> ## Documentation Index
> Fetch the complete documentation index at: https://dripart-comfy-docs-comfyapi-search.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# WanVaceToVideo - ComfyUI Built-in Node Documentation

> The WanVaceToVideo node prepares video conditioning data for VACE-controlled video generation models.

The WanVaceToVideo node prepares video conditioning data for VACE-controlled video generation models. It combines positive and negative conditioning with an optional control video, control masks, and a reference image, encodes them through a VAE, and outputs updated conditioning, an empty latent tensor, and a trim value.

## Inputs

| Parameter         | Description                                                                                                                                            | Data Type    | Required | Range                 |
| ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------ | -------- | --------------------- |
| `positive`        | Positive conditioning input for guiding the generation                                                                                                 | CONDITIONING | Yes      | -                     |
| `negative`        | Negative conditioning input for guiding the generation                                                                                                 | CONDITIONING | Yes      | -                     |
| `vae`             | VAE model used for encoding images and video frames                                                                                                    | VAE          | Yes      | -                     |
| `width`           | Output video width in pixels (default: 832, step: 16)                                                                                                  | INT          | Yes      | 16 to MAX\_RESOLUTION |
| `height`          | Output video height in pixels (default: 480, step: 16)                                                                                                 | INT          | Yes      | 16 to MAX\_RESOLUTION |
| `length`          | Number of frames in the video (default: 81, step: 4)                                                                                                   | INT          | Yes      | 1 to MAX\_RESOLUTION  |
| `batch_size`      | Number of videos to generate simultaneously (default: 1)                                                                                               | INT          | Yes      | 1 to 4096             |
| `strength`        | Condition strength for VACE control (default: 1.0, step: 0.01). This is not a LoRA strength. LoRA weights are applied through separate LoRA nodes.     | FLOAT        | Yes      | 0.0 to 1000.0         |
| `control_video`   | Optional input video used for control conditioning. If not provided, a neutral gray video is created automatically.                                    | IMAGE        | No       | -                     |
| `control_masks`   | Optional masks that determine which parts of the control video are active. If not provided, a full white mask is used.                                 | MASK         | No       | -                     |
| `reference_image` | Optional reference image for additional conditioning. When provided, it is encoded and prepended to the latent sequence. Only the first image is used. | IMAGE        | No       | -                     |

**Note:** When `control_video` is provided, it is truncated to `length` frames and upscaled to the specified `width` and `height`; if it has fewer frames than `length`, the missing frames are padded with neutral gray (value 0.5). When it is not provided, a neutral gray video of `length` frames is created automatically. `control_masks` are upscaled to the specified `width` and `height`, truncated to `length` frames, and padded with value 1.0 if shorter. The mask separates the control video into inactive and reactive parts, each VAE-encoded and concatenated along the channel dimension; the mask is also downsampled to latent resolution. When `reference_image` is provided, its first image is VAE-encoded and prepended to the latent sequence, and `trim_latent` reports the number of latent frames added. The latent frame count is calculated as `((length - 1) // 4) + 1`, and the latent spatial dimensions are `height / 8` and `width / 8`.

## Outputs

| Output Name   | Description                                                                                                     | Data Type    |
| ------------- | --------------------------------------------------------------------------------------------------------------- | ------------ |
| `positive`    | Positive conditioning with video control data (vace\_frames, vace\_mask, vace\_strength) applied                | CONDITIONING |
| `negative`    | Negative conditioning with video control data (vace\_frames, vace\_mask, vace\_strength) applied                | CONDITIONING |
| `latent`      | Empty latent tensor ready for video generation with shape \[batch\_size, 16, latent\_length, height/8, width/8] | LATENT       |
| `trim_latent` | Number of latent frames to trim when a reference image is used; 0 if no reference image is provided             | INT          |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanVaceToVideo/en.md)

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