> ## Documentation Index
> Fetch the complete documentation index at: https://dripart-docs-custom-nodes-sdk-v2-frontend.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# WanPhantomSubjectToVideo - ComfyUI Built-in Node Documentation

> The WanPhantomSubjectToVideo node prepares conditioning data and a latent for Wan video generation.

The WanPhantomSubjectToVideo node prepares conditioning data and a latent for Wan video generation. It creates an empty latent video from the requested width, height, length, and batch size, and, when reference images are supplied, encodes them with the VAE and adds them to the conditionings as time-dimensional visual guidance.

## Inputs

| Parameter    | Description                                                                    | Data Type    | Required | Range                 |
| ------------ | ------------------------------------------------------------------------------ | ------------ | -------- | --------------------- |
| `positive`   | Positive conditioning input for guiding video generation                       | CONDITIONING | Yes      | -                     |
| `negative`   | Negative conditioning input to avoid certain characteristics                   | CONDITIONING | Yes      | -                     |
| `vae`        | VAE model used to encode the reference images when they are provided           | VAE          | Yes      | -                     |
| `width`      | Output video width in pixels (default: 832, must be a multiple of 16)          | INT          | Yes      | 16 to MAX\_RESOLUTION |
| `height`     | Output video height in pixels (default: 480, must be a multiple of 16)         | INT          | Yes      | 16 to MAX\_RESOLUTION |
| `length`     | Number of frames in the generated video (default: 81, must be a multiple of 4) | INT          | Yes      | 1 to MAX\_RESOLUTION  |
| `batch_size` | Number of videos to generate simultaneously (default: 1)                       | INT          | Yes      | 1 to 4096             |
| `images`     | Optional reference images used as time-dimensional visual guidance             | IMAGE        | No       | -                     |

**Note:** When `images` are provided, they are automatically upscaled to match the specified `width` and `height`, and only the first `length` images are used for processing. Each image is encoded with the `vae` and concatenated along the time dimension, and only the RGB channels of each image are used.

## Outputs

| Output Name         | Description                                                                                                                                                              | Data Type    |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------ |
| `positive`          | Positive conditioning with time-dimensional concatenation of the encoded reference images when images are provided; otherwise the input `positive` is returned unchanged | CONDITIONING |
| `negative_text`     | Negative conditioning with time-dimensional concatenation of the encoded reference images when images are provided; otherwise the input `negative` is returned unchanged | CONDITIONING |
| `negative_img_text` | Negative conditioning with zeroed time-dimensional concatenation when images are provided; otherwise the input `negative` is returned unchanged                          | CONDITIONING |
| `latent`            | Zero-filled latent video tensor with 16 channels; its frame count is derived from `length` and its spatial dimensions from `height` and `width`                          | LATENT       |

> 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/WanPhantomSubjectToVideo/en.md)

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