Labelbox

GraphQL Introduction

A GraphQL API is very similar to a REST API however it provides a few great advantages for API consumers...

  • Everything is Typed: Both the request query and the response are strongly typed. That means you'll know your sending a valid query because the schema allows it.
  • Flexibility to pull needed data: Relationships between types are represented through the GraphQL graph allowing for complex data retrieval in a single request.
  • Easy exploration and strong tooling: Since everything is typed and built for powerful queries tools like our GraphQL explorer (https://app.labelbox.com/explorer) can be built to discover api requests and understand the API schema.

Labelbox Core Data Types

  • Label: Label represents an assessment on a DataRow. For example one label could contain 100 bounding boxes (annotations).
  • DataRow: A DataRow represents a single piece of data. For example, if you have a CSV with 100 rows, you will have 100 DataRows.
  • PredictionModel: A prediction model represents a specific version of a model.
  • Prediction: A prediction is a label made by a prediction model. Predictions can be used as a base labels to decrease labeling time.
  • AssetMetadata: AssetMetadata is a datatype to provide extra context about an asset while labeling.