Computer Vision Annotation Tool (CVAT)
CVAT is an open source computer vision annotation tool for labeling images and video. It allows for collaborative annotation of datasets with features like predefined tags, interpolation of bounding boxes across frames, and review/acceptance workflows.
image-annotation
video-annotation
computer-vision
open-source
Computer Vision Annotation Tool (CVAT)
Open source tool for collaborative image & video annotation, featuring predefined tags, bounding box interpolation, and review workflows
What is Computer Vision Annotation Tool (CVAT)?
CVAT is an open source web-based tool for computer vision annotation and labeling of images, video, and other data. It allows users to draw bounding boxes, segment objects, track objects across frames, assign tags, and more. Some key features of CVAT include:
- Platform agnostic - works in any modern browser
- Annotation tracking - interpolate bounding boxes across multiple frames
- Predefined tags - quickly assign common tags to annotations
- Review system - create review/acceptance workflows for annotation quality control
- Collaborative - multiple users can work on the same projects
- Plugin ecosystem - supports writing plugins to extend functionality
CVAT is implemented using modern web development stacks including Django, React, and Canvas. It can be self-hosted on an internal server or hosted in the cloud. The goal of CVAT is to provide a flexible and extensible computer vision annotation platform for teams to collaborate on dataset labeling and model training.
Computer Vision Annotation Tool (CVAT) Features
Features
- Image, video and 3D point cloud annotation
- Multiple user management with different roles
- Predefined tags and automatic annotation
- Interpolation of bounding boxes across frames
- Review and acceptance workflows
- REST API
- Integration with deep learning frameworks
Pricing
- Open Source
Pros
Open source and free
Active development and support community
Powerful annotation capabilities
Collaborative workflows
Integrates with popular ML/DL frameworks
Cons
Steep learning curve
Limited documentation
No native object tracking
Only supports COCO format natively
Official Links
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