// Update is called once per frame
void Update()
{
cap.Read(frame);
if (!frame.Empty())
{
//assume this part of the frame contains only background
smoothed_img = frame.Blur(new Size(5, 5));
frame_hsv = frame.CvtColor(ColorConversionCodes.BGR2HSV);
Scalar lb = new Scalar(0, 0, 50);
Scalar ub = new Scalar(180, 70, 180);
Mat disc = Cv2.GetStructuringElement(MorphShapes.Ellipse, new Size(7, 7));
Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, disc, null, 3);
contours = Cv2.FindContoursAsMat(thresh, RetrievalModes.List, ContourApproximationModes.ApproxSimple);
mask = new Mat(thresh.Size(), thresh.Type(), Scalar.All(0));
Cv2.Merge(new Mat[] { mask, mask, mask }, mask);
Cv2.BitwiseAnd(mask, frame, mask);
//Cv2.Merge(new Mat[]{frame_backproj,frame_backproj,frame_backproj},frame_backproj);
tex.LoadImage(smoothed_img.ToBytes(".png", new int[] { 0 }));
}
}
public Mat Detect(Mat input)
{
var canny = input.Blur(new Size(3, 3)).Canny(Threshold, Threshold * Ratio);
var output = new Mat(canny.Size(), canny.Type(), Scalar.All(0));
input.CopyTo(output, canny);
return(output);
}
/// <summary>
/// Try to match (part of) a large green circle on the screen.
/// </summary>
public CircleSegment FindCorona()
{
// see the Experiments for how this works
Bitmap cropped = CompassSensor.Crop(screen.bitmap,
screen.bitmap.Width * 1 / 3,
screen.bitmap.Height * 1 / 3,
screen.bitmap.Width * 2 / 3,
screen.bitmap.Height * 2 / 3);
Mat screenwhole = BitmapConverter.ToMat(cropped);
Point2f ShipPointerOffset = new Point2f(0, 0);
try
{
ShipPointerOffset = FindShipPointer(IsolateYellow(screenwhole));
}
catch (Exception)
{
// If we can't find the ship pointer (it's hard to see it against the sun) then use the middle of the screen.
}
// erase the vivid areas, otherwise the blur subtraction turns yellow near red to green
Mat brightHSV = screenwhole.CvtColor(ColorConversionCodes.BGR2HSV);
Mat darkAreasMask = brightHSV.InRange(InputArray.Create(new int[] { 0, 0, 0 }), InputArray.Create(new int[] { 180, 255, 180 }));
Mat darkAreas = new Mat();
screenwhole.CopyTo(darkAreas, darkAreasMask);
Mat screenblur = darkAreas - darkAreas.Blur(new OpenCvSharp.Size(10, 10));
Mat sourceHSV = screenblur.CvtColor(ColorConversionCodes.BGR2HSV);
Mat mask = sourceHSV.InRange(InputArray.Create(new int[] { 35, 204, 20 }), InputArray.Create(new int[] { 90, 255, 255 }));
Mat sourceHSVFiltered = new Mat();
sourceHSV.CopyTo(sourceHSVFiltered, mask);
Mat sourceGrey = sourceHSVFiltered.Split()[2].InRange(32, 256);
LineSegmentPoint[] result = sourceGrey.HoughLinesP(1, 3.1415 / 180, 5, 10, 2);
List <Point2d> points = new List <Point2d>();
foreach (var line in result)
{
points.Add(line.P1);
points.Add(line.P2);
}
if (points.Count < 8)
{
throw new ArgumentException("Not enough points in corona circle");
}
CircleSegment c = ComputeCircle(points);
sourceGrey.Line(c.Center, ShipPointerOffset, 255);
c.Center -= ShipPointerOffset; // adjust for camera movement by taking ship pointer offset
sourceGrey.Circle(c.Center, (int)c.Radius, 255);
debugWindow.Image = BitmapConverter.ToBitmap(sourceGrey);
return(c);
}
public Mat Process(Mat frame)
{
mFrame = frame;
Size blurWinSize = new Size(mBlurWinWidth, mBlurWinHeight);
mFrame.Blur(blurWinSize);
var reshaped = mFrame.Reshape(cn: 3, rows: mFrame.Rows * mFrame.Cols);
var samples = new Mat();
reshaped.ConvertTo(samples, MatType.CV_32FC3);
var bestLabels = new Mat();
var centers = new Mat();
Cv2.Kmeans(samples,
mClustNum,
bestLabels,
new TermCriteria(type: CriteriaType.Eps | CriteriaType.MaxIter, maxCount: 10, epsilon: 1.0),
3,
KMeansFlags.PpCenters,
centers);
//This is not optimal solution, but it works in this case.
Mat clusteredImage = new Mat(mFrame.Rows, mFrame.Cols, mFrame.Type());
for (var size = 0; size < mFrame.Cols * mFrame.Rows; size++)
{
var clusterIndex = bestLabels.At <int>(0, size);
var newPixel = new Vec3b
{
Item0 = (byte)(centers.At <float>(clusterIndex, 0)), // B
Item1 = (byte)(centers.At <float>(clusterIndex, 1)), // G
Item2 = (byte)(centers.At <float>(clusterIndex, 2)) // R
};
clusteredImage.Set(size / mFrame.Cols, size % mFrame.Cols, newPixel);
}
mFrame = clusteredImage;
Mat gray = mFrame.CvtColor(ColorConversionCodes.BGR2GRAY);
Mat thresh = gray.Threshold(140, 255, ThresholdTypes.Otsu);
Mat erode = thresh.Erode(new Mat());
Mat dilate = erode.Dilate(new Mat());
Mat morph = new Mat();
Cv2.BitwiseXor(erode, dilate, morph);
return(morph);
}
public static void MatchCorona()
{
Bitmap screen = new Bitmap("Screenshot_0028.bmp");
Bitmap cropped = CompassSensor.Crop(screen, screen.Width * 1 / 3, screen.Height * 1 / 3, screen.Width * 2 / 3, screen.Height * 2 / 3);
Mat screenwhole = BitmapConverter.ToMat(cropped);
// erase the vivid areas, otherwise the blur subtraction turns yellow near red to green
Mat brightHSV = screenwhole.CvtColor(ColorConversionCodes.BGR2HSV);
Mat darkAreasMask = brightHSV.InRange(InputArray.Create(new int[] { 0, 0, 0 }), InputArray.Create(new int[] { 180, 255, 180 }));
Mat darkAreas = new Mat();
screenwhole.CopyTo(darkAreas, darkAreasMask);
Mat screenblur = darkAreas - darkAreas.Blur(new OpenCvSharp.Size(10, 10));
Window w3 = new Window(screenblur);
//screenblur.SaveImage("sharplines.png");
Mat sourceHSV = screenblur.CvtColor(ColorConversionCodes.BGR2HSV);
/* Paint.Net uses HSV [0..360], [0..100], [0..100].
* OpenCV uses H: 0 - 180, S: 0 - 255, V: 0 - 255
* Paint.NET colors:
* 73 100 18 brightest part of green edge
* 72 98 9 very dark green
* suggested range [70..180], [80..100], [8..100] (paint.net)
* suggested range [35..90], [204..255], [20..255] (openCV)
* */
Mat mask = sourceHSV.InRange(InputArray.Create(new int[] { 35, 204, 20 }), InputArray.Create(new int[] { 90, 255, 255 }));
Mat sourceHSVFiltered = new Mat();
sourceHSV.CopyTo(sourceHSVFiltered, mask);
Window w5 = new Window("yellowfilter", sourceHSVFiltered.CvtColor(ColorConversionCodes.HSV2BGR));
Mat sourceGrey = sourceHSVFiltered.Split()[2].InRange(32, 256); // Value channel is pretty good as a greyscale conversion
Window w6 = new Window("yellowFilterValue", sourceGrey);
LineSegmentPoint[] result = sourceGrey.HoughLinesP(1, 3.1415 / 180, 5, 10, 2);
List <Point2d> points = new List <Point2d>();
foreach (var line in result)
{
points.Add(line.P1);
points.Add(line.P2);
darkAreas.Line(line.P1, line.P2, new Scalar(255, 0, 255));
}
CircleSegment c = CruiseSensor.ComputeCircle(points);
darkAreas.Circle(c.Center, (int)c.Radius, new Scalar(255, 255, 0));
Window w9 = new Window("final", darkAreas);
}
public Mat ChangeMeanBlur(Mat imageSource, int value)
{
if (imageSource == null)
{
return(null);
}
if (value == 1)
{
return(imageSource);
}
Size size = new Size(value, value);
return(imageSource.Blur(size));
}
public static Mat BinarizationMat(Mat src)
{
Mat gray = new Mat();
Mat binary = new Mat();
Cv2.CvtColor(src, gray, ColorConversionCodes.RGB2GRAY);
gray = gray.Blur(new Size(3, 3));
gray = gray.GaussianBlur(new Size(5, 5), 0);
gray = gray.BoxFilter(-1, new Size(10, 10), normalize: true);
Cv2.Threshold(gray, binary, 100, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
var element = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
binary = binary.Erode(element);
binary = binary.MorphologyEx(MorphTypes.Close, element);
//Cv2.ImShow("bin " + DateTime.Now, binary);
return(binary);
}
public static unsafe Mat NormalizeTextImage2(
Mat input,
Size size)
{
using var mean = input.Blur(size);
using var otsu = mean.
Threshold(100, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
using var ones = Mat.Ones(size.Width, size.Height, MatType.CV_8SC1);
using var dilate = otsu.Dilate(ones);
var mask = dilate;
using var maskInv = ~mask;
using InputArray maskInvInputArray = maskInv;
using var backgroundMean = new Mat();
using OutputArray backgroundMeanOutputArray = backgroundMean;
using var backgroundStdev = new Mat();
using OutputArray backgroundStdevOutputArray = backgroundStdev;
input.MeanStdDev(
backgroundMeanOutputArray,
backgroundStdevOutputArray,
maskInvInputArray);
var meanValue = backgroundMean.Get <double>(0);
var stdevValue = backgroundStdev.Get <double>(0);
var background = (byte)Math.Max(meanValue - stdevValue * 3, 0);
var output = new Mat(input.Size(), MatType.CV_8UC1, background);
input.CopyTo(output, mask);
output = output.Threshold(background, background, ThresholdTypes.Trunc);
//var clahe = Cv2.CreateCLAHE();
//clahe.Apply(output, output);
//using(new Window("Output", WindowMode.Normal | WindowMode.KeepRatio, output))
//{
// Cv2.WaitKey();
//}
return(output);
}
public override void CreateFilteredMat()
{
if (UseCastableDetection())
{
CasteableDetection = new Mat(this.CaptureSource, this.CastableDetectionArea);
CasteableDetection = CasteableDetection.Resize(new Size(1, 1), 0, 0, InterpolationFlags.Cubic);
ImageFilterHelper.reduceColor(CasteableDetection, 64);
}
FilteredMat = CaptureSource;
if (this.IsCastable() || !UseCastableDetection())
{
FilteredMat = new Mat(this.CaptureSource, new Rect(this.BorderCut, this.BorderCut, this.CaptureSource.Width - this.BorderCut * 2, this.CaptureSource.Height - this.BorderCut * 2));
FilteredMat = FilteredMat.Blur(new Size(5, 5), new Point(-1, -1));
ImageFilterHelper.killDarkPixel(FilteredMat, 60);
// ImageFilterHelper.KillGrayPixel(ref image, 60);
ImageFilterHelper.saturation(FilteredMat, 0, 2, 50);
}
}
async Task <Bitmap> CVBasic()
{
var kernel = Math.Pow(2, Slider0.Value * 10);
SliderLabel0.Text = kernel.ToString();
var t1 = Slider1.Value * 256;
var t2 = Slider2.Value * 256;
Bitmap bitmap = await GetBitmap();
await Task.Run(() =>
{
Mat mat = bitmap.ToMat();
mat = ~mat.CvtColor(ColorConversionCodes.RGBA2GRAY);
mat = mat.Blur(new OpenCvSharp.Size(kernel, kernel));
mat = mat.Threshold(t1, t2, ThresholdTypes.Otsu);
bitmap = mat.ToBitmap();
});
return(bitmap);
}
public static unsafe Mat RemoveWatermark(Mat input, byte background, Size size)
{
var output = new Mat(input.Size(), MatType.CV_8UC1);
var index = input.GetUnsafeGenericIndexer <byte>();
using var mean = input.Blur(size);
var meanIndex = mean.GetUnsafeGenericIndexer <byte>();
output.ForEachAsByte((value, position) =>
{
var y = position[0];
var x = position[1];
var invalue = index[y, x];
var mean = meanIndex[y, x];
*value = (mean < background) && (invalue < background) ?
invalue : background;
});
return(output);
}
// FaceTracking
void DoTracking()
{
//while (running)
//{
try
{
if (kinect.GetDepthRaw())
{
//lock (this)
//{
src = DoDepthBuffer(kinect.usersDepthMap, KinectWrapper.GetDepthWidth(), KinectWrapper.GetDepthHeight());
roi = src.Clone(new OpenCvSharp.CPlusPlus.Rect(roiX, roiY, roiW, roiH));
roi.ConvertTo(roi, OpenCvSharp.CPlusPlus.MatType.CV_8U, 255.0 / 32000.0);
Cv2.Subtract(new Mat(roiH, roiW, MatType.CV_8UC1, new Scalar(255)), roi, roi);
double threshMax = 255.0 - ((255.0 / 32000.0) * ((ushort)srcThreshMax << 3));
double threshMin = 255.0 - ((255.0 / 32000.0) * ((ushort)srcThreshMin << 3));
roi = roi.Threshold(threshMin, 255.0, ThresholdType.ToZeroInv);
roi = roi.Threshold(threshMax, 255.0, ThresholdType.ToZero);
// Flip up/down dimension and right/left dimension
if (!FlipUpDownAxis && FlipLeftRightAxis)
roi.Flip(FlipMode.XY);
else if (!FlipUpDownAxis)
roi.Flip(FlipMode.X);
else if (FlipLeftRightAxis)
roi.Flip(FlipMode.Y);
//Apply ellliptical mask
Mat ellipseMask = new Mat(roi.Rows, roi.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8U, new Scalar(0.0));
Cv2.Ellipse(ellipseMask, new Point(ellipseMaskCenterX, ellipseMaskCenterY), new Size(axisMaskX, axisMaskY), maskAngle, maskStartAngle, maskEndAngle, new Scalar(255.0), -1);
Cv2.BitwiseAnd(roi, ellipseMask, roi);
//Remove noise by morphologyEx
Mat kernel = Cv2.GetStructuringElement(StructuringElementShape.Ellipse, new Size(3, 3));
Cv2.MorphologyEx(roi, roi, MorphologyOperation.Open, kernel);
Cv2.MorphologyEx(roi, roi, MorphologyOperation.Close, kernel);
//Subtract background
if (first)
{
bg = roi.Clone();
//bg = bg.Blur(new Size(smoothBlur, smoothBlur));
first = false;
}
fg = bg.Clone();
//roi = roi.Blur(new Size(smoothBlur, smoothBlur));
Mat subMask = roi.Clone();
subMask = subMask.Threshold(smThresh, 255.0, ThresholdType.ToZero);
//Cv2.ImShow("sm",subMask);
bg.CopyTo(roi, subMask);
OpenCvSharp.Cv.AbsDiff(roi.ToCvMat(), bg.ToCvMat(), fg.ToCvMat());
//Threshold foreground image
fgthresh = fg.Threshold(threshold, 255.0, ThresholdType.Binary);
fgthresh = fgthresh.Blur(new Size(smoothBlur, smoothBlur));
//Detect Blobs
Mat roiToImg = new Mat(roi.Cols, roi.Rows, MatType.CV_8UC3);
Mat threshToImg = fgthresh.Clone();
Cv2.Merge(new Mat[] { roi, roi, roi }, roiToImg);
IplImage showImg = roiToImg.ToIplImage();
IplImage fgthreshImg = threshToImg.ToIplImage();
OpenCvSharp.Blob.CvBlobLib.Label(fgthreshImg, blobs);
OpenCvSharp.Blob.CvBlobLib.FilterByArea(blobs, blobMinArea, blobMaxArea);
OpenCvSharp.Blob.CvBlobLib.RenderBlobs(blobs, fgthreshImg, showImg, RenderBlobsMode.Color | RenderBlobsMode.Centroid);
UpdateTracks(blobs, tracks, blobMinDistance, blobMaxLife);
//OpenCvSharp.Blob.CvBlobLib.RenderTracks(tracks, fgthreshImg, showImg, RenderTracksMode.BoundingBox | RenderTracksMode.Id);
RenderTracks(showImg);
//Cv.ShowImage("thres", fgthreshImg);
Cv.ShowImage("showBlob", showImg);
//Check Blob Actions
//Debug.Log(tracks.Count);
//}
}
}
catch (System.Exception e)
{
//throw e;
Debug.Log(e.Message + " " + e.StackTrace);
}
//}
}
public unsafe static FeatureInfo Features(
TesseractEngine engine,
Mat input,
Size size,
byte background)
{
using var scope = new Scope();
var mask = input.
Threshold(100, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu).
Temp(scope).
Dilate(Mat.Ones(size.Width, size.Height, MatType.CV_8SC1).Temp(scope)).
In(scope);
mask.FindContours(
out var points,
out var hierarchy,
RetrievalModes.CComp,
ContourApproximationModes.ApproxSimple);
var nodes = points.
Select((contour, index) =>
{
if (hierarchy[index].Parent >= 0)
{
return(null);
}
var rect = Cv2.BoundingRect(contour);
if ((rect.Width < size.Width) && (rect.Height < size.Height))
{
return(null);
}
using var roi = new Mat(rect.Size, MatType.CV_8UC1, 0);
roi.DrawContours(
points,
index,
Scalar.White,
-1,
LineTypes.Link4,
null,
int.MaxValue,
-rect.TopLeft);
using var inputView = input[rect];
using var maskedInput =
new Mat(rect.Size, MatType.CV_8UC1, background);
inputView.CopyTo(maskedInput, roi);
using var fineMask = maskedInput.
Threshold(100, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu).
Dilate(new Mat());
fineMask.FindContours(
out var finePoints,
out var fineHierarchy,
RetrievalModes.CComp,
ContourApproximationModes.ApproxSimple);
using var fineMask2 = new Mat(rect.Size, MatType.CV_8UC1, 0);
fineMask2.DrawContours(finePoints, -1, Scalar.White, -1);
using var bluredFineMask2 = fineMask2.Blur(size);
using var maxedFineMask2 = new Mat(rect.Size, MatType.CV_8UC1);
var ix = bluredFineMask2.GetUnsafeGenericIndexer <byte>();
maxedFineMask2.ForEachAsByte((value, position) =>
{
var y = position[0];
var x = position[1];
var minx = Math.Max(x - (size.Width >> 1), 0);
var maxx = Math.Min(x + ((size.Width + 1) >> 1), rect.Width);
var miny = Math.Max(y - (size.Height >> 1), 0);
var maxy = Math.Min(y + ((size.Height + 1) >> 1), rect.Height);
var max = 0;
for (var iny = miny; iny < maxy; ++iny)
{
for (var inx = minx; inx < maxx; ++inx)
{
var invalue = ix[iny, inx];
if (max < invalue)
{
max = invalue;
}
}
}
var v = ix[y, x];
*value = v >= max && max > 0 ? (byte)255 : (byte)0;
});
//using(new Window("fineMask2 " + index, WindowMode.AutoSize, maxedFineMask2))
//{
// Cv2.WaitKey();
//}
using var smooth = Smooth(maskedInput, background, .1);
using var sharpened = Sharpen(smooth, size);
var lines = maxedFineMask2.HoughLinesP(
1,
Math.PI / 180,
100,
Math.Max(rect.Width, rect.Height) / 2,
size.Width);
//if (lines.Length == 0)
//{
// return null;
//}
var angle = 0;
//(int)(lines.
// Average(l => Math.Atan2(l.P2.Y - l.P1.Y, l.P2.X - l.P1.Y)) /
// Math.PI * 180);
//angle -= angle % 4;
var ocrView = sharpened;
//if(angle != 0)
//{
// using var rotation = Cv2.GetRotationMatrix2D(new Point2f(), angle, 1);
// var cos = Math.Abs(rotation.At<double>(0, 0));
// var sin = Math.Abs(rotation.At<double>(0, 1));
// var width = (int)(rect.Height * sin + rect.Width * cos);
// var height = (int)(rect.Height * cos + rect.Width * sin);
// rotation.At<float>(0, 2) = (width - rect.Width) / 2;
// rotation.At<float>(1, 2) = (height - rect.Height) / 2;
// ocrView = sharpened.WarpAffine(
// rotation,
// new Size(width, height),
// InterpolationFlags.Area,
// BorderTypes.Constant,
// new Scalar(background));
//}
using var ocrViewResource = ocrView;
var node = OCR(engine, ocrView, 225);
//if(index == 44)
//{
// index = 44;
//}
if (!(node?.Children?.Count > 0))
{
return(null);
}
node.Contours = finePoints;
node.Angle = angle;
node.Left = rect.Left;
node.Top = rect.Top;
node.Width = rect.Width;
node.Height = rect.Height;
return(node);
}).
ToArray();
return(new FeatureInfo
{
Contours = points,
Hierarchy = hierarchy,
Nodes = nodes
});
}
public Window1()
{
InitializeComponent();
Mat src = new Mat(@"./desktop.jpg");
Cv2.ImShow("src", src);
//src = src.Resize(new Size(src.Width / 2, src.Height / 2));
for (var y = 0; y < src.Height; y++)
{
for (var x = 0; x < src.Width; x++)
{
var color = src.Get <Vec3b>(y, x);
//if (color.Item2 < 175)
if (color.Item2 < 225)
{
color.Item0 = 255;
color.Item1 = 0;
color.Item2 = 0;
}
src.Set(y, x, color);
}
}
Cv2.ImShow("fade", src);
Mat gray = new Mat();
Mat binary = new Mat();
Cv2.CvtColor(src, gray, ColorConversionCodes.RGB2GRAY);
gray = gray.GaussianBlur(new Size(5, 5), 0);
gray = gray.Blur(new Size(5, 5));
gray = gray.BoxFilter(-1, new Size(10, 10), normalize: true);
Cv2.ImShow("gray", gray);
Cv2.Threshold(gray, binary, 100, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
var element = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
binary = binary.Erode(element);
binary = binary.MorphologyEx(MorphTypes.Close, element);
Cv2.ImShow("bin", binary);
//var line = binary.Canny(100, 200);
//Cv2.ImShow("line", line);
//Cv2.WaitKey();
//建立轮廓接受数组
Point[][] contours;
HierarchyIndex[] hierarchy;
Cv2.FindContours(binary, out contours, out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxTC89KCOS);
//最小外接矩形接收数组
MessageBox.Show(contours.Length.ToString());
RotatedRect[] rotateRect = new RotatedRect[contours.Length];
Point[][] contours_poly = new Point[contours.Length][];
for (int i = 0; i < contours.Length; i++)
{
contours_poly[i] = Cv2.ApproxPolyDP(contours[i], 30, true); //返回凸包，单线长大于30过滤
rotateRect[i] = Cv2.MinAreaRect(contours_poly[i]); //最小外接矩形集合
Point2f[] pot = new Point2f[4]; //新建点集合接收点集合
//for (int i = 0; i < rotateRect.Length; i++)
//{
var angle = rotateRect[i].Angle; //矩形角度
pot = rotateRect[i].Points(); //矩形的4个角
var line1 = Math.Sqrt((pot[0].X - pot[1].X) * (pot[0].X - pot[1].X) + (pot[0].Y - pot[1].Y) * (pot[0].Y - pot[1].Y));
var line2 = Math.Sqrt((pot[0].X - pot[3].X) * (pot[0].X - pot[3].X) + (pot[0].Y - pot[3].Y) * (pot[0].Y - pot[3].Y));
if (line1 * line2 < 1000)//过滤，太小的矩形直接pass
{
continue;
}
if (line1 > line2)//依据实际情况进行判断
{
angle += 90;
}
Mat Roi = new Mat(src.Size(), MatType.CV_8UC3);
Roi.SetTo(0);//全黑
//Cv2.DrawContours(binary, contours, -1, Scalar.White, -1);//在二值图像中圈出轮廓区域并染白
Cv2.DrawContours(binary, contours, -1, Scalar.White, 1);
Cv2.ImShow("bin", binary);
src.CopyTo(Roi, binary);//将原图通过mask抠图到Roi
Cv2.ImShow("Roi", Roi);
Mat afterRotato = new Mat(src.Size(), MatType.CV_8UC3);
afterRotato.SetTo(0);
Point2f center = rotateRect[i].Center;
Mat M = Cv2.GetRotationMatrix2D(center, angle, 1); //计算变换矩阵
Cv2.WarpAffine(Roi, afterRotato, M, Roi.Size(), InterpolationFlags.Linear, BorderTypes.Wrap); //得到变换后的图像，滤除其他信息
Cv2.ImShow("旋转后", afterRotato);
Mat bin2 = new Mat();
Cv2.ImShow("after", afterRotato);
Cv2.CvtColor(afterRotato, bin2, ColorConversionCodes.RGB2GRAY);
Cv2.Threshold(bin2, bin2, 50, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
Point[][] con;
HierarchyIndex[] temp;//接收矫正后的轮廓信息
Cv2.FindContours(bin2, out con, out temp, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
for (int j = 0; j < con.Length; j++)
{
Rect rect = Cv2.BoundingRect(con[j]); //直接使用矫正矩形，因为矫正后不需要再旋转
if (rect.Height * rect.Width < 8000) //过滤干扰信息
{
continue;
}
Mat dstImg = new Mat(afterRotato, rect);
dstImg = dstImg.CvtColor(ColorConversionCodes.RGB2GRAY);
dstImg = dstImg.Threshold(50, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
Cv2.BitwiseNot(dstImg, dstImg, new Mat());
dstImg = new Mat(dstImg, new Rect(100, 100, dstImg.Width - 200, dstImg.Height - 200));
Cv2.ImShow("dst", dstImg);
dstImg.SaveImage("dst1.jpg");
var engine = new TesseractEngine("./tessdata", "eng", EngineMode.Default);
var resProcess = engine.Process(Pix.LoadTiffFromMemory(dstImg.ToBytes(".tiff")));
MessageBox.Show(resProcess.GetText());
////string name = "dst" + i;//主要看调试的时候有几个结果
//dstImg = dstImg.CvtColor(ColorConversionCodes.RGB2GRAY);
//dstImg = dstImg.Threshold(10, 255, ThresholdTypes.Otsu);
//Cv2.ImShow("chan", dstImg.Canny(100, 200));
//dstImg.FindContours(out var con1, out var hie1, RetrievalModes.External,
// ContourApproximationModes.ApproxNone);
//dstImg.DrawContours(con1, -1, Scalar.Green, 3);
//Cv2.ImShow("dst2", dstImg);
}
}
Cv2.WaitKey();
Console.ReadLine();
}
