The ocl convolution doesn't support tensorflow padMode well.
Add fallback check if we meet this situation, it could fix the
tensorflow MobileNet SSD failure.
Signed-off-by: Li Peng <peng.li@intel.com>
* fix faster_rcnn sample crashed at PoolingInvoker operator() of pooling_layer.
* find_odj onmouse bug about find matched point status.
* reverted AutoBuffer back to std::vector
* 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
- 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
* 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