private static void PrintDigit(DigitInputData digit)
{
Console.WriteLine();
for (var i = 0; i < 28; i++)
{
for (var j = 0; j < 28; j++)
{
Console.Write(digit.PixelValues[i * 28 + j].ToString().PadLeft(4, ' '));
}
Console.WriteLine();
}
}
public static int PredictDigit2(DigitInputData digit)
{
PrintDigit(digit);
var mlContext = new MLContext();
var trainedModel = mlContext.Model.Load(ModelPath, out var modelInputSchema);
// Create prediction engine related to the loaded trained model
var predEngine = mlContext.Model.CreatePredictionEngine <DigitInputData2, DigitOutputData>(trainedModel);
var mapped = MapToAlternateInput(GetZero());
var prediction = predEngine.Predict(mapped);
var predictedDigit = 0;
var maxProbability = (float)0;
for (var i = 0; i < prediction.Score.Length; i++)
{
if (!(prediction.Score[i] > maxProbability))
{
continue;
}
maxProbability = prediction.Score[i];
predictedDigit = i;
}
Console.WriteLine($"Actual: {digit.Number} Predicted probability:");
Console.WriteLine($" zero: {prediction.Score[0]:0.####}");
Console.WriteLine($" one : {prediction.Score[1]:0.####}");
Console.WriteLine($" two: {prediction.Score[2]:0.####}");
Console.WriteLine($" three: {prediction.Score[3]:0.####}");
Console.WriteLine($" four: {prediction.Score[4]:0.####}");
Console.WriteLine($" five: {prediction.Score[5]:0.####}");
Console.WriteLine($" six: {prediction.Score[6]:0.####}");
Console.WriteLine($" seven: {prediction.Score[7]:0.####}");
Console.WriteLine($" eight: {prediction.Score[8]:0.####}");
Console.WriteLine($" nine: {prediction.Score[9]:0.####}");
Console.WriteLine($"Prediction: {predictedDigit}");
Console.WriteLine();
return(predictedDigit);
}
public static DigitInputData2 MapToAlternateInput(DigitInputData data)
{
var array = new float[49];
for (var i = 0; i < 28; i++)
{
for (var j = 0; j < 28; j++)
{
if (data.PixelValues[i * 28 + j] > 0)
{
var iCoord = i / 4;
var jCoord = j / 4;
array[iCoord * 7 + jCoord]++;
}
}
}
return(new DigitInputData2
{
PixelValues = array,
Number = data.Number
});
}
