Ask performers to draw pixelwise boundaries for each object instance or group of objects.
Ask performers to identify objects in images that match certain classes and use bounding boxes to mark the location.
Ask performers to identify objects in images that match certain classes and draw pixel-perfect polygons around the exact shape.
Performers can label feature details in human faces to identify facial landmarks, expressions or emotions.
Use Yandex.Toloka to classify images by matching visual content with one or more pre-defined categories.
Ask performers to transcribe text in PDF files. Use labeled data to train your text recognition algorithms, or validate and fine-tune the output of your own OCR models.
Use side-by-side image comparisons to verify or clean up your data. Ask crowd performers to look at two images and pick which one is better.
Collect datasets of videos or images related to a common theme, or with a specific type of lighting or environment. Ask crowd performers to record video snippets according to your specifications and instructions.
Ask performers to draw pixelwise boundaries for each object instance or group of objects.
Konstantin Simonchik, science director and co-founder of ID R&D:
"Using Yandex.Toloka, we collected the world's largest database of 200,000 unique photos and videos to secure biometric systems against hackers and train neural networks to distinguish real faces from fakes. We chose Yandex.Toloka because of the user-friendly interface, active performers and optimal quality for the price."
Dmitry Akimov, VisionLabs data engineer:
"Yandex.Toloka is an excellent tool for data processing. We use it to collect and annotate thousands of images and videos every month in order to improve the performance of our algorithms.
We chose Yandex.Toloka because of the fast turnaround time and the active participation of performers."
Alexey Hahunov, founder and CTO of Dbrain, IT company and Y Combinator alumnus:
"Yandex.Toloka helped us tackle the challenge of recognizing handwritten text in documents. We send anonymous text fragments to Yandex.Toloka, where qualified performers rewrite the text and send the results back to the Dbrain system for further AI training. This meant we were able to resolve even the most difficult recognition cases for our customers."
Anton Slesarev, head of Technologies in the self-driving cars division at Yandex:
"Toloka is my favorite Yandex service and the first place we go to prepare data for AI. To train the neural network, we need tens of thousands of annotated images. You can buy them for $4 each, or you can have images marked up in Yandex.Toloka 10 times cheaper and get datasets that are ready to use for training algorithms. We use these datasets for developing self-driving vehicle technology."
Konstantin Simonchik, science director and co-founder of ID R&D:
"Using Yandex.Toloka, we collected the world's largest database of 200,000 unique photos and videos to secure biometric systems against hackers and train neural networks to distinguish real faces from fakes. We chose Yandex.Toloka because of the user-friendly interface, active performers and optimal quality for the price."
Dmitry Akimov, VisionLabs data engineer:
"Yandex.Toloka is an excellent tool for data processing. We use it to collect and annotate thousands of images and videos every month in order to improve the performance of our algorithms.
We chose Yandex.Toloka because of the fast turnaround time and the active participation of performers."
Alexey Hahunov, founder and CTO of Dbrain, IT company and Y Combinator alumnus:
"Yandex.Toloka helped us tackle the challenge of recognizing handwritten text in documents. We send anonymous text fragments to Yandex.Toloka, where qualified performers rewrite the text and send the results back to the Dbrain system for further AI training. This meant we were able to resolve even the most difficult recognition cases for our customers."
Anton Slesarev, head of Technologies in the self-driving cars division at Yandex:
"Toloka is my favorite Yandex service and the first place we go to prepare data for AI. To train the neural network, we need tens of thousands of annotated images. You can buy them for $4 each, or you can have images marked up in Yandex.Toloka 10 times cheaper and get datasets that are ready to use for training algorithms. We use these datasets for developing self-driving vehicle technology."