public void handleOpenCV(String fileName)
{
PARSE_RESULT = "";
ERROR_MESSAGE = "";
BITMAP = null;
Mat matRead = Cv2.ImRead(fileName, ImreadModes.Grayscale);
// CROP: https://076923.github.io/posts/C-opencv-9/
OpenCvSharp.Rect rect = new OpenCvSharp.Rect(452, 182, 1024, 728);
Mat subMat = matRead.SubMat(rect);
//Cv2.ImShow(strFIle, matRead);
BITMAP = BitmapConverter.ToBitmap(subMat);
try
{
// System.DllNotFoundException: Failed to find library "leptonica-1.80.0.dll" for platform x86.
using (var engine = new TesseractEngine(@"./tessdata", "eng", EngineMode.TesseractOnly))
{
using (var page = engine.Process(BITMAP))
PARSE_RESULT = page.GetText();
Debug.WriteLine(PARSE_RESULT);
}
}
catch (Exception ex)
{
ERROR_MESSAGE = ex.ToString();
Debug.WriteLine(ERROR_MESSAGE);
}
}
private void MatchAndReplaceFaceRectangles(FaceAPI.Contract.Face[] faces, OpenCvSharp.Rect[] clientRects)
{
// Use a simple heuristic for matching the client-side faces to the faces in the
// results. Just sort both lists left-to-right, and assume a 1:1 correspondence.
// Sort the faces left-to-right.
var sortedResultFaces = faces
.OrderBy(f => f.FaceRectangle.Left + 0.5 * f.FaceRectangle.Width)
.ToArray();
// Sort the clientRects left-to-right.
var sortedClientRects = clientRects
.OrderBy(r => r.Left + 0.5 * r.Width)
.ToArray();
// Assume that the sorted lists now corrrespond directly. We can simply update the
// FaceRectangles in sortedResultFaces, because they refer to the same underlying
// objects as the input "faces" array.
for (int i = 0; i < Math.Min(faces.Length, clientRects.Length); i++)
{
// convert from OpenCvSharp rectangles
OpenCvSharp.Rect r = sortedClientRects[i];
sortedResultFaces[i].FaceRectangle = new FaceAPI.Contract.FaceRectangle {
Left = r.Left, Top = r.Top, Width = r.Width, Height = r.Height
};
}
}
private static Cv.Rect FixInvalidRects(Cv.Rect rect, int width, int height)
{
if (rect.X < 0)
{
rect.X = 0;
}
if (rect.Y < 0)
{
rect.Y = 0;
}
if (rect.X > width)
{
rect.Width = width;
}
if (rect.Y > height)
{
rect.Height = height;
}
if (rect.Width + rect.X > width)
{
rect.Width = width - rect.X;
}
if (rect.Height + rect.Y > height)
{
rect.Height = height - rect.Y;
}
return(rect);
}
void TransformImage(Point[] corners)
{
//4頂点が検出されていなければ何もしない
if (corners == null)
{
return;
}
//4頂点の並べ替え
SortCorners(corners);
//検出された4頂点の座標を入力
Point2f[] input = { corners[0], corners[1],
corners[2], corners[3] };
//テクスチャとして使用する正方形画像の4頂点の座標を入力
Point2f[] square =
{ new Point2f(0, 0), new Point2f(0, 255),
new Point2f(255, 255), new Point2f(255, 0) };
//歪んだ四角形を正方形に変換するパラメータを計算
Mat transform = Cv2.GetPerspectiveTransform(input, square);
//変換パラメータに基づいて画像を生成
Cv2.WarpPerspective(bgr, bgr, transform, new Size(256, 256));
int s = (int)(256 * 0.05f); //今回、枠の太さを幅の5%と設計
int w = (int)(256 * 0.9f); //両サイドを差し引いた90%が内側の幅
OpenCvSharp.Rect innerRect = new OpenCvSharp.Rect(s, s, w, w);
bgr = bgr[innerRect];
}
public TempletGenerator(
int maxTempletSize,
MatType matType,
int numRotationSteps,
Point plantCenter,
int plantCenterWidth,
float maxSteamLengthRatio,
OpenCvSharp.Rect maxMatchingRect,
Mat plantMask,
float outsideMaskRatio)
{
generatorState = State.NotSet;
this.templetCenter = maxTempletSize / 2;
this.shiftDistance = plantCenterWidth / 2;
this.uperPlantCenterCorner = new Point(plantCenter.X - shiftDistance,
plantCenter.Y - shiftDistance);
this.maxSteamLengthRatio = maxSteamLengthRatio;
this.maxMatchingRect = maxMatchingRect;
this.plantMaskInvert = 255 - plantMask;
this.outsideMaskRatio = outsideMaskRatio;
rotatPoint = new RotatPoint(numRotationSteps);
templetContureMat = Mat.Zeros(maxTempletSize, maxTempletSize, matType);
templetFillMat = Mat.Zeros(maxTempletSize, maxTempletSize, matType);
matchingArea = new Point[8];
for (int i = 0; i < matchingArea.Length; ++i)
{
matchingArea [i] = new Point();
}
}
public bool checkAgainstMask(Point location)
{
if (generatorState < State.TempletSet)
{
Debug.Log("Templet not set.");
return(false);
}
double templetValue = Cv2.Sum(templetFill).Val0;
OpenCvSharp.Rect maskRect = new OpenCvSharp.Rect(matchingBoxRect.X + location.X,
matchingBoxRect.Y + location.Y,
templetFill.Width,
templetFill.Height);
Mat mask = new Mat(plantMaskInvert, maskRect);
Mat bitwiseResult = new Mat();
Cv2.BitwiseAnd(mask, templetFill, bitwiseResult);
double outsideMaskValue = Cv2.Sum(bitwiseResult).Val0;
double templetOutsideMaskRatio = 0.0;
if (templetValue > 0.0)
{
templetOutsideMaskRatio = outsideMaskValue / templetValue;
}
if (templetOutsideMaskRatio > outsideMaskRatio)
{
return(false);
}
return(true);
}
private void FindPlantBounds()
{
Mat nonZero = new Mat();
Cv2.FindNonZero(plantSegmentasionImage, nonZero);
plantBounds = Cv2.BoundingRect(nonZero);
}
/// <summary>
/// Crops an image to a square shape <br/>
///Image processing algorithm
/// </summary>
/// <param name="img">input image, of type OpenCvSharp.Mat</param>
/// <returns>output image, of type OpenCvSharp.Mat</returns>
public Mat CropToROI(ref Mat img)
{
// If images are the same height and width, no crop is necessary
if (img.Width == img.Height)
{
return(img);
}
// If image width is larger than image height
else if (img.Width > img.Height)
{
this.ROI = new OpenCvSharp.Rect((img.Width - img.Height) / 2, 0, img.Height, img.Height);
}
// If image height is larger than image width
else
{
this.ROI = new OpenCvSharp.Rect((img.Height - img.Width) / 2, 0, img.Width, img.Width);
}
// Create empty image with specified size and fill it with data
new Mat(img, ROI).CopyTo(newImgROI);
return(newImgROI);
}
void crop_image(Mat outimg)
{
try
{
Mat copy = new Mat();
outimg.CopyTo(copy);
OpenCvSharp.Rect rect = new OpenCvSharp.Rect(500, 0, 1100, 1080);
crop = new Mat(outimg, rect);
crop.CopyTo(outputimg);
// Cv2.ImWrite("crop" + ".bmp", crop);
if (outputimg.Channels() == 1)
{
Cv2.CvtColor(outputimg, outputimg, ColorConversionCodes.GRAY2BGR);
}
thread(crop);
Holes1(crop);
}
catch (Exception Ex)
{
//MessageBox.Show(Ex.Message.ToString());
log.Error("Error Message: " + Ex.Message.ToString(), Ex);
}
}
private List <List <Cv.Rect> > GroupRects(List <Cv.Rect> rects, Mat debug)
{
rects.Sort((l, r) => l.Y.CompareTo(r.Y));
List <List <Cv.Rect> > grouped = new List <List <Cv.Rect> >();
List <int> ignoreIndices = new List <int>();
for (int i = 0; i < rects.Count; i++)
{
if (ignoreIndices.Contains(i))
{
continue;
}
var current = rects[i];
if (IsTooLarge(current, debug))
{
continue;
}
List <Cv.Rect> group = new List <Cv.Rect>();
group.Add(rects[i]);
for (int j = i + 1; j < rects.Count; j++)
{
if (IsTooLarge(rects[j], debug))
{
ignoreIndices.Add(j);
continue;
}
if (rects[j].Y > current.Y + current.Height + (rects[j].Height * 2))
{
continue;
}
var l = new Cv.Rect(rects[i].X, 0, rects[i].Width, rects[i].Height);
var r = new Cv.Rect(rects[j].X, 0, rects[j].Width, rects[j].Height);
if (l.IntersectsWith(r))
{
var intersect = l.Intersect(r);
var intersectArea = intersect.Width * intersect.Height;
var lArea = rects[i].Width * rects[i].Height;
var rArea = rects[j].Width * rects[j].Height;
if (intersectArea > (lArea * 0.25) && intersectArea > (rArea * 0.25))
{
current = current.Union(rects[j]);
group.Add(rects[j]);
}
}
}
grouped.Add(group);
}
return(grouped);
}
private OpenCvSharp.Rect AdjustBoundingBox(OpenCvSharp.Rect faceRect)
{
int w = faceRect.Width;
int h = faceRect.Height;
faceRect.X -= (int)(0.067 * w);
faceRect.Y -= (int)(0.028 * h);
faceRect.Width += (int)(0.15 * w);
faceRect.Height += (int)(0.13 * h);
if (faceRect.Width < faceRect.Height)
{
var dx = (faceRect.Height - faceRect.Width);
faceRect.X -= dx / 2;
faceRect.Width += dx;
}
else
{
var dy = (faceRect.Width - faceRect.Height);
faceRect.Y -= dy / 2;
faceRect.Height += dy;
}
return(faceRect);
}
public Mat Overlay(Mat frame, OpenCvSharp.Point offset)
{
if (this.State != GmapState.Collapsed && this.Gmap.Empty())
{
return(frame);
}
var area = new OpenCvSharp.Rect(offset, this.GetGmapSize(frame));
if (this.State == GmapState.Collapsed)
{
frame = frame.CvtColor(ColorConversionCodes.BGR2BGRA);
var icon = this._icon.Resize(area.Size);
var mask = this._mask.Resize(area.Size);
icon.CopyTo(new Mat(frame, area), mask);
frame = frame.CvtColor(ColorConversionCodes.BGRA2BGR);
}
else if (this.State == GmapState.Expanded)
{
var gmap = this.Gmap.Resize(area.Size);
gmap.CopyTo(new Mat(frame, area));
}
else
{
var gmap = this.Gmap.Resize(area.Size);
frame = gmap;
}
this._currentFrame = frame;
return(this._currentFrame);
}
protected override bool ProcessTexture(WebCamTexture input, ref Texture2D output) {
// 1. Obtain Frame
Mat img = Unity.TextureToMat (input, TextureParameters);
// 2. Rezise frame , for now the best size to analize is 10% of the original size 1280*720
Mat rzImg = img.Resize (Size.Zero, rs.downScale, rs.downScale);
// 3. Calculate and draw rect
OpenCvSharp.Rect fgRect = rs.DrawRect (imageTransform, img, rzImg, TextureParameters, ref output);
if (rs.isTracking) {
// 3. Apply grabcut Initializating I recommend 5 iterations
Mat mask = new Mat (Size.Zero, MatType.CV_8U);
Mat bgModel = new Mat ();
Mat fgModel = new Mat ();
Cv2.GrabCut (rzImg, mask, fgRect, bgModel, fgModel, iterations, GrabCutModes.InitWithRect);
// 4. Use foreground or bg as mask
mask = (mask & 1) * 255; // Takes the mask and convert every non 0 value to 255 (White)
mask = mask.Resize (new Size (img.Width, img.Height), 0, 0, InterpolationFlags.Lanczos4);
// 5. Aply the mask while coping the original image to a green background
Mat bg = new Mat (img.Size(), rzImg.Type(), green);
img.CopyTo (bg, mask);
// 6. Show result
output = Unity.MatToTexture (bg, output);
}
return true;
}
void Button2Click(object sender, EventArgs e)
{
Bitmap roibmp;
Pix roipix;
Mat src;
buttonRight.Enabled = false;
buttonNext.Enabled = false;
button2.Enabled = false;
OpenCvSharp.Rect roi = ramka.getRoi();
Cursor = Cursors.WaitCursor;
if (roi.X != -1)
{
src = ramka.Image[roi];
}
else
{
src = ramka.Image;
}
roibmp = src.ToBitmap();
roipix = PixConverter.ToPix(roibmp);
Pix roipix1 = roipix.Deskew();
Bitmap newbm = PixConverter.ToBitmap(roipix1);
Mat newmat = BitmapConverter.ToMat(newbm);
ramka.Image = newmat;
Cursor = Cursors.Default;
src.Dispose();
newbm.Dispose();
roipix.Dispose();
buttonRight.Enabled = true;
buttonNext.Enabled = true;
button2.Enabled = true;
}
public Reading Analyze(Mat input)
{
var resized = input.ResizePreserveAspectRatio(maxSize: _settings.InputAnalysisMaxSize);
var grayScale = resized.Image.CvtColor(ColorConversionCodes.BGR2GRAY);
var noiseReduced = grayScale.Erode(new Mat()).Dilate(new Mat());
var meterNumberRectangles = DetectMeterNumbers(noiseReduced);
if (!meterNumberRectangles.Any())
{
return(new Reading(""));
}
Mat[] croppedImages;
if (_settings.DarkSectors)
{
croppedImages = meterNumberRectangles.Select(r =>
{
var rect = new Rect(r.Position.X, r.Position.Y, r.Width, r.Height);
return(new Mat(noiseReduced, rect)
.Threshold(0, 255, ThresholdTypes.Otsu)
.Erode(new Mat())
.ResizePreserveAspectRatio(_settings.DarkSectorsSeparateMeterNumbersResizeMaxSize).Image);
}).ToArray();
}
else
{
croppedImages = meterNumberRectangles.Select(r =>
{
var rect = new Rect(r.Position.X, r.Position.Y, r.Width, r.Height);
return(new Mat(noiseReduced, rect)
.AdaptiveThreshold(255, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.BinaryInv, _settings.LightSectorsAdaptiveThresholdBlockSize, _settings.LightSectorsAdaptiveThresholdC)
.ResizePreserveAspectRatio(_settings.LightSectorsSeparateMeterNumbersResizeMaxSize).Image);
}).ToArray();
croppedImages = croppedImages.Select(i =>
{
var rect = new BlobDetector().GetLargestBlob(i);
return(new Mat(i, rect));
}).ToArray();
}
var resizedCroppedNumbers = croppedImages.ResizeToAverageHeight();
var combinedNumbers = resizedCroppedNumbers.Skip(1)
.Aggregate(croppedImages[0], (a, b) => a.CombineImages(b), r => r);
var numbers = combinedNumbers.WidenEdges(10);
if (!_settings.DarkSectors)
{
Cv2.BitwiseNot(numbers, numbers);
}
var reading = new Reading(InsertDecimal(_stringExtractor.GetStringFromImage(numbers)),
GetScaledRectangles(resized.OriginalScale, meterNumberRectangles));
return(reading);
}
public static void ClickImg(Rect r, bool isClick = true)
{
MoveTo(r, false);
if (isClick)
{
LeftClick();
}
}
public static void Trnstxt(GameObject a, RectTransform rt, OpenCvSharp.Rect r)
{
var newVec = new Vector2(r.X, -r.Y) - new Vector2(rt.sizeDelta.x / 2.0f, -rt.sizeDelta.y / 2.0f);
Debug.LogFormat("r : {0}, sizeDelta : {1}", new Vector2(r.X, r.Y), new Vector2(rt.sizeDelta.x, rt.sizeDelta.y));
//a.transform.localPosition = (newVec);
a.transform.localPosition = (newVec + new Vector2((float)r.Width / 2.0f, 0)) * InstantiateText.Canvas.transform.localScale.x;
}
Mat Clamp(Mat mat, double maxWidth, double maxHeight)
{
var marginX = Math.Max(0, (int)Math.Ceiling((mat.Width - maxWidth) / 2));
var marginY = Math.Max(0, (int)Math.Ceiling((mat.Height - maxHeight) / 2));
var rect = new OpenCvSharp.Rect(marginX, marginX, mat.Width - marginX * 2, mat.Height - marginY * 2);
return(new Mat(mat, rect));
}
public void SetCastableDetectionArea(System.Windows.Rect captureRect)
{
this.CastableDetectionArea = new Rect(
(int)captureRect.X,
(int)captureRect.Y,
(int)captureRect.Width,
(int)captureRect.Height
);
}
public void SetCaptureRect(System.Windows.Rect captureRect)
{
this.CaptureRect = new Rect(
(int)captureRect.X,
(int)captureRect.Y,
(int)captureRect.Width,
(int)captureRect.Height
);
}
private void Detect(ref Mat src_img, ref Mat src_img2, int index)
{
Mat dst_img = new Mat();
List <float> Xpoint = new List <float>();
List <float> Ypoint = new List <float>();
//空Matに全座標の比較データ（配列）を格納
Cv2.MatchTemplate(src_img, _templateNumeric[index], dst_img, TemplateMatchModes.CCoeffNormed);
//比較データ(配列)のうち、しきい値0.7以下を排除(0)にする
Cv2.Threshold(dst_img, dst_img, 0.70, 1.0, ThresholdTypes.Tozero);
//0以上の座標データをXpoint Ypointに格納する
for (int x = 0; x < dst_img.Rows; x++)
{
for (int y = 0; y < dst_img.Cols; y++)
{
if (dst_img.At <float>(x, y) > 0)
{
Xpoint.Add(y);
Ypoint.Add(x);
}
}
}
dst_img.Dispose();
List <OpenCvSharp.Rect> rectangles = new List <OpenCvSharp.Rect>();
for (int i = 0; i < Xpoint.Count; i++)
{
OpenCvSharp.Rect rect = new OpenCvSharp.Rect(new OpenCvSharp.Point(Xpoint[i], Ypoint[i]), _templateNumeric[index].Size());
bool isIntersect = false;
foreach (OpenCvSharp.Rect r in rectangles)
{
if (isIntersect = r.IntersectsWith(rect))
{
break;
}
}
;
if (isIntersect)
{
continue;
}
rectangles.Add(rect);
Cv2.Rectangle(src_img2, rect, _colors[index], 2);
Cv2.PutText(src_img2, index.ToString(), rect.Location, HersheyFonts.HersheySimplex, 1, _colors[index], 2);
}
}
//模板匹配
public static List <Mat> MyMatchTemplate(Mat img, OpenCvSharp.Rect img_roi, string templatename, double threshold, int tubey, List <OpenCvSharp.Rect> rect_list = null)
{
List <Mat> imgs = new List <Mat>();
Stopwatch sw = new Stopwatch();
Mat img_gray = new Mat();
img = img.Clone();
img = img.SubMat(img_roi);
Cv2.CvtColor(img, img_gray, ColorConversionCodes.BGR2GRAY);
var template = GetTimplateImage(templatename);
Mat result = new Mat();
double minVal, maxVal;
OpenCvSharp.Point minLoc, maxLoc, maxFloc;
Cv2.MatchTemplate(img_gray, template, result, TemplateMatchModes.CCoeffNormed);
Cv2.MinMaxLoc(result, out minVal, out maxVal, out minLoc, out maxLoc);
maxFloc = maxLoc;
int count = 0;
OpenCvSharp.Rect last_rect = new OpenCvSharp.Rect();
int ww = img.Width / template.Width - 1;
for (int i = 0; i < ww; i++)
{
int px = i * template.Width;
int py = maxFloc.Y;
OpenCvSharp.Rect roi = new OpenCvSharp.Rect(px, py, template.Width, template.Height);
if (roi.Y + roi.Height > result.Height)
{
roi.Height = result.Height - roi.Y;
}
Mat RoiResult = new Mat(result, roi);
Cv2.MinMaxLoc(RoiResult, out minVal, out maxVal, out minLoc, out maxLoc);//查找极值
var rect = new OpenCvSharp.Rect(px + maxLoc.X, py + maxLoc.Y, template.Width, template.Height);
if (maxVal > threshold && Math.Abs(last_rect.X - rect.X) > 50)
{
count++;
if (tubey != 0)
{
rect.Y = tubey - img_roi.Y;
}
Mat retimg = new Mat(img, rect);
if (rect_list != null)
{
rect_list.Add(rect);
}
last_rect = rect;
imgs.Add(retimg);
if (count >= 8)
{
break;
}
}
}
return(imgs);
}
public void GetRects(Mat temp, Mat wafer)
{
//读取图片
Mat result = new Mat(); //匹配结果
//模板匹配
Cv2.MatchTemplate(wafer, temp, result, TemplateMatchModes.CCoeffNormed);//最好匹配为1,值越小匹配越差
Double minVul;
Double maxVul;
OpenCvSharp.Point minLoc = new OpenCvSharp.Point(0, 0);
OpenCvSharp.Point maxLoc = new OpenCvSharp.Point(0, 0);
OpenCvSharp.Point matchLoc = new OpenCvSharp.Point(0, 0);
Cv2.Normalize(result, result, 0, 1, NormTypes.MinMax, -1); //归一化
Cv2.MinMaxLoc(result, out minVul, out maxVul, out minLoc, out maxLoc); //查找极值
matchLoc = maxLoc; //最大值坐标
//result.Set(matchLoc.Y, matchLoc.X, 0);//改变最大值为最小值
Mat mask = wafer.Clone(); //复制整个矩阵
//画框显示
Cv2.Rectangle(mask, matchLoc, new OpenCvSharp.Point(matchLoc.X + temp.Cols, matchLoc.Y + temp.Rows), Scalar.Green, 2);
Console.WriteLine("最大值：{0}，X:{1}，Y:{2}", maxVul, matchLoc.Y, matchLoc.X);
Console.WriteLine("At获取最大值(Y,X)：{0}", result.At <float>(matchLoc.Y, matchLoc.X));
Console.WriteLine("result的类型：{0}", result.GetType());
//循环查找画框显示
Double threshold = 0.8;
Mat maskMulti = wafer.Clone(); //复制整个矩阵
for (int i = 1; i < result.Rows - temp.Rows; i += temp.Rows) //行遍历
{
for (int j = 1; j < result.Cols - temp.Cols; j += temp.Cols) //列遍历
{
OpenCvSharp.Rect roi = new OpenCvSharp.Rect(j, i, temp.Cols, temp.Rows); //建立感兴趣
Mat RoiResult = new Mat(result, roi);
Cv2.MinMaxLoc(RoiResult, out minVul, out maxVul, out minLoc, out maxLoc); //查找极值
matchLoc = maxLoc; //最大值坐标
if (maxVul > threshold)
{
//画框显示
Cv2.Rectangle(maskMulti, new OpenCvSharp.Point(j + maxLoc.X, i + maxLoc.Y), new OpenCvSharp.Point(j + maxLoc.X + temp.Cols, i + maxLoc.Y + temp.Rows), Scalar.Green, 2);
string axis = '(' + Convert.ToString(i + maxLoc.Y) + ',' + Convert.ToString(j + maxLoc.X) + ')';
Cv2.PutText(maskMulti, axis, new OpenCvSharp.Point(j + maxLoc.X, i + maxLoc.Y), HersheyFonts.HersheyPlain, 1, Scalar.Red, 1, LineTypes.Link4);
}
}
}
//新建窗体显示图片
Cv2.Resize(maskMulti, maskMulti, new OpenCvSharp.Size(512, 384));
using (new OpenCvSharp.Window("maskMulti image", maskMulti))
{
Cv2.WaitKey();
}
}
public static GameObject Instxt(RectTransform rt, OpenCvSharp.Rect r)
{
var newVec = new Vector2((float)r.X, -(float)r.Y) - new Vector2(rt.sizeDelta.x / 2.0f, -rt.sizeDelta.y / 2.0f);
Debug.Log(newVec);
GameObject a = GameObject.Instantiate(Text, Canvas.transform);
a.transform.localPosition = (newVec + new Vector2((float)r.Width / 2.0f, 0)) * Canvas.transform.localScale.x;
return(a);
}
public void RunScript()
{
// Checking that that there exist a file of any type.
if (!File.Exists(imageFilePath))
{
Debug.Log("Image File do not exist!");
//return;
}
Mat image = Cv2.ImRead(imageFilePath, ImreadModes.Color);
if (image.Empty())
{
Debug.Log("No readable image file.");
return;
}
Cv2.NamedWindow("Image", WindowMode.KeepRatio);
Cv2.NamedWindow("Image2", WindowMode.KeepRatio);
Cv2.NamedWindow("subImage", WindowMode.KeepRatio);
Cv2.ImShow("Image", image);
// OpenCvSharp.Rect roi = new OpenCvSharp.Rect (image.Width / 4, image.Height / 4, image.Width / 2, image.Height / 2);
// Mat subImage = new Mat (image, roi);
// //subImage = new Scalar (255, 255, 255) - subImage;
// Cv2.Add (subImage, subImage, subImage);
// Cv2.ImShow ("subImage", subImage);
// Cv2.ImShow ("Image2", image);
Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY) / 10;
// NB! EmptyClone do not overwrite memory, old contntent in memory makes glitch's
//Mat canvas = imageGray.EmptyClone ();
Mat canvas = Mat.Zeros(imageGray.Size(), imageGray.Type());
Vector2 drawingCanvasSize = new Vector2(canvas.Width - squareSize, canvas.Height - squareSize);
for (int i = 0; i < iteration; ++i)
{
OpenCvSharp.Rect drawingRegion = new OpenCvSharp.Rect(
(int)Random.Range(0, drawingCanvasSize.x - 1),
(int)Random.Range(0, drawingCanvasSize.y - 1),
squareSize, squareSize);
Mat drawingCanvas = new Mat(canvas, drawingRegion);
Mat drawingSource = new Mat(imageGray, drawingRegion);
Cv2.Add(drawingCanvas, drawingSource, drawingCanvas);
Cv2.ImShow("Image2", canvas);
}
}
public static void render_2D(ref OpenCvSharp.Mat left_display, sl.float2 img_scale, ref sl.Objects objects, bool render_mask, bool isTrackingON)
{
OpenCvSharp.Mat overlay = left_display.Clone();
OpenCvSharp.Rect roi_render = new OpenCvSharp.Rect(0, 0, left_display.Size().Width, left_display.Size().Height);
OpenCvSharp.Mat mask = new OpenCvSharp.Mat(left_display.Rows, left_display.Cols, OpenCvSharp.MatType.CV_8UC1);
int line_thickness = 2;
for (int i = 0; i < objects.numObject; i++)
{
sl.ObjectData obj = objects.objectData[i];
if (Utils.renderObject(obj, isTrackingON))
{
OpenCvSharp.Scalar base_color = Utils.generateColorID_u(obj.id);
// Display image scale bouding box 2d
if (obj.boundingBox2D.Length < 4)
{
continue;
}
Point top_left_corner = Utils.cvt(obj.boundingBox2D[0], img_scale);
Point top_right_corner = Utils.cvt(obj.boundingBox2D[1], img_scale);
Point bottom_right_corner = Utils.cvt(obj.boundingBox2D[2], img_scale);
Point bottom_left_corner = Utils.cvt(obj.boundingBox2D[3], img_scale);
// Create of the 2 horizontal lines
Cv2.Line(left_display, top_left_corner, top_right_corner, base_color, line_thickness);
Cv2.Line(left_display, bottom_left_corner, bottom_right_corner, base_color, line_thickness);
// Creation of two vertical lines
Utils.drawVerticalLine(ref left_display, bottom_left_corner, top_left_corner, base_color, line_thickness);
Utils.drawVerticalLine(ref left_display, bottom_right_corner, top_right_corner, base_color, line_thickness);
// Scaled ROI
OpenCvSharp.Rect roi = new OpenCvSharp.Rect(top_left_corner.X, top_left_corner.Y, (int)top_right_corner.DistanceTo(top_left_corner), (int)bottom_right_corner.DistanceTo(top_right_corner));
overlay.SubMat(roi).SetTo(base_color);
sl.float2 position_image = getImagePosition(obj.boundingBox2D, img_scale);
Cv2.PutText(left_display, obj.label.ToString(), new Point(position_image.x - 20, position_image.y - 12), HersheyFonts.HersheyComplexSmall, 0.5f, new Scalar(255, 255, 255, 255), 1);
if (!float.IsInfinity(obj.position.Z))
{
string text = Math.Abs(obj.position.Z).ToString("0.##M");
Cv2.PutText(left_display, text, new Point(position_image.x - 20, position_image.y), HersheyFonts.HersheyComplexSmall, 0.5, new Scalar(255, 255, 255, 255), 1);
}
}
}
// Here, overlay is as the left image, but with opaque masks on each detected objects
Cv2.AddWeighted(left_display, 0.7, overlay, 0.3, 0.0, left_display);
}
public static unsafe Mat ExtractRect(Mat src, OpenCvSharp.Rect position)
{
Mat ret = new Mat(position.Height, position.Width, MatType.CV_8UC3);
int top = position.Top;
int bottom = position.Bottom;
int left = position.Left;
int right = position.Right;
int src_channels = src.Channels();
long ret_step = ret.Step();
long src_step = src.Step();
int src_height = src.Height;
int src_width = src.Width;
byte *ps = (byte *)src.Data.ToPointer();
byte *pr = (byte *)ret.Data.ToPointer();
#if RELEASE_PARALLEL
Parallel.For(0, src_height, y =>
{
if (top <= y && y <= bottom)
{
for (int x = 0; x < src_width; ++x)
{
if (left <= x && x <= right)
{
for (int c = 0; c < src_channels; ++c)
{
*(pr + (y - top) * ret_step + (x - left) * src_channels + c) = *(ps + y * src_step + x * src_channels + c);
}
}
}
}
});
#else
for (int y = 0; y < src_height; ++y)
{
if (top <= y && y <= bottom)
{
for (int x = 0; x < src_width; ++x)
{
if (left <= x && x <= right)
{
for (int c = 0; c < src_channels; ++c)
{
*(pr + (y - top) * ret_step + (x - left) * src_channels + c) = *(ps + y * src_step + x * src_channels + c);
}
}
}
}
}
#endif
return(ret);
}
void drawColorSampler(Mat input)
{
int frameWidth = input.Size().Width, frameHeight = input.Size().Height;
int rectangleSize = 40;
Scalar rectangleColor = new Scalar(255, 0, 255);
skinColorSamplerRectangle1 = new OpenCvSharp.Rect(160, frameHeight / 2, rectangleSize, rectangleSize);
skinColorSamplerRectangle2 = new OpenCvSharp.Rect(160, frameHeight / 3, rectangleSize, rectangleSize);
Cv2.Rectangle(
input,
skinColorSamplerRectangle1,
rectangleColor
);
Cv2.Rectangle(
input,
skinColorSamplerRectangle2,
rectangleColor
);
backgroundColorSamplerRectangle1 = new OpenCvSharp.Rect(80, 80, rectangleSize, rectangleSize);
backgroundColorSamplerRectangle2 = new OpenCvSharp.Rect(560, 80, rectangleSize, rectangleSize);
backgroundColorSamplerRectangle3 = new OpenCvSharp.Rect(80, 400, rectangleSize, rectangleSize);
backgroundColorSamplerRectangle4 = new OpenCvSharp.Rect(560, 400, rectangleSize, rectangleSize);
Cv2.Rectangle(
input,
backgroundColorSamplerRectangle1,
rectangleColor
);
Cv2.Rectangle(
input,
backgroundColorSamplerRectangle2,
rectangleColor
);
Cv2.Rectangle(
input,
backgroundColorSamplerRectangle3,
rectangleColor
);
Cv2.Rectangle(
input,
backgroundColorSamplerRectangle4,
rectangleColor
);
}
private List <Cv.Rect> MergeRects(List <Cv.Rect> rects, int width, int height)
{
List <int> ignoreIndices = new List <int>();
rects.Sort((l, r) => l.X.CompareTo(r.X));
for (int i = 0; i < rects.Count; i++)
{
if (ignoreIndices.Contains(i))
{
continue;
}
for (int j = i + 1; j < rects.Count; j++)
{
if (rects[j].Height < 5 || rects[j].Width < 5)
{
ignoreIndices.Add(j);
continue;
}
var hExpand = (int)Math.Round(width * 0.01, 0);
var r = new Cv.Rect(rects[j].X, rects[j].Y, rects[j].Width, rects[j].Height);
r.Inflate(hExpand / 2, 0);
if (rects[i].IntersectsWith(r))
{
var union = rects[i].Union(rects[j]);
if (union.Width < width * 0.30 && union.Height < height * 0.05)
{
rects[i] = union;
ignoreIndices.Add(j);
}
}
}
}
var merged = new List <Cv.Rect>();
for (int i = 0; i < rects.Count; i++)
{
rects[i] = FixInvalidRects(rects[i], width, height);
if (!ignoreIndices.Contains(i))
{
merged.Add(rects[i]);
}
}
return(merged);
}
public bool CreateGrabCut(ref System.Drawing.Bitmap src, out System.Drawing.Bitmap dst, bool displayWindows = false)
{
dst = null;
Mat srcImg = BitmapConverter.ToMat(src);
Cv2.CvtColor(srcImg, srcImg, ColorConversionCodes.BGRA2BGR);
Mat mask = new Mat(new OpenCvSharp.Size(src.Width, src.Height), MatType.CV_8UC1, 0);
//dilate process
//Cv2.Dilate(srcImg, dstImg, new Mat());
//grabcut
//Mat bgdModel = new Mat(new OpenCvSharp.Size(65, 1), MatType.CV_64FC1);
//Mat fgdModel = new Mat(new OpenCvSharp.Size(65, 1), MatType.CV_64FC1);
Mat bgdModel = new Mat();
Mat fgdModel = new Mat();
OpenCvSharp.Rect r = new OpenCvSharp.Rect(50, 50, (int)Width - 100, (int)Height - 100);
Cv2.GrabCut(srcImg, mask, r, bgdModel, fgdModel, 1, GrabCutModes.InitWithRect);
for (int i = mask.Cols / 2 - 50; i < mask.Cols / 2 + 50; i++)
{
for (int j = mask.Rows / 2 - 25; j < mask.Rows / 2 + 75; j++)
{
mask.Set <byte>(j, i, 1);
}
}
Cv2.GrabCut(srcImg, mask, r, bgdModel, fgdModel, 1, GrabCutModes.InitWithMask);
for (int i = 0; i < mask.Cols; i++)
{
for (int j = 0; j < mask.Rows; j++)
{
byte e = mask.Get <byte>(j, i);
if (e == 0 | e == 2)
{
mask.Set <byte>(j, i, 0);
}
else
{
mask.Set <byte>(j, i, 255);
}
}
}
Mat res = srcImg.Clone();
dst = BitmapConverter.ToBitmap(mask);
return(true);
}
// Use this for initialization
private void Start () {
if (isVid) {
frame = new Mat ();
//gray = new Mat();
cap = new VideoCapture (1);
tex = new Texture2D (cap.FrameWidth, cap.FrameHeight);
bkrnd_win_size = 20; //cap.FrameWidth / 5;
cap.Read (frame);
} else {
frame = new Mat(Application.dataPath + "/profile_photo.png", ImreadModes.Color);
tex = new Texture2D (frame.Width, frame.Height);
bkrnd_win_size = 20;//frame.Width / 5;
}
frame_backproj = new Mat ();
mask = new Mat ();
tex.LoadImage (frame.ToBytes (".png", new int[]{0}));
go.GetComponent<Renderer> ().material.mainTexture = tex;
//myDetector = new CascadeClassifier ("C:/Users/admin/opencv/build/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml");
bkrnd_rect = new OpenCvSharp.Rect(1,1,bkrnd_win_size,bkrnd_win_size);
}
