Update imageSegmentation.cpp, imageSegmentation.py

diff --git a/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp b/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
index 201466e99b518d4ba286e776e82c4a0c327392d2..818fcb473559226a68aa43ee914551035c050b88 100644 (file)
--- a/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
+++ b/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
@@ -24,23 +24,16 @@ int main(int argc, char *argv[])
         return -1;
     }
 
-    // Show source image
+    // Show the source image
     imshow("Source Image", src);
     //! [load_image]
 
     //! [black_bg]
     // Change the background from white to black, since that will help later to extract
     // better results during the use of Distance Transform
-    for ( int i = 0; i < src.rows; i++ ) {
-        for ( int j = 0; j < src.cols; j++ ) {
-            if ( src.at<Vec3b>(i, j) == Vec3b(255,255,255) )
-            {
-                src.at<Vec3b>(i, j)[0] = 0;
-                src.at<Vec3b>(i, j)[1] = 0;
-                src.at<Vec3b>(i, j)[2] = 0;
-            }
-        }
-    }
+    Mat mask;
+    inRange(src, Scalar(255, 255, 255), Scalar(255, 255, 255), mask);
+    src.setTo(Scalar(0, 0, 0), mask);
 
     // Show output image
     imshow("Black Background Image", src);
@@ -124,7 +117,9 @@ int main(int argc, char *argv[])
 
     // Draw the background marker
     circle(markers, Point(5,5), 3, Scalar(255), -1);
-    imshow("Markers", markers*10000);
+    Mat markers8u;
+    markers.convertTo(markers8u, CV_8U, 10);
+    imshow("Markers", markers8u);
     //! [seeds]
 
     //! [watershed]

diff --git a/samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py b/samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py
index 0ab56cfb302307156e349b5f5952b1ec9a6cebcf..e5ed43f115cc1d3b34755c018895a85940901a05 100644 (file)
--- a/samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py
+++ b/samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py
@@ -102,7 +102,8 @@ for i in range(len(contours)):
 
 # Draw the background marker
 cv.circle(markers, (5,5), 3, (255,255,255), -1)
-cv.imshow('Markers', markers*10000)
+markers_8u = (markers * 10).astype('uint8')
+cv.imshow('Markers', markers_8u)
 ## [seeds]
 
 ## [watershed]