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Load random images from specified list for diverse AI art tasks.
The GetRandomFile
node is designed to load images from a specified list of filenames, providing a randomized selection of images for further processing. This node is particularly useful for AI artists who need to work with a diverse set of images without manually selecting each one. By leveraging the randomness, it ensures a varied input, which can be beneficial for tasks requiring different visual inputs, such as training models or generating unique art pieces. The node can handle various configurations, such as limiting the number of images, sorting them, or looping the sequence to ensure the first and last images are the same, making it a versatile tool in your image processing pipeline.
This parameter takes a list of filenames from which the images will be loaded. The filenames should be valid paths to the image files you want to use. The node will randomly select from these files based on the provided seed.
This parameter specifies the maximum number of images to load from the list. If set to 0, there is no limit, and all images in the list will be considered. This allows you to control the volume of data being processed, which can be useful for managing memory and processing time.
The seed parameter is used to initialize the random number generator, ensuring that the random selection of images is reproducible. By setting a specific seed, you can achieve the same random order of images each time you run the node, which is useful for consistency in experiments.
This boolean parameter determines whether the selected images should be sorted. If set to True
, the images will be sorted alphabetically by their filenames. This can be useful if you need a specific order for your images.
This boolean parameter, when set to True
, ensures that the last image in the sequence is the same as the first image. This is particularly useful for creating looping animations or ensuring continuity in a sequence of images.
The output of this node is a tensor containing the loaded images. If multiple images are loaded, they are concatenated into a single tensor. This tensor can then be used as input for further processing nodes, enabling seamless integration into your image processing workflow.
seed
parameter to a specific value.max_num_images
parameter to control the number of images being processed, which can help manage memory usage and processing time.sort
parameter to True
.loop_sequence
parameter to True
to ensure the first and last images are the same.filename
parameter are valid paths to existing image files.max_num_images
parameter or ensure that your system has sufficient memory to handle the specified number of images.© Copyright 2024 RunComfy. All Rights Reserved.