Merge pull request #16001 from alalek:backport_15995

doc/py_tutorials/py_gui/py_trackbar/py_trackbar.markdown

@@ -16,7 +16,7 @@ correspondingly window color changes. By default, initial color will be set to B
 
 For cv.getTrackbarPos() function, first argument is the trackbar name, second one is the window
 name to which it is attached, third argument is the default value, fourth one is the maximum value
-and fifth one is the callback function which is executed everytime trackbar value changes. The
+and fifth one is the callback function which is executed every time trackbar value changes. The
 callback function always has a default argument which is the trackbar position. In our case,
 function does nothing, so we simply pass.
 

doc/py_tutorials/py_ml/py_knn/py_knn_opencv/py_knn_opencv.markdown

@@ -54,7 +54,7 @@ print( accuracy )
 @endcode
 So our basic OCR app is ready. This particular example gave me an accuracy of 91%. One option
 improve accuracy is to add more data for training, especially the wrong ones. So instead of finding
-this training data everytime I start application, I better save it, so that next time, I directly
+this training data every time I start application, I better save it, so that next time, I directly
 read this data from a file and start classification. You can do it with the help of some Numpy
 functions like np.savetxt, np.savez, np.load etc. Please check their docs for more details.
 @code{.py}