| public static Round ( RectangleF value ) : Rectangle | ||
| value | RectangleF | |
| return | Rectangle | |
private void btnImgsrch_Click(object sender, RoutedEventArgs e)
{
IntPtr findwindow = FindWindow(null, AppName);
if (findwindow != IntPtr.Zero)
{
//플레이어를 찾았을 경우
lblState.Content = "찾았습니다.";
//찾은 플레이어를 바탕으로 Graphics 정보를 가져옵니다.
Graphics Graphicsdata = Graphics.FromHwnd(findwindow);
//찾은 플레이어 창 크기 및 위치를 가져옵니다.
Rectangle rect = Rectangle.Round(Graphicsdata.VisibleClipBounds);
//플레이어 창 크기 만큼의 비트맵을 선언해줍니다.
Bitmap bmp = new Bitmap(rect.Width, rect.Height);
//비트맵을 바탕으로 그래픽스 함수로 선언해줍니다.
using (Graphics g = Graphics.FromImage(bmp))
{
//찾은 플레이어의 크기만큼 화면을 캡쳐합니다.
IntPtr hdc = g.GetHdc();
PrintWindow(findwindow, hdc, 0x2);
g.ReleaseHdc(hdc);
}
// pictureBox1 이미지를 표시해줍니다.
printImg(bmp, imgPrint);
printImg(srcImg, imgSrcPrint);
searchIMG(bmp, srcImg);
}
}
public static void DrawRound(this Graphics graphics, Color color, Rectangle rectangle, int curve)
{
using (var pen = new Pen(color))
using (GraphicsPath graphicsPath = rectangle.Round(curve))
graphics.DrawPath(pen, graphicsPath);
}
public static void FillRoundGradient(this Graphics graphics, Color color1, Color color2, Rectangle rectangle, float angle, int curve)
{
using (var linearGradientBrush = new LinearGradientBrush(rectangle, color1, color2, angle))
using (GraphicsPath graphicsPath = rectangle.Round(curve))
graphics.FillPath(linearGradientBrush, graphicsPath);
}
public static void FillRound(this Graphics graphics, Color color, Rectangle rectangle, int curve)
{
using (var solidBrush = new SolidBrush(color))
using (GraphicsPath graphicsPath = rectangle.Round(curve))
graphics.FillPath(solidBrush, graphicsPath);
}
public DnnPage()
: base()
{
var button = this.GetButton();
button.Text = "Perform Mask-rcnn Detection";
button.Clicked += OnButtonClicked;
OnImagesLoaded += async(sender, image) =>
{
if (image == null || image[0] == null)
{
return;
}
SetMessage("Please wait...");
SetImage(null);
Task <Tuple <Mat, String, long> > t = new Task <Tuple <Mat, String, long> >(
() =>
{
InitDetector();
String msg = String.Empty;
using (Mat blob = DnnInvoke.BlobFromImage(image[0]))
using (VectorOfMat tensors = new VectorOfMat())
{
_maskRcnnDetector.SetInput(blob, "image_tensor");
Stopwatch watch = Stopwatch.StartNew();
_maskRcnnDetector.Forward(tensors, new string[] { "detection_out_final", "detection_masks" });
watch.Stop();
msg = String.Format("Mask RCNN inception completed in {0} milliseconds.",
watch.ElapsedMilliseconds);
using (Mat boxes = tensors[0])
using (Mat masks = tensors[1])
{
System.Drawing.Size imgSize = image[0].Size;
float[,,,] boxesData = boxes.GetData(true) as float[, , , ];
int numDetections = boxesData.GetLength(2);
for (int i = 0; i < numDetections; i++)
{
float score = boxesData[0, 0, i, 2];
if (score > 0.5)
{
int classId = (int)boxesData[0, 0, i, 1];
String label = _labels[classId];
MCvScalar color = _colors[classId];
float left = boxesData[0, 0, i, 3] * imgSize.Width;
float top = boxesData[0, 0, i, 4] * imgSize.Height;
float right = boxesData[0, 0, i, 5] * imgSize.Width;
float bottom = boxesData[0, 0, i, 6] * imgSize.Height;
RectangleF rectF = new RectangleF(left, top, right - left, bottom - top);
Rectangle rect = Rectangle.Round(rectF);
rect.Intersect(new Rectangle(Point.Empty, imgSize));
CvInvoke.Rectangle(image[0], rect, new MCvScalar(0, 0, 0, 0), 1);
CvInvoke.PutText(image[0], label, rect.Location, FontFace.HersheyComplex, 1.0,
new MCvScalar(0, 0, 255), 2);
int[] masksDim = masks.SizeOfDimension;
using (Mat mask = new Mat(
masksDim[2],
masksDim[3],
DepthType.Cv32F,
1,
masks.GetDataPointer(i, classId),
masksDim[3] * masks.ElementSize))
using (Mat maskLarge = new Mat())
using (Mat maskLargeInv = new Mat())
using (Mat subRegion = new Mat(image[0], rect))
using (Mat largeColor = new Mat(subRegion.Size, Emgu.CV.CvEnum.DepthType.Cv8U, 3))
{
CvInvoke.Resize(mask, maskLarge, rect.Size);
//give the mask at least 30% transparency
using (ScalarArray sa = new ScalarArray(0.7))
CvInvoke.Min(sa, maskLarge, maskLarge);
//Create the inverse mask for the original image
using (ScalarArray sa = new ScalarArray(1.0))
CvInvoke.Subtract(sa, maskLarge, maskLargeInv);
//The mask color
largeColor.SetTo(color);
if (subRegion.NumberOfChannels == 4)
{
using (Mat bgrSubRegion = new Mat())
{
CvInvoke.CvtColor(subRegion, bgrSubRegion, ColorConversion.Bgra2Bgr);
CvInvoke.BlendLinear(largeColor, bgrSubRegion, maskLarge, maskLargeInv, bgrSubRegion);
CvInvoke.CvtColor(bgrSubRegion, subRegion, ColorConversion.Bgr2Bgra);
}
}
else
{
CvInvoke.BlendLinear(largeColor, subRegion, maskLarge, maskLargeInv, subRegion);
}
}
}
}
}
}
long time = 0;
return(new Tuple <Mat, String, long>(image[0], msg, time));
});
t.Start();
var result = await t;
SetImage(t.Result.Item1);
//String computeDevice = CvInvoke.UseOpenCL ? "OpenCL: " + Ocl.Device.Default.Name : "CPU";
SetMessage(t.Result.Item2);
};
}
//백그라운드 워커가 실행하는 작업
//DoWork 이벤트 처리 메소드에서 lstNumber.Items.Add(i) 와 같은 코드를
//직접 실행시키면 "InvalidOperationException" 오류발생
private void myThread_DoWork(object sender, DoWorkEventArgs e)
{
//int count = (int)e.Argument;
int i = 0;
int prevKeyState = 0;
string str;
int count = 0;
RECT cRect, wRect;
int appPointX;
int appPointY;
int appSizeWidth;
int appSizeHeight;
bool b = false;
while (!myThread.CancellationPending)
{
if (GetAsyncKeyState(69) > 1 && prevKeyState <= 1)
{
//if (b) b = false;
//else b = true;
b = true;
}
if (b && tglRun.IsOn)
{
IntPtr hWnd = FindWindow(null, AppName);
if (hWnd != IntPtr.Zero)
{
GetClientRect(hWnd, out cRect);
GetWindowRect(hWnd, out wRect);
appPointX = wRect.left + (wRect.right - wRect.left - cRect.right) / 2;
appPointY = wRect.bottom - cRect.bottom - (wRect.right - wRect.left - cRect.right) / 2;
appSizeWidth = cRect.right;
appSizeHeight = cRect.bottom;
using (Bitmap bmp = new Bitmap(55, 55, PixelFormat.Format32bppArgb))
using (Graphics gr = Graphics.FromImage(bmp))
{
gr.CopyFromScreen(appPointX + 825, appPointY + 970, 0, 0, bmp.Size);
//printImg(bmp, imgSpeed);
using (Mat ScreenMat = OpenCvSharp.Extensions.BitmapConverter.ToMat(bmp))
using (Mat FindMat = OpenCvSharp.Extensions.BitmapConverter.ToMat(srcImg))
using (Mat FindMat2 = OpenCvSharp.Extensions.BitmapConverter.ToMat(srcImg2))
using (Mat res = ScreenMat.MatchTemplate(FindMat, TemplateMatchModes.CCoeffNormed))
using (Mat res2 = ScreenMat.MatchTemplate(FindMat2, TemplateMatchModes.CCoeffNormed))
{
double minval, maxval = 0;
double minval2, maxval2 = 0;
OpenCvSharp.Point minloc, maxloc;
OpenCvSharp.Point minloc2, maxloc2;
Cv2.MinMaxLoc(res, out minval, out maxval, out minloc, out maxloc);
Cv2.MinMaxLoc(res2, out minval2, out maxval2, out minloc2, out maxloc2);
if (maxval2 > 0.90)
{
//찾을때 이벤트
if (sp.IsOpen)
{
sp.Write("KDw");
Thread.Sleep(10);
sp.Write("KUw");
}
}
if (maxval > 0.90)
{
//찾을때 이벤트
if (sp.IsOpen)
{
sp.Write("KDw");
Thread.Sleep(10);
sp.Write("KUw");
b = false;
}
}
}
}
}
}
this.Dispatcher.BeginInvoke(DispatcherPriority.Normal,
(ThreadStart) delegate()
{
if (b)
{
lblResult.Content = "실행중";
lblResult.Foreground = System.Windows.Media.Brushes.Blue;
}
else
{
lblResult.Content = "정지중";
lblResult.Foreground = System.Windows.Media.Brushes.Red;
}
});
if (GetAsyncKeyState(121) > 1 && prevKeyState <= 1 && false)
{
string strpos = "";
count++;
IntPtr hWnd = FindWindow(null, (string)e.Argument);
if (hWnd != IntPtr.Zero)
{
GetClientRect(hWnd, out cRect);
GetWindowRect(hWnd, out wRect);
appPointX = wRect.left + (wRect.right - wRect.left - cRect.right) / 2;
appPointY = wRect.bottom - cRect.bottom - (wRect.right - wRect.left - cRect.right) / 2;
appSizeWidth = cRect.right;
appSizeHeight = cRect.bottom;
strpos += "cRect.left : " + cRect.left + "\n";
strpos += "cRect.right : " + cRect.right + "\n";
strpos += "cRect.top : " + cRect.top + "\n";
strpos += "cRect.bottom : " + cRect.bottom + "\n\n";
strpos += "wRect.left : " + wRect.left + "\n";
strpos += "wRect.right : " + wRect.right + "\n";
strpos += "wRect.top : " + wRect.top + "\n";
strpos += "wRect.bottom : " + wRect.bottom + "\n\n";
strpos += "appPointX : " + appPointX + "\n";
strpos += "appPointY : " + appPointY + "\n";
strpos += "appSizeWidth : " + appSizeWidth + "\n";
strpos += "appSizeHeight : " + appSizeHeight + "\n";
//플레이어를 찾았을 경우
this.Dispatcher.BeginInvoke(DispatcherPriority.Normal,
(ThreadStart) delegate()
{
lblPos.Content = strpos;
IntPtr findwindow = FindWindow(null, AppName);
if (findwindow != IntPtr.Zero)
{
//플레이어를 찾았을 경우
lblState.Content = "찾았습니다.";
//찾은 플레이어를 바탕으로 Graphics 정보를 가져옵니다.
Graphics Graphicsdata = Graphics.FromHwnd(findwindow);
//찾은 플레이어 창 크기 및 위치를 가져옵니다.
Rectangle rect = Rectangle.Round(Graphicsdata.VisibleClipBounds);
//플레이어 창 크기 만큼의 비트맵을 선언해줍니다.
Bitmap bmp = new Bitmap(rect.Width, rect.Height);
//비트맵을 바탕으로 그래픽스 함수로 선언해줍니다.
using (Graphics g = Graphics.FromImage(bmp))
{
//찾은 플레이어의 크기만큼 화면을 캡쳐합니다.
IntPtr hdc = g.GetHdc();
PrintWindow(findwindow, hdc, 0x2);
g.ReleaseHdc(hdc);
}
// pictureBox1 이미지를 표시해줍니다.
printImg(bmp, imgPrint);
printImg(srcImg, imgSrcPrint);
searchIMG(bmp, srcImg);
}
});
}
else
{
//플레이어를 못찾을경우
this.Dispatcher.BeginInvoke(DispatcherPriority.Normal,
(ThreadStart) delegate()
{
lblState.Content = "못찾았어요";
});
}
}
prevKeyState = GetAsyncKeyState(69);
str = i++ + "\n정지신호 : " + myThread.CancellationPending.ToString() + "\nF9 상태 : " + GetAsyncKeyState(121).ToString() + "\ncount : " + count.ToString();
this.Dispatcher.BeginInvoke(DispatcherPriority.Normal,
(ThreadStart) delegate()
{
lblState.Content = str;
});
Thread.Sleep(50);
}
e.Cancel = true;
}
public DnnPage()
: base()
{
var button = this.GetButton();
button.Text = "Perform Mask-rcnn Detection";
button.Clicked += OnButtonClicked;
OnImagesLoaded += async(sender, image) =>
{
if (image == null || image[0] == null)
{
return;
}
SetMessage("Please wait...");
SetImage(null);
Task <Tuple <Mat, String, long> > t = new Task <Tuple <Mat, String, long> >(
() =>
{
String configFile = "mask_rcnn_inception_v2_coco_2018_01_28.pbtxt";
#if __ANDROID__
String path = System.IO.Path.Combine(Android.OS.Environment.ExternalStorageDirectory.AbsolutePath,
Android.OS.Environment.DirectoryDownloads, "dnn_data");
FileInfo configFileInfo = AndroidFileAsset.WritePermanantFileAsset(Android.App.Application.Context, configFile, "dnn_data", AndroidFileAsset.OverwriteMethod.AlwaysOverwrite);
configFile = configFileInfo.FullName;
#else
String path = "./dnn_data/";
#endif
String graphFile = DnnDownloadFile(path, "frozen_inference_graph.pb");
String lookupFile = DnnDownloadFile(path, "coco-labels-paper.txt");
string[] labels = File.ReadAllLines(lookupFile);
Emgu.CV.Dnn.Net net = Emgu.CV.Dnn.DnnInvoke.ReadNetFromTensorflow(graphFile, configFile);
Mat blob = DnnInvoke.BlobFromImage(image[0]);
net.SetInput(blob, "image_tensor");
using (VectorOfMat tensors = new VectorOfMat())
{
net.Forward(tensors, new string[] { "detection_out_final", "detection_masks" });
using (Mat boxes = tensors[0])
using (Mat masks = tensors[1])
{
System.Drawing.Size imgSize = image[0].Size;
float[,,,] boxesData = boxes.GetData(true) as float[, , , ];
//float[,,,] masksData = masks.GetData(true) as float[,,,];
int numDetections = boxesData.GetLength(2);
for (int i = 0; i < numDetections; i++)
{
float score = boxesData[0, 0, i, 2];
if (score > 0.5)
{
int classId = (int)boxesData[0, 0, i, 1];
String label = labels[classId];
float left = boxesData[0, 0, i, 3] * imgSize.Width;
float top = boxesData[0, 0, i, 4] * imgSize.Height;
float right = boxesData[0, 0, i, 5] * imgSize.Width;
float bottom = boxesData[0, 0, i, 6] * imgSize.Height;
RectangleF rectF = new RectangleF(left, top, right - left, bottom - top);
Rectangle rect = Rectangle.Round(rectF);
rect.Intersect(new Rectangle(Point.Empty, imgSize));
CvInvoke.Rectangle(image[0], rect, new MCvScalar(0, 0, 0, 0), 1);
CvInvoke.PutText(image[0], label, rect.Location, FontFace.HersheyComplex, 1.0,
new MCvScalar(0, 0, 255), 2);
int[] masksDim = masks.SizeOfDimension;
using (Mat mask = new Mat(
masksDim[2],
masksDim[3],
DepthType.Cv32F,
1,
//masks.DataPointer +
//(i * masksDim[1] + classId )
//* masksDim[2] * masksDim[3] * masks.ElementSize,
masks.GetDataPointer(i, classId),
masksDim[3] * masks.ElementSize))
using (Mat maskLarge = new Mat())
using (Mat maskLargeInv = new Mat())
using (Mat subRegion = new Mat(image[0], rect))
using (Mat largeColor = new Mat(subRegion.Size, Emgu.CV.CvEnum.DepthType.Cv8U, 3))
{
CvInvoke.Resize(mask, maskLarge, rect.Size);
//give the mask at least 30% transparency
using (ScalarArray sa = new ScalarArray(0.7))
CvInvoke.Min(sa, maskLarge, maskLarge);
//Create the inverse mask for the original image
using (ScalarArray sa = new ScalarArray(1.0))
CvInvoke.Subtract(sa, maskLarge, maskLargeInv);
//The mask color
largeColor.SetTo(new Emgu.CV.Structure.MCvScalar(255, 0, 0));
if (subRegion.NumberOfChannels == 4)
{
using (Mat bgrSubRegion = new Mat())
{
CvInvoke.CvtColor(subRegion, bgrSubRegion, ColorConversion.Bgra2Bgr);
CvInvoke.BlendLinear(largeColor, bgrSubRegion, maskLarge, maskLargeInv, bgrSubRegion);
CvInvoke.CvtColor(bgrSubRegion, subRegion, ColorConversion.Bgr2Bgra);
}
}
else
{
CvInvoke.BlendLinear(largeColor, subRegion, maskLarge, maskLargeInv, subRegion);
}
}
}
}
}
}
long time = 0;
return(new Tuple <Mat, String, long>(image[0], null, time));
});
t.Start();
var result = await t;
SetImage(t.Result.Item1);
String computeDevice = CvInvoke.UseOpenCL ? "OpenCL: " + Ocl.Device.Default.Name : "CPU";
SetMessage(t.Result.Item2);
};
}
