{ "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": { "widget_ue_connectable": {}, "input_ue_unconnectable": {} }, "cnr_id": "comfy-core", "ver": "0.43.0", "Node name for S&R": "VAELoader" }, "widgets_values": [ "qwen_image_2.1_vae_bf16.safetensors" ], "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": "data:image/webp;base64,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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", "type": "LATENT", "link": 9 }, { "localized_name": "vae", "name": "vae", "type": "VAE", "link": 4 } ], "outputs": [ { "localized_name": "图像", "name": "IMAGE", "type": "IMAGE", "links": [ 10 ] } ], "properties": { "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {} }, "cnr_id": "comfy-core", "ver": "0.43.0", "Node name for S&R": "VAEDecode" } }, { "id": 8, "type": "SaveImage", "pos": [ 1750, 90 ], "size": [ 270, 58 ], "flags": {}, "order": 8, "mode": 0, "inputs": [ { "localized_name": "图片", "name": "images", "type": "IMAGE", "link": 10 }, { "localized_name": "文件名前缀", "name": "filename_prefix", "type": "STRING", "widget": { "name": "filename_prefix" }, "link": null } ], "outputs": [ { "localized_name": "images", "name": "images", "type": "IMAGE", "links": null } ], "properties": { "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {} }, "cnr_id": "comfy-core", "ver": "0.43.0", "Node name for S&R": "SaveImage" }, "widgets_values": [ "pose_qwen" ], "widgets_values_named": { "filename_prefix": "pose_qwen" } }, { "id": 9, "type": "Note", "pos": [ 440, 620 ], "size": [ 980, 400 ], "flags": {}, "order": 4, "mode": 0, "inputs": [], "outputs": [], "properties": {}, "widgets_values": [ "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)" ], "widgets_values_named": { "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)" }, "color": "#432", "bgcolor": "#653" } ], "links": [ [ 1, 1, 0, 6, 0, "MODEL" ], [ 4, 3, 0, 7, 1, "VAE" ], [ 2, 2, 0, 5, 0, "CLIP" ], [ 5, 4, 0, 5, 1, "IMAGE" ], [ 3, 3, 0, 5, 3, "VAE" ], [ 6, 5, 0, 6, 1, "CONDITIONING" ], [ 7, 5, 1, 6, 2, "CONDITIONING" ], [ 8, 5, 2, 6, 3, "LATENT" ], [ 9, 6, 0, 7, 0, "LATENT" ], [ 10, 7, 0, 8, 0, "IMAGE" ] ], "groups": [ { "id": 1, "title": "加载模型", "bounding": [ 20, 50, 330, 490 ], "color": "#3f789e", "flags": {} }, { "id": 2, "title": "参考姿势 → 出图", "bounding": [ 410, 50, 1580, 440 ], "color": "#8a6d3b", "flags": {} } ], "config": {}, "extra": { "ds": { "scale": 0.62, "offset": [ 60, 80 ] } }, "version": 0.4 }