NumSharp 0.30.0
dotnet add package NumSharp --version 0.30.0
NuGet\Install-Package NumSharp -Version 0.30.0
<PackageReference Include="NumSharp" Version="0.30.0" />
paket add NumSharp --version 0.30.0
#r "nuget: NumSharp, 0.30.0"
// Install NumSharp as a Cake Addin #addin nuget:?package=NumSharp&version=0.30.0 // Install NumSharp as a Cake Tool #tool nuget:?package=NumSharp&version=0.30.0
NumSharp is the fundamental library for scientific computing with .NET providing a similar API to python's numpy scientific library. NumSharp has full N-D, broadcasting and axis support. If you want to use .NET to get started with machine learning, NumSharp will be your best tool.
| 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-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 | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
| .NET Framework | 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. |
| Tizen | tizen40 was computed. tizen60 was computed. |
| Xamarin.iOS | xamarinios was computed. |
| Xamarin.Mac | xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos was computed. |
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.NETStandard 2.0
- System.Memory (>= 4.5.4)
NuGet packages (22)
Showing the top 5 NuGet packages that depend on NumSharp:
| Package | Downloads |
|---|---|
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Microsoft.Quantum.Simulators
Classical simulators of quantum computers for the Q# programming language. |
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Microsoft.Quantum.Standard
Microsoft's Quantum standard libraries. |
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Bigtree.Algorithm
Machine Learning library in .NET Core. |
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FaceAiSharp
FaceAiSharp allows you to work with face-related computer vision tasks easily. It currently provides face detection, face recognition, facial landmarks detection, and eye state detection functionalities. FaceAiSharp leverages publicly available pretrained ONNX models to deliver accurate and efficient results and offers a convenient way to integrate them into your .NET applications. Whether you need to find faces, recognize individuals, detect facial landmarks, or determine eye states, FaceAiSharp simplifies the process with its simple API. ONNXRuntime is used for model inference, enabling hardware acceleration were possible. All processing is done locally, with no reliance on cloud services. This package contains just FaceAiSharp's managed code and does not include any ONNX models. Take a look at FaceAiSharp.Bundle for a batteries-included package with everything you need to get started. |
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FaceAiSharp.Bundle
FaceAiSharp allows you to work with face-related computer vision tasks easily. It currently provides face detection, face recognition, facial landmarks detection, and eye state detection functionalities. FaceAiSharp leverages publicly available pretrained ONNX models to deliver accurate and efficient results and offers a convenient way to integrate them into your .NET applications. Whether you need to find faces, recognize individuals, detect facial landmarks, or determine eye states, FaceAiSharp simplifies the process with its simple API. ONNXRuntime is used for model inference, enabling hardware acceleration were possible. All processing is done locally, with no reliance on cloud services. This is a bundle package that installs FaceAiSharp's managed code and multiple AI models in the ONNX format. |
GitHub repositories (9)
Showing the top 5 popular GitHub repositories that depend on NumSharp:
| Repository | Stars |
|---|---|
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stakira/OpenUtau
Open singing synthesis platform / Open source UTAU successor
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SciSharp/NumSharp
High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
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kendryte/nncase
Open deep learning compiler stack for Kendryte AI accelerators ✨
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SciSharp/SiaNet
An easy to use C# deep learning library with CUDA/OpenCL support
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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.
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| Version | Downloads | Last updated |
|---|---|---|
| 0.30.0 | 703,544 | 2/14/2021 |
| 0.20.5 | 724,940 | 12/31/2019 |
| 0.20.4 | 334,819 | 10/5/2019 |
| 0.20.3 | 3,571 | 9/28/2019 |
| 0.20.2 | 2,444 | 9/11/2019 |
| 0.20.1 | 18,200 | 9/1/2019 |
| 0.20.0 | 3,796 | 8/20/2019 |
| 0.10.6 | 26,941 | 7/24/2019 |
| 0.10.5 | 2,636 | 7/22/2019 |
| 0.10.4 | 2,482 | 7/18/2019 |
| 0.10.3 | 12,421 | 6/15/2019 |
| 0.10.2 | 2,156 | 5/25/2019 |
| 0.10.1 | 3,675 | 5/11/2019 |
| 0.10.0 | 2,423 | 5/5/2019 |
| 0.9.0 | 3,439 | 4/15/2019 |
| 0.8.3 | 2,017 | 3/29/2019 |
| 0.8.2 | 2,766 | 3/25/2019 |
| 0.8.1 | 2,187 | 3/22/2019 |
| 0.8.0 | 2,309 | 3/12/2019 |
| 0.7.4 | 1,876 | 3/7/2019 |
| 0.7.3 | 549,410 | 2/20/2019 |
| 0.7.2 | 2,363 | 2/18/2019 |
| 0.7.1 | 2,397 | 2/12/2019 |
| 0.7.0 | 1,948 | 1/28/2019 |
| 0.6.6 | 2,354 | 1/26/2019 |
| 0.6.5 | 2,386 | 1/11/2019 |
| 0.6.4 | 2,389 | 1/7/2019 |
| 0.6.3 | 1,895 | 12/30/2018 |
| 0.6.2 | 5,941 | 12/27/2018 |
| 0.6.1 | 1,899 | 12/26/2018 |
| 0.6.0 | 1,974 | 12/21/2018 |
| 0.5.0 | 1,942 | 12/5/2018 |
| 0.4.0 | 1,878 | 11/21/2018 |
| 0.3.0 | 1,870 | 11/7/2018 |
| 0.2.0 | 3,992 | 10/29/2018 |
| 0.1.0 | 2,158 | 10/10/2018 |