Found via `codespell`

* Added the imagesFromBlob method to the dnn module.

* Rewritten imagesFromBlob based on first dkurt comments

* Updated code with getPlane()

* Modify comment of imagesFromBlob() in dnn module

* modified comments, removed useless assertions & added OutputArrayOfArray

* replaced tabs with whitespaces & put vectorOfChannels instantiation outside the loop

* Changed pre-commit.sample to pre-commit in .git/hooks/

* Added a test for imagesFromBlob in test_misc.cpp (dnn)

* Changed nbOfImages, robustified test with cv::randu, modified assertion

* cmake: add ocv_get_smart_file_name() macro

* cmake: avoid adding files for unavailable dispatch modes

Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

* Intel Inference Engine deep learning backend.

* OpenFace network using Inference Engine backend

- removed tr1 usage (dropped in C++17)
- moved includes of vector/map/iostream/limits into ts.hpp
- require opencv_test + anonymous namespace (added compile check)
- fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions
- added missing license headers

* Do not build protobuf if dnn is disabled

* Added BUILD_LIST cmake option to the cache

* Moved protobuf to the top level

* Fixed static build

* Fixed world build

* fixup! Fixed world build

it fuse ocl kernels to reduce kernel enqueue
Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

* Add a 512 bit codepath to the AVX512 fastConv function

this patch adds a 512 wide codepath to the fastConv() function for
AVX512 use.
The basic idea is to process the first N * 16 elements of the vector
with avx512, and then run the rest of the vector using the traditional
AVX2 codepath.

* dnn: use unaligned AVX512 load (OpenCV aligns data on 32-byte boundary)

* dnn: change "vecsize" condition for AVX512

* dnn: fix indentation

https://github.com/rbgirshick/py-faster-rcnn
https://github.com/YuwenXiong/py-R-FCN

Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

cut one ocl kernel if normVariance is disabled,
also use native_powr for performance reason.
Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

and add parametric unit test for crop layer.

Signed-off-by: Li Peng <peng.li@intel.com>

Signed-off-by: Li Peng <peng.li@intel.com>

use a batch_norm ocl kernel to do the work
Signed-off-by: Li Peng <peng.li@intel.com>

* UMat blobs are wrapped

* Replace getUMat and getMat at OpenCLBackendWrapper

Signed-off-by: Li Peng <peng.li@intel.com>