本文整理汇总了C#中Image.Not方法的典型用法代码示例。如果您正苦于以下问题：C# Image.Not方法的具体用法？C# Image.Not怎么用？C# Image.Not使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Image的用法示例。
在下文中一共展示了Image.Not方法的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: GetTheBestNoteExtraction
public static Bitmap GetTheBestNoteExtraction(Bitmap bmp1, Bitmap bmp2)
{
lock (sync)
{
Image<Gray, byte> extraction_1 = new Image<Gray, byte>(bmp1);
Image<Gray, byte> extraction_2 = new Image<Gray, byte>(bmp2);
Image<Gray, byte> dif = extraction_1.AbsDiff(extraction_2);
extraction_1 = extraction_1.Not();
Gray sum_1 = extraction_1.GetSum();
extraction_2 = extraction_2.Not();
Gray sum_2 = extraction_2.GetSum();
Gray sum_dif = dif.GetSum();
Bitmap big = sum_1.Intensity >= sum_2.Intensity ? bmp1 : bmp2;
Bitmap small = sum_1.Intensity < sum_2.Intensity ? bmp1 : bmp2;
Gray bigSum = sum_1.Intensity >= sum_2.Intensity ? sum_1 : sum_2;
Gray smallSum = sum_1.Intensity < sum_2.Intensity ? sum_1 : sum_2;
if (smallSum.Intensity == 0)
{
return big;
}
else
{
if (sum_dif.Intensity / smallSum.Intensity > 0.3)
{
return small;
}
else
{
return big;
}
}
}
}示例2: GetMoving
public Image<Bgr, Byte> GetMoving(Image<Bgr, Byte> source)
{
//var sub = currentImage.AbsDiff(_prevImage).Convert<Gray, Byte>();
var difference = MovingDetection(source).Convert<Gray, Byte>();
_prevImage = source.Copy();
difference = difference.ThresholdBinary(new Gray(50), new Gray(255));
var distTransformed = new Image<Gray, float>(source.Width, source.Height);
CvInvoke.cvDistTransform(difference.Ptr, distTransformed.Ptr, DIST_TYPE.CV_DIST_L2, 3, new[] { 1f, 1f }, IntPtr.Zero);
var byteDist = distTransformed.ThresholdBinary(new Gray(2), new Gray(255)).Convert<Gray, byte>();
Image<Gray, byte> mask = new Image<Gray, byte>(byteDist.Width + 2, byteDist.Height + 2);
mask.ROI = new Rectangle(1, 1, byteDist.Width, byteDist.Height);
CvInvoke.cvCopy(byteDist, mask, IntPtr.Zero);
mask.ROI = new Rectangle(0, 0, byteDist.Width + 2, byteDist.Height + 2);
mask = mask.Not();
//return mask.Convert<Bgr, Byte>();
var result = mask.Convert<Bgr, Byte>();
for (int i = 0; i < difference.Width; i++)
{
for (int j = 0; j < difference.Height; j++)
{
if (mask.Data[j, i, 0] == 0)
{
var comp = new MCvConnectedComp();
CvInvoke.cvFloodFill(
difference.Ptr,
new Point(i, j),
new MCvScalar(200, 200, 200, 0), // Color
new MCvScalar(0, 0, 0), // Lo
new MCvScalar(0, 0, 0), // Up
out comp,
Emgu.CV.CvEnum.CONNECTIVITY.EIGHT_CONNECTED,
Emgu.CV.CvEnum.FLOODFILL_FLAG.DEFAULT,
mask.Ptr
);
if (comp.area > 500 && comp.area < 2500
&& comp.rect.Size.Height > 10 && comp.rect.Size.Height < 230
&& comp.rect.Size.Width > 10 && comp.rect.Size.Width < 230)
{
ReplaceColors(result, comp.rect);
}
}
}
}
return result.Convert<Bgr, Byte>();
}示例3: InvertColors
public static Bitmap InvertColors(Bitmap srcimg)
{
using (Image<Gray, byte> img = new Image<Gray, byte>(srcimg))
{ return img.Not().ToBitmap(); }
}示例4: MainLoop
private void MainLoop()
{
CurrentFrame = Cam.QueryFrame().Convert<Hsv, byte>();
Image<Gray, byte>[] channels;
Image<Gray, byte> HistImg1 = new Image<Gray, byte>(500, 500);
Image<Gray, byte> HistImg2 = new Image<Gray, byte>(500, 500);
Image<Gray, byte> ProbImage;
DenseHistogram hist1 = new DenseHistogram(new int[] { 10, 10 }, new RangeF[] { new RangeF(0, 255), new RangeF(0, 255) });
DenseHistogram hist2 = new DenseHistogram(new int[] { 10, 10 }, new RangeF[] { new RangeF(0, 255), new RangeF(0, 255) });
MCvConnectedComp comp;
MCvTermCriteria criteria = new MCvTermCriteria(10, 1);
MCvBox2D box;
while (true)
{
CurrentFrame = Cam.QueryFrame().Convert<Hsv, byte>();
if (OnSettingArea && TrackArea != Rectangle.Empty)
{
CurrentFrame.ROI = TrackArea;
channels = CurrentFrame.Split();
hist1.Calculate(new Image<Gray, byte>[] { channels[0], channels[1] }, false, null);
CurrentFrame.Not().CopyTo(CurrentFrame);
CurrentFrame.ROI = Rectangle.Empty;
CurrentFrame.Draw(TrackArea, new Hsv(100, 100, 100), 2);
imageBox1.Image = CurrentFrame;
}
else
{
if (TrackArea != Rectangle.Empty)
{
channels = CurrentFrame.Split();
ProbImage = hist1.BackProject<byte>(new Image<Gray, byte>[] { channels[0], channels[1] });
imageBox_Hist2.Image = ProbImage.Convert<Gray, byte>();
lock (LockObject)
{
if (TrackArea.Height * TrackArea.Width > 0)
{
CvInvoke.cvCamShift(ProbImage, TrackArea, criteria, out comp, out box);
TrackArea = comp.rect;
CurrentFrame.Draw(box, new Hsv(100, 100, 100), 2);
}
/**
ResetContourPoints();
for (int i = 0; i < 60; i++)
{
ProbImage.Snake(ContourPoints, (float)1.0, (float)0.5, (float)1.5, new Size(17, 17), criteria, true);
}
CurrentFrame.DrawPolyline(ContourPoints, true, new Hsv(100, 100, 100), 2);
*/
}
}
imageBox1.Image = CurrentFrame;
//calculate histogram;
//channels = CurrentFrame.Split();
//hist2.Calculate(new Image<Gray, byte>[] { channels[0], channels[1] }, false, null);
//hist2.Normalize(1);
//HistImg1.SetZero();
//DrawHist2D(HistImg1, hist1);
//imageBox_Hist1.Image = HistImg1;
}
}
}示例5: TestSub
public void TestSub()
{
Image<Bgr, Byte> img = new Image<Bgr, Byte>(101, 133);
Image<Bgr, Byte> r1 = img.Not();
Image<Bgr, Byte> r2 = 255 - img;
EmguAssert.IsTrue(r1.Equals(r2));
Image<Bgr, Byte> img2 = img - 10;
}示例6: TestInplaceNot
public void TestInplaceNot()
{
if (CudaInvoke.HasCuda)
{
Image<Bgr, Byte> img = new Image<Bgr, byte>(300, 400);
CudaImage<Bgr, Byte> gpuMat = new CudaImage<Bgr, byte>(img);
CudaInvoke.BitwiseNot(gpuMat, gpuMat, null, null);
Assert.IsTrue(gpuMat.Equals(new CudaImage<Bgr, Byte>(img.Not())));
}
}示例7: GetMovingEvents
public List<Event> GetMovingEvents(Image<Bgr, Byte> source)
{
var events = new List<Event>();
var difference = MovingDetection(source).Convert<Gray, Byte>();
_prevImage = source.Copy();
difference = difference.ThresholdBinary(new Gray(80), new Gray(255));
var distTransformed = new Image<Gray, float>(source.Width, source.Height);
CvInvoke.cvDistTransform(difference.Ptr, distTransformed.Ptr, DIST_TYPE.CV_DIST_L2, 3, new[] { 1f, 1f }, IntPtr.Zero);
var byteDist = distTransformed.ThresholdBinary(new Gray(1), new Gray(255)).Convert<Gray, byte>();
Image<Gray, byte> mask = new Image<Gray, byte>(byteDist.Width + 2, byteDist.Height + 2);
mask.ROI = new Rectangle(1, 1, byteDist.Width, byteDist.Height);
CvInvoke.cvCopy(byteDist, mask, IntPtr.Zero);
mask.ROI = new Rectangle(0, 0, byteDist.Width + 2, byteDist.Height + 2);
mask = mask.Not();
//return mask.Convert<Bgr, Byte>();
var result = difference.Convert<Bgr, Byte>();
for (int i = 0; i < difference.Width; i++)
{
for (int j = 0; j < difference.Height; j++)
{
if (mask.Data[j, i, 0] == 0)
{
var comp = new MCvConnectedComp();
CvInvoke.cvFloodFill(
difference.Ptr,
new Point(i, j),
new MCvScalar(200, 200, 200, 0), // Color
new MCvScalar(0, 0, 0), // Lo
new MCvScalar(0, 0, 0), // Up
out comp,
Emgu.CV.CvEnum.CONNECTIVITY.EIGHT_CONNECTED,
Emgu.CV.CvEnum.FLOODFILL_FLAG.DEFAULT,
mask.Ptr
);
if (comp.area > 500 && comp.area < 2500
&& comp.rect.Size.Height > 10 && comp.rect.Size.Height < 230
&& comp.rect.Size.Width > 10 && comp.rect.Size.Width < 230
&& BlobDetector.IsAreaColorMousable(comp, source, mask))
{
events.Add(new Event(comp.rect, Event.EventType.SomethingIsMoving));
}
}
}
}
return events.Count > 3 ? new List<Event>() : events;
}示例8: ProcessImage
public Image<Bgr, byte> ProcessImage(Image<Bgr, byte> img)
{
//return ProcessImageHough(img);
var inputImage = img.Clone();
_bg.Update(img);
img = _bg.BackgroundMask.Convert<Bgr, Byte>();
_a.OnFrameUpdated(img);
img = img.Erode(1);
img = img.Dilate(1);
_b.OnFrameUpdated(img);
//img.SmoothBlur(3, 3);
img = FillBlobs(img);
//DrawBlobs(img);
_c.OnFrameUpdated(img);
//use image as mask to display original image
var temp = inputImage.Sub(img);
_d.OnFrameUpdated(temp);
//float[] BlueHist = GetHistogramData(img[0]);
//Image<Bgr, byte> image = new Image<Bgr, byte>(img.Width, img.Height);
//for (int i = 0; i < BlueHist.Length; i++)
//{
// image.Draw(new LineSegment2D(new Point(i, (int)BlueHist[i]), new Point(i, 0)), new Bgr(Color.Red), 1);
//}
//_e.OnFrameUpdated(image);
//only display skin
img = img.Not();
//img = DetectSkin(img);
//img = img.Erode(2);
//img = img.Dilate(2);
//img = img.Not();
//DrawHoughLines(img);
_e.OnFrameUpdated(ProcessImageLinearOptimization(img));
//img.MorphologyEx()
//List<Contour<Point>> allContours;
//var contours = DetectBlobs(img.Convert<Gray, byte>(), out allContours);
//Image<Bgr, byte> image = new Image<Bgr, byte>(img.Width, img.Height, new Bgr(Color.White));
//if (allContours != null)
//{
// foreach (Contour<Point> contour in allContours.Take(3))
// {
// var convexityDefact = contour.GetConvexityDefacts(new MemStorage(), Emgu.CV.CvEnum.ORIENTATION.CV_CLOCKWISE);
// foreach (MCvConvexityDefect mCvConvexityDefect in convexityDefact)
// {
// PointF startPoint = new PointF(mCvConvexityDefect.StartPoint.X, mCvConvexityDefect.StartPoint.Y);
// CircleF startCircle = new CircleF(startPoint, 5f);
// image.Draw(startCircle, new Bgr(Color.Red), 5);
// }
// Draw(image, contour, false);
// //Draw(image, contour, true);
// }
//}
//_a.OnFrameUpdated(image);
return img;
}示例9: TestSub
public void TestSub()
{
Image<Bgr, Byte> img = new Image<Bgr, Byte>(101, 133);
Assert.IsTrue(img.Not().Equals(255 - img));
Image<Bgr, Byte> img2 = img - 10;
}