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Automate batch resizing of images with upscale methods and crop options for AI artists, saving time and ensuring quality.
The Batch Resize Image for SDXL node is designed to streamline the process of resizing multiple images within a specified directory. This node is particularly useful for AI artists who need to prepare a large number of images for further processing or analysis. By leveraging various upscale methods and crop options, this node ensures that your images are resized efficiently and consistently, maintaining the desired quality and dimensions. The primary goal of this node is to automate the batch resizing process, saving you time and effort while providing flexibility in how images are scaled and cropped.
This parameter specifies the directory where the images to be resized are located. It is a string input that should point to the folder containing your image files. The node will process all supported image formats within this directory, including .png
, .jpg
, .jpeg
, .webp
, .bmp
, and .gif
. Ensure that the directory path is correct and accessible to avoid errors during execution.
This parameter determines the method used to upscale the images. The available options are nearest-exact
, bilinear
, area
, and bicubic
. Each method has its own characteristics: nearest-exact
is fast but may produce blocky results, bilinear
offers a balance between speed and quality, area
is suitable for downscaling, and bicubic
provides high-quality results but is slower. Choose the method that best fits your quality and performance needs.
This parameter specifies the cropping method to be applied during the resizing process. The available options are disabled
and center
. When disabled
, no cropping is performed, and the image is resized as is. When center
is selected, the image is cropped from the center to fit the desired dimensions. This is useful for maintaining the focus on the central part of the image.
The output parameter is a list of resized images. Each image in the list has been processed according to the specified upscale method and crop option. The images are returned in a format ready for further processing or analysis, ensuring consistency in size and quality across the entire batch.
image_directory
path is correct and contains only the images you want to resize to avoid processing unnecessary files.upscale_method
based on your quality and performance requirements. For high-quality results, bicubic
is recommended, while nearest-exact
is suitable for faster processing.center
crop option if you need to maintain the focus on the central part of the images, especially for portraits or centered subjects.<image_directory>
does not exist.png
, .jpg
, .jpeg
, .webp
, .bmp
, .gif
).© Copyright 2024 RunComfy. All Rights Reserved.