PTI.Microservices.Library.AzureCustomVision 7.0.0

PTI.Microservices.Library.AzureCustomVision

Facilitates the consumption of the APIs in Azure Custom Vision

Examples:

Note: The examples below are passing null for the logger, if you want to use the logger make sure to pass the parameter with a value other than null

Analyze Image

string iterationCode = ITERATION_CODE;
Guid projectId = Guid.Parse(PROJECT_ID);
Guid imageId = Guid.Parse(IMAGE_ID);
AzureCustomVisionService azureCustomVisionService = CreateCustomVisionClient();
var originalImageBytes = new HttpClient()
    .GetByteArrayAsync(IMAGE_URL)
    .Result;
MemoryStream originalImageStream = new MemoryStream(originalImageBytes);
Stream sstr = File.Open(IMAGE_FILE_PATH, FileMode.Open);
var predictionResult = await azureCustomVisionService.DetectImageAsync(sstr,
    projectId, iterationCode);
Assert.IsNotNull(predictionResult);
//cropping seems to be working, but prediction has a higher probability for incorrect section,
//custom vision projects needs more training.
var ingredientsRegions = predictionResult.Predictions.Where(p => p.TagName == "Ingredients")
    .Where(p=>p.Probability > 0.5)
    .OrderByDescending(p => p.Probability).ToArray();
ImagesService imagesService = new ImagesService(null);
for (int i=0; i < ingredientsRegions.Count(); i++)
{
    var ingredientsRegion = ingredientsRegions[i];
    originalImageStream = new MemoryStream(originalImageBytes);
    System.Drawing.Image img = System.Drawing.Image.FromStream(originalImageStream);
    originalImageStream = new MemoryStream(originalImageBytes);
    var croppedImage = imagesService.Crop(originalImageStream,
        (float)ingredientsRegion.BoundingBox.Width * img.Width,
        (float)ingredientsRegion.BoundingBox.Height * img.Height,
        (float)ingredientsRegion.BoundingBox.Left * img.Width,
        (float)ingredientsRegion.BoundingBox.Top * img.Height);
    System.IO.File.WriteAllBytes($@"C:\Temp\PredictedImage_{i}.png", croppedImage);
}

Create Image From Regions

Guid projectId = Guid.Parse(PROJECT_ID);
Guid imageId = Guid.Parse(IMAGE_ID);
AzureCustomVisionService azureCustomVisionService = CreateCustomVisionClient();
var images = await azureCustomVisionService.CreateImageFromRegionsAsync(projectId, imageId, "Ingredients");
Assert.IsTrue(images.Count() > 0);
for (int i = 0; i < images.Count(); i++)
{
    System.IO.File.WriteAllBytes($@"C:\Temp\{i}.png", images[i].ToArray());
}

Query Predictions

Guid projectId = Guid.Parse(PROJECT_ID);
AzureCustomVisionService azureCustomVisionService = CreateCustomVisionClient();
var results = await azureCustomVisionService.QueryPredictionsAsync(projectId);
var imageUrl = results.Results.First().OriginalImageUri;
var imageBytes = new HttpClient().GetByteArrayAsync(imageUrl).Result;
System.IO.File.WriteAllBytes(@"C:\TestResultImage.png", imageBytes);

Basic Import/Upload Flow

AzureCustomVisionService azureCustomVisionService = CreateCustomVisionClient();
var firstDomain = (await azureCustomVisionService.GetDomainsAsync()).First();
string projectName = "Automated Tests Project";
var existentProject = await azureCustomVisionService.GetProjectByNameAsync(projectName);
if (existentProject != null)
    await azureCustomVisionService.DeleteProjectAsync(existentProject.Id);
var project = await azureCustomVisionService.CreateProjectAsync(projectName, "Created from PTI Microservices library Automated Tests",
    firstDomain.Id, AzureCustomVisionService.ClassificationType.Multiclass);
Assert.IsNotNull(project);
System.Collections.Generic.List<Uri> lstUris = new List<Uri>()
{
    new Uri(this.TestComputerVisionImageUri),
    new Uri(this.TestFaceImageUrl)
};
var uploadImagesResult = await azureCustomVisionService.UploadImagesAsync(lstUris,
    project.Id);
List<string> testTags = new List<string>()
{
    "Cat0","Cat1","Cat2"
};
foreach (var singleImage in uploadImagesResult)
{
    var createImageTagsResult = await azureCustomVisionService
        .CreateImageTagsAsync(project.Id, singleImage.Image.Id, testTags, addTagsToSuggestedRegions: true);
    await Task.Delay(TimeSpan.FromSeconds(5));
}
try
{
    var trainingResult = await azureCustomVisionService.TrainProjectAsync(project.Id);
}
catch (Microsoft.Azure.CognitiveServices.Vision.CustomVision.Training.Models.CustomVisionErrorException ex)
{
    //expected exception since we are not sending enough images tagged
}