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Resize input image to match reference image size using interpolation for alignment and consistency, with method flexibility.
The scale_with_reference
node is designed to adjust the size of an input image to match the dimensions of a reference image. This node is particularly useful when you need to ensure that two images are of the same size for further processing or analysis. By utilizing interpolation techniques, it maintains the quality of the image while resizing, making it an essential tool for tasks that require image alignment or consistency in dimensions. The node offers flexibility in choosing the interpolation method, allowing you to balance between speed and quality based on your specific needs.
The image_in
parameter represents the input image that you want to scale. This image will be resized to match the dimensions of the reference image. It is crucial to provide a valid image tensor here, as this is the primary image that will undergo transformation.
The image_ref
parameter is the reference image whose dimensions will be used as the target size for scaling the input image. This image acts as a template, ensuring that the output image matches its size. Providing a reference image with the desired dimensions is essential for achieving the correct output size.
The scale_mode
parameter determines the interpolation method used during the scaling process. Options include various interpolation techniques, with "bilinear" being the default. This parameter affects the quality and speed of the scaling operation, allowing you to choose a method that best suits your requirements. The choice of interpolation can impact the smoothness and clarity of the scaled image.
The image_out
parameter is the resulting image after the input image has been scaled to match the reference image's dimensions. This output image retains the content of the input image but is resized to the specified size, making it suitable for applications that require uniform image dimensions.
image_ref
) has the desired dimensions before using it, as the output image will match its size.scale_mode
options to find the best balance between processing speed and image quality for your specific use case.image_in
and image_ref
are correctly formatted image tensors before passing them to the node.scale_mode
parameter.scale_mode
is set to a supported interpolation method, such as "bilinear", and check for any typos or incorrect values.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.