ProdigyExplosion
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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.
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About
Radically efficient machine teaching. An annotation tool powered by active learning. Prodigy is a scriptable annotation tool so efficient that data scientists can do the annotation themselves, enabling a new level of rapid iteration. Today’s transfer learning technologies mean you can train production-quality models with very few examples. With Prodigy you can take full advantage of modern machine learning by adopting a more agile approach to data collection. You'll move faster, be more independent and ship far more successful projects. Prodigy brings together state-of-the-art insights from machine learning and user experience. With its continuous active learning system, you're only asked to annotate examples the model does not already know the answer to. The web application is powerful, extensible and follows modern UX principles. The secret is very simple: it's designed to help you focus on one decision at a time and keep you clicking – like Tinder for data.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Web-based image annotation tool that allows researchers to label images and share the annotations with the world
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Audience
Data scientists, AI developers, data labelers
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
$490 one-time fee
Per seat, available in packs of 5 seats
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationLabelMe
labelme.csail.mit.edu/Release3.0/
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Company InformationExplosion
Founded: 2016
Germany
prodi.gy/
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Categories |
Categories |
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Data Labeling Features
Human-in-the-loop
Not Supported
Labeling Automation
Supported
Labeling Quality
Not Supported
Performance Tracking
Not Supported
Polygon, Rectangle, Line, Point
Not Supported
SDK
Not Supported
Supports Audio Files
Not Supported
Task Management
Supported
Team Collaboration
Not Supported
Training Data Management
Not Supported
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Integrations
ZenML
Not Supported
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