MatAnyone2 Video Matting for ComfyUI

Interactive video matting inside ComfyUI with a built-in SAM point editor and MatAnyone2 propagation. Queue once to open the editor on the first frame, queue again to render a clean foreground pass, alpha matte, and preview composite across the full clip.

Features

• Two-pass interactive workflow: fast first queue to open the editor, full second queue to render the matte.
• Built-in SAM overlay: positive and negative point editing happens directly in ComfyUI.
• Multi-target masking: create and compare multiple mask targets before committing.
• Pinned vendor snapshots: the package ships known-good MatAnyone2 and Segment Anything source snapshots in vendor/.
• Bundled starter clip: the sample workflow ships with a tiny demo video that install.py copies into ComfyUI/input/.
• Manager-ready packaging: requirements.txt, install.py, workflow example, and registry metadata are all included.

Installation

ComfyUI Manager

Search for MatAnyone2 Video Matting or MatAnyone2 in ComfyUI Manager and install the latest stable version.

Registry page: registry.comfy.org/nodes/matanyone2-video-matting

Manager will:

1. Install Python dependencies from requirements.txt
2. Run install.py to validate the bundled vendor snapshots and copy matanyone2-demo-input.mp4 into ComfyUI/input/
3. Ask for a ComfyUI restart

Manual Install

cd ComfyUI/custom_nodes
git clone https://github.com/dreamrec/MatAnyone2_ComfyUI.git
cd MatAnyone2_ComfyUI
python -m pip install -r requirements.txt
python install.py

Restart ComfyUI after installation.

Companion Node for the Demo Workflow

The bundled workflow uses ComfyUI-VideoHelperSuite for video input and output.

Models

Models download automatically on first use if they are missing.

| Model | Default location | Auto-download | |------|------|------| | MatAnyone2 checkpoint | ComfyUI/models/matanyone/ | Yes | | SAM ViT-H | ComfyUI/models/sams/ | Yes | | SAM ViT-L | ComfyUI/models/sams/ | Yes | | SAM ViT-B | ComfyUI/models/sams/ | Yes |

Included Workflows

Basic Demo

workflows/matanyone2_demo.json is a ready-to-run example that wires video loading, frame selection, the interactive editor, and final matte export.

It defaults to the bundled matanyone2-demo-input.mp4 starter clip that install.py copies into ComfyUI/input/. Swap the Load Video node to your own footage whenever you are ready.

LoadVideo -> SliceFrames -> SelectFrame -> Interactive SAM -> Matte -> SaveVideo x3

How to use it:

1. Drag workflows/matanyone2_demo.json onto the ComfyUI canvas.
2. Queue once on the bundled starter clip, or replace Load Video with your own clip first.
3. Queue once to open the editor on the first frame.
4. Left-click for foreground points and right-click for background points.
5. Click Apply in the editor.
6. Queue again to render the full matte outputs.

Extended Demo (All 12 Nodes)

workflows/matanyone2_extended_demo.json showcases every node in the pack with two parallel paths:

Interactive path (top) — the same editor-based flow from the basic demo.

Scripted/programmatic path (bottom) — builds SAM prompts entirely in-node, no editor needed:

SAM Loader ──────────────────────────────────────────────────────┐
                                                                 │
Prompt Start → Add Point (+) → Add Point (-) → SAM Refine ──→ Merge Masks → Matte
                                                     ↑              ↑
Prompt From Text ─────────────────────→ SAM Refine ──┘    Preview Masks

This workflow demonstrates how to use SAM Loader, Prompt Start, Add Point, Prompt From Text, SAM Refine, Merge Masks, and Preview Masks for scripted or batch matting without the interactive editor.

Gallery

Real workflow + editor capture from the live node pack:

Node Overview

Nodes are grouped under MatAnyone2 and MatAnyone2/SAM in the Add Node menu.

| Node | What it does | |------|------| | MatAnyone2 Model Loader | Loads MatAnyone or MatAnyone2 checkpoints | | MatAnyone2 SAM Loader | Loads a SAM checkpoint for programmatic refinement | | MatAnyone2 Slice Frames | Splits a video image batch into frame data | | MatAnyone2 Select Frame | Pulls a single frame for interactive setup | | MatAnyone2 Prompt Start | Creates an empty point prompt structure | | MatAnyone2 Prompt From Text | Builds prompts from text coordinates | | MatAnyone2 Add Point | Adds foreground or background points in-node | | MatAnyone2 SAM Refine | Runs SAM refinement with explicit prompts | | MatAnyone2 Merge Masks | Merges up to four masks into one | | MatAnyone2 Preview Masks | Draws mask overlays on the source frame | | MatAnyone2 Interactive SAM | Launches the built-in multi-target editor | | MatAnyone2 Matte | Propagates the first-frame mask through the whole clip |

Requirements

• ComfyUI with Python 3.10+
• PyTorch with CUDA, MPS, or CPU support
• 8 GB VRAM minimum, 12+ GB recommended for longer or higher-resolution clips
• Internet access on first run if you want automatic model downloads

Troubleshooting

• If the editor does not open, queue the workflow once so the first-frame preview exists.
• If the demo workflow shows missing video nodes, install VideoHelperSuite first.
• If Load Video is blank or points at /input/, rerun install.py so the bundled demo clip is copied into ComfyUI/input/, or choose your own video in the VHS node before queueing.
• If ComfyUI Manager shows a security warning for network access, you are likely on an older registry build from before the vendor sources were bundled directly in the package.
• If VRAM is tight, use a smaller SAM variant and lower max_internal_size.
• If you already keep checkpoints elsewhere, pass an explicit checkpoint_path to the loader nodes.

Credits

• MatAnyone2 for the video matting model
• Segment Anything for interactive segmentation
• ComfyUI for the host runtime

License

This repository is licensed under GPL-3.0.

Vendored upstream dependencies keep their own licenses:

• MatAnyone2: Apache-2.0
• Segment Anything: Apache-2.0

┌─────────────────────────────────────────────────────────────────────┐
│ dreamrec // MatAnyone2 // queue once, edit, queue again            │
└─────────────────────────────────────────────────────────────────────┘