* Fix integer overflow in cv::Luv2RGBinteger::process.

For LL=49, uu=205, vv=23, we end up with x=7373056 and y=458
which overflows y*x.

* imgproc(test): adjust test parameters to cover SIMD code

* dnn: LSTM optimisation

This uses the AVX-optimised fastGEMM1T for matrix multiplications where available, instead of the standard cv::gemm.

fastGEMM1T is already used by the fully-connected layer.  This commit involves two minor modifications:
 - Use unaligned access.  I don't believe this involves any performance hit in on modern CPUs (Nehalem and Bulldozer onwards) in the case where the address is actually aligned.
 - Allow for weight matrices where the number of columns is not a multiple of 8.

I have not enabled AVX-512 as I don't have an AVX-512 CPU to test on.

* Fix warning about initialisation order

* Remove C++11 syntax

* Fix build when AVX(2) is not available

In this case the CV_TRY_X macros are defined to 0, rather than being undefined.

* Minor changes as requested:

 - Don't check hardware support for AVX(2) when dispatch is disabled for these
 - Add braces

* Fix out-of-bounds access in fully connected layer

The old tail handling in fastGEMM1T implicitly rounded vecsize up to the next multiple of 8, and the fully connected layer implements padding up to the next multiple of 8 to cope with this.  The new tail handling does not round the vecsize upwards like this but it does require that the vecsize is at least 8.  To adapt to the new tail handling, the fully connected layer now rounds vecsize itself at the same time as adding the padding(which makes more sense anyway).

This also means that the fully connected layer always passes a vecsize of at least 8 to fastGEMM1T, which fixes the out-of-bounds access problems.

* Improve tail mask handling

 - Use static array for generating tail masks (as requested)
 - Apply tail mask to the weights as well as the input vectors to prevent spurious propagation of NaNs/Infs

* Revert whitespace change

* Improve readability of conditions for using AVX

* dnn(lstm): minor coding style changes, replaced left aligned load

- remove similar test from IE scope under HAVE_INF_ENGINE

resolves #21038

* remove C assert

* revert C header

* fix several points in review

* fix test_ds.cpp

https://pypi.org/project/codespell/

Avoid `SyntaxWarning` on Python >= 3.8
```
>>> "convolutional" == "convolutional"
True
>>> "convolutional" is "convolutional"
<stdin>:1: SyntaxWarning: "is" with a literal. Did you mean "=="?
True
```
Related to #21121

https://github.com/libjpeg-turbo/libjpeg-turbo/releases/tag/2.1.2

In case of very small negative h (e.g. -1e-40), with the current implementation,
you will go through the first condition and end up with h = 6.f, and will miss
the second condition.

issue #20617 addresses lack of warnings on
seamlessClone() function when src is None.
This commit adds source check using CV_Assert
therefore debugging would be easier.
Signed-off-by: Nnickjackolson <metedurlu@gmail.com>

Add a warning message using CV_LOG__WARNING().
This way api behaviour is preserved. Outputs are
the same but user gets an extra warning in case
fopen() fails to access image file for some reason.
This would help new users and also debugging
complex apps which use imread()
Signed-off-by: Nnickjackolson <metedurlu@gmail.com>

QR code (encoding process)

* add qrcode encoder

* qr encoder fixes

* qr encoder: fix api and realization

* fixed qr encoder, added eci and kanji modes

* trigger CI

* qr encoder constructor fixes
Co-authored-by: NAPrigarina <ann73617@gmail.com>

* dnn(ocl4dnn): fix LRN layer accuracy problems

- FP16 intermediate computation is not accurate and may provide NaN values

* dnn(test): update tolerance for FP16

Fix seg fault houghlinespointset

* Clarify parameter doc for HoughLinesPointSet

* Fix seg fault.

* Add regression test.

* Fix latex typo