Microsoft.ML.OnnxRuntime.Gpu 1.5.1

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There is a newer version of this package available.
See the version list below for details.
dotnet add package Microsoft.ML.OnnxRuntime.Gpu --version 1.5.1
NuGet\Install-Package Microsoft.ML.OnnxRuntime.Gpu -Version 1.5.1
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="1.5.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.ML.OnnxRuntime.Gpu --version 1.5.1
#r "nuget: Microsoft.ML.OnnxRuntime.Gpu, 1.5.1"
#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=1.5.1

// Install Microsoft.ML.OnnxRuntime.Gpu as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntime.Gpu&version=1.5.1
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 was computed.  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 (22)

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

Package Downloads
Aspose.Ocr.Cpp-GPU

Aspose.OCR for C++ 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 applications 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. Aspose.OCR can recognize scanned images or even smartphone photos. The library also allows you to process images directly from the web without downloading them locally. The recognition results are returned in the most popular document and data exchange formats: plain text, PDF, Word, 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: - Added the ability to customize recognition settings for individual images in a batch.

Aspose.Ocr.Cpp-Linux-Gpu

Aspose.OCR for C++ 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 applications 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. Aspose.OCR can recognize scanned images or even smartphone photos. The library also allows you to process images directly from the web without downloading them locally. The recognition results are returned in the most popular document and data exchange formats: plain text, PDF, Word, 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: - Added the ability to customize recognition settings for individual images in a batch.

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.

Yolov8.Net

Yolov5 and Yolov8 ONNX interface for .NET 6

GitHub repositories (9)

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

Repository Stars
microsoft/psi
Platform for Situated Intelligence
microsoft/Microsoft-Rocket-Video-Analytics-Platform
A highly extensible software stack to empower everyone to build practical real-world live video analytics applications for object detection and counting with cutting edge machine learning algorithms.
cassiebreviu/StableDiffusion
Inference Stable Diffusion with C# and ONNX Runtime
sstainba/Yolov8.Net
A .net 6 implementation to use Yolov5 and Yolov8 models via the ONNX Runtime
dme-compunet/YOLOv8
Use YOLOv8 in real-time, for object detection, instance segmentation, pose estimation and image classification, via ONNX Runtime.
Version Downloads Last updated
1.17.3 453 4/10/2024
1.17.1 5,480 2/25/2024
1.17.0 4,015 1/31/2024
1.16.3 38,216 11/20/2023
1.16.2 16,958 11/9/2023
1.16.1 17,048 10/11/2023
1.16.0 38,878 9/19/2023
1.15.1 72,492 6/16/2023
1.15.0 32,639 5/24/2023
1.15.0-alpha 848 5/13/2023
1.14.1 73,903 2/27/2023
1.14.0 16,221 2/10/2023
1.13.1 77,020 10/24/2022
1.12.1 90,827 8/4/2022
1.12.0 20,734 7/22/2022
1.11.0 83,400 3/25/2022
1.10.0 38,131 12/7/2021
1.9.0 42,966 9/22/2021
1.8.1 69,507 7/7/2021
1.8.0 5,577 6/3/2021
1.7.1 26,241 3/4/2021
1.6.0 11,712 12/10/2020
1.5.2 7,504 10/15/2020
1.5.1 1,761 9/29/2020
1.4.0 20,672 7/17/2020
1.3.0 9,720 5/18/2020
1.2.0 5,235 3/10/2020
1.1.2 4,321 2/21/2020
1.1.1 1,495 1/24/2020
1.1.0 1,765 12/19/2019
1.0.0 1,817 10/30/2019
0.5.1 923 10/12/2019
0.5.0 3,731 8/1/2019
0.4.0 1,150 5/2/2019
0.3.1 852 4/9/2019
0.3.0 889 3/14/2019
0.2.1 1,083 2/1/2019
0.1.5 13,698 1/4/2019

Release Def:
Branch: refs/heads/rel-1.5.1
Commit: 5de47affb14bbb7e0cea35c0f12c6b7f0436025e
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=134239