private async void btnTrain_Click(object sender, RoutedEventArgs e)
{
//btnTrain.IsEnabled = false;
//var someTask = Task.Factory.StartNew(() => Train());
//await someTask;
//btnTrain.IsEnabled = true;
// Now there are images with tags start training the project
Log("Training");
var iteration = await trainingApi.TrainProjectAsync(project.Id);
// The returned iteration will be in progress, and can be queried periodically to see when it has completed
while (iteration.Status == "Training")
{
Thread.Sleep(1000);
// Re-query the iteration to get it's updated status
iteration = trainingApi.GetIteration(project.Id, iteration.Id);
}
// The iteration is now trained. Make it the default project endpoint
iteration.IsDefault = true;
trainingApi.UpdateIteration(project.Id, iteration.Id, iteration);
Log("Done Training!");
}
private static async Task TrainProject(TrainingApi trainingApi, Guid projectId)
{
var iteration = await trainingApi.TrainProjectAsync(projectId);
while (iteration.Status == "Training")
{
Console.Clear();
Console.WriteLine("Training in progress...");
Thread.Sleep(1000);
iteration = await trainingApi.GetIterationAsync(projectId, iteration.Id);
}
iteration.IsDefault = true;
trainingApi.UpdateIteration(projectId, iteration.Id, iteration);
Console.WriteLine();
Console.WriteLine("Project successfully trained... Press any key to continue");
Console.ReadLine();
}
private async Task TrainProjectsAsync()
{
this.progressControl.IsActive = true;
bool trainingSucceeded = true;
try
{
Iteration iterationModel = await trainingApi.TrainProjectAsync(this.CurrentProject.Id);
while (true)
{
iterationModel = await trainingApi.GetIterationAsync(this.CurrentProject.Id, iterationModel.Id);
if (iterationModel.Status != "Training")
{
if (iterationModel.Status == "Failed")
{
trainingSucceeded = false;
}
break;
}
await Task.Delay(500);
}
this.needsTraining = false;
}
catch (Exception ex)
{
await Util.GenericApiCallExceptionHandler(ex, "Failure requesting training");
}
this.progressControl.IsActive = false;
if (!trainingSucceeded)
{
await new MessageDialog("Training failed.").ShowAsync();
}
}
private async void TriggerActiveLearningButtonClicked(object sender, RoutedEventArgs e)
{
this.activeLearningFlyout.Hide();
var currentProject = ((ProjectViewModel)this.projectsComboBox.SelectedValue).Model;
try
{
var tags = this.PredictionDataForRetraining.Where(d => d.HasTag).Select(d => d.TagId).ToList();
if (tags.Any())
{
var test = await this.userProvidedTrainingApi.CreateImagesFromPredictionsAsync(currentProject.Id,
new ImageIdCreateBatch
{
TagIds = tags,
Images = new List <ImageIdCreateEntry>(new ImageIdCreateEntry[] { new ImageIdCreateEntry(this.PredictionDataForRetraining.First().PredictionResultId) })
});
}
else
{
await new MessageDialog("You need to select at least one Tag in order to save and re-train.").ShowAsync();
return;
}
}
catch (Exception ex)
{
await Util.GenericApiCallExceptionHandler(ex, "Failure adding image to the training set");
return;
}
this.progressRing.IsActive = true;
bool trainingSucceeded = true;
try
{
Iteration iterationModel = await userProvidedTrainingApi.TrainProjectAsync(currentProject.Id);
while (true)
{
iterationModel = await userProvidedTrainingApi.GetIterationAsync(currentProject.Id, iterationModel.Id);
if (iterationModel.Status != "Training")
{
if (iterationModel.Status == "Failed")
{
trainingSucceeded = false;
}
break;
}
await Task.Delay(500);
}
}
catch (Exception ex)
{
await Util.GenericApiCallExceptionHandler(ex, "The image was added to the training set, but re-training failed. You can try re-training later via the Custom Vision Setup page.");
}
if (!trainingSucceeded)
{
await new MessageDialog("The image was added to the training set, but re-training failed. You can try re-training later via the Custom Vision Setup page.").ShowAsync();
}
this.progressRing.IsActive = false;
}
public static async Task TrainAsync(ParsingOptions options)
{
// Create the Api, passing in the training key
var trainingApi = new TrainingApi {
ApiKey = options.TrainingKey
};
if (options.Delete)
{
try
{
await DeleteImagesAndTagsAsync(options, trainingApi);
Console.WriteLine("Images and tags successfully deleted.");
}
catch
{
}
return;
}
var fullFolder = Path.GetFullPath(options.Folder);
if (!Directory.Exists(fullFolder))
{
Console.WriteLine($"Error: folder \"{fullFolder}\" does not exist.");
Console.WriteLine(string.Empty);
return;
}
try
{
await DeleteImagesAndTagsAsync(options, trainingApi);
// Creates the string for resized images.
string resizeString = null;
if (options.Width.GetValueOrDefault() > 0)
{
resizeString += $"width={options.Width}&";
}
if (options.Height.GetValueOrDefault() > 0)
{
resizeString += $"height={options.Height}&";
}
if (!string.IsNullOrWhiteSpace(resizeString))
{
resizeString += "crop=auto&scale=both";
}
foreach (var dir in Directory.EnumerateDirectories(fullFolder).Where(f => !Path.GetFileName(f).StartsWith("!")))
{
var tagName = Path.GetFileName(dir).ToLower();
Console.WriteLine($"\nCreating tag '{tagName}'...");
var tag = await trainingApi.CreateTagAsync(options.ProjectId, tagName);
var images = Directory.EnumerateFiles(dir, "*.*", SearchOption.AllDirectories)
.Where(s => s.EndsWith(".jpg", StringComparison.InvariantCultureIgnoreCase) ||
s.EndsWith(".jpeg", StringComparison.InvariantCultureIgnoreCase) ||
s.EndsWith(".png", StringComparison.InvariantCultureIgnoreCase) ||
s.EndsWith(".bmp", StringComparison.InvariantCultureIgnoreCase));
foreach (var image in images)
{
var imageName = Path.GetFileName(image);
Console.WriteLine($"Uploading image {imageName}...");
// Resizes the image before sending it to the service.
using (var input = new MemoryStream(File.ReadAllBytes(image)))
{
if (!string.IsNullOrWhiteSpace(resizeString))
{
using (var output = new MemoryStream())
{
ImageBuilder.Current.Build(input, output, new ResizeSettings(resizeString));
output.Position = 0;
await trainingApi.CreateImagesFromDataAsync(options.ProjectId, output, new List <string>() { tag.Id.ToString() });
}
}
else
{
await trainingApi.CreateImagesFromDataAsync(options.ProjectId, input, new List <string>() { tag.Id.ToString() });
}
}
}
}
// Now there are images with tags start training the project
Console.WriteLine("\nTraining...");
var iteration = await trainingApi.TrainProjectAsync(options.ProjectId);
// The returned iteration will be in progress, and can be queried periodically to see when it has completed
while (iteration.Status == "Training")
{
await Task.Delay(1000);
// Re-query the iteration to get it's updated status
iteration = trainingApi.GetIteration(options.ProjectId, iteration.Id);
}
// The iteration is now trained. Make it the default project endpoint
iteration.IsDefault = true;
trainingApi.UpdateIteration(options.ProjectId, iteration.Id, iteration);
Console.WriteLine("Training completed.\n");
}
catch (Exception ex)
{
Console.WriteLine($"\nUnexpected error: {ex.GetBaseException()?.Message}.\n");
}
}
public static async Task TrainAsync(ParsingOptions options)
{
// Create the Api, passing in the training key
var trainingApi = new TrainingApi {
ApiKey = options.TrainingKey
};
CognitiveServiceTrainerStorage storageImages = new CognitiveServiceTrainerStorage();
if (options.Delete)
{
try
{
await DeleteImagesAndTagsAsync(options, trainingApi);
storageImages.DeleteDB();
Console.WriteLine("Images and tags successfully deleted.");
}
catch
{
}
if (string.IsNullOrEmpty(options.Folder))
{
return;
}
}
var fullFolder = Path.GetFullPath(options.Folder);
if (!Directory.Exists(fullFolder))
{
Console.WriteLine($"Error: folder \"{fullFolder}\" does not exist.");
Console.WriteLine(string.Empty);
return;
}
try
{
//await DeleteImagesAndTagsAsync(options, trainingApi);
foreach (var dir in Directory.EnumerateDirectories(fullFolder).Where(f => !Path.GetFileName(f).StartsWith("!")))
{
var tagName = Path.GetFileName(dir).ToLower();
Console.WriteLine($"\nCheck latest images uploaded '{tagName}'...");
IList <Microsoft.Cognitive.CustomVision.Training.Models.Image> imagesAlreadyExists = new List <Microsoft.Cognitive.CustomVision.Training.Models.Image>();
IList <Microsoft.Cognitive.CustomVision.Training.Models.Image> imagesAlreadyExistsTmp = new List <Microsoft.Cognitive.CustomVision.Training.Models.Image>();
int skip = 0;
while ((imagesAlreadyExistsTmp = await trainingApi.GetTaggedImagesAsync(options.ProjectId, tagIds: new[] { tagName }, take: 50, skip: skip)).Any())
{
skip += 50;
foreach (var item in imagesAlreadyExistsTmp)
{
imagesAlreadyExists.Add(item);
}
}
Console.WriteLine($"\nCreating tag '{tagName}'...");
var tagExist = storageImages.FindTag(tagName, options.ProjectId);
Tag tag = null;
if (tagExist == null)
{
tag = await trainingApi.CreateTagAsync(options.ProjectId, tagName);
storageImages.InsertTag(new Storage.Collections.StorageTag {
IdCustomVision = tag.Id, TagName = tag.Name, ProjectId = options.ProjectId
});
}
else
{
if (trainingApi.GetTag(tagExist.ProjectId, tagExist.IdCustomVision) == null)
{
await trainingApi.DeleteTagAsync(options.ProjectId, tagExist.IdCustomVision);
tag = await trainingApi.CreateTagAsync(options.ProjectId, tagName);
storageImages.InsertTag(new Storage.Collections.StorageTag {
IdCustomVision = tag.Id, TagName = tag.Name, ProjectId = options.ProjectId
});
}
else
{
tag = new Tag(tagExist.IdCustomVision, tagName);
}
}
var images = Directory.EnumerateFiles(dir, "*.*", SearchOption.AllDirectories)
.Where(s => s.EndsWith(".jpg", StringComparison.InvariantCultureIgnoreCase) ||
s.EndsWith(".jpeg", StringComparison.InvariantCultureIgnoreCase) ||
s.EndsWith(".png", StringComparison.InvariantCultureIgnoreCase) ||
s.EndsWith(".bmp", StringComparison.InvariantCultureIgnoreCase)).ToList();
List <ImageDto> tempImages = new List <ImageDto>();
for (int i = 0; i < images.Count; i++)
{
Stream imageToUpload = null;
string image = images.ElementAt(i);
var imageName = Path.GetFileName(image);
var storageImage = storageImages.FindImage(image, options.ProjectId);
if (storageImage == null || !imagesAlreadyExists.Any(x => x.Id == storageImage.IdCustomVision))
{
// Resizes the image before sending it to the service.
using (var input = new MemoryStream(File.ReadAllBytes(image)))
{
if (options.Width.GetValueOrDefault() > 0 || options.Height.GetValueOrDefault() > 0)
{
imageToUpload = await ResizeImageAsync(input, options.Width.GetValueOrDefault(), options.Height.GetValueOrDefault());
}
else
{
imageToUpload = input;
}
tempImages.Add(new ImageDto
{
FullName = image,
FileName = imageName,
Content = imageToUpload.ToByteArray(),
Tag = tag
});
imageToUpload.Dispose();
}
}
else
{
Console.WriteLine($"Image already exist {imageName}...");
}
//Persist batch images
if (tempImages.Count % 32 == 0 && tempImages.Any() || (i == images.Count - 1))
{
await UploadImagesAsync(tempImages);
tempImages.Clear();
tempImages.Capacity = 0;
}
}
}
// Now there are images with tags start training the project
Console.WriteLine("\nTraining...");
var iteration = await trainingApi.TrainProjectAsync(options.ProjectId);
// The returned iteration will be in progress, and can be queried periodically to see when it has completed
while (iteration.Status == "Training")
{
await Task.Delay(1000);
// Re-query the iteration to get it's updated status
iteration = trainingApi.GetIteration(options.ProjectId, iteration.Id);
}
// The iteration is now trained. Make it the default project endpoint
iteration.IsDefault = true;
trainingApi.UpdateIteration(options.ProjectId, iteration.Id, iteration);
Console.WriteLine("Training completed.\n");
}
catch (Exception ex)
{
Console.WriteLine($"\nUnexpected error: {ex.GetBaseException()?.Message}.\n");
}
async Task UploadImagesAsync(List <ImageDto> images)
{
ImageFileCreateBatch imageFileCreateBatch = new ImageFileCreateBatch();
imageFileCreateBatch.Images = new List <ImageFileCreateEntry>();
foreach (var img in images)
{
imageFileCreateBatch.Images.Add(new ImageFileCreateEntry
{
Name = img.FullName,
TagIds = new [] { img.Tag.Id },
Contents = img.Content
});
Console.WriteLine($"Uploading image {img.FileName}...");
}
await Policy
.Handle <Exception>()
.WaitAndRetryAsync(retries)
.ExecuteAsync(async() =>
{
ImageCreateSummary reponseCognitiveService = await trainingApi.CreateImagesFromFilesAsync(options.ProjectId, imageFileCreateBatch);
if (reponseCognitiveService.Images != null)
{
for (int i = 0; i < reponseCognitiveService.Images.Count; i++)
{
var img = reponseCognitiveService.Images.ElementAt(i);
// https://docs.microsoft.com/en-us/rest/api/cognitiveservices/customvisiontraining/createimagesfrompredictions/createimagesfrompredictions
if ((img.Status == "OK" || img.Status == "OKDuplicate") && img.Image != null)
{
var uploadedImage = img.Image;
var tagsToStore = uploadedImage.Tags?
.Select(x => new Storage.Collections.StorageImageTag()
{
Created = x.Created,
TagId = x.TagId
}).ToList();
storageImages.InsertImage(new Storage.Collections.StorageImage()
{
ProjectId = options.ProjectId,
FullFileName = imageFileCreateBatch.Images.ElementAt(i).Name,
IdCustomVision = uploadedImage.Id,
ImageUri = uploadedImage.ImageUri,
Created = uploadedImage.Created,
Height = uploadedImage.Height,
Tags = tagsToStore,
ThumbnailUri = uploadedImage.ThumbnailUri,
Width = uploadedImage.Width
});
}
else
{
Console.WriteLine($"API bad response: {img.Status }");
throw new InvalidOperationException($"API bad response: {img.Status }");
}
}
}
});
await Task.Delay(500);
}
}
private static async Task <bool> MainAsync(string[] args)
{
try
{
trainingApi.ApiKey = CustomVisionTrainingApiKey;
// Create project
var projects = await trainingApi.GetProjectsAsync();
var project = projects.Where(x => x.Name == projectName).FirstOrDefault();
if (project == null)
{
Console.WriteLine($"\nCreating project '{projectName}'");
project = await trainingApi.CreateProjectAsync(projectName);
}
// Retrieve all tags
var tagsList = await trainingApi.GetTagsAsync(project.Id);
#region Create Object tag
var objectTag = tagsList.Tags.Where(x => x.Name == objectTagName).FirstOrDefault();
if (objectTag == null)
{
Console.WriteLine($"\nCreating tag '{objectTagName}'");
objectTag = await trainingApi.CreateTagAsync(project.Id, objectTagName);
}
// add images to tag
Console.WriteLine($"\nAdding images to tag '{objectTagName}'");
List <ImageFileCreateEntry> imageFiles = (Directory.GetFiles(objectTrainImagesPath)).Select(img => new ImageFileCreateEntry(Path.GetFileName(img), File.ReadAllBytes(img))).ToList();
await trainingApi.CreateImagesFromFilesAsync(project.Id, new ImageFileCreateBatch(imageFiles, new List <Guid>()
{
objectTag.Id
}));
#endregion
#region Create Ocean tag
var oceanTag = tagsList.Tags.Where(x => x.Name == oceanTagName).FirstOrDefault();
if (oceanTag == null)
{
Console.WriteLine($"\nCreating tag '{oceanTagName}'");
oceanTag = await trainingApi.CreateTagAsync(project.Id, oceanTagName);
}
// add images
Console.WriteLine($"\nAdding images to tag '{oceanTagName}'");
imageFiles = (Directory.GetFiles(noObjectTrainImagesPath)).Select(img => new ImageFileCreateEntry(Path.GetFileName(img), File.ReadAllBytes(img))).ToList();
await trainingApi.CreateImagesFromFilesAsync(project.Id, new ImageFileCreateBatch(imageFiles, new List <Guid>()
{
oceanTag.Id
}));
#endregion
#region Train the classifier
Console.WriteLine("\nTraining");
var iteration = await trainingApi.TrainProjectAsync(project.Id);
do
{
Thread.Sleep(1000);
iteration = await trainingApi.GetIterationAsync(project.Id, iteration.Id);
}while (string.Equals("training", iteration.Status, StringComparison.OrdinalIgnoreCase));
if (!string.Equals(iteration.Status, "completed", StringComparison.OrdinalIgnoreCase))
{
throw new Exception($"An error occurred training the classifier. Iteration status is {iteration.Status}");
}
iteration.IsDefault = true;
await trainingApi.UpdateIterationAsync(project.Id, iteration.Id, iteration);
#endregion
Console.WriteLine(
$@"\n
Your custom vision project ID is {project.Id.ToString()}.
Copy this Guid and add it to your application settings under the name 'CustomVisionProjectId'
"
);
Console.WriteLine("\nFinished. Press Enter to exit");
Console.Read();
return(true);
}
catch (Exception e)
{
Console.Write(e);
Console.WriteLine("\nPress Enter to exit");
Console.Read();
return(false);
}
}