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High-quality data labeling for the automotive industry - from the manufacturing and assembly process to training data for autonomous vehicles.

Expert Labeling
of Automotive Data

Image & Video Annotation for Autonomous Vehicles and the Automotive Industry.
Image & Video Annotation for Autonomous Vehicles

Keymakr provides professional data annotation for autonomous vehicles. Our experienced in-house annotation teams will ensure that your machine learning for self-driving car projects go smoothly.

Our proprietary annotation platform features a full suite of annotation techniques that can be adapted for your specific needs. Our annotators are comfortable working with all types, and qualities of data. We can also collect data for you from legal, open-source repositories, or even create bespoke data with our in-house studio.

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Annotation Types

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01. Automatic Annotation

Using machine learning for fast and accurate annotation of your automotive data - the labeling process is curated by humans for accuracy.

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Automatic Annotation

02. Bounding Box

Among the most common types of annotation in the automotive industry, bounding boxes help you label objects quickly and efficiently.

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Bounding Box

03. Oriented Bounding Box

Helps us label target objects received from automotive images or videos with added precision by placing them at the right angle.

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Oriented Bounding Box

04. Cuboid

Simulates 3D qualities of an object such as weight and height. Useful to classify other cars or trucks in your datasets.

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05. Polygon

Outlines more complex and irregular shapes that don’t normally fit into other categories. Useful for more specific automotive data.

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06. Semantic Segmentation

Classifies objects to carefully catalog entire scenes - including the whole highway, backgrounds, sky, and so on.

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Semantic Segmentation

07. Instance Segmentation

Creates individual labels for every single instance of your object, used for complex scenes where detail matters.

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Instance Segmentation

08. Skeletal

Represents a human with the help of connected lines - useful for classifying drivers, their posture, and position.

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09. Key Points

A granular method often used for individual parts of faces - it helps detect fine details such as emotions, tiredness, etc.

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Key Points

10. Lane

Annotates lanes and roads in given automotive data for proper recognition by your computer vision systems.

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11. Bitmap

Identifies separated parts of your image or video as belonging to the same object - useful for incomplete or complex scenes.

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12. 3D Point Cloud

Complex data with entire 3D environments where specific coordinates and spatial measurements matter.

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3D Point Cloud

13. Custom

Combines different types of annotation for your automotive data to perfectly match the specific needs of your training process.

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Custom annotation

Professional Data Annotation
Autonomous Vehicles


Get accurately labeled data for your computer vision systems in the automotive industry!

01 Annotation for in-cabin AI

Keymakr in-cabin applications in autonomous vehicles:

  • In-cabin behavior monitoring
  • Emotion recognition
  • In-cabin object recognition
  • Driver's assistant

02 Use Cases

  • Driver Monitoring Systems analyze multiple factors including road conditions, steering response, facial expression and gaze to determine if the driver is dozing off at the wheel.
  • Keymakr can annotate drivers’ faces and expressions up to a pixel-perfect level of detail.
  • Semantic segmentation of all objects in the car including people can help detect forgotten items or even pets forgotten in cars.
  • Skeletal annotation and movement tracking of the driver and passenger.
  • In-cabin AI is made possible by careful annotation. Keymakr’s unique project management systems empower developers by delivering valuable annotated video data quickly and at an affordable price.

03 Best Performing AI Starts with Accurately Annotated Data

We offer training visuals for self-driving cars, as well as custom image annotation solutions for autonomous vehicles and other AI-backed transportation systems.

A fully functioning and safe autonomous vehicle must be competent in a wide range of machine-learning processes before it can be trusted to drive on its own. From processing visual data in real-time to safely coordinating with other vehicles via IoT, the need for AI is essential. Self-driving cars could not do any of this without a huge volume of different types of training data, created and tagged for specific purposes.

To guarantee accuracy for your computer vision project, Keymakr utilizes three layers of human verification, followed by a final automated quality assurance check. By making use of multiple layers of verification it is possible to create error-free annotated training data for autonomous vehicle deep learning.

04 Artificial Intelligence Drives Intelligent Cars

The number of autonomous cars and algorithms being tested on the road increases yearly. Accurate perception of the driving environment requires enormous amounts of data to be captured and carefully annotated.

AI learns to recognize the surroundings, detecting vehicles and objects, roads, lanes, road signs, traffic lights, and other potential real-time hazards. Deep neural network algorithms may yet enable autonomous cars to drive better than human-driven cars, achieving safer and more effective transportation.

Overcoming data bias is critical for the success of AI in autonomous driving. Keymakr can play a part in troubleshooting persistent bias problems by creating and labeling varied, bespoke datasets. Our experienced teams of annotators can take on the burden of image and video annotation so that your data accurately reflects nighttime driving, low visibility weather, or road conditions in different countries.


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"Delivering Quality and Excellence"

The upside of working with Keymakr is their strategy to annotations. You are given a sample of work to correct before they begin on the big batches. This saves all parties time and...


"Great service, fair price"

bility to accommodate different and not consistent workflows.
Ability to scale up as well as scale down.
All the data was in the custom format that...


"Awesome Labeling for ML"

I have worked with Keymakr for about 2 years on several segmentation tasks.
They always provide excellent edge alignment, consistency, and speed...



We bring deep hands-on experience with validating, labeling, and creating data to your project so you can focus on what you
do best - developing amazing solutions.

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Keymakr started with a core team of 10 employees in 2015 and grew to employ over 1000 in-house team members in just two years. We are not only helping to create the best AI possible, we are
creating jobs for people that are as passionate as we are about technology.

To achieve this, we created a proprietary data annotation platform that enables us and our partners to provide high-quality clean data to anyone in need of it.

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