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Documentation Index

Fetch the complete documentation index at: https://docs.encord.com/llms.txt

Use this file to discover all available pages before exploring further.

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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Prerequisites

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Calculate Metrics & Embeddings

  1. Navigate to Projects > Explore.
  2. Click Metrics & Embeddings.
  3. Click Compute for either option.
  4. 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.
  5. Click Start computation.

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Using Embedding Plots

  1. Navigate to Projects > Explore.
  2. Click Frames or Labels.
  3. 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