Roboflow + Labelbox

Upload a Labelbox JSON export to Roboflow to convert it, train a model on it and deploy the model.

Labelbox is a data labeling platform used by teams that bring their own labelers or buy labeling as a service. Roboflow takes over once the labels exist.

The handoff is a file. Roboflow reads Labelbox JSON, the per-label export with geometry for each class, plus Labelbox's video JSON for labeled video frames. Upload the export with your images, and Roboflow keeps the class names, converts the labels to the format your model needs, and lets you train and deploy from the same project.

How to connect Labelbox to Roboflow

4 steps
  1. Export labels from Labelbox

    Export your project's labels from Labelbox as JSON.

  2. Create a Roboflow project

    Create a project with the same task type as your labels, for example object detection.

  3. Upload the export

    Drag the JSON file onto the upload page. Roboflow asks whether to fetch the images from Labelbox or use images you upload.

  4. Generate a version and train

    Generate a dataset version with preprocessing and augmentation, then train a model such as RF-DETR.

What teams build with Labelbox

  • Train on labels bought from a labeling service

    Bring a finished Labelbox project into Roboflow and train a model without writing a parser.

  • Convert Labelbox labels to another format

    Export the same labels as COCO, YOLO or Pascal VOC from Roboflow for training elsewhere.

Questions

Roboflow reads Labelbox JSON and Labelbox video JSON. Check the structure on our format pages before exporting a large project.

Yes. Upload each new export to the same Roboflow project and generate a new version when you are ready to retrain.

Why are companies choosing Roboflow?

The end-to-end platform for vision AI: create datasets, train models and deploy to production.

  • Flexible deployment modes

    Move from a scalable cloud API to edge hardware like NVIDIA Jetson without managing complex dependencies.

  • Integrated workflow builder

    Combine multiple AI models, custom business logic and third-party integrations into one production-ready pipeline in a low-code editor.

  • Model monitoring and alerts

    Dashboards track confidence, inference time and request volume for your deployed models, and email alerts tell your team when confidence suddenly drops.

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