public async void ImageClassifierWorkerPoolSmokeTest()
{
var configuration = new ImageClassifierConfiguration
{
ClassifierType = "MNISTClassifier",
ImageHeight = 28, ImageWidth = 28,
Labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" },
PathToModel = "TestData/traced_model.pt"
};
var factory = new ImageClassifierFactory();
var pool = new ImageClassifierWorkerPool(factory, configuration, 5);
using var source = new CancellationTokenSource();
await pool.StartWorkers(source.Token);
var image = Image.FromFile("TestData/seven.png");
var results = new List <Task <string> >();
for (var i = 0; i < 100; i++)
{
results.Add(pool.Classify(image));
}
var labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" };
foreach (var taskResult in results)
{
Assert.Contains(await taskResult, labels);
}
source.Cancel();
await pool.StopWorkers();
}
public void ModelNotLoadedExceptionThrownTest()
{
var configuration = new ImageClassifierConfiguration
{
ImageHeight = 28, ImageWidth = 28,
Labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" },
PathToModel = "TestData/not_exist.pt"
};
var classifier = new MnistImageClassifier(configuration);
Assert.Throws <ModelNotLoadedException>(() => classifier.LoadModel());
}
public void UnknowClassifierTypeExceptionThrownTest()
{
var configuration = new ImageClassifierConfiguration
{
ClassifierType = "Unknown",
ImageHeight = 28, ImageWidth = 28,
Labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" },
PathToModel = "TestData/traced_model.pt"
};
var factory = new ImageClassifierFactory();
Assert.Throws <UnknownClassifierTypeException>(() => factory.GetClassifier(configuration));
}
public void SmokeTestClassifierFactory()
{
var configuration = new ImageClassifierConfiguration
{
ClassifierType = "MNISTClassifier",
ImageHeight = 28, ImageWidth = 28,
Labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" },
PathToModel = "TestData/traced_model.pt"
};
var factory = new ImageClassifierFactory();
var classifier = factory.GetClassifier(configuration);
Assert.IsType <MnistImageClassifier>(classifier);
}
public void RecognizeNumberTest()
{
var configuration = new ImageClassifierConfiguration
{
ImageHeight = 28, ImageWidth = 28,
Labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" },
PathToModel = "TestData/traced_model.pt"
};
var classifier = new MnistImageClassifier(configuration);
classifier.LoadModel();
var image = Image.FromFile("TestData/seven.png");
var label = classifier.ClassifyImage(image);
Assert.Contains(label, configuration.Labels);
}
public async Task SmokeTestWorkers()
{
using var cancellationTokenSource = new CancellationTokenSource();
var workers = new List <IImageClassifierWorker>();
for (var i = 0; i < 5; ++i)
{
var configuration = new ImageClassifierConfiguration
{
ImageHeight = 28, ImageWidth = 28,
Labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" },
PathToModel = "TestData/traced_model.pt"
};
var classifier = new MnistImageClassifier(configuration);
var worker = new ImageClassifierWorker(classifier);
await worker.StartWorker(cancellationTokenSource.Token);
workers.Add(worker);
}
var image = Image.FromFile("TestData/seven.png");
var results = new List <Task <string> >();
foreach (var worker in workers)
{
for (var i = 0; i < 10; i++)
{
results.Add(worker.Classify(image));
}
}
var labels = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" };
foreach (var taskResult in results)
{
Assert.Contains(await taskResult, labels);
}
cancellationTokenSource.Cancel();
foreach (var worker in workers)
{
worker.StopWorker();
}
}