Label Studio

Label Studio is a free and open-source data annotation tool launched by Human Signal (formerly Heartex). The project has a star rating of nearly 14000 on GitHub, which can help developers fine tune large language models, prepare training data, or validate AI models.
Features of Label Studio
Support labeling of various types of data, including images, sound, text, time series, multi domain, video, etc
Flexible and configurable, with configurable layouts and templates to combine with one’s own dataset and workflow
Machine learning assisted labeling, using prediction to assist the labeling process through ML backend integration, thus saving time
Multiple projects and users, supporting multiple projects, use cases, and data types on the same platform
Integrate with your ML/AI pipeline and use Webhooks, Python SDK, and APIs for authentication, project creation, task import, model prediction management, and more.
How to start using Label Studio
First, confirm that the installation and dependencies have been installed on the computer
Then use the command to install Label Studio
Starting Label Studio using Terminal/Command Line
By http://localhost:8080 Open Label Studio UI
Register using a self created email address and password
Click Create to create the project and start tagging data
Name the project, enter the project description and choose a color
Click on Data Import and upload the data file you want to use. If you want to use data from local directories, cloud storage, or databases, you can temporarily skip this step
Click on Labeling Setup settings and select a template to customize annotation names based on your use cases
Click Save to save your project
For more settings and related operations, please refer to the official documentation https://labelstud.io/guide/get_started.html