# YoloSharp
**Repository Path**: wangyabing/YoloSharp
## Basic Information
- **Project Name**: YoloSharp
- **Description**: No description available
- **Primary Language**: C#
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-08-21
- **Last Updated**: 2025-08-31
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# 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, Yolov11 and Yolov12 now.
- Support Predict and Segment 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/yolo11 and yolov12(converted).
- Support .Net6 or higher.
## Models
You can download yolov5/yolov8 pre-trained models here.
Prediction Checkpoints
| model | n| s | m | l | x |
| --- | ----------- | ----------- | ----------- | ----------- | ----------- |
| yolov5 | [yolov5n](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5n.bin) | [yolov5s](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5s.bin) | [yolov5m](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5m.bin) | [yolov5l](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5l.bin) | [yolov5x](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5x.bin) |
| yolov5 | [yolov5nu](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5nu.bin) | [yolov5su](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5su.bin) | [yolov5mu](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5mu.bin) | [yolov5lu](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5lu.bin) | [yolov5xu](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov5xu.bin) |
| yolov8 | [yolov8n](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8n.bin) | [yolov8s](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8s.bin) | [yolov8m](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8m.bin) | [yolov8l](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8l.bin) | [yolov8x](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8x.bin) |
| yolov11 | [yolov11n](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11n.bin) | [yolov11s](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11s.bin) | [yolov11m](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/yolov11m.bin) | [yolov11l](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11l.bin) | [yolov11x](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11x.bin) |
Segmention Checkpoints
| model | n| s | m | l | x |
| --- | ----------- | ----------- | ----------- | ----------- | ----------- |
| yolov8 | [yolov8n](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8n-seg.bin) | [yolov8s](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8s-seg.bin) | [yolov8m](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8m-seg.bin) | [yolov8l](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8l-seg.bin) | [yolov8x](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov8x-seg.bin) |
| yolov11 | [yolov11n](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11n-seg.bin) | [yolov11s](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11s-seg.bin) | [yolov11m](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11m-seg.bin) | [yolov11l](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11l-seg.bin) | [yolov11x](https://github.com/IntptrMax/YoloSharp/releases/download/1.0.6/Yolov11x-seg.bin) |
## How to use
You can download the code or add it from nuget.
dotnet add package IntptrMax.YoloSharp
> [!NOTE]
> Please 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 to execute.
In your code you can use it as below.
### Predict
You can use it with the code below:
```CSharp
MagickImage predictImage = new MagickImage(predictImagePath);
// Create predictor
Predictor predictor = new Predictor(sortCount, yoloType: yoloType, deviceType: deviceType, yoloSize: yoloSize, dtype: dtype);
// Train model
predictor.LoadModel(preTrainedModelPath, skipNcNotEqualLayers: true);
predictor.Train(trainDataPath, valDataPath, outputPath: outputPath, batchSize: batchSize, epochs: epochs, useMosaic: true);
//ImagePredict image
predictor.LoadModel(Path.Combine(outputPath, "best.bin"));
List predictResult = predictor.ImagePredict(predictImage, predictThreshold, iouThreshold);
```
Use yolov5n pre-trained model to detect.
### Segment
You can use it with the code below:
```CSharp
MagickImage predictImage = new MagickImage(predictImagePath);
// Create segmenter
Segmenter segmenter = new Segmenter(sortCount, yoloType: yoloType, deviceType: deviceType, yoloSize: yoloSize, dtype: dtype);
segmenter.LoadModel(preTrainedModelPath, skipNcNotEqualLayers: true);
// Train model
segmenter.Train(trainDataPath, valDataPath, outputPath: outputPath, batchSize: batchSize, epochs: epochs, useMosaic: false);
segmenter.LoadModel(Path.Combine(outputPath, "best.bin"));
// ImagePredict image
var (predictResult, resultImage) = segmenter.ImagePredict(predictImage, predictThreshold, iouThreshold);
```
Use yolov8n-seg pre-trained model to detect.
