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The embedding plot is a 2D visualization of your high-dimensional data, where proximity between points indicates similarity. This makes it easy to spot clusters, outliers, and patterns at a glance.
You can draw a rectangular selection on the plot to isolate and explore a specific subset of data points. Use the Order by drop-down to switch the visualization between data and label embeddings.

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Calculate Metrics and Embeddings

  1. Navigate to Projects.
  2. Open the Explore tab.
  3. Click Metrics & Embeddings.
  4. Click Compute for either option.
  5. Specify the following:
    • Similarity & Natural language search and quality metrics: Enable to compute embeddings and quality metrics. Access quality metrics for filtering and sorting.
    • Select embeddings: Default embeddings are computed by Encord. Alternatively, import and select your own custom embeddings.
    • Embeddings plot, Diversity and Uniqueness metrics: Enable to compute UMAP reduction to generate 2D embeddings plots to visualize your data. Also access diversity and uniqueness metrics for curation.
  6. Click Start computation.

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Using Embedding Plots

To use embedding plots for label validation, you must calculate metrics and embeddings.
  1. Navigate to Projects
  2. Open the Explore tab.
  3. Click Frames or Labels.
  4. Click the Embeddings View icon.
  • Use the V + E shortcut to access the Embeddings View.
  • In addition to selecting points within a rectangular area, you can use filters (but not sort or natural language or image search) on the data or labels.
Data Embedding Plot
Label Embedding Plot