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Horizontally stack and align two images in a square canvas for seamless visual transition.
The tri3d_H_Stack_Images
node is designed to horizontally stack two images, aligning them side by side within a larger square canvas. This node is particularly useful for creating composite images where two separate images need to be displayed together in a single frame. The process involves determining the maximum dimension required to accommodate both images and then placing each image in the appropriate position on the canvas. This ensures that both images are centered vertically and aligned horizontally, providing a seamless visual transition between them. The node is beneficial for artists and designers who need to combine images for comparison, presentation, or creative purposes, offering a straightforward method to achieve a clean and organized layout.
The image_L
parameter represents the left image in the horizontal stack. It is an image input that will be placed on the left side of the resulting composite image. The function of this parameter is to provide the first image that will be combined with the second image. There are no specific minimum, maximum, or default values for this parameter, as it is expected to be an image tensor. The quality and dimensions of this image will directly affect the final output, as it will be part of the composite image.
The image_R
parameter represents the right image in the horizontal stack. Similar to image_L
, this is an image input that will be placed on the right side of the resulting composite image. This parameter's function is to provide the second image that will be combined with the first image. Like image_L
, there are no specific minimum, maximum, or default values for this parameter, as it is expected to be an image tensor. The characteristics of this image will also influence the final output, as it will be part of the composite image.
The output parameter IMAGE
is the resulting composite image created by horizontally stacking the two input images. This output is a single image tensor that contains both input images aligned side by side on a square canvas. The importance of this output lies in its ability to present two images together in a cohesive manner, making it easier for users to compare or showcase them in a single frame. The output image maintains the original quality of the input images while ensuring they are properly aligned and centered.
image_L
and image_R
) have similar dimensions to achieve a more balanced and visually appealing composite image.RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Playground, enabling artists to harness the latest AI tools to create incredible art.