Amazon SageMaker Ground Truth now supports synthetic data generation
We are excited to announce that Amazon SageMaker Ground Truth now provides support so you can generate labeled synthetic data without collecting large amounts of real-world, manually labeled data. Amazon SageMaker provides two data labeling offerings, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth. You can use both options to identify raw data (such as images, text files, and videos) and add informative labels to create high-quality training datasets for your machine learning (ML) models.
We are excited to announce that Amazon SageMaker Ground Truth now provides support so you can generate labeled synthetic data without collecting large amounts of real-world, manually labeled data. Amazon SageMaker provides two data labeling offerings, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth. You can use both options to identify raw data (such as images, text files, and videos) and add informative labels to create high-quality training datasets for your machine learning (ML) models.
SageMaker Ground Truth can generate labeled synthetic data on your behalf so that you can use synthetic data with real-world data to train ML models across a wide range of computer vision use cases. You specify your synthetic image requirements or provide 3D assets and baseline images, and AWS digital artists can generate hundreds of thousands of synthetic images that are automatically labeled. The generated images imitate pose and placement of objects, include object or scene variations, and optionally add specific inclusions, such as scratches, dents, and other alterations that are not often included in ML training datasets.
Amazon SageMaker Ground Truth support for synthetic data generation is generally available in the US East (N. Virginia) Region.
To learn more, read our blog post about generating synthetic data. To get started, fill out the project form or visit the SageMaker Ground Truth console.