ComfyUI > Nodes > ComfyUI Wan VACE Prep

ComfyUI Extension: ComfyUI Wan VACE Prep

Repo Name

ComfyUI-Wan-VACE-Prep

Author
stuttlepress (Account age: 597 days)
Nodes
View all nodes(8)
Latest Updated
2026-03-31
Github Stars
0.03K

How to Install ComfyUI Wan VACE Prep

Install this extension via the ComfyUI Manager by searching for ComfyUI Wan VACE Prep
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter ComfyUI Wan VACE Prep in the search bar
After installation, click the Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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ComfyUI Wan VACE Prep Description

ComfyUI Wan VACE Prep is a ComfyUI node designed to create a VACE control video and mask, facilitating seamless transitions between two videos.

ComfyUI-Wan-VACE-Prep Introduction

ComfyUI-Wan-VACE-Prep is an extension designed to enhance video editing workflows by providing specialized nodes for video and mask creation, particularly for transitions and extensions. This extension is particularly useful for AI artists who want to create smooth transitions between video clips or extend video sequences seamlessly. By using ComfyUI-Wan-VACE-Prep, you can automate and simplify the process of joining video clips, managing transitions, and handling batch video processing, all while maintaining high-quality outputs.

How ComfyUI-Wan-VACE-Prep Works

At its core, ComfyUI-Wan-VACE-Prep leverages the VACE (Video and Contextual Editing) model to facilitate video transitions and extensions. The extension works by using context frames from the edges of video clips to guide the generation of new frames, ensuring smooth transitions. It discards and regenerates frames at the transition edges, creating a blend zone that seamlessly connects two video clips. This process is akin to stitching two pieces of fabric together, where the context frames act as the thread that binds them.

ComfyUI-Wan-VACE-Prep Features

VACE Join

This feature allows you to join two video clips smoothly. It uses context frames from each clip to guide the transition, ensuring a seamless blend. You can customize parameters such as the number of context frames, replace frames, and new frames to control the transition's smoothness and duration.

VACE Join (Batch)

Ideal for processing multiple video pairs, this batch-aware version of VACE Join handles edge cases for the first and last iterations. It allows you to process large collections of video clips efficiently.

VACE Batch Context

This node is essential for batch video processing workflows, managing file paths and iteration tracking. It supports a loop mode for creating seamless looping videos by pairing the last video with the first.

VACE Extend

Extend a video from any frame position using context frames to build a VACE control video. This feature is perfect for adding new content to the end of a video clip.

Load Videos From Folder (Simple)

Load and concatenate videos from a folder into a single image batch. This feature is useful for handling large video collections without running out of system memory.

Visual Frame Selector

An interactive tool for selecting specific frame ranges within a video. It provides a visual scrubber and transport controls, making it easy to choose frames for further processing.

VACE Inline

This node allows you to regenerate a specific section of a single video using VACE, without manually splitting the clip. It's perfect for smoothing or enhancing particular video segments.

ComfyUI-Wan-VACE-Prep Models

ComfyUI-Wan-VACE-Prep supports various models that enhance its functionality. These include:

  • Wan 2.2 Fun VACE: Available in bf16, fp8, and GGUF formats, this model is ideal for generating fun and creative video transitions.
  • Wan 2.1 VACE: Available in fp16 and GGUF formats, this model is suitable for more traditional video editing tasks.
  • Kijai’s Fun Vace 2.2 Modules: These modules can be used alongside standard T2V models for additional flexibility.

Troubleshooting ComfyUI-Wan-VACE-Prep

Here are some common issues and solutions:

  • Tensor Size Mismatch: Ensure your input video dimensions are divisible by 16.
  • Brightness/Color Shift: This can occur due to the VACE model's inherent characteristics. Consider using a color match node or interpolating the framerate to mitigate this effect.
  • Framerate Issues: The Wan models are optimized for 16 fps. Adjust your context and replace frames accordingly if your input videos have a higher framerate.
  • Workflow Errors: If you encounter issues, try updating ComfyUI or check for missing dependencies.

Learn More about ComfyUI-Wan-VACE-Prep

For further assistance and resources, consider exploring the following:

  • ComfyUI-Wan-VACE-Video-Joiner GitHub for related workflows.
  • CivitAI for model downloads and discussions.
  • Community forums and GitHub issues for troubleshooting and support. By utilizing these resources, you can enhance your understanding and usage of ComfyUI-Wan-VACE-Prep, making your video editing projects more efficient and creative.

ComfyUI Wan VACE Prep Related Nodes

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RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Models, enabling artists to harness the latest AI tools to create incredible art.

ComfyUI Wan VACE Prep detailed guide | ComfyUI