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
You can find more information here Waiting for your feedback here: Discord, LinkedIn, Gitter, GitHub. Source: over 1 year ago
I use CVAT for all my projects: Https://github.com/opencv/cvat. Source: over 1 year ago
It really depends on what you are trying to achieve, what your budget is, and where you are in your model development cycle. Nevertheless, I would recommend starting in self-service mode with the simplest tool you can find. This might be something like CVAT, though there are a number of other options (paid, free, SaaS, etc.) out there that a simple google search will return. Once you're ready to scale, you might... Source: over 1 year ago
For image annotations, have you seen CVAT? https://github.com/opencv/cvat/. Source: over 1 year ago
The post examines the implementation of Identity and Access Management (IAM) in the Computer Vision Annotation Tool (CVAT), which is a part of the OpenCV ecosystem. CVAT helps to annotate raw images and video files to produce a ready-to-use Computer Vision dataset in popular formats such as MS COCO, PASCAL VOC, YOLO, etc. Here we will cover:. Source: over 1 year ago
I recently completed a project leveraging CVAT, and it was a great experience. You can export the annotations in different formats, load the images one by one, split videos up by frame, etc. It is probably not the best one out there, but it's free and did the job for me. They even have a hosted online version for smaller projects. Source: over 2 years ago
Check out CVAT. Has assisted labeling and can output in YOLO format. Source: almost 3 years ago
CVAT - Very similar to labelstudio (but was done first). Source: almost 3 years ago
CVAT is an option that’s available now. It includes the front end which is nice Https://github.com/openvinotoolkit/cvat. Source: almost 3 years ago
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