The most flexible data labeling platform to fine-tune LLMs, prepare training data or validate AI models.
# Install the package
# into python virtual environment
pip install -U label-studio
# Launch it!
# Install the cask
brew install humansignal/tap/label-studio
# Launch it!
# Clone repo
git clone https://github.com/HumanSignal/label-studio.git
# Install dependencies
pip install -e .
# Apply DB migrations
python label_studio/manage.py migrate
# Collect static files
python label_studio/manage.py collectstatic
python label_studio/manage.py runserver
# Run latest Docker version
docker run -it -p 8080:8080 -v `pwd`/mydata:/label-studio/data HumanSignal/label-studio:latest
# Now visit http://localhost:8080/
Label every data type.
Put images into categories
Detect objects on image, boxes, polygons, circular, and keypoints supported
Partition image into multiple segments. Use ML models to pre-label and optimize the processQuick Start
Audio & Speech Applications
Put audio into categories
Partition an input audio stream into homogeneous segments according to the speaker identity
Tag and identify emotion from the audio
Write down verbal communication in textQuick Start
NLP, Documents, Chatbots, Transcripts
Classify document into one or multiple categories. Use taxonomies of up to 10000 classes
Extract and put relevant bits of information into pre-defined categories
Answer questions based on context
Determine whether a document is positive, negative or neutralQuick Start
Robots, Sensors, IoT Devices
Put time series into categories
Identify regions relevant to the activity type you're building your ML algorithm for
Label single events on plots of time series dataQuick Start
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 dataQuick Start
Put videos into categories
Label and track multiple objects frame-by-frame
Add keyframes and automatically interpolate bounding boxes between keyframesQuick Start
Flexible 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.
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
Join the largest community of Data Scientists working on enhancing their models.