`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.
AArch64 semihosting
* [ts] Disable filesystem support in the TS module.
Because of this change, all the tests loading data will file, but tat
least the core module can be tested with the following line:
opencv_test_core --gtest_filter=-"*Core_InputOutput*:*Core_globbing.accuracy*"
* [aarch64] Build OpenCV for AArch64 semihosting.
This patch provide a toolchain file that allows to build the library
for semihosting applications [1]. Minimal changes have been applied to
the code to be able to compile with a baremetal toolchain.
[1] https://developer.arm.com/documentation/100863/latest
The option `CV_SEMIHOSTING` is used to guard the bits in the code that
are specific to the target.
To build the code:
cmake ../opencv/ \
-DCMAKE_TOOLCHAIN_FILE=../opencv/platforms/semihosting/aarch64-semihosting.toolchain.cmake \
-DSEMIHOSTING_TOOLCHAIN_PATH=/path/to/baremetal-toolchain/bin/ \
-DBUILD_EXAMPLES=ON -GNinja
A barematel toolchain for targeting aarch64 semihosting can be found
at [2], under `aarch64-none-elf`.
[2] https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads
The folder `samples/semihosting` provides two example semihosting
applications.
The two binaries can be executed on the host platform with:
qemu-aarch64 ./bin/example_semihosting_histogram
qemu-aarch64 ./bin/example_semihosting_norm
Similarly, the test and perf executables of the modules can be run
with:
qemu-aarch64 ./bin/opecv_[test|perf]_<module>
Notice that filesystem support is disabled by the toolchain file,
hence some of the test that depend on filesystem support will fail.
* [semihosting] Remove blank like at the end of file. [NFC]
The spurious blankline was reported by
https://pullrequest.opencv.org/buildbot/builders/precommit_docs/builds/31158.
* [semihosting] Make the raw pixel file generation OS independent.
Use the facilities provided by Cmake to generate the header file
instead of a shell script, so that the build doesn't fail on systems
that do not have a unix shell.
* [semihosting] Rename variable for semihosting compilation.
* [semihosting] Move the cmake configuration to a variable file.
* [semihosting] Make the guard macro private for the core module.
* [semihosting] Remove space. [NFC]
* [semihosting] Improve comment with information about semihosting. [NFC]
* [semihosting] Update license statement on top of sourvce file. [NFC]
* [semihosting] Replace BM_SUFFIX with SEMIHOSTING_SUFFIX. [NFC]
* [semihosting] Remove double space. [NFC]
* [semihosting] Add some text output to the sample applications.
* [semihosting] Remove duplicate entry in cmake configuration. [NFCI]
* [semihosting] Replace `long` with `int` in sample apps. [NFCI]
* [semihosting] Use `configure_file` to create the random pixels. [NFCI]
* [semihosting][bugfix] Fix name of cmakedefine variable.
* [semihosting][samples] Use CV_8UC1 for grayscale images. [NFCI]
* [semihosting] Add readme file.
* [semihosting] Remove blank like at the end of README. [NFC]
This fixes the failure at
https://pullrequest.opencv.org/buildbot/builders/precommit_docs/builds/31272.
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
* [build][option] Introduce `OPENCV_DISABLE_THREAD_SUPPORT` option.
The option forces the library to build without thread support.
* update handling of OPENCV_DISABLE_THREAD_SUPPORT
- reduce amount of #if conditions
* [to squash] cmake: apply mode vars in toolchains too
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
* Support cl_image conversion for CL_HALF_FLOAT (float16)
* Support cl_image conversion for additional channel orders:
CL_A, CL_INTENSITY, CL_LUMINANCE, CL_RG, CL_RA
* Comment on why cl_image conversion is unsupported for CL_RGB
* Predict optimal vector width for float16
* ocl::kernelToStr: support float16
* ocl::Device::halfFPConfig: drop artificial requirement for OpenCL
version >= 1.2. Even OpenCL 1.0 supports the underlying config
property, CL_DEVICE_HALF_FP_CONFIG.
* dumpOpenCLInformation: provide info on OpenCL half-float support
and preferred half-float vector width
* randu: support default range [-1.0, 1.0] for float16
* TestBase::warmup: support float16
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 ).
Fix dynamic loading of clBLAS and clFFT (formerly, clAmdBlas and clAmdFft)
* Fix dynamic loading of clBLAS and clFFT
* Update filenames and function names for clBLAS (formerly, clAmdBlas)
* Update filenames and function names for clFFT (formerly, clAmdFft)
* Uncomment teardown of clFFT; tear down clFFT in same way as clBLAS
* Fix generators for clBLAS and clFFT headers
* Update generators to parse recent clBLAS and clFFT library headers
* Update generators to be compatible with Python 3
* Re-generate OpenCV's clBLAS and clFFT headers
* Update function calls to match names in newly generated headers
* Disable (and comment on) teardown code for clBLAS and clFFT
* Renaming *clamd* files
* Renaming *clamdblas* files to *clblas*
* Renaming *clamdfft* files to *clfft*
* Update generator for CL headers
* Update generator to be compatible with Python 3
* extended C++ version of Levenberg-Marquardt (LM) solver to accommodate all features of the C counterpart.
* removed C version of LM solver
* made a few other little changes to make the code compile and run smoothly
* Add the support for riscv64 vector 0.7.1.
* fixed GCC warnings
* cleaned whitespaces
* Remove the worning by the use of internal API of compiler.
* Update the license header.
* removed trailing whitespaces
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@me.com>
Co-authored-by: yulj <linjie.ylj@alibaba-inc.com>
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
* Add Python Bindings for getCacheDirectory function
* Added getCacheDirectory interop test with image codecs.
Co-authored-by: Sergey Slashchinin <sergei.slashchinin@xperience.ai>
- 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
- 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)
- 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.
* implements https://github.com/opencv/opencv/issues/19147
* CAUTION: this PR will only functions safely in the
4+ branches that already include PR 19029
* CAUTION: this PR requires thread-safe startup of the alloc.cpp
translation unit as implemented in PR 19029
add thread-safe startup of fastMalloc and fastFree
* add perf test core memory allocation
* fix threading in isAlignedAllocationEnabled()
* tweaks requested by maintainer
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.
Added clapack
* bring a small subset of Lapack, automatically converted to C, into OpenCV
* added missing lsame_ prototype
* * small fix in make_clapack script
* trying to fix remaining CI problems
* fixed character arrays' initializers
* get rid of F2C_STR_MAX
* * added back single-precision versions for QR, LU and Cholesky decompositions. It adds very little extra overhead.
* added stub version of sdesdd.
* uncommented calls to all the single-precision Lapack functions from opencv/core/src/hal_internal.cpp.
* fixed warning from Visual Studio + cleaned f2c runtime a bit
* * regenerated Lapack w/o forward declarations of intrinsic functions (such as sqrt(), r_cnjg() etc.)
* at once, trailing whitespaces are removed from the generated sources, just in case
* since there is no declarations of intrinsic functions anymore, we could turn some of them into inline functions
* trying to eliminate the crash on ARM
* fixed API and semantics of s_copy
* * CLapack has been tested successfully. It's now time to restore the standard LAPACK detection procedure
* removed some more trailing whitespaces
* * retained only the essential stuff in CLapack
* added checks to lapack calls to gracefully return "not implemented" instead of returning invalid results with "ok" status
* disabled warning when building lapack
* cmake: update LAPACK detection
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
- 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
- Added cross compile cmake file for target riscv64-clang
- Extended cmake for RISC-V and added instruction checks
- Created intrin_rvv.hpp with C++ version universal intrinsics
* 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
* 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)
trying to fix handling file storages with extremely long lines
* trying to fix handling of file storages with extremely long lines: https://github.com/opencv/opencv/issues/11061
* * fixed errorneous pointer access in JSON parser.
* it's now crash-test time! temporarily set the initial parser buffer size to just 40 bytes. let's run all the test and check if the buffer is always correctly resized and handled
* fixed pointer use in JSON parser; added the proper test to catch this case
* fixed the test to make it more challenging. generate test json with
*
**
***
etc. shape
* 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
* add cv::compare test when Mat type == CV_16F
* add assertion in cv::compare when src.depth() == CV_16F
* cv::compare assertion minor fix
* core: add more checks