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.

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Use cases

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Autonomous driving

Powerful annotated video data results in more reliable self-driving vehicles

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In-cabin AI

Powerful annotated video data results in more reliable self-driving vehicles

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Recognition of surroundings:

Powerful annotated video data results in more reliable self-driving vehicles

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Lane recognition

Powerful annotated video data results in more reliable self-driving vehicles

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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

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Using the Keylabs annotation tools comes with a commitment to data safety. Keylabs employs a range of security measures to protect valuable and sensitive data. This includes comprehensive infrastructure security if you choose to access Keylabs through the cloud. Alternatively, Keylabs can be installed on premises, guaranteeing you total control over access. We will continue to emphasize data protections as a priority by utilizing a diverse array of security measures and industry best practices.

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:

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Z order

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Parent / Child

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In / out

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Unique visual id

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Metadata

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Project Management

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Metrics

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Annotation types

Keylabs gives developers access to a full suite of annotation techniques:

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Bounding Box

most common annotation type,
used to locate objects

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Polygon

connecting lines describe
irregular shapes

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Polyline

used to identify linear pathways

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Bitmask

links individual pixels to specific objects, allowing for annotations that are separated or contain gaps

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Points

allows you to label points of
interest

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Skeletal

tracks human movements from
frame to frame

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