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About

The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Configurable layouts and templates adapt to your dataset and workflow. Detect objects on images, boxes, polygons, circular, and key points supported. Partition the image into multiple segments. Use ML models to pre-label and optimize the process. Webhooks, Python SDK, and API allow you to authenticate, create projects, import tasks, manage model predictions, and more. Save time by using predictions to assist your labeling process with ML backend integration. Connect to cloud object storage and label data there directly with S3 and GCP. Prepare and manage your dataset in our Data Manager using advanced filters. Support multiple projects, use cases, and data types in one platform. Start typing in the config, and you can quickly preview the labeling interface. At the bottom of the page, you have live serialization updates of what Label Studio expects as an input.

About

The goal of LabelMe is to provide an online annotation tool to build image databases for computer vision research. You can contribute to the database by visiting the annotation tool. Organization of images into collections: You can organize the images into collections. You can also create collections inside collections just as you would do with folders. When you download your database, the collections will be organized into folders. Uploading and image annotation: You can upload images into your collections and annotate your images using the online LabelMe annotation tool. Unlisted collections are ones that anyone can view if they have access to the URL, but will not be displayed in the set of public folders. As the goal of LabelMe is to provide a tool for research, the images and annotations are expected to become available to the research comunity without restrictions.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers searching for a solution to label every data type and build custom UIs for computer vision processes

Audience

Web-based image annotation tool that allows researchers to label images and share the annotations with the world

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Label Studio
United States
labelstud.io

Company Information

LabelMe
labelme.csail.mit.edu/Release3.0/

Alternatives

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Klatch

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LinkedAI

LinkedAI

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Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth

Amazon Web Services
Mindkosh

Mindkosh

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Categories

Categories

Integrations

Amazon S3
Amazon SageMaker
ApertureDB
Azure Blob Storage
Docker
Flair
Galileo AI
Google Cloud Storage
Hugging Face
Lightly
Modzy
Pachyderm
PostgreSQL
PyTorch
Redis
Rosepetal AI
SQLite
Tesseract
ZenML
scikit-image

Integrations

Amazon S3
Amazon SageMaker
ApertureDB
Azure Blob Storage
Docker
Flair
Galileo AI
Google Cloud Storage
Hugging Face
Lightly
Modzy
Pachyderm
PostgreSQL
PyTorch
Redis
Rosepetal AI
SQLite
Tesseract
ZenML
scikit-image
Claim Label Studio and update features and information
Claim Label Studio and update features and information
Claim LabelMe and update features and information
Claim LabelMe and update features and information