Label at the speed of thought
Unlock the true value of your images with a data engine that's engineered for speed and accuracy. Anticipate and adapt to what your model needs with the most flexible annotations tools.
The standard in image labeling
With a focus on speed, simplicity and use case diversity, this is simply the most powerful vector labeling tool on the planet. It's also the most intuitive. Configure in minutes, scale up to any size team, and create the right training data through rapid iteration.
Supports bounding box, polygons, points, lines, segmentation, relationships, classifications, hierarchical classes and more.
Label faster than ever with automation
Achieve up to 80% in labeling efficiency gains with model-assisted labeling – use models to pre-label data, and let humans focus on corrective actions to generate ground truth so they don’t need to start from scratch.
Optimize time and costs with auto labeling
Using dynamic filters operating on the content, metadata, or text embeddings, automatically add a label on matching results at scale and queue them for human review.
Create better labels with more context
Bring additional attachments such as text, videos, images, overlays or even custom HTML widgets to aid data labelers to create perfect labels. Labelbox image editor is optimized to get the most out of your imagery data, quickly.
Access the world’s best labeling teams at a click of a button
Access the world’s best data labeling teams to label your data on demand, at scale. The data labeling teams are specialized in use-cases and languages spanning industries such as geospatial, insurance, healthcare and working with content in over 20 languages.
Your toolset to find and fix errors
Easily search for image data using filters such as annotation, metadata, and similarity embeddings to prioritize image to label or create review tasks to fix issues that matter the most.
“With Labelbox, we’re able to generate high-quality annotations by allowing our team of domain experts and labelers to collaborate more efficiently. The workflow we’ve built queues up all the work for our labelers to create image annotations, which are then sampled and reviewed by experts, and fed into ML models to make better AI diagnoses.”
Miao Zhang
AI Scientist
Genentech