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

Struggling to choose between VGG Image Annotator (VIA) and Computer Vision Annotation Tool (CVAT)? Both products offer unique advantages, making it a tough decision.

VGG Image Annotator (VIA) is a Ai Tools & Services solution with tags like image-annotation, machine-learning, computer-vision, dataset-creation.

It boasts features such as Image annotation, Region, rectangle, ellipse, polygon and point annotations, Image-level labels, Keyboard shortcuts, Project management, Import/export annotations, Plugin ecosystem and pros including Open source, Easy to use interface, Support for multiple annotation types, Active development community, Cross-platform.

On the other hand, Computer Vision Annotation Tool (CVAT) is a Ai Tools & Services product tagged with image-annotation, video-annotation, computer-vision, open-source.

Its standout features include 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, and it shines with pros like Open source and free, Active development and support community, Powerful annotation capabilities, Collaborative workflows, Integrates with popular ML/DL frameworks.

Feature	VGG Image Annotator (VIA)	Computer Vision Annotation Tool (CVAT)
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Ai Tools & Services

Product Overview

VGG Image Annotator (VIA)

Description: VGG Image Annotator (VIA) is an open source image annotation tool for labeling images to create datasets for machine learning models. It supports region, rectangle, ellipse, polygon, point, and image-level annotations.

Computer Vision Annotation Tool (CVAT)

Description: 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.

Key Features Comparison

VGG Image Annotator (VIA) Features

• Image annotation
• Region, rectangle, ellipse, polygon and point annotations
• Image-level labels
• Keyboard shortcuts
• Project management
• Import/export annotations
• Plugin ecosystem

Computer Vision Annotation Tool (CVAT) 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

Pros & Cons Analysis

VGG Image Annotator (VIA)

Pros

• Open source
• Easy to use interface
• Support for multiple annotation types
• Active development community
• Cross-platform

Cons

• Limited documentation
• Less features than some commercial options
• Only supports images (no video)
• No built-in data augmentation tools

Computer Vision Annotation Tool (CVAT)

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

Pricing Comparison

VGG Image Annotator (VIA)

• Open Source

Computer Vision Annotation Tool (CVAT)

• Open Source