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Overview

The Select Unique Items tool helps reduce dataset redundancy by highlighting the most visually distinct samples in your dataset. This is especially useful when curating balanced datasets for training or review—ensuring that only diverse, non-repetitive content is prioritized. Visual Layer assigns each image or object a uniqueness score, then filters out near-duplicates according to a user-defined threshold.

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Use Cases

  • Reduce redundancy before model training or export
  • Create compact datasets that preserve diversity
  • Reveal long tail content often hidden behind common or repetitive examples

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How It Works

  • Every image or object is assigned a uniqueness score between 0 and 1
    • 0 = highly redundant
    • 1 = highly unique
  • When the filter is applied, only samples with the highest uniqueness scores are retained
  • The action is automatically applied as an Exclude rule in the Query Panel

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How to Apply the Filter

  1. Navigate to theDataset Exploration View
  2. Click the Select Uniques button (located next to the search bar)
  3. Adjust the threshold slider to your preferred level of uniqueness
  4. The filter will appear in the Query Panel under the Exclude section
This workflow lets you focus on the most varied content in your dataset—ideal for debugging, QA, or preparing smaller benchmark sets.

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Uniqueness in Exported Data

If you export data with this filter applied, the retained items will include their uniqueness score in the JSON payload: 
"uniqueness_score": 0.9285714285714288