`PyObject*` to `std::vector<T>` conversion logic:
- If user passed Numpy Array
- If array is planar and T is a primitive type (doesn't require
constructor call) that matches with the element type of array, then
copy element one by one with the respect of the step between array
elements. If compiler is lucky (or brave enough) copy loop can be
vectorized.
For classes that require constructor calls this path is not
possible, because we can't begin an object lifetime without hacks.
- Otherwise fall-back to general case
- Otherwise - execute the general case:
If PyObject* corresponds to Sequence protocol - iterate over the
sequence elements and invoke the appropriate `pyopencv_to` function.
`std::vector<T>` to `PyObject*` conversion logic:
- If `std::vector<T>` is empty - return empty tuple.
- If `T` has a corresponding `Mat` `DataType` than return
Numpy array instance of the matching `dtype` e.g.
`std::vector<cv::Rect>` is returned as `np.ndarray` of shape `Nx4` and
`dtype=int`.
This branch helps to optimize further evaluations in user code.
- Otherwise - execute the general case:
Construct a tuple of length N = `std::vector::size` and insert
elements one by one.
Unnecessary functions were removed and code was rearranged to allow
compiler select the appropriate conversion function specialization.
Improves support for Unix non-Linux systems, including QNX
* Fixes#20395. Improves support for Unix non-Linux systems. Focus on QNX Neutrino.
Signed-off-by: promero <promero@mathworks.com>
* Update system.cpp
There can be an int overflow.
cv::norm( InputArray _src, int normType, InputArray _mask ) is fine,
not cv::norm( InputArray _src1, InputArray _src2, int normType, InputArray _mask ).
Improve performance on Arm64
* Improve performance on Apple silicon
This patch will
- Enable dot product intrinsics for macOS arm64 builds
- Enable for macOS arm64 builds
- Improve HAL primitives
- reduction (sum, min, max, sad)
- signmask
- mul_expand
- check_any / check_all
Results on a M1 Macbook Pro
* Updates to #20011 based on feedback
- Removes Apple Silicon specific workarounds
- Makes #ifdef sections smaller for v_mul_expand cases
- Moves dot product optimization to compiler optimization check
- Adds 4x4 matrix transpose optimization
* Remove dotprod and fix v_transpose
Based on the latest, we've removed dotprod entirely and will revisit in a future PR.
Added explicit cats with v_transpose4x4()
This should resolve all opens with this PR
* Remove commented out lines
Remove two extraneous comments
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
* 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
