Skip to main content

Python SDK for the Unitlab.ai data annotation platform

Project description



PyPI Python Downloads License

Unitlab.ai is an AI-driven data annotation platform that automates the collection of raw data, facilitating collaboration with human annotators to produce highly accurate labels for your machine learning models. With our service, you can optimize work efficiency, improve data quality, and reduce costs.

Unitlab Python SDK

Python SDK and CLI for the Unitlab.ai data annotation platform. Manage projects, upload data, and download datasets programmatically or from the command line.

Installation

pip install --upgrade unitlab

Requires Python 3.10+.

Configuration

Get your API key from unitlab.ai and configure the CLI:

# Set API key
unitlab configure --api-key YOUR_API_KEY

# Set a custom API URL
unitlab configure --api-url https://api.unitlab.ai

# Set both at once
unitlab configure --api-key YOUR_API_KEY --api-url https://api.unitlab.ai

Or set environment variables:

export UNITLAB_API_KEY=YOUR_API_KEY

# Optional: point to a custom API server (e.g. self-hosted)
export UNITLAB_API_URL=https://api.unitlab.ai

Python SDK

from unitlab import UnitlabClient

# Initialize with an explicit key
client = UnitlabClient(api_key="YOUR_API_KEY")

# Or read from UNITLAB_API_KEY env var / config file
client = UnitlabClient()

The client can also be used as a context manager:

with UnitlabClient() as client:
    projects = client.projects()

Projects

# List all projects
projects = client.projects()

# Get project details
project = client.project("PROJECT_ID")

# Get project members
members = client.project_members("PROJECT_ID")

Upload data

client.project_upload_data(
    project_id="PROJECT_ID",
    directory="./images",
)

Additional options for specific project types:

# Text projects
client.project_upload_data("PROJECT_ID", "./docs", sentences_per_chunk=10)

# Video projects
client.project_upload_data("PROJECT_ID", "./videos", fps=30.0)

Datasets

# List all datasets
datasets = client.datasets()

# Download annotations (COCO, YOLOv8, YOLOv5, etc.)
path = client.dataset_download("DATASET_ID", export_type="COCO", split_type="train")

# Download raw files
folder = client.dataset_download_files("DATASET_ID")

CLI

Projects

# List projects
unitlab project list

# Project details
unitlab project detail PROJECT_ID

# Project members
unitlab project members PROJECT_ID

# Upload data to a project
unitlab project upload PROJECT_ID --directory ./images

Datasets

# List datasets
unitlab dataset list

# Download annotations
unitlab dataset download DATASET_ID --export-type COCO --split-type train

# Download raw files
unitlab dataset download DATASET_ID --download-type files

Documentation

See the full documentation for detailed guides:

License

MIT

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

unitlab-2.4.4.tar.gz (11.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

unitlab-2.4.4-py3-none-any.whl (11.1 kB view details)

Uploaded Python 3

File details

Details for the file unitlab-2.4.4.tar.gz.

File metadata

  • Download URL: unitlab-2.4.4.tar.gz
  • Upload date:
  • Size: 11.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for unitlab-2.4.4.tar.gz
Algorithm Hash digest
SHA256 9be1aa4c0149945b763adf7609ef4a9bf7dca286a58ee74b7e952cf544f28c5b
MD5 b921ee5fb8d5b4d92b6db8f207f90dcf
BLAKE2b-256 5910e5c7cde177f973b5b379c3dc72aca356c66bcc771103933fe07de900d0f0

See more details on using hashes here.

File details

Details for the file unitlab-2.4.4-py3-none-any.whl.

File metadata

  • Download URL: unitlab-2.4.4-py3-none-any.whl
  • Upload date:
  • Size: 11.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for unitlab-2.4.4-py3-none-any.whl
Algorithm Hash digest
SHA256 6783b97e72aa160c550004774e55c764a847540f21faa0657f50602c187d397f
MD5 e111249401a2c1e45a048694ba76fef1
BLAKE2b-256 3950a445132a24948de33d96eeaf3eab0afedbbc5c58b78243e950e71e6488a6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page