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工作流 / 视频 / Bernini-R：视频编辑
Bernini-R：视频编辑

Bernini-R：视频编辑

Bernini-R: Video Edit

使用 Bernini-R 生成一致重新照明的编辑视频。非常适合肖像和产品重新照明、电子商务目录摄影以及在照片集中创建一致的照明。

视频 12 个节点 2 个输入 298 次使用 ComfyUI ≥ 0.25.0 ComfyUI 104 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 5 个权重文件，其中 5 个能在本站模型库里找到。

Wan2_1_VAE_bf16.safetensors 在模型库查看
lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors 在模型库查看
umt5_xxl_fp8_e4m3fn_scaled.safetensors 在模型库查看
wan2.2_bernini_r_high_noise_fp8_scaled.safetensors 在模型库查看
wan2.2_bernini_r_low_noise_fp8_scaled.safetensors 在模型库查看

节点构成

MarkdownNote × 3
LoadVideo × 1
SaveVideo × 1
BatchImagesNode × 1
LoadImage × 1
Video Slice × 1
GetVideoComponents × 1
GetImageSize × 1
PreviewAny × 1
69c3c422-bcfe-4955-bc23-8bac307287a8 × 1

官方标注的模型

Bernini-R

工作流 JSON

和上面「下载工作流 JSON」是同一份文件。

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109 "## Bernini-R · Video Editing Workflow\n\n**Official repos**\n- Inference & task docs: [bytedance/Bernini](https://github.com/bytedance/Bernini)\n- Bernini-R weights (ComfyUI): [Comfy-Org/Bernini-R](https://huggingface.co/Comfy-Org/Bernini-R)\n- Paper: [Bernini: Latent Semantic Planning for Video Diffusion](https://arxiv.org/abs/2605.22344)\n\n---\n\n### What is this workflow?\n\nBuilt for **Bernini-R video editing** in ComfyUI: **source video** + optional **reference image(s)** / **reference video** → pick **task type** → write prompt → run.\n\nBernini-R is ByteDance's **renderer-only** Wan 2.2 model (in-context conditioning). It does **not** include the full Bernini MLLM planner. For official-quality long prompts, see `--use_pe` in the [Bernini repo](https://github.com/bytedance/Bernini).\n\n| Task | What to connect |\n|------|-----------------|\n| Text to Video | No media |\n| Video Editing (`v2v`, `mv2v`) | `source_video` only |\n| Reference to Video (`r2v`) | `reference_image(s)` only |\n| **Video Editing with Reference (`rv2v`)** | `source_video` + `reference_image(s)` — **outfit / look swap** |\n| Ads / Content Insertion (`ads2v`) | `source_video` + `reference_video` |\n\n**Prompt format:** `{system prompt from task type}` + `{your English description}` via **Prompt Construction**.\n\n---\n\n### Inputs: source video, reference images, reference video\n\n**`source_video` (required for most edits)**\n- The clip to edit (canvas). Loaded via **Load Video** → subgraph `source_video`.\n- Resized to **`width × height`** and trimmed to **`length`** frames.\n- Match output size to your clip (e.g. portrait **832 × 1104**, landscape **848 × 480**). Both dimensions should be **multiples of 16**.\n\n**`reference_image(s)` (optional — group: Reference Image input)**\n- Used for **`rv2v`** (edit guided by refs), **`r2v`** (refs only), or multi-item outfits.\n- Each image is encoded as a **separate in-context stream**; long edge capped by **`ref_max_size`** (default **848**), **aspect ratio preserved**.\n- **How to wire:** put one or more **Load Image** nodes into **Batch Images** (`image0`, `image1`, …) → connect **Batch Images → IMAGE** to the subgraph input **`reference_image`**.\n- **Multi-image tips:** e.g. flat-lay coat + pants + boots on separate Load Image slots; in prompt use **image0, image1, …** (order = batch / slot order). Official training supports ~**5** reference streams reliably; the node allows up to **8** slots inside the graph.\n- **Not** resized to full canvas — only long-edge limited (unlike `source_video`).\n\n**`reference_video` (optional)**\n- Used for **`ads2v`** — content to **insert into** the source scene (moving clip, screen content, etc.).\n- Connect a **second video** (often **Load Video → Get Video Components → images**) to subgraph **`reference_video`**, or feed frame sequence as IMAGE.\n- Same **`ref_max_size`** / aspect rules as reference images; trimmed to **`length`** frames.\n- Prompt can be short: *Add the video on the computer.*\n\nLeave unused inputs **disconnected** for tasks that do not need them.\n\n---\n\n### Turbo mode (`enable_turbo_mode`)\n\n**Turbo = fast preview / iteration**, not the official Bernini-R sampling recipe.\n\n| | **Turbo ON** (default) | **Turbo OFF** (Original settings) |\n|--|------------------------|-----------------------------------|\n| **LightX2V distill LoRA** | ON (high noise **3.0**, low noise **1.5**) | OFF (pure Bernini-R weights) |\n| **Total steps** | **6** | **40** (official default) |\n| **High / low split** | **3** / **3** | **20** / **20** |\n| **CFG** | **1** | **5** |\n\nTurbo is much **faster** and lighter on VRAM, but **quality and edit fidelity** are usually below official **40-step** inference (which also uses APG guidance in Python — not fully replicated here). Use Turbo to test prompts and wiring; turn **Turbo OFF** for final exports or difficult edits (outfit swap, fine detail).\n\nToggle **`enable_turbo_mode`** on the main subgraph widget (or **Boolean Enable Turbo LoRA?** inside the graph).\n\nOfficial defaults reference: [gradio_demo.py](https://github.com/bytedance/Bernini/blob/main/gradio_demo.py)\n\n---\n\n### Recommended resolution & length\n\n| Setting | Recommended |\n|---------|-------------|\n| **width × height** | **848 × 480** or **832 × 480** (landscape); match source aspect for portrait |\n| **ref_max_size** | **848** (raise to **1280** for 720p experiments) |\n| **length** | **81** frames @ 16 fps; must be **4n+1** |\n\nNegative prompt: Wan 2.2 **Chinese default** in `bernini/cli.py`.\n\n---\n\n### Task types & prompt examples\n\nEdits: **what to change** + **what stays unchanged**.\n\n- **`rv2v` (outfit swap):** *Remove the hat. Replace the person's clothing with the full outfit from the reference image … Keep pose, framing, lighting, background, and motion unchanged.*\n- **`v2v`:** *Add a snowman on the right … Keep the dog, road, and scene unchanged.*\n- **`mv2v`:** *Change the person's motion to crouch … preserving framing and background.*\n- **`ads2v`:** *Add the video on the computer.*\n- **`r2v`:** *The subject from image0 wearing items from image1 and image2 …*\n\nMore: [assets/testcases/](https://github.com/bytedance/Bernini/tree/main/assets/testcases/)\n\n---\n\n### Capability notes\n\n**Strengths:** video edit, reference-guided edit, outfit swap (`rv2v`), content insertion (`ads2v`), reference-to-video (`r2v`).\n\n**Limits:** no Bernini planner; Turbo ≠ official 40-step APG; long / 720p needs more VRAM; flat-lay outfit refs are harder than on-person reference photos.\n"
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129 "outputs": [],
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133 "Guide: [Subgraph](https://docs.comfy.org/interface/features/subgraph)\n\n## Model Links\n\n- [Hugging Face:Comfy-Org/Wan_2.1_ComfyUI_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged)\n- [ModelScope:Comfy-Org/Wan_2.1_ComfyUI_repackaged](https://modelscope.cn/models/Comfy-Org/Wan_2.1_ComfyUI_repackaged)\n- [Hugging Face:Comfy-Org/Bernini-R](https://huggingface.co/Comfy-Org/Bernini-R)\n- [ModelScope:Comfy-Org/Bernini-R](https://modelscope.cn/models/Comfy-Org/Bernini-R)\n\n**text_encoders**\n\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true) (6.27 GB)\n\n**vae**\n\n- [Wan2_1_VAE_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/resolve/main/Wan2_1_VAE_bf16.safetensors?download=true) (242 MB)\n\n**loras**\n\n- [lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/resolve/main/Lightx2v/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors?download=true) (601.5 MB)\n\n**diffusion_models**\n\n- [wan2.2_bernini_r_high_noise_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Bernini-R/resolve/main/diffusion_models/wan2.2_bernini_r_high_noise_fp8_scaled.safetensors) (14.51 GB)\n- [wan2.2_bernini_r_low_noise_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Bernini-R/resolve/main/diffusion_models/wan2.2_bernini_r_low_noise_fp8_scaled.safetensors) (14.51 GB)\n\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 text_encoders/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 vae/\n│ │ └── Wan2_1_VAE_bf16.safetensors\n│ ├── 📂 loras/\n│ │ └── lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors\n│ └── 📂 diffusion_models/\n│ ├── wan2.2_bernini_r_high_noise_fp8_scaled.safetensors\n│ └── wan2.2_bernini_r_low_noise_fp8_scaled.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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