Inputs
| Parameter | Description | Data Type | Required | Range |
|---|---|---|---|---|
positive | Positive conditioning input for guiding the video generation | CONDITIONING | Yes | - |
negative | Negative conditioning input for guiding the video generation | CONDITIONING | Yes | - |
vae | VAE model used for encoding images to latent space | 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 sequence (default: 81, step: 4) | INT | Yes | 1 to MAX_RESOLUTION |
batch_size | Number of video sequences to generate (default: 1) | INT | Yes | 1 to 4096 |
ref_image | Optional reference image for providing visual guidance | IMAGE | No | - |
control_video | Optional control video for guiding the generation process | IMAGE | No | - |
length parameter is processed in chunks of 4 frames, and the node automatically handles temporal scaling for the latent space. When ref_image is provided, it influences the conditioning through reference latents. When control_video is provided, it directly affects the concat latent representation used in conditioning. The start_image parameter is not exposed as an input in this node’s schema but is referenced in the execution logic.
Outputs
| Output Name | Description | Data Type |
|---|---|---|
positive | Modified positive conditioning with video-specific latent data including concat latent, mask, and optional reference latents | CONDITIONING |
negative | Modified negative conditioning with video-specific latent data including concat latent, mask, and optional reference latents | CONDITIONING |
latent | Empty latent tensor with appropriate dimensions for video generation based on batch size, latent channels, and spatial/temporal scaling | LATENT |
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