小编Gum*_*shy的帖子

我在StackOverflow中经历了很多问题,能够开发小程序来正确检测正方形和矩形.这是我的示例代码

public static CvSeq findSquares(final IplImage src, CvMemStorage storage) {
    CvSeq squares = new CvContour();
    squares = cvCreateSeq(0, sizeof(CvContour.class), sizeof(CvSeq.class), storage);
    IplImage pyr = null, timg = null, gray = null, tgray;
    timg = cvCloneImage(src);
    CvSize sz = cvSize(src.width(), src.height());
    tgray = cvCreateImage(sz, src.depth(), 1);
    gray = cvCreateImage(sz, src.depth(), 1);
    // cvCvtColor(gray, src, 1);
    pyr = cvCreateImage(cvSize(sz.width() / 2, sz.height() / 2), src.depth(), src.nChannels());
    // down-scale and upscale the image to filter out the noise
    // cvPyrDown(timg, pyr, CV_GAUSSIAN_5x5);
    // …

我正在使用JavaCV开发一个形状识别项目,我发现了一些OpenCV代码来识别特定图像中的U形状.我试图将其转换为JavaCV,但它没有提供相同的输出.你能帮我把这个OpenCV代码转换成JavaCV吗？

这是OpenCV代码:

import cv2
import numpy as np

img = cv2.imread('sofud.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(gray,127,255,1)
contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)

for cnt in contours:
    x,y,w,h = cv2.boundingRect(cnt)
    if 10 < w/float(h) or w/float(h) < 0.1:
        cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2)

cv2.imshow('res',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

这是预期的产出

这是转换后的代码:

import com.googlecode.javacpp.Loader;
import com.googlecode.javacv.CanvasFrame;
import static com.googlecode.javacpp.Loader.*;
import static com.googlecode.javacv.cpp.opencv_core.*;
import static com.googlecode.javacv.cpp.opencv_imgproc.*;
import static com.googlecode.javacv.cpp.opencv_highgui.*;
import java.io.File;
import javax.swing.JFileChooser;

public class TestBeam {
    public static void main(String[] args) {
        CvMemStorage storage=CvMemStorage.create();
        CvSeq squares = new CvContour();
        squares = …

目前我正在开发图像处理项目,我正在使用javacv开发图像处理组件.我能够提取图像的一些有趣部分,现在我需要读取这些对象的x和y坐标.这是我提取的图像

我需要识别这些对象并围绕这些对象绘制正方形.我浏览了一些教程并尝试使用以下代码识别对象.

    IplImage img="sourceimage";
    CvSize sz = cvSize(img.width(), img.height());
    IplImage gry=cvCreateImage(sz, img.depth(), 1);
    cvCvtColor(img, gry, CV_BGR2GRAY);
    cvThreshold(gry, gry, 200, 250, CV_THRESH_BINARY);


    CvMemStorage mem = CvMemStorage.create();
    CvSeq contours = new CvSeq();
    CvSeq ptr = new CvSeq();
    cvFindContours(gry, mem, contours, Loader.sizeof(CvContour.class) , CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));

    CvRect boundbox;

    for (ptr = contours; ptr != null; ptr = ptr.h_next()) {
        boundbox = cvBoundingRect(ptr, 0);
        if(boundbox.height()>10||boundbox.height()>10){
            cvRectangle( gry, cvPoint( boundbox.x(), boundbox.y() ), cvPoint( boundbox.x() + boundbox.width(), boundbox.y() + boundbox.height()),CvScalar.BLUE, 0, 0, 0 );
            System.out.println(boundbox.x()+", "+boundbox.y()); …