Import and upload data

To upload data to Labelbox, you'll need to create a dataset and import your data as data rows into that dataset.

Individual data assets are stored in data rows; you upload and associate a variety of annotations , such as labels , metadata, predictions, custom metrics, and more. Individual data rows are identified using global keys unique to your workspace.

There are several ways to do this; you can:

• Set up data integrations through Census with remote sources, such as relational databases (RDBMS), data warehouses, or data lakes.
• Import data rows from local file locations or cloud storage buckets.
• Use the SDK to upload data rows, assets, and annotations.

Common tasks

Here are the most common data import tasks:

• Create a dataset
• Upload local files
• Import from URLs
• Upload data from cloud storage
  • Amazon Web Services (AWS) storage (S3)
  • Google Cloud Storage (GCS)
  • Microsoft Azure storage  
• Python SDK tutorials & examples:
  • Import images
  • Import text
  • Import annotation
• Integrate with remote data
  • Set up Census integration to import from more than twenty (20) different data sources.
  • Legacy connectors:
    • Databricks (no code)
    • Databricks
    • Google BigQuery
    • Snowflake

Data types & import specs

The following data types can be imported.

SDK tutorials

The following tutorials show how to use the SDK to work with common objects:

• Datasets
• Data rows
• Metadata