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1.6 KiB
1.6 KiB
HunyuanVideo15ImageToVideo
Category: conditioning/video_models
Display Name: positive
Description
This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub
The HunyuanVideo15ImageToVideo node prepares conditioning and latent space data for video generation based on the HunyuanVideo 1.5 model. It creates an initial latent representation for a video sequence and can optionally integrate a starting image or a CLIP vision output to guide the generation process.
Inputs
| Parameter | Type | Default | Description |
|---|---|---|---|
| positive | Conditioning | — | |
| negative | Conditioning | — | |
| vae | Vae | — | |
| width | Int | 848 | |
| height | Int | 480 | |
| length | Int | 33 | |
| batch_size | Int | 1 | |
| start_image | Image | — | |
| clip_vision_output | ClipVisionOutput | — |
Outputs
| Output Name | Data Type | Description |
|---|---|---|
positive |
CONDITIONING | The modified positive conditioning, which may now include the encoded starting image or CLIP vision output. |
negative |
CONDITIONING | The modified negative conditioning, which may now include the encoded starting image or CLIP vision output. |
latent |
LATENT | An empty latent tensor with dimensions configured for the specified batch size, video length, width, and height. |
Source: comfy_extras/nodes_hunyuan.py
Used in 1 template(s)