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How This Helps

Tagging makes it easy to group, track, and manage data for training, QA, relabeling, or experimentation. Whether you’re cleaning data, preparing a subset, or tracking annotation status — tags let you move faster and stay organized.
Tags help you quickly organize, filter, and take action on relevant items in your dataset. They can be applied across Clusters, Images, or Objects, and used to streamline curation, quality review, or experimental workflows. Use cases include:
  • Data Curation: Group items for training, validation, or internal evaluation. Tags like train, test, representative help define clear splits.
  • Data Cleaning: Identify problematic items with tags like low_quality, duplicate, or needs_review.
  • Workflow Management: Add review state tags such as approved, rejected, for-review, or priority labels like urgent.
  • Experiment Tracking: Label data used in experiments (exp-103, baseline-set) for traceability and auditability.

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Tag Multiple Items

You can assign tags to many items at once across views.
  1. Navigate to a dataset and select Clusters, Images, or Objects of interest.
  2. Click the Selected Items icon in the top right.
  3. Click Manage Tags and choose from existing tags or create new ones.

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View and Remove Tags

You can view and edit tags in the Assigned Tags panel.
  1. Select your items and open the Assigned Tags panel.
  2. Click a tag to remove it from any selected items — even if it’s not applied to all of them.

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Tag Individual Images

You can also tag single images directly in the Image Details Page.
  1. Open the Image Details Page for the image you want to tag.
  2. Click Assign User Tags in the right-hand pane.
  3. Select an existing tag or create a new one.
  4. To remove a tag, click the X next to its label in the right pane.
You can mix and match tag workflows — start with bulk tagging, refine at the image level, or export tagged items for review, relabeling, or exclusion.