Open Source
Data Labeling Platform
The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates.
Last Commit:
Latest version:
# Install the package
# into python virtual environmentpip install -U label-studio
# Launch it!
label-studio
# Install the cask
brew install heartexlabs/tap/label-studio
# Launch it!
label-studio
# Clone repo
git clone https://github.com/heartexlabs/label-studio.git
# Install dependencies
cd label-studio
pip install -e .# Apply DB migrations
python label_studio/manage.py migrate
# Collect static files
python label_studio/manage.py collectstatic
# Launch
python label_studio/manage.py runserver
# Run latest Docker version
docker run -it -p 8080:8080 -v `pwd`/mydata:/label-studio/data heartexlabs/label-studio:latest
# Now visit http://localhost:8080/
Label every data type.
Computer Vision
Image Classification
Put images into categories
Object Detection
Detect objects on image, boxes, polygons, circular, and keypoints supported
Semantic Segmentation
Partition image into multiple segments. Use ML models to pre-label and optimize the process
Quick StartAudio & Speech Applications
Classification
Put audio into categories
Speaker Diarization
Partition an input audio stream into homogeneous segments according to the speaker identity
Emotion Recognition
Tag and identify emotion from the audio
Audio Transcription
Write down verbal communication in text
Quick StartNLP, Documents, Chatbots, Transcripts
Classification
Classify document into one or multiple categories. Use taxonomies of up to 10000 classes
Named Entity
Extract and put relevant bits of information into pre-defined categories
Question Answering
Answer questions based on context
Sentiment Analysis
Determine whether a document is positive, negative or neutral
Quick StartRobots, Sensors, IoT Devices
Classification
Put time series into categories
Segmentation
Identify regions relevant to the activity type you're building your ML algorithm for
Event Recognition
Label single events on plots of time series data
Quick StartMulti-Domain Applications
Dialogue Processing
Call center recording can be simultaneously transcribed and processed as text
Optical Character Recognition
Put an image and text right next to each other
Time Series with Reference
Use video or audio streams to easier segment time series data
Quick StartVideo
Classification
Put videos into categories
Object Tracking
Label and track multiple objects frame-by-frame
Assisted Labeling
Add keyframes and automatically interpolate bounding boxes between keyframes
Quick StartFlexible and configurable
Configurable layouts and templates adapt to your dataset and workflow.
Integrate with your ML/AI pipeline
Webhooks, Python SDK and API allow you to authenticate, create projects, import tasks, manage model predictions, and more.
ML-assisted labeling
Save time by using predictions to assist your labeling process with ML backend integration.
Connect your cloud storage
Connect to cloud object storage and label data there directly with S3 and GCP.
Explore & understand your data
Prepare and manage your dataset in our Data Manager using advanced filters.
Multiple projects and users
Support multiple projects, use cases and data types in one platform.
Trusted by companies large and small
Global Community
Join the largest community of Data Scientists working on enhancing their models.
Millions of data items labeled
6,000+ Slack members
10,000+ GitHub stars
Thanks to our Core Contributors
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