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Extract specific subset of images efficiently from a larger batch while maintaining original quality and dimensions.
The ImageFromBatch
node is designed to extract a specific subset of images from a larger batch of images. This is particularly useful when working with large datasets or when you need to isolate and process a specific segment of your image batch. By specifying the starting index and the length of the subset, you can efficiently manage and manipulate your image data without having to handle the entire batch at once. This node ensures that the extracted images maintain their original quality and dimensions, making it an essential tool for tasks that require precise image selection and processing.
This parameter represents the batch of images from which you want to extract a subset. The batch should be in the form of a tensor, where the first dimension corresponds to the number of images in the batch. Each image in the batch should have the same dimensions and format. The quality and integrity of the extracted images depend on the quality of the input batch.
This parameter specifies the starting index of the subset of images you want to extract from the batch. It determines the position in the batch from which the extraction begins. The value must be an integer, with a default value of 0, a minimum value of 0, and a maximum value of 4095. If the specified index exceeds the number of images in the batch, it will be adjusted to the last valid index.
This parameter defines the number of images to extract from the batch, starting from the batch_index
. It determines the size of the subset. The value must be an integer, with a default value of 1, a minimum value of 1, and a maximum value of 4096. If the specified length exceeds the number of available images from the batch_index
, it will be adjusted to include only the remaining images.
The output is a subset of the original batch of images, extracted based on the specified batch_index
and length
. This subset retains the original quality and dimensions of the images, allowing for further processing or analysis. The output is in the form of a tensor, similar to the input batch, but with a reduced number of images.
batch_index
and length
parameters are set correctly to avoid out-of-bounds errors.batch_index
is greater than the number of images in the batch.batch_index
is within the valid range of the batch. If necessary, adjust the batch_index
to a value less than the total number of images in the batch.length
exceeds the number of available images from the batch_index
.length
parameter to ensure it does not exceed the number of images available from the specified batch_index
. If necessary, reduce the length
to fit within the remaining images in the batch.© Copyright 2024 RunComfy. All Rights Reserved.