Computer Vision

We provide the training data that teaches machines how to see the world

Machines need training data to learn how to see the world. But raw images aren’t enough. After all, people don’t have a problem identifying a can of soda or a mother pushing a stroller in a .jpg, but to an untrained machine, those are just collections of different pixels. Annotated images teach AI how to see the world.

We understand that different machine learning experts use different approaches for different initiatives and we support every major enrichment strategy. Our platform powers:

Bounding Boxes

Bounding boxes are frequently used to identify objects in images from your pre-existing ontologies. Tell us what’s important and we’ll create the training data to power your models.

Dots

Dots help identify key points in images. They’re often used for training gesture or facial recognition models.

Pixel labeling semantic segmentation (PLSS)

Pixel-level labeling help a machine understand every part of an image. We understand what you need to train your models and our tool helps human annotators label every inch of your photo quickly and accurately.

Instance-based PLSS

A row of cars or a cluster of cells often need to be labeled individually so a model can understand each instance of an object. We can help you create a robust labeling schema for your project so you can get the discrete annotations you need.

Whether you’re looking to annotate the topology of the world from an orbiting satellite or label the cells from a microscopy image, we’ve got you covered. Our platform combines human and machine intelligence to power high-quality annotation for autonomous vehicles, medical imagery, consumer packaged goods, and more.

Figure Eight & Blue River Technology

“Walking through the field, taking tallies on how many weeds we hit, how many we missed, and our accuracy was in the high 90s on that test.
We’re really excited about bringing this technology to the farmer and using AI to really modernize farming.”

– Chris Padwick,
Tech Fellow, Machine Learning Team Lead, Blue River Technology

Trusted by today’s leading brands

Related Resources

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Introducing Instance-Based Pixel Labeling

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eBook: What We Learned Labeling 1 Million Images

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