Robotics

High-quality data labeling for robotics machine learning - from factories to industrial projects, household appliances, and more.

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Expert Labeling
of Robotics Data

Robotics Data Annotation services for a wide range of computer vision applications.

Keymakr provides Computer Vision annotation for robotics AI with highly accurate training and validation data.

The development of artificial intelligence for robotics promises to transform a wide range of industries. This technology will increase manufacturing efficiency, improve quality control, and increase the safety of both our homes and production lines. We developed a cutting-edge annotation platform and employ experienced teams of annotators to support any robotics applications your team is working on:

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Robotics
Annotation Types

01. Automatic Annotation

Fast AI-assisted labeling for your CV data - our team will implement quality control measures to ensure the accuracy of every frame.

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Automatic Annotation

02. Bounding Box

Label individual objects in your vision system and track them between frames with this simple and flexible technique.

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03. Oriented Bounding Box

Some objects may be angled or oriented - we employ this technique to teach AI more specific directions for recognition.

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Oriented Bounding Box

04. Cuboid

This is handy for extrapolating 3-dimensional objects from images - for example, an approximate volume of a car or a container.

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05. Polygon

Helps label non-standard shapes such as production objects, household items, furniture, and anything else your robotics system needs.

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06. Semantic Segmentation

Annotate everything in a given image or video, including the background to provide accurate labels for precise training.

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Semantic Segmentation

07. Instance Segmentation

More complex spin on semantic segmentation, we individually label and color every single instance of an object for specialized datasets.

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Instance Segmentation

08. Skeletal

Helps your robotics systems recognize humans and animals by assigning limbs and body shapes to objects.

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09. Key Points

Used for granular images where detail matters - precision lasers, emotion recognition for household robots or appliances, and so on.

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10. Lane

Label lanes such as roads, conveyors, paths, and so on for your robotics systems to get more familiar with the infrastructure.

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11. Bitmap

Helps robotics understand continuity by labeling separated or partial objects as belonging to the same entity.

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12. 3D Point Cloud

More advanced process that involves using lidar to help robots understand 3-dimensional space and relationships between objects.

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13. Custom

Every robotics AI has unique needs and it’s our job to help you mix and match annotation techniques for perfect training datasets.

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13

Need
custom solution

Professional Data Annotation
for Robotics

Get accurately labeled data for your robotics projects from leading annotation teams!

01. Clean Datasets for Robotics AI

Datasets for Robotics AI

Precise image and video annotation helps machine vision increase inspection rates without sacrificing accuracy:

Properly trained cameras can help manufacturing robots consistently spot the slightest manufacturing defects missed by the human eye.
Emotion and facial recognition data can help household robots understand human behavior and offer better services.
Food handling robotics can learn to better distinguish items to simplify handling and safety.
Medical robotics systems can accurately diagnose patients and even offer surgical assistance with the right data.

02. Use Cases for Robotics Datasets

Image and video labeling serve a crucial role in automation and robotics. Keymakr can support the development of this technology in any environment thanks to our annotation experience, skilled in-house teams, and unique annotation tools. Get clean data for:

Object detection
Environmental sensing
Inventory and logistics
Inventory sorting
Quality control
Predictive maintenance
Waste management

03. Environmental Perception

Environmental Perception

Highly functional industrial robots can recognize objects and map their path without hitting any obstacles. This training comes from carefully annotated datasets of images and videos.

Video annotation allows a computer vision model to recognize objects in its environment and interact with them or avoid them as necessary. This technology has the potential to greatly improve safety on the production line and increase the efficiency of manufacturing operations.

04. Waste Management

Waste Management

Robots are actively used in industries like waste management to help humans avoid potentially dangerous situations and hazardous conditions.

To effectively sort the waste and identify recycling materials, industrial robots will need a carefully prepared dataset with manual annotation and classification of different waste types. This is just one example of many where computer vision systems revolutionize the way we treat processes.

Reviews
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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...

Meet
Keylabs

We created a proprietary annotation platform with enterprise-grade tools capable of achieving pixel-perfect labeling for all your AI training datasets.

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Keylabs can help you handle annotation projects of any complexity. Our platform was originally created for internal use, so usability and quality are main priorities. Keylabs features a full suite of annotation techniques that can be adapted for your specific needs.

You can work with projects of any size and label vast quantities of data. The in-built management tools will help you collaborate on projects and get the most out of your data.

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