YoloV8 1.0.0
There is a newer version of this package available.
See the version list below for details.
See the version list below for details.
dotnet add package YoloV8 --version 1.0.0
NuGet\Install-Package YoloV8 -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="YoloV8" Version="1.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add YoloV8 --version 1.0.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: YoloV8, 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 YoloV8 as a Cake Addin
#addin nuget:?package=YoloV8&version=1.0.0
// Install YoloV8 as a Cake Tool
#tool nuget:?package=YoloV8&version=1.0.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
YOLOv8
Use YOLOv8 in real-time, for object detection, instance segmentation, pose estimation and image classification, via ONNX Runtime
Use
Export from PyTorch
Run the following Python code to export the model to ONNX format:
from ultralytics import YOLO
# Load a model
model = YOLO('path/to/model')
# export the model to ONNX format
model.export(format='onnx', opset=15)
Note: Pay attention to specify opset=15
because the ONNX Runtime currently only supports up to Opset 15.
Use in C# with ONNX Runtime
using var predictor = new YoloV8(model);
var result = predictor.Detect("path/to/image");
Console.WriteLine(result);
Plotting
You can use the following code to predict and plot a image, and save to file:
var image = "path/to/image";
using var predictor = new YoloV8("path/to/model");
var result = predictor.Pose(image);
using var origin = Image.Load<Rgb24>(image);
using var ploted = result.PlotImage(origin);
ploted.Save("./pose_demo.jpg")
Examples:
Detection:
Pose:
Segmentation:
License
MIT License
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net7.0 is compatible. 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. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
net7.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.14.1)
- SixLabors.ImageSharp (>= 3.0.1)
- SixLabors.ImageSharp.Drawing (>= 1.0.0-beta15)
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:
Repository | Stars |
---|---|
babalae/better-genshin-impact
📦BetterGI · 更好的原神 - 自动拾取 | 自动剧情 | 全自动钓鱼(AI) | 全自动七圣召唤 | 自动伐木 | 自动刷本 - UI Automation Testing Tools For Genshin Impact
|
Version | Downloads | Last updated |
---|---|---|
4.1.5 | 660 | 4/14/2024 |
4.1.4 | 91 | 4/14/2024 |
4.0.0 | 821 | 3/6/2024 |
3.1.1 | 456 | 2/4/2024 |
3.1.0 | 154 | 1/29/2024 |
3.0.0 | 1,264 | 11/27/2023 |
2.0.1 | 1,423 | 10/10/2023 |
2.0.0 | 285 | 9/27/2023 |
1.6.0 | 320 | 9/21/2023 |
1.5.0 | 231 | 9/15/2023 |
1.4.0 | 295 | 9/8/2023 |
1.3.0 | 1,073 | 8/29/2023 |
1.2.0 | 200 | 8/21/2023 |
1.0.1 | 192 | 8/16/2023 |
1.0.0 | 336 | 7/23/2023 |