Log message:
Don't try to use eigen if happens to find it.

Log message:
NetBSD's v4l2 emulation doesn't currently have focus-related settings,
so conditionalize parts.

Log message:
Remove manual OPSYSVARS additions which are now part of the default set.

Log message:
Update graphics/opencv to 3.1.0.

* A lot of new functionality has been introduced during GSoC 2015:
  - "Omnidirectional Cameras Calibration and Stereo 3D Reconstruction"
    opencv_contrib/ccalib module
  - "Structure From Motion" - opencv_contrib/sfm module
  - "Improved Deformable Part-based Models" - opencv_contrib/dpm module
  - "Real-time Multi-object Tracking using Kernelized Correlation Filter"
    - opencv_contrib/tracking module
  - "Improved and expanded Scene Text Detection" - opencv_contrib/text
    module
  - "Stereo correspondence improvements" - opencv_contrib/stereo module
  - "Structured-Light System Calibration" - opencv_contrib/structured_light
  - "Chessboard+ArUco for camera calibration" - opencv_contrib/aruco
  - "Implementation of universal interface for deep neural network
    frameworks" - opencv_contrib/dnn module
  - "Recent advances in edge-aware filtering, improved SGBM stereo
    algorithm" - opencv/calib3d and opencv_contrib/ximgproc
  - "Improved ICF detector, waldboost implementation"
    - opencv_contrib/xobjdetect
  - "Multi-target TLD tracking" - opencv_contrib/tracking module
  - "3D pose estimation using CNNs" - opencv_contrib/cnn_3dobj

* 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

* 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

See full changelog:

  https://github.com/Itseez/opencv/wiki/ChangeLog

Log message:
fix broken dynamic library handling on Darwin

Log message:
Revbump after updating graphics/libwebp

Log message:
Recursive revbump from multimedia/libvpx

Log message:
Add SHA512 digests for distfiles for graphics category

Problems found with existing digests:
	Package fotoxx distfile fotoxx-14.03.1.tar.gz
	ac2033f87de2c23941261f7c50160cddf872c110 [recorded]
	118e98a8cc0414676b3c4d37b8df407c28a1407c [calculated]
	Package ploticus-examples distfile ploticus-2.00/plnode200.tar.gz
	34274a03d0c41fae5690633663e3d4114b9d7a6d [recorded]
	da39a3ee5e6b4b0d3255bfef95601890afd80709 [calculated]

Problems found locating distfiles:
	Package AfterShotPro: missing distfile AfterShotPro-1.1.0.30/AfterShotPro_i386.deb
	Package pgraf: missing distfile pgraf-20010131.tar.gz
	Package qvplay: missing distfile qvplay-0.95.tar.gz

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.

Log message:
Don't fetch 3rd party modules during build from the Internet.
Don't require C++14 for no obvious reason.

Log message:
Update graphics/opencv to 3.0.0.

Major changes (besides bugfixes):
- opencv_contrib (http://github.com/itseez/opencv_contrib) repository
  has been added.
- 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.
- 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.
- ~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: http://docs.opencv.org/master/
- 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
- 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

For full changelog see:

  http://code.opencv.org/projects/opencv/wiki/ChangeLog

For 2.4 to 3.0 transition, see the transition guide:

  http://docs.opencv.org/master/db/dfa/tutorial_transition_guide.html