Visit ComfyUI Online for ready-to-use ComfyUI environment
Automate batch cropping and resizing of images in place for AI artists, saving time and ensuring consistency.
The Batch Crop Resize Inplace node is designed to streamline the process of cropping and resizing multiple images in a batch, directly modifying the original images. This node is particularly useful for AI artists who need to prepare large sets of images for further processing or analysis. By automating the cropping and resizing tasks, it saves time and ensures consistency across all images. The node allows you to specify the amount to crop from each image and the method to use for resizing, making it a versatile tool for various image preprocessing needs.
This parameter specifies the directory where the images to be processed are located. It should be a string representing the path to the directory. The node will read all supported image files (e.g., .png, .jpg, .jpeg, .webp, .bmp, .gif) from this directory. Ensure that the directory exists and contains the images you want to process.
This parameter determines the fraction of the image to be cropped from each side. It is a floating-point value, with a default of 0.05, meaning 5% of the image width and height will be cropped from each side. Adjusting this value will change the amount of cropping applied to the images.
This parameter specifies the method to use for resizing the images after cropping. The available options are "nearest-exact", "bilinear", "area", and "bicubic". Each method has its own characteristics in terms of quality and performance, allowing you to choose the one that best fits your needs.
This parameter defines the cropping method to be used. The available options are "disabled" and "center". "Disabled" means no additional cropping will be applied after resizing, while "center" will crop the image to the center.
The output of this node is a list of processed images. Each image in the list has been cropped and resized according to the specified parameters. The images are returned in the same format as they were read, ensuring compatibility with subsequent processing steps.
crop_amount
parameter to control how much of the image is cropped from each side. A smaller value will result in less cropping, while a larger value will crop more of the image.upscale_method
that best fits your quality and performance needs. For example, "bicubic" provides high-quality results but may be slower, while "nearest-exact" is faster but may result in lower quality.crop
parameter to control additional cropping after resizing. "Center" cropping is useful for focusing on the central part of the image.<directory_path>
does not exist© Copyright 2024 RunComfy. All Rights Reserved.