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

• Files Changed
• Browse Source

- 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)

• Files Changed
• Browse Source

- 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)

• Files Changed
• Browse Source

- 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

• Files Changed
• Browse Source

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

• Files Changed
• Browse Source

- 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

• Files Changed
• Browse Source

- 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.

• Files Changed
• Browse Source

• Files Changed
• Browse Source

• Files Changed
• Browse Source

- 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

• Files Changed
• Browse Source

- update to 4.5.5, highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version455
  * 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

• Files Changed
• Browse Source

- 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

• Files Changed
• Browse Source

- Remove dependency on IlmBase, opencv never uses this directly.

• Files Changed
• Browse Source

- update to 4.5.2, highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version452
  * 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,
	BackgroundSubtractor)
      - 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

• Files Changed
• Browse Source

- Enable aruco module (recognize markers to detect camera pose)
(planning to use it for  https://github.com/kacpertopol/cam_board)

• Files Changed
• Browse Source

- update to 4.5.1, highlights below, for details check
  https://github.com/opencv/opencv/wiki/ChangeLog#version451
  * 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
      Recognition
    + 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
      @YashasSamaga)
  * 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

• Files Changed
• Browse Source

• Files Changed
• Browse Source

- 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.

• Files Changed
• Browse Source

- update to 4.5.0, see
  https://github.com/opencv/opencv/wiki/ChangeLog#version450
  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

• Files Changed
• Browse Source

• Files Changed
• Browse Source