import comfy.utils from comfy.cldm.control_types import UNION_CONTROLNET_TYPES from comfy_api.v3 import io class ControlNetApplyAdvanced_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( node_id="ControlNetApplyAdvanced_V3", display_name="Apply ControlNet _V3", category="conditioning/controlnet", inputs=[ 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"), ], ) @classmethod def execute( cls, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[] ) -> io.NodeOutput: if strength == 0: return io.NodeOutput(positive, negative) control_hint = image.movedim(-1, 1) cnets = {} out = [] for conditioning in [positive, negative]: c = [] for t in conditioning: d = t[1].copy() prev_cnet = d.get("control", None) if prev_cnet in cnets: c_net = cnets[prev_cnet] else: c_net = control_net.copy().set_cond_hint( control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat ) c_net.set_previous_controlnet(prev_cnet) cnets[prev_cnet] = c_net d["control"] = c_net d["control_apply_to_uncond"] = False n = [t[0], d] c.append(n) out.append(c) return io.NodeOutput(out[0], out[1]) class SetUnionControlNetType_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( node_id="SetUnionControlNetType_V3", category="conditioning/controlnet", inputs=[ io.ControlNet.Input("control_net"), io.Combo.Input("type", options=["auto"] + list(UNION_CONTROLNET_TYPES.keys())), ], outputs=[ io.ControlNet.Output("control_net_out"), ], ) @classmethod 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: control_net.set_extra_arg("control_type", [type_number]) else: control_net.set_extra_arg("control_type", []) return io.NodeOutput(control_net) class ControlNetInpaintingAliMamaApply_V3(ControlNetApplyAdvanced_V3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( node_id="ControlNetInpaintingAliMamaApply_V3", category="conditioning/controlnet", inputs=[ 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"), ], ) @classmethod 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])) mask_apply = comfy.utils.common_upscale(mask, image.shape[2], image.shape[1], "bilinear", "center").round() image = image * mask_apply.movedim(1, -1).repeat(1, 1, 1, image.shape[3]) extra_concat = [mask] return super().execute( positive, negative, control_net, image, strength, start_percent, end_percent, vae=vae, extra_concat=extra_concat, ) NODES_LIST: list[type[io.ComfyNodeV3]] = [ ControlNetApplyAdvanced_V3, SetUnionControlNetType_V3, ControlNetInpaintingAliMamaApply_V3, ]