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Average Ratings 0 Ratings
Description
Annotator is a versatile open source JavaScript library that simplifies the integration of annotation features into any webpage. Users can enhance their annotations with comments, tags, links, and user identifiers, among other capabilities. The library is crafted for straightforward extensibility, making it easy to implement new features or functionalities. Additionally, Annotator cultivates a vibrant community of developers across four continents, who contribute by creating third-party plugins that support annotation for PDFs, EPUBs, videos, images, audio, and beyond. Integrating annotations into a website is a breeze with Annotator; simply download the library and add it to your HTML. The platform boasts a robust plugin architecture, allowing developers to include additional features such as user permissions, tagging, filtering, and text formatting. Over a dozen projects depend on Annotator for their digital annotation requirements, many of which are open source. Furthermore, users can easily share their text and video annotations via social media or email, enhancing collaboration and engagement. Through its extensive capabilities, Annotator empowers users to enrich their online content with meaningful annotations.
Description
LabelMe aims to offer an online platform for annotating images, facilitating the creation of image databases for research in computer vision. By utilizing the annotation tool, users can actively contribute to the growing database. Images can be systematically organized into collections, with the flexibility to create nested collections akin to folders. When a user downloads their database, the organization of collections will reflect this folder structure. Users can also upload images to their collections and annotate them using the LabelMe tool. Furthermore, unlisted collections allow for viewing by anyone with access to the specific URL, although they won't be featured among public folders. Ultimately, LabelMe's objective is to ensure that both images and annotations are made accessible to the research community without any limitations, fostering collaboration and innovation. This commitment to open access highlights the importance of shared resources in advancing computer vision research.
API Access
Has API
No
API Access
Has API
No
Integrations
HTML
No
JavaScript
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Annotator
Website
annotatorjs.org
Vendor Details
Company Name
LabelMe
Website
labelme.csail.mit.edu/Release3.0/