IntptrMax.YoloSharp 1.0.0

.NET 8.0 This package targets .NET 8.0. The package is compatible with this framework or higher. 
dotnet add package IntptrMax.YoloSharp --version 1.0.0                

                    
                

            
NuGet\Install-Package IntptrMax.YoloSharp -Version 1.0.0
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="IntptrMax.YoloSharp" Version="1.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add IntptrMax.YoloSharp --version 1.0.0                

                    
                

            
#r "nuget: IntptrMax.YoloSharp, 1.0.0"
#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 IntptrMax.YoloSharp as a Cake Addin
#addin nuget:?package=IntptrMax.YoloSharp&version=1.0.0

// Install IntptrMax.YoloSharp as a Cake Tool
#tool nuget:?package=IntptrMax.YoloSharp&version=1.0.0

YoloSharp

Train Yolo model in C# with TorchSharp. With the help of this project you won't have to transform .pt model to onnx, and can train your own model in C#.

Feature

  • Written in C# only.
  • Train and predict your own model.
  • Support Yolov5, Yolov5u, Yolov8 and Yolov11 now.
  • Support n/s/m/l/x size.
  • Support LetterBox and Mosaic4 method for preprocessing images.
  • Support NMS with GPU.
  • Support Load PreTrained models from ultralytics/yolov5/yolov8 and yolo11 (converted).

Models

You can download yolov5/yolov8 pre-trained models here.

model n s m l x
yolov5 yolov5n yolov5s yolov5m yolov5l yolov5x
yolov5u yolov5nu yolov5su yolov5mu yolov5lu yolov5xu
yolov8 yolov8n yolov8s yolov8m yolov8l yolov8x
yolov11 yolov11n yolov11s yolov11m yolov11l yolov11x

How to use:

1.Add Nuget pack: IntptrMax.YoloSharp.

2.Add one of libtorch-cpu, libtorch-cuda-12.1, libtorch-cuda-12.1-win-x64 or libtorch-cuda-12.1-linux-x64 version 2.5.1.0.

3.And Then in your program, you only have to do the below:

// Create predictor

Predictor predictor = new Predictor(sortCount, yoloType: yoloType, deviceType: deviceType, yoloSize: yoloSize, dtype: dtype);

// Train model

predictor.LoadModel(preTraindModelPath);

predictor.Train(trainDataPath, valDataPath, outputPath: outputPath, batchSize: batchSize, epochs: epochs);

// Predict image

Bitmap inputBitmap = new Bitmap(predictImagePath);

predictor.LoadModel(Path.Combine(outputPath, "best.bin"));

var results = predictor.ImagePredict(inputBitmap, predictThreshold, iouThreshold);

Product Compatible and additional computed target framework versions.
.NET net8.0 is compatible.  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. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

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Version Downloads Last updated
1.0.0 53 1/2/2025