potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-31 00:03:03 +04:00
Code Packages Releases Wiki Activity

doc: fix misused "see also" doxygen command

Browse Source
This commit is contained in:
Alexander Alekhin
2020-03-21 00:25:49 +00:00
parent 183e4d50ed
commit 2fb1d9d02e
9 changed files with 14 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/py_tutorials/py_imgproc/py_contours/py_contours_more_functions/py_contours_more_functions.markdown
+1 -1
View File
@@ -113,7 +113,7 @@ I got following results:
See, even image rotation doesn't affect much on this comparison.
@sa [Hu-Moments](http://en.wikipedia.org/wiki/Image_moment#Rotation_invariant_moments) are seven
@note [Hu-Moments](http://en.wikipedia.org/wiki/Image_moment#Rotation_invariant_moments) are seven
moments invariant to translation, rotation and scale. Seventh one is skew-invariant. Those values
can be found using **cv.HuMoments()** function.
doc/py_tutorials/py_imgproc/py_histograms/py_histogram_begins/py_histogram_begins.markdown
+1 -1
View File
@@ -94,7 +94,7 @@ hist is same as we calculated before. But bins will have 257 elements, because N
as 0-0.99, 1-1.99, 2-2.99 etc. So final range would be 255-255.99. To represent that, they also add
256 at end of bins. But we don't need that 256. Upto 255 is sufficient.
@sa Numpy has another function, **np.bincount()** which is much faster than (around 10X)
@note Numpy has another function, **np.bincount()** which is much faster than (around 10X)
np.histogram(). So for one-dimensional histograms, you can better try that. Don't forget to set
minlength = 256 in np.bincount. For example, hist = np.bincount(img.ravel(),minlength=256)