1
0
mirror of https://github.com/opencv/opencv.git synced 2026-07-31 08:13:04 +04:00

Merge branch 4.x

This commit is contained in:
Alexander Smorkalov
2024-01-15 17:23:10 +03:00
531 changed files with 20900 additions and 12934 deletions
@@ -79,9 +79,12 @@ Functions are extended using `CV_EXPORTS_W` macro. An example is shown below.
@code{.cpp}
CV_EXPORTS_W void equalizeHist( InputArray src, OutputArray dst );
@endcode
Header parser can understand the input and output arguments from keywords like
InputArray, OutputArray etc. But sometimes, we may need to hardcode inputs and outputs. For that,
macros like `CV_OUT`, `CV_IN_OUT` etc. are used.
Header parser can understand the input and output arguments from keywords like InputArray,
OutputArray etc. The arguments semantics are kept in Python: anything that is modified in C++
will be modified in Python. And vice-versa read-only Python objects cannot be modified by OpenCV,
if they are used as output. Such situation will cause Python exception. Sometimes, the parameters
that are passed by reference in C++ may be used as input, output or both.
Macros `CV_OUT`, `CV_IN_OUT` allow to solve ambiguity and generate correct bindings.
@code{.cpp}
CV_EXPORTS_W void minEnclosingCircle( InputArray points,
CV_OUT Point2f& center, CV_OUT float& radius );
@@ -111,7 +111,7 @@ frames per second (fps) and frame size should be passed. And the last one is the
`True`, the encoder expect color frame, otherwise it works with grayscale frame.
[FourCC](http://en.wikipedia.org/wiki/FourCC) is a 4-byte code used to specify the video codec. The
list of available codes can be found in [fourcc.org](http://www.fourcc.org/codecs.php). It is
list of available codes can be found in [fourcc.org](https://fourcc.org/codecs.php). It is
platform dependent. The following codecs work fine for me.
- In Fedora: DIVX, XVID, MJPG, X264, WMV1, WMV2. (XVID is more preferable. MJPG results in high
@@ -141,7 +141,7 @@ Additional Resources
--------------------
1. [NPTEL notes on Pattern Recognition, Chapter
11](https://nptel.ac.in/courses/106/108/106108057/)
11](https://nptel.ac.in/courses/106108057)
2. [Wikipedia article on Nearest neighbor search](https://en.wikipedia.org/wiki/Nearest_neighbor_search)
3. [Wikipedia article on k-d tree](https://en.wikipedia.org/wiki/K-d_tree)
@@ -129,7 +129,6 @@ Additional Resources
--------------------
-# [NPTEL notes on Statistical Pattern Recognition, Chapters
25-29](http://www.nptel.ac.in/courses/106108057/26).
25-29](https://nptel.ac.in/courses/117108048)
Exercises
---------