Implement color conversion from RGB to YUV422 family #24333
Related PR for extra: https://github.com/opencv/opencv_extra/pull/1104
Hi,
This patch provides CPU and OpenCL implementations of color conversions from RGB/BGR to YUV422 family (such as UYVY and YUY2).
These features would come in useful for enabling standard RGB images to be supplied as input to algorithms or networks that make use of images in YUV422 format directly (for example, on resource constrained devices working with camera images captured in YUV422).
The code, tests and perf tests are all written following the existing pattern. There is also an example `bin/example_cpp_cvtColor_RGB2YUV422` that loads an image from disk, converts it from BGR to UYVY and then back to BGR, and displays the result as a visual check that the conversion works.
The OpenCL performance for the forward conversion implemented here is the same as the existing backward conversion on my hardware. The CPU implementation, unfortunately, isn't very optimized as I am not yet familiar with the SIMD code.
Please let me know if I need to fix something or can make other modifications.
Thanks!
### Pull Request Readiness Checklist
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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
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- [x] The feature is well documented and sample code can be built with the project CMake
Also bring perf_imgproc CornerMinEigenVal accuracy requirements in line with
the test_imgproc accuracy requirements on that test and fix indentation on
the latter.
Partially addresses issue #9821
The MinEigenVal path through the corner.cl kernel makes use of native_sqrt,
a math builtin function which has implementation defined accuracy.
Partially addresses issue #9821
* goodFeaturesToTrack returns also corner value
(cherry picked from commit 4a8f06755c)
* Added response to GFTT Detector keypoints
(cherry picked from commit b88fb40c6e)
* Moved corner values to another optional variable to preserve backward compatibility
(cherry picked from commit 6137383d32)
* Removed corners valus from perf tests and better unit tests for corners values
(cherry picked from commit f3d0ef21a7)
* Fixed detector gftt call
(cherry picked from commit be2975553b)
* Restored test_cornerEigenValsVecs
(cherry picked from commit ea3e11811f)
* scaling fixed;
mineigen calculation rolled back;
gftt function overload added (with quality parameter);
perf tests were added for the new api function;
external bindings were added for the function (with different alias);
fixed issues with composition of the output array of the new function (e.g. as requested in comments) ;
added sanity checks in the perf tests;
removed C API changes.
* minor change to GFTTDetector::detect
* substitute ts->printf with EXPECT_LE
* avoid re-allocations
Co-authored-by: Anas <anas.el.amraoui@live.com>
Co-authored-by: amir.tulegenov <amir.tulegenov@xperience.ai>
* loosen some test threshold mainly for integer types
* use relative error for floating points result
* avoid division by zero by following the comment
* fix the indentation
- 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
Add new 5x5 gaussian blur kernel for CV_8UC1 format,
it is 50% ~ 70% faster than current ocl kernel in the perf test.
Signed-off-by: Li Peng <peng.li@intel.com>
Add new OpenCL kernels for bicubic interploation, it is 20% faster
than current warp image kernel with bicubic interploation.
Signed-off-by: Li Peng <peng.li@intel.com>
Add new ocl kernels for warpAffine and warpPerspective,
The average performance improvemnt is about 30%. The new
ocl kernels require CV_8UC1 format and support nearest
neighbor and bilinear interpolation.
Signed-off-by: Li Peng <peng.li@intel.com>
This ocl kernel is 46%~171% faster than current laplacian 3x3
ocl kernel in the perf test, with image format "CV_8UC1".
Signed-off-by: Li Peng <peng.li@intel.com>
This ocl kernel is for 3x3 kernel size and CV_8UC1 format
It is 115% ~ 300% faster than current ocl path in perf test
python ./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_GaussianBlurFixture*
Signed-off-by: Li Peng <peng.li@intel.com>
This kernel is for CV_8UC1 format and 3x3 kernel size,
It is about 33% ~ 55% faster than current ocl kernel with below perf test
python ./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_ErodeFixture*
python ./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_DilateFixture*
Also add accuracy test cases for this kernel, the test command is
./bin/opencv_test_imgproc --gtest_filter=OCL_Filter/MorphFilter3x3*
Signed-off-by: Li Peng <peng.li@intel.com>
The optimization is for CV_8UC1 format and 3x3 box filter,
it is 15%~87% faster than current ocl kernel with below perf test
./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_BlurFixture*
Also add test cases for this ocl kernel.
Signed-off-by: Li Peng <peng.li@intel.com>
IPP_VERSION_MAJOR * 100 + IPP_VERSION_MINOR*10 + IPP_VERSION_UPDATE
to manage changes between updates more easily.
IPP_DISABLE_BLOCK was added to ease tracking of disabled IPP functions;
