./graphics/opencv, Library for computer vision problems

[ CVSweb ] [ Homepage ] [ RSS ] [ Required by ] [ Add to tracker ]

Branch: CURRENT, Version: 3.4.1nb2, Package name: opencv-3.4.1nb2, Maintainer: anthony.mallet

OpenCV means Intel(R) Open Source Computer Vision Library. It is a
collection of C functions and a few C++ classes that implement many
popular Image Processing and Computer Vision algorithms.

OpenCV provides cross-platform middle-to-high level API that includes
about 300 C functions and a few C++ classes. Also there are Python
bindings to OpenCV. OpenCV has no strict dependencies on external
libraries, though it can use some (such as libjpeg, ffmpeg, GTK+ etc.)

OpenCV provides transparent interface to Intel(R) Integrated Performance
Primitives (IPP). That is, it loads automatically IPP libraries optimized
for specific processor at runtime, if they are available.

Required to run:
[graphics/jasper] [graphics/tiff] [graphics/png] [graphics/openexr] [x11/gtk2] [math/py-numpy] [lang/python27] [graphics/libwebp]

Required to build:
[pkgtools/x11-links] [x11/xcb-proto] [x11/fixesproto4] [pkgtools/cwrappers] [x11/xorgproto]

Master sites:

SHA1: 1e2a04746eaeee520e58f81002c556c435ef0dce
RMD160: d9f6de36b3d43e0ec5ce7dcfe752a7529f1c4daa
Filesize: 88850.486 KB

Version history: (Expand)

CVS history: (Expand)

   2018-04-16 16:35:28 by Thomas Klausner | Files touched by this commit (1284)
Log message:
Recursive bump for new fribidi dependency in pango.
   2018-03-12 12:18:01 by Thomas Klausner | Files touched by this commit (2155)
Log message:
Recursive bumps for fontconfig and libzip dependency changes.
   2018-03-02 17:24:21 by Filip Hajny | Files touched by this commit (5) | Package updated
Log message:
graphics/opencv: Update to 3.4.1.

== OpenCV 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, such
  as convolution and fully-connected layers
- SSD-based models trained and retrained in TensorFlow Object
  Detection API can be easier imported by a single invocation of
  python script making a text graph representation
- Performance of pthreads backend of cv::parallel_for_() has been
  greatly improved on many core machines
- OpenCL backend has been expanded to cover more layers
- Several bugs in various layers have been fixed

- On-disk caching of precompiled OpenCL kernels has been fixed to
  comply with OpenCL standard
- Certain cases with UMat deadlock when copying UMats in different
  threads has been fixed

- Supported Android NDK16
- Added build.gradle into OpenCV 4 Android SDK
- Added initial support of Camera2 API via JavaCamera2View interface

- C++11: added support of multi-dimentional cv::Mat creation via C++
  initializers lists
- C++17: OpenCV source code and tests comply C++17 standard

- opencv_contrib: added GMS matching
- opencv_contrib: added CSR-DCF tracker
- opencv_contrib: several improvements in OVIS module

== OpenCV 3.4

- New background subtraction algorithms have been integrated.

- 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
- It's now possible to load and run pre-compiled OpenCL kernels via
- Bit-exact 8-bit and 16-bit resize has been implemented
   2018-02-26 09:19:32 by Adam Ciarcinski | Files touched by this commit (89) | Package updated
Log message:
revbump after x264-devel update
   2017-11-06 14:30:27 by Thomas Klausner | Files touched by this commit (1)
Log message:
opencv: follow redirect
   2017-09-04 17:23:49 by Filip Hajny | Files touched by this commit (11) | Package updated
Log message:
Update graphics/opencv to 3.3.0.
Sync opencv-contrib-face too.

Main changes:

- DNN module from opencv_contrib was promoted to the main repository,
  improved and accelerated it a lot. An external BLAS implementation is
  not needed anymore. For GPU there is experimental DNN acceleration using
  Halide (http://halide-lang.org).
- OpenCV can now be built as C++ 11 library using the flag ENABLE_CXX11.
  Some cool features for C++ 11 programmers have been added.
- We've also enabled quite a few AVX/AVX2 and SSE4.x optimizations in
  the default build of OpenCV thanks to the feature called 'dynamic
  dispatching'. The DNN module also has some AVX/AVX2 optimizations.
- Intel Media SDK can now be utilized by our videoio module to do
  hardware-accelerated video encoding/decoding. MPEG1/2, as well as
  H.264 are supported.
- Embedded into OpenCV Intel IPP subset has been upgraded from 2015.12
  to 2017.2 version, resulting in ~15% speed improvement in our core &
  imgproc perf tests.

Full release notes:

   2017-05-03 10:38:46 by Jonathan Perkin | Files touched by this commit (95)
Log message:
Convert CXXFLAGS setting C++ standard to USE_LANGUAGES.
   2017-03-16 22:59:13 by Patrick Welche | Files touched by this commit (11) | Package removed
Log message:
Update opencv to 3.2

Many Darwin library handling patches removed because of commit 912592de4ce
  Remove "INSTALL_NAME_DIR lib" target property

Full changelog at



     * Results from 11 GSoC 2016 projects have been submitted to the
       library, 9 of them have been integrated already, 2 still pending
       (the numbers below are the id's of the Pull Requests in opencv or
       opencv_contrib repository):
          + Ambroise Moreau (Delia Passalacqua) - sinusoidal patterns for
            structured light and phase unwrapping module (711)
          + Alexander Bokov (Maksim Shabunin) - 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 (689, 708, 722, 736, 745, 747)
          + Tyan Vladimir (Antonella Cascitelli) - CNN based tracking
            algorithm (GOTURN) (718, 899)
          + Vladislav Samsonov (Ethan Rublee) - PCAFlow and Global Patch
            Collider algorithms implementation (710, 752)
          + Jo o Cartucho (Vincent Rabaud) - Multi-language OpenCV
            Tutorials in Python, C++ and Java (7041)
          + Jiri Horner (Bo Li) - New camera model and parallel processing
            for stitching pipeline (6933)
          + Vitaliy Lyudvichenko (Anatoly Baksheev) - Optimizations and
            improvements of dnn module (707, 750)
          + Iric Wu (Vadim Pisarevsky) - Base64 and JSON support for file
            storage (6697, 6949, 7088). Use names like
            `"myfilestorage.xml?base64"` when writing file storage to
            store big chunks of numerical data in base64-encoded form.
          + Edgar Riba (Manuele Tamburrano, Stefano Fabri) - tiny_dnn
            improvements and integration (720: pending)
          + Yida Wang (Manuele Tamburrano, Stefano Fabri) - Quantization
            and semantic saliency detection with tiny_dnn
          + Anguelos Nicolaou (Lluis Gomez) - Word-spotting CNN based
            algorithm (761: pending)