public static void Pixbuf(Pixbuf Digit, ManagedCNN cnn, ref int digit, ref double[] Probability)
{
// Bitmap Data is transposed
var Transposed = new ManagedArray(28, 28, 1);
var TestDigit = new ManagedArray(28, 28, 1);
var ScaledDigit = Digit.ScaleSimple(28, 28, InterpType.Hyper);
Convert(ScaledDigit, TestDigit);
ManagedMatrix.Transpose(Transposed, TestDigit);
cnn.FeedForward(Transposed);
digit = 0;
double max = double.MinValue;
for (int y = 0; y < cnn.Output.y; y++)
{
var val = cnn.Output[0, y];
Probability[y] = val;
if (val > max)
{
max = val;
digit = y;
}
}
ScaledDigit.Dispose();
ManagedOps.Free(TestDigit, Transposed);
}
public static Pixbuf Get(ManagedCNN cnn, int layer, int i, int j)
{
if (layer >= 0 && layer < cnn.Layers.Count && cnn.Layers[layer].Type == LayerTypes.Convolution && i >= 0 && i < cnn.Layers[layer].FeatureMap.i && j >= 0 && j < cnn.Layers[layer].FeatureMap.j)
{
var FeatureMap = new ManagedArray(cnn.Layers[layer].FeatureMap.x, cnn.Layers[layer].FeatureMap.y, cnn.Layers[layer].FeatureMap.z);
var Transposed = new ManagedArray(FeatureMap);
var pixbuf = new Pixbuf(Colorspace.Rgb, false, 8, FeatureMap.y, FeatureMap.x);
ManagedOps.Copy4DIJ2D(FeatureMap, cnn.Layers[layer].FeatureMap, i, j);
ManagedMatrix.Transpose(Transposed, FeatureMap);
// Get normalization values
double min = Double.MaxValue;
double max = Double.MinValue;
FullyConnected.GetNormalization(Transposed, ref min, ref max);
Activation.Draw(pixbuf, Transposed, min, max);
ManagedOps.Free(Transposed);
return(pixbuf);
}
// return empty pixbuf
return(new Pixbuf(Colorspace.Rgb, false, 8, 1, 1));
}
public static Pixbuf Get(ManagedCNN cnn, int layer)
{
if (layer >= 0 && layer < cnn.Layers.Count && cnn.Layers[layer].Type == LayerTypes.Convolution)
{
var Transposed = new ManagedArray(cnn.Layers[layer].Bias);
ManagedMatrix.Transpose(Transposed, cnn.Layers[layer].Bias);
var pixbuf = new Pixbuf(Colorspace.Rgb, false, 8, Transposed.x, Transposed.y);
// Get normalization values
double min = Double.MaxValue;
double max = Double.MinValue;
FullyConnected.GetNormalization(Transposed, ref min, ref max);
Activation.Draw(pixbuf, Transposed, min, max);
ManagedOps.Free(Transposed);
return(pixbuf);
}
// return empty pixbuf
return(new Pixbuf(Colorspace.Rgb, false, 8, 1, 1));
}
public static void Bitmap(Bitmap Digit, ManagedCNN cnn, ref int digit, ref double[] Probability)
{
// Bitmap Data is transposed
var Transposed = new ManagedArray(28, 28, 1);
var TestDigit = new ManagedArray(28, 28, 1);
var ScaledDigit = Resize(Digit, 28, 28, true);
Convert(ScaledDigit, TestDigit);
ManagedMatrix.Transpose(Transposed, TestDigit);
cnn.FeedForward(Transposed);
digit = 0;
double max = 0;
for (int y = 0; y < cnn.Output.y; y++)
{
var val = cnn.Output[0, y];
Probability[y] = val;
if (val > max)
{
max = val;
digit = y;
}
}
ScaledDigit.Dispose();
ManagedOps.Free(TestDigit, Transposed);
}
public static Bitmap Get(ManagedCNN cnn, int layer, bool transpose = true)
{
if (layer >= 0 && layer < cnn.Layers.Count && cnn.Layers[layer].Type == LayerTypes.Convolution)
{
if (transpose)
{
var Transposed = new ManagedArray(cnn.Layers[layer].Bias, false);
ManagedMatrix.Transpose(Transposed, cnn.Layers[layer].Bias);
var bitmap = new Bitmap(Transposed.x, Transposed.y, PixelFormat.Format24bppRgb);
// Get normalization values
double min = Double.MaxValue;
double max = Double.MinValue;
GetNormalization(Transposed, ref min, ref max);
Draw(bitmap, Transposed, min, max);
ManagedOps.Free(Transposed);
return(bitmap);
}
else
{
var bitmap = new Bitmap(cnn.Layers[layer].Bias.x, cnn.Layers[layer].Bias.y, PixelFormat.Format24bppRgb);
// Get normalization values
double min = Double.MaxValue;
double max = Double.MinValue;
GetNormalization(cnn.Layers[layer].Bias, ref min, ref max);
Draw(bitmap, cnn.Layers[layer].Bias, min, max);
return(bitmap);
}
}
// return empty bitmap
return(new Bitmap(1, 1, PixelFormat.Format24bppRgb));
}
public static Bitmap Get(ManagedCNN cnn, int layer, int map)
{
if (layer >= 0 && layer < cnn.Layers.Count && map >= 0 && map < cnn.Layers[layer].Activation.i)
{
var Activation = new ManagedArray(cnn.Layers[layer].Activation.x, cnn.Layers[layer].Activation.y, cnn.Layers[layer].Activation.z);
var Transposed = new ManagedArray(Activation);
var bitmap = new Bitmap(cnn.Layers[layer].Activation.x, cnn.Layers[layer].Activation.y, PixelFormat.Format24bppRgb);
ManagedOps.Copy4D2D(Activation, cnn.Layers[layer].Activation, 0, map);
ManagedMatrix.Transpose(Transposed, Activation);
// Get normalization values
double min = Double.MaxValue;
double max = Double.MinValue;
for (int y = 0; y < Transposed.y; y++)
{
for (int x = 0; x < Transposed.x; x++)
{
if (Transposed[x, y] > max)
{
max = Transposed[x, y];
}
if (Transposed[x, y] < min)
{
min = Transposed[x, y];
}
}
}
Draw(bitmap, Transposed, min, max);
ManagedOps.Free(Activation, Transposed);
return(bitmap);
}
// return empty bitmap
return(new Bitmap(1, 1, PixelFormat.Format24bppRgb));
}
public static Pixbuf Get(ManagedCNN cnn, int layer, int map)
{
if (layer >= 0 && layer < cnn.Layers.Count && map >= 0 && map < cnn.Layers[layer].Activation.i)
{
var Activation = new ManagedArray(cnn.Layers[layer].Activation.x, cnn.Layers[layer].Activation.y, cnn.Layers[layer].Activation.z);
var Transposed = new ManagedArray(Activation);
var pixbuf = new Pixbuf(Colorspace.Rgb, false, 8, Activation.y, Activation.x);
ManagedOps.Copy4D2D(Activation, cnn.Layers[layer].Activation, 0, map);
ManagedMatrix.Transpose(Transposed, Activation);
// Get normalization values
double min = Double.MaxValue;
double max = double.MinValue;
for (int y = 0; y < Transposed.y; y++)
{
for (int x = 0; x < Transposed.x; x++)
{
if (Transposed[x, y] > max)
{
max = Transposed[x, y];
}
if (Transposed[x, y] < min)
{
min = Transposed[x, y];
}
}
}
Draw(pixbuf, Transposed, min, max);
ManagedOps.Free(Activation, Transposed);
return(pixbuf);
}
// return empty pixbuf
return(new Pixbuf(Colorspace.Rgb, false, 8, 1, 1));
}
public static Bitmap Get(ManagedCNN cnn, int layer, int i, int j)
{
if (layer >= 0 && layer < cnn.Layers.Count && i >= 0 && i < cnn.Layers[layer].FeatureMap.i && j >= 0 && j < cnn.Layers[layer].FeatureMap.j)
{
var FeatureMap = new ManagedArray(cnn.Layers[layer].FeatureMap.x, cnn.Layers[layer].FeatureMap.y, cnn.Layers[layer].FeatureMap.z);
var Transposed = new ManagedArray(FeatureMap);
var bitmap = new Bitmap(cnn.Layers[layer].FeatureMap.x, cnn.Layers[layer].FeatureMap.y, PixelFormat.Format24bppRgb);
ManagedOps.Copy4DIJ2D(FeatureMap, cnn.Layers[layer].FeatureMap, i, j);
ManagedMatrix.Transpose(Transposed, FeatureMap);
// Get normalization values
double min = Double.MaxValue;
double max = Double.MinValue;
for (int y = 0; y < Transposed.y; y++)
{
for (int x = 0; x < Transposed.x; x++)
{
if (Transposed[x, y] > max)
{
max = Transposed[x, y];
}
if (Transposed[x, y] < min)
{
min = Transposed[x, y];
}
}
}
Draw(bitmap, Transposed, min, max);
ManagedOps.Free(FeatureMap, Transposed);
return(bitmap);
}
// return empty bitmap
return(new Bitmap(1, 1, PixelFormat.Format24bppRgb));
}
void InitializeNetwork()
{
cnn = Utility.LoadCNN(BaseDirectory, "modelcnn");
}
