OCI Data LabelingOracle
|
||||||
Related Products
|
||||||
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.
|
About
OCI Data Labeling is a service that enables developers and data scientists to build accurately labelled datasets for training AI and machine-learning models. It supports documents (PDF, TIFF), images (JPEG, PNG), and text, allowing users to upload raw data, apply annotations (such as classification labels, object-detection bounding boxes, or key-value pairs), and export the results in line-delimited JSON for seamless integration into model-training workflows. The service offers custom templates for different annotation formats, user interfaces, and public APIs for dataset creation and management, and smooth interoperability with other data and AI services, so annotated data can feed directly into custom vision or language models, as well as Oracle’s AI services. OCI Data Labeling lets users create a dataset, generate records, annotate them, and then use the export snapshot for model development.
|
|||||
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
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
|
|||||
Audience
Web-based image annotation tool that allows researchers to label images and share the annotations with the world
|
Audience
Data scientists and ML engineers looking for a solution to create, annotate and export labelled datasets across image, document and text modalities to train and deploy AI/ML models at scale
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
Pricing
$0.0002 per 1,000 transactions
Free Version
Not Supported
Free Trial
Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
|
|||||
Company InformationLabelMe
labelme.csail.mit.edu/Release3.0/
|
Company InformationOracle
Founded: 1977
United States
www.oracle.com/artificial-intelligence/data-labeling/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
|
|||||
|
|
||||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
JSON
Not Supported
Oracle AI Agent Platform
Not Supported
Oracle Cloud Infrastructure
Not Supported
Oracle Data Science
Not Supported
|
Integrations
JSON
Supported
Oracle AI Agent Platform
Supported
Oracle Cloud Infrastructure
Supported
Oracle Data Science
Supported
|
|||||
|
|
|