Introduction
Using Copilot to generate the code to retrieve an image from a security camera went surprisingly well so next step was something a bit more complex. For this post I have used Copilot prompts to generate code which uses Ultralytics YoloV8 and Compunet YoloSharp for object detection, object classification, pose estimation, and instance segmentation
using System;
using System.Drawing;
using YOLOSharp;
class Program
{
static void Main(string[] args)
{
string modelPath = "path/to/yolov8.onnx"; // Replace with the path to your YOLOv8 model
string imagePath = "path/to/image.jpg"; // Replace with the path to your image
// Load the YOLOv8 model
var yolo = new YOLO(modelPath);
// Load the image from disk
using (var image = Image.FromFile(imagePath))
{
// Run the YOLOv8 model on the image
var results = yolo.Predict(image);
// Display the results
foreach (var result in results)
{
Console.WriteLine($"Label: {result.Label}, Confidence: {result.Confidence}, BoundingBox: {result.BoundingBox}");
}
}
}
}
In this example:
Replace path/to/yolov8.onnx with the actual path to your YOLOv8 model file.
Replace path/to/image.jpg with the actual path to your image file.
This application loads the YOLOv8 model using YOLOSharp, loads an image from disk, runs the model on the image, and displays the results, including the label, confidence, and bounding box for each detected object.
Happy coding! 🚀
Copilot had “assumed” I meant object detection(reasonable) with YoloSharp and the code didn’t compile.
Object Detection
After some minor fixes and shifting the configuration to an appsettings file the application compiled.
using Compunet.YoloSharp;
using Microsoft.Extensions.Configuration;
using SixLabors.ImageSharp;
class Program
{
static void Main(string[] args)
{
Model.ApplicationSettings applicationSettings;
Console.WriteLine($"{DateTime.UtcNow:yy-MM-dd HH:mm:ss} 0.3.CameraHTTPClient starting");
#if RELEASE
Console.WriteLine("RELEASE");
#else
Console.WriteLine("DEBUG");
#endif
// load the app settings into configuration
var configuration = new ConfigurationBuilder()
.AddJsonFile("appsettings.json", false, true)
.Build();
applicationSettings = configuration.GetSection("ApplicationSettings").Get<Model.ApplicationSettings>();
// Load the YOLOv8 model
var yolo = new YoloPredictor(applicationSettings.ModelPath);
// Load the image from disk
using (var image = Image.Load(applicationSettings.ImagePath))
{
// Run the YOLOv8 model on the image
var results = yolo.Detect(image);
// Display the results
foreach (var result in results)
{
Console.WriteLine($"Label: {result.Name}, Confidence: {result.Confidence}, BoundingBox: {result.Bounds}");
}
}
}
}
I tested the implementation with sample “sports” image from the YoloSharp Github repository
The console application output looked reasonable
I manually compared the output of the console application with the Ultralytics Hub model preview tab and the results looked close enough.
Pose
My Copilot prompt
please write a C# console application that uses Compunet YoloSharp to run a yolov8 pose model on an image loaded from disk
using Compunet.YoloSharp;
using Microsoft.Extensions.Configuration;
using SixLabors.ImageSharp;
class Program
{
static void Main(string[] args)
{
Model.ApplicationSettings applicationSettings;
Console.WriteLine($"{DateTime.UtcNow:yy-MM-dd HH:mm:ss} 0.3.CameraHTTPClient starting");
#if RELEASE
Console.WriteLine("RELEASE");
#else
Console.WriteLine("DEBUG");
#endif
// load the app settings into configuration
var configuration = new ConfigurationBuilder()
.AddJsonFile("appsettings.json", false, true)
.Build();
applicationSettings = configuration.GetSection("ApplicationSettings").Get<Model.ApplicationSettings>();
// Load the YOLOv8 pose model
var yolo = new YoloPredictor(applicationSettings.ModelPath);
// Load the image from disk
using (var image = Image.Load(applicationSettings.ImagePath))
{
// Run the YOLOv8 pose model on the image
var results = yolo.Pose(image);
// Display the results
foreach (var result in results)
{
Console.WriteLine($"Label: {result.Name.Name}, Confidence: {result.Confidence}, BoundingBox: {result.Bounds}");
Console.WriteLine("Keypoints:");
foreach (var keypoint in result)
{
Console.WriteLine($" - {keypoint.Point}");
}
}
}
}
}
After some minor fixes and shifting the configuration to an appsettings file the application compiled. I tested the implementation with sample “sports” image from the YoloSharp Github repository
The console application output looked reasonable
I manually compared the output of the console application with the Ultralytics Hub model preview tab and the results were reasonable
Classification
My Copilot prompt
please write a C# console application that uses Compunet YoloSharp to run a yolov8 pose model on an image loaded from disk
using Compunet.YoloSharp;
using Microsoft.Extensions.Configuration;
using SixLabors.ImageSharp;
class Program
{
static void Main(string[] args)
{
Model.ApplicationSettings applicationSettings;
Console.WriteLine($"{DateTime.UtcNow:yy-MM-dd HH:mm:ss} 0.3.CameraHTTPClient starting");
#if RELEASE
Console.WriteLine("RELEASE");
#else
Console.WriteLine("DEBUG");
#endif
// load the app settings into configuration
var configuration = new ConfigurationBuilder()
.AddJsonFile("appsettings.json", false, true)
.Build();
applicationSettings = configuration.GetSection("ApplicationSettings").Get<Model.ApplicationSettings>();
// Load the YOLOv8 classification model
var yolo = new YoloPredictor(applicationSettings.ModelPath);
// Load the image from disk
using (var image = Image.Load(applicationSettings.ImagePath))
{
// Run the YOLOv8 classification model on the image
var results = yolo.Classify(image);
// Display the results
foreach (var result in results)
{
Console.WriteLine($"Label: {result.Name.Name}, Confidence: {result.Confidence}");
}
}
}
}
After some minor fixes and shifting the configuration to an appsettings file the application compiled. I tested the implementation with sample “toaster” image from the YoloSharp Github repository
The console application output looked reasonable
I’m pretty confident the input image was a toaster.
Summary
The Copilot prompts to generate code which uses Ultralytics YoloV8 and Compunet YoloSharp and may have produced better code with some “prompt engineering”. Using Visual Studio intellisense the generated code was easy to fix.
The Copilot generated code in this post is not suitable for production
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