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Seamlessly blend inpainted regions with original latent image using specified mask for image integration.
The OverlayInpaintedLatent
node is designed to seamlessly blend inpainted regions with the original latent image using a specified mask. This node is particularly useful in the context of image inpainting, where you want to integrate newly generated content into an existing image while maintaining a natural and coherent appearance. By leveraging the mask, the node ensures that only the designated areas of the original image are replaced with the inpainted content, preserving the integrity of the untouched regions. This functionality is essential for creating high-quality, realistic images in AI art and other creative applications.
The original
parameter represents the latent image that serves as the base for the overlay process. This is the image that will be partially replaced by the inpainted content based on the mask. The latent image should be in the format of a dictionary containing a key "samples"
with a tensor value. This parameter is crucial as it provides the context and background for the inpainted regions.
The inpainted
parameter is the latent image containing the newly generated content that will be overlaid onto the original image. Similar to the original
parameter, it should be a dictionary with a key "samples"
and a tensor value. This parameter is essential for introducing new elements into the original image, guided by the mask.
The mask
parameter is a tensor that defines the regions of the original image to be replaced by the inpainted content. The mask should have the same batch size as the original
and inpainted
images. It acts as a guide, ensuring that only the specified areas are affected by the overlay process. The mask values typically range from 0 to 1, where 1 indicates full replacement and 0 indicates no replacement.
The output of the OverlayInpaintedLatent
node is a latent image that combines the original and inpainted content based on the mask. The output is a dictionary with a key "samples"
containing a tensor. This blended image retains the original content in unmasked areas while incorporating the inpainted content in masked regions, resulting in a coherent and natural-looking final image.
original
, inpainted
, and mask
parameters have the same batch size to avoid errors and ensure proper overlay functionality.inpainted
content, as this can significantly impact the quality and realism of the final image.original
and inpainted
images do not match.original
and inpainted
parameters have the same batch size before passing them to the node.original
image and the mask
do not match.mask
parameter has the same batch size as the original
image to ensure proper overlay functionality.© Copyright 2024 RunComfy. All Rights Reserved.