Label Studio

4.80

RATING

987 M+

EXPOSURE

About this tool

Name

Label Studio

Category

tools

Label Studio is an open-source data labeling platform that supports a wide variety of data types including text, images, audio, video, and time-series data. It is designed to help machine learning teams create high-quality training datasets by offering flexible annotation interfaces, advanced configuration options, and seamless integrations with ML pipelines. Label Studio is ideal for both individual researchers and large annotation teams.

Ratings and Reviews

Versatile and Customizable

4.60

Label Studio is by far the most flexible annotation tool I’ve used. The XML config is powerful once you get the hang of it.

May 30, 2025

Daniel M.

Great for Multi-Modal Projects

4.80

I used it to annotate both text and video for a hybrid NLP + CV model. Love the open-source flexibility and active community.

June 1, 2025

Chloe Y.

Needs a Smoother UX

4.30

Feature-rich and powerful, but the user interface can feel clunky at times, especially for new users or non-engineers.

June 3, 2025

Mark T.

How to use

Install or Use the Cloud Version: Deploy Label Studio on your local machine or server using Docker, or sign up for the hosted version at labelstud.io. Create a Project: Start a new project and choose the data type you want to annotate (e.g., image classification, text sentiment, object detection). Configure the Labeling Interface: Use the visual configuration tool or XML to set up custom labeling templates suited to your use case. Upload Your Data: Import data directly via file upload, API, or integration with cloud storage. Start Annotating: Label the data manually or use model-assisted labeling. Collaborate with others and assign tasks if working in teams. Export Results or Integrate with ML Tools: Export labels in multiple formats (JSON, CSV, etc.) or connect to ML frameworks like PyTorch, TensorFlow, or Hugging Face.

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