head 1.4; access; symbols pkgsrc-2017Q4:1.3.0.6 pkgsrc-2017Q4-base:1.3 pkgsrc-2017Q3:1.3.0.4 pkgsrc-2017Q3-base:1.3 pkgsrc-2017Q2:1.2.0.12 pkgsrc-2017Q2-base:1.2 pkgsrc-2017Q1:1.2.0.10 pkgsrc-2017Q1-base:1.2 pkgsrc-2016Q4:1.2.0.8 pkgsrc-2016Q4-base:1.2 pkgsrc-2016Q3:1.2.0.6 pkgsrc-2016Q3-base:1.2 pkgsrc-2016Q2:1.2.0.4 pkgsrc-2016Q2-base:1.2 pkgsrc-2016Q1:1.2.0.2 pkgsrc-2016Q1-base:1.2 pkgsrc-2015Q4:1.1.0.2 pkgsrc-2015Q4-base:1.1; locks; strict; comment @// @; 1.4 date 2018.03.02.16.24.21; author fhajny; state dead; branches; next 1.3; commitid NiCvv3m79dPuYTsA; 1.3 date 2017.09.04.15.23.49; author fhajny; state Exp; branches; next 1.2; commitid UcVmQyjHJObcoT5A; 1.2 date 2016.02.21.14.10.46; author fhajny; state Exp; branches; next 1.1; commitid oUpgwBhk2q1m1NVy; 1.1 date 2015.10.08.17.45.59; author fhajny; state Exp; branches; next ; commitid diAE3W0NRpqBzkEy; desc @@ 1.4 log @graphics/opencv: Update to 3.4.1. == OpenCV 3.4.1 dnn - Added support for quantized TensorFlow networks - OpenCV is now able to use Intel DL inference engine as DNN acceleration backend - Added AVX-512 acceleration to the performance-critical kernels, such as convolution and fully-connected layers - SSD-based models trained and retrained in TensorFlow Object Detection API can be easier imported by a single invocation of python script making a text graph representation - Performance of pthreads backend of cv::parallel_for_() has been greatly improved on many core machines - OpenCL backend has been expanded to cover more layers - Several bugs in various layers have been fixed OpenCL - On-disk caching of precompiled OpenCL kernels has been fixed to comply with OpenCL standard - Certain cases with UMat deadlock when copying UMats in different threads has been fixed Android - Supported Android NDK16 - Added build.gradle into OpenCV 4 Android SDK - Added initial support of Camera2 API via JavaCamera2View interface C++ - C++11: added support of multi-dimentional cv::Mat creation via C++ initializers lists - C++17: OpenCV source code and tests comply C++17 standard Misc - opencv_contrib: added GMS matching - opencv_contrib: added CSR-DCF tracker - opencv_contrib: several improvements in OVIS module == OpenCV 3.4 - New background subtraction algorithms have been integrated. dnn - Added faster R-CNN support - Javascript bindings have been extended to cover DNN module - DNN has been further accelerated for iGPU using OpenCL OpenCL - On-disk caching of precompiled OpenCL kernels has been finally implemented - It's now possible to load and run pre-compiled OpenCL kernels via T-API - Bit-exact 8-bit and 16-bit resize has been implemented @ text @$NetBSD: patch-modules_core_src_parallel__pthreads.cpp,v 1.3 2017/09/04 15:23:49 fhajny Exp $ PTHREAD_RECURSIVE_MUTEX_INITIALIZER doesn't exist on SunOS. --- modules/core/src/parallel_pthreads.cpp.orig 2017-08-03 23:58:23.000000000 +0000 +++ modules/core/src/parallel_pthreads.cpp @@@@ -220,6 +220,10 @@@@ private: ThreadManagerPoolState m_pool_state; }; +#ifndef PTHREAD_RECURSIVE_MUTEX_INITIALIZER +#define PTHREAD_RECURSIVE_MUTEX_INITIALIZER PTHREAD_MUTEX_INITIALIZER +#endif + const char ThreadManager::m_env_name[] = "OPENCV_FOR_THREADS_NUM"; ForThread::~ForThread() @ 1.3 log @Update graphics/opencv to 3.3.0. Sync opencv-contrib-face too. Main changes: - DNN module from opencv_contrib was promoted to the main repository, improved and accelerated it a lot. An external BLAS implementation is not needed anymore. For GPU there is experimental DNN acceleration using Halide (http://halide-lang.org). - OpenCV can now be built as C++ 11 library using the flag ENABLE_CXX11. Some cool features for C++ 11 programmers have been added. - We've also enabled quite a few AVX/AVX2 and SSE4.x optimizations in the default build of OpenCV thanks to the feature called 'dynamic dispatching'. The DNN module also has some AVX/AVX2 optimizations. - Intel Media SDK can now be utilized by our videoio module to do hardware-accelerated video encoding/decoding. MPEG1/2, as well as H.264 are supported. - Embedded into OpenCV Intel IPP subset has been upgraded from 2015.12 to 2017.2 version, resulting in ~15% speed improvement in our core & imgproc perf tests. Full release notes: https://github.com/opencv/opencv/wiki/ChangeLog @ text @d1 1 a1 1 $NetBSD: patch-modules_core_src_parallel__pthreads.cpp,v 1.2 2016/02/21 14:10:46 fhajny Exp $ @ 1.2 log @Update graphics/opencv to 3.1.0. * A lot of new functionality has been introduced during GSoC 2015: - "Omnidirectional Cameras Calibration and Stereo 3D Reconstruction" opencv_contrib/ccalib module - "Structure From Motion" - opencv_contrib/sfm module - "Improved Deformable Part-based Models" - opencv_contrib/dpm module - "Real-time Multi-object Tracking using Kernelized Correlation Filter" - opencv_contrib/tracking module - "Improved and expanded Scene Text Detection" - opencv_contrib/text module - "Stereo correspondence improvements" - opencv_contrib/stereo module - "Structured-Light System Calibration" - opencv_contrib/structured_light - "Chessboard+ArUco for camera calibration" - opencv_contrib/aruco - "Implementation of universal interface for deep neural network frameworks" - opencv_contrib/dnn module - "Recent advances in edge-aware filtering, improved SGBM stereo algorithm" - opencv/calib3d and opencv_contrib/ximgproc - "Improved ICF detector, waldboost implementation" - opencv_contrib/xobjdetect - "Multi-target TLD tracking" - opencv_contrib/tracking module - "3D pose estimation using CNNs" - opencv_contrib/cnn_3dobj * Many great contributions made by the community, such as: - Support for HDF5 format - New/Improved optical flow algorithms - Multiple new image processing algorithms for filtering, segmentation and feature detection - Superpixel segmentation * IPPICV is now based on IPP 9.0.1, which should make OpenCV even faster on modern Intel chips * opencv_contrib modules can now be included into the opencv2.framework for iOS * Newest operating systems are supported: Windows 10 and OSX 10.11 (Visual Studio 2015 and XCode 7.1.1) * Interoperability between T-API and OpenCL, OpenGL, DirectX and Video Acceleration API on Linux, as well as Android 5 camera. * HAL (Hardware Acceleration Layer) module functionality has been moved into corresponding basic modules; the HAL replacement mechanism has been implemented along with the examples See full changelog: https://github.com/Itseez/opencv/wiki/ChangeLog @ text @d1 1 a1 1 $NetBSD: patch-modules_core_src_parallel__pthreads.cpp,v 1.1 2015/10/08 17:45:59 fhajny Exp $ d5 1 a5 1 --- modules/core/src/parallel_pthreads.cpp.orig 2015-12-18 15:02:16.000000000 +0000 d7 1 a7 1 @@@@ -221,6 +221,10 @@@@ private: d17 1 a17 1 #ifdef ANDROID @ 1.1 log @Update graphics/opencv to 3.0.0. Major changes (besides bugfixes): - opencv_contrib (http://github.com/itseez/opencv_contrib) repository has been added. - a subset of Intel IPP (IPPCV) is given to us and our users free of charge, free of licensing fees, for commercial and non-commerical use. - T-API (transparent API) has been introduced, this is transparent GPU acceleration layer using OpenCL. It does not add any compile-time or runtime dependency of OpenCL. When OpenCL is available, it's detected and used, but it can be disabled at compile time or at runtime. - ~40 OpenCV functions have been accelerated using NEON intrinsics and because these are mostly basic functions, some higher-level functions got accelerated as well. - There is also new OpenCV HAL layer that will simplifies creation of NEON-optimized code and that should form a base for the open-source and proprietary OpenCV accelerators. - The documentation is now in Doxygen: http://docs.opencv.org/master/ - We cleaned up API of many high-level algorithms from features2d, calib3d, objdetect etc. They now follow the uniform "abstract interface - hidden implementation" pattern and make extensive use of smart pointers (Ptr<>). - Greatly improved and extended Python & Java bindings (also, see below on the Python bindings), newly introduced Matlab bindings - Improved Android support - now OpenCV Manager is in Java and supports both 2.4 and 3.0. - Greatly improved WinRT support, including video capturing and multi-threading capabilities. Thanks for Microsoft team for this! - Big thanks to Google who funded several successive GSoC programs and let OpenCV in. The results of many successful GSoC 2013 and 2014 projects have been integrated in opencv 3.0 and opencv_contrib (earlier results are also available in OpenCV 2.4.x). We can name: - text detection - many computational photography algorithms (HDR, inpainting, edge-aware filters, superpixels,...) - tracking and optical flow algorithms - new features, including line descriptors, KAZE/AKAZE - general use optimization (hill climbing, linear programming) - greatly improved Python support, including Python 3.0 support, many new tutorials & samples on how to use OpenCV with Python. - 2d shape matching module and 3d surface matching module - RGB-D module - VTK-based 3D visualization module For full changelog see: http://code.opencv.org/projects/opencv/wiki/ChangeLog For 2.4 to 3.0 transition, see the transition guide: http://docs.opencv.org/master/db/dfa/tutorial_transition_guide.html @ text @d1 1 a1 1 $NetBSD$ d5 1 a5 1 --- modules/core/src/parallel_pthreads.cpp.orig 2015-06-03 17:21:34.000000000 +0000 d7 1 a7 1 @@@@ -244,6 +244,10 @@@@ private: d15 3 a17 3 #ifndef PTHREAD_RECURSIVE_MUTEX_INITIALIZER_NP #define PTHREAD_RECURSIVE_MUTEX_INITIALIZER_NP PTHREAD_RECURSIVE_MUTEX_INITIALIZER #endif @