I think it would help to change all 3 of the the input file arguments to be "positional" for consistency with the other tutorials. This also simplifies the command line input to run this tutorial by reducing typing, and helpfully prints the "usage" info if any of the 3 required inputs are missing.

I'm new to OpenCV and working through the tutorials. I kept getting runtime errors with this one until I realized that the arguments weren't positional, and I was missing the "--input1", "--input2, "--input3" flags preceding the filenames. All of the previous tutorials had required filenames as positional arguments and didn't require this.

The original code would require each input to be specified like this:
./compareHist_Demo --input1 filename1 --input2 filename2 --input3 filename3 

But with this change, the above command is simplified to:
./compareHist_Demo  filename1 filename2 filename3

This avoids a confusing runtime error to make things simpler for newcomers like me :)

Extend optical flow tutorial (#14314)

* extend python optical flow tutorial with cpp example code and add it to general tutorial directory

* remove unused parameters, fix comparison between signed and unsigned int

* fix hsv range problem

* switch to samples::findFile for sample file location

* switch to command line parameter for path

* remove old tutorial as in 14393

* minor fixes

Extend meanshift tutorial (#14393)

* copy original tutorial and python code

* add cpp code, fix python code

* add camshift cpp code, fix bug in meanshift code

* add description to ToC page

* fix shadowing previous local declaration

* fix grammar: with -> within

* docs: remove content of old py_meanshift tutorial, add link

* docs: replace meanshift tutorial subpage in Python tutorials

* switch to ref to fix wrong breadcrumb navigation

* switch to cmdline for path as in #14314

* Apply suggestions from code review

* order programming languages alphabetically

Fix arguments parsing. Add possibility to choose between different features type. Add keypoints matching visualization. Auto format code.

Add a function that draws frame axes. Useful for debugging purpose and to check the correctness of the output of a pose estimation method.

find innercircle of contour by using pointPolygonTest: (#12206)

* doc: add new tutorial motion deblur filter

* Update motion_deblur_filter.markdown

a few minor changes

except header file with conversion routines (will be removed in OpenCV 4.0)

Found via `codespell -q 3 -I ../opencv-whitelist.txt --skip="./3rdparty"`

In this tutorial you will learn:
- what is a degradation image model
- what is a PSF of an out-of-focus image
- how to restore a blurred image
- what is the Wiener filter

      - Changing the contrast and brightness of an image!
      - Operations with images

Add Java and Python code for AKAZE local features matching tutorial. Fix incorrect uses of Mat.mul() in Java code.

Uniform Lowe's ratio test in the code.

Add Java and Python code for Image Segmentation with Distance Transform and Watershed Algorithm tutorial. Use more Pythonic code.

Add Java and Python code for the following imgproc tutorials: Finding contours in your image, Convex Hull, Creating Bounding boxes and circles for contours, Creating Bounding rotated boxes and ellipses for contours, Image Moments, Point Polygon Test.

Add Java and Python code for the following features2d tutorials: Harris corner detector, Shi-Tomasi corner detector, Creating your own corner detector, Detecting corners location in subpixels, Feature Detection, Feature Description, Feature Matching with FLANN, Features2D + Homography to find a known object. Use Lowe's ratio test to filter the matches.

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

Add Java and Python code for the following imgproc tutorials: Canny, Remap, threshold and threshold inRange. Use HSV colorspace instead of RGB for inRange threshold tutorial.

* Custom deep learning layers support

* Stack custom deep learning layers

- CV_RGB() macro is moved into opencv2/imgproc.hpp from imgproc_c.h
- samples/cpp/filestorage_base64.cpp is dropped

also add comments explaining the change

- allow installing samples sources on all platforms
  even if BUILD_EXAMPLES is disabled,  fixed minor
  issues in sources installation process
- use 'example_<group>_<name>' scheme for target and binary file naming
- use single function for sample executable creation