Software Alternatives, Accelerators & Startups

Computer Vision Annotation Tool (CVAT) VS VGG Image Annotator (VIA)

Compare Computer Vision Annotation Tool (CVAT) VS VGG Image Annotator (VIA) and see what are their differences

Computer Vision Annotation Tool (CVAT) logo Computer Vision Annotation Tool (CVAT)

Powerful and efficient Computer Vision Annotation Tool (CVAT) - opencv/cvat

VGG Image Annotator (VIA) logo VGG Image Annotator (VIA)

VGG Image Annotator is a simple and standalone manual annotation software for image, audio and video. VIA runs in a web browser and does not require any installation or setup.
  • Computer Vision Annotation Tool (CVAT) Landing page
    Landing page //
    2023-08-26
  • VGG Image Annotator (VIA) Landing page
    Landing page //
    2022-09-08

Computer Vision Annotation Tool (CVAT) features and specs

  • Open Source
    CVAT is open-source, meaning its source code is freely available for anyone to use, modify, and distribute. This encourages community contributions and transparency.
  • Rich Annotation Features
    CVAT provides a wide range of annotation tools for bounding boxes, polygons, polylines, points, and more, which are essential for creating detailed datasets.
  • User-Friendly Interface
    The tool has an intuitive and responsive web interface that simplifies the annotation process, making it easier for users of all experience levels.
  • Collaboration and Multi-User Support
    CVAT supports multiple users working collaboratively on the same project, which enhances productivity in team environments.
  • Integration Capabilities
    CVAT can be easily integrated with other tools and workflows via its REST API, making it adaptable to various project needs.
  • Customizability
    Users can customize the labeling interface and adapt the platform to fit specific task requirements, adding flexibility to its use.

Possible disadvantages of Computer Vision Annotation Tool (CVAT)

  • Installation Complexity
    Setting up CVAT can be complex, requiring knowledge of Docker and command-line operations, which may be challenging for non-technical users.
  • Resource Intensive
    CVAT can be demanding on system resources, particularly when handling large datasets, which may affect performance on less powerful machines.
  • Limited Offline Functionality
    As a largely web-based application, CVAT has limited offline capabilities, which can be a constraint in environments with unreliable internet access.
  • Learning Curve
    Despite its user-friendly interface, mastering all features of CVAT can take time, particularly for users who are new to annotation tools or advanced functionalities.
  • Scalability Challenges
    While CVAT supports multiple users, scaling it for very large teams or extremely large projects may require additional infrastructure and management.

VGG Image Annotator (VIA) features and specs

  • Ease of Use
    VIA is user-friendly and simple to set up, making it accessible to users without extensive technical knowledge.
  • No Installation Required
    As a web-based tool, VGG Image Annotator runs directly in a browser and doesn't require any installation or special software.
  • Lightweight
    The tool has a small footprint and can be run effectively on systems with limited resources, making it efficient for quick tasks and analysis.
  • Versatility
    VIA supports various annotation types like points, rectangles, polygons, and allows for both manual and automatic annotation, catering to diverse project needs.
  • Customizable
    VIA's source code is available for modification, offering customization possibilities to fit specific project requirements.
  • Collaboration Features
    It allows users to save annotations in JSON format, making it easy to share and integrate into larger workflows or collaborate within teams.

Possible disadvantages of VGG Image Annotator (VIA)

  • Limited Performance for Large Datasets
    When dealing with large datasets, VIA can become slow or unresponsive due to its reliance on browser-based operation which hampers performance scalability.
  • Basic Interface
    The interface is quite simplistic and may lack the advanced features or aesthetics found in more sophisticated, dedicated annotation software.
  • Lack of Automation for Advanced Needs
    While it supports basic automatic annotation, it is not as advanced or robust for complex tasks, which might require more manual input or additional tools.
  • Limited Support
    Being an open-source project, it may not offer the same level of professional customer support or regular updates as commercial tools.

Computer Vision Annotation Tool (CVAT) videos

Computer Vision Annotation Tool (CVAT): annotation mode

VGG Image Annotator (VIA) videos

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Category Popularity

0-100% (relative to Computer Vision Annotation Tool (CVAT) and VGG Image Annotator (VIA))
Data Science And Machine Learning
Image Annotation
64 64%
36% 36
AI
84 84%
16% 16
Data Labeling
82 82%
18% 18

User comments

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Social recommendations and mentions

Based 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.

Computer Vision Annotation Tool (CVAT) mentions (14)

  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    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 / over 1 year ago
  • Need help identifying a good open source data annotation tool
    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: over 1 year ago
  • Way to label yolov7 images fast
    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 2 years ago
  • Segment Anything Model is now available in the open-source CVAT
    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 2 years ago
  • How to build computer vision dataset labeling team in-house
    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 2 years ago
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VGG Image Annotator (VIA) mentions (0)

We have not tracked any mentions of VGG Image Annotator (VIA) yet. Tracking of VGG Image Annotator (VIA) recommendations started around Mar 2021.

What are some alternatives?

When comparing Computer Vision Annotation Tool (CVAT) and VGG Image Annotator (VIA), you can also consider the following products

Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...

CrowdFlower - Enterprise crowdsourcing for micro-tasks

Segments.ai - Multi-sensor labeling platform for robotics and autonomous driving

Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset

Amazon Mechanical Turk - The online market place for work.

AWS SageMaker Ground Truth - Build highly accurate training datasets using machine learning and reduce data labeling costs by up to 70%.