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Facilitates loading images from directory, supports configurations for managing large image datasets efficiently.
The VHS_LoadImages node is designed to facilitate the loading of images from a specified directory, making it an essential tool for AI artists who need to work with large batches of images. This node allows you to upload images directly from a directory, providing flexibility and efficiency in managing image data. It supports various configurations such as limiting the number of images loaded, skipping initial images, and selecting every nth image, which can be particularly useful for handling large datasets. By leveraging this node, you can streamline your workflow, ensuring that only the necessary images are processed, thereby saving time and computational resources.
This parameter specifies the path to the directory from which images will be loaded. It is crucial to provide a valid directory path to ensure the node can locate and load the images. If the directory does not exist, an error will be raised. There is no default value for this parameter, and it must be provided by the user.
This parameter sets the maximum number of images to load from the directory. If set to 0, all images in the directory will be loaded. This is useful for limiting the dataset size for quicker processing. The default value is 0, with a minimum value of 0 and no specified maximum value.
This parameter allows you to skip a specified number of initial images in the directory. This can be useful if you want to bypass certain images that are not relevant to your current task. The default value is 0, with a minimum value of 0 and no specified maximum value.
This parameter enables you to select every nth image from the directory, which can be useful for downsampling the dataset. For example, setting this to 2 will load every second image. The default value is 1, with a minimum value of 1 and no specified maximum value.
This optional parameter is used for batch processing, allowing you to manage and process images in batches. If not provided, the node will process images individually. There is no default value for this parameter.
This optional parameter is used to uniquely identify the batch of images being processed. It is particularly useful when working with multiple batches to ensure that each batch is processed correctly. There is no default value for this parameter.
This output parameter contains the loaded images as a tensor. The images are converted to a format suitable for further processing in AI models. If the images have an alpha channel, it will be separated from the main image data.
This output parameter contains the masks for the images if they have an alpha channel. If the images do not have an alpha channel, this parameter will contain a tensor of zeros.
This output parameter indicates the number of images successfully loaded from the directory. It provides a quick reference to verify that the expected number of images has been processed.
image_load_cap
parameter to limit the number of images loaded, which can help in managing memory usage and processing time.skip_first_images
and select_every_nth
parameters to fine-tune the selection of images, especially when working with large datasets.unique_id
parameter to avoid conflicts.© Copyright 2024 RunComfy. All Rights Reserved.