功能优化,新增通用隐藏节点

This commit is contained in:
严浪
2025-05-23 17:09:52 +08:00
parent f555497bfc
commit 4620513cc1
18 changed files with 1748 additions and 4 deletions
+644
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"title": "CLIP文本编码器"
}
},
"6": {
"inputs": {
"control_net_name": "control_v11p_sd15_lineart.pth"
},
"class_type": "ControlNetLoader",
"_meta": {
"title": "ControlNet加载器"
}
},
"7": {
"inputs": {
"strength": 1,
"conditioning": [
"3",
0
],
"control_net": [
"6",
0
],
"image": [
"22",
0
]
},
"class_type": "ControlNetApply",
"_meta": {
"title": "ControlNet应用(旧版)"
}
},
"8": {
"inputs": {
"seed": 275540587861329,
"steps": 8,
"cfg": 1,
"sampler_name": "lcm",
"scheduler": "karras",
"denoise": 1,
"model": [
"14",
0
],
"positive": [
"7",
0
],
"negative": [
"4",
0
],
"latent_image": [
"2",
0
]
},
"class_type": "KSampler",
"_meta": {
"title": "K采样器"
}
},
"9": {
"inputs": {
"samples": [
"8",
0
],
"vae": [
"1",
2
]
},
"class_type": "VAEDecode",
"_meta": {
"title": "VAE解码"
}
},
"14": {
"inputs": {
"lora_name": "lcm-lora-sdv1-5.safetensors",
"strength_model": 1,
"model": [
"1",
0
]
},
"class_type": "LoraLoaderModelOnly",
"_meta": {
"title": "LoRA加载器(仅模型)"
}
},
"16": {
"inputs": {
"image": [
"22",
0
]
},
"class_type": "GetImageSize+",
"_meta": {
"title": "获取图像尺寸"
}
},
"17": {
"inputs": {
"text_trans": ""
},
"class_type": "ZhPromptTranslator",
"_meta": {
"title": "正向提示词"
}
},
"18": {
"inputs": {
"text_trans": ""
},
"class_type": "ZhPromptTranslator",
"_meta": {
"title": "反向提示词"
}
},
"20": {
"inputs": {
"channel": "red",
"image": [
"25",
0
]
},
"class_type": "ImageToMask",
"_meta": {
"title": "图像到遮罩"
}
},
"21": {
"inputs": {
"mask": [
"20",
0
]
},
"class_type": "InvertMask",
"_meta": {
"title": "遮罩反转"
}
},
"22": {
"inputs": {
"mask": [
"21",
0
]
},
"class_type": "MaskToImage",
"_meta": {
"title": "遮罩到图像"
}
},
"23": {
"inputs": {
"filename_prefix": "ComfyUI",
"images": [
"9",
0
]
},
"class_type": "SaveImgOutputLam",
"_meta": {
"title": "保存图像应用输出"
}
},
"24": {
"inputs": {
"appName": "简笔画",
"appType": "paint-board",
"appDesc": "",
"styles": ""
},
"class_type": "AppParams",
"_meta": {
"title": "应用参数管理"
}
},
"25": {
"inputs": {
"image": ""
},
"class_type": "LamLoadImageBase64",
"_meta": {
"title": "Base64图片加载"
}
}
}
+205
View File
@@ -0,0 +1,205 @@
{
"3": {
"inputs": {
"seed": 156680208700286,
"steps": 20,
"cfg": 8,
"sampler_name": "euler",
"scheduler": "normal",
"denoise": 1,
"model": [
"4",
0
],
"positive": [
"11",
1
],
"negative": [
"7",
0
],
"latent_image": [
"5",
0
]
},
"class_type": "KSampler",
"_meta": {
"title": "K采样器"
}
},
"4": {
"inputs": {
"ckpt_name": "yamer_Cartoon_xenoArcadiaCD.safetensors"
},
"class_type": "CheckpointLoaderSimple",
"_meta": {
"title": "Checkpoint加载器(简易)"
}
},
"5": {
"inputs": {
"width": 512,
"height": 512,
"batch_size": 1
},
"class_type": "EmptyLatentImage",
"_meta": {
"title": "空Latent"
}
},
"6": {
"inputs": {
"text": "",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP文本编码器"
}
},
"7": {
"inputs": {
"text": "text, watermark",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP文本编码器"
}
},
"8": {
"inputs": {
"samples": [
"3",
0
],
"vae": [
"4",
2
]
},
"class_type": "VAEDecode",
"_meta": {
"title": "VAE解码"
}
},
"10": {
"inputs": {
"image": ""
},
"class_type": "LamLoadImageBase64",
"_meta": {
"title": "Base64图片加载"
}
},
"11": {
"inputs": {
"strength": 1,
"start_percent": 0,
"end_percent": 1,
"positive": [
"6",
0
],
"negative": [
"7",
0
],
"control_net": [
"12",
0
],
"image": [
"17",
0
],
"vae": [
"4",
2
]
},
"class_type": "ControlNetApplyAdvanced",
"_meta": {
"title": "ControlNet应用(旧版高级)"
}
},
"12": {
"inputs": {
"control_net_name": "control_v11p_sd15_lineart.pth"
},
"class_type": "ControlNetLoader",
"_meta": {
"title": "ControlNet加载器"
}
},
"13": {
"inputs": {
"filename_prefix": "ComfyUI",
"images": [
"8",
0
]
},
"class_type": "SaveImgOutputLam",
"_meta": {
"title": "保存图像应用输出"
}
},
"15": {
"inputs": {
"channel": "red",
"image": [
"10",
0
]
},
"class_type": "ImageToMask",
"_meta": {
"title": "图像到遮罩"
}
},
"16": {
"inputs": {
"mask": [
"15",
0
]
},
"class_type": "InvertMask (segment anything)",
"_meta": {
"title": "反转遮罩"
}
},
"17": {
"inputs": {
"mask": [
"16",
0
]
},
"class_type": "MaskToImage",
"_meta": {
"title": "遮罩到图像"
}
},
"18": {
"inputs": {
"appName": "简笔画2",
"appType": "paint-board",
"appDesc": "",
"styles": ""
},
"class_type": "AppParams",
"_meta": {
"title": "应用参数管理"
}
}
}
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+2 -1
View File
@@ -496,8 +496,9 @@ async function addConvertToGroupOptions() {
const options = getNodeMenuOptions.apply(this, arguments);
if (!GroupNodeHandler.isGroupNode(node)&&node.type!='AppParams'&&node.widgets){
let toInput = [];
let wNames=node.inputs.filter(obj => obj.widget !== undefined && obj.link === null).map(obj => obj.name);
for (const w of node.widgets) {
if (w.options?.forceInput) {
if (w.options?.forceInput || !wNames.includes(w.name)) {
continue;
}
if (w.type !== CONVERTED_TYPE) {
+1 -1
View File
@@ -6,7 +6,7 @@ import {CUSTOM_INT, recursiveLinkUpstream, transformFunc, swapInputs,swapOutputs
app.registerExtension({
name: "Comfy.lam.MultiTextConcatenate",
async beforeRegisterNodeDef(nodeType, nodeData, app) {
var showNames=["IfInnerExecute",'MultiIntFormula','MultiParamFormula','ForInnerEnd','DoWhileEnd',"LamSwitcherCase"]
var showNames=["IfInnerExecute",'MultiIntFormula','MultiParamFormula','ForInnerEnd','DoWhileEnd',"LamSwitcherCase","LamCommonHidden"]
if (showNames.indexOf(nodeData.name)>=0) {
const onDrawForeground = nodeType.prototype.onDrawForeground;
let oldText=''
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+104
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@@ -0,0 +1,104 @@
from .src.utils.uitls import AlwaysEqualProxy,AlwaysTupleZero
import comfy.samplers
import base64
class LamCommonHidden:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"hidden": {
"hidden": ("STRING",{"multiline": True}), #隐藏参数
"unique_id": "UNIQUE_ID", #节点编号
"dynprompt": "DYNPROMPT",
"prompt": "PROMPT", #流程节点信息
"extra_pnginfo": "EXTRA_PNGINFO" #前端流程图信息
}
}
RETURN_TYPES = AlwaysTupleZero(AlwaysEqualProxy("*"),)
FUNCTION = "commm_hidden"
OUTPUT_NODE = True
CATEGORY = "lam"
def commm_hidden(self,hidden="",unique_id=None,extra_pnginfo=None,**kwargs):
if hidden=="":
hidden=[node['properties']['hidden'] for node in extra_pnginfo['workflow']['nodes'] if int(node['id'])==int(unique_id)][0]
lookup = {}
for arg in kwargs:
lookup[arg] = kwargs[arg]
msg='完成'
r=""
expand=None
if hidden:
hidden = base64.b64decode(hidden).decode("utf-8")
exec(hidden, lookup)
if 'result' in lookup:
r = lookup['result']
if "expand" in lookup:
expand = lookup['expand']
else:
raise SyntaxError("隐藏节点语法错误")
if not isinstance(r, tuple):
r = (r,)
return {"ui": {"value": [msg]}, "result": r,"expand":expand}
class LamSamplerName:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"tooltip": "The algorithm used when sampling, this can affect the quality, speed, and style of the generated output."})
}
}
RETURN_TYPES = (AlwaysEqualProxy("*"),)
RETURN_NAMES = ("sampler_name",)
FUNCTION = "sampler_name"
CATEGORY = "lam"
def sampler_name(self, sampler_name):
return (sampler_name,)
class LamScheduler:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"tooltip": "The scheduler controls how noise is gradually removed to form the image."})
}
}
RETURN_TYPES = (AlwaysEqualProxy("*"),)
RETURN_NAMES = ("scheduler",)
FUNCTION = "scheduler"
CATEGORY = "lam"
def scheduler(self, scheduler):
return (scheduler,)
NODE_CLASS_MAPPINGS = {
"LamCommonHidden": LamCommonHidden,
"LamSamplerName":LamSamplerName,
"LamScheduler": LamScheduler
}
NODE_DISPLAY_NAME_MAPPINGS = {
"LamCommonHidden": "通用隐藏节点",
"LamSamplerName": "采样器名称",
"LamScheduler": "调度器名称"
}