Time per annotation
High
Cost per annotation
Expensive
Shape perception
Absent
Spatial perception
Present
Well-designed tools to support large number of classes of interest.
Consensus models to verify each of the annotations by multiple users for label accuracy & annotation perfection.
Recursive checks from multiple users to detect all the objects of interest in the frame.
Used to train computer vision models for spatial cognition from 2D images or videos. Relative distance of each mobile object from the ego car and vanishing point can be measured.
Used to build 3D simulated worlds from 2D information captured by cameras.
All shape annotations on single media
Support for hundreds of classes
Guaranteed highly accurate results
Contexual information from the data
Guaranteed accuracy. We know you’d have it no other way.
Use our API to get responses within minutes.
We do the heavy lifting so that you can relax.
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