public override void Test()
{
var wizard = new ModelWizard();
var task = wizard.AddImageClassificationTask <TransferLearning>(new TaskOptions
{
DataDir = @"image_classification_v1\flower_photos",
ModelPath = @"image_classification_v1\saved_model.pb"
});
var result = task.Test();
accuracy = result.Accuracy;
}
/// <summary>
/// Prediction
/// labels mapping, it's from output_lables.txt
/// 0 - daisy
/// 1 - dandelion
/// 2 - roses
/// 3 - sunflowers
/// 4 - tulips
/// </summary>
public override void Predict()
{
// predict image
var wizard = new ModelWizard();
var task = wizard.AddImageClassificationTask <TransferLearning>(new TaskOptions
{
ModelPath = @"image_classification_v1\saved_model.pb"
});
var imgPath = Path.Join("image_classification_v1", "flower_photos", "daisy", "5547758_eea9edfd54_n.jpg");
var input = ImageUtil.ReadImageFromFile(imgPath);
var result = task.Predict(input);
Debug.Assert(result.Label == "daisy");
}
public override void Train()
{
// get a set of images to teach the network about the new classes
string fileName = "flower_photos.tgz";
string dataDir = "image_classification_v1";
string url = $"http://download.tensorflow.org/example_images/{fileName}";
Web.Download(url, dataDir, fileName);
Compress.ExtractTGZ(Path.Join(dataDir, fileName), dataDir);
// using wizard to train model
var wizard = new ModelWizard();
var task = wizard.AddImageClassificationTask <TransferLearning>(new TaskOptions
{
DataDir = @"image_classification_v1\flower_photos",
});
task.Train(new TrainingOptions());
}
