Hey, there! In this tutorial, we'll learn how to call an Azure Custom Vision object recognition model from a .NET application.
As an example, we will recognize these objects in an image: hats, faces, guitars, and bottles.
Note: In this tutorial we can see the process to create the Custom Vision model: Object detection with Azure Custom Vision.
Source code of this example: GitHub - Azure Object Recognition.
Custom Vision API
As a first point, in our .NET project we must install the following NuGet packages:
Microsoft.Azure.CognitiveServices.Vision.CustomVision.TrainingMicrosoft.Azure.CognitiveServices.Vision.CustomVision.Prediction
These packages will allow us to call our Custom Vision model using their access and information methods.
CustomVision.cs class
With the NuGet packages installed we can create a new class, and here as a first instance we will need to establish the variables that will allow us to refer to our specific Azure Custom Vision project:
private string Key = "YOUR_CUSTOMVISION_KEY";
private string Endpoint = "YOUR_ENDPOINT";
private string ProjectID = "YOUR_PROJECT_ID";
private string publishedModelName = "YOUR_MODEL_NAME";
private double minProbability = 0.75;
These values can be found in the general settings of your project:
With these attributes we can generate the respective endpoint for authentication of our project, and finally define a DetectObjects method, sending as a parameter the path of the image to be analyzed, and receiving as a response the JSON with the detected objects.
This would be the source code of the entire C# class:
using Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction;
using Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.Models;
using Microsoft.Azure.CognitiveServices.Vision.CustomVision.Training;
using Microsoft.Azure.CognitiveServices.Vision.CustomVision.Training.Models;
using ApiKeyServiceClientCredentials = Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.ApiKeyServiceClientCredentials;
namespace CognitiveServices;
public class CustomVision
{
private string Key = "YOUR_CUSTOMVISION_KEY";
private string Endpoint = "YOUR_ENDPOINT";
private string ProjectID = "YOUR_PROJECT_ID";
private string publishedModelName = "YOUR_MODEL_NAME";
private double minProbability = 0.75;
private CustomVisionTrainingClient trainingApi;
private CustomVisionPredictionClient predictionApi;
private Project project;
public CustomVision()
{
trainingApi = AuthenticateTraining(Endpoint, Key);
predictionApi = AuthenticatePrediction(Endpoint, Key);
project = trainingApi.GetProject(new Guid(ProjectID));
}
private CustomVisionTrainingClient AuthenticateTraining(string endpoint, string trainingKey)
{
return new CustomVisionTrainingClient(new Microsoft.Azure.CognitiveServices.Vision.CustomVision.Training.ApiKeyServiceClientCredentials(trainingKey))
{
Endpoint = endpoint
};
}
private CustomVisionPredictionClient AuthenticatePrediction(string endpoint, string predictionKey)
{
return new CustomVisionPredictionClient(new ApiKeyServiceClientCredentials(predictionKey))
{
Endpoint = endpoint
};
}
public List<PredictionModel> DetectObjects(string imageFile)
{
using (var stream = File.Open(imageFile, FileMode.Open, FileAccess.Read, FileShare.ReadWrite))
{
var result = predictionApi.DetectImage(project.Id, publishedModelName, stream);
return result.Predictions.Where(x => x.Probability > minProbability).ToList();
}
}
}
Program.cs / Call example
In a new class we can define a collection of type List<PredictionModel> to store the recognized objects of a particular image, after calling the previously defined DetectObjects method.
This would be the source code of this new class:
using CognitiveServices;
var customVision = new CustomVision();
var imagePath = "image.jpg";
var objects = customVision.DetectObjects(imagePath);
Console.WriteLine("Object - Probability - Position(X,Y)");
foreach (var obj in objects)
{
Console.WriteLine("{0}: {1} - ({2},{3})",
obj.TagName,
obj.Probability,
obj.BoundingBox.Left,
obj.BoundingBox.Top);
}
And this is the result in the console for the previous example:
Thanks for reading!
If you have any questions or ideas in mind, it will be a pleasure to be able to be in communication with you, and together exchange knowledge with each other.
See you on Twitter / esDanielGomez.com.
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