OpenCV Template Matching example in Android

Question

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; } 

Answer 1

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.