mirror of
https://github.com/comfyanonymous/ComfyUI.git
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142 lines
5.1 KiB
Python
142 lines
5.1 KiB
Python
import comfy.utils
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from comfy.cldm.control_types import UNION_CONTROLNET_TYPES
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from comfy_api.v3 import io
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class ControlNetApplyAdvanced_V3(io.ComfyNodeV3):
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@classmethod
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def DEFINE_SCHEMA(cls):
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return io.SchemaV3(
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node_id="ControlNetApplyAdvanced_V3",
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display_name="Apply ControlNet _V3",
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category="conditioning/controlnet",
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inputs=[
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io.Conditioning.Input("positive"),
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io.Conditioning.Input("negative"),
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io.ControlNet.Input("control_net"),
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io.Image.Input("image"),
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io.Float.Input("strength", default=1.0, min=0.0, max=10.0, step=0.01),
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io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
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io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
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io.Vae.Input("vae", optional=True),
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],
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outputs=[
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io.Conditioning.Output("positive_out", display_name="positive"),
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io.Conditioning.Output("negative_out", display_name="negative"),
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],
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)
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@classmethod
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def execute(
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cls, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[]
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) -> io.NodeOutput:
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if strength == 0:
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return io.NodeOutput(positive, negative)
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control_hint = image.movedim(-1, 1)
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cnets = {}
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out = []
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for conditioning in [positive, negative]:
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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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prev_cnet = d.get("control", None)
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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(
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control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat
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)
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c_net.set_previous_controlnet(prev_cnet)
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cnets[prev_cnet] = c_net
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d["control"] = c_net
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d["control_apply_to_uncond"] = False
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n = [t[0], d]
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c.append(n)
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out.append(c)
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return io.NodeOutput(out[0], out[1])
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class SetUnionControlNetType_V3(io.ComfyNodeV3):
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@classmethod
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def DEFINE_SCHEMA(cls):
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return io.SchemaV3(
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node_id="SetUnionControlNetType_V3",
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category="conditioning/controlnet",
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inputs=[
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io.ControlNet.Input("control_net"),
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io.Combo.Input("type", options=["auto"] + list(UNION_CONTROLNET_TYPES.keys())),
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],
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outputs=[
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io.ControlNet.Output("control_net_out"),
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],
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)
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@classmethod
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def execute(cls, control_net, type) -> io.NodeOutput:
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control_net = control_net.copy()
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type_number = UNION_CONTROLNET_TYPES.get(type, -1)
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if type_number >= 0:
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control_net.set_extra_arg("control_type", [type_number])
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else:
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control_net.set_extra_arg("control_type", [])
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return io.NodeOutput(control_net)
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class ControlNetInpaintingAliMamaApply_V3(ControlNetApplyAdvanced_V3):
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@classmethod
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def DEFINE_SCHEMA(cls):
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return io.SchemaV3(
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node_id="ControlNetInpaintingAliMamaApply_V3",
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category="conditioning/controlnet",
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inputs=[
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io.Conditioning.Input("positive"),
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io.Conditioning.Input("negative"),
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io.ControlNet.Input("control_net"),
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io.Vae.Input("vae"),
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io.Image.Input("image"),
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io.Mask.Input("mask"),
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io.Float.Input("strength", default=1.0, min=0.0, max=10.0, step=0.01),
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io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
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io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
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],
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outputs=[
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io.Conditioning.Output("positive_out", display_name="positive"),
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io.Conditioning.Output("negative_out", display_name="negative"),
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],
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)
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@classmethod
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def execute(
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cls, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent
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) -> io.NodeOutput:
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extra_concat = []
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if control_net.concat_mask:
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mask = 1.0 - mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1]))
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mask_apply = comfy.utils.common_upscale(mask, image.shape[2], image.shape[1], "bilinear", "center").round()
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image = image * mask_apply.movedim(1, -1).repeat(1, 1, 1, image.shape[3])
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extra_concat = [mask]
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return super().execute(
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positive,
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negative,
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control_net,
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image,
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strength,
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start_percent,
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end_percent,
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vae=vae,
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extra_concat=extra_concat,
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)
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NODES_LIST: list[type[io.ComfyNodeV3]] = [
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ControlNetApplyAdvanced_V3,
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SetUnionControlNetType_V3,
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ControlNetInpaintingAliMamaApply_V3,
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]
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