Microsoft.ML.OnnxRuntime 1.1.2

Prefix Reserved
.NET Standard 1.1 This package targets .NET Standard 1.1. The package is compatible with this framework or higher.
There is a newer version of this package available.
See the version list below for details. 
dotnet add package Microsoft.ML.OnnxRuntime --version 1.1.2                

                    
                

            
NuGet\Install-Package Microsoft.ML.OnnxRuntime -Version 1.1.2
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" Version="1.1.2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Microsoft.ML.OnnxRuntime --version 1.1.2                

                    
                

            
#r "nuget: Microsoft.ML.OnnxRuntime, 1.1.2"
#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 as a Cake Addin
#addin nuget:?package=Microsoft.ML.OnnxRuntime&version=1.1.2

// Install Microsoft.ML.OnnxRuntime as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntime&version=1.1.2

This package contains ONNX Runtime for .Net platforms

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 (96)

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

Package Downloads
Aspose.OCR

Powerful and developer-friendly OCR API for extracting text from images and creating searchable PDFs. Add optical character recognition to on-premises solutions, web sites, cloud services, and serverless functions with just a few lines of native .NET code. Effortlessly transform scanned pages, photos, screenshots, handwritten memos, and other images into machine-readable text, regardless of the font, layout and styles. Find and compare text on images. Bulk-recognize all images from folders and archives; read multi-page PDF documents and TIFF images. Aspose.OCR is a universal solution for document processing, data extraction, and content digitization on a global scale. Supporting over 130 European, Middle East, Asian, African and American languages, the library allows you to recognize texts in Latin, Cyrillic, Arabic, Chinese, and Hindi scrips, including text in mixed languages. The library can be used virtually everywhere, catering to both small and medium businesses as well as multinational corporations. With Aspose.OCR, optical character recognition becomes a trivial and straightforward task, even for developers new to the technology. You can focus at business task rather than complex maths, neural networks, and other technical intricacies. Powerful image processing and customizable content structure detection algorithms enable text extraction from virtually any image, ranging from high-quality scans to street photos. Aspose.OCR for .NET can work with virtually any file you can get from a scanner or camera, including PDF document and multi-page TIFF images. Recognition results are returned in the most popular file and data exchange formats that can be saved, imported to a database, or analyzed in real time. Changelog: - Korean language recognition, including mixed texts in Korean and English. - Japanese language recognition, with support for mixed texts in Japanese and English. - Enhanced support for custom fonts in searchable PDFs. - Faster and more precise text extraction across various document types. Check for details at https://releases.aspose.com/ocr/net/release-notes/2024/aspose-ocr-for-net-24-11-0-release-notes/ Resources: Product page: https://products.aspose.com/ocr/net/ Advanced OCR models: https://github.com/aspose-ocr/resources Online documentation: https://docs.aspose.com/ocr/net/ Solutions: https://docs.aspose.com/ocr/net/use-cases/ Free support forum: https://forum.aspose.com/c/ocr/16
GroupDocs.Parser

GroupDocs.Parser for .NET is a useful parsing class library which allows to extract different data from documents of various formats. The data extraction API supports PDF, DOC, DOCX, PPT, PPTX, XLS, XLSX and many more formats.
BarCode

IronBarCode - An advanced package that leverages Machine Learning for more accurate Barcode detection Quickstart guide: https://ironsoftware.com/csharp/barcode/ IronBarcode allows developers to read & write Barcodes and QR Codes within .NET Applications & websites. Reading or writing barcodes only requires a single line of code with Iron Barcode. The .NET Barcode Library reads and writes most Barcode and QR standards. These include code 39/93/128, UPC A/E, EAN 8/13, ITF, RSS 14 / Expanded, Databar, CodaBar, Aztec, Data Matrix, MaxiCode, PDF417, MSI, Plessey, USPS, and QR. The barcode result data includes type, text, binary data, page, and image file. Barcode reading engine includes automatic image correction and barcode detection technology to take the pain out of locating and reading from imperfect scans. Multithreading, cropping, and batch scanning provides fast and accurate scanning of multi page documents. Barcode writing API checks and verifys format, length, number, checksum to automatically avoid encoding errors. Barcode writer allows for styling, resizing, margins, borders, recoloring, and adding text annotations. Write to image, PDF or HTML file. Key library features include: * Read single or multiple Barcodes and QR Codes from images or PDFs. * Image correction for skewing, orientation, noise, low resolution, contrast etc. * Create barcodes and apply to images or PDF documents. * Embed barcodes into html documents. * Style Barcodes and add annotation text. * QR Code Writing allows adding of logos, colors, and advanced QR alignment. IronBarcode can be used within C#, VB.NET, ASP .NET projects, MVC, Web Services, Console & Desktop Applications. Supports: * .NET Framework 4.6.2 + * .NET Core 2.0 + * .NET 5 * .NET 6 * .NET 7 * .NET 8 Licensing & Support available for commercial deployments. For code examples, documentation & more visit https://ironsoftware.com/csharp/barcode/ For support please email us at support@ironsoftware.com
our1314.work

Package Description
Microsoft.ML.OnnxRuntimeGenAI

ONNX Runtime Generative AI Native Package

GitHub repositories (18)

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

Repository Stars
microsoft/semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
rocksdanister/lively
Free and open-source software that allows users to set animated desktop wallpapers and screensavers powered by WinUI 3.
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
stakira/OpenUtau
Open singing synthesis platform / Open source UTAU successor
Webreaper/Damselfly
Damselfly is a server-based Photograph Management app. The goal of Damselfly is to index an extremely large collection of images, and allow easy search and retrieval of those images, using metadata such as the IPTC keyword tags, as well as the folder and file names. Damselfly includes support for object/face detection.
Version Downloads Last updated
1.20.0 13,460 10/31/2024
1.19.2 105,333 9/3/2024
1.19.1 37,772 8/21/2024
1.19.0 14,570 8/15/2024
1.18.1 143,562 6/27/2024
1.18.0 111,937 5/17/2024
1.17.3 84,384 4/10/2024
1.17.1 263,150 2/25/2024
1.17.0 157,764 1/31/2024
1.16.3 301,440 11/20/2023
1.16.2 28,759 11/9/2023
1.16.1 102,159 10/11/2023
1.16.0 146,607 9/19/2023
1.15.1 357,649 6/16/2023
1.15.0 64,337 5/24/2023
1.15.0-rc 4,941 5/17/2023
1.15.0-alpha 4,914 5/12/2023
1.14.1 187,249 2/27/2023
1.14.0 97,304 2/10/2023
1.13.1 242,437 10/24/2022
1.12.1 284,748 8/4/2022
1.12.0 22,395 7/22/2022
1.11.0 366,938 3/25/2022
1.10.0 213,725 12/7/2021
1.9.0 126,764 9/22/2021
1.8.1 142,897 7/7/2021
1.8.0 54,338 6/3/2021
1.7.0 237,483 3/2/2021
1.6.0 126,465 12/10/2020
1.5.2 83,590 10/15/2020
1.5.1 25,944 9/29/2020
1.4.0 121,955 7/17/2020
1.3.0 101,651 5/18/2020
1.2.0 75,448 3/10/2020
1.1.2 9,314 2/21/2020
1.1.1 19,523 1/24/2020
1.1.0 12,402 12/19/2019
1.0.0 90,641 10/30/2019
0.5.1 180,769 10/12/2019
0.5.0 17,039 8/1/2019
0.4.0 69,879 5/2/2019
0.3.1 6,076 4/9/2019
0.3.0 40,372 3/14/2019
0.2.1 41,125 2/1/2019
0.1.5 11,146 12/1/2018

Release Def:
Branch: refs/heads/rel-1.1.2
Commit: a8efa42d6885212627f0e4e3bd251caedc6a8d7c
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=118451