public ActionResult PredictMnist(string imageRaw)
{
try
{
var image = ImageFunctions.Base64ToImage(imageRaw);
image = ImageFunctions.Resize(image, 28, 28);
var directory = AppDomain.CurrentDomain.BaseDirectory;
var path = Path.Combine(directory, "CNNModel");
string outputModelPath = Path.Combine(path, "model.mod");
var label = CNNManager.TestItems(outputModelPath, image);
return(new JsonResult()
{
Data = new { Status = "Success", Message = "Complete", Label = label },
JsonRequestBehavior = JsonRequestBehavior.DenyGet
});
}
catch (Exception ex)
{
return(new JsonResult()
{
Data = new { Status = "Failure", Message = "Error making prediction." },
JsonRequestBehavior = JsonRequestBehavior.DenyGet
});
}
}
public static void RunCNN()
{
//Get images
var directory = Directory.GetParent(Directory.GetCurrentDirectory()).Parent.FullName;
var path = Path.Combine(directory, "training-set");
var virtualFolder = new Uri(path).LocalPath;
string outputModelPath = Path.Combine(path, "model.mod");
CNNManager.TrainCNN(path, outputModelPath);
}
