Skip to content
SPECIFICTION
Get listed

LabelMe

labelme.csail.mit.edu

WebWindowsLinuxSelf-hosted
Visit labelme.csail.mit.edu
Spec score 7.5 #17 of 24 in AI Image Annotation Tools

What it is

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

Spec sheet

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

Strong points and limits

Strong points

  • Supports polygon, scribble, and mask annotations.
  • Annotations are saved in XML format.
  • Collections can be built with a command-line script.
  • The tool is free to use.

Limits

  • Self-hosting requires Apache and Perl/CGI support.
  • Quick start specifies .jpg images and simple names.
  • Online dataset access may be slow.

Who it suits

LabelMe suits researchers who need to annotate and share image datasets, including with polygon, scribble, or mask labels. Self-hosting requires a web server configured with the stated software and permissions.

Verdict

LabelMe covers annotation, collection navigation, and XML output for image research. Its server requirements and filename constraints matter if you plan to host it yourself.

Where Specifiction places it

Alternatives to LabelMeAll alternatives →