Yolov8.Net
1.1.3
See the version list below for details.
dotnet add package Yolov8.Net --version 1.1.3
NuGet\Install-Package Yolov8.Net -Version 1.1.3
<PackageReference Include="Yolov8.Net" Version="1.1.3" />
paket add Yolov8.Net --version 1.1.3
#r "nuget: Yolov8.Net, 1.1.3"
// Install Yolov8.Net as a Cake Addin #addin nuget:?package=Yolov8.Net&version=1.1.3 // Install Yolov8.Net as a Cake Tool #tool nuget:?package=Yolov8.Net&version=1.1.3
Yolov8.Net
https://github.com/sstainba/Yolov8.Net
This is a .NET interface for using Yolov5 and Yolov8 models on the ONNX runtime. At the time this is published, the ONNX Runtime only supports up to Opset 15. If you are training a custom model, be sure to export the model to the ONNX format with the --Opset=15 flag.
NOTE: If you want to use the GPU, you must have BOTH the CUDA drivers AND CUDNN installed!!!!!! Please use v11.x of the CUDNN as the 12.x versions are not yet supported. Loading the model is time consuming, so initial predictions will be slow. Subsequent predictions will be significantly faster.
// Create new Yolov8 predictor, specifying the model (in ONNX format)
// If you are using a custom trained model, you can provide an array of labels. Otherwise, the standard Coco labels are used.
using var yolo = YoloV8Predictor.Create("./assets/yolov8m.onnx");
// Provide an input image. Image will be resized to model input if needed.
using var image = Image.FromFile("Assets/rufus.jpg");
var predictions = yolo.Predict(image);
// Draw your boxes
using var graphics = Graphics.FromImage(image);
foreach (var pred in predictions)
{
var originalImageHeight = image.Height;
var originalImageWidth = image.Width;
var x = Math.Max(pred.Rectangle.X, 0);
var y = Math.Max(pred.Rectangle.Y, 0);
var width = Math.Min(originalImageWidth - x, pred.Rectangle.Width);
var height = Math.Min(originalImageHeight - y, pred.Rectangle.Height);
////////////////////////////////////////////////////////////////////////////////////////////
// *** Note that the output is already scaled to the original image height and width. ***
////////////////////////////////////////////////////////////////////////////////////////////
// Bounding Box Text
string text = $"{pred.Label.Name} [{pred.Score}]";
using (Graphics graphics = Graphics.FromImage(image))
{
graphics.CompositingQuality = CompositingQuality.HighQuality;
graphics.SmoothingMode = SmoothingMode.HighQuality;
graphics.InterpolationMode = InterpolationMode.HighQualityBicubic;
// Define Text Options
Font drawFont = new Font("consolas", 11, FontStyle.Regular);
SizeF size = graphics.MeasureString(text, drawFont);
SolidBrush fontBrush = new SolidBrush(Color.Black);
Point atPoint = new Point((int)x, (int)y - (int)size.Height - 1);
// Define BoundingBox options
Pen pen = new Pen(Color.Yellow, 2.0f);
SolidBrush colorBrush = new SolidBrush(Color.Yellow);
// Draw text on image
graphics.FillRectangle(colorBrush, (int)x, (int)(y - size.Height - 1), (int)size.Width, (int)size.Height);
graphics.DrawString(text, drawFont, fontBrush, atPoint);
// Draw bounding box on image
graphics.DrawRectangle(pen, x, y, width, height);
}
}
References
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net6.0 is compatible. 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. |
-
net6.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.15.1)
- SixLabors.ImageSharp (>= 3.0.1)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories (1)
Showing the top 1 popular GitHub repositories that depend on Yolov8.Net:
Repository | Stars |
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codeproject/CodeProject.AI-Server
CodeProject.AI Server is a self contained service that software developers can include in, and distribute with, their applications in order to augment their apps with the power of AI.
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