static void Main()
{
string assetsPath = Path.Combine(new FileInfo(typeof(Program).Assembly.Location).Directory.FullName, "assets");
var trainingImages = Path.GetFullPath("../../../assets/inputs/train"); // "C:\\repo\\Image-classification-transfer-learning\\grocery\\train2\\";
var testingImages = Path.GetFullPath("../../../../ImageClassification.Test/assets/test/thor");
var featurizerModel = Path.Combine(assetsPath, "inputs", "inception", "tensorflow_inception_graph.pb");
string trainedModelLocation = Path.GetFullPath("../../../imageClassifier.zip");
//Train model
try
{
var modelBuilder = new ModelBuilder(trainingImages, featurizerModel, trainedModelLocation);
modelBuilder.Train();
}
catch (Exception ex)
{
ConsoleHelpers.ConsoleWriteException(ex.Message);
}
//Test model
ConsoleHelpers.ConsoleWriteHeader("Test model with few sample images");
try
{
ConsoleHelpers.ConsoleWriteHeader("Load saved model");
TrainedModel model = new TrainedModel(trainedModelLocation);
ImagePrediction prediction = new ImagePrediction();
List <PredictionResult> results = new List <PredictionResult>();
List <ImageData> imageList = DataHelper.ReadFromFolder(testingImages);
foreach (ImageData image in imageList)
{
prediction = model.predictor.Predict(image);
PredictionResult result = new PredictionResult(Path.GetFileName(image.ImagePath).ToString(), prediction.PredictedLabelValue, prediction.Score.Max());
results.Add(result);
}
var output = JsonConvert.SerializeObject(results, Formatting.Indented);
Console.WriteLine(output);
}
catch (Exception ex)
{
ConsoleHelpers.ConsoleWriteException(ex.Message);
}
}
public ImageWithLabelPrediction(ImagePrediction pred, string label)
{
Label = label;
Score = pred.Score;
PredictedLabelValue = pred.PredictedLabelValue;
}
