[How To] OpenCV Video Player

[How To] OpenCV Video Player

Apr 27, 2021 | How To

OpenCV Video Player   In one of our latest blog posts we introduced video labeling feature. This article introduces our new video features within our  Python API. We implemented export labels functionality to export the whole project as well as a specific project...
[How To] Prepare and Upload Coco Labels

[How To] Prepare and Upload Coco Labels

May 4, 2020 | How To

Prepare and Upload Coco Labels to DATAGYM   In one of our latest Blog posts we introduced how to use our “Python API”  to import annotated image data directly into your DATAGYM Projects. The feature enables users to inspect and correct the results of...
[Feature introduction] Review Labels

[Feature introduction] Review Labels

Apr 29, 2020 | Feature Introduction

New Feature: Review Labels   Sophisticated machine learning projects can quickly grow in size, encompassing thousands of images to annotate and a large number of people working on a single project simultaneously. As a project manager, it is often hard to keep...
[How To] Upload Label Predictions with Python

[How To] Upload Label Predictions with Python

Apr 8, 2020 | How To

Upload Label Predictions with our Python API   In our latest Blog post we introduced the “Import Label” feature which allows DataGym users to import their annotated image data directly into their DataGym Projects. The feature enables users to inspect...
Together against Coronavirus (COVID-19)!

Together against Coronavirus (COVID-19)!

Mar 24, 2020 | General

MDs, researchers, medical labs, clinics, scientists, data engineers – if you need an image annotation tool to fight #coronavirus and label e.g. x-ray images, then we offer our platform www.datagym.ai for FREE. Please send an email to support@datagym.ai and we’ll be...
The No. 1 Productivity Killer in Machine Learning Projects

The No. 1 Productivity Killer in Machine Learning Projects

Feb 10, 2020 | General

The 80/20 Data Science Dilemma Most of you that are familiar with machine learning may have heard of the 80/20 dilemma: It roughly states, that data scientists and machine learning experts spend about 80 % of their time for generating, preparing and labeling data and...