Introducing version 0.6.0 - Nested data labeling
Specify multiple classification options for more accurate labeling decisions. Read more in our blog.
Data Scientists, Machine Learning Engineers, and aspiring developers are using Label Studio to produce innovative machine learning models for real-world applications.
# Install the package
pip install label-studio
# Create a new project
label-studio init my_project
# Launch it!
label-studio start my_project
Check out the templates configured for specific data labeling needs.Templates
Why Label Studio?
Using HTML-like tags, you can quickly configure the UI for your particular needs. It's not just an image or text. It can be a pairwise comparison, multi-type classification, and beyond. Label Studio is a swiss army knife of data labeling and annotation.Learn More
Multiple data types
Label Studio is type agnostic. The overall goal is to be able to process all data types. Right now it
supports Audio, Text, Images, and HTML.
Each interface can include a mix of the types with different workflows.
Embeddable and Extendable
Label Studio includes a powerful embedding feature that enables you to embed entire UI in your pipeline. You can extend core functionality with new visual constructs and customize it for different use cases.Read More
Compatible with major libraries & frameworks
Looking to scale?
- — Do you have more data than you can possibly label by hand?
- — Do you want to distribute the labeling to multiple annotators?
- — Do you want to control the quality of the annotations?
- — Do you want to include your entire team into the process to achive greater results?
We provide commercial offering built on top of Label Studio.