private async void UpdateResults(ImageAnalyzer img)
{
this.searchErrorTextBlock.Visibility = Visibility.Collapsed;
Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.Models.ImagePrediction result = null;
var currentProjectViewModel = (ProjectViewModel)this.projectsComboBox.SelectedValue;
var currentProject = ((ProjectViewModel)this.projectsComboBox.SelectedValue).Model;
var trainingApi = this.userProvidedTrainingApi;
var predictionApi = this.userProvidedPredictionApi;
try
{
var iteractions = await trainingApi.GetIterationsAsync(currentProject.Id);
var latestTrainedIteraction = iteractions.Where(i => i.Status == "Completed").OrderByDescending(i => i.TrainedAt.Value).FirstOrDefault();
if (latestTrainedIteraction == null)
{
throw new Exception("This project doesn't have any trained models yet. Please train it, or wait until training completes if one is in progress.");
}
if (img.ImageUrl != null)
{
result = await CustomVisionServiceHelper.PredictImageUrlWithRetryAsync(predictionApi, currentProject.Id, new Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.Models.ImageUrl(img.ImageUrl), latestTrainedIteraction.Id);
}
else
{
result = await CustomVisionServiceHelper.PredictImageWithRetryAsync(predictionApi, currentProject.Id, img.GetImageStreamCallback, latestTrainedIteraction.Id);
}
}
catch (Exception ex)
{
await Util.GenericApiCallExceptionHandler(ex, "Error");
}
this.progressRing.IsActive = false;
this.resultsDetails.Visibility = Visibility.Visible;
var matches = result?.Predictions?.Where(r => Math.Round(r.Probability * 100) > 0);
if (matches == null || !matches.Any())
{
this.searchErrorTextBlock.Visibility = Visibility.Visible;
}
else
{
if (!currentProjectViewModel.IsObjectDetection)
{
this.resultsGridView.ItemsSource = matches.Select(t => new { Tag = t.TagName, Probability = string.Format("{0}%", Math.Round(t.Probability * 100)) });
}
else
{
this.resultsDetails.Visibility = Visibility.Collapsed;
this.currentDetectedObjects = matches.Where(m => m.Probability >= 0.6);
ShowObjectDetectionBoxes(this.currentDetectedObjects);
}
}
if (result?.Predictions != null && !currentProjectViewModel.IsObjectDetection)
{
this.activeLearningButton.Opacity = 1;
this.PredictionDataForRetraining.Clear();
this.PredictionDataForRetraining.AddRange(result.Predictions.Select(
t => new ActiveLearningTagViewModel
{
PredictionResultId = result.Id,
TagId = t.TagId,
TagName = t.TagName,
HasTag = Math.Round(t.Probability * 100) > 0
}));
}
else
{
this.activeLearningButton.Opacity = 0;
}
}
public IList <Result> predictingImages(String imgUrl)
{
IList <Result> predictionResult = new List <Result>();
CustomVisionPredictionClient endpoint = new CustomVisionPredictionClient()
{
ApiKey = predictionKey,
Endpoint = SouthCentralUsEndpoint
};
projectID = new Guid(ConfigurationManager.AppSettings["CustomVisionProjectID"]);
Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.Models.ImageUrl testImage = new Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.Models.ImageUrl(imgUrl);
Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction.Models.ImagePrediction result1 = endpoint.ClassifyImageUrl(projectID, "Veg Classifier", testImage);
foreach (var output in result1.Predictions)
{
Result finalresult = new Result();
finalresult.probability = output.Probability * 100;
finalresult.tagName = output.TagName;
predictionResult.Add(finalresult);
}
return(predictionResult);
}