Collect training samples

• Collect samples using the input imagery layer and basemap for context in individual work units.
• Use editing tools to create training samples.
  • Rectangle
  • Circle
  • Polygon
  • Select sample
  • Delete
  • Layers
  • Basemap
  • Filter

  Tip:

  For the Delete button to be active, a sample must be selected in the viewer.

• You can add contextual layers to the map to improve the training sample collection process.

Import training samples

• Import existing feature layers.
• Import feature layers from other Deep Learning Studio projects in your organization.
• Import work units from other Deep Learning Studio projects in your organization.

Edit training sample labels

• Edit existing training sample labels.
• If a schema contains more than one label, you can switch existing sample labels.

Review training samples

• Review collected samples and measure the training sample collection progress in a dashboard interface.
• Review work units individually.
• View samples in map or table view.

Manage image chips

• Export approved training samples as image chips for model training.
• Register training samples that were created outside of Deep Learning Studio.
• Maintain records of labeled image chips created in Deep Learning Studio.
• View exported labeled image chips in the list.
• View examples of image chips to review the process.

Manage label schema

• Add labels to the schema.
• Import label schemas from other Deep Learning Studio projects.
• Edit or rename existing labels.

Edit instructions URL

• Add a website for instructions on label creation.