* Fix compile against lapack-3.10.0
Fix compilation against lapack >= 3.9.1 and 3.10.0 while not breaking older versions
OpenCVFindLAPACK.cmake & CMakeLists.txt: determine OPENCV_USE_LAPACK_PREFIX from LAPACK_VERSION
hal_internal.cpp : Only apply LAPACK_FUNC to functions whose number of inputs depends on LAPACK_FORTRAN_STR_LEN in lapack >= 3.9.1
lapack_check.cpp : remove LAPACK_FUNC which is not OK as function are not used with input parameters (so lapack.h preprocessing of "LAPACK_xxxx(...)" is not applicable with lapack >= 3.9.1
If not removed lapack_check fails so LAPACK is deactivated in build (not want we want)
use OCV_ prefix and don't use Global, instead generate OCV_LAPACK_FUNC depending on CMake Conditions
Remove CONFIG from find_package(LAPACK) and use LAPACK_GLOBAL and LAPACK_NAME to figure out if using netlib's reference LAPACK implementation and how to #define OCV_LAPACK_FUNC(f)
* Fix typos and grammar in comments
Fixed threshold(THRESH_TOZERO) at imgproc(IPP)
* Fixed#16085: imgproc(IPP): wrong result from threshold(THRESH_TOZERO)
* 1. Added test cases with float where all bits of mantissa equal 1, min and max float as inputs
2. Used nextafterf instead of cast to hex
* Used float value in test instead of hex and casts
* Changed input value in test
When computing:
t1 = (bayer[1] + bayer[bayer_step] + bayer[bayer_step+2] + bayer[bayer_step*2+1])*G2Y;
there is a T (unsigned short or char) multiplied by an int which can overflow.
Then again, it is stored to t1 which is unsigned so the overflow disappears.
Keeping all unsigned is safer.
Further optimize DNN for RISC-V Vector.
* Optimize DNN on RVV by using vsetvl.
* Rename vl.
* Update fastConv by using setvl instead of mask.
* Fix fastDepthwiseConv
- QGLWidget changed to QOpenGLWidget in window_QT.h for Qt6 using
typedef OpenCVQtWidgetBase for handling Qt version
- Implement Qt6/OpenGL functionality in window_QT.cpp
- Swap QGLWidget:: function calls for OpenCVQtWidgetBase:: function calls
- QGLWidget::updateGL deprecated, swap to QOpenGLWidget::update for Qt6
- Add preprocessor definition to detect Qt6 -- HAVE_QT6
- Add OpenGLWidgets to qdeps list in highgui CMakeLists.txt
- find_package CMake command added for locating Qt module OpenGLWidgets
- Added check that Qt6::OpenGLWidgets component is found. Shut off Qt-openGL functionality if not found.
Fow now, it is possible to define valid rectangle for which some
functions overflow (e.g. br(), ares() ...).
This patch fixes the intersection operator so that it works with
any rectangle.
G-API: oneVPL merge DX11 acceleration
* Merge DX11 initial
* Fold conditions row in MACRO in utils
* Inject DeviceSelector
* Turn on DeviceSelector in DX11
* Change sharedLock logic & Move FMT checking in FrameAdapter c-tor
* Move out NumSuggestFrame to configure params
* Drain file source fix
* Fix compilation
* Force zero initializetion of SharedLock
* Fix some compiler warnings
* Fix integer comparison warnings
* Fix integers in sample
* Integrate Demux
* Fix compilation
* Add predefined names for some CfgParam
* Trigger CI
* Fix MultithreadCtx bug, Add Dx11 GetBlobParam(), Get rif of ATL CComPtr
* Fix UT: remove unit test with deprecated video from opencv_extra
* Add creators for most usable CfgParam
* Eliminate some warnings
* Fix warning in GAPI_Assert
* Apply comments
* Add VPL wrapped header with MSVC pragma to get rid of global warning masking
Added CV_PROP_RW macro to keypoints
* Added CV_PROP_RW macro to keypoints
As outlined in the feature request in the issue https://github.com/opencv/opencv/issues/21171 : the keypoints field has been made parsable by the bindings.
* Added test for keypoints
Added test to check if the CV_PROP_RW macro added in the previous commit makes keypoints public and accessible through the python API.
Audio MSMF: added the ability to set sample per second
* Audio MSMF: added the ability to set sample per second
* changed the valid sampling rate check
* fixed docs
* add test
* fixed warning
* fixed error
* fixed error
Update RVV backend for using Clang.
* Update cmake file of clang.
* Modify the RVV optimization on DNN to adapt to clang.
* Modify intrin_rvv: Disable some existing types.
* Modify intrin_rvv: Reinterpret instead of load&cast.
* Modify intrin_rvv: Update load&store without cast.
* Modify intrin_rvv: Rename vfredsum to fredosum.
* Modify intrin_rvv: Rewrite Check all/any by using vpopc.
* Modify intrin_rvv: Use reinterpret instead of c-style casting.
* Remove all macros which is not used in v_reinterpret
* Rename vpopc to vcpop according to spec.
New odometry Pipeline
* first intergation
* tests run, but not pass
* add previous version of sigma calc
* add minor comment
* strange fixes
* fix fast ICP
* test changes; fast icp still not work correctly
* finaly, it works
* algtype fix
* change affine comparison
* boolean return
* fix bug with angle and cos
* test pass correctly
* fix for kinfu pipeline
* add compute points normals
* update for new odometry
* change odometry_evaluation
* odometry_evaluation works
* change debug logs
* minor changes
* change depth setting in odometryFrame
* fastICP works with 4num points
* all odometries work with 4mun points
* odometry full works on 4num points and normals
* replace ICP with DEPTH; comments replacements
* create prepareFrame; add docs for Odometry
* change getPyramids()
* delete extra code
* add intrinsics; but dont works
* bugfix with nan checking
* add gpu impl
* change createOdometryFrame func
* remove old fastICP code
* comments fix
* add comments
* minor fixes
* other minor fixes
* add channels assert
* add impl for odometry settings
* add pimpl to odometry
* linux warning fix
* linux warning fix 1
* linux warning fix 2
* linux error fix
* linux warning fix 3
* linux warning fix 4
* linux error fix 2
* fix test warnings
* python build fix
* doxygen fix
* docs fix
* change normal tests for 4channel point
* all Normal tests pass
* plane works
* add warp frame body
* minor fix
* warning fixes
* try to fix
* try to fix 1
* review fix
* lvls fix
* createOdometryFrame fix
* add comment
* const reference
* OPENCV_3D_ prefix
* const methods
* OdometryFramePyramidType ifx
* add assert
* precomp moved upper
* delete types_c
* add assert for get and set functions
* minor fixes
* remove core.hpp from header
* ocl_run add
* warning fix
* delete extra comment
* minor fix
* setDepth fix
* delete underscore
* odometry settings fix
* show debug image fix
* build error fix
* other minor fix
* add const to signatures
* fix
* conflict fix
* getter fix
* Fix integer overflow in cv::Luv2RGBinteger::process.
For LL=49, uu=205, vv=23, we end up with x=7373056 and y=458
which overflows y*x.
* imgproc(test): adjust test parameters to cover SIMD code
Accelerated 3D point cloud Farthest Point Sampling calculation using SIMD.
* Add several 3D point cloud sampling functions: Random, VoxelGrid, FarthestPoint.
* Made some code detail changes and exposed the random number generator parameters at the interface.
* Add simple tests for sampling.
* Modify interface output parameters.
* Modify interface return value.
* The sampling test is modified for the new changes of function interface.
* Improved test of VoxelGridFilterSampling
* Improved test of VoxelGridFilterSampling and FPS.
* Add test for the dist_lower_limit arguments of FPS function.
* Optimization function _getMatFromInputArray.
* Optimize the code style and some details according to the suggestions.
* Clear prefix cv: in the source code.
* Change the initialization of Mat in the sampling test.
* 1. Unified code style
2. Optimize randomSampling method
* 1. Optimize code comments.
2. Remove unused local variables.
* Rebuild the structure of the test, make the test case more reliable, and change the code style.
* Update test_sampling.cpp
Fix a warning.
* Use SIMD to optimize the farthest point sampling.
* Optimize the farthest point sampling SIMD code.
* 1. remove `\n` from the ptcloud.hpp comment.
2. updated the default value of the argument arrangement_of_points in the _getMatFromInputArray function in ptcloud_utils.hpp from 0 to 1, since the latter is more commonly used (such arrangement is easier for SIMD acceleration).
3. removed two functions in ptcloud_utils.hpp that were not used.
* Remove the <br> in the comment.
* Fix whitespace issues.
* dnn: LSTM optimisation
This uses the AVX-optimised fastGEMM1T for matrix multiplications where available, instead of the standard cv::gemm.
fastGEMM1T is already used by the fully-connected layer. This commit involves two minor modifications:
- Use unaligned access. I don't believe this involves any performance hit in on modern CPUs (Nehalem and Bulldozer onwards) in the case where the address is actually aligned.
- Allow for weight matrices where the number of columns is not a multiple of 8.
I have not enabled AVX-512 as I don't have an AVX-512 CPU to test on.
* Fix warning about initialisation order
* Remove C++11 syntax
* Fix build when AVX(2) is not available
In this case the CV_TRY_X macros are defined to 0, rather than being undefined.
* Minor changes as requested:
- Don't check hardware support for AVX(2) when dispatch is disabled for these
- Add braces
* Fix out-of-bounds access in fully connected layer
The old tail handling in fastGEMM1T implicitly rounded vecsize up to the next multiple of 8, and the fully connected layer implements padding up to the next multiple of 8 to cope with this. The new tail handling does not round the vecsize upwards like this but it does require that the vecsize is at least 8. To adapt to the new tail handling, the fully connected layer now rounds vecsize itself at the same time as adding the padding(which makes more sense anyway).
This also means that the fully connected layer always passes a vecsize of at least 8 to fastGEMM1T, which fixes the out-of-bounds access problems.
* Improve tail mask handling
- Use static array for generating tail masks (as requested)
- Apply tail mask to the weights as well as the input vectors to prevent spurious propagation of NaNs/Infs
* Revert whitespace change
* Improve readability of conditions for using AVX
* dnn(lstm): minor coding style changes, replaced left aligned load
[G-API] Fix issue of getting 1D Mat out of RMat::View
* Fix issue of getting 1D Mat out of RMat::View
- added test
- fixed for standalone too (removed Assert(dims.empty()))
* Fixed asVeiw() function for standalone
* Put more detailed comment
Add capacity to Videocapture to return the extraData from FFmpeg when required
* Update rawMode to append any extra data recieved during the initial negotiation of an RTSP stream or during the parsing of an MPEG4 file header.
For h264[5] RTSP streams this ensures the parameter sets if available are always returned on the first call to grab()/read() and has two purposes:
1) To ensure the parameter sets are available even if they are not transmitted in band. This is common for axis ip camera's.
2) To allow callers of VideoCapture::grab()[read()] to write to split the raw stream over multiple files by appending the parameter sets to the begining of any new files.
For (1) there is no alternative, for (2) if the parameter sets were provided in band it would be possible to parse the raw bit stream and search for the parameter sets however that would be a lot of work when that information is already provided by FFMPEG.
For MPEG4 files this information is only suplied in the header and is required for decoding.
Two properties are also required to enable the raw encoded bitstream to be written to multiple files, these are;
1) an indicator as to whether the last frame was a key frame or not - each new file needs to start at a key frame to avoid storing unusable frame diffs,
2) the length in bytes of the paramater sets contained in the last frame - required to split the paramater sets from the frame without having to parse the stream. Any call to VideoCapture::get(CAP_PROP_LF_PARAM_SET_LEN) returning a number greater than zero indicates the presense of a parameter set at the begining of the raw bitstream.
* Adjust test data to account for extraData
* Address warning.
* Change added property names and remove paramater set start code check.
* Output extra data on calls to retrieve instead of appending to the first packet.
* Reverted old test case and added new one to evaluate new functionality.
* Add missing definition.
* Remove flag from legacy api.
Add property to determine if returning extra data is supported.
Always allow extra data to be returned on calls to cap.retrieve()
Update test case.
* Update condition which indicates CAP_PROP_CODEC_EXTRADATA_INDEX is not supported in test case.
* Include compatibility for windows dll if not updated.
Enforce existing return status convention.
* Fix return error and missing test constraints.
[GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN
* Add WebNN backend for OpenCV DNN Module
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Add WebNN head files into OpenCV 3rd partiy files
Create webnn.hpp
update cmake
Complete README and add OpenCVDetectWebNN.cmake file
add webnn.cpp
Modify webnn.cpp
Can successfully compile the codes for creating a MLContext
Update webnn.cpp
Update README.md
Update README.md
Update README.md
Update README.md
Update cmake files and
update README.md
Update OpenCVDetectWebNN.cmake and README.md
Update OpenCVDetectWebNN.cmake
Fix OpenCVDetectWebNN.cmake and update README.md
Add source webnn_cpp.cpp and libary libwebnn_proc.so
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
update dnn.cpp
update op_webnn
update op_webnn
Update op_webnn.hpp
update op_webnn.cpp & hpp
Update op_webnn.hpp
Update op_webnn
update the skeleton
Update op_webnn.cpp
Update op_webnn
Update op_webnn.cpp
Update op_webnn.cpp
Update op_webnn.hpp
update op_webnn
update op_webnn
Solved the problems of released variables.
Fixed the bugs in op_webnn.cpp
Implement op_webnn
Implement Relu by WebNN API
Update dnn.cpp for better test
Update elementwise_layers.cpp
Implement ReLU6
Update elementwise_layers.cpp
Implement SoftMax using WebNN API
Implement Reshape by WebNN API
Implement PermuteLayer by WebNN API
Implement PoolingLayer using WebNN API
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Implement poolingLayer by WebNN API and add more detailed logs
Update dnn.cpp
Update dnn.cpp
Remove redundant codes and add more logs for poolingLayer
Add more logs in the pooling layer implementation
Fix the indent issue and resolve the compiling issue
Fix the build problems
Fix the build issue
FIx the build issue
Update dnn.cpp
Update dnn.cpp
* Fix the build issue
* Implement BatchNorm Layer by WebNN API
* Update convolution_layer.cpp
This is a temporary file for Conv2d layer implementation
* Integrate some general functions into op_webnn.cpp&hpp
* Update const_layer.cpp
* Update convolution_layer.cpp
Still have some bugs that should be fixed.
* Update conv2d layer and fc layer
still have some problems to be fixed.
* update constLayer, conv layer, fc layer
There are still some bugs to be fixed.
* Fix the build issue
* Update concat_layer.cpp
Still have some bugs to be fixed.
* Update conv2d layer, fully connected layer and const layer
* Update convolution_layer.cpp
* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)
* Delete bib19450.aux
* Add WebNN backend for OpenCV DNN Module
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Add WebNN head files into OpenCV 3rd partiy files
Create webnn.hpp
update cmake
Complete README and add OpenCVDetectWebNN.cmake file
add webnn.cpp
Modify webnn.cpp
Can successfully compile the codes for creating a MLContext
Update webnn.cpp
Update README.md
Update README.md
Update README.md
Update README.md
Update cmake files and
update README.md
Update OpenCVDetectWebNN.cmake and README.md
Update OpenCVDetectWebNN.cmake
Fix OpenCVDetectWebNN.cmake and update README.md
Add source webnn_cpp.cpp and libary libwebnn_proc.so
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
update dnn.cpp
update op_webnn
update op_webnn
Update op_webnn.hpp
update op_webnn.cpp & hpp
Update op_webnn.hpp
Update op_webnn
update the skeleton
Update op_webnn.cpp
Update op_webnn
Update op_webnn.cpp
Update op_webnn.cpp
Update op_webnn.hpp
update op_webnn
update op_webnn
Solved the problems of released variables.
Fixed the bugs in op_webnn.cpp
Implement op_webnn
Implement Relu by WebNN API
Update dnn.cpp for better test
Update elementwise_layers.cpp
Implement ReLU6
Update elementwise_layers.cpp
Implement SoftMax using WebNN API
Implement Reshape by WebNN API
Implement PermuteLayer by WebNN API
Implement PoolingLayer using WebNN API
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Implement poolingLayer by WebNN API and add more detailed logs
Update dnn.cpp
Update dnn.cpp
Remove redundant codes and add more logs for poolingLayer
Add more logs in the pooling layer implementation
Fix the indent issue and resolve the compiling issue
Fix the build problems
Fix the build issue
FIx the build issue
Update dnn.cpp
Update dnn.cpp
* Fix the build issue
* Implement BatchNorm Layer by WebNN API
* Update convolution_layer.cpp
This is a temporary file for Conv2d layer implementation
* Integrate some general functions into op_webnn.cpp&hpp
* Update const_layer.cpp
* Update convolution_layer.cpp
Still have some bugs that should be fixed.
* Update conv2d layer and fc layer
still have some problems to be fixed.
* update constLayer, conv layer, fc layer
There are still some bugs to be fixed.
* Update conv2d layer, fully connected layer and const layer
* Update convolution_layer.cpp
* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)
* Update dnn.cpp
* Fix Error in dnn.cpp
* Resolve duplication in conditions in convolution_layer.cpp
* Fixed the issues in the comments
* Fix building issue
* Update tutorial
* Fixed comments
* Address the comments
* Update CMakeLists.txt
* Offer more accurate perf test on native
* Add better perf tests for both native and web
* Modify per tests for better results
* Use more latest version of Electron
* Support latest WebNN Clamp op
* Add definition of HAVE_WEBNN macro
* Support group convolution
* Implement Scale_layer using WebNN
* Add Softmax option for native classification example
* Fix comments
* Fix comments
In case of very small negative h (e.g. -1e-40), with the current implementation,
you will go through the first condition and end up with h = 6.f, and will miss
the second condition.
issue #20617 addresses lack of warnings on
seamlessClone() function when src is None.
This commit adds source check using CV_Assert
therefore debugging would be easier.
Signed-off-by: nickjackolson <metedurlu@gmail.com>
Add a warning message using CV_LOG__WARNING().
This way api behaviour is preserved. Outputs are
the same but user gets an extra warning in case
fopen() fails to access image file for some reason.
This would help new users and also debugging
complex apps which use imread()
Signed-off-by: nickjackolson <metedurlu@gmail.com>
G-API: Removing G-API test code that is a reflection of ts module
* gapi: don't hijack testing infrastructure
* Removed initDataPath functionality (ts module exists)
* Removed false for ocv_extra data from findDataFile
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
QR code (encoding process)
* add qrcode encoder
* qr encoder fixes
* qr encoder: fix api and realization
* fixed qr encoder, added eci and kanji modes
* trigger CI
* qr encoder constructor fixes
Co-authored-by: APrigarina <ann73617@gmail.com>
[G-API] Fix bugs in GIEBackend
* Remove inputs/outputs map from IEUnit
* Add test
* Add NV12 test
* Reorganize setBlob function
* Check that backend don't overwrite blob precision
* Stop setting config to global IE::Core
* Replace mutable to const_cast
* Update modules/gapi/test/infer/gapi_infer_ie_test.cpp
* Update modules/gapi/test/infer/gapi_infer_ie_test.cpp
* Make blob parameter as const ref
* Cosmetic fixes
* Fix failed test on inferROI
* Removed double ref for ii
* Disable tests
* Skip tests if device not available
* Use Sync prim under shared_ptr to avoid issue on MAC
* Apply WA for IE::Core
* Apply WA for MAC build
* Try to apply another WA
* Not release IE::Core for apple
* Put comment
* Support PreprocInfo for
* InferROI
* InferList
* InferList2
* Remove empty line
* Fix alignment
Co-authored-by: Maxim Pashchenkov <maxim.pashchenkov@intel.com>
Fix the following build failure with gcc 4.8:
In file included from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg_impl.hpp💯0,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg.cpp:50:
/home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg_hw.hpp: In constructor 'HWAccelIterator::HWAccelIterator(cv::VideoAccelerationType, bool, AVDictionary*)':
/home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg_hw.hpp:939:23: error: use of deleted function 'std::basic_istringstream<char>& std::basic_istringstream<char>::operator=(const std::basic_istringstream<char>&)'
s_stream_ = std::istringstream(accel_list);
^
In file included from /home/buildroot/autobuild/instance-3/output-1/host/opt/ext-toolchain/arm-none-linux-gnueabi/include/c++/4.8.3/complex:45:0,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/core/include/opencv2/core/cvstd.inl.hpp:47,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/core/include/opencv2/core.hpp:3306,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/include/opencv2/videoio.hpp:46,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/precomp.hpp:57,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg.cpp:42:
/home/buildroot/autobuild/instance-3/output-1/host/opt/ext-toolchain/arm-none-linux-gnueabi/include/c++/4.8.3/sstream:272:11: note: 'std::basic_istringstream<char>& std::basic_istringstream<char>::operator=(const std::basic_istringstream<char>&)' is implicitly deleted because the default definition would be ill-formed:
class basic_istringstream : public basic_istream<_CharT, _Traits>
^
/home/buildroot/autobuild/instance-3/output-1/host/opt/ext-toolchain/arm-none-linux-gnueabi/include/c++/4.8.3/sstream:272:11: error: use of deleted function 'std::basic_istream<char>& std::basic_istream<char>::operator=(const std::basic_istream<char>&)'
Fixes:
- http://autobuild.buildroot.org/results/60f8846b435dafda0ced412d59ffe15bdff0810d
Signed-off-by: Fabrice Fontaine <fontaine.fabrice@gmail.com>
* dnn(ocl4dnn): fix LRN layer accuracy problems
- FP16 intermediate computation is not accurate and may provide NaN values
* dnn(test): update tolerance for FP16
1. Code uses PPC_FEATURE_HAS_VSX, but it's not checked similarly to
PPC_FEATURE2_ARCH_3_00 and PPC_FEATURE2_ARCH_3_00 for availability. FreeBSD has
those macros in machine/cpu.h, but I went with the way chosen for
PPC_FEATURE2_ARCH_3_00 and PPC_FEATURE2_ARCH_3_00. Other than that, FreeBSD also
has sys/auxv.h and that's where elf_aux_info() is defined.
2. getauxval() is actually Linux-only, but code checked for __unix__. It won't
work on all UNIX, so change it back to __linux__. Add another code variant
strictly for FreeBSD.
3. Update comment. This commit adds code for FreeBSD, but recently there
appeared support for powerpc64 in OpenBSD.
G-API: oneVPL - Performance: Add async decode pipeline & add cached pool
* Add async decode pipeline & intro cached pool
* Fix performacne test with checking OPENCV_EXTRA
* Add sip perf test with no VPL
* Fix misprint
* Remove empty line..
* Apply some comments
* Apply some comments
* Make perf test fail if no OPENCV_TEST_DATA_PATH declared
fix bug: wrong output dimension when "keep_dims" is false in pooling layer.
* fix bug in max layer
* code align
* delete permute layer and add test case
* add name assert
* check other cases
* remove c++11 features
* style:add "const" remove assert
* style:sanitize file names
Fix: #21021
NDK API AMediaCodec_getOutputBuffer() returns MediaCodecBuffer::data()
which is actually ABuffer::data(). The returned buffer address is already
adjusted by offset.
More info:
ABuffer::base() returns base address without offset
ABuffer::data() returns base + offset
Change-Id: I2936339ce4fa9acf657a5a7d92adc1275d7b28a1
Add 3D point cloud sampling functions to branch next
* Add several 3D point cloud sampling functions: Random, VoxelGrid, FarthestPoint.
* Made some code detail changes and exposed the random number generator parameters at the interface.
* Add simple tests for sampling.
* Modify interface output parameters.
* Modify interface return value.
* The sampling test is modified for the new changes of function interface.
* Improved test of VoxelGridFilterSampling
* Improved test of VoxelGridFilterSampling and FPS.
* Add test for the dist_lower_limit arguments of FPS function.
* Optimization function _getMatFromInputArray.
* Optimize the code style and some details according to the suggestions.
* Clear prefix cv: in the source code.
* Change the initialization of Mat in the sampling test.
* 1. Unified code style
2. Optimize randomSampling method
* 1. Optimize code comments.
2. Remove unused local variables.
* Rebuild the structure of the test, make the test case more reliable, and change the code style.
* Update test_sampling.cpp
Fix a warning.
G-API: Disable Windows warnings with 4996 code
* Windows warnings 4503 and 4996 are disabled with dnn style
* Applying comments to review
* Reproducing
* Added check MSVC_VERSION for both warnings
* bmp specified BI_BITFIELDS should take care RGBA bit mask
* change the name
* support xrgb bmp file
* support xrgb bmp file(add test case)
* update testing code
Add DNN-based face detection and face recognition into modules/objdetect
* Add DNN-based face detector impl and interface
* Add a sample for DNN-based face detector
* add recog
* add notes
* move samples from samples/cpp to samples/dnn
* add documentation for dnn_face
* add set/get methods for input size, nms & score threshold and topk
* remove the DNN prefix from the face detector and face recognizer
* remove default values in the constructor of impl
* regenerate priors after setting input size
* two filenames for readnet
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face_recognize.cpp
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update face.hpp
* Update dnn_face.markdown
* add regression test for face detection
* remove underscore prefix; fix warnings
* add reference & acknowledgement for face detection
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update ts.hpp
* Update test_face.cpp
* Update face_match.cpp
* fix a compile error for python interface; add python examples for face detection and recognition
* Major changes for Vadim's comments:
* Replace class name FaceDetector with FaceDetectorYN in related failes
* Declare local mat before loop in modules/objdetect/src/face_detect.cpp
* Make input image and save flag optional in samples/dnn/face_detect(.cpp, .py)
* Add camera support in samples/dnn/face_detect(.cpp, .py)
* correct file paths for regression test
* fix convertion warnings; remove extra spaces
* update face_recog
* Update dnn_face.markdown
* Fix warnings and errors for the default CI reports:
* Remove trailing white spaces and extra new lines.
* Fix convertion warnings for windows and iOS.
* Add braces around initialization of subobjects.
* Fix warnings and errors for the default CI systems:
* Add prefix 'FR_' for each value name in enum DisType to solve the
redefinition error for iOS compilation; Modify other code accordingly
* Add bookmark '#tutorial_dnn_face' to solve warnings from doxygen
* Correct documentations to solve warnings from doxygen
* update FaceRecognizerSF
* Fix the error for CI to find ONNX models correctly
* add suffix f to float assignments
* add backend & target options for initializing face recognizer
* add checkeq for checking input size and preset size
* update test and threshold
* changes in response to alalek's comments:
* fix typos in samples/dnn/face_match.py
* import numpy before importing cv2
* add documentation to .setInputSize()
* remove extra include in face_recognize.cpp
* fix some bugs
* Update dnn_face.markdown
* update thresholds; remove useless code
* add time suffix to YuNet filename in test
* objdetect: update test code
* Fix gst error handling
* Use the return value instead of the error, which gives no guarantee of being NULL in case of error
* Test err pointer before accessing it
* Remove unreachable code
* videoio(gstreamer): restore check in writer code
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Fix ORB integer overflow
* set size_t step to fix integer overflow in ptr0 offset
* added issue_537 test
* minor fix tags, points
* added size_t_step and offset to remove mixed unsigned and signed operations
* features2d: update ORB checks
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
* dnn: fix unaligned memory access crash on armv7
The getTensorContent function would return a Mat pointing to some
member of a Protobuf-encoded message. Protobuf does not make any
alignment guarantees, which results in a crash on armv7 when loading
models while bit 2 is set in /proc/cpu/alignment (or the relevant
kernel feature for alignment compatibility is disabled). Any read
attempt from the previously unaligned data member would send SIGBUS.
As workaround, this commit makes an aligned copy via existing clone
functionality in getTensorContent. The unsafe copy=false option is
removed. Unfortunately, a rather crude hack in PReLUSubgraph in fact
writes(!) to the Protobuf message. We limit ourselves to fixing the
alignment issues in this commit, and add getTensorContentRefUnaligned
to cover the write case with a safe memcpy. A FIXME marks the issue.
* dnn: reduce amount of .clone() calls
* dnn: update FIXME comment
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Make the implementation of optimization in DNN adjustable to different vector sizes with RVV intrinsics.
* Update fastGEMM for multi VLEN.
* Update fastGEMM1T for multi VLEN.
* Update fastDepthwiseConv for multi VLEN.
* Update fastConv for multi VLEN.
* Replace malloc with cv::AutoBuffer.
dnn : int8 quantized layers support in onnx importer
* added quantized layers support in onnx importer
* added more cases in eltwise node, some more checks
* added tests for quantized nodes
* relax thresholds for failed tests, address review comments
* refactoring based on review comments
* added support for unsupported cases and pre-quantized resnet50 test
* relax thresholds due to int8 resize layer
* Prefix global javascript functions with sub-namespaces
* js: handle 'namespace_prefix_override', update filtering
- avoid functions override with same name but different namespace
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Add ExpandDims layer of tf_importer.cpp
* Add ExpandDims to tf_importer.
* add -1 expand test case.
* Support different dimensions of input.
* Compatible with 5-dimensional NDHWC data
* Code align
* support 3-dim input.
* 3-dim bug fixed.
* fixing error of code format.
