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What is Scalabel?

Enable a diverse range of annotation types for images and videos through a versatile, open-source web tool. This platform is built to scale effectively and features user-friendly “click and drag” capabilities that simplify the process of adding numerous attributes. It includes functionalities that allow the fitting of boundaries with Bezier curves and the option to duplicate common boundaries, enhancing efficiency. Users can pinpoint the specific areas where a driver is active and delineate lane lines, which is crucial for improving vision-based vehicle localization and trajectory planning. An easy four-click approach is utilized to precisely encapsulate objects of interest, while sophisticated algorithms leverage object tracking and interpolation methods to forecast annotations across different frames for bounding boxes. The tool also extends its prediction capabilities to individual object instances, with 2D tracking that has been further developed into a three-dimensional framework, thereby enriching the overall annotation experience. By incorporating these advanced features, this tool strives to optimize the workflow for individuals engaged in tasks related to image and video annotation, ultimately leading to enhanced productivity and accuracy. Furthermore, the platform's adaptability ensures that it can cater to the evolving needs of various users in this field.

What is LabelMe?

LabelMe is designed as a web-based platform that enables users to annotate images, thereby assisting in the development of image databases vital for research in the field of computer vision. Through its annotation tool, users can play an integral role in expanding this growing database. Images can be arranged into organized collections, and users have the option to create nested collections similar to traditional folder structures. When downloading their database, users will find that the arrangement of collections mirrors this folder organization. Additionally, users can upload their images to these collections and annotate them using the LabelMe tool. There are also unlisted collections that can be accessed by anyone with the specific URL, even though they remain hidden from public view. Ultimately, LabelMe strives to make both images and annotations freely available to the research community, promoting collaboration and fostering innovation. This dedication to open access underscores the significance of shared resources in propelling advancements in computer vision research, while also encouraging diverse contributions from various users.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Scalabel

Company Website

www.scalabel.ai/

Company Facts

Organization Name

LabelMe

Company Website

labelme.csail.mit.edu/Release3.0/

Categories and Features

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

Video Annotation

Not specified

Categories and Features

Image Annotation

Not specified

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