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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 

Screenshots View All

Screenshots View All

Integrations

HTML Yes 
JavaScript Yes 

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/

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Product Features

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