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工作流 / 视频 / MiniMax H3 Fun ControlNet Union
MiniMax H3 Fun ControlNet Union

MiniMax H3 Fun ControlNet Union

MiniMax H3 Fun ControlNet Union

使用MiniMax-H3和ControlNet-Union检查点，从姿态参考视频生成视频，在应用提示词的同时保留输入的运动和结构。非常适合角色动画、运动迁移和编舞可视化项目。此工作流仅用于姿态控制。

视频 39 个节点 1 个输入 111 次使用 ComfyUI ≥ 0.35.0 ComfyUI 89 KB

下载工作流 JSON 查看官方来源

下载后把文件拖进 ComfyUI 窗口即可打开。

需要的权重

这个工作流引用了 8 个权重文件，其中 8 个能在本站模型库里找到。

minimax_h3_audio_vae_fp32.safetensors 在模型库查看
minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors 在模型库查看
minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors 在模型库查看
minimax_h3_ref2va_pruned_int8_convrot.safetensors 在模型库查看
minimax_h3_video_vae_int8_convrot.safetensors 在模型库查看
qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors 在模型库查看
rt_detr_v4-x-hgnet_fp16.safetensors 在模型库查看
sdpose_wholebody_fp16.safetensors 在模型库查看

节点构成

MarkdownNote × 6
VAELoader × 2
ComfySwitchNode × 2
PrimitiveInt × 2
PrimitiveBoolean × 2
ResolutionSelector × 1
VAEDecodeAudio × 1
VAEDecode × 1
KSamplerSelect × 1
BasicScheduler × 1
SamplerCustomAdvanced × 1
BasicGuider × 1
UNETLoader × 1
CLIPLoader × 1
RandomNoise × 1
CreateVideo × 1

官方标注的模型

MiniMax H3

工作流 JSON

和上面「下载工作流 JSON」是同一份文件。

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84 "## MiniMax H3 Fun ControlNet-Union\n\n[MiniMax-H3-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/MiniMax-H3-Fun-Controlnet-Union) is a single ControlNet-Union branch trained with VideoX-Fun. One checkpoint conditions MiniMax H3 on **Canny, Depth, HED, MLSD, or Pose** control video, and also runs **video inpainting**. Load it on top of a MiniMax H3 transformer (`fl2va` or `ref2va`).\n\nPackaged weights: [🤗 Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3) (`minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors`).\n\n## ComfyUI links\n- [ComfyUI#15224](https://github.com/Comfy-Org/ComfyUI/pull/15224) (MiniMax H3)\n- [ComfyUI#15975](https://github.com/Comfy-Org/ComfyUI/pull/15975) (Fun ControlNet as model patch)\n- [🤗 alibaba-pai/MiniMax-H3-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/MiniMax-H3-Fun-Controlnet-Union)\n- [🤗 Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)\n\n## About this workflow\n\nThis graph is a **Pose control** example only. The Union checkpoint can take Canny / Depth / HED / MLSD or an inpaint mask as well, but those paths are not wired here.\n\n**What this graph does**\n\n1. **Load Video (Control Video)** reads `dancer_field_pose.mp4`. Optional **Video Slice** trims the clip.\n2. **SDPose Video Pose Extractor [Multi-Person]** detects people and draws whole-body skeletons (body, hands, face, feet). That skeleton sequence is the control video, not the raw RGB footage.\n3. **Preview Image** shows the pose frames, then feeds them into **Apply MiniMax H3 Fun ControlNet** as `control_video`.\n4. **MiniMax H3 Reference to Video** builds text conditioning and the joint audio+video latent. In this demo the `ref_*` slots are empty, so the run is text-to-video locked to the pose. You can still attach reference images, videos, or audio if you want identity or voice lock on top of the control.\n5. Sampling and decode stay the same as other H3 templates: joint latent → video VAE + audio VAE → muxed MP4.\n\n**Apply MiniMax H3 Fun ControlNet**\n\n- **model_patch**: Fun ControlNet-Union from **ModelPatchLoader**\n- **vae**: MiniMax H3 **video** VAE (used to encode the control frames)\n- **control_video**: preprocessed frames. This template uses SDPose skeletons\n- **mask** / **source_video**: leave empty here. `mask` (1 = regenerate) plus optional `source_video` is the inpaint path\n- **strength**: how hard the control skip is added (same role as `control_context_scale` on the original model). `1.0` is strongest and is what this graph uses. Values below `1.0` loosen the pose. `0` turns the branch off\n- **start_percent** / **end_percent**: which part of sampling the control is active (`0` → `1` here)\n\n**Length and size**\n\n- Frames snap to the video VAE grid `17n + 5` at 24fps. This template uses **5s → 124 frames**. Cap is about 15 seconds\n- A control clip longer than `length` is taken from the start. A shorter clip holds its last frame\n- To match the control video length, use the bypassed group and wire `batch_size` into **MiniMax H3 Reference to Video** `length`\n\n**Prompt**\n\n[Guide here](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md)\n\n**Using the other Union modes**\n\nKeep **Apply MiniMax H3 Fun ControlNet** and swap only the preprocessor that writes `control_video`:\n\n- **Canny**: Detect Edges\n- **Depth**: Depth Anything 3 or MoGe\n- **Pose**: this graph (SDPose), or SAM3D Body\n- **HED / MLSD**: no built-in preprocessor; use a community pack if you need them\n- **Inpaint**: connect `mask` and optional `source_video`. `control_video` can stay empty or add extra structure\n\nSee the **Preparing the control video** note for official preprocessor tutorials.\n"
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86 "widgets_values_named": {
87 "text": "## MiniMax H3 Fun ControlNet-Union\n\n[MiniMax-H3-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/MiniMax-H3-Fun-Controlnet-Union) is a single ControlNet-Union branch trained with VideoX-Fun. One checkpoint conditions MiniMax H3 on **Canny, Depth, HED, MLSD, or Pose** control video, and also runs **video inpainting**. Load it on top of a MiniMax H3 transformer (`fl2va` or `ref2va`).\n\nPackaged weights: [🤗 Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3) (`minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors`).\n\n## ComfyUI links\n- [ComfyUI#15224](https://github.com/Comfy-Org/ComfyUI/pull/15224) (MiniMax H3)\n- [ComfyUI#15975](https://github.com/Comfy-Org/ComfyUI/pull/15975) (Fun ControlNet as model patch)\n- [🤗 alibaba-pai/MiniMax-H3-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/MiniMax-H3-Fun-Controlnet-Union)\n- [🤗 Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)\n\n## About this workflow\n\nThis graph is a **Pose control** example only. The Union checkpoint can take Canny / Depth / HED / MLSD or an inpaint mask as well, but those paths are not wired here.\n\n**What this graph does**\n\n1. **Load Video (Control Video)** reads `dancer_field_pose.mp4`. Optional **Video Slice** trims the clip.\n2. **SDPose Video Pose Extractor [Multi-Person]** detects people and draws whole-body skeletons (body, hands, face, feet). That skeleton sequence is the control video, not the raw RGB footage.\n3. **Preview Image** shows the pose frames, then feeds them into **Apply MiniMax H3 Fun ControlNet** as `control_video`.\n4. **MiniMax H3 Reference to Video** builds text conditioning and the joint audio+video latent. In this demo the `ref_*` slots are empty, so the run is text-to-video locked to the pose. You can still attach reference images, videos, or audio if you want identity or voice lock on top of the control.\n5. Sampling and decode stay the same as other H3 templates: joint latent → video VAE + audio VAE → muxed MP4.\n\n**Apply MiniMax H3 Fun ControlNet**\n\n- **model_patch**: Fun ControlNet-Union from **ModelPatchLoader**\n- **vae**: MiniMax H3 **video** VAE (used to encode the control frames)\n- **control_video**: preprocessed frames. This template uses SDPose skeletons\n- **mask** / **source_video**: leave empty here. `mask` (1 = regenerate) plus optional `source_video` is the inpaint path\n- **strength**: how hard the control skip is added (same role as `control_context_scale` on the original model). `1.0` is strongest and is what this graph uses. Values below `1.0` loosen the pose. `0` turns the branch off\n- **start_percent** / **end_percent**: which part of sampling the control is active (`0` → `1` here)\n\n**Length and size**\n\n- Frames snap to the video VAE grid `17n + 5` at 24fps. This template uses **5s → 124 frames**. Cap is about 15 seconds\n- A control clip longer than `length` is taken from the start. A shorter clip holds its last frame\n- To match the control video length, use the bypassed group and wire `batch_size` into **MiniMax H3 Reference to Video** `length`\n\n**Prompt**\n\n[Guide here](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md)\n\n**Using the other Union modes**\n\nKeep **Apply MiniMax H3 Fun ControlNet** and swap only the preprocessor that writes `control_video`:\n\n- **Canny**: Detect Edges\n- **Depth**: Depth Anything 3 or MoGe\n- **Pose**: this graph (SDPose), or SAM3D Body\n- **HED / MLSD**: no built-in preprocessor; use a community pack if you need them\n- **Inpaint**: connect `mask` and optional `source_video`. `control_video` can stay empty or add extra structure\n\nSee the **Preparing the control video** note for official preprocessor tutorials.\n"
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111 "## Input Asset\n\n- [dancer_field_pose.mp4](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/dancer_field_pose.mp4)\n\n## Model Links\n\n- [Hugging Face:Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)\n- [Hugging Face:Comfy-Org/SDPose](https://huggingface.co/Comfy-Org/SDPose)\n\n**ModelScope mirrors** (alternative repo location)\n\n- [ModelScope:Comfy-Org/MiniMax-H3](https://modelscope.cn/models/Comfy-Org/MiniMax-H3)\n- [ModelScope:Comfy-Org/SDPose](https://modelscope.cn/models/Comfy-Org/SDPose)\n\n**vae**\n\n- [minimax_h3_video_vae_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/vae/minimax_h3_video_vae_int8_convrot.safetensors) (2.62 GB)\n- [minimax_h3_audio_vae_fp32.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/vae/minimax_h3_audio_vae_fp32.safetensors) (577.2 MB)\n\n**diffusion_models**\n\n- [minimax_h3_ref2va_pruned_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/diffusion_models/minimax_h3_ref2va_pruned_int8_convrot.safetensors) (19.53 GB)\n- [rt_detr_v4-x-hgnet_fp16.safetensors](https://huggingface.co/Comfy-Org/SDPose/resolve/main/diffusion_models/rt_detr_v4-x-hgnet_fp16.safetensors) (118.2 MB)\n\n**text_encoders**\n\n- [qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors) (14.61 GB)\n\n**loras**\n\n- [minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/loras/minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors) (1.82 GB)\n\n**model_patches**\n\n- [minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/model_patches/minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors) (2.14 GB)\n\n**checkpoints**\n\n- [sdpose_wholebody_fp16.safetensors](https://huggingface.co/Comfy-Org/SDPose/resolve/main/checkpoints/sdpose_wholebody_fp16.safetensors) (1.79 GB)\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 vae/\n│ │ ├── minimax_h3_video_vae_int8_convrot.safetensors\n│ │ └── minimax_h3_audio_vae_fp32.safetensors\n│ ├── 📂 diffusion_models/\n│ │ ├── minimax_h3_ref2va_pruned_int8_convrot.safetensors\n│ │ └── rt_detr_v4-x-hgnet_fp16.safetensors\n│ ├── 📂 text_encoders/\n│ │ └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors\n│ ├── 📂 loras/\n│ │ └── minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors\n│ ├── 📂 model_patches/\n│ │ └── minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors\n│ └── 📂 checkpoints/\n│ └── sdpose_wholebody_fp16.safetensors\n```\n\n## Report Issue\n\nNote: Please update ComfyUI first ([guide](https://docs.comfy.org/installation/update_comfyui)) and prepare required models. Desktop/Cloud updates follow stable releases, so some nightly-supported models may not be available yet.\n\n- Cannot run / runtime errors: [ComfyUI/issues](https://github.com/comfyanonymous/ComfyUI/issues)\n- UI / frontend issues: [ComfyUI_frontend/issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)\n- Workflow issues: [workflow_templates/issues](https://github.com/Comfy-Org/workflow_templates/issues)\n"
112 ],
113 "widgets_values_named": {
114 "text": "## Input Asset\n\n- [dancer_field_pose.mp4](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/dancer_field_pose.mp4)\n\n## Model Links\n\n- [Hugging Face:Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)\n- [Hugging Face:Comfy-Org/SDPose](https://huggingface.co/Comfy-Org/SDPose)\n\n**ModelScope mirrors** (alternative repo location)\n\n- [ModelScope:Comfy-Org/MiniMax-H3](https://modelscope.cn/models/Comfy-Org/MiniMax-H3)\n- [ModelScope:Comfy-Org/SDPose](https://modelscope.cn/models/Comfy-Org/SDPose)\n\n**vae**\n\n- [minimax_h3_video_vae_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/vae/minimax_h3_video_vae_int8_convrot.safetensors) (2.62 GB)\n- [minimax_h3_audio_vae_fp32.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/vae/minimax_h3_audio_vae_fp32.safetensors) (577.2 MB)\n\n**diffusion_models**\n\n- [minimax_h3_ref2va_pruned_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/diffusion_models/minimax_h3_ref2va_pruned_int8_convrot.safetensors) (19.53 GB)\n- [rt_detr_v4-x-hgnet_fp16.safetensors](https://huggingface.co/Comfy-Org/SDPose/resolve/main/diffusion_models/rt_detr_v4-x-hgnet_fp16.safetensors) (118.2 MB)\n\n**text_encoders**\n\n- [qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors) (14.61 GB)\n\n**loras**\n\n- [minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/loras/minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors) (1.82 GB)\n\n**model_patches**\n\n- [minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/model_patches/minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors) (2.14 GB)\n\n**checkpoints**\n\n- [sdpose_wholebody_fp16.safetensors](https://huggingface.co/Comfy-Org/SDPose/resolve/main/checkpoints/sdpose_wholebody_fp16.safetensors) (1.79 GB)\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 vae/\n│ │ ├── minimax_h3_video_vae_int8_convrot.safetensors\n│ │ └── minimax_h3_audio_vae_fp32.safetensors\n│ ├── 📂 diffusion_models/\n│ │ ├── minimax_h3_ref2va_pruned_int8_convrot.safetensors\n│ │ └── rt_detr_v4-x-hgnet_fp16.safetensors\n│ ├── 📂 text_encoders/\n│ │ └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors\n│ ├── 📂 loras/\n│ │ └── minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors\n│ ├── 📂 model_patches/\n│ │ └── minimax_h3_fun_controlnet_union_pruned_int8_convrot.safetensors\n│ └── 📂 checkpoints/\n│ └── sdpose_wholebody_fp16.safetensors\n```\n\n## Report Issue\n\nNote: Please update ComfyUI first ([guide](https://docs.comfy.org/installation/update_comfyui)) and prepare required models. Desktop/Cloud updates follow stable releases, so some nightly-supported models may not be available yet.\n\n- Cannot run / runtime errors: [ComfyUI/issues](https://github.com/comfyanonymous/ComfyUI/issues)\n- UI / frontend issues: [ComfyUI_frontend/issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)\n- Workflow issues: [workflow_templates/issues](https://github.com/Comfy-Org/workflow_templates/issues)\n"
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1853 "## Preparing the control video with built-in preprocessing\n\nThe Fun ControlNet follows the control video you feed it, so the quality of that video's edges, depth or pose decides the quality of the control. ComfyUI ships with built-in preprocessing nodes, and each control type has an official tutorial:\n\n- **Edges (Canny)**: [Detect Edges (Canny) node](https://docs.comfy.org/built-in-nodes/Canny)\n- **Depth**: [Depth Anything 3 tutorial](https://docs.comfy.org/tutorials/utility/depth-anything-3) / [MoGe nodes](https://docs.comfy.org/built-in-nodes/MoGeInference)\n- **Pose**: [SAM3D Body tutorial](https://docs.comfy.org/tutorials/utility/sam3d-body) / [SDPose Keypoint Extractor](https://docs.comfy.org/built-in-nodes/SDPoseKeypointExtractor)\n- **All preprocessors overview**: [ComfyUI preprocessor workflows](https://docs.comfy.org/tutorials/utility/preprocessors)\n\n**Mask / segmentation (for inpainting mode)**:\n- [SAM3 video segmentation tutorial](https://docs.comfy.org/tutorials/utility/video-segment-sam3)\n\nNote: HED and MLSD have no built-in preprocessing nodes. Canny, Depth and Pose cover most use cases; install a community pack if you need the others."
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