/// <summary>
/// Gets information about the image file
/// </summary>
public string GetImageInfo()
{
string info = "";
try
{
MWArray res = new MWStructArray();
res = FEC.getImageInfo(this.imagePath.ToString());
info = res.ToString();
return(info);
}
catch (Exception ex)
{
return(info);
}
}
static void Main(string[] args)
{
MLTestClass theModel = null; /* Stores deployment class instance */
MWStructArray inputs = null; /* Sample input data */
MWArray[] result = null; /* Stores the result */
MWNumericArray prediction = null; /* Ouptut data extracted from result */
MWNumericArray score = null; /* Ouptut data extracted from result */
/* Create the new deployment object */
theModel = new MLTestClass();
/* Create an MWStructArray */
String[] myFieldNames = { "1", "2", "3", "4", "5", "6", "7", "8" };
inputs = new MWStructArray(1, 8, myFieldNames);
/* Populate struct with some sample inputs */
inputs["1", 1] = 1;
inputs["2", 2] = 2;
inputs["3", 3] = 3;
inputs["4", 4] = 4;
inputs["5", 5] = 5;
inputs["6", 6] = 6;
inputs["7", 7] = 7;
inputs["8", 8] = 8;
/* Show some of the sample data */
Console.WriteLine("Inputs: ");
Console.WriteLine(inputs.ToString());
/* Pass it to a MATLAB function */
result = theModel.fnTrainedClassifier(1, inputs);
prediction = (MWNumericArray)result[0];
score = (MWNumericArray)result[1];
/* Show the results */
Console.WriteLine("Prediction: ");
Console.WriteLine(prediction.ToString());
Console.WriteLine("Score: ");
Console.WriteLine(prediction.ToString());
}
