LabelMe

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What LabelMe is

LabelMe is a web-based image annotation tool for researchers who label images and share annotations. It supports polygon, scribble and mask annotation, with options to create and edit polygons, rename objects, change polygon control points, delete objects or view polygons without editing them. URL settings provide navigation to another image in a folder, a random image or the next image in a collection, and include a Mechanical Turk mode. A command-line script can create collections from all images or a specified folder. Annotations are saved as XML in an Annotations folder; downloads are described through a MATLAB toolbox or tar files. The toolbox can download a dataset or access images and annotations online, though online access may be slow. The software is free, and source code is available as a zip or through its GitHub repository. It is intended for installation on a web server and use in a browser, with Docker files included. Setup requires Apache, server-side includes and Perl/CGI support. Instructions specify .jpg images and simple alphanumeric folder and file names. The server needs readable image files and writable annotation, temporary annotation and log locations.

Who it suits

LabelMe suits researchers and computer vision projects that need image annotation and shared XML output. It is also relevant to users who can install and maintain the required web server setup.

What it does well

Free to use.
Supports polygon, scribble and mask annotations.
Exports annotations as XML.
Includes a MATLAB toolbox and tar-file downloads.
URL options support Mechanical Turk workflows.

What to know first

Installation requires Apache and Perl/CGI support.
Quick start specifies .jpg image files.
Online dataset access may be slow.
Server folders require specific read and write permissions.

Getting started

Download the source as a zip file or from the GitHub repository.
Install it on a web server with Apache, server-side includes, and Perl/CGI support.
Prepare .jpg images in folders and files named with alphanumeric characters.
Give the web server read access to images and write access to annotation, temporary annotation, and log locations.
Create image collections with the command-line script if needed, then use LabelMe through a browser.

Verdict

LabelMe provides annotation modes, collection navigation and XML output for image-labeling work. Its web-server requirements and file constraints are important to review before setup.

Questions

Is LabelMe free?

Yes. LabelMe is listed as free and its repository lists an MIT license.

Which annotation types does it support?

It supports polygon, scribble, and mask annotations.

What format are annotations saved in?

Annotations are saved as XML files in an Annotations folder. Downloads are described through a MATLAB toolbox or tar files.

Can LabelMe run on a self-hosted server?

Yes. The source is intended for web-server installation and browser use, and the repository includes Docker files. Setup requires Apache, server-side includes, and Perl/CGI support.

What image files can I use?

The quick start instructions specify .jpg images and folder and file names made of alphanumeric characters without spaces or unusual characters.

Does LabelMe provide AI-assisted labeling?

No. AI-assisted labeling is listed as unavailable.

Facts from LabelMe's own pages

Annotations: The tool saves annotations in an Annotations folder and supports scribble mode with masks and scribbles. · github.com, 7 Oct 2026
Collections: A command-line script can create image collections from all images or from a specified folder. · github.com, 7 Oct 2026
Configuration: URL options can select images and collections, set a labeling username, restrict available actions, and supply a dropdown list of object names. · github.com, 7 Oct 2026
Data export: Annotations are saved as XML files, and the page describes downloads through a MATLAB toolbox or tar files. · people.csail.mit.edu, 7 Oct 2026
Dataset access: The MATLAB toolbox can download the dataset or access online images and annotations directly; the page says online access may be slow. · people.csail.mit.edu, 7 Oct 2026
Deployment: The source code is intended to be installed on a web server and used through a browser; the repository includes Docker files for installation. · github.com, 7 Oct 2026
Download: The source code is available as a zip download or through the GitHub repository. · github.com, 7 Oct 2026
Founded: 2005 · labelme.csail.mit.edu, 28 Sept 2026
Headquarters: Cambridge, Massachusetts, United States · labelme.csail.mit.edu, 28 Sept 2026
Image annotations: The tool supports creating and editing polygons, with URL options to rename objects, modify polygon control points, delete objects, or view polygons without editing. · github.com, 7 Oct 2026
Image file constraint: The quick start instructions specify .jpg images and folder and file names containing alphanumeric characters without spaces or unusual characters. · github.com, 7 Oct 2026
Intended use: The repository categorizes the tool under annotation and computer vision. · github.com, 7 Oct 2026
Labeling modes: URL options include a Mechanical Turk mode and modes for moving to the next image in a folder, a random image, or the next image in a collection. · github.com, 7 Oct 2026
License: The repository lists an MIT license. · github.com, 7 Oct 2026
Logging: The tool records its actions in annotationCache/Logs/logfile.txt, which must be writable by the server. · github.com, 7 Oct 2026
Mechanical Turk: The tool has a Mechanical Turk mode with options for sandbox testing, minimum polygon counts, and custom worker instructions. · github.com, 7 Oct 2026
Output format: Annotation file layouts can be changed by editing an XML template for a collection. · github.com, 7 Oct 2026
Project attribution: The repository credits the MIT Computer Science and Artificial Intelligence Laboratory. · github.com, 7 Oct 2026
Purpose: LabelMe is a JavaScript tool for online image labeling that lets people access the tool from anywhere and collaborate without installing or copying the image dataset to their computers. · github.com, 7 Oct 2026
Security and permissions: Setup instructions require readable image files and writable annotation and temporary annotation folders on the web server. · github.com, 7 Oct 2026
Server requirements: The setup instructions require Apache, server-side includes, and Perl/CGI support. · github.com, 7 Oct 2026
Storage permissions: The web server needs read permission for images and write permission for annotation and temporary annotation folders. · github.com, 7 Oct 2026

Where LabelMe stands on Freedom251

AI Image Annotation Tools#7 of 24