LabelMe
LabelMe is a web-based image annotation tool for researchers labeling images and sharing annotations.
What LabelMe is
LabelMe is a web-based image annotation tool for researchers labeling images and sharing annotations. It supports polygon, scribble, and mask annotation; polygon tools can create shapes, rename objects, change control points, or remove objects. URL options provide navigation through a folder or collection, random image selection, and a Mechanical Turk mode. A command-line script can create image collections from all images or a chosen folder. Annotations are saved as XML in an Annotations folder, with downloads available through a MATLAB toolbox or tar files. The toolbox can retrieve a dataset or access images and annotations online, though online access may be slow. The source is intended for installation on a web server and use through a browser, and Docker files are included. Setting it up requires Apache, server-side includes, and Perl/CGI support. The quick start specifies JPG images and alphanumeric folder and file names without spaces or unusual characters. The server also needs read access to images and write access to annotation, temporary annotation, and log locations.
Good
- Supports polygon, scribble, and mask annotation
- Annotations are saved as XML
- Command-line script can create image collections
- Source code and Docker files are available
Watch out
- Setup requires Apache, server-side includes, and Perl/CGI
- Quick start specifies JPG images and simple file names
- Online dataset access may be slow
- Server needs writable annotation and log locations
Who it suits
LabelMe suits researchers who need to annotate image datasets with polygons, scribbles, or masks and share the results. It is a fit for users prepared to install and configure a web server.
Verdict
LabelMe offers multiple annotation types and XML output for image-labeling work. Its web-server requirements and file-name constraints are important to consider before choosing it.
The facts
Each one read from LabelMe's own pages, with the date it was checked.
What it does
- Annotations
- The tool saves annotations in an Annotations folder and supports scribble mode with masks and scribbles.checked 7 Oct 2026
- Collections
- A command-line script can create image collections from all images or from a specified folder.checked 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.checked 7 Oct 2026
- Data export
- Annotations are saved as XML files, and the page describes downloads through a MATLAB toolbox or tar files.checked 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.checked 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.checked 7 Oct 2026
- Download
- The source code is available as a zip download or through the GitHub repository.checked 7 Oct 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.checked 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.checked 7 Oct 2026
- Intended use
- The repository categorizes the tool under annotation and computer vision.checked 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.checked 7 Oct 2026
- License
- The repository lists an MIT license.checked 7 Oct 2026
- Logging
- The tool records its actions in annotationCache/Logs/logfile.txt, which must be writable by the server.checked 7 Oct 2026
- Mechanical Turk
- The tool has a Mechanical Turk mode with options for sandbox testing, minimum polygon counts, and custom worker instructions.checked 7 Oct 2026
- Output format
- Annotation file layouts can be changed by editing an XML template for a collection.checked 7 Oct 2026
- Project attribution
- The repository credits the MIT Computer Science and Artificial Intelligence Laboratory.checked 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.checked 7 Oct 2026
- Security and permissions
- Setup instructions require readable image files and writable annotation and temporary annotation folders on the web server.checked 7 Oct 2026
- Server requirements
- The setup instructions require Apache, server-side includes, and Perl/CGI support.checked 7 Oct 2026
- Storage permissions
- The web server needs read permission for images and write permission for annotation and temporary annotation folders.checked 7 Oct 2026
The company
- Founded
- 2005checked 28 Sep 2026
- Headquarters
- Cambridge, Massachusetts, United Stateschecked 28 Sep 2026
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