Build AI with production grade tooling

Join a growing community of companies using AI to inspect solar panels, identify welding defects, teach robots to perform surgery and many other use cases.

create accountContact Sales

Label data with advanced annotation tools

Labelbox interfaces are intuitive to use and have full hotkey support to increase labeler productivity. To get started, configure a labeling interface for your task in minutes using one or more of the segmentation and classification tools. Or, build your own custom interface to use with Labelbox.

Upload or connect to your training data

Labelbox integrates with your ML pipeline by hosting or connecting to your training data (labeled and unlabeled). Supports both private cloud and on-premise data sources.

Distribute work to your internal team and outsourced services

Label data with internal and external teams simultaneously. Review annotations collaboratively. Keep track of activity and progress.

Ensure accurate and consistent training data

Catch bad labels in real time using the consensus system to automaticaly identify and correct inconsistent annotations. Set up review workflows to correct annotations and ensure accuracy of the training data.

Export your training data to standard ML formats with one click

Move your labeled data into a training environment seamlessly by exporting to popular ML formats including COCO, Pascal VOC, Tensorflow, JSON XY and CSV.

Extensible and Developer Friendly

Set up ingest, ETL, and egress integrations between your ML pipeline and Labelbox. Connect your ML models to supercharge labeling productivity and orchestrate active learning. Labelbox is API-first so you can do just about anything!


from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')

data = client.execute('
  mutation {
    createDataRow(
      data: {
        rowData: "<DATA_THAT_NEEDS_TO_BE_LABELED>",
        dataset: {
          connect: {
            id: "<DATASET_ID_HERE>"
          }
        },
        organization: {
          connect: {
            id: "<INSERT_YOUR_ORGANIZATION_ID_FROM_ABOVE_HERE>"
          }
        },
      }
    )
  }
')
 

from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')

data = client.execute('
  mutation {
    createLabel(
      data: {
        label:"<INSERT_LABEL_DATA_STRING_HERE>",
        secondsToLabel: 42,
        dataRow: {
          connect: {
            id: "<INSERT_DATA_ROW_ID_HERE>"
          }
        },
        project: {
          connect: {
            id: "<INSERT_PROJECT_ID_HERE>"
          }
        },
        type: {
          connect: {
            name: "Any"
          }
        }
      })  {
        id
        label
    }}
')

from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')

data = client.execute('
  mutation{
    createPrediction(data:{
      label:"<should-be-the-exact-same-as-label.label>",
      predictionModelId:"<from-the-prediction-model-you-created-earlier>",
      projectId:"<any-project-id>",
      dataRowId:"<any-datarow-id>",
    }){
      id
    }
  }
')

from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')

data = client.execute('
  query {
    project(where:{id: "<INSERT_PROJECT_ID_HERE>"}) {
      labels(first: 5){
        id
        label
        createdBy{
          id
          email
        }
        type {
          id
          name
        }
        secondsToLabel
        agreement
        dataRow {
          id
          rowData
        }
      }
    }
  }
')

Customers ♥ Labelbox

Labelbox has become essential to our process. It is the beginning of every single deep learning exercise we do. The only thing that comes before Labelbox is recording the data.

Gal Ozery

AI Product Owner, Genius Sports

Labelbox is very well integrated as a part of our overall system design. Labelbox has helped us efficiently collect and analyze data through their strong infrastructure support. We’re able to get the labels we need for all different types of video and image analysis.

Stephen Krotosky

Manager, Applied Machine Learning

Get started with a free account

Join the next industrial revolution