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electricty00-ComfyUI-Toggle…/example_workflows/Pose Reference Editing.json
T
GBrain af57d757eb feat: PoseReference node, sampler presets, model-type rename, auto clip_type rework, output reorder 
新增 / New
- PoseReference 节点：姿势素材库（线稿 / 深度两套）+ 节点内缩略图，选中素材以 data URI 内嵌进工作流
- 采样器「⚡预设」下拉：一键填 采样器/调度器/步数/CFG/Sigma曲线；预设表只有一份在 sampler.py，
  前端走 /toggle_pass/sampler_presets 拉取；手改任一参数自动退回「手动（不套用）」
- ToggleEmptyLatent 新增 latent类型（4 档：SD 4ch/8x、SD3-Flux-Krea2 16ch/8x、Qwen2.1 64ch/16x、Flux2 128ch/16x）
- DynamicRefImageEncode 新增专门的 negative 输出（内部编空文本），替代 ConditioningZeroOut

变更 / Changed
- 模型类型：SD / SDXL → SD / SDXL / Z-Image（前后端双层别名迁移，旧工作流自动改写）
- DynamicRefImageEncode 输出口顺序 → conditioning / negative / latent，老工作流按 link 类型自动迁移连线
- clip_type 从 14 项补到 40 项；auto 重做为「精确表 → MRO 继承链 → 前缀规则」三层
- CLIP 校验加固：手工表未登记的模型改问 model_config.clip_target()，覆盖 106/108 个模型类
- 统一加载器支持 FIBO 2.0 / MOSS-Image；采样器预设新增 FIBO 2.0 turbo（4步）

修复 / Fixed
- Krea2 的 reference_latents_method: index_timestep_zero → index（前者会把参考线稿「描」进画面）
- Krea2 参考图 latent fit 到出图网格
- 修正三处 Flux2 空 latent 的通道 / 尺寸（Ref Image Encode / OneImageMultiPrompt / Ref Independent）
- 广播：槽位小点点亮、端点圆点改到节点下层、修「紫线伸向空白处断掉」（零尺寸 boundingRect 误判）
- 输出口顺序迁移只在 onConfigure 跑一次太早（graph.links 要几百毫秒才建好）⇒ 改为阶梯重试，
  否则会出现「槽位改名了、连线没搬」

其他 / Misc
- 新增诊断命令 __tpAudit()：打印每条广播线两端坐标 / 归属节点 / 是否悬空
- 画布菜单新增「🔄 刷新姿势素材库」
- 移除示例 Krea2 Pose Editing (Ostris).json（硬依赖外部节点包且会换人）

版本 / Version
- 新增 pyproject.toml（ComfyUI-Manager / Registry 元数据入口），版本号 v1.0.0
- __init__.py 增加 __version__，启动打印 [Toggle-Pass] v1.0.0 loaded — 13 nodes
- README 顶部加版本标识
2026-11-07 21:29:09 +08:00

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{
"id": "92e0572f-4e3e-4173-9e4f-067267af190c",
"revision": 0,
"last_node_id": 9,
"last_link_id": 10,
"nodes": [
{
"id": 1,
"type": "UNETLoader",
"pos": [
60,
110
],
"size": [
270,
82
],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [
{
"localized_name": "UNet名称",
"name": "unet_name",
"type": "COMBO",
"widget": {
"name": "unet_name"
},
"link": null
},
{
"localized_name": "数据类型",
"name": "weight_dtype",
"type": "COMBO",
"widget": {
"name": "weight_dtype"
},
"link": null
}
],
"outputs": [
{
"localized_name": "模型",
"name": "MODEL",
"type": "MODEL",
"links": [
1
]
}
],
"properties": {
"ue_properties": {
"widget_ue_connectable": {},
"input_ue_unconnectable": {}
},
"cnr_id": "comfy-core",
"ver": "0.43.0",
"Node name for S&R": "UNETLoader"
},
"widgets_values": [
"Qwen\\qwen_image_2.1_turbo_int8_convrot.safetensors",
"default"
],
"widgets_values_named": {
"unet_name": "Qwen\\qwen_image_2.1_turbo_int8_convrot.safetensors",
"weight_dtype": "default"
}
},
{
"id": 2,
"type": "CLIPLoader",
"pos": [
60,
255
],
"size": [
270,
106
],
"flags": {},
"order": 1,
"mode": 0,
"inputs": [
{
"localized_name": "CLIP名称",
"name": "clip_name",
"type": "COMBO",
"widget": {
"name": "clip_name"
},
"link": null
},
{
"localized_name": "类型",
"name": "type",
"type": "COMBO",
"widget": {
"name": "type"
},
"link": null
},
{
"localized_name": "设备",
"name": "device",
"shape": 7,
"type": "COMBO",
"widget": {
"name": "device"
},
"link": null
}
],
"outputs": [
{
"localized_name": "CLIP",
"name": "CLIP",
"type": "CLIP",
"links": [
2
]
}
],
"properties": {
"ue_properties": {
"widget_ue_connectable": {},
"input_ue_unconnectable": {}
},
"cnr_id": "comfy-core",
"ver": "0.43.0",
"Node name for S&R": "CLIPLoader"
},
"widgets_values": [
"qwen\\qwen3vl_8b_int8_convrot.safetensors",
"qwen_image",
"default"
],
"widgets_values_named": {
"clip_name": "qwen\\qwen3vl_8b_int8_convrot.safetensors",
"type": "qwen_image",
"device": "default"
}
},
{
"id": 3,
"type": "VAELoader",
"pos": [
60,
435
],
"size": [
270,
58
],
"flags": {},
"order": 2,
"mode": 0,
"inputs": [
{
"localized_name": "vae名称",
"name": "vae_name",
"type": "COMBO",
"widget": {
"name": "vae_name"
},
"link": null
}
],
"outputs": [
{
"localized_name": "VAE",
"name": "VAE",
"type": "VAE",
"links": [
3,
4
]
}
],
"properties": {
"ue_properties": {
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},
"cnr_id": "comfy-core",
"ver": "0.43.0",
"Node name for S&R": "VAELoader"
},
"widgets_values": [
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],
"widgets_values_named": {
"vae_name": "qwen_image_2.1_vae_bf16.safetensors"
}
},
{
"id": 4,
"type": "PoseReference",
"pos": [
440,
90
],
"size": [
340,
300
],
"flags": {},
"order": 3,
"mode": 0,
"inputs": [
{
"localized_name": "category",
"name": "category",
"type": "COMBO",
"widget": {
"name": "category"
},
"link": null
},
{
"localized_name": "group",
"name": "group",
"type": "COMBO",
"widget": {
"name": "group"
},
"link": null
},
{
"localized_name": "pose",
"name": "pose",
"type": "COMBO",
"widget": {
"name": "pose"
},
"link": null
},
{
"localized_name": "view",
"name": "view",
"type": "COMBO",
"widget": {
"name": "view"
},
"link": null
},
{
"localized_name": "source",
"name": "source",
"shape": 7,
"type": "COMBO",
"widget": {
"name": "source"
},
"link": null
},
{
"localized_name": "long_edge",
"name": "long_edge",
"shape": 7,
"type": "INT",
"widget": {
"name": "long_edge"
},
"link": null
},
{
"localized_name": "flip",
"name": "flip",
"shape": 7,
"type": "COMBO",
"widget": {
"name": "flip"
},
"link": null
}
],
"outputs": [
{
"localized_name": "image",
"name": "image",
"type": "IMAGE",
"links": [
5
]
}
],
"properties": {
"ue_properties": {
"widget_ue_connectable": {},
"input_ue_unconnectable": {}
},
"aux_id": "electricty00/ComfyUI-Toggle-Pass",
"ver": "60665017a9f0f1fb0cb53714f294d7ccee961066",
"Node name for S&R": "PoseReference",
"tp_pose": {
"key": "全身单人・标准系|站姿|P019_站立・双臂上举伸展|斜侧|线稿",
"img": 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"
}
},
"widgets_values": [
"全身单人・标准系",
"站姿",
"P019_站立・双臂上举伸展",
"斜侧",
"线稿",
1024,
"关"
],
"widgets_values_named": {
"category": "全身单人・标准系",
"group": "站姿",
"pose": "P019_站立・双臂上举伸展",
"view": "斜侧",
"source": "线稿",
"long_edge": 1024,
"flip": "关"
}
},
{
"id": 5,
"type": "TextEncodeQwenImage21",
"pos": [
840,
90
],
"size": [
400,
226
],
"flags": {},
"order": 5,
"mode": 0,
"inputs": [
{
"localized_name": "clip",
"name": "clip",
"type": "CLIP",
"link": 2
},
{
"localized_name": "image_1",
"name": "images.image_1",
"shape": 7,
"type": "IMAGE",
"link": 5
},
{
"localized_name": "image_2",
"name": "images.image_2",
"shape": 7,
"type": "IMAGE",
"link": null
},
{
"localized_name": "vae",
"name": "vae",
"shape": 7,
"type": "VAE",
"link": 3
},
{
"localized_name": "prompt",
"name": "prompt",
"type": "STRING",
"widget": {
"name": "prompt"
},
"link": null
},
{
"localized_name": "negative_prompt",
"name": "negative_prompt",
"type": "STRING",
"widget": {
"name": "negative_prompt"
},
"link": null
},
{
"localized_name": "resolution",
"name": "resolution",
"type": "INT",
"widget": {
"name": "resolution"
},
"link": null
}
],
"outputs": [
{
"localized_name": "positive",
"name": "positive",
"type": "CONDITIONING",
"links": [
6
]
},
{
"localized_name": "negative",
"name": "negative",
"type": "CONDITIONING",
"links": [
7
]
},
{
"localized_name": "latent",
"name": "latent",
"type": "LATENT",
"links": [
8
]
}
],
"properties": {
"ue_properties": {
"widget_ue_connectable": {},
"input_ue_unconnectable": {}
},
"cnr_id": "comfy-core",
"ver": "0.43.0",
"Node name for S&R": "TextEncodeQwenImage21"
},
"widgets_values": [
"Render this pose reference into a photorealistic full-body photo of a young East Asian woman wearing a simple white dress, standing on a pure white studio background with soft even lighting. Keep her pose, body proportions and camera angle exactly as shown in the reference.",
"",
1024
],
"widgets_values_named": {
"prompt": "Render this pose reference into a photorealistic full-body photo of a young East Asian woman wearing a simple white dress, standing on a pure white studio background with soft even lighting. Keep her pose, body proportions and camera angle exactly as shown in the reference.",
"negative_prompt": "",
"resolution": 1024
}
},
{
"id": 6,
"type": "KSampler",
"pos": [
1230,
90
],
"size": [
270,
262
],
"flags": {},
"order": 6,
"mode": 0,
"inputs": [
{
"localized_name": "模型",
"name": "model",
"type": "MODEL",
"link": 1
},
{
"localized_name": "正面条件",
"name": "positive",
"type": "CONDITIONING",
"link": 6
},
{
"localized_name": "负面条件",
"name": "negative",
"type": "CONDITIONING",
"link": 7
},
{
"localized_name": "Latent图像",
"name": "latent_image",
"type": "LATENT",
"link": 8
},
{
"localized_name": "种子",
"name": "seed",
"type": "INT",
"widget": {
"name": "seed"
},
"link": null
},
{
"localized_name": "步数",
"name": "steps",
"type": "INT",
"widget": {
"name": "steps"
},
"link": null
},
{
"localized_name": "cfg",
"name": "cfg",
"type": "FLOAT",
"widget": {
"name": "cfg"
},
"link": null
},
{
"localized_name": "采样器名称",
"name": "sampler_name",
"type": "COMBO",
"widget": {
"name": "sampler_name"
},
"link": null
},
{
"localized_name": "调度器",
"name": "scheduler",
"type": "COMBO",
"widget": {
"name": "scheduler"
},
"link": null
},
{
"localized_name": "降噪",
"name": "denoise",
"type": "FLOAT",
"widget": {
"name": "denoise"
},
"link": null
}
],
"outputs": [
{
"localized_name": "Latent",
"name": "LATENT",
"type": "LATENT",
"links": [
9
]
}
],
"properties": {
"ue_properties": {
"widget_ue_connectable": {},
"input_ue_unconnectable": {}
},
"cnr_id": "comfy-core",
"ver": "0.43.0",
"Node name for S&R": "KSampler"
},
"widgets_values": [
20261102,
"fixed",
8,
1,
"euler",
"simple",
1
],
"widgets_values_named": {
"seed": 20261102,
"control_after_generate": "fixed",
"steps": 8,
"cfg": 1,
"sampler_name": "euler",
"scheduler": "simple",
"denoise": 1
}
},
{
"id": 7,
"type": "VAEDecode",
"pos": [
1510,
90
],
"size": [
230,
46
],
"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"localized_name": "Latent",
"name": "samples",
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},
{
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}
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{
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],
"outputs": [
{
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"name": "images",
"type": "IMAGE",
"links": null
}
],
"properties": {
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"cnr_id": "comfy-core",
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"widgets_values": [
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"widgets_values_named": {
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{
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"flags": {},
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"参考姿势 · 用姿势素材生成图片\n\n▸ 怎么用\n 1. 在「参考姿势」节点上选：类别 / 姿势组 / 姿势 / 视角（前三个联动）\n 2. 执行，节点上会直接画出选中的素材，先确认姿势对不对\n 3. 改 prompt 描述你要的画面（服装、背景、风格），执行\n\n▸ 源：线稿 / 深度\n 默认「线稿」。实测深度图 3/3 会自己补出不存在的鞋或护具\n （深度没有边界线，脚底和地面亮度太接近），线稿只有 1/3 有瑕疵。\n 深度唯一的优势是遮挡关系，肢体交叠复杂的姿势可以切过去试。\n\n▸ 长边 / 翻转\n 素材原始只有 300x400，「长边」默认放大到 1024。\n 「翻转」做左右镜像，反方向的姿势不用另找素材。\n\n▸ 换编辑模型\n 这个节点的输出是普通 IMAGE，直接把「参考姿势」接到别的编辑编码器的\n images 输入即可：\n · TextEncodeQwenImage21（当前用的，Qwen-Image-2.1）\n · TextEncodeFibo2（FIBO 2.0，记得 CLIPLoader 类型选 fibo2、VAE 换 flux2-vae）\n · TextEncodeQwenImageEditPlus / DynamicRefImageEncode 等\n 图片尺寸建议跟 model 的出图尺寸一致，不然模型会自己裁。\n\n▸ 参数\n Qwen-Image-2.1 turbo：steps 8 / cfg 1.0 / euler / simple / denoise 1.0\n 用文件\n unet: Qwen/qwen_image_2.1_turbo_int8_convrot.safetensors\n clip: qwen/qwen3vl_8b_int8_convrot.safetensors（类型 qwen_image）\n vae : qwen_image_2.1_vae_bf16.safetensors（64 通道，别选 qwen_image_vae）"
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"text": "参考姿势 · 用姿势素材生成图片\n\n▸ 怎么用\n 1. 在「参考姿势」节点上选：类别 / 姿势组 / 姿势 / 视角（前三个联动）\n 2. 执行，节点上会直接画出选中的素材，先确认姿势对不对\n 3. 改 prompt 描述你要的画面（服装、背景、风格），执行\n\n▸ 源：线稿 / 深度\n 默认「线稿」。实测深度图 3/3 会自己补出不存在的鞋或护具\n （深度没有边界线，脚底和地面亮度太接近），线稿只有 1/3 有瑕疵。\n 深度唯一的优势是遮挡关系，肢体交叠复杂的姿势可以切过去试。\n\n▸ 长边 / 翻转\n 素材原始只有 300x400，「长边」默认放大到 1024。\n 「翻转」做左右镜像，反方向的姿势不用另找素材。\n\n▸ 换编辑模型\n 这个节点的输出是普通 IMAGE，直接把「参考姿势」接到别的编辑编码器的\n images 输入即可：\n · TextEncodeQwenImage21（当前用的，Qwen-Image-2.1）\n · TextEncodeFibo2（FIBO 2.0，记得 CLIPLoader 类型选 fibo2、VAE 换 flux2-vae）\n · TextEncodeQwenImageEditPlus / DynamicRefImageEncode 等\n 图片尺寸建议跟 model 的出图尺寸一致，不然模型会自己裁。\n\n▸ 参数\n Qwen-Image-2.1 turbo：steps 8 / cfg 1.0 / euler / simple / denoise 1.0\n 用文件\n unet: Qwen/qwen_image_2.1_turbo_int8_convrot.safetensors\n clip: qwen/qwen3vl_8b_int8_convrot.safetensors（类型 qwen_image）\n vae : qwen_image_2.1_vae_bf16.safetensors（64 通道，别选 qwen_image_vae）"
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{
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"config": {},
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