/// <summary>
/// Finds contours in given mat. Basically all found shapes.
/// Uses RetrExternal to only provide outer bounds.
/// </summary>
/// <param name="mat"></param>
/// <returns>List of contours and their hierarchy</returns>
public (IList <MatOfPoint>, Mat) FindContours(Mat mat)
{
Mat ret = mat.Clone();
IList <MatOfPoint> contours = new JavaList <MatOfPoint>();
List <MatOfPoint> filteredContours = new List <MatOfPoint>();
Mat hierachy = new Mat();
Imgproc.FindContours(mat, contours, hierachy, Imgproc.RetrExternal, Imgproc.ChainApproxNone);
return(contours, hierachy);
}
public void Process(Mat rgbaImage)
{
Log.Info(TAG, "Process rgbaImages");
Imgproc.PyrDown(rgbaImage, mPyrDownMat);
Imgproc.PyrDown(mPyrDownMat, mPyrDownMat);
Imgproc.CvtColor(mPyrDownMat, mHsvMat, Imgproc.ColorRgb2hsvFull);
Core.InRange(mHsvMat, mLowerBound, mUpperBound, mMask);
Imgproc.Dilate(mMask, mDilatedMask, new Mat());
IList <MatOfPoint> contours = new JavaList <MatOfPoint>();
Imgproc.FindContours(mDilatedMask, contours, mHierarchy, Imgproc.RetrExternal, Imgproc.ChainApproxSimple);
// Find max contour area
double maxArea = 0;
foreach (var each in contours)
{
MatOfPoint wrapper = each;
double area = Imgproc.ContourArea(wrapper);
if (area > maxArea)
{
maxArea = area;
}
Log.Info(TAG, "Process rgbaImages\t-- Imgproc.ContourArea(wrapper)");
}
// Filter contours by area and resize to fit the original image size
mContours.Clear();
foreach (var each in contours)
{
MatOfPoint contour = each;
if (Imgproc.ContourArea(contour) > mMinContourArea * maxArea)
{
Core.Multiply(contour, new Scalar(4, 4), contour);
mContours.Add(contour);
Log.Info(TAG, "Process rgbaImages\t-- mContours.Add(contour)");
}
}
}
private bool Detect(Mat bin)
{
// Reset
mRects.Clear();
// Find contours
Mat hierarchy = new Mat();
IList <MatOfPoint> contoursList = new JavaList <MatOfPoint>();
Imgproc.FindContours(bin.Clone(), contoursList, hierarchy, Imgproc.RetrTree, Imgproc.ChainApproxSimple);
// Filter contours
bool detected = false;
for (int iContour = 0; iContour < contoursList.Count(); iContour++)
{
// Areas
Core.Rect rect = Imgproc.BoundingRect(contoursList[iContour]);
double ellipseArea = PI * (rect.Width / 2) * (rect.Height / 2);
double area = Imgproc.ContourArea(contoursList[iContour]);
// Ratios
double boundWidthPerHeight = (double)rect.Width / rect.Height;
double areaPerEllipse = (double)(area) / ellipseArea;
double rectPerFrame = (double)(rect.Area()) / (bin.Size().Width *bin.Size().Height);
// Check constraints
if (rectPerFrame > MIN_SIGN_SIZE_PER_FRAME)
{
if (1 - LIMIT_DIF_SIGN_SIZE < boundWidthPerHeight && boundWidthPerHeight < 1 + LIMIT_DIF_SIGN_SIZE)
{
if (1 - LIMIT_DIF_SIGN_AREA < areaPerEllipse && areaPerEllipse < 1 + LIMIT_DIF_SIGN_AREA)
{
mRects.Add(rect);
detected = true;
}
}
}
}
return(detected);
}
private IList <MatOfPoint> ProcessImage()
{
Mat grayMat = new Mat();
Mat blurMat = new Mat();
Mat edgesMat = new Mat();
Mat final = new Mat();
Mat h = new Mat();
IList <MatOfPoint> contours = new JavaList <MatOfPoint>();
OpenCV.Android.Utils.BitmapToMat(originalImage, originalMat);
originalImage.Dispose();
Imgproc.CvtColor(originalMat, grayMat, Imgproc.ColorBgr2gray);
Imgproc.GaussianBlur(grayMat, blurMat, new OpenCV.Core.Size(3, 3), 0);
Imgproc.Canny(blurMat, edgesMat, 10, 250);
Mat kernel = Imgproc.GetStructuringElement(Imgproc.MorphRect, new Size(3, 3));
Imgproc.MorphologyEx(edgesMat, final, Imgproc.MorphClose, kernel);
Imgproc.FindContours(final, contours, h, Imgproc.RetrExternal, Imgproc.ChainApproxSimple);
return(contours);
}
public override bool OnOptionsItemSelected(IMenuItem item)
{
Log.Info(Tag, "Menu Item selected " + item);
if (item == _itemPickPhoto)
{
var imageIntent = new Intent();
imageIntent.SetType("image/*");
imageIntent.SetAction(Intent.ActionGetContent);
StartActivityForResult(Intent.CreateChooser(imageIntent, "Select photo"), 0);
}
else if (item == _itemGray)
{
// 灰度图
_gray = new Mat(_raw.Width(), _raw.Height(), CvType.Cv8uc1);
Imgproc.CvtColor(_raw, _gray, Imgproc.ColorRgb2gray);
ShowImage(_gray);
}
else if (item == _itemThreshold)
{
// 二值化
_threshold = new Mat(_image.Width, _image.Height, CvType.Cv8uc1);
Imgproc.Threshold(_gray, _threshold, 168, 255, Imgproc.ThreshBinary);
ShowImage(_threshold);
}
else if (item == _itemFindContours)
{
// 查找最大连通区域
IList <MatOfPoint> contours = new JavaList <MatOfPoint>();
Mat hierarchy = new Mat();
var target = _threshold.Clone();
Imgproc.FindContours(target, contours, hierarchy, Imgproc.RetrExternal, Imgproc.ChainApproxNone);
MatOfPoint max = new MatOfPoint();
double contour_area_max = 0;
if (contours.Any())
{
foreach (var contour in contours)
{
var contour_area_temp = Math.Abs(Imgproc.ContourArea(contour));
if (contour_area_temp > contour_area_max)
{
contour_area_max = contour_area_temp;
max = contour;
}
}
}
var last = new JavaList <MatOfPoint>();
last.Add(max);
Imgproc.DrawContours(_raw, last, -1, new Scalar(255, 0, 0));
ShowImage(_raw);
}
else if (item == _itemCreateTrimap)
{
// 生成三元图 暂时先用生成的图替代
var imageIntent = new Intent();
imageIntent.SetType("image/*");
imageIntent.SetAction(Intent.ActionGetContent);
StartActivityForResult(Intent.CreateChooser(imageIntent, "Select photo"), 1);
}
else if (item == _itemSharedMatting)
{
// 扣图
var sharedMatting = new SharedMatting();
sharedMatting.SetImage(_raw);
sharedMatting.SetTrimap(_trimap);
sharedMatting.SolveAlpha();
}
return(base.OnOptionsItemSelected(item));
}
public static async Task <string> detectAndExtractText(Bitmap img)
{
//Matrix für die Bilder
Mat large = new Mat();
Mat small = new Mat();
Mat rgb = new Mat();
//Bild zu Matrix umwandeln
Utils.BitmapToMat(img, large);
// downsample and use it for processing
Imgproc.PyrDown(large, rgb);
//Grey
Imgproc.CvtColor(rgb, small, Imgproc.ColorBgr2gray);
//Gradiant
Mat grad = new Mat();
Size morphsize = new Size(3.0, 3.0);
Mat morphKernel = Imgproc.GetStructuringElement(Imgproc.MorphEllipse, morphsize);
Imgproc.MorphologyEx(small, grad, Imgproc.MorphGradient, morphKernel);
//Binarize
Mat bw = new Mat();
Imgproc.Threshold(grad, bw, 0.0, 255.0, Imgproc.ThreshBinary | Imgproc.ThreshOtsu);
// connect horizontally oriented regions
Mat connected = new Mat();
Size connectsize = new Size(9.0, 1.0);
morphKernel = Imgproc.GetStructuringElement(Imgproc.MorphRect, connectsize);
Imgproc.MorphologyEx(bw, connected, Imgproc.MorphClose, morphKernel);
// find contours
Mat mask = Mat.Zeros(bw.Size(), CvType.Cv8uc1);
JavaList <MatOfPoint> contours = new JavaList <MatOfPoint>();
Mat hierarchy = new Mat();
OpenCV.Core.Point contourPoint = new OpenCV.Core.Point(0, 0);
Imgproc.FindContours(connected, contours, hierarchy, Imgproc.RetrCcomp, Imgproc.ChainApproxSimple, contourPoint);
Scalar zero = new Scalar(0, 0, 0);
Scalar contourscal = new Scalar(255, 255, 255);
Scalar rectScalar = new Scalar(0, 255, 0);
OpenCV.Core.Rect rect;
Mat maskROI;
double r;
double[] contourInfo;
string resulttext = "";
string part;
Bitmap bmpOcr;
Mat croppedPart;
for (int i = 0; i >= 0;)
{
rect = Imgproc.BoundingRect(contours[i]);
maskROI = new Mat(mask, rect);
maskROI.SetTo(zero);
//fill the contour
Imgproc.DrawContours(mask, contours, i, contourscal, Core.Filled);
// ratio of non-zero pixels in the filled region
r = (double)Core.CountNonZero(maskROI) / (rect.Width * rect.Height);
/* assume at least 45% of the area is filled if it contains text */
/* constraints on region size */
/* these two conditions alone are not very robust. better to use something
* like the number of significant peaks in a horizontal projection as a third condition */
if (r > .45 && (rect.Height > 8 && rect.Width > 8))
{
//Imgproc.Rectangle(rgb, rect.Br(), rect.Tl(), rectScalar, 2);
try
{
croppedPart = rgb.Submat(rect);
bmpOcr = Bitmap.CreateBitmap(croppedPart.Width(), croppedPart.Height(), Bitmap.Config.Argb8888);
Utils.MatToBitmap(croppedPart, bmpOcr);
part = await OCR.getText(bmpOcr);
resulttext = resulttext + part;
Console.WriteLine("------------------Durchlauf-------------");
}
catch (Exception e)
{
Android.Util.Log.Debug("Fehler", "cropped part data error " + e.Message);
}
}
//Nächste Element bestimmen
contourInfo = hierarchy.Get(0, i);
i = (int)contourInfo[0];
}
return(resulttext);
}
