Microsoft.ML.OnnxRuntime.Gpu 1.16.0

Prefix Reserved
There is a newer version of this package available.
See the version list below for details.
dotnet add package Microsoft.ML.OnnxRuntime.Gpu --version 1.16.0                
NuGet\Install-Package Microsoft.ML.OnnxRuntime.Gpu -Version 1.16.0                
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Microsoft.ML.OnnxRuntime.Gpu" Version="1.16.0" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.ML.OnnxRuntime.Gpu --version 1.16.0                
#r "nuget: Microsoft.ML.OnnxRuntime.Gpu, 1.16.0"                
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install Microsoft.ML.OnnxRuntime.Gpu as a Cake Addin
#addin nuget:?package=Microsoft.ML.OnnxRuntime.Gpu&version=1.16.0

// Install Microsoft.ML.OnnxRuntime.Gpu as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntime.Gpu&version=1.16.0                

This package contains native shared library artifacts for all supported platforms of ONNX Runtime.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp1.0 was computed.  netcoreapp1.1 was computed.  netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard1.1 is compatible.  netstandard1.2 was computed.  netstandard1.3 was computed.  netstandard1.4 was computed.  netstandard1.5 was computed.  netstandard1.6 was computed.  netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net45 was computed.  net451 was computed.  net452 was computed.  net46 was computed.  net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
native native is compatible. 
Tizen tizen30 was computed.  tizen40 was computed.  tizen60 was computed. 
Universal Windows Platform uap was computed.  uap10.0 was computed. 
Windows Phone wpa81 was computed. 
Windows Store netcore was computed.  netcore45 was computed.  netcore451 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (27)

Showing the top 5 NuGet packages that depend on Microsoft.ML.OnnxRuntime.Gpu:

Package Downloads
Aspose.Ocr.Cpp-GPU

Accelerate your C++ Windows applications by offloading resource-demanding OCR tasks to NVIDIA® CUDA® enabled GPU. Extract editable text from scanned documents, photos, screenshots, and more with just a few lines of code. The library can handle various fonts, layouts, and styles, bulk-recognize entire folders and archives of images, process multi-page PDFs and TIFFs. GPU-accelerated Aspose.OCR for C++ is well-fit for global scale content digitization. It supports a vast range of languages across Europe, Middle East, Asia, Africa, and the Americas, including the ability to recognize mixed languages within a document. This versatile library empowers businesses of all sizes, from startups to global corporations. Changelog: - Improved loading of external OCR modules. - Minor enhancements and fixes.

Aspose.Ocr.Cpp-Linux-Gpu

Accelerate your C++ Linux applications and services by offloading resource-demanding OCR tasks to NVIDIA® CUDA® enabled GPU. Extract editable text from scanned documents, photos, screenshots, and more with just a few lines of code. The library can handle various fonts, layouts, and styles, bulk-recognize entire folders and archives of images, process multi-page PDFs and TIFFs. GPU-accelerated Aspose.OCR for C++ is well-fit for global scale content digitization. It supports a vast range of languages across Europe, Middle East, Asia, Africa, and the Americas, including the ability to recognize mixed languages within a document. This versatile library empowers businesses of all sizes, from startups to global corporations. Changelog: - Improved loading of external OCR modules. - Minor enhancements and fixes.

Aspose.OCR-GPU

Aspose.OCR for .NET is a powerful yet easy-to-use and cost-effective API for extracting text from scanned images, photos, screenshots, PDF documents, and other files. It allows you to add optical character recognition (OCR) functionality to your .NET desktop or web application in less than 10 lines of code without worrying about complex formulas, neural networks and other technical details. Advanced machine learning models and artificial intelligence allow you to read text in 26 languages based on Latin and Cyrillic scripts, as well as Chinese. Various pre-processing filters allow you to correct rotated and noisy images without loss of recognition accuracy. To further improve recognition results, you can turn on spell checker, which finds and automatically corrects spelling errors. Aspose.OCR can recognize scanned images or even smartphone photos in the most popular formats: PDF, JPG, TIFF, PNG, BMP, GIF, or DjVu. You can also perform batch image recognition from a folder or ZIP archive in one call. The recognition results are returned in the most popular document and data exchange formats: plain text, PDF, Word, Excel, JSON and XML and can be further parsed and analyzed programmatically. The library is fully compatible with other Aspose products. You can build solutions of any complexity using familiar concepts with minimal code. Changelog - Improved text overlay matching to the original image. DEPRECATION WARNING: Several classes and methods from previous versions of Aspose.OCR remain functional but are marked deprecated. They will be removed in release 23.11.0 (November 2023) in favor of the new API introduced in this release. Please adapt your code to replace them with the new APIs before then. See the Release Notes for more details. Check for details at https://docs.aspose.com/ocr/net/aspose-ocr-for-net-23-10-1-release-notes/ Resources: Online documentation: https://docs.aspose.com/ocr/net/ Free support forum: https://forum.aspose.com/c/ocr/

FaceONNX.Gpu

Face recognition and analytics library based on deep neural networks and ONNX runtime. Gpu implementation.

Microsoft.ML.OnnxRuntimeGenAI.Cuda

ONNX Runtime Generative AI Native Package

GitHub repositories (11)

Showing the top 5 popular GitHub repositories that depend on Microsoft.ML.OnnxRuntime.Gpu:

Repository Stars
codeproject/CodeProject.AI-Server
CodeProject.AI Server is a self contained service that software developers can include in, and distribute with, their applications in order to augment their apps with the power of AI.
microsoft/psi
Platform for Situated Intelligence
NickSwardh/YoloDotNet
YoloDotNet - A C# .NET 8.0 project for Classification, Object Detection, OBB Detection, Segmentation and Pose Estimation in both images and videos.
dme-compunet/YoloSharp
🚀 Use YOLO11 in real-time for object detection tasks, with edge performance ⚡️ powered by ONNX-Runtime.
sstainba/Yolov8.Net
A .net 6 implementation to use Yolov5 and Yolov8 models via the ONNX Runtime
Version Downloads Last updated
1.20.1 532 11/21/2024
1.20.0 2,230 10/31/2024
1.19.2 12,817 9/3/2024
1.19.1 3,061 8/21/2024
1.19.0 1,737 8/17/2024
1.19.0-dev-20240812-1833-cc... 230 8/13/2024
1.18.1 6,648 6/27/2024
1.18.0 6,280 5/17/2024
1.17.3 12,363 4/10/2024
1.17.1 9,456 2/25/2024
1.17.0 7,404 1/31/2024
1.16.3 79,233 11/20/2023
1.16.2 25,542 11/9/2023
1.16.1 20,296 10/11/2023
1.16.0 71,873 9/19/2023
1.15.1 106,609 6/16/2023
1.15.0 38,705 5/24/2023
1.15.0-alpha 1,290 5/13/2023
1.14.1 95,731 2/27/2023
1.14.0 17,827 2/10/2023
1.13.1 88,643 10/24/2022
1.12.1 106,443 8/4/2022
1.12.0 28,145 7/22/2022
1.11.0 99,726 3/25/2022
1.10.0 47,842 12/7/2021
1.9.0 47,188 9/22/2021
1.8.1 88,674 7/7/2021
1.8.0 5,919 6/3/2021
1.7.1 27,307 3/4/2021
1.6.0 12,455 12/10/2020
1.5.2 7,825 10/15/2020
1.5.1 1,983 9/29/2020
1.4.0 21,354 7/17/2020
1.3.0 10,071 5/18/2020
1.2.0 5,394 3/10/2020
1.1.2 4,466 2/21/2020
1.1.1 1,613 1/24/2020
1.1.0 1,973 12/19/2019
1.0.0 1,917 10/30/2019
0.5.1 1,001 10/12/2019
0.5.0 3,789 8/1/2019
0.4.0 1,242 5/2/2019
0.3.1 918 4/9/2019
0.3.0 974 3/14/2019
0.2.1 1,177 2/1/2019
0.1.5 13,835 1/4/2019

Release Def:
Branch: refs/heads/rel-1.16.0
Commit: e7a0495a874251e9747b2ce0683e0580282c54df
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=356670