LabelMe v5.11.4 is released: introduce 'reset layout'.
Includes SAM2 + SAM3 AI annotation. Offline, no API key required

Label any image with AI
Offline, private, yours

Annotate in one click, build datasets in minutes. One-time purchase, no subscription.

  • From download to your first AI annotation in minutes. No setup
  • Auto-segment and detect with SAM2, SAM3 & YOLO-World. No API key
  • 100% offline. Your data stays on your machine, always
LabelMe annotation app interface
Self-driving car image annotation exampleImage classification annotation example
User review 6User review 3User review 5User review 7
5.0·760+ users·15K+ GitHub stars

How it works

1. Annotate images with polygon, rectangle, or any shapes with Annotation app

2. Validate & export annotations as a dataset with Toolkit

3. Train your AI model

LabelMe workflow: annotate images, validate and export, train AI model
LabelMe annotation app interface

Annotation app

Desktop app to annotate images with polygons, rectangles, and more.

Dataset creation toolkit

Toolkit

A set of command-line tools to streamline dataset creation.

Starter guide for image annotation

Starter guide

Guide to get you started with annotating the first image fast.

Dataset guide for annotation and export

Dataset guide

Guide to help you create, validate, and export a high-quality dataset fast.

Annotation app

LabelMe annotation app interface

Annotation app

Offline-first app you download and run on your computer.

Easy-to-use UI

Everything you need in a single window.

LabelMe easy-to-use annotation UI

Offline & private

Keep data private & work confidently.

Offline and private annotation workflow

Any shapes

Polygon, rectangle, circle, line, & more.

Annotation shapes: polygon, rectangle, circle, line

Rich attributes

Add details (flags, texts) to annotations.

Rich annotation attributes with flags and text

AI assisted

Real-time feedback & auto-annotation with AI. See more.

AI-assisted click-to-annotate feature

Multi-language

14 languages: English, 中文 (简体/繁體), Français, 日本語, Deutsch, Magyar, 한국어, Español, فارسی, Nederlands, Português, Italiano, Tiếng Việt

Multi-language support for 14 languages

Automation toolkit

Dataset creation toolkit

Toolkit

Command-line tools to streamline dataset creation.

Batch process

Annotate, edit, validate, and export many at once.

Batch processing of annotations

Automation ready

Integrate with your workflow and other tools. Accessible from CLI, easily connectable.

Automation-ready CLI integration

AI assisted annotation

Prompt to annotations

Type what to annotate for the AI to get it annotated.

Models: YOLO-World, SAM3

Shapes: rectangles, polygons, mask

Text prompt to AI annotation

A click to annotation

Instant object annotation by a few clicks with AI.

Models: EfficientSAM, SAM1, SAM2

Shapes: polygons, mask

Click-to-annotate with AI

Rectangle to polygon

Convert rough rectangles to accurate polygons with AI.

Perfect for objects with complex shapes (e.g., irregular, curved).

AI-powered rectangle to polygon conversion

Examples

Make image annotations for any applications with any shapes & AI-assist.

Actively maintained

Story

Kentaro Wada, LabelMe founder

Kentaro Wada

Founder

Mujin logoImperial College London logoUniversity of Tokyo logoJSK Robotics Lab logo

Automation obsessor. Solo-built LabelMe (15K+ stars), Gdown (4.7K+), and 9+ times top trending developers on GitHub.

Lead computer vision at Mujin (robotics startup), PhD at Imperial (early graduate, full-funded), UTokyo JSK robotics lab (first who went abroad in its 50-year history).

Hi, I'm Kentaro!

Here is the story behind LabelMe.

I built it when I was at the end of my bachelor's degree / beginning of my master's. I was working in a robotics lab and created it to teach my robot to see the world.

Around 2015-2016, Amazon Robotics held the Amazon Picking Challenge (APC) shortly after acquiring Kiva Robotics, the company who developed the AGVs used at Amazon. They had automated material delivery in warehouses but were looking for an automation solution for material picking.

We participated as a team from the lab (Can you spot me in the picture?), and I ended up building LabelMe for the challenge.

For the full story, check out my tweet.

Team photo from the Amazon Picking Challenge

Explore more

Frequently asked questions

What is LabelMe?

LabelMe is an image annotation tool for creating datasets. The free open-source version is a Python-based editor. The paid plans (Starter and Pro) add a standalone desktop app with built-in AI models that runs offline on Windows, macOS, and Linux.

Does LabelMe work offline?

Yes. LabelMe runs entirely offline with no internet connection required. The Starter and Pro apps bundle AI models (SAM2, SAM3, YOLO-World) locally, so your images never leave your computer.

What AI models does LabelMe include?

The Starter and Pro apps ship with SAM2 and SAM3 for one-click segmentation, and YOLO-World for text-prompt object detection. No API keys or cloud services needed. The free open-source version provides manual annotation without built-in AI.

What annotation types does LabelMe support?

All versions support polygons, bounding boxes (rectangles), circles, lines, and points. The Starter and Pro apps add AI-assisted annotation for pixel-accurate masks with a single click.

What export formats are available?

The Pro plan includes a dataset toolkit that exports to YOLO, Pascal VOC, and COCO formats, with automated conversion and validation for direct use in training pipelines.

Is LabelMe open source?

The core LabelMe annotation tool is open source with 15,000+ GitHub stars. Starter adds a standalone app with built-in AI models. Pro adds the dataset toolkit, ready-to-train exports, and priority support.

Start building your dataset today

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