A machine learning model is only as good as its training data. Labelbox is an end-to-end platform to create and manage high-quality training data all in one place, while supporting your production pipeline with powerful APIs.
When every pixel matters, you need accurate and intuitive image segmentation tools. Customize the tools to support your specific use case, including instances, custom attributes and much more.
Bounding box
Points & lines
Polygons
Instance segmentation toolkit (pen & superpixels)
Supports complex ontologies with nested classifications
Support for tiled imagery (slippy maps)
Label directly on the video up to 30 FPS with frame level. Additionally, Labelbox provides per frame label feature analytics enabling you to create better models faster.
Learn moreLabel text strings, conversations, paragraphs, and documents with fast & customizable classification and named entity recognition tools.
Text classification
Named entity recognition (beta)
Supports complex ontologies with nested classifications
Label data with internal and external teams simultaneously. Review annotations collaboratively. Keep track of activity and progress.
Manage access to data and projects for your internal team members. Ensure access controls when working with a labeling service.
Stay in the loop on internal and external labeler productivity and work quality.
Scale your labeling project with one-click outsourcing to one or multiple labeling services.
Labelbox provides tools and workflows to choose the right data to label as well as pre-label the data with your models
Seed un-labeled data with model predictions as a starting point for the annotation process. Use your own model by integrating it with the Labelbox Prediction API.
Always label the most important data with API driven labeling queue prioritization. This technique can greatly improve labeling productivity. Combine this with model-predicted labels as a starting point for the annotation process to see the largest improvements.
Knowing feature counts and object analytics for your training data means informed decision making about the state of your model capabilities today and how to improve them. Labelbox puts all of this information and more at your fingertips.
Get accurate insights into human labeling performance. Labelbox provides the ultimate transparency and standardization across internal and external labeling teams.
Labelbox is API-first so you can use it as infrastructure for your training data pipeline. Use our GraphQL and Python APIs to stream data into Labelbox, push labeled data into training environments, and programmatically work with your data.
import Labelbox
image_url = 'https://labelbox.com/tesla_model3.jpg'
datasets = Labelbox.datasets()
Labelbox.add_row_to_dataset({
'dataset_id': datasets[0]['id'],
'data': image_url
})
Import data row
Import labels
Import model prediction
Export label
Search, browse and curate all of your training data in one place. Investigate bad or inconsistent labels. Improve your training data collaboratively.