* significantly reduced OpenCV binary size by disabling IPP calls in some OpenCV functions: Sobel, Scharr, medianBlur, GaussianBlur, filter2D, mean, meanStdDev, norm, sum, minMaxIdx, sort.
* re-enable IPP in norm, since it's much faster (without adding too much space overhead)
* integrated the new C++ persistence; removed old persistence; most of OpenCV compiles fine! the tests have not been run yet
* fixed multiple bugs in the new C++ persistence
* fixed raw size of the parsed empty sequences
* [temporarily] excluded obsolete applications traincascade and createsamples from build
* fixed several compiler warnings and multiple test failures
* undo changes in cocoa window rendering (that was fixed in another PR)
* fixed more compile warnings and the remaining test failures (hopefully)
* trying to fix the last little warning
- initialize arithmetic dispatcher
- add new universal intrinsic v_absdiffs
- add new universal intrinsic v_pack_b
- add accumulate version of universal intrinsic v_round
- fix sse/avx2:uint8 multiplication overflow
- reimplement arithmetic, logic and comparison operations into wide universal intrinsics
with full support for all types
- reimplement IPP arithmetic, logic and comparison operations in a sperate file arithm_ipp.hpp
- avoid scalar multiplication if scaling factor eq 1 and use integer multiplication
- move C arithmetic operations to precomp.hpp and delete [arithm_simd|arithm_core].hpp
- add compatibility with new opencv4 divide policy
Exceptions caught by value incur needless cost in C++, most of them can
be caught by const-reference, especially as nearly none are actually
used. This could allow compiler generate a slightly more efficient code.
* js: update build script
- support emscipten 1.38.12 (wasm is ON by default)
- verbose build messages
* js: use builtin Math functions
* js: disable tracing code completelly
Fixes for instrumentation of IPP and OCL (#12637)
* fixed warning about re-declaring variable when both IPP and instrumentation are enabled
* fixed segfault when no funName provided
* compilation fixed when both OCL and instrumentation are enabled
- avoid updating of input image during equalizeHist() call
- avoid for() with double variable (use 'int' instead)
- more CV_Check*() macros
- use Mat_<T>, Matx
- static for local variables
* Remove isIntel check from deep learning layers
* Remove fp16->fp32 fallbacks where it's not necessary
* Fix Kernel::run to prevent localsize > globalsize
* added basic support for CV_16F (the new datatype etc.). CV_USRTYPE1 is now equal to CV_16F, which may break some [rarely used] functionality. We'll see
* fixed just introduced bug in norm; reverted errorneous changes in Torch importer (need to find a better solution)
* addressed some issues found during the PR review
* restored the patch to fix some perf test failures
* may be an typo fix
* remove identical branch,may be paste error
* add parentheses around macro parameter
* simplify if condition
* check malloc fail
* change the condition of branch removed by commit 3041502861
* rewrote Mat::convertTo() and convertScaleAbs() to wide universal intrinsics; added always-available and SIMD-optimized FP16<=>FP32 conversion
* fixed compile warnings
* fix some more compile errors
* slightly relaxed accuracy threshold for int->float conversion (since we now do it using single-precision arithmetics, not double-precision)
* fixed compile errors on iOS, Android and in the baseline C++ version (intrin_cpp.hpp)
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
fix some errors found by static analyzer. (#12391)
* fix possible divided by zero and by negative values
* only 4 elements are used in these arrays
* fix uninitialized member
* use boolean type for semantic boolean variables
* avoid invalid array index
* to avoid exception and because base64_beg is only used in this block
* use std::atomic<bool> to avoid thread control race condition
* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)
* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.
* Add coditional iclusion of hpx_main.hpp to cpp cpu modules
* Remove start/stop version of hpx backend
- use '3.4.x' cache name for current maintenance series (there are no serious changes between releases)
- message is shown only once during creation of new cache directory
- use OPENCV_CACHE_SHOW_CLEANUP_MESSAGE=0 to hide this warning
for some big negative values less than -INT_MAX+32767 the sign of the numbers is lost due to overflow that leads to
incorrect saturation to MAX value, instead of zero.
The issue is not reproduced with CV_ENABLED_INTRINSICS=OFF
Changed the type of variable *r* from int to size_t.
This change makes sure that a valid result of std::max(r + delta,
(r*3+1)/2) can be passed into the reserve function.
* 1. changed static const __m128/256 to const __m128/256 to avoid wierd instructions and calls inserted by compiler.
2. added universal intrinsics that wrap MOVNTPS and other such (non-temporary or "no cache" store) instructions. v_store_interleave() and v_store() got respective flags/overloaded variants
3. rewrote split & merge to use the "no cache" store instructions. It resulted in dramatic performance improvement when processing big arrays
* hopefully, fixed some test failures where 4-channel v_store_interleave() is used
* added missing implementation of the new universal intrinsics (v_store_aligned_nocache() etc.)
* fixed silly typo in the new intrinsics in intrin_vsx.hpp
* still trying to fix VSX compiler errors
* still trying to fix VSX compiler errors
* still trying to fix VSX compiler errors
* still trying to fix VSX compiler errors
* fixed/updated v_load_deinterleave and v_store_interleave intrinsics; modified split() and merge() functions to use those intrinsics
* fixed a few compile errors and bug in v_load_deinterleave(ptr, v_uint32x4& a, v_uint32x4& b)
* fixed few more compile errors
* core:OE-27 prepare universal intrinsics to expand (#11022)
* core:OE-27 prepare universal intrinsics to expand (#11022)
* core: Add universal intrinsics for AVX2
* updated implementation of wide univ. intrinsics; converted several OpenCV HAL functions: sqrt, invsqrt, magnitude, phase, exp to the wide universal intrinsics.
* converted log to universal intrinsics; cleaned up the code a bit; added v_lut_deinterleave intrinsics.
* core: Add universal intrinsics for AVX2
* fixed multiple compile errors
* fixed many more compile errors and hopefully some test failures
* fixed some more compile errors
* temporarily disabled IPP to debug exp & log; hopefully fixed Doxygen complains
* fixed some more compile errors
* fixed v_store(short*, v_float16&) signatures
* trying to fix the test failures on Linux
* fixed some issues found by alalek
* restored IPP optimization after the patch with AVX wide intrinsics has been properly tested
* restored IPP optimization after the patch with AVX wide intrinsics has been properly tested
* a part of https://github.com/opencv/opencv/pull/11364 by Tetragramm. Rewritten and extended findNonZero & PSNR to support more types, not just 8u.
* fixed compile & doxygen warnings
* fixed small bug in findNonZero test
fixes handling of empty matrices in some functions (#11634)
* a part of PR #11416 by Yuki Takehara
* moved the empty mat check in Mat::copyTo()
* fixed some test failures
* make sure that the matrix with more than INT_MAX elements is marked as non-continuous, and thus all the pixel-wise functions process it correctly (i.e. row-by-row, not as a single row, where integer overflow may occur when computing the total number of elements)
* Fix CV_Asserts with negation of strings
{!"string"} causes some compilers to throw a warning.
The value of the string is not that important -- it's only for printing
the assertion message.
Replace these calls with:
CV_Error(Error::StsError, "string")
to suppress the warning.
* remove unnecessary 'break' after CV_Error()
OpenCV pthreads-based implementation changes:
- rework worker threads pool, allow to execute job by the main thread too
- rework synchronization scheme (wait for job completion, threads 'pong' answer is not required)
- allow "active wait" (spin) by worker threads and by the main thread
- use _mm_pause() during active wait (support for Hyper-Threading technology)
- use sched_yield() to avoid preemption of still working other workers
- don't use getTickCount()
- optional builtin thread pool profiler (disabled by compilation flag)
UMatData locks are not mapped on real locks (they are mapped to some "pre-initialized" pool).
Concurrent execution of these statements may lead to deadlock:
- a.copyTo(b) from thread 1
- c.copyTo(d) from thread 2
where:
- 'a' and 'd' are mapped to single lock "A".
- 'b' and 'c' are mapped to single lock "B".
Workaround is to process locks with strict order.
fix the "initializing global variables with values that are not
compile-time constants" issue in Intel SDK for OpenCL. The root cause
is when initializing global variables with value, the variable need is
compile-time constants.
Thanks Zheng, Yang <yang.zheng@intel.com>,
Chodor, Jaroslaw <jaroslaw.chodor@intel.com> give a help.
Signed-off-by: Liu,Kaixuan <kaixuan.liu@intel.com>
Signed-off-by: Jun Zhao <jun.zhao@intel.com>
* remove raw SSE2/NEON implementation from convert.cpp
* remove raw implementation from Cvt_SIMD
* remove raw implementation from cvtScale_SIMD
* remove raw implementation from cvtScaleAbs_SIMD
* remove duplicated implementation cvt_<float, short>
* remove duplicated implementation cvtScale_<short, short, float>
* add "from double" version of Cvt_SIMD
* modify the condition of test ConvertScaleAbs
* Update convert.cpp
fixed crash in cvtScaleAbs(8s=>8u)
* fixed compile error on Win32
* fixed several test failures because of accuracy loss in cvtScale(int=>int)
* fixed NEON implementation of v_cvt_f64(int=>double) intrinsic
* another attempt to fix test failures
* keep trying to fix the test failures and just introduced compile warnings
* fixed one remaining test (subtractScalar)
- don't store ProgramSource in compiled Programs (resolved problem with "source" buffers lifetime)
- completelly remove Program::read/write methods implementation:
- replaced with method to query RAW OpenCL binary without any "custom" data
- deprecate Program::getPrefix() methods
* fixed OpenCL functions on Mac, so that the tests pass
* fixed compile warnings; temporarily disabled OCL branch of TV L1 optical flow on mac
* fixed other few warnings on macos
If there are no OpenCL/UMat methods calls from application.
OpenCL subsystem is initialized:
- haveOpenCL() is called from application
- useOpenCL() is called from application
- access to OpenCL allocator: UMat is created (empty UMat is ignored) or UMat <-> Mat conversions are called
Don't call OpenCL functions if OPENCV_OPENCL_RUNTIME=disabled
(independent from OpenCL linkage type)
* add accuracy test and performance check for matmul
* add performance tests for transform and dotProduct
* add test Core_TransformLargeTest for 8u version of transform
* remove raw SSE2/NEON implementation from matmul.cpp
* use universal intrinsic instead of raw intrinsic
* remove unused templated function
* add v_matmuladd which multiply 3x3 matrix and add 3x1 vector
* add v_rotate_left/right in universal intrinsic
* suppress intrinsic on some function and platform
* add pure SW implementation of new universal intrinsics
* add test for new universal intrinsics
* core: prevent memory access after the end of buffer
* fix perf tests
- changed behavior of vec_ctf, vec_ctu, vec_cts
in gcc and clang to make them compatible with XLC
- implemented most of missing conversion intrinsics in gcc and clang
- implemented conversions intrinsics of odd-numbered elements
- ignored gcc bug warning that caused by -Wunused-but-set-variable in rare cases
- replaced right shift with algebraic right shift for signed vectors
to shift in the sign bit.
- added new universal intrinsics v_matmuladd, v_rotate_left/right
- avoid using floating multiply-add in RNG
Exampls of these are gnu/kfreebsd and gnu/hurd, both available as
unofficial Debian ports.
They don't define __linux__ (as they are non-linux…) but still define
__GLIBC__, so check on that.
Signed-off-by: Mattia Rizzolo <mattia@mapreri.org>
* Update OpenCVCompilerOptimizations.cmake
Neon not supported on MSVC ARM breaking build fix
* Update OpenCVCompilerOptimizations.cmake
Whitespace
* Update intrin.hpp
Many problems in MSVC ARM builds (at least on VS2017) being fixed in this PR now.
C:\Users\Gregory\DOCUME~1\MYLIBR~1\OPENCV~3\opencv\sources\modules\core\include\opencv2/core/hal/intrin.hpp(444): error C3861: '_tzcnt_u32': identifier not found
* Update hal_replacement.hpp
Passing variadic expansion in a macro to another macro does not work properly in MSVC and a famous known workaround is hereby applied. Discussion of it: https://stackoverflow.com/questions/5134523/msvc-doesnt-expand-va-args-correctly
Only needed the fix for ARM builds: TEGRA_ macros are used for cv_hal_ functions in the carotene library.
C:\Users\Gregory\Documents\My Libraries\opencv330\opencv\sources\modules\core\src\arithm.cpp(2378): warning C4003: not enough actual parameters for macro 'TEGRA_ADD'
C:\Users\Gregory\Documents\My Libraries\opencv330\opencv\sources\modules\core\src\arithm.cpp(2378): error C2143: syntax error: missing ')' before ','
C:\Users\Gregory\Documents\My Libraries\opencv330\opencv\sources\modules\core\src\arithm.cpp(2378): error C2059: syntax error: ')'
* Update hal_replacement.hpp
All hal_replacement's using carotene\hal\tegra_hal.hpp TEGRA_ functions as macros preprocessed by variadic macros should be changed, identical as was done in core.
C:\Users\Gregory\Documents\My Libraries\opencv330\opencv\sources\modules\imgproc\src\color.cpp(9604): warning C4003: not enough actual parameters for macro 'TEGRA_CVTBGRTOBGR'
C:\Users\Gregory\Documents\My Libraries\opencv330\opencv\sources\modules\imgproc\src\color.cpp(9604): error C2059: syntax error: '=='
* Update OpenCVCompilerOptimizations.cmake
* Update hal_replacement.hpp
* Update hal_replacement.hpp
The same code was repeated several time for different data types, so
it was extracted as a templated function to improve maintability and
make a code more clear.
Exception may be rasied inside the body of a copying constructor after
refcount has been increased, and beacause in the case of the exception
destrcutor is never called what causes memory leak. This commit adds a
workaround that calls the release() function before the exception is
thrown outside the contructor.
add libdnn acceleration to dnn module (#9114)
* import libdnn code
Signed-off-by: Li Peng <peng.li@intel.com>
* add convolution layer ocl acceleration
Signed-off-by: Li Peng <peng.li@intel.com>
* add pooling layer ocl acceleration
Signed-off-by: Li Peng <peng.li@intel.com>
* add softmax layer ocl acceleration
Signed-off-by: Li Peng <peng.li@intel.com>
* add lrn layer ocl acceleration
Signed-off-by: Li Peng <peng.li@intel.com>
* add innerproduct layer ocl acceleration
Signed-off-by: Li Peng <peng.li@intel.com>
* add HAVE_OPENCL macro
Signed-off-by: Li Peng <peng.li@intel.com>
* fix for convolution ocl
Signed-off-by: Li Peng <peng.li@intel.com>
* enable getUMat() for multi-dimension Mat
Signed-off-by: Li Peng <peng.li@intel.com>
* use getUMat for ocl acceleration
Signed-off-by: Li Peng <peng.li@intel.com>
* use CV_OCL_RUN macro
Signed-off-by: Li Peng <peng.li@intel.com>
* set OPENCL target when it is available
and disable fuseLayer for OCL target for the time being
Signed-off-by: Li Peng <peng.li@intel.com>
* fix innerproduct accuracy test
Signed-off-by: Li Peng <peng.li@intel.com>
* remove trailing space
Signed-off-by: Li Peng <peng.li@intel.com>
* Fixed tensorflow demo bug.
Root cause is that tensorflow has different algorithm with libdnn
to calculate convolution output dimension.
libdnn don't calculate output dimension anymore and just use one
passed in by config.
* split gemm ocl file
split it into gemm_buffer.cl and gemm_image.cl
Signed-off-by: Li Peng <peng.li@intel.com>
* Fix compile failure
Signed-off-by: Li Peng <peng.li@intel.com>
* check env flag for auto tuning
Signed-off-by: Li Peng <peng.li@intel.com>
* switch to new ocl kernels for softmax layer
Signed-off-by: Li Peng <peng.li@intel.com>
* update softmax layer
on some platform subgroup extension may not work well,
fallback to non subgroup ocl acceleration.
Signed-off-by: Li Peng <peng.li@intel.com>
* fallback to cpu path for fc layer with multi output
Signed-off-by: Li Peng <peng.li@intel.com>
* update output message
Signed-off-by: Li Peng <peng.li@intel.com>
* update fully connected layer
fallback to gemm API if libdnn return false
Signed-off-by: Li Peng <peng.li@intel.com>
* Add ReLU OCL implementation
* disable layer fusion for now
Signed-off-by: Li Peng <peng.li@intel.com>
* Add OCL implementation for concat layer
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* libdnn: update license and copyrights
Also refine libdnn coding style
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
Signed-off-by: Li Peng <peng.li@intel.com>
* DNN: Don't link OpenCL library explicitly
* DNN: Make default preferableTarget to DNN_TARGET_CPU
User should set it to DNN_TARGET_OPENCL explicitly if want to
use OpenCL acceleration.
Also don't fusion when using DNN_TARGET_OPENCL
* DNN: refine coding style
* Add getOpenCLErrorString
* DNN: Use int32_t/uint32_t instread of alias
* Use namespace ocl4dnn to include libdnn things
* remove extra copyTo in softmax ocl path
Signed-off-by: Li Peng <peng.li@intel.com>
* update ReLU layer ocl path
Signed-off-by: Li Peng <peng.li@intel.com>
* Add prefer target property for layer class
It is used to indicate the target for layer forwarding,
either the default CPU target or OCL target.
Signed-off-by: Li Peng <peng.li@intel.com>
* Add cl_event based timer for cv::ocl
* Rename libdnn to ocl4dnn
Signed-off-by: Li Peng <peng.li@intel.com>
Signed-off-by: wzw <zhiwen.wu@intel.com>
* use UMat for ocl4dnn internal buffer
Remove allocateMemory which use clCreateBuffer directly
Signed-off-by: Li Peng <peng.li@intel.com>
Signed-off-by: wzw <zhiwen.wu@intel.com>
* enable buffer gemm in ocl4dnn innerproduct
Signed-off-by: Li Peng <peng.li@intel.com>
* replace int_tp globally for ocl4dnn kernels.
Signed-off-by: wzw <zhiwen.wu@intel.com>
Signed-off-by: Li Peng <peng.li@intel.com>
* create UMat for layer params
Signed-off-by: Li Peng <peng.li@intel.com>
* update sign ocl kernel
Signed-off-by: Li Peng <peng.li@intel.com>
* update image based gemm of inner product layer
Signed-off-by: Li Peng <peng.li@intel.com>
* remove buffer gemm of inner product layer
call cv::gemm API instead
Signed-off-by: Li Peng <peng.li@intel.com>
* change ocl4dnn forward parameter to UMat
Signed-off-by: Li Peng <peng.li@intel.com>
* Refine auto-tuning mechanism.
- Use OPENCV_OCL4DNN_KERNEL_CONFIG_PATH to set cache directory
for fine-tuned kernel configuration.
e.g. export OPENCV_OCL4DNN_KERNEL_CONFIG_PATH=/home/tmp,
the cache directory will be /home/tmp/spatialkernels/ on Linux.
- Define environment OPENCV_OCL4DNN_ENABLE_AUTO_TUNING to enable
auto-tuning.
- OPENCV_OPENCL_ENABLE_PROFILING is only used to enable profiling
for OpenCL command queue. This fix basic kernel get wrong running
time, i.e. 0ms.
- If creating cache directory failed, disable auto-tuning.
* Detect and create cache dir on windows
Signed-off-by: Li Peng <peng.li@intel.com>
* Refine gemm like convolution kernel.
Signed-off-by: Li Peng <peng.li@intel.com>
* Fix redundant swizzleWeights calling when use cached kernel config.
* Fix "out of resource" bug when auto-tuning too many kernels.
* replace cl_mem with UMat in ocl4dnnConvSpatial class
* OCL4DNN: reduce the tuning kernel candidate.
This patch could reduce 75% of the tuning candidates with less
than 2% performance impact for the final result.
Signed-off-by: Zhigang Gong <zhigang.gong@intel.com>
* replace cl_mem with umat in ocl4dnn convolution
Signed-off-by: Li Peng <peng.li@intel.com>
* remove weight_image_ of ocl4dnn inner product
Actually it is unused in the computation
Signed-off-by: Li Peng <peng.li@intel.com>
* Various fixes for ocl4dnn
1. OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel())
2. Ptr<OCL4DNNInnerProduct<float> > innerProductOp
3. Code comments cleanup
4. ignore check on OCL cpu device
Signed-off-by: Li Peng <peng.li@intel.com>
* add build option for log softmax
Signed-off-by: Li Peng <peng.li@intel.com>
* remove unused ocl kernels in ocl4dnn
Signed-off-by: Li Peng <peng.li@intel.com>
* replace ocl4dnnSet with opencv setTo
Signed-off-by: Li Peng <peng.li@intel.com>
* replace ALIGN with cv::alignSize
Signed-off-by: Li Peng <peng.li@intel.com>
* check kernel build options
Signed-off-by: Li Peng <peng.li@intel.com>
* Handle program compilation fail properly.
* Use std::numeric_limits<float>::infinity() for large float number
* check ocl4dnn kernel compilation result
Signed-off-by: Li Peng <peng.li@intel.com>
* remove unused ctx_id
Signed-off-by: Li Peng <peng.li@intel.com>
* change clEnqueueNDRangeKernel to kernel.run()
Signed-off-by: Li Peng <peng.li@intel.com>
* change cl_mem to UMat in image based gemm
Signed-off-by: Li Peng <peng.li@intel.com>
* check intel subgroup support for lrn and pooling layer
Signed-off-by: Li Peng <peng.li@intel.com>
* Fix convolution bug if group is greater than 1
Signed-off-by: Li Peng <peng.li@intel.com>
* Set default layer preferableTarget to be DNN_TARGET_CPU
Signed-off-by: Li Peng <peng.li@intel.com>
* Add ocl perf test for convolution
Signed-off-by: Li Peng <peng.li@intel.com>
* Add more ocl accuracy test
Signed-off-by: Li Peng <peng.li@intel.com>
* replace cl_image with ocl::Image2D
Signed-off-by: Li Peng <peng.li@intel.com>
* Fix build failure in elementwise layer
Signed-off-by: Li Peng <peng.li@intel.com>
* use getUMat() to get blob data
Signed-off-by: Li Peng <peng.li@intel.com>
* replace cl_mem handle with ocl::KernelArg
Signed-off-by: Li Peng <peng.li@intel.com>
* dnn(build): don't use C++11, OPENCL_LIBRARIES fix
* dnn(ocl4dnn): remove unused OpenCL kernels
* dnn(ocl4dnn): extract OpenCL code into .cl files
* dnn(ocl4dnn): refine auto-tuning
Defaultly disable auto-tuning, set OPENCV_OCL4DNN_ENABLE_AUTO_TUNING
environment variable to enable it.
Use a set of pre-tuned configs as default config if auto-tuning is disabled.
These configs are tuned for Intel GPU with 48/72 EUs, and for googlenet,
AlexNet, ResNet-50
If default config is not suitable, use the first available kernel config
from the candidates. Candidate priority from high to low is gemm like kernel,
IDLF kernel, basick kernel.
* dnn(ocl4dnn): pooling doesn't use OpenCL subgroups
* dnn(ocl4dnn): fix perf test
OpenCV has default 3sec time limit for each performance test.
Warmup OpenCL backend outside of perf measurement loop.
* use ocl::KernelArg as much as possible
Signed-off-by: Li Peng <peng.li@intel.com>
* dnn(ocl4dnn): fix bias bug for gemm like kernel
* dnn(ocl4dnn): wrap cl_mem into UMat
Signed-off-by: Li Peng <peng.li@intel.com>
* dnn(ocl4dnn): Refine signature of kernel config
- Use more readable string as signture of kernel config
- Don't count device name and vendor in signature string
- Default kernel configurations are tuned for Intel GPU with
24/48/72 EUs, and for googlenet, AlexNet, ResNet-50 net model.
* dnn(ocl4dnn): swap width/height in configuration
* dnn(ocl4dnn): enable configs for Intel OpenCL runtime only
* core: make configuration helper functions accessible from non-core modules
* dnn(ocl4dnn): update kernel auto-tuning behavior
Avoid unwanted creation of directories
* dnn(ocl4dnn): simplify kernel to workaround OpenCL compiler crash
* dnn(ocl4dnn): remove redundant code
* dnn(ocl4dnn): Add more clear message for simd size dismatch.
* dnn(ocl4dnn): add const to const argument
Signed-off-by: Li Peng <peng.li@intel.com>
* dnn(ocl4dnn): force compiler use a specific SIMD size for IDLF kernel
* dnn(ocl4dnn): drop unused tuneLocalSize()
* dnn(ocl4dnn): specify OpenCL queue for Timer and convolve() method
* dnn(ocl4dnn): sanitize file names used for cache
* dnn(perf): enable Network tests with OpenCL
* dnn(ocl4dnn/conv): drop computeGlobalSize()
* dnn(ocl4dnn/conv): drop unused fields
* dnn(ocl4dnn/conv): simplify ctor
* dnn(ocl4dnn/conv): refactor kernelConfig localSize=NULL
* dnn(ocl4dnn/conv): drop unsupported double / untested half types
* dnn(ocl4dnn/conv): drop unused variable
* dnn(ocl4dnn/conv): alignSize/divUp
* dnn(ocl4dnn/conv): use enum values
* dnn(ocl4dnn): drop unused innerproduct variable
Signed-off-by: Li Peng <peng.li@intel.com>
* dnn(ocl4dnn): add an generic function to check cl option support
* dnn(ocl4dnn): run softmax subgroup version kernel first
Signed-off-by: Li Peng <peng.li@intel.com>
This adds the possibility to use multi-channel masks for the functions
cv::mean, cv::meanStdDev and the method Mat::setTo. The tests have now a
probability to use multi-channel masks for operations that support them.
This also includes Mat::copyTo, which supported multi-channel masks
before, but there was no test confirming this.
This function is the counterpart of "Context::getProg".
With this function, users have chance to unload a program
from global run-time cached programs, and save resource.
OpenCL runtime does not require OpenCL development file (libOpenCL.so),
just the "run" library (so.1).
This patch searches for the run library (so.1) if the dev library (.so)
is not found.
Web search shows that this error has been present since at least 2015
http://answers.opencv.org/question/80532/haveopencl-return-false/
Signed-off-by: Ricardo Ribalda Delgado <ricardo.ribalda@gmail.com>
- Optimizations set change. Now IPP integrations will provide code for SSE42, AVX2 and AVX512 (SKX) CPUs only. For HW below SSE42 IPP code is disabled.
- Performance regressions fixes for IPP code paths;
- cv::boxFilter integration improvement;
- cv::filter2D integration improvement;
RGB2Lab_f added, bugs fixed, moved to float
several bugs fixed
LUT fixed, no switch in tetraInterpolate()
temporary code; to be removed and rewritten
before refactoring
extra interpolations removed, some things to do left
added Lab2RGB_b +XYZ version, etc.
basic version is done, to be sped up
tetra refactored
interpolations: LUT for weights, refactor., etc.
address arithm optimized
initial version of vectorized code added (not compiling now)
compilation fixed, now segfaults
a lot of fixes, vectorization temp. disabled
fixed trilinear shift size, max error dropped from 19 to 10
fixed several bugs (255 vs 256, signed vs unsigned, bIdx)
minor changes
packed: address arithmetics fixed
shorter code
experiments with pure integer calculations
Lab2RGB max error decreased to 2; need to clean the code
ready for vectorization; need cleaning
vectorized, to be debugged
precision fixed, max error is 2
Lab->XYZ shortened
minor fixes
Lab2RGB_f version fixed, to be completely rewritten using _b code
RGB2Lab_f vectorized
minors
moved to separate file
refactored Lab2RGB to float and int versions
minor fix
Lab2RGB_f vectorized
minor refactoring
Lab2RGBint refactored: process methods, vectorize by 4 pix
Lab2RGB_f int version is done
cleanup extra code
code copied to color.cpp
fixed blue idx bug
optimizations enabled when testing; mulFracConst introduced
divConst -> mulFracConst
calc min time in perf instead of avg
minors
process() slightly sped up
Lab2RGB_f: disabled int version
reinterpret added, minor fixes in names
some warnings fixed
changes transferred to color.cpp
RGB2Lab_f code (and trilinear interpolation code) moved to rgb2lab_faster
whitespace
shift negative fixed
more warnings fixed
"constant condition" warnings fixed, little speed up
minor changes
test_photo decolor fixed
changes copied to test_lab.cpp
idx bounds checking in LUT init
several fixes
WIP: softfloat almost integrated
test_lab partially rewritten to SoftFloat
color.cpp rewritten to SoftFloat
test_lab.cpp: accuracy code added
several fixes
RGB2Lab_b testing fixed
splineBuild() rewritten to SoftFloat
accuracy control improved
rounding fixed
Luv <=> RGB: rewritten to SoftFloat
OCL cvtColor Lab and Lut rewritten to SoftFloat
minor fixes
refactored to new SoftFloat interface
round() -> cvRound, etc.
fixed OCL tests
softfloat.cpp: internal functions made static, unused ones removed
meaningful constants
extra lines removed
unused function removed
unfinished work
it works, need to fix TODOs
refactoring; more calls rewritten
mulFracConst removed
constants made bit exact; minors
changes moved to color.cpp
fixed 1 bug and 4 warnings
OCL: fixed constants
pow(x, _1_3f) replaced by cubeRoot(x)
fixed compilation on MSVC32
magic constants explained
file with internal accuracy&speed tests moved to lab_tetra branch
Fixed snprintf for VS 2013 (#8816)
* Fixed snprintf for VS 2013
* snprintf: removed declaration from header, changed implementation
* cv_snprintf corrected according to comments
* update snprintf patch
* avoid link error (move the implementation of software version to header)
* make getConvertFuncFp16 local (move from precomp.hpp to convert.hpp)
* fix error on 32bit x86
- persistence.cpp code expects special sizeof value for passed structures
- this assumption is lead to memory corruption problems
- fixed/workarounded test to prevent memory corruption on Linux 32-bit systems
Updated integrations for:
cv::split
cv::merge
cv::insertChannel
cv::extractChannel
cv::Mat::convertTo - now with scaled conversions support
cv::LUT - disabled due to performance issues
Mat::copyTo
Mat::setTo
cv::flip
cv::copyMakeBorder - currently disabled
cv::polarToCart
cv::pow - ipp pow function was removed due to performance issues
cv::hal::magnitude32f/64f - disabled for <= SSE42, poor performance
cv::countNonZero
cv::minMaxIdx
cv::norm
cv::canny - new integration. Disabled for threaded;
cv::cornerHarris
cv::boxFilter
cv::bilateralFilter
cv::integral
Add support for std::array<T, N> (#8535)
* Add support for std::array<T, N>
* Add std::array<Mat, N> support
* Remove UMat constructor with std::array parameter
Gemm kernels for Intel GPU (#8104)
* Fix an issue with Kernel object reset release when consecutive Kernel::run calls
Kernel::run launch OCL gpu kernels and set a event callback function
to decreate the ref count of UMat or remove UMat when the lauched workloads
are completed. However, for some OCL kernels requires multiple call of
Kernel::run function with some kernel parameter changes (e.g., input
and output buffer offset) to get the final computation result.
In the case, the current implementation requires unnecessary
synchronization and cleanupMat.
This fix requires the user to specify whether there will be more work or not.
If there is no remaining computation, the Kernel::run will reset the
kernel object
Signed-off-by: Woo, Insoo <insoo.woo@intel.com>
* GEMM kernel optimization for Intel GEN
The optimized kernels uses cl_intel_subgroups extension for better
performance.
Note: This optimized kernels will be part of ISAAC in a code generation
way under MIT license.
Signed-off-by: Woo, Insoo <insoo.woo@intel.com>
* Fix API compatibility error
This patch fixes a OCV API compatibility error. The error was reported
due to the interface changes of Kernel::run. To resolve the issue,
An overloaded function of Kernel::run is added. It take a flag indicating
whether there are more work to be done with the kernel object without
releasing resources related to it.
Signed-off-by: Woo, Insoo <insoo.woo@intel.com>
* Renaming intel_gpu_gemm.cpp to intel_gpu_gemm.inl.hpp
Signed-off-by: Woo, Insoo <insoo.woo@intel.com>
* Revert "Fix API compatibility error"
This reverts commit 2ef427db91.
Conflicts:
modules/core/src/intel_gpu_gemm.inl.hpp
* Revert "Fix an issue with Kernel object reset release when consecutive Kernel::run calls"
This reverts commit cc7f9f5469.
* Fix the case of uninitialization D
When C is null and beta is non-zero, D is used without initialization.
This resloves the issue
Signed-off-by: Woo, Insoo <insoo.woo@intel.com>
* fix potential output error due to 0 * nan
Signed-off-by: Woo, Insoo <insoo.woo@intel.com>
* whitespace fix, eliminate non-ASCII symbols
* fix build warning
Although both `cl_platform_info` and `cl_device_info` are defined as macro `cl_uint`, it needs to use `cl_platform_info` to get
the platform information.
- don't use undefined flag=0. It should be CONSTANT instead.
- don't allow 'UMat* m=NULL' argument (except LOCAL/CONSTANT flags).
This case is not handled well to provide NULL __global pointers.
It is better to use '-D' macro defines instead (at least for performance)
Append zero to trailing decimal place for FileStorage JSON write of a float or double value (#7952)
* Fix for FileStorage JSON write of a float or double value that has no fractional part; appends a zero character after the trailing decimal place to meet JSON standard.
* strlen return to size_t type rather than unnecessary cast to int
* moved BLAS/LAPACK detection scripts from opencv_contrib/dnn to the main repository.
* trying to fix the bug with undefined symbols sgesdd_ and dgesdd_
* removed extra whitespaces; disabled LAPACK on IOS
Currently, to select a submatrix of a N-dimensional matrix, it requires
two lines of code while only one line of code is required if using a 2D
array.
I added functionality to be able to select an N-dim submatrix using a
vector list instead of a Range pointer. This allows initializer lists to
be used for a one-line selection.
This allows for an N-dimensional array to be setup in one line instead of two when using C++11 initializer lists. cv::Mat(3, {zDim, yDim, xDim}, ...) can be used instead of having to create an int pointer to hold the size array.
Maximum depth limit var was added to the instrumentation structure;
Trace names output console output fix: improper tree formatting could happen;
Output in case of error was added;
Custom regions improvements;
Improved timing and weight calculation for parallel regions; New TC (threads counter) value to indicate how many different threads accessed particular node;
parallel_for, warnings fixes and ReturnAddress code from Alexander Alekhin;
* use hasSIMD128 rather than calling checkHardwareSupport
* add SIMD check in spartialgradient.cpp
* add SIMD check in stereosgbm.cpp
* add SIMD check in canny.cpp
In YAML 1.0 the colon is mandatory. See http://yaml.org/spec/1.0/#id2558635.
This also allows prior releases to read YAML files created with the current version.
* use __GNUC_MINOR__ in correct place to check the version of GCC
* check processor support of FP16 at run time
* check compiler support of FP16 and pass correct compiler option
* rely on ENABLE_AVX on gcc since AVX is generated when mf16c is passed
* guard correctly using ifdef in case of various configuration
* use v_float16x4 correctly by including the right header file
- calculate ticksTotal instead of ticksMean
- local / global width is based on ticksTotal value
- added instrumentation for OpenCL program compilation
- added instrumentation for OpenCL kernel execution
Minor fix in MatAllocator::upload
Minor fix in MatAllocator::copy
Minor fix in setSize function
Minor fix in Mat::Mat
Minor fix in cvMatNDToMat function
Minor fix in _InputArray::getMatVector
Minor fix in _InputArray::getUMatVector
Minor fix in cv::hconcat
Minor fix in cv::vconcat
Minor fix in cv::setIdentity
Minor fix in cv::trace
Minor fix in transposeI_ template function
Minor fix in reduceC_ template function
Minor fix in sort_ template function
Minor fix in sortIdx_ template function
Minor fix in cvRange function
Minor fix in MatConstIterator::seek
Minor fix in SparseMat::create
Minor fix in SparseMat::copyTo
Minor fix in SparseMat::convertTo
Minor fix in SparseMat::convertTo
Minor fix in SparseMat::ptr
Minor fix in SparseMat::resizeHashTab
Fixes indentation
* use v_float16x4 (universal intrinsic) instead of raw SSE/NEON implementation
* define v_load_f16/v_store_f16 since v_load can't be distinguished when short pointer passed
* brush up implementation on old compiler (guard correctly)
* add test for v_load_f16 and round trip conversion of v_float16x4
* fix conversion error
* raise an error when wrong bit depth passed
* raise an build error when wrong depth is specified for cvtScaleHalf_
* remove unnecessary safe check in cvtScaleHalf_
* use intrinsic instead of direct pointer access
* update the explanation
Major changes:
- modify the Base64 functions to compatible with `cvWriteRawData` and so
on.
- add a Base64 flag for FileStorage and outputs raw data in Base64
automatically.
- complete all testing and documentation.
The three new functions:
```cpp
void cvStartWriteRawData_Base64(::CvFileStorage * fs, const char* name,
int len, const char* dt);
void cvWriteRawData_Base64(::CvFileStorage *
fs, const void* _data, int len);
void
cvEndWriteRawData_Base64(::CvFileStorage * fs);
```
Test is also updated. (And it's remarkable that there is a bug in
`cvWriteReadData`.)
* check compiler more strictly
* use gcc version of fp16 conversion if it's possible (gcc 4.7 and later)
* use current SW implementation in other cases
