Skip to main content
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.

​
Prerequisites

​
Calculate Metrics & 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.

​
Using Embedding Plots

  1. Navigate to Data > 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