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Concatenates multiple images into a cohesive output for AI artists, maintaining dimensions and consistency.
The ImageConcanateOfUtils
node is designed to concatenate multiple images into a single cohesive output. This node is particularly useful for AI artists who need to combine several images while maintaining their original dimensions and ensuring consistency across the final output. The node processes each image, applies necessary transformations, and concatenates them into a unified image tensor. This functionality is essential for creating complex image compositions, enhancing the workflow of image manipulation, and ensuring that the final output is seamless and visually appealing.
The image
parameter represents the input image or a sequence of images that you want to concatenate. This parameter is crucial as it serves as the primary data source for the node's operations. The images should be in a format that can be processed by the node, and they must have consistent dimensions to ensure proper concatenation.
The upscale_model
parameter specifies the model to be used for upscaling the image if necessary. This parameter is important when the input images are of lower resolution and need to be upscaled to match the desired output quality. The choice of the upscale model can significantly impact the final image quality.
The threshold_of_xl_area
parameter determines the threshold for the image area beyond which the upscaling model will be applied. It is a float value with a default of 0.9, a minimum of 0.0, and a maximum of 64.0. This parameter helps in controlling the conditions under which the upscaling is triggered, ensuring that only images exceeding a certain size are upscaled, thus optimizing performance and resource usage.
The IMAGE
output parameter represents the concatenated image tensor resulting from the node's operations. This output is crucial as it provides the final combined image, ready for further processing or use in your projects. The concatenated image maintains the original dimensions and quality of the input images, ensuring a seamless and visually consistent output.
threshold_of_xl_area
parameter based on the size of your images to optimize performance and avoid unnecessary upscaling.© Copyright 2024 RunComfy. All Rights Reserved.