Microsoft.ML.OnnxRuntime 1.11.0 The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org. Prefix Reserved

.NET Standard 1.1 
Install-Package Microsoft.ML.OnnxRuntime -Version 1.11.0
dotnet add package Microsoft.ML.OnnxRuntime --version 1.11.0
<PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.11.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Microsoft.ML.OnnxRuntime --version 1.11.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support. 
#r "nuget: Microsoft.ML.OnnxRuntime, 1.11.0"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. 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=1.11.0

// Install Microsoft.ML.OnnxRuntime as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntime&version=1.11.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

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

Product Versions
.NET net5.0 net5.0-windows net6.0 net6.0-android net6.0-ios net6.0-maccatalyst net6.0-macos net6.0-tvos net6.0-windows
.NET Core netcoreapp1.0 netcoreapp1.1 netcoreapp2.0 netcoreapp2.1 netcoreapp2.2 netcoreapp3.0 netcoreapp3.1
.NET Standard netstandard1.1 netstandard1.2 netstandard1.3 netstandard1.4 netstandard1.5 netstandard1.6 netstandard2.0 netstandard2.1
.NET Framework net45 net451 net452 net46 net461 net462 net463 net47 net471 net472 net48
MonoAndroid monoandroid monoandroid11.0
MonoMac monomac
MonoTouch monotouch
native native
Tizen tizen30 tizen40 tizen60
Universal Windows Platform uap uap10.0
Windows Phone wpa81
Windows Store netcore netcore45 netcore451
Xamarin.iOS xamarinios xamarinios10
Xamarin.Mac xamarinmac
Xamarin.TVOS xamarintvos
Xamarin.WatchOS xamarinwatchos
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (17)

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

Package Downloads
Aspose.OCR

Aspose.OCR for .NET is a robust optical character recognition API. Developers can easily add OCR functionalities in their applications. API is extensible, easy to use, compact and provides a simple set of classes for controlling character recognition.
Aspose.Ocr.Cpp

Aspose.OCR for C and C++ is a robust optical character recognition API. Developers can easily add OCR functionalities in their applications. API is extensible, easy to use, compact and provides a simple set of classes for controlling character recognition. It supports commonly used image formats and provides noise removal filters, determine text fields and automatic alignment of the document. The library requires onnxruntime.dll installed in the system.
FaceONNX

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

Package Description
SmartSelectors

A set of machine learning models to predict if an image is a certain type of web element.

GitHub repositories (6)

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

Repository Stars
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
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, and face-recognition.
stakira/OpenUtau
Open source UTAU successor
microsoft/psi
Platform for Situated Intelligence
microsoft/CryptoNets
CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.
Version Downloads Last updated
1.11.0 20,712 3/25/2022
1.10.0 62,813 12/7/2021
1.9.0 37,994 9/22/2021
1.8.1 44,845 7/7/2021
1.8.0 16,201 6/3/2021
1.7.0 90,244 3/2/2021
1.6.0 42,803 12/10/2020
1.5.2 47,380 10/15/2020
1.5.1 12,410 9/29/2020
1.4.0 59,419 7/17/2020
1.3.0 55,093 5/18/2020
1.2.0 63,697 3/10/2020
1.1.2 6,316 2/21/2020
1.1.1 7,390 1/24/2020
1.1.0 8,873 12/19/2019
1.0.0 67,834 10/30/2019
0.5.1 157,037 10/12/2019
0.5.0 13,069 8/1/2019
0.4.0 59,306 5/2/2019
0.3.1 4,549 4/9/2019
0.3.0 34,137 3/14/2019
0.2.1 36,647 2/1/2019
0.1.5 8,162 12/1/2018

Release Def:
Branch: refs/heads/rel-1.11.0
Commit: b713855a980056d89a1e550ad81dc3c19573d7a0
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=199094