Extensions/ComfyUI-VOID
ComfyUI Extension

ComfyUI-VOID

ComfyUI nodes for VOID — Video Object and Interaction Deletion (netflix/void-model)

By shanef3d·Created 4 months ago·Updated 4 months ago· 0
shanef3d/ComfyUI-VOID
Nodes5
On cloudLocal install
CategoryVOID
Stars0
Updated4 months ago

Nodes (5)

VOID Inference
VOID
VOID Loader
VOID
VOID Load Text Encoder
VOID
VOID Load VAE
VOID
VOID Quadmask Builder
VOID
Readme

ComfyUI-VOID

A ComfyUI custom node pack for running VOID (Video Object and Interaction Deletion) inference directly inside ComfyUI workflows. VOID removes objects and their physical interactions — shadows, contact patches, reflections — from video clips using interaction-aware inpainting built on CogVideoX-Fun-V1.5-5b-InP.

VOID workflow

Nodes

| Node | Description | |---|---| | VOID Load VAE | Loads the CogVideoX-Fun 3D VAE from models/vae/. | | VOID Load Text Encoder | Loads the T5-XXL text encoder (fp8 supported) from models/clip/. | | VOID Loader | Loads both VOID transformer checkpoints and assembles the inference pipelines. | | VOID Inference | Runs Pass 1 base inpainting and optional Pass 2 warped-noise refinement. | | VOID Quadmask Builder | Compiles a VOID quadmask from SAM2 / SAM3 segmentation masks. |

Requirements

  • ComfyUI with the V3 node API (comfy_api.latest)
  • diffusers >= 0.33.1 — CogVideoX requires a newer version than ComfyUI ships by default
  • Python packages: see requirements.txt

Install dependencies:

pip install -r requirements.txt

Installation

  1. Clone this repository into your ComfyUI/custom_nodes/ directory:
cd ComfyUI/custom_nodes
git clone https://github.com/shanef3d/ComfyUI-VOID
  1. Restart ComfyUI. The VOID nodes will appear in the VOID category.

Model Weights

Download the following files manually and place them in the specified folders:

| Model | Source | File | Save to | |---|---|---|---| | CogVideoX VAE (~1.5 GB) | alibaba-pai/CogVideoX-Fun-V1.5-5b-InP | vae/diffusion_pytorch_model.safetensors | ComfyUI/models/vae/ | | T5-XXL text encoder (~5 GB, fp8) | Comfy-Org/flux1-dev | t5xxl_fp8_e4m3fn.safetensors | ComfyUI/models/clip/ | | VOID Pass 1 transformer (~10 GB) | netflix/void-model | void_pass1.safetensors | ComfyUI/models/void-model/ | | VOID Pass 2 transformer (~10 GB) | netflix/void-model | void_pass2.safetensors | ComfyUI/models/void-model/ |

The T5 tokenizer (~800 KB) is downloaded automatically from HuggingFace on first use and cached locally — no manual step required.

Typical Workflow

VHS Load Video ──────────────────────────────────────────────────┐
                                                                  ↓
SAM3 Video Segmentation → SAM3 Propagate → SAM3 Video Output → VOID Quadmask Builder
                                                                  ↓
VOID Load VAE ──────────────────┐                        VOID Inference
VOID Load Text Encoder ──────────┤→ VOID Loader →  Pass 1 output ──→ VHS Save Video
                                └────────────────→  Pass 2 output ──→ VHS Save Video

Mask generation uses ComfyUI-SAM3 — SAM3 Video Segmentation, SAM3 Propagate, and SAM3 Video Output nodes feed directly into VOID Quadmask Builder. SAM2-based mask nodes are also compatible.

Credits

License

MIT — see LICENSE.

The VOID model weights are released by Netflix under the Apache 2.0 License.