* Updated cpp reference implementations for a few intrinsics to address wide universal intrinsics as well
* Updated cpp reference implementations for a few more universal intrinsics
* Update polynom_solver.cpp
This pull request is in the response to Issue #19526. I have fixed the problem with the cube root calculation of 2*R. The Issue was in the usage of pow function with negative values of R, but if it is calculated for only positive values of R then changing x0 according to the parity of R, the Issue is resolved. Kindly consider it, Thanks!
* add cv::cubeRoot(double)
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
- to reduce binaries size of FFmpeg Windows wrapper
- MinGW linker doesn't support -ffunction-sections (used for FFmpeg Windows wrapper)
- move code to improve locality with its used dependencies
- move UMat::dot() to matmul.dispatch.cpp (Mat::dot() is already there)
- move UMat::inv() to lapack.cpp
- move UMat::mul() to arithm.cpp
- move UMat:eye() to matrix_operations.cpp (near setIdentity() implementation)
- move normalize(): convert_scale.cpp => norm.cpp
- move convertAndUnrollScalar(): arithm.cpp => copy.cpp
- move scalarToRawData(): array.cpp => copy.cpp
- move transpose(): matrix_operations.cpp => matrix_transform.cpp
- move flip(), rotate(): copy.cpp => matrix_transform.cpp (rotate90 uses flip and transpose)
- add 'OPENCV_CORE_EXCLUDE_C_API' CMake variable to exclude compilation of C-API functions from the core module
- matrix_wrap.cpp: add compile-time checks for CUDA/OpenGL calls
- the steps above allow to reduce FFmpeg wrapper size for ~1.5Mb (initial size of OpenCV part is about 3Mb)
backport is done to improve merge experience (less conflicts)
backport of commit: 65eb946756
- follows iso c++ guideline C.44
- enables default compiler-created constructors to
also be noexcept
original commit: 77e26a7db3
- handled KernelArg, Image2D
* fix core module android arm64 build
* fix core module android build when neon is off
When building for Android ARM platform, cmake with
`-D CV_DISABLE_OPTIMIZATION=ON`, the expected behavior is
not using ARM NEON, using naive computation instead.
This commit fix the un-expected compile error for neon intrinsincs.
* [hal][neon] Optimize the v_dotprod_fast intrinsics for aarch64.
On Armv8 in AArch64 execution mode, we can skip the sequence
v<op>_<ty>(vget_high_<ty>(x), vget_high_<ty>(y))
in favour of
v<op>_high_<ty>(x, y)
This has better changes for recent compilers to use less data movement
operations and better register allocation. See for example:
https://godbolt.org/z/bPq7vd
* [hal][neon] Fix build failure on armv7.
* [hal][neon] Address review comments in PR.
PR: https://github.com/opencv/opencv/pull/19486
* [hal][neon] Define macro to check for the AArch64 execution state of Armv8.
* [hal][neon] Fix macro definition for AArch64.
The fix is needed to prevent warnings when building for Armv7.
they might be thrown from third-party code (notably Ogre in the ovis
module).
While Linux is kind enough to print them, they cause instant termination
on Windows.
Arguably, they do not origin from OpenCV itself, but still this helps
understanding what went wrong when calling an OpenCV function.
The most of target machine use one type cpu unit resource
to execute some one type of instruction, e.g.
all vx_load API use load/store cpu unit,
and v_muladd API use mul/mula cpu unit, we interleave
vx_load and v_muladd to improve performance on most targets like
RISCV or ARM.
[GSoC] OpenCV.js: WASM SIMD optimization 2.0
* gsoc_2020_simd Add perf test for filter2d
* add perf test for kernel scharr and kernel gaussianBlur
* add perf test for blur, medianBlur, erode, dilate
* fix the errors for the opencv PR robot
fix the trailing whitespace.
* add perf tests for kernel remap, warpAffine, warpPersepective, pyrDown
* fix a bug in modules/js/perf/perf_imgproc/perf_remap.js
* add function smoothBorder in helpfun.js and remove replicated function in perf test of warpAffine and warpPrespective
* fix the trailing white space issues
* add OpenCV.js loader
* Implement the Loader with help of WebAssembly Feature Detection, remove trailing whitespaces
* modify the explantion for loader in js_setup.markdown and fix bug in loader.js
- OpenCL kernel cleanup processing is asynchronous and can be called even after forced clFinish()
- buffers are released later in asynchronous mode
- silence these false positive cases for asynchronous cleanup
* Add documentation about usage of cv2eigen functions in eigen.hpp
* Fixed Doxygen syntax.
Co-authored-by: Alexander Smorkalov <smorkalov.a.m@gmail.com>
* fixed#17044
1. fixed Python part of the tutorial about using OpenCV XML-YAML-JSON I/O functionality from C++ and Python.
2. added startWriteStruct() and endWriteStruct() methods to FileStorage
3. modifed FileStorage::write() methods to make them work well inside sequences, not only mappings.
* try to fix the doc builder
* added Python regression test for FileStorage I/O API ([TODO] iterating through long sequences can be very slow)
* fixed yaml testing
* Fix integer overflow in parseOption().
Previous code does not work for values like 100000MB.
* Fix warning during 32-bit build on inactive code path.
* fix build without C++11
* add eigen tensor conversion functions
* add eigen tensor conversion tests
* add support for column major order
* update eigen tensor tests
* fix coding style and add conditional compilation
* fix conditional compilation checks
* remove whitespace
* rearrange functions for easier reading
* reformat function documentation and add tensormap unit test
* cleanup documentation of unit test
* remove condition duplication
* check Eigen major version, not minor version
* restrict to Eigen v3.3.0+
* add documentation note and add type checking to cv2eigen_tensormap()
* fixed several problems when running tests on Mac:
* OCL_pyrUp
* OCL_flip
* some basic UMat tests
* histogram badarg test (out of range access)
* retained the storepix fix in ocl_flip only for 16U/16S datatype, where the OpenCL compiler on Mac generates incorrect code
* moved deletion of ACCESS_FAST flag to non-SVM branch (where SVM is shared virtual memory (in OpenCL 2.x), not support vector machine)
* force OpenCL to use read/write for GPU<=>CPU memory transfers on machines with discrete video only on Macs. On Windows/Linux the drivers are seemingly smart enough to implement map/unmap properly (and maybe more efficiently than explicit read/write)
* Reduce LLC loads, stores and multiplies on MulTransposed - 8% faster on VSX
* Add is_same method so c++11 is not required
* Remove trailing whitespaces.
* Change is_same to DataType depth check
Vectorize minMaxIdx functions
* Updated documentation and intrinsic tests for v_reduce
* Add other files back in from the forced push
* Prevent an constant overflow with v_reduce for int8 type
* Another alternative to fix constant overflow warning.
* Fix another compiler warning.
* Update comments and change comparison form to be consistent with other vectorized loops.
* Change return type of v_reduce_min & max for v_uint8 and v_uint16 to be same as lane type.
* Cast v_reduce functions to int to avoid overflow. Reduce number of parameters in MINMAXIDX_REDUCE macro.
* Restore cast type for v_reduce_min & max to LaneType