Labelme v5.11 is released! (SAM3 is here)

The offline image annotation for vision AI

Build training datasets faster, privately.

  • Simple UI for polygons, rectangles, and any shape you need
  • Auto-label with SAM3, YOLO-World, and smart suggestions
  • 100% offline. Your data never leaves your machine
5.0·740+ 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

Annotation app

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

Toolkit

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

Starter guide

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

Dataset guide

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

Annotation app

Annotation app

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

Easy-to-use UI

Everything you need in a single window.

Offline & private

Keep data private & work confidently.

Any shapes

Polygon, rectangle, circle, line, & more.

Rich attributes

Add details (flags, texts) to annotations.

AI assisted

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

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

Automation toolkit

Toolkit

Command-line tools to streamline dataset creation.

Batch process

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

Automation ready

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

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

A click to annotation

Instant object annotation by a few clicks with AI.

Models: EfficientSAM, SAM1, SAM2

Shapes: polygons, mask

Rectangle to polygon

Convert rough rectangles to accurate polygons with AI.

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

Examples

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

Story

Kentaro Wada

Founder

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.

Explore more

Start building your dataset today

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