opencv-4.10.0-bp160.1.22

- update to 4.10.0,  highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version4100
  * Core Module:
    + Added CV_FP16 data type for cv::Mat #24892, #24918.
    Deprecated convertFp16 function, added FP16 support to
    cv::Mat::convertTo and analogs.
    + Fixed undefined behaviour in some cases related to FP16
    arithmetic #25598 + Extended HAL API for minMaxIdx #25563,
    LUT #25554, meanStdDev #25483, moments 25490,
    normHamming #25491. HAL entries for transpose #25342,
    some arithmetic functions #25574, #25506
    + Persistence: output reals as human-friendly expression.
    [#25351]
    + Added cgroups v2 support to parallel framework #25285
    + Added in-place support for cartToPolar and polarToCart
    [#24893]
  * Imgproc Module:
    + Added relative displacement field option to cv::remap #24621
    + Added new findContours implementation #25146, #25680, #25385
    + Refactored EMD algorithm to get rid of C-API usage #25469
    + Fixed bug in stackBlur with large kernels #25513
    + Extended HAL for projectPoints #25511, equalizeHist #25565,
    Otsu threshold #25509. Added new HAL entries for
    gaussianBlur#25397, remap #25399, bilaterialFilter #25343.
  * Calib3d Module:
    + Fixed several bugs in hand-eye calibration methods #24897,
    [#25423]
    + Fixed several bugs in findHomography implementation
    [#25308], #25665
    + Multiple improvements in findChessboardCorners
    implementation: #25365, 25195, 25177, 25182, 25145, 24779,
    24710, 24833, 25090
    + Improved symmetric circles grid pattern detection #25258
    + Fixed possible infinite loop in USAC #24987
    + Changed approach for initial estimation for focal length in
    fisheye calibration #25030
    + Added solvePnP implementation for Fisheye camera model #25028
  * DNN module:
    + Significantly improved DNN memory consumption #25181, 25163
    + Added Net::dumpToPbtxt method to review optimized graph with
    Netron #25582
    + Added support for several TFLite layers: Global_Pool_2D
    [#25613], Transpose #25297, HardSwishInt8 #24985, split, fully
    connected, SoftMax, Cast #25273.
    + Fixed bugs in several ONNX layers: Slice #25660, Range
    [#25414], Clip #25319, ReduceMean #25120, Einsum #25100,
    Norm #24808, negative axis support in Concat #24865.
    + Added new ONNX layers: Mod #24765, GroupNorm layer #24610.
    + Added more DNN layers with OpenVINO #25524, #25291, 25518.
    + Optimized fastDepthwiseConv #25361 and int8 layers 25230 for
    RISC-V with RVV extension
    + Optimized fastDepthwiseConv for RISC-V P Packed SIMD
    Extension v0.5.2 #24556
    + Optimized Attention #24476, #25271, #25238, #24613, 25076.
    + Added parallel version for scatter and scatterND #24813
    + Added broadcasting if a.rank() != b.rank() with
    CuDNN backend #24834
    + Tuned Winograd algorithm usage for convolutions #24709
    + Added Raft model support and tracking sample with it #24913
    + Added Vulkan backend for NaryEltwiseLayer in DNN
    module #24768
    + Imporved modern Yolo detectors support. Added sample and
    documentation #24898, #24611
    + Added CuDNN 9+ support #25412
    + Added OpenVINO 2024 support #25199
  * G-API module:
    + Ported G-API ONNXRT backend into V2 API #25662
    + Implement concurrent executor #24845
    + A quick value-initialization support GMat #25055
    + Fixed support of mean/scale preprocessing in OV backend for
    non-real types #24704
  * Objdetect module:
    + Fixed inaccurate Charuco board generation in some cases
    (.generateImage()) #24873, #25673
    + Fixed Aruco detector thread safety issue #24807, made Aruco
    detector more deterministic #24829
    + Added QR codes Structured Append decoding mode #24548
    + Several bug fixes in QR code detector and decoder #25026
    + Fixed barcode detectAndDecode #25035
    + Ported remaning Aruco and Charuco documentation and samples
    to modern API #23018
  * VideoIO:
    + Fix race condition in InternalFFMpegRegister initialization.
    [#25419]
    + Orbbec Camera supports MacOS，Gemini2 and Gemini2L support Y16
    format #24877
    + Added V4L2_PIX_FMT_SGRBG8 pixel format support to V4L2 backend
    [#25249]
    + Fix incorrect timestamps returned by VideoCapture when
    CAP_PROP_FORMAT == -1 #24828
  * Python Bindings:
    + Experimental NumPy 2.0 support
    + Added python bindings for Rect2f and Point3i #24919
    + Switched to numeric dtype for MatLike instead of generic
    [#25406]
    + Added path-like objects support wherever file names are
    expected #24773
  * Platforms support:
    + CUDA 12.4+ support #25658
    + Wayland back-end for Linux #25551, #25510, #25502
    + New LAPACK interface support on MacOS and derivatives
    [#24804], #25625
    + Added initial version of HAL for RISC-V processors with
    P-extension (v0.5.2, Andes platforms) #25167
    + Added ARM KleidiCV as HAL for ARM v8 and v9 processors
    (-DWITH_KLEIDICV=ON CMake option) #25443, #25618, ARM
    announcement.
    + Added zlib-ng as alternative to classic zlib
    (-DWITH_ZLIB_NG=ON CMake option) #24782
    + OneAPI 2024 support (IPP, TBB)

- Add %{?sle15allpythons} and build python bindings for all
  configured versions (also for Tumbleweed)

- update to 4.9.0,  highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version490
  Highlights of this release:
  * Core Module:
    + Added cv::broadcast
    + Fixed several rounding issues on ARM platform
    + Added detection & dispatching of some modern NEON
    instructions (NEON_FP16, NEON_BF16)
    + Added optimization for LoongArch 128-bit vector,
    detection & dispatching of LoongArch
  * DNN module patches:
    + Experimental transformers support
    + ONNX Attention layer support
    + ONNX Einsum layer support
    + OpenVINO backend for INT8 models
    + ONNX Gather Elements layer
    + ONNX InstanceNorm layer
    + Better support of ONNX Expand layer with cv::broadcast
    + Improved DNN graph fusion with shared nodes and commutative
    operations
    + New fastGEMM implementation and several layers on top of it
    + Winograd fp16 optimizations on ARM
    + Tests and multiple fixes for Yolo family models support
    + New layers support and bug fixes in CUDA backend: GEMM,
    Gelu, Add
    + CANN backend: bug fix, support HardSwish,
    LayerNormalization and InstanceNormalization
    + LayerNormalization: support OpenVINO, OpenCL and
    CUDA backend.
  * G-API module:
    + Intel® OpenVINO™ DL inference backend:
  - Introduced "inferenence only" ("benchmark") mode
    in the OV2.0 backend.
  - Fixed model layout setting issue in the OV2.0 backend.
  - Fixed/relaxed various asserts in the OV2.0 backend.
    + Core and image processing functionality:
  - Fluid kernels were rewritten to new universal intrinsics.
    Thanks for this contribution!
    + Streaming and video functionality:
  - Introduced a QueueSource: an alternative way to manually
    push input frames to the G-API pipeline in the streaming
    mode.
  - Introduced VAS Object Tracker (OT) for the various video
    analytics scenarios.
    +  Python bindings:
  - Exposed VAS OT in G-API Python bindings.
    + Other changes and fixes:
  - Updated ADE (the G-API's graph library) to the latest
    version.
  - Various code clean-ups and warning fixes.
  * Objdetect module:
    + Implemented own QR code decoder as replacement for QUIRC
    library
    + Bug fixes in QR code encoder version estimation
    + More accurate Aruco marker corner refinement with
    dynamic window
    + Fixed contour filtering in ArUco
    + QR code detection sample for Android
    + Multiple local bug fixes and documentation update for
    Aruco makers, Charuco boards and QR codes.
  * Video:
    + Google Summer of Code: added a new object tracking API
    TrackerVit for a vision transformer-based VitTrack.
    This work is done by LIU Pengyu.
  * VideoIO:
    + Videoio: Add raw encoded video stream encapsulation
    to cv::VideoWriter with CAP_FFMPEG
    + Fix GStreamer backend with manual pipelines.
  * Calibration module:
    + Multiple fixes and improvements chess board calibration
    rig detector.
    + calibrateCamera throws exception, if calibration system
    is underconstrained.
    + Fixed bug in findEssentialMat with USAC
    + Fixed out-of-image access in cv::cornerSubPix
    + Fixed crash in ap3p
    + Fixed stereoRectify image boundaries
    + Fixed "use after free" issue in essential_solver.cpp
  * Python Bindings:
    + Added type stub generation for missed types and manually
    wrapped types.
    + Added read-only flag handling for Numpy arrays.
    + Fixed exception handling and bindings for in module.
    + Improved error messages in Numpy array type handling.
    + Fixed constructors documentation in Python.
  * Platforms and hardware Support:
    + Experimental CUDA support as first class language in CMake
    + Added experimental support for Apple VisionOS platform
    + Add support Orbbec Gemini2 and Gemini2 XL camera
    + Fix fullscreen behavior on macOS
  * Other:
    + OpenCV Summer of Code: semi-automated refactoring across
    multiple pull requests by HAN Liutong made our CPU-optimized
    code compatible with SIMD with variable vector
    length (RISC-V RVV)

- update to 4.8.1
  * WebP security update for CVE-2023-4863
  * Depthwise convolution 5x5 performance regression fix
- update to 4.8.0, highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version480
  Highlights of this release:
  * DNN module patches:
    + TFLite models support, including int8 quantized models.
    + Enabled DNN module build without Protobuf dependency.
    + Improved layers => supported more models:
  - ONNX: Layer normalization, GELU and QLinearSoftmax.
  - Fixes in CANN backend:
  * support ONNX Split, Slice, Clip (Relu6) and
    Conv with auto_pad.
  * support ONNX Sub, PRelu, ConvTranspose.
  - Reduce Refactor for robustness and potential
    follow-up improvements.
  - Fixes for Segment Anything Model by Meta.
  - Fixes in nary element wise layer about broadcast:
  * Fixes in CPU.
  * and Fixes in CUDA backend.
  - Further increased DNN speed on ARM and X86 by improving
    convolution, covering 1D and 3D cases, supporting
    convolution+element-wise op fusion.
  - Added full FP16 computation branch on ARMv8 platform, 1.5x
    faster than FP32 (FP16 Winograd is still pending).
  - Vulkan backend refactor for better performance and
    robustness. It runs 4X faster than before.
  - Added API blobFromImageParam to build network inputs
    with pre-processings.
  - Modern OpenVINO support.
  * G-API module:
    + Intel® OpenVINO™ inference backend:
  - Streamlined preprocessing in OpenVINO
    Inference Engine (ie) API 1.0 backend. Note: this backend
    will be deprecated after OpenVINO removes the API 1.0
    support in its subsequent releases.
  - Aligned OpenVINO IE API 1.0 backend with the latest
    OpenVINO 2023.0 (as some features were removed there).
  - Introduced a brand new OpenVINO API 2.0 backend.
  - Implemented the required inference operations for
    the OpenVINO API 2.0 backend.
    + Python bindings:
  - Exposed varions normalization options for ONNX RT
    backend in Python bindings.
  - Exposed Fluid kernels and kernel package manipulation
    functions (combine()) in Python.
  - Fixed issues in Stateful Python kernel state
    handling; also fixed various issues in Python tests.
  - Fixed issue with opaque kernel output information
    handling which broke Python custom kernels.
    + Samples:
  - Introduced a new Segmentation demo with desync() to enable
    slow-running networks in the real-time.
  - Updated stats calculation in the G-API-based pipeline
    modelling tool.
    + Other changes and fixes:
  - Fixed tolerance in Fluid resize tests to avoid issues
    on ARM.
  - Fluid backend: extended Merge3 kernel with more
    supported data types.
  - Fixed standalone mode compilation issues.
  * Objdetect module:
    + FaceDetectorYN upgrade for better performance,
    accuracy and facial landmarks support.
    + New QR code detection algorithm based on ArUco code.
    + Bar code detector and decoder moved from Contrib to
    main repository.
    + Introduced common API for all graphical codes like bar
    codes and QR codes.
    + Added flag for legacy pre-4.6.0 ChAruco boards support.
    + Multiple bug fixes and improvements in QR code detection
    and decoding pipelines.
    + Multiple bug fixes and improvements in ArUco based pipelines.
  * Calibration module:
    + USAC framework improvements.
    + Fixed stddev estimation in camera calibration pipelines.
    + Fixed incorrect pixel grid generation in icvGetRectangles
    that improves accuracy of getOptimalNewCameraMatrix,
    stereoRectify and some other calibration functions.
    Charuco board support in patterns generator, interactive
    calibration tool and calibration samples.
  * Image processing module:
    + Various fixes in line segments detector.
    + Fixed even input dimensions for INTER_NEAREST_EXACT
    in resize.
    + Optimise local cost computation in
    IntelligentScissorsMB::buildMap.
    + Keep inliers for linear remap with BORDER_TRANSPARENT
    + Fix distransform to work with large images.
  * Features2d module:
    + SIFT accuracy improvements.
  * Core module:
    + Added REDUCE_SUM2 option to cv::reduce.
    + Introduced cv::hasNonZero function.
    + Update IPP binaries update to version 20230330.
    + Improved RISC-V RVV vector extensions support.
  - Support RVV v0.11 intrinsics available in LLVM 16
    and GCC 13
  - Support build with T-Head RISC-V toolchain
    (RVV 0.7.1 and 1.0)
    + Several OpenCL vendor and version handling improvements.
  * Multimedia:
    + Added AVIF support through libavif.
    + Orbbec Femto Mega cameras support.
    + HEVC/H265 support in VideoWriter with MS Media
    Foundation backend.
    + Fixed FPS computation on some videos for FFmpeg backend.
    + Added support for VideoCapture CAP_PROP_AUTO_WB and
    CV_CAP_PROP_WHITE_BALANCE_BLUE_U for DShow backend.
    + Fixes OBS Virtual Camera capture.
    + CV_32S encoding support with tiff.
  * Python Bindings:
    + Python typing stubs.
    + Fix reference counting errors in registerNewType.
    + Fixed ChAruco and diamond boards detector bindings.
    + Added bindings to allow GpuMat and Stream objects to
    be initialized from memory initialized in other libraries
    + np.float16 support.
    + Python bindings for RotatedRect, CV_MAKETYPE, CV_8UC(n).
  * JavaScript bindings:
    + Added possibility for disabling inlining wasm in opencv.js
    + Extended JS bindings for Aruco, Charuco, QR codes and
    bar codes.
  * Other:
    + Several critical issue fixes in wechat_qrcode module
    (opencv_contrib)

- update to 4.7.0, highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version470
  Highlights of this release:
  * DNN:
    + New ONNX layers: Scatter and ScatterND, Tile, ReduceL1,
    ReduceMin and more.
    + Signinficant performance optimization for convolutions.
    Winograd algoritm implementation.
    + Element-wise operation (add, sub, mul, div, ...):
    Broadcasting.
    + OpenVino 2022.1 support.
    + CANN backend support.
  * Algorithms:
    + ArUco markers and April tags support including ChAruco and
    diamond boards detection and calibration.
    + QR code detection and decoding quality imrovement. Alignment
    markers support. Benchmark for QR codes: link
    + Nanotrack v2 tracker based on neural networks.
    + Stackblur algoruthm implementation.
  * Multimedia:
    + FFmpeg 5.x support.
    + CUDA 12.0 support. Hardware accelerated video codecs support
    on NVIDIA platforms with modern Video Codec SDK (NVCUVID and
    NVENCODEAPI).
    + CV_16UC1 read/write video support with FFmpeg.
    + Orientation meta support on Mac with native media API.
    + New iterator-based API for multi-page image formats.
    + libSPNG support for PNG format.
    + SIMD acceleration for self-built libJPEG-Turbo
    + H264/H265 support on Android. Multiple fixes for video
    decoder, endcoder and camera memory layout.
  * G-API
    + Exposed all core APIs to Python, including stateful kernels.
  * Optimization:
    + New universal intrinsics backend for scalable vector
    instructions. The first scalable implementation for
    RISC-V RVV 1.0.
    + DNN module patches:
  - Improved layers / supported more models:
  * Scatter and ScatterND #22529, Tile #22809
  * Fixes in Slice (support negative step #22898)
  * Support some reduce layers of ONNX #21601
  - Added CANN backend support #22634. Link to the manual:
    https://github.com/opencv/opencv/wiki/Huawei-CANN-Backend.
  - Added bacthed NMS for multi-class object detection #22857
  - Accelerating convolution, especially for ARM CPU.
  - Winograd's convolution optimization
  + And many other contributions:
    +   Added n-dimensional flip to core #22898
    +   Add StackBlur for imgproc #20379
- Removed upstream opencv-ffmpeg5.patch

- Add upstream change to fix include issue with FFmpeg 5:
  * opencv-ffmpeg5.patch

- update to 4.6.0, highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version460
  * OpenCV project infrastructure migrating on GitHub Actions
    workflows for CI and release purposes
  * Added support for GCC 12, Clang 15
  * Added support for FFmpeg 5.0
  * DNN module patches:
    + Improved layers / activations / supported more models:
  - LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
    depth2space, space2depth
  - fixes in Reduce, Slice, Expand
    + Disabled floating-point denormals processing #21521
    + Changed layer names in ONNX importer to support "output"
    entities properly
    + Added TIM-VX NPU backend support:
    https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
    + Added Softmax parameter to ClassificationModel
    + Added audio speech recognition sample (C++) #21458
    + Intel® Inference Engine backend (OpenVINO):
  - added initial support for OpenVINO 2022.1 release
  - removed support of legacy API (dropped since 2020.3)
  * G-API module:
    + G-API framework:
  - Introduced a Grayscale image format support for
    cv::MediaFrame: #21511;
  - Enabeled .reshape() support in the CPU backend: #21669;
  - Fixed possible hang in streaming execution mode with constant
    inputs: #21567;
  - Introduced proper error/exception propagation in the
    asynchronous streaming execution mode: #21660;
  - Fixed new stream event handling: #21731.
    + Fluid backend:
  - Fixed horizontal pass in the Resize kernel, fixed Valgrind
    issues: #21144;
  - Extended Resize kernel with F32 version: #21678,
    added AVX: #21728.
  - Enabled dynamic dispatch for Split4 kernel: #21520;
  - Enabled dynamic dispatch for Merge3 kernel: #21529;
  - Added a SIMD version for DivC kernel: #21474;
  - Added a SIMD version for DivRC kernel: #21530;
  - Enabled dynamic dispatch for Add kernel: #21686;
  - Enabled dynamic dispatch for Sub kernel: #21746;
  - Added a SIMD version for ConvertTo kernel: #21777;
  - Fixed kernel matrix size for Sobel kernel: #21613.
    + Intel® OpenVINO™ inference backend:
  - Fixed NV12 format support for remote memory when OpenVINO
    remote context is used: #21424.
  - Implemented correct error handling in the backend: #21579.
  - Fixed ngraph warnings #21362.
    + OpenCV AI Kit backend:
  - Introduced a new backend to program OpenCV AI Kit boards via
    G-API. Currently the backend is in experimental state, but allows
    to build Camera+NN pipeline and supports heterogeneity (mixing
    with host-side code): #20785, #21504.
    + Media integration:
  - Enabled GPU inference with oneVPL and DirectX11 on Windows in
    Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
    [#21688]. Now GPU textures decoded by oneVPL decoder can be
    preprocessed and inferred on GPU with no extra host processing.
  - Enabled oneVPL support on Linux: #21883.
  - Extended GStreamer pipeline source with Grayscale image format
    support: #21560.
    + Python bindings:
  - Exposed GStreamer pipeline source in Python bindings: #20832.
  - Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
    modules in OpenCV Contrib.
    + Samples:
  - Introduced a pipeline modelling tool for cascaded model
    benchmarking: #21477, #21636, #21719. The tool supports a
    declarative YAML-based config to describe pipelines with simulated
    pre-/post-processing. The tool collects and reports latency and
    throughput information for the modelled pipeline.
    + Other changes and fixes:
  - Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
    alias remain for compatibility: #21318;
  - Moved Resize kernel from core to imgproc kernel packages for
    CPU, OpenCL, and Fluid backends: #21157. Also moved tests
    appropriately: #21475;
  - Avoided sporadic test failures in DivC: #21626;
  - Fixed 1D Mat handling in the framework: #21782;
  - Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
  * 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
  * videoio_initial_FFmpeg_5_0_support.patch
  * videoio_ffmpeg_avoid_memory_leaks.patch

- Add upstream patches for FFmpeg 5.0 support, add
  * videoio_initial_FFmpeg_5_0_support.patch
  * videoio_ffmpeg_avoid_memory_leaks.patch

- Restore memoryperjob constraint, avoid being scheduled on a 16
  core system and use less than half of it.
- Adjust %limit_build to 1800, to avoid recurrent build failures
  on aarch64. (People should not care for their pet architecture
  only, but also carefully check if they break others.)
- Add missing libopencv_aruco dependency in devel package.

- Remove the memoryperjob constraint which doesn't work as one
  would expect and breaks ppc64 builds.
- Use %limit_memory -m 1700 to set the number of concurrent
  jobs to a sane value and fix OOM errors when building in
  workers with many cores.
- Decrease the disk constraint to 9G which seems to be enough

- Add CVE-2019-15939.patch: add input check in HOG detector
  (boo#1149742 CVE-2019-15939).

- 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).

- Add CVE-2019-15939.patch: add input check in HOG detector
  (boo#1149742 CVE-2019-15939).

- 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).

- 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 ).

- 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

- 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.

- Update licensing information

- change requires of python-numpy-devel to build in Leap and
  to not break factory in future

- fix build error/unresolvable for Leap 42.2 and 42.3

- Update to version 3.3.1:
  * Lots of various bugfixes
- Update source url

- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages

- Update to 3.3
- Dropped obsolete patches
  * opencv-gcc6-fix-pch-support-PR8345.patch
  * opencv-gles.patch
- Updated opencv-build-compare.patch

- 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

- 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

- 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

- 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

- Enable ffmpeg support unconditional

- 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.

- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
  PCH for GCC6.

- Test for python versions greater than or equal to the current
  version.

- Add python 3 support