- Get started
- Label Studio features
Install and Upgrade
- Install and upgrade Label Studio
- Install Label Studio Enterprise on-premises using Docker
- Install Label Studio Enterprise on AWS Private Cloud
- Database setup
- Start Label Studio
Security and Privacy
- Secure Label Studio
- Set up authentication
- Set up user accounts
- Manage access
- Get data
- Import pre-annotations
- Sync data from external storage
Labeling and Projects
- Project setup
- Set up your labeling interface
- Label and annotate data
- Review annotations
- Annotation statistics
- Export annotations
Machine Learning Setup
- Machine learning setup
- Write your own ML backend
- ML Examples and Tutorials
- Troubleshoot machine learning
- Frontend library
- Frontend reference
- Backend API
- Update scripts and API calls
Set up your labeling interface
All labeling activities in Label Studio occur in the context of a project. After you create a project and import data, set up the labeling interface and labeling configuration for your project. This setup process is essential to your labeling project.
Configure the labels and task type for annotators using the templates included with Label Studio or by defining your own combination of tags to set up the labeling interface for your project.
- Select a template from the available templates or customize one.
- Label Studio automatically selects the field to label based on your data. If needed, modify the selected field.
- Add label names on new lines.
- (Optional) Choose new colors for the labels by clicking the label name and choosing a new color using the color selector.
- Configure additional settings relevant to the labeling interface functionality. For example, when labeling text you might have the option to Select text by words.
- Click Save.
You can make changes to the labeling interface and configuration in the project settings.
- In Label Studio UI, open the project you want to modify.
- Click Settings.
- Click Labeling Interface.
- Browse templates, update the available labels,
Note: After you start to annotate tasks, you cannot remove labels or change the type of labeling being performed, for example by choosing a new template, unless you delete the completed annotations using those labels.
You can customize a labeling config template or use a custom configuration that you create from scratch. If you create a custom configuration that might be useful to other Label Studio users, consider contributing the configuration as a template.
The labeling configuration for a project is an XML file that contains three types of tags specific to Label Studio.
|Tag type||When to use|
|Object||Specify the data type and input data sources from your dataset.|
|Control||Configure how the annotation results appear.|
|Visual||Define how the user interface looks for labeling.|
You can combine these tags to create a custom label configuration for your dataset.
For example, to classify images that are referenced in your data as URLs (
$image_url) into one of two classes, Cat or Dog, use this example labeling config:
<View> <Image name="image_object" value="$image_url"/> <Choices name="image_classes" toName="image_object"> <Choice value="Cat"/> <Choice value="Dog"/> </Choices> </View>
If you want to customize this example, such as to allow labelers to select both Cat and Dog labels for a single image, modify the parameters used with the Choices control tag:
<View> <Image name="image_object" value="$image_url"/> <Choices name="image_classes" toName="image_object" choice="multiple"> <Choice value="Cat"/> <Choice value="Dog"/> </Choices> </View>
If you want to specify a labeling configuration for your project without using the Label Studio UI, you can use the command line or the API.
You can define the labeling configuration in a
config.xml file and initialize a specific project in Label Studio with that file.
label-studio my_new_project start --label-config config.xml
You can configure your labeling configuration with the server API. See the Backend API documentation for more details.