public static RowDataset8 GetRowDataset8(MnistDatasource mds, int[] classes)
{
if (mds.NSamples() == 0)
throw new Exception("MNIST database is empty!");
// определим максимальный индекс
byte maxLabel = 0;
foreach (byte label in mds.Labels)
{
if (label > maxLabel)
maxLabel = label;
}
// проверим соответствие индексов Mnist указанному списку классов
if (maxLabel >= classes.Length)
throw new Exception("Classes do not correspond to the MNIST!");
// создаем тренировочную базу
RowDataset8 ds = new RowDataset8(mds.NSamples());
// перебираем MNIST базу
for (int i = 0; i < mds.NSamples(); i++)
{
int label = mds.Labels[i];
StdInput stdInp = new StdInput(mds.ImagesData[i], mds.ImgHeight, mds.ImgWidth);
ds.Add(stdInp.ToFloatarray(), classes[label]);
}
return ds;
}
public void TestArrays()
{
string imgfn = "test-c3.png";
// load Bytearray
Bytearray ba = new Bytearray(1, 1);
ImgIo.read_image_gray(ba, imgfn);
OcrRoutine.Invert(ba);
//NarrayUtil.Sub((byte)255, image);
byte[] bytes1 = ba.To1DArray();
NarrayShow.ShowConsole(ba);
StdInput linput1 = new StdInput(ba);
Console.WriteLine();
// load StdInput
Bitmap bitmap = ImgIo.LoadBitmapFromFile(imgfn);
StdInput linput2 = StdInput.FromBitmap(bitmap);
//NarrayShow.ShowConsole(linput2);
// test convert
Floatarray fa = linput2.ToFloatarray();
StdInput linput3 = new StdInput(fa);
Console.WriteLine("Arrays is identical? {0}", Equals(linput1.GetDataBuffer(), linput2.GetDataBuffer()));
Console.WriteLine("Arrays is identical? {0}", Equals(linput2.GetDataBuffer(), linput3.GetDataBuffer()));
}
public void TestArrays()
{
string imgfn = "test-c3.png";
// load Bytearray
Bytearray ba = new Bytearray(1, 1);
ImgIo.read_image_gray(ba, imgfn);
OcrRoutine.Invert(ba);
//NarrayUtil.Sub((byte)255, image);
byte[] bytes1 = ba.To1DArray();
NarrayShow.ShowConsole(ba);
StdInput linput1 = new StdInput(ba);
Console.WriteLine();
// load StdInput
Bitmap bitmap = ImgIo.LoadBitmapFromFile(imgfn);
StdInput linput2 = StdInput.FromBitmap(bitmap);
//NarrayShow.ShowConsole(linput2);
// test convert
Floatarray fa = linput2.ToFloatarray();
StdInput linput3 = new StdInput(fa);
Console.WriteLine("Arrays is identical? {0}", Equals(linput1.GetDataBuffer(), linput2.GetDataBuffer()));
Console.WriteLine("Arrays is identical? {0}", Equals(linput2.GetDataBuffer(), linput3.GetDataBuffer()));
}
public void TestRowDataset()
{
DRandomizer.Default.init_drand(DateTime.Now.Millisecond);
// load Mnist datasource
MnistDatasource mds = new MnistDatasource();
mds.LoadFromFile(mnistFileNamePrefix);
// convert mnist to RowDataset8
RowDataset8 ds8 = MnistDatasetConvert.GetRowDataset8(mds, classes);
// show random sample to console
Floatarray fa = new Floatarray();
int isample = (int)DRandomizer.Default.drand(ds8.nSamples(), 0);
ds8.Input(fa, isample);
Console.WriteLine("Char is '{0}'", (char)ds8.Cls(isample));
NarrayShow.ShowConsole(fa);
// compare random float sample and original mnist
StdInput inp1 = new StdInput(mds.ImagesData[isample], mds.ImgHeight, mds.ImgWidth);
StdInput inp2 = new StdInput(fa);
Console.WriteLine("Arrays is identical? {0}", Equals(inp1.GetDataBuffer(), inp2.GetDataBuffer()));
// save RowDataset8 to file
Console.WriteLine("Saving {0} samples..", ds8.nSamples());
ds8.Save(mnistFileNamePrefix + dsExt);
// load RowDataset8 from file
RowDataset8 ds = new RowDataset8();
ds.Load(mnistFileNamePrefix + dsExt);
Console.WriteLine("Loaded {0} samples", ds.nSamples());
}
public TrainInfo TestDense(IDataset ts)
{
TrainInfo trInfo = new TrainInfo();
bool first = true;
Floatarray v = new Floatarray();
// Send Test Dataset to Lenet
for (int i = 0; i < ts.nSamples(); i++)
{
ts.Input(v, i);
if (v.Rank() == 1)
{
v.Reshape(csize, csize, 0, 0);
}
StdInput linput = new StdInput(v);
if (first)
{
first = false;
BeginTestEpoch(HrLenet, linput.Height, linput.Width, ts.nSamples()); // init test
}
try
{
if (C2i.ContainsKey(ts.Cls(i)))
{
AddSampleToTestOfEpoch(HrLenet, linput.GetDataBuffer(), linput.Length, C2i[ts.Cls(i)]);
}
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
{
Global.Debugf("error", sbout.ToString() + "\r\nException in AddSampleToTestOfEpoch");
}
throw new Exception("Exception in AddSampleToTestOfEpoch\r\n" + e.Message);
}
}
// do test one epoch
try
{
EndAndRunTestEpoch(HrLenet, ref trInfo);
}
catch (Exception e)
{
GetStdout(sbout); // get test messages
if (sbout.Length > 0)
{
Global.Debugf("error", sbout.ToString() + "\r\nException in EndAndRunTestEpoch");
}
throw new Exception("Exception in EndAndRunTestEpoch\r\n" + e.Message);
}
return(trInfo);
}
public static void ShowConsole(StdInput a)
{
for (int y = 0; y < a.Height; y++)
{
for (int x = 0; x < a.Width; x++)
{
Console.Write("{0,-3}", a[y, x]);
}
Console.WriteLine();
}
}
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);
}
public static RowDataset8 GetRowDataset8(MnistDatasource mds, int[] classes)
{
if (mds.NSamples() == 0)
{
throw new Exception("MNIST database is empty!");
}
// определим максимальный индекс
byte maxLabel = 0;
foreach (byte label in mds.Labels)
{
if (label > maxLabel)
{
maxLabel = label;
}
}
// проверим соответствие индексов Mnist указанному списку классов
if (maxLabel >= classes.Length)
{
throw new Exception("Classes do not correspond to the MNIST!");
}
// создаем тренировочную базу
RowDataset8 ds = new RowDataset8(mds.NSamples());
// перебираем MNIST базу
for (int i = 0; i < mds.NSamples(); i++)
{
int label = mds.Labels[i];
StdInput stdInp = new StdInput(mds.ImagesData[i], mds.ImgHeight, mds.ImgWidth);
ds.Add(stdInp.ToFloatarray(), classes[label]);
}
return(ds);
}
public void TestRowDataset()
{
DRandomizer.Default.init_drand(DateTime.Now.Millisecond);
// load Mnist datasource
MnistDatasource mds = new MnistDatasource();
mds.LoadFromFile(mnistFileNamePrefix);
// convert mnist to RowDataset8
RowDataset8 ds8 = MnistDatasetConvert.GetRowDataset8(mds, classes);
// show random sample to console
Floatarray fa = new Floatarray();
int isample = (int)DRandomizer.Default.drand(ds8.nSamples(), 0);
ds8.Input(fa, isample);
Console.WriteLine("Char is '{0}'", (char)ds8.Cls(isample));
NarrayShow.ShowConsole(fa);
// compare random float sample and original mnist
StdInput inp1 = new StdInput(mds.ImagesData[isample], mds.ImgHeight, mds.ImgWidth);
StdInput inp2 = new StdInput(fa);
Console.WriteLine("Arrays is identical? {0}", Equals(inp1.GetDataBuffer(), inp2.GetDataBuffer()));
// save RowDataset8 to file
Console.WriteLine("Saving {0} samples..", ds8.nSamples());
ds8.Save(mnistFileNamePrefix + dsExt);
// load RowDataset8 from file
RowDataset8 ds = new RowDataset8();
ds.Load(mnistFileNamePrefix + dsExt);
Console.WriteLine("Loaded {0} samples", ds.nSamples());
}
public virtual TrainInfo TrainBatch(IDataset ds, IDataset ts, int epochs)
{
TrainInfo trInfo = new TrainInfo();
bool first = true;
Floatarray v = new Floatarray();
// Send Train Dataset to Lenet
for (int i = 0; i < ds.nSamples(); i++)
{
ds.Input(v, i);
if (v.Rank() == 1)
{
v.Reshape(csize, csize, 0, 0);
}
StdInput linput = new StdInput(v);
try
{
if (first)
{
first = false;
//StartRedirectStdout(); // start redirect cout to string buffer
BeginTrainEpoch(HrLenet, linput.Height, linput.Width, ds.nSamples(), ts.nSamples()); // init train
}
if (C2i.ContainsKey(ds.Cls(i)))
{
AddSampleToTrainOfEpoch(HrLenet, linput.GetDataBuffer(), linput.Length, C2i[ds.Cls(i)]);
}
else
{
Global.Debugf("error", "class '{0}' is not contained in the char list", (char)ds.Cls(i));
}
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
{
Global.Debugf("error", sbout.ToString() + "\r\nException in AddSampleToTrainOfEpoch");
}
throw new Exception("Exception in AddSampleToTrainOfEpoch\r\n" + e.Message);
}
}
// Send Test Dataset to Lenet
for (int i = 0; i < ts.nSamples(); i++)
{
ts.Input(v, i);
if (v.Rank() == 1)
{
v.Reshape(csize, csize, 0, 0);
}
StdInput linput = new StdInput(v);
try
{
if (C2i.ContainsKey(ts.Cls(i)))
{
AddSampleToTestOfEpoch(HrLenet, linput.GetDataBuffer(), linput.Length, C2i[ts.Cls(i)]);
}
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
{
Global.Debugf("error", sbout.ToString() + "\r\nException in AddSampleToTestOfEpoch");
}
throw new Exception("Exception in AddSampleToTestOfEpoch\r\n" + e.Message);
}
}
// debug save mnist
//SaveTrainMnist(HrLenet, "debug-images-idx3-ubyte", "debug-labels-idx1-ubyte");
// do train epochs
for (int epoch = 0; epoch < epochs; epoch++)
{
trInfo = new TrainInfo();
try
{
DateTime startDate = DateTime.Now;
EndAndRunTrainEpoch(HrLenet, ref trInfo); // do train one epoch
// show train info
Global.Debugf("info",
String.Format("|{0,7}| Energy:{1:0.#####} Correct:{2:0.00#%} Errors:{3:0.00#%} Count:{4} ",
trInfo.age, trInfo.energy, (trInfo.correct / (float)trInfo.size),
(trInfo.error / (float)trInfo.size), trInfo.size));
Global.Debugf("info",
String.Format(" TEST Energy={0:0.#####} Correct={1:0.00#%} Errors={2:0.00#%} Count={3} ",
trInfo.tenergy, (trInfo.tcorrect / (float)trInfo.tsize),
(trInfo.terror / (float)trInfo.tsize), trInfo.tsize));
TimeSpan spanTrain = DateTime.Now - startDate;
Global.Debugf("info", String.Format(" training time: {0} minutes, {1} seconds",
(int)spanTrain.TotalMinutes, spanTrain.Seconds));
// get dll stdout messages
GetStdout(sbout);
if (sbout.Length > 0)
{
Console.Write(sbout.ToString());
}
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
{
Global.Debugf("error", sbout.ToString() + "\r\nException in EndAndRunTrainEpoch");
}
throw new Exception("Exception in EndAndRunTrainEpoch\r\n" + e.Message);
}
}
return(trInfo);
}
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;
}
public virtual TrainInfo TrainBatch(IDataset ds, IDataset ts, int epochs)
{
TrainInfo trInfo = new TrainInfo();
bool first = true;
Floatarray v = new Floatarray();
// Send Train Dataset to Lenet
for (int i = 0; i < ds.nSamples(); i++)
{
ds.Input(v, i);
if (v.Rank() == 1)
v.Reshape(csize, csize, 0, 0);
StdInput linput = new StdInput(v);
try
{
if (first)
{
first = false;
//StartRedirectStdout(); // start redirect cout to string buffer
BeginTrainEpoch(HrLenet, linput.Height, linput.Width, ds.nSamples(), ts.nSamples()); // init train
}
if (C2i.ContainsKey(ds.Cls(i)))
AddSampleToTrainOfEpoch(HrLenet, linput.GetDataBuffer(), linput.Length, C2i[ds.Cls(i)]);
else
Global.Debugf("error", "class '{0}' is not contained in the char list", (char)ds.Cls(i));
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
Global.Debugf("error", sbout.ToString() + "\r\nException in AddSampleToTrainOfEpoch");
throw new Exception("Exception in AddSampleToTrainOfEpoch\r\n" + e.Message);
}
}
// Send Test Dataset to Lenet
for (int i = 0; i < ts.nSamples(); i++)
{
ts.Input(v, i);
if (v.Rank() == 1)
v.Reshape(csize, csize, 0, 0);
StdInput linput = new StdInput(v);
try
{
if (C2i.ContainsKey(ts.Cls(i)))
AddSampleToTestOfEpoch(HrLenet, linput.GetDataBuffer(), linput.Length, C2i[ts.Cls(i)]);
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
Global.Debugf("error", sbout.ToString() + "\r\nException in AddSampleToTestOfEpoch");
throw new Exception("Exception in AddSampleToTestOfEpoch\r\n" + e.Message);
}
}
// debug save mnist
//SaveTrainMnist(HrLenet, "debug-images-idx3-ubyte", "debug-labels-idx1-ubyte");
// do train epochs
for (int epoch = 0; epoch < epochs; epoch++)
{
trInfo = new TrainInfo();
try
{
DateTime startDate = DateTime.Now;
EndAndRunTrainEpoch(HrLenet, ref trInfo); // do train one epoch
// show train info
Global.Debugf("info",
String.Format("|{0,7}| Energy:{1:0.#####} Correct:{2:0.00#%} Errors:{3:0.00#%} Count:{4} ",
trInfo.age, trInfo.energy, (trInfo.correct / (float)trInfo.size),
(trInfo.error / (float)trInfo.size), trInfo.size) );
Global.Debugf("info",
String.Format(" TEST Energy={0:0.#####} Correct={1:0.00#%} Errors={2:0.00#%} Count={3} ",
trInfo.tenergy, (trInfo.tcorrect / (float)trInfo.tsize),
(trInfo.terror / (float)trInfo.tsize), trInfo.tsize));
TimeSpan spanTrain = DateTime.Now - startDate;
Global.Debugf("info", String.Format(" training time: {0} minutes, {1} seconds",
(int)spanTrain.TotalMinutes, spanTrain.Seconds));
// get dll stdout messages
GetStdout(sbout);
if (sbout.Length > 0)
Console.Write(sbout.ToString());
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
Global.Debugf("error", sbout.ToString() + "\r\nException in EndAndRunTrainEpoch");
throw new Exception("Exception in EndAndRunTrainEpoch\r\n" + e.Message);
}
}
return trInfo;
}
public TrainInfo TestDense(IDataset ts)
{
TrainInfo trInfo = new TrainInfo();
bool first = true;
Floatarray v = new Floatarray();
// Send Test Dataset to Lenet
for (int i = 0; i < ts.nSamples(); i++)
{
ts.Input(v, i);
if (v.Rank() == 1)
v.Reshape(csize, csize, 0, 0);
StdInput linput = new StdInput(v);
if (first)
{
first = false;
BeginTestEpoch(HrLenet, linput.Height, linput.Width, ts.nSamples()); // init test
}
try
{
if (C2i.ContainsKey(ts.Cls(i)))
AddSampleToTestOfEpoch(HrLenet, linput.GetDataBuffer(), linput.Length, C2i[ts.Cls(i)]);
}
catch (Exception e)
{
GetStdout(sbout); // get train messages
if (sbout.Length > 0)
Global.Debugf("error", sbout.ToString() + "\r\nException in AddSampleToTestOfEpoch");
throw new Exception("Exception in AddSampleToTestOfEpoch\r\n" + e.Message);
}
}
// do test one epoch
try
{
EndAndRunTestEpoch(HrLenet, ref trInfo);
}
catch (Exception e)
{
GetStdout(sbout); // get test messages
if (sbout.Length > 0)
Global.Debugf("error", sbout.ToString() + "\r\nException in EndAndRunTestEpoch");
throw new Exception("Exception in EndAndRunTestEpoch\r\n" + e.Message);
}
return trInfo;
}
