/// <summary>
/// Обновляет свойства InputMatrix и OutputMatrix новыми значениями, полученными из colorMatrix.
/// </summary>
public void UpdateImages(IImageMatrix colorMatrix)
{
if(colorMatrix != null)
{
InputMatrix = colorMatrix.ToMat();
OutputMatrix = InputMatrix.Clone();
}
}
/// <summary>
/// Обновляет свойства InputMatrix и OutputMatrix новыми значениями, полученными из bitmap.
/// </summary>
public void UpdateImages(System.Drawing.Bitmap bitmap)
{
if(bitmap != null)
{
Mat mat = BitmapConverter.ToMat(bitmap);
InputMatrix = mat;
OutputMatrix = InputMatrix.Clone();
}
}
public bool HW1()
{
string dbgout = "";
DebugLog.Log("HW1 - Simple");
InputMatrix in1 = new InputMatrix(5);
SubZone sz1 = new SubZone(5);
OutputMatrix out1 = new OutputMatrix(5);
in1.setUpSubZone(sz1);
sz1.setDownSubZones(in1);
sz1.setUpSubZone(out1);
out1.addInputs(sz1);
DebugLog.Log("Learn");
bool[][] in_p1 = new bool[][] {
new bool[] { true, false, false, false, false },
new bool[] { false, true, false, false, false },
new bool[] { false, false, true, false, false },
new bool[] { false, false, false, true, false },
new bool[] { false, false, false, false, true },
};
for (int i = 0; i < in_p1.Length; i++)
{
in1.setBooleans(in_p1[i]);
sz1.setColumnNeurons(i, in1.inputs);
}
for (int n = 0; n < in_p1.Length; n++)
{
out1.reset();
DebugLog.Log("Analyse " + n + " pattern");
in1.setBooleans(in_p1[n]);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].active > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Pattern : " + dbgout);
in1.sendSignals();
sz1.analyze();
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (out1.inputsActives[i] > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Columns : " + dbgout);
out1.reset();
}
//sz1.teach();
return(true);
}
//
/**/
/// <summary>
/// Создаёт объект <see cref="FaceDetector"/>
/// </summary>
/// <param name="colorMatrix"> Цветная матрица изображения. </param>
public FaceDetector(ColorMatrix colorMatrix)
{
Classifier = new CascadeClassifier(
Path.Combine(
Directory.GetCurrentDirectory(),
"Samples",
"haarcascade_frontalface_default.xml"));
//getting bitmap from colorMatrix
System.Drawing.Bitmap bitmap = colorMatrix.CreateBitmap();
//converting System.Drawing.Bitmap -> OpenCVSharp.CPlusPlus.Mat
Mat mat = BitmapConverter.ToMat(bitmap);
InputMatrix = mat;
OutputMatrix = InputMatrix.Clone();
FacesRepository = new List<Mat>();
}
/// <summary>
/// Создаёт объект <see cref="FaceDetector"/>
/// </summary>
/// <param name="videoImage"> Изображение. </param>
public FaceDetector(VideoImage videoImage)
{
Classifier = new CascadeClassifier(
Path.Combine(
Directory.GetCurrentDirectory(),
"Samples",
"haarcascade_frontalface_default.xml"));
//creating bitmap
System.Drawing.Bitmap bitmap = videoImage.Matrix.CreateBitmap();
//converting System.Drawing.Bitmap -> OpenCVSharp.CPlusPlus.Mat
if(bitmap != null) {
Mat mat = BitmapConverter.ToMat(bitmap);
InputMatrix = mat;
OutputMatrix = InputMatrix.Clone();
}
FacesRepository = new List<Mat>();
}
public static void DrawMatrix(List <Cart> carts)
{
for (var x = 0; x < InputMatrix.GetLength(0); x++)
{
for (var y = 0; y < InputMatrix.GetLength(1); y++)
{
var cart = carts.FirstOrDefault(c => c.Point.X == x && c.Point.Y == y);
if (cart is null)
{
Console.Write(InputMatrix[x, y]);
}
else
{
Console.Write(cart.Orientation);
}
}
Console.WriteLine();
}
}
private void вводМатрицыToolStripMenuItem_Click(object sender, EventArgs e)
{
if (вводМатрицыToolStripMenuItem.Checked)
{
InputMatrix inputMatrix = new InputMatrix();
inputMatrix.MdiParent = this;
inputMatrix.Show();
}
else
{
bool fl = true;
for (int i = 0; fl && i < this.MdiChildren.Length; i++)
{
if (MdiChildren[i] is InputMatrix)
{
MdiChildren[i].Close();
fl = false;
}
}
}
}
/// <summary>
/// Обнаружение лиц на изображении.
/// </summary>
/// <returns>
/// Возвращает массивы прямоугольников <seealso cref="Rect"/> обнаруженных лиц.
/// </returns>
public Rect[] DetectFaces()
{
// Detect face rectangles
DetectedFaces = Classifier.DetectMultiScale(
image: InputMatrix,
scaleFactor: 1.35,
minNeighbors: 5,
flags: HaarDetectionType.ScaleImage,
minSize: new Size(30, 30),
maxSize: InputMatrix.Size());
foreach(var faceRect in DetectedFaces)
{
Mat face = new Mat(InputMatrix, roi: faceRect)
.ResizeImage(IMG_WIDTH, IMG_HEIGHT)
.ConvertToGray();
FacesRepository.Add(face);
}
return DetectedFaces;
}
public static void Main(string[] args)
{
/*
* XorShift160 lol = new XorShift160();
* double runningSum = 0;
*
* while (!Console.KeyAvailable)
* {
* Console.WriteLine(lol.NextDouble());
* }
* return;
*/
IStateMatrix A = new StateMatrix(2, 2);
A.SetValue(0, 0, 0);
A.SetValue(0, 1, 1);
A.SetValue(1, 0, 0);
A.SetValue(1, 0, 0);
/*
* var c = new CompiledMatrix<IStateMatrix>(A);
* c.Compile();
*/
IInputMatrix B = new InputMatrix(2, 1);
B.SetValue(0, 0, 0);
B.SetValue(1, 0, 1);
IOutputMatrix C = new OutputMatrix(2, 2);
C.SetValue(0, 0, 1);
C.SetValue(0, 1, 0);
C.SetValue(1, 0, 0);
C.SetValue(1, 1, 1);
IFeedthroughMatrix D = new FeedthroughMatrix(2, 1);
D.SetValue(0, 0, 0);
D.SetValue(1, 0, 0);
ControlVector u = new ControlVector(1);
u.SetValue(0, 1);
// TODO: Construct vectors and matrices by factory and let the simulation driver compile them after every external change
IStateVector x = new StateVector(2);
/*
* IStateVector dx = new StateVector(x.Length);
* IStateVector dxu = new StateVector(x.Length);
* IOutputVector y = new OutputVector(C.Rows);
* IOutputVector yu = new OutputVector(C.Rows);
*/
CancellationTokenSource cts = new CancellationTokenSource();
CancellationToken ct = cts.Token;
Semaphore startCalculation = new Semaphore(0, 2);
Semaphore calculationDone = new Semaphore(0, 2);
SimulationTime simulationTime = new SimulationTime();
IStateVector dx = new StateVector(x.Length);
Task inputToState = new Task(() =>
{
IStateVector dxu = new StateVector(x.Length);
while (!ct.IsCancellationRequested)
{
startCalculation.WaitOne();
Thread.MemoryBarrier();
A.Transform(x, ref dx);
B.Transform(u, ref dxu); // TODO: TransformAndAdd()
dx.AddInPlace(dxu);
Thread.MemoryBarrier();
calculationDone.Release();
}
});
IOutputVector y = new OutputVector(C.Rows);
Task stateToOutput = new Task(() =>
{
IOutputVector yu = new OutputVector(C.Rows);
while (!ct.IsCancellationRequested)
{
startCalculation.WaitOne();
Thread.MemoryBarrier();
C.Transform(x, ref y);
D.Transform(u, ref yu); // TODO: TransformAndAdd()
y.AddInPlace(yu);
Thread.MemoryBarrier();
calculationDone.Release();
}
});
Task control = new Task(() =>
{
Stopwatch watch = Stopwatch.StartNew();
int steps = 0;
while (!ct.IsCancellationRequested)
{
// wait for a new u to be applied
// TODO: apply control vector
startCalculation.Release(2);
// wait for y
calculationDone.WaitOne();
calculationDone.WaitOne();
Thread.MemoryBarrier();
// wait for state vector to be changeable
// TODO: perform real transformation
x.AddInPlace(dx); // discrete integration, T=1
// video killed the radio star
if (steps % 1000 == 0)
{
var localY = y;
double thingy = steps / watch.Elapsed.TotalSeconds;
Trace.WriteLine(simulationTime.Time + " Position: " + localY.GetValue(0) + ", Velocity: " + localY.GetValue(1) + ", Acceleration: " + u.GetValue(0) + ", throughput: " + thingy);
}
// cancel out acceleration
if (steps++ == 10)
{
u.SetValue(0, 0);
}
// advance simulation time
simulationTime.Add(TimeSpan.FromSeconds(1));
}
});
inputToState.Start();
stateToOutput.Start();
control.Start();
Console.ReadKey(true);
cts.Cancel();
/*
* while (!Console.KeyAvailable)
* {
* A.Transform(x, ref dx);
* B.Transform(u, ref dxu); // TODO: TransformAndAdd()
* dx.AddInPlace(dxu);
*
* // TODO: perform transformation
* x.AddInPlace(dx); // discrete integration, T=1
*
* C.Transform(x, ref y);
* D.Transform(u, ref yu); // TODO: TransformAndAdd()
* y.AddInPlace(yu);
*
* // video killed the radio star
* if (steps%1000 == 0)
* {
* Trace.WriteLine("Position: " + y[0] + ", Velocity: " + y[1] + ", Acceleration: " + u[0] + ", throughput: " + steps/watch.Elapsed.TotalSeconds);
* }
*
* // cancel out acceleration
* if (steps++ == 10)
* {
* u[0] = 0;
* }
* }
*/
}
public void InputMatrix(string key, InputMatrix inputMatrix)
{
InputMatrices[key] = inputMatrix;
}
public void HW2()
{
string dbgout = "";
DebugLog.Log("HW2 - Sequence");
InputMatrix in1 = new InputMatrix(5);
SubZone sz1 = new SubZone(5);
OutputMatrix out1 = new OutputMatrix(5);
in1.setUpSubZone(sz1);
sz1.setDownSubZones(in1);
sz1.setUpSubZone(out1);
out1.addInputs(sz1);
DebugLog.Log("Learn");
bool[][] in_p1 = new bool[][] {
new bool[] { true, true, false, false, false },
new bool[] { false, true, true, false, false },
};
for (int i = 0; i < in_p1.Length; i++)
{
in1.setBooleans(in_p1[i]);
sz1.setColumnNeurons(0, in1.inputs);
}
bool[][] in_p2 = new bool[][] {
new bool[] { false, false, true, true, false },
new bool[] { false, false, false, true, true },
};
for (int i = 0; i < in_p2.Length; i++)
{
in1.setBooleans(in_p2[i]);
sz1.setColumnNeurons(1, in1.inputs);
}
bool[][] in_p3 = new bool[][] {
new bool[] { false, false, true, true, false },
new bool[] { false, true, true, false, false },
new bool[] { true, true, false, false, false },
};
for (int i = 0; i < in_p3.Length; i++)
{
in1.setBooleans(in_p3[i]);
sz1.setColumnNeurons(2, in1.inputs);
}
bool[][] in_p4 = new bool[][] {
new bool[] { true, false, false, false, true },
new bool[] { false, true, false, true, false },
new bool[] { false, false, true, false, false },
};
for (int i = 0; i < in_p4.Length; i++)
{
in1.setBooleans(in_p4[i]);
sz1.setColumnNeurons(3, in1.inputs);
}
bool[][] in_p5 = new bool[][] {
new bool[] { true, false, false, false, false },
new bool[] { false, true, false, false, false },
new bool[] { false, false, true, false, false },
new bool[] { false, false, false, true, false },
new bool[] { false, false, false, false, true },
};
for (int i = 0; i < in_p5.Length; i++)
{
in1.setBooleans(in_p5[i]);
sz1.setColumnNeurons(4, in1.inputs);
}
bool[][] in_p = new bool[][] {
new bool[] { true, false, false, false, false }, // 5
new bool[] { false, true, false, false, false }, // 5
new bool[] { false, false, true, false, false }, // 5
new bool[] { false, false, false, true, false }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, true, true }, // _
new bool[] { false, false, true, true, false }, // 2, 3
new bool[] { false, true, true, false, false }, // 3
new bool[] { true, true, false, false, false }, // 3, 1
new bool[] { false, true, true, false, false }, // 1
new bool[] { false, false, true, true, false }, // 2
new bool[] { false, false, false, true, true }, // 2
new bool[] { true, false, false, false, true }, // 4
new bool[] { false, true, false, true, false }, // 4
new bool[] { false, false, true, false, false }, // 4
new bool[] { false, false, false, true, false }, // _
new bool[] { false, false, false, false, true }, // _
new bool[] { true, false, false, false, false }, // 5
new bool[] { false, true, false, false, false }, // 5
new bool[] { false, false, true, false, false }, // 5
new bool[] { true, false, false, false, true }, // 4
new bool[] { false, true, false, true, false }, // 4
new bool[] { false, false, true, true, false }, // 3
new bool[] { false, true, true, false, false }, // 3
new bool[] { true, true, false, false, false }, // 3
new bool[] { true, false, false, false, true }, // 4
new bool[] { true, true, false, false, false }, // 1
new bool[] { false, true, true, false, false }, // 1
new bool[] { false, false, true, true, false }, // 3
new bool[] { false, false, false, true, true }, // _
};
bool[][] in_e = new bool[][] {
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, false }, // _
new bool[] { false, true, true, false, false }, // 2, 3
new bool[] { false, false, true, false, false }, // 3
new bool[] { true, false, true, false, false }, // 3, 1
new bool[] { true, false, false, false, false }, // 1
new bool[] { false, true, false, false, true }, // 2, 5
new bool[] { false, true, false, false, false }, // 2
new bool[] { false, false, false, true, false }, // 4
new bool[] { false, false, false, true, false }, // 4
new bool[] { false, false, false, true, false }, // 4
new bool[] { false, false, false, false, false }, // _
new bool[] { false, false, false, false, false }, // _
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, false, true }, // 5
new bool[] { false, false, false, true, false }, // 4
new bool[] { false, false, false, true, false }, // 4
new bool[] { false, true, true, false, false }, // 3, 2
new bool[] { false, false, true, false, false }, // 3
new bool[] { false, false, true, false, false }, // 3
new bool[] { false, false, false, true, false }, // 4
new bool[] { true, false, false, false, false }, // 1
new bool[] { true, false, false, false, false }, // 1
new bool[] { false, true, false, false, false }, // 2
new bool[] { false, true, false, false, false }, // 2
};
for (int n = 0; n < in_p.Length; n++)
{
DebugLog.Log("Analyse " + n + " pattern");
in1.setBooleans(in_p[n]);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].active > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Pattern : " + dbgout);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in_e[n][i] ? "A" : "_") + " ";
}
DebugLog.Log("Etalon : " + dbgout);
in1.sendSignals();
sz1.analyze();
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (out1.inputsActives[i] > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Columns : " + dbgout);
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].prediction >= 0.5f ? "A" : "_") + " ";
}
DebugLog.Log("Prediction : " + dbgout);
out1.reset();
}
//sz1.teach();
}
public void HW4()
{
string dbgout = "";
DebugLog.Log("HW4 - Motor");
InputMatrix in1 = new InputMatrix(5);
SubZone sz1 = new SubZone(5);
OutputMatrix out1 = new OutputMatrix(5);
in1.setUpSubZone(sz1);
sz1.setDownSubZones(in1);
sz1.setUpSubZone(out1);
out1.setDownSubZones(sz1);
out1.addInputs(sz1);
DebugLog.Log("Learn");
bool[][] in_p2 = new bool[][] {
new bool[] { false, false, true, true, false },
new bool[] { false, false, false, true, true },
};
for (int i = 0; i < in_p2.Length; i++)
{
in1.setBooleans(in_p2[i]);
sz1.setColumnNeurons(1, in1.inputs);
}
bool[][] in_p3 = new bool[][] {
new bool[] { false, false, true, true, false },
new bool[] { false, true, true, false, false },
new bool[] { true, true, false, false, false },
};
for (int i = 0; i < in_p3.Length; i++)
{
in1.setBooleans(in_p3[i]);
sz1.setColumnNeurons(2, in1.inputs);
}
bool[][] in_p = new bool[][] {
new bool[] { false, false, false, true, false }, // _
new bool[] { false, false, true, true, false }, // 2,3
};
for (int n = 0; n < in_p.Length; n++)
{
DebugLog.Log("Analyse " + n + " pattern");
in1.setBooleans(in_p[n]);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].active > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Pattern : " + dbgout);
in1.sendSignals();
sz1.analyze();
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (out1.inputsActives[i] > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Columns : " + dbgout);
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].prediction >= 0.5f ? "A" : "_") + " ";
}
DebugLog.Log("Prediction : " + dbgout);
for (int p = 0; p < 5; p++)
{
DebugLog.Log("Motor " + p + " pattern");
out1.outSignalMotor(p);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in1.getMotorValues()[i] >= 0.5f ? "A" : "_") + " ";
}
DebugLog.Log("Motor : " + dbgout);
in1.reset();
}
out1.reset();
}
sz1.onDeactive();
}
