We teach cars how to see the world
At Figure Eight, we work with Tier 1 and Tier 2 suppliers, OEMs, and more to create high-quality training data for self-driving car projects. We specialize in image annotation, doing everything from simple image classification to bounding boxes to semantic segmentation. So however you’re approaching the problem, we can help.
Bounding boxes are often used to identify the most important classes in a computer vision model and our platform quality controls and baked-in machine learning make sure those boxes are accurate.
Lines and polygons are typically used to mark lane lines and other important road markers for self-driving algorithms. Our line tool can also be used to outline oddly shaped or occluded objects.
More and more, autonomous vehicle algorithms are relying on exacting pixel-level labeling. We support dozens of classes per image and have the capacity to label massive datasets quickly–and most importantly–accurately.
Overlapping objects or myriad instances of one class in a single image can sometimes be confused for your models. That’s why we pioneered instance-based pixel labeling. Ask us if it can work for your use case.
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