Hasty’s end-to-end AI platform helps automate and accelerate the whole life-cycle of implementing vision AI in real life for agricultural, manufacturing, logistic, mining, and other industrial companies. Our data-centric platform allows companies with unique data to build and deploy vision AI applications faster and more reliably across any infrastructure – helping you bring value-added services to your product.
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Based on our record, Computer Vision Annotation Tool (CVAT) should be more popular than Hasty.ai. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Try https://hasty.ai, seems to be pretty much exactly what you're looking for. Source: over 2 years ago
At hasty.ai, we're working on agile ML tooling for vision AI to help our users get to production more reliably. A huge part of this is to automate and speed the data preparation process. Source: over 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 / 5 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: 5 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: 12 months 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
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