private void Test3()
{
byte[] imageData = System.IO.File.ReadAllBytes(@"./wwwroot/images/template2.png");
Mat img1 = Mat.FromImageData(imageData, ImreadModes.Color);
Mat gray1 = Mat.FromImageData(imageData, ImreadModes.Grayscale);
//gray1 = gray1.GaussianBlur (new OpenCvSharp.Size(3, 3), 0);
gray1 = gray1.AdaptiveThreshold(255, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.BinaryInv, 105, 2); // 11,2 ; 75,10 ; 60,255
//gray1 = gray1.Threshold(60, 255, ThresholdTypes.BinaryInv);
//Canny Edge Detector
//Image<Gray, Byte> cannyGray = gray1.Canny(20, 50);
//Image<Bgr, Byte> imageResult = img1.Copy();
//Mat cannyGray = gray1.Canny(20, 35); // 0, 12, blur 9; 2, 17, blur 7; 0, 25 blur 13; 20 35 blur 0
//var cannyGray = gray1;
//Cv2.FindContours(cannyGray, out var contours, out var hierarchy, mode: RetrievalModes.Tree, method: ContourApproximationModes.ApproxSimple);
Mat copy = gray1.Clone();
copy.SaveImage("wwwroot/images/output.png");
}
public static Mat AdaptiveTresholding(Mat greyImage, int c = 2, double perc = 0.001)
{
//var spix = (int)Math.Sqrt(greyImage.Width * greyImage.Height * perc);
//spix = spix % 2 == 1 ? spix : spix + 1;
//spix = spix < 3 ? 3 : spix;
var thresh = greyImage.AdaptiveThreshold(255, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.Binary, 11, c);
return(thresh);
}
private Rectangle[] DetectMeterNumbers(Mat image)
{
var blobDetector = new BlobDetector();
var threshold = image.AdaptiveThreshold(255,
AdaptiveThresholdTypes.GaussianC,
_settings.DarkSectors ? ThresholdTypes.Binary : ThresholdTypes.BinaryInv,
_settings.NumbersDetectionAdaptiveThresholdBlockSize,
_settings.NumbersDetectionAdaptiveThresholdC);
return(blobDetector.DetectMeterNumbers(threshold).ToArray());
}
private static Mat apply_doc_filters(Mat image)
{
//if closed rectangle of the document cant be detected then we will not transform the image but just apply simple filter to make it look like scanned doc
//apply grayscale
//Step 6: grayscale it to give it that 'black and white' paper effect
image = image.CvtColor(ColorConversionCodes.BGR2GRAY);
//transformImage = transformImage.Threshold(127, 255, ThresholdTypes.Binary);
//transformImage = transformImage.Dilate(null);
image = image.AdaptiveThreshold(255, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.Binary, 17, 11);
////add a border to the image to act as border of the doc
//modifiedImage = modifiedImage.CopyMakeBorder(5, 5, 5, 5, BorderTypes.Constant, value: Scalar.Black);
return(image);
}
static void Main(string[] args)
{
string filePath = @"SampleImage.jpg";
var img = new Mat(filePath, ImreadModes.Grayscale);
Mat orginalImg = new Mat();
img.CopyTo(orginalImg);
img = ReSizeImage(img);
Mat edges = DetectEdges(img);
var points = GetContours(edges);
Mat warpedImg = PointTransform(img, points);
warpedImg = warpedImg.CvtColor(ColorConversionCodes.BayerBG2GRAY);
var thresh = warpedImg.AdaptiveThreshold(225, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.Binary, 11, 2);
Cv2.ImShow("results", thresh);
Cv2.WaitKey();
}
