Import and upload data

Shows how to set up your data and bring it into Labelbox Catalog, either by importing or integrating with a database or other source.

To upload data into a Labelbox dataset, you import (or ingest) it into a 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:

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

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.

Name	Kinds	SDK Import specifications
Images	PNG, JPEG, BMP	Image import format
Video	MP4	Video import format
Text	TXT (UTF-8)	Text import format
Conversational text	TXT (UTF-8)	Conversational text import format
Geospatial imagery	Tile Map Server	Geospatial import format
Simple tiled	Tile Map Server	Simple tiled import format
Audio	MP3, WAV, M4A	Audio import format
Documents	PDF	Documents import format
HTML	HTML	HTML import format
DICOM	DCM	DICOM import format

SDK tutorials

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

• Datasets
• Data rows
• Metadata