Related Products
|
||||||
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
We offer the highest quality SLA (>95%), even on the most complex workflows. Our team assists with anything from implementing a robust quality rubric to raising edge cases. As an ethical AI company, we have provided economic opportunities for over 52,000 people from underserved and marginalized communities. ML Assisted annotation created up to 3-4x efficiency improvement for a single class annotation. We quickly adapt to ramp-ups, focus shifts, and edge cases. ISO certified delivery centers, biometric authentication, and user authentication with 2FA ensure a secure work environment. Seamlessly re-prioritize tasks, provide quality feedback, and monitor models in production. We support data of all types. Get more with less. We combine machine learning and humans in the loop to filter data and select images relevant to your use case. Receive sample results based on your initial guidelines. We work with you to identify edge cases and recommend annotation best practices.
|
|||||
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
|
Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Developers searching for a solution to label every data type and build custom UIs for computer vision processes
|
Audience
Enterprises seeking a tool to automate data annotation and improve their machine learning model validation processes
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Supported
Free Trial
Supported
|
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
|
|||||
Company InformationLabel Studio
United States
labelstud.io
|
Company InformationSama
United States
www.sama.com
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Integrations
Amazon SageMaker
Supported
ApertureDB
Supported
Azure Blob Storage
Supported
Canva
Not Supported
Flair
Supported
Galileo AI
Supported
Google
Not Supported
Google Cloud Storage
Supported
Kubernetes
Supported
Lightly
Supported
|
Integrations
Amazon SageMaker
Not Supported
ApertureDB
Not Supported
Azure Blob Storage
Not Supported
Canva
Supported
Flair
Not Supported
Galileo AI
Not Supported
Google
Supported
Google Cloud Storage
Not Supported
Kubernetes
Not Supported
Lightly
Not Supported
|
|||||
|
|
|