Overview
The LightlyOne Worker internally uses our open-source Lightly Python Client to allow you to use self-supervised learning in a straightforward and efficient way and even create embeddings of your unlabeled data. However, we can do much more than just train and embed datasets. Once you have embeddings of your data, you might still require some labels to train a model. But which samples do you pick for labeling and training a model?
This is exactly why we built the LightlyOne Platform. The platform helps you analyze your unlabeled data, keep track of your dataset and, by using various methods, pick the relevant samples for your task.
The video below gives you a quick tour of the platform:
Core Concepts
Analyze and Filter
Advanced
Additional Concepts
Further concepts of the LightlyOne Platform can be found in our Glossary
Updated 3 months ago