Scale Down To Size

Documentation

• Class name: ImageScaleDownToSize
• Category: Art Venture/Utils
• Output node: False

The ImageScaleDownToSize node is designed for resizing images to a specific size, scaling them down while maintaining their aspect ratio. It offers a mode to scale based on the maximum or minimum dimension, ensuring flexibility in how the image's dimensions are reduced.

Input types

Required

• images
  • The images parameter represents the collection of images to be scaled down. It is crucial for defining the input images that will undergo the resizing process.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• size
  • The size parameter specifies the target size to which the images will be scaled down. It plays a pivotal role in determining the new dimensions of the images.
  • Comfy dtype: INT
  • Python dtype: int
• mode
  • The mode parameter determines whether the scaling should consider the maximum or minimum dimension of the images. This choice affects how the aspect ratio is preserved during scaling.
  • Comfy dtype: BOOLEAN
  • Python dtype: bool

Output types

• image
  • Comfy dtype: IMAGE
  • The output is a tensor of images that have been scaled down to the specified size, with their aspect ratio maintained.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class UtilImageScaleDownToSize(UtilImageScaleDownBy):
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "images": ("IMAGE",),
                "size": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}),
                "mode": ("BOOLEAN", {"default": True, "label_on": "max", "label_off": "min"}),
            }
        }

    RETURN_TYPES = ("IMAGE",)
    CATEGORY = "Art Venture/Utils"
    FUNCTION = "image_scale_down_to_size"

    def image_scale_down_to_size(self, images, size, mode):
        width = images.shape[2]
        height = images.shape[1]

        if mode:
            scale_by = size / max(width, height)
        else:
            scale_by = size / min(width, height)

        scale_by = min(scale_by, 1.0)
        return self.image_scale_down_by(images, scale_by)