Data labeling
for computer vision
Label images and videos and take full control of your training data.
Power your computer vision algorithm with datasets of any size.
Annotations we support
With Toloka, you can control data labeling accuracy to build a predictable pipeline of high-quality training data that impacts your CV algorithms. Our platform supports annotation for image classification, semantic segmentation, object detection and recognition, and instance segmentation. Labeling tools include bounding boxes, polygons and keypoint annotation.
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Real-time insights
Why Toloka
State-of-the-art technologies
Crowd management tools and quality control options backed by 10 years of industry experience and research
- Multiple quality control methods
- Adaptive crowd selection
- Smart matching mechanisms
Global crowd
Millions of Tolokers across every time zone for on-demand labeling, instant scaling, and multilingual projects
- 40+ languages, 100+ countries
- 200k+ monthly active Tolokers
- 800+ daily active projects
Robust infrastructure
Fault-tolerant high-load system for rapid
knowledge enrichment that prioritizes
data security and privacy- High throughput – 499M+ tasks per month
- GDPR-compliant, ISO 27001-certified
- Secure data storage options
For developers
Python SDK
Our Python toolkit covers all API
functionality to give you the full
power of TolokaJava SDK
Our Java client library provides a lightweight
interface to the Toloka API that works
in any Java enviroment
Have a data labeling project?
Take advantage of Toloka technologies. Chat with our expert to learn how to get reliable training data for machine learning at any scale.
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