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Description
Amazon SageMaker enables the identification of various types of unprocessed data, including images, text documents, and videos, while also allowing for the addition of meaningful labels and the generation of synthetic data to develop high-quality training datasets for machine learning applications. The platform provides two distinct options, namely Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which grant users the capability to either leverage a professional workforce to oversee and execute data labeling workflows or independently manage their own labeling processes. For those seeking greater autonomy in crafting and handling their personal data labeling workflows, SageMaker Ground Truth serves as an effective solution. This service simplifies the data labeling process and offers flexibility by enabling the use of human annotators through Amazon Mechanical Turk, external vendors, or even your own in-house team, thereby accommodating various project needs and preferences. Ultimately, SageMaker's comprehensive approach to data annotation helps streamline the development of machine learning models, making it an invaluable tool for data scientists and organizations alike.
Description
Advanced video analysis technology can identify more than 20,000 different objects, locations, and activities within video content. It allows for the extraction of comprehensive metadata across various levels, including the entire video, individual shots, or specific frames. Users have the capability to define custom entity labels through AutoML Video Intelligence, tailoring the tool to their needs. Additionally, it offers the ability to gather insights in near real-time, using streaming video annotation alongside object-based event triggers. This functionality enables the creation of captivating customer experiences through highlight reels and personalized recommendations. Furthermore, it supports the recognition of over 20,000 objects, places, and actions in both stored and live video feeds. Users can search their video libraries in a manner similar to document searches, facilitating easier access to specific content. The rich metadata extracted can also serve to index, organize, and filter video assets, ensuring that the most relevant content is highlighted. With these features, organizations can leverage video data more effectively to enhance their operations and engage their audiences.
API Access
Has API
API Access
Has API
Integrations
Amazon SageMaker
Amazon SageMaker Unified Studio
BOSCO
Google Cloud AutoML
Google Cloud Platform
Unremot
ZenML
Integrations
Amazon SageMaker
Amazon SageMaker Unified Studio
BOSCO
Google Cloud AutoML
Google Cloud Platform
Unremot
ZenML
Pricing Details
$0.08 per month
Free Trial
Free Version
Pricing Details
$0.10 per minute
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon Web Services
Founded
2006
Country
United States
Website
aws.amazon.com/es/sagemaker/data-labeling/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/video-intelligence
Product Features
Data Labeling
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management