1.0,
min=0.0,
max=10.0,
step=0.01,
),
io.Float.Input(
"start_percent",
display_name="start percent",
default=0.0,
min=0.0,
max=1.0,
step=0.001,
),
io.Float.Input(
"end_percent",
display_name="end percent",
default=1.0,
min=0.0,
max=1.0,
step=0.001,
),
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
io.ControlNet.Input("control_net"),
io.Vae.Input("vae"),
io.Image.Input("image"),
io.Mask.Input("mask"),
io.Float.Input("strength", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
],
outputs=[
io.Conditioning.Output(
"positive_out",
display_name="positive",
),
io.Conditioning.Output(
"negative_out",
display_name="negative",
),
io.Conditioning.Output("positive_out", display_name="positive"),
io.Conditioning.Output("negative_out", display_name="negative"),
],
)
@classmethod
def execute(cls, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent):
def execute(cls, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent) -> io.NodeOutput:
extra_concat = []
if control_net.concat_mask:
mask = 1.0 - mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1]))