dotnet add package Microsoft.ML.OnnxRuntime.Extensions --version 0.9.0
NuGet\Install-Package Microsoft.ML.OnnxRuntime.Extensions -Version 0.9.0
<PackageReference Include="Microsoft.ML.OnnxRuntime.Extensions" Version="0.9.0" />
paket add Microsoft.ML.OnnxRuntime.Extensions --version 0.9.0
#r "nuget: Microsoft.ML.OnnxRuntime.Extensions, 0.9.0"
// Install Microsoft.ML.OnnxRuntime.Extensions as a Cake Addin #addin nuget:?package=Microsoft.ML.OnnxRuntime.Extensions&version=0.9.0 // Install Microsoft.ML.OnnxRuntime.Extensions as a Cake Tool #tool nuget:?package=Microsoft.ML.OnnxRuntime.Extensions&version=0.9.0
OnnxRuntime.Extensions NuGet Package
ONNX Runtime Extensions is a library of custom ONNX operators used for pre and post processing ONNX models.
|Product||Versions 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-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-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.|
This package has no dependencies.
NuGet packages (3)
Showing the top 3 NuGet packages that depend on Microsoft.ML.OnnxRuntime.Extensions:
OnnxRuntime Integration Library for .NET Core This repository harnesses the capabilities of both ONNX Runtime and Microsoft ML, offering a comprehensive solution that empowers developers to build, deploy, and execute machine learning models seamlessly in .NET environments, unlocking a world of possibilities for intelligent applications.
An EXPERIMENTAL implementation of Diffusers in .NET, ported from Python libraries
Recognizes the license plates of many european countries together with the vehicle types
GitHub repositories (1)
Showing the top 1 popular GitHub repositories that depend on Microsoft.ML.OnnxRuntime.Extensions:
Inference Stable Diffusion with C# and ONNX Runtime
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.