protected override float Outputs(OutputVector result, Floatarray v)
{
result.Clear();
charclass.Object.XOutputs(result, v);
CHECK_ARG(result.nKeys() > 0, "result.nKeys() > 0");
if (PGetb("junk") && !DisableJunk && !junkclass.IsEmpty)
{
result.Normalize();
OutputVector jv = new OutputVector();
junkclass.Object.XOutputs(jv, v);
for (int i = 0; i < result.nKeys(); i++)
{
result.Values[i] *= jv.Value(0);
}
result[jc()] = jv.Value(1);
}
if (PGeti("ul") > 0 && !ulclass.IsEmpty)
{
throw new Exception("ulclass not implemented");
}
return(0.0f);
}
protected override float Outputs(OutputVector result, Floatarray v)
{
result.Clear();
charclass.Object.XOutputs(result, v);
CHECK_ARG(result.nKeys() > 0, "result.nKeys() > 0");
if (PGetb("junk") && !DisableJunk && !junkclass.IsEmpty)
{
result.Normalize();
OutputVector jv = new OutputVector();
junkclass.Object.XOutputs(jv, v);
for (int i = 0; i < result.nKeys(); i++)
result.Values[i] *= jv.Value(0);
result[jc()] = jv.Value(1);
}
if (PGeti("ul") > 0 && !ulclass.IsEmpty)
{
throw new Exception("ulclass not implemented");
}
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));
}
