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v2.11.0

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@piotrgrubicki piotrgrubicki released this 09 Jul 15:23
· 445 commits to main since this release
v2.11.0
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Release Notes

Geti keeps evolving - and thanks to your feedback, version 2.11.0 introduces several improvements and new features to elevate your experience.

Summary of major features and improvements

  • 💡 Added Support for Single Object Keypoint Detection: As part of Geti 2.11, this new task allows users to identify and locate specific points of interest (keypoints) in an image, enabling use cases such as pose estimation. With its custom annotation tool, users can prepare their own keypoint detection datasets to train their model.

  • 🖥️ Optimized Resource Utilization for Lower-Spec Hardware: Geti can now run on systems with 16 CPU cores and 32 GB RAM. For users who have large datasets or want to use heavy models, 64 GB of memory is still recommended.

  • 🔄 Platform Upgrades Now Supported via Helm Charts: This facilitates a direct upgrade of your Geti instance without requiring the use of the installer.

  • 🚀 Increased Inference Efficiency: FP16 models generate predictions with an accuracy comparable to their FP32 version, but with significantly reduced latency and memory footprint. By defaulting to FP16, Geti inference is now more responsive and resource efficient.

  • ☁️ Installation Guide for AWS & Azure cloud VM: A comprehensive, step-by-step guide is now available for installing and configuring Intel Geti on AWS and Azure. It covers the virtual machines setup, recommended configurations, installation, upgrades, and best practices for maintaining Geti in the cloud – designed to be clear and accessible for everyone.

  • ☁️ Geti™ Available on AWS Marketplace: Geti can now be deployed via AWS Marketplace for free, making it more accessible to users who are already operating in the AWS cloud

  • 🎨 Interface and Workflow Improvements:

    • Job filtering by time range: to make it easier for users to keep track on their work, the new calendar-based filter can be used to show jobs started within a given time range.

    • Training job visibility: for each project, all scheduled and in-progress training jobs are now listed on the Models screen for better visibility.

    • Label ordering: users can now rearrange the order of labels and their groups as they like, so that they can put the labels that they are most interested in on top for better visibility.

    • Project import and renaming: it is now possible to directly assign a new name to a project before uploading it to avoid project name duplication.

    • Improved user flow for Live Prediction: as part of Geti’s testing capabilities, we improved the user experience of Live Prediction. With minimal clicks, users can now directly use their camera inside the Tests screen to capture a test image.

Download this release

Installer

Download installer.

Container Images and Helm charts

Container images and Helm charts are available at ghcr.io/open-edge-platform/geti/*

Source code for open source components, provided as required by license.

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