Import pre-annotated data into Label Studio

If you have predictions generated for your dataset from a model, either as pre-annotated tasks or pre-labeled tasks, you can import the predictions with your dataset into Label Studio for review and correction. Label Studio automatically displays the pre-labels that you import on the Labeling page for each task.

To import predicted labels into Label Studio, you must use the Basic Label Studio JSON format and set up your tasks with the predictions JSON key. The Label Studio ML backend also outputs tasks in this format.

You must use different IDs for each task elements, annotations, predictions and their result items.

Example of importing predicted labels

For example, import predicted labels for tasks to determine whether an item in an image is an airplane or a car.

Use the following labeling configuration:

<View>
  <Choices name="choice" toName="image" showInLine="true">
    <Choice value="Boeing" background="blue"/>
    <Choice value="Airbus" background="green" />
  </Choices>

  <RectangleLabels name="label" toName="image">
    <Label value="Airplane" background="green"/>
    <Label value="Car" background="blue"/>
  </RectangleLabels>

  <Image name="image" value="$image"/>
</View>

After you set up an example project, import this task into Label Studio. Save it as a file first, for example, example_prediction_task.json.

{
  "data": {
    "image": "http://localhost:8080/static/samples/sample.jpg" 
  },

  "predictions": [{
    "result": [
      {
        "id": "result1",
        "type": "rectanglelabels",        
        "from_name": "label", "to_name": "image",
        "original_width": 600, "original_height": 403,
        "image_rotation": 0,
        "value": {
          "rotation": 0,          
          "x": 4.98, "y": 12.82,
          "width": 32.52, "height": 44.91,
          "rectanglelabels": ["Airplane"]
        }
      },
      {
        "id": "result2",
        "type": "rectanglelabels",        
        "from_name": "label", "to_name": "image",
        "original_width": 600, "original_height": 403,
        "image_rotation": 0,
        "value": {
          "rotation": 0,          
          "x": 75.47, "y": 82.33,
          "width": 5.74, "height": 7.40,
          "rectanglelabels": ["Car"]
        }
      },
      {
        "id": "result3",
        "type": "choices",
        "from_name": "choice", "to_name": "image",
        "value": {
          "choices": ["Airbus"]
        }
      }
    ]
  }]
}

In this example there are 3 results inside of 1 prediction:

• result1 - the first bounding box
• result2 - the second bounding box
• result3 - choice selection

In the Label Studio UI, the imported prediction for this task looks like the following: