Computer Vision Annotation Tool (CVAT)
AWS SageMaker Ground Truth
Labelbox
Supervisely
Segments.ai
V7
SuperAnnotate
Hasty.ai
Universal Data Tool
Labelbox
CrowdFlower
Supervisely
Amazon Mechanical Turk
Labeling AI
Segments.ai
Playment
The Universal Data Tool (UDT) is an open-source web or downloadable tool for labeling data for usage in machine learning or data processing systems.
The Universal Data Tool supports Computer Vision, Natural Language Processing (including Named Entity Recognition and Audio Transcription) workflows.
The UDT uses an open-source data format (.udt.json / .udt.csv) that can be easily read by programs as a ground-truth dataset for machine learning algorithms.
Computer Vision Annotation Tool (CVAT) Universal Data ToolBased on our record, Computer Vision Annotation Tool (CVAT) seems to be more popular. 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.
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
AWS SageMaker Ground Truth - Build highly accurate training datasets using machine learning and reduce data labeling costs by up to 70%.
Labelbox - Build computer vision products for the real world
CrowdFlower - Enterprise crowdsourcing for micro-tasks
Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...
Segments.ai - Multi-sensor labeling platform for robotics and autonomous driving
Amazon Mechanical Turk - The online market place for work.
