Microsoft.ML.OnnxRuntime.Extensions 0.13.0

Prefix Reserved
.NET 6.0 This package targets .NET 6.0. The package is compatible with this framework or higher. .NET Standard 1.1 This package targets .NET Standard 1.1. The package is compatible with this framework or higher. 
dotnet add package Microsoft.ML.OnnxRuntime.Extensions --version 0.13.0                

                    
                

            
NuGet\Install-Package Microsoft.ML.OnnxRuntime.Extensions -Version 0.13.0
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.Extensions" Version="0.13.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Microsoft.ML.OnnxRuntime.Extensions --version 0.13.0                

                    
                

            
#r "nuget: Microsoft.ML.OnnxRuntime.Extensions, 0.13.0"
#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.Extensions as a Cake Addin
#addin nuget:?package=Microsoft.ML.OnnxRuntime.Extensions&version=0.13.0

// Install Microsoft.ML.OnnxRuntime.Extensions as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxRuntime.Extensions&version=0.13.0

OnnxRuntime.Extensions NuGet Package

ONNX Runtime Extensions is a library of custom ONNX operators used for pre and post processing ONNX models.

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-android31.0 is compatible.  net6.0-ios was computed.  net6.0-ios15.4 is compatible.  net6.0-maccatalyst was computed.  net6.0-maccatalyst14.0 is compatible.  net6.0-macos was computed.  net6.0-macos12.3 is compatible.  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.  monoandroid11.0 is compatible. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
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.  xamarinios10 is compatible. 
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.

This package has no dependencies.

NuGet packages (4)

Showing the top 4 NuGet packages that depend on Microsoft.ML.OnnxRuntime.Extensions:

Package Downloads
OnnxStack.Core

OnnxRuntime Integration Library for .NET OnnxStack transforms machine learning in .NET, Seamlessly integrating with ONNX Runtime and Microsoft ML, this library empowers you to build, deploy, and execute machine learning models entirely within the .NET ecosystem. Bid farewell to Python dependencies and embrace a new era of intelligent applications tailored for .NET
SharpDiffusion

An EXPERIMENTAL implementation of Diffusers in .NET, ported from Python libraries
CapCognition.Forms.LicensePlateDetection

Recognizes the license plates of many european countries together with the vehicle types
CapCognition.Maui.LPR

License plate recognition library

GitHub repositories (4)

Showing the top 4 popular GitHub repositories that depend on Microsoft.ML.OnnxRuntime.Extensions:

Repository Stars
cassiebreviu/StableDiffusion
Inference Stable Diffusion with C# and ONNX Runtime
TensorStack-AI/OnnxStack
C# Stable Diffusion using ONNX Runtime
microsoft/ai-dev-gallery
An open-source project for Windows developers to learn how to add AI with local models and APIs to Windows apps.
Particle1904/DatasetHelpers
Dataset Helper program to automatically select, re scale and tag Datasets (composed of image and text) for Machine Learning training.
Version Downloads Last updated
0.13.0 4,776 10/31/2024
0.12.0 7,768 8/16/2024
0.11.0-dev-20240524-2333-8d... 916 5/28/2024
0.10.0 12,167 2/6/2024
0.9.0 4,383 9/20/2023
0.8.1-alpha 3,737 5/31/2023
0.8.0 2,447 5/26/2023
0.8.0-beta 790 5/16/2023
0.8.0-alpha.1 217 5/9/2023
0.8.0-alpha 536 4/27/2023

1. NuGet package for the .NET platform. This package offers comprehensive platform support, including Windows, Linux, MacOS, Android, and iOS. Both x64 and arm64 architectures are supported, where applicable.
     2. Support for pre-processing and post-processing of the Whisper model, inclusive of Audio and Tokenizer decoding operators.
     3. Extends support for pre-processing and post-processing of object-detection models, including a new DrawBoundingBoxes operator. Pre/post processing tools can add non-max-suppression to the model to select the best bounding boxes, and scale those to the original image. See the end-to-end example in yolo_e2e.py.
     4. Introduces the Audio Domain, complemented with AudioCodec and optimized STFT Operators, enhancing audio processing capabilities.
     5. Enabled optional input/output support for some operators such as GPT2Tokenizer, CLIPTokenizer, and RobertaTokenizer.
     6. Refined the implementation of offset mapping for BBPE-style tokenizers for more operators and efficiency improvement.
     7. Other bug and security fixes.