Microsoft.ML.OnnxRuntime 1.7.0

The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org. Prefix Reserved
There is a newer version of this package available.
See the version list below for details.
dotnet add package Microsoft.ML.OnnxRuntime --version 1.7.0
NuGet\Install-Package Microsoft.ML.OnnxRuntime -Version 1.7.0
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" Version="1.7.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.ML.OnnxRuntime --version 1.7.0
#r "nuget: Microsoft.ML.OnnxRuntime, 1.7.0"
#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 as a Cake Addin
#addin nuget:?package=Microsoft.ML.OnnxRuntime&version=1.7.0

// Install Microsoft.ML.OnnxRuntime as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntime&version=1.7.0

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 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 (80)

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

Package Downloads
Aspose.OCR

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: - Extended support for TIFF file variants and compression schemes. Check for details at https://releases.aspose.com/ocr/net/release-notes/2024/aspose-ocr-for-net-24-3-1-release-notes/ Resources: Online documentation: https://docs.aspose.com/ocr/net/ Free support forum: https://forum.aspose.com/c/ocr/

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

Aspose.Ocr.Cpp

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.

FaceONNX

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

our1314.work

Package Description

GitHub repositories (18)

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

Repository Stars
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.
babalae/better-genshin-impact
📦BetterGI · 更好的原神 - 自动拾取 | 自动剧情 | 全自动钓鱼(AI) | 全自动七圣召唤 | 自动伐木 | 自动刷本 - UI Automation Testing Tools For Genshin Impact
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
1.17.1 33,442 2/25/2024
1.17.0 32,690 1/31/2024
1.16.3 107,765 11/20/2023
1.16.2 19,088 11/9/2023
1.16.1 60,339 10/11/2023
1.16.0 68,370 9/19/2023
1.15.1 268,148 6/16/2023
1.15.0 48,349 5/24/2023
1.15.0-rc 4,234 5/17/2023
1.15.0-alpha 4,118 5/12/2023
1.14.1 137,623 2/27/2023
1.14.0 73,776 2/10/2023
1.13.1 193,034 10/24/2022
1.12.1 225,129 8/4/2022
1.12.0 20,493 7/22/2022
1.11.0 299,328 3/25/2022
1.10.0 185,832 12/7/2021
1.9.0 114,683 9/22/2021
1.8.1 112,358 7/7/2021
1.8.0 46,082 6/3/2021
1.7.0 213,344 3/2/2021
1.6.0 105,749 12/10/2020
1.5.2 73,598 10/15/2020
1.5.1 23,446 9/29/2020
1.4.0 104,658 7/17/2020
1.3.0 91,298 5/18/2020
1.2.0 73,116 3/10/2020
1.1.2 9,052 2/21/2020
1.1.1 17,096 1/24/2020
1.1.0 11,997 12/19/2019
1.0.0 88,426 10/30/2019
0.5.1 178,316 10/12/2019
0.5.0 16,525 8/1/2019
0.4.0 68,391 5/2/2019
0.3.1 5,950 4/9/2019
0.3.0 39,461 3/14/2019
0.2.1 40,494 2/1/2019
0.1.5 10,202 12/1/2018

Release Def:
Branch: refs/heads/rel-1.7.0
Commit: 40b092961c1c57a0422d53f14692855b550b1422
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=145599