If you are working with synthetic data and would like to learn more, check out the blogpost that demonstrates how to automatically detect issues in synthetic customer reviews data generated from the http://Gretel.ai LLM synthetic data generator. Source: 11 months ago

I was chatting with the founder of GretelAI recently and learned a lot about the area of synthetic data. Source: about 1 year ago

The requirement is to build out synthetic data with very similar size and shape to our production data and ideally have a framework to do this, maybe at some level use our data and "de-productionize" it. gretel.ai looks like it may be a fit, but from what I see I need to upload production data to their environment and that's a no-go. Source: over 1 year ago

> https://gretel.ai/ Where were you the last decade of my professional life? I couldn’t find anyone to take my money for exactly this. - Source: Hacker News / almost 2 years ago

[2] https://gretel.ai/blog/how-to-safely-work-with-another-companys-data. - Source: Hacker News / almost 2 years ago

Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision. - Source: dev.to / 6 months ago

CVAT has an open source repo under MIT license: https://github.com/opencv/cvat I've not worked with it directly but it might be a good place to start. Source: 6 months ago

An open source annotation tool that integrates object detectors is CVAT https://github.com/opencv/cvat however, using your own detector might require some coding. There is an integration for yolov5, but without modification it only loads the pretrained models. Source: about 1 year ago

This integration is currently available in the open-source version of Computer Vision Annotation Tool (http://github.com/opencv/cvat)! Please use it for your computer vision projects to segment images faster. - Source: Hacker News / about 1 year ago

You can download the CVAT docker from a github (Link) and install it yourself, keeping all data local. And here are two options - locally on your personal computer (or company server) or in your own cloud (there are instructions on how to do this with AWS). - Source: dev.to / about 1 year ago