protected override float Outputs(OutputVector result, Floatarray v)
{
result.Clear();
if (v.Rank() == 1)
{
v.Reshape(csize, csize, 0, 0);
}
// byte array input
StdInput vinput = new StdInput(v);
byte[] buffer = vinput.GetDataBuffer();
// char classifier compute outputs
if (CharClass.AsciiTarget)
{
// net output 0..~ (lower - winner)
CharClass.ComputeOutputs(buffer, vinput.Length, vinput.Height, vinput.Width, result);
}
else
{
// net output 0..1; (higher - winner)
CharClass.ComputeOutputsRaw(buffer, vinput.Length, vinput.Height, vinput.Width, result);
}
// junk classifier
if (PGetb("junk") && !DisableJunk && !JunkClass.IsEmpty)
{
OutputVector jv = new OutputVector();
if (JunkClass.AsciiTarget)
{
JunkClass.ComputeOutputs(buffer, vinput.Length, vinput.Height, vinput.Width, jv);
result[jc()] = jv.Value(1);
}
else
{
//result.Normalize();
result.Normalize2();
JunkClass.ComputeOutputsRaw(buffer, vinput.Length, vinput.Height, vinput.Width, jv);
jv.Normalize2();
for (int i = 0; i < result.nKeys(); i++)
{
result.Values[i] *= jv.Value(0);
}
result[jc()] = jv.Value(1);
}
}
return(0.0f);
}
private void DoTestRecognize(LenetClassifier classifier)
{
OutputVector ov = new OutputVector();
Floatarray v = new Floatarray();
Bytearray ba = new Bytearray(1, 1);
ImgIo.read_image_gray(ba, testPngFileName);
NarrayUtil.Sub(255, ba);
v.Copy(ba);
v /= 255.0;
classifier.XOutputs(ov, v);
Console.WriteLine("Featured output class '{0}', score '{1}'", (char)ov.Key(ov.BestIndex), ov.Value(ov.BestIndex));
}
protected override float Outputs(OutputVector result, Floatarray v)
{
result.Clear();
if (v.Rank() == 1)
v.Reshape(csize, csize, 0, 0);
// byte array input
StdInput vinput = new StdInput(v);
byte[] buffer = vinput.GetDataBuffer();
// char classifier compute outputs
if (CharClass.AsciiTarget)
// net output 0..~ (lower - winner)
CharClass.ComputeOutputs(buffer, vinput.Length, vinput.Height, vinput.Width, result);
else
// net output 0..1; (higher - winner)
CharClass.ComputeOutputsRaw(buffer, vinput.Length, vinput.Height, vinput.Width, result);
// junk classifier
if (PGetb("junk") && !DisableJunk && !JunkClass.IsEmpty)
{
OutputVector jv = new OutputVector();
if (JunkClass.AsciiTarget)
{
JunkClass.ComputeOutputs(buffer, vinput.Length, vinput.Height, vinput.Width, jv);
result[jc()] = jv.Value(1);
}
else
{
//result.Normalize();
result.Normalize2();
JunkClass.ComputeOutputsRaw(buffer, vinput.Length, vinput.Height, vinput.Width, jv);
jv.Normalize2();
for (int i = 0; i < result.nKeys(); i++)
result.Values[i] *= jv.Value(0);
result[jc()] = jv.Value(1);
}
}
return 0.0f;
}