Set up your labeling project

All labeling activities in Label Studio occur in the context of a project.

After you start Label Studio and create an account, create a project to start labeling your data.

1. Create a project
2. Import data.
3. Select a template to configure the labeling interface for your dataset. Set up the labeling interface for your project.
4. (Optional) Set up instructions for data labelers.

Create a project

When you’re creating a project, you can save your progress at any time. You don’t need to import your data and set up the labeling interface all at the same time, but you can.

1. In the Label Studio UI, click Create.
2. Type a project name and a description. If you want, choose a color for your project.
3. If you’re ready to import your data, click Data Import and import data from the Label Studio UI. For details about import formats and data types, see Get data into Label Studio.
4. If you’re ready to set up the labeling interface, click Labeling Setup and choose a template or create a custom configuration for labeling. See Set up the labeling interface for your project on this page.
5. When you’re done, click Save to save your project.

After you save a project, any other collaborator with access to the Label Studio instance can view your project, perform labeling, and make changes. To use role-based access control, you need to use Label Studio Enterprise Edition.

Set up the labeling interface for your 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.

1. Select a template from the available templates or customize one.
2. Label Studio automatically selects the field to label based on your data. If needed, modify the selected field.
3. Add label names on new lines.
4. (Optional) Choose new colors for the labels by clicking the label name and choosing a new color using the color selector.
5. Configure additional settings relevant to the labeling interface functionality. For example, when labeling text you might have the option to Select text by words.
6. Click Save.

Modify the labeling interface

You can make changes to the labeling interface and configuration in the project settings.

1. In Label Studio UI, open the project you want to modify.
2. Click Settings.
3. Click Labeling Interface.
4. 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.

Delete tasks or annotations

If you have duplicate tasks, or want to remove annotations, you can delete tasks and annotations from Label Studio.

1. In Label Studio UI, open the project you want to update.
2. Filter the Data Manager page to show only the data you want to delete. For example, specific annotations, or tasks annotated by a specific annotator.
3. Select the checkboxes for the tasks or annotations that you want to delete.
4. Select the dropdown with the number of tasks, and choose Delete tasks or Delete annotations.
5. Click Ok to confirm your action.

If you want to make changes to the labeling interface or perform a different type of data labeling, first select all the annotations for your dataset and delete the annotations.

Customize a template

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.

See All Available Tags

Example labeling config

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>

This labeling config references the image resource in the Image object tag, and specifies the available labels to select in the Choices control tag.

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>

Set up labeling config in other ways

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.

Add a labeling config from the command line

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

Add a labeling config with the API

You can configure your labeling configuration with the server API. See the Backend API documentation for more details.

Set up instructions for data labelers

In the project settings, you can add instructions and choose whether or not to show the instructions to annotators before they perform labeling.

1. Within a project on the Label Studio UI, click Settings.
2. Click Instructions.
3. Type instructions and choose whether or not to show the instructions to annotators before labeling.
4. Click Save.
   Click the project name to return to the data manager view.

Annotators can view instructions at any time when labeling by clicking the (i) button from the labeling interface.

Where Label Studio stores your project data and configurations

All labeling activities in Label Studio occur in the context of a project.

Starting in version 1.0.0, Label Studio stores your project data and configurations in a SQLite database. You can choose to use PostgreSQL or Redis instead. See Sync data from cloud or database storage.

In versions of Label Studio earlier than 1.0.0, when you start Label Studio for the first time, it launches from a project directory that Label Studio creates, called ./my_project by default.

label-studio start ./my_project --init

Project directory structure

In versions of Label Studio earlier than 1.0.0, the project directory is structured as follows:

├── my_project
│   ├── config.json     // project settings
│   ├── tasks.json      // all imported tasks in a JSON dictionary: {task_id: task}
│   ├── config.xml      // labeling config for the current project
│   ├── completions     // directory with all completed annotations stored in one file for each task_id 
│   │   ├── <task_id>.json
│   ├── export          // stores archives with all results exported from Label Studio UI 
│   │   ├── 2020-03-06-15-23-47.zip

Warning: Modifying any of the internal project files is not recommended and can lead to unexpected behavior. Use the Label Studio UI or command line arguments (run label-studio start --help) to import tasks, export completed annotations, or to change label configurations.