Documentation Index
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This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHubThe LTXVLatentUpsampler node increases the spatial resolution of a video latent representation by a factor of two. It uses a specialized upscale model to process the latent data, which is first un-normalized and then re-normalized using the provided VAE’s channel statistics. This node is designed for video workflows within the latent space.
Inputs
| Parameter | Data Type | Required | Range | Description |
|---|---|---|---|---|
samples | LATENT | Yes | The input latent representation of the video to be upscaled. | |
upscale_model | LATENT_UPSCALE_MODEL | Yes | The loaded model used to perform the 2x upscaling on the latent data. | |
vae | VAE | Yes | The VAE model used to un-normalize the input latents before upscaling and to normalize the output latents afterwards. |
Outputs
| Output Name | Data Type | Description |
|---|---|---|
LATENT | LATENT | The upscaled latent representation, with spatial dimensions doubled compared to the input. The output latent has the same batch size, number of channels, and temporal length as the input. The noise_mask from the input, if present, is removed from the output. |
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