Overview

Model Lifecycle
Start building AI with Intel® Geti™, covering the complete computer vision model lifecycle from data preparation to model training and deployment.

Model Lifecycle
Data Labeling
Model Testing
Start building computer vision models in a fraction of the time and with less data. Intel® Geti™ eases laborious data labeling, model training and optimization tasks across the AI model development process, empowering everyone to build OpenVINO optimized computer vision models suitable for deployment at scale. Intel® Geti™ provides you with an end-to-end workflow to prepare state-of-the-art computer vision models in minutes. With the interactive model training flow, you can get started with as little as 20-30 images or videos: by using Active Learning, Intel® Geti™ will help you teach the model as it incrementally learns from your data.
Highlights
- Interactive Model Training: Get started annotating data with as few as 20 to 30 images, and then let active learning help you teach the model as it learns.
- Smart Annotations: Expedite data annotation and easily segment images with professional drawing features like a pencil, a polygon tool, OpenCV GrabCut, and AI models such as the Segment Anything Model.
- Production-Ready Models: Output deep learning models in TensorFlow* or PyTorch* formats (where available) or as an optimized model for the OpenVINO toolkit to run on Intel architecture CPUs, GPUs, and VPUs.
Details
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Features and programs
Financing for AWS Marketplace purchases
Pricing
Dimension | Cost/hour |
---|---|
g4dn.8xlarge Recommended | $0.00 |
g4dn.12xlarge | $0.00 |
g4dn.16xlarge | $0.00 |
g4dn.4xlarge | $0.00 |
Vendor refund policy
It is Free!
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Content disclaimer
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Fixed a bug where Geti installation failed because bitnami-shell container image was removed from the Bitnami repository.
Additional details
Usage instructions
- Connect to the instance using SSH
- Navigate to cd ~/platform_2.10.2 directory
- Run sudo ./platform_installer uninstall. This clears the required directories for install.
- Run sudo ./platform_installer install
- During the installer, use /data as the dataset location
- Connect to the instance web interface to login with your username and password
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.