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Facilitates structured assignment of labels to segments for AI artists, enhancing organization and workflow efficiency.
The ImpactSEGSLabelAssign
node is designed to facilitate the assignment of labels to segments (SEGS) in a structured and efficient manner. This node is particularly useful for AI artists who need to organize and categorize different segments within their projects. By providing a list of labels, you can systematically assign these labels to corresponding segments, ensuring that each segment is properly identified and categorized. This process helps in maintaining a well-organized workflow and enhances the ability to manage and manipulate segments based on their assigned labels. The node ensures that the labels are assigned in the order they are provided, making it easy to keep track of which label corresponds to which segment.
This parameter represents the segments (SEGS) that you want to label. It is a required input and should be provided in the format expected by the node. The segments are typically a collection of elements that need to be categorized or identified with specific labels.
This parameter is a string that contains the list of labels to be assigned to the segments. The labels should be listed in the order of the segments and separated by commas. This input supports multiline text and provides a placeholder to guide you in listing the labels correctly. The labels are stripped of any leading or trailing whitespace before being assigned to the segments.
The output parameter is the labeled segments (SEGS). This output contains the original segments with the newly assigned labels, allowing you to easily identify and categorize each segment based on the provided labels. The labeled segments are returned in the same structure as the input, ensuring consistency and ease of use in subsequent processing steps.
{len(labels)}
) != length of segs ({len(segs[1])}
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