Add Java and Python code for the following imgproc tutorials: Affine Transformations, Histogram Equalization, Histogram Calculation, Histogram Comparison, Back Projection.

2026-07-29 07:13:02 +04:00 · 2018-05-23 19:44:27 +02:00
parent 3654fb10d7
commit 4c1c3147d9
24 changed files with 2014 additions and 608 deletions
@@ -17,72 +17,73 @@ using namespace cv;
 */
 int main(int argc, char** argv)
 {
-  Mat src, dst;
+    //! [Load image]
+    CommandLineParser parser( argc, argv, "{@input | ../data/lena.jpg | input image}" );
+    Mat src = imread( parser.get<String>( "@input" ), IMREAD_COLOR );
+    if( src.empty() )
+    {
+        return -1;
+    }
+    //! [Load image]

-  /// Load image
-  String imageName( "../data/lena.jpg" ); // by default
+    //! [Separate the image in 3 places ( B, G and R )]
+    vector<Mat> bgr_planes;
+    split( src, bgr_planes );
+    //! [Separate the image in 3 places ( B, G and R )]

-  if (argc > 1)
-  {
-      imageName = argv[1];
-  }
+    //! [Establish the number of bins]
+    int histSize = 256;
+    //! [Establish the number of bins]

-  src = imread( imageName, IMREAD_COLOR );
+    //! [Set the ranges ( for B,G,R) )]
+    float range[] = { 0, 256 }; //the upper boundary is exclusive
+    const float* histRange = { range };
+    //! [Set the ranges ( for B,G,R) )]

-  if( src.empty() )
-    { return -1; }
+    //! [Set histogram param]
+    bool uniform = true, accumulate = false;
+    //! [Set histogram param]

-  /// Separate the image in 3 places ( B, G and R )
-  vector<Mat> bgr_planes;
-  split( src, bgr_planes );
+    //! [Compute the histograms]
+    Mat b_hist, g_hist, r_hist;
+    calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );
+    calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate );
+    calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate );
+    //! [Compute the histograms]

-  /// Establish the number of bins
-  int histSize = 256;
+    //! [Draw the histograms for B, G and R]
+    int hist_w = 512, hist_h = 400;
+    int bin_w = cvRound( (double) hist_w/histSize );

-  /// Set the ranges ( for B,G,R) )
-  float range[] = { 0, 256 } ;
-  const float* histRange = { range };
+    Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) );
+    //! [Draw the histograms for B, G and R]

-  bool uniform = true; bool accumulate = false;
+    //! [Normalize the result to ( 0, histImage.rows )]
+    normalize(b_hist, b_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
+    normalize(g_hist, g_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
+    normalize(r_hist, r_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
+    //! [Normalize the result to ( 0, histImage.rows )]

-  Mat b_hist, g_hist, r_hist;
+    //! [Draw for each channel]
+    for( int i = 1; i < histSize; i++ )
+    {
+        line( histImage, Point( bin_w*(i-1), hist_h - cvRound(b_hist.at<float>(i-1)) ),
+              Point( bin_w*(i), hist_h - cvRound(b_hist.at<float>(i)) ),
+              Scalar( 255, 0, 0), 2, 8, 0  );
+        line( histImage, Point( bin_w*(i-1), hist_h - cvRound(g_hist.at<float>(i-1)) ),
+              Point( bin_w*(i), hist_h - cvRound(g_hist.at<float>(i)) ),
+              Scalar( 0, 255, 0), 2, 8, 0  );
+        line( histImage, Point( bin_w*(i-1), hist_h - cvRound(r_hist.at<float>(i-1)) ),
+              Point( bin_w*(i), hist_h - cvRound(r_hist.at<float>(i)) ),
+              Scalar( 0, 0, 255), 2, 8, 0  );
+    }
+    //! [Draw for each channel]

-  /// Compute the histograms:
-  calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );
-  calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate );
-  calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate );
-
-  // Draw the histograms for B, G and R
-  int hist_w = 512; int hist_h = 400;
-  int bin_w = cvRound( (double) hist_w/histSize );
-
-  Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) );
-
-  /// Normalize the result to [ 0, histImage.rows ]
-  normalize(b_hist, b_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
-  normalize(g_hist, g_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
-  normalize(r_hist, r_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
-
-  /// Draw for each channel
-  for( int i = 1; i < histSize; i++ )
-  {
-      line( histImage, Point( bin_w*(i-1), hist_h - cvRound(b_hist.at<float>(i-1)) ) ,
-                       Point( bin_w*(i), hist_h - cvRound(b_hist.at<float>(i)) ),
-                       Scalar( 255, 0, 0), 2, 8, 0  );
-      line( histImage, Point( bin_w*(i-1), hist_h - cvRound(g_hist.at<float>(i-1)) ) ,
-                       Point( bin_w*(i), hist_h - cvRound(g_hist.at<float>(i)) ),
-                       Scalar( 0, 255, 0), 2, 8, 0  );
-      line( histImage, Point( bin_w*(i-1), hist_h - cvRound(r_hist.at<float>(i-1)) ) ,
-                       Point( bin_w*(i), hist_h - cvRound(r_hist.at<float>(i)) ),
-                       Scalar( 0, 0, 255), 2, 8, 0  );
-  }
-
-  /// Display
-  namedWindow("calcHist Demo", WINDOW_AUTOSIZE );
-  imshow("calcHist Demo", histImage );
-
-  waitKey(0);
-
-  return 0;
+    //! [Display]
+    imshow("Source image", src );
+    imshow("calcHist Demo", histImage );
+    waitKey();
+    //! [Display]

+    return 0;
 }