Automotive
AI in the Automotive industry. Training data for ai-backed autonomous driving.
AI is changing the way that we travel. Autonomous vehicles are becoming commonplace on roads across the world, promising safer and more efficient travel. Keylabs is the ideal annotation tool for developers seeking to innovate in this vital and growing sector. Unique data management features and project management capabilities allow automotive AI developers to craft varied, high-quality annotated datasets at scale.

Use cases
Autonomous driving
Powerful annotated video data results in more reliable self-driving vehicles
In-cabin AI
Powerful annotated video data results in more reliable self-driving vehicles
Recognition of surroundings:
Powerful annotated video data results in more reliable self-driving vehicles
Lane recognition
Powerful annotated video data results in more reliable self-driving vehicles




If you are developing a unique computer vision use case for the automotive industry, reach out to us. Keylabs is an adaptable platform that can fit the needs of the most innovative AI projects.
Securing your data

Take control of your labeling process with unique annotation tool features
Annotation projects can be a time-consuming distraction for busy managers and engineers. Keylabs was designed by annotation experts to accelerate the labeling of image and video data without compromising on the quality of training datasets. Core capabilities include:
Z order
Parent / Child
In / out
Unique visual id
Metadata
Project Management
Metrics
Annotation types
Keylabs gives developers access to a full suite of annotation techniques:
Bounding Box
most common annotation type,
used to locate objects
Polygon
connecting lines describe
irregular shapes
Polyline
used to identify linear pathways
Bitmask
links individual pixels to specific objects, allowing for annotations that are separated or contain gaps
Points
allows you to label points of
interest
Skeletal
tracks human movements from
frame to frame
