Visit ComfyUI Online for ready-to-use ComfyUI environment
Converts latent images for visualization in ComfyUI-Impact-Pack, aiding AI artists in model refinement with diverse preview methods.
The PreviewBridge
node is designed to facilitate the conversion and preview of latent images within the ComfyUI-Impact-Pack framework. This node is particularly useful for AI artists who need to visualize the intermediate stages of their generative models. By decoding latent representations into viewable images, PreviewBridge
allows you to inspect and refine your models more effectively. It supports various preview methods tailored to different latent formats, ensuring compatibility and flexibility. The node also manages caching to optimize performance, reducing the need for repeated computations.
The latent
parameter represents the latent image data that you want to convert into a previewable format. This data is typically a multi-dimensional tensor containing the encoded information of an image. The latent data must be compatible with the selected preview method to ensure accurate decoding. There are no specific minimum or maximum values, but the structure of the latent data must match the expected format for the chosen preview method.
The preview_method
parameter specifies the method used to decode the latent data into a viewable image. It supports various options such as "Latent2RGB-SD15", "Latent2RGB-SDXL", "Latent2RGB-SD3", "Latent2RGB-SD-X4", "Latent2RGB-Playground-2.5", "Latent2RGB-SC-Prior", and "Latent2RGB-SC-B". Each method corresponds to a different latent format and decoding process. The choice of preview method directly impacts the compatibility and quality of the resulting image. There are no default values; you must select an appropriate method based on your latent data.
The vae_opt
parameter is optional and represents the Variational Autoencoder (VAE) options used during the decoding process. If provided, it ensures that the VAE settings are applied to the latent data, potentially improving the quality of the decoded image. If not provided, the node will use default settings based on the selected preview method. This parameter is particularly useful for advanced users who want to fine-tune the decoding process.
The unique_id
parameter is a unique identifier for the current preview operation. It is used to manage caching and ensure that the node does not recompute previews unnecessarily. This parameter helps optimize performance by reusing previously computed results when possible. There are no specific values for this parameter; it should be a unique string or number for each preview operation.
The ui
output parameter contains the user interface elements related to the previewed image. This typically includes the path to the saved image file and any additional metadata required for displaying the image within the UI. This output is essential for integrating the previewed image into the broader ComfyUI framework.
The result
output parameter is a tuple containing the decoded image data and an optional mask. The image data is the actual pixel values of the decoded image, while the mask is used to apply any necessary transformations or filters. This output is crucial for further processing or analysis of the previewed image.
latent
data is compatible with the selected preview_method
to avoid errors during decoding.unique_id
parameter to manage caching effectively, especially when working with large datasets or multiple preview operations.preview_method
options to find the one that best suits your latent data and desired output quality.vae_opt
settings to fine-tune the decoding process and improve image quality.latent
data and preview_method
are compatible. Refer to the documentation for supported formats and methods.<preview_method>
' is unsupported preview method.'preview_method
is not supported by the node.preview_method
from the supported options listed in the documentation.unique_id
is correctly set and that the input parameters have not changed unexpectedly. If necessary, clear the cache and recompute the preview.© Copyright 2024 RunComfy. All Rights Reserved.