public async Task Main()
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
TrainingApi trainingApi = new TrainingApi()
{
ApiKey = CustomVisionAPIKey
};
trainingApi.HttpClient.Timeout = TimeSpan.FromMinutes(TimeoutMins);
if (!QuickTest)
{
Console.WriteLine($"Creating Custom Vision Project: {ProjectName}");
var project = trainingApi.CreateProject(ProjectName);
Console.WriteLine($"Scanning subfolders within: {ImagePath}");
List <Tag> allTags = new List <Tag>();
foreach (var folder in Directory.EnumerateDirectories(ImagePath))
{
string folderName = Path.GetFileName(folder);
var tagNames = folderName.Contains(",") ? folderName.Split(',').Select(t => t.Trim()).ToArray() : new string[] { folderName };
// Create tag for each comma separated value in subfolder name
foreach (var tag in tagNames)
{
// Check we've not already created this tag from another subfolder
if (!allTags.Any(t => t.Name.Equals(tag)))
{
Console.WriteLine($"Creating Tag: {tag}");
var imageTag = trainingApi.CreateTag(project.Id, tag);
allTags.Add(imageTag);
}
}
}
foreach (var currentFolder in Directory.EnumerateDirectories(ImagePath))
{
string folderName = Path.GetFileName(currentFolder);
var tagNames = folderName.Contains(",") ? folderName.Split(',').Select(t => t.Trim()).ToArray() : new string[] { folderName };
try
{
// Load the images to be uploaded from disk into memory
Console.WriteLine($"Uploading: {ImagePath}\\{folderName} images...");
var images = Directory.GetFiles(currentFolder).ToList();
var folderTags = allTags.Where(t => tagNames.Contains(t.Name)).Select(t => t.Id).ToList();
var imageFiles = images.Select(img => new ImageFileCreateEntry(Path.GetFileName(img), File.ReadAllBytes(img), folderTags)).ToList();
var imageBatch = new ImageFileCreateBatch(imageFiles);
var summary = await trainingApi.CreateImagesFromFilesAsync(project.Id, new ImageFileCreateBatch(imageFiles));
// List any images that didn't make it
foreach (var imageResult in summary.Images.Where(i => !i.Status.Equals("OK")))
{
Console.WriteLine($"{ImagePath}\\{folderName}\\{imageResult.SourceUrl}: {imageResult.Status}");
}
Console.WriteLine($"Uploaded {summary.Images.Where(i => i.Status.Equals("OK")).Count()}/{images.Count()} images successfully from {ImagePath}\\{folderName}");
}
catch (Exception exp)
{
Console.WriteLine($"Error processing {currentFolder}: {exp.Source}:{exp.Message}");
}
}
try
{
// Train CV model and set iteration to the default
Console.WriteLine($"Training model");
var iteration = trainingApi.TrainProject(project.Id);
while (iteration.Status.Equals("Training"))
{
Thread.Sleep(1000);
iteration = trainingApi.GetIteration(project.Id, iteration.Id);
Console.WriteLine($"Model status: {iteration.Status}");
}
if (iteration.Status.Equals("Completed"))
{
iteration.IsDefault = true;
trainingApi.UpdateIteration(project.Id, iteration.Id, iteration);
Console.WriteLine($"Iteration: {iteration.Id} set as default");
}
else
{
Console.WriteLine($"Iteration status: {iteration.Status}");
}
}
catch (Exception exp)
{
Console.WriteLine($"Error training model (check you have at least 5 images per tag and 2 tags)");
Console.WriteLine($"Error {exp.Source}: {exp.Message}");
}
}
else
{
// Quick test existing (trained) model
Console.WriteLine($"Custom Vision Quick test: {ProjectName} with image {ImagePath}");
// Retrieve CV project
var projects = trainingApi.GetProjects();
var project = projects.Where(p => p.Name.Equals(ProjectName)).FirstOrDefault();
if (project == null)
{
Console.WriteLine($"Can't find Custom Vision Project: {ProjectName}");
return;
}
// Read test image
if (!File.Exists(ImagePath))
{
Console.WriteLine($"Can't find image: {ImagePath}");
return;
}
var image = new MemoryStream(File.ReadAllBytes(ImagePath));
// Get the default iteration to test against and check results
var iterations = trainingApi.GetIterations(project.Id);
var defaultIteration = iterations.Where(i => i.IsDefault == true).FirstOrDefault();
if (defaultIteration == null)
{
Console.WriteLine($"No default iteration has been set");
return;
}
var result = trainingApi.QuickTestImage(project.Id, image, defaultIteration.Id);
foreach (var prediction in result.Predictions)
{
Console.WriteLine($"Tag: {prediction.Tag} Probability: {prediction.Probability}");
}
}
// fin
stopwatch.Stop();
Console.WriteLine($"Done.");
Console.WriteLine($"Total time: {stopwatch.Elapsed}");
}