//static Mat pre_Prosessing()
//{
// Mat fdfdfd= new Mat();
// return fdfdfd; 이미지와 배열을 리턴해줘야한다.
//}//전처리하는부분
static void Main(string[] args)
{
Mat src = Cv2.ImRead("./samples2/209.bmp");
Mat gray = new Mat(src.Size(), MatType.CV_8UC1);
Mat binary = new Mat(src.Size(), MatType.CV_8UC1);
Mat dst = src.Clone();
Mat rotate = new Mat();
Mat Roi = new Mat();
double angle = default;
Point[][] contours;
HierarchyIndex[] hier;
Mat kernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);
Cv2.Threshold(gray, binary, 40, 255, ThresholdTypes.Binary);
Cv2.ImShow("aa", binary);
// 존좋탱
//Point[][] contour;
//HierarchyIndex[] hieracy;
//Cv2.FindContours(binary, out contour, out hieracy, RetrievalModes.CComp, ContourApproximationModes.ApproxSimple);
//Cv2.DrawContours(src, contour, -1, new Scalar(0, 0, 255), 3);
//Cv2.ImShow("cc", src);
// 진우탱 : 레이블을 계산 - 2개 초과이면 불량품
Mat ds = gray.Clone();
Mat noise = new Mat();
Cv2.Threshold(ds, ds, 195, 255, ThresholdTypes.Binary);
Cv2.BitwiseXor(binary, ds, noise);
Cv2.BitwiseXor(noise, ds, noise);
Cv2.ImShow("noise", noise);
Point[][] contour;
HierarchyIndex[] hieracy;
Cv2.FindContours(ds, out contour, out hieracy, RetrievalModes.CComp, ContourApproximationModes.ApproxNone);
Cv2.DrawContours(src, contour, -1, new Scalar(0, 0, 255), 3);
Cv2.ImShow("linecheck", src);
Console.WriteLine("개수 : " + contour.Length);
if (contour.Length > 2)
{
Console.WriteLine("불량품");
}
else
{
Console.WriteLine("양품");
}
//Cv2.ImShow("bb", binary - gray);
//Cv2.MorphologyEx(binary, binary, MorphTypes.Close, kernel, new Point(-1, -1), 5);
//Cv2.MorphologyEx(binary, binary, MorphTypes.Erode, kernel, new Point(-1, -1), 20);
//Cv2.MorphologyEx(binary, binary, MorphTypes.Dilate, kernel, new Point(-1, -1), 20);
//Cv2.FindContours(binary, out contours, out hier, RetrievalModes.External, ContourApproximationModes.ApproxTC89KCOS);
//Point[] point_rect = new Point[4];
//for (int i = 0; i < contours.Length; i++)
//{
// double perimeter = Cv2.ArcLength(contours[i], true);
// double epsilon = perimeter * 0.04;
// Point[] approx = Cv2.ApproxPolyDP(contours[i], epsilon, true);
// Point[][] draw_approx = new Point[][] { approx };
// // Cv2.DrawContours(dst, contours, -1, new Scalar(0, 0, 255), 2, LineTypes.AntiAlias);
// Cv2.DrawContours(dst, draw_approx, -1, new Scalar(255, 0, 0), 2, LineTypes.AntiAlias);
// // 좌표를 표시하는 부분
// for (int j = 0; j < approx.Length; j++)
// {
// Cv2.Circle(dst, approx[j], 1, new Scalar(0, 0, 255), 3);
// point_rect[j] = approx[j];
// Console.WriteLine(point_rect[j]);
// }
//}
////ROI를 검출하는 로직 x의 min, max 과 y의 min,max 찾기
//int max_x = 0;
//int min_x = int.MaxValue;
//int max_y = 0;
//int min_y = int.MaxValue;
//angle = calculate_angle(point_rect);
//Roi = make_ROI(dst, min_y, max_y, min_x, max_x, point_rect);
//rotate = Rotate_rect(Roi, angle);
//Console.WriteLine(angle);
//Cv2.ImShow("src", src);
//Cv2.ImShow("binary", binary);
//Cv2.ImShow("dst", dst);
//Cv2.ImShow("Roi", Roi);
//Cv2.ImShow("Rotate", rotate);
Cv2.WaitKey(0);
Cv2.DestroyAllWindows();
}
void Form3_FormClosed(object sender, FormClosedEventArgs e)
{
Cv2.DestroyAllWindows();
timer1.Enabled = true;
Show();
}
public static FormExtractionResult ProcessImage(string filename, FormExtractionOptions options = null)
{
if (options == null)
{
// Assume recommanded parameters.
options = new FormExtractionOptions();
}
var orig = new Mat(filename);
var image = new Mat(filename, ImreadModes.GrayScale);
Cv2.AdaptiveThreshold(image, image, 255, AdaptiveThresholdTypes.MeanC, ThresholdTypes.Binary, 9, 4);
// Resize image if too large.
if (image.Width > options.ResizeWidth)
{
var height = options.ResizeWidth * image.Height / image.Width;
Cv2.Resize(image, image, new Size(options.ResizeWidth, height));
}
Cv2.BitwiseNot(image, image);
Cv2.Dilate(image, image, Cv2.GetStructuringElement(MorphShapes.Cross, new Size(2, 2)));
MatOfByte mat = new MatOfByte(image);
MatIndexer <byte> indexer = mat.GetIndexer();
var row = image.Height;
var col = image.Width;
Mat newImage = new Mat(row, col, MatType.CV_8UC3);
newImage.SetTo(Scalar.Black);
// We must determine if it "may" be an interesting blob.
Stopwatch watch = new Stopwatch();
watch.Start();
int[] imgData = new int[row * col];
for (int y = 0; y < row; y++)
{
for (int x = 0; x < col; x++)
{
imgData[y + x * row] = indexer[y, x];
}
}
var result = HasBoxes(imgData, row, col, options);
watch.Stop();
result.Duration = watch.Elapsed;
// Preview
if (result.Boxes.Any() && image.Width != 0 && options.ShowDebugImage)
{
var img = CreateImage(result.DebugImg, hasColor: true);
Cv2.BitwiseOr(newImage, img, newImage);
Cv2.BitwiseNot(image, image);
int width = 400;
var height = width * image.Height / image.Width;
Cv2.Resize(orig, orig, new Size(width, height));
Cv2.Resize(image, image, new Size(width, height));
Cv2.Resize(newImage, newImage, new Size(width, height));
using (new Window("orig", orig))
using (new Window("pre", image))
using (new Window("post", newImage))
{
Cv2.WaitKey();
Cv2.DestroyAllWindows();
}
}
// Dispose.
orig.Dispose();
image.Dispose();
newImage.Dispose();
mat.Dispose();
return(result);
}
public void Locate(Mat mat, MyFlags localiseFlags)
{
if (mat == null || mat.Empty())
{
return;
}
if (localiseFlags == null)
{
return;
}
using (Mat hsv = new Mat())
using (Mat ball = new Mat())
using (Mat car1 = new Mat())
using (Mat car2 = new Mat())
//using (Mat merged = new Mat())
using (Mat black = new Mat(mat.Size(), MatType.CV_8UC1))
{
Cv2.CvtColor(mat, hsv, ColorConversionCodes.RGB2HSV);
MyFlags.LocConfigs configs = localiseFlags.configs;
Cv2.InRange(hsv,
new Scalar(configs.hue0Lower, configs.saturation0Lower, configs.valueLower),
new Scalar(configs.hue0Upper, 255, 255),
ball);
Cv2.InRange(hsv,
new Scalar(configs.hue1Lower, configs.saturation1Lower, configs.valueLower),
new Scalar(configs.hue1Upper, 255, 255),
car1);
Cv2.InRange(hsv,
new Scalar(configs.hue2Lower, configs.saturation2Lower, configs.valueLower),
new Scalar(configs.hue2Upper, 255, 255),
car2);
if (localiseFlags.showMask)
{
Cv2.ImShow("Ball", ball);
Cv2.ImShow("CarA", car1);
Cv2.ImShow("CarB", car2);
}
else
{
Cv2.DestroyAllWindows();
}
Point2i[][] contours0, contours1, contours2;
contours0 = Cv2.FindContoursAsArray(ball, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
contours1 = Cv2.FindContoursAsArray(car1, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
contours2 = Cv2.FindContoursAsArray(car2, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
foreach (Point2i[] c0 in contours0)
{
Point2i centre = new Point2i();
Moments moments = Cv2.Moments(c0);
centre.X = (int)(moments.M10 / moments.M00);
centre.Y = (int)(moments.M01 / moments.M00);
double area = moments.M00;
if (area <= configs.areaLower / 4)
{
continue;
}
centres0.Add(centre);
}
foreach (Point2i[] c1 in contours1)
{
Point2i centre = new Point2i();
Moments moments = Cv2.Moments(c1);
centre.X = (int)(moments.M10 / moments.M00);
centre.Y = (int)(moments.M01 / moments.M00);
double area = moments.M00;
if (area <= configs.areaLower)
{
continue;
}
centres1.Add(centre);
}
foreach (Point2i[] c2 in contours2)
{
Point2i centre = new Point2f();
Moments moments = Cv2.Moments(c2);
centre.X = (int)(moments.M10 / moments.M00);
centre.Y = (int)(moments.M01 / moments.M00);
double area = moments.M00;
if (area <= configs.areaLower)
{
continue;
}
centres2.Add(centre);
}
foreach (Point2i c0 in centres0)
{
Cv2.Circle(mat, c0, 1, new Scalar(0x1b, 0xa7, 0xff), -1);
}
foreach (Point2i c1 in centres1)
{
Cv2.Circle(mat, c1, 10, new Scalar(0x1b, 0xff, 0xa7), -1);
}
foreach (Point2i c2 in centres2)
{
Cv2.Circle(mat, c2, 10, new Scalar(0x00, 0x98, 0xff), -1);
}
if (localiseFlags.gameState != GameState.Unstart)
{
for (int i = 0; i < localiseFlags.currPersonNum; ++i)
{
int x10 = localiseFlags.posPersonStart[i].X - 8;
int y10 = localiseFlags.posPersonStart[i].Y - 8;
Cv2.Rectangle(mat, new Rect(x10, y10, 16, 16), new Scalar(0xf3, 0x96, 0x21), -1);
}
}
//Cv2.Merge(new Mat[] { car1, car2, black }, merged);
//Cv2.ImShow("binary", merged);
}
}
private void Form1_Load(object sender, EventArgs e)
{
var model = "opencv_face_detector_uint8.pb"; //tensorflow 학습된 모델 파일
var config = "opencv_face_detector.pbtxt"; // 구성 파일
var confidence = 0.0;
var x1 = 0.0;
var x2 = 0.0;
var y1 = 0.0;
var y2 = 0.0;
int cnt = 0;
video = new VideoCapture(1); //video 1번(ManyCam) 사용
if (!video.IsOpened()) //video 초기화 안될 시 error
{
Console.WriteLine("error");
return;
}
Net net = CvDnn.ReadNet(model, config);
if (net.Empty())
{
Console.WriteLine("error");
return;
}
frame = new Mat();
while (true)
{
video.Read(frame);
if (frame.Empty())
{
break;
}
//frame blob 입력 설정된 부분을 net
Mat blob = CvDnn.BlobFromImage(frame, 1.0, new OpenCvSharp.Size(300, 300), new Scalar(104, 177, 123));
net.SetInput(blob);
Mat res = net.Forward();
var detect = res.Reshape(1, res.Cols * res.Rows);
for (int i = 0; i < detect.Rows; i++) //Face recongition
{
confidence = detect.At <float>(i, 2);
if (confidence < 0.5)
{
break; //Face recongition 0.5 이하는 무시
}
//get center and width/height
x1 = Math.Round(detect.At <float>(i, 3) * frame.Cols); //좌표 계산
y1 = Math.Round(detect.At <float>(i, 4) * frame.Rows);
x2 = Math.Round(detect.At <float>(i, 5) * frame.Cols);
y2 = Math.Round(detect.At <float>(i, 6) * frame.Rows);
string Label = string.Format("Face:" + confidence); // 1. Face recongition을 시각화하는 작업
//2. confidence > 0.955 greenbox 생성
if (confidence > 0.955)
{
Cv2.Rectangle(frame, new OpenCvSharp.Point(x1, y1), new OpenCvSharp.Point(x2, y2), new Scalar(0, 255, 0));
Cv2.PutText(frame, Label, new OpenCvSharp.Point(x1, y1 - 1), OpenCvSharp.HersheyFonts.Italic, 0.8, new Scalar(0, 255, 0));
}
//2. 아닐 시 redbox 생성
else
{
Cv2.Rectangle(frame, new OpenCvSharp.Point(x1, y1), new OpenCvSharp.Point(x2, y2), new Scalar(0, 0, 255));
Cv2.PutText(frame, Label, new OpenCvSharp.Point(x1, y1 - 1), OpenCvSharp.HersheyFonts.Italic, 0.8, new Scalar(0, 0, 255));
}
}
Cv2.ImShow("FACE ID", frame);
if (confidence > 0.997910)
{
cnt++;
if (cnt >= 30) //30번 인식시 파일 save
{
_saveName = "C:/images/" + DateTime.Now.ToString("yyyy/MM/dd_hh_mm_ss") + ".jpeg";
Cv2.ImWrite(_saveName, frame);
video.Release();
Cv2.DestroyAllWindows();
break;
}
}
if (Cv2.WaitKey(1) == 27) //아스키코드 27 : esc
{
break;
}
}
Delay(100);
inCvImage = Cv2.ImRead(_saveName); //2번
Cv2.Transpose(inCvImage, inCvImage);
outCvImage = new Mat();
Cv2.CvtColor(inCvImage, outCvImage, ColorConversionCodes.BGR2GRAY);
Cv2.EqualizeHist(outCvImage, outCvImage);
Cv2ToOutImage();
//사각박스 내부만 나오게 설정
for (int rgb = 0; rgb < 3; rgb++)
{
for (int i = 0; i < _outH; i++)
{
for (int k = 0; k < _outW; k++)
{
if ((x1 <= i && i <= x2) && (y1 <= k && k <= y2))
{
_outImage[rgb, i, k] = (byte)(255 - _outImage[rgb, i, k]);
}
else
{
_outImage[rgb, i, k] = 0;
}
}
}
}
DisplayImage();
connStr = "Server=127.0.0.1; Uid=root; Pwd=1234;Database=HYDB;CHARSET=UTF8";
conn = new MySqlConnection(connStr);
//db로 전달
dbUpload();
CCTV ma = new CCTV();
ma.ShowDialog();
Close();
} //1. 얼굴인식 후 저장 및 blob 업로드
//1ms FL = 40 binary threshold
public bool Test()
{
var rootDir = @"P:\Projects\N3 Imaging\Images\06272018_16natural_4_syn_binning\SWUV lamp phos";
var files = Directory.GetFiles(rootDir, "*.bmp", SearchOption.TopDirectoryOnly);
Mat combinedMask = null;
Mat whiteLight = Cv2.ImRead(@"P:\Projects\N3 Imaging\Images\06272018_16natural_4_syn_binning\whitelight.bmp");
foreach (var file in files)
{
var fl = Cv2.ImRead(file);
Mat mask;
var res = PlMask(fl, 20, out mask);
if (combinedMask == null)
{
combinedMask = Mat.Zeros(mask.Size(), mask.Type());
}
Cv2.Add(mask, combinedMask, combinedMask);
}
Mat element = Cv2.GetStructuringElement(MorphShapes.Ellipse,
new OpenCvSharp.Size(9, 9),
new OpenCvSharp.Point(2, 2));
Cv2.Dilate(combinedMask, combinedMask, element);
//find contours on this mask
Mat[] contours;
var hierarchy = new List <Point>();
Cv2.FindContours(combinedMask, out contours, OutputArray.Create(hierarchy), RetrievalModes.External,
ContourApproximationModes.ApproxSimple);
//remove small size contours
List <Mat> bigContours = new List <Mat>();
foreach (var contour in contours)
{
if (Cv2.ContourArea(contour) > 400)
{
bigContours.Add(contour);
}
}
combinedMask = Mat.Zeros(combinedMask.Size(), MatType.CV_8UC1);
Cv2.DrawContours(combinedMask, bigContours, -1, Scalar.White);
//get centers of contours
for (int i = 0; i < bigContours.Count; i++)
{
var c = bigContours[i];
var m = c.Moments(true);
var x = m.M10 / m.M00;
var y = m.M01 / m.M00;
Cv2.DrawContours(whiteLight, bigContours, i, new Scalar(255, 0, 0), 4);
Cv2.PutText(whiteLight, "F", new Point(x, y), HersheyFonts.HersheySimplex, 1, new Scalar(0, 0, 255), 4);
}
Cv2.ImShow("mask", combinedMask);
Cv2.ImShow("whiteLight", whiteLight);
Cv2.WaitKey();
Cv2.DestroyAllWindows();
return(true);
}
