- 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.
[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
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.
* [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 building with OpenEXR 3.x
* Support OpenEXR 3.0
Try to find OpenEXR 3.0 using the upstream cmake config, and fallback to the previous algorithm if not found
* Add explicit ImfFrameBuffer.h include
This was transitively included with OpenEXR 2.x, but that's no longer the case with OpenEXR 3.x
* Workaround for IPP linking problem
* Apply -Bsymbolic to all cases when IPP is on
* Tried to hide symbols on MacOS
* Tried on --exclude-libs option
* Fixed macos and win warnings
* Fixed win build
* cmake(IPP): move --exclude-libs,libippcore.a to IPP CMake file
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Android NDK camera support
* Add native camera video backend for Android
* In the event of a "No buffer available error" wait for the appropriate callback and retry
* Fix stale context when creating a new AndroidCameraCapture
* Add property handling
* fix find zlib.so instead of zlib.a when NDK >= 19
On Android platform, `libopencv_imgcodecs.a` is built, expected to
depend on `libz.so`. However, since Android NDK r19, NDK's `libz.a`
is found instead of `libz.so`, leading to link error
(not found libz.a) on machines without same NDK version & direcotry.
Since Android NDK-r19, toolchain pieces are installed to
`$NDK/toolchains/llvm/prebuilt/<host-tag>/...`, including `libz.so`.
Also installed to old paths (`<NDK>/platforms` and `<NDK>/sysroot`)
in NDK r19, r20, r21, but since NDK 22, old paths are removed.
- https://github.com/android/ndk/wiki/Changelog-r19
- https://github.com/android/ndk/wiki/Changelog-r22
With this commit, `libz.so` can be correctly found in NDK<19 and NDK>=19.
`ZLIB_LIBRARIES` is also simplified as `z`, by appending match (regex)
patterns for new toolchain installation directory's libz.so's paths.
* simplify libz.so match pattern for abbreviation
Support XCFramework builds, Catalyst
* Early work on xcframework support
* Improve legibility
* Somehow this works
* Specify ABIs in a place where they won't get erased
If you pass in the C/CXX flags from the Python script, they won't be respected. By doing it in the actual toolchain, the options are respected and Catalyst successfully links.
* Clean up and push updates
* Actually use Catalyst ABI
Needed to specify EXE linker flags to get compiler tests to link to the Catalyst ABIs.
* Clean up
* Revert changes to common toolchain that don't matter
* Try some things
* Support Catalyst build in OSX scripts
* Remove unnecessary iOS reference to AssetsLibrary framework
* Getting closer
* Try some things, port to Python 3
* Some additional fixes
* Point Cmake Plist gen to osx directory for Catalyst targets
* Remove dynamic lib references for Catalyst, copy iOS instead of macos
* Add flag for building only specified archs, remove iOS catalyst refs
* Add build-xcframework.sh
* Update build-xcframework.sh
* Add presumptive Apple Silicon support
* Add arm64 iphonesimulator target
* Fix xcframework build
* Working on arm64 iOS simulator
* Support 2.7 (replace run with check_output)
* Correctly check output of uname_m against arch
* Clean up
* Use lipo for intermediate frameworks, add python script
Remove unneeded __init__.py
* Simplify python xcframework build script
* Add --only-64-bit flag
* Add --framework-name flag
* Document
* Commit to f-strings, improve console output
* Add i386 to iphonesimulator platform in xcframework generator
* Enable objc for non-Catalyst frameworks
* Fix xcframework builder for paths with spaces
* Use arch when specifying Catalyst build platform in build command
* Fix incorrect settings for framework_name argparse configuration
* Prefer underscores instead of hyphens in new flags
* Move Catalyst flags to where they'll actually get used
* Use --without=objc on Catalyst target for now
* Remove get_or_create_folder and simplify logic
* Remove unused import
* Tighten up help text
* Document
* Move common functions into cv_build_utils
* Improve documentation
* Remove old build script
* Add readme
* Check for required CMake and Xcode versions
* Clean up TODOs and re-enable `copy_samples()`
Remove TODO
Fixup
* Add missing print_function import
* Clarify CMake dependency documentation
* Revert python2 change in gen_objc
* Remove unnecessary builtins imports
* Remove trailing whitespace
* Avoid building Catalyst unless specified
This makes Catalyst support a non-breaking change, though defaults should be specified when a breaking change is possible.
* Prevent lipoing for the same archs on different platforms before build
* Rename build-xcframework.py to build_xcframework.py
* Check for duplicate archs more carefully
* Prevent sample copying error when directory already exists
This can happen when building multiple architectures for the same platform.
* Simplify code for checking for default archs
* Improve build_xcframework.py header text
* Correctly resolve Python script paths
* Parse only known args in ios/osx build_framework.py
* Pass through uncaptured args in build_xcframework to osx/ios build
* Fix typo
* Fix typo
* Fix unparameterized build path for intermediate frameworks
* Fix dyanmic info.plist path for catalyst
* Fix utf-8 Python 3 issue
* Add dynamic flag to osx script
* Rename platform to platforms, remove armv7s and i386
* Fix creation of dynamic framework on maccatalyst and macos
* Update platforms/apple/readme.md
* Add `macos_archs` flag and deprecate `archs` flag
* Allow specification of archs when generating xcframework from terminal
* Change xcframework platform argument names to match archs flag names
* Remove platforms as a concept and shadow archs flags from ios/osx .py
* Improve documentation
* Fix building of objc module on Catalyst, excluding Swift
* Clean up build folder logic a bit
* Fix framework_name flag
* Drop passthrough_args, use unknown_args instead
* minor: coding style changes
Co-authored-by: Chris Ballinger <cballinger@rightpoint.com>
* G-API: Introduce ONNX backend for Inference
- Basic operations are implemented (Infer, -ROI, -List, -List2);
- Implemented automatic preprocessing for ONNX models;
- Test suite is extended with `OPENCV_GAPI_ONNX_MODEL_PATH` env for test data
(test data is an ONNX Model Zoo repo snapshot);
- Fixed kernel lookup logic in core G-API:
- Lookup NN kernels not in the default package, but in the associated
backend's aux package. Now two NN backends can work in the same graph.
- Added Infer SSD demo and a combined ONNX/IE demo;
* G-API/ONNX: Fix some of CMake issues
Co-authored-by: Pashchenkov, Maxim <maxim.pashchenkov@intel.com>
changed OpenCV license from BSD to Apache 2 license
* as discussed and announced earlier, changed OpenCV license from BSD to Apache 2. Many files still contain old-style copyrights though
* changed wording a bit; preserve the original OpenCV BSD license
- 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
