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|Name: libopencv3_3||Distribution: SUSE Linux Enterprise 15|
|Version: 3.3.1||Vendor: SUSE LLC <https://www.suse.com/>|
|Release: 6.6.1||Build date: Mon Oct 21 14:33:43 2019|
|Group: System/Libraries||Build host: mourvedre|
|Size: 19614056||Source RPM: opencv-3.3.1-6.6.1.src.rpm|
|Summary: Libraries to use OpenCV computer vision|
The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL and utilizes Intel Integrated Performance Primitives for better performance.
* Thu Oct 17 2019 email@example.com - Add CVE-2019-15939.patch: add input check in HOG detector (boo#1149742 CVE-2019-15939). * Wed Oct 16 2019 firstname.lastname@example.org - Add opencv-cmake-rel-deb-info.patch: rework MAP_IMPORTED_CONFIG to prevent unintended build failures (boo#1154091). - Add opencv-check-macros.patch: Add "check" macros (boo#1144352 boo#1144348). - Add CVE-2019-14491.patch: objdetect: validate feature rectangle when reading (boo#1144352 boo#1144348 CVE-2019-14491 CVE-2019-14492). * Mon May 21 2018 email@example.com - Add opencv-imgproc-fix-bounds-check.patch: make backport from commit 4ca89db to fix imgproc(hdr) bounds check in HdrDecoder::checkSignature ( bsc#1074312, CVE-2017-18009 ). * Mon Jan 08 2018 firstname.lastname@example.org - Add conditionals for python2 and python3 to allow us enabling only desired python variants when needed - Do not depend on sphinx as py2 and py3 seem to collide there * Sat Nov 25 2017 email@example.com - Readd opencv-gles.patch, it is *not* included upstream; otherwise build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64) - add fix_processor_detection_for_32bit_on_64bit.patch - Correctly set optimizations and dynamic dispatch on ARM, use OpenCV 3.3 syntax on x86. * Mon Nov 13 2017 firstname.lastname@example.org - Update licensing information * Wed Nov 08 2017 email@example.com - change requires of python-numpy-devel to build in Leap and to not break factory in future * Sat Nov 04 2017 firstname.lastname@example.org - fix build error/unresolvable for Leap 42.2 and 42.3 * Fri Nov 03 2017 email@example.com - Update to version 3.3.1: * Lots of various bugfixes - Update source url * Thu Nov 02 2017 firstname.lastname@example.org - Rename python subpackage to python2 - Do not explicitly require python-base for python subpackages * Mon Oct 09 2017 email@example.com - Update to 3.3 - Dropped obsolete patches * opencv-gcc6-fix-pch-support-PR8345.patch * opencv-gles.patch - Updated opencv-build-compare.patch * Sat Jul 15 2017 firstname.lastname@example.org - Add 0001-Do-not-include-glx.h-when-using-GLES.patch Fix build for 32bit ARM, including both GLES and desktop GL headers causes incompatible pointer type errors * Mon Jun 05 2017 email@example.com - Add conditional for the qt5/qt4 integration * This is used only for gui tools, library is not affected - Add provides/obsoletes for the qt5 packages to allow migration - Drop patch opencv-qt5-sobump.diff * Used only by the obsoleted qt5 variant * Mon Jun 05 2017 firstname.lastname@example.org - Cleanup a bit with spec-cleaner - Use %cmake macros - Remove the conditions that are not really needed - Add tests conditional disabled by default * Many tests fail and there are missing testdata - Switch to pkgconfig style dependencies * Sun May 28 2017 email@example.com - Update to OpenCV 3.2.0 - Results from 11 GSoC 2016 projects have been submitted to the library: + sinusoidal patterns for structured light and phase unwrapping module [Ambroise Moreau (Delia Passalacqua)] + DIS optical flow (excellent dense optical flow algorithm that is both significantly better and significantly faster than Farneback’s algorithm – our baseline), and learning-based color constancy algorithms implementation [Alexander Bokov (Maksim Shabunin)] + CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)] + PCAFlow and Global Patch Collider algorithms implementation [Vladislav Samsonov (Ethan Rublee)] + Multi-language OpenCV Tutorials in Python, C++ and Java [João Cartucho (Vincent Rabaud)] + New camera model and parallel processing for stitching pipeline [Jiri Horner (Bo Li)] + Optimizations and improvements of dnn module [Vitaliy Lyudvichenko (Anatoly Baksheev)] + Base64 and JSON support for file storage. Use names like “myfilestorage.xml?base64” when writing file storage to store big chunks of numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)] + tiny_dnn improvements and integration [Edgar Riba (Manuele Tamburrano, Stefano Fabri)] + Quantization and semantic saliency detection with tiny_dnn [Yida Wang (Manuele Tamburrano, Stefano Fabri)] + Word-spotting CNN based algorithm [Anguelos Nicolaou (Lluis Gomez)] - Contributions besides GSoC: + Greatly improved and accelerated dnn module in opencv_contrib: - Many new layers, including deconvolution, LSTM etc. - Support for semantic segmentation and SSD networks with samples. - TensorFlow importer + sample that runs Inception net by Google. + More image formats and camera backends supported + Interactive camera calibration app + Multiple algorithms implemented in opencv_contrib + Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12 + Lot’s of optimizations for IA and ARM archs using parallelism, vector instructions and new OpenCL kernels. + OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL, Apple’s Accelerate, OpenBLAS and Atlas) for acceleration - Refreshed opencv-build-compare.patch - Dropped upstream opencv-gcc5.patch - Replace opencv-gcc6-disable-pch.patch with upstream patch opencv-gcc6-fix-pch-support-PR8345.patch - Enable TBB support (C++ threading library) - Add dependency on openBLAS * Thu Jul 21 2016 firstname.lastname@example.org - Enable ffmpeg support unconditional * Tue Jun 07 2016 email@example.com - In case we build using GCC6 (or newer), add -mlra to CFLAGS to workaround gcc bug https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294. * Wed May 25 2016 firstname.lastname@example.org - Apply upstream patch opencv-gcc6-disable-pch.patch to disable PCH for GCC6. * Mon Mar 21 2016 email@example.com - Test for python versions greater than or equal to the current version. * Wed Mar 09 2016 firstname.lastname@example.org - Add python 3 support * Thu Mar 03 2016 email@example.com - Added opencv_contrib_face-3.1.0.tar.bz2 * This tarball is created to take only the face module from the contrib package. The Face module is required by libkface, which in its turn is required by digikam. * Sun Feb 28 2016 firstname.lastname@example.org - Added _constraints file to avoid random failures on small workers (at least for builds on PMBS) * Sat Feb 27 2016 email@example.com - Update to OpenCV 3.1.0 - A lot of new functionality has been introduced during Google Summer of Code 2015: + “Omnidirectional Cameras Calibration and Stereo 3D Reconstruction” – opencv_contrib/ccalib module (Baisheng Lai, Bo Li) + “Structure From Motion” – opencv_contrib/sfm module (Edgar Riba, Vincent Rabaud) + “Improved Deformable Part-based Models” – opencv_contrib/dpm module (Jiaolong Xu, Bence Magyar) + “Real-time Multi-object Tracking using Kernelized Correlation Filter” – opencv_contrib/tracking module (Laksono Kurnianggoro, Fernando J. Iglesias Garcia) + “Improved and expanded Scene Text Detection” – opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky) + “Stereo correspondence improvements” – opencv_contrib/stereo module (Mircea Paul Muresan, Sergei Nosov) + “Structured-Light System Calibration” – opencv_contrib/structured_light (Roberta Ravanelli, Delia Passalacqua, Stefano Fabri, Claudia Rapuano) + “Chessboard+ArUco for camera calibration” – opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski) + “Implementation of universal interface for deep neural network frameworks” – opencv_contrib/dnn module (Vitaliy Lyudvichenko, Anatoly Baksheev) + “Recent advances in edge-aware filtering, improved SGBM stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc (Alexander Bokov, Maksim Shabunin) + “Improved ICF detector, waldboost implementation” – opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin) + “Multi-target TLD tracking” – opencv_contrib/tracking module (Vladimir Tyan, Antonella Cascitelli) + “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj (Yida Wang, Manuele Tamburrano, Stefano Fabri) - 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 and much more - 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 - Removed improve-sphinx-search.diff, opencv-altivec-vector.patch, opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream. - Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch, opencv-gcc5.patch and opencv-gles.patch. - Version OpenCV 3.0.0 + ~1500 patches, submitted as PR @ github. All our patches go the same route. + opencv_contrib (http://github.com/itseez/opencv_contrib) repository has been added. A lot of new functionality is there already! opencv_contrib is only compatible with 3.0/master, not 2.4. Clone the repository and use “cmake … - D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …” to build opencv and opencv_contrib together. + 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. It’s used by default in x86 and x64 builds on Windows, Linux and Mac. + 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. It covers ~100 OpenCV functions. This work has been done by contract and with generous support from AMD and Intel companies. + ~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 (still in alpha stage). + 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 - etc. + Besides Google, we enjoyed (and hope that you will enjoy too) many useful contributions from community, like: - biologically inspired vision module - DAISY features, LATCH descriptor, improved BRIEF - image registration module - etc. * Fri Jan 22 2016 firstname.lastname@example.org - Reduce build-compare noise opencv-build-compare.patch * Wed Dec 23 2015 email@example.com - Remove BuildRequirement for python-sphinx in SLE12, since it's not available there and it's not a mandatory requirement. * Wed Dec 02 2015 firstname.lastname@example.org - Reduce differences between two spec files * Tue Sep 22 2015 email@example.com - Use pkgconfig for ffmpeg BuildRequires * Fri Jul 24 2015 firstname.lastname@example.org - Update improve-sphinx-search.diff for new python-Sphinx(1.3.1) * now that sphinx-build disallow executing without arguments and give you "Insufficient arguments" error, use "sphinx-build -h" instead * the default usages output ie. sphinx-build(or --help) no longer are standard error but standard output, drop OUTPUT_QUIET and add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well * Wed Apr 29 2015 email@example.com - support gcc 5 (i.e. gcc versions without minor version): opencv-gcc5.patch * Wed Apr 29 2015 firstname.lastname@example.org - Update to OpenCV 2.4.11 - can't find NEWS or Changelog merely collecting bug fixes while 3.0 is in the making, 2.4.11 didn't even make it on their web page, it's only on download server - remove opencv-underlinking.patch as obsolete - remove upstream patch bomb_commit_gstreamer-1x-support.patch - commenting out opencv-pkgconfig.patch - possibly it requires a rebase, but the problem it tries to solve is unclear * Mon Jan 26 2015 email@example.com - Add specific buildrequires for libpng15, so that we are building against the system provided libpng.
/usr/lib64/libopencv_calib3d.so.3.3 /usr/lib64/libopencv_calib3d.so.3.3.1 /usr/lib64/libopencv_core.so.3.3 /usr/lib64/libopencv_core.so.3.3.1 /usr/lib64/libopencv_dnn.so.3.3 /usr/lib64/libopencv_dnn.so.3.3.1 /usr/lib64/libopencv_face.so.3.3 /usr/lib64/libopencv_face.so.3.3.1 /usr/lib64/libopencv_features2d.so.3.3 /usr/lib64/libopencv_features2d.so.3.3.1 /usr/lib64/libopencv_flann.so.3.3 /usr/lib64/libopencv_flann.so.3.3.1 /usr/lib64/libopencv_highgui.so.3.3 /usr/lib64/libopencv_highgui.so.3.3.1 /usr/lib64/libopencv_imgcodecs.so.3.3 /usr/lib64/libopencv_imgcodecs.so.3.3.1 /usr/lib64/libopencv_imgproc.so.3.3 /usr/lib64/libopencv_imgproc.so.3.3.1 /usr/lib64/libopencv_ml.so.3.3 /usr/lib64/libopencv_ml.so.3.3.1 /usr/lib64/libopencv_objdetect.so.3.3 /usr/lib64/libopencv_objdetect.so.3.3.1 /usr/lib64/libopencv_photo.so.3.3 /usr/lib64/libopencv_photo.so.3.3.1 /usr/lib64/libopencv_shape.so.3.3 /usr/lib64/libopencv_shape.so.3.3.1 /usr/lib64/libopencv_stitching.so.3.3 /usr/lib64/libopencv_stitching.so.3.3.1 /usr/lib64/libopencv_superres.so.3.3 /usr/lib64/libopencv_superres.so.3.3.1 /usr/lib64/libopencv_video.so.3.3 /usr/lib64/libopencv_video.so.3.3.1 /usr/lib64/libopencv_videoio.so.3.3 /usr/lib64/libopencv_videoio.so.3.3.1 /usr/lib64/libopencv_videostab.so.3.3 /usr/lib64/libopencv_videostab.so.3.3.1
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