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问题描述
我是一个初学者的OpenCV。我试图做一个样本Android应用程序，以匹配模板图像使用OpenCV的模板匹配给定的图像。我搜索在互联网上，我无法找到一个合适的Android或Java的code满足我的要求。但我有C ++ code。我不知道如何翻译它。http://docs.opencv.org/doc/tutorials/imgproc/histograms/template_matching/template_matching.html
能否请你帮我找到合适的Java或者Android code。否则，请帮我翻译这个C ++ code到Java，我可以使用里面的Android应用程序。
感谢你在前进。
C ++ code
的#includeopencv2 /一下HighGUI / highgui.hpp
＃包括opencv2 / imgproc / imgproc.hpp
＃包括＆LT;的iostream＆GT;
＃包括＆LT; stdio.h中＆GT;
使用名字空间std;
使用命名空间的简历;
///全局变量
垫IMG;垫TEMPL;垫的结果;
char *之image_window =源图像;
char *之result_window =结果窗口;
INT match_method;
INT max_Trackbar = 5;
///功能标题
无效MatchingMethod（INT，无效*）;
/ ** @function主* /
INT主（INT ARGC，字符** argv的）
{
///加载图像和模板
的img = imread（的argv [1]，1）;
TEMPL = imread（的argv [2]，1）;
///创建Windows
namedWindow（image_window，CV_WINDOW_AUTOSIZE）;
namedWindow（result_window，CV_WINDOW_AUTOSIZE）;
///创建的TrackBar
字符* trackbar_label =方法：\ñ0：SQDIFF \ N + 1：SQDIFF赋范\ N 2：TM CCORR \ñ3：TM CCORR赋范\ñ4：TM COEFF \ N 5：TM COEFF赋范;
createTrackbar（trackbar_label，image_window，和放大器; match_method，max_Trackbar，MatchingMethod）;
MatchingMethod（0，0）;
waitKey（0）;
返回0;
}
/ **
* @function MatchingMethod
* @brief的TrackBar回调
* /
无效MatchingMethod（INT，无效*）
{
///源图像显示
太img_display;
img.copyTo（img_display）;
///创建结果矩阵
INT result_cols = img.cols - templ.cols + 1;
INT result_rows = img.rows - templ.rows + 1;
result.create（result_cols，result_rows，CV_32FC1）;
///做匹配和规范
matchTemplate（IMG，TEMPL，结果，match_method）;
正常化（结果，结果是，0,1，NORM_MINMAX，-1，垫（））;
///本地化与minMaxLoc最佳匹配
双MINVAL;双MAXVAL;点minLoc;点MAXLOC;
点matchLoc;
minMaxLoc（结果，与放大器; MINVAL，和放大器; MAXVAL，和放大器; minLoc，和放大器; MAXLOC，垫（））;
///对于SQDIFF和SQDIFF_NORMED，最佳匹配较低值。对于所有的其他的方法，越高越好
如果（match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED）
{matchLoc = minLoc; }
其他
{matchLoc = MAXLOC; }
/// 告诉我你得到了什么
矩形（img_display，matchLoc，点（matchLoc.x + templ.cols，matchLoc.y + templ.rows），标量::所有（0），2，8，0）;
矩形（结果，matchLoc，点（matchLoc.x + templ.cols，matchLoc.y + templ.rows），标量::所有（0），2，8，0）;
imshow（image_window，img_display）;
imshow（result_window，结果）;
返回;
}
解决方案
我面临你做了同样的问题。没有源在Java中可用。在JavaDoc一些搜索和一些提示常量值后，我写了这个，这几乎是样品code以上用Java编写的：
包OpenCV的;
进口org.opencv.core.Core;
进口org.opencv.core.Core.MinMaxLocResult;
进口org.opencv.core.CvType;
进口org.opencv.core.Mat;
进口org.opencv.core.Point;
进口org.opencv.core.Scalar;
进口org.opencv.highgui.Highgui;
进口org.opencv.imgproc.Imgproc;
类MatchingDemo {
公共无效的run（字符串INFILE，字符串templateFile，字符串不过outFile，INT match_method）{
的System.out.println（\ N运行模板匹配）;
垫IMG = Highgui.imread（INFILE）;
垫TEMPL = Highgui.imread（templateFile）;
// /创建结果矩阵
INT result_cols = img.cols（） - templ.cols（）+ 1;
INT result_rows = img.rows（） - templ.rows（）+ 1;
垫结果=新材料（result_rows，result_cols，CvType.CV_32FC1）;
// /做匹配和规范
Imgproc.matchTemplate（IMG，TEMPL，结果，match_method）;
Core.normalize（结果，结果是，0,1，Core.NORM_MINMAX，-1，新垫（））;
// /本地化与minMaxLoc最佳匹配
MinMaxLocResult MMR = Core.minMaxLoc（结果）;
点matchLoc;
如果（match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED）{
matchLoc = mmr.minLoc;
} 其他 {
matchLoc = mmr.maxLoc;
}
// / 告诉我你得到了什么
Core.rectangle（IMG，matchLoc，新点（matchLoc.x + templ.cols（）
matchLoc.y + templ.rows（）），新的标量（0，255，0））;
//保存的可视化检测。
的System.out.println（写+不过outFile）;
Highgui.imwrite（不过outFile，IMG）;
}
}
公共类TemplateMatching {
公共静态无效的主要（字串[] args）{
的System.loadLibrary（opencv_java246）;
新MatchingDemo（）跑（参数[0]，的args [1]的args [2]，Imgproc.TM_CCOEFF）。
}
}
现在，用下面的选项运行程序： lena.png template.png templatematch.png ，你应该得到同样的结果我做到了。请当然，确保文件被运行时到达，并，OpenCV的2.4.6库注册到类路径中。
I'm a beginner to OpenCV. I'm trying to do a sample android application to match a template image in a given image using OpenCV Template matching. I searched in the internet and I couldn't find a proper android or java code which satisfy my requirement. But I have C++ code. I dont know how to translate it.http://docs.opencv.org/doc/tutorials/imgproc/histograms/template_matching/template_matching.html
Can you please help me to find a proper java or android code. Or else please help me with translate this C++ code into java, which I can use inside android application.
Thank you in advance.
C++ code
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
/// Global Variables
Mat img; Mat templ; Mat result;
char* image_window = "Source Image";
char* result_window = "Result window";
int match_method;
int max_Trackbar = 5;
/// Function Headers
void MatchingMethod( int, void* );
/** @function main */
int main( int argc, char** argv )
{
/// Load image and template
img = imread( argv[1], 1 );
templ = imread( argv[2], 1 );
/// Create windows
namedWindow( image_window, CV_WINDOW_AUTOSIZE );
namedWindow( result_window, CV_WINDOW_AUTOSIZE );
/// Create Trackbar
char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
createTrackbar( trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod );
MatchingMethod( 0, 0 );
waitKey(0);
return 0;
}
/**
* @function MatchingMethod
* @brief Trackbar callback
*/
void MatchingMethod( int, void* )
{
/// Source image to display
Mat img_display;
img.copyTo( img_display );
/// Create the result matrix
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;
result.create( result_cols, result_rows, CV_32FC1 );
/// Do the Matching and Normalize
matchTemplate( img, templ, result, match_method );
normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );
/// Localizing the best match with minMaxLoc
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;
minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );
/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if( match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
{ matchLoc = minLoc; }
else
{ matchLoc = maxLoc; }
/// Show me what you got
rectangle( img_display, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );
rectangle( result, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );
imshow( image_window, img_display );
imshow( result_window, result );
return;
}
解决方案
I was facing the same problem you did. No source in Java available. Some search in the JavaDoc and some hints for const values later, I wrote this, which is almost the sample code above written in Java:
package opencv;
import org.opencv.core.Core;
import org.opencv.core.Core.MinMaxLocResult;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;
class MatchingDemo {
public void run(String inFile, String templateFile, String outFile, int match_method) {
System.out.println("\nRunning Template Matching");
Mat img = Highgui.imread(inFile);
Mat templ = Highgui.imread(templateFile);
// / Create the result matrix
int result_cols = img.cols() - templ.cols() + 1;
int result_rows = img.rows() - templ.rows() + 1;
Mat result = new Mat(result_rows, result_cols, CvType.CV_32FC1);
// / Do the Matching and Normalize
Imgproc.matchTemplate(img, templ, result, match_method);
Core.normalize(result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat());
// / Localizing the best match with minMaxLoc
MinMaxLocResult mmr = Core.minMaxLoc(result);
Point matchLoc;
if (match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED) {
matchLoc = mmr.minLoc;
} else {
matchLoc = mmr.maxLoc;
}
// / Show me what you got
Core.rectangle(img, matchLoc, new Point(matchLoc.x + templ.cols(),
matchLoc.y + templ.rows()), new Scalar(0, 255, 0));
// Save the visualized detection.
System.out.println("Writing "+ outFile);
Highgui.imwrite(outFile, img);
}
}
public class TemplateMatching {
public static void main(String[] args) {
System.loadLibrary("opencv_java246");
new MatchingDemo().run(args[0], args[1], args[2], Imgproc.TM_CCOEFF);
}
}
Now, run the program with the following options: lena.png template.png templatematch.png and you should receive the same result I did. Make sure the files are accessible by your runtime and, of course, opencv 2.4.6 library is registered to your classpath.
这篇关于OpenCV的模板匹配例如，在安卓的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！