Changelog for opencv-devel-4.1.2-3.2.i586.rpm :

* Sun Nov 03 2019 Stefan Brüns - Limit build parallelism with limit_build, some ARM and PPC workers have a high SMP/memory ratio and run out of memory otherwise.- Apply memory constraints (3GB) to all architectures, avoid being scheduled on very weak workers.
* Sat Oct 12 2019 Stefan Brüns - Update to 4.1.2
* DNN module: + Intel Inference Engine backend (OpenVINO): - 2019R3 has been supported - Support modern IE Core API - New approach for custom layers management. Now all the OpenCV layers fallbacks are implemented as IE custom layers which helps to improve efficiency due less graph partitioning. - High-level API which introduces dnn::Model class and set of task-specific classes such dnn::ClassificationModel, dnn::DetectionModel, dnn::SegmentationModel. It supports automatic pre- and post-processing for deep learning networks.
* Performance improvements and platforms support: + MSA SIMD implementation has been contributed for MIPS platforms: https://github.com/opencv/opencv/pull/15422 + OpenCV.js optimization (threading and SIMD as part of GSoC project): https://github.com/opencv/opencv/pull/15371 + More optimizations using SIMD intrinsics: dotProd, FAST corners, HOG, LK pyramid (VSX), norm, warpPerspective, etc + Fixed detection of Cascade Lake CPUs
* And many other great patches from OpenCV community: + GUI: support topmost window mode (Win32/COCOA): https://github.com/opencv/opencv/pull/14872 + Java: fix Mat.toString() for higher dimensions: https://github.com/opencv/opencv/pull/15181 + Implementation of colormap \"Turbo\" https://github.com/opencv/opencv/pull/15388 + QR-Code detection accuracy improvement: https://github.com/opencv/opencv/pull/15356 + GSoC: Add learning-based super-resolution module: https://github.com/opencv/opencv_contrib/pull/2229 and https://github.com/opencv/opencv_contrib/pull/2231 + Detection accuracy improvement of the white marker aruco corners: https://github.com/opencv/opencv_contrib/pull/2236 + Added pattern generator tool for aruco: https://github.com/opencv/opencv_contrib/pull/2250 + and special thanks to AATTsturkmen72 for improvind and cleaning up code of samples/tutorials
* Breaking changes: + fixed values thresholding accuracy in calcHist()
* Security fixes: CVE-2019-15939 (boo#1149742).- Enable Graph API (G-API)- Minor spec file cleanup
* Wed Aug 28 2019 Marius Kittler - Include pkg-config file in opencv-devel package
* Add opencv-includedir.patch
* Tue Aug 27 2019 Jan Engelhardt - Avoid use of ®/™ signs in specfiles as per guidelines.
* Mon Aug 19 2019 Jonathan Brielmaier - Disable LTO on ppc64le for now, as it fails to build when enabled (boo#1146096).
* Sat Aug 10 2019 Christophe Giboudeaux - Increase the disk space needed to build opencv.
* Fri Aug 09 2019 Christophe Giboudeaux - Update to 4.1.1
* DNN module:
* 3D convolution networks initial support
* A lot of improvements for ONNX and TenforFlow importers
* Performance improvements
* Added IPPE method for planar pose estimation in solvePnP
* Added solvePnPRefineLM and solvePnPRefineVVS
* Security fixes: CVE-2019-14491 (boo#1144352), CVE-2019-14492 (boo#1144348).- Check https://github.com/opencv/opencv/wiki/ChangeLog#version411 for the complete list of changes.- Drop fix_processor_detection_for_32bit_on_64bit.patch. Fixed upstream- Drop 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch Fixed upstream- Refresh 0001-Do-not-include-glx.h-when-using-GLES.patch and opencv-build-compare.patch.
* Tue Jul 02 2019 Stefan Brüns - Update to version 4.1.0
* DNN module: + Reduced peak memory consumption for some models up to 30%. + Inference Engine - Inference Engine 2018R3 is now a minimal supported version of IE. - Myriad X (Intel® Neural Compute Stick 2) is now supported and tested. - Automatic IR network reshaping for different inputs. - Improved samples to work with models from OpenVINO Open Model Zoo + New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements: + More optimization using AVX2 instruction set. + Automatic runtime dispatching is available for large set of functions from core and imgproc modules.
* Other improvements: + Matplotlib Perceptually Uniform Sequential colormaps + Add keypoints matching visualization for real-time pose estimation tutorial + Add Hand-Eye calibration methods + Java: improved support for multidimensional arrays (Mat) + Dynamically loaded videoio backends (FFmpeg, GStreamer) + opencv_contrib: Robust local optical flow (RLOF) implementations + opencv_contrib: Implementation of Quasi Dense Stereo algorithm + opencv_contrib: New module: Image Quality Analysis (IQA) API + opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API Check https://github.com/opencv/opencv/wiki/ChangeLog#version410- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON) in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler. Thanks to the extended C++11 standard library, we could get rid of hand-crafted cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_ we now use std::thread\'s instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements A few hundreds of basic kernels in OpenCV have been rewritten using so-called \"wide universal intrinsics\". Those intrinsics map to SSE2, SSE4, AVX2, NEON or VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib. Check https://github.com/opencv/opencv/wiki/ChangeLog#version400- Drop obsolete opencv-lib_suffix.patch- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch- As this is a major version upgrade, the old 3.4.x package is still available as opencv3
* Mon Oct 29 2018 Christophe Giboudeaux - Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel\'s Inference Engine backend
* Enabled import of Intel\'s OpenVINO pre-trained networks from intermediate representation (IR).
* tutorials improvements Check https://github.com/opencv/opencv/wiki/ChangeLog#version343 for the complete changelog.- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch (fixed upstream)- Refresh patches
* Tue May 29 2018 fabianAATTritter-vogt.de- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
* Mon May 28 2018 fvogtAATTsuse.com- Update to 3.4.1:
* 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
* Fix cmake mapping of RelWithDebInfo (boo#1154091).
* For more information, read https://github.com/opencv/opencv/wiki/ChangeLog#version341- Update contrib modules to 3.4.1:
* No changelog available- Change mechanism the contrib modules are built- Include LICENSE of contrib tarball as well- Build with python3 on >= 15- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch- Mention all libs explicitly- Rebase 3.4.0 update from iAATTmarguerite.su- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to cover DNN module
* DNN has been further accelerated for iGPU using OpenCL
* On-disk caching of precompiled OpenCL kernels has been finally implemented
* possible to load and run pre-compiled OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been implemented (currently supported only bilinear interpolation)- update face module to 3.4.0- add opencv-lib_suffix.patch, remove LIB_SUFFIX from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL _LIBDIR is arch dependent.
* Mon Mar 12 2018 schwabAATTsuse.de- Add option to build without openblas
* Mon Jan 08 2018 tchvatalAATTsuse.com- 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