org.opencv.imgproc.Imgproc.findContours()方法的使用及代码示例

x33g5p2x  于2022-01-21 转载在 其他  
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本文整理了Java中org.opencv.imgproc.Imgproc.findContours()方法的一些代码示例，展示了Imgproc.findContours()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Imgproc.findContours()方法的具体详情如下：
包路径：org.opencv.imgproc.Imgproc
类名称：Imgproc
方法名：findContours

Imgproc.findContours介绍

[英]Finds contours in a binary image.

The function retrieves contours from the binary image using the algorithm [Suzuki85]. The contours are a useful tool for shape analysis and object detection and recognition. See squares.c in the OpenCV sample directory.

Note: Source image is modified by this function. Also, the function does not take into account 1-pixel border of the image (it's filled with 0's and used for neighbor analysis in the algorithm), therefore the contours touching the image border will be clipped.

Note: If you use the new Python interface then the CV_ prefix has to be omitted in contour retrieval mode and contour approximation method parameters (for example, use cv2.RETR_LIST and cv2.CHAIN_APPROX_NONE parameters). If you use the old Python interface then these parameters have the CV_ prefix (for example, use cv.CV_RETR_LIST and cv.CV_CHAIN_APPROX_NONE).

Note:

  • An example using the findContour functionality can be found at opencv_source_code/samples/cpp/contours2.cpp
  • An example using findContours to clean up a background segmentation result at opencv_source_code/samples/cpp/segment_objects.cpp
  • (Python) An example using the findContour functionality can be found at opencv_source/samples/python2/contours.py
  • (Python) An example of detecting squares in an image can be found at opencv_source/samples/python2/squares.py
    [中]在二值图像中查找轮廓。
    该函数使用算法[Suzuki85]从二值图像检索轮廓。轮廓线是形状分析、目标检测和识别的有用工具。请参见OpenCV示例目录中的squares.c。
    注意：源image由此函数修改。此外，该函数不考虑图像的1像素边界（它用0填充，并在算法中用于邻居分析），因此将剪裁与图像边界接触的轮廓。
    注意：如果使用新的Python接口，则在轮廓检索模式和轮廓近似方法参数中必须省略CV_前缀（例如，使用cv2.RETR_LIST和cv2.CHAIN_APPROX_NONE参数）。如果使用旧的Python接口，则这些参数具有CV_前缀（例如，使用cv.CV_RETR_LIST和cv.CV_CHAIN_APPROX_NONE）。
    注:
    *使用findContour功能的示例可在opencv_source_code/samples/cpp/contours2中找到。cpp
    *在opencv_源代码/samples/cpp/segment_对象上，使用FindOntours清除背景分割结果的示例。cpp
    *（Python）可以在opencv_source/samples/python2/contours上找到使用findContour功能的示例。派克
    *（Python）在opencv_source/samples/python2/squares中可以找到一个检测图像中正方形的示例。派克

代码示例

代码示例来源：origin: RaiMan/SikuliX2

public static List<MatOfPoint> getContours(Mat mBase, boolean external) {
 Mat mHierarchy = Element.getNewMat();
 List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
 if (external) {
  Imgproc.findContours(mBase, contours, mHierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
 } else {
  Imgproc.findContours(mBase, contours, mHierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
 }
 return contours;
}

代码示例来源：origin: RaiMan/SikuliX2

public static List<Element> detectChanges(Mat base, Mat mChanged) {
 int PIXEL_DIFF_THRESHOLD = 3;
 int IMAGE_DIFF_THRESHOLD = 5;
 Mat mBaseGray = Element.getNewMat();
 Mat mChangedGray = Element.getNewMat();
 Mat mDiffAbs = Element.getNewMat();
 Mat mDiffTresh = Element.getNewMat();
 Mat mChanges = Element.getNewMat();
 List<Element> rectangles = new ArrayList<>();
 Imgproc.cvtColor(base, mBaseGray, toGray);
 Imgproc.cvtColor(mChanged, mChangedGray, toGray);
 Core.absdiff(mBaseGray, mChangedGray, mDiffAbs);
 Imgproc.threshold(mDiffAbs, mDiffTresh, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
 if (Core.countNonZero(mDiffTresh) > IMAGE_DIFF_THRESHOLD) {
  Imgproc.threshold(mDiffAbs, mDiffAbs, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
  Imgproc.dilate(mDiffAbs, mDiffAbs, Element.getNewMat());
  Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
  Imgproc.morphologyEx(mDiffAbs, mDiffAbs, Imgproc.MORPH_CLOSE, se);
  List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
  Mat mHierarchy = Element.getNewMat();
  Imgproc.findContours(mDiffAbs, contours, mHierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
  rectangles = contoursToRectangle(contours);
  Core.subtract(mDiffAbs, mDiffAbs, mChanges);
  Imgproc.drawContours(mChanges, contours, -1, new Scalar(255));
  //logShow(mDiffAbs);
 }
 return rectangles;
}

代码示例来源：origin: nroduit/Weasis

public static List<MatOfPoint> findContours(RenderedImage source, Rectangle area) {
  Mat srcImg = ImageConversion.toMat(Objects.requireNonNull(source), area);
  List<MatOfPoint> contours = new ArrayList<>();
  Mat hierachy = new Mat();
  Imgproc.findContours(srcImg, contours, hierachy, Imgproc.RETR_CCOMP, Imgproc.CHAIN_APPROX_SIMPLE);
  return contours;
}

代码示例来源：origin: openpnp/openpnp

public FluentCv findContours(List<MatOfPoint> contours, String... tag) {
  Mat hierarchy = new Mat();
  Imgproc.findContours(mat, contours, hierarchy, Imgproc.RETR_LIST,
      Imgproc.CHAIN_APPROX_NONE);
  return store(mat, tag);
}

代码示例来源：origin: JavaOpenCVBook/code

Imgproc.findContours(contourMat, contours, new Mat(), Imgproc.CHAIN_APPROX_NONE,Imgproc.CHAIN_APPROX_SIMPLE);
System.out.println("Number of found contours: "+contours.size());
for(int i=0;i<contours.size();i++){

代码示例来源：origin: openpnp/openpnp

@Override
  public Result process(CvPipeline pipeline) throws Exception {
    Mat mat = pipeline.getWorkingImage();
    List<MatOfPoint> contours = new ArrayList<>();
    Mat hierarchy = new Mat();
    Imgproc.findContours(mat, contours, hierarchy, retrievalMode.getCode(), approximationMethod.getCode());
    hierarchy.release();
    return new Result(null, contours);
  }
}

代码示例来源：origin: hschott/Camdroid

protected void execute() {
    out = gray();
    Imgproc.equalizeHist(out, out);
    synchronized (mog) {
      mog.apply(out, this.mask, (double) (-10 + learning_rate) / 10);
    }
    Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_DILATE,
        new Size(3, 3));
    Imgproc.dilate(mask, mask, kernel);
    ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Imgproc.findContours(this.mask, contours, new Mat(),
        Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
    double maxheight = object_max_size * this.in.height() / 100;
    double minheight = object_min_size * this.in.height() / 100;
    Iterator<MatOfPoint> each = contours.iterator();
    each = contours.iterator();
    while (each.hasNext()) {
      MatOfPoint contour = each.next();
      Rect rect = Imgproc.boundingRect(contour);
      if (rect.height > minheight && rect.height < maxheight) {
        Imgproc.rectangle(out, rect.tl(), rect.br(), new Scalar(255,
            0, 0), 1);
      }
    }
  }
}

代码示例来源：origin: nroduit/Weasis

public List<MatOfPoint> getIsoDoseContourPoints(KeyDouble slicePosition, double isoDoseThreshold) {
  List<MatOfPoint> contours = new ArrayList<>();
  // Convert from threshold in cCy to raw pixel value threshold
  double rawThreshold = (isoDoseThreshold / 100) / this.doseGridScaling;
  DicomImageElement dosePlane = (DicomImageElement) this.getDosePlaneBySlice(slicePosition.getValue());
  int rows = dosePlane.getImage().toMat().rows();
  int cols = dosePlane.getImage().toMat().cols();
  Mat src = new Mat(rows, cols, CvType.CV_32FC1);
  Mat thr = new Mat(rows, cols, CvType.CV_32FC1);
  dosePlane.getImage().toMat().convertTo(src, CvType.CV_32FC1);
  Mat hierarchy = new Mat();
  
  Imgproc.threshold(src, thr, rawThreshold, 255, Imgproc.THRESH_BINARY);
  Mat thrSrc = new Mat(rows, cols, CvType.CV_8U);
  thr.convertTo(thrSrc, CvType.CV_8U);
  
  Imgproc.findContours(thrSrc, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);
  return contours;
}

代码示例来源：origin: com.sikulix/sikulixapi

public boolean hasChanges(Mat current) {
 int PIXEL_DIFF_THRESHOLD = 5;
 int IMAGE_DIFF_THRESHOLD = 5;
 Mat bg = new Mat();
 Mat cg = new Mat();
 Mat diff = new Mat();
 Mat tdiff = new Mat();
 Imgproc.cvtColor(base, bg, Imgproc.COLOR_BGR2GRAY);
 Imgproc.cvtColor(current, cg, Imgproc.COLOR_BGR2GRAY);
 Core.absdiff(bg, cg, diff);
 Imgproc.threshold(diff, tdiff, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
 if (Core.countNonZero(tdiff) <= IMAGE_DIFF_THRESHOLD) {
  return false;
 }
 Imgproc.threshold(diff, diff, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
 Imgproc.dilate(diff, diff, new Mat());
 Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5,5));
 Imgproc.morphologyEx(diff, diff, Imgproc.MORPH_CLOSE, se);
 List<MatOfPoint> points = new ArrayList<MatOfPoint>();
 Mat contours = new Mat();
 Imgproc.findContours(diff, points, contours, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
 int n = 0;
 for (Mat pm: points) {
  log(lvl, "(%d) %s", n++, pm);
  printMatI(pm);
 }
 log(lvl, "contours: %s", contours);
 printMatI(contours);
 return true;
}

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