Labelbox

What is Labelbox?

Labelbox is a data labeling platform for preparing training data for machine learning models. It provides annotation tools for images, videos, and text, helping teams produce high-quality labels. It also supports team collaboration, quality checks, and project management throughout the labeling process. By simplifying data labeling, Labelbox helps companies ship machine learning models faster with accurately labeled datasets.

Who created Labelbox?

Labelbox was founded by Manu Sharma. The company was officially started on February 17, 2021, as a software platform for managing data labeling for machine learning applications.

What is Labelbox used for?

• AI-assisted labeling and alignment
• Quality control over training data
• Building AI applications from the ground up
• Training and fine-tuning models
• Automating tasks with Labelbox Machine Learning Models
• Data curation and organization
• Labeling services
• Model training support and issue diagnosis
• Access to a global network of expert human labelers

Who is Labelbox for?

Labelbox serves a range of professionals, including data scientists, machine learning engineers, AI researchers, software developers, product managers, data analysts, image annotation specialists, QA testers, project managers, and business analysts.

How to use Labelbox?

1. Sign up for an account on the Labelbox platform.
2. Create a project with a name, description, and the type of data you’ll be labeling.
3. Import data such as images, videos, or text files.
4. Label data using annotation tools like bounding boxes, polygons, and classification. You can label yourself or assign tasks to team members.
5. Review quality by checking labeled data for accuracy and consistency, correcting mistakes as needed.
6. Collaborate by inviting team members and assigning specific tasks.
7. Iterate by incorporating feedback and refining labels over time.
8. Export data in your chosen format, ready for use in machine learning workflows.