我正在开发关于javacv的项目,我需要知道如何识别下面的图像并使用特定的颜色填充图像?
我尝试通过这个question,这是我使用的图像
我尝试浏览此代码并在javacv中开发了代码
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_highgui.*;
import static com.googlecode.javacv.cpp.opencv_imgproc.*;
import java.io.File;
import javax.swing.JFileChooser;
public class PolyGonIdentification {
public static void main(String[] args) {
CanvasFrame cnvs=new CanvasFrame("Polygon");
cnvs.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE);
CvMemStorage storage=CvMemStorage.create();
CvSeq squares = new CvContour();
squares = cvCreateSeq(0, sizeof(CvContour.class), sizeof(CvSeq.class), storage);
JFileChooser f=new JFileChooser();
int result=f.showOpenDialog(f);//show dialog box to choose files
File myfile=null;
String path="";
if(result==0){
myfile=f.getSelectedFile();//selected file taken to myfile
path=myfile.getAbsolutePath();//get the path of the file
}
IplImage src = cvLoadImage(path);//hear path is actual path to image
IplImage gry=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);
cvCvtColor(src, gry, CV_BGR2GRAY);
cvThreshold(gry, gry, 230, 255, CV_THRESH_BINARY_INV);
cvFindContours(gry, storage, squares, Loader.sizeof(CvContour.class), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
System.out.println(squares.total());
for (int i=0; i<squares.total(); i++)
{
cvDrawContours(gry, squares, CvScalar.ONE, CvScalar.ONE, 127, 1, 8);
}
IplConvKernel mat=cvCreateStructuringElementEx(7, 7, 3, 3, CV_SHAPE_RECT, null);
cvDilate(gry, gry, mat, CV_C);
cvErode(gry, gry, mat, CV_C);
cnvs.showImage(gry);
}
}
我的最终结果应该像这张图片
上面的代码产生了这种形象。有人可以帮我解决这个问题吗?
答案 0 :(得分:1)
代码完全符合预期:
// as stated [in the answer to your previous question][1], findContours leaves gry set to 0, or black
cvFindContours(gry, storage, squares, Loader.sizeof(CvContour.class),
CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
System.out.println(squares.total()); // nothing interesting
for (int i = 0; i < squares.total(); i++)
{
// draw a gray contour (127) on a black image
cvDrawContours(gry, squares, CvScalar.ONE, CvScalar.ONE, 127, 1, 8);
}
要纠正它,你必须将gry设置为255(白色,在任何调用drawContours之前,并绘制黑色轮廓!即0,而不是127.)
答案 1 :(得分:1)
您只需使用外部检索模式找到轮廓:
CV_RETR_EXTERNAL retrives only the extreme outer contours
在您的情况下,这是最好的模式,因为您有一个外部轮廓,这个轮廓是您正在寻找的。 Here's文件。
在此之后,只需使用drawContours并使用CV_FILLED
作为厚度参数来绘制它,以填充外部多边形。
答案 2 :(得分:1)
您可以使用此代码
对其进行归档 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_highgui.*;
import static com.googlecode.javacv.cpp.opencv_imgproc.*;
import java.io.File;
import javax.swing.JFileChooser;
public class Ishape {
public static void main(String[] args) {
CanvasFrame cnvs=new CanvasFrame("Polygon");
cnvs.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE);
CvMemStorage storage=CvMemStorage.create();
CvSeq squares = new CvContour();
squares = cvCreateSeq(0, sizeof(CvContour.class), sizeof(CvSeq.class), storage);
JFileChooser f=new JFileChooser();
int result=f.showOpenDialog(f);//show dialog box to choose files
File myfile=null;
String path="";
if(result==0){
myfile=f.getSelectedFile();//selected file taken to myfile
path=myfile.getAbsolutePath();//get the path of the file
}
IplImage src = cvLoadImage(path);//hear path is actual path to image
IplImage gry=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);
cvCvtColor(src, gry, CV_BGR2GRAY);
cvThreshold(gry, gry, 230, 255, CV_THRESH_BINARY_INV);
cvFindContours(gry, storage, squares, Loader.sizeof(CvContour.class), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
CvSeq ss=null;
for (int i=0; i<1; i++)
{
cvDrawContours(gry, squares, CvScalar.WHITE, CV_RGB(248, 18, 18), 1, -1, 8);
ss=cvApproxPoly(squares, sizeof(CvContour.class), storage, CV_POLY_APPROX_DP, 8, 0);
}
IplConvKernel mat=cvCreateStructuringElementEx(7, 7, 3, 3, CV_SHAPE_RECT, null);
cvDilate(gry, gry, mat, CV_C);
cvErode(gry, gry, mat, CV_C);
cnvs.showImage(gry);
}
}
结果
这将是最终结果,我相信这可以帮助您解决问题。