* Error in the documentation for cv::getRectSubPix. #9788
The function name is corrected to GetRectSubPix since, it uses the notation
of src, dst and center. Also added the number of channel assertion criteria.
* Error in the documentation for cv::getRectSubPix. #9788
Replace dst with patch in the formula, reverted function name to
getRectSubPix, removed BorderTypes comment line due to no explicit call
to the function found.
* Error in the documentation for cv::getRectSubPix. #9788
Replace dst with patch in the formula, reverted function name to
getRectSubPix, removed BorderTypes comment line due to no explicit call
to the function found.
- 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
getViewerPose() doesn't modify an object of the class so it can be
made const. It also makes this method consistent with other getters
in the class as they are defined as const.
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
These two typdefs are not compiled when BUILD_opencv_dnn is set to
false, however there are other modules that uses these typedef so
it may cause build errors. Moving typedef to the python module
ensures they are always defined.
The original template based mat ptr for indexing is not implemented,
add the similar implementation as uchar type, but cast to
user-defined type from the uchar pointer.
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.
The entire AssetsLibrary framework is deprecated since iOS 8.0. The code
used in the camera example code can use UIKit to save videos to the
camera instead, which allows to avoid linking with PhotoKit instead to
prevent increasing the iOS deployment target.
Adds fitEllipseDirect to imgproc: The Direct least square (Direct) method by Fitzgibbon1999.
New Tests are included for the methods.
fitEllipseAMS Tests
fitEllipseDirect Tests
Comparative examples are added to fitEllipse.cpp in Samples.
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>
imgproc: use universal intrinsic as much as possible (#9714)
* use universal intrinsic as much as possible
* make SSE3 part as common as possible with universal intrinsic implementation
* put the reducing part out of the main loop
* follow the comment
* fix the typo
* use v_reduce_sum4
* follow the comment again
* remove all CV_SSE3 part from smooth.cpp
The non-maximum suppression in the Hough accumulator incorrectly ignores maxima that extend over more than one cell, i.e. two neighboring cells both have the same accumulator value. This maximum is dropped completely instead of picking at least one of the entries. This frequently results in obvious circles being missed.
The behavior is now changed to be the same as for hough_lines.
See also https://github.com/opencv/opencv/issues/4440
GSoC 2017: Improve and Extend the JavaScript Bindings for OpenCV (#9466)
* Initial support for build with emscripten
mkdir build_js
cd build_js
cmake -D CMAKE_TOOLCHAIN_FILE=/path/to/emsdk/emsdk-portable/emscripten/master/cmake/Modules/Platform/Emscripten.cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local ..
* Add js module
The output is build/bin/opencv_js.js
* Fix opencv2/calib3d.hpp not found issue
* Add module name
Usage:
var cv = cv();
* Add total memory as 128MB and allow growth
* Add compilation flags for emscripten
* Use EMSCRIPTEN build target
* Disable js module for non emscripten build
* Bind the preload file path to root
Usage:
face_cascade.load('haarcascade_frontalface_default.xml');
* add test folder
* fix test files
* Copy js module test to bin
* Support to run tests on Node.js
Fix tests to import cv Module when runtime is node.
Add tests.js to use qunit to auto run tests.
Modify umd wrapper to support Module is not defined.
Usage:
node tests.js
* Support UMD and file system
Wrap the opencv_js.js to opencv.js by UMD wrapper
Use emscripten file system API to load files instead of generating data file or
embedding them. It supports both browser and node.js usages.
* Fix incorrect module name in tests
* Add package.json to add dependence of qunit
* Add js_tutorials folder and a intro page of opencv.js
Enable BUILD_DOCS in CMakeLists.txt.
Add new folder of js_tutorials in folder opencv/doc.
Imitate the tutorials of OpenCV-Python to create a intro page of opencv.js and a setup guide
* Import and use binding gen from opencvjs project
* Modify the embindgen.py to pass the build and test
* Add classes and functions white list
* Consolidate hdr_parser.py (#31)
Use hdr_parser.py of python module
Add js flag to support js binding generator.
* Use emscripten::vecFromJSArray for input vector param
Fix part of #23
* Fix test cases after #34Fix#39
* Expose groupRectangles and CascadeClassifier.empty
* Add js highgui tutorials
add tutorials of imread&imshow and createTrackbar in doc/js_tutorials/js_gui folder
add interactive tutorial webpage for imread&imshow and createTrackbar in doc/js_tutorials/js_interactive_tutorials folder, and some images needed.
change doc/CMakeLists.txt to copy the interactive tutorial webpage and opencv.js to the tutorials' destination folder
* rm useless annotation in doc/CMakeLists.txt
* fix some nonstandard indentation and space
* add check if canvas is valid
* Expose BackgroundSubtractorMOG2
Fix#43
* Fix build of js doc
Limit copy_js_interactive_tutorials for doxygen build
Add dep to opencv.js
Fix#53
* Implement cv.imread & cv.imshow and insert interactive pages in tutorials (#55)
* add helper.js
* delete ALL in add target copy_js_interactive_tutorials to avoid dependence error
* Insert interactive pages in tutorials
insert the old interactive pages in markdown by using \htmlonly and \endhtmlonly command.
delete the useless interactive page
rename js_interactive_tutorials to js_assets to put some images needed in
* fix the depends of the target doxygen
add opencv.js to depends and delete the useless target of copy_js_assets
* change filename helper.js to helpers.js
* disable button or trankbar before opencv.js is ready
* Expose CV_64F
Fix#65
* improve cv.imshow to display different types as native imshow
* add utils.js to reuse functions and update tutorials
* Make doxygen depend on bin/opencv.js
* Fix memory issue of matFromArray
Fix#37
* Merge pull request from ganwenyao/tutorial_18
* Add notes for ganwenyao/tutorial_18
* Modifying for ganwenyao/tutorial_18
* Change Mat constructor with data to 5 parameters
* Mat supports constructor with Scalar
Fix#60
* update cv.imread cause the memory issue of matFromArray has been fixed
* fix canvas name and default input image
* Expose cv::Moments
Fix#85
* Add -Wno-missing-prototypes for emscripten build
* fix canvas name
* add tutorial of video input and output
* Expose enums as emscripten consts
Fix#72
* update the tutorial to use Mat constructor with Scalar and change lena.jpg
* Exclude cv::Mat for vecFromJSArray
Fix#82
* Add unit tests for cv.moments
* Fix the unit tests.
* add checkbox and stop button
* add adapter.js to make sure compatibility fo video tutorials
* Support default parameters with function overloading
* modify enums to constants
* Use https URL for MathJax.js
Fix#109
* Comment out the debug print in embindgen.py
* Expose RotatedRect
Fix#96
* replace enum with constants and improve onload function
* delete some useless paras cause #105 fixed this
* Modify const name
* Modify Contour Properties
* tutorials for imgprc2 and objdec
* Expose more functions for img proc tutorials
Fix#76
* Expose polylines for video analysis tutorial
Fix#121
* Expose constants for default parameters of img proc tutorials
Fix#122
* Fix wrong parameter types of Mat.copyTo
Fix#87
* Support default parameters of mat.convertTo
Fix#123
* Support default parameters for external constructors
Fix#131
* Revert "Expose polylines for video analysis tutorial"
This reverts commit 3ce7615652e510d30e3c0014706ac38c98883189.
Fix#121
* Support cv.minMaxLoc
Fix#127
* Expose cv.minEnclosingCircle
Fix#126
* Add video analysis tutorials
add three video tutorials, Meanshift and Camshift, Optical Flow Background Subtraction
add cup.mp4 and box.mp4 for demo in tutorials
* improve image processing tutorials
* repalce console.warn with throw to throw exception
* add try-catch to throw exception in code demo
* Change mat.size() return value to JS Array object
Fix#140
* add a note about different channels order between canvas and native opencv
* add a note about how to capture video from video files
* Binding cv.Scalar to JS array
Fix#147
* Add JS cv.Scalar object into helpers.js
* Update Install OpenCV-JavaScript tutorial page
Fix#44
* Update the OpenCV-JavaScript introduction page
Fix#44
* add cv.VideoCapture and read() function
* set the size of the hidden canvas same as the video
* Add Using OpenCV-JavaScript tutorial page
Fix#44
* fix some bad code style
* Update tutorials after 8/2 sync meeting
Changes include:
- Use OpenCV.js name instead of OpenCV-JavaScript
- Put using OpenCV.js ahead of build OpenCV.js
- Refine usage and introduction page
- Muted the video in tutorials
* Fix a typo in introduction page
* use cv.VideoCapture and its read() function to read video
* replace OpenCV-JavaScript with OpenCV.js
* Use onload of async script in js_usage tutorial
* add more info about mat.data
* Change Size to value_object
* Integrate Moh and Sajjad's editing into introduction page
* Change Point to value_object
* Change Rect to value_object with helper object
* Add helper objects for Point and Size
* Change RotatedRect to value_object with helpers
* Change MinMaxLoc and Circle to value_object
* Change TermCriteria to value_object
* Fix core_bindings.cpp for MinMaxLoc and Circle
* Remove unused types
* Change meanShift and CamShift to return Rect
* Change methods of RotatedRect to static
* Change mat.data from methods to property
Fix#75 and #77
* support img id and element in cv.imread
* Change mat.size to property and add mat.step
Fix#163
* Add matFromArray and matFromImageData as JS helpers
Fix#79, #78
* Lower camel case for Mat element getters
Fix#81
* Mat.getRoiRect and tests
Fix#86
* Support type for Mat.ptr
Fix#83
* Name changing of Mat element getters
'getUcharAt` -> 'ucharAt'
* fix code style and args names
* Fix helpers.js due to cv.Mat API update
* Fix opencv.js usage tutorial
* Fix a typo of js_setup
* Change Moments to value_object
* Add Range as value_object
Fix#171
* Support Mat.diag and Mat.isContinous
Fix#84 and #89
* Support Mat.setTo
Fix#88
* Apply edits to js_intro
* Apply edits to js_usage
* Apply edits to js_setup
* update tutorials to apply data type change
* Modify tutorials
* add core tutorials
* delete MatVector elements and delete useless set operation
* add tutorials_objdec_camera
* Add instructions for WebAssembly
* apply tech writer's feedbacks into tutorials
* Organize white list by modules
* Change size to method and bind to MatExpr.size()
Fix#177
* improve tutorials
* Modify core tutorials
* add params list and explanations for OpenCV.js functions
* remove face_profile from Face Detection in Video Capture
* Add demos link
* Change Gui to GUI
* Update js_intro based on Moh and Sajjad's edits
* Fixup for 3.3.0 rebase
* Update js_intro per Moh's suggestion
* Update contributors list per Moh's idea
* add adapter.js in video_display tutorial
* Change Mat.getRoiRect to Mat.roi
Fix#194
* Remove unnecessary files for test
Fix#192
* Licenses updated to UC BSD 3-Clause
* Apply OpenCV coding style for C++ files
* Add OpenCV license for python and js files
* Fix coding style issue in helpers.js
* Remove unused test_commons.js
* Fix coding style of test_imgproc.js
* Fix coding style of test_mat.js
* Fix space before semicolon
* Fix coding style of test_objdetect.js
* Fix coding style of tests.js
* Fix coding style of test_utils.js
* Fix coding style of test_video.js
* Fix failures of node.js tests
* Add eslint rule config and fix eslint errors
* Add eslint config for js/src and fix eslint errors
* Clean up the opencv.js dependencies
Fix#186
* Fix build issue for python generator
* Fix doxygen buildbot failure
* delete trailing whitespace, blank line at EOF and replace tab with space
* Fix tutorial_js_root reference issue for non opencv.js build
* replace the file with small size
* Initial commit of build_js.py
* Move the js build configurations to build script
* Add wasm build support
* Update OpenCV.js build tutorial by using script
* Fix global var issue in tests
* Add a README.md for build_js.py
* Copy the haar cascade files from data dir for tutorials
* Not use memory init file
* Disable debug print for modules/js/CMakeLists.txt
* Check files when build done
* Fix image name in js_gradients tutorial
* Fix image load issue in js_trackbar tutorial
* Find the opencv source directory via relative path by default
* Make the cmake args based on build_doc option
* Fix a typo in js_setup.markdown
* Fix make failure issue on config generated by build_js.py
* Eliminate js branch of hdr_parser.py
* Extract examples from js_basic_ops tutorial
* Fix coding style of utils.js
* Improve examples error handling
Handle:
1. opencv.js loading errors
2. script errors (Error)
3. cv::Exception
Fix#217
* Add enable_exception option into build_js.py
* Support print exception for exception catching disabled build
* Extract example from js_usage tutorial
* Avoid copying .eslintrc.json when building doc
Fix#223
* Revert to use onload as opencv.js ready event
* Use 4 spaces indention for js examples
* embed html in tutorials with iframe tag
* Revert to use onload as opencv.js ready event
* Extract examples from js_video_display tutorial
* Implement Utils object
* modify core imgprc and face_detection tutorials
* Fix examples of js_gui tutorials
* Fix coding style of utils.js
* Modify tutorials
* Extract example from js_face_detection_camera tutorial
* Disable new-cap check in eslint
* Extract examples from js_meanshift tutorial
* Extract examples from video tutorials
* Remove new-cap declaration and update grammer in comments
* Change textarea width to 100 to align with eslint config
* Fix printError issue when opencv.js loading fails
* Remove BUILD_opencv_js dependency for doc build
Fix#213
* Expose cv::getBuildInformation
* Dump opencv build info when opencv.js loaded for live examples
* Make the button to stand out in js live examples
Fix#235
* Style for disabled button
* Add js_imgproc_camera.html example
* Fix coding style of imgproc_camera example
* Add js_imgproc_camera tutorial
* Remove link to opencv.js demos
* doc: copy opencv.js on build, use absolute paths for assets
* doc: reuse existed file box.mp4
Added gradiantSize param into goodFeaturesToTrack API (#9618)
* Added gradiantSize param into goodFeaturesToTrack API
Removed hardcode value 3 in goodFeaturesToTrack API, and
added new param 'gradinatSize' in this API so that user can
pass any gradiant size as 3, 5 or 7.
Signed-off-by: Vipin Anand <anand.vipin@gmail.com>
Signed-off-by: Nilaykumar Patel<nilay.nilpat@gmail.com>
Signed-off-by: Prashanth Voora <prashanthx85@gmail.com>
* fixed compilation error for java test
Signed-off-by: Vipin Anand <anand.vipin@gmail.com>
* Modifying code for previous binary compatibility and fixing other warnings
fixed ABI break issue
resolved merged conflict
compilation error fix
Signed-off-by: Vipin Anand <anand.vipin@gmail.com>
Signed-off-by: Patel, Nilaykumar K <nilay.nilpat@gmail.com>
- use GTest tuple definitions instead of std::tr1
- use "const static" for cv::Size contants to reduce generated binary code
- PERF_TEST_P() violates TEST_P() original semantic. Added PERF_TEST_P_() macro
* lab_tetra squashed
* initial version is almost written
* unfinished work
* compilation fixed, to be debugged
* Lab test removed
* more fixes
* Luv2RGBinteger: channels order fixed
* Lab structs removed
* good trilinear interpolation added
* several fixes
* removed Luv2RGB interpolations, XYZ tables; 8-cell LUT added
* no_interpolate made 8-cell
* interpolations rewritten to 8-cell, minor fixes
* packed interpolation added for RGB2Luv
* tetra implemented
* removing unnecessary code
* LUT building merged
* changes ported to color.cpp
* minor fixes; try to suppress warnings
* fixed v range of Luv
* fixed incorrect src channel number
* minor fixes
* preliminary version of Luv2RGBinteger is done
* Luv2RGB_b is in progress
* XYZ color constants converted to softfloat
* Luv test: precision fixed
* Luv bit-exactness test added
* warnings fixed
* compilation fixed, error message fixed
* Luv check is limited to [0-2,0-2,0-2] by XYZ
* L->Y generation moved to LUT
* LUTs added for up and vp of Luv2RGB_b
* still works
* fixed-point is done, works at maxerr 2
* vectorized code is done, 2x slower than original
* perf improved by 10%
* extra comments removed
* code moved to color.cpp
* test_lab.cpp updated
* minor refactoring
* test added for Luv2RGB
* OCL Luv2RGB_b: XYZ are limited to [0, 2]; docs updated
* Luv2RGB_b rewritten to universal intrinsics
* test_lab.cpp moved to luv_tetra branch
* Using environment variable to store options parsed by av_dict_parse_string(ENV{OPENCV_FFMPEG_CAPTURE_OPTIONS}, ";", "|")
* Adding missing mandatory flags parameter
* Guarding against missing function via LIBAVUTIL version
* Code review fixes
Copy/paste error due to coder mistake reverted
Proper version checking for LIBAVUTIL_BUILD
* Imgproc_ColorLab_Full.accuracy test fixed
* Lab and Luv tests: rewritten, constants explained
* CV_ColorCvtBaseTest: added methods for 8u implementations
* Lab2RGB_b: bit-exactness enabled for all modes; non-vectorized code fixed to comply with vectorized
* srgb support added
* XYZ constants made softdouble
* bit-exact tests written for Lab
* ColorLab_full test fixed
* reverted: no 8u convertors for CV_ColorCvtBaseTest
* added checksum-based test for Lab bit-exactness
* extra declarations removed
* Lab test fix: stop at first mismatch
* test info output improved
* error message fixed
* lab_tetra squashed
* initial version is almost written
* unfinished work
* compilation fixed, to be debugged
* Lab test removed
* more fixes
* Luv2RGBinteger: channels order fixed
* Lab structs removed
* good trilinear interpolation added
* several fixes
* removed Luv2RGB interpolations, XYZ tables; 8-cell LUT added
* no_interpolate made 8-cell
* interpolations rewritten to 8-cell, minor fixes
* packed interpolation added for RGB2Luv
* tetra implemented
* removing unnecessary code
* LUT building merged
* changes ported to color.cpp
* minor fixes; try to suppress warnings
* fixed v range of Luv
* fixed incorrect src channel number
* minor fixes
* preliminary version of Luv2RGBinteger is done
* Luv2RGB_b is in progress
* XYZ color constants converted to softfloat
* Luv test: precision fixed
* Luv bit-exactness test added
* warnings fixed
* compilation fixed, error message fixed
* test_lab.cpp removed
Added forkfour Latex command to math js support.
Split cv::norm documentation between the cv::norm and its overload, to make things clearer
Corrected some typos and cleaned up grammar.
Result is clearer documentation for the norms.
Work pending...
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.
CUDA implementation wants to convert std::vector<KeyPoint> <-> GpuMat.
There is no direct mapping from KeyPoint (mix of int/float fields)
into cv::Mat element type, so this conversion must be avoided.
Legacy mode is turned back for CUDA builds.
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;
[GSOC] Enable OCL for AKAZE (#9330)
* revert e0489cb - reenable OCL for AKAZE
* deal with conversion internally in AKAZE
* pass InputArray directly to AKAZE to allow distiguishing input Mat/UMat. deal with conversion there
* ensure that keypoints orientations are always computed. prevents misuse of internal AKAZE class.
* covert internal AKAZE functions to use InputArray/OutputArray
* make internal functions private in AKAZE
* split OCL and CPU paths in AKAZE
* create 2 separate pyramids, 1 for OCL and 1 for CPU
* template functions that use temporaries to always store them as correct type (UMat/Mat)
* remove variable used only in OCL path
causes unused variable warning
* update AKAZE documentation
* run ocl version only when ocl is enabled
* add tests for OCL path in AKAZE
* relax condition for keypoints angle
[GSOC] Speeding-up AKAZE, part #3 (#9249)
* use finding of scale extremas from fast_akaze
* incorporade finding of extremas and subpixel refinement from Hideaki Suzuki's fast_akaze (https://github.com/h2suzuki/fast_akaze)
* use opencv parallel framework
* do not search for keypoints near the border, where we can't compute sensible descriptors (bugs fixed in ffd9ad99f4, 2c5389594b), but the descriptors were not 100% correct. this is a better solution
this version produces less keypoints with the same treshold. It is more effective in pruning similar keypoints (which do not bring any new information), so we have less keypoints, but with high quality. Accuracy is about the same.
* incorporate bugfix from upstream
* fix bug in subpixel refinement
* see commit db3dc22981e856ca8111f2f7fe57d9c2e0286efc in Pablo's repo
* rework finding of scale space extremas
* store just keypoints positions
* store positions in uchar mask for effective spatial search for neighbours
* construct keypoints structs at the very end
* lower inlier threshold in test
* win32 has lower accuracy
[GSOC] Speeding-up AKAZE, part #2 (#8951)
* feature2d: instrument more functions used in AKAZE
* rework Compute_Determinant_Hessian_Response
* this takes 84% of time of Feature_Detection
* run everything in parallel
* compute Scharr kernels just once
* compute sigma more efficiently
* allocate all matrices in evolution without zeroing
* features2d: add one bigger image to tests
* now test have images: 600x768, 900x600 and 1385x700 to cover different resolutions
* explicitly zero Lx and Ly
* add Lflow and Lstep to evolution as in original AKAZE code
* reworked computing keypoints orientation
integrated faster function from https://github.com/h2suzuki/fast_akaze
* use standard fastAtan2 instead of getAngle
* compute keypoints orientation in parallel
* fix visual studio warnings
* replace some wrapped functions with direct calls to OpenCV functions
* improved readability for people familiar with opencv
* do not same image twice in base level
* rework diffusity stencil
* use one pass stencil for diffusity from https://github.com/h2suzuki/fast_akaze
* improve locality in Create_Scale_Space
* always compute determinat od hessian and spacial derivatives
* this needs to be computed always as we need derivatives while computing descriptors
* fixed tests of AKAZE with KAZE descriptors which have been affected by this
Currently it computes all first and second order derivatives together and the determiant of the hessian. For descriptors it would be enough to compute just first order derivates, but it is not probably worth it optimize for scenario where descriptors and keypoints are computed separately, since it is already very inefficient. When computing keypoint and descriptors together it is faster to do it the current way (preserves locality).
* parallelize non linear diffusion computation
* do multiplication right in the nlp diffusity kernel
* rework kfactor computation
* get rid of sharing buffers when creating scale space pyramid, the performace impact is neglegible
* features2d: initialize TBB scheduler in perf tests
* ensures more stable output
* more reasonable profiles, since the first call of parallel_for_ is not getting big performace hit
* compute_kfactor: interleave finding of maximum and computing distance
* no need to go twice through the data
* start to use UMats in AKAZE to leverage OpenCl in the future
* fixed bug that prevented computing determinant for scale pyramid of size 1 (just the base image)
* all descriptors now support writing to uninitialized memory
* use InputArray and OutputArray for input image and descriptors, allows to make use UMAt that user passes to us
* enable use of all existing ocl paths in AKAZE
* all parts that uses ocl-enabled functions should use ocl by now
* imgproc: fix dispatching of IPP version when OCL is disabled
* when OCL is disabled IPP version should be always prefered (even when the dst is UMat)
* get rid of copy in DeterminantHessian response
* this slows CPU version considerably
* do no run in parallel when running with OCL
* store derivations as UMat in pyramid
* enables OCL path computing of determint hessian
* will allow to compute descriptors on GPU in the future
* port diffusivity to OCL
* diffusivity itself is not a blocker, but this saves us downloading and uploading derivations
* implement kernel for nonlinear scalar diffusion step
* download the pyramid from GPU just once
we don't want to downlaod matrices ad hoc from gpu when the function in AKAZE needs it. There is a HUGE mapping overhead and without shared memory support a LOT of unnecessary transfers.
This maps/downloads matrices just once.
* fix bug with uninitialized values in non linear diffusion
* this was causing spurious segfaults in stitching tests due to propagation of NaNs
* added new test, which checks for NaNs (added new debug asserts for NaNs)
* valgrind now says everything is ok
* add nonlinear diffusion step OCL implementation
* Lt in pyramid changed to UMat, it will be downlaoded from GPU along with Lx, Ly
* fix bug in pm_g2 kernel. OpenCV mangles dimensions passed to OpenCL, so we need to check for boundaries in each OCL kernel.
* port computing of determinant to OCL
* computing of determinant is not a blocker, but with this change we don't need to download all spatial derivatives to CPU, we only download determinant
* make Ldet in the pyramid UMat, download it from CPU together with the other parts of the pyramid
* add profiling macros
* fix visual studio warning
* instrument non_linear_diffusion
* remove changes I have made to TEvolution
* TEvolution is used only in KAZE now
* Revert "features2d: initialize TBB scheduler in perf tests"
This reverts commit ba81e2a711.
In OpenCL code in activations.cl, make the type of floating point
literals to be float. Otherwise the values will be interpreted as
doubles, causing Beignet to have type conversion issues.
Previously, only file-based encoding and decoding were supported with
the libtiff library, leading to the possible use of temporary files.
This fixes issue #8483.
Previously, the return value of fwrite and fclose were not properly
checked, leading to possible silent truncation of the data if writing
failed, e.g. due to lack of disk space.
Fixes issue #9251.
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
Add constructors taking initializer_list for some of OpenCV data types (#9034)
* Add a constructor taking initializer_list for Matx
* Add a constructor taking initializer list for Mat and Mat_
* Add one more method to initialize Mat to the corresponding tutorial
* Add a note how to initialize Matx
* CV_CXX_11->CV_CXX11
Add gstreamer capture capability for some YUV formats (#8914)
* Add gstreamer capture capability for some YUV formats.(only for gstreamer-1.0)
* avoid cross initialization error
* add checking if pipeline is manualpipeline, for compatibility.
fixed problem in concat layer by disabling memory re-use in layers with multiple inputs
trying to fix the tests when Halide is used to run deep nets
another attempt to fix Halide tests
see if the Halide tests will pass with concat layer fusion turned off
trying to fix failures in halide tests; another try
one more experiment to make halide_concat & halide_enet tests pass
continue attempts to fix halide tests
moving on
uncomment parallel concat layer
seemingly fixed failures in Halide tests and re-enabled concat layer fusion; thanks to dkurt for the patch
BufferPoolController has a non virtual protected destructor (which is legitimate)
However, Visual Studio sees this as a bug, if you enable more warnings, like below
```
add_compile_options(/W3) # level 3 warnings
add_compile_options(/we4265) # warning about missing virtual destructors
```
This is a proposition in order to silence this warning.
See https://github.com/ivsgroup/boost_warnings_minimal_demo for a demo of the same problem
with boost/exception.hpp
merge_histogram kernel only need "BINS" theads to accumulate the
histgrams, it is not efficient to directly use maxGroupSize as
local size if maxGroupSize is far greater then BINS.
Remove unnecessary Non-ASCII characters from source code (#9075)
* Remove unnecessary Non-ASCII characters from source code
Remove unnecessary Non-ASCII characters and replace them with ASCII
characters
* Remove dashes in the @param statement
Remove dashes and place single space in the @param statement to keep
coding style
* misc: more fixes for non-ASCII symbols
* misc: fix non-ASCII symbol in CMake file
The old error message was not giving any hint which input array (image)
led to an ill conditioned matrix. This made it near impossible to
identify poor images in a larger set.
A better approach would be to implement a checker function which gives
each image a rating before the real calibration is performed. This could
also include some image properties like sharpness, etc.
The objective is to:
*Reduce greatly the number of lines of code in the Java codes;
*Make it easy for Java users to add a trackbar and show the results;
*Get the code more similar between C++, Java and Python, making the tutorials more uniform.
Main purpose of this namespace is to avoid using of incompatible
binaries that will cause applications crashes.
This additional namespace will not impact "Source code API".
This change allows to maintain ABI checks (with easy filtering out).
Enable p3p and ap3p in solvePnPRansac (#8585)
* add paper info
* allow p3p and ap3p being RANSAC kernel
* keep previous code
* apply catrees comment
* fix getMat
* add comment
* add solvep3p test
* test return value
* fix warnings
* another round of dnn optimization:
* increased malloc alignment across OpenCV from 16 to 64 bytes to make it AVX2 and even AVX-512 friendly
* improved SIMD optimization of pooling layer, optimized average pooling
* cleaned up convolution layer implementation
* made activation layer "attacheable" to all other layers, including fully connected and addition layer.
* fixed bug in the fusion algorithm: "LayerData::consumers" should not be cleared, because it desctibes the topology.
* greatly optimized permutation layer, which improved SSD performance
* parallelized element-wise binary/ternary/... ops (sum, prod, max)
* also, added missing copyrights to many of the layer implementation files
* temporarily disabled (again) the check for intermediate blobs consistency; fixed warnings from various builders
