public void BinaryDilation3x3Test1()
{
string basePath = NUnit.Framework.TestContext.CurrentContext.TestDirectory;
#region doc_binary_dilation_3x3
// Let's start with one of the default
// color test images in the framework:
var test = new TestImages(basePath);
// Let's get Lena's picture
Bitmap bmp = test["lena.bmp"];
// And transform it to a binary mask
// using Niblack's threshold class
var niblack = new NiblackThreshold();
Bitmap binary = niblack.Apply(bmp);
// The result can be seen below:
// ImageBox.Show(binary);
// Now, let's finally apply the dilation
// filter to the binarized image below:
var dil3x3 = new BinaryDilation3x3();
Bitmap result = dil3x3.Apply(binary);
// The result can be seen below:
// ImageBox.Show(result);
#endregion
//result.Save(@"C:\Projects\morpho-dilation3x3-result.png");
//binary.Save(@"C:\Projects\morpho-dilation3x3-binary.png");
}
public mErosionDilation()
{
BitmapType = mFilter.BitmapTypes.GrayscaleBT709;
Effect = new BinaryDilation3x3();
filter = Effect;
}
/// <summary>
/// Called when videoPlayer receives a new frame.
/// </summary>
/// <param name="sender"></param>
/// <param name="image"></param>
private void videoPlayer_NewFrame(object sender, ref Bitmap frame)
{
if (previousFrame != null)
{
// find the thresholded euclidian difference between two subsequent frames
ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
threshold.OverlayImage = previousFrame;
var difference = threshold.Apply(frame);
// only keep big blobs
var filter = new BlobsFiltering();
filter.CoupledSizeFiltering = true;
filter.MinHeight = 50;
filter.MinWidth = 50;
filter.ApplyInPlace(difference);
// dilate remaining blobs
var dilate = new BinaryDilation3x3();
dilate.ApplyInPlace(difference);
dilate.ApplyInPlace(difference);
dilate.ApplyInPlace(difference);
dilate.ApplyInPlace(difference);
// put this image in the thresholded picturebox
thresholdedBox.Image = difference.Clone() as Bitmap;
// use this as a mask for the current frame
var mask = new ApplyMask(difference);
var maskedFrame = mask.Apply(frame);
// put this image in the masked picturebox
maskedBox.Image = maskedFrame.Clone() as Bitmap;
// now find all moving blobs
if (frameIndex % 10 == 0)
{
var counter = new BlobCounter();
counter.ProcessImage(difference);
// only keep blobs that:
// - do not overlap with known cars
// - do not overlap with other blobs
// - have crossed the middle of the frame
// - are at least 100 pixels tall
var blobs = counter.GetObjectsRectangles();
var newBlobs = from r in counter.GetObjectsRectangles()
where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r)) &&
!blobs.Any(b => b.IntersectsWith(r) && b != r) &&
r.Top >= 240 && r.Bottom <= 480 &&
r.Height >= 100
select r;
// set up new camshift trackers for each detected blob
foreach (var rect in newBlobs)
{
trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
}
}
// now kill all car trackers that have expanded by too much
trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// and kill all trackers that have lived for 30 frames
trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
// let all remaining trackers process the current frame
var img = UnmanagedImage.FromManagedImage(maskedFrame);
trackers
.ForEach(t => t.Tracker.ProcessFrame(img));
// remember this frame for next iteration
previousFrame.Dispose();
previousFrame = frame.Clone() as Bitmap;
// draw labels on all tracked cars
var outputFrame = frame.Clone() as Bitmap;
trackers
.FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
.ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// return the processed frame to the video
frame = outputFrame;
}
// or else just remember this frame for next iteration
else
{
previousFrame = frame.Clone() as Bitmap;
}
frameIndex++;
}
/// <summary>
/// Called when videoPlayer receives a new frame.
/// </summary>
/// <param name="sender"></param>
/// <param name="image"></param>
private void videoPlayer_NewFrame(object sender, ref Bitmap frame)
{
// use an rgb filter to remove everything but mario's outfit
var filter = new ColorFiltering(
new IntRange(220, 240),
new IntRange(200, 220),
new IntRange(160, 180)
);
var filteredFrame = filter.Apply(frame);
// convert the image to grayscale
var gray = new GrayscaleBT709();
var trackingFrame = gray.Apply(filteredFrame);
// use a threshold to make the image black & white
var threshold = new Threshold(1);
threshold.ApplyInPlace(trackingFrame);
// apply agressive dilation
var dilation = new BinaryDilation3x3();
dilation.ApplyInPlace(trackingFrame);
dilation.ApplyInPlace(trackingFrame);
dilation.ApplyInPlace(trackingFrame);
// use image to mask the original frame
var mask = new ApplyMask(trackingFrame);
var maskedFrame = mask.Apply(frame);
// is the camshift tracker still tracking mario?
// - the tracking object cannot be empty
// - the tracking rectangle has to be small
bool isTracking = tracker.TrackingObject?.IsEmpty == false &&
tracker.TrackingObject?.Rectangle.Width <= 50;
if (!isTracking)
{
// no - so do a blob search
var blobSearch = new BlobCounter();
blobSearch.FilterBlobs = true;
blobSearch.MinHeight = 25;
blobSearch.MinWidth = 25;
blobSearch.ProcessImage(trackingFrame);
if (blobSearch.ObjectsCount > 0)
{
// assume the first blog we find is mario
var rectangles = blobSearch.GetObjectsRectangles();
var rect = rectangles.First();
// use camshift to track mario from now on
var img = UnmanagedImage.FromManagedImage(maskedFrame);
tracker.SearchWindow = rect;
tracker.ProcessFrame(img);
}
}
else
{
// track mario using camshift
var img = UnmanagedImage.FromManagedImage(maskedFrame);
tracker.ProcessFrame(img);
// draw the reticle where mario is
var rect = tracker.TrackingObject.Rectangle;
rect.Inflate(30, 30);
DrawReticle(frame, rect);
}
// update pictureboxes
thresholdedBox.Image = trackingFrame;
maskedBox.Image = maskedFrame;
frameIndex++;
}
/// <summary>
/// Called when videoPlayer receives a new frame.
/// </summary>
/// <param name="sender"></param>
/// <param name="image"></param>
private void videoPlayer_NewFrame_1(object sender, ref Bitmap frame)
{
//if (cmb_fuente.SelectedIndex==1)
//{
// RotateBicubic filter = new RotateBicubic(90, true);
// frame = filter.Apply(frame);
//}
if (previousFrame != null)
{
// find the thresholded euclidian difference between two subsequent frames
//ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(thr);
threshold.OverlayImage = previousFrame;
var difference = threshold.Apply(frame);
// only keep big blobs
var filter = new BlobsFiltering();
filter.CoupledSizeFiltering = true;
filter.MinHeight = int.Parse(txt_tamanio2.Text);
filter.MinWidth = int.Parse(txt_tamanio2.Text);
filter.ApplyInPlace(difference);
//var sobl = new SobelEdgeDetector();
//sobl.ApplyInPlace(difference);
//erode image
var erode = new Erosion3x3();
for (int i = 0; i < int.Parse(txt_ers.Text); i++)
{
erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
}
// dilate remaining blobs
var dilate = new BinaryDilation3x3();
for (int i = 0; i < int.Parse(txt_dils.Text); i++)
{
dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
}
// put this image in the thresholded picturebox
thresholdedBox.Image = difference.Clone() as Bitmap;
// use this as a mask for the current frame
var mask = new ApplyMask(difference);
var maskedFrame = mask.Apply(frame);
// put this image in the masked picturebox
maskedBox.Image = maskedFrame.Clone() as Bitmap;
// now find all moving blobs
if (frameIndex % 10 == 0)
{
var counter = new BlobCounter();
counter.ProcessImage(difference);
// only keep blobs that:
// - do not overlap with known cars
// - do not overlap with other blobs
// - have crossed the middle of the frame
// - are at least 100 pixels tall
var blobs = counter.GetObjectsRectangles();
var newBlobs = from r in counter.GetObjectsRectangles()
where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r)) &&
!blobs.Any(b => b.IntersectsWith(r) && b != r) &&
r.Top >= 240 && r.Bottom <= 480 &&
r.Height >= int.Parse(txt_tamanio.Text)
select r;
// set up new camshift trackers for each detected blob
foreach (var rect in newBlobs)
{
trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
}
}
// now kill all car trackers that have expanded by too much
trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// and kill all trackers that have lived for 30 frames
//trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
trackers.RemoveAll(t => frameIndex - t.StartIndex > frames);
// let all remaining trackers process the current frame
var img = UnmanagedImage.FromManagedImage(maskedFrame);
trackers
.ForEach(t => t.Tracker.ProcessFrame(img));
// remember this frame for next iteration
previousFrame.Dispose();
previousFrame = frame.Clone() as Bitmap;
//escribir etiqueta para cada vehiculo
var outputFrame = frame.Clone() as Bitmap;
trackers
.FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
.ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// regresar frame procesado
frame = outputFrame;
}
else
{ // recordar para siguiente iteracion
previousFrame = frame.Clone() as Bitmap;
}
frameIndex++;
//if (previousFrame != null)
//{
// // find the thresholded euclidian difference between two subsequent frames
// ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
// threshold.OverlayImage = previousFrame;
// var difference = threshold.Apply(frame);
// // only keep big blobs
// var filter = new BlobsFiltering();
// filter.CoupledSizeFiltering = true;
// filter.MinHeight = 50;
// filter.MinWidth = 50;
// filter.ApplyInPlace(difference);
// // dilate remaining blobs
// var dilate = new BinaryDilation3x3();
// dilate.ApplyInPlace(difference);
// //dilate.ApplyInPlace(difference);
// //dilate.ApplyInPlace(difference);
// //dilate.ApplyInPlace(difference);
// // put this image in the thresholded picturebox
// thresholdedBox.Image = difference.Clone() as Bitmap;
// // use this as a mask for the current frame
// var mask = new ApplyMask(difference);
// var maskedFrame = mask.Apply(frame);
// // put this image in the masked picturebox
// maskedBox.Image = maskedFrame.Clone() as Bitmap;
// // now find all moving blobs
// if (frameIndex % 10 == 0)
// {
// var counter = new BlobCounter();
// counter.ProcessImage(difference);
// // only keep blobs that:
// // - do not overlap with known cars
// // - do not overlap with other blobs
// // - have crossed the middle of the frame
// // - are at least 100 pixels tall
// var blobs = counter.GetObjectsRectangles();
// var newBlobs = from r in counter.GetObjectsRectangles()
// where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r))
// && !blobs.Any(b => b.IntersectsWith(r) && b != r)
// && r.Top >= 240 && r.Bottom <= 480
// && r.Height >= 100
// select r;
// // set up new camshift trackers for each detected blob
// foreach (var rect in newBlobs)
// {
// trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
// }
// }
// // now kill all car trackers that have expanded by too much
// trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// // and kill all trackers that have lived for 30 frames
// trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
// // let all remaining trackers process the current frame
// var img = UnmanagedImage.FromManagedImage(maskedFrame);
// trackers
// .ForEach(t => t.Tracker.ProcessFrame(img));
// // remember this frame for next iteration
// previousFrame.Dispose();
// previousFrame = frame.Clone() as Bitmap;
// // draw labels on all tracked cars
// var outputFrame = frame.Clone() as Bitmap;
// trackers
// .FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
// .ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// // return the processed frame to the video
// frame = outputFrame;
//}
//// or else just remember this frame for next iteration
//else
// previousFrame = frame.Clone() as Bitmap;
//frameIndex++;
}
private void Cap_ImageGrabbed(object sender, EventArgs e)
{
try
{
Mat imagen = new Mat();
cap.Retrieve(imagen);
//pb_lprptzanalitica.Image = imagen.Bitmap;
Bitmap frame = new Bitmap(imagen.Bitmap);
//pb_ipcam.Image = frame.Clone() as Bitmap;
if (previousFrame != null)
{
// find the thresholded euclidian difference between two subsequent frames
//ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(thr);
threshold.OverlayImage = previousFrame;
var difference = threshold.Apply(frame.Clone() as Bitmap);
// only keep big blobs
var filter = new BlobsFiltering();
filter.CoupledSizeFiltering = true;
filter.MinHeight = int.Parse(txt_tamanio2.Text);
filter.MinWidth = int.Parse(txt_tamanio2.Text);
filter.ApplyInPlace(difference);
//var sobl = new SobelEdgeDetector();
//sobl.ApplyInPlace(difference);
//erode image
var erode = new Erosion3x3();
for (int i = 0; i < int.Parse(txt_ers.Text); i++)
{
erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
}
// dilate remaining blobs
var dilate = new BinaryDilation3x3();
for (int i = 0; i < int.Parse(txt_dils.Text); i++)
{
dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
}
// put this image in the thresholded picturebox
thresholdedBox.Image = difference.Clone() as Bitmap;
// use this as a mask for the current frame
var mask = new ApplyMask(difference);
var maskedFrame = mask.Apply(frame);
// put this image in the masked picturebox
maskedBox.Image = maskedFrame.Clone() as Bitmap;
// now find all moving blobs
if (frameIndex % 10 == 0)
{
var counter = new BlobCounter();
counter.ProcessImage(difference);
// only keep blobs that:
// - do not overlap with known cars
// - do not overlap with other blobs
// - have crossed the middle of the frame
// - are at least 100 pixels tall
var blobs = counter.GetObjectsRectangles();
var newBlobs = from r in counter.GetObjectsRectangles()
where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r)) &&
!blobs.Any(b => b.IntersectsWith(r) && b != r) &&
r.Top >= 240 && r.Bottom <= 480 &&
r.Height >= int.Parse(txt_tamanio.Text)
select r;
// set up new camshift trackers for each detected blob
foreach (var rect in newBlobs)
{
trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
}
}
// now kill all car trackers that have expanded by too much
trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// and kill all trackers that have lived for 30 frames
//trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
trackers.RemoveAll(t => frameIndex - t.StartIndex > frames);
// let all remaining trackers process the current frame
var img = UnmanagedImage.FromManagedImage(maskedFrame);
trackers
.ForEach(t => t.Tracker.ProcessFrame(img));
// remember this frame for next iteration
previousFrame.Dispose();
previousFrame = frame.Clone() as Bitmap;
//escribir etiqueta para cada vehiculo
var outputFrame = frame.Clone() as Bitmap;
trackers
.FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
.ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// regresar frame procesado
frame = outputFrame;
//pb_ipcam.Image = outputFrame;
pb_lprptzanalitica.Image = outputFrame;
}
else
{ // recordar para siguiente iteracion
previousFrame = frame.Clone() as Bitmap;
}
frameIndex++;
}
catch (Exception)
{
MessageBox.Show("Error al decodificar video de PTZ, LPR o ANALITICA");
}
}
private void Detection()
{
var watch = System.Diagnostics.Stopwatch.StartNew();
if (Video.Image != null)
{
if (ModeList.selectedIndex == 0)
{
training = 1;
int prev = AlphabetList.selectedIndex;
if (AlphabetList.selectedIndex == 26 || prev == 26)
{
label = 67;
}
else if (AlphabetList.selectedIndex == -1)
{
label = prev;
}
else
{
label = AlphabetList.selectedIndex;
}
}
else
{
training = 0;
}
ProgressBar.Visible = true;
ProgressBar.Value = 0;
ProgressBar.Maximum_Value = 9;
ProgressBar.Value += 1;
CapturedBox.Image = (Bitmap)Video.Image.Clone();
Bitmap src = new Bitmap(CapturedBox.Image);
//skin detection
var image = new Rectangle(0, 0, src.Width, src.Height);
var value = src.LockBits(image, ImageLockMode.ReadWrite, src.PixelFormat);
var size = Bitmap.GetPixelFormatSize(value.PixelFormat) / 8;
var buffer = new byte[value.Width * value.Height * size];
Marshal.Copy(value.Scan0, buffer, 0, buffer.Length);
System.Threading.Tasks.Parallel.Invoke(
() =>
{
Skin_process(buffer, 0, 0, value.Width / 2, value.Height / 2, value.Width, size);
},
() =>
{
Skin_process(buffer, 0, value.Height / 2, value.Width / 2, value.Height, value.Width, size);
},
() =>
{
Skin_process(buffer, value.Width / 2, 0, value.Width, value.Height / 2, value.Width, size);
},
() =>
{
Skin_process(buffer, value.Width / 2, value.Height / 2, value.Width, value.Height, value.Width, size);
}
);
Marshal.Copy(buffer, 0, value.Scan0, buffer.Length);
src.UnlockBits(value);
SkinBox.Image = src;
if (Skin == 1)
{
ProgressBar.Value += 1;
//Dilation & Erosion
src = Grayscale.CommonAlgorithms.BT709.Apply(src);
BinaryDilation3x3 dilatation = new BinaryDilation3x3();
BinaryErosion3x3 erosion = new BinaryErosion3x3();
for (int a = 1; a <= 10; a++)
{
src = dilatation.Apply(src);
}
for (int a = 1; a <= 10; a++)
{
src = erosion.Apply(src);
}
ProgressBar.Value += 1;
NoiseBox.Image = src;
//Blob
try
{
ExtractBiggestBlob blob = new ExtractBiggestBlob();
src = blob.Apply(src);
x = blob.BlobPosition.X;
y = blob.BlobPosition.Y;
ProgressBar.Value += 1;
}
catch
{
this.Show();
//MessageBox.Show("Lightning conditions are not good for detecting the gestures", "Bad Lights", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
//Merge
Bitmap srcImage = new Bitmap(CapturedBox.Image);
Bitmap dstImage = new Bitmap(src);
var srcrect = new Rectangle(0, 0, srcImage.Width, srcImage.Height);
var dstrect = new Rectangle(0, 0, dstImage.Width, dstImage.Height);
var srcdata = srcImage.LockBits(srcrect, ImageLockMode.ReadWrite, srcImage.PixelFormat);
var dstdata = dstImage.LockBits(dstrect, ImageLockMode.ReadWrite, dstImage.PixelFormat);
var srcdepth = Bitmap.GetPixelFormatSize(srcdata.PixelFormat) / 8;
var dstdepth = Bitmap.GetPixelFormatSize(dstdata.PixelFormat) / 8;
//bytes per pixel
var srcbuffer = new byte[srcdata.Width * srcdata.Height * srcdepth];
var dstbuffer = new byte[dstdata.Width * dstdata.Height * dstdepth];
//copy pixels to buffer
Marshal.Copy(srcdata.Scan0, srcbuffer, 0, srcbuffer.Length);
Marshal.Copy(dstdata.Scan0, dstbuffer, 0, dstbuffer.Length);
System.Threading.Tasks.Parallel.Invoke(
() =>
{
//upper-left
Merge_process(srcbuffer, dstbuffer, x, 0, y, 0, x + (dstdata.Width / 2), dstdata.Width / 2, y + (dstdata.Height / 2), dstdata.Height / 2, srcdata.Width, dstdata.Width, srcdepth, dstdepth);
},
() =>
{
//upper-right
Merge_process(srcbuffer, dstbuffer, x + (dstdata.Width / 2), dstdata.Width / 2, y, 0, x + (dstdata.Width), dstdata.Width, y + (dstdata.Height / 2), dstdata.Height / 2, srcdata.Width, dstdata.Width, srcdepth, dstdepth);
},
() =>
{
//lower-left
Merge_process(srcbuffer, dstbuffer, x, 0, y + (dstdata.Height / 2), dstdata.Height / 2, x + (dstdata.Width / 2), dstdata.Width / 2, y + (dstdata.Height), dstdata.Height, srcdata.Width, dstdata.Width, srcdepth, dstdepth);
},
() =>
{
//lower-right
Merge_process(srcbuffer, dstbuffer, x + (dstdata.Width / 2), dstdata.Width / 2, y + (dstdata.Height / 2), dstdata.Height / 2, x + (dstdata.Width), dstdata.Width, y + (dstdata.Height), dstdata.Height, srcdata.Width, dstdata.Width, srcdepth, dstdepth);
}
);
//Copy the buffer back to image
Marshal.Copy(srcbuffer, 0, srcdata.Scan0, srcbuffer.Length);
Marshal.Copy(dstbuffer, 0, dstdata.Scan0, dstbuffer.Length);
srcImage.UnlockBits(srcdata);
dstImage.UnlockBits(dstdata);
src = dstImage;
ProgressBar.Value += 1;
CropBox.Image = src;
//Resize
ResizeBilinear resize = new ResizeBilinear(200, 200);
src = resize.Apply(src);
ProgressBar.Value += 1;
//Edges
src = Grayscale.CommonAlgorithms.BT709.Apply((Bitmap)src);
SobelEdgeDetector edges = new SobelEdgeDetector();
src = edges.Apply(src);
ProgressBar.Value += 1;
EdgeDetectorBox.Image = src;
//HOEF
Bitmap block = new Bitmap(src);
int[] edgescount = new int[50];
double[] norm = new double[200];
String text = null;
int sum = 0;
int z = 1;
for (int p = 1; p <= 6; p++)
{
for (int q = 1; q <= 6; q++)
{
for (int x = (p - 1) * block.Width / 6; x < (p * block.Width / 6); x++)
{
for (int y = (q - 1) * block.Height / 6; y < (q * block.Height / 6); y++)
{
Color colorPixel = block.GetPixel(x, y);
int r = colorPixel.R;
int g = colorPixel.G;
int b = colorPixel.B;
if (r != 0 & g != 0 & b != 0)
{
edgescount[z]++;
}
}
}
z++;
}
}
for (z = 1; z <= 36; z++)
{
sum = sum + edgescount[z];
}
for (z = 1; z <= 36; z++)
{
norm[z] = (double)edgescount[z] / sum;
text = text + " " + z.ToString() + ":" + norm[z].ToString();
}
if (training == 1)
{
File.AppendAllText(@"D:\train.txt", label.ToString() + text + Environment.NewLine);
ProgressBar.Value += 1;
}
else
{
File.WriteAllText(@"D:\test.txt", label.ToString() + text + Environment.NewLine);
ProgressBar.Value += 1;
//SVM
Problem train = Problem.Read(@"D:\train.txt");
Problem test = Problem.Read(@"D:\test.txt");
Parameter parameter = new Parameter()
{
C = 32,
Gamma = 8
};
Model model = Training.Train(train, parameter);
Prediction.Predict(test, @"D:\result.txt", model, false);
int value1 = Convert.ToInt32(File.ReadAllText(@"D:\result.txt"));
String alphabet = null;
if (value1 == 27)
{
alphabet += "Welcome ";
}
else if (value1 == 28)
{
alphabet += "Good Morning";
}
else if (value1 == 29)
{
alphabet += "Thank You";
}
else
{
alphabet += (char)(65 + value1);
}
OutputText.Text = alphabet;
SpeechSynthesizer speechSynthesizer = new SpeechSynthesizer();
speechSynthesizer.SetOutputToDefaultAudioDevice();
speechSynthesizer.Volume = 100;
speechSynthesizer.Rate = -2;
speechSynthesizer.SelectVoiceByHints(VoiceGender.Female, VoiceAge.Child);
speechSynthesizer.SpeakAsync(alphabet);
if (alphabet == " ")
{
speechSynthesizer.SpeakAsync(OutputText.Text);
}
ProgressBar.Value += 1;
}
}
else
{
this.Show();
}
watch.Stop();
var time = (watch.ElapsedMilliseconds);
float secs = (float)time / 1000;
ExecutionTimeBox.Text = Convert.ToString(secs) + " " + "Seconds";
}
}
