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libopencv409-4.9.0-150600.1.16 RPM for x86_64

From OpenSuSE Leap 15.6 for x86_64

Name: libopencv409 Distribution: SUSE Linux Enterprise 15
Version: 4.9.0 Vendor: SUSE LLC <>
Release: 150600.1.16 Build date: Thu May 9 17:08:25 2024
Group: System/Libraries Build host: h01-ch3a
Size: 26801404 Source RPM: opencv-4.9.0-150600.1.16.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.






* Fri Jan 19 2024
  - Add %{?sle15allpythons} and build python bindings for all
    configured versions (also for Tumbleweed)
* Sat Dec 30 2023
  - update to 4.9.0,  highlights below, for details check
    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
      + 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
    - 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
    - Various code clean-ups and warning fixes.
    * Objdetect module:
      + Implemented own QR code decoder as replacement for QUIRC
      + 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)
* Sun Oct 01 2023
  - 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
    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
      + 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
* Thu Dec 29 2022
  - update to 4.7.0, highlights below, for details check
    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, ...):
      + 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
      + 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:
    - 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
* Tue Aug 23 2022
  - Add upstream change to fix include issue with FFmpeg 5:
    * opencv-ffmpeg5.patch
* Sun Jun 19 2022
  - update to 4.6.0, highlights below, for details check
    * 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:
      + 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
* Fri Apr 29 2022
  - Add upstream patches for FFmpeg 5.0 support, add
    * videoio_initial_FFmpeg_5_0_support.patch
    * videoio_ffmpeg_avoid_memory_leaks.patch
* Sat Apr 09 2022
  - 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.
* Mon Jan 10 2022
  - 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
* Sat Dec 25 2021
  - update to 4.5.5, highlights below, for details check
    * Audio support as part of VideoCapture API: GStreamer #21264
    * Updated SOVERSION handling rules: #21178
    * DNN module patches:
      + Added tests to cover ONNX conformance test suite: #21088
      + Improved layers / activations / supported more models
      + Upgraded builtin protobuf from 3.5.2 to 3.19.1
      + More optimizations for RISC-V platform
      + Intel® Inference Engine backend ( OpenVINO™ ):
      added support for OpenVINO 2021.4.2 LTS release
    * G-API module:
      + G-API framework:
    - Fixed issue with accessing 1D data from cv::RMat: #21103
    - Restricted passing the G-API types to graph inputs/outputs
      for execution: #21041
    - Various fixes in G-API Doxygen reference: #20924
    - Renamed various internal structures for consistency #20836 #21040
      + Fluid backend:
    - Introduced a better vectorized version of Resize: #20664.
    - Added vectorized version of Multiply kernel: #21024
    - Added vectorized version of Divide kernel: #20914
    - Added vectorized version of AddC kernel: #21119
    - Added vectorized version of SubC kernel: #21158
    - Added vectorized version of MulC kernel: #21177
    - Added vectorized version of SubRC kernel: #21231
    - Enabled SIMD dispatching for AbsDiffC: #21204
      + OpenCL backend:
    - Fixed sporadic test failures in Multiply kernel running
      on GPU: #21205
      + Intel® OpenVINO™ inference backend:
    - Extended ie::Params to support static batch size as input
      to inference: #20856
    - Enabled 2D input tensor support in IE backend: #20925
    - Fixed various issues with imported (pre-compiled)
      networks: #20918
      + Media integration:
    - Introduced a GStreamer-based pipeline source for
      G-API: #20709
    - Completed the integration of Intel® oneVPL as a pipeline
      source for G-API #20773 with device selection #20738,
    asynchronous execution #20901, intial demux support #21022,
    and GPU-side memory allocation via DirectX 11 #21049.
      + Samples:
    - Replaced custom kernels with now-standard G-API operations
      in several samples #21106
    - Moved API snippets from G-API samples to a dedicated
      place #20857
      + Other changes and fixes:
    - Fixed various static analysis issues for OpenVINO 2021.4
      release: #21083 and #21212
    - Fixed various build warnings introduced after OpenVINO
      update: #20937
    - Continued clean-up in the G-API test suite on GTest macros
      [#20922] and test data #20995
    - Added custom accuracy comparison functions to Fluid
      performance tests: #21150.
    * And many other contributions:
      + Added QRcode encoder: #17889
      + GSoC - OpenCV.js: Accelerate OpenCV.js DNN via WebNN: #20406
      + Add conventional Bayer naming: #20970
      + (opencv_contrib) Add Radon transform function to ximgproc: #3090
      + (opencv_contrib) New superpixel algorithm (F-DBSCAN): #3093
      + Created Stitching Tool: #21020
      + Improve CCL with new algorithms and tests: #21275
      + (opencv_contrib) Update ArUco tutorial: #3126
  - Adjust memory constraints (mostly required for aarch64 on Leap)
  - Add 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* Wed Nov 24 2021
  - update to 4.5.4:
    * 8-bit quantization in the dnn module
    * Improved Julia bindings
    * Speech recognition sample
    * dnn module optimizations for RISC-V
    * Tutorial about universal intrinsics and parallel_for usage
    * Improvements in the dnn module:
    - New layers and models support
    - Some existing layers have been fixed
    - Soft-NMS implementation
    - Supported OpenVINO 2021.4.1 LTS release
* Mon Aug 30 2021
  - Remove dependency on IlmBase, opencv never uses this directly.
* Sat May 01 2021
  - update to 4.5.2, highlights below, for details check
    * core: added support for parallel backends.
    * imgproc: added IntelligentScissors implementation (JS demo).
    * videoio: improved hardware-accelerated video de-/encoding tasks.
    * DNN module:
      + Improved debugging of TensorFlow parsing errors: #19220
      + Improved layers / activations / supported more models:
    - optimized: NMS processing, DetectionOutput
    - fixed: Div with constant, MatMul, Reshape
      (TensorFlow behaviour)
    - added support: Mish ONNX subgraph, NormalizeL2 (ONNX),
      LeakyReLU (TensorFlow), TanH + SAM (Darknet), Exp
      + Intel® Inference Engine backend ( OpenVINO™ ):
      added support for OpenVINO 2021.3 release
    * G-API module:
      + Python support:
    - Introduced a new Python backend - now G-API can run custom
      kernels written in Python as part of the pipeline: #19351
    - Extended Inference support in the G-API bindings: #19318
    - Added more graph data types in the G-API bindings: #19319
      + Inference support:
    - Introduced dynamic input / CNN reshape functionality in the
      OpenVINO inference backend #18240
    - Introduced asynchronous execution support in the OpenVINO
      inference backend, now it can run in multiple parallel
    requests to increase stream density/throughput: #19487, #19425
    - Extended supported data types with INT64/INT32 in ONNX
      inference backend and with INT32 in the OpenVINO inference
    backend #19792
    - Introduced cv::GFrame / cv::MediaFrame and constant support
      in the ONNX backend: #19070
      + Media support:
    - Introduced cv::GFrame / cv::MediaFrame support in the
      drawing/rendering interface: #19516
    - Introduced multi-stream input support in Streaming mode
      and frame synchronization policies to support cases like
    Stereo: #19731
    - Added Y and UV operations to access NV12 data of cv::GFrame
      at the graph level; conversions are done on-the-fly if the
    media format is different: #19325
      + Operations and kernels:
    - Added performance tests for new operations (MorphologyEx,
      BoundingRect, FitLine, FindContours, KMeans, Kalman,
    - Fixed RMat input support in the PlaidML backend: #19782
    - Added ARM NEON optimizations for Fluid AbsDiffC, AddWeighted,
      and bitwise operations: #18466, #19233
    - Other various static analysis and warning fixes
      + Documentation:
    - [GSoC] Added TF/PyTorch classification conversion: #17604
    - [GSoC] Added TF/PyTorch segmentation conversion: #17801
    - [GSoC] Added TF/PyTorch detection model conversion: #18237
    - Updated documentation to address Wide Universal Intrinsics
    (WUI) SIMD API: #18952
      + And many other great contributions from OpenCV community:
    - core: cuda::Stream constructor with stream flags: #19286
    - highgui: pollKey() implementation for w32 backend: #19411
    - imgcodecs: Added Exif parsing for PNG: #19439
    - imgcodecs: OpenEXR compression options: #19540
    - imgproc: connectedComponents optimizations: (Spaghetti
      Labeling): #19631
    - videoio: Android NDK camera support #19597
    - (contrib) WeChat QRCode module open source: #2821
    - (contrib) Implemented cv::cuda::inRange(): #2803
    - (contrib) Added algorithms from Edge Drawing Library: #2313
    - (contrib) Added Python bindings for Viz module: #2882
  - Add libva build dependency for HW accelerated videoio
  - Slight bump for memory constraints
* Thu Feb 11 2021
  - Enable aruco module (recognize markers to detect camera pose)
* Sat Jan 02 2021
  - update to 4.5.1, highlights below, for details check
    * Continued merging of GSoC 2020 results:
      + Develop OpenCV.js DNN modules for promising web use cases
      together with their tutorials
      + OpenCV.js: WASM SIMD optimization 2.0
      + High Level API and Samples for Scene Text Detection and
      + SIFT: SIMD optimization of GaussianBlur 16U
    * DNN module:
      + Improved layers / activations / supported more models:
    - optimized: 1D convolution, 1D pool
    - fixed: Resize, ReduceMean, Gather with multiple outputs,
      importing of Faster RCNN ONNX model
    - added support: INT32 ONNX tensors
      + Intel® Inference Engine backend (OpenVINO):
    - added support for OpenVINO 2021.2 release
    - added preview support for HDDL
      + Fixes and optimizations in DNN CUDA backend (thanks to
    * G-API Framework:
      + Introduced serialization for cv::RMat, including
      serialization for user-defined memory adapters
      + Introduced desync, a new Operation for in-graph asynchronous
      execution - to allow different parts of the graph run with
      a different latency
      + Introduced a notion of "in-graph metadata", now various
      media-related information can be accessed in graph directly
      (currently only limited to timestamps and frame IDs)
      + Introduced a new generic task-based executor, based on
      Threading Building Blocks (TBB)
      + Extended infer<>() API to accept a new cv::GFrame data
      structure to allow handling of various media formats without
      changes in the graph structure
      + Made copy() an intrinsic where real copy may not happen
      (optimized out) based on graph structure, extended it to
      support cv::GFrame
      + Various fixes, including addressig static analysis,
      documentation, and test issues
    * G-API Operations:
      + Introduced new operations morphologyEx, boundingRect,
      fitLine, kmeans, Background Subtractor, Kalman filter
    * G-API Intel® Inference Engine backend (OpenVINO):
      + Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
      pre-compiled ones) instead of passing .XML and .BIN files;
      also enabled configuring Inference Engine plugins via
      this structure
      + Added a new overload to infer<>() to run inference over a
      single region of interest
      + Added support for cv::MediaFrame input data type (projected
      from cv::GFrame) and handling for NV12 input image format
    * G-API Python bindings:
      + Exposed G-API's Inference and Streaming APIs in the OpenCV
      Python bindings
      + Added initial Python support for cv::GArray data structure
    * Significant progress on RISC-V port.
  - Updated constraints, bump memory to 5 GB
  - Cleaned up spec file
* Mon Nov 02 2020
  - Split library package, move all libraries with external
    dependencies (Qt5, ffmpeg, gstreamer) into separate packages
  - Move haar and LBP cascades into separate package, pull in from
    objdetect and face (detect) libraries.
* Wed Oct 28 2020
  - update to 4.5.0, see
    for details, highlights:
    * OpenCV license has been changed to Apache 2 (OpenCV 3.x will
      keep using BSD)
    * GSoC is over, all projects were success and most of them have
      already been merged. Optimizations for RISC-V, bindings for
      Julia language, real-time single object tracking, improved SIFT
      and others
    * OpenJPEG is now used by default for JPEG2000
    * Supported multiple OpenCL contexts
    * Improvements in dnn module:
      + Support latest OpenVINO 2021.1 release
      + Tengine lite support for inference on ARM
      + Many fixes and optimizations in CUDA backend
    * Added Python bindings for G-API module
    * Multiple fixes and improvements in flann module
    * Added Robot-World/Hand-Eye calibration function
* Sun Sep 13 2020
  - update to 4.4.0:
    * SIFT (Scale-Invariant Feature Transform) algorithm has been
    moved to the main repository (patent on SIFT is expired)
    * DNN module:
    * State-of-art Yolo v4 Detector: #17148.
    * onnx: Add support for Resnet_backbone
    * EfficientDet models
    * add text recognition sample / demo
    * FlowNet2 optical flow
    * Intel Inference Engine backend
    * added support for OpenVINO 2020.3 LTS / 2020.4 releases
    * support of NN Builder API is planned for removal in the next release
    * Many fixes and optimizations in CUDA backend
    * Obj-C / Swift bindings: #17165
    * Julia bindings as part of ongoing GSoC project
    * BIMEF: A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement
    * Enable Otsu thresholding for CV_16UC1 images
    * Add Stroke Width Transform algorithm for Text Detection
    * Planned migration on Apache 2 license for next releases
  - remove opencv-includedir.patch (obsolete)
* Thu Aug 20 2020
  - Use memoryperjob constraint instead of %limit_build macro.
* Sat Jun 13 2020
  - Update to 4.3.0
    * DNN module:
      + Improved layers / activations / supported more models:
    - ONNX: LSTM, Broadcasting, Algebra over constants, Slice with
    multiple inputs
    - DarkNet: grouped convolutions, sigmoid, swish, scale_channels
    - MobileNet-SSD v3: #16760
      + New samples / demos:
    - Clothes parts segmentation and CP-VTON
    - DaSiamRPN tracker
      Intel® Inference Engine backend (OpenVINO™):
    - added support for custom layers through nGraph OpenVINO
    API: #16628
    - nGraph OpenVINO API is used by default: #16746
      + Many fixes and optimizations in CUDA backend (thanks to
      + OPEN AI LAB team submitted the patch that accelerates OpenCV
      DNN on ARM using their Tengine library
    * G-API module:
      + Introduced a new graph-level data type GOpaque<T>. This type
      can be used to pass arbitrary user data types between G-API
      nodes in the graph (supported for CPU/OpenCV backend only).
      + Introduced a way to declare G-API CPU (OpenCV) kernels in-place
      + Added a new sample "Privacy masking camera", combining Deep
      Learning with traditional Image Processing (link)
      + Added more operations in the default library: WarpAffine,
      WarpPerspective, NV12toGray.
    * Performance improvements:
      + IPP-ICV library with CPU optimizations has been updated to
      version 2020.0.0 Gold
      + SIMD intrinsics: integral, resize, (opencv_contrib) RLOF
      implementation #2476
    * And many other great contributions from OpenCV community:
      + (opencv_contrib) Computer Vision based Alpha Matting
      (GSoC 2019) #2306
      + calib3d: findChessboardCornersSB improvements: #16625
      + calib3d: updated documentation for RT matrices: #16860
      + core: improved getNumberOfCPUs(): #16268
      + imgproc: new algorithm HOUGH_GRADIENT_ALT is added to
      HoughCircles() function #16561. It has much better recall
      and precision
      + imgcodecs: added initial support for OpenJPEG library
      (version 2+): #16494
      + highgui(Qt): added Copy to clipboard: #16677
      + dnn: TensorFlow, Darknet and ONNX importers improvements
      by @ashishkrshrivastava
      + (opencv_contrib) added rapid module for silhouette based 3D
      object tracking: #2356
      + (opencv_contrib) SIFT detector is enabled by default due
      patents expiration (without requirement of NONFREE build
      + help materials: OpenCV Cheat Sheet in Python: #4875
    * Changes that can potentially break compatibility:
      + image filtering functions throws exception on empty input
      (voting results)
  - Packaging changes:
    * Stop mangling CMake diagnostic output, no dependency versions
      end up in the packages anyway, drop opencv-build-compare.patch
    * Set empty OPENCV_DOWNLOAD_TRIES_LIST, skip downloads even when
      network is available during builds (e.g. local build).
    * Drop upstream GLES patches:
      + 0001-Do-not-include-glx.h-when-using-GLES.patch
      + opencv-gles.patch
* Fri Jun 12 2020
  - Disable Python 2 bindings for Tumbleweed.
* Tue Jan 21 2020
  - Drop Jasper (i.e jpeg2k) support (boo#1130404, boo#1144260)
    JasPer is unmaintained, CVEs are not being addressed (some issues
    received patches submitted to the upstream github project, but are
    not being merged, other CVEs are considered unfixable). openSUSE
    follows other distros in dropping JasPer now (much later than
    most others, incl. Debian).
* Mon Jan 20 2020
  - Add webp build dependency to use system libwebp instead of bundled
  - Enable dispatch of AVX512 optimized code.
* Wed Dec 25 2019
  - Update to 4.2.0
    * DNN module:
      + Integrated GSoC project with CUDA backend: #14827
      + Intel® Inference Engine backend ( OpenVINO™ ):
    - support for nGraph OpenVINO API (preview / experimental): #15537
    * G-API module:
      + Enabled in-graph inference: #15090. Now G-API can express more
      complex hybrid CV/DL algorithms;
    - Intel® Inference Engine backend is the only available now,
      support for DNN module will be added in the future releases.
      + Extended execution model with streaming support: #15216. Decoding,
      image processing, inference, and post-processing are now pipelined
      efficiently when processing a video stream with G-API.
      + Added tutorials covering these new features: Face analytics
      pipeline and a sample Face beautification algorithm.
    * Performance improvements:
      + SIMD intrinsics: StereoBM/StereoSGBM algorithms, resize, integral,
      flip, accumulate with mask, HOG, demosaic, moments
      + Muti-threading: pyrDown
    * And many other great patches from OpenCV community:
      + VideoCapture: video stream extraction (demuxing) through
      FFmpeg backend.
      + VideoCapture: waitAny() API for camera input multiplexing
      (Video4Linux through poll() calls).
      + (opencv_contrib) new algorithm Rapid Frequency Selective
      Reconstruction (FSR): #2296 + tutorial.
      + (opencv_contrib) RIC method for sparse match interpolation: #2367.
      + (opencv_contrib) LOGOS features matching strategy: #2383.
    * Breaking changes:
      + Disabled constructors for legacy C API structures.
      + Implementation of Thread Local Storage (TLS) has been improved to
      release data from terminated threads. API has been changed.
      + Don't define unsafe CV_XADD implementation by default.
      + Python conversion rules of passed arguments will be updated in
      next releases: #15915.
* Sun Nov 03 2019
  - 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
  - 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:
      + OpenCV.js optimization (threading and SIMD as part of GSoC
      + 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):
      + Java: fix Mat.toString() for higher dimensions:
      + Implementation of colormap "Turbo"
      + QR-Code detection accuracy improvement:
      + GSoC: Add learning-based super-resolution module: and
      + Detection accuracy improvement of the white marker aruco
      + Added pattern generator tool for aruco:
      + and special thanks to @sturkmen72 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
  - Include pkg-config file in opencv-devel package
    * Add opencv-includedir.patch
* Tue Aug 27 2019
  - Avoid use of ®/™ signs in specfiles as per guidelines.
* Mon Aug 19 2019
  - Disable LTO on ppc64le for now, as it fails to build when enabled
* Sat Aug 10 2019
  - Increase the disk space needed to build opencv.
* Fri Aug 09 2019
  - 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
  - Check 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
* Tue Jul 02 2019
  - 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
  - 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.
  - 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
  - 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
    for the complete changelog.
  - Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
    (fixed upstream)
  - Refresh patches
* Tue May 29 2018
  - Add patch to fix use of headers from C:
    * build-workaround-issues-with-c.patch
* Mon May 28 2018
  - 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
  - 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
  - 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
    _LIBDIR is arch dependent.
* Mon Mar 12 2018
  - Add option to build without openblas
* Mon Jan 08 2018
  - 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
  - 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
  - Update licensing information
* Wed Nov 08 2017
  - change requires of python-numpy-devel to build in Leap and
    to not break factory in future
* Sat Nov 04 2017
  - fix build error/unresolvable for Leap 42.2 and 42.3
* Fri Nov 03 2017
  - Update to version 3.3.1:
    * Lots of various bugfixes
  - Update source url
* Thu Nov 02 2017
  - Rename python subpackage to python2
  - Do not explicitly require python-base for python subpackages
* Mon Oct 09 2017
  - 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
  - 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
  - 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
  - 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
  - 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
  - Enable TBB support (C++ threading library)
  - Add dependency on openBLAS
* Thu Jul 21 2016
  - Enable ffmpeg support unconditional
* Tue Jun 07 2016
  - In case we build using GCC6 (or newer), add -mlra to CFLAGS to
    workaround gcc bug
* Wed May 25 2016
  - Apply upstream patch opencv-gcc6-disable-pch.patch to disable
    PCH for GCC6.
* Mon Mar 21 2016
  - Test for python versions greater than or equal to the current
* Wed Mar 09 2016
  - Add python 3 support
* Thu Mar 03 2016
  - 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
  - Added _constraints file to avoid random failures on small workers
    (at least for builds on PMBS)
* Sat Feb 27 2016
  - 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 (
      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:
    + 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
  - Reduce build-compare noise
* Wed Dec 23 2015
  - Remove BuildRequirement for python-sphinx in SLE12, since it's
    not available there and it's not a mandatory requirement.
* Wed Dec 02 2015
  - Reduce differences between two spec files
* Tue Sep 22 2015
  - Use pkgconfig for ffmpeg BuildRequires
* Fri Jul 24 2015
  - 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"
    * 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
  - support gcc 5 (i.e. gcc versions without minor version):
* Wed Apr 29 2015
  - 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
  - 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
  - Add specific buildrequires for libpng15, so that we are
    building against the system provided libpng.



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Fabrice Bellet, Tue May 21 23:39:22 2024