Etiketai — speed up training your AI models with a free open source app

A little bit of context

  • Not available in all devices. It can only be downloaded as a desktop application.
  • Requires installation. It requires installation and it isn’t very beginner-friendly. Depending on your OS and Python version the dependencies will be different. For example on Mac with Python 3+, you need to install first some dependencies like qt and libxml2 with Homebrew, and pyqt5 and lxml with pip.
  • Security. The application manipulates the files on your system. In theory, it only manipulates files related to annotations. I say “in theory”, because we hope there won’t be a bug in the future touching what it shouldn’t…
  • Updates are not automatic. Related to the previous point, many updates are made for security reasons, especially if it has dependencies. The fact that updates are not done automatically makes it your responsibility to keep your application up to date.

Launching Etiketai

  • Available in all devices. Being a web application makes it accessible from any device, even tablets, and mobiles.
  • No installation required. It speeds up the start, as it does not require installation and has no dependencies on your operating system. Only the browser.
  • Automatic updates. You will always have the latest version available.
  • Security. No file on your system is directly manipulated. Files are imported/saved using the security layer of your browser.
  • Beginner-friendly. We want it to be an easy-to-use process without losing flexibility. To start, you only need to open a browser with any device.
Etiketai demo
  • Improve tablet / mobile experience. Now the support is minimal, it works, but not as well as some users would like. For example, it is not very responsive. This should be improved in a next version.
  • Possibility to train directly your labeled images with the same app and also to save the generated model.
  • Offline support. Now it only works online, but one of the improvements would be to support it offline as PWA.

Try it



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