Merge remote-tracking branch 'upstream/3.4' into merge-3.4

doc/tutorials/imgproc/anisotropic_image_segmentation/anisotropic_image_segmentation.markdown

@@ -1,6 +1,9 @@
 Anisotropic image segmentation by a gradient structure tensor {#tutorial_anisotropic_image_segmentation_by_a_gst}
 ==========================
 
+@prev_tutorial{tutorial_motion_deblur_filter}
+@next_tutorial{tutorial_periodic_noise_removing_filter}
+
 Goal
 ----
 
@@ -45,28 +48,65 @@ The orientation of an anisotropic image:
 Coherency:
 \f[C = \frac{\lambda_1 - \lambda_2}{\lambda_1 + \lambda_2}\f]
 
-The coherency ranges from 0 to 1. For ideal local orientation (\f$\lambda_2\f$ = 0, \f$\lambda_1\f$ > 0) it is one, for an isotropic gray value structure (\f$\lambda_1\f$ = \f$\lambda_2\f$ > 0) it is zero.
+The coherency ranges from 0 to 1. For ideal local orientation (\f$\lambda_2\f$ = 0, \f$\lambda_1\f$ > 0) it is one, for an isotropic gray value structure (\f$\lambda_1\f$ = \f$\lambda_2\f$ \> 0) it is zero.
 
 Source code
 -----------
 
 You can find source code in the `samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp` of the OpenCV source code library.
 
-@include cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp
+@add_toggle_cpp
+    @include cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp
+@end_toggle
+
+@add_toggle_python
+    @include samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py
+@end_toggle
 
 Explanation
 -----------
 An anisotropic image segmentation algorithm consists of a gradient structure tensor calculation, an orientation calculation, a coherency calculation and an orientation and coherency thresholding:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp main
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp main
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py main
+@end_toggle
 
 A function calcGST() calculates orientation and coherency by using a gradient structure tensor. An input parameter w defines a window size:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp calcGST
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp calcGST
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py calcGST
+@end_toggle
+
 
 The below code applies a thresholds LowThr and HighThr to image orientation and a threshold C_Thr to image coherency calculated by the previous function. LowThr and HighThr define orientation range:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp thresholding
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp thresholding
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py thresholding
+@end_toggle
+
 
 And finally we combine thresholding results:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp combining
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp combining
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py combining
+@end_toggle
+
 
 Result
 ------

doc/tutorials/imgproc/motion_deblur_filter/motion_deblur_filter.markdown

@@ -1,6 +1,9 @@
 Motion Deblur Filter {#tutorial_motion_deblur_filter}
 ==========================
 
+@prev_tutorial{tutorial_out_of_focus_deblur_filter}
+@next_tutorial{tutorial_anisotropic_image_segmentation_by_a_gst}
+
 Goal
 ----
 

doc/tutorials/imgproc/out_of_focus_deblur_filter/out_of_focus_deblur_filter.markdown

@@ -2,6 +2,7 @@ Out-of-focus Deblur Filter {#tutorial_out_of_focus_deblur_filter}
 ==========================
 
 @prev_tutorial{tutorial_distance_transform}
+@next_tutorial{tutorial_motion_deblur_filter}
 
 Goal
 ----

doc/tutorials/imgproc/periodic_noise_removing_filter/periodic_noise_removing_filter.markdown

@@ -1,6 +1,8 @@
 Periodic Noise Removing Filter {#tutorial_periodic_noise_removing_filter}
 ==========================
 
+@prev_tutorial{tutorial_anisotropic_image_segmentation_by_a_gst}
+
 Goal
 ----